An Evaluation of the Contribution of Stability and Manipulation in the Characterization Of

An evaluation of the contribution of stability and manipulation in the characterization of

footedness using preference and performance measures

Mark Garrett

A thesis submitted to the Faculty of Graduate Studies of the

University of Manitoba

in partial fulfillment of the requirements of the degree

DOCTOR OF PHILOSOPHY

Department of Human Anatomy and Cell Science

Rady Faculty of Health Sciences

University of Manitoba

Winnipeg, Manitoba

ABSTRACT

Footedness is commonly defined in the literature through manipulation preference exclusively, with the opposite “non-dominant” leg assigned to an unsubstantiated stability dominant role.

Female athletes are twice as likely to injure the ACL of their non-dominant as their dominant lower limb, and this has not been rationalized given its presumed role of stability dominance.

Some researchers have suggested that lower limb stability is multifaceted, with changing sidedness depending on task and context. The aim of this study was to characterize footedness through examination of the contribution of individual manipulation and stability questions used to assign footedness, assessment of the relationship between lower limb preference and performance in stability and manipulation tasks, and identification of functional asymmetry in gait and cutting (implicated in ACL injury). A cross-sectional, observational design was used and 52 adult participants (25 females, 27 males) with a mean age of 25.5 years were recruited.

Preference for manipulation and stability was evaluated using the Waterloo and Chapman footedness instruments, and performance in lower limb manipulation, stability, gait and cutting tasks was assessed bilaterally. Findings include that footedness should be identified with a combination of manipulation and stability tasks, and familiar tasks are more likely to elicit a lateralized response. Stability is task dependent and multimodal, with dynamic stability on the left and static and reach stability on the right. There is coherence between preference and performance across the stability modes, but preference for manipulation is substantially lateralized relative to performance (92% vs 61%). Males were nearly symmetrical in cutting

(3.6%, NS), while females demonstrated sex dependent asymmetry left-to-right (35%, p<0.05) and in acceleration control during left plant, and also showed poorer dynamic stability on the left. This is consistent with their asymmetrical ACL injury incidence. Conclusions are that

ii footedness is not exclusively determined by manipulation but should include stability components localized to the same side, and that the lower limb contralateral to the manipulation preferred lower limb is not automatically the stability preferred lower limb since stability laterality is task dependent. Explicit terminology related to limb preference and performance was developed and found to be effective in clarifying limb identification and functional roles.

iii ACKNOWLEDGMENTS

I would like to thank my advisor, Dr. Dean Kriellaars, for his willingness to guide me on

this incredible journey. Dean’s deep knowledge of the many areas traversed by our project

and his genius for always keeping the forest in view ensured our path was well lit, while his

indefatigable optimism and infinite patience enabled me to navigate the intensely competing

demands of my full-time work and young family. I will be forever in his debt.

I would also like to thank my advisory committee members, Dr. James Thliveris, Dr.

Phillip Gardiner and Dr. Brian MacNeil, for their generosity of spirit in supporting my

learning. Their wisdom and cheerful insights served as a reliable compass, helping to keep

our project on course.

Finally, I would like to dedicate this thesis to the memory of my parents for their

inspiring, life-long curiosity, and to my wife, Diane Kading, and children, Matthew and

Rachel, for their constant love and support during my pursuit of this dream.

iv TABLE OF CONTENTS

ABSTRACT ...... II

ACKNOWLEDGMENTS ...... IV

TABLE OF CONTENTS ...... V

LIST OF TABLES ...... X

LIST OF FIGURES ...... XII

LIST OF PHOTOGRAPHS ...... XIV

REVIEW OF LITERATURE ...... 1

STRUCTURAL BILATERAL SYMMETRY AND CENTRAL NERVOUS SYSTEM (CNS) LATERALITY ...... 1

Laterality, Preference and Performance ...... 2

Speech, Eyedness and Earedness ...... 3

HANDEDNESS ...... 4

Assessment of Handedness ...... 7

Handedness Summary ...... 10

FOOTEDNESS ...... 11

Footedness Terminology ...... 11

Assessments of Footedness ...... 13

Waterloo Footedness Questionnaire-Revised...... 16

Chapman Behavioural Inventory of Foot Preference and Sokal Self-Report of Foot Preference ...... 17

Comparison of Current Handedness and Footedness Assessment Approaches ...... 19

Conventional Assignment of Complementary Functional Roles to the Lower Limbs ...... 20

ASYMMETRY IN LOWER LIMB ANATOMY AND FUNCTION ...... 21

Task Dependency and Stability Function ...... 21

v Anatomical Asymmetry...... 22

Structural and Functional Asymmetry: Leg Length Inequality ...... 23

Gait ...... 25

FUNCTIONAL ASYMMETRY AND ITS RELATIONSHIP TO INJURY MECHANISM ...... 27

AN OPERATIONAL DEFINITION OF FOOTEDNESS ...... 31

PURPOSE ...... 34

RESEARCH AIM ...... 34

RESEARCH QUESTIONS AND GENERAL HYPOTHESES ...... 34

Footedness Preference ...... 34

Research Questions ...... 34

Hypotheses ...... 35

Footedness Performance ...... 35

Research Questions ...... 35

Hypotheses ...... 35

Asymmetry in Functional Tasks ...... 36

Research Questions ...... 36

Hypotheses ...... 36

METHODOLOGY ...... 37

EXPERIMENTAL DESIGN ...... 37

PARTICIPANTS ...... 37

Recruitment ...... 37

Inclusion and Exclusion Criteria ...... 37

PARTICIPANT CHARACTERISTICS ...... 38

PROTOCOL ...... 39

Order Effects ...... 39

INSTRUMENTS AND ASSESSMENTS ...... 40

Anthropometry ...... 40

vi Preference Assessment ...... 41

Stability and Manipulation Evaluation Questionnaire (SAME) ...... 41

Laterality Indices ...... 42

Assignment of Manipulation Preference ...... 44

Performance Assessments ...... 45

Rationale for Selection of Performance Assessments ...... 45

Manipulation Performance Assessment Procedure ...... 48

Targeting...... 48

Stability Performance Assessment Procedures ...... 51

Static Balance ...... 51

Dynamic Balance ...... 52

Reach ...... 54

Functional Performance Assessment Procedures ...... 55

Gait - Walking (3 mph) and Running (6 mph) ...... 55

Cutting ...... 56

STATISTICAL ANALYSIS ...... 58

Statistical Analysis for Preference Data ...... 58

Statistical Analysis for Performance Data ...... 59

RESULTS ...... 60

LATERALITY CHARACTERISTICS ...... 60

MANIPULATION AND STABILITY PREFERENCE ...... 60

Waterloo and Chapman Foot Preference Instruments ...... 60

Correlations between Composite and Aggregate Scores ...... 66

Multimodal Nature of Stability Preference ...... 66

Waterloo and Chapman Receiver Operating Characteristic Analysis ...... 67

Sex Dependent Preference ...... 72

MANIPULATION AND STABILITY PERFORMANCE ...... 73

Targeting ...... 73

Coherence between Targeting Performance and Preference ...... 75

vii Stability ...... 77

Static Stability ...... 77

Dynamic Stability ...... 78

Reach ...... 79

Functional Tests ...... 80

Gait ...... 80

Cutting ...... 81

Laterality of Preference and Performance ...... 83

Prediction of Manipulation Preferred Foot using Performance Measures ...... 85

DISCUSSION ...... 87

TASK FAMILIARITY IN FOOTEDNESS ASSESSMENT ...... 87

STABILITY IN FOOTEDNESS ASSESSMENT ...... 88

Effectiveness of Preference Instruments...... 88

Challenging the Convention that “the Non-dominant Foot is the Stability Dominant Foot” ...... 91

The Multimodal Distribution of Stability Preference ...... 92

Reach Stability ...... 94

MANIPULATION PREFERENCE AND PERFORMANCE COHERENCE ...... 96

SEX DEPENDENT DIFFERENCES AND FUNCTIONAL ACTIVITIES ...... 98

TERMINOLOGY ...... 101

OPERATIONAL DEFINITION OF FOOTEDNESS REVISITED ...... 102

LIMITATIONS ...... 103

CONCLUSIONS ...... 106

IMPLICATIONS ...... 108

FUTURE RESEARCH QUESTIONS ...... 110

APPENDIX 1–ACL INJURY VIDEO ANALYSIS SUMMARY ...... 112

viii APPENDIX 2–SAME QUESTIONNAIRE ...... 113

APPENDIX 3–WATERLOO AND CHAPMAN LATERALITY INDICES ...... 123

APPENDIX 4–MANIPULATION ITEMS FROM THE SAME...... 125

APPENDIX 5–ETHICS APPROVAL ...... 126

APPENDIX 6–PARTICIPANT CONSENT FORM...... 127

APPENDIX 7–DATA COLLECTION FORM ...... 134

REFERENCES ...... 137

ix LIST OF TABLES

Table 1. Common handedness assessment instruments...... 9

Table 2. Waterloo Footedness Questionnaire-Revised questions and their functional type...... 16

Table 3. Chapman Behavioural Inventory of Foot Preference questions and their functional type.

The original version consisted of 13 items, while the final had 11 as the last two items

(shaded) were removed due to poor item-scale correlation scores...... 18

Table 4. Terminology used to describe lower limb functional roles from a sample of studies since

1988...... 20

Table 5. Participant characteristics...... 38

Table 6. Participant assessments included in study...... 39

Table 7. Order effects table...... 39

Table 8. The primary statistical method and dependent variable list for each performance

assessment...... 59

Table 9. Footedness classification and laterality characteristics based upon the composite scores

for the Waterloo and Chapman instruments...... 62

Table 10. Laterality indices for each of the items of the Waterloo (top 10 items - grey) and

Chapman (bottom 13 items - light blue) instruments...... 63

Table 11. Correlation matrix (r, p value) between composite and aggregate scores for the

Waterloo and Chapman instruments...... 66

Table 12. Laterality indices of the stability items from the Waterloo (grey) and Chapman (blue)

instruments sorted based upon laterality percentage (L%). A laterality percentage less than

50 indicates left preference...... 67

x Table 13. Items meeting the criteria for “true” manipulation preferred foot based upon the

Waterloo and Chapman instruments...... 68

Table 14. Left to right differences in targeting performance. Side to side differences were all

significant (p<0.05)...... 74

Table 15. Sex dependent differences in targeting performance. P values indicate significance

between males and females, otherwise NS...... 75

Table 16. Static stability variability during a 30 second single leg standing trial...... 77

Table 17. A bilateral comparison of the excursion (cm) for each direction and total excursion of

the star excursion reach test...... 79

Table 18. Bilateral comparison of gait spatiotemporal durations for walk and run. Mean and SD

shown in parentheses...... 80

Table 19. The peak accelerations for P1 and P2, and the P1/P2 control ratio for the right and

left plant phase of the cutting manoeuvre. The left to right asymmetry was computed and

expressed as a percentage. (Independent t-test, between sexes; Paired t-test, between sides).

...... 82

Table 20. Lower limb laterality percentages showing alignment in degree of sidedness of

preference (upper half of table) and performance (lower half of table) domains...... 84

Table 21. Classification table for BLR of manipulation preferred foot with performance

measures...... 86

xi LIST OF FIGURES

Figure 1. Assessment methods for footedness assignment in footedness studies. The pie chart

summarizes the percentage of studies utilizing each category of footedness evaluation. .... 15

Figure 2. The Waterloo Footedness Questionnaire-Revised weighted scale...... 41

Figure 3. Resultant trunk acceleration for a representative static balance trial (20 seconds)...... 52

Figure 4. Representative resultant trunk acceleration for a left to right cut. Phase 1 and 2 (P1 and

P2) occur during the single support of the cutting limb (left plant). The P1 phase

corresponds primarily to anterior-posterior deceleration, and the P2 to medial-lateral

acceleration...... 57

Figure 5. Waterloo (left panel) and Chapman (right panel) composite score histograms...... 61

Figure 6. Histograms of the aggregate scores of the Waterloo manipulation items (left panel) and

Waterloo stability items (right panel)...... 64

Figure 7. Histograms of the aggregate scores of the Chapman manipulation items (left panel) and

Chapman stability items (right panel). In the right histogram, the three stability questions

from the original Chapman inventory were combined to create an aggregate score for

stability. Note that the current version of the Chapman inventory has removed two of the

stability questions...... 65

Figure 8. ROC curves for the composite scores of the Waterloo and Chapman footedness

instruments, as well as the manipulation and stability aggregate scores for each instrument.

The composite scores and aggregate scores for manipulation have 100% accuracy in

classification (area under the curve =1.0). The stability aggregate scores both show similar

xii trajectories and very good area under curve (AUC) indicating good footedness predictive

ability...... 69

Figure 9. ROC curves for each item of the Waterloo instrument. AUC for each item is shown.

The table to the right shows manipulation items in bold italics and stability items in regular

font...... 70

Figure 10. ROC curves for each item of the original 13 item Chapman instrument. The revised

Chapman instrument includes items 1 to 11 only. Area under the curve (AUC) for each item

is shown. The table to the right shows manipulation items in bold italics and stability items

in regular font...... 71

Figure 11. Bar plot of the averaged scores for each of the Waterloo items grouped by sex...... 73

Figure 12. Histograms of manipulation preference (top panel: Chapman Manipulation Aggregate

Scores) and performance (bottom panel: bilateral difference in average targeting error). ... 76

Figure 13. Scatterplot of right and left variability (SD) in static balance coded by sex.

Correlation of r=0.519, p<0.001)...... 78

xiii LIST OF PHOTOGRAPHS

Photo 1. Targeting assessment setup. The left photo shows the lateral view of participant

positioning for testing of the right foot, and the right photo shows the superior view. The

start line and target lines #1 and #2 for the right foot are shown (7.5 cm spacing)...... 48

Photo 2. The starting position for the NuStar test is shown on the left. A single trial of anterior

pylon touch during left lower limb single support is shown on the right...... 53

xiv REVIEW OF LITERATURE

STRUCTURAL BILATERAL SYMMETRY AND CENTRAL

NERVOUS SYSTEM (CNS) LATERALITY

The gross anatomy of the human locomotor system is considered to be bilaterally symmetrical due to its ability to be bisected into two mirrored parts by the median plane

(Martindale & Henry, 1998; Moore, Dalley, & Agur, 2014). Bilateral symmetry is one of three major anatomical symmetry patterns expressed in the body plans of multicellular organisms, the other forms being radial symmetry, in which multiple planes pass through the central axis to produce identical parts (e.g. sea anemones), and asymmetry, where there is no plane or axis of symmetry (e.g. sponges) (Manuel, 2009). The key morphological features of the bilateral symmetry pattern are organized around the median plane to create left and right sides, dorsal and ventral surfaces, anterior cephalization, and transversely paired sense organs and limbs (Allard &

Tabin, 2009; Finnerty, 2005). Humans share the bilateral symmetry platform with more than

99% of all animal species, and the overwhelming success of this model is thought to be due to its selective evolutionary advantage for directed locomotion (Finnerty, 2005; Shubin, 2009). By contrast, this ability is absent in organisms with radially symmetrical and asymmetrical anatomy

(Holló & Novák, 2012).

While the human locomotor system conforms grossly to the bilateral symmetry body plan, there is evidence of both anatomical and functional asymmetries in each of its constituent muscular, skeletal and neurological systems (Kang, Herron, Ettlinger, & Woods, 2015; Knutson,

2005a; Sone et al., 2006). Structural anomalies in musculoskeletal anatomy between the left and right sides are well known (Moore et al., 2014), and interhemispheric anatomical asymmetry of the cerebral cortex with associated lateral functional differences has been identified as a fundamental feature of brain organization (Goldberg et al., 2013).

Laterality, Preference and Performance

Laterality refers to functional asymmetry of the CNS (Schneiders et al., 2010; Tran,

Stieger, & Voracek, 2014), so a function that is governed by one cerebral hemisphere more than the other is said to be lateralized to that side (Vannest, Karunanayaka, Schmithorst, Szaflarski, &

Holland, 2009). The key lateralized areas in humans are speech and language processing, vision, hearing, and upper and lower limb function, and the superiority of one side of the body over the other with each of these is known as sidedness or dominance, or more specifically as eyedness, earedness, handedness and footedness.

Sidedness is expressed through both preference and performance. Preference is the self- selection of one side of the bilaterally paired sense organs or limbs that an individual instinctively feels is superior at performing a unilateral task that could be done by either side

(Porac, 1997; Suar, Mandal, Misra, & Suman, 2007). This is also termed bias (Carey et al.,

2009). Preference can be determined through use of self-report and behavioural measures. Self- report involves use of questionnaires that present functional scenarios designed to obtain the individual’s choice of favoured side through recall only (Elias, Bryden, & Bulman-Fleming,

1998). Behavioural determination requires the individual to physically complete functional tasks in order to elicit selection of their favoured side, but does not involve measurement or

2 comparison of the actual performance of the two sides (Chapman, Chapman, & Allen, 1987).

Performance is the identification of the superior side based on comparison of the quality (e.g. speed or precision) of the execution of a particular task (Chisnal, 2012). Interestingly, the implication of this definition is that it permits the assignment of dominance to a limb for a specific task within a particular functional domain (e.g. manipulation or stability) and context.

For example, the typical right-handed baseball player will prefer using their right hand for the manipulation task of throwing a ball, but will prefer using their left for the manipulation task of catching the same ball. Both tasks are in the manipulation domain, however context and task are also determinants in the expression of sidedness. Also, although preference and performance sidedness for a given task are not perfectly coherent, preference for one side is commonly utilized to predict performance superiority for that side without verification through bilateral comparative performance testing (Elias et al., 1998; Watson, Pusakulich, Ward, & Hermann,

1998).

Speech, Eyedness and Earedness

Speech and language functions are considered to be lateralized to the left cerebral hemisphere in more than 90% of people (Vannest et al., 2009; Watson et al., 1998). This is consistent with the asymmetrical anatomical findings of enlargement of the left inferior frontal gyrus (pars opercularis and triangularis) corresponding to Broca’s area for speech, the posterior aspect of the left superior temporal gyrus (planum temporale) where Wernicke’s language processing area is located, and the arcuate fasciculus that links the two (Fink, Frampton, Lyden,

& Lees, 2008; Geschwind & Levitsky, 1968; Kang et al., 2015; Matsumoto et al., 2008). The locations of these areas for speech and language are classically thought to determine the

3 “dominant” cerebral hemisphere, and were famously identified during the 19th century in patients with unilateral brain lesions (Lazar & Mohr, 2011). This aspect of CNS laterality is considered to reflect genetically mediated hemisphere specialization at the species level rather than random lateralization at the individual level (Elliot & Roy, 1996).

Lateralized function of the key paired sense organs located in the head is evident with 64-

71% of people demonstrating right eyedness and 60-68% right earedness (Bosten et al., 2015;

Dittmar, 2002; Porac, 1981; Reiss & Reiss, 1997b, 1999). While strong right-sidedness across eyedness, eardness, handedness and footedness in humans suggests a common underlying biological mechanism (Carey et al., 2001), the specific associations between these functions remain unclear (Brandler & Paracchini, 2014; Brown & Taylor, 1988; Polemikos & Papaeliou,

2000).

HANDEDNESS

Handedness is the most observable functional expression of cerebral lateralization in humans, and is also the most investigated due to its perceived ability to provide insight into cerebral organization (Lust et al., 2011; Saudino & McManus, 1998; Somers et al., 2015). It can be defined as the consistent preference and/or superior performance of one upper limb over the other with single handed manual tasks (i.e. it is the superior manipulation side) (Corey, Hurley,

& Foundas, 2001). Approximately 90% of people in the developed world are right hand preferred (Bourassa, 1996; Peters, Reimers, & Manning, 2006), and of strong left-handers, 73% are also left hemisphere dominant (Elias & Bryden, 1998; Knecht et al., 2000; Pujol, Deus,

4 Losilla, & Capdevila, 1999). This bimodal, J-shaped prevalence curve for handedness is so skewed to the right that the relatively small population of non-right handed individuals has been cited as a limiting factor in handedness and cerebral dominance research due to the difficulty of recruiting adequate numbers of these participants (Kopiez et al., 2012)

Neuroanatomically, right handedness and footedness are congruent with left cerebral hemisphere dominance due to decussation of the corticospinal tract (the major descending motor pathway associated with voluntary limb movement), which occurs mostly in the medulla oblongata en route from the left primary motor cortex to the right (i.e. contralateral) limbs

(Purves, 2012). This is consistent with the anatomical finding of unilateral enlargement of the left basal nuclei (Kang et al., 2015), which have an important role in the regulation of movement of the right upper and lower limbs.

Homo sapiens is the only species to show strong (right) handedness, and there is evidence of the origins of this lateralization dating back 500,000 years in right-handed wear patterns on the labial faces of pre-Neanderthal incisor and canine teeth (Frayer et al., 2012). It appears there is a genetic, non-Mendelian influence on sidedness, and Sicotte, Woods, and Mazziotta (1999) found in a meta-analysis that identical twins are more likely to share handedness that non- identicals. In another large twins study, Medland et al. (2009) assessed the heritability of handedness at a modest 24%, in contrast to the estimated 80% and 61% for eye and hair colour respectively (Brauer & Chopra, 1978). Annett’s 1978 model of a single right shift gene is now considered inadequate (Annett, 2003), and there is support for a more current and complex polygenic model involving multiple loci for the development of sidedness (Armour, Davison, &

5 McManus, 2014; Warren, Stern, Duggirala, Dyer, & Almasy, 2006). Sidedness is evident early in life, with consistent sucking of the right thumb observed in 90% fetuses utero from week 15 to term (Hepper, Shahidullah, & White, 1991).

