Acute relieves through peripheral and cognitive

mechanisms in healthy adults

Matthew D. Jones

A thesis in fulfilment of the requirements for the degree of

Doctor of Philosophy

School of Medical Sciences

Faculty of Medicine

August 2017

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Acknowledgements

Firstly, I would like to thank my primary supervisor Benjamin Barry for the enormous amount of time and effort that you have devoted towards my PhD candidature. You have been an incredible mentor and have contributed a great deal to me becoming a better research scientist. You have also been a very good friend outside of the lab, and for this I am particularly thankful. To my co-supervisors Janet Taylor and John Booth, thank you both for all of your assistance throughout my studies. I have been very lucky to have the two of you as supervisors for so long, and I appreciate all the help and guidance you have given me along the way.

Secondly, I would like to thank my colleagues from Exercise Physiology and from NeuRA – David Mizrahi, Natalie Kwai, Gemma Whitley, Carolina Sandler,

Brianna Clifford, Alexander Engel, Jessica Bellamy, James Nuzzo, Harrison Finn and

Arkiev D’Souza – who made my time as a student so much more enjoyable. I would particularly like to thank James Nuzzo for his help with data collection in Chapter 4.

Thank you also to all of the Exercise Physiology staff – Andrew Keech, Jeanette Thom,

Rachel Ward, Belinda Parmenter, David Simar and Nancy Van Doorn – for your help and support over the last few years.

Finally, I must thank my family. To my beautiful wife Em, thank you so much for your patience and understanding during my time as a postgraduate student. I suspect you will be happier/more relieved than I am now that it’s finally over! I love you. To my Mum and Dad, thank you both for being such good role models and for providing me with the opportunity to go to university and receive an education. I like to think that

I have a reasonably good work ethic, and I know a lot of this comes from you. I’m looking forward to spending more time with all of you now that my time as a student has finally come to an end.

i Table of Contents

Acknowledgements i

Table of Contents ii

Publications x

List of Abbreviations xi

List of Figures xii

List of Tables xxiv

Chapter 1: Introduction 1

1.1. General introduction 1

1.2. Chapter overviews 3

Chapter 2: How does exercise relieve pain in healthy adults and people with ? 7

2.1. Introduction 7

2.1.1 About pain 7

2.1.2. Overview 13

2.2. How is pain assessed? 14

2.2.1. Self-report 14

2.2.2. Quantitative sensory testing 15

2.2.3. Evoked potentials 16

2.2.4. Neuroimaging 17

2.3. About 18

2.4 About knee osteoarthritis 20

2.5. Chronic exercise and pain 21

ii 2.5.1. The effect of chronic exercise on pain in people with

fibromyalgia or knee osteoarthritis 21

2.5.2. Mechanisms of pain relief by chronic exercise in people with

fibromyalgia or knee osteoarthritis 23

2.5.3. The effect of chronic exercise on pain in healthy individuals 25

2.6. Acute exercise and pain: what is exercise induced ? 26

2.6.1. Magnitude of exercise-induced hypoalgesia in healthy adults and

people with chronic pain 27

2.6.2. Sex and age-related differences in exercise-induced hypoalgesia 30

2.6.3. Are the effects of acute and chronic exercise on pain related? 31

2.7. Mechanisms of exercise-induced hypoalgesia 32

2.7.1. Healthy individuals 34

2.7.2. Fibromyalgia and knee osteoarthritis 38

2.8. Conclusion 41

Chapter 3: Exploring the mechanisms of exercise-induced hypoalgesia using somatosensory and laser evoked potentials 43

3.1. Abstract 43

3.2. Introduction 44

3.3. Methods 46

3.3.1. Participants 46

3.3.2. Procedures 47

3.3.3. Data processing and statistical analysis 54

3.4. Results 57

3.4.1. Isometric exercise 57

iii 3.4.2. Pressure pain thresholds 57

3.4.3. Heat pain thresholds 58

3.4.4. Electrical and laser heat stimulation for the evoked potentials 58

3.4.5. Evoked potential waveforms 60

3.4.6. Modulation of SEPs and LEPs 60

3.4.7. Effect of exercise and rest on SEPs 60

3.4.8. Effect of exercise and rest on LEPs 64

3.4.9. Comparison of SEP and LEP amplitude changes 64

3.4.10. Pain and anxiety ratings 66

3.5. Discussion 70

3.6. Conclusion 78

Chapter 4: Limited change of laser-heat pain thresholds and evoked potentials following aerobic exercise 79

4.1. Abstract 79

4.2. Introduction 80

4.3. Methods 82

4.3.1. Participants 82

4.3.2. Procedures 82

4.3.3. Data processing and statistical analysis 87

4.4. Results 90

4.4.1. Aerobic exercise 90

4.4.2. Pressure pain thresholds 90

4.4.3. Heat pain thresholds 92

4.4.4. Comparison of EIH for pressure and heat pain over a similar site 92

iv 4.4.5. Laser heat stimulation and skin temperature 92

4.4.6. Ratings of pain and anxiety during laser stimulation 93

4.4.7. LEP N2P2 amplitude and onset latency 95

4.4.8. Comparison of pain thresholds and ratings over time 96

4.5. Discussion 96

4.6. Conclusion 104

Chapter 5: Occlusion of flow attenuates exercise-induced hypoalgesia in the occluded limb in healthy adults 105

5.1. Abstract 105

5.2. Introduction 106

5.3. Methods 108

5.3.1. Participants 108

5.3.2. Procedures 109

5.3.3. Data processing and statistical analysis 112

5.4. Results 114

5.4.1. Participant characteristics and exercise intensity 114

5.4.2. Pressure pain thresholds 115

5.4.3. Pain ratings during occlusion 118

5.4.4. Sex differences in pressure pain thresholds and pain ratings 118

5.5. Discussion 120

5.6. Conclusion 126

v Chapter 6: Explicit education about exercise-induced hypoalgesia influences pain responses to acute exercise in healthy adults: A randomised controlled trial 127

6.1. Abstract 127

6.2. Introduction 128

6.3. Methods 129

6.3.1. Participants 129

6.3.2. Procedures 130

6.3.3. Data processing and statistical analysis 134

6.4. Results 135

6.4.1. Participant characteristics 135

6.4.2. Effect of education on knowledge and beliefs about exercise

and pain 136

6.4.3. Aerobic exercise 138

6.4.4. Pressure pain thresholds 139

6.4.5. Correlation between beliefs about exercise-induced hypoalgesia

and the change in pressure pain threshold 142

6.5. Discussion 142

6.6. Conclusion 146

vi Chapter 7: Exercise-induced hypoalgesia in people with fibromyalgia or knee osteoarthritis: A systematic review and meta-analysis 147

7.1. Abstract 147

7.2. Introduction 148

7.3. Methods 149

7.3.1. Literature searches 149

7.3.2. Data processing and statistical analysis 151

7.4. Results 152

7.4.1. Exercise-induced hypoalgesia 152

7.4.2. Associations between physical activity or fitness and pain 157

7.5. Discussion 164

7.6. Conclusion 168

Chapter 8: Discussion 169

8.1. Summary of findings 169

8.2. Comparability of EIH to previous studies of this phenomena 170

8.3 Paradoxical effects of acute exercise and daily physical activity on

pain in healthy adults and people with chronic pain 171

8.4. Acute exercise reduces pain in healthy adults through a peripheral

mechanism 171

8.5. Acute exercise has greater effects on pressure pain compared to

thermal pain 174

8.6. Cognitive factors contribute to exercise-induced hypoalgesia 176

8.7. Future directions 177

8.8. Conclusion 181

vii References 182

Appendices 242

A: Script for the education of healthy participants, including explicit description of exercise-induced hypoalgesia. 242

B: Figure A - used to describe exercise-induced hypoalgesia to participants in the intervention group. 249

C: Script for the education of healthy participants, excluding explicit description of exercise-induced hypoalgesia. 250

D: Figure B – used to describe delayed onset muscle soreness to participants in the control group. 256

E: Questions to assess the participant’s knowledge and beliefs about exercise and pain arising from the education intervention. 257

F: Questions for experimenter’s appraisal of the participant’s engagement in, and understanding of, the education intervention. 260

G: Script for education of people with fibromyalgia or osteoarthritis, including explicit description of exercise-induced hypoalgesia. 261

H: Script for education of people with fibromyalgia or osteoarthritis, excluding explicit description of exercise-induced hypoalgesia. 268

I: Figure C – used to describe good/appropriate pain and bad/inappropriate

pain. 274

J: Figure D – used to show that being fitter is associated with less pain in people with knee osteoarthritis. 275

K: Figure E – used to show that different types of exercise reduce pain in people with knee osteoarthritis (top panel), regardless of exercise intensity

(bottom panel). 276

viii L: Figure F – used to show that being more physically active and fit is associated with less pain in people with fibromyalgia. 277

M: Figure G – used to show that aerobic and strength exercise reduce pain in people with fibromyalgia. 278

N: Quality assessment of studies in the literature synthesis of the associations between physical activity and fitness with pain in healthy individuals 279

O: Quality assessment of studies in the literature synthesis of the associations between physical activity and fitness with pain in people with fibromyalgia 280

P: Quality assessment of studies in the literature synthesis of the associations between physical activity and fitness with pain in people with knee osteoarthritis 282

Q: Quality assessment of studies in the systematic review and meta-analysis of the effect of the effect of acute aerobic and isometric exercise on pain in people with fibromyalgia 284

R: Quality assessment of studies in the systematic review and meta-analysis of the effect of the effect of acute aerobic and isometric exercise on pain in people with knee osteoarthritis 286

ix Publications

Jones MJ, Booth J, Taylor JL and Barry BK. (2016). Limited association between aerobic fitness and pain in healthy individuals: A cross-sectional study. Pain Med

17(10): 1799-1808.

Jones MJ, Taylor JL, Booth J and Barry BK. (2016). Exploring the mechanisms of exercise-induced hypoalgesia using somatosensory and laser evoked potentials. Front

Physiol 7: 581.

Jones MJ, Taylor JL and Barry BK. (2017). Occlusion of blood flow attenuates exercise-induced hypoalgesia in the occluded limb of healthy adults. J Appl Physiol

122(5): 1284-1291.

Jones MJ, Booth J, Taylor JL and Barry BK. (2017). Explicit education about exercise- induced hypoalgesia influences pain responses to acute exercise in healthy adults: A randomised controlled trial. J Pain DOI: 10.1016/j.pain.2017.07.006.

Jones MJ, Nuzzo JL, Taylor JL and Barry BK. (submitted for review). Limited change of laser-heat pain thresholds and evoked potentials following aerobic exercise.

x List of Abbreviations

ANOVA Analysis of variance

ACR American College of Rheumatology

BMI Body mass index

CI Confidence interval

CNS Central nervous system

EEG Electroencephalography

ES Effect size

EIH Exercise-induced hypoalgesia

FDI First dorsal interosseous

FM Fibromyalgia fMRI Functional magnetic resonance imaging

HPT Heat pain threshold

LEP Laser evoked potential

MET Metabolic equivalent of task

MVC Maximal voluntary contraction

OA Osteoarthritis

PPT Pressure pain threshold

QST Quantitative sensory testing

RPE Rating of perceived exertion

SD Standard deviation

SEP Somatosensory evoked potential

W Watts

xi List of Figures

Figure 2.1. Activation of peripheral pain receptors (also called ) by noxious stimuli generates signals that travel to the dorsal horn of the spinal cord via the dorsal root ganglion. From the dorsal horn, the signals are carried along the ascending pain pathway, primarily the spinothalamic tract, to the thalamus and the cortex. Pain can be controlled by pain-inhibiting and pain-facilitating neurons. Descending signals originating in supraspinal centres can modulate activity in the dorsal horn by controlling spinal pain transmission. Abbreviation: CNS, central nervous system. From Bingham et al31.

Figure 2.2. Nociceptive information from the thalamus is projected to the insula, anterior cingulate cortex (ACC), primary somatosensory cortex (S1) and secondary somatosensory cortex (S2), whereas information from the amygdala (AMY) is projected to the basal ganglia (BG). PAG, periaqueductal grey; PB, parabrachial nucleus; PFC, prefrontal cortex. From Bushnell et al34.

Figure 2.3. Mean pain ratings (black diamonds) immediately before the 16 individual exercise sessions within the 8-week exercise period, at baseline examination (white square) and at 8 weeks follow-up (white triangle). Error bars are 95% confidence intervals. n = number of people with available data at the specific time points. NRS =

Numerical Rating Scale, ranging from 0 to 10, best to worst.

Figure 2.4. Increase in acute pain from before to immediately after each of the 16 exercise sessions within the 8-week exercise period (grey area). Exacerbation of pain is apparent in the earlier exercise sessions and gradually diminishes to approach a hypoalgesic response. Error bars are 95% confidence intervals. n = number of people with available data at the specific time points. NRS = Numerical Rating Scale, ranging from 0 to 10, best to worst.

xii Figure 3.1. Panel A) and B) show the order of procedures in Experiment 1 (SEPs) and

Experiment 2 (LEPs), respectively, when exercise was performed first. In both experiments, evoked potentials were recorded on five occasions during electrical stimulation (Experiment 1) or laser heat stimulation (Experiment 2). Pressure pain thresholds were assessed before and after isometric exercise and before quiet rest in each experiment. Heat pain thresholds were assessed before and after isometric exercise and before quiet rest in Experiment 2 only. A 30 min wash out period was included to ensure possible exercise-induced alterations in pain were gone prior to commencing the next block of evoked potential recordings. This was confirmed by the re-assessment of

PPTs (Experiment 1 and 2) and HPTs (Experiment 2 only) prior to the next block of evoked potential recordings. The order of exercise or quiet rest was counterbalanced across participants in each study.

Figure 3.2. Individual data for pressure pain thresholds (PPTs; left side of vertical dotted line) and the differences in PPTs for individual participants and the group (mean and 95% confidence interval; right side of vertical line) at m. biceps brachii in

Experiment 1 (A) and Experiment 2 (C) and m. first dorsal interosseous in Experiment 1

(B) and Experiment 2 (D). Individual data for heat pain thresholds (HPTs; left side of vertical dotted line) and the differences in HPTs for individual participants and the group (mean and 95% confidence interval; right side of vertical line) at the forearm (E) and hand (F) in Experiment 2 are also shown. ∆ baseline is the difference between the pre rest and pre exercise measures and ∆ ex (exercise) is the difference between the pre exercise and post exercise measures. Data to the left of the vertical dotted line are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis.

xiii Figure 3.3. Somatosensory evoked potentials recorded at Cz from 16 participants in

Experiment 1 (SEPs, panels A, C & E on the left) and laser evoked potentials recorded at Cz from 16 participants in Experiment 2 (panels B, D & F on the right). These traces are the grand averages across participants of individual waveform averages from approximately 500 stimuli for the SEPs and from approximately 30 stimuli for the

LEPs. Data are shown for SEPs and LEPs recorded during the modulation test (A, B) or immediately before and after exercise (C, D) or rest (E, F). For the modulation test, two stimulus intensities corresponding to either mild or moderate pain were randomly presented within the same sequence of 5 test blocks. For the SEPs, data are shown for

50 ms before and 450 ms following the stimulus onset; the stimulus artefact is visible on each plot and has been truncated for the illustration. For the LEPs, data are shown for

50 ms before and 950 ms following the stimulus onset; the vertical dashed lines represent stimulus onset.

Figure 3.4. Each panel presents individual and group data (mean and 95% confidence interval) for the N2P2 evoked potential amplitude to the left side of vertical dotted line and individual and group differences (∆; mean and 95% confidence interval) in evoked potential amplitude to the right side of vertical dotted line. SEP data from Experiment 1 are in the left panels (SEPs, panels A, C & E) and LEP data from Experiment 2 are in the right panels (LEPs, panels B, D & F). A) and B) Responses to mild and moderate

(mod) pain stimuli recorded in the modulation blocks. C) and D) Responses recorded before (pre) and after (post) exercise. E) and F) Responses recorded before and after a period of rest. In each of these plots the zero-difference level on the right-hand y-axis is aligned to the group mean for the reference condition of moderate stimulation intensity

(A, B), pre-exercise (C, D) or pre-rest (E, F). Data to the left of the vertical dashed line

xiv are plotted against the left-hand y-axis and data to the right of the vertical dashed line are plotted against the right-hand y-axis.

Figure 3.5. Individual and group data (mean and 95% confidence interval) for ratings of pain intensity, pain unpleasantness and anxiety (left side of vertical dotted lines in each graph) before (pre) and after (post) exercise (left panels) or rest (right panels) during

Experiment 1. Five ratings were averaged to give a single value for ratings of pain intensity and pain unpleasantness for the sets of electrical stimuli and 3 ratings were averaged to give a single value for anxiety. Individual and group differences (∆; mean and 95% confidence interval) in ratings from pre to post exercise or rest are shown to the right side of the vertical dotted line in each graph. In each of these plots the zero- difference level on the right-hand y-axis is aligned to the group mean for the pre- exercise reference condition. Data to the left of the vertical dotted line are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis.

Figure 4.1. Pressure pain thresholds (PPTs), heat pain thresholds (HPTs) and laser evoked potentials (LEPs) were measured before and after 15 min of moderate-vigorous intensity cycle ergometer exercise and an equivalent duration of light activity. The interventions were presented in a randomised and counterbalanced order. A 30 min wash out period was included so that, in participants who exercised first, any exercise- induced changes in pain were gone before commencing the next block of pain threshold and laser evoked potential recordings. The post measures were completed within 10 min of the cessation of exercise or light activity and were always performed in the same order (i.e. PPTs, HPTs and then LEPs). The order of pain assessments made prior to exercise and light activity differed slightly depending on which intervention was performed first. For participants randomised to light activity first (not shown), the order

xv of pain assessments was the same prior to the light activity and exercise interventions

(i.e. LEPs, HPTs and then PPTs). For those randomised to exercise first (shown), the same order of pain assessments was used pre and post exercise (i.e., LEPs, HPTs and then PPTs) but prior to light activity the order of pain assessments was: PPTs, HPTs and then LEPs. In this instance, the assessment of PPTs first was necessary to verify the return of pain to baseline following the wash out period.

Figure 4.2. Data to the left of the vertical dotted line show the individual data (grey dots) and group data (mean and 95% confidence interval, black lines) before and after light activity (LA) and exercise (Ex) for pressure pain thresholds at the rectus femoris

(A) and tibialis anterior (C) muscles as well as heat pain thresholds at the foot (B) and tibialis anterior (D). Data to the right of the vertical dotted line show the individual data

(grey dots) and group data (mean and 95% confidence interval, black lines) for the percentage change in pain thresholds between the pre light activity and post light activity measures (∆ LA) and between the pre exercise and post exercise measures (∆

Ex). Data to the left of the vertical dotted line are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis.

For data plotted against the right-hand y-axis, the horizontal dotted line indicates a zero change score.

Figure 4.3. Individual and group data (mean and 95% confidence interval) for ratings of pain intensity, pain unpleasantness and anxiety (left side of vertical dotted lines and plotted against left-hand y-axis) pre and post light activity (left panels) and exercise

(right panels). Differences (∆) for individuals and the group (mean and 95% confidence interval) are shown to the right side of the vertical dotted line and are plotted against the right-hand y-axis. In each of these plots the zero-difference level on the right-hand y- axis is aligned to the group mean for the pre-light activity or pre-exercise condition.

xvi Figure 4.4. Laser evoked potentials recorded from 16 participants. These traces are the grand averages of individual waveform averages from approximately 30 stimuli recorded pre and post light activity (panels A, C, D & E) or exercise (panels B, F, G &

H). Data are shown for 50 ms before and 950 ms following the stimulus onset (signified by the vertical dashed line). The amplitude of laser evoked potentials was largest at electrode Cz (panels A & B), but the pattern of change with light activity and exercise was similar across the four sites.

Figure 4.5. Individual and group data (mean and 95% confidence interval) for the peak- to-peak amplitude of the laser evoked potentials (left side of vertical dotted lines and plotted against left-hand y-axis) collected pre and post light activity (A) and exercise

(B). Differences (∆) for individuals and the group (mean and 95% confidence interval) are shown to the right side of the vertical dotted line and are plotted against the right- hand y-axis. In each of these plots the zero-difference level on the right-hand y-axis is aligned to the group mean for the pre-light activity or pre-exercise condition.

Figure 4.6. Individual (grey dots) and group data (mean and 95% confidence interval, black lines) showing the temporal stability of each pressure pain threshold (A), heat pain threshold (B) and rating of laser pain intensity (C) across the experiment. Data for the pressure and heat pain thresholds are for values recorded over the tibialis anterior/lower leg. Ex, exercise; LA, light activity

Figure 5.1. Pressure pain thresholds (black circles) were assessed over the rectus femoris muscle of the right leg and over the first dorsal interosseous muscles of both arms prior to and during upper limb occlusion using a tourniquet that was placed around the upper arm and inflated to 240 mmHg. Both arms were occluded during the experiment, but only one arm was occluded at a time and the order of the arm that was occluded first was counterbalanced across participants. During occlusion (dashed

xvii rectangles), pressure pain thresholds were assessed before and after 5 min of high intensity cycle exercise as well as before and after an equivalent period of quiet rest.

The order of exercise or quiet rest was randomised and counterbalanced across participants. A 30 min wash-out period was included to ensure any exercise-induced alterations in pain were gone prior to commencing the next round of pressure pain threshold measures.

Figure 5.2. Individual data (grey dots) and group data (mean and 95% confidence interval, black lines) prior to cuff inflation (baseline) as well as during cuff inflation before and after rest and exercise (Ex) for pressure pain thresholds (PPTs) at the rectus femoris muscle (A) and the non-occluded and occluded first dorsal interosseous muscles

(FDI, panels B and C, respectively).

Figure 5.3. Individual data (grey dots) and group data (mean and 95% confidence interval, black lines) for the change (∆) in pressure pain thresholds (PPT) with rest and exercise (Ex) at the rectus femoris muscle (left column) and the non-occluded and occluded first dorsal interosseous muscles (FDI, middle and right columns, respectively).

Figure 5.4. Data to the left of the vertical dotted line in each graph show the individual data (grey dots) and group data (mean and 95% confidence interval, black lines) before and after rest and exercise (Ex) for ratings of cuff pressure pain intensity (A) and unpleasantness (B) as well as ratings of ischaemic pain intensity (C) and unpleasantness

(D) during occlusion. Data to the right of the vertical dotted lines show the individual data (grey dots) and group data (mean and 95% confidence interval, black lines) for the differences in pain ratings between the pre rest and post rest measures (∆ Rest) and between the pre exercise and post exercise measures (∆ Ex). Data to the left of the

xviii vertical dotted lines are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis.

Figure 6.1. Participants were randomised to receive education about exercise-induced hypoalgesia (intervention) or more general education about exercise and pain (control).

The education session for both groups lasted approximately 15 min, after which measurements of the participant’s pressure pain threshold were made. Participants then performed 20 min of moderate-vigorous intensity cycle ergometer exercise, after which pressure pain thresholds were re-assessed.

Figure 6.2. Individual data (black lines) for the combined pressure pain threshold pre and post exercise for the intervention (Int) and control (Ctl) groups. Group data (box and whisker plots, i.e. the median, interquartile range and range) for the combined PPT change score after exercise for the intervention and control groups are also shown. Data to the left side of the vertical dotted line are plotted against the left-hand y-axis and data to the right side of the vertical dotted line are plotted against the right-hand y-axis.

Figure 6.3. Individual data (black lines) for the pressure pain threshold pre and post exercise for the intervention (Int) and control (Ctl) groups over the rectus femoris (A), tibialis anterior (B) and first dorsal interosseous (C). Group data (box and whisker plots) for the PPT change score after exercise for the intervention and control groups at each site are also shown. Data to the left side of the vertical dotted line are plotted against the left-hand y-axis and data to the right side of the vertical dotted line are plotted against the right-hand y-axis.

xix Figure 7.1. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute aerobic exercise on pain in healthy adults (circles), including meta-analysis of these studies (diamond). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Significant associations (p < 0.05) are shown in black and non-significant associations have grey symbols and error bars. Abbreviations: CPI = cold pain intensity; EPT = electrical pain threshold; HPI = heat pain intensity; PPI = pressure pain intensity; PPT = pressure pain threshold.

Figure 7.2. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute isometric and dynamic resistance exercise on pain in healthy adults (circles), including meta-analysis of these studies

(diamonds). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Significant associations (p < 0.05) are shown in black and non-significant associations have grey symbols and error bars. Abbreviations: EPI = electrical pain intensity; HPI = heat pain intensity; PPI = pressure pain intensity; PPT = pressure pain threshold; PPTOL = pressure .

Figure 7.3. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute exercise on pain in people with fibromyalgia (circles), including meta-analysis of these studies (diamonds). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Significant associations (p < 0.05) are shown in black and non-significant associations have grey

xx symbols and error bars. Abbreviations: HPI = heat pain intensity; PPT = pressure pain threshold.

Figure 7.4. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute exercise on pain in people with knee osteoarthritis (circles), including meta-analysis of these studies (diamonds). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Non- significant associations have grey symbols and error bars. Abbreviations: PPT = pressure pain threshold; WOMAC = Western Ontario and McMaster Universities

Arthritis Index.

Figure 7.5. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between physical activity or fitness and pain in healthy individuals. Data to the left of the vertical dotted line indicate an inverse association between physical fitness/activity and pain (e.g. more activity and less pain) and data to the right of the vertical dotted line indicate a positive association between physical fitness/activity and pain (e.g. more activity and more pain). Significant associations (p < 0.05) are shown in black and non-significant associations are shown in grey. Abbreviations: D = m. deltoid; IFP = infrapatellar fat pad; KE = knee extensor; KF = knee flexor; LB = lower body; UB = upper body; VL = m. vastus lateralis; VO2peak = peak aerobic capacity.

Figure 7.6. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between physical activity or fitness and pain in people with fibromyalgia. Data to the left of the vertical dotted line indicate an inverse association between physical fitness/activity and pain (e.g. more fitness and less pain) and data to the right of the vertical dotted line indicate a positive

xxi association between physical fitness/activity and pain (e.g. more fitness and more pain).

Significant associations (p < 0.05) are shown in black and non-significant associations are shown in grey. Abbreviations: 6MWT = 6-minute walk test; FIQ = Fibromyalgia

Impact Questionnaire; KE = knee extensor; KF = knee flexor; MPI = Multidimensional

Pain Inventory; SF-36 = Medical Outcomes Study Short-form 36 health survey; VO2peak

= peak aerobic capacity.

Figure 7.7. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between physical activity and pain in people with knee osteoarthritis (filled circles). Data to the left of the vertical dotted line indicate an inverse association between physical activity and pain (e.g. more activity and less pain) and data to the right of the vertical dotted line indicate a positive association between physical activity and pain (e.g. more activity and more pain).

Significant associations (p < 0.05) are shown in black and non-significant associations have grey symbols and error bars. The results of the fixed and random effects meta- analyses are shown by the empty diamond symbols. Abbreviations: NRS = Numerical

Rating Scale; SF-36 = Medical Outcomes Study Short-form 36 health survey; WOMAC

= Western Ontario and McMaster Universities Osteoarthritis Index.

Figure 7.8. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between fitness and pain in people with knee osteoarthritis (filled circles). Data to the left of the vertical dotted line indicate an inverse association between fitness and pain (e.g. greater fitness, less pain) and data to the right of the vertical dotted line indicate a positive association between physical activity and pain (e.g. greater fitness, more pain). Significant associations (p <

0.05) are shown in black and non-significant associations have grey symbols and error bars. The results of the fixed and random effects meta-analyses are shown by the empty

xxii diamond symbols. Abbreviations: AIMS = Arthritis Impact Measurement Scales; KOS-

ADLS = Knee Outcome Survey Activities of Daily Living Scale; KOOS = Knee Injury and Osteoarthritis Outcome Score; NRS = Numerical Rating Scale; WOMAC =

Western Ontario and McMaster Universities Osteoarthritis Index; VAS = .

xxiii List of Tables

Table 3.1. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms), and effect size of the change, for the SEP N2P2 waveform at Cz in Experiment 1. The baseline-to- peak amplitude (µV) and onset latency (ms) of the SEP N1 waveform, and effect size of the change, is also presented.

Table 3.2. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms), and effect size of the change, for the LEP N2P2 waveform at Cz in Experiment 2.

Table 3.3. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms), and effect size of the change, for the SEP N2P2 waveform at Fz, Pz and C3 in Experiment 1.

Table 3.4. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms) of the LEP

N2P2 waveform at Fz, Pz and C3 in Experiment 2.

Table 4.1. Mean ± SD skin temperature (°C) over each site across the experiment.

Table 4.2. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms) of the LEP

N2P2 waveform.

Table 5.1. Participant characteristics and exercise intensity

Table 6.1. Group data (median (interquartile range)) for participant responses to the knowledge and beliefs about exercise and pain questionnaire as well as the experimenter’s appraisal of the participants’ engagement in, and understanding of, the education provided.

Table 6.2. Mean ± SD work-rate for aerobic exercise and the associated heart rate and perceptual responses.

xxiv Chapter 1:

Introduction

1.1 General introduction

Pain is an unpleasant but important sensation designed to protect the body from harm. In some instances, however, pain becomes maladaptive. This can involve pain persisting well beyond the expected healing time and pain intensity disproportionate to the amount of tissue damage. Persistent or chronic pain is a prevalent1,2 and debilitating condition3,4 that imposes significant costs to healthcare5. As the complete abolition of pain is unlikely for many chronic pain conditions, the aims of treatment are to reduce pain and disability and improve quality of life6.

Pain is personal and multifactorial, so there is no one-size-fits-all approach for its management. Individualised multimodal treatments delivered using a biopsychosocial approach are usually the most evidence based7, but the effectiveness of many therapies used in this approach are mixed. For example, patient education and cognitive behavioural therapies have only a small effect on reducing pain8-10 and there are too few high quality studies to determine the effectiveness of physical modalities for reducing pain (e.g. acupuncture, massage and transcutaneous electrical nerve stimulation)11. As for less conservative treatments such as drugs and surgery, these can be expensive, are not without risk and side effects, and do not always produce clinically relevant improvements in pain12-15. Clearly, more efficacious treatments are needed to reduce the personal and societal impact of chronic pain.

Exercise is one promising treatment modality, with systematic reviews and meta-analyses consistently showing that exercise is an effective therapy for people with a variety of musculoskeletal chronic pain conditions16-19. For example, exercise is as

1 effective as for reducing pain secondary to knee osteoarthritis19 and has comparable efficacy to drugs used to manage fibromyalgia20. Exercise can also improve co-morbidities often present in people with chronic pain, such as sleep disturbances and mood disorders21,22. Importantly, these ubiquitous effects of exercise on improving pain, functional disability and quality of life in people with chronic pain are realised with little to no adverse events.

Therefore, exercise may be the single most effective therapy for people with chronic pain with regard to simultaneously improving pain, function and quality of life.

While the literature shows that exercise is an effective treatment modality for chronic musculoskeletal pain, the underlying mechanisms are unclear. Increasing current understanding of the mechanisms through which exercise reduces pain could have important clinical implications. For example, a greater understanding of how exercise influences the biological and cognitive contributors to pain may allow for more effective therapies to be developed; for instance, appropriate combinations of exercise, drug and education or cognitive-behavioural therapies. This would likely provide greater benefits to people with chronic pain for reducing the impact of pain on their life compared to the therapies currently available.

The aim of this thesis was to enhance understanding of the mechanisms through which exercise affects pain. The first step in this approach was to explore the mechanisms through which acute exercise influences pain in healthy adults. The techniques and methods used to do this are not new, but their application here to investigate the mechanisms of exercise-induced hypoalgesia (i.e., the transient reduction in pain that occurs during or following acute exercise) is novel. It is hoped that the experiments contained in this thesis will not only enhance current understanding of how exercise affects pain, but will provide avenues for future research into how exercise

2 might best be used to treat pain in people with chronic pain. The specific aims of each chapter are outlined below.

1.2. Chapter overviews

Chapter 2: How does exercise relieve pain in healthy adults and people with chronic pain?

The chapter was a review of the literature of the effect of exercise on pain.

Experiments investigating the effect of acute and chronic exercise on pain in healthy adults and in people with chronic pain, specifically fibromyalgia and knee osteoarthritis, are reviewed. Possible mechanisms mediating the pain-modulatory effect of exercise in these populations are also discussed, with emphasis on the mechanisms underlying changes in pain after a single bout of exercise.

Chapter 3: Exploring the mechanisms of exercise-induced hypoalgesia using somatosensory and laser evoked potentials

Exercise-induced hypoalgesia is well described but the underlying mechanisms are not clear. The first experimental chapter of this thesis investigated the effect of exercise on pain thresholds, pain ratings and evoked potentials to noxious electrical

(Experiment 1) and laser heat stimuli (Experiment 2) in healthy adults. The comparison of the effect of exercise on somatosensory and laser evoked potentials provided some insight into the effect of exercise on the excitability of somatosensory and nociceptive pathways, in particular the possible role of the peripheral .

3 Chapter 4: Limited change of laser-heat pain thresholds and evoked potentials following aerobic exercise

Exercise-induced hypoalgesia is often greatest when mechanical stimuli are used to evoke pain, but the reason for this is unknown. The aim of this study – involving healthy adults – was to determine whether aerobic exercise differentially affects sensitivity to noxious mechanical and heat stimuli when these different stimuli are similar with regard to their site of application, duration of application, and indices of pain assessed. A secondary aim was to determine whether any effect of exercise on laser evoked potentials identified in Chapter 3 is different when aerobic exercise is used.

Pressure pain thresholds, heat pain thresholds, laser evoked potentials and pain ratings to laser stimulation were measured before and after aerobic exercise as well as before and after an equivalent duration of light activity.

Chapter 5: Occlusion of blood flow attenuates exercise-induced hypoalgesia in the occluded limb of healthy adults

Animal studies show an important contribution of peripheral changes to exercise-induced hypoalgesia, but whether peripheral changes also contribute to exercise-induced hypoalgesia in humans is not known. The aim of this third experimental chapter was to investigate whether exercise-induced hypoalgesia in healthy adults is mediated, at least in part, by peripheral factors. Blood flow to one arm was blocked by an inflated cuff while pressure pain thresholds were measured over the leg (exercised limb) and over both hands (unexercised limb) before and after aerobic exercise as well as before and after an equivalent period of quiet rest.

4 Chapter 6: Explicit education about exercise-induced hypoalgesia influences pain responses to acute exercise in healthy adults

There is evidence that cognitive factors are associated with exercise-induced hypoalgesia in healthy adults and in people with chronic pain. However, their direct involvement as a mediator of exercise-induced hypoalgesia has not been studied, nor is it clear whether these cognitive factors can be manipulated to influence pain responses after exercise. The aim of this final experimental chapter was to determine whether exercise-induced hypoalgesia could be influenced by preceding exercise with education about the pain relieving effect of exercise. In this randomised controlled trial, participants were randomly assigned to receive education about exercise-induced hypoalgesia (intervention group) or more general pain education (control group).

Following the education intervention, pressure pain thresholds were measured before and after aerobic exercise to quantify the magnitude of exercise-induced hypoalgesia for comparison between the groups.

Chapter 7: Exercise-induced hypoalgesia in people with fibromyalgia or knee osteoarthritis: A systematic review and meta-analysis

Chronic exercise consistently reduces pain in people with chronic pain whereas acute exercise has more varied effects on pain. Associations between pain and physical activity or fitness have also been observed, but these associations have not been systematically reviewed. The aim of this chapter was to better understand how physical activity and fitness relate to pain in healthy adults and people with chronic pain, and to compare this to the effect of acute exercise on pain in the same populations. To this end, systematic literature reviews, and meta-analyses where appropriate, were conducted and are discussed.

5 Chapter 8: Discussion

The major findings are summarised and the key experimental results are discussed in this chapter. The implications of the results of this thesis are also discussed, as are possible directions for future research.

6 Chapter 2:

How does exercise relieve pain in healthy adults and people with

chronic pain?

2.1. Introduction

2.1.1. About pain

Pain is “an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage”23. There are two main categories of pain: acute and chronic. Acute pain arises in response to a specific disease or injury and serves to protect the individual from further harm. It is usually related to the amount of nociceptive input, is recent in onset, and short in duration. Chronic pain on the other hand is pain that persists well beyond the expected healing time, often in the absence of tissue damage and sometimes even in the absence of tissue (e.g. phantom limb pain). For pain to be considered chronic, it must present in one or more anatomic regions for at least 3 months24. The transition from acute to chronic pain involves a number of processes. These include: persistent noxious signalling in the periphery; maladaptive neuroplastic changes in the central nervous system; an impaired ability to modulate pain (i.e. less pain inhibition and greater pain facilitation); and aberrant changes in the structure, function and connectivity of pain-related brain areas25. Because pain is personal and multifactorial, pain experiences of individuals differ greatly between people even when they have similar pathologies. Hence, treatments must be tailored to each individual to be maximally effective.

7 2.1.1.1. Basic anatomy and physiology of pain

The processing of pain occurs on at least three levels – peripheral, spinal and supraspinal (Figure 2.1). At the periphery, specialised sensory neurons called nociceptors detect tissue stress in response to noxious mechanical, thermal and chemical stimuli. Nociceptors then convert this mechanical, thermal or chemical energy into an action potential and conduct it through the primary nociceptive afferents (i.e. A-delta and C-fibres, also known respectively as group III and group IV afferents). A-fibre nociceptors are predominantly heat- and/or mechanosensitive, however A-fibre nociceptors that respond to noxious cold and chemical stimuli (e.g. capsaicin) have also been found26. A-delta fibres are thinly myelinated, have a moderate conduction velocity

(2-30 m/s), and are associated with the sensation of sharp localised pain after exposure to a (i.e. first pain)26. C-fibre nociceptors are mostly polymodal, meaning that they respond to thermal, mechanical and chemical stimuli. Silent C-fibres

- nociceptors that are normally insensitive to pressure and heat, but become sensitive to these stimuli after being sensitised by inflammatory mediators - have also been observed26. Because C-fibres are unmyelinated, they have a slow conduction velocity (<

2m/s) and so are associated with the duller and more dispersed sensation following exposure to a noxious stimulus (i.e. second pain)26.

Centrally, A-delta and C-fibres fibres enter the dorsal root ganglion and then the dorsal horn of the spinal cord. Here, some modulation of nociceptive input occurs.

Mechanisms of this modulation include descending inhibitory and facilitatory inputs from higher centres27 as well as segmental changes involving various pain-related substances (e.g. opioids, glutamate and noradrenaline)28. This modulation of nociceptive input involves direct actions on dorsal horn cells, inhibition of excitatory neurons, and/or excitation of inhibitory neurons27, all of which alter the amount of nociceptive

8 input that is sent to the brain. Spinal modulation of pain can also occur via the activity of non-nociceptive sensory afferents to ‘close the gate’ on pain29. That is, activity from

A-beta fibres stimulates inhibitory neurons in the spinal cord that prevent projection neurons from sending signals to the brain, even in the presence of afferent input from nociceptive fibres30. This is akin to vigorously rubbing an injured area to make it less painful.

Figure 2.1. The nociceptive pain pathway

Activation of peripheral pain receptors (also called nociceptors) by noxious stimuli generates signals that travel to the dorsal horn of the spinal cord via the dorsal root ganglion. From the dorsal horn, the signals are carried along the ascending pain pathway, primarily the spinothalamic tract, to the thalamus and the cortex. Pain can be controlled by pain-inhibiting and pain-facilitating neurons. Descending signals originating in supraspinal centres can modulate activity in the dorsal horn by controlling spinal pain transmission. Abbreviation: CNS, central nervous system. From Bingham et al.31

9 From the spinal cord, nociceptive signals reach the brain via projections to the brainstem, hypothalamus and thalamus, though the majority of nociceptive input is conveyed by the spinothalamic tract to the thalamus31. Neurons from the thalamus project to other pain-related brain areas that are differentially involved in encoding the sensory-discriminative and affective motivational components of pain.

For example, the primary and secondary somatosensory cortices are more involved in the sensory component of pain (e.g. localisation, intensity, type) whereas the insular cortex and limbic system are more involved in the emotional aspect of pain (e.g. distress)31. It is this integration of sensations, emotions and cognitions that lead to the perception of pain.

Key areas involved in the cortical processing of pain are illustrated in Figure 2.2.

A variety of neuroimaging and recording techniques have been used to investigate the neural bases of pain (e.g. functional magnetic resonance imaging (fMRI), positron emission tomography, magnetoencephalography and scalp electroencephalography

(EEG)), including methods to study the neurobiology of pain in the brain (e.g. diffusion tensor imaging, volumetric imaging and spectroscopy)32. Despite these many investigations, the network of brain regions responsible for the experience of pain is only partly understood32.

Supraspinal areas also have an important role in pain modulation. While there is some evidence that pain can be modulated cortically33, the majority of supraspinal modulation occurs through descending pathways from the brainstem to the spinal cord dorsal horn. The periaqueductal grey and rostral ventromedial medulla are the two brainstem areas responsible for descending pain modulation, with noradrenaline and serotonin the two neurotransmitters most involved in these processes. The

10 periaqueductal grey functions to inhibit pain, whereas descending projections from the rostral ventromedial medulla can both facilitate and inhibit pain27.

Figure 2.2. Areas involved in the cortical processing of pain

Nociceptive information from the thalamus is projected to the insula, anterior cingulate cortex (ACC), primary somatosensory cortex (S1) and secondary somatosensory cortex (S2), whereas information from the amygdala (AMY) is projected to the basal ganglia (BG). PAG, periaqueductal grey; PB, parabrachial nucleus; PFC, prefrontal cortex. From Bushnell et al.34

2.1.1.2. Sensitisation as a hallmark feature of chronic pain

For people with chronic pain, discordance between tissue damage and pain is common. Sensitisation is a likely reason for this. Sensitisation is defined as an

“increased responsiveness of neurons to their normal input or recruitment of a response to normally subthreshold inputs”23 and can be peripheral or central. Peripheral sensitisation refers to the “increased responsiveness and reduced threshold of nociceptive neurons in the periphery to stimulation of their receptive fields”23 whereas 11 central sensitisation is the “increased responsiveness of nociceptive neurons in the central nervous system to their normal or subthreshold afferent input”23. Common manifestations of sensitisation include (exaggerated responses to noxious stimuli) and (pain provocation to non-noxious stimuli). These exaggerated pain responses and an impaired ability to modulate pain are associated with greater pain and disease severity in people with chronic pain35. Therefore, therapies that diminish sensitisation are of obvious clinical importance.

2.1.1.3. Managing acute and chronic pain

Numerous conservative and non-conservative modalities are used to manage pain. Most acute pain is treated with analgesic drugs (e.g. opioids and non-steroidal anti-inflammatories) and passive modalities such as tissue mobilisation techniques, acupuncture and electromodalities. Then, as pain and inflammation diminish, treatment becomes more active (e.g. exercise). Historically, people were recommended to rest in the acute post-injury period, but this is now actively discouraged because people who continue to move, within their limits, experience better outcomes36. Bed rest may also serve to reinforce fear of movement, activity avoidance and other negative pain-related behaviours.

For chronic pain, multidisciplinary approaches incorporating psychological and physical interventions seem to be the most efficacious37 and should be delivered using a bio-psycho-social treatment approach38. This treatment approach addresses the biological, psychological and social aspects that contribute to the individuals’ pain experience and shift the emphasis from pain abolition to improving function, and managing and coping better with symptoms. Drugs, education and exercise are all important parts of this approach, but this literature review and thesis will focus

12 primarily on the role of exercise. Indeed, there is considerable evidence for the benefits of exercise for a wide range of chronic pain conditions17,18,39,40. However, the mechanisms by which exercise relieves pain remain unclear.

2.1.2. Overview

This chapter is a review of the effects of exercise on pain. First, the various methods used to assess pain will be discussed. Then, the chronic pain states fibromyalgia (FM) and knee osteoarthritis (OA) will be briefly discussed. These two conditions were chosen because they share several pathophysiological similarities, yet are distinguished by the extent of bodily pain, and because the effect of exercise on pain in each condition has been extensively studied. The associations between physical activity and fitness with pain in people with FM and knee OA are systematically reviewed later in this thesis (Chapter 7), but the effects of chronic exercise on pain and the possible mechanisms underlying these effects in both conditions will be briefly discussed here in this chapter. The few studies that have investigated the effect of chronic exercise on pain in healthy adults will be described here as well.

Following this, the effect of acute exercise on pain will be outlined. This will focus on the phenomenon of exercise-induced hypoalgesia (EIH); the transient reduction in pain that occurs during or following a single bout of exercise. Studies of

EIH in healthy adults and people with FM and knee OA will be briefly described here and are systematically reviewed in Chapter 7. Then, the possible mechanisms underlying EIH will be discussed. Because our current understanding of the mechanisms of EIH is limited, much of this discussion is speculative. Studies in

Chapters 3-6 of this thesis attempt to more specifically identify some of these

13 mechanisms, including the sites in the nervous system where changes might be occurring.

2.2. How is pain assessed?

There is no single measure that can adequately capture the complex nature of pain, particularly chronic pain. Accordingly, a number of methods are often used in research and clinical settings to assess pain. These range from the very basic (e.g. visual analogue and numeric rating scales) to the more complex (e.g. evoked potentials and fMRI)), and each have their own advantages and disadvantages.

2.2.1 Self-report

Pain is subjective so it makes sense that self-report methods would be useful for its assessment. Common self-report methods to quantify pain include questionnaires and pain rating scales, both of which are easy to administer41 and allow researchers and clinicians to track a person’s levels of pain over time. The psychometric properties of these instruments for pain assessment have been demonstrated42 and their superiority to neuroimaging for tracking pain has also been established43-45. The primary limitation of pain rating scales is that many of them assume pain to be a unidimensional experience that can be measured with a single item. This is not the case and while pain rating scales and questionnaires can be used to assess different dimensions of pain (e.g. intensity, unpleasantness, affective, etc), they are not without limitation.

14 2.2.2. Quantitative sensory testing

Another disadvantage of self-report measures is that they provide little insight into the neurophysiological factors that might be contributing to the pain and sensitisation. This information is better determined using quantitative sensory testing

(QST). Quantitative sensory testing describes a series of tests that measure the perceptual responses to systematically applied and quantifiable sensory stimuli46. The standard QST battery takes approximately 1 hour and permits examination of A-beta,

A-delta and C fibre function, including their projection pathways to the brain47. The simplicity and reliability of these techniques make them useful tools for the assessment of pain to different noxious stimuli and their usefulness for the study of chronic pain has been demonstrated48.

Because the full QST protocol is quite lengthy, often only subsets of the tests are used in research settings. These tests will typically involve the assessment of a person’s pain threshold or pain tolerance which are, respectively, the minimum intensity of a stimulus that is perceived as painful and the maximum intensity of a noxious stimulus that the participant is willing to tolerate23. Ratings of pain intensity and unpleasantness during exposure to various noxious stimuli might also be measured. Thresholds, ratings and tolerance of noxious stimuli are considered static or unidimensional measures of pain, but it has been argued that dynamic measures better reflect the clinical pain experience49. These dynamic methods are commonly used to assess an individual’s ability to modulate pain and include temporal summation, spatial summation, conditioned pain modulation and offset analgesia. Of these methods, temporal summation and conditioned pain modulation are used most often.

Temporal summation refers to an increase in pain following repetitive stimulation at the same intensity50 and is considered a behavioural correlate of wind-up,

15 which is the frequency dependent increase in C-fibre evoked responses of dorsal horn neurons following repetitive stimulation at a constant intensity51. Temporal summation paradigms provide information mostly about facilitatory mechanisms underlying nociceptive processes46. In contrast, conditioned pain modulation provides an index of the strength of pain inhibition. Conditioned pain modulation (i.e. ‘pain inhibits pain’) involves the application of two noxious stimuli over two different areas of the body, with the more pronounced noxious stimulus (conditioning stimulus) subsequently inhibiting the perception of the weaker noxious stimulus (test stimulus)52. Temporal summation and conditioned pain modulation responses are often impaired in people with chronic pain, with these impairments associated with more severe and widespread pain in these individuals35.

2.2.3. Evoked potentials

Evoked potentials are commonly used to investigate the function of the somatosensory system, including the nociceptive pathways. To generate an evoked potential, a brief and intense stimulus is delivered to a particular area of the body during which time cortical responses are recorded at the scalp using EEG. A range of noxious stimuli have been used to generate evoked potentials (e.g. electrical, mechanical, chemical and thermal) and there are advantages and disadvantages of each53. Of these different stimuli, laser evoked potentials (LEPs) are considered the gold standard for the study of the nociceptive pathways using evoked potentials. This is because thermal energy from lasers is confined to the most superficial layers of the skin where the transducer nerve terminals are located and because stimulation from a laser rapidly and quite selectively activates nociceptive afferents (i.e. A-delta and C-fibres)54.

16 Evoked potentials are described by their polarities (negative (N) and positive

(P)), latencies and amplitudes, and consist of early, late and ultra-late components. The timing of these components depends on the body site measured and the stimulus modality, but for the example of LEPs in the hand the respective periods for early, late and ultra-late components are < 200ms, 230 – 380 ms and > 800 ms55,56. The late and ultra-late components are considered the parts most related to and are thought to reflect activity of A-delta and C-fibres, respectively57. When analysing pain- related evoked potentials the N1, N2 and P2 are the primary components of interest.

The N1 is thought to represent the earliest arrival of nociceptive input to the cortex58 whereas the peak-to-peak amplitude of the N2P2 is the component most related to nociception whereby larger N2P2 amplitude is associated with more pain55. There is evidence that both the sensory-discriminative and affective aspects of pain are captured by this late component of the evoked potential55,59-61. Somatosensory and laser evoked potentials will be described more in Chapters 3 and 4 where these techniques are used to investigate the mechanisms of EIH. Rather than providing a valid and reliable measure of pain, the primary application of evoked potentials is to examine the integrity and function of nociceptive pathways.

2.2.4. Neuroimaging

Numerous studies have investigated the brain regions associated with pain62.

From these investigations, a large brain network involved in coding pain has been identified (i.e. the pain matrix). In this network, the insular cortex and anterior cingulate cortex appear to play the most central role63. In people with chronic pain, structural and functional abnormalities within and between these key brain areas are often reported64-

67. Several studies have also shown that combining neuroimaging with evoked potential

17 techniques can provide additional information about pain68,69. However, associations of pain and disease severity with abnormalities on neuroimaging are not always apparent70,71 and these techniques can be expensive and time-consuming. . Therefore, while neuroimaging can provide useful information about the brain areas involved in pain, it is perhaps not the best way to measure pain.

2.3. About fibromyalgia

Fibromyalgia is a polysymptomatic illness characterised primarily by chronic widespread pain in addition to joint stiffness, sleep disturbances, mood disorders and cognitive impairment72. It is more prevalent in women than in men73 and can have a significant negative impact on both physical and mental health. According to the latest diagnostic criteria, FM may be diagnosed when all of the following are met74:

• Generalised pain, defined as pain in at least 4 of 5 regions, is present

• Symptoms have been present at a similar level for at least 3 months

• Widespread pain index ≥ 7 and symptom severity score ≥ 5 OR widespread pain

index of 4-6 and symptom severity score of ≥ 9

• A diagnosis of FM is valid irrespective of other diagnoses. A diagnosis of FM

does not exclude the presence of other clinically important illnesses

The pathophysiology of FM is not fully understood, with the polysymptomatic nature of the condition likely the result of complex interplay between biological75 and psychosocial factors76. However, this understanding of the pathophysiology of FM is complicated by the number of co-morbidities that are often present (e.g. irritable bowel syndrome, major mood disorders and chronic fatigue syndrome)77. Possible factors

18 contributing to the pathophysiology of FM and the extent and severity of its symptoms include:

• Genetics78

• Dysfunction within the peripheral79-81 and central nervous systems67,82-84

• Dysfunction within the autonomic nervous system85,86

• Neuroendocrine abnormalities87,88

• Sleep disturbances89-91 and mood disorders92

While some people with FM do spontaneously remit and become pain free, FM is otherwise incurable, so the aims of management are to reduce symptoms, manage co- morbidities and improve quality of life. The most recent recommendations for FM management state that initial therapy should involve patient education and focus on non-pharmacological interventions93. If unsuccessful, then additional therapies should be used (e.g. psychological, pharmacological and multimodal), but this will differ on a case-by-case basis.

