A Pilot Study of a Multiple Health Behavior Change Intervention for Smokers

University of Kentucky UKnowledge

Theses and Dissertations--Clinical and Translational Science Behavioral Science

2019

A PILOT STUDY OF A MULTIPLE HEALTH BEHAVIOR CHANGE INTERVENTION FOR SMOKERS

Srihari Seshadri University of Kentucky, [email protected] Author ORCID Identifier: https://orcid.org/0000-0002-0540-4843 Digital Object Identifier: https://doi.org/10.13023/etd.2019.303

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Recommended Citation Seshadri, Srihari, "A PILOT STUDY OF A MULTIPLE HEALTH BEHAVIOR CHANGE INTERVENTION FOR SMOKERS" (2019). Theses and Dissertations--Clinical and Translational Science. 10. https://uknowledge.uky.edu/cts_etds/10

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REVIEW, APPROVAL AND ACCEPTANCE

The document mentioned above has been reviewed and accepted by the student’s advisor, on behalf of the advisory committee, and by the Director of Graduate Studies (DGS), on behalf of the program; we verify that this is the final, approved version of the student’s thesis including all changes required by the advisory committee. The undersigned agree to abide by the statements above.

Srihari Seshadri, Student

Dr. Nancy E. Schoenberg, Major Professor

Dr. Claire D. Clark, Director of Graduate Studies

A PILOT STUDY OF A MULTIPLE HEALTH BEHAVIOR CHANGE INTERVENTION FOR SMOKERS

______

DISSERTATION ______A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the College of Medicine at the University of Kentucky

By Srihari Seshadri Lexington, Kentucky Director: Nancy E. Schoenberg, PhD, Marion Pearsall Professor of Behavioral Science Lexington, Kentucky 2019

ABSTRACT OF DISSERTATION

A PILOT STUDY OF A MULTIPLE HEALTH BEHAVIOR CHANGE INTERVENTION FOR SMOKERS

Background: Being both obese and a smoker increases the probability of developing type 2 diabetes, cardiovascular disease, and cancer, diseases that impact Kentucky residents disproportionately. Kentucky (KY) has a high incidence of obesity (34.2%) and smoking (24.5 %). Weight gain associated with smoking cessation also can undermine health benefits of quitting, and may lead to smoking relapse.

Aim: The aim of the pilot study was to implement and evaluate a Multiple Health Behavioral Change (MHBC) program that combines Cooper Clayton Method to Stop Smoking (CCMSS) and the Diabetes Prevention Program (DPP) for weight control.

Method: A 15-week intervention was administered in Appalachian (Perry County/Hazard, KY) and non-Appalachian (Warren County/Bowling Green, KY) counties. Baseline assessments consisted of height, weight, waist circumference, and breathe carbon monoxide level. Approximately one week after baseline assessment, participants attended weekly classes. During the initial 3 weeks, the CCMSS was administered. At week 4, facilitators introduced a modified 12-week DPP phase of the program concurrently with CCMSS sessions. Posttest assessment included participation feedback and a repeated assessment.

Result: Seven (31.8%) of the 22 participants who attended at least one session quit smoking. At the posttest assessment session of the MHBC program 6 participants remained abstinent and experienced an average weight gain of 4.5lbs (-8lbs. to 11.4 lbs.) and 0.4-inch decrease in waist circumference (-4.5 to 1 inch).

Discussion: Recruitment was successful; however, participant retention fell short of expectations, therefore the program lacked feasibility. Poor retention is not surprising, given the duration of the intervention as well as the challenge of an intervention that

addresses two of our most difficult health behavior changes of weight control and smoking. All seven participants who successfully completed the program expressed a high degree of satisfaction. Four participants indeed expressed that the combined challenge had been overwhelming and that they needed a support group to maintain a non-smoking status.

KEYWORDS: Multiple Health Behavior Change, Pilot Study, Smoking Cessation, Weight Control, Cooper Clayton Method to Stop Smoking, Diabetes Prevention Program

Srihari Seshadri (Name of Student)

07/11/2019 Date

A PILOT STUDY OF A MULTIPLE HEALTH BEHAVIOR CHANGE INTERVENTION FOR SMOKERS

By Srihari Seshadri

Nancy E. Schoenberg, Ph.D. Director of Dissertation

Claire D. Clark, Ph.D., MPH Director of Graduate Studies

07/11/2019 Date

DEDICATION

To My Community

ACKNOWLEDGMENTS

The following dissertation, while an individual work, benefited from the insights, support, encouragement and direction of several people. First, my Dissertation

Chair, Dr. Nancy E. Schoenberg, exemplifies the high quality scholarship and dedication to research to which I aspire. She provided timely and instructive comments and evaluation at every stage of the dissertation process, allowing me to complete this project. Next, I wish to thank the complete Dissertation Committee: Dr. Jamie Studts,

Dr. Brady Reynolds, and Dr. Steve Browning. Each one of them provided insights that guided and challenged my thinking, substantially improving the finished product. I also need to thank Dr. Thomas Kelly for his guidance and help throughout the program.

Special thanks to Department of Medical Behavioral Science faculty and staff.

In addition to the technical and instrumental assistance above, I received equally important on-going support from my family and friends. My good friend, well-wisher and former colleague Ms. Elizabeth Siddens provided on-going support and encouragement throughout my PhD program including but not limited to editing/proofing my dissertation. I honestly would not have been able to complete this dissertation without her help. I could not have done my research project without the help of numerous former colleagues/work family at Barren River District Health

Department in Bowling Green, KY: our Cooper Clayton Method to Stop Smoking

(CCMSS) facilitators Ms. Joyce Adkins and Carol Douglas; and our Diabetes

Prevention Program (DPP) facilitator Ms. Megan Givan. Special thanks to Mr. Dennis

R. Chaney, Ms. Crissy Rowland, Ms. Diane Sprowl and Ms. Lisa Houchin, for encouraging and supporting us to conduct this research project in the Barren River

iii

District. I need to specially thank Ms. Beth Bowling, Rural Project Manager, UK

Center of Excellence in Rural Health, for serving as the backbone of this study at the

Little Flower Clinic in Hazard, KY. A hearty shout out to AmeriCorps Vista workers

Ms. Aly Cooper and Ms. Kathryn Beach for facilitating both the CCMSS and DPP curriculum at the Little Flower Clinic. Special thanks to the Little Flower Clinic,

Hazard, KY and the Foundry Christian Community Center, Bowling Green, KY for allowing us to use their facility to conduct this research project. I am sure I have left out several people who helped me through my PhD journey – my hearty thanks to them as well. I certainly thank the participants of my study (who remain anonymous for confidentiality purposes), and wish each of them success in their health improvement efforts.

My most important acknowledgement goes to my parents, Seshadri and

Nagamani, wife, Jayashree, and daughter, Shriya. Their understanding, patience and flexibility have been critical to my pursuit of education, and their loving support is my ongoing source of happiness.