The majority of human cultures exhibit right handed bias, and this highly pervasive influence is reflected in many languages. The meaning of right translates variously as positive terms such as correct, straight, lawful and manually skilled, while left is rendered negatively as evil, illegal, weak and awkward (Google Translate, 2017). There is even evidence of this right- sided bias influencing provision of health care services, where patients presenting with left cerebrovascular accidents have been found to receive earlier, more aggressive treatment (Foerch et al., 2005) despite bilaterally equal incidence of stroke between the hemispheres (Fink et al.,

2008). It is postulated this reflects heightened awareness among patients, community members and health care professionals regarding the impact of left (i.e. typically dominant) cerebral hemisphere stroke on the higher profile behaviours of speech and right hand function (Foerch et al., 2005).

It is thought that strong right-sided cultural bias may have influenced a proportion of older individuals with right cerebral hemisphere dominance to self-identify as right or mixed handers (Chapman et al., 1987) as a result of many years of imposed right hand practice.

Repetition-induced neural adaptation associated with forced dextrality in schools [i.e. the obligatory use of the right hand by left handers for functional tasks such as writing that was commonly practiced in Western society until as recently as the 1970s (Porac, 1981)], the historical non-availability of equipment designed for left-handers, and even playing the piano

6 (most piano music involves significantly more notes for the right hand) may have resulted in the right hands of older innate left handers performing as well as or better than their left (Kopiez et al., 2012). A 1999 survey of adults in Switzerland found the proportion of innately left-handed subjects who used their right hand for writing declined from 88.9% in 65-74 year-olds to 26.6% in 35-44 year-olds, and a corresponding increase in prevalence of innate left-handedness from

6.2% to 11.9% for the same age groups (Galobardes, Bernstein, & Morabia, 1999). This increased prevalence of left handedness and associated decreased right and mixed handedness observed in younger people may reflect easing of real world, right-side bias pressures over the past few decades, but it is interesting to note that there has been no matching change in footedness prevalence over that time (Brackenridge, 1981; Ellis, Ellis, Marshall, Windridge, &

Jones, 1998; Kushner, 2011; Mandal, Suar, & Bhattacharya, 2001; Suar et al., 2007). Similarly,

Fagard and Dahmen (2004) found that while Tunisian children showed a significantly lower prevalence of left handedness than French children of a similar age, there was no difference in footedness prevalence between the two groups. The discrepancy in their upper limb sidedness was assessed through both preference and performance testing, and is postulated to reflect differing cultural attitudes between Tunisia, where use of the left hand for activities such as eating is prohibited, and France, where there are no social restrictions on left hand use. This latter study provides evidence of the influence of context (in this case culture) as a principal determinant of the sidedness of upper limb preference and performance.

Assessment of Handedness

There is long-standing interest in CNS laterality research in the development of an handedness measure to accurately and reliably determine cerebral dominance. Self-report

7 preference is the favoured format and most frequently used due to its advantage of convenient administration in comparison to behavioural preference and performance measures which usually require equipment and direct observation by the tester. It is also inexpensive and low risk relative to other procedures such as fMRI brain mapping (Binder et al., 1997) and invasive Wada testing

[the anesthetizing of each cerebral hemisphere individually via intracarotid sodium amobarbital injection (Wada, 1997), with its attendant risk of stroke and encephalopathy (Loddenkemper,

Morris, & Moddel, 2008)]. Researchers and clinicians from a variety of disciplines (e.g. neuropsychology, neurosurgery, physical rehabilitation and sports science) require a simple and reliable means of establishing upper limb dominance to assist them in their diverse approaches to investigation of upstream brain functions such as language and emotion, provision of individual client clinical interventions and enhancement of athletic performance (Elias et al., 1998;

Schneiders et al., 2010; Watson et al., 1998).

Table 1 shows a range of published handedness instruments, including self-report and behavioural preference measures and performance measures. Common to these handedness instruments is the notable feature that they all consist almost exclusively of familiar, unimanual tasks involving object manipulation and control. Some items also feature cultural bias. For example, self-report questionnaires typically include items involving identification of the hand used for writing, throwing a ball and holding a spoon for self-feeding; behavioural instruments entail observation of which hand is used in the execution of tasks such as opening a lock with a key and using a screwdriver; and performance tests require measurement of speed and accuracy

(i.e. “targeting”) associated with fine motor tasks such as inserting pegs in holes (Brown,

Jahanshahi, & Marsden, 1993; Brown, Roy, Rohr, Snider, & Bryden, 2004; Corey et al., 2001).

8 Interestingly, though coherent, there is a distinct discrepancy between the results obtained from preference and performance testing. Results from upper limb preference testing are bimodal and much more lateralized (Oldfield, 1971) than those obtained from performance testing, which tend to be unimodal and only mildly right-skewed (Corey et al., 2001). Brown et al. (2004) report that coherence between two preference instruments, the self-report Waterloo Handedness

Questionnaire-Revised (WHO-R) (Elias et al., 1998) and the behavioural Wathand Box Test was much greater (r=0.88) than either test achieved with a range of performance measures.

Table 1. Common handedness assessment instruments. Type of Percentage of Handedness Reference Assessment Manipulation Items Edinburgh Handedness Oldfield (1971) Preference: 90% Inventory self-report (1 ambiguous manipulation item) Handedness questionnaire Raczkowski and Preference: 100% as used by Chapman et al. Kalat (1973) self-report (1987) Lateral Preference Coren (1993) Preference: 100% Inventory self-report (upper limb items only) Waterloo Handedness Elias et al. (1998) Preference: 94% Questionnaire-Revised self-report (1 ambiguous manipulation item (WHQ-R) & 1 strength item) Annett Handedness Annett (1967) Preference: 75% Questionnaire self-report (2 ambiguous manipulation items (2 types of assessment) & 1 strength item) Preference: 100% behavioural Wathand Box Test Bryden, Pryde, and Preference: 100% Roy (2000) behavioural Grooved Pegboard Corey et al. (2001) Performance 100% Grip Strength Corey et al. (2001) Performance 0% (1 strength item) Annett Pegboard Brown et al. (2004) Performance 100% Finger Tapping Brown et al. (2004) Performance 100%

9 Some instruments in Table 1 are identified as consisting of less than 100% manipulation items (column 4), and this is due to their inclusion of a small number of items that are: (a) ambiguous in that they are difficult to classify in terms of function [e.g. “the hand used to hold a walking stick” (Elias et al., 1998) involves manipulation, but also has strength and stability components and a cultural bias since “walking stick” is a British expression meaning “cane”, which may be mistaken in North America for “trekking pole” that is used bilaterally], and/or (b) exclusively involve the strength of the limb. However, it is very clear from the commonly used instruments that the accepted principal determinant of handedness (preference and performance) is the side showing superior manipulation ability. Interestingly, while there are no items exclusively related to a stability role for the upper limb in any of the self-report instruments shown, the widely used footedness instruments developed by Chapman et al. (1987) and Elias et al. (1998) include mixed stability and manipulation content. This is in marked contrast to the manipulation-focused “handedness questionnaire” (Raczkowski & Kalat, 1973) and WHQ-R used by these authors in the development of their footedness instruments. It is possible though unevaluated that, like footedness, handedness has contextually specific aspects of manipulation and stability function, that a stability role should be a component of handedness characterization, and that stability preference and performance are co-localized largely to the manipulation side.

Handedness Summary

Approximately 90% of the adult population is considered to be right handed, although this sidedness is believed to be modifiable with practice as is suggested by the lower rates of left and mixed handedness among people whose childhoods were spent in cultures where use of the left hand for functional activities such as writing and eating was discouraged. Handedness

10 determination tends to utilize self-report preference measures rather than performance measures, presumably due to their ease of use. Both preference and performance-based handedness instruments employ familiar, unilateral manipulation tasks almost exclusively, thereby attributing a strong manipulation character to upper limb sidedness. It is possible that this near absence of stability tasks in evaluation has limited the understanding of potential contextual features of handedness. There is coherence between upper limb preference and performance assignment, however preference is the much more strongly lateralized of the two.

FOOTEDNESS

Although less lateralized than handedness, the majority (approximately 85%) of people are right footed (Coren, 1993). Footedness is believed to be a better indicator of cerebral dominance than handedness due to the reduced influence of cultural and environmental biases on lower limb selection for functional tasks (Ellis et al., 1998; Searleman, 1980). Similar to handedness, footedness can be assigned through both preference and performance measures, with preference measures being much more heavily represented in published studies.

Footedness Terminology

Reviewing the literature reveals that currently there is no accepted standardized terminology associated with footedness publications, resulting in a lack of clarity regarding which characteristic – preference, performance, manipulation or stability – is being identified.

For example, a sample of recent articles incorporating assignment of lower limb sidedness shows

11 a variety of expressions being used as equivalent, generic terms for footedness, including

“preferred foot” (Tran & Voracek, 2016), “preferred leg” (Hiraoka et al., 2015), “preferred lower limb” (Bini, Jacques, Carpes, & Vaz, 2017), “dominant foot” (Smith, Stinear, Alan Barber, &

Stinear, 2016) and “dominant limb” (Goodarzi, Dabbaghi, Valipour, & Vafadari, 2015). These terms do not explicitly or reliably convey the determining laterality characteristic they represent

(e.g. preference, performance, manipulation or stability), which can be problematic as these laterality characteristics may not be coherent in terms of sidedness. Compounding the terminology issue, the lower limb contralateral to the preferred limb is typically designated as the

“stability dominant”, “non-dominant” or “non-preferred” leg, and assigned an unsubstantiated stability and support role (Brophy, Silvers, Gonzales, & Mandelbaum, 2010; Gabbard & Hart,

1996; Peters, 1988; Sadeghi, Allard, Prince, & Labelle, 2000).

To aid future research around the footedness construct, a more precise, reliable terminology is needed. In a study comparing hand preference and performance in humans and monkeys, Chatagny et al. (2013) chose the terms preference for the limb instinctively selected for a task (as is customary in sidedness research), and dominance for the limb that was measured to be the more efficient at the performance of a task. A problem with this approach to terminology is that dominance is already commonly used in the literature as a generic label meaning the better side in terms of preference or performance (e.g. 28% of footedness studies published since 2010 refer to the preferred limb as the dominant limb). To eliminate any potential for confusion in this thesis, the following terminology has been developed to ensure consistent, explicit identification of both the limb and the specific function being discussed:

 Manipulation-preferred lower limb: the lower limb that is instinctively selected for a

12 manipulation task.

 Manipulation-performance lower limb: the lower limb that is measurably superior at

performing a manipulation task.

 Static stability-preferred lower limb: the lower limb that is instinctively selected for a

static stability task.

 Static stability-performance lower limb: the lower limb that is measurably superior at

performing a static stability task.

 Dynamic stability-preferred lower limb: the lower limb that is instinctively selected

for a dynamic stability task.

 Dynamic stability-performance lower limb: the lower limb that is measurably

superior at performing a dynamic stability task.

The above set of terms are limited to the specific evaluations performed within the thesis

and are not meant to be comprehensive. Other identified footedness contexts (e.g. effect

of perturbations on stability) would require creation of additional terms, however the

taxonomy established here would accommodate any needed additional categories.

Assessments of Footedness

Similar to the upper limb, there are two major streams in the literature driving development of measures to determine lower limb sidedness. The neuropsychology and neurosurgery focus tends to be on improving understanding of upstream relationships regarding

CNS laterality functions generally and identification of the dominant cerebral hemisphere in particular, while the physical rehabilitation and sports science focus is on downstream (i.e. local)

13 unilateral characteristics of lower limb performance to reduce injury risk, improve treatment outcomes and enhance athletic competitiveness. The major footedness measures have traditionally come from the neuropsychology field, and have been adopted to some extent by the other disciplines for their purposes.

A Pubmed search of footedness on April 12, 2016 returned 163 articles dating back approximately 40 years. Seventy-two of the articles were studies in which a footedness measure was directly utilized to determine participants’ preferred lower limb. Figure 1 shows the distribution of the footedness assessments utilized. Of the 72 studies, 27% used the Waterloo

Footedness Questionnaire-Revised (Elias et al., 1998), 11% used the Chapman behavioural inventory of foot preference (Chapman et al., 1987), 47% used some subset of questions from the

Waterloo questionnaire and/or Chapman inventory (or other similar questions), and 15% used only one question, a variant of the classic manipulation preference item “Which foot do you use to kick a ball?” (Figure 1). The table lists the breakdown of studies composing the four groups. It is interesting to note that a kicking question was used in 100% of the 72 studies as both the

Waterloo questionnaire and Chapman inventory include one, and the studies that used a subset of questions (or other similar questions) from these two instruments always chose to include a kicking question.

14 Waterloo 27% Chapman 11%

Kick only 15%

Partial Waterloo/Chapman 47%

Instrument Studies a) Waterloo (Elias et al., 1998; Girard & Cheyne, 2004; Grouios, Hatzitaki, Kollias, & Koidou, Footedness 2009; Hardt, Benjanuvatra, & Blanksby, 2009; Hiraoka et al., 2015; Kang & Harris, Questionnaire- 2000; Kiyota & Fujiwara, 2014; Mohr & Lievesley, 2007; Ocklenburg et al., 2013; Revised Ocklenburg et al., 2010; Ocklenburg & Güntürkün, 2009; Paquet, Jehu, & Lajoie, 2016; Paquet, Taillon-Hobson, & Lajoie, 2014; Savitz, van der Merwe, Solms, & Ramesar, 2007; Stöggl, Hébert-Losier, & Holmberg, 2013; Taylor, Strike, & Dabnichki, 2007; van der Kamp & Canal-Bruland, 2011; Wang & Newell, 2013; Zverev, 2006; Zverev & Mipando, 2007) b) Chapman (Asai, Sugimori, & Tanno, 2011; Bohm, Mersmann, Marzilger, Schroll, & behavioural Arampatzis, 2015a; Carey et al., 2009; Chapman et al., 1987; de la Vega, Graebe, inventory of Härtner, Dudschig, & Kaup, 2015; Golomer & Mbongo, 2004; Karev, 2009; Sokal & footedness Allen, 2008; Stochl & Croudace, 2013) c) Partial (Barcellos et al., 2012; Bell & Gabbard, 2000; Bhushan & Khan, 2006; Borod, Caron, Waterloo & Koff, 1984; Coren & Searleman, 1987; Dittmar, 2002; Gentry & Gabbard, 1995; questionnaire, Hart & Gabbard, 1997; Lawton, Czarnolewski, & Eliot, 2015; Mandal, Sabharwal, Chapman Misra, Suman, & Suar, 2012; Mandal et al., 2001; Markoulakis, Scharoun, Bryden, & inventory or Fletcher, 2012; Martin & Machado, 2005; Martin & Porac, 2007; Maupas, Paysant, Datie, Martinet, & André, 2002; Maupas, Paysant, Martinet, & André, 1999; similar Mikheev, Mohr, Afanasiev, Landis, & Thut, 2002; Musalek, 2014; Nissan, Berman, Gross, Haim, & Chaushu, 2011; Nissan, Gross, Shifman, Tzadok, & Assif, 2004; Peter & Durding, 1979; Polemikos & Papaeliou, 2000; Putnam, Noonan, Bellia, & Previc, 1996; Reiss, 1999; Reiss & Reiss, 1997a; Rovira-Lastra, Flores-Orozco, Ayuso-Montero, Peraire, & Martinez-Gomis, 2016; Rustagi, Thakyal, & Vv Gopichand, 2014; Schiffman, Pestle, Mednick, Ekstrom, & Sorensen, 2005; Schneiders et al., 2010; Suar et al., 2007; Tran & Voracek, 2015a; Tran et al., 2014; Tran, Stieger, & Voracek, 2015; Tran & Voracek, 2015b; Watson et al., 1998) d) Kick only (Bacelar & Teixeira, 2015; Carey et al., 2001; Dahmen & Fagard, 2005; De Agostini & Dellatolas, 2001; Fagard & Dahmen, 2004; Heikkinen, Alvesalo, Osborne, & Tienari, 2001; Ooki, 2005, 2006; Reio, Czarnolewski, & Eliot, 2004; Singh, Manjary, & Dellatolas, 2001; Williams, Buss, & Eskenazi, 1992) Figure 1. Assessment methods for footedness assignment in footedness studies. The pie chart summarizes the percentage of studies utilizing each category of footedness evaluation.

15 Waterloo Footedness Questionnaire-Revised

Elias et al. (1998) developed the Waterloo Footedness Questionnaire-Revised

(“Waterloo”) for a study examining footedness as a predictor of cerebral lateralization for emotional perception. This widely-used 10 item self-report questionnaire for foot preference consists of five manipulation and five stability items (Table 2). Results showed significant correlation between cerebral lateralization of emotion and the responses to the manipulation items but not to the stability items (Elias et al., 1998). This illustrates the differing character of manipulation and stability functions in the lower limbs and the complexity resulting from the inclusion of both in one measure.

Table 2. Waterloo Footedness Questionnaire-Revised questions and their functional type. Item Waterloo Footedness Questionnaire-Revised Functional Type W1 Which foot would you use to kick a stationary ball at a target straight Manipulation in front of you? W2 If you had to stand on one foot, which foot would it be? Stability W3 Which foot would you use to smooth sand at the beach? Manipulation W4 If you had to step up onto a chair, which foot would you place on the Stability chair first? W5 Which foot would you use to stomp on a fast-moving bug? Manipulation W6 If you were to balance on one foot on a railway track, which foot Stability would you use? W7 If you wanted to pick up a marble with your toes, which foot would Manipulation you use? W8 If you had to hop on one foot, which foot would you use? Stability W9 Which foot would you use to help push a shovel into the ground? Manipulation W10 During relaxed standing, which foot do you put most of your weight Stability on first?

16 Chapman Behavioural Inventory of Foot Preference and Sokal Self-Report of

Foot Preference

The potential for footedness to be a more reliable predictor of cerebral dominance than handedness led Chapman et al. (1987) to develop the Chapman behavioural inventory of foot preference (“Chapman”). The protocol involves observation of participants’ choice of foot while executing 11 tasks with their lower limbs. Of the 13 items originally included in the instrument,

10 were manipulation tasks and three were stability (Table 3). The three stability tasks received the lowest item-scale correlation scores (<0.5), resulting in the removal of the two lowest scorers and retention of the third lowest item (the rationale for this retention was not provided). Of the

11 items in the final version, nine have a bilateral context in that the participant is in a standing position and asked to perform manipulation tasks such as kicking a ball at a target or writing their name in sand with their foot. The tester records the foot chosen to perform the kicking and writing tasks rather than the foot chosen to support the body. Only two of the 11 items do not utilize a bilateral weight-bearing condition (tapping a tune with one foot in sitting, and hopping on one foot), and perhaps not surprisingly given their distinctly different functional nature, these two items scored lowest of the 11 items in terms of correlation with scale. It is evident from the strong manipulation character of nine of the 11 items that this inventory effectively identifies the manipulation-preferred lower limb.

Twenty-one years after the publication of the Chapman inventory, Allen (the last author on the original Chapman paper) led a large follow-up study in which nearly 5,000 participants trialed the Chapman behavioural inventory for reliability in self-report format (Sokal & Allen,

2008). Participants completed the self-report before being observed executing each item, and the

17 finding of good correlation (r=0.77) between the self-report and behavioural versions for manipulation preference indicated that the Chapman behavioural inventory shows good reliability between self report and behaviourally assessed preferences (Sokal & Allen, 2008).

Table 3. Chapman Behavioural Inventory of Foot Preference questions and their functional type. The original version consisted of 13 items, while the final had 11 as the last two items (shaded) were removed due to poor item-scale correlation scores. Item Chapman Behavioural Inventory of Foot Preference Functional Type C1 You kick a soccer ball into a basket across the room. Which Manipulation foot kicks the ball? C2 You stamp an aluminum can into a perfect circle. Which Manipulation foot stamps the can? C3 You navigate a golf ball through a maze as quickly as you Manipulation can with your bare foot. Which foot guides the ball? C4 You write your name in the sand with your bare foot. Which Manipulation foot writes your name? C5 After writing your name in the sand, you smooth the sand Manipulation with your bare foot to erase your name. Which foot smooths the sand? C6 Using your bare foot, you attempt to arrange five pebbles in Manipulation a straight line with approximately 2 inches between pebbles. Which foot moves the pebbles? C7 You attempt to balance a 3 foot long wooden rod vertically Manipulation on your foot. On which foot does the rod rest? C8 You attempt to roll a golf ball around a circle painted on the Manipulation floor. Which foot guides the ball? C9 Kicking one foot into the air, you try to get that foot as high Manipulation/Force as possible. Which foot is in the air? C10 You sit down to tap out the rhythm of a simple tune (e.g. Manipulation Yankee Doodle) with your foot. Which foot does the tapping? C11 You stand on one foot and hop up and down as quickly as Stability/Force possible. On which foot do you stand? C12 Stand on one foot and hold as still as possible for one Stability minute. On which foot do you stand? (Item removed from final version) C13 Step up on a low stool (10 inches tall) and reach as high as Stability possible on the wall. Which foot do you place on the stool? (Item removed from final version)

18 Comparison of Current Handedness and Footedness Assessment Approaches

As discussed, common handedness instruments have a preference format and consist almost exclusively of familiar, unilateral manipulative tasks such as writing and using a spoon, which reflect the currently accepted strong manipulative character of upper limb function. The familiarity of these tasks elicits positive lateral responses to enable identification of the manipulation preferred upper limb. Performance-based handedness measures are similarly manipulation focused and show good coherence with preference measure findings in identifying the preferred limb.