19 2.4. About knee osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease characterised radiographically by joint space narrowing, osteophyte formation and bony sclerosis and symptomatically by pain, stiffness and reduced function94. It is the most common form of arthritis and is one of the leading causes of pain, disability, activity limitation and reduced health- related quality of life4,95,96. Osteoarthritis can occur in any diarthrodial (synovial) joint and multiple joints are often involved, but it can also be limited to a single joint97. This thesis will focus specifically on OA of the knee.

The pathophysiology of knee OA is not fully understood and numerous modifiable and non-modifiable risk factors contribute to its onset, progression and severity. It is likely that the many phenotypes of knee OA98 are explained by inter- individual differences in these factors99, some of which include:

• Genetics100,101, age and sex (the prevalence of knee OA increases with age and is

higher in women)102,103

• Being overweight or obese (increases joint loading and associated inflammation

and metabolic abnormalities have negative effects as well)104-106

• Physical inactivity107,108 and participation in certain sports (e.g. soccer, elite-

level long-distance running and weightlifting)109

• Muscle , particularly of the knee extensors,110 and varus and valgus

knee joint alignments111-113

• Dysfunction within the peripheral and central nervous systems leading to the

maintenance and enhancement of pain83,114-117

20 Because OA is an incurable pathology that often worsens over time, the aims of treatment are to relieve pain and improve function and quality of life. Drugs, education and exercise are the most common treatments used in the conservative management of knee OA, but in more severe cases total knee replacement surgery may be used118.

Appropriate management of co-morbidities is also important given their negative impacts on disease severity119, patient-reported outcomes120 and physical function121.

2.5. Chronic exercise and pain

2.5.1. The effect of chronic exercise on pain in people with fibromyalgia or knee osteoarthritis

Regular physical activity can protect against the development of chronic pain108,122, even in those who are at an increased risk of developing it107. For those already living with chronic pain, cross-sectional data show that being fitter and more physically active is associated with less pain123. These studies will be described in more detail in Chapter 7. Longitudinal studies provide further evidence for the positive effect of chronic exercise on pain in people with FM and knee OA. These studies show that exercise produces small-moderate but clinically meaningful improvements in pain in these individuals17,124-126. Taken together, these studies show that regular exercise protects against the development of chronic pain and can reduce its severity and impact in people already living with it.

Evidence-based guidelines for the management of FM consistently recommend exercise as a first-line treatment93,127. Systematic reviews by the Cochrane Collaboration have consistently shown that exercise reduces pain and symptoms and improves function in people with FM, regardless of the type of exercise performed (e.g. aerobic, resistance, aquatic)39,125,126. Less mainstream exercise modalities such as meditative

21 movement therapies (e.g. Yoga and Tai Chi) can have positive effects on physical and psychological function as well128,129, but this is based on low-quality evidence.

Therefore, these types of therapies might best be used as an adjunct to more traditional exercise programs. When people with FM commence an exercise program, it is important that the volume and intensity of exercise performed are increased gradually.

This will help minimise the risk of symptom flare-ups. If symptom flares do occur, patients should be encouraged to maintain the exercise frequency but reduce the intensity130. Strategies that increase exercise adherence should also be implemented131.

In people with knee OA, pain is best managed with a combination of pharmacological and non-pharmacological interventions118,132, particularly exercise.

Interestingly, a recent meta-analysis of trials included in Cochrane systematic reviews found that exercise was as effective as oral analgesics for relieving pain secondary to knee OA19. Small-moderate short-term effects of aerobic, resistance and aquatic exercise on improving pain and function in people with knee OA have been consistently shown17,124, with these benefits persisting for 2-6 months after treatment17. Supervised aerobic exercise as well as knee extensor strength training appear the most beneficial in terms of reducing pain133, whereas the intensity at which exercise is performed does not appear to matter too much134. Positive effects of meditative movement therapies135,136 and neuromuscular exercise (i.e. exercise designed to improve sensorimotor defects and functional instability by emphasising movement quality and efficiency)137-141 have been found as well. However, these types of exercise intervention have been studied less often so more studies of their safety and efficacy are needed before they can be routinely recommended to people with knee OA. Further study of the patients that respond best to neuromuscular exercise is also warranted because, while there is little difference overall between the efficacy of neuromuscular exercise compared to regular

22 exercise for people with knee OA137-139, subgroup analyses of randomised controlled trials shows that some patients do benefit more from neuromuscular exercise142,143.

Once again, strategies that improve exercise adherence should be implemented131. These might include the use of behaviour change interventions that target common barriers and facilitators of exercise in people with knee OA144 as well as co-morbidity adapted exercise programs145.

2.5.2. Mechanisms of pain relief by chronic exercise in people with fibromyalgia or knee osteoarthritis

Despite the large number of studies that have shown chronic exercise to reduce pain in people with FM and knee OA, the mechanisms by which it does this are poorly understood. This is largely because many of the studies did not analyse which changes occurring with exercise (biological and/or psychological changes) were associated with the observed improvements in pain. Moreover, few if any of the studies investigated where in the nociceptive pathways (i.e., peripheral, spinal and/or supraspinal) changes might be occurring with exercise that could account for the consistently observed reductions in pain. As a result, the precise mechanisms of pain attenuation by chronic exercise are not known, but several possibilities exist that are likely common to people with FM and knee OA.

Improved structure and function of the musculoskeletal system is one such possibility. In people with knee OA, chronic exercise can improve several musculoskeletal factors important in the development and progression of the disease including body mass, joint alignment, proprioception, cartilage structure and function, inflammation, and muscle strength146,147, but not necessarily joint moments during gait148,149. Of these possible mediators, improvements in muscle strength are the

23 strongest contributor to the positive effect of physical exercise on improved OA symptoms147. These same mediators have not been well investigated in people with FM, but data from cross-sectional studies would suggest that they are important (i.e., having lower body weight, less inflammation and greater muscle strength is associated with less pain)123,150,151. This requires confirmation by more longitudinal studies.

Desensitisation of the nervous system is another possibility. Data from rodents show that exercise improves numerous pain-related CNS factors and that these changes are associated with improvements in pain152. Briefly, these include changes in levels of serotonin153, calcitonin gene-related peptide 154,155, glutamate156 and gamma-

157 158-160 aminobutyric acid as well as reduced activity of microglia and astrocytes . In humans, exercise-induced changes in biomarkers associated with pain pathways have been reported (e.g. inflammatory factors and neurotransmitters)161, but again it is not clear whether these changes reduce pain due to the peripheral or central actions of these factors. Preliminary evidence shows that exercise can normalise aberrant brain activity in people with FM162. This finding is in agreement with the results of a few cross- sectional studies showing that people with FM who are more physically active have more typical brain responses to pain compared to less active individuals163,164. However, not all studies have shown chronic exercise to attenuate aberrant brain responses in people with chronic pain165, so the role of changes in brain activity as a mechanism of pain relief by regular exercise remains unclear.

Improvements in sleep could be another shared mechanism through which chronic exercise improves pain in FM and OA. The reciprocal relation between sleep and pain is well described166-168 and there are many neurobiological changes that accompany sleep disturbances that are common in people with chronic pain as well (e.g. changes in pro-inflammatory cytokines, neurotrophins and neurotransmitters)169. Acute

24 and chronic exercise both improve sleep21, but whether this in turn is associated with less pain is not clear.

Finally, exercise-induced improvements in mood could be another shared mediator of the positive effect of exercise on pain in people with FM and knee OA. The role of both general (e.g. depression and anxiety) and pain-specific (e.g. catastrophizing and self-efficacy) psychosocial processes in the development and maintenance of chronic pain is clear76. Many of these psychosocial factors are positively influenced by exercise130,170-178, so it is plausible that this could result in improvements in pain either directly or indirectly through changes in both the sensory and emotional aspects of pain.

In summary, chronic exercise has small-moderate effects on reducing pain in people with FM and knee OA, but how it does this is not known. Changes in the nociceptive and pain pathways are possible and could include peripheral, spinal and/or supraspinal adaptations to exercise, but this is not known. In all likelihood, all aspects of pain perception (e.g. sensory-discriminative and cognitive-affective-motivational) are affected by chronic exercise, with changes at peripheral and central sites underlying the improvements in pain that occur with regular exercise.

2.5.3. The effect of chronic exercise on pain in healthy adults

There have been relatively few investigations of the effect of chronic exercise on pain in healthy adults. The results of these few longitudinal studies show chronic aerobic exercise to have a hypoalgesic effect179-182, particularly with regard to increasing pain tolerance. This increase in pain tolerance is consistent with studies comparing pain between athletes and non-athletes that show athletes to have a higher pain tolerance183.

Interestingly, this difference occurs largely independent of a difference in pain threshold between the groups183, implying that the ability to discriminate painful from non-painful

25 stimuli is similar between athletes and non-athletes, but that the processing of pain, post pain threshold, is different. The results of cross-sectional studies are somewhat in opposition to these longitudinal studies however, as significant associations between activity and fitness with pain are not reliably observed123. Inverse relations between pain with moderate-vigorous activity appear to be more consistent184-189, so it may be that exercise needs to be performed regularly at moderate-high intensities to exert positive effects on pain in healthy adults. This will be discussed more in Chapter 7.

2.6. Acute exercise and pain: what is exercise-induced hypoalgesia?

Exercise-induced hypoalgesia refers to the transient reduction in pain that occurs during or following an acute bout of exercise190. Exercise-induced hypoalgesia has been demonstrated for a variety of noxious stimuli (e.g. mechanical, thermal and electrical) and is typically greatest when mechanical stimuli are used to evoke pain190. This modality dependence of EIH will be investigated in Chapter 4. Exercise-induced hypoalgesia can occur in exercised and unexercised limbs190, is more robust following moderate-high intensity exercise191, and usually lasts 5-15 min following exercise cessation190. Reductions in pain after exercise typically manifest as an increase in pain threshold and/or a reduction in pain ratings after exercise, but increases in pain tolerance have also been reported. The effect of exercise on pain modulation (i.e. temporal summation and conditioned pain modulation) has also been explored, with the results of these studies showing that acute exercise typically reduces temporal summation (i.e. reduces pain facilitation)192-196 but has little effect on conditioned pain modulation (i.e., does not enhance pain inhibition)197. The effect of exercise on pain-related evoked potentials has seldom been explored198,199, but will be investigated in Chapters 3 and 4.

26 2.6.1. Magnitude of exercise-induced hypoalgesia in healthy adults and people with chronic pain

Studies of exercise-induced hypoalgesia are systematically reviewed in Chapter

7 but are briefly described hereafter. The acute effects of exercise on pain are difficult to describe concisely because several factors are important. Factors that influence the magnitude of EIH include the modality and intensity of exercise, the type of noxious stimulus used, and whether pain is assessed using a tolerance, threshold or pain rating measure. Age and sex might influence EIH as well. Typically, the effect sizes of EIH in healthy individuals correspond to an increase in pain threshold of 15-30%200 and a reduction in pain ratings of 1-2 points on an 11-point scale192,193. These changes may sound small, but reductions in pain of this magnitude are considered clinically relevant for people with chronic pain201. Whether people with chronic pain experience EIH of a similar magnitude is examined in Chapter 7.

In healthy individuals, when averaged across pain stimuli, there is a small- moderate effect of aerobic exercise on increasing pain threshold (unbiased Cohen’s d =

0.43) and reducing ratings of pain intensity (d = 0.64). The magnitude of EIH following aerobic exercise is larger with higher intensities of exercise200,202-204, is greater in exercised compared to non-exercised limbs200,204 and, when measured within an individual, is greater compared to EIH observed after isometric exercise200,205,206. For specific pain stimuli, aerobic exercise has the largest effect on increasing pressure pain threshold (d = 0.58) compared to thermal heat and cold pain thresholds (d = 0.04 and

0.30, respectively), whereas its influence on reducing ratings of mechanical and thermal pain intensity are more comparable (d = 0.69, 0.59 and 0.61 for ratings of pressure, heat and cold pain intensity, respectively)190. The effect of aerobic exercise on different types of pain will be investigated in Chapter 4.

27 Concerning EIH and isometric exercise in healthy individuals, large effects on increasing pain threshold (d = 1.05) and reducing ratings of pain intensity (d = 0.72) have been reported and appear partly dependent on the duration and intensity of the contraction200,207, though not always196,208. For example, contractions of 1 minute or less produce less EIH (d = 0.51 and 0.87 for pain threshold and ratings of pain intensity, respectively) compared to contractions lasting 2-3 min (d = 0.96 and 0.83 for pain threshold and ratings of pain intensity, respectively) or more than 5 min (d = 1.74 and

1.70 for pain threshold and ratings of pain intensity, respectively). As for intensity, contractions at 40-50% of maximal voluntary contraction (MVC) have larger effects on reducing pain intensity (d = 1.75) compared to contractions at 10-25% MVC (d = 0.67) or 80-100% MVC (d = 0.50). However, contractions at 10-25% and 40-50% MVC have similarly large effects on increasing pain threshold (d = 1.12 and 1.13, respectively) whereas contractions at 80-100% have only a moderate effect on increasing pain threshold (d = 0.57)190. This smaller EIH with higher intensity contractions is perhaps not surprising because these contractions are usually brief (< 5 s) which, as indicated above, results in less EIH. Hence, EIH from isometric exercise depends on the intensity and the duration of contractions.

Isometric exercise causes slightly larger reductions in ratings of pain intensity at contracting (d = 2.02) compared to remote body areas (d = 1.54)190, but in both instances the effect is still large. Again, these changes correspond to a reduction of approximately 1-2 points on a 0 – 10 scale209,210. The meta-analysis by Naugle et al190 found that isometric exercise had a similar effect on increasing pain threshold at contracting (d = 1.74) and remote body areas (d = 1.73). This was based on a limited number of studies however, many of which had small sample sizes. The results of more recent studies show that, like aerobic exercise200,204, increases in pain threshold after

28 isometric exercise are generally greater at exercised compared to remote body areas200,211,212.

Few studies have investigated EIH after dynamic resistance exercise in healthy adults. The meta-analysis by Naugle et al190 included only two such studies, the results of which showed that dynamic resistance exercise increased pain threshold (d = 0.83) and reduced ratings of pain intensity (d = 0.75) immediately after exercise. However, these effects quickly diminished over time such that they were only small when pain was re-assessed 15 min following exercise cessation (d = 0.21 and 0.18 for pain threshold and pain intensity ratings, respectively). Since then, three more studies of EIH with dynamic resistance exercise have been published213-215 but with somewhat conflicting results. For example, Burrows et al214 found that exercise increased pain threshold but not pain tolerance whereas Baiamonte et al213 found exercise to increase pain tolerance but not pain threshold. The exercise protocols and the methods used to assess pain were similar between these two studies so the reasons for this difference are not clear. Nonetheless, the results of these studies further confirm the hypoalgesic effect of dynamic resistance exercise in healthy adults.

In people with chronic pain, acute exercise has much more varied effects on pain. For example, the meta-analysis by Naugle et al190 showed that the magnitude and direction of the effect of acute exercise on pain varied considerably for aerobic (range of d = -1.13 to 1.50) and isometric exercise (range of d = -2.2 to 2.7). The overall effect is still one of pain reduction, at least for aerobic exercise (d = 0.15 and 0.43 for increasing pain threshold and reducing ratings of pain intensity, respectively). However, the effect of isometric exercise on pain varies greatly depending on whether pain is measured using thresholds (d = 0.17; hypoalgesic effect) or ratings of pain intensity (d = -1.92; hyperalgesic effect)190. Exercise intensity is also important, with studies in people with

29 FM showing EIH after submaximal aerobic exercise216,217, particularly for exercise at a self-selected intensity216, but exacerbations in pain following maximal aerobic exercise195.

More recent studies of EIH in people with chronic pain have confirmed this variability, with acute exercise found to increase, decrease, or cause no change in pain197,214,218-220. The particular chronic pain condition and the intensity of exercise account for some of this variability (e.g. higher intensities of exercise are more likely to exacerbate pain in people with FM190), but baseline pain and pain modulatory capacity are also important. That is, those with high pain at baseline and/or a reduced capacity to inhibit pain (i.e. reduced conditioned pain modulation) experience less EIH220,221. This will be discussed more in Chapter 7, as will the notion that EIH is disrupted in people with chronic pain.

2.6.2. Sex and age-related differences in exercise-induced hypoalgesia

Pain differs between the sexes222-224 and across the lifespan225,226 with women and older adults more likely to experience pain and be adversely affected by it.

However, evidence for an effect of sex or age on EIH is more mixed. For example, some studies have found greater EIH in women compared to men200,208,227-230 whereas others have observed no difference200,202,207,231 or have even found the opposite to be true232. Concerning age, most studies of EIH have been performed on young and middle-aged adults, but more recent investigations have begun to examine whether acute exercise reduces pain in adolescents and older adults as well. The results of these studies show that both adolescents and older adults can experience EIH of a similar magnitude to young and middle-aged adults200,208,214,228,233,234, with only limited evidence that EIH is greater in those who are younger235. Interestingly, the dose-

30 response effect of isometric exercise on EIH in young healthy adults207 appears blunted in older adults as both low-moderate and high intensity contractions were shown to elicit similar EIH208. Further investigation into sex and age-related differences in EIH is warranted as this could have important implications for exercise prescription in the clinical setting.

2.6.3. Are the effects of acute and chronic exercise on pain related?

The relation between the acute and chronic effects of exercise on pain is unclear.

The notion that the acute effect of exercise is relevant to chronic exercise adaptations in pain will be explored in more detail in Chapters 7 and 8 but is briefly outlined hereafter.

In healthy adults, there have been relatively few studies investigating whether those who are more physically active experience greater EIH. The results of these studies show that EIH is similar between inactive and active healthy adults irrespective of the type of exercise they regularly perform (i.e. aerobic or strength training) and the methods used to assess physical activity (i.e. self-report or objectively measured using accelerometry)189,236,237.

To my knowledge, only two studies have investigated whether physical activity levels predict pain responses to acute exercise in people with chronic pain. Coriolano et al (2015) found that people with knee OA who self-reported more physical activity experienced less exacerbation in pain after completing performance-based tests (six minute walk test, timed up and go test, and the modified Margaria stair climbing test) and a physiological test (submaximal arm ergometer test)238. Specifically, self-reported physical activity accounted for 37% of the variance in self-reported pain after exercise238. In people with FM, Umeda et al (2015) showed that participants who were more physically active reported less of an increase in ratings of muscle pain intensity

31 during isometric handgrip exercise239. Taken together, these results suggest that being more physically active is associated with reduced pain responses to acute exercise in people with chronic pain.

Though not a direct investigation of EIH, a study by Fleng-Sandal et al (2016) provides some interesting insight into how acute and chronic exercise responses interact to influence pain in people with chronic pain. In this study, participants with persistent knee or hip pain reported joint pain on a 0 to 10 numeric rating scale before and after an

8-week exercise program as well as before and after each exercise session completed throughout the program. The results showed that exercise reduced baseline pain (Figure

2.3) and pain-flares by exercise (Figure 2.4), with time-dependent effects evident for both outcomes. Specifically, the number of exercise sessions explained 64% of the variance of the change in baseline pain and 84% of the variance of the size of acute pain flares240.

2.7. Mechanisms of exercise-induced hypoalgesia

There are numerous biological and cognitive factors that contribute to pain, so changes in any one or more of these by acute exercise could account for EIH. It is not clear however, what these mechanisms are or whether the mechanisms are similar or distinct between healthy individuals and people with chronic pain. The contrasting magnitude of EIH between pain-free adults and people with chronic pain190 suggests that the mechanisms of EIH are disrupted in people with chronic pain. That is, some aspect of chronic pain (e.g. inflammation, sensitisation, fear of movement) interferes with the normal hypoalgesic effect of acute exercise.

32 Figure 2.3. Mean pain ratings (black diamonds) immediately before the 16 individual exercise sessions within the 8-week exercise period, at baseline examination (white square) and at 8 weeks follow-up

(white triangle). Error bars are 95% confidence intervals. n = number of people with available data at the specific time points. NRS = Numerical Rating Scale, ranging from 0 to 10, best to worst.

Figure 2.4. Increase in acute pain from before to immediately after each of the 16 exercise sessions within the 8-week exercise period (grey area). Exacerbation of pain is apparent in the earlier exercise sessions and gradually diminishes to approach a hypoalgesic response. Error bars are 95% confidence intervals. n = number of people with available data at the specific time points. NRS = Numerical Rating

Scale, ranging from 0 to 10, best to worst.

33 Before the mechanism of this disruption can be determined however, the variables that mediate EIH in healthy adults require elucidation. Such is the primary aim of this thesis.

Some of the possible mechanisms underlying EIH in healthy adults and people with FM and knee OA are outlined below.

2.7.1. Healthy individuals

The most commonly proposed mechanism of EIH is enhanced descending inhibition by activation of the opioid and cannabinoid systems. The contraction of increases the discharge of mechanosensitive afferents (i.e. A-delta and

C-fibres), which, in turn, activates central descending opioid pain pathways241,242.

Exercise also increases the release of endogenous cannabinoids243,244. These opioid and cannabinoid pathways have receptors throughout the peripheral and central nervous systems that produce analgesia when stimulated241,242 and studies in rats and mice have shown that these opioids and cannabinoids are directly involved in EIH through actions at both peripheral and central sites245-248.

Human studies investigating the role of opioids and cannabinoids in EIH have yielded more equivocal findings. For example, opioid antagonists such as naloxone and naltrexone have been shown to increase249, decrease250, or have no effect on EIH192,250-

253. Moreover, correlations between EIH and exercise-induced changes in plasma concentrations of beta-endorphins and endocannabinoids are not always observed181,192,251,253. A limitation of these human investigations is that they are more constrained than rodent studies in their ability to investigate whether opioids and cannabinoids are acting through peripheral and/or central actions to influence pain after exercise. Interestingly, studies in rats have shown that opioids and cannabinoids have different effects on pain when they are co-administered peripherally (antagonistic effect,

34 less pain relief)254 or centrally (synergistic effect, more pain relief)255-257. Therefore, it is possible that the concomitant release of opioids and cannabinoids by exercise could augment EIH if their actions are predominantly central, but could decrease EIH if they act more peripherally. This is speculative but could be an interesting avenue of future research. The contribution of peripheral factors to EIH will be investigated in Chapters

3-5 of this thesis.

Several other substances have been implicated in EIH as well. For example, the

258-260 nitric oxide/cGMP/KATP pathway contributes to EIH in mice and rats , possibly through an increase in the release of serotonin from neurons within the periaqueductal grey260 and the actions of nitric oxide on reducing sensitivity of spinal neurons261,262.

Exercise-induced hypoalgesia might also be a form of stress-induced analgesia, related to the release of various stress hormones during exercise. However, evidence to support this in humans is mixed. For example, EIH is related to increases in growth hormone during exercise263, but another study found that the suppression of exercise-induced growth hormone release by cyproheptadine had no effect on EIH264. Dexamethasone, a steroid medication, has been shown to attenuate EIH by reducing secretion of adrenocorticotropin265, however other studies have found no effect of dexamethasone on pain in healthy individuals266. A small pilot study of seven healthy adults showed that exercise-induced changes in neuropeptide Y, allopregnalone, pregnalone, and dehydroepiandrosterone were related to EIH267. However, as concentrations of these substances were only measured in the plasma, it is not clear whether they were acting through peripheral or central mechanisms to influence pain. Moreover, as this was only a small pilot study, more studies are needed to confirm the findings.

35 A primary aim of this thesis was to explore the contribution of peripheral factors to EIH. Accordingly, the substances released during exercise that act on nociceptors and their afferents are described in more detail hereafter. Nociceptors express receptors and contain ligands268 for many of the substances released during exercise (e.g. opioids, cannabinoids, catecholamines and nitric oxide), so it is reasonable that exercise-induced changes in these substances could influence nociceptor sensitivity and subsequently pain. While direct evidence for this notion is lacking, it is partially supported by studies in rats showing the peripheral administration of opioid, cannabinoid, catecholamine and nitric oxide antagonists to diminish or abolish EIH246,247,258,269. The exact site of peripheral nervous system adaptation mediating these effects was not studied, but it was hypothesised that the aforementioned analgesic substances act alone or in combination to reduce pain by inhibiting the release of nociceptive peptides and transmitters from primary afferent terminals, subsequently reducing the flow of nociceptive input to the

CNS 269,270.

While acute exercise can transiently reduce pain, the intensity of exercise required to produce this hypoalgesic effect is itself often painful. This pain arises largely from peripheral changes as well. Both skeletal muscle contraction and the resultant metabolic acidosis stimulate group III/IV nociceptive afferents, giving rise to sensations of fatigue and pain271,272. This pain is largely due to the number of algesic substances that are released during exercise that activate and sensitise nociceptors via receptors such as transient receptor potential vanilloid subfamily member 1, acid sensing ion channels and adenosine triphosphate-gated P2X receptor cation channels.272,273.

Interestingly, exogenous administration of some of these algesic substances (i.e. protons, lactate and ATP) has been demonstrated to produce pain in humans only when

36 delivered in combinations and concentrations typical of what is observed with exercise274. The role of algesic substances in EIH will be discussed more in Chapter 5.

In addition to changes in circulating levels of algesic and analgesic substances, exercise-induced changes in the cardiovascular system have also been proposed as a mechanism of EIH. That is, elevations in blood pressure by exercise are thought to attenuate pain via baroreceptor related mechanisms (i.e., the activation of arterial baroreceptors by exercise subsequently activates pain-related brain areas involved in pain modulation). While it is true that people with high blood pressure are less sensitive to pain (i.e. hypertension-associated hypoalgesia)275, there is currently little evidence that acute changes in blood pressure by exercise are related to EIH232,276-280. Moreover, acute increases in blood pressure by exercise could not account for the persistence of

EIH after exercise (e.g. 15 min following exercise cessation281) as blood pressure would have presumably returned to baseline by this time.

The influence of exercise on reducing the sensitivity of the CNS has also been explored as a mechanism of EIH. These studies show that acute exercise can reduce temporal summation193-195 and increase thresholds to elicit the nociceptive withdrawal reflex282, though there is some evidence contrary to the latter observation199. These results imply that exercise can reduce pain through reductions in CNS sensitivity at spinal and supraspinal levels, but exactly where in the nociceptive pathway these changes occur is not known. Improved efficacy of descending inhibitory pathways by exercise has been studied as a mechanism of EIH as well, but there is little direct evidence to support this. For example, Meeus et al (2015) found no effect of aerobic exercise on conditioned pain modulation in healthy individuals197 and Ellingson et al

(2014) showed that EIH was comparable for non-painful and painful exercise280, even though the latter should have evoked a larger ‘pain inhibits pain’ effect. A few studies

37 have found small positive correlations between conditioned pain modulation and

EIH233,237,279 suggesting that the two may share similar mechanisms; however EIH is usually larger and more enduring than conditioned pain modulation so the two are likely distinct200,233.

Changes in pain cognition might also account for some of the effect of acute exercise on pain. It has been shown that exercise can reduce ratings of pain unpleasantness in the absence of a change in ratings of pain intensity211, suggesting that alterations in the appraisal of noxious stimuli contribute to EIH. Cognitive and psychosocial factors including pain self-efficacy, coping strategies, fear of pain and stress are known to underlie some of the difference in pain between athletes and non- athletes283-285, but their relation to EIH is less clear. For example, several studies have shown that individuals with higher levels of catastrophizing experience less

EIH194,286,287, though this is not always observed233 and correlations between EIH and other psychosocial factors (e.g. fear of pain, pain attitudes and anxiety) appear negligible233. Therefore, the contribution of cognitive factors to EIH remains poorly understood but appears limited. More studies are needed to investigate whether these cognitive factors are related to EIH and, more importantly, whether they can be manipulated to augment it. This will be investigated in Chapter 6.

38 2.7.2. Fibromyalgia and knee osteoarthritis

The mechanisms of EIH in people with chronic pain are equally if not more unclear. Because exercise has such varying effects on pain within and between people with FM and knee OA (Chapter 7), it is difficult to determine whether there is a consistent mechanism that contributes to changes in pain with acute exercise. Moreover, it is not clear if the mechanisms of EIH in people with chronic pain are the same as healthy adults and are just disrupted, or whether separate mechanisms related to the presence of chronic pain are involved as well.

The fact that EIH can occur at exercised and remote sites in people with chronic pain shows that EIH is not always disrupted in these individuals216,219,288,289. However, there are also several demonstrations that exercise with a painful joint or muscle can either diminish EIH compared to when a non-painful body part is exercised (i.e., exercise of the upper limb in people with knee OA, but pain measurement in the lower limb)214 or, worse, can increase pain290,291. These results are both opposite to what is normally seen in pain-free adults where EIH is usually greatest for the exercised body part. Therefore, the results of the above studies provide some evidence that, compared to healthy individuals, the mechanisms of EIH in people with chronic pain are both similar and distinct. However, because the mechanisms of EIH are so poorly understood in both groups, there is little direct evidence to support this. Some of the possible mechanisms that might disrupt EIH in people with chronic pain are outlined below.

Regarding mechanisms of EIH that may be similar, but disrupted, in people with chronic pain compared to healthy adults, altered excitability of the CNS after exercise is perhaps the most obvious. In healthy adults, acute exercise reliably reduces temporal summation193,195,196 whereas the opposite effect has been observed in people with chronic pain195,221. In contrast, one of the few studies to combine acute exercise with

39 analgesic medication showed that paracetamol and placebo had comparable effects on temporal summation and conditioned pain modulation after exercise in healthy adults and people with chronic pain197. As paracetamol is a predominantly central acting agent that can affect opioids, cannabinoid and serotonergic pathways292, this finding provides little support to the notion that exercise reduces pain through central changes in these pathways or that differences in the sensitivity of these pathways via exercise accounts for the greater EIH in healthy adults compared to people with chronic pain. More studies using drugs with less ubiquitous effects would be useful to further investigate how different substances are involved in EIH in humans and whether these differ between healthy adults and people with chronic pain.

As for mechanisms of EIH that might be distinct between healthy adults and people with chronic pain, reductions in inflammation by acute exercise are one such possibility. Inflammation plays a key role in the pathogenesis of FM and knee OA293,294, so it is possible that reductions in inflammation by exercise295 may reduce pain in these individuals. However, the results of studies examining the effect of acute exercise on inflammation in people with FM and knee OA are mixed and the relation between the changes in inflammatory markers and pain has seldom been explored296-300. Moreover, differences in the exercise-induced changes in inflammatory markers between people with chronic pain and healthy adults were only sometimes296,298, but not always297,298, observed. Therefore, it remains unclear to what extent EIH is related to acute changes in inflammation by exercise in people with FM or knee OA or whether this is a distinct mechanism of EIH in these populations.

Cortically, differences in the activity of pain-related brain regions after exercise have been observed between people with FM and healthy adults288. Specifically, greater brain activity bilaterally in the anterior insular after exercise was observed in people

40 with FM whereas greater activity in the right parietal operculum and the right pre/postcentral gryus after exercise was observed in healthy individuals. Despite these differences however, no differences between the groups were observed in the association of exercise-induced brain changes with EIH288. On this basis, there is currently little evidence to support the hypothesis that EIH differs between healthy adults and people with chronic pain due to different effects of acute exercise on cortical activity in pain-related brain areas.

2.8. Conclusion

This chapter demonstrates that chronic and acute exercise have variable effects on pain in healthy adults and people with FM and knee OA and that pain responses to acute and chronic exercise in these populations are not clearly related. This chapter also highlights the current lack of understanding about the mechanisms through which exercise influences pain. Hence, the primary aim of this thesis is to better understand why acute exercise affects pain.

In humans, the mechanisms of EIH have largely been probed with drug studies that have produced mixed results and offer only limited insight into where in the nervous system the effects are occurring. Animal studies have used drugs with more discrimination to extend on these human investigations, but the results are by no means conclusive. Chapters 3, 4 and 5 of this thesis employ, for the first time, neurophysiological and occlusion techniques in an attempt to better understand the role of peripheral changes to EIH in humans. Evidence from human studies that pain education, cognitive factors and expectations around pain and exercise are related to

EIH show that pain cognition is likely important for EIH as well, but this has not been

41 directly investigated. Chapter 6 of this thesis will examine whether cognitive factors do indeed contribute to EIH in healthy adults.

Owing to the lack of certainty of the mechanisms of EIH in healthy adults, it is beyond the scope of this thesis to investigate the mechanisms of EIH in people with FM or knee OA. Nonetheless, the review of literature in this chapter does suggest that EIH is disrupted in people with these conditions. To clarify this, a systematic review and meta-analysis of EIH in healthy adults and people with chronic pain (FM and knee OA) is performed in Chapter 7 to identify the extent of this disruption. Studies examining associations between pain and activity or fitness are also systematically reviewed.

42 Chapter 3:

Exploring the mechanisms of exercise-induced hypoalgesia using

somatosensory and laser evoked potentials

3.1. Abstract

The aim of this study was to examine the effect of exercise on somatosensory evoked potentials (SEPs), laser evoked potentials (LEPs), pressure pain thresholds

(PPTs) and heat pain thresholds (HPTs). These were recorded before and after 3-min of isometric elbow flexion exercise at 40% of the participant’s maximal voluntary force, or an equivalent period of rest. Exercise-induced hypoalgesia was confirmed in two experiments (Experiment 1 – SEPs; Experiment 2 – LEPs) by increased PPTs at biceps brachii (24.3% and 20.6% increase in Experiment 1 and 2, respectively; both d > 0.84 and p < 0.001) and first dorsal interosseous (18.8% and 21.5% increase in Experiment 1 and 2, respectively; both d > 0.57 and p < 0.001). In contrast, HPTs were not significantly different after exercise (forearm: 10.8% increase, d = 0.35, p = 0.10; hand:

3.6% increase, d = 0.06, p = 0.74). Contrasting effects of exercise on the amplitude of

LEPs (14.6% decrease, d = -0.42, p = 0.004) and SEPs (10.9% increase, d = -0.02, p =

1) were also observed, while an equivalent period of rest showed similar habituation

(LEP: 7.3% decrease, d = -0.25, p = 0.14; SEP: 20.7% decrease, d = -0.32, p = 0.006).

The differential response of PPTs and HPTs exercise is consistent with relative insensitivity of thermal nociception to the acute hypoalgesic effects of exercise. The different behaviour of the SEPs to the LEPs following exercise may reflect non- nociceptive contributions to the somatosensory evoked potential, but could also indicate that excitability of peripheral nociceptors contributes to exercise-induced hypoalgesia.

43 3.2. Introduction

Exercise relieves pain for many chronic diseases17,18,39, but the mechanisms are poorly understood. The well described phenomenon of exercise-induced hypoalgesia

(EIH)190 suggests that exercise can reduce pain directly via adjustments at some point(s) in the transduction, transmission and processing of noxious stimuli. Though typically investigated for acute bouts of exercise, there is evidence from cross-sectional185-187,301 and longitudinal179,180 studies that long-term exercise can lead to sustained hypoalgesic effects in healthy adults. EIH is usually measured by obtaining a threshold, tolerance and/or rating of a noxious stimulus and is greatest when mechanical stimuli are used to evoke pain190,302. Moderate effects of exercise on pain are observed when noxious thermal stimuli are used whereas for electrical stimuli, the effect of exercise is smaller still and is less frequently observed190.

Numerous human and animal investigations have failed to clearly identify the mechanism(s) of EIH. Animal studies have shown that exercise-induced changes in opioids, cannabinoids, catecholamines and nitrite might all contribute to EIH247,248,258-

260,269, whereas human investigations have yielded more equivocal findings192,250,251,264,265. It has also been proposed that exercise activates an inhibitory arterial baroreceptor mechanism that causes the hypoalgesia276, but there is little evidence to support this232,277. Several studies in healthy individuals have found a positive association between the magnitude of conditioned pain modulation (i.e., pain inhibits pain) and the robustness of EIH233,237. However, Ellingson et al. (2014) showed that conditioned pain modulation is likely only a minor contributor to EIH.

Few of these studies in animals, and none in humans, have permitted description of the sites in the nervous system from which EIH arises. For example, animal studies have shown that the effects of drugs acting as or blocking neurotransmitters might arise

44 from several sites in the peripheral and central nervous systems153,246,247,258,303,304. These include activation of peripheral alpha-2 adrenoceptors and subsequent inhibition of

269 primary afferents or the spinal and supraspinal actions of the nitric oxide/cGMP/KATP pathways259.

Non-invasive neurophysiological techniques have the potential to translate and extend these findings in humans. Laser evoked potentials (LEPs) and somatosensory evoked potentials (SEPs) include components (termed ‘N2’ and ‘P2’) that scale with the intensity and pain rating of a noxious stimulus55, and occur at latencies consistent with the activation of A-delta or group III afferents56,305. The associated laser and electrical stimuli activate, respectively, nociceptors and nerve axons53,54 and a comparison of

LEPs and SEPs provides some insight into the role of the peripheral nociceptor in EIH.

That is, if LEPs but not SEPs were to change with exercise, this may indicate a role of the peripheral nociceptor in EIH. However, there are also differences in the ascending and central pathways that contribute to the LEP and SEP, even when a noxious electrical stimulus is used to elicit an SEP306,307.

To the best of my knowledge, only one study has examined LEPs before and after exercise198 and few studies have examined SEPs before and after exercise198,199,308.

Only one of these studies was designed to investigate EIH199 and it is unclear to what extent LEPs and SEPs are influenced by exercise; in particular the components of these potentials that are associated with pain. It is well established that the SEP is inferior to the LEP for investigating the activity of nociceptive pathways57. In this investigation, the SEP provided data that were used as a complement to the primary measure of the

LEP. The SEP in response to noxious stimulation has been used for a similar complementary purpose in a number of recent papers309-311.

45 The aim of this study was to examine the effect of isometric exercise on LEPs and SEPs to identify changes in excitability of neural pathways accompanying EIH.

Pressure pain thresholds (PPTs) and heat pain thresholds (HPTs) were measured to quantify the magnitude of EIH and ratings of pain intensity, pain unpleasantness and anxiety were also recorded throughout the experiments. It was hypothesised that increases in pressure and heat pain thresholds following exercise would be accompanied by a reduction in the amplitude of LEPs and SEPs.

3.3. Methods

3.3.1. Participants

This study comprised two experiments to examine the influence of acute isometric exercise on SEPs (Experiment 1) and LEPs (Experiment 2). For each experiment, participants were recruited through advertisements placed on billboards around campus. Eligibility criteria included 1) apparently healthy with no history of chronic pain or chronic disease, 2) between the ages of 18 and 60 years, and 3) absence of a current diagnosis of depression or any other major mood disorder. Sixteen volunteers (age: 22.3 ± 2.9 years, 9 females) participated in Experiment 1 and 16 volunteers (age: 24.8 ± 6.0, 5 females) participated in Experiment 2, of whom 6 had previously participated in Experiment 1. All participants were students from the university.

46 3.3.2. Procedures

All procedures were approved by the University of New South Wales Human

Research Ethics Committee (HC 14065) and conformed to the requirements of the

Declaration of Helsinki (2008). Written informed consent was obtained from each participant prior to testing. Before the experiment, participants were asked to abstain from vigorous exercise for 24 h and caffeine for 4 h. Compliance to these requests was confirmed verbally at the start of the session. Each experiment consisted of a single session and lasted approximately 2 - 3 h. The procedures for each experiment are outlined in Figure 3.1. Briefly, in each experiment, pain thresholds, pain ratings and

EEG responses to painful stimuli were measured before and after isometric exercise and before and after rest. In Experiment 1, evoked potentials during electrical stimulation were recorded on five occasions (i.e. baseline, before and after rest, and before and after exercise) and pressure pain thresholds were measured before rest as well as before and after exercise. In Experiment 2, evoked potentials during laser heat stimulation were recorded on five occasions (i.e. baseline, before and after rest, and before and after exercise) and pressure pain thresholds and heat pain were measured before rest as well as before and after isometric exercise. The order of exercise or rest was counterbalanced across participants in each study. A 30 min wash out period was included to ensure possible exercise-induced alterations in pain were gone prior to commencing the next block of evoked potential recordings. This was confirmed by the re-assessment of PPTs

(Experiment 1 and 2) and HPTs (Experiment 2 only) prior to the next block of evoked potential recordings. The 30 – 50 min required to setup the recording and stimulation equipment ensured that any mild hypoalgesic effect of the preliminary maximal voluntary contractions (MVCs) would have subsided before the collection of evoked potentials.

47 3.3.2.1. Electrical stimulation for SEPs (Experiment 1)

Electrical stimuli to the digital nerve (1-ms rectangular pulses, frequency 2 Hz,

Grass S88, Grass Technologies, Warwick, RI, USA) were delivered through flexible metal ring electrodes attached to the participant’s right index finger (cathode proximal).

Adhesive electrode gel (Tensive Conductive Adhesive Gel, Parker Laboratories Inc,

Fairfield, NJ, USA) and constant current stimulation (Grass CCU1, Grass Technologies,

Warwick, RI, USA) was used to maintain consistency of the electrical stimulus throughout the experiment. Each block of stimulation lasted approximately 10 min and consisted of 1000 stimuli (500 at each of two different intensities, delivered randomly).

Each block of stimulation comprised five smaller series (100 at each of two different intensities, delivered randomly), separated by 45-60 s.

To determine the intensities used for stimulation, the participant’s perceptual threshold was determined by the ascending method of limits and the stimulus intensity corresponding to 1.5 times perceptual threshold was calculated. Then, using a 0-10 numerical and categorical pain rating scale (0 = no pain and 10 = worst possible pain), stimuli were delivered at progressively increasing intensities to determine the intensity that elicited mild pain (3/10) and moderate pain (5-6/10). A short train of stimuli

(approximately 10 s) was then delivered at intensities corresponding to 1.5 times perceptual threshold, mild pain and moderate pain, and participants were asked to rate the intensity of pain produced by each short train. This procedure was to ensure that any wind-up effect of repeated stimulation was accommodated in the pain ratings and, if necessary, intensities were adjusted to achieve the desired pain ratings on the scale described above (i.e., moderate pain (5-6/10)).

For the first block of stimulation (modulation), stimulus intensities corresponding to mild and moderate pain were used to determine whether SEP

48 amplitude scaled with different intensities of noxious stimulation. For the remaining four blocks of electrical stimulation that occurred before and after rest and before and after exercise, the two stimulus intensities used were non-painful (1.5 times perceptual threshold) and producing moderate pain (5-6/10). During this time, participants were asked to attend to the stimulation occurring at their finger to minimise the possible influence of distraction on the SEP waveform. Following each series of stimulation, participants provided ratings of pain intensity using the scale described above and ratings of pain unpleasantness using a 0-10 pain unpleasantness scale (0 = not at all unpleasant, 10 = most unpleasant imaginable). Anxiety ratings were also obtained after the first, third and fifth series of stimulation within each block on a 0-10 scale (0 = not at all anxious, 10 = worst anxiety imaginable) to account for the possible influence of anxiety on SEP amplitude166.

3.3.2.2. Heat stimulation for LEPs (Experiment 2)

Throughout the experiment, all persons present in the laboratory wore protective laser goggles for safety. Radiant heat stimuli (30 - 50 ms duration, 10.6 µm wave length, 3.5 mm beam diameter) were delivered to the dorsal surface of the participant’s right hand by a carbon dioxide laser (Synrad 48-1 10 W series, Synrad Inc., Mukilteo,

WA, USA). The laser beam was visualised with a He-Ne diode pointer (DP, Synrad

Inc,) and laser output was controlled by custom built software (LabVIEW version 9.0,

National Instruments, Austin, TX; Spike 2, Cambridge Electronic Design, Cambridge,

UK) and a closed-loop stabilisation kit (UC-2000, Synrad Inc.). An area of approximately 4 x 4 cm2 between the wrist and the base of the 3rd - 5th metacarpals was chosen as the target zone for stimulation. To minimise skin damage and reduce the likelihood of nociceptor sensitisation or fatigue, successive laser stimuli were delivered

49 to different locations on the hand in a random order such that the same site was never stimulated more than 2 - 3 times throughout the experiment. The participant’s right hand and forearm were placed in an opaque acrylic box lined with laser absorbent cloth and their palm was rested against a padded block with the forearm semi-supinated. Skin temperature was monitored continuously throughout Experiment 2 using a digital thermode affixed to the base of the participant’s right wrist near the anatomical snuffbox.

Figure 3.1. Panel A) and B) show the order of procedures in Experiment 1 (SEPs) and Experiment 2

(LEPs), respectively, when exercise was performed first. In both experiments, evoked potentials were recorded on five occasions during electrical stimulation (Experiment 1) or laser heat stimulation

(Experiment 2). Pressure pain thresholds were assessed before and after isometric exercise and before quiet rest in each experiment. Heat pain thresholds were assessed before and after isometric exercise and before quiet rest in Experiment 2 only. A 30 min wash out period was included to ensure possible exercise-induced alterations in pain were gone prior to commencing the next block of evoked potential recordings. This was confirmed by the re-assessment of PPTs (Experiment 1 and 2) and HPTs

(Experiment 2 only) prior to the next block of evoked potential recordings. The order of exercise or quiet rest was counterbalanced across participants in each study.

50 To familiarise participants with the laser stimulation, a single stimulus was delivered every 5 s at an increasing energy (0.5 mJ/mm2) until perceived by the participant (i.e., perceptual threshold). This procedure was repeated two more times and perceptual threshold was recorded as the average of the three trials. Single stimuli were then delivered every 5-6 s at increasing energies to determine the intensity that corresponded to mild pain and moderate pain (i.e., 3/10 and 5/10, respectively). Five blocks of LEPs were recorded throughout the experiment. The first block (modulation) comprised 60 total stimuli and was delivered in two separate series of 30 stimuli (15 each of mild and moderate pain, pseudo-random in order, (7-9 s inter-stimulus interval) with approximately 30 s between each series. For the remaining four LEP recording blocks occurring before and after exercise and before and after quiet rest, 30 moderately painful stimuli were delivered in two separate series of 15 (7-9 s inter-stimulus interval and 30 s between series). Ratings of pain intensity, pain unpleasantness and anxiety were recorded after each series. Throughout the recording of LEPs, participants were asked to count the number of stimuli they received at their hand. This was done to ensure attention to the laser stimuli and to minimise the influence of distraction on the

LEP waveform.

3.3.2.3. EEG recordings

During the recording of evoked potentials in each experiment, participants were seated upright in a dark and quiet room. Silver/silver chloride electrodes (10 mm diameter) were placed along the scalp midline (Cz, Fz and Pz) and left side of the head

(C3) and referred to the left earlobe (10-20 International system). A large ground electrode was placed across the forehead. Electrode sites were prepared with NuPrep

(Weaver and Company, Aurora, CO, USA), abraded with sandpaper (CIVCO, Kalona,

51 IA, USA) and adhered with Ten20 conductive paste (Weaver and Company) and tape.

A small plastic probe was used to further agitate the skin as necessary to reduce impedance at each electrode to less than 5000 ohms. Contact impedance was monitored and recorded throughout each experiment using built-in features of the EEG amplifiers and kept below 5000 ohms.

The EEG signal was amplified 5000x for SEPs and 1000x for LEPs (NL844 and

NL820A, Digitimer NeuroLog System, Hertfordshire, England), filtered (0.1 Hz – 2 kHz, NL144 and NL135/6,) and collected on a computer (Spike 2 and Micro1401 mkII,

Cambridge Electronic Design) at 5000 samples per second. Electrooculography (EOG) was recorded using 6 mm gold cup electrodes placed above and below the left eye and was monitored continuously by one of the experimenters. When necessary, participants were guided to relax to maintain the baseline stability of these signals.

3.3.2.4. Pressure pain threshold

In each experiment, PPT was assessed over the biceps brachii and first dorsal interosseous muscles. All measurements were made on the right side of the body. Two practice trials were performed on the left biceps brachii prior to testing to familiarise the participant with the procedure. The rubber-tipped probe of a handheld algometer

(Wagner Force 10 FDX-25, Wagner Instruments, Greenwich, CT) was applied perpendicularly to the participant’s skin and the force was increased gradually at a rate of approximately 1 kg/s. Participants were instructed to give a verbal command of

‘‘stop’’ when the sensation of pressure turned to pain. This procedure was repeated two more times for a total of three measurements per site. Pressure pain threshold was recorded as the average of these three measurements.

52 3.3.2.5. Heat pain threshold

In Experiment 2 only, brief laser stimuli (20 ms pulse width) were delivered at a frequency of 5.55 Hz at a progressively increasing intensity (~0.5 mJ/mm2/s) to the dorsal surface of the participant’s right hand. Participants were instructed to give a verbal command of ‘‘stop’’ as soon as the stimulation became painful. This procedure was repeated three more times for a total of four measurements and HPT was recorded as the average of these four measurements. The frequency, duration and intensity of this stimulation was chosen so that HPTs were obtained over a similar time period and evoked a similar sensation to PPTs (i.e., a continuous sensation, gradually increased in intensity until painful). After several experimental sessions, an assessment of HPT at the right forearm was added (n = 13), akin to measuring PPTs at the hand and upper arm. The forearm was used because of safety concerns about directing the laser at the upper arm, nearer the face and eyes.

3.3.2.6. Isometric exercise

In each experiment, participants were seated upright in an adjustable chair with their forearm neutral and rested on a padded support parallel to the floor. Participants grasped, with their right hand, a custom built device that was instrumented with a force transducer (SBO-100, Transducer techniques, Temecula, CA, USA). The force transducer measured the medially-directed force of elbow flexion via a hand grip. The signal was amplified and filtered (200x, 0-100 Hz, NL109, Digitimer Neurolog System) and was recorded at 200 Hz (Spike 2 software). At the start of the experiment, participants performed three MVCs, each separated by 60 s, and the highest value of these three attempts was recorded as MVC. For the experimental isometric exercise task, a 3-min sustained contraction at 40% of MVC was performed. During this time,

53 participants were asked to match the target force displayed on a monitor and to provide ratings of perceived exertion (RPE) every 30 s on a Borg 0-10 scale.

3.3.2.7. Quiet rest and wash out

In each experiment, a period of quiet rest (approximately 4 min) was included to correspond to the time it took to set up and perform the isometric exercise task. During quiet rest, participants remained seated and relaxed but were allowed to talk to the experimenters. A wash out period of approximately 30 min was also included to ensure any hypoalgesic effect of the exercise would have subsided before the collection of the next series of evoked potentials.

3.3.3. Data processing and statistical analysis

3.3.3.1. EEG and evoked potential analysis

Evoked potentials were extracted using computer software (Spike 2) by averaging the EEG signal following the electrical or laser stimuli. Prior to averaging, signals were visually inspected and stimulation triggers were removed when artefacts were apparent in the EOG recording. On average (mean ± SD), 10 ± 15 triggers were removed prior to averaging for SEPs and 2 ± 3 triggers were removed prior to averaging for LEPs. A digital filter (Finite Impulse Response, 30-Hz lowpass) was applied to the

EEG recordings before processing the LEPs. No digital filtering was necessary for the

SEP recordings. In Experiment 1, EEG data were divided into 550-ms epochs, each lasting from -50 ms to +500 ms with respect to stimulus onset. The N2P2 component of the SEP was analysed at each of the 4 EEG sites according to the procedures described by Luck (2005)312. The baseline signal was calculated as the root mean square amplitude in the 50 ms prior to each electrical stimulus. The N2P2 onset was quantified

54 as the time in which the EEG signal was 1 standard deviation above baseline (negative polarity) 100-300 ms after stimulus onset. N2P2 amplitude was calculated as the difference between the N2 and P2 peak amplitudes, which were measured from 100-300 ms (N2) and 150-400 ms (P2). N1 amplitude was calculated for the SEPs as the difference between the baseline signal and the peak negative polarity 20-60 ms after stimulus onset. In Experiment 2, EEG data were divided into 1050-ms epochs, each lasting from -50 ms to +1000 ms with respect to stimulus onset. The N2P2 component was analysed at each of the 4 EEG sites as described above but for slightly later time periods (N2 150-500 ms; P2: 200-550 ms) to account for the longer stimulus duration and activation of nociceptors by the laser heat stimulus.

3.3.3.2. Sample size calculations

Each participant was tested before and after exercise intervention and rest, meaning that they acted as their own control, which allowed changes to be reliably detected with relatively few participants. Notably absent from most evoked potential studies313, sample size calculations were performed using G*Power (version 3.1.9.2)314.