TABLE OF CONTENTS

ACKNOWLEDGMENTS ...... iii

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

CHAPTER 1. INTRODUCTION ...... 1 1.1 Health Risks of Tobacco Use and Obesity ...... 1 1.2 Appalachian Kentucky ...... 2 1.3 Multiple Health Behavior Change ...... 3 1.4 Objectives ...... 6 1.5 Background ...... 7 1.5.1 Cooper Clayton Method to Stop Smoking ...... 7 1.5.1.1 Nicotine Replacement Therapy (NRT) ...... 8 1.5.2 Diabetes Prevention Program ...... 8

CHAPTER 2. METHODS ...... 10 2.1 Session setting and overview ...... 10 2.2 Theoretical bases ...... 12 2.3 Participant recruitment, enrollment and facilitators ...... 13 2.4 Measures ...... 16 2.4.1 The study participants also completed the following questionnaires: ...... 16 2.4.1.1 The Fagerström Tolerance Questionnaire (FTQ) ...... 16 2.4.1.2 The Short Form-12 Version 2 (SF-12v2) Health Survey ...... 17 2.4.1.3 The MOS Social Support Survey ...... 17 2.4.1.4 Timeline Follow Back (TLFB) ...... 17 2.4.2 Breath carbon monoxide (CO) level ...... 18 2.4.3 Weight measurement ...... 18 2.5 Study Design ...... 19 2.5.1 Smoking cessation with weight control intervention ...... 19 2.6 Feasibility ...... 26 2.7 Acceptability ...... 27 2.8 Outcomes...... 27 2.9 Statistical analysis...... 28

CHAPTER 3. RESULTS ...... 31 3.1 Sample characteristics ...... 33 3.2 Feasibility ...... 42 3.3 Attrition ...... 42

3.4 Acceptability ...... 51 3.5 Outcomes...... 54 3.5.1 Smoking Quit Rates Outcome ...... 54 3.5.2 Weight Change Outcome...... 55 3.5.3 Waist Circumference Outcome ...... 60

CHAPTER 4. DISCUSSION ...... 61 4.1 Limitations ...... 67 4.2 Next steps ...... 68

CHAPTER 5. CONCLUSION ...... 69

APPENDIX 1. PARTICIPANT FEEDBACK FORM ...... 70

REFERENCES ...... 75

VITA ...... 84

LIST OF TABLES

Table 1. Measures - Assessment Schedule ...... 22 Table 2. Demographics including Socioeconomic Status and Practices, Perry County and Warren County, Kentucky, USA, 2013-2014 ...... 34 Table 3. Baseline characteristics, Perry County and Warren County, Kentucky, USA, 2013-2014 ...... 40 Table 4. Participant Attrition ...... 46 Table 5. Study participants weekly session attendance ...... 47 Table 6. Comparison of continuous baseline variables by early dropouts, late dropouts and pilot study completers (N=27) ...... 49 Table 7. Participant Feedback Evaluation (N=7) - How satisfied were you with…… .... 52 Table 8. Participant Feedback Evaluation (N=7) - How much did PIOKIO help you to do the following? ...... 53 Table 9. Outcome of participants that completed the program at the 20-week evaluation session ...... 56

vii

LIST OF FIGURES

Figure 1. Pilot Study Assessment and Intervention Delivery Timeline………………… 20 Figure 2. Study Flow Diagram, Perry County and Warren County, Kentucky, USA, 2013- 2014……………………………………………………………………………………... 32 Figure 3. Retention of PIOKIO participants across 15 weekly sessions……………….. 43 Figure 4. Retention across sessions by residents of Appalachian and non-Appalachian county participants……………………………………………………………………….44 Figure 5. Weekly weight change (Median) based on outcome smoking status at program completion (week 20-Posttest) …………………………………………………………..58 Figure 6. Weekly weight change (Median) based on Appalachian and non-Appalachian county of residence for those who stay quit (week 20-Posttest)…………………………59

viii

CHAPTER 1. INTRODUCTION

A pilot study of a multiple health behavior change (MHBC) intervention for

smokers “Put It Out and Keep It Off” (PIOKIO) was conducted in an Appalachian county

(KY) and non-Appalachian county (KY). It was the intention of the PIOKIO pilot study

to examine the feasibility and acceptability of combining the Cooper Clayton Method to

Stop Smoking (CCMSS) Program with the Diabetes Prevention Program (DPP) within a

community setting. CCMSS and DPP were chosen as they are proven effective to address

smoking cessation and weight control respectively, and CCMSS was a widely utilized program in Kentucky. This paper outlines the program backgrounds, the psychosocial instruments, recruitment, attrition, barriers to retention, feasibility, acceptability and the outcome of the study.

1.1 Health Risks of Tobacco Use and Obesity

Tobacco use is the leading preventable cause of disease, disability, and death in

the United States, linked to heart disease and stroke, several types of cancer, pregnancy

complications, and other serious health problems as well as lung diseases.1-3 Cigarette smoking is the leading cause of lung cancer, which accounted for 26% of all U.S. cancer deaths in 2015.4 Smokers are 15 to 30 times more likely to be diagnosed with lung cancer

or to die from lung cancer than non-smokers.5,6 In 2016, 17.5% of adult U.S. men and

13.5% of adult U.S. women reported being smokers.7 In Kentucky, a state which

historically depended on tobacco as a significant part of the economy, 25% of adult men

and 24% of adult women reported being smokers in 2016.8 Women and men from

Kentucky’s Appalachian counties smoke cigarettes at rates 1.8 times and 1.6 times

higher, respectively, than their national counterparts.9 The economic burden of smoking

tobacco is considerable, estimated to be over $300 billion in health care expenditures and

productivity loss within the United States.1

Obesity and overweight, the second leading preventable cause of death, is another significant and costly public health concern affecting over two-thirds of U.S. adults.10

Obesity-related health conditions include heart disease, stroke, type 2 diabetes, and

certain types of cancer, which are among the leading causes of preventable death.

Kentucky has been classified as one of the 20 states with an obesity prevalence greater

than 30% but less than 35%.11 In 2016, obesity and overweight prevalence in KY was

34.2% and 34.9% respectively.12 In addition to grave health consequences, overweight

and obesity significantly increase medical costs and pose a staggering burden on the U.S.

medical care delivery system.13 The estimated annual medical cost of obesity in the U.S.

ranges from $147 billion to $210 billion per year.13-15

1.2 Appalachian Kentucky

Adult smoking rates are high in the Appalachian counties of Kentucky (KY), at

25.9%, compared to 22.0% for non-Appalachian counties. Overall 24.5% of Kentucky’s

adults are current smokers, compared to a rate of only 15.5% for the nation.8 The

smoking prevalence is highest among individuals of lower socioeconomic status.16

Several factors contribute to high smoking rates in Appalachian KY. Among them are

poverty and less education. In Appalachian KY, 25.9% of residents live in poverty (non-

Appalachian KY rate of 16.2%; US rate of 15.1%). Among individuals who are 25 years

and older, 22.8 % have less than a high school diploma (non-Appalachian KY rate of

12.6%; US rate of 13%). Among adults age 25 to 64 years, 8.3% are unemployed (non-

Appalachian KY rate of 5.7%; US rate of 6.1%).17 Smoking is an accepted behavior in

Appalachian KY, and individuals tend to model smoking behaviors practiced by family,

friends, and the community.18 In addition, Kruger et al. have identified both lack of

reliable transportation and childcare as barriers to participation in group health promotion

programs such as smoking cessation or weight management programs that are based on

continued attendance.19 Given these circumstances it may be more challenging to quit

smoking in Appalachian KY.