The most widely used footedness measures also utilize a preference format, however they consist of a mix of manipulation and stability tasks, and unilateral and bilateral contexts. This presumably recognizes the bilateral nature of much of lower limb functional activity (e.g. ambulation). The findings of the footedness instruments are less lateralized than for handedness, and this is likely due to the inclusion of stability items, and because a number of questions present unfamiliar, complex scenarios (e.g. balancing a 3-foot rod vertically on the dorsum of the foot) (Chapman et al., 1987). This lack of task familiarity could cause participants to feel

“unsure” regarding which limb they would use, thereby reducing the certainty (or laterality) of their responses. As the item response rating scales in the questionnaires do not offer an “unsure” category, participants in this situation likely choose “equal” or “either”, which conveys a false impression of ambidexterity rather than uncertainty.

19 Conventional Assignment of Complementary Functional Roles to the Lower

Limbs

There is a persistent attribution of complementary functional roles to the lower limbs in the literature, where the preferred foot is assigned dominance for manipulation activities and the non-preferred limb is automatically relegated to an unsubstantiated stability dominant role. This categorical assignment of roles can be seen in Table 4, which shows the terminology used in a sample of studies representing the conventional view over the past 30 years.

Table 4. Terminology used to describe lower limb functional roles from a sample of studies since 1988. Attributed Functional Roles Reference Preferred Lower Limb Non-preferred Lower Limb manipulation or mobilization postural support Wang and Newell (2013) preferred kicking preferred stance or support Brophy et al. (2010) gesture postural stabilization Kimmerle (2010) mobilization stability or unskilled Schneiders et al. (2010) object manipulation postural support Hardt et al. (2009) mobilization postural support Grouios et al. (2009) manipulation & mobilization support and stabilization Zverev and Mipando (2007) action towards goal support Sadeghi et al. (2000) object manipulation postural control Elias and Bryden (1998) goal oriented power, postural and Peters (1988) stabilizing support

While the superiority of the preferred lower limb for manipulation is well established, the stability behaviour of the non-preferred lower limb is unclear (Schneiders et al., 2010). A stability dominant role would be expected to feature structural adaptation in response to consistent higher loading, however the evidence is equivocal (as will be detailed in the section:

Anatomical Asymmetry, pp. 23-4). As well, there are indications that stability dominance is task

20 dependent, rather than a continuous condition of the non-preferred leg (as will be discussed in the section: Footedness Task Dependency for Stability, p. 22). The lack of clarity regarding the stability role of the non-preferred lower limb has important implications for lower limb injury studies, which report disproportionately high rates of anterior cruciate ligament (ACL) injury in the “non-dominant” knees of young female athletes (as will be discussed in detail in the section:

Asymmetry and its Relationship to Injury Mechanism, pp. 28-31). It is imperative that there is improved understanding of sex-based, functional asymmetry in lower limb stability to enable development of strategies to lessen the risk of injury and disability in this sector of the population.

ASYMMETRY IN LOWER LIMB ANATOMY AND FUNCTION

In order to clarify the relationship between stability and manipulation functions in the legs, the following section will examine lower limb stability through a variety of tasks, anatomy

(including leg length inequality), and functional asymmetry in gait and cutting (a common sports manoeuvre associated with the high incidence of “non-dominant” leg ACL injuries in young female athletes). Improved understanding of lower limb stability function and footedness assignment may help to identify individuals at risk of injury and facilitate development of programs to reduce incidence.

Task Dependency and Stability Function

Hart and Gabbard (1997) recognized the possible influence that the behavioural context of the lower body could have over the assignment of manipulation and stability roles in the lower

21 limbs. They observed manipulation and stability preference to be assigned to opposing legs in a bilateral context, but that in a unilateral context the stability role could shift to the manipulation preferred leg. This suggests stability sidedness is dependent on the task – in this case the context

(unilateral vs. bilateral) and complexity. More recent studies have presented additional evidence of complex task dependence for stability. Maupas et al. (2002) suggested three possible aspects of footedness reflecting three types of motor activity: an effector (manipulation) foot, a static support (stability) foot and a dynamic support (stability) foot. In examining static versus dynamic task dependence during balance perturbations, Kiyota and Fujiwara (2014) found dominance for static balance to be equally distributed between right and left legs, while dominance for dynamic balance shifted from the left leg for low frequency dynamic perturbations to the right leg for high frequency dynamic perturbations. This suggests that task dependence is differentiated between static and dynamic stability subdomains in the context of perturbation frequency. Bacelar and

Teixeira (2015) also reported that stability was associated more with the right side, which goes against the conventional construct of stability preference assignment to the side contralateral to the manipulation-preferred limb (i.e. the left foot for most). Through use of preference and performance measures, these studies have shown a stability preference and performance distribution that spans both the right and left legs, and have added support to the concept of task dependency for stability in the multiple contexts of unilateral vs. bilateral support, simple to complex behaviours, static to dynamic stability, and perturbation frequency within dynamic balance.

Anatomical Asymmetry

Although the neuromusculoskeletal anatomy of the lower limbs appears grossly

22 bilaterally symmetrical, unilateral structural variation has been identified (Moore et al., 2014). A cadaveric study found the left leg to weigh significantly more than the right in 70% of cases

(Chhibber & Singh, 1970), skeletal studies have determined the left femur to be larger and longer

(Auerbach & Ruff, 2006; Cuk, Leben-Seljak, & Stefancic, 2001) and male athletes’ “non- dominant” legs of to have higher bone mineral density (McClanahan et al., 2002; Sone et al.,

2006). While these findings could suggest load-induced adaptations of bone and soft tissue in response to a greater support and stability role for the left leg, the evidence is inconsistent. MRI failed to show any difference in total quadriceps volume and cross-sectional area between sides in a study of young athletes who play sports involving quick changes of direction, jumping and running (Tate, Williams, Barrance, & Buchanan, 2006), and a study of rowers failed to show any between-sides difference in leg strength regardless of their handedness (Parkin, Nowicky,

Rutherford, & McGregor, 2001). MRI has also shown that side differences in knee cartilage volume, thickness and surface area are unrelated to lower limb dominance (Eckstein et al., 2002).

These latter findings fail to show evidence of unilaterally increased load bearing stresses

(Racunica et al., 2007) that might be expected with a dedicated stability role for the non- dominant lower limb. This is congruent with stability function shifting relatively equally between the limbs as a result of the bilateral nature of most lower limb functional use.

Structural and Functional Asymmetry: Leg Length Inequality

Leg length inequality (LLI) or anisomelia is the most common anatomical lower limb asymmetry, observed in 65-90% of the population. Of interest is that 53-75% of the time, this is due to the left leg being longer than the right (Knutson, 2005a), which aligns with the conventional but unsubstantiated view regarding a preferred stability role for the left, typically

23 non-dominant leg. There are no significant gender differences in prevalence, side or magnitude of LLI, and the average length discrepancy in adults is only 5.2 mm (Knutson, 2005a), which represents a very small proportion of overall leg length.

LLI can be structural or functional (i.e. apparent) (Walsh, Connolly, Jenkinson, &

O'Brien, 2000). Structural LLI is defined as asymmetry of length between the femoral head and ankle mortice of each leg (Knutson, 2005b). Functional LLI occurs in lower limbs that are skeletally symmetrical yet appear to be of unequal length due to postural asymmetries such as excessive unilateral foot pronation on the short leg side (Rothbart, 2006), or pelvic torsion where the innominate bone is rotated anteriorly on the short leg side or posteriorly on the long leg side about a horizontal axis running transversely through the symphysis pubis (Cooperstein & Lew,

2009). LLI is most accurately determined with imaging techniques including x-ray, CT, MRI and

3D ultrasonography (Gurney, 2002), however the standard clinical approach is to use the mean of two measures (Beattie, Isaacson, Riddle, & Rothstein, 1990) from anterior superior iliac spine to medial or lateral malleolus (Woerman & Binder-Macleod, 1984). The literature shows little consensus regarding the clinical threshold for orthopedic issues secondary to LLI, reporting a large minimum range (3-49 mm) for risk of developing posture and balance problems, stress fractures, low back pain and gait asymmetry (Gurney, 2002; Kaufman, Miller, & Sutherland,

1996; Kendall, Bird, & Azari, 2014).

Thus, in spite of apparent lower limb bilateral symmetry, there are side-to-side skeletal and soft tissue differences between the legs. The left side tends to be longer, denser and heavier, which is consistent with the conventional assumption that it is the stability or support limb.

24 However, these findings are sufficiently modest and variable to not be incompatible with stability function shifting from one limb to the other in a task dependent manner.

Gait

Walking is a defining human activity comprising a sequence of rhythmically repeated, alternating lower limb manipulation and stability tasks, and is conventionally considered to be bilaterally symmetrical in able-bodied individuals (Sadeghi et al., 2000). This presumption of symmetry has resulted in much of the research into normal gait relying on measurement of only one side to simplify data collection and analysis (Gundersen et al., 1989). In a similar way, a major aim of lower limb rehabilitation for clients with a wide range of unilateral neurological and musculoskeletal conditions is the restoration of presumed premorbid bilaterally symmetrical gait (Cikajlo & Bajd, 2003; Yang et al., 2012). The conditions described below are commonly seen in rehabilitation settings and typically result in pathological gait that deviates significantly from the “normal” bilaterally symmetrical pattern. Stroke patients tend to produce significantly more mechanical power during stance phase on their unaffected side (Mahon, Farris, Sawicki, &

Lewek, 2015); patients with recent total joint arthroplasty exhibit reduced operative joint range of motion and vertical ground reaction force (GRF) on the affected side (Li et al., 2015); lower limb amputees have reduced stance time and vertical and horizontal impulses on the prosthetic side (Schaarschmidt, Lipfert, Meier-Gratz, Scholle, & Seyfarth, 2012); patients with Parkinson’s disease show asymmetrical stride-to-stride variability, increased cadence, decreased gait velocity and arm swing (Ricciardi et al., 2015); and patients recovering from ACL reconstruction surgery undergo increased affected side knee flexion during weight acceptance and a smaller internal knee extensor moment during affected side stance phase (Di Stasi, Logerstedt, Gardinier, &

25 Snyder-Mackler, 2013). Rehabilitation with these types of clients is directed at assisting them to regain the efficiency and cosmesis of their walking specifically through identification of the underlying causes of their present gait asymmetry (e.g. muscle weakness, altered muscle tone, reduced joint range of motion, or pain) and provision of gait retraining with the goal of re- establishing their presumed premorbid symmetrical pattern.

However, there are reports in the literature of “normal” gait showing asymmetry, such as stance phase hip acceleration being 14% greater on the left side (Horvath, Taylor, Marsh, &

Kriellaars, 2007); EMG muscle profiles showing a greater activation level corresponding to stronger “push off” with one calf (Ounpuu & Winter, 1989); varying maximum knee extension ranges (Gundersen et al., 1989) and toe-out angles (Zverev, 2006); and greater amplitude of arm swing on the left than the right (Kuhtz-Buschbeck, Brockmann, Gilster, Koch, & Stolze, 2008).

As stated previously, LLI is the most common anatomical asymmetry, and its magnitude determines whether it is considered normal or pathological and hence its likelihood of having an impact on function. Kaufman et al. (1996), for example, reported the LLI threshold for gait asymmetry “greater than that observed in the normal population” to be >20 mm (p. 144). Gait asymmetries in the pathological range include reduced short limb stance phase and greater vertical GRF and peak plantar pressures on the long limb side (Perttunen, Anttila, Södergård,

Merikanto, & Komi, 2004). It is unknown whether lateralized stability and manipulation roles of the legs (and any related non-pathological anatomical differences such as LLI) manifest as bilateral asymmetry in able-bodied gait. There is a need for studies specifically examining the relationship between gait asymmetry and lower limb preference and performance for

26 manipulation and stability using bilateral data from both males and females. These findings would inform researchers regarding the need for bilateral data collection in studies involving gait, and rehabilitation clinicians regarding the setting of more rational goals for gait retraining of patients with neuromusculoskeletal anatomical and functional differences.

In summary, the convention in the sport and rehabilitation literature for the leg contralateral to the manipulation preferred leg to be assigned a stability dominant role is not strongly supported in the literature. A growing body of work has shown a stability task dependency for footedness based on preference and performance, raising questions regarding the type of stability items that should be included in footedness instruments, and on the automatic relegation of the leg contralateral to the manipulation preferred leg to a stability role. Further study is required to expand understanding of task dependency in functions such as static and dynamic balance, and the interrelationship between stability preference and performance.

FUNCTIONAL ASYMMETRY AND ITS RELATIONSHIP TO

INJURY MECHANISM

Functional asymmetry of the lower limbs may be a contributing factor in the incidence of lower limb musculoskeletal injuries. There is evidence of a relationship between lower limb dominance, sex, and the incidence of ACL injury. Young female soccer players are at four to six times greater risk of ACL injury than their male counterparts (Filipa, Byrnes, Paterno, Myer, &

Hewett, 2010; Hewett, Ford, Hoogenboom, & Myer, 2010). In the case of non-contact ACL ruptures, female soccer players are more than twice as likely to injure the ACL of their non-

27 dominant side as their dominant side, and two to three times more likely to injure their non- dominant side ACL than are males (Brophy et al., 2010). Reudl et al (2012) found a very similar incidence among skiers with young females rupturing the ACL of their non-dominant leg at twice the rate of equivalent males. In soccer, males show no significant relationship between lower limb dominance and ACL injury in non-contact incidents (Brophy et al., 2010; Waldén et al., 2015).

In a systematic video analysis of 39 ACL injuries involving top male FIFA soccer players that occurred during matches between 2001 to 2011, Waldén et al. (2015) reported that 85% of the injuries featured non- or indirect contact, and most commonly occurred with deceleration associated with cutting manoeuvres (Pappas et al., 2015)

In June, 2014, the author conducted a review of ACL injury video clips posted on

Youtube as a component of this research project (see Appendix 1 for summary). Twenty-five video clips were available, consisting of 19 male and 6 female athletes who had been filmed in the moments they sustained their ACL injuries while engaged in sports such as basketball, soccer, tennis, gymnastics and BMX. Similar to the findings subsequently published by Waldén et al. (2015), the mechanism was observed to be overwhelmingly non-contact (96%), and the most common circumstance at the time of injury was sudden deceleration, often accompanied by a change in direction (e.g. the cutting manoeuvre). Injuries sustained by the female athletes were

100% non-contact and involved their left (conventionally “non-dominant”) knee at twice the rate of their right, in keeping with the report of Brophy et al. (2010). By comparison, only 42% of male injuries involved the left knee. The underlying mechanism for the very high ACL injury rate

28 on the non-preferred (conventionally “stability dominant”) side in females in non-contact incidents has not been definitively established, but could relate to sex differences in differential manipulation and stability proficiency between the lower limbs.

In ACL injury studies, the methodology of footedness assignment may be contributing to misleading results. For example, studies examining ACL injury (Andersen, Floerenes, Arnason,

& Bahr, 2004; Anderson et al., 2000; Brophy et al., 2010; Faude, Junge, Kindermann, & Dvorak,

2005) may have assigned the manipulation preferred limb by asking a variation of the question

“Which is your preferred kicking leg?”, and then automatically designating the side opposite as the stability limb. This is problematic due to the possibility that stability is task dependent

(Kiyota & Fujiwara, 2014). Therefore, researchers and clinicians may have been identifying

ACL failure to be happening on the “stability dominant” side, when really the stability status of that limb was unknown. A more evolved and precise definition of footedness is required to understand the mechanisms underlying injuries such as ACL that feature lateralized incidence in both males and females.

Since sidedness is a known difference between males and females in ACL injury incidence, studies involving cutting manoeuvres should assign footedness appropriately and compare sexes and movement proficiency bilaterally. However, the vast majority of recent publications examining cutting as an ACL injury mechanism failed to incorporate these factors in study design. Of the 21 most recent cutting related articles (2012-16), only 13 objectively assessed lower limb cutting, and of those only three compared males and females, only three studied lower limb motion bilaterally, and none of the 21 studies examined motion bilaterally in

29 both males and females (Azidin, Sankey, Drust, Robinson, & Vanrenterghem, 2015; Bates,

Nesbitt, Shearn, Myer, & Hewett, 2015a, 2015b; Collins, Almonroeder, Ebersole, & O'Connor,

2016; Cong, Lam, Cheung, & Zhang, 2014; Cronin, Johnson, Chang, Pollard, & Norcross, 2016;

Dai et al., 2015; Delahunt et al., 2013; Dowling, Favre, & Andriacchi, 2012; Jones, Herrington,

& Graham-Smith, 2016; McGovern et al., 2015; Nagano, Sasaki, Higashihara, & Ishii, 2016;

Pappas et al., 2015; Pappas, Shiyko, Ford, Myer, & Hewett, 2016; Pollard, Stearns, Hayes, &

Heiderscheit, 2015; Sankey et al., 2015; Sheu, Gray, Brown, & Smith, 2015; Sugimoto et al.,

2015; Wesley, Aronson, & Docherty, 2015; Zaslow et al., 2016).

Thus a study comparing right to left cutting asymmetry in relation to sex and footedness, done in the context of a more developed footedness definition that no longer oversimplifies stability dominance to the side opposite the preferred limb, could improve understanding of ACL injury mechanism and the very high, skewed incidence rate of this injury in young females, and inform development of prevention and treatment strategies.

30 AN OPERATIONAL DEFINITION OF FOOTEDNESS

In 2009, Grouios et al. observed footedness to be a complex behaviour that had resisted unified explanation, and this remains a valid comment today. In his seminal 1988 article on footedness, Peters provided a sweeping review of the development of the construct, before presenting his classic definition for the preferred foot as the one to manipulate or lead out, and the nonpreferred foot to provide postural support and stability. This definition continues to be highly influential, and Table 4 traces its direct lineage in the literature from 1988 to the present.

A review of the 25 studies published between 2010 and 2016 that incorporated footedness determination in their protocols (search details p. 13) shows that their operational definitions of footedness (expressed either explicitly or implicitly through the type of footedness measures utilized in their studies) continue to align strongly with Peters’ manipulation role for the preferred foot (Bohm, Mersmann, Marzilger, Schroll, & Arampatzis, 2015b; Schneiders et al.,

2010; Wang & Newell, 2014).

The most significant change regarding footedness since the publication of Peter’s paper relates to the role of the nonpreferred foot and the growing recognition of task dependency of lower limb stability function. Rather than being a permanent characteristic of the nonpreferred limb, studies have shown stability preference and performance distribution to span both the right and left legs, depending on the context and particular stability subdomain involved (for detailed review and supporting references, see section: Task Dependency and Stability Function, pp. 21-2). Changes in functional context, including unilateral or bilateral lower limb support, level of task complexity, static or dynamic balance subdomain, and perturbation frequency within the dynamic balance subdomain have been found to elicit a side-to-side shift in the laterality of

31 lower limb stability preference and performance (Hart & Gabbard, 1997; Kiyota & Fujiwara,

2014; Teixeira, De Oliveira, Romano, & Correa, 2011). Given this multi-faceted, bilateral distribution for stability, the set of preference measure questions or battery of performance tasks used for dichotomous assignment of footedness will require investigation to ensure that the appropriate mix of stability questions has been included.

Peters’ assumption that the stability role of the nonpreferred limb is less neurologically demanding than the preferred limb’s “focal” manipulation role (Gabbard & Hart, 1996) is under review due to evidence suggesting the stability role, though subtle, is neurologically complex and involves all body segments (Wang & Newell, 2014). The impression that there is less neurological demand involved with the support leg than the mobilizing leg during kicking could be due to the distinction between data derived under the controlled, static conditions of laboratory testing and the vigorous, dynamic reality of actual match conditions (Carey et al.,

2001). It is realistic to consider that the neurological demand of the support leg in the simultaneous achievement of precise, optimal foot placement adjacent the ball and controlled deceleration of the rapidly moving body in a game situation must be at least equivalent to the neurological demand of the manipulation limb to deliver the actual kick.

In developing an operational definition of footedness, it is reasonable to begin with

Peters’ definition (1988), as it has received wide acceptance over many years (Table 4). Peters’ initial contention that the role of the preferred foot can be defined as the manipulator or the foot to lead out is supported by the foregoing literature review, although the wording requires realignment with the improved terminology developed for this project that explicitly identifies

32 the functional characteristic involved and uses “lower limb” rather than “foot” as the more representative term. Peters’ follow-up contention regarding the role of the nonpreferred foot as the provider of postural support and stability is no longer adequate as it does not agree with the more recent findings of task dependent behaviour of stability function of the legs. Leading the thinking regarding the emerging multifaceted nature of lower limb stability, Gabbard & Hart

(1996) postulated that footedness should be operationally defined in terms of the behavioural context and complexity of the task (p. 295). The operational definition for footedness proposed for this project supports their approach, as follows:

Footedness is operationally defined as the foot that can be identified with familiar

manipulation tasks and a combination of context dependent stability tasks.