These were made for the pain threshold and evoked potential measures on the basis of changes observed in previous investigations. For the effect of acute exercise on pressure pain thresholds, I estimated a mean ± SD change of 0.30 ± 0.16 kg/cm2 203, corresponding to a large effect size (d = 1.87). On this basis, it was estimated that a sample size of ≥ 5 participants was required to detect exercise-induced hypoalgesia using pressure pain thresholds with a repeated measures test, 80% power and alpha of

0.05. Very limited data were available to estimate the effect of exercise on pain-related evoked potentials. Small to moderate effect sizes were anticipated on the basis of reported changes in the P1 (0.8 ± 0.5 mV) and P2 (0.15 ± 0.13 mV) amplitude of

55 somatosensory evoked potentials after acute exercise308 and from changes in the nociceptive flexion reflex following exercise (11 ± 12 mA)282. A sample size of 8 – 12 was computed to be required to detect a small-moderate effect size (d = 0.4) of change in the evoked potentials. A target sample of 14 - 16 participants was planned for each study to provide more power and precision, and to account for the possibility of participant drop out.

3.3.3.3. Statistical analysis

Descriptive statistics were calculated using the IBM Statistical Package for

Social Sciences (version 22, Chicago, IL, USA). Differences in pressure and heat pain thresholds were examined using a repeated measures ANOVA and differences in pain ratings and evoked potential amplitude were tested with a two way repeated measures

ANOVA (time: pre, post; condition: rest, exercise). To compare changes in PPTs and evoked potential amplitude between Experiment 1 and 2, a repeated measures ANOVA with time (pre, post) and condition (rest, exercise) as within subject factors and the experimental condition (SEP – Experiment 1 or LEP – Experiment 2) as a between subjects factor was used. Normality of the data was assessed using the Shapiro-Wilk

Test. Greenhouse-Geisser corrections were used if sphericity was violated. To identify sources of differences revealed by the ANOVA, paired sample post hoc t-tests were conducted with alpha set at 0.05 and the p values for the t-tests multiplied by the number of comparisons within the ANOVA model. Effect sizes (unbiased Cohen’s d) and 95% confidence intervals (CIs) were also calculated to aid comparisons between different measures and between Experiment 1 and 2. Effect sizes (ES) were interpreted as small (0.2), medium (0.5) or large (0.8) 315. The unbiased Cohen’s d was used because it is a conservative estimate that avoids overestimation of effect sizes when

56 using small sample sizes (i.e., n < 30). The 95% CIs of the effect size were calculated using a non-central t distribution316. Except where stated, values are reported as the mean and 95% CI.

3.4. Results

3.4.1. Isometric exercise

All participants were able to maintain the target force during the 3-min contraction. The average RPE (mean ± SD) at the end of the contraction was 7.9 ± 1.4 and 9.2 ± 1.2 in Experiment 1 and 2, respectively. This corresponded to a perceived effort between ‘very hard’ and ‘very, very hard (maximal)’. The average RPE at the end of isometric exercise was higher in Experiment 2 than Experiment 1 (d = 0.93 (0.21 to

1.68), p = 0.01).

3.4.2. Pressure pain thresholds

Data for PPTs are presented in Figure 3.2. ANOVA indicated a significant effect of time for PPT over the biceps brachii (Experiment 1: (F(2,30) = 33.06, p < 0.001;

Experiment 2: F(2, 30) = 69.42, p < 0.001) and first dorsal interosseous muscles

(Experiment 1: F (1.15, 17.19) = 10.53, p = 0.008; Experiment 2: F (2,30) = 68.28, p < 0.001).

T-tests showed there was a large and significant effect of isometric exercise on increasing PPT over biceps brachii (Experiment 1: 24.3 ± 17.6% increase (mean ± SD), d = 0.84 (0.45 to 1.3), p < 0.001; Experiment 2: 20.6 ± 8.3% increase (mean ± SD), d =

0.99 (0.59 to 1.49), p < 0.001) and a moderate and significant effect on increasing PPT over first dorsal interosseous (Experiment 1: 18.8 ± 11.6% increase (mean ± SD), d =

0.57 (0.28 to 0.9), p < 0.001; Experiment 2: 21.5 ± 11.1% increase (mean ± SD), d =

0.67 (0.42 to 0.98), p < 0.001), whereas PPTs at both muscles were similar before rest

57 and before exercise (range of mean change = 0.9% to 4.7% increase, all d < 0.13 and p

> 0.32; Figure 3.2). The magnitude of EIH, as quantified by the increase of PPTs, was similar between the experiments at biceps brachii (Experiment 1: 0.81 ± 0.53 kg/cm2

(mean ± SD); Experiment 2: 1.00 ± 0.39, p = 0.25) and first dorsal interosseous

(Experiment 1: 0.70 ± 0.55 (mean ± SD); Experiment 2: 0.89 ± 0.35; p = 0.26).

3.4.3. Heat pain thresholds

Data for HPTs (Experiment 2) are presented in Figure 3.2. There was no significant effect of time on HPTs over the forearm (F(2,24) = 2.23, p = 0.10) or hand

(F(1.27,19.05) = 0.39, p = 0.74).

3.4.4. Electrical and laser heat stimulation for the evoked potentials

The average electrical stimulus intensities used to elicit mild and moderate pain during modulation in Experiment 1 were 23.5 ± 12.0 mA and 43.0 ± 21.5 mA (mean ±

SD), respectively. For the remaining four blocks of stimulation, the intensities that corresponded to 1.5 times perceptual threshold and moderate pain were 3.0 ± 0.6 mA and 42.0 ± 20.0 mA (mean ± SD), respectively. In Experiment 2, the average stimulus intensities used to elicit mild and moderate pain were 13.45 ± 8.75 mJ/mm2 and 19.44 ±

6.13 mJ/mm2 (mean ± SD), respectively. Skin temperature remained stable throughout the experiment for each participant (range 1.51 ± 0.51ºC, (mean ± SD). Laser stimulation caused small red spots to appear on the skin of all participants during the session. Within 1-2 days these darkened and then disappeared after 2-3 weeks. This was never reported as painful, but was sometimes reported as being itchy. All participants were informed of this common effect of carbon dioxide lasers prior to giving their informed consent.

58 Figure 3.2. Individual data for pressure pain thresholds (PPTs; left side of vertical dotted line) and the differences in PPTs for individual participants and the group (mean and 95% confidence interval; right side of vertical line) at m. biceps brachii in Experiment 1 (A) and Experiment 2 (C) and m. first dorsal interosseous in Experiment 1 (B) and Experiment 2 (D). Individual data for heat pain thresholds (HPTs; left side of vertical dotted line) and the differences in HPTs for individual participants and the group

(mean and 95% confidence interval; right side of vertical line) at the forearm (E) and hand (F) in

Experiment 2 are also shown. ∆ baseline is the difference between the pre rest and pre exercise measures and ∆ ex (exercise) is the difference between the pre exercise and post exercise measures. Data to the left of the vertical dotted line are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis.

59 3.4.5. Evoked potential waveforms

Grand average evoked potential waveforms from Cz are shown in Figure 3.3 and individual and group data are shown in Figure 3.4. Summary data from Cz for the N2P2 evoked potential amplitude and onset latency for each condition in Experiment 1 and 2 are shown in Tables 3.1 and 3.2, respectively

3.4.6. Modulation of SEPs and LEPs

Moderate-large and significant effects of higher stimulus intensity on increasing

SEP amplitude (p < 0.001) and onset latency (p = 0.011) were observed for the N2P2

(Figures 3.3 A and 3.4 A, and Table 3.1). In contrast, the amplitude (p = 0.69) and onset latency (p = 0.21) of the N1 potential of the SEP was unchanged for the mild and moderate intensities of stimulation (Table 3.1). For the LEPs, there was a moderate and significant effect (p = 0.041) of higher stimulus intensity on increasing N2P2 amplitude

(Figures 3.3 B and 3.4 B, and Table 3.2) but no effect on the LEP N2P2 onset latency (p

= 0.06; Table 3.2).

3.4.7. Effect of exercise and rest on SEPs

For the exercise and rest conditions in Experiment 1, two stimulus intensities corresponding to either moderate pain or non-painful stimulation at 1.5 x perceptual threshold were randomly presented within the same sequence of 5 test blocks. The reported N1 and N2P2 responses were elicited by the stimulus intensity that caused moderate pain, while stimulation at 1.5 x perceptual threshold did not consistently yield measurable responses. For SEP N1 amplitude during moderately painful stimulation, there was no significant effect of time (F(1,15) = 2.14, p = 0.16) or condition (F(1,15) =

2.47, p = 0.14), but a significant time x condition interaction (F(1,15) = 6.99, p = 0.018)

60 Figure 3.3. Somatosensory evoked potentials recorded at Cz from 16 participants in Experiment 1 (SEPs, panels A, C & E on the left) and laser evoked potentials recorded at Cz from 16 participants in

Experiment 2 (panels B, D & F on the right). These traces are the grand averages across participants of individual waveform averages from approximately 500 stimuli for the SEPs and from approximately 30 stimuli for the LEPs. Data are shown for SEPs and LEPs recorded during the modulation test (A, B) or immediately before and after exercise (C, D) or rest (E, F). For the modulation test, two stimulus 61 intensities corresponding to either mild or moderate pain were randomly presented within the same sequence of 5 test blocks. For the SEPs, data are shown for 50 ms before and 450 ms following the stimulus onset; the stimulus artefact is visible on each plot and has been truncated for the illustration. For the LEPs, data are shown for 50 ms before and 950 ms following the stimulus onset; the vertical dashed lines represent stimulus onset.

was observed. SEP N1 amplitude was significantly lower after quiet rest (p = 0.024) but not exercise (p = 0.18) (Table 3.1). Similarly, for SEP N1 onset, there was no significant effect of time (F(1,15) = 4.12, p = 0.06) or condition (F(1,15) = 1.43, p = 0.25), but a significant time x condition interaction (F(1,15) = 7.75, p = 0.014) was observed.

SEP N1 was earlier after quiet rest (p = 0.008) but not exercise (p = 0.66) (Table 3.1).

For SEP N2P2 amplitude during moderately painful stimulation, there was no significant effect of condition (p = 0.85), but a significant effect of time (F(1,15) = 7.39, p

= 0.016) and a significant time x condition interaction (F(1,15) = 4.71, p = 0.047) were observed. SEP amplitudes were significantly lower after quiet rest (p = 0.006) but not exercise (p = 1) (Table 3.1, Figure 3.4 E & C, respectively). Comparison between the changes in SEP N2P2 amplitude in the exercise and quiet rest conditions showed a moderate to large effect, which was significant (d = -0.77 (-1.59 to -0.01), p = 0.047).

There was no significant effect of time, condition, nor a time x condition interaction on

N2P2 onset (all p > 0.19). The pattern of change in the SEP N2P2 waveform at the other

EEG sites (Fz, Pz and C3) was similar to that of Cz but generally smaller in magnitude

(Table 3.3).

62 Figure 3.4. Each panel presents individual and group data (mean and 95% confidence interval) for the

N2P2 evoked potential amplitude to the left side of vertical dotted line and individual and group differences (∆; mean and 95% confidence interval) in evoked potential amplitude to the right side of vertical dotted line. SEP data from Experiment 1 are in the left panels (SEPs, panels A, C & E) and LEP data from Experiment 2 are in the right panels (LEPs, panels B, D & F). A) and B) Responses to mild and moderate (mod) pain stimuli recorded in the modulation blocks. C) and D) Responses recorded before

63 (pre) and after (post) exercise. E) and F) Responses recorded before and after a period of rest. In each of these plots the zero-difference level on the right-hand y-axis is aligned to the group mean for the reference condition of moderate stimulation intensity (A, B), pre-exercise (C, D) or pre-rest (E, F). Data to the left of the vertical dashed line are plotted against the left-hand y-axis and data to the right of the vertical dashed line are plotted against the right-hand y-axis.

3.4.8. Effect of exercise and rest on LEPs

There was a significant effect of time (F(1,15) = 13.66, p = 0.002) but not condition (F(1, 15) = 1.47, p = 0.24) nor a time x condition interaction (F(1,15) = 1.18, p =

0.29) on LEP amplitude. In accord with the time effect, mean LEP amplitudes were lower after rest and exercise (Table 3.2 and Figure 3.4 D & F). For LEP onset, there was no significant effect of time, condition, or a time x condition interaction (all p > 0.13).

The pattern of change in the LEP N2P2 waveform at the other EEG sites (Fz, Pz and

C3) was similar to that of Cz but was generally smaller in magnitude (Table 3.4).

3.4.9. Comparison of SEP and LEP amplitude changes

Comparing the evoked potentials in each experiment, N2P2 onset latency was significantly later for LEPs in Experiment 2 than SEPs in Experiment 1 (Experiment 1:

119 ± 12 ms (mean ± SD); Experiment 2: 229 ± 34 ms; (d = 4.13 (2.95 to 5.50), p <

0.001). A contrast of both experiments and the rest and exercise conditions using repeated measures ANOVA revealed a significant experiment x condition x time effect

64 Table 3.1. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms), and effect size of the change, for the SEP N2P2 waveform at Cz in Experiment 1. The

baseline-to-peak amplitude (µV) and onset latency (ms) of the SEP N1 waveform, and effect size of the change, is also presented.

Modulation Modulation ∆ Modulation Pre rest Post rest ∆ Rest Pre exercise Post exercise ∆ Exercise

(mild) (moderate)

N2P2

Amplitude 4.63 ± 2.07 8.61 ± 4.03 1.18 (0.58 to 1.89)† 9.63 ± 5.26 7.96 ± 4.90 -0.32 (-0.55 to -0.11)* 8.77 ± 5.16 8.68 ± 4.38 -0.02 (-0.23 to 0.19)

Onset 108.2 ± 16.0 114.9 ± 12.2 0.45 (0.11 to 0.83)* 125.1 ± 19.0 121.6 ± 20.3 -0.17 (-0.59 to 0.24) 118.7 ± 18.6 117.4 ± 15.2 -0.07 (-0.66 to 0.51)

N1

Amplitude 1.45 ± 0.98 1.39 ± 0.93 -0.07 (-0.41 to 0.27) 1.82 ± 1.31 0.87 ± 0.4 -0.93 (-1.72 to -0.21)* 1.42 ± 1.16 1.76 ± 1.19 0.27 (-0.05 to 0.61) 65

Onset 41.5 ± 14.7 35.8 ± 13.1 -0.39 (-1.03 to 0.22) 46.5 ± 12.0 33.1 ± 11.2 -1.09 (-1.91 to -0.35)* 42.1 ± 14.5 45.9 ± 13.2 0.28 (-0.29 to 0.87)

The grey columns show the effect size and 95% confidence interval for the change in each of these waveform components for each condition (modulation, rest and exercise).

Unless specified, all data relate to responses to moderately painful stimulation. * p < 0.02; † p < 0.001.

Table 3.2. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms), and effect size of the change, for the LEP N2P2 waveform at Cz in Experiment 2.

Modulation Modulation ∆ Modulation Pre rest Post rest ∆ Rest Pre exercise Post exercise ∆ Exercise

(mild) (moderate)

Amplitude 16.05 ± 7.90 20.45 ± 8.61 0.51 (0.02 to 1.03)* 17.13 ± 7.96 15.26 ± 6.12 -0.25 (-0.53 to 0.02) 18.80 ± 7.88 15.66 ± 6.23 -0.42 (-0.72 to -0.16)†

Onset 252.9 ± 39.9 233.8 ± 41.3 -0.44 (-0.93 to -0.02) 223.3 ± 44.3 217.2 ± 48.8 -0.10 (-0.38 to 0.17) 237.6 ± 41.3 235.4 ± 42.2 -0.05 (-0.29 to 0.18)

The grey columns show the effect size and 95% confidence interval for the change in each of these waveform components for each condition (modulation, rest and exercise).

* p < 0.05; † p < 0.01.

65 on N2P2 amplitude (p = 0.047). Based on the mean change scores, the influence of rest on the amplitude of the evoked potentials was not statistically different between experiments (Experiment 1: -20.7 ± 20.6 % (mean ± SD); Experiment 2: -7.3 ± 21.8 %; d = 0.61 (-0.09 to 1.33), p = 0.08, Figure 3.4 E & F). In contrast, the effect of exercise on the amplitude of SEPs and LEPs differed significantly and with a moderate-large effect size (Experiment 1: 10.9 ± 44.6 % increase (mean ± SD); Experiment 2: 14.6 ±

16.0 % decrease; d = -0.74 (-1.48 to 0.04), p = 0.04) (Figure 3.4 C & D).

3.4.10. Pain and anxiety ratings

For electrical stimulation, there was no significant effect of time, condition, nor a time x condition interaction for ratings of pain intensity (all p > 0.12). There was no significant effect of time (p = 0.23) or condition (p = 0.07) for ratings of pain unpleasantness, but a significant time x condition interaction was observed (F(1,15) =

11.92, p = 0.004). Ratings of pain unpleasantness were significantly lower after exercise

(d = -0.37 (-0.65 to -0.11), p = 0.01) but not quiet rest (d = 0.22 (0.001 to 0.45), p =

0.10; Figure 3.5). For ratings of anxiety, there was a significant effect of time (F(1,15) =

6.73, p = 0.02) but not condition (p = 0.05) nor a time x condition interaction (p = 0.15)

For laser stimulation, there was no significant effect of time, condition, or a time x condition interaction for ratings of pain intensity, pain unpleasantness or anxiety (all p

> 0.19). Hence, quiet rest had no effect on ratings of pain intensity (pre: 5.1 ± 1.6; post:

5.2 ± 1.4, d = 0.04 (-0.09 to 0.20), pain unpleasantness (pre: 4.7 ± 2.1; post: 4.8 ± 2.0, d

= 0.05 (-0.06 to 0.2) or anxiety (pre: 2.1 ± 2.0; post: 1.9 ± 1.8, d = -0.06 (-0.18 to 0.05).

66 Table 3.3. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms), and effect size of the change, for the SEP N2P2 waveform at Fz, Pz and C3 in Experiment 1.

Modulation Modulation ∆ Modulation Pre rest Post rest ∆ Rest Pre exercise Post exercise ∆ Exercise

(mild) (moderate)

Fz

Amplitude 2.92 ± 1.02 4.53 ± 1.40 1.25 (0.71 to 1.90)* 5.09 ± 2.05 4.26 ± 1.98 -0.39 (-0.88 to 0.06) 4.38 ± 2.02 4.52 ± 1.59 0.08 (-0.31 to 0.48)

Onset 120.0 ± 32.4 112.2 ± 22.1 -0.27 (-1.08 to 0.52) 113.3 ± 19.1 110.1 ± 22.8 -0.14 (-0.60 to 0.31) 113.7 ± 24.9 111.3 ± 22.2 -0.09 (-0.46 to 0.27)

Pz 67

Amplitude 3.66 ± 1.53 5.66 ± 2.61 0.91 (0.42 to 1.47)* 6.20 ± 2.86 5.71 ± 3.39 -0.15 (-0.46 to 0.15) 6.19 ± 3.47 5.89 ± 3.07 -0.08 (-0.27 to 0.10)

Onset 110.4 ± 16.1 122.4 ± 27.5 0.51 (-0.35 to 1.40) 108.6 ± 25.6 116.1 ± 21.3 0.30 (-0.23 to 0.85) 118.0 ± 26.3 123.9 ± 29.6 0.20 (-0.26 to 0.67)

C3

Amplitude 3.41 ± 1.58 5.10 ± 2.11 0.86 (0.39 to 1.41)* 5.79 ± 2.55 4.79 ± 2.50 -0.38 (-0.61 to -0.17)* 5.15 ± 2.55 5.37 ± 2.46 0.09 (-0.10 to 0.28)

Onset 102.8 ± 8.8 103.5 ± 8.0 0.08 (-0.33 to 0.50) 103.1 ± 14.3 106.9 ± 14.5 0.25 (-0.40 to 0.92) 108.7 ± 17.2 105.2 ± 19.1 -0.18 (-0.84 to 0.46)

The grey columns show the effect size and 95% confidence interval for the change in each of these waveform components for each condition (modulation, rest and exercise).

Unless specified, all data relate to responses to moderately painful stimulation. * p < 0.001.

67 Table 3.4. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms) of the LEP N2P2 waveform at Fz, Pz and C3 in Experiment 2.

Modulation Modulation ∆ Modulation Pre rest Post rest ∆ Rest Pre exercise Post exercise ∆ Exercise

(mild) (moderate)

Fz

Amplitude 9.43 ± 3.98 13.29 ± 5.93 0.72 (0.17 to 1.34)* 11.28 ± 4.08 10.91 ± 4.60 -0.08 (-0.40 to 0.23) 13.35 ± 4.91 11.02 ± 4.30 -0.48 (-1.06 to 0.07)

Onset 259.6 ± 52.3 237.0 ± 42.9 -0.45 (-1.12 to 0.19) 221.5 ± 60.9 239.8 ± 60.2 0.29 (-0.31 to 0.90) 231.4 ± 61.1 243.5 ± 46.8 0.21 (-0.41 to 0.85)

Pz

13.79 ± 6.56 17.45 ± 6.91 0.51 (0.14 to 0.93)† 14.95 ± 6.86 13.12 ± 5.30 -0.28 (-0.63 to 0.04) 16.87 ± 7.60 13.27 ± 6.00 -0.50 (-0.89 to -0.15)* 68 Amplitude

Onset 256.9 ± 63.6 245.7 ± 42.4 -0.19 (-0.68 to 0.27) 222.5 ± 30.7 246.7 ± 34.3 0.71 (0.03 to 1.43) 242.6 ± 42.9 253.0 ± 47.6 0.22 (-0.44 to 0.89)

C3

Amplitude 10.27 ± 4.48 14.04 ± 5.56 0.71 (0.10 to 1.37)* 12.67 ± 4.29 11.44 ± 3.92 -0.29 (-0.72 to 0.13) 13.02 ± 4.00 11.50 ± 3.71 -0.37 (-0.78 to -0.01)

Onset 224.7 ± 28.9 222.8 ± 32.9 -0.06 (-0.76 to 0.64) 232.1 ± 33.2 219.8 ± 34.1 -0.35 (-0.71 to -0.01) 219.1 ± 32.9 229.2 ± 34.1 0.29 (-0.12 to 0.70)

The grey columns show the effect size and 95% confidence interval for the change in each of these waveform components for each condition (modulation, rest and exercise).

Unless specified, all data relate to responses to moderately painful stimulation. * p < 0.05; † p < 0.01.

68

Figure 3.5. Individual and group data (mean and 95% confidence interval) for ratings of pain intensity, pain unpleasantness and anxiety (left side of vertical dotted lines in each graph) before (pre) and after

(post) exercise (left panels) or rest (right panels) during Experiment 1. Five ratings were averaged to give a single value for ratings of pain intensity and pain unpleasantness for the sets of electrical stimuli and 3 ratings were averaged to give a single value for anxiety. Individual and group differences (∆; mean and

95% confidence interval) in ratings from pre to post exercise or rest are shown to the right side of the

69 vertical dotted line in each graph. In each of these plots the zero-difference level on the right-hand y-axis is aligned to the group mean for the pre-exercise reference condition. Data to the left of the vertical dotted line are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis.

Similarly, exercise had no effect on ratings of pain intensity (pre: 4.9 ± 1.3; post: 5.0 ±

1.7, d = 0.07 (-0.25 to 0.41), pain unpleasantness (pre: 4.8 ± 2.0; post: 4.8 ± 2.2, d =

0.04 (-0.15 to 0.23) or anxiety (pre: 2.2 ± 2.1; post: 2.1 ± 2.2, d = -0.07 (-0.22 to 0.08).

There were no significant differences between the experiments in the average ratings

(mean ± SD) of pain intensity (Experiment 1: 5.5 ± 0.7; Experiment 2: 4.8 ± 1.3; d = -

0.65 (-1.37 to 0.05), p = 0.07), pain unpleasantness (Experiment 1: 5.1 ± 1.3;

Experiment 2: 4.5 ± 1.8; d = -0.34 (-1.04 to 0.35), p = 0.33) or anxiety (Experiment 1:

1.7 ± 1.6; Experiment 2: 2.0 ± 1.8; d = 0.15 (-0.54 to 0.85, p = 0.66).

3.5. Discussion

This novel investigation of the mechanisms by which exercise acutely relieves pain in healthy adults did not produce a straightforward result. The hypoalgesic effect of isometric exercise was clear in pressure pain thresholds but absent for heat pain thresholds. There were small but non-significant effects of exercise and rest on reducing

LEPs, the responses to painful heat stimuli. SEPs in response to painful electrical stimuli were unchanged after exercise but significantly reduced after a similar period of rest. Finally, neither exercise nor rest changed ratings of pain intensity for either the electrical or laser stimuli, but exercise did reduce ratings of pain unpleasantness and anxiety for the electrical stimuli only. Thus, inconsistencies were apparent in the effect of exercise on EEG and perceptual responses as well as on different modalities of pain.

70 3.5.1. Verifying the acute hypoalgesic effect of exercise

A similar and substantial hypoalgesic effect of exercise in both experiments was verified by the elevation of pressure pain thresholds (PPTs) over the exercised muscle

(biceps brachii) and elsewhere (first dorsal interosseous (FDI)). The larger increases in

PPTs at biceps brachii than FDI were consistent with previous reports of greater increases in PPT for exercised compared to non-exercised limbs or muscles194,200,209.

The measurement of PPT directly over the muscle, including the FDI, contrasted with the application of electrical stimuli to the index finger (Experiment 1) or laser stimuli to the dorsum of the hand (Experiment 2) for the evoked potentials. However, other investigators have reported similar large increases in pain threshold to mechanical pressure applied over bones of the finger, confirming that the hypoalgesic effect of exercise is not confined to nociceptive input from muscles207,209.

Although pain thresholds were not re-evaluated during or immediately following the measurement of evoked potentials, it is well established that EIH endures for at least 10 minutes after exercise190,317. This duration of EIH would have spanned the approximately 7-minutes for the evoked potential recordings, which commenced within

1-2 minutes of the exercise and immediately following the pain threshold measurements. Pain thresholds were measured again 30 minutes after the exercise to verify that by that time the EIH had dissipated. Measurement of MVCs at the beginning of the experiment also preceded the initial measurement of evoked potentials and pain thresholds by at least 30 minutes to ensure that there was no effect of EIH from this initial muscle activity.

71 3.5.2. Habituation of the evoked potentials

Habituation of evoked potentials, thought to involve both peripheral and central components318,319, has previously been reported59,318,320 and was not an unexpected finding in either of the experiments. It is, however, an obvious limitation in the utility of evoked potentials to explore the mechanisms of EIH and needs to be addressed in future studies that use these techniques. The inclusion of a rest condition was an important component of the experiment design. It identified how much change in evoked potential amplitude arose from habituation alone (i.e., ~21 % for SEPs and ~7% for LEPs) as a basis to carefully interpret any observed changes with exercise.

3.5.3. Modulation of the evoked potentials

The measured N2P2 components of the evoked potentials were larger when stimulus intensity was increased and the stimuli were rated as more painful. This modulation condition of the experiments verified that the evoked potentials scaled with stimulus intensity and were sensitive to change. Evoked potential amplitude is affected by stimulus intensity, analgesics, mood and attention55,321-324, suggesting that both the nociceptive/affective and evaluative/functional aspects of pain are represented. It was ensured that all key influences - such as anxiety, attention to the noxious stimulus and electrode impedance - were held constant throughout the experiment. Hence, these factors are unlikely to have influenced the results.

3.5.4. Minimal reduction of the laser evoked potentials

Consistent with the hypothesis, there was a small effect of exercise on reducing the amplitude of LEPs, but this finding should be interpreted with caution because the effects of rest and exercise on LEP amplitude were not significantly different. The

72 minor influence of exercise on the LEPs may arise from the limited influence of exercise on heat pain, in addition to these measures being distant from the exercised muscle. EIH is known to be larger and more consistent when mechanical rather than thermal stimuli are used to evoke pain190,212,302. This is supported by the current study, as the effect of exercise on heat pain thresholds (HPTs) was absent compared to that on

PPTs. There are several possible explanations for this. First, HPT was not assessed at the primary exercised muscle where EIH would have been greatest. Second, in order to equate the method of measuring heat pain with that of pressure pain, a much smaller surface area was stimulated with more rapidly increased heat than previous studies325,326. Third, EIH is larger and more consistent when mechanical rather than thermal stimuli are used to evoke pain190,212,302, but exactly why this occurs is not known. It is possible that evoking EEG potentials using a painful mechanical stimulus327-329 may detect greater change with exercise than was detected using LEPs.

However, techniques for eliciting these pinprick evoked potentials are still in their infancy and would not have been feasible in the experimental design. Further, pinprick evoked potentials remain poorly understood with regard to the component(s) of these potentials that are most associated with pain. It is also possible that a greater dose of exercise may have elicited more EIH and had a bigger influence on HPT and LEP amplitude.

A further consideration for the comparative effects of exercise on LEPs and pain threshold measures is that these responses may be subserved by different classes of nociceptive afferents which exercise may affect differentially. The latency of the LEP

N2P2 component was consistent with activity of A-delta fibres. The activation of nociceptors by heat from a laser requires energy transmission to the receptor followed by transduction of this energy and action potential generation330. A-delta fibres respond

73 within approximately 40 – 100 ms of the rapid application of heat energy, depending on the stimulus intensity and the proximity of the laser beam to the receptive field of the nociceptor331,332. Thus, the approximately 230-ms onset latency of the N2P2 component of the LEP was consistent with the combination of the stimulus transduction time and the conduction velocity of A-delta fibres. Responses to brief punctate noxious stimuli

(i.e. pinpricks) are conveyed by A-delta fibres26, however the assessment of PPTs occurred over a period of seconds and elicited a sensation of gradually increasing blunt pressure and then pain. This is obviously different to a pinprick sensation and it is possible that pain thresholds to this slower application of pressure are associated more with activity of C-fibres. Hence, if exercise has greater effects on C-fibres compared to

A-delta fibres, this might explain why PPTs changed after exercise much more so than

LEPs, but this is speculative.

3.5.5. Negligible change of the somatosensory evoked potentials

Habituation makes it difficult to conclude whether exercise genuinely had no effect on SEP amplitude or simply alleviated the effect of quiet rest. It is even possible that exercise led to increased signal from some generators of the SEP and that this was superimposed on habituation, resulting in no net effect. Despite a similar degree of habituation following rest, the SEP and LEP responses to exercise clearly differed.

Several factors could explain the different effect of exercise on the SEP and the LEP.

An inherent limitation of comparing SEPs and LEPs is the different neural pathways engaged by each type of stimulus and the extent to which these reveal nociceptive activity. LEPs and SEPs are often compared to distinguish changes in nociceptive pathways, such as assessing the spinothalamic tract (LEPs) versus non- nociceptive sensory pathways like the dorsal column-lemniscal system (SEPs)333,334.

74 However, such comparisons typically involve the early components of the SEP whereas in the current study, the late N2P2 response to painful electrical stimulation was measured. The so-labelled ‘noxious component’ of the SEP involves the activation of

A-delta fibres335, shares common cortical and subcortical generators with the equivalent component of the LEP336, and has been shown in several investigations to be reduced by analgesic medication337,338.

In the current study, the SEP scaled with the intensity and rating of noxious electrical stimulation. Notably, the stimulus intensity to elicit mild pain was approximately 10x perceptual threshold and that to elicit moderate pain was approximately 14x perceptual threshold. Since both these intensities exceed the typical recruitment thresholds for large-fibre sensory cutaneous afferents, yet the peak-to-peak amplitude of the N2P2 component of the SEP increased markedly (Figure 3.4 A), a contribution from the higher threshold, thinly myelinated A-delta fibres seems likely.

Indicative of saturation in the large diameter afferent contribution to the EEG, the N1 potential amplitude did not increase from the mild-pain to moderate-pain stimulation intensities, which provides further support for the A-delta contribution to the N2P2 measure. Nonetheless, the possibility cannot be excluded that the electrically-evoked

N2P2 was insensitive to the analgesic effects of exercise because of the contribution of non-nociceptive pathways to the SEP. Notably, the influence of exercise and rest on N1 potential amplitude was similar to that for the N2P2 component of the SEP.

Another possible reason for the absence of a reduction in the SEP amplitude or the rating of pain intensity with exercise is that the electrical activation of nerve axons in the index finger may have been inherently less sensitive to EIH by not involving the peripheral nociceptors. The approximately 120 ms onset latency of the N2P2 component of the SEP was consistent with the direct activation of the A-delta afferent

75 axons for the electrically-evoked response (i.e., approximately 8 ms-1 for the fastest of the afferents contributing to the N2P2). Though this study did not measure nociceptor activity directly, a change in excitability of the peripheral nociceptors in response to exercise is physiologically plausible; nociceptive primary afferents can be modulated via receptors at the periphery268, and many of the substances that influence nociceptor sensitivity are increased in the blood during exercise (e.g. opioids and catecholamines)241,269,339.

There were also differences in the stimuli for SEPs and LEPs other than the involvement or not of peripheral nociceptors. For example, the electrical stimuli were more frequent, far briefer, and would have evoked less temporally dispersed volleys than the heat stimuli. Thus, some possible explanations for the different behaviours of the SEP and LEP after exercise are that exercise directly affected the nociceptors, or that the different stimulus profiles may have been differently sensitive to spinally- mediated inhibitory control mechanisms.

3.5.6. Ratings of pain intensity, unpleasantness and anxiety

Despite the small effects of exercise and rest on reducing LEP amplitude, there was no effect of exercise (or rest) on the rating of pain intensity, pain unpleasantness or anxiety with the brief infrequent laser heat stimuli. Previous studies showing an effect of exercise on ratings of pain intensity have used a contact thermode to deliver a continuous (30-120 s) heat stimulus to participants who rated their pain every 5-

10s194,326. This continuous method may provide participants with a greater ability to discern between different intensities of heat. For the electrical stimulus, there was no effect of exercise on ratings of pain intensity. This was consistent with no reduction in

SEP amplitude, but is in contrast to previous reports of reduced ratings of pain

76 intensity190,199,236. Again, this might be due to methodological differences between our study and past investigations.

While ratings of pain intensity were unaffected, ratings of anxiety and pain unpleasantness of the electrical stimuli were both reduced after exercise. These findings suggest that EIH may involve a central effect on higher order psychological processes.

A previous investigation from our laboratory demonstrated that aerobic training increased tolerance of a noxious ischemic stimulus independent of a change in its perceived intensity180 and cross-sectional studies have also found that athletes are more tolerant of pain despite having similar pain thresholds to non-athletes183. The results of

Experiment 1, as well as those of past studies212,232,280, show that acute exercise can exert a similar effect and suggest that changes in pain appraisal contribute to EIH.

3.5.7. Limitations

There were several limitations to the current study. First, there were differences between

SEPs and LEPs apart from the involvement or not of peripheral nociceptors that could have contributed to the different effects of exercise on these potentials. Second, pain thresholds were not re-evaluated during or immediately following the measurement of evoked potentials, so it cannot be said with certainty that evoked potentials were measured quickly enough after exercise to capture EIH. Third, LEPs are reliant on the stimulation of skin nociceptors whereas EIH predominantly involves muscle nociceptors, so LEPs are likely not the most sensitive technique for investigating the mechanisms of EIH. Lastly, as only young healthy men and women were recruited, the results cannot be generalised to children or old adults, nor to people with chronic pain.

Further to this last point, because the type of chronic pain treated by exercise is almost

77 exclusively musculoskeletal in nature, LEPs may not be the most appropriate technique for investigating the mechanisms of EIH in people with chronic pain.

3.6. Conclusion

The novel application of neurophysiological techniques has highlighted that changes in central and peripheral areas of the nervous system might underlie EIH in healthy adults. The results showed that isometric exercise increased PPTs but not HPTs.

Further, the effect of exercise on the amplitude of SEPs and LEPs was negligible when compared to the change observed with quiet rest (i.e. habituation). Changes in ratings of pain unpleasantness and anxiety during SEP recordings, without a change in pain intensity, support a centrally-mediated influence of exercise. The different behaviour of the somatosensory evoked potentials to the laser evoked potentials following exercise could indicate that excitability of peripheral nociceptors contributes to exercise-induced hypoalgesia. Overall, the small or absent changes in the N2P2 component of the evoked potentials suggest a minor influence of exercise on A-delta pathways although there are substantial changes in pressure pain threshold.

Investigations using techniques that can directly isolate and examine these subsections of the nociceptive pathways are needed to determine exactly where the changes might be occurring. With regard to the utility of EEG evoked potentials for this purpose, this will be restricted by habituation of these potentials, it may require the measurement of potentials in response to painful mechanical stimuli, and could benefit from the application of protocols to record C-fibre responses in addition to A-delta responses.

78 Chapter 4:

Limited change of laser-heat pain thresholds and evoked potentials

following aerobic exercise

4.1. Abstract

The hypoalgesic effects of exercise are well described, but there are conflicting findings for different modalities of pain; in particular for mechanical versus thermal noxious stimuli, which are the most commonly used in studies of exercise-induced hypoalgesia. In this study, pressure and heat pain thresholds, and pain ratings to laser stimulation, were measured before and after aerobic cycling exercise as well as before and after an equivalent period of light activity. To identify possible changes in the excitability of nociceptive pathways that accompanied exercise-induced hypoalgesia, laser evoked potentials were also measured. For 16 healthy adults, pressure pain thresholds increased substantially after exercise (> 26.9% increase, d > 0.61 and p <

0.001) whereas heat pain thresholds did not (< 4.2% increase, d < 0.30, p > 0.27). Laser evoked potentials and laser heat pain ratings also changed minimally after exercise (d between -0.59 to 0.3, p > 0.06). These results show that aerobic exercise has greater effects on reducing mechanical compared to thermal pain sensitivity. This is the first investigation to compare the effects of exercise on pressure and heat pain using the same stimulation site and pattern.

79 4.2. Introduction

Exercise acutely reduces pain in healthy adults190, a phenomenon termed exercise-induced hypoalgesia (EIH). Studies of EIH in humans have examined how various types, durations and intensities of exercise influence sensitivity in different pain modalities190,191. Many human and animal studies have also explored the mechanisms underlying this phenomenon. This has typically been done by administration of drugs192,250,265,340, application of different noxious stimuli to assess wind-up193,196,200 or conditioned pain modulation197,200,280, and, more recently, pain-related evoked potentials211 and the occlusion of blood flow (see Chapter 5). While these studies have failed to clearly elucidate the mechanisms of EIH they have produced one relatively consistent finding; that EIH tends to be greatest when mechanical (pressure) stimuli are used to evoke pain in comparison to more modest effects on thermal (heat) stimuli190,302.

However, this effect has not been well investigated when the methods used to deliver the pressure and heat stimuli are well equated.

The results of studies examining EIH for mechanical and thermal pain within an individual are mixed192,194,203,212,326,340 and methodological differences between these studies make it difficult to determine the exact effect of exercise on different pain modalities. For example, the pressure and heat stimuli often differed with regard to the body site stimulated, the stimulus profile (constant, rising and/or suprathreshold), the apparatus used (handheld versus cuff algometers and contact thermodes versus lasers), and the way pain was quantified (threshold, tolerance and/or ratings). The manner in which noxious stimuli are applied has a significant influence on the subsequent pain response whereby pressure pain thresholds (PPT) and heat pain thresholds (HPT) are higher when smaller surface areas are stimulated341,342 or when the rate of increase in pressure and heat application is, respectively, faster and slower343,344. To better

80 understand the effect of exercise on different pain modalities, the different noxious stimuli need to be applied in a similar fashion, but this has seldom been done.

The previous chapter explored the effect of isometric exercise on PPT and HPT that were closely matched with regard to their temporal and spatial profiles and found that exercise had a large effect on increasing PPT but not HPT211. It also investigated whether EIH was accompanied by a change in the amplitude of laser evoked potentials

(LEPs), a crude neurophysiological correlate of pain and well established technique for studying thermal nociceptive pathways57. While a significant effect of exercise on reducing LEP amplitude was observed, LEPs were also reduced after quiet rest (i.e. habituation) such that the difference between the change with exercise and rest was not significant211. The mechanisms of habituation in LEPs are unclear59,318,319,345, but it is possible that if it is related to arousal, habituation may occur less with gentle activity than with sitting at rest. Additionally, aerobic exercise has been shown in some studies to produce a more profound and enduring EIH than isometric contractions205,206, and may have greater effects on LEPs and HPTs. Therefore, comparing aerobic exercise and a light-activity control might more clearly elucidate the effect of exercise on LEPs and associated sensitivity to noxious heat.

The aim of this study was to investigate the effect of aerobic exercise on pressure and heat pain sensitivity and LEPs. It was hypothesised that pressure and heat pain thresholds would increase, indicative of EIH, and that the largest effects would be observed for the pressure stimuli. It was also hypothesised that changes in pain threshold would be accompanied by a reduction in the amplitude of the LEPs and associated ratings of pain following exercise, while the light activity condition would not show LEP habituation.

81 4.3. Methods

4.3.1. Participants

All procedures were approved by the University of New South Wales Human

Research Ethics Committee (HC 14065). Written informed consent was obtained from each participant prior to testing. Participants were recruited through advertisements placed on billboards around campus. Eligibility criteria included 1) apparently healthy with no history of chronic pain or chronic disease, 2) between the ages of 18 and 60 years and 3) absence of a current diagnosis of depression or any other major mood disorder. Twenty volunteers (age: 23.6 ± 3.9 years (mean ± SD)) participated in the experiment. All volunteers were students from the university.

4.3.2. Procedures

Briefly, pressure pain thresholds (PPTs), heat pain thresholds (HPTs), laser evoked potentials (LEPs) and pain ratings during noxious laser stimulation were obtained before and after exercise as well as before and after an equivalent duration of light activity (Figure 4.1). The order of exercise or light activity was counterbalanced across participants. Pain assessments were always made in the same order following exercise and light activity (i.e., PPTs, HPTs and then LEPs) as well as prior to exercise and light activity for participants randomised to light activity first (i.e. LEPs, HPTs and then PPTs). However, the order of the pain assessments prior to light activity for participants who were randomised to exercise first differed slightly (Figure 4.1). For these participants, pain assessments prior to light activity were made in the following orders: PPTs, HPTs and then LEPs. This revised order with PPTs assessed first was necessary to ensure that any hypoalgesic effect of exercise had subsided before the collection of the next series of evoked potentials.

82 4.3.2.1. Aerobic exercise

Aerobic exercise was performed using a stationary cycle ergometer (Monark

828e, Vansbro, Sweden). Prior to exercise, the participant’s resting heart rate and age- predicted maximum heart rate were determined and the values corresponding to 60% and 70% of heart rate reserve were calculated346. Aerobic exercise at this intensity is considered moderate-vigorous347 and reliably produces EIH in healthy adults190,191.

Exercise began with a 5 min warm-up at 50 watts (W), after which the work-rate was increased to correspond to the intensity that elicited a heart rate between 60-70% of heart rate reserve. Participants were then required to maintain this intensity for 15 min, during which time measurements of work-rate (W), heart rate and ratings of perceived exertion (RPE; Borg 6-20 scale) were recorded every 90 s. When necessary, adjustments were made to the work-rate so that participants remained within their target heart rate reserve zone.

4.3.2.2. Light activity and wash out

A 20 min period of light activity was included to correspond to the time it took to perform the aerobic exercise task. Light activity rather than quiet rest was chosen to see if it reduced or prevented LEP habituation that is well described in the literature318,345. During light activity, participants sat on the bike and pedalled slowly against very light resistance so that their RPE did not increase above resting. A wash out period of approximately 30 min was also included between the pain assessments of the first and second intervention to ensure any hypoalgesic effect of exercise (when performed first by randomisation) had subsided before the collection of the next series of evoked potentials and pain threshold assessments.

83 Figure 4.1. Pressure pain thresholds (PPTs), heat pain thresholds (HPTs) and laser evoked potentials

(LEPs) were measured before and after 15 min of moderate-vigorous intensity cycle ergometer exercise and an equivalent duration of light activity. The interventions were presented in a randomised and counterbalanced order. A 30 min wash out period was included so that, in participants who exercised first, any exercise-induced changes in pain were gone before commencing the next block of pain threshold and laser evoked potential recordings. The post measures were completed within 10 min of the cessation of exercise or light activity and were always performed in the same order (i.e. PPTs, HPTs and then LEPs).

The order of pain assessments made prior to exercise and light activity differed slightly depending on which intervention was performed first. For participants randomised to light activity first (not shown), the order of pain assessments was the same prior to the light activity and exercise interventions (i.e. LEPs,

HPTs and then PPTs). For those randomised to exercise first (shown), the same order of pain assessments was used pre and post exercise (i.e., LEPs, HPTs and then PPTs) but prior to light activity the order of pain assessments was: PPTs, HPTs and then LEPs. In this instance, the assessment of PPTs first was necessary to verify the return of pain to baseline following the wash out period.

4.3.2.3. Pressure pain threshold

Pressure pain threshold was assessed over the rectus femoris and tibialis anterior muscles on the right side of the body. With the participant seated, the mid-belly of each muscle was located and marked by measuring half the distance between the inguinal fold and proximal aspect of the patella for the rectus femoris, and one-third the distance between the lateral tibial condyle and lateral malleolus for the tibialis anterior.

Following two familiarisation trials on the left rectus femoris muscle, the rubber-tipped

84 probe of a handheld algometer (Wagner Force 10 FDX-25, Wagner Instruments,

Greenwich, CT) was applied perpendicularly to the participant’s skin and the force was increased gradually at a rate of approximately 1 kg/s. Participants were instructed to say

‘‘stop’’ when the sensation of pressure turned to pain. This procedure was repeated over the tibialis anterior muscle and then continued in this rotational order until PPT had been recorded three times at each site. Pressure pain threshold was recorded as the average of these three measurements.

4.3.2.4. Laser-heat pain threshold

Brief laser stimuli (20 ms pulse width) were delivered at a frequency of 5.55 Hz at a progressively increasing intensity (~0.5 mJ/mm2/s) using a carbon dioxide laser

(Synrad 48-1 10 W series, Synrad Inc., Mukilteo, WA, USA) controlled with a closed- loop beam monitor (UCL-2000, Synrad Inc.) and custom software (LabVIEW version

9.0, National Instruments, Austin, TX) interfaced with Spike 2 software (Cambridge

Electronic Design, Cambridge, UK) via hardware (Micro1401, Cambridge Electronic

Design; USB-6211, National Instruments). Stimuli were delivered at two locations: 1) the dorsal surface of the participant’s right foot, and 2) the anterolateral surface of the lower leg midway along the shank, within approximately 5-10 cm of the pressure pain threshold site for tibialis anterior. The exact site of stimulation was visualised with a

He-Ne diode pointer (DP, Synrad Inc.) and was maintained with the laser supported by a custom X-Y jig. The frequency and duration of the stimuli was perceived as a continuously increasing sense of warmth that turned to pain. Participants were instructed to say ‘‘stop’’ as soon as the stimulation became painful. This procedure was then repeated and continued in this rotational order until HPT had been recorded four times at each site. Heat pain threshold was recorded as the average of these four

85 measurements at each site. The precise location of the stimulus was varied slightly (~1 -

2 cm) between each trial in order to avoid sensitisation of the skin or fatigue of the targeted nociceptors.

4.3.2.5. Laser evoked potentials and heat pain ratings

Radiant heat stimuli (30 - 50 ms duration, 10.6 µm wave length, 3.5 mm beam diameter) were delivered to the dorsal surface of the participant’s right foot using the laser system described above. To reduce the likelihood of sensitisation, successive laser stimuli were delivered to different locations on the foot in a random order such that the same site was never stimulated more than 2 - 3 times throughout the experiment. Skin temperature was monitored using an infrared camera (ThermaCAM® P45, FLIR systems, Wilsonville, OR, USA).

Prior to the recording of LEPs, single laser stimuli were delivered at gradually increasing energies to determine the intensity that corresponded to the participant’s perceptual threshold and a moderate pain (4-5/10). Laser evoked potentials recorded before and after exercise and before and after light activity consisted of 30 moderately- painful stimuli (3 x 10 with a 10-12 s inter-stimulus interval and 45-60 s between each series). Following each series, participants were asked to rate the pain intensity, pain unpleasantness and anxiety of the stimulation using 0-10 numerical and categorical scales (0 = none, 10 = worst imaginable). A total of 3 ratings were made for each condition and the average of these was calculated. Participants were instructed that they could use decimals to rate their pain. Immediately following the first block of LEP recordings, a waveform average for electrode Cz was generated and visually inspected.

If an LEP was not clearly visible, the participant was excluded from taking any further part in the rest of experiment (n = 4).

86 Silver/silver chloride electrodes (10 mm diameter) were placed along the scalp midline (Cz, Fz and Pz) and left side of the head (C3) and referred to the left earlobe

(10-20 International system). A ground electrode was placed across the forehead.

Electrode sites were prepared with NuPrep (Weaver and Company, Aurora, CO, USA), abraded with sandpaper (CIVCO, Kalona, IA, USA) and adhered with Ten20 conductive paste (Weaver and Company, Aurora, CO, USA) and tape. A small plastic probe was used to further agitate the skin as necessary to reduce impedance at each electrode to less than 5000 ohms. Contact impedance was monitored and recorded throughout each experiment using built-in features of the EEG amplifiers. The EEG signal was amplified 1000x (NL844 and NL820A, Digitimer NeuroLog System,

Hertfordshire, England), filtered (0.1 Hz – 2 kHz, NL144 and NL135/6, Digitimer

Neurolog System, Hertfordshire, England) and collected on a computer (Spike 2 and

Micro1401 mkII, Cambridge Electronic Design, Cambridge, UK) at 5000 samples per second. Electrooculography (EOG) was recorded using 6 mm gold cup electrodes placed above and below the left eye and was monitored continuously by one of the experimenters.

4.3.3. Data processing and statistical analysis

4.3.3.1 Evoked potential analysis

Evoked potentials were extracted using computer software (Spike 2, Cambridge

Electronic Design, Cambridge, England) by averaging the EEG signal in response to laser stimulation. A digital filter (Finite Impulse Response, 30-Hz lowpass, Spike2,

CED) was applied to the EEG recordings before processing the LEPs. EEG data were divided into 1050-ms epochs, each lasting from -50 ms to +1000 ms with respect to stimulus onset. The N2P2 component of the LEP was analysed at each of the 4 EEG

87 sites according to the procedures described by Luck312. The baseline signal was calculated as the root mean square amplitude in the 50 ms prior to each laser stimulus.

The N2P2 onset was quantified as the time at which the EEG signal was 1 standard deviation above baseline (negative polarity) 100-500 ms after stimulus onset. N2P2 amplitude was calculated as the difference between the N2 and P2 peak amplitudes, which were measured from 150-500 ms (N2) and 250-550 ms (P2).

4.3.3.2. Sample size calculations

Sample size calculations were performed using G*Power (version 3.1.9.2,

Dusseldorf, Germany)314 and were made for the pain threshold and evoked potential measures on the basis of changes observed the previous chapter211. For the effect of acute exercise on pressure pain thresholds, heat pain thresholds and laser evoked potentials, a mean change of 0.92 ± 0.49 kg/cm², 0.37 ± 0.47 mJ/mm² and 3.14 ± 3.36

µV, respectively, was estimated. These changes correspond to a large effect of exercise on PPTs and small-moderate effects of exercise on HPTs and LEPs. On this basis, it was estimated that at least 5, 14 and 12 participants, respectively, were required to detect exercise-induced hypoalgesia using PPTs, HPTs and LEPs using a repeated measures test with 80% power and alpha of 0.05. A target sample of 15-16 participants was planned to provide more power and precision, and to account for the possibility of participant drop out.

88 4.3.3.3. Statistical analysis

Descriptive statistics were calculated using the IBM Statistical Package for

Social Sciences (version 22, Chicago, IL, USA). Differences in pressure and heat pain thresholds, laser evoked potential amplitude and onset latency, pain ratings in response to laser stimulation, and skin temperature were examined using two way repeated measures ANOVA (time: pre, post; condition: light activity, exercise). Two way repeated measures ANOVA was also used to examine the temporal stability of individual HPTs, as opposed to the average HPT, at the lower leg (time: 1, 2, 3 and 4; test block: pre light activity, post light activity, pre exercise, post exercise). Similarly, two way repeated measures ANOVA was used to examine the temporal stability of individual lower leg PPTs and ratings of laser pain intensity (time: 1, 2 and 3; test block: pre light activity, post light activity, pre exercise, post exercise). Normality of the data was assessed using the Shapiro-Wilk statistic. Greenhouse-Geisser corrections were used if sphericity was violated. Paired sample post hoc t-tests were conducted to identify the source of differences in pain thresholds, pain ratings and/or evoked potentials that were detected by ANOVA. Alpha was set at 0.05 and the p value for the t-tests was multiplied by the number of comparisons for each ANOVA model

(Bonferroni correction). Effect sizes (unbiased Cohen’s d) and 95% confidence intervals

(CIs) were also calculated to aid comparisons between the different measures for the light activity and exercise conditions as well as to compare the effect of exercise on PPT and HPT over a similar site (i.e. the lower leg). Effect sizes were interpreted as small

(0.2), moderate (0.5) or large (0.8)315. The 95% CIs of the effect size were calculated using a non-central t distribution316. Except where stated, values are reported as the mean and 95% CI and the LEP data presented are for electrode Cz.