Adult obesity rates are high within Kentucky’s Appalachian counties as well. The

percentage of adults who are obese in the Appalachian counties, the non-Appalachian

counties, all of Kentucky, and the U.S is 35.2%, 31.2%, 32.3% and 27.4% respectively.16

One of the factors leading to obesity is physical inactivity, and 32.8% of Appalachian KY

residents report a sedentary lifestyle, compared to 27.1% of those living in non-

Appalachian KY. For the state overall, 28.6% of adults are physically inactive, compared

to only 23.1% for the U.S.16,17

1.3 Multiple Health Behavior Change

Researchers have found that quitting smoking and even modest weight reduction

or control can improve health considerably.20 The joint attainment of smoking cessation without a weight increase reduces the risk for chronic disease and the costs associated

with both health behaviors.21-23 However, weight gain associated with smoking cessation

can undermine the health benefits of quitting24-27 and may lead to smoking relapse.28

Unfortunately, adults and a growing number of adolescents in the U.S. tend to engage in

one or more unhealthy lifestyle behavior, rather than one of them in isolation.29-32 The

most common clustering of unhealthy behaviors are smoking, overweight and/or lack of

physical activity.33 These unhealthy behaviors are associated or interrelated.29 The result

for public health status is poor quality of life, and higher rates of chronic illness and

premature death.30,34

Multiple Health Behavior Change (MHBC) interventions are defined as efforts

to treat two or more health behaviors either simultaneously or sequentially within a

limited time period.35 Effective MHBC interventions could increase health benefits and reduce healthcare cost.36 MHBC interventions are estimated to have the potential of

reducing chronic diseases by 68 to 71%37, improving quality of life38, and saving over

$16 billion in the U.S in annual medical costs.39 At the household level, research has

shown that by treating two behaviors effectively, a person’s medical costs could decrease

by approximately $2,000 per year.40

Most researchers conducting MHBC interventions are likely to target tobacco, nutrition, and stress management.41,42 Some researchers have noted that multiple

simultaneous behavior change interventions may be promising for addictive behaviors

and for multiple cancer prevention behaviors including diet, physical activity, and obesity

prevention.30 Success in changing one or more lifestyle behaviors may also increase self-

confidence or self-efficacy to improve risk behaviors for which an individual may have

low impetus to change.43 For example, providing effective weight control programming

may promote participation in smoking cessation programs, thus bolstering quit attempts

and reducing relapse.44

Some advancement in the area of MHBC research is providing insights, and

researchers are sharing their recommendations. One consideration is whether to plan the

interventions for simultaneous vs. sequential delivery. Researchers have found that

simultaneous behavioral interventions are time and cost effective,45,46 but participants

who find such an ambitious effort to be overwhelming may prematurely drop out of the

intervention.46-48 Simultaneous interventions may also fail to address any behavior in

sufficient depth.46,49,50 On the other hand, sequentially delivered interventions take

longer, increase costs, and reduce participant adherence, but may help develop stronger

habits.36,46,51,52 Either way, concurrent change in multiple behaviors should be assessed in

the context of co-occurring risks to determine the consistency, robustness, and synergy in

patterns of multiple behavior change outcomes.53

Another consideration for designing a MHBC intervention is delivery to

individuals vs. group sessions. Some weight-loss interventions have found that participants enrolled in a group-based intervention fare better than individuals undertaking an individual-based intervention.54-58 Allowing participants to access the

program individually, such as an online program, is much less expensive but such a

delivery may be missing critical peer support. A group-based MHBC intervention is

natural for worksite settings, but the design and delivery should consider

sociodemographic and social contextual factors like gender, marital status, and perceived

discrimination.59

Other challenges when designing MHBC interventions include the need to

examine relationships between behaviors, and to choose between different assessment

methods.30 Evidence regarding the most effective mechanisms for MHBC is currently

lacking and we need to better understand the relationship between behaviors, certain

associations, and the related motivating mechanisms.29 We also need to identify

correlated behaviors that have common underlying processes. Large gaps remain in our

knowledge about the efficacy of combining two or more existing single-behavior intervention programs to address multiple risk factors.60 We need appropriate and

consistent methodology for a comprehensive lifestyle metric. Advanced methods are

needed to quantify and report valid changes across several health behaviors. There is a

lack of agreement on how to best conceptualize and analyze multiple risk behavior change. Finally, to reduce the data collection burden on participants we need to simplify assessment tools,36 as well as processes and tools for logging/reporting behaviors.

MHBC interventions are promising as sustainable interventions that may result in

long-term health lifestyle improvements; however, the most effective program designs

and implementation are yet to be established.29 There is a great need to conduct more

multiple behavior change studies across a wider range of behaviors, populations,

treatments, and time frames. Until such studies are funded and completed, public health

agencies may be able to contribute valuable insight by modifying delivery of their

existing programs and services to address MHBC needs, and by collecting data on the

challenges and outcomes.

1.4 Objectives

The PIOKIO pilot study combined two programs that are currently in use by

Kentucky’s local health departments, a design that explores the use of existing public

6 health resources to addresses this urgent public health problem. The Put It Out and Keep

It Off (PIOKIO) pilot study had three objectives: (1) Assessment of the feasibility of

PIOKIO for smokers living within the selected communities, including its appeal to them and the feasibility of program completion; (2) Identification of barriers to implementation of PIOKIO while maintaining the integrity of both behavior change programs; and (3)

Efficacy testing for intermediate outcomes of changes in smoking habits and in weight maintenance.

1.5 Background

1.5.1 Cooper Clayton Method to Stop Smoking

The Cooper-Clayton Method to Stop Smoking (CCMSS) is a comprehensive behavioral modification program that utilizes group support and Nicotine Replacement

Therapy (NRT) to support individuals who smoke cigarettes. It has been documented that

31% to 47% of CCMSS participants remained smoke-free one year after program completion.61 As an empirically-based program, CCMSS uses the Transtheoretical Model

(TTM) and social cognitive theory (SCT) constructs, including enhancing knowledge, skill-building, and social support.61

The CCMSS program consists of twelve weekly classes conducted by facilitators who have been trained in the Cooper and Clayton Method. The three major programmatic components include cognitive-behavioral strategies for coping with tobacco addiction and smoking cessation, the use of Nicotine Replacement Therapy (NRT) products, and group discussion. This program has been widely used by local health departments and healthcare facilities in Kentucky for several years to address the high rate of smoking.

The CCMSS program has also been delivered in rural Appalachian churches by lay

health advisors, and has been shown in both settings to reduce smoking rates and improve

individuals' health.62

1.5.1.1 Nicotine Replacement Therapy (NRT)

The aim of NRT is to temporarily replace much of the nicotine from cigarettes to

reduce motivation to smoke and nicotine withdrawal symptoms, thus easing the transition

from cigarette smoking to complete abstinence.63

1.5.2 Diabetes Prevention Program

The Diabetes Prevention Program (DPP) is a lifestyle change program that has

repeatedly demonstrated efficacy in participants losing 5% to 7% of their body weight.64

The primary approach to behavioral weight loss is a structured program that emphasizes

lifestyle changes that include education, reduced energy and fat intake (approximately

30% of total energy), regular physical activity, and participant contact. The DPP is a

group-based program that utilizes peer support. This lifestyle change program is typically

delivered in two parts: 16 core sessions and 15 post-core sessions. Both the core and post- core sessions include individual lessons focused on goal setting, nutrition, physical activity, contingency management, stress management, and self-monitoring, among others.