As discussed, the known contexts to be considered include unilateral and bilateral weight bearing, complexity and familiarity, static and dynamic balance, and perturbation frequency. The exact combination of stability contexts and tasks has yet to be determined. Studies need to be conducted which examine the task dependent context contribution to the determination of footedness. The operational definition for footedness will be explored in light of the project findings.

33 PURPOSE

The purpose of this study is to characterize footedness based on preference and performance. Greater knowledge of the relationship between the manipulation and stability roles of the lower limbs will improve understanding of sex differences in functional mobility including the cutting manoeuvre that contribute to the disproportionately high incidence of serious knee injury in young female athletes.

RESEARCH AIM

The aim of this project is to assess each individual item from two widely used footedness preference measures and an additional set of performance tasks for their laterality characteristics and relationship to the operational definition of footedness.

RESEARCH QUESTIONS AND GENERAL HYPOTHESES

Footedness Preference

Research Questions

1. What are the contributions of manipulation and stability items in determining the

assignment of footedness preference?

2. Is stability sidedness task dependent?

34 Hypotheses

 Stability preference will exhibit a multi-modal distribution and sidedness.

 Static stability preference will be assigned to the right side.

 Dynamic stability preference will be assigned on the left side.

Footedness Performance

Research Questions

1. Is stability sidedness task dependent in terms of static, dynamic and reach performance?

2. What is the relationship between preference and performance measures?

Hypotheses

 Static stability performance will demonstrate right-sided laterality.

 Dynamic stability performance will demonstrate left-sided laterality.

 Preference and performance measures will be coherent.

The proposed operational definition for footedness will be explored in light of these findings.

35 Asymmetry in Functional Tasks

Research Questions

1. Does laterality manifest as asymmetry in walking and running gait?

2. Does sex dependent asymmetry manifest in cutting?

Hypotheses

 There will be right to left differences in gait spatiotemporal parameters.

 There will be sex dependent differences in acceleration magnitudes during cutting.

It is important to characterize the impact of the participants’ footedness using the proposed operational definition on the between sexes sidedness of cutting and other functional activity. It will show that there are stability differences between the sexes and that the stability preferred/performance lower limb is not simply the limb contralateral to the manipulation preferred/performance lower limb as is commonly assumed in the ACL injury literature.

36 METHODOLOGY

EXPERIMENTAL DESIGN

This study utilized a cross-sectional, observational design and was conducted at the

Bannatyne campus of the University of Manitoba from May to October, 2012. Approval of the study was granted by the Health Research Ethics Board at the Bannatyne Campus, University of

Manitoba (Ethics File Number H2012:074) on February 27, 2012, prior to participant recruitment.

PARTICIPANTS

Recruitment

Fifty-two participants were recruited through word of mouth and posters displayed at various locations around the Bannatyne campus of the University of Manitoba.

Inclusion and Exclusion Criteria

Participant recruitment was open to males and females aged between 16 and 45 years who were in good health and had the ability to comprehend written and spoken English.

Excluded were individuals with current symptoms related to lower limb injury or surgery, and pregnant or lactating females.

37 PARTICIPANT CHARACTERISTICS

There were 52 participants consisting of 25 females and 27 males. The physical characteristics of the participants are shown in Table 8. The number of participants who were overweight (BMI >25< 30) was 13 (25%), while none were obese. Self-report of exercise frequency revealed that six participants exercised less than 1x/week, 12 reported 2-3x/week, 21 were more than 3x/week, 11 were daily exercisers, and two reported elite competitive training.

Table 5. Participant characteristics. Female n = 25 Male n = 27 Parameter Mean SD Mean SD Age (years)* 23.4 4.53 28.6 7.24 Height (cm)* 165.7 6.76 177.6 5.03 Body mass (kg)* 62.4 7.79 76.1 10.79 BMI, p=0.07 22.7 2.13 24.1 2.87 * p< 0.05, between sex, independent t test, two tailed

Mean structural (anatomical) leg length on the right was 81.87 cm (SD 4.87) and on the left was 82.16 cm (SD 4.87), with a difference of 0.298 cm (p=0.005). Mean functional

(postural) leg length on the right was 90.23 cm (SD 5.3) and on the left was 90.49 cm (SD 5.4), with a difference of 0.260 (p=0.003). Twenty-seven participants had left legs longer than right,

11 had right longer than left, and 14 had legs of equal length.

38 PROTOCOL

Participants were instructed to avoid heavy exercise in the 24 hours preceding the testing session, and to wear athletic shorts, T-shirt or tank top and running shoes. The duration of the testing session was 1 1/2 to 2 hours. The list of participant assessments is shown in Table 5.

Table 6. Participant assessments included in study. Type Assessment Domain Anthropometry Height, body mass, leg length Physical measurements Preference Stability and Manipulation Evaluation (SAME) Self-report & behavioural questionnaires Performance Targeting Test (“Single Limb Targeting”) Manipulation Static Balance Test (“Stork”) Stability - static Dynamic Balance Test (“NuStar”) Stability - dynamic Reach Balance Test (“Star Excursion”) Stability - reach Gait: Walking (3 mph) and Running (6 mph) Functional Cutting Functional

Order Effects

Fatigue and learning were two possible confounders that were addressed in the experimental design by utilization of a balanced order and allocation of two minute rest periods between tasks (Table 6). Males and females were entered into the study in a balanced manner.

Table 7. Order effects table. Percentage of Order of Assessment Components Participants 25% Component A: R then L, followed by Component B: R then L 25% Component A: L then R, followed by Component B: L then R 25% Component B: R then L, followed by Component A: R then L 25% Component B: L then R, followed by Component A: L then R

39 Assessment Component A: Manipulation and Stability Tasks

1. Targeting Test

2. Static Balance Test

3. Dynamic Balance Test

4. Reach Balance Test

Assessment Component B: Functional Tasks

1. Gait

a. Walking (3 mph)

b. Running (6 mph)

2. Cutting

INSTRUMENTS AND ASSESSMENTS

Anthropometry

Participants’ mass (kg) and height (cm) were measured utilizing a mechanical beam scale and height rod. Leg length (cm) was measured bilaterally with a steel measuring tape as follows: structural (anatomical) length was measured ipsilaterally from greater trochanter to lateral malleolus in supine, and functional (postural) leg length was measured ipsilaterally from anterior superior iliac spine to lateral malleolus in standing.

40 Preference Assessment

Stability and Manipulation Evaluation Questionnaire (SAME)

Participants completed the SAME, an electronic, composite self-report and behavioural preference instrument (Appendix 1). The SAME combines the Waterloo Footedness

Questionnaire-Revised (Elias et al., 1998) and the Chapman inventory of foot preference

(Chapman et al., 1987; Sokal & Allen, 2008). The SAME also includes some additional items created by the author, including several background laterality and stability questions and two manipulation questions (one self-report and one behavioural).

The Waterloo questionnaire consists of 10 items (five manipulation and five stability) and utilizes a five point weighted scale (Figure 2). The total Waterloo score is determined as the sum of the weighted responses of all 10 items. Scores below zero assign the participant to left preference, scores above zero to right preference, and aggregate scores of zero to an “either” preference. In addition, scores were tabulated for the five manipulation and five stability items separately to allow assignment for “manipulation preference” and “stability preference”.

Waterloo Scoring -2 -1 0 1 2 Always left Usually left Either Usually right Always right

Figure 2. The Waterloo Footedness Questionnaire-Revised weighted scale.

The Chapman inventory consists of 11 items (10 manipulation and one stability). The original version of the Chapman inventory had two additional stability items (subsequently removed due to low scores) for a total of 13, including 10 manipulation and three stability. These

41 two original stability items were included in the SAME questionnaire to enable capture of additional data for enhanced insight into preferences for stability tasks (Appendix 2). The score for the Chapman inventory was tabulated for the 11 items using the following weighting: -1 for left, 0 for equal, +1 for right. In addition, scores for the 10 manipulation items and all three original stability items were tabulated.

The Waterloo and Chapman instruments were selected for inclusion in the SAME due to their popularity and their differing composition in terms of stability and manipulation items. This difference will enable a contrast to be made between the almost exclusive manipulation orientation of the Chapman inventory with the balanced manipulation and stability perspective of the Waterloo questionnaire, and essentially serve as an examination of the validity of these two approaches.

Laterality Indices

Four indices were derived for characterization of laterality (footedness) of preference and performance assessments: Laterality Coefficient (LC), Laterality Percentage (L%), Right to Left

Ratio (RL), and Ambiguity as defined below. Laterality Coefficient and Laterality Percentage are conventionally reported in laterality research (Oldfield, 1971), however it is interesting to note that these two indices are rarely differentiated in publications despite the fact that they are not equivalent. The Right to Left Ratio is derived from the standard laterality indices but reflects a ratio that is suitable for the sample size used in this study. Ambiguity (%) was calculated to characterize the instruments or instrument items based upon the percentage of responses that included “either or both”. This index could reflect either ambidexterity or the uncertainty of the

42 participant in choosing a limb based upon familiarity with the task, the complexity of the task, or even the clarity of the wording describing the task.

Laterality Coefficient

– LC = [(R – L) / (R + L)] x 100

– -100% is all responders indicating left and 100% is all responders indicating right.

– LC ignores the responses indicating “equal” or “either”.

Laterality Percentage

– L% = # of R / Total x 100

– L% represents the percentage of total participants with right preference.

– Range of L% is 0 to 100%, with <50% corresponding to left preference and >50%

corresponding to right preference.

Right to Left Ratio

– RL = # of R / # of L

– RL should be >5.5 given 85% lower limb laterality of the general population with

n=52.

Ambiguity (%)

– Ambiguity % = (# of “equal” or “either” limb / total) x 100

– Ambiguity % represents the percentage of ambidextrous participants, or those

who may be uncertain of their response as the questionnaires do not provide an

43 “unsure” check box.

– It is a simple (limited) “familiarity index”, developed in direct response to the

need in the literature.

Assignment of Manipulation Preference

In order to determine the manipulation preferred lower limb, the laterality indices were utilized to identify items with suitable laterality characteristics consistent with published literature. The laterality thresholds (LC and L%) were based on a study involving a large adult sample (N=3,307) that employed four items: kick, pick up pebble, stomp on a bug, and step-up

(Coren, 1993). Three of these four items are clearly manipulation in character, and one (step-up) is a combined manipulation and stability task. Interestingly, all four items were subsequently included in the Waterloo questionnaire. Coren (1993) found that 86.3% of the participants were right foot preferred, so the current study conservatively identified only those items with a

Laterality Percentage greater than 85% and a Laterality Coefficient greater than 80% (LC does not include the “either or both” participants). Due to the fixed sample size of 52 participants in this study, the Right to Left Ratio was derived for an 85R:15L and a 90R:10L split. The corresponding RL ratios were 5.5 (44/8) and 9.4 (47/5), so 5.5 was conservatively selected as the sample size specific threshold. For Ambiguity, items with a high percentage of answers that were

“either” or “both” legs were eliminated using a threshold of 10%. In summary, the thresholds applied for item selection were LC >80%, L% >85%, RL >5.5, and Ambiguity <10%.

The assignment of the manipulation preferred lower limb was based on the aggregate score from the top five items from the Waterloo and Chapman instruments identified with these

44 population-based laterality criteria. In addition, the two items from the SAME additional questions (self-report: pick up ring with toes, and behavioural: write initials on floor with toe) were identified as having characteristics that met the laterality criteria. In fact, the assignment of footedness preference using the aggregate score of the top five questions from the Waterloo and

Chapman instruments was found to be identical to the assignment using the aggregate score from the two items from the SAME additional questions (Table 22). This assignment was then used for the purposes of receiver operating characteristic and binary logistic regression analysis.

Performance Assessments

Performance assessments were completed for manipulation, stability and functional tasks as listed in Table 5. The rationale for the selection of the performance tasks for each category is discussed below, followed by a detailed description of each individual performance task.

Rationale for Selection of Performance Assessments

It was important that this footedness study include both preference and performance assessment given the known “magnification” effect from handedness performance to preference laterality.

Manipulation

The manipulation performance assessment of Single Limb Targeting, a foot placement accuracy task performed in a single (transverse) plane, was based on established upper limb uniplanar manipulation tasks used in laterality research such as the peg board test (Brown et al.,

1993; Brown et al., 2004; Corey et al., 2001). It is also representative of the “bug stomp”

45 manipulation preference question in the Waterloo instrument, and has also been utilized in a number of studies as a miscellaneous item for assigning footedness (Figure 1, Group c). The task was performed in sitting to prevent the opposite limb from contributing to the targeting performance. Motion was limited to a single, medial-lateral dimension as it uniquely provided the participant with an unobstructed view of the edge of their test-side shoe relative to the target lines. As the test description will show, this was an essential condition for testing foot placement accuracy. Lower limb motion in the anterior-posterior dimension was considered but not utilized, as the participant’s view of the tip of their shoe relative to the target lines was found to be obscured by the shoe’s toe box. The choice of this task was guided by the need for precise measurement of manipulation function combined with a high degree of experimental control of potentially confounding variables, however external validity may have been slightly limited as a result. It should be noted that the study did not include a standing kick performance task as the complexity of this action would have introduced multiple confounding variables related to the kicking leg (type of kick - e.g. instep, toe, etc., propulsion requirements – e.g. speed, direction, distance, etc.), the non-kicking leg (combined manipulation and stability demands), and the equipment (ball and target specifications). A comprehensive study of kicking performance and its relationship to simple, single limb targeting performance is needed, but was beyond the scope of the current study and hence is a delimitation.

Stability

The stability performance assessments overall were comprehensive from a content validity perspective. The Stork test is a research standard for static balance assessment in the literature, having high face, content, construct, and internal validity, and mildly lower external validity. The

46 Star Excursion test is well-accepted in the literature as a lower limb stability test, however it suffers from internal and construct validity issues related to its performance being dependent on numerous variables including response bias due to a significant learning effect, and movement strategy differences that are potentially dependent on familiarity and flexibility. The NuStar balance test was selected in response to the need for dynamic balance assessment to increase the project’s overall content validity of stability assessments. As well, a range of stability tasks was indicated due to prior research findings of task dependence for preference and performance in stability function.

Functional

Functional assessment examined the two basic forms of human locomotion of walking and running through analysis of treadmill gait. Treadmill gait exhibits very high overall validity with some limitations (e.g. is limited to one primary plane of motion similar to the single limb targeting task), however it allows a high degree of experimental control. The second functional assessment, the cutting task, was selected based upon its high external validity as a manoeuvre that is strongly associated with lower limb injury. Recent injury research studies have primarily utilized evaluations involving 45° or 90° cuts. The more abrupt 90° cut was selected for this study in order to amplify the performance differences between the two sides.

47 Manipulation Performance Assessment Procedure

Targeting

Setup and Procedure: Manipulation performance of the lower limbs was assessed with a

Single Limb Targeting test in the transverse plane, consisting of moving the foot to one of two laterally located targets (Photo 1).

Photo 1. Targeting assessment setup. The left photo shows the lateral view of participant positioning for testing of the right foot, and the right photo shows the superior view. The start line and target lines #1 and #2 for the right foot are shown (7.5 cm spacing).

Participants perched on a dense but moldable cushion (20 kg bag of salt) placed on a height adjustable stool. The stool height was adjusted so the hips and knees were flexed to 35°, and the cushion was molded around the pelvis to ensure stability without restricting lateral motion of the test limb during targeting. Participants were instructed to maintain a comfortably erect posture with both feet flat on the floor, and to distribute their body weight evenly over their buttocks and non-test foot to eliminate any support role for the test foot.

48 Three 30 cm strips of adhesive tape were arranged on the floor in a parallel, anterior- posterior orientation 30 cm in front of the participant’s feet. There was a 7.5 cm separation between the midlines of each strip. For testing of the right foot, the left-hand strip was the start line, the middle strip was target #1 (7.5 cm) and the right-hand strip was target #2 (15 cm). This order was reversed for testing of the left foot. The video camera was positioned 2.5 m anterior to the midpoint of the target strips at a height of 1.0 m and with a forward inclination of 20° to ensure an unobstructed view of the start line, the two targets and the lateral border of the participant’s test foot at all times. The starting position for the test foot was approximately midway along the length of the start line with the lateral border of the shoe at the fifth metatarsal head placed as close to the edge of the strip as possible. A prerecorded, digital audio file was used to present a series of 20 spoken commands, one every three seconds, instructing participants to move to target #1 or #2 (10 per target) in a randomized order to minimize anticipation. On receiving the command, participants quickly moved their test foot laterally, placing it flat on the floor with the lateral border of their shoe as close as possible to the nominated target and then returning it to the start line to await the next command. Participants had an unobstructed view of the targets and the lateral border of their shoe at all times throughout the test.

Assessment: Participants were evaluated with high speed digital video (Casio EX-FH100,

120 fps, 640 x 480 resolution). Targeting accuracy was computed using video motion analysis software (Kinovea, Version 0.8.15) to examine the 10 repetitions for target #2 only. The start and finish markers were digitized (x,y coordinates), and a scale factor was derived using the known distance (15 cm) for target #2. For each repetition, the lateral border of the shoe at the level of the fifth metatarsal head was used to demark the location of the foot placement for each target

49 attempt. The targeting error was calculated as the difference between the target line and foot placement, and expressed as a percentage of the total distance. For each foot, the average percentage error (of 10 repetitions), maximum error (%) from 10 repetitions, and the coefficient of variation (CV) were computed. For laterality assessment (dominance), the laterality percentage and laterality coefficient were computed based upon the maximum and average error, as well as the CV per side.

50 Stability Performance Assessment Procedures

Three functional stability measures were selected to be utilized in this study in order to advance understanding of different aspects of stability dominance. The measures assessed static and dynamic stability, and a reaching task combined both stability assessment of the stance limb and manipulation assessment of the reaching limb.

Static Balance

Setup and Procedure: A single leg support test, the Stork test, was used to assess lower limb pseudo-static stability. Participants were evaluated using a trunk mounted, wireless triaxial accelerometer (G-Link wireless accelerometer, Micro-strain, 120 Hz sampling) to measure body sway. Participants were positioned facing a featureless screen with eyes open and arms folded across the chest. They were instructed to stand on the test leg with the dorsum of the non-test foot hooked behind the test knee to inhibit the non-test leg from assisting with maintenance of stability. The test consisted of participants maintaining single leg stance for 30 seconds, following which the task was repeated using the opposite leg.

Assessment: A total of four, 30 second trials were performed for each lower limb. Only the first and fourth (last) trials were recorded for analysis. The average of the first and fourth

(last) trials was used for analysis. This average represented the novel exposure of the first trial and the task experience and potential fatigue of the fourth (last) trial in order to provide the greatest opportunity for capturing differences between sides. The resultant acceleration of the three axes of acceleration was computed (Figure 3). Measures of variability of the resultant trunk acceleration were range, SD, and RMS derived from the first 20 seconds of the trial. For

51 laterality assessment (dominance), the laterality percentage and coefficient were computed based on the average SD per side.

1 0.98 0.96

0.94 Accleration(g) 0.92 0.9 0 500 1000 1500 2000 2500 Sample

Figure 3. Resultant trunk acceleration for a representative static balance trial (20 seconds).

Dynamic Balance

Setup and procedure: A single leg support balance test, the NuStar balance test, was used to assess dynamic stability (Photo 2). Participants stood on the test (support) limb facing a suspended target located 0.50 m anterior to their sternal manubrium. Their non-test hip and knee were maintained in a comfortable, moderately flexed position throughout the assessment to avoid that foot contacting the floor and assisting with balance. Four 15 cm high pylons were placed on the floor around the test foot in a “star” pattern (anterior, posterior and to either side), each at a distance of 0.50 m. Participants were instructed to use their test-side index finger to touch the suspended target and then each pylon in turn (anterior, lateral, posterior, and lateral). Participants completed one clockwise circuit of pylon touches followed by one counter-clockwise circuit on each foot (i.e. a total of eight pylon touches on each foot). A one minute rest was provided

52 between circuits.

Photo 2. The starting position for the NuStar test is shown on the left. A single trial of anterior pylon touch during left lower limb single support is shown on the right.

Assessment: The total number of losses of balance resulting in actual touchdowns of the non-test foot to the floor were tabulated for each test foot, and for each direction (one clockwise and one counter-clockwise circuit). Also, the total number of participants who lost balance and touched down for each stance leg was derived. For laterality assessment (dominance), the laterality percentage and laterality coefficient were computed based upon the number of participants who lost balance per side, as well as the total touchdowns per side.

53 Reach

Setup and Procedure: Participants’ lower limb reach was assessed using the Star

Excursion test (Filipa et al, 2011; Plisky et al, 2006), which is a lower limb task incorporating both stability (support) and manipulation (targeting). Participants stood on their test foot with the tip of their great toe at the intersection of three 2.00 m straight strips of adhesive tape arranged on the floor in a three limb star pattern (i.e. lines radiating out at 120° to each other in anterior, posteromedial and posterolateral directions). Participants were instructed to reach with their non- test foot as far as possible along each of the three lines in turn without moving their test (stance) foot, returning the non-test foot to be adjacent the test foot following each reach. This sequence was repeated seven times on each leg, the first five trials being discarded as there is a well documented accommodation period.

Assessment: Participants were evaluated using a steel tape to measure the reach of their non-test lower limb from the centre of the star along each of three axes for the final two circuits.