89 4.4. Results

Following the first block of LEP recordings, four participants were excluded from the study on the basis of having no clear LEP leaving a total of 16 participants for whom the full data set was collected and analysed.

4.4.1. Aerobic exercise

The average (mean ± SD) work-rate and percent of heart rate reserve during aerobic exercise was 139.4 ± 45.5 W and 71.8 ± 4.7 %, respectively. The average (mean

± SD) RPE during exercise was 15.3 ± 1.2 for the legs and 14.3 ± 1.4 overall, indicating that participants perceived the exercise to be ‘hard’.

4.4.2. Pressure pain thresholds

Individual and group data for PPTs are shown in Figure 4.2. There was a significant effect of time (F(1, 15) = 52.64, p < 0.001), condition (F(1, 15) = 73.08, p <

0.001), and a time x condition interaction (F(1, 15) = 81.45, p < 0.001) for PPT over the rectus femoris. A significant effect of time (F(1, 15) = 46.22, p < 0.001), condition (F(1, 15)

= 25.44, p = 0.001), and a time x condition interaction (F(1, 15) = 120.62, p < 0.001) was also observed for PPT over the tibialis anterior. There was no significant effect of light activity on PPT over the rectus femoris (d = 0.05 (-0.09 to 0.20), p = 0.96) or tibialis anterior (d = 0.02 (-0.10 to 0.15), p = 1). In contrast, there was a large and significant effect of aerobic exercise on increasing PPT over the rectus femoris (d = 0.83 (0.52 to

1.22), p < 0.001) and a moderate and significant effect of aerobic exercise on increasing

PPT over the tibialis anterior (d = 0.61 (0.39 to 0.88), p < 0.001).

90 Figure 4.2. Data to the left of the vertical dotted line show the individual data (grey dots) and group data

(mean and 95% confidence interval, black lines) before and after light activity (LA) and exercise (Ex) for pressure pain thresholds at the rectus femoris (A) and tibialis anterior (C) muscles as well as heat pain thresholds at the foot (B) and tibialis anterior (D). Data to the right of the vertical dotted line show the individual data (grey dots) and group data (mean and 95% confidence interval, black lines) for the percentage change in pain thresholds between the pre light activity and post light activity measures (∆

LA) and between the pre exercise and post exercise measures (∆ Ex). Data to the left of the vertical dotted line are plotted against the left-hand y-axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis. For data plotted against the right-hand y-axis, the horizontal dotted line indicates a zero change score.

91 4.4.3. Heat pain thresholds

Individual and group data for HPTs are shown in Figure 4.2. There was no significant effect of time (F(1, 15) = 1.27, p = 0.28) nor a time x condition interaction (F(1,

15) = 2.45, p = 0.14) for HPT over the lower leg, but a significant effect of condition was observed (F(1, 15) = 7.10, p = 0.018). HPTs over the lower leg were higher for the exercise compared to the light activity condition. No significant effect of time

(F(1, 15) = 0.001, p = 0.98) nor a time x condition interaction (F(1, 15) = 0.07, p = 0.79) was observed for HPT over the foot, but a significant effect of condition was observed

(F(1, 15) = 5.07, p = 0.04). HPTs over the foot were higher for the exercise compared to the light activity condition.

4.4.4. Comparison of EIH for pressure and heat pain over a similar site

Comparison of the change in PPT (26.9 (20.2 to 33.6) %) and HPT (4.2 (-0.9 to

9.3) %) measured over tibialis anterior before and after exercise revealed a large and significant effect of exercise on increasing PPT compared to HPT (d = 1.77 (0.82 to

2.87), p < 0.001, Figure 4.2).

4.4.5. Laser heat stimulation and skin temperature

The average (mean ± SD) stimulus intensity used to elicit moderate pain was

17.6 ± 4.7 mJ/mm2. Data for skin temperature across the experiment are presented in

Table 4.1. There was no significant effect of time (F(1, 15) = 1.77, p = 0.20), condition

(F(1, 15) = 0.47, p = 0.50), nor a time x condition interaction (F(1, 15) = 2.18, p = 0.16) on skin temperature at the lower leg. Similarly, there was no significant effect of time (F(1,

15) = 0.66, p = 0.43), condition (F(1, 15) = 1.74, p = 0.21), nor a time x condition interaction (F(1, 15) = 0.14, p = 0.72) on skin temperature at the foot.

92 Table 4.1. Mean ± SD skin temperature (°C) over each site across the experiment.

Light activity Exercise

Pre Post Pre Post

Tibialis anterior 29.7 ± 0.7 29.7 ± 0.9 29.8 ± 0.5 29.4 ± 1.0

Foot 29.3 ± 1.5 29.1 ± 1.6 28.8 ± 1.3 28.7 ± 1.6

4.4.6. Ratings of pain and anxiety during laser stimulation

Individual and group data for ratings of pain and anxiety during laser stimulation are shown in Figure 4.3. There was no significant effect of time (F(1, 15) = 4.6, p = 0.05), condition (F(1, 15) = 0.81, p = 0.38), nor a time x condition interaction (F(1, 15) = 1.42, p =

0.09) for ratings of pain intensity. For ratings of pain unpleasantness, there was no significant effect of time (F(1, 15) = 1.8, p = 0.20) or condition (F(1, 15) = 0.78, p = 0.39), but a significant time x condition interaction was observed (F(1, 15) = 7.19, p = 0.017).

There was a moderate effect of exercise on reducing ratings of pain unpleasantness (d =

-0.59 (-1.17 to -0.07)), but it was not significant (p = 0.26). Ratings of pain unpleasantness were unchanged or higher after light activity (d = 0.18 (-0.12 to 0.49), p

= 1). There was no significant effect of time (F(1, 15) = 4.34, p = 0.05), condition (F(1, 15)

= 0.63, p = 0.44) nor a time x condition interaction (F(1, 15) = 1.61, p = 0.22) for ratings of anxiety.

93 Figure 4.3. Individual and group data (mean and 95% confidence interval) for ratings of pain intensity, pain unpleasantness and anxiety (left side of vertical dotted lines and plotted against left-hand y-axis) pre and post light activity (left panels) and exercise (right panels). Differences (∆) for individuals and the group (mean and 95% confidence interval) are shown to the right side of the vertical dotted line and are plotted against the right-hand y-axis. In each of these plots the zero-difference level on the right-hand y- axis is aligned to the group mean for the pre-light activity or pre-exercise condition.

94 4.4.7. LEP N2P2 amplitude and onset latency

Data for the evoked potential amplitude and onset latency for each condition are shown in Table 4.2. Grand average evoked potential waveforms are shown in Figure

4.4. There was a significant effect of time (F(1, 15) = 7.79, p = 0.014) but not condition

(F(1,15) = 4.12, p = 0.06) nor a time x condition interaction (F(1, 15) = 0.59, p = 0.45) on

LEP amplitude. There was a small effect of light activity on reducing LEP amplitude (d

= -0.29 (-0.68 to 0.07)) and a moderate effect of exercise on reducing LEP amplitude (d

= -0.51 (-1.01 to -0.05); Figure 4.5), but neither of these changes were statistically significant (p > 0.064). There was no significant effect of time, condition, or a time x condition interaction on LEP onset latency (all p > 0.18).

Table 4.2. Mean ± SD peak-to-peak amplitude (µV) and onset latency (ms) of the LEP N2P2 waveform.

Light activity Exercise

Pre Post ∆ Pre Post ∆

Cz

Amplitude 16.14 ± 6.18 14.55 ± 3.89 -0.29 (-0.68 to 0.07) 14.94 ± 6.12 12.28 ± 3.47 -0.51 (-1.01 to -0.05)

Onset 248.3 ± 34.6 239.5. ± 48.9 -0.22 (-0.63 to 0.17) 247.8 ± 59.8 252.4 ± 35.6 0.08 (-0.42 to 0.59)

Fz

Amplitude 11.14 ± 7.80 11.02 ± 6.27 -0.02 (-0.33 to 0.29) 9.63 ± 5.68 8.08 ± 2.38 -0.34 (-0.82 to 0.12)

Onset 288.3 ± 35.3 261.4 ± 45.5 -0.63 (-1.27 to -0.03) 274.4 ± 65.3 247.4 ± 44.8 -0.001 (-0.58 to 0.58)

Pz

Amplitude 13.57 ± 4.71 12.81 ± 4.51 -0.16 (-0.47 to 0.15) 13.11 ± 5.64 11.13 ± 3.37 -0.41 (-0.86 to 0.02)

Onset 252.4 ± 34.9 243.6 ± 38.3 -0.23 (-0.65 to 0.18) 259.9 ± 60.4 272.2 ± 38.9 0.23 (-0.41 to 0.89)

C3

* Amplitude 12.72 ± 5.29 10.39 ± 3.34 -0.50 (-0.89 to -0.15) 10.64 ± 3.91 9.72 ± 3.03 -0.25 (-0.64 to 0.12)

Onset 261.1 ± 38.8 252.3 ± 32.3 -0.23 (-0.84 to 0.36) 251.9 ± 39.7 271.3 ± 39.4 0.47 (-0.16 to 1.13)

The grey columns show the effect size and 95% confidence interval for the change in each of these waveform components for each condition (light activity and exercise). * p = 0.012.

95 4.4.8. Comparison of pain thresholds and ratings over time

Data comparing the temporal stability of individual lower leg PPTs, lower leg

HPTs and ratings of pain intensity to laser stimulation are shown in Figure 4.6. There was no significant effect of time (F(1.238, 18.563) = 2.63, p = 0.117) nor a time x test block interaction (F(3.04, 45.57) = 1.36, p = 0.27) for PPT over the tibialis anterior, but a significant effect of test block was observed (F(3,45) = 48.9, p < 0.001) whereby PPTs were higher after exercise compared to the other three test blocks (all p < 0.001). For

HPT measured over the lower leg, there was a significant effect of time (F(3, 45) = 4.34, p

= 0.009) and test block (F(3, 45) = 3.29, p = 0.029), but no significant time x test block interaction (F(9, 135) = 1.04, p = 0.41). For ratings of heat pain intensity to laser stimulation, no significant effect of time (F(1.38, 20.66) = 0.47, p = 0.63), test block (F(3, 45)

= 0.66, p = 0.58), nor a time x test block interaction (F(6, 90) = 0.97, p = 0.45) was observed.

4.5. Discussion

Aerobic exercise caused a substantial increase in pressure pain threshold (PPT) but not heat pain threshold (HPT). This was despite the application of pressure and heat over a similar time course, surface area and region (anterior surface of the lower leg).

Laser evoked potentials (LEPs) and accompanying ratings of laser pain were also not significantly different after exercise. These results confirm the limited influence of exercise on the sensitivity to noxious heat in contrast to noxious mechanical stimuli.

96 Figure 4.4. Laser evoked potentials recorded from 16 participants. These traces are the grand averages of individual waveform averages from approximately 30 stimuli recorded pre and post light activity (panels

A, C, D & E) or exercise (panels B, F, G & H). Data are shown for 50 ms before and 950 ms following the stimulus onset (signified by the vertical dashed line). The amplitude of laser evoked potentials was largest at electrode Cz (panels A & B), but the pattern of change with light activity and exercise was similar across the four sites.

A number of studies have investigated the effect of exercise on pressure and heat pain within an individual192,194,203,212,326,340, but the results are highly variable and the stimulus profiles of the pressure and heat used were never well equated. For example, the algometers and thermodes differed in their size (typically 1 cm2 and ~10 cm2 contact areas, respectively), and the pressure and heat stimuli were often delivered to different body sites for different durations and at different rates. Because the stimulation area

97 Figure 4.5. Individual and group data (mean and 95% confidence interval) for the peak-to-peak amplitude of the laser evoked potentials (left side of vertical dotted lines and plotted against left-hand y- axis) collected pre and post light activity (A) and exercise (B). Differences (∆) for individuals and the group (mean and 95% confidence interval) are shown to the right side of the vertical dotted line and are plotted against the right-hand y-axis. In each of these plots the zero-difference level on the right-hand y- axis is aligned to the group mean for the pre-light activity or pre-exercise condition.

and rate of stimulus application influence sensitivity to pressure and heat341-344, these are important differences that could have contributed to the mixed results. The results of the present study may therefore better reflect the effect of exercise on pressure and heat pain because the apparatus used were closely matched - the pressure and heat stimuli were perceived as similarly focal, and stimuli were delivered over a comparable amount of time (~6 – 10 s) and to a similar body site. Although the diameter of the laser beam

(0.35 cm) was smaller than that for the pressure algometer (1.12 cm), the perception of a similarly sized area of stimulation presumably arose from the rapid transmission of heat energy throughout the skin surrounding the laser beam due to the thermal conductive properties of skin330-332. Mechanical force from the pressure algometer would also have been transmitted beyond the perimeter of the rubber-tipped probe, but this would be limited by the application of force over compliant skin, adipose and muscle.

98 Figure 4.6. Individual (grey dots) and group data (mean and 95% confidence interval, black lines) showing the temporal stability of each pressure pain threshold (A), heat pain threshold (B) and rating of laser pain intensity (C) across the experiment. Data for the pressure and heat pain thresholds are for values recorded over the tibialis anterior/lower leg. Ex, exercise; LA, light activity.

99 The reasons for the greater EIH for mechanical versus thermal stimuli are unclear. When measured within an individual, low-moderate correlations between different pain modalities are observed348,349, so it is reasonable that these same pain modalities could be similarly sensitive to change following an intervention. This is not always the case however, particularly for exercise, as shown in both rodent and human studies of EIH194,203,212,246,258,259,269,326. From an evolutionary perspective, the ability to ignore mechanical pain during exercise would be of importance in a fight or flight situation. In contrast, becoming too desensitized to heat would likely be detrimental given that body temperature must be tightly controlled during exercise to sustain performance and avoid tissue damage350-353. How this relates to EIH requires further investigation. Evolutionary influences on pain are important and the presence of EIH in animals implies an innate presence of this pain response354.

The different effects of exercise on pressure and heat pain might be explained by differences in the type of exercise investigated. It has been argued that reductions in thermal sensitivity may simply be the result of altered blood flow355. Changes in skin blood flow, and hence skin temperature, would likely be greater following aerobic compared to isometric exercise356 and this could subsequently affect HPT whilst minimally influencing PPT357. This has seldom been investigated. However, the results of the current study, and my previous one211, suggest that skin temperature is not likely influential because for both aerobic and isometric exercise, skin temperature was remarkably consistent before, during and following exercise. Moreover, skin temperature only influences HPT when the participant’s reaction time is not a factor357, but this is rarely the case for EIH studies as participants are usually required to push a button or say ‘stop’ to indicate their HPT.

100 In addition to the exercise type, other methodological differences between studies could contribute to the lack of a consistent difference in EIH between pressure and heat pain. First, rodent studies are constrained in their ability to gauge pain by self- report, arguably the most valid and reliable method of pain assessment43,44. Attempts have been made to address this358, but it remains a limitation of rodent studies of EIH as key information regarding the effect of exercise on the appraisal of a noxious stimulus is lost. Second, different devices are used to assess pain between and sometimes even within modalities. There are nociceptors specialised for noxious mechanical and noxious thermal stimuli as well as nociceptors that respond to both26, but exactly which are activated will depend on the stimulus used. For example, in addition to activating group III/IV afferents, pressure algometers will activate non-nociceptive afferents (i.e. group I/II afferents) to a much greater extent than will thermal laser stimuli. Moreover, the size of difference may depend on whether handheld or cuff algometers are used. It should also be acknowledged that the nociceptors that respond preferentially to noxious mechanical and or/thermal stimuli may do so independent of site, size and/or pattern of the noxious stimulus delivered. The data from the present suggest that this is indeed the case, but it was still important to control for these possible influences as much as possible.

Another possible explanation for the dissimilar effect of exercise on pressure and heat pain is that thermal nociceptive pathways are inherently less sensitive to change. Anaesthetics, analgesics, transcutaneous electrical nerve stimulation and manual therapy have all been shown to reduce mechanical pain more than thermal pain359-365, yet some studies have found limited evidence for a difference in their effects on mechanical compared to thermal pain366-368. Specific to exercise, delayed onset muscle soreness increases the sensitivity of mechanical but not thermal C-fibres369,370.

101 While the net effect of this would be to increase pain, and is distinct from EIH, it does provide evidence that muscle damage from exercise has a differential effect on mechanical and thermal nociception (however delayed onset muscle soreness itself appears to have little effect on EIH279).

The work discussed in the next chapter demonstrating the role of changes at peripheral nociceptors as a key mechanism of EIH raises other possibilities regarding the mechanisms of a modality specific change. It was shown that occlusion of blood flow to a limb significantly diminished EIH in that limb, implying that substances carried in the blood and acting at the periphery influence EIH. Greater blood flow to muscles versus the skin during exercise could contribute to a different effect of exercise on pressure and heat pain. There could also be differences in the sensitivity of mechanical and thermal nociceptors that make them more or less sensitive to agents that are released into the blood during exercise and that influence pain (e.g. opioids, cannabinoids and catecholamines)241,242,339,371. However, neither blood flow nor these agents were measured in this study or the previous chapter. Measurements of heat pain threshold were not included in the occlusion study either (Chapter 5).

Measurements of PPT, HPT and heat pain ratings were necessarily made at different times in the 10 minutes following exercise. However, EIH lasts at least 10-15 minutes190 and the data did not show a monotonic change across time for PPTs, HPTs or ratings of heat pain intensity during LEP recordings (Figure 4.6). With regard to ratings of the intensity of a constant noxious stimulus, it was hypothesised that aerobic exercise would lead to a greater reduction in ratings of laser pain intensity. This occurred to some extent, as aerobic exercise reduced pain intensity (d = -0.59) more so than what was observed for isometric exercise in the previous chapter (d = 0.07)211. However, the reduction was not significantly different to the change observed after light activity.

102 The absence of effect of exercise on the LEP amplitudes most likely arose from the insensitivity of heat pain to EIH. Slowly appearing pain thresholds may be mediated by C-fibre activity344 in contrast to the predominantly A-delta contribution to the N2P2 component of the LEP55. Methods for reliably evoking and measuring the C-fibre related components of LEPs are available54,55 but were not feasible in this study.

Nonetheless, the absence of a change in HPT, in addition to heat pain ratings, suggests that the C-fibre component of the LEP would also change little with exercise. It is also possible that measuring LEPs at the rectus femoris or the tibialis anterior may have been more sensitive to the effects of exercise, or that a greater dose of exercise could potentially uncover an LEP response, but the magnitude of EIH revealed by PPTs in this study was large, so this is unlikely. Regardless, habituation of LEPs resulting in changes independently of exercise needs to be addressed. Despite the attempt in the current study to minimise habituation using light activity, LEPs amplitudes still decreased.

Until methods are developed to minimise, prevent or explain evoked potential habituation, LEPs will likely be of limited utility in exploring the mechanisms of EIH.

There were several limitations to the present study that limit the applicability of the findings. First, no measurements of the nociceptors and afferents activated by the pressure and thermal stimuli were made, so the effect of exercise on these cannot be directly determined. Second, the assessment of PPTs, HPTs and LEPs was always done in blocks as opposed to being randomly intermingled, so order effects of testing cannot be ruled out. An order effect here is unlikely however, because the temporal stability of pain thresholds within each block was demonstrated. Third, HPTs and LEPs were not assessed over the dominant exercised muscle where EIH was largest. Had this been done, changes in these measures may have been more apparent. Lastly, as only pain-free

103 young adults were tested, the findings are not applicable to people with chronic pain, children, or old adults.

4.6. Conclusion

In conclusion, when the stimulus profiles are well equated, EIH is greater for mechanical versus thermal stimuli. The mechanisms responsible for the greater effect of exercise on pressure versus heat pain are not clear but warrant further investigation to enhance our understanding of how exercise acutely reduces pain.

104 Chapter 5:

Occlusion of blood flow attenuates exercise-induced hypoalgesia in the

occluded limb of healthy adults

5.1. Abstract

Animal studies have demonstrated an important role of peripheral mechanisms as contributors to exercise-induced hypoalgesia (EIH). Whether these same mechanisms contribute to EIH in humans is not known. In the current study, pain thresholds were assessed in healthy volunteers (n = 36) before and after 5 min of high intensity leg cycling exercise and an equivalent period of quiet rest. Pressure pain thresholds (PPT) were assessed over the rectus femoris muscle of one leg and first dorsal interosseous muscles (FDI) of both arms. Blood flow to one arm was occluded by a cuff throughout the 5-min period of exercise (or rest) and post-exercise (or rest) assessments. Ratings of pain intensity and pain unpleasantness during occlusion were also measured. Pain ratings during occlusion increased over time (range: 1.5 to 3.5/10, all d > 0.63, p <

0.001) similarly between the rest and exercise conditions (d < 0.35, p > 0.4). PPTs at all sites were unchanged following rest (range: -1.3% to + 0.9%, all d < 0.05, p > 0.51).

Consistent with EIH, exercise significantly increased PPT at the leg (+ 29%, d = 0.69, p

< 0.001) and the non-occluded (+ 23%, d = 0.56, p < 0.001) and occluded (+ 8%, d =

0.19, p = 0.003) unexercised arms. However, the increase in the occluded arm was significantly smaller (d = -1.03, p < 0.001). These findings show that blocking blood flow to a limb during exercise attenuates EIH, suggesting that peripheral factors contribute to EIH in healthy adults.

105 5.2. Introduction

Exercise-induced hypoalgesia (EIH) is a reduction in pain that occurs during or following exercise and is well demonstrated for exercise of various modalities, durations and intensities190. Identifying the mechanisms of pain relief from exercise involves investigations of acute192,232,280 and chronic adaptations180,304,372 which may be similar or distinct. For example, acute exercise might transiently reduce pain through changes in the release of analgesic substances192,250 whereas chronic exercise might reduce pain more through changes in the cognitive appraisal of a noxious stimulus180.

The fact that exercise acutely reduces pain suggests that changes must occur somewhere in the nociceptive pathways, but whether these changes are predominantly peripheral, central, or a combination of both, is not known. Studies in animals have identified numerous substances that contribute to EIH (e.g. opioids, cannabinoids, noradrenaline and nitrite). These substances are synthesised and released from multiple sites within the peripheral and central nervous systems, the endocrine system, the immune system and blood vessels (e.g., endothelium and skeletal muscle for nitric oxide, adrenal medulla and peripheral sympathetic nerves for catecholamines, the pituitary gland and immune cells for opioids, and central and peripheral neurons for endocannabinoids)371,373-376. With regard to exercise, whether these substances reduce pain predominantly through their actions at peripheral or central sites is not clear245,246,248,259,269.

In rats, the systemic but not central administration of alpha-2 adrenoceptor antagonists reverses EIH269, implying that catecholamines released during exercise reduce pain through peripheral actions. Nociceptors, through their rich expression of ligands, receptors and neurotransmitters, have autocrine and paracrine actions and can modify input before it reaches the central nervous system268. Many of the substances

106 that influence nociceptor sensitivity are increased in the blood during exercise (e.g. opioids, cannabinoids and noradrenaline)241,242,339,371 and remain elevated in a manner consistent with the persistence of EIH following exercise251, so it is reasonable that these exercise-induced changes could reduce nociceptor sensitivity. The distribution of blood during exercise377 also corresponds, albeit not exactly, with the gradient in the magnitude of EIH across different body regions. That is, like blood flow, EIH is typically greater in exercised than unexercised limbs194,200. This is revealed by the relatively smaller increase in pain thresholds for the arms versus the legs following cycling or running exercise204. However, EIH does occur in unexercised limbs.

Therefore, blocking blood flow to an unexercised limb during exercise provides a means to determine whether a blood-borne factor contributes to EIH via actions in the periphery.

The important role of peripherally acting catecholamines as mediators of EIH shown in rats269 has yet to be directly explored in humans. The results of Chapter 3 provided indirect evidence of a possible role of the peripheral nociceptor in EIH211.

Somatosensory evoked potentials to noxious electrical stimuli were unchanged after exercise whereas laser evoked potentials decreased after exercise. This was despite clear

EIH in both instances. This result suggests that the peripheral nociceptor might be involved in EIH in humans211 because laser heat stimuli activate peripheral nociceptors whereas electrical stimuli bypass the receptors by activating the axons of the nociceptive afferents53,54. However, the role of central factors cannot be discounted.

Animal studies have shown that centrally acting drugs can influence EIH245,246,248,259 and the occurrence of EIH in humans could also be explained by the actions of the central nervous system194,196,200,231,378.

107 It appears likely that both peripheral and central changes contribute to EIH, but the relative contribution of each is not known. To my knowledge, no studies have directly explored the contribution of peripheral factors to EIH in healthy adults.

Therefore, the purpose of this study was to investigate if during high intensity lower limb cycling, EIH, as measured by an increase in pressure pain threshold (PPT) in a non-exercising arm, would be reduced in the other arm in which blood flow was occluded during exercise. It was hypothesised that a circulating factor with a peripheral action contributes to EIH and, therefore, the increase in PPT after exercise would be less in the occluded versus the non-occluded arm.

5.3. Methods

5.3.1. Participants

Participants were recruited through advertisements placed on billboards around campus. Eligibility criteria included 1) apparently healthy with no history of chronic pain or chronic disease, 2) between the ages of 18 and 60 years, and 3) absence of a current diagnosis of depression or any other major mood disorder as this can influence pain thresholds379. Written informed consent was obtained from each participant prior to testing. All procedures were approved by the University of New South Wales Human

Research Ethics Committee (HC 14065) and conformed to the requirements of the

Declaration of Helsinki (2008). All participants were students of the university.

108 5.3.2. Procedures

Before the experiment, participants were asked to abstain from vigorous exercise for 24 h and caffeine for 4 h. Compliance to these requests was confirmed verbally at the start of the session. The experiment consisted of a single session that lasted approximately 1 h. The experimental procedures are outlined in Figure 5.1. With the participant seated on the recumbent cycle ergometer, PPTs were determined at three sites (rectus femoris and first dorsal interosseous (FDI) muscle of both arms). Blood flow to one arm was occluded by inflating a blood pressure cuff on the upper arm to 240 mmHg. The occluded arm was counterbalanced across participants. Once the target pressure was achieved, PPTs were again determined. The participant then either cycled at a high intensity for 5 min or remained at rest for 5 min. Immediately upon cessation of exercise, or at the end of 5-min rest, PPTs were again determined. Occlusion to the arm was then removed and a 30 min ‘wash-out’ period ensued. After this, PPTs were obtained again at rest, after which blood flow to the other arm was occluded. Once the target pressure was achieved, PPTs were re-assessed. Then, the participant either remained at rest for 5 min, or cycled at a high intensity for 5 min, after which PPTs were again determined. The occlusion to the arm was then removed. The order of exercise and rest were randomized between participants. The assessment of PPTs prior to occlusion was to account for any influence of occlusion on PPTs as well as to provide a baseline to ensure that, in the participants who exercised first, PPTs had returned to baseline after the post-exercise wash-out period. Approximately 1.5 - 2.5 minutes were required to complete the PPT measures. Therefore, the time of occlusion ranged from 8

- 10 min (i.e. 1.5 - 2.5 min for PPT assessment, 5 min intervention [rest or exercise], and 1.5 - 2.5 min for PPT re-assessment).

109 Figure 5.1. Experimental procedures

Pressure pain thresholds (black circles) were assessed over the rectus femoris muscle of the right leg and over the first dorsal interosseous muscles of both arms prior to and during upper limb occlusion using a tourniquet that was placed around the upper arm and inflated to 240 mmHg. Both arms were occluded during the experiment, but only one arm was occluded at a time and the order of the arm that was occluded first was counterbalanced across participants. During occlusion (dashed rectangles), pressure pain thresholds were assessed before and after 5 min of high intensity cycle exercise as well as before and after an equivalent period of quiet rest. The order of exercise or quiet rest was randomised and counterbalanced across participants. A 30 min wash-out period was included to ensure any exercise- induced alterations in pain were gone prior to commencing the next round of pressure pain threshold measures.

5.3.2.1. Pressure pain thresholds

Pressure pain threshold was assessed over the right rectus femoris muscle and the FDI muscles of both arms in a random order. These measurements were interspersed so that PPT was assessed once over each site and this was then repeated in the same order until three measurements had been obtained for each site. Pressure pain threshold was recorded as the average of these three measurements. Two practice trials were performed on the left rectus femoris muscle prior to testing to familiarise the participant with the procedure. The rubber-tipped probe of a handheld algometer (Wagner Force 10

FDX-25, Wagner Instruments, Greenwich, CT) was applied perpendicularly to the participant’s skin and the force was increased gradually at a rate of approximately 1

110 kg/s. Participants were instructed to give a verbal command of ‘‘stop’’ when the sensation of pressure turned to pain. The duration of pressure application for each PPT measure was similar for each site (~5 s over the hand and ~6 s over the rectus femoris).

5.3.2.2. Upper limb occlusion

The sleeve of a standard sphygmomanometer was placed around the participant’s upper arm and the cuff was inflated to 240 mm Hg. This high pressure was chosen so that occlusion of the limb would be maintained despite elevations in systolic blood pressure during dynamic exercise380. Each period of occlusion lasted approximately 8-10 min, which corresponded to the time it took to assess PPTs before and after exercise or rest as well as the 5 min intervention itself. Immediately after cuff inflation and prior to the intervention (pre), participants were asked to rate the intensity and unpleasantness of any pain from the pressure of the cuff on their arm using a 0-10 numerical and categorical scale (0 = no pain, 10 = worst possible pain). Ratings were also made of the intensity and unpleasantness of any painful ischaemic sensations in the forearm and hand. These ratings were obtained again immediately prior to cuff deflation following the intervention (post). To account for any effect of altered sensation by occlusion on PPTs, tactile sensation was assessed at the same time points as the pain ratings by lightly brushing the fingertips of the participant’s occluded hand with cotton wool and asking them to describe the sensation. A familiarisation trial prior to occlusion was provided so that participants were aware of what their ‘normal’ sensation felt like.

To reduce the influence of any residual effects from the first period of occlusion, both arms were occluded during the experiment – one for rest and the other for exercise – and the order of the arm that was occluded first was randomised.

111 5.3.2.3. Aerobic exercise

Short duration exercise was used to minimise the amount of time participants spent with their arm occluded. Short duration aerobic exercise has not previously been used in studies of EIH, so high intensity exercise was used to increase the likelihood that exercise would evoke EIH202,326. Further, recumbent cycling was used to minimise/negate any influence that forcefully gripping the handlebars during exercise might have had on PPTs at the hand. Participants were seated behind a stationary cycle ergometer (Monark 828e, Vansbro, Sweden) with their arms relaxed by their sides.

Because it takes several minutes for heart rate to increase and then stabilise after the commencement of exercise, exercise intensity was based on ratings of perceived exertion (RPE, Borg’s 6-20 scale). The aerobic exercise bout consisted of 5 min of high-intensity cycling in which participants were instructed to pedal at a work-rate corresponding to a RPE of 17 or greater (i.e., very hard). Measurements of work-rate and RPE were recorded every 30 s during the exercise bout and, when necessary, the work-rate was adjusted so that participants maintained their target intensity.

5.3.3. Data processing and statistical analysis

5.3.3.1. Sample size calculation

Sample size calculations were performed using G*Power (version 3.1.9.2,

Dusseldorf, Germany)314. The primary outcome in this study was the effect of exercise on PPT at the occluded versus the non-occluded limb. Exercise has a moderate effect on increasing pain thresholds at non-exercised limbs190,214, however a difference in PPT between limbs (i.e. occluded versus non-occluded) would be an inherently smaller effect. A physiologically meaningful difference for PPT was estimated to be in the order of 0.4 ± 0.7 kg/cm2 (mean ± SD), which corresponded to approximately one-third of the

112 typical elevation of pressure pain threshold in an unexercised limb following high- intensity exercise of a large muscle group237. Assuming an effect of this size, and using a paired sample t-test with an alpha of 0.05 and 90% power, it was calculated that 35 participants were needed for this study.

5.3.3.2. Statistical analysis

Descriptive statistics were calculated using the IBM Statistical Package for

Social Sciences (version 22, Chicago, IL, USA). Differences in pressure pain threshold at each muscle were examined with a three (time: baseline, pre, post) x two (condition: rest, exercise) repeated measures analysis of variance (ANOVA). Pain ratings during limb occlusion by the cuff were tested with a two (time: pre, post) x two (condition: rest, exercise) repeated measures ANOVA. Normality of the data was assessed using the

Kolmogorov Smirnov statistic. Paired sample post hoc tests were conducted to identify the source differences in pain thresholds and pain ratings that were detected by ANOVA and to investigate differences in EIH between men and women. There have been several investigations of sex differences in EIH208,228,237, but the comparison of EIH between men and women in the present study was purely a secondary analysis. The study was not designed, nor powered, to test for a sex difference in EIH. If sphericity was violated,

Huynh-Feldt and Greenhouse-Geisser corrections were used when epsilon was > 0.75 and < 0.75, respectively. Alpha was set at 0.05 and the p value for the t-tests was multiplied by the number of comparisons for each ANOVA model. Bonferroni corrected Student’s paired sample t-tests were also used to compare change scores in pressure pain thresholds to contrast the effects of rest and exercise. Cohen’s d effect sizes (ES) and 95% confidence intervals (CIs) were also calculated to aid these comparisons and were interpreted as small (0.2), medium (0.5) or large (0.8)315 . The

113 95% CIs of the effect size were calculated using a non-central t distribution316. Except where stated, values are reported as the mean and 95% CI. Absolute units are used for presentation of PPT data in figures whereas percent changes are used in text to enable easier interpretation and comparison of the results.

5.4. Results

5.4.1. Participant characteristics and exercise intensity

Thirty-six volunteers participated in this study. Participant characteristics and exercise intensity data are outlined in Table 5.1. The majority of participants were undergraduate students who did not regularly participate in moderate-high intensity exercise and had minimal experience with cycle ergometer exercise. This was evident from the relatively high RPE during exercise despite modest work-rates (Table 5.1).

The participants’ level of perceived exertion during exercise was slightly below the target RPE of 17, but the values indicate that the participants still perceived the exercise to be between ‘hard (heavy)’ and ‘very hard’.

Table 5.1. Participant characteristics and exercise intensity

All (n = 36) Males (n = 18) Females (n = 18)

Age (years) 22.1 ± 1.6 21.6 ± 3.9 22.6 ± 3.3

Work-rate (W) 151 ± 45 186 ± 25 116 ± 29

RPE (legs) 16.1 ± 1.1 16.2 ± 1.1 16.0 ± 1.2

RPE (overall) 15.5 ± 1.6 15.3 ± 1.8 15.6 ± 1.4

Values represent mean ± standard deviation. RPE, rating of perceived exertion. W, watts.

114 5.4.2. Pressure pain thresholds

Data for PPTs are shown in Figure 5.2. There was a significant effect of time

(F(1.13, 39.50) = 37.75, p < 0.001) and condition (F(1, 35) = 10.37, p = 0.003), as well as a significant time x condition interaction (F(2, 70) = 64.32, p < 0.001), for PPT over the rectus femoris muscle. A significant effect of time (F(1.61, 56.25) = 24.78, p < 0.001), condition (F(1, 35) = 12.08, p = 0.001) and a time x condition interaction (F(1.71, 59.71) =

52.37, p < 0.001) was also observed for PPT over the non-occluded FDI muscle. There was no effect of time (F(1.31, 46.02) = 1.86, p = 0.16) or condition (F(1, 35) = 2.42, p = 0.13) for PPT over the occluded FDI muscle, however a significant time x condition interaction was observed (F(1.58, 55.32) = 10.37, p = 0.017). Post-hoc comparisons of pain thresholds prior to cuff inflation (i.e. baseline) to those measured before rest or exercise

(but still during cuff inflation) showed no significant effect of occlusion on PPTs over any muscle (range of mean change: -1.4% to +3.9%, all d < 0.09 and p > 0.54). There was also no significant effect of quiet rest on PPT over any muscle (range of mean change: -1.3% to +0.9%, all d < 0.05 and p > 0.51). In contrast, exercise significantly increased PPT over the rectus femoris (+29.3 ± 13.9 % (mean ± SD), d = 0.69 (0.47 to

0.90), p < 0.001), non-occluded FDI (+22.7 ± 13.9) % (mean ± SD), d = 0.56 (0.38 to

0.74), p < 0.001) and occluded FDI muscles (+8.3 ± 13.6 % (mean ± SD), d = 0.19

(0.07 to 0.32), p = 0.018).

115 Figure 5.2. Pressure pain thresholds

Individual data (grey dots) and group data (mean and 95% confidence interval, black lines) prior to cuff inflation (baseline) as well as during cuff inflation before and after rest and exercise (Ex) for pressure pain thresholds (PPTs) at the rectus femoris muscle (A) and the non-occluded and occluded first dorsal interosseous muscles (FDI, panels B and C, respectively). * indicates a significant increase in PPT after exercise (p = 0.018); ** indicates a significant increase in PPT after exercise (p < 0.001).

116 Data for the change scores of the PPTs (in kg/cm2) are shown in Figure 5.3. The increase in PPT after exercise was significantly smaller in the occluded limb versus the non-occluded limb (-14.4 ± 13.0 % (mean ± SD) of the difference), d = -1.03 (-1.44 to -

0.65), p < 0.001), as shown in the change scores plotted in Figure 5.3. The smaller exercise-induced change in PPT for the occluded versus non-occluded limb was also apparent when these changes were expressed relative to the change with quiet rest (-

13.2 ± 15.2 % (mean ± SD) of the difference), d = -0.89 (-1.27 to -0.49, p < 0.001). That is, EIH was diminished when blood flow to that limb was occluded.

Figure 5.3. Change in pressure pain thresholds

Individual data (grey dots) and group data (mean and 95% confidence interval, black lines) for the change

(∆) in pressure pain thresholds (PPT) with rest and exercise (Ex) at the rectus femoris muscle (left column) and the non-occluded and occluded first dorsal interosseous muscles (FDI, middle and right columns, respectively). Comparisons for these data were only made on the differences between the FDI sites. * indicates a significant difference between the non-occluded and occluded arm for the change in

PPT after exercise (p < 0.001). # indicates a significant difference between the non-occluded and occluded arm for the change in PPT after quiet rest compared to exercise (p < 0.001).

117 5.4.3. Pain ratings during occlusion

Data for ratings of pain intensity and pain unpleasantness during occlusion are shown in Figure 5.4. Pain from cuff pressure and ischaemic pain were rated separately.

There was a significant effect of time on ratings of cuff pressure pain intensity (F(1, 35) =

60.86, p < 0.001), cuff pressure pain unpleasantness (F(1, 35) = 68.9, p < 0.001), ischaemic pain intensity (F (1, 35) = 59.7, p < 0.001) and ischaemic pain unpleasantness

(F (1, 35) = 89.78, p < 0.001). All pain ratings significantly increased over time during rest

(range of mean increase: 2.2 to 3.1, all d > 0.91 and p < 0.001) and exercise (range of mean increase: 1.5 to 3.5, all d > 0.63 and p < 0.001), but there were no significant time x condition interactions and no differences in the increase between the rest and exercise conditions were observed (range of mean difference: 0.07 to 0.71, all d ≥ -0.27 and ≤

0.35, all p > 0.40).

Paraesthesia of varying degrees was reported by all participants by the end of occlusion, but all participants were still able to feel the cotton wool on their fingertips by the end of the occlusion period. That is, light touch was diminished but still present in all participants irrespective of the rest or exercise condition.

5.4.4. Sex differences in pressure pain thresholds and pain ratings

There were no significant sex differences in baseline PPTs (all p > 0.16) or PPT change scores after rest and exercise at any site (all p > 0.07). Similarly, no significant differences between men and women were observed for ratings of pain intensity or pain unpleasantness immediately after cuff inflation (all p > 0.13) or for the change in these pain ratings after rest and exercise (all p > 0.14).

118 Figure 5.4. Pain ratings during occlusion

Data to the left of the vertical dotted line in each graph show the individual data (grey dots) and group data (mean and 95% confidence interval, black lines) before and after rest and exercise (Ex) for ratings of cuff pressure pain intensity (A) and unpleasantness (B) as well as ratings of ischaemic pain intensity (C) and unpleasantness (D) during occlusion. Data to the right of the vertical dotted lines show the individual data (grey dots) and group data (mean and 95% confidence interval, black lines) for the differences in pain ratings between the pre rest and post rest measures (∆ Rest) and between the pre exercise and post exercise measures (∆ Ex). Data to the left of the vertical dotted lines are plotted against the left-hand y- axis and data to the right of the vertical dotted line are plotted against the right-hand y-axis. * indicates a significant increase in pain ratings from pre to post (p < 0.001).

119 5.5. Discussion

The current study shows that short-duration high-intensity aerobic exercise increases pressure pain thresholds (PPT) both locally and in unexercised limbs in healthy adults. This increase was significantly diminished in a limb to which blood flow was occluded. These results suggest that substances released into the blood during high intensity dynamic exercise contribute to exercise-induced hypoalgesia (EIH) through peripheral analgesic actions. However, other factors unrelated to the occlusion of blood flow to the limb must also be involved in EIH as PPTs were still significantly increased in the occluded limb after exercise.

In the current study, short duration exercise was used to minimise the time that participants spent with their arm occluded, but it was unclear whether this duration of exercise would be sufficient to elicit EIH. The effect of moderate duration (> 15-20 min) aerobic exercise on reducing pain is well demonstrated190, particularly for higher intensities of exercise (i.e. 60-75% of maximal aerobic capacity)191. Typically, these studies have used similar modalities of exercise (cycle ergometer) and methods of pain assessment (PPT over exercise and non-exercised sites) to those used in the current study, and have produced similar findings. That is, an increase in PPT at exercised and remote sites. For shorter duration aerobic exercise, the effects on pain are less clear. In healthy young men, cycle ergometer interval exercise (4 x 4 min at 85% of heart rate reserve separated by 2 min recovery at 60% of heart rate reserve) was found to reduce sensitivity to noxious thermal stimuli but have no effect on PPT, which was assessed over the muscle belly of a non-exercised muscle (extensor carpi radialis) using a handheld algometer326. This method of PPT assessment was comparable to that used in the current study. Shorter duration (10 min) continuous aerobic exercise has also been shown to reduce thermal280 but not pressure pain sensitivity202, which in this case was

120 assessed by pain ratings every 10 s during the 2 min application of a 9.8N stimulus to the nondominant index finger. The different measures of pressure pain may contribute to the different results214. Nonetheless, the results of this study contrast with the abovementioned studies as moderate increases in PPT at both the exercised and non- exercised, non-occluded muscles demonstrated the presence of EIH.

Following exercise, an approximately 23% and 8% increase, respectively, was observed for PPT at a non-occluded and occluded limb, both of which were unexercised. However, the difference in the increase in PPT between these two sites after exercise was large and significant. That is, blocking blood flow to a limb during exercise diminished EIH in that limb by >60%. Importantly, this same effect was not observed during an equivalent period of quiet rest. These results show that blocking the peripheral delivery of agents released during exercise and carried by the blood markedly diminishes EIH. While it was not within the scope of this study to investigate which agents contribute to this effect, data from animals and humans suggest a likely role of cannabinoids, opioids, catecholamines and nitrite192,245,247,250,258,260,269. Evidence for a significant effect of catecholamines is particularly strong given that their plasma concentrations are greatly increased during high intensity exercise339 and that blocking their peripheral actions reverses EIH in rats269. Furthermore, the time course of elevated catecholamines in the blood following exercise339 corresponds with the typical duration and decrement of EIH following the cessation of exercise302.

The analgesic action of agents released into the blood during exercise represents an interesting mechanism for EIH, which may also account for the consistent observation that EIH is greatest at body sites nearest to exercised muscle200,211. The gradient of blood flow to exercised versus unexercised limbs377,381,382 could provide a reasonable account for these variations in EIH if there are effects at the peripheral

121 nociceptors. That is, the greater delivery of analgesic factors released into the blood during exercise would have greater effects on reducing pain in the exercised limb(s) and muscles that receive the majority of the blood flow, possibly through actions at the peripheral nociceptors. During moderate-high intensity cycling exercise, blood flow to the arms increases only slightly compared to the changes observed for the legs377,381,382.

While this relative difference in blood flow to the arms and legs during cycling does not exactly match the relative increase in PPT at the arms and legs following a comparable dose of cycling200,204,237, some similarities are apparent.

In line with the hypothesis, a significant elevation of PPT in the occluded limb was still observed following exercise, and there are a few possible reasons for this. First, occlusion of blood flow would not be expected to completely eliminate EIH as other peripheral changes would still occur. For example, exercise-induced increases in muscle sympathetic nerve activity would have been ongoing in the occluded arm383-385 and could have influenced pain via the release of agents acting locally on peripheral nociceptors. Second, centrally mediated changes at spinal and/or supraspinal levels231,378 as well as cognitive factors might have also contributed194,284,285, however these were not measured in the present study. It is also possible that EIH in the occluded limb may have been blunted by noxious biochemicals (e.g. metabolites) related to the occlusion that were trapped in the arm by the inflated cuff. While this was not directly examined, the influence of trapped algesic biochemicals on pain would presumably have been captured to some degree in the ratings of ischaemic pain. These ratings did not differ between the exercise and rest conditions.

It is well demonstrated that the same intensity of noxious mechanical stimulation is often perceived as less intense or unpleasant after exercise190. Our current data do not support this however because ratings of cuff pressure pain and ischaemic pain did not

122 differ between the rest and exercise conditions. While spinal, supraspinal and/or cognitive contributors to EIH could influence ratings of cuff pressure pain and ischemic pain, the result showing no effect of exercise on these ratings is consistent with the hypothesis that a circulating factor contributes to EIH. That is, because the cuff was inflated prior exercise specifically to occlude circulation, a circulating factor would not be able to influence pain ratings. Had the cuff been inflated after exercise to cause pain instead, then we would have expected an effect, although EIH is not well demonstrated for ischaemic stimuli190 and is less consistent following aerobic exercise when cuff algometry is used to assess pain196,212,219. Differences in the temporal and spatial properties of cuff versus manual algometry are likely reasons for this. For example, during cuff algometry, the widespread application of pressure over muscle, bone and nerves is likely to activate different tissues and do so less vigorously than when a small probe is used, as evidenced by the greater time it takes to reach pain threshold during cuff algometry (~ 25 s for the leg and ~ 30 s for the arm)341 versus handheld algometry

(~ 6-7 s for the leg and ~ 4-5 s for the arm, present data). Handheld algometry and cuff pressure were both used in the current study, but only thresholds of pain were solicited for algometry while only ratings of pain intensity were solicited for cuff pressure, and the cuff pressure stimulus was present throughout the entire exercise and assessment period compared with only transient measurements with handheld algometry.

Several elements of the experimental design warrant further discussion. First, a very high cuff pressure was used around the arm. This was done to ensure that occlusion of blood flow to the limb was maintained despite large elevations in systolic blood pressure during exercise, often as high as 200 mmHg or more380,386. Accordingly, a cuff pressure of 240 mmHg was chosen for all participants. This cuff pressure was immediately rated by participants as mild-moderately painful (i.e. 4/10) and was

123 therefore of sufficient intensity to potentially induce a conditioned pain modulation or

‘pain inhibits pain’ effect387. Indeed, even non-noxious pressure applied to one body site can reduce pain sensitivity at another site388. The magnitude and reliability of conditioned pain modulation varies based on inter-personal (e.g. age, gender, attention to the conditioning stimulus and expectations about its subsequent effect on pain)389 and experimental factors (e.g. the type of conditioning and test stimuli used, whether pain is assessed during or following the conditioning stimulus)390, whereas psychological factors are less influential391. However, the considerable heterogeneity and risk of bias in the existing conditioned pain modulation literature means that normative values for healthy adults have not been established. Therefore, it is unclear to what extent, if any, a

‘pain inhibits pain’ effect should have been expected in this study. Inspection of the individual data in Figure 5.2 shows that while occlusion did increase PPTs in some participants, many participants also experienced a reduction in their pain thresholds and so the overall group effect of occlusion on PPT was negligible.

Another consideration was whether occlusion of blood flow for 8 – 10 min may have directly influenced the nociceptive afferent axons (i.e. group III/IV afferents aka

A-delta and C fibres). The sensitivity of both fast and slow-conducting afferents are influenced by ischaemic pressure blocks, though it is generally accepted that the faster conducting afferents are affected first392-394. While there is some evidence contrary to this395, it is likely that tactile sensation would have to disappear during occlusion before any effect of occlusion on the nociceptive afferents would be observed in the hand396.

Paraesthesia of varying degrees was reported by all participants during occlusion, however tactile sensation was still present in all participants at the end of occlusion, albeit reduced. This shows that the approximately 10 min period of occlusion in the present study was too short in duration to influence the axons of nociceptive afferents,

124 which is in line with previous studies392,393,395,396 and is supported by the stability of

PPTs observed during occlusion and quiet rest in the current study.

The primary limitation of this study was that the experimenter who assessed

PPTs was not blinded to the limb that was occluded or whether the participant had just rested or exercised. However, blinding would have been difficult for two reasons. First, obvious visible changes occur in the occluded limb during occlusion (i.e. discolouration), so the experimenter would have known which arm was occluded even if it was concealed. Second, the high intensity nature of the exercise meant that participants were often still short of breath when PPTs were being assessed immediately after exercise, and immediate assessment was required to limit the period of occlusion.

Other limitations were that blood pressure was not measured during exercise, so it cannot be said with certainty that complete occlusion of blood flow was maintained during exercise. If it was the case that blood flow was not always blocked completely, it would simply have diminished the observed effect of occlusion. Further, the possible biochemicals mediating the observed effect (e.g. opioids, cannabinoids, catecholamines) were not measured, nor were other changes that could have contributed to differences between the occluded and non-occluded limb (e.g. muscle sympathetic nerve activity, algesic biochemicals, and spinal or supraspinal factors). Lastly, EIH was not measured in participants with and without occlusion of any limb, so it is possible that the background pain from occlusion could have influenced EIH.

125 5.6. Conclusion

In conclusion, this study provides evidence that the reduction in pain sensation after exercise is mediated, at least partially, by factors that are released into the blood during exercise and act at the periphery. Future studies should aim to determine the agents involved in this effect (e.g. opioids, cannabinoids, catecholamines and nitrite) and whether combining exercise with drugs that increase these substances and/or upregulate their receptors has additive effects on relieving pain.

126 Chapter 6:

Explicit education about exercise-induced hypoalgesia influences pain

responses to acute exercise in healthy adults:

A randomised controlled trial

6.1. Abstract

Numerous studies have shown that a single bout of exercise can transiently reduce pain (exercise-induced hypoalgesia (EIH)), but the mechanisms through which it does this are poorly understood. There is some evidence that cognitive processes contribute to EIH, but it is not known whether these higher order processes can be manipulated to influence EIH. The aim of this study was to determine if education about

EIH affected pain responses after acute exercise in healthy adults. In this randomised controlled trial, participants received 15 min of education either about EIH

(intervention, n = 20) or more general education about exercise and pain (control, n =

20). Following this, the participants’ knowledge and beliefs about exercise and pain were assessed. Pressure pain thresholds (PPT) were then measured before and after 20 minutes of cycle ergometer exercise. The results showed that compared to the control group, the intervention group believed more strongly that pain could be reduced by a single session of exercise (p = 0.001) and that the information they had just received had changed what they thought about the effect of exercise on pain (p = 0.009). After exercise, PPT increased in both groups, but the median increase was greater in the intervention group compared to the control group (intervention = 0.78 kg/cm2, control =

0.24 kg/cm2, p = 0.002, effect size (r) of difference = 0.49). Taken together, these results show that cognitive processes in the appraisal of pain can be manipulated to influence EIH in healthy adults. 127 6.2. Introduction

In healthy adults, it is well demonstrated that acute exercise can transiently reduce pain (exercise-induced hypoalgesia, (EIH))190. Relatively few studies have explored where in the nervous system the changes that account for this reduction in pain with exercise might occur. There is some evidence in rats269 and humans211 (Chapter 5) that changes at a peripheral level are important. Human studies show that alterations in the cognitive appraisal of pain also likely contribute180,211,280. For example, higher pain catastrophizing is associated with less EIH194,286,287, though not always233, and acute exercise can reduce ratings of pain unpleasantness in the absence of a change in pain intensity211. Chronic exercise has also been shown to increase pain tolerance independent of a change in pain threshold180. Taken together, the results of these studies suggest that cognitive processes contribute to EIH. The aim of the current study was to demonstrate that a cognitive manipulation can influence EIH and hence, confirm the involvement of cognitive processes in the acute hypoalgesic effect of exercise.