The DPP is a goal-based behavioral intervention program with clearly defined behavioral and outcome goals. The two primary goals are to achieve and maintain a weight loss of 7% of the participant’s initial body weight and to establish the behavior of

at least 150 minutes of moderate physical activity per week that is similar in intensity to

brisk walking.64 These goals were adopted by DPP researchers because they were

determined to be feasible, effective, and maintained. The DPP has been successfully

adapted to numerous populations and in various settings such as primary care, YMCA,

communities, and churches.65-69 The joint use of DPP with other programs has not been reported in the literature.

For this pilot study, the 16-week core and post-core DPP sessions were modified to 12 weekly sessions and were aligned with the CCMSS sessions to reinforce the behavioral modification strategies. Both curricula were reviewed, and sessions with common themes were combined into one. This adaptation was based on an adaptation of the Group Lifestyle Balance (GLB) program developed by University of Pittsburg. The

GLB program is a direct adaptation of the DPP. While maintaining the goals and key learning objective of the DPP curriculum, several members of the DPP Lifestyle

Resource Core modified the program from individual delivery to group delivery, and reduced the number of sessions from 16 to 12.70

CHAPTER 2. METHODS

2.1 Session setting and overview

The pilot study was conducted in two Kentucky counties from 2013 to 2014. The

study took place in a non-Appalachian county (Warren County) at The Foundry Christian

Community Center, a faith-based community development center situated in a low- income neighborhood in Bowling Green and in an Appalachian county (Perry County) at the Little Flower Clinic, located in Hazard.

The population of Warren County (KY) was 113,792, and 31.2% of the county population resided in rural areas. The percentage of population that was non-Hispanic

African American, Hispanic, and non-Hispanic white were 9.2%, 5.1%, and 79.8% respectively.71 The poverty rate in Warren County (KY) was 25% higher than that of the nation, and per capita income was only 90% of the amount of the U.S. average.72 In 2013,

26% of adults were smokers, 29% of adults were obese, and 29% were physically

inactive.73

The population of Perry County (KY) was 28,712, and 74.1 % of the county

population resided in rural areas. The percentage of population that was non-Hispanic

African American, Hispanic, and non-Hispanic white were 1.5%, 1%, and 95.5%

respectively.74 The poverty rate in Perry County (KY) was nearly double the U.S. rate, and per capita income was only about two-thirds of the amount of the U.S. average. Only

74.9% of adults over age 25 had attained high school graduation or higher, i.e. about 90%

of the rate in the U.S.75

Among the 120 counties of KY, the 2013 County Health Rankings listed Perry

County at 119th for poor health outcomes and 120th for health behaviors. Thirty-three

percent of adults were smokers, 39% of adults were obese, and 40% were physically

inactive.73 Over 14.5% (US-9.4%) had been diagnosed with diabetes.76 Perry County residents had a high incidence of cancer (587.3/100,000 compared to the national rate of

448.7).77,78 The county heart disease death rate per 100,000 for individuals thirty-five years and older was more than twice (665.0) that of the nation (324.3).79

This pilot study was conducted in a group setting. Studies have shown that

participants who are enrolled in a group-based intervention fare better than an individual- based intervention in inducing weight loss.54-58 A 2017 Cochrane systematic review of

smoking cessation interventions found that group-based intervention are more effective than self-help, or other low-intensity interventions such as advice from a healthcare provider. However, they did not find enough evidence to evaluate whether group-based

intervention are more effective than individual intensive face-to- face intervention.80 A group setting provides participants the opportunity to share and to learn from each other’s life experiences. The support of these peers who are making the same behavior changes and facing the same obstacles can be powerful for program participants. An effective group setting creates a supportive and open atmosphere that motivates participants to be accountable to one another. Participants who share their problems expect that the group will help them to identify potential solutions, and the setting encourages them to be accountable to the group for testing the potential solutions between sessions. During group discussion, participants can learn how their fellow participants pursue their goals,

which in turn helps each of them to self-manage their behavior changes to reach their

own goals.81

2.2 Theoretical bases

CCMSS uses the Transtheoretical Model (TTM) and social cognitive theory

(SCT) constructs, including enhancing knowledge, skill building training, and social

support.61,82 The behavioral strategies utilized in the Diabetes Prevention Program (DPP)

also include both SCT and TTM.83

SCT is an interpersonal level theory that emphasizes that a person’s behavior is

influenced by their past-experience, the actions of others, and the social environment

(external social context). SCT considers how the individual acquires and maintains a

behavior. The model’s center of focus is self-efficacy.84-88 The TTM, also referred to as stages of change model, postulates that there are five stages of change through which an individual progresses on their way toward changing behavior. It can be considered as a cyclical process. As individuals progress through the stages, they may backslide to a previous stage, and then continue to cycle and recycle through the stages. Relapsing is seen as a natural part of the change process. The TTM model was developed by studying the experiences of smokers who quit on their own. It is understood that people quit smoking when they are ready to give up smoking.88-90 SCT and TTM complement one

another. The elements common to SCT and TTM are attitudes (decision making), self-

efficacy (an individual’s perceived behavioral control), reinforcements, rewards, and cues

to action.

For this pilot study of a multiple health behavior change intervention, the use of

CCMSS with DPP seemed promising for several reasons. Both programs have been shown to be effective. Both train participants in problem-solving techniques to address

behavior change barriers, use self-monitoring tools with feedback, and are delivered by

trained facilitators. Multiple group sessions provide participants the opportunity to share

and learn within a peer support setting. Written materials are used to reinforce verbal

advice. Participants are taught to shape behavior change with small steps, identify

personal barriers to change, work with peers on problem solving, and develop strategies

for relapse. Participants self-monitor by keeping logs of smoking (Timeline Follow Back

Method), physical activity, weight, and diet (DPP Food and Activity Tracker). Both

programs are designed to increase confidence to change (self-efficacy) and utilize

decisional balance to increase motivation for dietary modification and physical activity.

The stages of change (SOC) component of the Transtheoretical Model is used to classify

participants to their stage of readiness to change, and is often used to tailor or

individualize facilitator advice. Goal-setting is one of the key strategies in both (SCT &

TTM) theoretical models, and it is utilized in both CCMSS and DPP programs.

2.3 Participant recruitment, enrollment and facilitators

The pilot study procedures were approved by the University of Kentucky

Institutional Review Board. Study participants were recruited through convenience

sampling, a type of non-probability sampling, as a list of smokers who wanted to quit

smoking did not exist or was not readily available. Study personnel did not directly

approach the participant; rather, each participant volunteered to take part in the pilot

study on his/her own. Participants were recruited from the community through a feature

13 on a local television mid-day program, an article submitted to the county newspaper, and the national CenterWatch website, which is the leading online resource for patients interested in clinical trial participation that serves as a portal for both researchers and potential clinical trial participants. In addition, flyers were posted at some local healthcare provider offices, community centers, and local health departments. The announcement offered a free smoking cessation program with weight loss or weight control.

There are both advantages and disadvantages with convenience sampling.91 The key advantages are that it can reduce the amount of time necessary to recruit research participants, important for a study with limited staffing resources. More important, research participants recruited in this way are probably more likely to be committed to participation in the program, which in turn can help improve retention and attendance.