The average reach distance for each direction and foot was calculated, and expressed as an absolute length (cm) and relative to the participant’s ipsilateral structural leg length. Further, the sum of the average reach distances along each of the three axes was determined and expressed with respect to leg length. For laterality assessment (dominance), the Laterality Percentage and

Laterality Coefficient were computed based upon the height normalized reach distance for each of the three directions.

54 Functional Performance Assessment Procedures

Gait - Walking (3 mph) and Running (6 mph)

Setup and Procedure: Two forms of gait, walking and running, were used to assess temporal gait symmetry. The tests were conducted on a treadmill, and high speed digital video

(Casio EX-FH100, 120 fps, 640 x 480 resolution) was recorded for each gait speed trial. Two cameras were utilized, one positioned on each side of the participant at a distance of 1.50 m perpendicular to the treadmill midline and at a height of 0.50 m to ensure unobstructed lateral views of the participant’s full heel-to-toe shoe contact with the treadmill belt while ambulating.

1) The Walking test consisted of a single two minute trial of treadmill walking at a belt

speed of 1.34 m/s or 3 mph. The participant straddled the stationary treadmill belt

while holding onto the railing, the test speed was set and the belt was activated. Once

the test speed was attained, the participant stepped onto the moving belt with their

right foot, released the railing when confident and commenced regular ambulation.

After two minutes of uninterrupted ambulation, the participant was instructed to

carefully step off the moving belt with their right foot first and the treadmill was

stopped. The participant was given a two minute break before proceeding to the

running test.

2) The Running test consisted of a single two minute trial of treadmill running at a belt

speed of at 2.68 m/s or 6 mph. The procedure for the test was identical to the walking

test (above), but utilized the higher belt speed.

55 Assessment: The digital video was imported into motion analysis software (Kinovea, www.softonic.com) and the time was recorded for intial contact (heel strike) and pre-swing (toe- off) for four consecutive steps plus the initial contact of the next step. The total gait cycle duration was computed using the consecutive initial contacts from the same side. Two stance and swing durations were computed for each side. The average stance and swing durations for the right and left sides were derived. Laterality was assessed by identifying asymmetry in stance and swing phase durations between the sides.

Cutting

Setup and Procedure: Participants performed a 90° cutting manoeuvre on each lower limb, and evaluation was with a trunk mounted, wireless triaxial accelerometer (G-Link wireless accelerometer, Micro-strain, 120 Hz sampling). Participants stood behind the start line facing two foot-sized corrals outlined in adhesive tape on the floor 0.65 metre anterior to the start line and 0.50 metre apart. They were instructed to step forward explosively, plant their test foot in the ipsilateral corral, immediately change their line of progression medially by 90° (i.e. perform a

“90° cut”) to plant their non-test foot in the adjacent corral, and then quickly step back to the starting point. Participants repeated the same cutting sequence with the opposite leg. There were two practice trials on each leg before the final two trials were recorded for analysis to obtain data from a “left to right” cut on the left limb, and a “right to left” cut on the right limb.

Assessment: The resultant trunk acceleration was derived from the three axes of acceleration using the Pythagorean formula. Figure 4 shows the resultant trunk acceleration for a left to right cut. During single support on the cutting leg, the initial acceleration phase (P1)

56 represents the deceleration of the body after the approach, and the second peak (P2) represents the lateral acceleration during the 90° medial shift. The resultant acceleration waveform during single support bears a strong resemblance to the stance phase ground reaction force waveform as measured by force platforms. The time and peak magnitudes were extracted from the resultant acceleration waveform for P1 and P2. The ratio of P1 to P2 was derived. The duration from peaks P1 to P2 was also computed.

3.5 P1 3

2.5 P2

1.5

1 Resultant Acceleration (g) (g) Acceleration Resultant 0.5 Single Limb Support 0 840 850 860 870 880 890

Figure 4. Representative resultant trunk acceleration for a left to right cut. Phase 1 and 2 (P1 and P2) occur during the single support of the cutting limb (left plant). The P1 phase corresponds primarily to anterior-posterior deceleration, and the P2 to medial-lateral acceleration.

57 STATISTICAL ANALYSIS

SPSS 22 and Excel were used to compute descriptive and inferential statistics. P values less than 0.05 were considered to be significant. Trending values were reported when p was under 0.10.

Statistical Analysis for Preference Data

Histograms were used to describe the characteristics of the Waterloo and Chapman instruments (composite scores and sub-scores). Laterality indices were computed for the composite scores, the sub-scores and each of the items of the two instruments. Pearson correlation was used to relate composite and sub-scores of both instruments. Receiver operating characteristic (ROC) analysis was performed on the composite scores, the sub-scores and each of the items of the two instruments, and the area under the curve (AUC) was derived for each ROC curve. Binary logistic regression (BLR) was performed utilizing the manipulation and stability measures to predict the dichotomous variable of the manipulation preferred foot.

58 Statistical Analysis for Performance Data

Table 7 identifies the dependent variables and the primary statistical procedures utilized for each performance assessment. The laterality percentage was computed and reported for each assessment. In addition, a binary logistic regression was performed using the performance measures to predict the dichotomous variable “manipulation preferred lower limb”.

Table 8. The primary statistical method and dependent variable list for each performance assessment. Category Assess- Right vs. Male vs. Female Dependent Variables ment Left Manipulation Targeting Paired t-test Independent t-test Maximum error (%) Pearson Mean error (%) Correlation Coefficient of variation Stability Static Paired t-test Independent t-test Standard deviation Pearson RMS Correlation Dynamic Chi-square Chi-square test # of losses of balance test # of participants who lost balance Reach Paired t-test Independent t-test Step excursion (cm) in A, Pearson PM and PL directions Correlation Total excursion Functional Gait: Paired t-test Independent t-test Duration (ms) of gait cycle, Walking stance and swing phases Gait: Paired t-test Independent t-test Duration (ms) of gait cycle, Running stance and swing phases Cut Paired t-test Independent t-test Magnitude (g) of P1 and P2 phases P1/P2 ratio Left to right ratios of P1, P2 and P1/P2 A – Anterior, PM – Posterior-Medial, PL – Posterior-Lateral P1 – first acceleration peak during single leg support in cutting P2 – second acceleration peak during single leg support in cutting

59 RESULTS

LATERALITY CHARACTERISTICS

Participants reported right hand preference for manipulation of 96.1%. There was one left handed female and one left handed male. Right eye dominance was reported by 74%. Based on the Chapman inventory composite score, 92.3% reported their right foot as preferred for manipulation. Interestingly, 61.5% reported right foot preference for stability/support based upon the aggregate score of the stability questions from the Waterloo questionnaire. There were no left footed females, which is consistent with the findings of Coren (1993) who reported a statistically higher percentage of right footedness in females than males. When laterality was assessed using both upper and lower limbs, 90.4% of participants exhibited right handedness and right footedness (RR) characteristics. Of the 9.6% of participants with “left sidedness”, one was left handed & left footed (LL), 3 were right handed & left footed (RL), and one was left handed & right footed (LR).

MANIPULATION AND STABILITY PREFERENCE

Waterloo and Chapman Foot Preference Instruments

Histograms of the composite scores for the Waterloo and Chapman instruments are shown in Figure 5. The frequency distribution for the Waterloo composite scores is shown in the left panel. The Waterloo composite score can range from -20 (left) to 20 (right), given 10

60 questions with -2 to +2 weighting. Using the Waterloo composite score, two participants are identified as having equal footedness, five are left (one weakly) and 45 are right.

Figure 5. Waterloo (left panel) and Chapman (right panel) composite score histograms.

The right panel of Figure 5 shows the frequency distribution of the Chapman composite scores, which can range from -11 (left) to +11 (right) given 11 questions with -1 to +1 weighting.

It is evident in this histogram that there are two clusters of responses, one right and one left, with a gap spanning zero. Four participants are identified as left, while 48 are identified as right.

Interestingly, in the histogram of the Waterloo scores, two clusters are evident but the gap separating the clusters is not spanning the zero point. The four participants who were identified as left footed in the Chapman were identical to the cluster of four participants with greater negative scores in the Waterloo.

The classification of footedness and laterality is summarized in Table 9. Three participants (5.8%) were mismatched in footedness classification between the two instruments.

61 Accordingly, there was a difference in magnitude of the laterality indicators. The correlation between the composite scores of the two footedness instruments was only moderate (Pearson, r=0.68, p<0.01).

Table 9. Footedness classification and laterality characteristics based upon the composite scores for the Waterloo and Chapman instruments.

Waterloo Chapman Classification Right 45 48 (# of participants) Either 2 0 Left 5 4 Total 52 52

Laterality Indices L% 86.5 92.3 LC 80.0 84.6 AMBIGUITY 3.8 0.0 RL 9 12 L% - Laterality Percentage = # of R / Total x 100 LC - Laterality Coefficient % = [(R – L) / (R + L)] x 100 Ambiguity % = (# of “equal” or “either” limb / total) x 100 RL - Right to Left Ratio = # of R / # of L

In Table 10, the laterality characteristics of each item from the Waterloo and Chapman instruments are illustrated. The Chapman instrument items illustrated strong right sidedness based upon the key item-averaged laterality indicators (81.7 L% and 83.4 LC), which is consistent with published values. The Waterloo instrument items had lower overall average laterality scores (70.4 L% and 50.9% LC). Correspondingly, the average RL ratio was demonstrably higher for the Chapman items (16.9) than the Waterloo (5.2). The average ambiguity, referring to those people who answered “both equal” or “either”, was 10.9 and 6.9% for the Chapman and Waterloo instruments respectively. Using the laterality percentage, two

Waterloo questions were left oriented, both of which were stability questions (items 6 and 10).

62 However, the remaining stability questions (three from Waterloo and three from Chapman) were all right oriented. Based upon all the stability items, the laterality was right oriented (53.1 L%,

30% LC, RL = 2.0) and had an average ambiguity of 9.3%.

Table 10. Laterality indices for each of the items of the Waterloo (top 10 items - grey) and Chapman (bottom 13 items - light blue) instruments.

RL - Right to Left Ratio = # of R / # of L Ambiguity % = (# of “equal” or “either” limb / total) x 100 L% - Laterality Percentage = # of R / Total x 100 LC - Laterality Coefficient % = [(R – L) / (R + L)] x 100

Figure 6 shows the histograms for the Waterloo questionnaire separated based upon items related to manipulation (left panel) and stability (right panel). Comparison of the histogram of

63 the Waterloo manipulation scores to the histogram of the Chapman composite scores (Figure 5, right panel) reveals a very similar distribution and results in identical classification (4 left, 48 right), and therefore nearly identical laterality indicators.

Figure 6. Histograms of the aggregate scores of the Waterloo manipulation items (left panel) and Waterloo stability items (right panel).

The histogram of the aggregate score for the five Waterloo stability questions (Figure 6, right panel) is not as right skewed as previous histograms, and a tri-modal distribution is evident.

Using the Waterloo stability items for classification of laterality, there are 19 left, 1 equal and 32 right). The tri-modal distribution has one mode that is left, a mode slightly right and a mode moderately right.

Figure 7. Histograms of the aggregate scores of the Chapman manipulation items (left panel) and Chapman stability items (right panel). In the right histogram, the three stability questions from the original Chapman inventory were combined to create an aggregate score for stability. Note that the current version of the Chapman inventory has removed two of the stability questions.

The histogram for the aggregate score of the ten manipulation questions of the Chapman questionnaire is shown in the left panel of Figure 7. This histogram clearly resembles the overall

Chapman histogram (Figure 5, right panel) since it retains 10 of the 11 items. For the histogram shown in the right panel of Figure 7, the original three stability questions used in the first version of Chapman were combined to provide greater insight into modal characteristics of stability questions on categorization of laterality. Once again, similar to the Waterloo stability item aggregate histogram (Figure 6, right panel), a tri-modal distribution, albeit blunted, is suggested.

Interestingly, the assignment of footedness was similar when using the stability items from

Chapman (L16, E3, R33) and Waterloo (L19, E1, R32). The footedness assignment based upon stability items is in stark contrast to that returned by the manipulation items for either instrument

(48R, 4L for both).

65 Correlations between Composite and Aggregate Scores

The correlation matrix was computed between the composite and aggregate scores from the Chapman and Waterloo instruments (Table 11). It is interesting to note that the correlation between the two accepted footedness questionnaires is only moderate (r=0.681). The correlation coefficient is strong between the manipulation aggregate scores from Waterloo and Chapman

(r=0.8). Finally, there are only fair correlations between manipulation and stability aggregate scores for either Waterloo (r=0.443) and Chapman (r=0.356).

Table 11. Correlation matrix (r, p value) between composite and aggregate scores for the Waterloo and Chapman instruments. WaterMANIP WaterSTAB Chapman ChapMANIP ChapSTAB Waterloo 0.822 0.875 0.681 0.642 0.677 <0.001 <0.001 <0.001 <0.001 <0.001 WaterMANIP 0.443 0.792 0.8 0.379 0.001 <0.001 <0.001 0.006 WaterSTAB 0.398 0.329 0.744 0.004 0.017 <0.001 Chapman 0.986 0.474 <0.001 <0.001 ChapMANIP 0.356 0.01

Multimodal Nature of Stability Preference

In order to investigate the contribution of stability items from Waterloo and Chapman to the tri-modal stability distributions evident in the right panels of Figures 6 & 7, the laterality indicators for the stability items were sorted based upon laterality (Table 12). It is evident that there is a shift in laterality from left to right consistent with a change in the type of stability task.

Dynamic balance and weight shifting items were left shifted (L% <50), static items were slightly right shifted (L% 55.3 and 57.7), and hop and reach tasks were moderately right (L% >60). The

66 six right sided stability items (L% >50 in Table 12) had much lower right laterality magnitudes

(average L% of 64) than those of manipulation items (average L% of 82.8).

Table 12. Laterality indices of the stability items from the Waterloo (grey) and Chapman (blue) instruments sorted based upon laterality percentage (L%). A laterality percentage less than 50 indicates left preference.

Waterloo and Chapman Receiver Operating Characteristic Analysis

Receiver operating characteristic (ROC) curves were utilized to examine the prognostic ability of items of the Waterloo and Chapman instruments for detection of the “true” manipulation preferred foot. The true manipulation preferred foot was identified using the items from each instrument that satisfied the following strong laterality criteria (Ambiguity =<10, RL ratio >5.5, L% >85, LC >80%). Table 13 shows the top five items that met the criteria. A manipulation score was computed using these items and the true manipulation preferred limb was assigned for each participant. ROC curves were then used to examine the predictive ability of the instrument composite scores, as well as the individual items to classify footedness.

67 Table 13. Items meeting the criteria for “true” manipulation preferred foot based upon the Waterloo and Chapman instruments. Item Ambiguity RL L% LC Waterloo Kick 0 12 92.3 84.6 Chapman Kick 2 15.7 92.2 88 Chapman Stamp 2 15.7 92.2 88 Chapman Align 10 21.5 86 91.1 Chapman Circle 6 10.8 86 83 Ambiguity % = (# of “equal” or “either” limb / total) x 100 RL - Right to Left Ratio = # of R / # of L L% - Laterality Percentage = # of R / Total x 100 LC - Laterality Coefficient % = [(R – L) / (R + L)] x 100

Figure 8 is an ROC curve of the two composite scores, as well as the aggregate scores based upon manipulation and stability: Waterloo Manipulation, Waterloo Stability, Chapman

Manipulation and Chapman Stability (as shown in histograms above). There was 100% identification of “true” manipulation preference for the Waterloo and Chapman composite scores, as well as the manipulation aggregate scores from either instrument. Interestingly, ROC curves are not bound by utilization of a zero threshold to classify right and left and as such, the

Waterloo scores in ROC curves have 100% ability to detect true right and true left since the threshold is adjusted downward from zero (optimal threshold). This threshold utilized by ROC for classification is apparent in the Waterloo histogram at approximately -5 (Figure 5, left panel).

Using the zero threshold for classification, the Waterloo composite score resulted in 5 left, 45 right and 2 as either.

Examination of the curves for the stability aggregate scores reveals them to have reduced sensitivity (true positive rate for identifying right) and specificity (true negative rate for identifying left).

Figure 8. ROC curves for the composite scores of the Waterloo and Chapman footedness instruments, as well as the manipulation and stability aggregate scores for each instrument. The composite scores and aggregate scores for manipulation have 100% accuracy in classification (area under the curve =1.0). The stability aggregate scores both show similar trajectories and very good area under curve (AUC) indicating good footedness predictive ability.

69 ROC analysis was performed on each item of the Waterloo (Figure 9). The area under the curve (AUC) for each item is shown in the table to the right of each ROC curve set. An AUC greater than 0.95 can be considered excellent classification accuracy. The AUC for the items ranged from 0.417 to 1 with three items rated as excellent (AUC >0.95). The average manipulation AUC was 0.95 and the average stability AUC was 0.78.

Item AUC

W1 1 W2 0.844

W3 0.878 W4 0.875

W5 0.99 W6 0.888

W7 0.953

W8 0.885

W9 0.948 W10 0.417

Figure 9. ROC curves for each item of the Waterloo instrument. AUC for each item is shown. The table to the right shows manipulation items in bold italics and stability items in regular font.

Inspection of the ROC curves with the associated AUC reveals that the stability items have lower true positive rates to detect right or left than the manipulation items. In fact, one item

(W10, the foot you put most of your weight when standing) is “flipped”, running on the opposite half of the ROC space. When this occurs, it represents an item that should be reversed in its

70 classification weighting, but since the curve is roughly running along the reference line, it indicates that the item has poor predictive ability (no better than 50/50) and can be discarded.

Item AUC C1 1 C2 1 C3 0.99 C4 0.969 C5 0.604 C6 0.969 C7 0.969 C8 0.99 C9 0.844 C10 0.865 C11 0.917 C12 0.865 C13 0.682

Figure 10. ROC curves for each item of the original 13 item Chapman instrument. The revised Chapman instrument includes items 1 to 11 only. Area under the curve (AUC) for each item is shown. The table to the right shows manipulation items in bold italics and stability items in regular font.

The ROC curve and tables for the original 13 item Chapman instrument are shown in

Figure 10. The AUC for the items ranged from 0.604 to 1 with seven items rated as excellent

(AUC >0.95). The average manipulation AUC was 0.92 and the average stability AUC was 0.82.

71 All but one the manipulation items performed well. Item 5 (smoothing sand) has a low AUC

(0.604) representing just better than 50/50 in predicting true manipulation preferred limb. The wording of this question does not demand high precision for manipulation.

Not surprisingly, the five manipulation items that were used to identify the true manipulation preferred limb returned high AUC (Waterloo Kick 1, Chapman Kick 1, Chapman

Stamp 1, Chapman Align 0.969 and Chapman Circle 0.99). However, it is interesting to identify the items that also had excellent AUC (>0.95) beyond those that were used to identify the true manipulation preferred limb. Four items met this criterion, one from Waterloo (W5 stomp) and three from Chapman (C3 maze, C4 write, C7 rod). All of these items identified with high AUC are tasks requiring high precision manipulation of the limb (see task descriptions in Tables 2 and

3).

Sex Dependent Preference

Sex dependent differences in the “certainty” of footedness preference for the Waterloo instrument were observed. Figure 11 shows the average response for each item of the Waterloo instrument grouped by sex. The average magnitude of response for the Waterloo manipulation aggregate score was significantly greater (p<0.05) for females than males. Two (W5 Stomp and

W7 Marble) of the five manipulation items were significantly different between sexes (p<0.05), with trending values for W3 smooth (p=0.08). The stability aggregate scores were not significantly different, however the railway track stability question (W6) was trending (p=0.092).

Figure 11. Bar plot of the averaged scores for each of the Waterloo items grouped by sex.

MANIPULATION AND STABILITY PERFORMANCE

Targeting

The right side was superior in targeting performance compared to the left in all three measures (p<0.05) (Table 14). The right to left difference in maximum error over 10 trials was just over 6%, while there was a modest difference of 0.9 % for mean error. The right side consistency in targeting was 11.7 % better than the left.

There was a moderate correlation between targeting performances bilaterally (r=0.49, p<0.001). The laterality percentage was 67% based upon maximum error, and 61% based upon mean error, and 50% based on the coefficient of variation.

Table 14. Left to right differences in targeting performance. Side to side differences were all significant (p<0.05). Measure Side Mean SD Max Error Left 22.5 17.16 Right 16.2 8.99 Mean Error Left 7.8 3.86 Right 6.9 3.13 CV Error Left 84.8 32.62 Right 73.0 20.67

Comparison in targeting performance between the sexes revealed relatively equal targeting ability on the left side, but a significant difference in targeting performance on the right side (Table 15). Males had 1.3% lower mean error on the right side than the females (p=0.05), and the difference in maximum error of 3.8% was trending (p=0.059).

74 Table 15. Sex dependent differences in targeting performance. P values indicate significance between males and females, otherwise NS. Side Measure Sex Mean SD LE FT MAX Male 21.8 13.63 Female 21.5 19.32 MEAN Male 7.9 3.22 Female 7.6 4.34 CV Male 82.0 32.96 Female 82.4 32.98 RIGHT MAX Male 14.0 5.95 p=0.059 Female 17.8 10.46 MEAN Male 6.2 2.93 p=0.05 Female 7.5 2.95 CV Male 72.6 21.09 Female 73.0 19.95

Coherence between Targeting Performance and Preference

Figure 12 shows the comparison of histograms for manipulation preference to manipulation performance. The top panel shows the frequency distributions for manipulation preference using the Chapman manipulation aggregate scores (48 L: 4R). The bottom panel shows the frequency distribution of the bilateral difference in mean targeting error. For this histogram, a positive score represents superior targeting performance on the right side, and a negative score favouring the left. Unlike the bimodal distribution of the preference data, the performance data reveals a nearly normal distribution which is just slightly right shifted (20 L:

32 R, 61% laterality).

Figure 12. Histograms of manipulation preference (top panel: Chapman Manipulation Aggregate Scores) and performance (bottom panel: bilateral difference in average targeting error).