Manipulation of these cognitive factors has been shown to modulate pain in other contexts397-400. Changing expectations about pain – via conditioning, verbal suggestion or imagery – are capable of increasing or decreasing pain depending on the type of expectation provided401. Studies in people with chronic pain show that expectation interventions have medium to large effects on reducing experimental pain and small effects on relieving chronic pain402. Expectation interventions can also affect pain and physical performance in healthy adults403-406. Education is another means by which expectations about pain can be altered. Several studies have shown that a single session of pain neuroscience education can reduce pain and enhance function in people with chronic pain407-409. It is not known whether expectation can influence the hypoalgesic effect of a single bout of exercise

128 Therefore, this study investigated whether education about EIH influenced pain responses to acute exercise in healthy adults. It was hypothesised that EIH would occur in both groups, but that it would be larger in the intervention group who received explicit education about EIH compared to the control group who received more general pain education about pain and exercise.

6.3. Methods

6.3.1. Participants

This was a randomised controlled trial of the effect of a single session of education on pain responses after acute exercise in healthy adults. All procedures were approved by the University of New South Wales Human Research Ethics Committee

(HC 15438) and written informed consent was obtained from each volunteer prior to testing. The trial was registered prospectively with the Australian New Zealand Clinical

Trials Registry (ANZCTRN12616001141437).

Healthy individuals who were reportedly pain free were recruited for this study via advertisements posted on billboards around the university campus and by word-of- mouth. Inclusion criteria were that participants were aged 18 years and above, and were able to speak, read and write English. Participants were excluded if they were currently in pain, had musculoskeletal pain in the last 3 months, or had a history of chronic pain.

Participants were also excluded if they had a severe musculoskeletal, psychiatric, cardiovascular, pulmonary, metabolic and/or neurological disease, or if they knew of any other medical reason that it was not suitable for them to perform moderate-intensity aerobic exercise. All participants were students of the university.

129 6.3.2. Procedures

The experimental procedures are outlined in Figure 6.1. The experiment was conducted in a single session at Neuroscience Research Australia and was approximately 90 min in duration. During the session, participants: 1) completed a series of questionnaires; 2) participated in a one-to-one education session about exercise and pain; 3) performed a bout of aerobic exercise; and 4) had their pressure pain threshold (PPT) measured before and after exercise. Participants were randomised to the intervention or control group by having them blindly reach in to an envelope and pull out a small piece of paper that had written on it the number ‘1’ or ‘2’. Those who drew

‘1’ were assigned to the intervention group and those who drew ‘2’ were assigned to the control group. Participants were not made aware of the meaning of the numbers and the experimenter who assessed PPTs was blind to the study group of the participant.

Figure 6.1. Experimental procedures

Participants were randomised to receive education about exercise-induced hypoalgesia (intervention) or more general education about exercise and pain (control). The education session for both groups lasted approximately 15 min, after which measurements of the participant’s pressure pain threshold were made.

Participants then performed 20 min of moderate-vigorous intensity cycle ergometer exercise, after which pressure pain thresholds were re-assessed.

130 6.3.2.1. Questionnaires

All participants completed several validated questionnaires pertaining to their general health, physical activity levels and beliefs about exercise and pain. These included the SF-36 General Health Short-Form Survey410, the short-form of the

International Physical Activity Questionnaire411, the Tampa Scale for Kinesiophobia412, and the Pain Catastrophizing Scale413.

6.3.2.2. Education about pain and exercise

All subjects participated in a one-to-one educational session about exercise and pain delivered by an Accredited Exercise Physiologist. The scripts and supporting illustrations for the education sessions are included in Appendices A-D and are summarised hereafter. The education session lasted approximately 15 min and was closely matched in duration for the intervention and control groups. During the education session, all participants received information about muscle soreness that may arise during and following exercise, the difference between appropriate pain and inappropriate pain during exercise, and how self-report scales are used to measure pain and exertion. Participants in the intervention group received additional education

(approximately 5 min out of 15 min) about EIH (e.g. what it is, the type(s) of exercise likely to cause it, how long it lasts and the possible mechanisms underlying it) whereas participants in the control group received additional education (approximately 5 min out of 15 min) about pain ratings (e.g. the difference between pain intensity and pain unpleasantness) and how pain sometimes differs between athletes and non-athletes.

The same experimenter provided the education (intervention or control) to all participants. Standardisation of the education was achieved by following a rehearsed script that had been refined through pilot testing (Appendices A and C). Engagement of

131 participants in the education was supported by regular questions to check participant understanding, as well as to provide an opportunity to clarify any points of uncertainty and to relate the education content to their own understanding or experiences.

Immediately following the education session, the participant’s knowledge and beliefs about exercise and pain were assessed using a questionnaire designed specifically for this study (Appendix E). The questionnaire consisted of five items that were each scored on a 7-point Likert scale (0 = strongly disagree, 1 = disagree, 2 = somewhat disagree, 3 = neutral, 4 = somewhat agree, 5 = agree, 6 = strongly agree). The five items were: 1) Exercise is always painful; 2) There can be good pain and bad pain during exercise; 3) Regular exercise can help reduce pain; 4) Pain can be reduced from just a single session of exercise; and 5) The information you have just given me has changed what I thought about the effect of exercise on pain. To quantify the participant’s level of engagement in, and understanding of, the education intervention, two additional items were scored by the experimenter using the same 7-point Likert scale. These were: 1) The participant engaged in the discussion about exercise and pain; and 2) The participant understood the information that was being presented to them

(Appendix F).

6.3.2.3. Aerobic exercise

Aerobic exercise was performed using a stationary cycle ergometer (Monark

828e, Vansbro, Sweden). In healthy adults, EIH is well demonstrated for acute aerobic exercise at moderate-vigorous intensities190,191. Accordingly, moderate-vigorous intensity aerobic exercise was used in this study. Exercise intensity was based on the participant’s rating of perceived exertion (RPE; Borg 6-20 scale) and heart rate as a percent of heart rate reserve. Prior to exercise, the participant’s resting heart rate and

132 age-predicted maximum heart rate were determined414. Then, values corresponding to

65-75% of heart rate reserve were calculated. The target RPE during exercise was 14-15

(i.e. hard).

Exercise began with a 4 min warm-up at a low intensity (RPE < 8), after which the work-rate was increased to correspond to the intensity that elicited the participant’s target heart rate and RPE. Exercise was then continued at this intensity for 20 min, during which time the work-rate (W), heart rate, RPE and rating of pain (0 – 10 scale) were recorded every 2 min. Adjustments to the work-rate were made when necessary to ensure that participant’s remained within their target RPE zone. In some instances, this meant that participant’s had to exercise at intensities above or below their prescribed percentage of heart rate reserve.

6.3.2.4. Pressure pain thresholds

Pressure pain thresholds were measured on the right side of the body over the rectus femoris, tibialis anterior and first dorsal interosseous muscles. These measurements were made before and after exercise using a Wagner Force Ten FDX-50 pressure algometer (Wagner Instruments, Greenwich CT) which had a 1-cm diameter rubber footplate and measured the pressure in kg/cm2. The handheld algometer was placed on each site and then the pressure was gradually increased at a rate of approximately 1 kg/s until the sensation of pressure turned to pain (i.e. PPT). The assessor cycled through each site in a rotational order until three measures per site had been obtained, with the individual’s PPT quantified as the average of these three trials.

Prior to the baseline/pre-exercise measures, several test trials were performed on the left side of the body to familiarize the participant with the procedure.

133 6.3.3. Data processing and statistical analysis

6.3.3.1. Sample size calculation

Sample size calculations were made in G*Power (version 3.1.9.2., Dusseldorf,

Germany)314 using paired and independent sample t-tests with an alpha of 0.05 and power of 0.80. Paired sample t-tests were planned to determine how many participants would be needed to detect EIH (i.e., an increase in pressure pain threshold (PPT) after exercise). Independent sample t-tests on the PPT change scores were planned to determine how many participants would be needed to detect a difference in EIH between the intervention and control groups.

In healthy adults, aerobic exercise has a large effect on increasing PPTs (d =

0.89)190. Assuming this same effect, it was calculated that 12 healthy adults would be needed to detect EIH (i.e., 12 volunteers per study arm for a total of 24 participants).

For detecting a difference in EIH between the intervention and control study groups, we assumed a difference in PPT of 0.25 ± 0.25 kg/cm2 to represent a meaningful change.

On this basis, it was calculated that 20 healthy participants would be needed per study arm to detect a difference in EIH between the study groups (i.e., a total of 40 healthy participants). Therefore, a total of 40 healthy adults needed to be recruited to appropriately power this study.

6.3.3.2. Statistical analysis

Pressure pain thresholds before and after exercise were calculated separately at each site (rectus femoris, tibialis anterior and first dorsal interosseous) as well as using a grand average that was calculated by averaging the three thresholds measured at each site (referred to hereafter as ‘combined’). The grand average of all sites was designated a-priori as the primary outcome measure, accompanied by the questionnaire item “Pain

134 can be reduced from just a single session of exercise”. Descriptive statistics were calculated using the IBM Statistical Package for Social Sciences (version 22, Chicago,

IL, USA). Normality of the data was assessed using the Shapiro-Wilk statistic and equality of variances between the intervention and control groups was assessed using

Levene’s test. Non-parametric inferential statistics were used for data that were not normally distributed. Wilcoxon signed rank tests were used to examine the effect of exercise on PPT in each study group. Mann-Whitney U tests were used to examine differences between the study groups for: the effect of exercise on PPT; participants’ responses to the ‘knowledge and beliefs about exercise and pain’ questionnaire; and for the experimenter’s appraisal of the participants’ engagement in, and understanding of, the education session. Associations between the participants’ beliefs about exercise and pain and the PPT change scores were examined using Spearman’s ranked correlation coefficients as a post-hoc exploratory analysis. To enable comparisons within and between groups, effect sizes (r) were also calculated by dividing the z value of the relevant test by the square root of the number of observations. When necessary, effect sizes were direction adjusted so that an increase in PPT after exercise was signified by a positive effect size. Effect sizes interpreted as small (0.1), moderate (0.3) or large

(0.5)315. Significance for alpha was set at 0.05 for all tests.

6.4. Results

6.4.1. Participant characteristics

Initial screening did not identify any volunteers who were ineligible for this study and all those who attended the laboratory for the experiment completed the study.

Forty volunteers (22 male, 18 female) participated in this study. The number of males and females randomised to the intervention and control groups was similar

135 (intervention: 8 females, 12 males; control: 10 females 10 males). On average (mean ±

SD), participants were young (22 ± 3.6 years of age), a healthy weight (23.3 ± 2.8 body mass index), physically active (3348 ± 2733 MET-min/week), had low levels of kinesiophobia (29.5 ± 5.1 out of 68) and pain catastrophizing (9.5 ± 7.7 out of 52), and rated their general health as good (74.6 ± 14.1 out of 100). There were no significant differences between the intervention and control groups for median physical activity levels (intervention = 2613 MET-min/week, control = 3070 MET-min/week, U = 198.5, z = -0.41, p = 0.97) or pain catastrophizing (intervention = 6.5, control = 7.5, U = 156.5, z = 1.118, p = 0.24), however a significant difference for levels of kinesiophobia was observed. Participants in the control group had higher kinesiophobia (median = 31) than did participants in the intervention group (median = 27.5; U = 93, z = -2.92, p = 0.004).

6.4.2. Effect of education on knowledge and beliefs about exercise and pain

Group data for responses on the knowledge and beliefs about exercise and pain questionnaire are shown in Table 6.1, accompanied by scores for the experimenter’s appraisal of the participants’ engagement in, and understanding of, the education session. There were no significant differences between the intervention and control groups for scores on item 1 (p = 0.93), 2 (p = 1) or 3 (p = 0.69). However, significant differences between the intervention and control groups were observed between scores on items 4 and 5. Mann-Whitney U tests revealed that scores on item 4 (U = 80, z = -

3.397, p = 0.001, r = 0.54) and 5 (U = 107, z = -2.63, p = 0.009, r = 0.42) were higher in the intervention group compared to the control group, indicating that the intervention group felt more strongly that pain could be reduced from just a single session of exercise and also felt more strongly that the information they had received had changed what they thought about the effect of exercise on pain. For the items

136 Table 6.1. Group data (median (interquartile range)) for participant responses to the knowledge and beliefs about exercise and pain questionnaire as well as the

experimenter’s appraisal of the participants’ engagement in, and understanding of, the education provided.

Question Intervention group Control group

Questions answered by the participant

1. Exercise is always painful 1 (1) 1 (3)

2. There can be good pain and bad pain during exercise 5 (1) 5 (1)

3. Regular exercise can help reduce pain 5 (0) 5 (0)

4. Pain can be reduced from just a single session of exercise 5 (0)* 4 (1) 137

5. The information you have just given me has changed what I thought about the effect of exercise on pain 5 (2)* 4.5 (1)

Questions answered by the experimenter

1. The participant engaged in the discussion about exercise and pain 5 (2) 5 (1)

2. The participant understood the information that was being presented to them 5.5 (1)* 5 (1)

Questions were answered using a 7-point Likert scale where 0 = strongly disagree, 1 = disagree, 2 = somewhat disagree, 3 = neutral, 4 = somewhat agree, 5 = agree and 6 =

strongly agree. * indicates a significant difference (p < 0.01) between the intervention and control groups.

137 scored by the experimenter, there was no significant difference on scores for item 1 (p =

0.16) but a significant difference between groups was observed for scores on item 2 (U

= 75, z = -3.76, p < 0.001, r = 0.59). That is, the experimenter believed that the intervention group better understood the information being presented to them compared to the control group.

6.4.3. Aerobic exercise

Participants cycled at an average (mean ± SD) work-rate of 141.6 ± 48.6 W and percentage of heart rate reserve of 85.7 ± 4.8 %. This exercise elicited an average (mean

± SD) RPE of 14.2 ± 0.7 and rating of perceived pain of 3.1 ± 1.8, indicating that participants found the exercise to be hard and mildly painful. No significant differences between the intervention and control groups were observed for RPE (p = 0.81), rating of perceived pain (p = 0.79) or percentage of heart rate reserve (p = 0.82) during exercise

(Table 6.2).

Table 6.2. Mean ± SD work-rate for aerobic exercise and the associated heart rate and perceptual responses.

Intervention group (n = 20) Control group (n = 20)

Work-rate (W) 145.0 ± 53.5 138.3 ± 43.2

Heart rate reserve (%) 85.8 ± 5.7 85.6 ± 3.8

Rating of perceived exertion (6-20) 14.2 ± 0.7 14.2 ± 0.7

Rating of perceived pain (0-10) 3.2 ± 1.7 3.1 ± 1.8

W, watts

138 6.4.4. Pressure pain thresholds

Individual and group data for PPTs are shown in Figures 6.2 and 6.3. There were no significant differences in PPT prior to exercise between the intervention and control groups (combined: p = 0.062; rectus femoris: p = 0.13; tibialis anterior: p = 0.09; first dorsal interosseous: p = 0.10). For the intervention group, there was a large and significant effect of exercise on increasing PPT for the primary outcome of all sites combined (medians: pre = 4.07 kg/cm2, post = 4.61 kg/cm2, z = -3.85, p < 0.001, r =

0.61; Figure 6.2). For the separate sites, a large and significant effect of exercise on increasing PPT was observed for the rectus femoris (pre = 4.19 kg/cm2, post = 4.83 kg/cm2, z = -3.45, p = 0.001, r = 0.54) and tibialis anterior (pre = 4.48 kg/cm2, post =

5.43 kg/cm2, z = -3.66, p < 0.001, r = 0.58) and a moderate and significant effect of exercise on increasing PPT was observed for the first dorsal interosseous (pre = 3.14 kg/cm2, post = 3.45 kg/cm2, z = -3.00, p = 0.003, r = 0.47; Figure 6.3). For the control group, there was a moderate and significant effect of exercise on increasing PPT for the primary outcome of all sites combined (pre = 5.40 kg/cm2, post = 5.51 kg/cm2, z = -

2.01, p = 0.037, r = 0.33; Figure 6.3). For the separate sites, a moderate and significant effect of exercise on increasing PPT was observed for the rectus femoris (pre = 5.83 kg/cm2, post = 5.92 kg/cm2, z = -2.99, p = 0.003, r = 0.47) whereas changes for the tibialis anterior (pre = 6.83 kg/cm2, post = 6.7 kg/cm2, z = -0.15, p = 0.88, r = 0.02) and first dorsal interosseous sites (pre = 3.98 kg/cm2, post = 4.01 kg/cm2, z = -1.18, p =

0.24, r = 0.19) were not significant (Figure 6.3).

Differences between groups for the median PPT change score after exercise were moderate and significant for the combined sites (intervention = 0.78 kg/cm2, control = 0.24 kg/cm2, U = 85, z = -3.11, p = 0.002, r = 0.49), the rectus femoris

(intervention = 0.84 kg/cm2, control = 0.40 kg/cm2, U = 116, z = -2.27, p = 0.023, r =

139 0.36) and the tibialis anterior (intervention = 0.81 kg/cm2, control = 0.35 kg/cm2, U =

114, z = -2.33, p = 0.02, r = 0.37). In contrast, no significant difference between groups for the median PPT change score for the first dorsal interosseous after exercise was observed (intervention = 0.49 kg/cm2, control = 0.31 kg/cm2, U = 141, z = 1.60, p =

0.11, r = 0.25).

Figure 6.2. Effect of exercise on pressure pain threshold (all sites combined)

Individual data (black lines) for the combined pressure pain threshold pre and post exercise for the intervention (Int) and control (Ctl) groups. Group data (box and whisker plots, i.e. median with interquartile range and minimum to maximum range) for the combined PPT change score after exercise for the intervention and control groups are also shown. Data to the left side of the vertical dotted line are plotted against the left-hand y-axis and data to the right side of the vertical dotted line are plotted against the right-hand y-axis.

140 Figure 6.3. Effect of exercise on pressure pain threshold at each site

Individual data (black lines) for the pressure pain threshold pre and post exercise for the intervention (Int) and control (Ctl) groups over the rectus femoris (A), tibialis anterior (B) and first dorsal interosseous (C).

Group data (box and whisker plots) for the PPT change score after exercise for the intervention and control groups at each site are also shown. Data to the left side of the vertical dotted line are plotted against the left-hand y-axis and data to the right side of the vertical dotted line are plotted against the right-hand y-axis. 141 6.4.5. Correlation between beliefs about exercise-induced hypoalgesia and the change in pressure pain threshold

For the entire sample, small-moderate and significant positive correlations were observed between participant responses on ‘Pain can be reduced from just a single session of exercise’ and PPT change scores at the combined (ρ = 0.47, p = 0.002) and rectus femoris sites (ρ = 0.39, p = 0.013). However, the same relation was not observed for the tibialis anterior (ρ = 0.26, p = 0.11) or first dorsal interosseous sites (ρ = 0.12, p

= 0.46), nor were any significant correlations observed when the intervention and control groups were examined separately (all ρ > -0.12 and < 0.4, all p > 0.08).

6.5. Discussion

This is the first study to investigate the effect of education on exercise-induced hypoalgesia (EIH). The results show that education can alter beliefs about EIH, and that this subsequently affects pain responses after exercise in healthy adults. These effects were evidenced by: 1) the intervention group feeling more strongly that the education changed their perceptions about the effect of exercise on pain; 2) the intervention group feeling more strongly that pain could be reduced from a single session of exercise; and

3) the larger exercise-induced increases in pressure pain threshold (PPT) in the intervention group compared to the control group.

In line with previous research180,211, the results of the current study support the notion that EIH involves a central or cognitive component. Adding to past studies, the results show that this cognitive component can be manipulated to influence the effect of exercise on pain. There is evidence that expectation and other higher-order functions

(e.g. attention) can modulate pain responses402,415, however their effect on performance of physical tasks is less clear405,406 and their influence on pain in the context of exercise

142 had not been studied. Thus, this study of healthy adults provides the first evidence that the cognitive component of appraising a noxious stimulus can be manipulated to influence EIH.

It was hypothesised that explicit education about EIH would augment EIH, as evidenced by a greater increase in PPTs after aerobic exercise for the intervention group compared to the control group. This hypothesis was supported by the data. Few studies have examined whether education can acutely influence pain and none of these have been performed in the context of EIH. Case reports and small studies of people with chronic low show that a single session of pain neuroscience education can reduce pain, improve range of motion, and even alter brain activity during an abdominal hollowing task407,409,416. The content (pain physiology) and duration (75 min to 2.5 h) of education in these studies was markedly different to that used in the current study; only

15 min of education about exercise and pain was provided, 5 min of which was specific to EIH. This result provides preliminary evidence that very brief education about EIH can influence pain responses after acute exercise in healthy adults. This has potential implications for clinical practice that could be established by studies of people with chronic pain.

It is important to note that the EIH education in this study did not mention pain thresholds explicitly, only pain ratings, so participants were not aware of what effect, if any, exercise might have on their PPTs. Other important elements of the design were that the experimenter who assessed PPTs was blind to the study group of participants and that the duration of the education intervention and control sessions was matched.

The intervention and control groups also exercised at similar intensities and this evoked comparable levels of perceived exertion and pain. The number of males and females in each group was also similar. Therefore, it is unlikely that the between group differences

143 in PPT after exercise could have been attributable to age or sex differences in

EIH194,208,228,235, nor could it be attributed to dissimilarities in the intensity at which exercise was performed191. The non-normal distribution of the data for several of the outcomes was unexpected, but this was accounted for in the statistical analyses.

A surprising observation was that the control group displayed a smaller increase in PPT than would normally be observed in healthy adults following aerobic exercise of the duration and intensity used in this experiment190,191. Aerobic exercise does not always increase PPT at remote sites204,326 and EIH is generally greater in exercised compared to unexercised limbs200,237, but it is not known whether the control education contributed to the smaller than usual EIH. The content provided to participants in the control group was not intended to induce negative expectations about pain after exercise. Therefore, although both placebo and nocebo effects can influence pain appraisal417,418, a nocebo effect here is unlikely. The data support this because the median response of the control group to the “pain can be reduced from just a single session of exercise” was still “somewhat agree” (although this contrasts with the

“agree” from the intervention group). As both groups had positive expectations that exercise would reduce pain, the results suggest that the difference between the intervention and control groups is due to the added positive effect of the EIH education.

That is, the greater expectation of a reduction in pain after exercise mediated the greater increase in PPTs.

It is notable that in the control group, the only muscle over which a reliable increase in PPT was observed after exercise was the exercised rectus femoris. It has previously been shown that peripheral factors contribute to EIH, possibly through a factor released during exercise and carried in the blood that acts at peripheral nociceptors211 (Chapter 5). While this effect is still apparent in unexercised muscles, it

144 is assumed to be larger at the exercised muscles because these receive more blood flow377. Presumably, this peripheral contribution to EIH occurs regardless of the effects of education. Central and cognitive contributors to EIH may also differ in their influence on pain in exercised compared to unexercised limbs, but this is speculative and requires further study. The data do not clearly indicate whether or not there are interactions between the level of EIH, or the state of the limb tested, and the influence of education. Nonetheless, peripheral and central factors appear important in EIH.

There were limitations to the present study. First, as only young healthy men and women were included, the results cannot be generalised to older adults or other populations (e.g. patients with chronic pain). Second, there was the possibility for bias in the experimenter’s rating of the participant’s engagement in, and understanding of, the education intervention. However, there is no evidence that this occurred because these data merely complemented the participant’s own rating of their knowledge and beliefs about exercise and pain. Thirdly, participants in both groups at baseline were already of the belief that a single bout exercise could acutely reduce pain. This may have imposed a ceiling effect on the ability of the intervention to change this belief further. Lastly, and although not a limitation per se, participants were educated only to expect a reduction in their pain after exercise. Therefore, the addition of a group who were educated to expect an exacerbation in their pain after exercise would have provided a more complete test of the study hypothesis.

145 6.6. Conclusion

In conclusion, the results of this study show that education can influence pain responses after acute exercise in healthy adults. These findings support the notion of a cognitive contribution to EIH, which can be manipulated by education. These findings have potential clinical relevance whereby education might be used to increase the pain- relieving effects of a single bout of exercise, in particular for patient groups in whom exercise can often exacerbate rather than relieve pain.

146 Chapter 7:

Exercise-induced hypoalgesia in people with fibromyalgia or knee

osteoarthritis: A systematic review and meta-analysis

7.1. Abstract

The aim of this chapter was to better understand how acute and daily physical activity influence pain in people with fibromyalgia or knee osteoarthritis compared to healthy adults. Systematic reviews of exercise-induced hypoalgesia, and of cross- sectional studies investigating associations between physical activity or fitness and pain, were performed. In healthy adults, acute exercise reduced pain with a moderate effect (d

= -0.57 to -0.67), but there was no clear relation between physical activity or fitness and pain. In people with fibromyalgia, aerobic exercise had a small effect of acutely reducing pain (d = -0.16), isometric exercise had a small effect of increasing pain (d =

0.20), and small-moderate inverse associations between pain and physical activity or fitness were consistently observed (i.e., more pain with less activity or less fitness). In people with knee osteoarthritis, aerobic and resistance exercise both acutely reduced pain with small effects (d = -0.13 and -0.14, respectively) and there were similarly small inverse associations between pain and physical activity (β = -0.05 to -0.12) or fitness (β

= -0.23 to -0.35). Exercise-induced hypoalgesia is disrupted in people with fibromyalgia or knee osteoarthritis. Despite this, pain tended to be lower in people with fibromyalgia who completed more daily physical activity, while such a relation was not observed in healthy adults. The comparatively stronger inverse associations between pain and fitness for people with fibromyalgia or knee osteoarthritis are consistent with the reduction of pain from long-term exercise and physical activity (i.e., accompanying higher fitness), but limited acute relief of pain with physical activity. 147 7.2. Introduction

In healthy adults, acute190 and chronic exercise179,180 reduce experimentally- induced pain, and regular exercise and daily physical activity protects against the development of chronic pain108,122. While it is clear that regular exercise improves pain in people with chronic pain40, paradoxically, acute exercise can have the opposite effect and transiently exacerbate pain and symptoms195,210,238,419. The review of literature in

Chapter 2 highlighted that the mechanisms through which acute and chronic exercise influence pain are poorly understood. Accordingly, the reason(s) for the sometimes opposing effects of acute and chronic exercise on pain in people with chronic pain are not known. The results imply however, that the physiological and/or behavioural adaptations that occur with chronic exercise to reduce pain are not immediate and may instead take several weeks240,304,420.

The effect of acute exercise on pain in people with chronic pain was last reviewed in 2012190. Since then, more studies of exercise-induced hypoalgesia (EIH) in people with chronic pain have been published, but their results have not been synthesised. There have been numerous systematic reviews of longitudinal studies investigating the effect of regular exercise on pain in people with chronic pain40, but no studies have systematically reviewed how physical activity and fitness are related to pain in people with chronic pain. Synthesis of these acute and cross-sectional studies, including comparison to healthy adults, may improve understanding of how exercise affects pain in people with chronic pain. This approach is an avenue of inquiry to better understand the relation between the acute pain response to exercise and chronic adaptations to exercise.

148 Therefore, the aim of this chapter was to synthesise the literature investigating

EIH in healthy adults and people with chronic pain, specifically fibromyalgia (FM) or knee osteoarthritis (OA). Associations between pain and physical activity or fitness were also investigated. Systematic literature reviews were conducted, accompanied by meta-analysis where appropriate. It was hypothesised that EIH would be greater in healthy adults compared to people with FM and knee OA, but that associations between pain and physical activity or fitness would be larger in people with FM and knee OA compared to healthy adults.

7.3. Methods

7.3.1. Literature searches

For the systematic review and meta-analysis of EIH in healthy adults, data from a 2012 meta-analysis190 was supplemented with results from more recently published studies. These studies were identified using an online search of the PubMED and Web of Science databases from December 2012 to November 2016. The search terms (‘pain’,

‘exercise’, ‘contraction’, ‘hypoalgesia’ and ‘isometric’) and inclusion criteria (a repeated measures, within subject design; a pain threshold and/or pain intensity measure; a standardised pain induction protocol; and a standardised exercise protocol) were the same as the 2012 meta-analysis190.

For the systematic review and meta-analysis of EIH in people with FM and OA, data from the 2012 meta-analysis190 was supplemented with results from more recently published studies identified using the same search strategy outlined above.

“Fibromyalgia” and “osteoarthritis” were added as additional search terms to make the results of the literature search specific to these two chronic pain states. The inclusion

149 criteria were the same as those mentioned above, plus the additional criterion “a medical diagnosis of FM or knee OA”.

The systematic reviews of cross-sectional studies examining the associations between pain and physical activity or fitness in healthy adults and people with FM are described in detail elsewhere123. Briefly, studies were located using electronic searches of the PubMED and Web of Science databases until July 2015 and were complemented by examining the reference sections of published articles identified by the initial search.

Studies were included if they met the following criteria: 1) performed on healthy individuals or people with FM as described by a clinical questionnaire or diagnosis, 2) included a measure of pain, 3) included a measure of physical activity or fitness, and 4) examined the association between the measure of pain and measure of physical activity or fitness (or provided sufficient data to do so).

For people with knee OA, studies were located using an electronic search of the

PubMED and Web of Science databases until March 2016. Again, this search was complemented by examining the reference sections of published articles identified by the initial search. The search terms included: ‘knee osteoarthritis’ AND ‘pain’ AND

’exercise’, ‘fitness’, ‘strength’, ‘power’, ’aerobic fitness’, ‘cardiovascular fitness’,

‘cardiorespiratory fitness’, ‘physical activity’, ‘objective activity’, ‘activity level’,

‘accelerometer’, ‘activity monitor’, ‘pedometer’, ‘actigraphy’. Studies were included if they met the following criteria: 1) performed on people with knee OA as described by a clinical questionnaire or diagnosis, 2) included a measure of pain, 3) included a measure of physical activity, and 4) examined the association between the measure of pain and levels of physical activity.

150 7.3.2. Data processing and statistical analysis

For the meta-analyses of EIH in healthy adults and people with FM or knee OA, effect sizes (unbiased Cohen’s d) and 95% confidence intervals were calculated. In the cases where identified studies did not adequately report data for the calculation of effect sizes, means and standard deviations were estimated from the studies’ figures using the data extraction software GRABIT (MATLAB version R2012b, MA, USA). This software enables users to select specific points on a figure (e.g., the mean and variance of the data) and export them as numerical values based on their X and Y coordinates.

This software was used for the estimation of effect sizes in five studies of healthy adults200,204,234,378,421, two studies of people with FM378,422 and one study of people with knee OA298. When necessary, effect sizes were direction adjusted so that they were negative when acute exercise reduced pain (i.e., EIH) and positive when acute exercise exacerbated pain. Data from studies that investigated EIH in subgroups of participants

(i.e., men versus women, young versus old, or active versus inactive) were pooled to give a single EIH value for the entire sample. Heterogeneity of the included studies was quantified using the Q and I2 statistics316 and the effects of different exercise modalities

(aerobic and resistance (isometric or dynamic)) on pain were examined separately.

To enable comparison between the studies, which examined the associations between pain and physical activity or fitness, the results of analyses using correlation, linear regression, or effect sizes of differences between groups were converted to standardised beta coefficients (β) and their standard errors and 95% confidence intervals were calculated316,423. When necessary, β coefficients were direction adjusted so that they were negative when greater activity/fitness was associated with less pain and were positive when greater activity/fitness was associated with more pain. For the studies of healthy adults and people with FM, pooled effect sizes could not be calculated because

151 the multiple correlations used in these studies did not provide independent measures of an effect123. Instead, conclusions about the overall association between activity and fitness with pain in these populations were drawn from visual inspection of the data. For the studies of people with knee OA, heterogeneity was quantified using the Q and I2 statistics316 and the different indices of physical activity (total and moderate-vigorous) and fitness (aerobic capacity, muscle strength and muscle power) were analysed separately. The methodological quality of the included studies is outlined in Appendices

N-Q.

7.4. Results

7.4.1. Exercise-induced hypoalgesia

7.4.1.1. Healthy adults

The 2012 meta-analysis included two studies of dynamic resistance exercise424,425, eight studies of aerobic exercise195,202,229,426-430, and 11 studies of isometric exercise207,209,210,231,232,276,277,291,431-433. The literature search identified an additional 19 studies of aerobic exercise196,197,199,200,203-

205,220,234,235,237,280,281,288,313,326,340,421,434,435, 18 studies of isometric exercise189,192-

194,196,200,205,208,212,220,230,233,235,236,279,289,378,436 and four studies of dynamic resistance exercise213-215,228. The GRABIT software was used to extract data from six of these new studies200,204,234,378,421. The results of Chapters 3-6 of this thesis were also included. Of the newly identified studies, three were excluded because they did not provide adequate data or figures for the calculation of effect sizes236,288,289. Therefore, a total of 29, 26 and six studies of aerobic, isometric and dynamic resistance exercise, respectively, were included in the meta-analysis of EIH in healthy adults.

152 The results of the meta-analysis for aerobic and resistance exercise in healthy adults are shown in Figures 7.1 and 7.2, respectively. The Q and I2 values indicated that there was significant heterogeneity between the studies for aerobic (Q = 138.92, p <

0.001, I2 = 79.8 %), isometric (Q = 114.88, p < 0.001, I2 = 75.6 %) and dynamic resistance exercise (Q = 16.89, p = 0.005, I2 = 70.4 %), so the random effects model was used. Moderate and significant effects of all three types of exercise on reducing pain were observed (aerobic: d = -0.51 (-0.68 to -0.34), p < 0.001; isometric: d = -0.67 (-0.82 to -0.52), p < 0.001; dynamic resistance exercise: d = -0.62 (-0.94 to -0.29), p = 0.002)).

Figure 7.1. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute aerobic exercise on pain in healthy adults (circles), including meta- analysis of these studies (diamond). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise.

Significant effects (p < 0.05) are shown in black and non-significant effects have grey symbols and error bars. Abbreviations: CPI = cold pain intensity; EPT = electrical pain threshold; HPI = heat pain intensity;

PPI = pressure pain intensity; PPT = pressure pain threshold. 153 Figure 7.2. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute isometric and dynamic resistance exercise on pain in healthy adults

(circles), including meta-analysis of these studies (diamonds). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Significant associations (p < 0.05) are shown in black and non-significant associations have grey symbols and error bars. Abbreviations: EPI = electrical pain intensity; HPI = heat pain intensity; PPI = pressure pain intensity; PPT = pressure pain threshold; PPTOL = pressure pain tolerance.

154 7.4.1.2. Fibromyalgia

The 2012 meta-analysis included five studies of EIH in people with FM – two of aerobic exercise and four of isometric exercise190. The new literature search identified two more studies each of aerobic217,288 and isometric exercise378,422. One study of dynamic resistance exercise was also identified297, but it was excluded because it did not provide sufficient data for the calculation of effect sizes. Therefore, a total of four aerobic and six isometric exercise studies were included in the meta-analysis of EIH in people with FM.

The results of the meta-analysis are shown in Figure 7.3. The Q and I2 values indicated significant heterogeneity between the studies for aerobic (Q = 16.76, p <

0.001, I2 = 82.1 %) and isometric exercise (Q = 40.11, p < 0.001, I2 = 87.5 %), so the random effects model was used. There was a small and non-significant effect of aerobic exercise on reducing pain (d = -0.16 (-0.76 to 0.44), p = 0.59) and a small and non- significant effect of isometric exercise on increasing pain (d = 0.20 (-0.41 to 0.80), p =

0.52).

7.4.1.3. Knee osteoarthritis

There were no studies of EIH in people with knee OA included in the 2012 meta-analysis190. The new literature search identified six studies of EIH in people with

OA214,219,220,238,289,298. Several of these studies were excluded because they did not separate participants with knee and hip OA289, did not provide adequate data for calculation of effect sizes289, or used a non-standardised pain induction298 or exercise protocol238. Of the remaining three studies, two used isometric and aerobic exercise219,220 and one used dynamic resistance exercise214. The isometric and dynamic resistance exercise studies were analysed together in the meta-analysis.

155 Figure 7.3. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute exercise on pain in people with fibromyalgia (circles), including meta-analysis of these studies (diamonds). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Significant effects (p < 0.05) are shown in black and non-significant effects have grey symbols and error bars. Abbreviations: HPI = heat pain intensity; PPT = pressure pain threshold.

The results of the meta-analysis are shown in Figure 7.4. The Q and I2 values indicated sufficient homogeneity between the studies for aerobic (Q = 1.23, p = 0.27, I2

= 18.8 %) and resistance exercise (Q = 1.85, p = 0.39, I2 = 0.0 %). Small, non- significant effects of exercise on reducing pain were observed for aerobic (d = -0.13 (-

0.39 to 0.13), p = 0.34) and resistance exercise (d = -0.14 (-0.37 to 0.09), p = 0.25).

156 Figure 7.4. Forest plot (unbiased Cohen’s d (mean and 95% confidence intervals)) of findings from studies examining the effect of acute exercise on pain in people with knee osteoarthritis (circles), including meta-analysis of these studies (diamonds). Data to the left of the vertical dotted line indicate a hypoalgesic effect of exercise and data to the right of the vertical dotted line indicate a hyperalgesic effect of exercise. Significant effects (p < 0.05) are shown in black and non-significant effects have grey symbols and error bars. Abbreviations: PPT = pressure pain threshold.

7.4.2. Associations between physical activity or fitness and pain

The results of the studies of healthy adults and people with FM have previously been published elsewhere123. Briefly, seven studies of healthy adults were included, of which five provided data for the analysis of associations between physical activity and pain164,185-187,301 and two provided data for the analysis of associations between fitness and pain123,437. Ten studies of people with FM were included, of which two provided data for the analysis of associations between physical activity and pain163,164 and eight provided data for the analysis of associations between fitness and pain438-445. Thirty- three studies of people with knee OA were included, of which 14 provided data for the analysis of associations between physical activity and pain446-459 and 21 provided data for the associations between fitness and pain176,458,460-478.

157 7.4.2.1. Healthy adults

The studies of healthy adults comprised 57 associations between physical activity or fitness and pain (Figure 7.5). Positive associations (more activity/fitness, more pain) were found 16% of the time, but all of these were small (β < 0.2) and non- significant. Negative associations (more activity/fitness, less pain) were found more consistently, but only 12% of these were significant and they were generally only small to moderate in magnitude (range of β = -0.3 to -0.59). Due to the multiple correlations used within the included studies, meta-analysis could not be performed on these data.

However, visual inspection of Figure 7.5 suggests a small inverse association between pain and activity or fitness.

7.4.2.2. Fibromyalgia

The studies of people with FM included 46 associations between physical activity or fitness and pain (Figure 7.6). Greater activity/fitness was seldom associated with more pain (6% of the time) and when it was, the associations were small (β < 0.2) and non-significant. Negative associations between activity or fitness and pain were more common and the majority of these were significant for physical activity (67%) and muscle strength (89%). Significant associations between pain and aerobic capacity were observed less often (38% of the time). Again, due to the multiple correlations used within the included studies, meta-analysis could not be performed on these data.

However, visual inspection of Figure 7.6 suggests a small-moderate inverse association between pain and physical activity or fitness, particularly muscle strength, in people with FM.

158 Figure 7.5. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between physical activity or fitness and pain in healthy individuals. Data to the left of the vertical dotted line indicate an inverse association between physical fitness/activity and pain (e.g. more activity and less pain) and data to the right of the vertical dotted line indicate a positive association between physical fitness/activity and pain (e.g. more activity and more pain). Significant associations (p < 0.05) are shown in black. Abbreviations: D = m. deltoid; IFP = infrapatellar fat pad; KE = knee extensor; KF = knee flexor; LB = lower body; UB = upper body; VL = m. vastus lateralis; VO2peak = peak aerobic capacity.

159 Figure 7.6. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between physical activity or fitness and pain in people with fibromyalgia. Data to the left of the vertical dotted line indicate an inverse association between physical fitness/activity and pain (e.g. more fitness and less pain) and data to the right of the vertical dotted line indicate a positive association between physical fitness/activity and pain (e.g. more fitness and more pain). Significant associations (p < 0.05) are shown in black and non-significant associations are shown in grey. Abbreviations: 6MWT = 6-minute walk test; FIQ = Fibromyalgia Impact Questionnaire; KE = knee extensor; KF = knee flexor; MPI = Multidimensional Pain Inventory; SF-36 = Medical Outcomes Study

Short-form 36 health survey; VO2peak = peak aerobic capacity.

160 7.4.2.3. Knee osteoarthritis

The associations of physical activity and fitness with pain in people with knee

OA are shown in Figures 7.7 and 7.8, respectively. The Q and I2 values indicated that there was significant heterogeneity between the studies for total physical activity (Q =

125.12, p < 0.001, I2 = 91.2 %), moderate to vigorous physical activity (Q = 9.50, p =

0.049, I2 = 57.9 %), muscle strength (Q = 75.41, p < 0.001, I2 = 73.5 %) and muscle power (Q = 4.47, p = 0.034, I2 = 77.6 %), so the random effects model was used.

Studies of aerobic capacity were sufficiently homogenous (Q = 4.29, p = 0.12, I2 = 53.4

%), but the random effects model was used anyway as a more conservative estimate of the true effect size.

The overall effect size (β, mean and 95% confidence interval) of the association between total activity and pain was small and non-significant (β = -0.05 (-0.17 to 0.07).

The association between moderate-vigorous activity and pain was small as well (β = -

0.12 (-0.23 to -0.02), but it was significant. For fitness, small and significant associations between pain and aerobic capacity (β = -0.35 (-0.50 to -0.21), muscle power (β = -0.28 (-0.44 to -0.12) and muscle strength (β = -0.23 (-0.33 to -0.14) were observed.

161 Figure 7.7. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between physical activity and pain in people with knee osteoarthritis (filled circles), including meta-analysis of these data (diamonds). Data to the left of the vertical dotted line indicate an inverse association between physical activity and pain (e.g. more activity and less pain) and data to the right of the vertical dotted line indicate a positive association between physical activity and pain (e.g. more activity and more pain). Data for total activity are plotted above the horizontal dotted line and data for moderate-vigorous physical activity are plotted below the horizontal dotted line. Significant associations (p < 0.05) are shown in black and non-significant associations have grey symbols and error bars. Abbreviations: NRS = Numerical Ratings Scale; SF-36 = Medical Outcomes

Study Short-form 36 health survey; WOMAC = Western Ontario and McMaster Universities

Osteoarthritis Index.

162 Figure 7.8. Forest plot (standardised beta coefficients (mean and 95% confidence interval)) of findings from studies examining the association between fitness and pain in people with knee osteoarthritis (filled circles), including meta-analysis of these data (diamonds). Data to the left of the vertical dotted line indicate an inverse association between fitness and pain (e.g. greater fitness, less pain) and data to the right of the vertical dotted line indicate a positive association between physical activity and pain (e.g. greater fitness, more pain). Significant associations (p < 0.05) are shown in black and non-significant associations have grey symbols and error bars. Abbreviations: AIMS = Arthritis Impact Measurement

Scales; KOS-ADLS = Knee Outcome Survey Activities of Daily Living Scale; KOOS = Knee Injury and

Osteoarthritis Outcome Score; NRS = Numerical Ratings Scale; WOMAC = Western Ontario and

McMaster Universities Osteoarthritis Index; VAS = visual analogue scale.

163 7.5. Discussion

The results of this chapter show that, compared to healthy adults, exercise- induced hypoalgesia (EIH) is disrupted (smaller) in people with fibromyalgia (FM) or knee osteoarthritis (OA). However, associations between physical activity and pain in people with FM – whereby more physical activity was associated with less pain – were typically larger than those observed for healthy adults, while highly variable associations were reported for people with knee OA. Associations between pain and fitness in people with FM or knee OA were larger than for healthy adults and also larger than the associations between physical activity and pain. Taken together, these results imply that, in people with chronic pain, the short-term response to increased physical activity tends towards symptom exacerbation whereas the effect of long-term exercise is to reduce pain. Possible reasons for these discrepant findings are discussed hereafter.

The meta-analysis of EIH in healthy adults showed that aerobic, resistance and isometric exercise all reduced pain with a moderate effect. In contrast, acute exercise had only a small effect on reducing pain in people with knee OA; while for people with

FM aerobic exercise had a small effect of reducing pain but isometric exercise had a small effect of increasing pain. These results demonstrate that EIH in people with chronic pain is disrupted, but the reasons for this are not clear.

There was considerable heterogeneity between the studies, such as the disease status of the participants (FM or knee OA, level of disease severity, presence of co- morbidities), the exercise protocol (modality, intensity and duration), and the method of pain assessment (type of noxious stimulus, threshold/rating/tolerance, exercised/remote site), which would explain some of the variance of EIH across studies of people with

FM or knee OA. Given this considerable variation, as well as the limited number and size of available data sets, no meta-regression analyses were performed to seek to

164 identify the factors that most influence EIH in these patient populations. Further, the risk of bias in the included studies was not examined, so the strength of the evidence on which these conclusions are based is limited.

The relative contribution of physiological, cognitive or emotional changes associated with chronic pain that influence EIH has not been well investigated. There is some evidence that EIH is reduced in people with chronic pain who are more pain sensitive or have a blunted capacity to modulate pain220,221. However, this could be due to sensory changes, cognitive factors, or indeed, both. The metabolic and endocrine responses to acute exercise are well described, with changes in various muscle metabolites, catecholamines and cytokines apparent479. Many of these substances are involved in nociception, so they may be contributing to disrupt EIH in people FM or knee OA. However, clear supporting evidence is lacking, because acute exercise has varying effects on levels of these nociceptive substances in people with FM or knee

OA296-299 and a relation between these changes and a change in pain is not always apparent297,298.

Because cognitions and emotions contribute strongly to chronic pain as well76, they too may contribute to disrupted EIH. Certainly, high levels of pain catastrophizing predict worsening pain during exercise and poorer performance on tests of physical function in various chronic pain populations439,480,481. It is reasonable that these same psychosocial factors could disrupt EIH as well, but this has not been directly investigated. The occlusion (Chapter 5) and education (Chapter 6) techniques used in this thesis may be avenues through which to investigate differences in the mechanisms of EIH between healthy adults and people with chronic pain. This will be discussed more in the next chapter.

165 The systematic reviews of cross-sectional studies also identified differences between healthy adults and people with chronic pain for the associations between physical activity or fitness and pain. This time, however, the differences favoured people with chronic pain whereby inverse associations between fitness, and to a lesser extent physical activity, with pain were greater and more consistent in people with FM or knee OA compared to healthy adults. The clear association of less pain and more fitness in people with FM and knee OA support the longer-term benefit of exercise on pain in these individuals40. However, the small and widely varied associations between physical activity and pain in these same patient populations do not. These discrepant findings most likely arose from the combination of a disrupted acute exercise effect (i.e. pain exacerbation) but beneficial chronic exercise effect (i.e. pain relief). Indeed, studies where participants logged physical activity and symptom levels multiple times a day across a period of 1-2 weeks support this notion. That is, pain was increased subsequent to a period of increased physical activity, but those who engaged in more physical activity, particularly moderate-vigorous intensity activity, had less pain overall188

(Burrows et al, Unpublished data)446. Hence, the long-term benefits of regular physical activity support a negative association between pain and physical activity, while the short-term response to activity tends to drive a positive association between pain and physical activity.

A limitation of the cross-sectional studies in this chapter is that they do not allow for determination of causality. Therefore, the possibility that people experiencing more pain are less likely to exercise and be fit482 cannot be ruled out. The relation might even be bidirectional, whereby people experiencing more pain perform less activity, but being more active subsequently reduces pain483. Both situations could contribute to the relation between pain and daily physical activity, but the relative contribution of each

166 cannot be determined due to the cross-sectional nature of the included investigations.

However, studies showing physical activity levels to remain largely unchanged in people with chronic pain despite improvements in symptoms and function (e.g., following joint arthroplasty)484 argue against the notion of less pain, more activity.

Moreover, longitudinal studies show regular exercise to reduce pain in people with chronic musculoskeletal pain40. Thus, it can be said with some certainty that exercise drives the inverse association between pain and physical activity or fitness in people with FM and knee OA.

A discrepancy was observed between people with FM and knee OA whereby associations between daily activity and pain were smaller in people with knee OA, but

EIH after resistance exercise was more disrupted in people with FM. This latter result is consistent with other studies showing EIH to be more disrupted in people with FM compared to other chronic pain states (e.g. shoulder and rheumatoid arthritis)197,291. As for the smaller association between daily activity and pain in people with knee OA, it may be that walking, which was the dominant contributor to measurements of physical activity, is more likely to exacerbate pain from knee OA rather than pain from FM due to the loading of the knee during walking188,458. Again, heterogeneity between the studies and the cross-sectional nature of the data do not permit investigation of the factors contributing to these differences between people with

FM or knee OA. The results do show however, that pain responses to exercise are not uniform across different chronic pain states.

The strength of the associations between physical activity and fitness with pain in people with FM or knee OA were likely influenced by physical (e.g. sensations of exercise-related pain, fatigue and discomfort) and psychological factors (e.g. pain self- efficacy, pain catastrophizing and movement-related fear). However, the relative

167 contribution of each of these to the overall effect is not known. Large cross-sectional studies of people with FM show that both physical and psychological factors predict pain and disease severity better than either variable alone485-487, so both are important and should be considered when prescribing exercise to people with chronic pain.

However, more randomised controlled trials are needed to determine whether it is the physiological, psychological and/or behavioural adaptations to chronic exercise that mediate these associations and effects. A greater understanding of these factors would show that chronic exercise is indeed causal in reducing pain and would allow for more effective exercise interventions to be developed for people with chronic pain.

7.6. Conclusion

This chapter showed that EIH is disrupted in people with FM and knee OA. It is possible that this altered short-term response to acute exercise contributes to the small and widely varied associations between physical activity and pain in these same patient groups. In contrast, the clear associations between fitness and pain in people with FM or knee OA support the well demonstrated benefit of chronic exercise on reducing pain in these two chronic pain states. It will be informative to understand if and how the disrupted EIH in FM or knee OA improves with long-term exercise and to what extent such an adaptation contributes to the beneficial effect of chronic exercise.

168 Chapter 8:

Discussion

8.1. Summary of findings

The main aim of this thesis was to improve understanding of the mechanisms of exercise-induced hypoalgesia (EIH) in healthy adults. Through the novel application of evoked potentials, blood flow occlusion and education to investigate EIH, the studies in this thesis revealed two new mechanisms of this phenomenon in humans. First, a reduction in the sensitivity of the peripheral nervous system was implicated and the nociceptor emerged as a possible site of adaptation underlying this effect. This possibility was identified from the absence of reductions in somatosensory evoked potentials with exercise (Chapter 3) yet a small change in laser evoked potentials

(reduced; Chapters 3 and 4). The role of the peripheral nociceptor was verified by the attenuation of EIH that occurred when blood flow to a non-exercised limb was blocked during exercise (Chapter 5).

Second, the studies in this thesis highlighted that alterations in the cognitive appraisal of a noxious stimulus contribute to EIH in healthy adults. The most compelling evidence for this came from Chapter 6 where it was found that preceding exercise with education about EIH led to greater increases in pressure pain thresholds after exercise. The results of Chapters 3 and 4 provided some indirect evidence for a cognitive contribution to EIH as well, because exercise reduced ratings of pain unpleasantness. In one instance, this occurred independent of a reduction in ratings of pain intensity (electrical stimuli, Chapter 3), demonstrating that exercise can reduce the appraisal of a noxious stimulus even when that stimulus feels just as strong.