The main disadvantage of this sampling methodology is that the pilot study may have some inherent bias in the characteristics of the research participants and may not be representative of all smokers.

Interested individuals were asked to contact study personnel for further details. At each pilot study site, study personnel recruited participants by offering an enrollment session. During the enrollment session study personnel provided a clear explanation of the pilot study, and screened interested individuals for eligibility utilizing specified criteria. Enrollment criteria required participants to be 18 years or older, current smokers, able to speak and understand English, and able to provide informed consent. Exclusion criteria ruled out participants with a medical diagnosis of cancer, HIV, or any other

condition that affected body weight, orthopedic or joint problems that may prohibit

regular exercise, heart problems, chest pain, faintness or dizzy spells. Also excluded were

participants with a history of anorexia or bulimia nervosa or individuals who had been

hospitalized or diagnosed with a major psychiatric disorder within the last year.

Participants who were currently underweight (BMI<18.5 kg/m2), pregnant, nursing, or

less than 9 months postpartum, or who planned to move out of the area within 12 months

were also excluded.

Eligible participants who wished to participate in the study provided informed

consent and completed the baseline background questionnaire, the Fagerström Tolerance

Questionnaire to assess nicotine dependence in adults, the timeline follow-back calendar

(TLFB) to record number of cigarettes smoked each day in the last 2 weeks, the SF-12

health survey, and the Medical Outcomes Study (MOS) social support survey. Baseline

measurements were recorded for waist circumference at umbilicus, weight, height, and

breath carbon monoxide (CO) levels. Participants received $30 for completing the

questionnaires and baseline measurements. A total of 28 participants were enrolled in the

study.

At both study sites, the CCMSS was delivered by facilitators who had been

trained to offer the smoking cessation program curriculum. The adapted DPP program

was facilitated in Warren County by a Registered Dietitian (RD) who had been trained by

the Centers for Disease Control and Prevention (CDC), and who trained the facilitators

working or volunteering in Perry County. DPP does not require facilitators to be

Registered Dieticians. Trained facilitators were able to adapt, integrate, and implement

the pilot study into the existing requirement of offering the smoking cessation program

with integrity.

2.4 Measures

Basic sociodemographic and health data collected during enrollment included sex,

age, race, marital status, education, income, employment status, insurance coverage, self-

health rating, and religiousness.

2.4.1 The study participants also completed the following questionnaires:

2.4.1.1 The Fagerström Tolerance Questionnaire (FTQ)

The FTQ is an eight-item questionnaire designed to estimate the degree of nicotine dependence in tobacco smoking.92 The FTQ may predict outcomes with nicotine

replacement as a function of dose. This tool has a scoring range of 0-11 points, with a

score of 0 assumed indicative of minimum nicotine dependence and a score of 11

indicative of maximum nicotine dependence. The mean score is usually within the range

of 5-7 points, with a standard deviation of about 2.92 The Fagerström Test for Nicotine

Dependence (FTND) is a revision of FTQ.93 The FTND is a standard instrument used to

assess the intensity of physical addiction to nicotine. The test was designed to provide an

ordinal measure of nicotine dependence related to cigarette smoking. It contains six items

that evaluate the quantity of cigarette consumption, the compulsion to use, and

dependence. In scoring the Fagerström Test for Nicotine Dependence, yes/no items are

scored from 0 to 1 and multiple-choice items are scored from 0 to 3. The items are

16 summed to yield a total score of 0-10. The higher the total Fagerström score, the more intense is the patient's physical dependence on nicotine.93

2.4.1.2 The Short Form-12 Version 2 (SF-12v2) Health Survey

The SF-12v2 is an abbreviated version of the SF-36v2 that uses just 12 questions to measure functional health and well-being from the participant’s point of view. The 8 health component scales that can be computed from the questionnaire are physical function, role physical, bodily pain, general health, vitality, role emotional, mental health, and social functioning. In turn, these 8 components can be summarized into a physical health composite score (PCS-12) and a mental health composite score (MCS-12). Each of these scores falls within a 100-point range, with zero being the lowest level of health and

100 indicating the highest level. Scores are compared to a national norm with a mean score of 50 and standard deviation (SD) of 10 based on the general U.S. population.94 The standard four-week recall version was used in this pilot study.

2.4.1.3 The MOS Social Support Survey

The Medical Outcomes Study (MOS) social support survey is a multidimensional, self-administered, social support survey that was developed for patients.95 This survey was designed to be comprehensive in assessing social support. Responses scored on four functional support scales (emotional/informational, tangible, affectionate, and positive social interaction) can be used to construct an overall functional social support index.

2.4.1.4 Timeline Follow Back (TLFB)

TLFB is a method used to obtain quantitative estimates of cigarette use over 7

days to 2 years retrospectively.96-98 The TLFB can be administered by the facilitator or

researcher, or can be self-administered by the participant. For this pilot study’s baseline

assessment participants were asked to record two weeks of smoking history, and during

the intervention phase participants were asked to document smoking estimates for the

past week. Quantitative estimates can be used to measure changes in levels of cigarette

use for monitoring outcomes and evaluation studies. The TLFB can be used as a

motivational and tracking tool as well as a tool for providing feedback to participants in a

cessation program.96-98 On a weekly basis throughout the intervention phase, study participants completed a TLFB to record the number of cigarettes smoked each day during the previous week.

2.4.2 Breath carbon monoxide (CO) level

During every session, a breath carbon monoxide (CO) level was measured using a

Smokerlyzer. Monitoring carbon monoxide concentrations can be an unbiased indicator of cigarette use, and studies have shown self-reports may not always be accurate.99

Breath CO concentration provides an easy, noninvasive, and immediate way of assessing

a participant’s smoking status and a reading of greater than 6 ppm strongly suggests that

the participant has continued to smoke.100,101 CO monitoring helps participants track their progress. Studies have shown that combining biomarkers like CO monitoring with appropriate behavioral treatment may enhance health behavior change.102

2.4.3 Weight measurement

At baseline and beginning in the 4th week of the pilot study intervention phase,

weight was measured privately during each session using a portable digital scale by the

facilitators/study personnel. They were also encouraged to weigh themselves at home daily or a minimum of once per week. Studies have shown that frequent self-weighing was associated with greater weight loss or weight gain prevention.103-108 Emphasis was placed on using the scale as an important feedback and learning tool for how to better regulate personal diet and exercise behaviors.64

2.5 Study Design

2.5.1 Smoking cessation with weight control intervention

The two PIOKIO components (CCMSS and DPP curriculum) were provided in a

phased format over a total of 15 weeks. After the introductory session, enrolled

participants received 12 sessions of the CCMSS program. During Week 4 facilitators

introduced the DPP program, and continued to provide both programs simultaneously for

ten weeks. During the last two sessions, participants received DPP only. At the 20-week

posttest assessment session, participants provided measurements and completed a

feedback form. (Shown in Figure 1)

Figure 1. Pilot Study Assessment and Intervention Delivery Timeline

Enrollment Intro Smoking Cessation Session Session Program (Screening, Posttest Consent and

Baseline Weight Control Intervention Assessment)