76 Stability

Static Stability

The right side was superior in pseudo-static stability to the left (Table 16). There was lower variability in acceleration in terms of standard deviation (p=0.023) and RMS (p=0.015).

The laterality percentage was 68.6 %.

Table 16. Static stability variability during a 30 second single leg standing trial. Measure Side Mean SD SD* Right 9.35 1.99 (x1000) Left 10.09 2.72 RMS* Right 5.69 4.04 (x10000) Left 4.76 2.16 * p=<0.05 between sides

Although males had lower variability in static balance on both the right and left sides, only the right sided variability was significantly different (p<0.05), with females having greater variability than males. The right sided variability in static balance was correlated to the left

(Figure 13, r=0.516, p<0.001).

Figure 13. Scatterplot of right and left variability (SD) in static balance coded by sex. Correlation of r=0.519, p<0.001).

Dynamic Stability

The number of losses of balance was tallied per person per support limb, and there were

63 losses of balance on the right side and 43 on the left (p=0.037, Chi square = 4.32). The number of participants that lost balance on the right side was 43, and 33 were on the left (NS).

The number of losses of balance by the females during left support was 30, while the total number of losses of balance for the males was 13 (p =0.007, Chi square =7.08). Interestingly, the number of left falls was correlated (r=0.31, p=0.036) to the left sided variability in static balance.

The laterality percentage was derived to be 40.3%.

78 Reach

Table 17 shows the excursions for each of the three movement directions and the total excursions. The posterior/lateral reach with the right foot planted was 4.1 cm longer than with the left foot planted (p=0.05). The excursions in other directions were nearly identical in magnitude (NS), and there was a total excursion difference that was not significant.

Table 17. A bilateral comparison of the excursion (cm) for each direction and total excursion of the star excursion reach test.

Measure Support Side Mean SD Anterior Left 64.6 23.17 Right 65.1 15.25 Posterior -Medial Left 104.9 20.36 Right 104.1 19.27 Posterior-Lateral Left 124.1 24.02 p=0.05 Right 128.2 16.31 Total Left 302.9 50.09 Right 306.4 40.51

The total excursion on the right was strongly correlated to the left (r=0.81, p<0.001)

In order to compare males to females, the excursions were normalized to the height of the participant. No significant differences in reach were detected between the sexes in any direction, or for the total excursion. The laterality percentage for the reach test ranged from 51.8 to 61.5 % depending on the excursion direction, with an average of 60%.

79 Functional Tests

Gait

The bilateral asymmetry in walking and running gait is shown in Table 18. Stance and swing phase durations were asymmetrical bilaterally, with right side stance phase duration being marginally longer and right side swing phase duration marginally shorter.

Table 18. Bilateral comparison of gait spatiotemporal durations for walk and run. Mean and SD shown in parentheses. Walk Run Right Left Right Left Cycle (ms) 1044 1047 725 724 (52.2) (49.9) (42.9) (39.3) Stance (ms) 678* 672 297* 293 (36.8) (37.3) (21.6) (24.5) Swing (ms) 151* 155 65* 70 (13.5) (16.7) (24.8) (25.9) * p < 0.01 R to L, paired t-test

Females had shorter cycle (diff=30.5 ms), stance (diff=30 ms) and swing (diff=13 ms) durations compared to males for walking (p<0.05), but not for running. Interestingly, when the durations were normalised for height, the differences in durations remained (P<0.005), but when durations were normalized bilaterally for leg lengths, the differences became insignificantly different. Height as a measure of stature did not normalize the differences between sexes, however leg length did which reflects that the principal determinant of spatiotemporal gait differences (step frequency and step length) between males and females is leg length dependent.

80 The bilateral leg lengths were related to walking gait durations bilaterally with correlations to cycle durations (r=0.405 to 0.423, p<0.05), to stance duration (r=0.444 to 0.503, p<0.05), and to swing duration (r=0.488 to 0.517, p<0.05). Importantly, the asymmetry in leg length was correlated to the asymmetry in the walking gait durations. Bilateral leg length difference was correlated to the bilateral difference in stance phase duration (r=0.344, p=0.019), and to the bilateral difference in cycle duration (r=0.320, p=0.03), but not to the bilateral difference in swing duration. Overall leg length was not correlated to the bilateral asymmetry in walking gait durations.

Cutting

Table 19 shows the peak accelerations for the P1 and P2 phases, as well as the ratio of the phases (P1/P2), during the plant for each cut direction for the group overall, and separated by sex. The left to right asymmetry (%) was also computed and reported for each sex.

Examination of P1 (i.e. the anterior-posterior deceleration component) of the plant shows no differences between sides, or between males and females. However, consideration of the left to right asymmetry in P1 shows a trend (p=0.08) toward a difference between males and females from side to side, with the males having 10% higher P1 deceleration on the left, and females having nearly symmetrical (3.6%) peaks.

For the P2 phase (i.e. the medial-lateral acceleration component of the plant), there were no significant differences between right and left side magnitudes overall. There were significant differences between the sexes, as both the right and left sided P2 magnitudes were lower for

81 females than males, with the left side reaching significance and the right trending. The difference in P2 between males and females reached a substantial magnitude of 0.4 g (2.09 F vs 2.48 M).

Table 19. The peak accelerations for P1 and P2, and the P1/P2 control ratio for the right and left plant phase of the cutting manoeuvre. The left to right asymmetry was computed and expressed as a percentage. (Independent t-test, between sexes; Paired t-test, between sides). P1 Peak (g) P2 Peak (g) P1/P2 Ratio RIGHT PLANT R to L Cut 3.24 2.38 1.45 Mean 1.09 0.72 0.54 SD Female 3.17 2.23 1.47 Mean 1.24 0.70 0.49 SD Male 3.31 2.55 1.42 Mean 0.91 0.71 0.61 SD M vs F 0.32 0.06 0.39 P value LEFT PLANT L to R Cut 3.30 2.27 1.60 Mean 1.06 0.79 0.74 SD Female 3.32 2.09 1.82 Mean 0.97 0.79 0.89 SD Male 3.28 2.48 1.37 Mean 1.16 0.76 0.45 SD M vs F 0.45 0.04 0.02 P value L to R ASYMMETRY Female 3.62 -18.12 35.14 % Male -10.49 -9.29 -5.24 % M vs F 0.08 0.23 0.02 P value Overall 0.15 0.26 0.05 P value

Overall, for both sexes combined there were no significant differences between right and left sides for P1 and P2 magnitudes. However, there was a significant difference for the P1/P2 ratio (p=0.05), which likely arose due to the substantial and significant difference in the P1/P2 ratio between the right and left sided plants for the females (1.82 L: 1.47 R). Note that the P1/P2 ratios were similar in magnitude for the right-sided plant between males and females.

82 The females had a large 35% left to right difference in P1/P2 ratio, which arises from the bilateral asymmetries present (but not significant) in P1 and P2. Males show a more or less consistent bilateral difference for P1 and P2 (-10%), while females retain a slight positive difference in the P1 magnitude between sides (+3.6%), but with a -18% difference which leads to the dramatic difference in the P1/P2 control ratio.

The mean launch acceleration, corresponding to an anterior acceleration leading into the plant arising from the contralateral foot, was 1.56 g (SD =0.55). This was not different between males and females, or between sides.

Interestingly, one male participant, a competitive soccer player, demonstrated a large right to left asymmetry in cutting accelerations, with a P1/P2 asymmetry ratio of 1.8 on his right side. This P1/P2 ratio was consistent with the altered P1/P2 ratios for females on their left side.

Some months post-testing, this participant reported to the author having sustained an ACL rupture of his right knee during a soccer game. Although a case study, it is corroborating that an altered P1/P2 ratio as demonstrated on average for the female participants was coincident with subsequent ACL rupture.

Laterality of Preference and Performance

Table 20 illustrates that there was good to very good coherence between preference and performance measures. The dynamic balance performance measure and dynamic balance preference item (railway track) were both associated with left sidedness. The static balance performance measure had right-sided laterality consistent with both the static balance preference

83 items, which had slightly lower laterality indicators. There was also good agreement between the laterality of the reaching preference items with reaching performance. Interestingly, although the mean manipulation preference item sidedness was consistent with targeting performance, there was a substantial difference in degree of laterality (92 versus 61%).

Table 20. Lower limb laterality percentages showing alignment in degree of sidedness of preference (upper half of table) and performance (lower half of table) domains. LEFT RIGHT L% <50% 51 - 100% Stability: Stability: Hop 1 Manipulation Dynamic Static 1 67% 92% 46% 58% P R Stability: Hop 2 E Static 2 68 % F 55% E R Stability: E Reach 1 N 62% C E Stability: Reach 2 73%

Stability: Stability: P Dynamic Static E 40% 68% R

F Stability: O Reach R 60% M

A Manipulation: N Targeting C E 61%

84 Prediction of Manipulation Preferred Foot using Performance Measures

A binary logistic regression was performed utilizing the stability and manipulation performance tasks to predict the dichotomous variable of manipulation preferred foot (right or left). One participant was dropped due to missing data for one of the performance measures.

A backward conditional (Wald statistic) stepwise procedure was followed to predict

“manipulation preferred” where the following performance derived covariates were used:

 Mean left targeting error (%)

 Mean right targeting error (%)

 Number of right falls

 Number of left falls

 Posterior-lateral reach right (cm)

 Posterior-lateral reach left (cm)

 SD of static balance right

 SD of static balance left

All of the performance tasks were required to classify the manipulation preferred foot

(Chi square 28.04, p<0.001) with 100% accuracy (Table 21). All subsequent iterations (8 steps in total) which methodically changed the number of covariates resulted in a prediction with misclassification of sides.

85 Table 21. Classification table for BLR of manipulation preferred foot with performance measures. Predicted Manipulation Preferred Percentage Observed 0 1 Correct Manipulation 0 4 0 100.0 Preferred 1 0 47 100.0 Overall Percentage 100.0

86 DISCUSSION

In addressing our key research questions regarding the role of preference and performance in footedness and the expression of laterality through asymmetry in functional tasks, our study has strongly supported the concept of footedness being based on both manipulation and context dependent stability elements. More specifically, the findings support our operational definition of footedness, which is that limb assignment requires use of familiar manipulation tasks and a combination of context dependent stability tasks. The precise mix of stability characteristics for inclusion in the questionnaires and performance assessment batteries to be developed requires further research due to the complexity of stability task dependence.

TASK FAMILIARITY IN FOOTEDNESS ASSESSMENT

A key and novel finding of our study was the assessment of characteristics of individual items used in footedness measures. No previous study has performed a systematic examination of the characteristics of footedness assignment using both preference and performance measures with both manipulation and stability components. This study has clearly shown that items involving tasks that are unfamiliar or complicated by other factors such as requirements for increased level of force, low precision or having a “low stakes” outcome have poor laterality characteristics (i.e. higher Ambiguity or uncertainty and lower laterality). Inclusion of these types of items in scoring has been found to confound footedness assignment by eliciting more

“equal” or “either” responses from participants, generating a higher Ambiguity score and increasing separation between the Laterality Coefficient (considers right and left assignments only and ignores “equal” or “either” responses) and the Laterality Percentage (considers all 87 responses). For example, the Chapman instrument items “smoothing sand” and “tapping a tune” had high Ambiguity of 25% due to their very low demand for precision and quality of outcome.

Since none of the footedness questionnaires offer an “uncertain” option, it is likely that participants selected “equal” or “either” (which should mean ambidexterity or that both limbs are equally proficient) when they may have selected “uncertain” had that choice been available. This is supported by our finding that concise questions involving familiar and/or higher precision tasks are more likely to elicit a lateralized response and hence result in lower Ambiguity scores.

The need for an “equal” or “either” category should be limited if the question is effective at provoking sidedness.

STABILITY IN FOOTEDNESS ASSESSMENT

Effectiveness of Preference Instruments

The Chapman and Waterloo lower limb preference instruments each consist of manipulation and stability components. The composite (combined manipulation and stability) score for the Chapman instrument identified 48 of the 52 participants as being right lower limb preferred, compared with 45 for the Waterloo instrument (Figure 5). The correlation between the two composite scores was r=0.681. However, the manipulation aggregate scores for both instruments gave the identical classification of 48 right lower limb preferred (Figures 6 & 7).

This small mismatch of three participants in the overall limb assignment between the two measures is clearly due to the differing composition of their stability items, since their assignments were identical once their stability items were removed. That the assignment of the two instruments did not fully agree when the stability items were included is an indication of the

88 task dependent nature of stability function in the lower limbs. The stability item in the Chapman instrument involves hopping, which has a unilateral dynamic context. The Waterloo instrument also has a hopping item, but additionally presents an array of stability contexts including unilateral static, bilateral static, unilateral dynamic and bilateral step-up scenarios. The differing unilateral/bilateral and static/dynamic stability contexts between the two instruments are known to influence footedness determination (Hart & Gabbard, 1997; Kiyota & Fujiwara, 2014). The small mismatch resulting from the discrepancy in the composite scores indicates that the instruments with their mixed manipulation and stability items are effective at determining footedness. However, awareness of the complexity of the stability context has emerged since their items were selected (approximately 20-30 years ago), so further research is now required to identify a more appropriate set of stability items to be included with the manipulation items in instruments to ensure accurate determination of footedness.

The Receiver Operator Characteristic (ROC) analysis of the Chapman and Waterloo results was based on the “top” five items from both instruments that showed the strongest laterality in terms of the indices. Figure 8 shows that the composite Chapman and Waterloo scores achieved perfect accuracy [area under curve (AUC) of 1.0] for identifying lower limb preference, even though the top five reference items were all manipulation in character. Figures 9 and 10 show results of ROC analysis of the individual items from the Waterloo and Chapman instruments respectively. As expected, the manipulation items scored highest on AUC (between

0.8 and 1.0, with one exception) as their prediction accuracy is being measured against the five best manipulation items. The stability item curves also scored very high on AUC (again between

0.8 and 1.0, with one exception), and while they show greater spread than the manipulation

89 curves (representing their shift in laterality across multiple stability contexts), they maintain good coherence and hence ability to predict footedness. The laterality of the stability items shown in the ROC agree with their laterality indices as detailed in Table 12. The ROC analysis has therefore shown the effectiveness of the two instruments as footedness measures and the appropriateness of their inclusion of stability items. It also points to the need for further exploration of the contextual nature of stability in order to identify the most suitable (highest

AOC) combination of items to include in a footedness instrument. (For example, Figure 9 shows

Waterloo item #10, “Weight on one foot with other leg bent. Which foot do you put most of your weight on first?” to have a predictive value that is no better than chance so is unsuitable for inclusion.)

Binary logistic regression was performed to examine the relationship between footedness preference and the mix of manipulation and stability performance measures undertaken in this study (Table 21). It found that all of the performance measures (manipulation and stability) were required to make an accurate prediction of the manipulation preferred lower limb. Again, this result strongly supports the mixed manipulation and stability concept of footedness, and that both manipulation and stability performance tasks should be considered for inclusion in footedness measures.

Table 20 shows the relationship between preference and performance across the laterality continuum from left to right as derived from this study. It clearly shows task dependence for stability, with dynamic being mildly left, static mildly right and reach moderately right. It also shows that preference and performance for stability are quite closely aligned. By contrast, it

90 shows manipulation preference to be much more lateralized than manipulation performance - the

“magnification” effect. It gives an idea of the process for identifying suitable stability items for a footedness instrument, as selection will have to be made based on sidedness and as can be seen, not all stability types are on the same side. It can be clearly seen that in this case, footedness on the right is mixed manipulation and stability, and composed of several task dependent types of stability - all of the characteristics shown to the right of the midline.

In summary, we have seen that the Chapman and Waterloo instruments with their mixed manipulation and stability components are both effective at identifying footedness. However, they are not perfectly correlated (r=0.681) and there is a small mismatch (3 participants) due to differences in the content and context of their stability items. This analysis provides support for the continued use of the Chapman and Waterloo instruments with their mixed manipulation and stability content. It also highlights the need for further research into stability task dependence to identify the most appropriate combination of stability contexts for inclusion in footedness instruments to eliminate misassignment.

Challenging the Convention that “the Non-dominant Foot is the Stability

Dominant Foot”

An assumption in the sport science and rehabilitation literature that the leg contralateral to the manipulation-preferred lower limb is the stability preferred lower limb (Table 4) implies that the laterality indicators observed for lower limb manipulation preference (10% L:90% R) should be mirrored in the support/stability limb (i.e. 90% L:10% R). However, this is not the case, as our study clearly found both stability preference and performance to shift sides in a task

91 dependent manner (from 60% L:40% R to 40% L:60% R). The stability-preferred lower limb for each type of task was shown to not exhibit high laterality indices (i.e. >70%), and the average stability scores revealed stability to be associated with the right limb for both preference and performance. This result clearly indicates, contrary to the approach of Peters (1988), that the lower limb contralateral to the manipulation-performance lower limb, whether from a preference or performance perspective, is neither the stability preferred nor the stability performance lower limb. Unlike manipulation, stability is seen to be complex, with multiple sub-domains (static, dynamic, etc.), each requiring individual testing to provide discrete, specific stability classifications. This has important implications for lower limb injury prevention and treatment in sport and rehabilitation as it will enable more specific identification of risk factors for individual clients and development of more tailored training programs to address them.

The Multimodal Distribution of Stability Preference

Another novel finding of our study was the multimodal distribution of stability preference related to the static, dynamic and reach questionnaire items, and that its distribution was relatively coherent with stability performance for static, dynamic and reach tasks (Table 20).

Our study further illustrated task dependency, whereby there was a shift from left sided dynamic stability to right sided static stability performance based upon task. Our finding revealed that both stability preference and performance are task dependent and therefore unable to be assigned to a particular lower limb as they are dependent upon the specific stability sub-domain. The multi-modal stability performance observed in our study is consistent with the bimodal stability and frequency-dependent shift in laterality observed during balance perturbations reported by

Kiyota and Fujiwara (2014). They found the left limb to be more stable at lower frequency

92 perturbations and the right limb to be more stable at higher frequencies. Their key finding that stability dominance shifts from one limb to the other agrees with our study in showing that there is a complex task dependent laterality for stability function in the lower limbs. Thus stability preference is composed of a series of task dependencies which match with performance measures. This supports a much earlier observation of Dean and Reynolds (1997) that lateral preference is a “factorially complex variable” and should be considered in terms of a continuum from right to left on separate factors (p. 140).

That lower limb stability is not strongly uni-lateralized is not surprising since the two lower limbs carry out relatively equal amounts of daily practice in stability function during standing and ambulation. Every gait cycle requires each leg to alternately serve as the stance limb and perform a period of unilateral pseudo-static stability by supporting the body as the opposite limb swings forward to take the next step. Ideally, this exposure is repeated a minimum of 10,000 times per day (15,000 times for children) just to meet basic health recommendations

(Tudor-Locke, Craig, Beets, et al., 2011; Tudor-Locke, Craig, Brown, et al., 2011), and is augmented with countless additional daily repetitions of dynamic stability challenges in the form of walking across uneven surfaces, stepping over obstacles and picking up objects from the floor, etc. Bilateral lower limb balance training volume is therefore very high and largely symmetrical, so it is reasonable to find stability laterality closer to 50% L: 50% R. Cromie, Greenwood, and

McCullagh (2007) found evidence of the powerful influence of practice on footedness in a behavioural preference study comparing 100 Irish dancers and 100 non-dancers. Both groups were right handed for preference, with virtually identical rates of approximately 84%. On completing a mix of manipulation and stability footedness tests, a complete functional separation

93 between the two groups was found. Similar to the participants in our study, the non-dancers recorded a lower limb stability-preference rate of close to 50% L:50% R, with preference shifting between the limbs depending on the particular stability task. The dancers, however, were found to be very heavily lateralized, with the right foot preferred almost exclusively for all manipulation tasks (1% L: 99% R), and the left foot almost exclusively for the stability task

(98% L: 2% R vs. 53% L: 47% R for the non-dancers). This likely reflects the influence of prolonged, repetitive practice of the highly regimented Irish dance routines on footedness preference. Conversely, in a study comparing trained soccer players and non-athletes, Teixeira et al. (2011) found players to be less lateralized than non-athletes in terms of static and dynamic lower limb stability preference and performance. They attributed this to the emphasis on bilateral practice in a sport where the ability to kick equally well with both feet is considered a prized asset. Pedersen and Vereijken (2003) acknowledged the major developmental influence of practice on the determination of lower limb sidedness by proposing that our early, phylogenetically determined asymmetries (location of cerebral language centres, handedness, footedness, etc.) are influenced over time by environmental stimuli to become magnified in the upper limbs as strong unilateral dominance in response to specialized functional demands, and diminished in the lower limbs due to each leg’s relatively balanced, dual responsibilities for manipulation and stability during gait and other functional bilateral weight-bearing activities.