169 In combination, the results of the experiments in this thesis show that EIH in healthy adults is mediated, at least in part, by changes in the peripheral nervous system and in the cognitive appraisal of a noxious stimulus. These findings are not new hypotheses of how acute exercise reduces pain per se, but their direct involvement in

EIH in humans is demonstrated here for the first time. The implications of these results are discussed hereafter, along with possible avenues for future research.

8.2. Comparability of EIH to previous studies of this phenomena

As detailed in the literature review, acute exercise has varying effects on reducing pain depending on the type and intensity of exercise performed as well as the methods used to assess pain. In general, exercise has a large effect on increasing PPT, little to no effect on HPT, and a moderate effect on reducing ratings of heat pain. These results are mostly consistent with the results of this thesis where exercise consistently and markedly increased PPT, had little effect on HPT, and had varying effects on ratings of heat pain. Sample size calculations for each study were made on the basis of exercise having a large effect on PPT and indeed this was the case. The predicted effect sizes of exercise on PPT that were used in the sample size calculations for each study did differ, appropriately, between chapters in this thesis. This occurred because the studies used different types (i.e. isometric and or aerobic), durations (5 to 20 minutes) and intensities (moderate to very hard) of exercise. Furthermore, PPT was assessed over exercised and/or non-exercised muscles, and the various studies used different interventions (i.e. exercise only, exercise with or without blood flow occlusion, exercise with or without prior pain education). The different estimates of effect for the sample size calculation for each study reflect these varying experimental designs.

170 8.3. Paradoxical effects of acute and chronic exercise on pain in healthy adults and people with chronic pain

The results of the systematic reviews and meta-analyses in the preceding chapter showed that EIH is disrupted in people with fibromyalgia (FM) and knee osteoarthritis

(OA). In contrast, associations between pain and daily physical activity or fitness were typically greater and more consistent in people with FM or knee OA compared to healthy adults. Hence, the long-term benefits of regular physical activity support a negative association between pain and physical activity (more activity, less pain), but the short-term response to activity may often drive a positive association between pain and physical activity (more activity, more pain).

It was clear from the review of literature in Chapter 2 that the mechanisms underlying these superficially discrepant effects of acute exercise and daily physical activity levels on pain in people with FM or knee OA are incompletely understood.

Accordingly, it is difficult to say why acute exercise and daily levels of physical activity can have such contrasting effects on pain in healthy adults compared to people with FM or knee OA. A greater understanding of these mechanisms is necessary to optimise exercise prescription for people with chronic pain. Prior to this however, a greater understanding of the mechanisms of EIH in healthy adults is needed. Such was the primary aim of this thesis.

8.4. Acute exercise reduces pain in healthy adults through a peripheral mechanism

Studies in rodents show that substances released by the body during exercise

(e.g. opioids, cannabinoids, noradrenaline and nitrite) reduce pain through actions at peripheral and central sites245,246,248,258,259, with some evidence that the peripheral actions of these substances are more important to EIH than their central effects269. The

171 role of endorphins and cannabinoids as contributors to EIH in humans has also been investigated, but with mixed results192,197,249-251,267. Moreover, these human studies do not allow description of where in the nervous system changes occur with exercise, at least not with the same level of discrimination as studies in rodents. Hence, it is unclear to what extent peripheral changes mediate EIH in humans. Studies showing greater EIH in exercised compared to non-exercised limbs200,211 imply an important contribution of peripheral changes to EIH, but this had not been directly explored.

The novel application of the occlusion of blood flow to a non-exercised limb during exercise (Chapter 5) allowed investigation into the role of peripheral changes as contributors to EIH in healthy adults. The results showed that blocking blood flow to a limb during exercise significantly diminished EIH in that limb. These findings demonstrate a peripheral mechanism contributes to EIH in healthy adults. On this basis, it was suggested that the increase in pain thresholds might be due to the actions of substances that are released into the blood during exercise (e.g. catecholamines, opioids and/or cannabinoids) and act at the periphery to influence nociceptor sensitivity.

Nociceptors, traditionally considered conduits to relay nociceptive input from the peripheral to the central nervous system, are now better understood to be highly complex sensory neurons that can influence their own microenvironment268. They do this through paracrine and autocrine actions related to their expression of, and response to, a variety of receptors, ligands and neurotransmitters268.

Many of the substances that influence nociceptor sensitivity are increased in the blood during exercise (e.g. opioids, cannabinoids and noradrenaline)241,242,339,371 and remain elevated in a manner consistent with the persistence of EIH following exercise251. Therefore, it seems reasonable that these exercise-induced changes could reduce nociceptor sensitivity, and that this could explain the peripheral mechanism of

172 EIH identified in this thesis. This hypothesis also presents an explanation as to why EIH is often greater in exercised compared to unexercised exercised limbs. That is, the distribution of blood flow during exercise is greater to working muscles compared to unexercised sites377,381, so the working muscles would receive more of the analgesic substances released during exercise and hence experience greater EIH. Limitations of the occlusion experiment were that neither nociceptor sensitivity nor the substances released during exercise that might be contributing to the peripheral effect were examined.

The experiments in Chapters 3 and 4 using evoked potentials inspired the use of occlusion to examine the peripheral contribution to EIH. The novel measurements of somatosensory evoked potentials (SEPs, Chapter 3) and laser evoked potentials (LEPs,

Chapter 3 and 4) in conjunction with EIH yielded mixed results. Dissimilarities between

SEPs and LEPs apart from the involvement or not of peripheral nociceptors could have contributed to the differential effect of exercise on these potentials. For example, the ascending and central pathways that contribute to SEPs and LEPs are different, even when a noxious electrical stimulus is used306,307. Moreover, the habituation of SEPs and

LEPs that occurred with rest (Chapter 3) and persisted despite the use of light activity

(LEPs, Chapter 4) made it difficult to determine the true effect of exercise on the excitability of the thermal nociceptive pathways. Ultimately, habituation meant that the effect of exercise on LEPs was not significantly different from rest. Consequently, it could not be concluded that exercise reduced pain through a reduction in the excitability of the thermal nociceptive pathways, including the peripheral nociceptor.

It is possible that, because EIH is greater for mechanical stimuli190 (Chapter 4), a larger effect of exercise on reducing nociceptive pathway excitability might have been observed if a noxious mechanical stimulus was used to evoke pain. However, these

173 ‘pinprick-evoked potentials’ are still a relatively immature technique and are poorly understood with regard to the component most associated with pain327-329. The extent to which pin-prick evoked potentials habituate is not clear either, but if they habituate like

SEPs and LEPs, then they may also have limited utility for investigating EIH.

Notwithstanding these limitations, this thesis shows for the first time that a peripheral factor directly contributes to EIH in humans.

8.5. Acute exercise has greater effects on pressure pain compared to thermal pain

Using noxious pressure and heat stimuli that were similar with regard to their site and rate of application, as well as the dimension of pain assessed (i.e. pain threshold), the results of Chapters 3 and 4 showed that EIH is greater for pressure pain compared to thermal pain. This was an interesting finding, which may have important clinical applications for people with chronic musculoskeletal pain in whom sensitivity to mechanical stimuli is often exaggerated488,489 and in whom clinical pain is best mimicked experimentally by mechanical pain488. Therefore, the fact that exercise has larger effects on reducing mechanical pain implies that it should be effective for reducing clinical pain. This is certainly true for longer term exercise, with both experimentally-induced mechanical pain490,491 and clinical pain40 found to be lower after a period of exercise training.

Whether the same is true for acute exercise is less clear. Although studies in people with FM have found EIH for both pressure and thermal stimuli216,288, there is some evidence that submaximal intensity aerobic exercise reduces pressure pain more than thermal pain in people with FM217. A comparable study has not been done in people with knee OA; in fact, no studies of people with knee OA have used thermal stimuli to quantify EIH214,219,220,289. If the greater EIH for mechanical compared to

174 thermal pain demonstrated here in healthy adults also occurs in people with chronic pain, this may have important implications for exercise prescription and could provide interesting avenues for future research as well. The limited sensitivity of thermal pain to

EIH that has been noted in this thesis highlights the importance of the stimulus modality used to investigate EIH.

It was not within the scope of the experiments in Chapters 3 or 4 to investigate the mechanisms underlying the greater EIH for mechanical compared with thermal noxious stimuli, but there may be a few reasons why this occurred. First, exercise may have greater effects on mechanosensitive nociceptors. This cannot be said with certainty however because most nociceptors respond to both mechanical and thermal stimuli26 and the effect of exercise on different nociceptor subtypes has seldom been explored.

Some receptors expressed by nociceptors do differ in their sensitivity to mechanical and thermal stimuli492,493, so it may be that exercise primarily affects those receptors that are more sensitive to mechanical stimuli and this in turn preferentially influences nociceptor sensitivity. For example, mechanical pain and thermal pain are, respectively, controlled by delta and mu opioid receptors493 whereas cannabinoid receptors, although capable of modulating input from both mechanical and thermal stimuli, have greater influence over mechanical stimuli492. Therefore, it might be that the endogenous opioids and cannabinoids released during exercise act on these specific receptors at the nociceptor to have greater effects on mechanical pain, but again this is speculative. Another possibility is that, rather than exercise differentially affecting mechanical versus thermosensitive nociceptors or their specialised receptors, exercise influences nociceptors located within muscles more than those located in the skin. This could also contribute to greater EIH for mechanical compared to thermal pain, but again clear

175 evidence for this is lacking. Possible ways this could be investigated will be described in more detail below.

8.6. Cognitive factors contribute to exercise-induced hypoalgesia

Psychosocial and cognitive factors are heavily implicated in the development and persistence of chronic pain76. These same cognitive factors influence responses to experimental noxious stimuli in healthy adults as well494, but their relation to EIH has seldom been examined. Accordingly, it was not known whether cognitive factors are directly involved in EIH, or, perhaps more importantly, whether they could be manipulated to influence pain responses after exercise. The results of Chapter 6 showed that they can, with this novel finding offering another avenue to investigate, and indeed manipulate, EIH.

It remains to be determined however, whether preceding exercise with EIH education can also influence EIH in people who have chronic pain and in whom negative expectations about pain and exercise are more prevalent and therefore likely harder to change495. It may be that, because of their more entrenched negative beliefs about pain and exercise, more intensive EIH education is required in people with chronic pain to produce the same effect. Some combination of pain neuroscience education and EIH education might also be required. Nonetheless, if the effect can be replicated in people with chronic pain it could have important applications for exercise prescription in clinical practice. For example, preceding exercise with EIH education may be a useful means of normalising/improving pain responses to acute exercise in people with FM or knee OA. This may subsequently make these individuals less fearful of exercise and, as a result, more likely to participate in it. This is important given the

176 benefits of chronic exercise on pain, physical function and quality of life in people with chronic musculoskeletal pain40.

As an aside, it should be noted that the cognitive and peripheral mechanisms of

EIH identified in this thesis may not be entirely independent. That is, education could cause an increase in the release of substances into the blood that could act to reduce pain through a peripheral mechanism. This has not been well investigated, but studies by van

Oosterwijck and colleagues have shown that pain neuroscience education can increase pain thresholds and have positive effects on descending pain modulation496,497.

Mechanistically, this might be explained by the overlap of brain areas involved in cognition, emotion and descending pain inhibition, as well as the central release of serotonin or noradrenaline that act spinally or peripherally to modulate pain. However, this is speculative and requires further study.

8.7. Future directions

This thesis advances current understanding of the mechanisms of EIH in healthy adults. However, a few important questions worthy of further investigation have also been raised. First and most important, it remains to be determined whether the same mechanisms contribute to EIH in people with chronic pain. The systematic reviews and meta-analyses in Chapter 7 showed that EIH is disrupted in people with FM and knee

OA. Therefore, it can be assumed that the mechanisms underlying EIH in people with chronic pain compared to healthy adults are at least disrupted, if not distinct. For example, the underlying disease pathology in FM or knee OA might diminish EIH by reducing the acute adaptations that occur in healthy adults, such as the modulation of peripheral nociceptor sensitivity. Alternatively, in people with chronic pain EIH might arise from reductions in the responsiveness of a sensitised nervous system or from

177 modulation of an inflammatory environment, neither of which would be expected in healthy adults. This is speculative given that all studies in this thesis were performed on healthy young adults but nonetheless, such possibilities require further study.

Second, the specific mechanisms underlying the peripheral contribution to EIH warrant further study. The simplest way to do this might be to compare the effect of exercise on pressure pain over muscle versus bone, which would provide some insight into how exercise affects nociceptors located in muscle versus skin. Another possibility would be to use drugs whose peripheral actions can be discriminated from their central effects. Adopting this approach revealed an important role of peripheral alpha2- adrenergic receptors to EIH in rodents269, so a drug targeting these receptors might be an interesting place to start in humans. Otherwise, drug studies of EIH in humans that have mostly targeted opioids, cannabinoids and stress hormones192,197,250,264,265 could be extended by using agonists and antagonists that target peripheral receptors, or by combining drugs to see whether this has additive effects on EIH.

Third, the mechanisms underlying the greater sensitivity of mechanical compared with thermal noxious stimuli to EIH require elucidation. The methods used to investigate differences in EIH for mechanical and thermal stimuli in Chapter 4 could be improved by assessing sensitivity to both mechanical and thermal stimuli over the dominant exercised muscle, by obtaining suprathreshold ratings for noxious pressure, and/or by interspersing the assessments of pressure and heat pain after exercise to eliminate the possibility that the persistence of EIH after exercise might have influenced the results. A similar line of investigation could involve interspersing pin-prick evoked potentials and LEPs to study how exercise affects mechanosensitive and thermal nociceptive pathways, respectively. However, mechanical stimuli invariably excite fast- conducting sensory nerves as well and these can dominate the encephalogram498, so

178 efforts must be made to reduce the contribution of these non-nociceptive afferents to the pin-prick evoked potential. This could be achieved using a pressure nerve block, as activity from non-nociceptive afferents is reduced many minutes before A-delta and C- fibres are affected396,499. Thus, measurement of pin-prick evoked potentials during this window would allow better determination of the effect of exercise on mechanosensitive nociceptive pathway. Of course, there would be limitations to this study, the most obvious being that the time it takes for the pressure block to take effect (~15-20 min) is typically longer than the persistence of EIH after exercise (~10-15 min). To avoid this timing issue, the pressure nerve block could be applied to the lower limb while exercise is performed with the upper limb (or vice versa), but this would mean that any effect of exercise on the evoked potential would likely be small because it is not being measured in an exercised limb.

A related avenue of investigation would be to determine whether the differing effects of exercise on mechanically and thermally-sensitive nociceptive pathways instead arises from greater effects of exercise on deep compared with superficial tissues.

There are several ways this could be investigated. For example, the influence of tissue blood flow on thermal pain could be explored by examining whether exercise in hot and cold environments – which would increase and decrease skin blood flow, respectively – has any influence on EIH for thermal pain. Potential differences in skin temperature could be a confounding factor in such an experiment, but it would also be possible to measure pressure pain sensitivity in the superficial tissue layers by application of pressure to skin over bone in contrast to muscle or a pinch force to the skin. While not a direct comparison to the occlusion study in Chapter 5, where blood flow to tissues was completely blocked, the results of this study would provide insight as to whether tissue blood flow is responsible for different effects of EIH on mechanical and thermal pain.

179 Finally, because the results of Chapter 6 showed for the first time that education could augment EIH, this finding requires replication. The mechanisms underlying this cognitive contribution to EIH should be explored as well. I am currently investigating whether pain responses after exercise can be influenced by EIH education in people with FM or knee OA (ANZCTRN12616001141437). The design of this study is identical to that used in Chapter 6 for healthy adults, but the scripts and supporting illustrations are slightly different (Appendices B and E-M). If EIH education can influence pain responses after exercise in people with chronic pain, this finding would have important clinical applications for exercise prescription in the clinical setting.

While it is beyond the scope of this work to determine whether the same mechanisms identified here in healthy individuals are also relevant to people with chronic pain, these proposed avenues of future research could provide valuable insight into the mechanisms through which acute exercise affects pain in people with chronic pain. This new understanding may lead to the development of better therapies to enhance the pain relieving effects of acute and chronic exercise in people with chronic pain. As an example, this might include a combined exercise and drug intervention that is preceded by education about EIH. These acute studies could then be extended to investigate the mechanisms of the pain-relieving effect of chronic exercise in people with chronic pain.

180 8.8. Conclusion

This thesis establishes for the first time a clear influence of peripheral and cognitive factors on EIH in healthy adults. It must now be determined whether these same mechanisms contribute to EIH in people with chronic pain as well. Once the mechanisms of EIH are more clearly established, the changes that mediate reductions in in pain with chronic exercise can be further explored. The results of acute and chronic exercise studies could further substantiate the efficacy of exercise for the management of chronic pain and, hopefully, contribute to more effective treatments being developed for people with chronic pain. Exercise is medicine for people with chronic pain, but we still do not know exactly why. This thesis has taken some important steps toward enhancing understanding of the mechanisms of EIH in healthy adults.

181 References

1. Fayaz A, Croft P, Langford RM, Donaldson LJ, Jones GT. Prevalence of chronic

pain in the UK: a systematic review and meta-analysis of population studies.

BMJ Open. 2016;6(6):e010364.

2. Mansfield KE, Sim J, Jordan JL, Jordan KP. A systematic review and meta-

analysis of the prevalence of chronic widespread pain in the general population.

Pain. 2016;157(1):55-64.

3. Collaborators GBoDS. Global, regional, and national incidence, prevalence, and

years lived with disability for 301 acute and chronic diseases and injuries in 188

countries, 1990-2013: a systematic analysis for the Global Burden of Disease

Study 2013. Lancet. 2015;386(9995):743-800.

4. Wu M, Brazier JE, Kearns B, Relton C, Smith C, Cooper CL. Examining the

impact of 11 long-standing health conditions on health-related quality of life

using the EQ-5D in a general population sample. Eur J Health Econ.

2015;16(2):141-151.

5. Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain.

2012;13(8):715-724.

6. Mills S, Torrance N, Smith BH. Identification and management of chronic pain

in primary care: a review. Curr Psychiatry Rep. 2016;18(2):22.

7. Kamper SJ, Apeldoorn AT, Chiarotto A, et al. Multidisciplinary biopsychosocial

rehabilitation for chronic . Cochrane Database Syst Rev.

2014(9):CD000963.

8. Kroon FP, van der Burg LR, Buchbinder R, Osborne RH, Johnston RV, Pitt V.

Self-management education programmes for osteoarthritis. Cochrane Database

Syst Rev. 2014(1):CD008963.

182 9. Straube S, Harden M, Schroder H, et al. Back schools for the treatment of

chronic low back pain: possibility of benefit but no convincing evidence after 47

years of research - systematic review and meta-analysis. Pain.

2016;157(10):2160-2172.

10. Knoerl R, Lavoie Smith EM, Weisberg J. Chronic pain and cognitive behavioral

therapy: An integrative review. West J Nurs Res. 2016;38(5):596-628.

11. Wu PI, Meleger A, Witkower A, Mondale T, Borg-Stein J. Nonpharmacologic

options for treating acute and chronic pain. PM R. 2015;7(11 Suppl):S278-294.

12. Chopko B, Liu JC, Khan MK. Anatomic surgical management of chronic low

back pain. Neuromodulation. 2014;17 Suppl 2:46-51.

13. Thorlund JB, Juhl CB, Roos EM, Lohmander LS. Arthroscopic surgery for

degenerative knee: systematic review and meta-analysis of benefits and harms.

BMJ. 2015;350:h2747.

14. Cheatle MD. Prescription opioid misuse, abuse, morbidity, and mortality:

Balancing effective and safety. Pain Med. 2015;16 Suppl

1:S3-8.

15. Krashin D, Murinova N, Sullivan M. Challenges to treatment of chronic pain

and addiction during the "opioid crisis". Curr Pain Rep.

2016;20(12):65.

16. Bidonde J, Busch AJ, Bath B, Milosavljevic S. Exercise for adults with

fibromyalgia: An umbrella systematic review with synthesis of best evidence.

Curr Rheumatol Rev. 2014;10(1):45-79.

17. Fransen M, McConnell S, Harmer AR, Van der Esch M, Simic M, Bennell KL.

Exercise for osteoarthritis of the knee. Cochrane Database Syst Rev.

2015;1:CD004376.

183 18. Hayden JA, van Tulder MW, Malmivaara A, Koes BW. Exercise therapy for

treatment of non-specific low back pain. Cochrane Database Syst Rev.

2005(3):CD000335.

19. Henriksen M, Hansen JB, Klokker L, Bliddal H, Christensen R. Comparable

effects of exercise and analgesics for pain secondary to knee osteoarthritis: a

meta-analysis of trials included in Cochrane systematic reviews. J Comp Eff Res.

2016;5(4):417-431.

20. Perrot S, Russell IJ. More ubiquitous effects from non-pharmacologic than from

pharmacologic treatments for fibromyalgia syndrome: A meta-analysis

examining six core symptoms. Eur J Pain. 2014;18(8):1067-1080.

21. Kredlow MA, Capozzoli MC, Hearon BA, Calkins AW, Otto MW. The effects

of physical activity on sleep: a meta-analytic review. J Behav Med.

2015;38(3):427-449.

22. Powers MB, Asmundson GJ, Smits JA. Exercise for mood and anxiety

disorders: The state-of-the science. Cogn Behav Ther. 2015;44(4):237-239.

23. Loeser JD, Treede R. The Kyoto protocol of IASP basic pain terminology. Pain.

2008;137(3):473-477.

24. Taxonomy ITFo. Part III: Pain terms, A Current List with Definitions and Notes

on Usage. In: Merskey H, Bogduk N, eds. Classification of Chronic Pain.

Seattle: IASP Press; 2012:209-214.

25. Chapman CR, Vierck CJ. The transition of acute postoperative pain to chronic

pain: An integrative overview of research on mechanisms [epub ahead of print].

J Pain. 2016:doi: 10.1016/j.jpain.2016.1011.1004.

26. Dubin AE, Patapoutian A. Nociceptors: the sensors of the pain pathway. J Clin

Invest. 2010;120(11):3760-3772.

184 27. De Felice M, Ossipov MH. Cortical and subcortical modulation of pain. Pain

Manag. 2016;6(2):111-120.

28. Arendt-Nielsen L. Central sensitization in humans: assessment and

pharmacology. Handb Exp Pharmacol. 2015;227:79-102.

29. Melzack R, Wall PD. Pain mechanisms: A new theory. Science.

1965;150(3699):971-979.

30. Treede RD. Gain control mechanisms in the nociceptive system. Pain.

2016;157(6):1199-1204.

31. Bingham B, Ajit SK, Blake DR, Samad TA. The molecular basis of pain and its

clinical implications in rheumatology. Nat Clin Pract Rheumatol. 2009;5(1):28-

37.

32. Lee MC, Tracey I. Imaging pain: a potent means for investigating pain

mechanisms in patients. Br J Anaesth. 2013;111(1):64-72.

33. Ohara PT, Vit JP, Jasmin L. Cortical modulation of pain. Cell Mol Life Sci.

2005;62(1):44-52.

34. Bushnell MC, Ceko M, Low LA. Cognitive and emotional control of pain and

its disruption in chronic pain. Nat Rev Neurosci. 2013;14(7):502-511.

35. Vaegter HB, Graven-Nielsen T. Pain modulatory phenotypes differentiate

subgroups with different clinical and experimental pain sensitivity. Pain.

2016;157(7):1480-1488.

36. Koes BW, van Tulder M, Lin CW, Macedo LG, McAuley J, Maher C. An

updated overview of clinical guidelines for the management of non-specific low

back pain in primary care. Eur Spine J. 2010;19(12):2075-2094.

185 37. Guzman J, Esmail R, Karjalainen K, Malmivaara A, Irvin E, Bombardier C.

Multidisciplinary bio-psycho-social rehabilitation for chronic low back pain.

Cochrane Database Syst Rev. 2002(1):CD000963.

38. Gatchel RJ, Peng YB, Peters ML, Fuchs PN, Turk DC. The biopsychosocial

approach to chronic pain: scientific advances and future directions. Psychol Bull.

2007;133(4):581-624.

39. Busch AJ, Barber KA, Overend TJ, Peloso PM, Schacter CL. Exercise for

treating fibromyalgia syndrome. Cochrane Database Syst Rev.

2007(4):CD003786.

40. Geneen LJ, Moore RA, Clarke C, Martin D, Colvin LA, Smith BH. Physical

activity and exercise for chronic pain in adults: an overview of Cochrane

Reviews. Cochrane Database Syst Rev. 2017;1:CD011279.

41. Rapo-Pylkko S, Haanpaa M, Liira H. Subjective easiness of pain assessment

measures in older people. Arch Gerontol Geriatr. 2016;65:25-28.

42. Hjermstad MJ, Fayers PM, Haugen DF, et al. Studies comparing numerical

rating scales, verbal rating scales, and visual analogue scales for assessment of

pain intensity in adults: a systematic literature review. J Pain Symptom Manage.

2011;41(6):1073-1093.

43. Letzen JE, Boissoneault J, Sevel LS, Robinson ME. Test-retest reliability of

pain-related functional brain connectivity compared to pain self-report. Pain.

2015;157(3):546-551.

44. Letzen JE, Sevel LS, Gay CW, et al. Test-retest reliability of pain-related brain

activity in healthy controls undergoing experimental thermal pain. J Pain.

2014;15(10):1008-1014.

186 45. Robinson ME, O'Shea AM, Craggs J, Price DD, Letzen JE, Staud R.

Comparison of machine classification algorithms for fibromyalgia: Neuroimages

versus self-report. J Pain. 2015;16(5):472-477.

46. Cruz-Almeida Y, Fillingim RB. Can quantitative sensory testing move us closer

to mechanism-based pain management? Pain Med. 2014;15(1):61-72.

47. Mucke M, Cuhls H, Radbruch L, et al. Quantitative sensory testing (QST).

English version. Schmerz. 2016;28(635-48).

48. Uddin Z, MacDermid JC. Quantitative sensory testing in chronic

musculoskeletal pain. Pain Med. 2016;17(9):1694-1703.

49. Yarnitsky D, Granot M, Granovsky Y. Pain modulation profile and pain therapy:

Between pro- and antinociception. Pain. 2014;155(4):663-665.

50. Nie H, Graven-Nielsen T, Arendt-Nielsen L. Spatial and temporal summation of

pain evoked by mechanical pressure stimulation. Eur J Pain. 2009;13(6):592-

599.

51. Herrero JF, Laird JM, Lopez-Garcia JA. Wind-up of spinal cord neurones and

pain sensation: much ado about something? Prog Neurobiol. 2000;61(2):169-

203.

52. Yarnitsky D, Arendt-Nielsen L, Bouhassira D, et al. Recommendations on

terminology and practice of psychophysical DNIC testing. Eur J Pain.

2010;14(4):339.

53. Baumgartner U, Greffrath W, Treede RD. Contact heat and cold, mechanical,

electrical and chemical stimuli to elicit small fiber-evoked potentials: merits and

limitations for basic science and clinical use. Neurophysiol Clin.

2012;42(5):267-280.

187 54. Plaghki L, Mouraux A. How do we selectively activate skin nociceptors with a

high power infrared laser? Physiology and biophysics of laser stimulation.

Neurophysiol Clin. 2003;33(6):269-277.

55. Hu L, Cai MM, Xiao P, Luo F, Iannetti GD. Human brain responses to

concomitant stimulation of a-delta and C nociceptors. J Neurosci.

2014;34(34):11439-11451.

56. Truini A, Galeotti F, Romaniello A, Virtuoso M, Iannetti GD, Cruccu G. Laser-

evoked potentials: normative values. Clin Neurophysiol. 2005;116(4):821-826.

57. Valeriani M, Pazzaglia C, Cruccu G, Truini A. Clinical usefulness of laser

evoked potentials. Neurophysiol Clin. 2012;42(5):345-353.

58. Lee MC, Mouraux A, Iannetti GD. Characterizing the cortical activity through

which pain emerges from nociception. J Neurosci. 2009;29(24):7909-7916.

59. Greffrath W, Baumgartner U, Treede RD. Peripheral and central components of

habituation of heat pain perception and evoked potentials in humans. Pain.

2007;132(3):301-311.

60. Carlino E, Torta DM, Piedimonte A, Frisaldi E, Vighetti S, Benedetti F. Role of

explicit verbal information in conditioned analgesia. Eur J Pain.

2015;19(4):546-553.

61. Pazzaglia C, Testani E, Giordano R, Padua L, Valeriani M. Expectation to feel

more pain disrupts the habituation of laser-pain rating and laser-evoked potential

amplitudes. Neuroscience. 2016;333:244-251.

62. Peyron R, Laurent B, Garcia-Larrea L. Functional imaging of brain responses to

pain. A review and meta-analysis. Neurophysiol Clin. 2000;30(5):263-288.

188 63. Jensen KB, Regenbogen C, Ohse MC, Frasnelli J, Freiherr J, Lundstrom JN.

Brain activations during pain: a neuroimaging meta-analysis of pain patients and

healthy controls. Pain. 2016;157(6):1279-1286.

64. Cagnie B, Coppieters I, Denecker S, Six J, Danneels L, Meeus M. Central

sensitization in fibromyalgia? A systematic review on structural and functional

brain MRI. Semin Arthritis Rheum. 2014;44(1):68-75.

65. Kregel J, Meeus M, Malfliet A, et al. Structural and functional brain

abnormalities in chronic low back pain: A systematic review. Semin Arthritis

Rheum. 2015;45(2):229-237.

66. Pan PL, Zhong JG, Shang HF, et al. Quantitative meta-analysis of grey matter

anomalies in neuropathic pain. Eur J Pain. 2015;19(9):1224-1231.

67. Shi H, Yuan C, Dai Z, Ma H, Sheng L. Gray matter abnormalities associated

with fibromyalgia: A meta-analysis of voxel-based morphometric studies. Semin

Arthritis Rheum. 2016;46(3):330-337.

68. Reches A, Nir RR, Shram MJ, et al. A novel electroencephalography-based tool

for objective assessment of network dynamics activated by nociceptive stimuli.

Eur J Pain. 2016;20(2):250-262.

69. Stancak A, Cook S, Wright H, Fallon N. Mapping multidimensional pain

experience onto electrophysiological responses to noxious laser heat stimuli.

Neuroimage. 2015;125:244-255.

70. Coppieters I, Meeus M, Kregel J, et al. Relations between brain alterations and

clinical pain measures in chronic musculoskeletal pain: A systematic review. J

Pain. 2016;17(9):949-962.

189 71. Jutzeler CR, Curt A, Kramer JL. Relationship between chronic pain and brain

reorganization after deafferentation: A systematic review of functional MRI

findings. Neuroimage Clin. 2015;9:599-606.

72. Bellato E, Marini E, Castoldi F, et al. Fibromyalgia syndrome: etiology,

pathogenesis, diagnosis, and treatment. Pain Res Treat. 2012;2012:426130.

73. Queiroz LP. Worldwide epidemiology of fibromyalgia. Curr Pain Headache

Rep. 2013;17(8):356.

74. Wolfe F, Clauw DJ, Fitzcharles MA, et al. 2016 Revisions to the 2010/2011

fibromyalgia diagnostic criteria. Semin Arthritis Rheum. 2016;46(3):319-329.

75. Sluka KA, Clauw DJ. Neurobiology of fibromyalgia and chronic widespread

pain. Neuroscience. 2016;338:114-129.

76. Edwards RR, Dworkin RH, Sullivan MD, Turk DC, Wasan AD. The role of

psychosocial processes in the development and maintenance of chronic pain. J

Pain. 2016;17(9 Suppl):T70-T92.

77. Vincent A, Whipple MO, McAllister SJ, Aleman KM, St Sauver JL. A cross-

sectional assessment of the prevalence of multiple chronic conditions and

medication use in a sample of community-dwelling adults with fibromyalgia in

Olmsted County, Minnesota. BMJ Open. 2015;5(3):e006681.

78. Ablin JN, Buskila D. Update on the genetics of the fibromyalgia syndrome. Best

Pract Res Clin Rheumatol. 2015;29(1):20-28.

79. Caro XJ, Winter EF. Evidence of abnormal epidermal nerve fiber density in

fibromyalgia: Clinical and immunologic implications. Arthritis Rheumatol.

2014;66(7):1945-1954.

80. Serra J, Collado A, Sola R, et al. Hyperexcitable C nociceptors in fibromyalgia.

Ann Neurol. 2014;75(2):196-208.

190 81. Doppler K, Rittner HL, Deckart M, Sommer C. Reduced dermal nerve fiber

diameter in skin biopsies of patients with fibromyalgia. Pain.

2015;156(11):2319-2325.

82. Dehghan M, Schmidt-Wilcke T, Pfleiderer B, et al. Coordinate-based (ALE)

meta-analysis of brain activation in patients with fibromyalgia. Hum Brain

Mapp. 2016;37(5):1749-1758.

83. Lewis GN, Rice DA, McNair PJ. Conditioned pain modulation in populations

with chronic pain: a systematic review and meta-analysis. J Pain.

2012;13(10):936-944.

84. Pyke T, Osmotherly PG, Baines S. Measuring glutamate levels in the brains of

fibromyalgia patients and a potential role for glutamate in the pathophysiology

of fibromyalgia symptoms: A systematic review. [epub ahead of print]. Clin J

Pain. 2016:doi: 10.1097/ajp.0000000000000474.

85. Koenig J, Falvay D, Clamor A, et al. Pneumogastric (vagus) nerve activity

indexed by heart rate variability in chronic pain patients compared to healthy

controls: A systematic review and meta-analysis. Pain Physician.

2016;19(1):E55-E78.

86. Tracy LM, Ioannou L, Baker KS, Gibson SJ, Georgiou-Karistianis N,

Giummarra MJ. Meta-analytic evidence for decreased heart rate variability in

chronic pain implicating parasympathetic nervous system dysregulation. Pain.

2015;157(1):7-29.

87. Uceyler N, Hauser W, Sommer C. Systematic review with meta-analysis:

cytokines in fibromyalgia syndrome. BMC Musculoskelet Disord. 2011;12:245.

191 88. Crofford LJ, Demitrack MA. Evidence that abnormalities of central

neurohormonal systems are key to understanding fibromyalgia and chronic

fatigue syndrome. Rheum Dis Clin North Am. 1996;22(2):267-284.

89. Diaz-Piedra C, Di Stasi LL, Baldwin CM, Buela-Casal G, Catena A. Sleep

disturbances of adult women from fibromyalgia: A systematic review

of observational studies. Sleep Med Rev. 2014;21:86-99.

90. Markkula RA, Kalso EA, Kaprio JA. Predictors of fibromyalgia: a population-

based twin cohort study. BMC Musculoskelet Disord. 2016;17(1):29.

91. Sivertsen B, Lallukka T, Salo P, et al. Insomnia as a risk factor for ill health:

results from the large population-based prospective HUNT Study in Norway. J

Sleep Res. 2014;23(2):124-132.

92. Alciati A, Sgiarovello P, Atzeni F, Sarzi-Puttini P. Psychiatric problems in

fibromyalgia: clinical and neurobiological links between mood disorders and

fibromyalgia. Reumatismo. 2012;64(4):268-274.

93. Macfarlane GJ, Kronisch C, Dean LE, et al. EULAR revised recommendations

for the management of fibromyalgia. Ann Rheum Dis. 2017;76(2):318-328.

94. Zhang W, Doherty M, Peat G, et al. EULAR evidence-based recommendations

for the diagnosis of knee osteoarthritis. Ann Rheum Dis. 2010;69(3):483-489.

95. March LM, Bagga H. Epidemiology of osteoarthritis in Australia. Med J Aust.

2004;180(5 Suppl):S6-10.

96. Hootman JM, Helmick CG, Barbour KE, Theis KA, Boring MA. Updated

projected prevalence of self-reported doctor-diagnosed arthritis and arthritis-

attributable activity limitation among US adults, 2015-2040. Arthritis

Rheumatol. 2016;68(7):1582-1587.

192 97. Dieppe PA, Lohmander LS. Pathogenesis and management of pain in

osteoarthritis. Lancet. 2005;365(9463):965-973.

98. Dell'Isola A, Allan R, Smith SL, Marreiros SS, Steultjens M. Identification of

clinical phenotypes in knee osteoarthritis: a systematic review of the literature.

BMC Musculoskelet Disord. 2016;17(1):425.

99. Andriacchi TP, Favre J, Erhart-Hledik JC, Chu CR. A systems view of risk

factors for knee osteoarthritis reveals insights into the pathogenesis of the

disease. Ann Biomed Eng. 2015;43(2):376-387.

100. Valdes AM, Spector TD. Genetic epidemiology of hip and knee osteoarthritis.

Nat Rev Rheumatol. 2011;7(1):23-32.

101. Warner SC, Valdes AM. Genetic association studies in osteoarthritis: is it

fairytale? Curr Opin Rheumatol. 2017;29(1):103-109.

102. Blagojevic M, Jinks C, Jeffery A, Jordan KP. Risk factors for onset of

osteoarthritis of the knee in older adults: a systematic review and meta-analysis.

Osteoarthritis Cartilage. 2010;18(1):24-33.

103. Srikanth VK, Fryer JL, Zhai G, Winzenberg TM, Hosmer D, Jones G. A meta-

analysis of sex differences prevalence, incidence and severity of osteoarthritis.

Osteoarthritis Cartilage. 2005;13(9):769-781.

104. Zheng H, Chen C. Body mass index and risk of knee osteoarthritis: systematic

review and meta-analysis of prospective studies. BMJ Open.

2015;5(12):e007568.

105. Zhou ZY, Liu YK, Chen HL, Liu F. Body mass index and knee osteoarthritis

risk: A dose-response meta-analysis. Obesity (Silver Spring). 2014;22(10):2180-

2185.

193 106. Kapoor M, Martel-Pelletier J, Lajeunesse D, Pelletier JP, Fahmi H. Role of

proinflammatory cytokines in the pathophysiology of osteoarthritis. Nat Rev

Rheumatol. 2011;7(1):33-42.

107. Lier R, Mork PJ, Holtermann A, Nilsen TI. Familial risk of chronic

musculoskeletal pain and the importance of physical activity and body mass

index: Prospective Data from the HUNT Study, Norway. PLoS One.

2016;11(4):e0153828.

108. Landmark T, Romundstad PR, Borchgrevink PC, Kaasa S, Dale O. Longitudinal

associations between exercise and pain in the general population--the HUNT

pain study. PLoS One. 2013;8(6):e65279.

109. Driban JB, Hootman JM, Sitler MR, Harris K, Cattano NM. Is participation in

certain sports associated with knee osteoarthritis? A systematic review [epub

ahead of print]. J Athl Train. 2015:doi: 10.4085/1062-6050-4050.4082.4008.

110. Oiestad BE, Juhl CB, Eitzen I, Thorlund JB. Knee extensor is

a risk factor for development of knee osteoarthritis: A systematic review and

meta-analysis. Osteoarthritis Cartilage. 2015;23(2):171-177.

111. Bastick AN, Belo JN, Runhaar J, Bierma-Zeinstra SM. What are the prognostic

factors for radiographic progression of knee osteoarthritis? A meta-analysis.

Clin Orthop Relat Res. 2015;473(9):2969-2989.

112. Brouwer GM, van Tol AW, Bergink AP, et al. Association between valgus and

varus alignment and the development and progression of radiographic

osteoarthritis of the knee. Arthritis Rheum. 2007;56(4):1204-1211.

113. Tanamas S, Hanna FS, Cicuttini FM, Wluka AE, Berry P, Urquhart DM. Does

knee malalignment increase the risk of development and progression of knee

osteoarthritis? A systematic review. Arthritis Rheum. 2009;61(4):459-467.

194 114. Alshuft HM, Condon LA, Dineen RA, Auer DP. Cerebral cortical thickness in

chronic pain due to knee osteoarthritis: The effect of pain duration and pain

sensitization. PLoS One. 2016;11(9):e0161687.

115. Driscoll C, Chanalaris A, Knights C, et al. Nociceptive sensitizers are regulated

in damaged joint tissues, including the articular cartilage, when osteoarthritic

mice display pain behaviour. Arthritis Rheumatol. 2016;68(4):857-867.

116. Lluch E, Torres R, Nijs J, Van Oosterwijck J. Evidence for central sensitization

in patients with osteoarthritis pain: A systematic literature review. Eur J Pain.

2014;18(10):1367-1375.

117. Sofat N, Ejindu V, Kiely P. What makes osteoarthritis painful? The evidence for

local and central pain processing. Rheumatology (Oxford). 2011;50(12):2157-

2165.

118. Nelson AE, Allen KD, Golightly YM, Goode AP, Jordan JM. A systematic

review of recommendations and guidelines for the management of osteoarthritis:

The Chronic Osteoarthritis Management Initiative of the U.S. Bone and Joint

Initiative. Semin Arthritis Rheum. 2013;43(6):701-712.

119. Zambon S, Siviero P, Denkinger M, et al. Role of osteoarthritis, comorbidity and

pain in determining functional limitations in older populations: European project

on Osteoarthritis. Arthritis Care Res (Hoboken). 2016;68(6):801-810.

120. Zullig LL, Bosworth HB, Jeffreys AS, et al. The association of comorbid

conditions with patient-reported outcomes in Veterans with hip and knee

osteoarthritis. Clin Rheumatol. 2015;34(8):1435-1441.

121. de Rooij M, van der Leeden M, Heymans MW, et al. Prognosis of pain and

physical functioning in patients with knee osteoarthritis: Systematic review and

meta-analysis. Arthritis Care Res (Hoboken). 2016;68(4):481-492.

195 122. Landmark T, Romundstad P, Borchgrevink PC, Kaasa S, Dale O. Associations

between recreational exercise and chronic pain in the general population:

evidence from the HUNT 3 study. Pain. 2011;152(10):2241-2247.

123. Jones MD, Booth J, Taylor JL, Barry BK. Limited association between aerobic

fitness and pain in healthy individuals: A cross-sectional study. Pain Med.

2016;17(10):1799-1808.

124. Bartels EM, Juhl CB, Christensen R, et al. Aquatic exercise for the treatment of

knee and hip osteoarthritis. Cochrane Database Syst Rev. 2016;3:CD005523.

125. Bidonde J, Busch AJ, Webber SC, et al. Aquatic exercise training for

fibromyalgia. Cochrane Database Syst Rev. 2014;10:CD011336.

126. Busch AJ, Webber SC, Richards RS, et al. Resistance exercise training for

fibromyalgia. Cochrane Database Syst Rev. 2013;12:CD010884.

127. Angel Garcia D, Martinez Nicolas I, Saturno Hernandez PJ. Clinical approach to

fibromyalgia: Synthesis of evidence-based recommendations, a systematic

review. Reumatol Clin. 2016;12(2):65-71.

128. Langhorst J, Klose P, Dobos GJ, Bernardy K, Hauser W. Efficacy and safety of

meditative movement therapies in fibromyalgia syndrome: a systematic review

and meta-analysis of randomized controlled trials. Rheumatol Int.

2013;33(1):193-207.

129. Mist SD, Firestone KA, Jones KD. Complementary and alternative exercise for

fibromyalgia: a meta-analysis. J Pain Res. 2013;6:247-260.

130. Thomas EN, Blotman F. Aerobic exercise in fibromyalgia: a practical review.

Rheumatol Int. 2010;30(9):1143-1150.

196 131. Aitken D, Buchbinder R, Jones G, Winzenberg T. Interventions to improve

adherence to exercise for chronic musculoskeletal pain in adults. Aust Fam

Physician. 2015;44(1):39-42.

132. Bruyere O, Cooper C, Pelletier JP, et al. An algorithm recommendation for the

management of knee osteoarthritis in Europe and internationally: A report from

a task force of the European Society for Clinical and Economic Aspects of

Osteoporosis and Osteoarthritis (ESCEO). Semin Arthritis Rheum.

2014;44(3):253-263.

133. Juhl C, Christensen R, Roos EM, Zhang W, Lund H. Impact of exercise type and

dose on pain and disability in knee osteoarthritis: A systematic review and meta-

regression analysis of randomized controlled trials. Arthritis Rheum.

2014;66(3):622-636.

134. Regnaux JP, Lefevre-Colau MM, Trinquart L, et al. High-intensity versus low-

intensity physical activity or exercise in people with hip or knee osteoarthritis.

Cochrane Database Syst Rev. 2015;10:CD010203.

135. Kan L, Zhang J, Yang Y, Wang P. The effects of yoga on pain, mobility, and

quality of life in patients with knee osteoarthritis: A systematic review. Evid

Based Complement Alternat Med. 2016;2016:6016532.

136. Kong LJ, Lauche R, Klose P, et al. Tai Chi for chronic pain conditions: A

systematic review and meta-analysis of randomized controlled trials. Sci Rep.

2016;6:25325.

137. Bennell KL, Kyriakides M, Metcalf B, et al. Neuromuscular versus quadriceps

strengthening exercise in patients with medial knee osteoarthritis and varus

malalignment: a randomized controlled trial. Arthritis Rheumatol.

2014;66(4):950-959.

197 138. Knoop J, Dekker J, van der Leeden M, et al. Knee joint stabilization therapy in

patients with osteoarthritis of the knee: a randomized, controlled trial.

Osteoarthritis Cartilage. 2013;21(8):1025-1034.

139. Villadsen A, Overgaard S, Holsgaard-Larsen A, Christensen R, Roos EM.

Immediate efficacy of neuromuscular exercise in patients with severe

osteoarthritis of the hip or knee: A secondary analysis from a randomized

controlled trial. J Rheumatol. 2014;41(7):1385-1394.

140. Villadsen A, Overgaard S, Holsgaard-Larsen A, Christensen R, Roos EM.

Postoperative effects of neuromuscular exercise prior to hip or knee arthroplasty:

a randomised controlled trial. Ann Rheum Dis. 2014;73(6):1130-1137.

141. Fernandes L, Roos EM, Overgaard S, Villadsen A, Sogaard R. Supervised

neuromuscular exercise prior to hip and knee replacement: 12-month clinical

effect and cost-utility analysis alongside a randomised controlled trial. BMC

Musculoskelet Disord. 2017;18(1):5.

142. Bennell KL, Dobson F, Roos EM, et al. The influence of biomechanical

characteristics on pain and function outcomes from exercise in medial knee

osteoarthritis and varus malalignment: exploratory analyses from a randomised

controlled trial. Arthritis Care Res (Hoboken). 2015;67(9):1281-1288.

143. Knoop J, Steultjens MP, Roorda LD, et al. Improvement in upper leg muscle

strength underlies beneficial effects of exercise therapy in knee osteoarthritis:

secondary analysis from a randomised controlled trial. Physiotherapy.

2015;101(2):171-177.

144. Dobson F, Bennell KL, French SD, et al. Barriers and facilitators to exercise

participation in people with hip and/or knee osteoarthritis: Synthesis of the

198 literature using behavior change theory. Am J Phys Med Rehabil.

2016;95(5):372-389.

145. de Rooij M, van der Leeden M, Cheung J, et al. Efficacy of tailored exercise

therapy on physical functioning in patients with knee osteoarthritis and

comorbidity: A randomized controlled trial. Arthritis Care Res (Hoboken). 2016.

146. Beckwee D, Vaes P, Cnudde M, Swinnen E, Bautmans I. Osteoarthritis of the

knee: why does exercise work? A qualitative study of the literature. Ageing Res

Rev. 2013;12(1):226-236.

147. Runhaar J, Luijsterburg P, Dekker J, Bierma-Zeinstra SM. Identifying potential

working mechanisms behind the positive effects of exercise therapy on pain and

function in osteoarthritis; a systematic review. Osteoarthritis Cartilage.

2015;23(7):1071-1082.

148. Foroughi N, Smith RM, Lange AK, Baker MK, Fiatarone Singh MA,

Vanwanseele B. Lower limb muscle strengthening does not change frontal plane

moments in women with knee osteoarthritis: A randomized controlled trial. Clin

Biomech (Bristol, Avon). 2011;26(2):167-174.

149. McQuade KJ, de Oliveira AS. Effects of progressive resistance strength training

on knee biomechanics during single leg step-up in persons with mild knee

osteoarthritis. Clin Biomech (Bristol, Avon). 2011;26(7):741-748.

150. Rodriguez-Pinto I, Agmon-Levin N, Howard A, Shoenfeld Y. Fibromyalgia and

cytokines. Immunol Lett. 2014;161(2):200-203.

151. Segura-Jimenez V, Castro-Pinero J, Soriano-Maldonado A, et al. The

association of total and central body fat with pain, fatigue and the impact of

fibromyalgia in women; role of physical fitness. Eur J Pain. 2016;20(5):811-

821.

199 152. Kami K, Tajima F, Senba E. Exercise-induced hypoalgesia: potential

mechanisms in animal models of neuropathic pain. Anat Sci Int. 2017;92(1):79-

90.

153. Bobinski F, Alarcon Ferreira TA, Cordova MM, et al. Role of brainstem

serotonin in analgesia produced by low-intensity exercise on neuropathic pain

following sciatic nerve injury in mice. Pain. 2015;156(12):2595-2606.

154. Lopez-Alvarez VM, Modol L, Navarro X, Cobianchi S. Early increasing-

intensity treadmill exercise reduces neuropathic pain by preventing nociceptor

collateral sprouting and disruption of chloride cotransporters homeostasis after

peripheral nerve injury. Pain. 2015;156(9):1812-1825.

155. Nees TA, Tappe-Theodor A, Sliwinski C, et al. Early-onset treadmill training

reduces mechanical allodynia and modulates CGRP fiber density in lamina

III/IV in a mouse model of spinal cord contusion injury. Pain. 2016;157(3):687-

697.

156. Martins DF, Siteneski A, Ludtke DD, Dal-Secco D, Santos AR. High-intensity

swimming exercise decreases glutamate-induced nociception by activation of G-

protein-coupled receptors inhibiting phosphorylated protein kinase A [epub

ahead of print]. Mol Neurobiol. 2016:doi: 10.1007/s12035-12016-10095-12039.

157. Kami K, Taguchi Ms S, Tajima F, Senba E. Improvements in impaired GABA

and GAD65/67 production in the spinal dorsal horn contribute to exercise-

induced hypoalgesia in a mouse model of neuropathic pain. Mol Pain. 2016;12.

158. Almeida C, DeMaman A, Kusuda R, et al. Exercise therapy normalizes BDNF

upregulation and glial hyperactivity in a mouse model of neuropathic pain. Pain.

2015;156(3):504-513.

200 159. Cobianchi S, Marinelli S, Florenzano F, Pavone F, Luvisetto S. Short- but not

long-lasting treadmill running reduces allodynia and improves functional

recovery after peripheral nerve injury. Neuroscience. 2010;168(1):273-287.

160. Bernardi C, Tramontina AC, Nardin P, et al. Treadmill exercise induces

hippocampal astroglial alterations in rats. Neural Plast. 2013;2013:709732.

161. Kawi J, Lukkahatai N, Inouye J, Thomason D, Connelly K. Effects of exercise

on select biomarkers and associated outcomes in chronic pain conditions:

systematic review. Biol Res Nurs. 2016;18(2):147-159.

162. Flodin P, Martinsen S, Mannerkorpi K, et al. Normalization of aberrant resting

state functional connectivity in fibromyalgia patients following a three month

physical exercise therapy. Neuroimage Clin. 2015;9:134-139.

163. Ellingson LD, Shields MR, Stegner AJ, Cook DB. Physical activity, sustained

sedentary behavior, and pain modulation in women with fibromyalgia. J Pain.

2012;13(2):195-206.

164. McLoughlin MJ, Stegner AJ, Cook DB. The relationship between physical

activity and brain responses to pain in fibromyalgia. J Pain. 2011;12(6):640-

651.

165. Micalos PS, Korgaonkar MS, Drinkwater EJ, Cannon J, Marino FE. Cerebral

responses to innocuous somatic pressure stimulation following aerobic exercise

rehabilitation in chronic pain patients: a functional magnetic resonance imaging

study. Int J Gen Med. 2014;7:425-432.

166. Finan PH, Goodin BR, Smith MT. The association of sleep and pain: an update

and a path forward. J Pain. 2013;14(12):1539-1552.

167. Moldofsky H. Sleep and pain. Sleep Med Rev. 2001;5(5):385-396.

201 168. Bonvanie IJ, Oldehinkel AJ, Rosmalen JG, Janssens KA. Sleep problems and

pain: A longitudinal cohort study in Emerging adults. Pain. 2015;157(4):957-

963.