Week 1 Week 4 Week 13 Week 15 Week 20

During the enrollment session, study personnel provided a clear explanation of the pilot study and invited questions. Participants provided informed consent and completed the baseline background questionnaire, the Fagerström Tolerance Questionnaire to assess nicotine dependence in adults, the timeline follow-back calendar (TLFB) to record number of cigarettes smoked each day in the last two weeks, the SF-12 health survey to measure functional health and well-being from the participant’s point of view, and the

MOS social support survey to measure social support. Baseline waist circumference at umbilicus, weight, height, and breath carbon monoxide (CO) level were measured by study personnel/trained facilitators privately. Measured data was documented on a log sheet for each participant with their unique identification number. (Shown in Table 1)

Table 1. Measures - Assessment Schedule

Intervention Phase Posttest Weekly Weekly During Variable Baseline (week During Entire Weight Control 20) Phase Only Breath CO X X X X Fagerström X TLFB X X X X Weight X X X Height X Dietary Intake X Waist Circumference X X Smoking history X Health status X X Social support X Sociodemographic X Attendance X X X X Program Satisfaction X

All participants were scheduled to attend fifteen weekly sessions, excluding the

enrollment session with informed consents and baseline measurements. The first

intervention session was held approximately one week after baseline assessment, and

delivered weekly thereafter. The intervention was delivered by public health

professionals and volunteers who had been trained as CCMSS and DPP facilitators.

These facilitators maintained attendance rolls, and conducted all data collection.

The intervention was delivered in a group format at The Foundry Christian

Community Center, in Bowling Green, KY, and at the Little Flower Clinic, a primary

care clinic in Hazard, KY. Each session lasted approximately 90 minutes. At the

beginning or end of each session, participants exhaled into the Smokerlyzer to measure their breath carbon monoxide. The session was a combination of didactic information via

DVDs delivered by the developers of CCMSS, along with facilitated group discussion.

Participants were given a free weekly supply of nicotine patches (Nicoderm CQ,

GlaxoSmithKline, Pittsburgh, PA) at each session during the CCMSS intervention phase.

Participants had the option of using nicotine patches, gum, or lozenge. Based on

the number of cigarettes they had been smoking per day, participants were asked to start

with a 21-mg patch (10 or more cigarettes per day) or 14-mg patch (nine or fewer

cigarettes a day, or weight less than 100 pounds). Participants who smoked more than 10

cigarettes per day were asked to begin using one 21-mg patch per day for the first 6

weeks, then transition to 14 mg patches for the following 2 weeks, and finally transition

to 7-mg patches for the last 2 weeks. Participants were asked to change the patch daily at

approximately 6 AM and were recommended to wear the patch for 24 hours. If the

23 participants had started with a 14-mg patch, based on smoking nine or fewer cigarettes a day or weighing less than 100 pounds, they were recommended to wear a 14-mg patch for the first six weeks and then switch to a 7-mg patch for two weeks. These participants were recommended to wear each patch for 16 to 24 hours a day. If they experienced a craving for cigarettes when they woke up, they were asked to wear the patch for 24 hours.

During the initial 3 weeks, only the CCMSS curriculum was administered. On a weekly basis throughout the intervention phase, participants completed a TLFB to record the number of cigarettes smoked each day during the previous week.

At Week 4, facilitators introduced a modified 12-week DPP phase of the program concurrently with CCMSS sessions. During this session, participants were told that DPP recommends setting an achievable goal of losing 7% of their starting weight. For the

PIOKIO pilot, study personnel had set a less ambitious indicator of efficacy: participants would be able to maintain their starting weight (no weight gain) during the smoking cessation period and up to the 20-week posttest assessment session.

Based on each participant’s initial weight, study personnel had calculated a 7% weight loss, as well as goals for calorie and fat intake during the study period. Calorie goals were calculated by estimating the daily calories needed to maintain the participant’s starting weight and subtracting 500 to 1,000 calories/day to achieve an average weight loss of 1–2 pounds per week. Goals for fat intake, given in grams of fat per day, were based on 25% of calories from fat. Four standard calorie levels were used: 1,200 kcal/day

(33 g fat) for participants with an initial weight of 120–170 lbs., 1,500 kcal/day (42 g fat) for participants with a weight of 175–215 lbs., 1,800 kcal/day (50 g fat) for participants

with a weight of 220–245 lbs., and 2,000 kcal/day (55 g fat) for participants weighing

>250 lbs.64

Each participant was encouraged to exercise for a minimum of 150 minutes per

week at an intensity comparable to brisk walking.64 At the start of the 4th week of the

intervention phase, participants were given “DPP’s Food and Activity Tracker” log forms

which had spaces to record food intake with fat and calorie values, as well as physical

activity, over a period of seven days. Participants were also given a reference booklet,

“The DPP Lifestyle Balance Fat Counter” which indicated the fat and calorie content for

over 1,500 alphabetized food names, including regional/ethnic foods suggested by DPP

sites for their local population.64

It was stressed to the participants that, just as with smoking cessation, self-

monitoring was one of the most important strategies to change diet and exercise

behaviors.64 All participants were instructed to utilize the DPP Lifestyle Balance Fat

Counter, to help them total and record their fat and calorie intake daily. They were also

asked to record their minutes of physical activity in the provided food and activity

tracker. During each subsequent session, participants submitted the completed food and

activity tracker to the DPP facilitator. DPP facilitators briefly reviewed the self- monitoring booklets with the participants during each session, reinforcing any noticeable positive behavior change. Facilitators thoroughly reviewed participant tracker logs between the weekly sessions and provided written constructive comments as appropriate.

Beginning with the 4th week, participants were weighed privately on a portable

digital scale at the start of every session. They were also encouraged to weigh themselves

at home daily or a minimum of once per week. Studies have shown that frequent self- weighing was associated with greater weight loss or weight gain prevention.103-108

Emphasis was placed on using the scale as an important feedback and learning tool for

how to better regulate personal diet and exercise behaviors.64 During the last 2 weeks of

the pilot (Weeks 14 and 15), only the DPP curriculum was administered.

Both DPP and CCMSS are designed to utilize group discussion of barriers that

participants are experiencing to achieving their behavior change. Facilitators are trained

to encourage all participants to share their personal challenges and experiences with the

group throughout the program. They use this input to facilitate discussion for identifying

possible solutions to those barriers. Group sharing and discussion provided participants

the opportunity to learn more, but also to give and receive peer support. Written DPP and

CCMSS materials are used to reinforce verbal advice.

Participants who completed the intervention were invited to the 20-week posttest

assessment session. At the 20-week posttest assessment session, a final data collection procedure included measurements of breath carbon monoxide (CO) level, weight, and waist circumference. Participants were asked to repeat the timeline follow-back calendar

(TLFB), and the SF-12 health survey. They were also asked to complete a 32-item participant feedback form. Participants received $30 for completing the measurements and participant feedback form.

2.6 Feasibility

Feasibility was assessed by the ability to recruit 16 smokers into each pilot study

site, the percent of participants completing the intervention, and the posttest assessment.

Attending 12 weekly sessions (80%) would be considered sufficient for having received

the intervention. Facilitators/study personnel recorded each participant’s weekly

attendance on the participant log sheet. Retention rates were considered adequate for

PIOKIO if they were consistent with the CCMSS retention rates of 44.3%.109

2.7 Acceptability

Acceptability of the smoking cessation intervention was assessed through

feedback on the various program components from both the participants and the

facilitators throughout the intervention. For example, facilitators kept notes on feedback

during routine outreach phone calls to participants who had missed sessions. During the

Week 20 posttest assessment session, participants were asked to complete an intervention

feedback/evaluation form to provide feedback regarding the sessions and helpfulness of

the intervention for reaching their goals.