Reach Stability

The reach test (Star Excursion), is a complex, bilateral task that combines the manipulation role of targeting of the reaching leg with a stability role of body support for the contralateral limb. Although it is a popular test with researchers, rehabilitation clinicians and

94 athletic trainers for assessment of the stability function of the support limb, many factors could contribute to differences observed between sides. It is reasonable to consider that between-sides flexibility differences about the hip and ankle joints in multiple planes could influence test outcomes. The literature is inconclusive regarding bilateral symmetry of flexibility in the lower body. While Moseley, Crosbie, and Adams (2001) did not find any right to left differences in ankle flexibility in 300 adult participants, Allander, Bjornsson, Olafsson, Sigfusson, and

Thorsteinsson (1974) showed left hip range of motion to be less than that of the right.

Interestingly, our reach test showed a 4 cm greater excursion of the left reach leg (right leg supporting), when reduced flexibility of the left hip in the general population would be expected to limit travel of the left reach leg. This may reflect that greater stability of the right (support) leg is the predictor of excursion performance, and that limited flexibility may not be the main factor.

Recent work by McCann et al. (2016) on the impact of strength and flexibility on performance of the Star Excursion test reported that while general lower body functional ability (deep squat, in- line lunge, hurdle step, and straight leg raise) were not related to excursions achieved, hip range of motion of internal and external rotation (r=0.43) and hip strength (r=0.33) were implicated.

Endo and Sakamoto (2014) studied joint kinematics (relative joint angles) of the support and reach legs during execution of the Star Excursion test, and observed that joint angular displacement was correlated (0.39 to 0.57) to excursion in the various planes of movement.

Although the study relates limited angular excursion to muscle tightness, since actual flexibility was not measured it may be that the joint angles achieved during the excursions represent participants’ motor control strategies rather than flexibility limitations. Nonetheless, these studies clearly implicate numerous factors in the achievement of maximal excursion associated with the reach test. Our study did not include assessment of joint flexibility or muscle strength, so we are

95 unable to conclude that the excursions achieved were solely due to stability of the support limb or to flexibility and/or strength limitations of the lower body. We observed a laterality of 60% for this test, revealing a stronger performance for excursion with the right lower limb in the support role. Although task complexity prevents us from interpreting this exclusively as enhanced stability of the right lower limb, it is interesting to note that our finding is inconsistent with conventional thinking which allocates stability dominance to the lower limb contralateral to the manipulation-preferred or -performance side (Table 4).

MANIPULATION PREFERENCE AND PERFORMANCE

COHERENCE

Our study found preference for manipulation to exhibit a high degree of laterality at 92%, whereas performance for manipulation (i.e. targeting) was a substantially lower 61-67% (Figure

12). Looking more closely, the laterality of participants’ manipulation preferred lower limb was

4 L to 48 R, while the laterality of participants’ manipulation performance lower limb (for targeting was 19 L to 33 R. One possible explanation for the more moderately skewed distribution for performance relative to preference could be bilateral practice, since both lower limbs need to target repeatedly during foot placement in gait and other functional tasks.

However, examination of upper limb measures of preference and performance reveals a similar situation, where participants’ scores for upper limb manipulation-preference show a higher degree of laterality than their manipulation-performance scores using measures such as the peg board targeting task (Brown et al., 2004; Corey et al., 2001). It appears that performance informs preference for manipulation in both the upper and lower limbs, and while there is good

96 coherence between them, preference sidedness is magnified with respect to performance. Our study therefore has established that the findings for footedness are similar to those reported for handedness. The strong footedness laterality bias with preference relative to performance may arise as a result of socio-cultural factors such as a “forced dextrality” effect associated with the continual need to declare one’s manipulation sidedness throughout life. It is notable that this social affirmation of sidedness normally only ever concerns identification of the manipulation- preferred limb; rarely (if ever) does it involve stability. This may contribute to the magnification of the laterality of manipulation preference over manipulation performance at conscious and subconscious levels, whereas stability preference has a lower profile and so is left alone to align with performance.

Interestingly, an extension of this idea is that cerebral dominance may be better predicted by preference assessment, whereas assessment required in physical medicine, rehabilitation and sports science should utilize performance measures to determine the actual level of proficiency of each lower limb and the degree of asymmetry between sides. Certainly published cerebral dominance laterality rates (>90% left) align much more closely with our handedness and lower limb manipulation-preference data (96.1% and 92.3% right respectively) than with the lower limb manipulation-performance data (61% right) that we obtained in our study.

97 SEX DEPENDENT DIFFERENCES AND FUNCTIONAL

ACTIVITIES

A sex specific preference to performance observation emerged from our study, with females exhibiting much stronger lower limb preference than males (Figure 11). This sex dependent difference in preference strength was only detectable with the Waterloo instrument as its five point scale records a broader range of responses than does the Chapman three point scale.

Females were significantly more certain about their laterality in performance for all five manipulation items and one stability item (item 6, the dynamic stability task), and were trending for stability items 2 and 10. It was reasonable to expect the follow-up performance measures to be coherent with these sex dependent preference differences. Interestingly, females had significantly greater certainty of their stability limb than males for the dynamic balance preference task, and their stability performance showed them to be asymmetrical in loss of balance in the dynamic stability task, to have worse static stability on the right and to be 128% asymmetrical in cutting (males were 100%). Our stability findings reveal that females both perceived themselves as having greater asymmetry in dynamic stability preference, and actually demonstrated greater asymmetry in dynamic stability performance (losses of balance), static stability and cutting behaviour. In other words, females exhibited stronger laterality or asymmetry for stability than males. As well, their increased fall rate and asymmetry in cutting on the left side is consistent with their much higher incidence of ACL injury on the limb opposite to the manipulation-preferred side (Brophy et al., 2010).

98 Finally, females also revealed greater certainty of sidedness for manipulation than males.

We found that females had significantly poorer targeting performance than males on the right side, however they were more symmetrical than the males. This suggests they have accumulated less practice than males, in keeping with the findings of Teixeira et al. (2011) who observed a similar disparity between trained soccer players and non-athletes.

A question arises as to whether the preference certainty of females comes from awareness of their lower absolute proficiency or their asymmetry between limbs. It is interesting to ponder how the good coherence between preference and performance materializes for the three stability sub-domains (static, dynamic and reach) examined in our study. The cognitive process by which performance relates to preference is not known, however factors such as familiarity, comfort, flow, accuracy, proficiency or asymmetry may play a part. This is an area of laterality that would benefit from future studies.

A possible long term clinical application of the sex dependent findings from our study is for all young female competitive soccer players to undergo lower limb static, dynamic and reach balance testing bilaterally, and for individualized neuromuscular training programs to be prescribed based on any lateral deficiencies identified. In an ideal world, every young female player would be evaluated with accelerometry while performing the cutting manoeuvre on each foot (similar to our experiment) to identify their risk profile in terms of stability contexts, and then be provided with an individualized program based on the findings. Progress could be monitored through reassessment testing with accelerometry until bilateral symmetry of lower limb stability has been achieved.

Another novel finding of our study was that laterality manifests in normal human gait.

Sidedness in gait was found to be expressed through prolonged stance and shortened swing phase durations on the right side relative to the left. Although small, the bilateral difference in durations was shown to be related to the small difference in right to left leg lengths. A longer leg

(the left leg for the majority of participants) is associated with a longer ipsilateral swing phase duration and consequently a longer stance phase duration on the contralateral (right) side due to the reciprocating nature of the gait cycle. However, the bilateral leg length differential was found to only account for a small proportion of the bilateral difference in stance phase durations, which leads us to speculate that laterality differences intrinsic to the CNS locomotor control system may also be contributing to this observed asymmetry in participants’ gait spatiotemporal parameters.

The statistically significant differences observed in step cycle durations between right and left sides was shorter than the time between frames (120 Hz, 8.3 ms inter-frame interval). As such, we acknowledge that this difference was beyond the ability of the data capture to detect, and likely arose due to an averaging effect across the 52 participants. Although statistically significant, we do not regard these differences as clinically relevant.

A possible clinical application of our findings of laterality based gait asymmetry is for clinicians involved in gait training of clients to ease their expectations regarding goal setting based on the presumption of premorbid symmetrical gait in terms of stance and swing phase durations.

100 TERMINOLOGY

There is currently no universally accepted nomenclature for referring to the functional characteristics associated with lower limb sidedness in laterality research, and this the lack of uniformly applied terminology in the literature can result in confusion regarding which characteristics are being discussed. One concern is the equivalence of the terms preference and dominance, when these have quite different meanings in many publications. In this thesis, we operationally defined terminology for the lower limbs and were consistent in its application throughout, and believe that our approach is an important addition to the field due to its simple, descriptive taxonomy. Our recommended terminology for manipulation functions is manipulation-preferred lower limb and manipulation-performance lower limb. The manipulation-preferred lower limb is the lower limb that is instinctively selected as being superior at performing manipulation tasks, while the manipulation-performance lower limb is the lower limb that is actually superior in the performance of manipulation tasks. Our study found manipulation preference to be more strongly lateralized than manipulation performance, and that they are coherent and skewed to the right. Our study showed lower limb stability function to be task dependent, with the right leg tending to be superior in terms of static stability preference and performance, and the left leg with dynamic stability preference and performance. So, while there is no overall stability-preferred or stability-performance lower limb, the terms static stability- preferred lower limb, static stability-performance lower limb, dynamic stability-preferred lower limb and dynamic stability-performance lower limb can be used. Individual testing for each of these characteristics is required for limb assignment due to the task-dependent nature of stability sidedness. Additional terms can be easily generated based on this taxonomy as needed (e.g. if additional categories of stability context are identified).

101 OPERATIONAL DEFINITION OF FOOTEDNESS REVISITED

The findings of our study support the operational definition of footedness as proposed in the introduction, that it is the foot that can be identified with familiar manipulation tasks and a combination of context dependent stability tasks. This endorsement was achieved through showing the effectiveness of two well-established footedness instruments, the Chapman and the

Waterloo, which both use a combination of manipulation and stability items in their identification of the manipulation preferred foot. The reasonable success of these instruments was established through histogram and ROC analysis. Binary logistic regression was also used to demonstrate the need for a mix of manipulation and stability performance tasks to accurately predict the manipulation preferred foot. Our study went on to show the benefit of using familiar tasks to elicit a stronger lateralized response, and found stability to not manifest exclusively on the side contralateral to the manipulation preferred side but to be multimodal as a result of task dependency. Finally, our study acknowledged the need for more research to determine the precise mix of stability tasks that should be included with manipulation in footedness instruments, as this is currently unknown.

102 LIMITATIONS

Although our study has successfully addressed all of our research questions and hypotheses, some key delimitations and limitations are identified below.

Our study was delimited to an evaluation of manipulation performance using a simple targeting task to be consistent with similar studies of the upper limb. We believe an examination of the accuracy of kick performance would aid in our understanding of footedness. Kick preference questions are commonplace in the laterality and injury literature, yet an examination of the relationship between kicking preference and performance has not been performed.

Certainly there is very strong laterality for the kicking items in both the Chapman and Waterloo instruments, and it would be interesting to examine if the coherence (a shift between preference and performance) that we observed for targeting (Figure 12) is replicated with kicking. It should be noted that it would be difficult to achieve a reasonable level of experimental control with a kicking performance assessment due to the complex involvement of numerous variables associated with full body motion, the combination of simultaneous manipulation and stability demands of both lower limbs, the multiple contrasting types of kicking including dribbling, passing and shooting in multiple directions, and the possible wide range of participant experience.

The sample size for our study was adequate for the statistical analysis of the proposed questions and related hypotheses of the project, however we observed some type II errors for findings that emerged post-hoc. A post-hoc power analysis revealed that a sample of approximately 100 participants would address this limitation.

103 Since this was a cross-sectional, observational study relying primarily on correlation and associated techniques, we were limited in drawing conclusions related to mechanisms underlying the laterality observed. The findings of this study could inform interventional trials examining causal linkages such as the association between cutting asymmetry and ACL injury incidence. A biomechanically derived, motor control difference between males and females was reported for cutting, revealing a left sided footedness deficit in females on the same side that they experience a substantially higher ACL injury incidence. This association is important to identify and is consistent with a motor control deficit leading to ACL injury, however it is not causal.

It is important to note that the trunk acceleration measure that we used, similar to force platforms, does not directly measure knee function but rather represents the total body motion during the single support activity of cutting. As such, our acceleration magnitude assessments during the single support phases are limited to differences between sides arising from overall differences in motion control of the joints of the supporting lower limb, and potentially even upper body effects. These findings cannot be directly attributed to differences in knee joint control during cutting. Full 3D inverse dynamics calculations are required to compare the contributions of support limb ankle, knee and hip torques during cutting. Nevertheless, the finding of asymmetry in motion control during cutting in females is an important step towards identification of the factors that contribute to the large differential injury rates between sides in this sex.

A strength of this study is that we examined a heterogeneous population in terms of self- reported athletic ability, activity participation and even range of body composition

104 characteristics, unlike many studies which have been delimited to a homogenous athletic population (e.g. competitive soccer players). Although this may increase our generalizability to the overall population, we must be cautious as our average BMI was slightly leaner than the population average, particularly for the females. However, we had a relatively large range in

BMI for both groups overall, albeit with an under-representation of obese individuals. We utilized self-report rather than objectively assessed fitness and physical activity measures to classify the participants, and it is well-known that self-reported participation is over- representative of actual by up to factor of 10 (Troiano et al., 2008). Our average study participant self-reported a frequency of exercise of three sessions per week, but we had a large range from self-reported sedentary to elite athletic daily exercise. As such, although we had a broad range of participants in terms of self-reported activity and body composition, they were slightly leaner and there was an absence of obesity, which limits our generalizability to like populations.

Similarly, since very few participants were self-reported elite athletes, the extrapolation of these results and findings to athletes is also cautioned.

Instrument bias is another limitation of our study that needed to be considered in the interpretation of the results. We selected the stability and manipulation performance tasks that we were capable of measuring, and they do not represent the entire range of movement categories possible for stability and manipulation. Generalization to overall manipulation is therefore cautioned, and given the task dependent sidedness for stability revealed in this study, generalization to “general stability” has been demonstrated to be erroneous.

105 CONCLUSIONS

Footedness can be identified with a combination of manipulation and stability tasks. Use of familiar tasks is more likely to elicit a stronger, more lateralized response. Contrary to convention, stability is not a constant property of the lower limb contralateral to the manipulation-preferred lower limb, but is multimodal and task dependent, with dynamic stability being mildly left and static and reach stability being mildly and moderately right respectively.

Lower limb manipulation and stability preferences are roughly aligned with actual performance in each task. There is relatively strong coherence for stability, but preference for lower limb manipulation is substantially lateralized relative to manipulation (targeting) performance, perhaps due to magnification of laterality by social reinforcement of the manipulation preferred and performance side.

Laterality was observed to manifest in locomotor function including walking and running gaits. In cutting, males appeared symmetrical while females were substantially asymmetrical.

Further, females demonstrated asymmetrical performance in falling, lower limb static stability and targeting. The greater left-to-right asymmetry in cutting shown by females resulted in a large left sided asymmetry in acceleration control during planting, combined with a poorer dynamic stability on the left side. This is wholly consistent with asymmetrical ACL injury incidence statistics for women, however this finding should not be considered causal.

106 A concise framework of laterality terminology was developed and utilized in this thesis, and its use would contribute to decreasing the ambiguity of findings in laterality and functional asymmetry research.

107 IMPLICATIONS

The findings of our study in the context of other research has numerous clinical and research implications.

The convention of relegating the limb contralateral to the manipulation-preferred limb to a stability role should be reconsidered, and existing lower limb injury research that employed that classification should be reinterpreted given our finding that both preference and performance for stability shows task dependent sidedness. This has important implications for injury prevention, as well as for assessment and treatment. For example, the findings of our study show the need for individual evaluation of stability function of both lower limbs in order to assign preference and performance roles. Further, although there was general coherence between preference and performance, the utility of using a preference question to identify stability dominance is not supported.

Our study developed and utilized unambiguous laterality terminology which should be employed in future studies related to both footedness and handedness. In particular, the separation of terminology for footedness preference and performance , and the need for specification of the type of preference and performance (i.e. manipulation and the various forms of stability) have important implications for the researchers and clinicians who apply this nomenclature.

Utilization of our operational definition of footedness requires further research into the various contexts of lower limb stability function to determine the precise mix of manipulation

108 and stability items required for footedness designation.

The level of coherence we observed between preference and performance measures revealed that there might be utility in using preference items for CNS laterality assignment, while performance measures should be used for functional asymmetry in applied movement science and rehabilitation settings.

Finally, this study strongly supports a requirement for ACL injury mechanism research to include bilateral lower limb preference and performance assessment, and inclusion of both male and female groups for comparison.

109 FUTURE RESEARCH QUESTIONS

The following research questions have emerged as a result of the findings of our study and through comparison of these findings with existing research.

Our study has shown that there is task dependent sidedness for lower limb stability, and this leads inevitably to the question, “Is there task dependent sidedness for lower limb manipulation?” In a soccer game, we know that the foot opposite to the preferred kicking foot requires exquisite targeting to plant optimally beside the ball the instant before kicking, often under very difficult conditions. It may be that the limb opposite the preferred kicking limb is superior in foot plant targeting. This certainly could explain why the targeting performance distribution was not heavily right-shifted in alignment with the preference findings, as the limb opposite the manipulation-preferred lower limb would be practiced at targeting the plant foot. A study examining task dependency in a variety of lower limb manipulation skills is indicated.

This was not an intervention study, but the distribution of sidedness associated with various performance measures leads to the question “Is practice the primary determinate of sidedness?” A study could be designed to investigate requirements to shift manipulation or stability dominance (performance) from one limb to the other through practice. If a side-to-side shift in dominance is found to occur, a further question is raised “Does preference limb assignment also change to align with the shifted performance?” Certainly Cromie et al. (2007) showed the influence of long term practice on shifting side preference in Irish dancers, however verification of an associated performance shift is also required.

110 An important study would be to perform a two stage, clustered RCT, where the first stage evaluates efficacy of changing lower limb performance in cutting, stability and kicking, and the second stage compares interventional efficacy of these performance changes in ACL injury rates and on-field performance statistics. This RCT could also examine the impact of self-efficacy

(the ability to relate preference to performance) on injury incidence.

Portions of this study should be repeated in a homogeneous population of athletes, in particular soccer and basketball athletes, to determine if the findings we have observed are consistent with those of high performance athletes. In particular, it is important to determine the biomechanical and control profile for effective or proficient cutting mechanics. Also, it is important to relate different forms of stability performance to cutting ability, and ultimately to injury reduction.

Future analysis could include confirmatory factor analysis with structural equation modeling to validate the footedness construct using the proposed operational definition. It would involve examination and determination of the critical latent or contributory variables (i.e. the minimum set of elements) that explain footedness.

111 APPENDIX 1–ACL INJURY VIDEO ANALYSIS

SUMMARY

Land from Valgus Hi speed at Comp Other Intrinsic (1) Cut jump stance knee Twist knee time Accel (1) Web address Sex Side Sport /Voc participants Mechanism Extrinsic (2) Y (1) or N (2) Y (1) or N (2) Y (1) or N(2) Y (1) or N(2) Y (1) or N (2) Decel (2) https://www.youtube.com Plants L, decel cut L to /watch?v=Qsb17G_ASqo M L BB NBA Y shoot 1 1 1 1 2 1 2 https://www.youtube.com Wide plant R & veers L; /watch?v=Qsb17G_ASqo M R BB NBA Y valgus 1 1 2 1 2 1 2 https://www.youtube.com Lands on L unilat after /watch?v=Qsb17G_ASqo M L BB NBA Y shooting 1 2 1 1 2 2 2 https://www.youtube.com /watch?v=Qsb17G_ASqo M L BB NBA Y Plants wide bilat 1 2 1 2 2 1 2 https://www.youtube.com /watch?v=Qsb17G_ASqo M L BB NBA Y Decel wide plant 1 1 2 1 2 1 2 https://www.youtube.com /watch?v=Qsb17G_ASqo M L BB NBA Y L plant cuts R 1 1 2 1 2 1 2 https://www.youtube.com /watch?v=Qsb17G_ASqo M R BB NBA Y Wide L plant & valgus 1 2 2 1 2 1 2 https://www.youtube.com /watch?v=Qsb17G_ASqo M L BB NBA Y Lands bilat 1 2 1 1 2 1 2 https://www.youtube.com /watch?v=EBicoCe6y48 M L BB NBA Y Lands unilat L; huge valgus 1 2 1 1 2 1 2 https://www.youtube.com Plants L to decel R line of /watch?v=EBicoCe6y48 F L Tennis Y N prog 1 1 2 1 2 1 2 https://www.youtube.com Lands unilat L with R line /watch?v=EBicoCe6y48 M L BB NBA Y of prog; valgus 1 2 1 1 2 2 2 https://www.youtube.com Colle /watch?v=kMUDljxDh_I M R BB ge Y Lands unilat R; valgus 1 2 1 1 2 1 2 https://www.youtube.com Colle Lands unilat R with R line /watch?v=kMUDljxDh_I M R BB ge Y of prog; valgus 1 1 2 1 2 1 1 https://www.youtube.com /watch?v=kMUDljxDh_I M L BB NBA Y Lands R wide, cuts L on L 1 2 1 1 2 1 2 https://www.youtube.com /watch?v=kMUDljxDh_I M R BB NBA Y R stride, valgus 1 2 2 1 2 1 1 https://www.youtube.com /watch?v=kMUDljxDh_I M L BB NBA Y L, cut R 1 1 2 1 1 1 2 https://www.youtube.com /watch?v=Vu2p_8zkE_k M L BB NBA Y L stride, valgus 1 2 1 1 1 1 2 https://www.youtube.com Valgus blow from other /watch?v=PxQJdB-EKwo M R Soccer Y Y player 2 2 1 1 2 1 1 https://www.youtube.com Planting L following /watch?v=M1grA6u6aRI F L Soccer Y Y kicking with L 1 2 1 1 1 1 2 https://www.youtube.com /watch?v=7hXXb36lAk0 F R Soccer Y Y R sidestep, plants R 1 2 1 1 1 1 2 https://www.youtube.com Kicks ball with L. next step /watch?v=yGNXYg4PaDA F L Soccer Y Y with L is valgus 1 2 2 1 1 1 1 https://www.youtube.com /watch?v=auseKB2bPQA M R BMX Rec N Lands R, valgus 1 2 1 1 2 1 2 https://www.youtube.com /watch?v=LLjK7CeioVU F R Soccer Rec Y R stance, scoops with L 1 1 2 1 1 1 2 https://www.youtube.com Natio /watch?v=emjv467IkCg F L Soccer nal Y L stance, grapples with R 1 1 2 1 1 1 2 https://www.youtube.com Gymna /watch?v=LnL4aFy3PuM M R st Prov N Lands bilat 1 2 1 1 2 1 2

112 APPENDIX 2–SAME QUESTIONNAIRE

STABILITY AND MANIPULATION EVALUATION

Section 1: Waterloo Footedness Questionnaire - Revised (Elias, Bryden & Bulman-Fleming, 1998)

INSTRUCTIONS Answer each of the following questions as best you can. If you ALWAYS use one foot to perform the described activity, select "RIGHT always" or "LEFT always". If you USUALLY use one foot, select "RIGHT usually" or "LEFT usually" as appropriate. If you use BOTH feet equally, select "LEFT & RIGHT equally". Please do not simply select one answer for all questions, but imagine yourself performing each activity in turn, and then select the appropriate answer. If necessary, stop and pantomime the activity.