169. Boakye PA, Olechowski C, Rashiq S, et al. A critical review of neurobiological

factors involved in the interactions between chronic pain, depression, and sleep

disruption. Clin J Pain. 2016;32(4):327-336.

170. Bircan C, Karasel SA, Akgun B, El O, Alper S. Effects of muscle strengthening

versus aerobic exercise program in fibromyalgia. Rheumatol Int.

2008;28(6):527-532.

171. Gowans SE, deHueck A, Voss S, Silaj A, Abbey SE, Reynolds WJ. Effect of a

randomized, controlled trial of exercise on mood and physical function in

individuals with fibromyalgia. Arthritis Rheum. 2001;45(6):519-529.

172. Schachter CL, Busch AJ, Peloso PM, Sheppard MS. Effects of short versus long

bouts of aerobic exercise in sedentary women with fibromyalgia: a randomized

controlled trial. Phys Ther. 2003;83(4):340-358.

173. Valim V, Oliveira L, Suda A, et al. Aerobic fitness effects in fibromyalgia. J

Rheumatol. 2003;30(5):1060-1069.

174. Palstam A, Larsson A, Lofgren M, et al. Decrease of fear avoidance beliefs

following person-centered progressive resistance exercise contributes to reduced

pain disability in women with fibromyalgia: secondary exploratory analyses

from a randomized controlled trial. Arthritis Res Ther. 2016;18(1):116.

175. Rayahin JE, Chmiel JS, Hayes KW, et al. Factors associated with pain

experience outcome in knee osteoarthritis. Arthritis Care Res (Hoboken).

2014;66(12):1828-1835.

202 176. Rejeski WJ, Craven T, Ettinger WH, McFarlane M, Shumaker S. Self-efficacy

and pain in disability with osteoarthritis of the knee. J Gerentol B Psychol Sci

Soc Sci. 1996;51(1):24-29.

177. Kelley GA, Kelley KS, Hootman JM. Effects of exercise on depression in adults

with arthritis: a systematic review with meta-analysis of randomized controlled

trials. Arthritis Res Ther. 2015;17(1):21.

178. Kelley GA, Kelley KS, Jones DL. Efficacy and effectiveness of exercise on

tender points in adults with fibromyalgia: a meta-analysis of randomized

controlled trials. Arthritis. 2011;2011:125485.

179. Anshel MH, Russell KG. Effect of aerobic and strength training on pain

tolerance, pain appraisal and mood of unfit males as a function of pain location.

J Sports Sci. 1994;12(6):535-547.

180. Jones MD, Booth J, Taylor JL, Barry BK. Aerobic training increases pain

tolerance in healthy individuals. Med Sci Sports Exerc. 2014;46(8):1640-1647.

181. Oktedalen O, Solberg EE, Haugen AH, Opstad PK. The influence of physical

and mental training on plasma beta-endorphin level and pain perception after

intensive physical exercise. Stress Health. 2001;17:121-127.

182. Varrassi G, Bazzano C, Edwards WT. Effects of physical activity on maternal

plasma beta-endorphin levels and perception of labor pain. Am J Obstet

Gynecol. 1989;160(3):707-712.

183. Tesarz J, Schuster AK, Hartmann M, Gerhardt A, Eich W. Pain perception in

athletes compared to normally active controls: A systematic review with meta-

analysis. Pain. 2012;153(6):1253-1262.

203 184. Andrzejewski W, Kassolik K, Brzozowski M, Cymer K. The influence of age

and physical activity on the pressure sensitivity of soft tissues of the

musculoskeletal system. J Bodyw Mov Ther. 2010;14(4):382-390.

185. Ellingson LD, Colbert LH, Cook DB. Physical activity is related to pain

sensitivity in healthy women. Med Sci Sports Exerc. 2012;44(7):1401-1406.

186. Lemming D, Borsbo B, Sjors A, et al. Single-point but not tonic cuff pressure

pain sensitivity is associated with level of physical fitness - a study of non-

athletic healthy subjects. PLoS One. 2015;10(5):e0125432.

187. Naugle KM, Riley JL, 3rd. Self-reported physical activity predicts pain

inhibitory and facilitatory function. Med Sci Sports Exerc. 2014;46(3):622-629.

188. Ho A, Ashe MC, DeLongis A, Graf P, Khan KM, Hoppmann CA. Gender

differences in pain-physical activity linkages among older adults: Lessons

learned from daily life approaches. Pain Res Manag. 2016:1931590.

189. Black CD, Huber JK, Ellingson LD, et al. Exercise-induced hypoalgesia is not

influenced by physical activity type and amount [epub ahead of print]. Med Sci

Sports Exerc. 2016:doi: 10.1249/mss.0000000000001186.

190. Naugle KM, Fillingim RB, Riley JL, 3rd. A meta-analytic review of the

hypoalgesic effects of exercise. J Pain. 2012;13(12):1139-1150.

191. Koltyn KF. Exercise-induced hypoalgesia and intensity of exercise. Sports Med.

2002;32(8):477-487.

192. Koltyn KF, Brellenthin AG, Cook DB, Sehgal N, Hillard C. Mechanisms of

exercise-induced hypoalgesia. J Pain. 2014;15(12):1294-1304.

193. Koltyn KF, Knauf MT, Brellenthin AG. Temporal summation of heat pain

modulated by isometric exercise. Eur J Pain. 2013;17(7):1005-1011.

204 194. Naugle KM, Naugle KE, Fillingim RB, Riley JL, 3rd. Isometric exercise as a

test of pain modulation: effects of experimental pain test, psychological

variables, and sex. Pain Med. 2014;15(4):692-701.

195. Vierck CJ, Jr., Staud R, Price DD, Cannon RL, Mauderli AP, Martin AD. The

effect of maximal exercise on temporal summation of second pain (windup) in

patients with fibromyalgia syndrome. J Pain. 2001;2(6):334-344.

196. Vaegter HB, Handberg G, Graven-Nielsen T. Isometric reduce

temporal summation of pressure pain in humans. Eur J Pain. 2015;19(7):973-

983.

197. Meeus M, Hermans L, Ickmans K, et al. Endogenous pain modulation in

response to exercise in patients with rheumatoid arthritis, patients with chronic

fatigue syndrome and comorbid fibromyalgia, and healthy controls: A double-

blind randomized controlled trial. Pain Pract. 2015;15(12):98-106.

198. Friedman DB, Brennum J, Sztuk F, et al. The effect of epidural anaesthesia with

1% lidocaine on the pressor response to dynamic exercise in man. J Physiol.

1993;470:681-691.

199. Micalos PS, Harris J, Drinkwater EJ, Cannon J, Marino FE. Perceptual and

cerebro-spinal responses to graded innocuous and noxious stimuli following

aerobic exercise. J Sports Med Phys Fitness. 2015;55(11):1407-1415.

200. Vaegter HB, Handberg G, Graven-Nielsen T. Similarities between exercise-

induced hypoalgesia and conditioned pain modulation in humans. Pain.

2014;155(1):158-167.

201. Farrar JT, Young JP, Jr., LaMoreaux L, Werth JL, Poole RM. Clinical

importance of changes in chronic pain intensity measured on an 11-point

numerical pain rating scale. Pain. 2001;94(2):149-158.

205 202. Hoffman MD, Shepanski MA, Ruble SB, Valic Z, Buckwalter JB, Clifford PS.

Intensity and duration threshold for aerobic exercise-induced analgesia to

pressure pain. Arch Phys Med Rehabil. 2004;85(7):1183-1187.

203. Naugle KM, Naugle KE, Fillingim RB, Samuels B, Riley JL, 3rd. Intensity

thresholds for aerobic exercise-induced hypoalgesia. Med Sci Sports Exerc.

2014;46(4):817-825.

204. Micalos PS, Arendt-Nielsen L. Differential pain response at local and remote

muscle sites following aerobic cycling exercise at mild and moderate intensity.

Springerplus. 2016;5:91.

205. Drury DG, Stuempfle K, Shannon R, Miller J. An investigation of exercise-

induced hypoalgesia after isometric and cardiovascular exercise. J Exerc Physiol

Online. 2004;7(4):1-5.

206. Paalasmaa P, Kemppainen P, Pertovaara A. Modulation of skin sensitivity by

dynamic and isometric exercise in man. Eur J Appl Physiol Occup Physiol.

1991;62(4):279-285.

207. Hoeger Bement MK, Dicapo J, Rasiarmos R, Hunter SK. Dose response of

isometric contractions on pain perception in healthy adults. Med Sci Sports

Exerc. 2008;40(11):1880-1889.

208. Lemley KJ, Drewek B, Hunter SK, Hoeger Bement MK. Pain relief after

isometric exercise is not task-dependent in older men and women. Med Sci

Sports Exerc. 2014;46(1):185-191.

209. Koltyn KF, Umeda M. Contralateral attenuation of pain after short-duration

submaximal isometric exercise. J Pain. 2007;8(11):887-892.

206 210. Staud R, Robinson ME, Price DD. Isometric exercise has opposite effects on

central pain mechanisms in fibromyalgia patients compared to normal controls.

Pain. 2005;118(1-2):176-184.

211. Jones MD, Taylor JL, Booth J, Barry BK. Exploring the mechanisms of

exercise-induced hypoalgesia using somatosensory and laser evoked potentials.

Front Physiol. 2016;7:581.

212. Vaegter HB, Hoeger Bement M, Madsen AB, Fridriksson J, Dasa M, Graven-

Nielsen T. Exercise increases pressure pain tolerance but not pressure and heat

pain thresholds in healthy young men. Eur J Pain. 2017;21(1):73-81.

213. Baiamonte BA, Kraemer RR, Chabreck CN, et al. Exercise-induced

hypoalgesia: Pain tolerance, preference and tolerance for exercise intensity, and

physiological correlates following dynamic circuit resistance exercise [epub

ahead of print]. J Sports Sci. 2016:doi: 10.1080/02640414.02642016.01239833.

214. Burrows NJ, Booth J, Sturnieks DL, Barry BK. Acute resistance exercise and

pressure pain sensitivity in knee osteoarthritis: a randomised crossover trial.

Osteoarthritis Cartilage. 2014;22(3):407-414.

215. Keilman BM, Hanney WJ, Kolber MJ, et al. The short term effect of kettlebell

swings on lumbopelvic pressure pain thresholds: a randomized controlled trial. J

Strength Cond Res. 2016.

216. Newcomb LW, Koltyn KF, Morgan WP, Cook DB. Influence of preferred

versus prescribed exercise on pain in fibromyalgia. Med Sci Sports Exerc.

2011;43(6):1106-1113.

217. Staud R, Robinson ME, Weyl EE, Price DD. Pain variability in fibromyalgia is

related to activity and rest: role of peripheral tissue impulse input. J Pain.

2010;11(12):1376-1383.

207 218. Knauf MT, Koltyn KF. Exercise-induced modulation of pain in adults with and

without painful diabetic neuropathy. J Pain. 2014;15(6):656-663.

219. Vaegter HB, Handberg G, Emmeluth C, Graven-Nielsen T. Preoperative

hypoalgesia after and aerobic exercise is associated with pain

relief six months after total knee replacement. Clin J Pain. 2017;33(6):475-484.

220. Fingleton C, Smart K, Doody C. Exercise-induced hypoalgesia in people with

knee osteoarthritis with normal and abnormal conditioned pain modulation

[epub ahead of print]. Clin J Pain. 2017;33(5):395-404.

221. Vaegter HB, Handberg G, Graven-Nielsen T, Edwards R. Hypoalgesia after

exercise and cold pressor test are reduced in chronic musculoskeletal pain

patients with high pain sensitivity. Clin J Pain. 2016;32(1):58-69.

222. Gupta A, Mayer EA, Fling C, et al. Sex-based differences in brain alterations

across chronic pain conditions. J Neurosci Res. 2017;95(1-2):604-616.

223. Racine M, Tousignant-Laflamme Y, Kloda LA, Dion D, Dupuis G, Choiniere

M. A systematic literature review of 10 years of research on sex/gender and

experimental pain perception - part 1: are there really differences between

women and men? Pain. 2012;153(3):602-618.

224. Sorge RE, Totsch SK. Sex differences in pain [epub ahead of print]. J Neurosci

Res. 2016:doi: 10.1002/jnr.23841.

225. Gibson SJ, Farrell M. A review of age differences in the neurophysiology of

nociception and the perceptual experience of pain. Clin J Pain. 2004;20(4):227-

239.

226. Gibson SJ, Helme RD. Age-related differences in pain perception and report.

Clin Geriatr Med. 2001;17(3):433-456, v-vi.

208 227. Koltyn KF, Trine MR, Stegner AJ, Tobar DA. Effect of isometric exercise on

pain perception and blood pressure in men and women. Med Sci Sports Exerc.

2001;33(2):282-290.

228. Lemley KJ, Senefeld J, Hunter SK, Hoeger Bement M. Only women report

increase in pain threshold following fatiguing contractions of the upper

extremity. Eur J Appl Physiol. 2016;116(7):1379-1385.

229. Sternberg WF, Bokat C, Kass L, Alboyadjian A, Gracely RH. Sex-dependent

components of the analgesia produced by athletic competition. J Pain.

2001;2(1):65-74.

230. Gajsar H, Titze C, Hasenbring MI, Vaegter HB. Isometric back exercise has

different effects on pressure pain thresholds in healthy men and women [epub

ahead of print]. Pain Med. 2016:doi: 10.1093/pm/pnw1176.

231. Kosek E, Lundberg L. Segmental and plurisegmental modulation of pressure

pain thresholds during static muscle contractions in healthy individuals. Eur J

Pain. 2003;7(3):251-258.

232. Umeda M, Newcomb LW, Ellingson LD, Koltyn KF. Examination of the dose-

response relationship between pain perception and blood pressure elevations

induced by isometric exercise in men and women. Biol Psychol. 2010;85(1):90-

96.

233. Lemley KJ, Hunter SK, Hoeger Bement MK. Conditioned pain modulation

predicts exercise-induced hypoalgesia in healthy adults. Med Sci Sports Exerc.

2015;47(1):176-184.

234. Stolzman S, Danduran M, Hunter SK, Bement MH. Pain response after maximal

aerobic exercise in adolescents across weight status. Med Sci Sports Exerc.

2015;47(11):2431-2440.

209 235. Naugle KM, Naugle KE, Riley JL, 3rd. Reduced modulation of pain in older

adults following isometric and aerobic exercise. J Pain. 2016;17(6):719-728.

236. Umeda M, Kempka LE, Greenlee BT, Weatherby AC. A smaller magnitude of

exercise-induced hypoalgesia in African Americans compared to non-Hispanic

Whites: A potential influence of physical activity. Biol Psychol. 2016;113:46-

51.

237. Vaegter HB, Handberg G, Jorgensen MN, Kinly A, Graven-Nielsen T. Aerobic

exercise and cold pressor test induce hypoalgesia in active and inactive men and

women. Pain Med. 2015;16(5):923-933.

238. Coriolano K, Aiken A, Pukall C, Harrison M. Changes in self-reported disability

after performance-based tests in obese and non-obese individuals diagnosed with

osteoarthritis of the knee. Disabil Rehabil. 2015;37(13):1152-1161.

239. Umeda M, Corbin LW, Maluf KS. Examination of contraction-induced muscle

pain as a behavioral correlate of physical activity in women with and without

fibromyalgia. Disabil Rehabil. 2015;37(20):1864-1869.

240. Fleng Sandal L, Roos EM, Bogesvang SJ, Thorlund JB. Pain trajectory and

exercise-induced pain flares during 8 weeks of neuromuscular exercise in

individuals with knee and hip pain. Osteoarthritis Cartilage. 2016;24(4):589-

592.

241. Thoren P, Floras JS, Hoffmann P, Seals DR. Endorphins and exercise:

physiological mechanisms and clinical implications. Med Sci Sports Exerc.

1990;22(4):417-428.

242. Dietrich A, McDaniel WF. Endocannabinoids and exercise. Br J Sports Med.

2004;38(5):536-541.

210 243. Raichlen DA, Foster AD, Seillier A, Giuffrida A, Gerdeman GL. Exercise-

induced endocannabinoid signaling is modulated by intensity. Eur J Appl

Physiol. 2013;113(4):869-875.

244. Sparling PB, Giuffrida A, Piomelli D, Rosskopf L, Dietrich A. Exercise

activates the endocannabinoid system. Neuroreport. 2003;14(17):2209-2211.

245. Galdino G, Romero T, da Silva JF, et al. Acute resistance exercise induces

antinociception by activation of the endocannabinoid system in rats. Anesth

Analg. 2014;119(3):702-715.

246. Galdino G, Romero TR, Silva JF, et al. The endocannabinoid system mediates

aerobic exercise-induced antinociception in rats. Neuropharmacology.

2014;77:313-324.

247. Galdino GS, Duarte ID, Perez AC. Participation of endogenous opioids in the

antinociception induced by resistance exercise in rats. Braz J Med Biol Res.

2010;43(9):906-909.

248. Fuss J, Steinle J, Bindila L, et al. A runner's high depends on cannabinoid

receptors in mice. Proc Natl Acad Sci USA. 2015;112(42):13105-13108.

249. Haier RJ, Quaid K, Mills JC. Naloxone alters pain perception after jogging.

Psychiatry Res. 1981;5(2):231-232.

250. Janal MN, Colt EW, Clark WC, Glusman M. Pain sensitivity, mood and plasma

endocrine levels in man following long-distance running: effects of naloxone.

Pain. 1984;19(1):13-25.

251. Droste C, Greenlee MW, Schreck M, Roskamm H. Experimental pain thresholds

and plasma beta-endorphin levels during exercise. Med Sci Sports Exerc.

1991;23(3):334-342.

211 252. Olausson B, Eriksson E, Ellmarker L, Rydenhag B, Shyu BC, Andersson SA.

Effects of naloxone on dental pain threshold following muscle exercise and low

frequency transcutaneous nerve stimulation: a comparative study in man. Acta

Physiol Scand. 1986;126(2):299-305.

253. Droste C, Meyer-Blankenburg M, Greenlee W, Roskamm H. Effect of physical

exercise on pain thresholds and plasma beta-endorphins in patients with silent

and symptomatic myocardial ischaemia. European Heart Journal.

1988;9(Supplement N):25-33.

254. Auh QS, Chun YH, Melemedjian OK, Zhang Y, Ro JY. Peripheral interactions

between cannabinoid and opioid receptor agonists in a model of inflammatory

mechanical hyperalgesia. Brain Res Bull. 2016;125:211-217.

255. Maguire DR, Yang W, France CP. Interactions between mu-opioid receptor

agonists and cannabinoid receptor agonists in rhesus monkeys: antinociception,

drug discrimination, and drug self-administration. J Pharmacol Exp Ther.

2013;345(3):354-362.

256. Tham SM, Angus JA, Tudor EM, Wright CE. Synergistic and additive

interactions of the cannabinoid agonist CP55,940 with mu opioid receptor and

alpha2-adrenoceptor agonists in acute pain models in mice. Br J Pharmacol.

2005;144(6):875-884.

257. Grenald SA, Young MA, Wang Y, et al. Synergistic attenuation of chronic pain

using mu opioid and cannabinoid receptor 2 agonists. Neuropharmacology.

2016;116:59-70.

258. Galdino GS, Cortes SF, Duarte ID, Perez AC. Involvement of the nitric

oxide/(C)GMP/K(ATP) pathway in antinociception induced by exercise in rats.

Life Sci. 2010;86(13-14):505-509.

212 259. Galdino GS, Duarte ID, Perez AC. Central release of nitric oxide mediates

antinociception induced by aerobic exercise. Braz J Med Biol Res.

2015;48(9):790-797.

260. Galdino GS, Xavier CH, Almeida R, et al. The nitric oxide/GMP/KATP

pathway mediates systemic and central antinociception induced by resistance

exercise in rats. Int J Neurosci. 2015;125(10):765-773.

261. Garry MG, Richardson JD, Hargreaves KM. Sodium nitroprusside evokes the

release of immunoreactive calcitonin gene-related peptide and from

dorsal horn slices via nitric oxide-dependent and nitric oxide-independent

mechanisms. J Neurosci. 1994;14(7):4329-4337.

262. Schmid HA, Pehl U. Regional specific effects of nitric oxide donors and cGMP

on the electrical activity of neurons in the rat spinal cord. J Chem Neuroanat.

1996;10(3-4):197-201.

263. Pertovaara A, Huopaniemi T, Virtanen A, Johansson G. The influence of

exercise on dental pain thresholds and the release of stress hormones. Physiol

Behav. 1984;33(6):923-926.

264. Kemppainen P, Pertovaara A, Huopaniemi T, Johansson G. Elevation of dental

pain threshold induced in man by physical exercise is not reversed by

cyproheptadine-mediated suppression of growth hormone release. Neurosci Lett.

1986;70(3):388-392.

265. Kemppainen P, Paalasmaa P, Pertovaara A, Alila A, Johansson G.

Dexamethasone attenuates exercise-induced dental analgesia in man. Brain Res.

1990;519(1-2):329-332.

213 266. Wingenfeld K, Wolf S, Kunz M, Krieg JC, Lautenbacher S. No effects of

hydrocortisone and dexamethasone on pain sensitivity in healthy individuals.

Eur J Pain. 2015;19(6):834-841.

267. Scioli-Salter E, Forman DE, Otis JD, et al. Potential neurobiological benefits of

exercise in chronic pain and posttraumatic stress disorder: Pilot study. J Rehabil

Res Dev. 2016;53(1):95-106.

268. Carlton SM. Nociceptive primary afferents: they have a mind of their own. J

Physiol. 2014;592(Pt 16):3403-3411.

269. de Souza GG, Duarte ID, de Castro Perez A. Differential involvement of central

and peripheral alpha2 adrenoreceptors in the antinociception induced by aerobic

and resistance exercise. Anesth Analg. 2013;116(3):703-711.

270. Overland AC, Kitto KF, Chabot-Dore AJ, et al. Protein kinase C mediates the

synergistic interaction between agonists acting at alpha2-adrenergic and delta-

opioid receptors in spinal cord. J Neurosci. 2009;29(42):13264-13273.

271. Amann M. Significance of Group III and IV muscle afferents for the endurance

exercising human. Clin Exp Pharmacol Physiol. 2012;39(9):831-835.

272. O'Connor PJ, Cook DB. Exercise and pain: The neurobiology, measurement and

laboratory study of pain in relation to exercise in humans. Exerc Sport Sci Rev.

1999;27(1):119-166.

273. Light AR, Hughen RW, Zhang J, Rainier J, Liu Z, Lee J. Dorsal root ganglion

neurons innervating skeletal muscle respond to physiological combinations of

protons, ATP, and lactate mediated by ASIC, P2X, and TRPV1. J Neurophysiol.

2008;100(3):1184-1201.

214 274. Pollak KA, Swenson JD, Vanhaitsma TA, et al. Exogenously applied muscle

metabolites synergistically evoke sensations of and pain in

human subjects. Exp Physiol. 2014;99(2):368-380.

275. Sacco M, Meschi M, Regolisti G, et al. The relationship between blood pressure

and pain. J Clin Hypertens. 2013;15(8):600-605.

276. Ring C, Edwards L, Kavussanu M. Effects of isometric exercise on pain are

mediated by blood pressure. Biol Psychol. 2008;78(1):123-128.

277. Umeda M, Newcomb LW, Koltyn KF. Influence of blood pressure elevations by

isometric exercise on pain perception in women. Int J Psychophysiol.

2009;74(1):45-52.

278. Devoize L, Chalaye P, Lafrenaye S, Marchand S, Dallel R. Relationship

between adaptation and cardiovascular response to tonic cold and heat pain

Adaptability to tonic pain and cardiovascular responses. Eur J Pain.

2016;20(5):731-741.

279. Black CD, Tynes BK, Gonglach AR, Waddell DE. Local and generalized

endogenous pain modulation in healthy men: Effects of exercise and exercise-

induced muscle damage. Pain Med. 2016;17(12):2422-2433.

280. Ellingson LD, Koltyn KF, Kim JS, Cook DB. Does exercise induce hypoalgesia

through conditioned pain modulation? Psychophysiology. 2014;51(3):267-276.

281. Wonders KY, Drury DG. Exercise intensity as a determinant of exercise induced

hypoalgesia. J Exerc Physiol Online. 2011;14(4):134-144.

282. Guieu R, Blin O, Pouget J, Serratrice G. Nociceptive threshold and physical

activity. Can J Neurol Sci. 1992;19(1):69-71.

283. Geva N, Pruessner J, Defrin R. Acute psychosocial stress reduces pain

modulation capabilities in healthy men. Pain. 2014;155(11):2418-2425.

215 284. Johnson MH, Stewart J, Humphries SA, Chamove AS. Marathon runners'

reaction to potassium iontophoretic experimental pain: Pain tolerance, pain

threshold, coping and self-efficacy. Eur J Pain. 2012;16(5):767-774.

285. Ord P, Gijsbers K. Pain thresholds and tolerances of competitive rowers and

their use of spontaneous self-generated pain-coping strategies. Percept Mot

Skills. 2003;97(3 Pt 2):1219-1222.

286. Brellenthin AG, Crombie KM, Cook DB, Sehgal N, Koltyn KF. Psychosocial

influences on exercise-induced hypoalgesia. Pain Med. 2017;18(3):538-550.

287. Weissman-Fogel I, Sprecher E, Pud D. Effects of catastrophizing on pain

perception and pain modulation. Exp Brain Res. 2008;186(1):79-85.

288. Ellingson LD, Stegner AJ, Schwabacher IJ, Koltyn KF, Cook DB. Exercise

strengthens central nervous system modulation of pain in fibromyalgia. Brain

Sci. 2016;6(1):8.

289. Kosek E, Roos EM, Ageberg E, Nilsdotter A. Increased pain sensitivity but

normal function of exercise induced analgesia in hip and knee osteoarthritis -

treatment effects of neuromuscular exercise and total joint replacement.

Osteoarthritis Cartilage. 2013;21(9):1299-1307.

290. Coombes BK, Wiebusch M, Heales L, Stephenson A, Vicenzino B. Isometric

exercise above but not below an individual's pain threshold influences pain

perception in people with lateral epicondylalgia. Clin J Pain. 2016;32(12):1069-

1075.

291. Lannersten L, Kosek E. Dysfunction of endogenous pain inhibition during

exercise with painful muscles in patients with shoulder myalgia and

fibromyalgia. Pain. 2010;151(1):77-86.

216 292. Sharma CV, Mehta V. Paracetamol: mechanisms and updates. Contin Educ

Anaesth Crit Care Pain. 2014;14(4):153-158.

293. Bonnet CS, Walsh DA. Osteoarthritis, angiogenesis and inflammation.

Rheumatology (Oxford). 2005;44(1):7-16.

294. Ortega E, Garcia JJ, Bote ME, et al. Exercise in fibromyalgia and related

inflammatory disorders: known effects and unknown chances. Exerc Immunol

Rev. 2009;15:42-65.

295. Petersen AM, Pedersen BK. The anti-inflammatory effect of exercise. J Appl

Physiol. 2005;98(4):1154-1162.

296. Bote ME, Garcia JJ, Hinchado MD, Ortega E. Fibromyalgia: anti-inflammatory

and stress responses after acute moderate exercise. PLoS One.

2013;8(9):e74524.

297. Christidis N, Ghafouri B, Larsson A, et al. Comparison of the levels of pro-

inflammatory cytokines released in the vastus lateralis muscle of patients with

fibromyalgia and healthy controls during contractions of the quadriceps muscle -

A microdialysis study. PLoS One. 2015;10(12):e0143856.

298. Germanou EI, Chatzinikolaou A, Malliou P, et al. Oxidative stress and

inflammatory responses following an acute bout of isokinetic exercise in obese

women with knee osteoarthritis. Knee. 2013;20(6):581-590.

299. Gomes WF, Lacerda AC, Mendonca VA, et al. Effect of exercise on the plasma

BDNF levels in elderly women with knee osteoarthritis. Rheumatol Int.

2014;34(6):841-846.

300. Helmark IC, Mikkelsen UR, Borglum J, et al. Exercise increases interleukin-10

levels both intraarticularly and peri-synovially in patients with knee

217 osteoarthritis: a randomized controlled trial. Arthritis Res Ther.

2010;12(4):R126.

301. Umeda M, Lee W, Marino CA, Hilliard SC. Influence of moderate intensity

physical activity levels and gender on conditioned pain modulation. J Sports Sci.

2016;34(5):467-476.

302. Koltyn KF. Analgesia following exercise: a review. Sports Med. 2000;29(2):85-

98.

303. Leung A, Gregory NS, Allen LH, Sluka KA. Regular physical activity prevents

chronic pain by altering resident muscle macrophage phenotype and increasing

IL-10 in mice. Pain. 2016;157(1):70-79.

304. Sluka KA, O'Donnell JM, Danielson J, Rasmussen LA. Regular physical activity

prevents development of chronic pain and activation of central neurons. J Appl

Physiol. 2013;114(6):725-733.

305. Arendt-Nielsen L, Chen AC. Lasers and other thermal stimulators for activation

of skin nociceptors in humans. Neurophysiol Clin. 2003;33(6):259-268.

306. Bromm B, Lorenz J. Neurophysiological evaluation of pain. Electroencephalogr

Clin Neurophysiol. 1998;107(4):227-253.

307. Dowman R. Topographic analysis of painful laser and sural nerve electrical

evoked potentials. Brain Topogr. 2004;16(3):169-179.

308. Bulut S, Ozmerdivenli R, Bayer H. Effects of exercise on somatosensory-evoked

potentials. Int J Neurosci. 2003;113(3):315-322.

309. Arguissain FG, Biurrun Manresa JA, Morch CD, Andersen OK. On the use of

information theory for the analysis of synchronous nociceptive withdrawal

reflexes and somatosensory evoked potentials elicited by graded electrical

stimulation. J Neurosci Methods. 2015;240:1-12.

218 310. Ruscheweyh R, Baumler M, Feller M, Krafft S, Sommer J, Straube A. Learned

control over spinal nociception reduces supraspinal nociception as quantified by

late somatosensory evoked potentials. Pain. 2015;156(12):2505-2513.

311. Rustamov N, Tessier J, Provencher B, Lehmann A, Piche M. Inhibitory effects

of heterotopic noxious counter-stimulation on perception and brain activity

related to A-beta fiber activation. Eur J Neurosci. 2016;44(1):1771-1778.

312. Luck SJ. An Introduction to The Event-Related Potential Technique. Cambridge,

MA: The MIT Press; 2005.

313. Larson MJ, Carbine KA. Sample size calculations in human electrophysiology

(EEG and ERP) studies: A systematic review and recommendations for

increased rigor. Int J Psychophysiol. 2017;111:33-41.

314. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical

power analysis program for the social, behavioral, and biomedical sciences.

Behav Res Methods. 2007;39(2):175-191.

315. Cohen JW. Statistical Power Analysis for the Behavioral Sciences (2nd edn).

Hillsdale, NJ: Lawrence Erlbaum Associates; 1988.

316. Cumming G. Understanding The New Statistics: Effect Sizes, Confidence

Intervals, and Meta-Analyses. New York: Routledge; 2012.

317. Persson AL, Hansson GA, Kalliomaki A, Moritz U, Sjolund BH. Pressure pain

thresholds and electromyographically defined muscular fatigue induced by a

muscular endurance test in normal women. Clin J Pain. 2000;16(2):155-163.

318. Hullemann P, Mahn F, Shao YQ, et al. Repetitive ipsilateral painful A-delta

fibre stimuli induce bilateral LEP amplitude habituation. Eur J Pain.

2013;17(10):1483-1490.

219 319. Hullemann P, Watfeh R, Shao YQ, Nerdal A, Binder A, Baron R. Peripheral

sensitization reduces laser-evoked potential habituation. Neurophysiol Clin.

2015;45(6):457-467.

320. Smith BW, Tooley EM, Montague EQ, Robinson AE, Cosper CJ, Mullins PG.

Habituation and sensitization to heat and cold pain in women with fibromyalgia

and healthy controls. Pain. 2008;140(3):420-428.

321. Castro A, Amorim P, Nunes CS, de Almeida FG. Effect of propofol and

remifentanil on a somatosensory evoked potential indicator of pain perception

intensity in volunteers. J Clin Monit Comput. 2015;29(5):561-567.

322. Hoeben E, Smit JW, Upmalis D, et al. Dose-response relationship after single

oral dose administrations of morphine and oxycodone using laser-evoked

potentials on UVB- and capsaicin-irritated skin in healthy male subjects. Pain.

2012;153(8):1648-1656.

323. Vossen HG, van Os J, Hermens H, Lousberg R. Evidence that trait-anxiety and

trait-depression differentially moderate cortical processing of pain. Clin J Pain.

2006;22(8):725-729.

324. Wang AL, Mouraux A, Liang M, Iannetti GD. Stimulus novelty, and not neural

refractoriness, explains the repetition suppression of laser-evoked potentials. J

Neurophysiol. 2010;104(4):2116-2124.

325. Coronado RA, Bialosky JE, Bishop MD, et al. The comparative effects of spinal

and peripheral thrust manipulation and exercise on pain sensitivity and the

relation to clinical outcome: a mechanistic trial using a shoulder pain model. J

Orthop Sports Phys Ther. 2015;45(4):252-264.

326. Kodesh E, Weissman-Fogel I. Exercise-induced hypoalgesia - interval versus

continuous mode. Appl Physiol Nutr Metab. 2014;39(7):829-834.

220 327. Iannetti GD, Baumgartner U, Tracey I, Treede RD, Magerl W. Pinprick-evoked

brain potentials: a novel tool to assess central sensitization of nociceptive

pathways in humans. J Neurophysiol. 2013;110(5):1107-1116.

328. van den Broeke EN, Mouraux A, Groneberg AH, Pfau DB, Treede RD, Klein T.

Characterizing pinprick evoked brain potentials before and after experimentally-

induced secondary hyperalgesia. J Neurophysiol. 2015;114(5):2672-2681.

329. van den Broeke EN, Lambert J, Huang G, Mouraux A. Central sensitization of

mechanical nociceptive pathways is associated with a long-lasting increase of

pinprick-evoked brain potentials. Front Hum Neurosci. 2016;10:531.

330. Treede RD, Meyer RA, Raja SN, Campbell JN. Evidence for two different heat

transduction mechanisms in nociceptive primary afferents innervating monkey

skin. J Physiol. 1995;483 (Pt 3):747-758.

331. Xu F, Wen T, Lu TJ, Seffen KA. Modeling of nociceptor transduction in skin

thermal pain sensation. J Biomech Eng. 2008;130(4):041013.

332. Zhu YJ, Lu TJ. A multi-scale view of skin thermal pain: from nociception to

pain sensation. Philos Trans A Math Phys Eng Sci. 2010;368(1912):521-559.

333. de Tommaso M, Santostasi R, Devitofrancesco V, et al. A comparative study of

cortical responses evoked by transcutaneous electrical vs CO(2) laser

stimulation. Clin Neurophysiol. 2011;122(12):2482-2487.

334. Perchet C, Frot M, Charmarty A, et al. Do we activate specifically

somatosensory thin fibres with the concentric planar electrode? A scalp and

intracranial EEG study. Pain. 2012;153(6):1244-1252.

335. Dowman R, Bridgman PM. Effects of a selective A-beta afferent block on the

pain-related SEP scalp topography. Brain Topogr. 1995;8(1):57-65.

221 336. Cruccu G, Aminoff MJ, Curio G, et al. Recommendations for the clinical use of

somatosensory-evoked potentials. Clin Neurophysiol. 2008;119(8):1705-1719.

337. Bromm B, Ganzel R, Herrmann WM, Meier W, Scharein E. Pentazocine and

flupirtine effects on spontaneous and evoked EEG activity. Neuropsychobiology.

1986;16(2-3):152-156.

338. Kochs E, Scharein E, Mollenberg O, Bromm B, Schulte am Esch J. Analgesic

efficacy of low-dose ketamine. Somatosensory-evoked responses in relation to

subjective pain ratings. Anesthesiology. 1996;85(2):304-314.

339. Galbo H, Holst JJ, Christensen NJ. Glucagon and plasma catecholamine

responses to graded and prolonged exercise in man. J Appl Physiol.

1975;38(1):70-76.

340. Black CD, Gonglach AR, Renfroe JB, Hight RE. The effects of caffeine

ingestion on exercise-induced hypoalgesia: A pilot study. Physiol Behav.

2016;161:1-6.

341. Graven-Nielsen T, Vaegter HB, Finocchietti S, Handberg G, Arendt-Nielsen L.

Assessment of musculoskeletal pain sensitivity and temporal summation by cuff

pressure algometry: A reliability study. Pain. 2015;156(11):2193-2202.

342. Lautenbacher S, Nielsen J, Andersen T, Arendt-Nielsen L. Spatial summation of

heat pain in males and females. Somatosens Mot Res. 2001;18(2):101-105.

343. Jensen K, Andersen HO, Olesen J, Lindblom U. Pressure-pain threshold in

human temporal region. Evaluation of a new pressure algometer. Pain.

1986;25(3):313-323.

344. Yarnitsky D, Ochoa JL. Studies of heat pain sensation in man: perception

thresholds, rate of stimulus rise and reaction time. Pain. 1990;40(1):85-91.

222 345. Hullemann P, Shao YQ, Manthey G, Binder A, Baron R. Central habituation and

distraction alter C-fibre-mediated laser-evoked potential amplitudes. Eur J Pain.

2016;20(3):377-385.

346. Gellish RL, Goslin BR, Olson RE, McDonald A, Russi GD, Moudgil VK.

Longitudinal modeling of the relationship between age and maximal heart rate.

Med Sci Sports Exerc. 2007;39(5):822-829.

347. Norton K, Norton L, Sadgrove D. Position statement on physical activity and

exercise intensity terminology. J Sci Med Sport. 2010;13(5):496-502.

348. Neddermeyer TJ, Fluhr K, Lotsch J. Principle components analysis of pain

thresholds to thermal, electrical, and mechanical stimuli suggests a predominant

common source of variance. Pain. 2008;138(2):286-291.

349. Neziri AY, Curatolo M, Nuesch E, et al. Factor analysis of responses to thermal,

electrical, and mechanical painful stimuli supports the importance of multi-

modal pain assessment. Pain. 2011;152(5):1146-1155.

350. Nybo L. CNS fatigue provoked by prolonged exercise in the heat. Front Biosci.

2010;2:779-792.

351. Roelands B, De Pauw K, Meeusen R. Neurophysiological effects of exercise in

the heat. Scand J Med Sci Sports. 2015;25 Suppl 1:65-78.

352. Meeusen R, Roelands B. Central fatigue and neurotransmitters, can

thermoregulation be manipulated? Scand J Med Sci Sports. 2010;20 Suppl 3:19-

28.

353. Todd G, Butler JE, Taylor JL, Gandevia SC. Hyperthermia: a failure of the

motor cortex and the muscle. J Physiol. 2005;563(Pt 2):621-631.

354. Williams AC. What can evolutionary theory tell us about chronic pain? Pain.

2016;157(4):788-790.

223 355. El Bitar N, Pollin B, Karroum EG, Pincede I, Le Bars D. Entanglement between

thermoregulation and nociception in the rat: The case of morphine. J

Neurophysiol. 2016;116(6):2473-2496.

356. Lenasi H. Physical exercise and skin microcirculation. Period. Biol.

2014;116(1):21-28.

357. Pertovaara A, Kauppila T, Hamalainen MM. Influence of skin temperature on

heat pain threshold in humans. Exp Brain Res. 1996;107(3):497-503.

358. Sotocinal SG, Sorge RE, Zaloum A, et al. The Rat Grimace Scale: a partially

automated method for quantifying pain in the laboratory rat via facial

expressions. Mol Pain. 2011;7:55.

359. Liebano RE, Vance CG, Rakel BA, et al. Transcutaneous electrical nerve

stimulation and conditioned pain modulation influence the perception of pain in

humans. Eur J Pain. 2013;17(10):1539-1546.

360. Luginbuhl M, Schnider TW, Petersen-Felix S, Arendt-Nielsen L, Zbinden AM.

Comparison of five experimental pain tests to measure analgesic effects of

alfentanil. Anesthesiology. 2001;95(1):22-29.

361. Tong KC, Lo SK, Cheing GL. Alternating frequencies of transcutaneous electric

nerve stimulation: does it produce greater analgesic effects on mechanical and

thermal pain thresholds? Arch Phys Med Rehabil. 2007;88(10):1344-1349.

362. Vance CG, Rakel BA, Blodgett NP, et al. Effects of transcutaneous electrical

nerve stimulation on pain, pain sensitivity, and function in people with knee

osteoarthritis: a randomized controlled trial. Phys Ther. 2012;92(7):898-910.

363. Wehrfritz A, Namer B, Ihmsen H, et al. Differential effects on sensory functions

and measures of epidermal nerve fiber density after application of a lidocaine

patch (5%) on healthy human skin. Eur J Pain. 2011;15(9):907-912.

224 364. Weinkauf B, Obreja O, Schmelz M, Rukwied R. Differential effects of lidocaine

on nerve growth factor (NGF)-evoked heat- and mechanical hyperalgesia in

humans. Eur J Pain. 2012;16(4):543-549.

365. Voogt L, de Vries J, Meeus M, Struyf F, Meuffels D, Nijs J. Analgesic effects of

manual therapy in patients with musculoskeletal pain: a systematic review. Man

Ther. 2015;20(2):250-256.

366. Andresen T, Staahl C, Oksche A, Mansikka H, Arendt-Nielsen L, Drewes AM.

Effect of transdermal opioids in experimentally induced superficial, deep and

hyperalgesic pain. Br J Pharmacol. 2011;164(3):934-945.

367. King CD, Goodin B, Glover TL, et al. Is the pain-reducing effect of opioid

medication reliable? A psychophysical study of morphine and pentazocine

analgesia. Pain. 2013;154(3):476-483.

368. Petersen-Felix S, Arendt-Nielsen L, Bak P, et al. Analgesic effect in humans of

subanaesthetic isoflurane concentrations evaluated by experimentally induced

pain. Br J Anaesth. 1995;75(1):55-60.

369. Taguchi T, Sato J, Mizumura K. Augmented mechanical response of muscle

thin-fiber sensory receptors recorded from rat muscle-nerve preparations in vitro

after eccentric contraction. J Neurophysiol. 2005;94(4):2822-2831.

370. Queme F, Taguchi T, Mizumura K, Graven-Nielsen T. Muscular heat and

mechanical pain sensitivity after lengthening contractions in humans and

animals. J Pain. 2013;14(11):1425-1436.

371. Zouhal H, Jacob C, Delamarche P, Gratas-Delamarche A. Catecholamines and

the effects of exercise, training and gender. Sports Med. 2008;38(5):401-423.

225 372. Kami K, Taguchi S, Tajima F, Senba E. Histone acetylation in microglia

contributes to exercise-induced hypoalgesia in neuropathic pain model mice. J

Pain. 2016;17(5):588-599.

373. Alger BE. Endocannabinoids at the synapse a decade after the dies mirabilis (29

March 2001): what we still do not know. J Physiol. 2012;590(10):2203-2212.

374. Benarroch EE. Endogenous opioid systems: current concepts and clinical

correlations. Neurology. 2012;79(8):807-814.

375. Moncada S, Higgs EA. The discovery of nitric oxide and its role in vascular

biology. Br J Pharmacol. 2006;147 Suppl 1:S193-201.

376. Dyakova EY, Kapilevich LV, Shylko VG, Popov SV, Anfinogenova Y. Physical

exercise associated with NO production: signaling pathways and significance in

health and disease. Front Cell Dev Biol. 2015;3:19.

377. Calbet JA, Gonzalez-Alonso J, Helge JW, et al. Cardiac output and leg and arm

blood flow during incremental exercise to exhaustion on the cycle ergometer. J

Appl Physiol. 2007;103(3):969-978.

378. Ge HY, Nie H, Graven-Nielsen T, Danneskiold-Samsoe B, Arendt-Nielsen L.

Descending pain modulation and its interaction with peripheral sensitization

following sustained isometric muscle contraction in fibromyalgia. Eur J Pain.

2012;16(2):196-203.

379. Thompson T, Correll CU, Gallop K, Vancampfort D, Stubbs B. Is pain

perception altered in people with depression? A systematic review and meta-

analysis of experimental pain research. J Pain. 2016;17(12):1257-1272.

380. Astrand PO, Ekbolm B, Messin R, Saltin B, Stenberg J. Intra-arterial blood

pressure during exercise with different muscle groups. J Appl Physiol.

1965;20(2):253-256.

226 381. Daniels JW, Mole PA, Shaffrath JD, Stebbins CL. Effects of caffeine on blood

pressure, heart rate, and forearm blood flow during dynamic leg exercise. J Appl

Physiol. 1998;85(1):154-159.

382. Shiroishi K, Kime R, Osada T, Murase N, Shimomura K, Katsumura T.

Decreased muscle oxygenation and increased arterial blood flow in the non-

exercising limb during leg exercise. Adv Exp Med Biol. 2010;662:379-384.

383. Saito M, Tsukanaka A, Yanagihara D, Mano T. Muscle sympathetic nerve

responses to graded leg cycling. J Appl Physiol. 1993;75(2):663-667.

384. Seals DR, Victor RG. Regulation of muscle sympathetic nerve activity during

exercise in humans. Exerc Sport Sci Rev. 1991;19:313-349.

385. Victor RG, Seals DR, Mark AL. Differential control of heart rate and

sympathetic nerve activity during dynamic exercise. Insight from intraneural

recordings in humans. J Clin Invest. 1987;79(2):508-516.

386. Robinson TE, Sue DY, Huszczuk A, Weiler-Ravell D, Hansen JE. Intra-arterial

and cuff blood pressure responses during incremental cycle ergometry. Med Sci

Sports Exerc. 1988;20(2):142-149.

387. Pud D, Granovsky Y, Yarnitsky D. The methodology of experimentally induced

diffuse noxious inhibitory control (DNIC)-like effect in humans. Pain.

2009;144(1-2):16-19.

388. Honigman L, Bar-Bachar O, Yarnitsky D, Sprecher E, Granovsky Y. Non-

painful wide-area compression inhibits experimental pain. Pain.

2016;157(9):2000-2011.

389. Hermans L, Van Oosterwijck J, Goubert D, et al. Inventory of personal factors

influencing conditioned pain modulation in healthy people: A systematic

literature review. Pain Pract. 2016;16(6):758-769.

227 390. Kennedy DL, Kemp HI, Ridout D, Yarnitsky D, Rice AS. Reliability of

conditioned pain modulation: a systematic review. Pain. 2016;157(11):2410-

2419.

391. Nahman-Averbuch H, Nir RR, Sprecher E, Yarnitsky D. Psychological factors

and conditioned pain modulation: A meta-analysis. Clin J Pain. 2016;32(6):541-

554.

392. Dahlin LB, Shyu BC, Danielsen N, Andersson SA. Effects of nerve compression

or ischaemia on conduction properties of myelinated and non-myelinated nerve

fibres. An experimental study in the rabbit common peroneal nerve. Acta

Physiol Scand. 1989;136(1):97-105.

393. Graven-Nielsen T, Mense S, Arendt-Nielsen L. Painful and non-painful pressure

sensations from human skeletal muscle. Exp Brain Res. 2004;159(3):273-283.

394. Sinclair DC, Hinshaw JR. A comparison of the sensory dissociation produced by

procaine and by limb compression. Brain. 1950;73(4):480-498.

395. Yarnitsky D, Ochoa JL. Sensations conducted by large and small myelinated

afferent fibres are lost simultaneously under compression-ischaemia block. Acta

Physiol Scand. 1989;137(2):319.

396. Inui N, Walsh LD, Taylor JL, Gandevia SC. Dynamic changes in the perceived

posture of the hand during ischaemic anaesthesia of the arm. J Physiol.

2011;589(Pt 23):5775-5784.

397. Kjogx H, Kasch H, Zachariae R, Svensson P, Jensen TS, Vase L. Experimental

manipulations of pain catastrophizing influence pain levels in chronic pain

patients and healthy volunteers. Pain. 2016;157(6):1287-1296.

228 398. Terry EL, Thompson KA, Rhudy JL. Experimental reduction of pain

catastrophizing modulates pain report but not spinal nociception as verified by

mediation analyses. Pain. 2015;156(8):1477-1488.

399. Baker SL, Kirsch I. Cognitive mediators of pain perception and tolerance. J Pers

Soc Psychol. 1991;61(3):504-510.

400. Hsiao-Wei Lo G, Balasubramanyam AS, Barbo A, Street RL, Jr., Suarez-

Almazor ME. Link between positive clinician-conveyed expectations of

treatment effect and pain reduction in knee osteoarthritis, mediated by patient

self-efficacy. Arthritis Care Res (Hoboken). 2016;68(7):952-957.

401. Atlas LY, Wager TD. How expectations shape pain. Neurosci Lett.

2012;520(2):140-148.

402. Peerdeman KJ, van Laarhoven AI, Keij SM, et al. Relieving patients' pain with

expectation interventions: A meta-analysis. Pain. 2016;157(6):1179-1191.

403. Carlino E, Piedimonte A, Frisaldi E. The effects of placebos and nocebos on

physical performance. Handb Exp Pharmacol. 2014;225:149-157.

404. Evers AW, Bartels DJ, van Laarhoven AI. Placebo and nocebo effects in itch

and pain. Handb Exp Pharmacol. 2014;225:205-214.

405. Carlino E, Guerra G, Piedimonte A. Placebo effects: From pain to motor

performance. Neurosci Lett. 2016;632:224-230.

406. Peerdeman KJ, van Laarhoven AI, Donders AR, Hopman MT, Peters ML, Evers

AW. Inducing expectations for health: effects of verbal suggestion and imagery

on pain, itch, and fatigue as indicators of physical sensitivity. PLoS One.

2015;10(10):e0139563.

229 407. Louw A, Puentedura EL, Mintken P. Use of an abbreviated neuroscience

education approach in the treatment of chronic low back pain: a case report.

Physiother Theory Pract. 2012;28(1):50-62.

408. Moseley GL. Evidence for a direct relationship between cognitive and physical

change during an education intervention in people with chronic low back pain.

Eur J Pain. 2004;8(1):39-45.

409. Moseley GL. Widespread brain activity during an abdominal task markedly

reduced after pain physiology education: fMRI evaluation of a single patient

with chronic low back pain. Aust J Physiother. 2005;51(1):49-52.

410. Ware JE, Jr., Gandek B. Overview of the SF-36 Health Survey and the

International Quality of Life Assessment (IQOLA) Project. J Clin Epidemiol.

1998;51(11):903-912.

411. Craig CL, Marshall AL, Sjostrom M, et al. International physical activity

questionnaire: 12-country reliability and validity. Med Sci Sports Exerc.

2003;35(8):1381-1395.

412. French DJ, France CR, Vigneau F, French JA, Evans RT. Fear of

movement/(re)injury in chronic pain: a psychometric assessment of the original

English version of the Tampa scale for kinesiophobia (TSK). Pain. 2007;127(1-

2):42-51.

413. Sullivan MJL, Bischop S, Pivik J. The Pain Catastrophizing Scale: Development

and validation. Psychol Assess. 1995;7(4):524-532.

414. Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited.

J Am Coll Cardiol. 2001;37(1):153-156.

415. McCabe C, Lewis J, Shenker N, Hall J, Cohen H, Blake D. Don't look now! Pain

and attention. Clin Med (Lond). 2005;5(5):482-486.

230 416. Moseley GL, Nicholas MK, Hodges PW. A randomized controlled trial of

intensive neurophysiology education in chronic low back pain. Clin J Pain.

2004;20(5):324-330.

417. Tracey I. Getting the pain you expect: mechanisms of placebo, nocebo and

reappraisal effects in humans. Nat Med. 2010;16(11):1277-1283.

418. Wager TD, Atlas LY. The neuroscience of placebo effects: connecting context,

learning and health. Nat Rev Neurosci. 2015;16(7):403-418.

419. Focht BC, Ewing V, Gauvin L, Rejeski WJ. The unique and transient impact of

acute exercise on pain perception in older, overweight, or obese adults with knee

osteoarthritis. Ann Behav Med. 2002;24(3):201-210.

420. Sabharwal R, Rasmussen L, Sluka KA, Chapleau MW. Exercise prevents

development of autonomic dysregulation and hyperalgesia in a mouse model of

chronic muscle pain. Pain. 2016;157(2):387-398.

421. Kruger S, Khayat D, Hoffmeister M, Hilberg T. Pain thresholds following

maximal endurance exercise. Eur J Appl Physiol. 2016;116(3):535-540.