2.8 Outcomes

The pilot study was of quasi-experimental design with pretest/posttest measures.

The Timeline Follow-Back (TLFB) and CO levels (<6ppm) were used to assess which

participants had quit smoking by the end of the intervention, and which were still not

smoking at the 20-week posttest assessment session. These indicators were used to

calculate quit rates, as a percentage of all participants who had completed the intervention

program. A second outcome utilizing two indicators, weight change and change in waist

circumference, compared the baseline to final measurements at the 20th-week posttest assessment session.

A mixed methodology was utilized for study evaluation. The participant feedback

questionnaire that was administered in person during the 20th week posttest assessment

session included both items with a rating scale and open-ended questions. Items asked

about the length, frequency, and scheduling of sessions as well as the adequacy of

facilitators and session formats for both learning and sharing. Some questions asked

whether participants felt they had learned useful information and skills, and the degree to

which PIOKIO had helped with motivation to make the desired behavior changes. As

qualitative data, these responses were helpful for assessing participant satisfaction with

how the sessions were delivered, and the extent to which the PIOKIO program had

helped them to reach their personal goals.

2.9 Statistical analysis

All data collected from paper based questionnaires and participant log sheets was

entered into Research Electronic Data Capture (REDCap).110 Participant demographics,

socioeconomic status, and lifestyle practices were stratified based on smoking status at

posttest (20th week) and residence of Appalachian county versus non-Appalachian county. Only data from participants who attended at least one weekly session was included in the analysis. The mean, standard deviation, and median were calculated for continuous variables of demographic and baseline data. To compare these groups the

Mann-Whitney U test (nonparametric test) was performed. Based on each participant’s responses (Fagerström Tolerance Questionnaire, SF-12, and MOS: Social Support), a composite score was computed for each one of the questionnaires separately.

Participant attrition or dropout from the pilot study has a potential to threaten the

internal (attrition bias) and external validity of the study.111,112 To identify factors

associated with this pilot study attrition and provide useful information to minimize

dropouts in future studies, we analyzed the attrition data. For this purpose, data of all

participants (N=27) who consented and provided baseline assessment was included in the

analysis, except for one participant who died before the start of weekly sessions. Weekly

session attendance was stratified based on smoking status at posttest (20th week), residents of Appalachian county versus non-Appalachian county, and number of sessions attended. Based on when the participants dropped out of the intervention, they were assigned into three groups: early dropouts (before the fourth weekly session), late dropouts (after the fourth weekly session), and study completers. For continuous baseline data variables, the mean, standard deviation, and median were calculated. To compare these three groups (early dropouts, late dropouts, and study completers) the Mann-

Whitney U test (nonparametric test) was performed.

Outcomes were summarized by visit as change from baseline. The research question of the efficacy of PIOKIO was tested through the intermediate outcomes of changes in smoking habits, weight maintenance, and waist circumference. The change in weight, waist circumference, and BMI was calculated for those smokers who completed the program. Weight change was determined by subtracting baseline weight from weight at each visit, and the median weight change was analyzed for each timepoint across 13 timepoints. The change in waist circumference was determined by subtracting the baseline waist circumference from the waist circumference at the posttest assessment session (Week 20). The change in BMI was determined by subtracting the baseline BMI

29 from BMI at the posttest assessment session (Week 20). The Wilcoxon signed-rank test was performed to compare the baseline with posttest assessments (Table 8). IBM SPSS

25 was used for all analyses and statistical tests.

CHAPTER 3. RESULTS

Figure 2 shows the flow of participants throughout the pilot study.

Figure 2. Study Flow Diagram, Perry County and Warren County, Kentucky, USA, 2013- 2014

3.1 Sample characteristics

Table 2 represents the demographic, socioeconomic status, and lifestyle practices, and Table 3 represents baseline characteristics, of the 22 participants who attended at least one session. Of the 22 participants, 16 (73%) were female and 6 (27%) were male.

Thirteen (59%) and nine (41%) of the participants were residents of Appalachian and non-Appalachian counties (KY), respectively. Of the 13 Appalachian county participants,

11 (85%) were female and 2 (15%) were male. Of the 9 non-Appalachian county participants, 5 (56%) were female and 4 (44%) were male. Participants were 86% (19)

Caucasian and 14% (3) African American. All three of the African American participants were residents of the Appalachian county. Eleven (50%) of the participants were married/partnered. The average age of participants at baseline was 45 years (23-65 yrs.), with 68% over age 40. The majority of participants were obese with a mean BMI of 35.2

(+ 9.7) and a mean waist circumference of 44.11 inches (+ 7.82), were heavy smokers and moderately nicotine dependent, and reported below average physical and mental health, but good social support. When asked about educational attainment, 18.2% (4) reported having less than 12 years of formal education, with 31.8% (7) having completed high school or a GED, and 50% (11) having had education beyond high school. Twelve

(54.5%) participants were employed, with an overall average of 43.3 hours worked per week. Over 50% of participants reported that they struggled to make ends meet, and were moderately spiritual.

Table 2. Demographics including Socioeconomic Status and Practices, Perry County and Warren County, Kentucky, USA, 2013-2014

Smoking status at Posttest (20th week) Residents of Total Appalachian non- Appalachian Did not quit Quit Smoking Characteristics (n=22) county – Perry county- Warren smoking (n=16) (n=6) N (%) County (n=13) County (n=9) N (%) N (%) N (%) N (%) Sex Female 16 (72.7) 10 (62.5) 6 (37.5) 11 (84.6) 5 (55.6)

34 Male 6 (27.3) 6 (100) 0 (0) 2 (15.4) 4 (44.4)

Race White 19 (86.4) 15 (78.9) 4 (21.1) 10 (76.9) 9 (100) Black 3 (13.6) 1 (33.3) 2 (66.7) 3 (23.1) 0 (0) Marital Status Married/Partnered 11 (50) 8 (72.7) 3 (27.3) 4 (30.8) 7 (77.8) Divorced 4 (18.2) 4 (100) 0 (0) 3 (23.1) 1 (11.1) Widowed 2 (9.1) 1 (50) 1 (50) 1 (7.7) 1 (11.1) Never married 3 (13.6) 1 (33.3) 2 (66.7) 3 (23) 0 (0) Other 2 (9.1) 2 (100) 0 (0) 2 (15.4) 0 (0)

Table 2 (continued) Smoking status at Posttest (20th week) Residents of Total Appalachian non- Appalachian Did not quit Quit Smoking Characteristics (n=22) county – Perry county- Warren smoking (n=16) (n=6) N (%) County (n=13) County (n=9) N (%) N (%) N (%) N (%) Education <12th grade 4 (18.2) 4 (100) 0 (0) 3 (23.1) 1 (11.1) 12th grade 7 (31.8) 3 (42.9) 4 (57.1) 2 (15.4) 5 (55.6) 35 th >12 grade 11 (50) 9 (81.8) 2 (18.2) 8 (61.5) 3 (33.3) Household Annual Income Below $10,000 4 (27.3) 4 (100) 0 (0) 4 (30.8) 0 (0) $10,001 - $30,000 7 (31.8) 5 (71.4) 2 (28.6) 3 (42.9) 4 (57.1) $30,001 - $50,000 3 (13.6) 1 (33.3) 2 (66.7) 3 (100) 0 (0) Above $50,001 6 (27.3) 4 (66.7) 2 (33.3) 2 (15.4) 4 (44.5)