1) Which foot would you use to kick a stationary ball at a target straight in front of you? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

2) If you had to stand on one foot, which foot would it be? LEFT LEFT LEFT & RIGHT RIGHT

always usually RIGHT usually always equally

3) Which foot would you use to smooth sand at the beach?

113 LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

4) If you had to step up onto a chair, which foot would you place on the chair first? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

5) Which foot would you use to stomp on a fast-moving bug? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

6) If you were to balance on one foot on a railway track, which foot would you use? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

7) If you wanted to pick up a marble with your toes, which foot would you use? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

114 8) If you had to hop on one foot, which foot would you use? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

9) Which foot would you use to help push a shovel into the ground? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

10) During relaxed standing, people initially put most of their weight on one foot, leaving the other leg slightly bent. Which foot do you put most of your weight on first? LEFT & LEFT LEFT RIGHT RIGHT RIGHT always usually usually always equally

11) Is there any reason (e.g. injury) why you have changed your foot preference for any of the above activities? YES NO

12) Have you ever been given special training or encouragement to use a particular foot for certain activities? YES NO

13) If you have answered YES for either question 11 or 12, please explain:

115

Section 2: Self Report Footedness Inventory of Lateral Preference (Sokal & Allen, 2008)

INSTRUCTIONS Please select the limb you would prefer to use for each of the following activities.

1) You kick a soccer ball into a basket across the room. Which foot kicks the ball? Either LEFT LEFT or RIGHT RIGHT

2) You stamp an aluminum can into a perfect circle. Which foot stamps the can? Either LEFT LEFT or RIGHT RIGHT

3) You navigate a golf ball through a maze as quickly as you can with your bare foot. Which foot guides the ball? Either LEFT LEFT or RIGHT RIGHT

116 4) You write your name in the sand with your bare foot. Which foot writes your name? Either LEFT LEFT or RIGHT RIGHT

5) After writing your name in the sand, you smooth the sand with your bare foot to erase your name. Which foot smooths the sand? Either LEFT LEFT or RIGHT RIGHT

6) Using your bare foot, you attempt to arrange five pebbles in a straight line with approximately 2 inches between pebbles. Which foot moves the pebbles? Either LEFT LEFT or RIGHT RIGHT

7) You attempt to balance a 3 foot long wooden rod vertically on your foot. On which foot does the rod rest? Either LEFT LEFT or RIGHT RIGHT

8) You attempt to roll a golf ball around a circle painted on the floor. Which foot guides the ball? Either LEFT LEFT or RIGHT RIGHT

117

9) Kicking one foot into the air, you try to get that foot as high as possible. Which foot is in the air? Either LEFT LEFT or RIGHT RIGHT

10) You sit down to tap out the rhythm of a simple tune (e.g. Yankee Doodle) with your foot. Which foot does the tapping? Either LEFT LEFT or RIGHT RIGHT

11) You stand on one foot and hop up and down as quickly as possible. On which foot do you stand? Either LEFT LEFT or RIGHT RIGHT

12) Stand on one foot and hold as still as possible for one minute. On which foot do you stand? Either LEFT LEFT or RIGHT RIGHT

13) Step up on a low stool (10 inches tall) and reach as high as possible on the wall. Which foot do you place on the stool?

118 Either LEFT LEFT or RIGHT RIGHT

Section 3: Task dependence

INSTRUCTIONS Please select the limb you would prefer to use in each of the following scenarios

1) You need to change a light bulb located overhead. The available stool is low, on castors, and has a very small seat that provides room for only one foot. Which foot do you place on the stool in order to step up and change the bulb? LEFT RIGHT

2) You are a contestant on a reality TV show in which you are required to stand on one foot on top of a 3 foot high post for as long as possible. The contestant who remains standing the longest will be the winner. You can use a ladder to step up onto the top of the pole. The top of the pole consists of a small flat surface no larger than the sole of your foot. You must choose only one foot on which to stand throughout the contest. On which foot do you choose to stand? LEFT RIGHT

3) You have accidently dropped a valuable ring onto a small ledge over deep, murky water. You can only reach the ring with your toes. Which foot do you choose to use in your attempt to retrieve the ring? LEFT RIGHT

4) You are about to kick the winning goal in a game of soccer. Which foot do you plant in order to kick the ball?

119 LEFT RIGHT

5) You are standing in line waiting for a bus. Which foot do you tend to put more of your weight on during the 30 minute wait? LEFT RIGHT

6) You are wearing new, white running shoes and need to cross a large, muddy puddle. From which foot do you choose to push off as you take a large step over the water? LEFT RIGHT

7) You are riding your skateboard along the sidewalk. Which foot do you place on the skateboard as you use your other leg to propel yourself forward? LEFT RIGHT

Section 4: Performance Tasks

INSTRUCTIONS Read each of the following questions and then quickly perform the activity. Note which foot you use to perform the activity.

1) Sit and use your big toe to trace your initials quickly and accurately onto the floor. Which foot do you use? LEFT RIGHT

2) Stand for 2 minutes in the "stork" position by putting all of your weight onto one foot and placing the sole of your other foot on the inner thigh of your supporting leg, just above the knee. Do not hold onto or lean against any other

120 surface during the 2 minutes. On which foot do you choose to stand? LEFT RIGHT

3) Stand on one foot and hop in place 5 times quickly. On which foot do you choose to hop? LEFT RIGHT

4) Stand and step over a small obstacle about the size of a school backpack. With which foot do you choose to lead? LEFT RIGHT

Section 5: Laterality Questions

INSTRUCTIONS Please read the following questions and select your preferred side.

1) What is your sex? MALE FEMALE

2) Which hand do you use to hold a pen while writing? LEFT RIGHT

3) Which eye do you use to look through a telescope? LEFT RIGHT

4) When chewing gum, on which side of your mouth do you tend to chew?

121 LEFT RIGHT UNSURE

5) Which best describes your mother? LEFT RIGHT UNSURE handed handed

6) Which best describes your father? LEFT RIGHT UNSURE handed handed

122 APPENDIX 3–WATERLOO AND CHAPMAN

LATERALITY INDICES

Responses to the Waterloo (top 10 questions) and Chapman (bottom 11 questions) instruments. # QUESTION ASSESS E L R RL Ambiguity Laterality Laterality Ratio % Coefficient 1 KICK MANIP 0 4 48 12.0 0.0 92.3 84.6 2 STAND ONE STAB 4 18 21 1.2 9.3 48.8 7.7 3 SMOOTH MANIP 5 6 23 3.8 14.7 67.6 58.6 SAND 4 STEP UP STAB 4 10 25 2.5 10.3 64.1 42.9 5 STOMP MANIP 3 5 19 3.8 11.1 70.4 58.3 BUG 6 RAILWAY STAB 6 17 15 0.9 15.8 39.5 -6.3 7 PICK UP MANIP 5 4 24 6.0 15.2 72.7 71.4 MARBLE 8 HOP STAB 4 13 23 1.8 10.0 57.5 27.8 9 SHOVEL MANIP 2 12 16 1.3 6.7 53.3 14.3 PUSH 10 SHIFT STAB 3 24 16 0.7 7.0 37.2 -20.0 WEIGHT 1 KICK MANIP 1 3 47 15.7 2.0 92.2 88.0 2 STAMP MANIP 1 3 47 15.7 2.0 92.2 88.0 CAN 3 BALL IN MANIP 7 4 39 9.8 14.0 78.0 81.4 MAZE 4 WRITE MANIP 5 1 43 43.0 10.2 87.8 95.5 SAND 5 SMOOTH MANIP 13 3 33 11.0 26.5 67.3 83.3 SAND 6 ALIGN MANIP 5 2 43 21.5 10.0 86.0 91.1 PEBBLES 7 ROD MANIP 2 6 43 7.2 3.9 84.3 75.5 BALANCE 8 BALL IN MANIP 3 4 43 10.8 6.0 86.0 83.0 CIRCLE 9 KICK HIGH MANIP 4 4 42 10.5 8.0 84.0 82.6

123 10 TAP TUNE MANIP 13 1 37 37.0 25.5 72.5 94.7 11 HOP FAST STAB 6 10 34 3.4 12.0 68.0 54.5

124 APPENDIX 4–MANIPULATION ITEMS FROM THE

SAME

Manipulation items from Waterloo, Chapman and SAME additional questions with excellent laterality characteristics. The first five items (Waterloo and Chapman - pink shading) were used to identify “true” manipulation preference based upon laterality criteria; the middle four items (Waterloo and Chapman - blue shading) were in very good agreement with these based upon ROC; the final two items (SAME additional questions – green shading) share the identical assignment to the first five items. Instrument Item Full Questions from Waterloo, Chapman and SAME Additional Qs Waterloo W1 Which foot would you use to kick a stationary ball at a target straight Kick in front of you? Chapman C1 You kick a soccer ball into a basket across the room. Which foot Kick kicks the ball? Chapman C2 You stamp an aluminum can into a perfect circle. Which foot stamps Stamp the can? Chapman C6 Using your bare foot, you attempt to arrange five pebbles in a straight Align line with approximately 2 inches between pebbles. Which foot moves the pebbles? Chapman C8 You attempt to roll a golf ball around a circle painted on the floor. Circle Which foot guides the ball? Waterloo W5 Which foot would you use to stomp on a fast-moving bug? Stomp Chapman C3 You navigate a golf ball through a maze as quickly as you can with Maze your bare foot. Which foot guides the ball? Chapman C4 You write your name in the sand with your bare foot. Which foot Write writes your name? Chapman C7 You attempt to balance a 3 foot long wooden rod vertically on your Rod foot. On which foot does the rod rest? Additional A You have accidently dropped a valuable ring onto a small ledge over Ring Self- deep, murky water. You can only reach the ring with your toes. Report Which foot do you choose to use in your attempt to retrieve the ring? Additional A Sit and use your big toe to trace your initials quickly and accurately Write Behav’l. onto the floor.

125 APPENDIX 5–ETHICS APPROVAL

126 APPENDIX 6–PARTICIPANT CONSENT FORM

RESEARCH PARTICIPANT INFORMATION AND CONSENT FORM

Lower limb manipulation and stability preference and performance in relation to functional tasks and gait

Principal Investigator: Mark Garrett University of Manitoba

Co-Investigator: Dr. Dean Kriellaars University of Manitoba

You are being asked to participate in a research study. Please take your time to review this consent form and discuss any questions you may have with the study staff. You may take your time to make your decision about participating in this study and you may discuss it with your friends or family before you make your decision. This consent form may contain words that you do not understand. Please ask the study staff to explain any words or information that you do not clearly understand.

Purpose of Study This research study will look for differences in the way we use our right and left legs during a variety of situations including balancing on one foot, hopping, walking and running. This study will help us to understand how differences between left and right legs develop, and how these differences could result in injury.

A total of 60 people will participate in this study.

127

Study procedures If you agree to take part in this study and sign this informed consent form, you will participate in the following steps:

 Your age, sex, height, weight and leg lengths will be recorded.

 You will complete a questionnaire regarding which hand and foot you use for different tasks.

You will be asked to perform the following tasks:

. Hop on each foot and then jump on both feet as high as you can.

. Stand on one foot, initially while keeping still, and then while performing reaching tasks with your arms and non-supporting leg. These tasks will be repeated for both legs.

. Move your foot from an initial location to a target location a few inches away and then back to the initial location. This task will be repeated for both legs.

. Hop back and forth over two pairs of lines placed on the floor a few inches apart. This task will be repeated for both legs.

. Quickly step forward, to the side and then back to your starting position. This task will be repeated for both legs.

. Perform hop-scotch by taking a series of forward hops and landing in target squares. This task will be repeated for both legs.

. Walk while keeping your feet within a narrow track.

. Walk and run on a treadmill at a variety of speeds.

Participation in the study will be completed within two hours. This is the only session you will be asked to attend.

128

The researcher may decide to take you off this study if you are having significant difficulty performing the tasks as required due to physical limitations not previously identified.

You can stop participating at any time. However, if you decide to stop participating in the study, we encourage you to talk to the study staff first.

Participants who are interested in the final results of this study may contact the principal investigator by phone or e-mail after December 2012 and a copy of the overall results and conclusions will be provided. No individual information will be included in this report.

Risks and Discomforts There is a very low risk of acquiring a lower body injury such as a muscle strain or ligament sprain while participating in the physical tasks of this study. The risk of injury while participating in these tasks is no more than the risk of acquiring injury while participating in a regular exercise program. The investigators will explain all tasks in detail and allow supervised practice with more difficult tasks prior to testing in order to minimize the risk of injury due to improper technique. You will be encouraged to express your concerns and withdraw from the study if you feel that you are presented with a task that you cannot safely perform.

You may also experience very minor muscle soreness in the lower limbs in the hours following this study for up to 72 hours. This is a normal response to exercise and is not harmful to you in any way.

During the tests, small devices that measure your movement (approximately the size of a match box) will be attached to your breastbone and hip bones with adhesive tape. Removal of the tape may cause very minor discomfort, and slight redness may remain on the skin for a short period of time following completion of the study. People who are allergic to adhesives may experience a mild skin rash or local inflammation lasting several hours to a few days following removal of the tape. You will be asked to advise the investigator if you have a known allergy to adhesive tape.

129 Benefits There will be no direct benefit to you from participating in this study. We hope the information learned from this study will provide useful information regarding the role of the legs in the performance of functional tasks. This information can help guide physiotherapists and other fitness professionals in the development of appropriate rehabilitation programs or injury prevention programs.

Costs All the procedures, which will be performed as part of this study, are provided at no cost to you.

Payment for participation You will receive no payment or reimbursement for any expenses related to taking part in this study.

Confidentiality Information gathered in this research study may be published or presented in public forums, however your name and other identifying information will not be used or revealed. After you have completed the testing procedure, only a study ID is kept with your data, and no personal identifying information is retained. Despite efforts to keep your personal information confidential, absolute confidentiality cannot be guaranteed. Your personal information may be disclosed if required by law.

The consent form will be the only document that retains your name, and this form will be kept in a locked filing cabinet.

The University of Manitoba Health Research Ethics Board may review records related to the study for quality assurance purposes.

All records will be kept in a locked secure area and only those persons identified will have access to these records. After the digital videos are analyzed they will be deleted. If any of your research records need to be copied to any of the above, your name and all identifying information will be removed. No information revealing any personal information such as your name, address or telephone number will leave the University of Manitoba.

130 Voluntary Participation/Withdrawal from the Study Your decision to take part in this study is voluntary. You may refuse to participate or you may withdraw from the study at any time. If the study staff feel that it is in your best interest to withdraw you from the study, they will remove you without your consent.

We will tell you about any new information that may affect your health, welfare, or willingness to stay in this study.

If you are a student or an employee of one of the investigators, your decision to participate will not influence your performance evaluation.

Medical Care for Injury Related to the Study You are not waiving any of your legal rights by signing this consent form, nor releasing the investigator(s) or the sponsor(s) from their legal and professional responsibilities. Any injury arising from this study will be managed within the health care system.

Questions You are free to ask any questions that you may have about this study and your rights as a research participant. If any questions arise during or after the study, or if you have a research-related injury, contact the study staff: Mark Garrett at (204) or Dr. Dean Kriellaars at (204).

For questions regarding your rights as a research participant, contact The University of Manitoba, Bannatyne Campus Research Ethics Board Office at (204) 789-3389.

Do not sign this consent form unless you have had a chance to ask questions and have received satisfactory answers to all of your questions.

131 Statement of Consent I have read this consent form. I have had the opportunity to discuss this research study with Mark Garrett or Dr. Dean Kriellaars. I have had my questions answered by them in language I understand. The risks and benefits have been explained to me. I believe that I have not been unduly influenced by any study team member to participate in the research study by any statements or implied statements. Any relationship (such as employer, supervisor or family member) I may have with the study team has not affected my decision to participate. I understand that I will be given a copy of this consent form after signing it. I understand that my participation in this study is voluntary and that I may choose to withdraw at any time. I freely agree to participate in this research study.

I understand that information regarding my personal identity will be kept confidential, but that confidentiality is not guaranteed. I authorize the inspection of any of my records that relate to this study by The University of Manitoba Research Ethics Board for quality assurance purposes.

By signing this consent form, I have not waived any of the legal rights that I have as a participant in a research study.

Participant signature______Date ______(day/month/year) Participant printed name: ______

For participants under the age of 18 years:

Parent/legal guardian’s signature______Date ______(day/month/year) Parent/legal guardian’s printed name: ______

Child’s signature ______Date ______(day/month/year) Child’s printed name: ______

I, the undersigned, have fully explained the relevant details of this research study to the participant named above and believe that the participant has understood and has knowingly given their consent

132 Printed Name: ______Date ______(day/month/year) Signature: ______

Relationship (if any) to study team members:______

133 APPENDIX 7–DATA COLLECTION FORM

Mark Garrett PhD Data Collection Form (Component A/Right)

(Check boxes on completion of each item)

1. ADMINISTRATION DETAILS Participant Code: Date: Start time: End time: Accelerometer Node (sternum): Comments:

2. CONSENT □ Signature & initials each page Comments:

3. ANTHROPOMETRICS "Please remove shoes." □ Height (cm) □ Weight (kg) □ R leg length ASIS to LM GT to LM (cm) □ L leg length ASIS to LM GT to LM (cm) Comments:

4. SAME □ Completed electronically (insert anthropometrics & click submit) □ Completed as hardcopy Comments:

134 COMPONENT A

1. FOOT TARGETING (Video: pink camera) □ Left 10 x target #1, 10 x target #2, 3 sec intervals Upload Video □ Right 10 x target #1, 10 x target #2, 3 sec intervals Upload Video Comments:

2. STORK (Accelerometer) □ Left 30 secs Trial 1 Upload L1 □ Right 30 secs Upload R1 □ Left 30 secs Trial 2 Upload L2 □ Right 30 secs Upload R2 □ Left 30 secs Trial 3 Upload L3 □ Right 30 secs Upload R3 □ Left 30 secs Trial 4 Upload L4 □ Right 30 secs Upload R4 Comments:

3. NUSTAR "Use support side index finger." (Falls = touchdowns) Direction # Falls □ Left support Clockwise Upload # of Falls □ Left support Counter-clockwise Upload # of Falls □ Right support Clockwise Upload # of Falls □ Right support Counter-clockwise Upload # of Falls Comments:

4. STAR EXCURSION BALANCE TEST Reach Leg A (cm) PM (cm) PL (cm) □ L support R1 Upload R1 Reach □ R support L1 Upload L1 Reach □ L support R2 Upload R2 Reach □ R support L2 Upload L2 Reach Comments:

135 COMPONENT B

1.A) GAIT: WALKING (Video) "Straddle & start with R." (Cameras: L = yellow; R = pink) □ 3 mph x 2 min Upload Video L □ Upload Video R Comments:

1.B) GAIT: RUNNING (Video) "Straddle & start with R." □ 6 mph x 2 min Upload Video L □ Upload Video R Comments:

2. CUTTING (Accelerometer) "Leap forward." Left-right Practice Right-left Practice Left-right Practice Right-left Practice □ Left-right Record Upload L to R1 □ Right-left Record Upload R to L1 □ Left-right Record Upload L to R2 □ Right-left Record Upload R to L2 Comments:

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