422. Hoeger Bement MK, Weyer AD, Yoon T, Hunter SK. Corticomotor excitability

during a noxious stimulus before and after exercise in women with fibromyalgia.

J Clin Neurophysiol. 2014;31(1):94-98.

423. Nieminen P, Lehtiniemi H, Vahakangas K, Huusko A, Rautio A. Standardised

regression coefficient as an effect size index in summarising findings in

epidemiological studies. Epidemiology Biostatistics and Public Health.

2013;10(4):e8854 8851-8815.

424. Focht BC, Koltyn KF. Alterations in pain perception after resistance exercise

performed in the morning and evening. J Strength Cond Res. 2009;23(3):891-

897.

231 425. Koltyn KF, Arbogast RW. Perception of pain after resistance exercise. Br J

Sports Med. 1998;32(1):20-24.

426. Gurevich M, Kohn PM, Davis C. Exercise-induced analgesia and the role of

reactivity in pain sensitivity. J Sports Sci. 1994;12(6):549-559.

427. Kemppainen P, Hamalainen O, Kononen M. Different effects of physical

exercise on cold pain sensitivity in fighter pilots with and without history of

acute in-flight . Med Sci Sports Exerc. 1998;30(4):577-582.

428. Koltyn KF, Garvin AW, Gardiner RL, Nelson TF. Perception of pain following

aerobic exercise. Med Sci Sports Exerc. 1996;28(11):1418-1421.

429. Meeus M, Roussel NA, Truijen S, Nijs J. Reduced pressure pain thresholds in

response to exercise in chronic fatigue syndrome but not in chronic low back

pain: an experimental study. J Rehabil Med. 2010;42(9):884-890.

430. Ruble SB, Hoffman MD, Shepanski MA, Valic Z, Buckwalter JB, Clifford PS.

Thermal pain perception after aerobic exercise. Arch Phys Med Rehabil.

2005;86(5):1019-1023.

431. Hoeger Bement MK, Rasiarmos RL, DiCapo JM, et al. The role of the menstrual

cycle phase in pain perception before and after an isometric fatiguing

contraction. Eur J Appl Physiol. 2009;106(1):105-112.

432. Kadetoff D, Kosek E. The effects of static muscular contraction on blood

pressure, heart rate, pain ratings and pressure pain thresholds in healthy

individuals and patients with fibromyalgia. Eur J Pain. 2007;11(1):39-47.

433. Koltyn KF, Trine MR, Stegner AJ, Tobar DA. Effect of isometric exercise on

pain perception and blood pressure in men and women. Med Sci Sports Exerc.

2001;33(2):282-290.

232 434. Cook DB, Stegner AJ, Ellingson LD. Exercise alters pain sensitivity in Gulf War

veterans with chronic musculoskeletal pain. J Pain. 2010;11(8):764-772.

435. Drury DG, Greenwood K, Stuempfle KJ, Koltyn KF. Changes in pain perception

in women during and following an exhaustive incremental cycling exercise.

Journal of Sports Science and Medicine. 2005;4:215-222.

436. Kuppens K, Struyf F, Nijs J, et al. Exercise- and stress-induced hypoalgesia in

musicians with and without shoulder pain: A randomized controlled crossover

study. Pain Physician. 2016;19(2):59-68.

437. Henriksen M, Klokker L, Bartholdy C, Graven-Nielsen T, Bliddal H. The

associations between pain sensitivity and knee muscle strength in healthy

volunteers: A cross-sectional study. Pain Res Treat. 2013;2013:787054.

438. Carbonell-Baeza A, Aparicio VA, Sjostrom M, Ruiz JR, Delgado-Fernandez M.

Pain and functional capacity in female fibromyalgia patients. Pain Med.

2011;12(11):1667-1675.

439. de Bruijn ST, van Wijck AJ, Geenen R, et al. Relevance of physical fitness

levels and exercise-related beliefs for self-reported and experimental pain in

fibromyalgia: an explorative study. J Clin Rheumatol. 2011;17(6):295-301.

440. Henriksen M, Lund H, Christensen R, et al. Relationships between the

fibromyalgia impact questionnaire, tender point count, and muscle strength in

female patients with fibromyalgia: a cohort study. Arthritis Rheum.

2009;61(6):732-739.

441. Hooten WM, Rosenberg CJ, Eldrige JS, Qu W. Knee extensor strength is

associated with pressure pain thresholds in adults with fibromyalgia. PLoS One.

2013;8(4):e59930.

233 442. Hooten WM, Smith JM, Eldrige JS, Olsen DA, Mauck WD, Moeschler SM.

Pain severity is associated with muscle strength and peak oxygen uptake in

adults with fibromyalgia. J Pain Res. 2014;7:237-242.

443. Jespersen A, Dreyer L, Kendall S, et al. Computerized cuff pressure algometry:

A new method to assess deep-tissue hypersensitivity in fibromyalgia. Pain.

2007;131(1-2):57-62.

444. Mannerkorpi K, Svantesson U, Broberg C. Relationships between performance-

based tests and patients' ratings of activity limitations, self-efficacy, and pain in

fibromyalgia. Arch Phys Med Rehabil. 2006;87(2):259-264.

445. Soriano-Maldonado A, Ortega FB, Munguia-Izquierdo D. Association of

cardiorespiratory fitness with pressure pain sensitivity and clinical pain in

women with fibromyalgia. Rheumatol Int. 2014;35(5):899-904.

446. Burrows NJ, Jones MD, Sturnieks DL, Booth J, Barry BK. The relationship

between daily physical activity and pain in individuals with knee osteoarthritis.

Unpublished data. 2017.

447. Chmelo E, Nicklas B, Davis C, Miller GD, Legault C, Messier S. Physical

activity and physical function in older adults with knee osteoarthritis. J Phys Act

Health. 2013;10(6):777-783.

448. Connelly AE, Tucker AJ, Kott LS, Wright AJ, Duncan AM. Modifiable lifestyle

factors are associated with lower pain levels in adults with knee osteoarthritis.

Pain Res Manag. 2015;20(5):241-248.

449. Dunlop DD, Semanik P, Song J, et al. Moving to maintain function in knee

osteoarthritis: evidence from the osteoarthritis initiative. Arch Phys Med

Rehabil. 2010;91(5):714-721.

234 450. Dunlop DD, Song J, Semanik PA, et al. Relation of physical activity time to

incident disability in community dwelling adults with or at risk of knee arthritis:

prospective cohort study. BMJ. 2014;348:g2472.

451. Figueiredo Neto EM, Queluz TT, Freire BF. Physical activity and its association

with quality of life in patients with osteoarthritis. Rev Bras Reumatol.

2011;51(6):544-549.

452. Gyurcsik NC, Cary MA, Sessford JD, Flora PK, Brawley LR. Pain anxiety and

negative outcome expectations for activity: Negative psychological profiles

differ between the inactive and active. Arthritis Care Res (Hoboken).

2015;67(1):58-64.

453. Kretzschmar M, Lin W, Nardo L, et al. Association of physical activity

measured by accelerometer, knee joint abnormalities and cartilage T2-

measurements obtained from 3T MRI: Data from the Osteoarthritis Initiative.

Arthritis Care Res (Hoboken). 2015;67(9):1272-1280.

454. Lee J, Chang RW, Ehrlich-Jones L, et al. Sedentary behavior and physical

function: Objective Evidence from the Osteoarthritis Initiative. Arthritis Care

Res (Hoboken). 2015;67(3):366-373.

455. Manheim LM, Dunlop D, Song J, Semanik P, Lee J, Chang RW. Relationship

between physical activity and health-related utility among knee osteoarthritis

patients. Arthritis Care Res (Hoboken). 2012;64(7):1094-1098.

456. Mansournia MA, Danaei G, Forouzanfar MH, et al. Effect of physical activity

on functional performance and knee pain in patients with osteoarthritis: analysis

with marginal structural models. Epidemiology. 2012;23(4):631-640.

235 457. Perrot S, Poiraudeau S, Kabir-Ahmadi M, Rannou F. Correlates of pain intensity

in men and women with hip and knee osteoarthritis. Results of a national survey:

The French ARTHRIX study. Clin J Pain. 2009;25(9):767-772.

458. Robbins SM, Birmingham TB, Callaghan JP, Jones GR, Chesworth BM, Maly

MR. Association of pain with frequency and magnitude of knee loading in knee

osteoarthritis. Arthritis Care Res (Hoboken). 2011;63(7):991-997.

459. Thomas SG, Pagura SM, Kennedy D. Physical activity and its relationship to

physical performance in patients with end stage knee osteoarthritis. J Orthop

Sports Phys Ther. 2003;33(12):745-754.

460. Alnahdi AH, Zeni JA, Snyder-Mackler L. Hip abductor strength reliability and

association with physical function after unilateral total knee arthroplasty: a

cross-sectional study. Phys Ther. 2014;94(8):1154-1162.

461. Baert IA, Staes F, Truijen S, et al. Weak associations between structural changes

on MRI and symptoms, function and muscle strength in relation to knee

osteoarthritis. Knee Surg Sports Traumatol Arthrosc. 2014;22(9):2013-2025.

462. Barker K, Lamb SE, Toye F, Jackson S, Barrington S. Association between

radiographic joint space narrowing, function, pain and muscle power in severe

osteoarthritis of the knee. Clin Rehabil. 2004;18(7):793-800.

463. Costa RA, Oliveira LM, Watanabe SH, Jones A, Natour J. Isokinetic assessment

of the hip muscles in patients with osteoarthritis of the knee. Clinics (Sao

Paulo). 2010;65(12):1253-1259.

464. Dos Santos WT, Rodrigues Ede C, Mainenti MR. Muscle performance, body fat,

pain and function in the elderly with arthritis. Acta Ortop Bras. 2014;22(1):54-

58.

236 465. Javadian Y, Adabi M, Heidari B, et al. Quadriceps muscle strength correlates

with serum vitamin D and knee pain in knee osteoarthritis. Clin J Pain.

2017;33(1):67-70.

466. Kaur N, Verma SK. Quadriceps strength of patients of osteoarthritis knee:

Relationships to pain and disability. JESP. 2005;1(1-2):38-45.

467. Madsen OR, Bliddal H, Egsmose C, Sylvest J. Isometric and isokinetic

quadriceps strength in gonarthrosis; inter-relations between quadriceps strength,

walking ability, radiology, subchondral bone density and pain. Clin Rheumatol.

1995;14(3):308-314.

468. Maly MR, Calder KM, Macintyre NJ, Beattie KA. Relationship of intermuscular

fat volume in the thigh with knee extensor strength and physical performance in

women at risk of or with knee osteoarthritis. Arthritis Care Res (Hoboken).

2013;65(1):44-52.

469. O'Connell M, Farrokhi S, Fitzgerald GK. The role of knee joint moments and

knee impairments on self-reported knee pain during gait in patients with knee

osteoarthritis. Clin Biomech (Bristol, Avon). 2016;31:40-46.

470. Philbin EF, Groff GD, Ries MD, Miller TE. Cardiovascular fitness and health in

patients with end-stage osteoarthritis. Arthritis Rheum. 1995;38(6):799-805.

471. Reid KF, Price LL, Harvey WF, et al. Muscle power is an independent

determinant of pain and quality of life in knee osteoarthritis. Arthritis

Rheumatol. 2015;67(12):3166-3173.

472. Ries MD, Philbin EF, Groff GD. Relationship between severity of gonarthrosis

and cardiovascular fitness. Clin Orthop Relat Res. 1995(313):169-176.

237 473. Santos MLAD, Gomes WF, de Queiroz BZ, et al. Muscle performance, pain,

stiffness, and functionality in elderly women with knee osteoarthritis. Acta

Ortop Bras. 2011;19(4):193-197.

474. Serrao PR, Gramani-Say K, Lessi GC, Mattiello SM. Knee extensor torque of

men with early degrees of osteoarthritis is associated with pain, stiffness and

function. Rev Bras Fisioter. 2012;16(4):289-294.

475. Skou ST, Wrigley TV, Metcalf BR, Hinman RS, Bennell KL. Association of

knee confidence with pain, knee instability, muscle strength, and dynamic varus-

valgus joint motion in knee osteoarthritis. Arthritis Care Res (Hoboken).

2014;66(5):695-701.

476. Steultjens MP, Dekker J, van Baar ME, Oostendorp RA, Bijlsma JW. Muscle

strength, pain and disability in patients with osteoarthritis. Clin Rehabil.

2001;15(3):331-341.

477. Tevald MA, Murray A, Luc BA, Lai K, Sohn D, Pietrosimone B. Hip abductor

strength in people with knee osteoarthritis: A cross-sectional study of reliability

and association with function. Knee. 2016;23(1):57-62.

478. van Baar ME, Dekker J, Lemmens JA, Oostendorp RA, Bijlsma JW. Pain and

disability in patients with osteoarthritis of hip or knee: the relationship with

articular, kinesiological, and psychological characteristics. J Rheumatol.

1998;25(1):125-133.

479. Ball D. Metabolic and endocrine response to exercise: sympathoadrenal

integration with skeletal muscle. J Endocrinol. 2015;224(2):R79-95.

480. Nijs J, Meeus M, Heins M, Knoop H, Moorkens G, Bleijenberg G.

Kinesiophobia, catastrophizing and anticipated symptoms before stair climbing

238 in chronic fatigue syndrome: an experimental study. Disabil Rehabil.

2012;34(15):1299-1305.

481. Wideman TH, Finan PH, Edwards RR, et al. Increased sensitivity to physical

activity among individuals with knee osteoarthritis: Relation to pain outcomes,

psychological factors and responses to quantitative sensory testing. Pain.

2014;155(4):703-711.

482. Holla JF, van der Leeden M, Knol DL, et al. Predictors and outcome of pain-

related avoidance of activities in persons with early symptomatic knee

osteoarthritis: A 5-year follow-up study. Arthritis Care Res (Hoboken).

2015;67(1):48-57.

483. Rabbitts JA, Holley AL, Karlson CW, Palermo TM. Bidirectional associations

between pain and physical activity in adolescents. Clin J Pain. 2014;30(3):251-

258.

484. Arnold JB, Walters JL, Ferrar KE. Does physical activity increase after total hip

or knee arthroplasty for osteoarthritis? A systematic review. J Orthop Sports

Phys Ther. 2016;46(6):431-442.

485. Estevez-Lopez F, Gray CM, Segura-Jimenez V, et al. Independent and

combined association of overall physical fitness and subjective well-being with

fibromyalgia severity: the al-Andalus project. Qual Life Res. 2015;24(8):1865-

1873.

486. Soriano-Maldonado A, Estevez-Lopez F, Segura-Jimenez V, et al. Association

of physical fitness with depression in women with fibromyalgia. Pain Med.

2016;17(8):1542-1552.

239 487. Soriano-Maldonado A, Ruiz JR, Aparicio VA, et al. Association of physical

fitness with pain in women with fibromyalgia: The al-Andalus project. Arthritis

Care Res (Hoboken). 2015;67(11):1561-1570.

488. Suokas AK, Walsh DA, McWilliams DF, et al. Quantitative sensory testing in

painful osteoarthritis: a systematic review and meta-analysis. Osteoarthritis

Cartilage. 2012;20(10):1075-1085.

489. Rakel B, Vance C, Zimmerman MB, Petsas-Blodgett N, Amendola A, Sluka

KA. Mechanical hyperalgesia and reduced quality of life occur in people with

mild knee osteoarthritis pain. Clin J Pain. 2015;31(4):315-322.

490. Henriksen M, Klokker L, Graven-Nielsen T, et al. Exercise therapy reduces pain

sensitivity in patients with knee osteoarthritis: A randomized controlled trial.

Arthritis Care Res (Hoboken). 2014;66(12):1836-1843.

491. Ote Karaca S, Demirsoy N, Gunendi Z. Effects of aerobic exercise on pain

sensitivity, heart rate recovery, and health-related quality of life in patients with

chronic musculoskeletal pain [epub ahead of print]. Int J Rehabil Res. 2016:doi:

10.1097/mrr.0000000000000212.

492. Agarwal N, Pacher P, Tegeder I, et al. Cannabinoids mediate analgesia largely

via peripheral type 1 cannabinoid receptors in nociceptors. Nat Neurosci.

2007;10(7):870-879.

493. Scherrer G, Imamachi N, Cao YQ, et al. Dissociation of the opioid receptor

mechanisms that control mechanical and heat pain. Cell. 2009;137(6):1148-

1159.

494. Peters ML. Emotional and Cognitive Influences on Pain Experience. Mod

Trends Pharmacopsychiatri. 2015;30:138-152.

240 495. Perrot S, Trouvin AP, Rondeau V, et al. Kinesiophobia and physical therapy

related-pain in musculoskeletal pain: A national multicenter cohort study on

patients and their general physicians [epub ahead of print]. Joint Bone Spine.

2017:doi: 10.1016/j.jbspin.2016.1012.1014.

496. Van Oosterwijck J, Meeus M, Paul L, et al. Pain physiology education improves

health status and endogenous pain inhibition in fibromyalgia: a double-blind

randomized controlled trial. Clin J Pain. 2013;29(10):873-882.

497. Van Oosterwijck J, Nijs J, Meeus M, et al. Pain neurophysiology education

improves cognitions, pain thresholds, and movement performance in people with

chronic whiplash: a pilot study. J Rehabil Res Dev. 2011;48(1):43-58.

498. Gandevia SC, Burke D, McKeon B. The projection of muscle afferents from the

hand to cerebral cortex in man. Brain. 1984;107 (Pt 1):1-13.

499. Han SE, Lin CS, Boland RA, Bilston LE, Kiernan MC. Changes in human

sensory axonal excitability induced by focal nerve compression. J Physiol.

2010;588(Pt 10):1737-1745.

241 Appendices

Appendix A: Script for the education of healthy participants, including explicit description of exercise-induced hypoalgesia

Participant has been deemed eligible to participate in the study and arrives at the clinic and informed consent and introduction formalities are completed.

Pain education (10-15 min) script

Experimenter: “Can you tell me what type of exercise, if any, you regularly participate in and how often?”

Participant responds:

Experimenter: Summarise key points about modality and frequency and then ask:

“Have you ever engaged in exercise that is intense enough to cause pain during or immediately following the exercise?”

Participant responds:

Experimenter: Summarise relevant information and add:

“Muscle pain during and immediately following strenuous exercise is called acute muscle soreness and generally disappears shortly after finishing exercise. The pain is the result of end products of energy metabolism, often referred to as ‘metabolites’ and one of these you might have heard of is . The increase in these metabolites in our muscles sends pain signals to the brain, which eventually contribute to feeling exhausted from exercise. The feeling of exhaustion prompts us to rest and to let our

242 muscles recover. So the pain during exercise has a role to protect us from exercising for too long or too hard. Are you familiar with this type of muscle pain during exercise?”

Participant responds:

Experimenter: Summarise relevant information and add:

“Another type of muscle pain that occurs after strenuous or unaccustomed exercise or physical activity is termed delayed onset muscle soreness, or DOMS. The pain associated with DOMS often gets worse in the 48-72 hours following exercise before slowly reducing. The pain is thought to be caused by micro trauma to the muscle fibres.

You’re particularly likely to get DOMS if you’ve been walking or running up and down hills. Have you ever experienced DOMS?”

Participant responds:

Experimenter: Respond to the participant’s answer and add:

“While DOMS can be quite painful, the muscles adapt quickly. If you get DOMS once from some exercise you probably won’t get DOMS the second time you do that exercise

– or at least not nearly so bad. It just indicates that our muscles are repairing after some unaccustomed exercise and are getting stronger. While most people know about how good regular exercise is for things like managing weight, improving lung and heart function, and even our mood, what we are starting to learn is that even a single bout of exercise can provide physical and psychological benefits. Have you come across much information about the benefits of just a single bout of exercise?

Participant responds:

243 Experimenter: summarises key points raised by the participant and affirms these with the participant:

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Yes, some research has shown that even short bouts of exercise, as little as 10-20 minutes, can improve fitness, health and wellbeing. However, some people who decide to commence more strenuous exercise experience acute muscle soreness or DOMS and this often discourages them from further participation in exercise. This study that you have volunteered to take part in is about pain during a bout of normal intensity exercise for 20 min and requires me to explain a bit more to you about pain during this type of exercise. I’ll start by asking you a question. When you exercise, how do you determine if it is safe to continue if your pain increases or do you see the increase in pain as an indication to stop?”

Participant responds:

Experimenter: summarise any relevant information provided and then:

“It’s normal to feel an increase in discomfort during exercise and this is not an indication that you are causing further damage to the muscle or that you are hurting yourself. It is safe to continue to exercise when the increases in pain you experience are tolerable and feel manageable. This discomfort should level out during exercise and reduce shortly after you finish. If you feel the muscles are getting too tired or hurting too much during the exercise, then you should just drop the intensity slightly back to an easier level. You can apply this to the exercise bout you are about to undertake for this

244 study. Before we continue, do you have any questions about pain and discomfort during exercise?”

Participant responds:

Experimenter: Answers any of the questions raised by the participant and then:

“I would now like to quickly talk about how levels of pain and exertion are typically measured during exercise. Do you know anything about this?”

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Because pain and exertion are both subjective sensations, they are normally assessed using self-report scales. For example, I might ask you to rate your pain during exercise on a 0 to 10 scale whereby 0 is no pain and 10 is the worst possible pain. I could use a similar scale to ask you about your level of exertion during exercise, and this information would be useful for me to know how hard you are finding the exercise.

Have you used these types of scales before?”

Participant responds:

Experimenter: Answers any of the questions raised by the participant and then:

“The next thing I would like to discuss is something called exercise-induced hypoalgesia. Do you know anything about this?

Participant responds:

245 Experimenter: Acknowledges any key points and then, with the aid of Figure A

(Appendix B), provides the following explanation:

“Exercise-induced hypoalgesia refers to a decrease in pain following exercise. A lot of studies show that this happens in both men and women and can last for about 30 minutes following exercise. So, when we ask a person to rate their level of pain before exercise it is typical that their rating of pain after exercise has dropped. This can happen following walking, cycling, running or weight training exercise and it tends to happen more if we exercise longer or harder. We don’t know exactly what causes exercise-induced hypoalgesia, but it seems to involve the release of substances within the body that reduce pain. Endorphins or natural opioids are the most obvious example that you might have heard of. Have you heard of endorphins?”

Participant responds:

Experimenter: Acknowledges any key points and then, with the aid of Figure A

(Appendix B):

“These endorphins, along with other changes that occur with exercise, act to reduce the pain signals sent from the exercising muscles to the brain. The end result of this is that you experience less pain. This exercise analgesia might be why exercise is such an effective treatment for people with chronic pain. It’s kind of a neat thing that the body becomes a little less sensitive to pain during exercise as it helps us to keep moving longer and to work harder. It’s really cool that this effect lasts for a bit after we stop exercising, kind of like taking a painkiller. Do you have any questions about exercise- induced hypoalgesia?”

Participant responds:

246 [Experimenter presents and explains Figure A (Appendix B) of how exercise might act at various points in the pain pathway to reduce pain]

Experimenter: Responds to any questions then:

“Okay, well it’s good that you are now a little more familiar with some of the causes of pain during exercise as well as how exercise can reduce pain and how this might be measured as you are going to be asked to rate these sensations when you are exercising later on. Is it ok if I summarise the key points we talked about before we commence exercise?”

[Key points on a card]:

• It is normal to experience some muscle pain and discomfort during and for a

short time following exercise and pain during exercise doesn’t mean that you are

causing lasting damage or injury.

• It is also normal to experience longer lasting muscle pain, or DOMS, after

intense or unaccustomed exercise, but the muscles gradually adapt to this and

the pain subsides

• During exercise at an intensity that causes some discomfort, tolerable increases

in pain are normal and safe.

• Exercise-induced hypoalgesia is a reduction in pain that occurs after exercise

and this can last for up to 30 min following exercise. It is common to experience

exercise-induced hypoalgesia following aerobic exercise like walking and

cycling, particularly when exercise is performed at higher intensities

247 “I just have a few final questions before we go on with the rest of the experiment.

[Experimenter presents the 5 questions (Appendix E) and asks the participant to indicate their level of agreement with each question. The experimenter then circles their response]

Experimenter: “Thank you. Do you have any questions before we commence?”

Participant responds:

Experimenter: “Alright, well I hope that information was useful for you and that you have learned something about pain during exercise as well as how exercise can help to acutely reduce pain. Now I would just like to quickly explain what is going to happen for the rest of the experiment, after which I will hand over to one of my colleagues who will take you through the exercise bout and some pain assessments.”

Following description of experimental procedures:

Experimenter: “Thank you again for your time and for agreeing to participate in this study. I will leave you with my colleague and see you again when you’re done.”

248 Appendix B: Figure A – used to describe exercise-induced hypoalgesia to participants in the intervention group

249 Appendix C: Script for the education of healthy participants, excluding explicit description of exercise-induced hypoalgesia

Participant has been deemed eligible to participate in the study and arrives at the clinic and informed consent and introduction formalities are completed.

Pain education (10-15 min) script

Experimenter: “Can you tell me what type of exercise, if any, you regularly participate in and how often?”

Participant responds:

Experimenter: Summarise key points about modality and frequency and then ask:

“Have you ever engaged in exercise that is intense enough to cause pain during or immediately following the exercise?”

Participant responds:

Experimenter: Summarise relevant information and add:

“Muscle pain during and immediately following strenuous exercise is called acute muscle soreness and generally disappears shortly after finishing exercise. The pain is the result of end products of energy metabolism, often referred to as ‘metabolites’ and one of these you might have heard of is lactic acid. The increase in these metabolites in our muscles sends pain signals to the brain, which eventually contribute to feeling exhausted from exercise. The feeling of exhaustion prompts us to rest and to let our muscles recover. So the pain during exercise has a role to protect us from exercising for too long or too hard. Are you familiar with this type of muscle pain during exercise?”

250 Participant responds:

Experimenter: Summarise relevant information and, with the aid of Figure B

(Appendix D), adds:

“Another type of muscle pain that occurs after strenuous or unaccustomed exercise or physical activity is termed delayed onset muscle soreness, or DOMS. The pain associated with DOMS often gets worse in the 24-72 hours following exercise before slowly reducing. The pain is thought to be caused by micro trauma to the muscle fibres.

You’re particularly likely to get DOMS if you’ve been walking or running up and down hills. Have you ever experienced DOMS?”

Participant responds:

Experimenter: Responds to the participant’s answer and adds:

“While DOMS can be quite painful, the muscles adapt quickly. If you get DOMS once from some exercise you probably won’t get DOMS the second time you do that exercise

– or at least not nearly so bad. It just indicates that our muscles are repairing after some unaccustomed exercise and are getting stronger. While most people know about how good regular exercise is for things like managing weight, improving lung and heart function, and even our mood, what we are starting to learn is that even a single bout of exercise can provide physical and psychological benefits. Have you come across much information about the benefits of just a single bout of exercise?

Participant responds:

251 Experimenter: summarises key points raised by the participant and affirms these with the participant:

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Yes, some research has shown that even short bouts of exercise, as little as 10-20 minutes, can improve fitness, health and wellbeing. However, some people who decide to commence more strenuous exercise experience acute muscle soreness or DOMS and this often discourages them from further participation in exercise. This study that you have volunteered to take part in is about pain during a bout of normal intensity exercise for 20 min and requires me to explain a bit more to you about pain during this type of exercise. I’ll start by asking you a question. When you exercise, how do you determine if it is safe to continue if your pain increases or do you see the increase in pain as an indication to stop?”

Participant responds:

Experimenter: summarise any relevant information provided and then:

“It’s normal to feel an increase in discomfort during exercise and this is not an indication that you are causing further damage to the muscle or that you are hurting yourself. It is safe to continue to exercise when the increases in pain you experience are tolerable and feel manageable. This discomfort should level out during exercise and reduce shortly after you finish. If you feel the muscles are getting tired or hurting too much during the exercise, then you should just drop the intensity slightly back to an easier level. You can apply this to the exercise bout you are about to undertake for this

252 study. Before we continue, do you have any questions about pain and discomfort during exercise?”

Participant responds:

Experimenter: Answers any of the questions raised by the participant and then:

“I would now like to quickly talk about how levels of pain and exertion are typically measured during exercise. Do you know anything about this?”

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Because pain and exertion are both subjective sensations, they are normally assessed using self-report scales. For example, I might ask you to rate your pain during exercise on a 0 to 10 scale whereby 0 is no pain and 10 is the worst possible pain. I could use a similar scale to ask you about your level of exertion during exercise, and this information would be useful for me to know how hard you are finding the exercise.

Have you used these types of scales before?”

Participant responds:

“Another useful aspect of these types of scales is that they can be used to assess different aspects of pain such as pain intensity and pain unpleasantness. Pain intensity describes how strong the pain is whereas pain unpleasantness describes how bothersome it is and just because something is intense, that doesn’t necessarily mean that it is bothersome and vice versa. For example, you might find the pain from a hard massage to be quite intense but not necessarily unpleasant. There is some interesting research in athletes using these different types of pain ratings showing that sportsmen

253 and women typically have lower ratings of pain unpleasantness and higher pain tolerances compared to non-athletes. Basically, athletes find things to be just as painful but are willing to tolerate them for longer. This is probably a big part of why endurance athletes like marathon runners and cyclists are able to exercise at high intensities for so long. Now I don’t wish to create an impression that with exercise we can all become stoical like elite athletes and learn to ignore pain. The point is simply that we recognise the different aspects of the pain experience and how these interact with exercise. Do you have any questions about this?”

Participant responds:

Experimenter: summarises key points raised by the participant and then:

“Okay, well it’s good that you are now a little more familiar with some of the causes of pain during exercise as well as how pain and exertion are measured during exercise as you are going to be asked to rate these sensations later on when you are exercising. Is it okay if I summarise the key points we talked about before we commence exercise?”

[Key points on a card]:

• It is normal to experience some muscle pain and discomfort during and for a

short time following exercise and pain during exercise doesn’t mean that you are

causing lasting damage or injury.

• It is also normal to experience longer lasting muscle pain, or DOMS, after

intense or unaccustomed exercise, but the muscles gradually adapt to this and

the pain subsides

254 • During exercise at an intensity that causes some discomfort, tolerable increases

in pain are normal and safe. We can monitor these increases in pain and

discomfort during exercising using self-report scales.

“I just have a few final questions before we go on with the rest of the experiment.

[Experimenter presents the 5 questions (Appendix E) and asks the participant to indicate their level of agreement with each question. The experimenter then circles their response]

Experimenter: “Thank you. Do you have any questions before we commence?”

Participant responds:

Experimenter: “Alright, well I hope that information was useful for you and that you have learned something about pain during exercise. Now I would just like to quickly explain what is going to happen for the rest of the experiment, after which I will hand over to one of my colleagues who take you through the exercise bout and pain assessments.”

Following description of experimental procedures:

Experimenter: “Thank you again for your time and for agreeing to participate in this study. I will leave you with my colleague and see you again when you’re done.”

255 Appendix D: Figure B – used to describe delayed onset muscle soreness to participants in the control group

256 Appendix E: Questions to assess the participant’s knowledge and beliefs about exercise and pain arising from the education intervention

Questions to participant:

1) Exercise is always painful:

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

2) There can be good pain and bad pain during exercise:

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

257 3) Regular exercise can help reduce pain:

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

4) Pain can be reduced from just one session of exercise

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

258 5) The information you have just given me has changed what I thought about the effect of exercise on pain:

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

259 Appendix F: Questions for experimenter’s appraisal of the participant’s engagement in, and understanding of, the education intervention

1) The participant engaged in the discussion about exercise and pain.

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

2) The participant understood the information that was being presented to them.

Strongly agree

Agree

Somewhat agree

Neutral

Somewhat disagree

Disagree

Disagree strongly

260 Appendix G: Script for education of people with fibromyalgia or osteoarthritis, including explicit description of exercise-induced hypoalgesia

Participant has been deemed eligible to participate in the study and arrives at the clinic.

Introduction formalities and informed consent are completed.

Pain education script (10-15 min)

Experimenter: “Can you give me some understanding of how much pain impacts on your daily life; work, social activities, recreation, exercise”

Participant responds:

Experimenter: Summarise key points raised by the participant then:

“Yes, pain can have a big impact on people’s lives and make it hard to do the things that you need to do, let alone participating in regular exercise like walking or swimming. Is there any type of exercise that you regularly participate in?”

Participant responds:

Experimenter: Summarise the participant’s relevant points and then:

“You know the funny thing is that while most people know about how good regular exercise is for things like managing weight, improving lung and heart function, and even our mood, we are starting to learn more about the benefits of exercise for chronic pain like osteoarthritis/fibromyalgia. Have you come across much information about the benefits of exercise for chronic pain?”

Participant responds:

261 Experimenter: summarises key points raised by the participant and then:

“One of the most important benefits of exercise for people with osteoarthritis/ fibromyalgia is that it can reduce pain. Have you heard anything about this?”

Participant responds:

Experimenter: reflects on relevant points the participant has raised and then:

“To describe the research about how exercise influences pain requires me to explain a bit more to you about pain and exercise. The first thing I would like to discuss is pain during exercise. When you exercise and your pain increases, can you tell me how you determine if it is safe for you to continue or if the pain is an indication that you should stop?”

Participant responds:

Experimenter: summarise any relevant points then, with the aid of Figure C (Appendix

I), adds:

“It’s normal to feel an increase in discomfort/pain during exercise. This is not an indication that you are causing further damage to the muscle or that you are hurting yourself. It is safe to continue to exercise when the increases in pain you experience are tolerable and feel manageable. This discomfort should level out during exercise and reduce shortly after you finish. If you feel your muscles are getting tired or hurting too much during the exercise, then you should just drop the intensity slightly back to an easier level. Does any of this sound like how you deal with pain during exercise?

Participant responds:

262 Experimenter: reflects on relevant points the participant has raised and then:

“Taking this approach to pain during exercise seems to be the most beneficial for people with chronic pain and I would encourage you to apply this approach to the exercise bout you are about to complete for this study. By exercising with some degree of pain or discomfort at a safe and low level you can manage to maintain or get back to normal levels of activity and to improve your general quality of life. Before we continue, do you have any questions about pain and discomfort during exercise?”

Participant responds:

Experimenter: answers any of the questions raised by participant and then:

“So I mentioned before that exercise can reduce pain from osteoarthritis and fibromyalgia. This benefit of exercised comes after weeks and months of regular exercise. It can be as effective as taking a pain medication, which also has to be done consistently to reduce pain. Here, I’ll show you some data pulled together from many scientific studies to demonstrate the benefit of exercise. For osteoarthritis, the evidence of the benefits of exercise has been known since 2002!”

[Experimenter presents and explains Figures D and E (Appendix J and K, respectively) for participants with osteoarthritis or Figures F and G (Appendix L and M, respectively) for participants with fibromyalgia]

“Do you have any questions about these graphs?”

Participant responds:

263 Experimenter: Answers any of the questions raised by the participant and then:

“The next point I would like to discuss is something called exercise-induced hypoalgesia. Do you know anything about this?

Participant responds:

Experimenter: Acknowledges any key points and then, with the aid of Figure A

(Appendix B), provides the following explanation:

“Exercise-induced hypoalgesia refers to a decrease in pain following exercise. So, when we ask a person to rate their level of pain before exercise it is typical that their rating of pain after exercise has dropped, particularly if they exercised a little harder or for a little longer. This reduction in pain has been shown for people with osteoarthritis and people with fibromyalgia and lasts for a bit after we stop exercising; it’s kind of like taking a painkiller. It’s also a clue as to why exercise is one of the most effective ways to manage pain from osteoarthritis or fibromyalgia. Now that I have explained a little more about it, do you think that exercise-induced hypoalgesia is something you have ever experienced?

Participant responds:

Experimenter: Acknowledges any key points and, with the aid of Figure A (Appendix

B), relays the following:

We don’t know exactly what causes exercise-induced hypoalgesia, but it seems to involve the release of substances within the body that reduce pain. Endorphins or natural opioids are the most obvious example that you might have heard of. These endorphins, along with other changes that occur with exercise, act to reduce the pain signals sent from the exercising muscles to the brain. The end result of this is that you

264 experience less pain. It’s kind of a neat thing that the body becomes a little less sensitive to pain during exercise as it helps us to keep moving longer and to work harder. Do you have any questions about exercise-induced hypoalgesia?”

Participant responds:

Experimenter: Answers any of the questions raised by the participant and then:

“I would now like to talk about how levels of pain and exertion are typically measured during exercise. Do you know anything about this?”

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Because pain and exertion are both subjective sensations, they are normally assessed using self-report scales. For example, I might ask you to rate your pain during exercise on a 0 to 10 scale whereby 0 is no pain and 10 is the worst possible pain. I could use a similar scale to ask you about your level of exertion during exercise, and this information would be useful for me to gauge how hard you are finding the exercise.

Have you used these types of scales before?”

Participant responds:

Experimenter: Reflects on relevant points and then:

“Okay well it’s good that you are now a little more familiar with what is considered safe and tolerable levels of pain and discomfort during exercise as well as how these are measured so you can apply this to the exercise bout later on. Now I will just summarise the key points we have talked about before we go on with the rest of the experiment, if that is okay?”

265 [Key points on a card]:

• Exercise is strongly recommended for people with osteoarthritis and people with

fibromyalgia because of its physical and psychological benefits, including pain

management

• Pain during exercise doesn’t mean you that are causing further damage to your

muscles or joints. A small increase in pain/discomfort during exercise that levels

off and then reduces shortly after exercise is a common and normal response

when people with osteoarthritis or fibromyalgia exercise

• Exercise-induced hypoalgesia is a reduction in pain that occurs after exercise

and this can last for up to 30 min following exercise. It is common to experience

exercise-induced hypoalgesia following aerobic exercise like walking and

cycling, particularly when exercise is performed at slightly higher intensities.

This is the same for people with osteoarthritis fibromyalgia and as well.

“I just have a few final questions before we go on with the rest of the experiment.

[Experimenter presents the 5 questions (Appendix E) and asks the participant to indicate their level of agreement with each question. The experimenter then circles their response]

Experimenter: “Thank you. Do you have any questions before we commence?”

Participant responds:

266 Experimenter: “Alright, well I hope that information was useful for you and that you have learned something about pain during exercise. Now I would just like to quickly explain what is going to happen for the rest of the experiment, after which I will hand over to one of my colleagues who will take you through the exercise bout and some pain assessments.”

Following explanation of experimental procedures:

Experimenter: “Thank you again for your time and for agreeing to participate in this study. I will leave you with my colleague and see you again when you’re done.”

267 Appendix H: Script for education of people with fibromyalgia or osteoarthritis, excluding explicit description of exercise-induced hypoalgesia

Participant has been deemed eligible to participate in the study and arrives at the clinic.

Introduction formalities and informed consent are completed.

Pain education script (10-15 min)

Experimenter: “Can you give me some understanding of how much pain impacts on your daily life; work, social activities, recreation, exercise”

Participant responds:

Experimenter: Summarise key points raised by the participant then:

“Yes, pain can have a big impact on people’s lives and make it hard to do the things that you need to do, let alone participating in regular exercise like walking or swimming. Is there any type of exercise that you regularly participate in?”

Participant responds:

Experimenter: Summarise the participant’s relevant points and then:

“You know the funny thing is that while most people know about how good regular exercise is for things like managing weight, improving lung and heart function, and even our mood, we are starting to learn more about the benefits of exercise for chronic pain like osteoarthritis/fibromyalgia. Have you come across much information about the benefits of exercise for chronic pain?”

Participant responds:

268 Experimenter: summarises key points raised by the participant and then:

“One of the most important benefits of exercise for people with osteoarthritis/ fibromyalgia is that it can reduce pain. Have you heard anything about this?”

Participant responds:

Experimenter: reflects on relevant points the participant has raised and then:

“To describe the research about how exercise influences pain requires me to explain a bit more to you about pain and exercise. The first thing I would like to discuss is pain during exercise. When you exercise and your pain increases, can you tell me how you determine if it is safe for you to continue or if the pain is an indication that you should stop?”

Participant responds:

Experimenter: summarise any relevant points then, with the aid of Figure C (Appendix

I), adds:

“It’s normal to feel an increase in discomfort or pain during exercise. This is not an indication that you are causing further damage to the muscle or that you are hurting yourself. It is safe to continue to exercise when the increases in pain you experience are tolerable and feel manageable. This discomfort should level out during exercise and reduce shortly after you finish. If you feel the muscles are getting tired or hurting too much during the exercise, then you should just drop the intensity slightly back to an easier level. Does any of this sound like how you deal with pain during exercise?

Participant responds:

269 Experimenter: reflects on relevant points the participant has raised and then:

“Taking this approach to pain during exercise seems to be the most beneficial for people with chronic pain. I would encourage you to apply this approach to the exercise bout you are about to complete for this study. By exercising with some degree of pain or discomfort at a safe and low level you can manage to maintain or get back to normal levels of activity and to improve your general quality of life. Before we continue, do you have any questions about pain and discomfort during exercise?”

Participant responds:

Experimenter: answers any of the questions raised by participant and then:

“So, I mentioned before that exercise can reduce pain from osteoarthritis and fibromyalgia. This benefit of exercised comes after weeks and months of regular exercise. It can be as effective as taking a pain medication, which also has to be done consistently to reduce pain. Here, I’ll show you some data pulled together from many scientific studies to demonstrate the benefit of exercise. For osteoarthritis, the evidence of the benefits of exercise has been known since 2002!”

[Experimenter presents and explains Figures D and E (Appendix J and K, respectively) for participants with osteoarthritis or Figures F and G (Appendix L and M, respectively) for participants with fibromyalgia]

“Do you have any questions about these graphs?”

Participant responds:

270 Experimenter: Answers any of the questions raised by the participant and then:

“I would now like to talk about how levels of pain and exertion are typically measured during exercise. Do you know anything about this?”

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Because pain and exertion are both subjective sensations, they are normally assessed using self-report scales. For example, I might ask you to rate your pain during exercise on a 0 to 10 scale whereby 0 is no pain and 10 is the worst possible pain. I could use a similar scale to ask you about your level of exertion during exercise, and this information would be useful for me to gauge how hard you are finding the exercise.

Have you used these types of scales before?”

Participant responds:

Experimenter: reflects on any relevant points the participant has raised and then:

“Another useful aspect of these types of scales is that they can be used to assess different aspects of pain such as pain intensity and pain unpleasantness. Pain intensity describes how strong the pain is whereas pain unpleasantness describes how bothersome it is. Now, just because something is intense, that doesn’t necessarily mean that it is bothersome and vice versa. For example, you might find the pain from a hard massage to be quite intense but not necessarily unpleasant. There is some interesting research in athletes using these different types of pain scales showing that sportsmen and women typically have lower ratings of pain unpleasantness and higher pain tolerances compared to non-athletes. Basically, athletes find things to be just as painful but are willing to tolerate them for longer. This is probably a big part of why endurance

271 athletes like marathon runners and cyclists are able to exercise at high intensities for so long. Now I don’t wish to create an impression that with exercise we can all become stoical like elite athletes and learn to ignore pain. The point is simply that we recognise the different aspects of the pain experience and how these interact with exercise. Do you have any questions about this?”

Participant responds:

Experimenter: summarises key points raised by the participant and then:

“Okay well it’s good that you are now a little more familiar with what is considered safe and tolerable levels of pain and discomfort during exercise as well as how these are measured because you are going to be asked to rate these sensations during exercise later on. Now I will just summarise the key points we have talked about before we go on with the rest of the experiment, if that is okay?”

[Key points on a card]:

• Exercise is strongly recommended for people with osteoarthritis and people with

fibromyalgia because of its physical and psychological benefits, including pain

management

• Pain during exercise doesn’t mean you that are causing further damage to your

muscles or joints. A small but tolerable increase in pain/discomfort during

exercise that levels off and then reduces shortly after exercise is a common and

normal response when people with chronic pain such as osteoarthritis or

fibromyalgia exercise

272 • During exercise at an intensity that causes some discomfort, tolerable increases

in pain are normal and safe. We can monitor these increases in pain and

discomfort during exercising using self-report scales.

“I just have a few final questions before we go on with the rest of the experiment.

[Experimenter presents the 5 questions (Appendix E) and asks the participant to indicate their level of agreement with each question. The experimenter then circles their response]

Experimenter: “Thank you. Do you have any questions before we commence?”

Participant responds:

Experimenter: “Alright, well I hope that was useful for you and that you have learned something about pain during exercise. Now I would just like to quickly explain what is going to happen for the rest of the experiment, after which I will hand over to one of my colleagues who will take you through the exercise bout and some pain assessments.”

Following explanation of experimental procedures:

Experimenter: “Thank you again for your time and for agreeing to participate in this study. I will leave you with my colleague and see you again when you’re done.”

273 Appendix I: Figure C – used to describe good/appropriate pain and bad/inappropriate pain

274 Appendix J: Figure D – used to show that being fitter is associated with less pain in people with knee osteoarthritis

275 Appendix K: Figure E – used to show that different types of exercise reduce pain in people with knee osteoarthritis (top panel), regardless of intensity (bottom panel)

276 Appendix L: Figure F – used to show that being more physically active and fit is associated with less pain in people with fibromyalgia

277 Appendix M: Figure G – used to show that aerobic and strength exercise reduce pain in people with fibromyalgia

278 Appendix N: Quality assessment of studies in the literature synthesis of the associations between physical activity and fitness with pain

in healthy individuals.

Power Valid and reliable Biological/physical Psychological Statistical tests calculation measures confounders: confounders: accounted for accounted for measured measured in analysis in analysis Physical activity Ellingson et al, 2012 N Y Y N Y Y Spearman’s correlation and regression analysis Lemming et al, 2015 Y Y N N N N T-test and analysis of variance

279 McLoughlin et al, N Y N N N N Pearson’s correlation and

2011 regression analysis Naugle et al, 2014 N Y Y Y Y Y Spearman’s correlation and hierarchical linear regression Umeda et al, 2016 Y Y Y N N N Analysis of variance

Physical Fitness Henriksen et al, 2013 N Y Y Y N N Pearson’s correlation, univariable and multivariable regression Jones et al, 2016 Y Y Y Y Y N Pearson’s correlation Biological/physical confounders included: age, BMI, sex and/or medications. Psychological confounders included depression and/or self-efficacy.

279 Appendix O: Quality assessment of studies in the literature synthesis of the associations between physical activity and fitness with pain in

people with fibromyalgia.

Power FM diagnosis Valid and reliable Biological/physical Psychological Statistical tests calculation measures confounders: confounders: accounted for accounted for measured measured in analysis in analysis Physical Activity Ellingson et al, 2012 N Patient’s care Y Y Y N N Pearson’s correlation and provider regression analysis McLoughlin et al, N Physician Y Y N N N Pearson’s correlation and 2011 regression analysis

280 Physical Fitness

Carbonell-Baeze et N Self-report medical Y N N N N Spearman’s correlation al, 2011 diagnosis de Bruijn et al, 2011 Y Rheumatologist Y Y N Y N Spearman’s correlation Henrisken et al, 2009 N Rheumatologist Y Y N N N Pearson’s correlation and multivariable regression Hooten et al 2013 N Rheumatologist Y Y Y N N Univariable and multivariable regression Hooten et al 2014 N Rheumatologist Y Y Y N N Univariable and multivariable regression Jespersen et al, 2007 N Rheumatologist Y Y N Y N Pearson’s correlation

280

Mannerkorpi et al, N Self-report medical Y Y N Y N Spearman’s correlation 2006 diagnosis Soriano-Maldonado N Self-report medical Y Y Y N N Pearson’s correlation and et al, 2014 diagnosis multivariable regression Biological/physical confounders included: age, BMI, sex, medications and/or disease severity. Psychological confounders included depression and/or self-efficacy. 281

281 Appendix P: Quality assessment of studies in the literature synthesis of the associations between physical activity and fitness with pain in

people with knee osteoarthritis.

Power OA diagnosis Valid and reliable Biological/physical Psychological Statistical tests calculation measures confounders: confounders: accounted for accounted for measured measured in analysis in analysis Burrows et al 2017 Y Self-report medical Y Y N Y N Pearson’s correlation (unpublished data) diagnosis Chmelo et al 2013 N Physician Y Y Y N N Pearson’s correlation and stepwise regression Connelly et al 2015 N Physician N (physical Y Y N N Multiple linear regression and activity) group comparison 282 Dunlop et al 2010 N Physician Y Y Y Y Y Logistic regression

Dunlop et al 2014 N Physician Y Y Y N N Linear regression Figueiredo et al 2011 N Rheumatologist Y N N N N Pearson’s correlation and linear regression Gyurcsik et al 2015 N Self-report medical N (physical Y Y Y Y Group comparison (ANOVA diagnosis activity) and MANOVA) Kretzschmar et al N Physician Y Y Y N N Multiple linear regression 2015 Lee et al 2015 N Physician Y Y Y N N Multiple linear regression Manheim et al, 2012 N Physician Y Y Y N N Generalised estimating regression analysis

282 Mansournia et al N Physician Y Y Y Y Y Marginal structural modelling 2012 Perrot et al 2003 N Self-report medical N (physical Y Y N N Linear regression and odds diagnosis activity) ratios Robbins et al 2011 N Physician Y Y Y N N Pearson’s correlation and linear regression Thomas et al 2003 Y Surgeon Y Y N N N Pearson’s correlation Notation in parentheses specifies the measured deemed to lack validity and reliability. Biological/physical confounders included: age, BMI, sex, medications and/or disease severity. Psychological confounders included depression and/or self-efficacy. 283

283

Appendix Q: Quality assessment of studies in the systematic review and meta-analyses of the effect of acute aerobic and isometric

exercise on pain in people with fibromyalgia

Power FM diagnosis Valid and reliable Biological/physical Psychological Statistical tests calculation measures confounders: confounders: accounted for accounted for measured measured in analysis in analysis Aerobic exercise Ellingson et al, 2016 N Physician Y Y N N N Effect sizes (Cohen’s d) and analysis of variance Newcomb et al, 2011 Y 1990 ACR criteria Y Y N Y N Effect sizes (Cohen’s d) and analysis of variance Staud et al, 2010 N 1990 ACR criteria Y Y Y N N Analysis of variance 284 Vierck et al, 2001 N 1990 ACR criteria Y Y N N N Analysis of variance

Isometric exercise Ge et al, 2012 Y 1990 ACR criteria Y N N N N Analysis of variance and Pearson’s correlation Hoeger Bement et al, N Not specified Y Y Y Y Y Analysis of variance, 2011 Pearson’s correlation and stepwise multiple regression Hoeger Bement et al, Y Rheumatologist Y N N N N Analysis of variance and 2014 Pearson’s correlation

284

Kadetoff & Kosek, 1990 ACR criteria Y N N N N Analysis of variance and 2007 Spearman' rank order correlation Lannersten & Kosek, N 1990 ACR criteria Y Y N N N Analysis of variance 2010 Staud et al, 2005 N Not specified Y Y N Y N Analysis of variance Biological/physical confounders included medications and/or disease severity. Psychological confounders included depression, anxiety and/or kinesiophobia. Abbreviations: ACR = American College of Rheumatology 285

285

Appendix R: Quality assessment of studies in the systematic review and meta-analyses of the effect of acute aerobic and isometric

exercise on pain in people with knee osteoarthritis

Power OA diagnosis Valid and reliable Biological/physical Psychological Statistical tests calculation measures confounders: confounders: accounted accounted for measured measured for in in analysis analysis Aerobic exercise Fingleton et al, Y ACR classification Y Y Y Y N Analysis of variance 2016 and pain > 3/10 Vaegter et al, 2016 Radiograph and Y Y N Y N Effect sizes (Cohen’s d), orthopaedic analysis of variance and 286 surgeon Pearson’s correlation

Resistance exercise Burrows et al, 2014 Y Self-report medical Y Y N N N Effect sizes (Cohen’s d) and diagnosis analysis of variance Fingleton et al, Y ACR classification Y Y Y Y N Analysis of variance 2016 and pain > 3/10 Germanou et al, Y Not specified Y Y N N N Analysis of variance 2013 Vaegter et al, 2016 Radiograph and Y Y N Y N Effect sizes (Cohen’s d), orthopaedic analysis of variance and surgeon Pearson’s correlation Biological/physical confounders included medications and/or disease severity. Psychological confounders included depression, anxiety, self-efficacy and/or kinesiophobia. Abbreviations: ACR = American College of Rheumatology.

286