Don't know/Prefer not to 2 (9.1) 2 (100) 0 (0) 1 (7.7) 1 (11.1) say Financial Status I have just about enough 5 (22.7) 3 (60) 2 (40) 0 (0) 5 (55.6) to get by

Insurance Private Insurance 1 (4.5) 1(100) 0 (0) 0 (0) 1 (11.1) Company Sponsored 9 (40.9) 5 (55.6) 4 (44.4) 4 (30.8) 5 (55.6) Insurance Medicare 4 (18.2) 2 (50) 2 (50) 1 (7.7) 3 (33.3) Medicaid 2 (9.1) 2 (100) (0) 2 (15.4) 0 (0) None 5 (22.7) 4 (80) 1(20) 4 (30.8) 1 (11.1) Other 3 (13.6) 3 (100) (0) 2 (15.4) 1 Self-Health Rating Excellent 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

Poor 1 (4.6) 1 (100) 0 (0) 1 (7.7) 0 (0) Employment Status Employed 12 (54.5) 9 (75) 3 (25) 6 (46.2) 6 (66.7) Unemployed 10 (45.5) 7 (70) 3 (30) 7 (53.8) 3 (33.3) Religiousness Very religious 6 (27.3) 4 (66.7) 2 (33.3) 5 (38.5) 1 (11.1) Moderately religious 10 (45.5) 7 (70) 3 (30) 5 (38.5) 5 (55.6) Slightly religious 5 (22.7) 4 (80) 1 (20) 2 (15.4) 3 (33.3) Not religious at all 1 (4.5) 1 (100) 0 (0) 1 (7.7) 0 (0)

Slightly spiritual 3 (13.6) 2 (66.7) 1 (33.3) 0 (0) 3 (33.3) Not spiritual at all 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Frequency of attending church or other religious meetings More than once a week 4 (18.2) 3 (75) 1 (25) 4 (30.8) 0 (0) Once a week 5 (22.7) 3 (60) 2 (40) 3 (23.1) 2 (22.2) A few times a month 3 (13.6) 2 (66.7) 1 (33.3) 1 (7.7) 2 (22.2) A few times a year 3 (13.6) 2 (66.7) 1 (33.3) 2 (15.4) 1 (11.1) Once a year or less 4 (18.2) 3 (75) 1 (25) 0 (0) 4 (44.4) Never 3 (13.6) 3 (100) 0 (0) 3 (23.1) 0 (0)

Two or more times a 3 (13.6) 1 (33.3) 2 (66.7) 1 (7.7) 2 (22.2) week Once a week 2 (9.1) 2 (100) 0 (0) 2 (15.4) 0 (0) A few times a month 3 (13.6) 1 (33.3) 2 (66.7) 2 (15.4) 1 (11.1) Rarely or never 5 (22.7) 5 (100) 0 (0) 1 (7.7) 4 (44.4)

Table 3. Baseline characteristics, Perry County and Warren County, Kentucky, USA, 2013-2014

Smoking status at Posttest (20th week) Residents of All Participants (N=22) Did Not Quit Smoking (n=16) Quit Smoking p Appalachian county-Perry non- Appalachian county- p Characteristics (n=6) (Mann County (n=13) Warren County (n=9) (Mann - - Whitn Whitn Mean SD Mean SD Median Mean SD Median Mean SD Median Mean SD Median ey) ey)

Age (years) 45 11.44 41.25 9.84 41 55 9.70 58.5 0.013 43.30 10.6 43 47.45 12.78 47 0.525

Weight (pounds) 215.46 59.68 230.41 58.25 219 175.60 46.43 160.2 0.047 208.65 52.76 201 225.31 70.65 224.2 0.617

Hours worked per 23.64 22.73 25 23.58 36.25 20 21.91 20 0.726 17.88 20.15 0 31.94 24.80 40 0.097

40 week

Body Mass Index 35.20 9.69 36.83 10.27 34.57 30.84 6.84 29.83 0.210 35.22 9.98 32.55 35.19 9.88 33.59 0.973

Waist Circumference 44.11 7.82 45.09 7.56 44.5 41.5 8.60 40.75 0.438 42.98 7.59 44 45.75 8.30 46 0.367 (inches)

Cigarettes Smoked 21 10.17 22.81 9.97 20 16.50 10.07 15 0.256 20.69 12.3 20 21.67 6.61 20 0.373 Per Day

Fagerström Test of Nicotine 5.91 2.07 6.25 2.08 7 5 1.90 5 0.201 6.08 2.50 7 5.67 1.32 6 0.340 Dependence Expired air carbon monoxide (parts 28.45 15.20 31.38 16.02 31 20.67 9.99 20.5 0.113 32.62 14.36 30 22.45 15.11 24 0.161 per million)

Table 3 (continued)

Smoking status at Posttest (20th week) Residents of All Participants (N=22) Did Not Quit Smoking (n=16) Quit Smoking p Appalachian county-Perry non- Appalachian county- p Characteristics (n=6) (Mann County (n=13) Warren County (n=9) (Mann - - Whitn Whitn ey) ey) Mean SD Mean SD Median Mean SD Median Mean SD Median Mean SD Median

SF-12v2

Physical Health Composite Score 38.51 13.23 39.56 13.91 39.4 35.72 11.91 39.8 0.606 39.3 13.21 38.7 37.37 13.97 40.3 0.973 (PCS-12) 41 Mental Health Composite Score 49.4 8.87 50.02 8.3 47.8 47.75 10.92 52.7 0.883 49.02 9.69 48.2 49.94 8.07 51 0.920 (MCS-12)

Social Support Mean of Support 78.95 18.69 77.17 21.16 81.05 83.68 9.36 84.74 0.711 80.17 23.49 88.42 77.19 9.15 75.79 0.149 Index

Mean of 0 to 100 73.68 23.37 71.46 26.45 76.32 79.61 11.70 80.92 0.711 75.20 29.36 85.53 71.49 11.43 69.74 0.149 Scale

3.2 Feasibility

Community response to the recruitment effort was overwhelming, particularly from women, in response to a brief interview during a morning news/talk program on a regional television station: program staff logged 20 contacts in only 3 hours. Facilitator input and responses during 32 participant recruitment interviews identified a high level of interest in a program that could address the common concern of weight gain following smoking cessation. The first 32 participants who called to inquire about the study and met the eligibility criteria were invited to attend the enrollment session. Twenty-eight of the

32 invited participants attended the enrollment session and provided informed consent.

The retention rate of the study (31.8%) was lower than the retention rate of CCMSS

(44.3%).

3.3 Attrition

Pilot study attrition challenges began immediately after the baseline assessment: five (18.5%) of the 27 participants completed the enrollment paperwork and assessment but did not return for any other sessions (Figure 3). By the fourth weekly session, the overall attrition rate was 40.7% (11). Attrition was much higher among participants at the

Hazard, KY (Appalachian county) site than among those enrolled at the Bowling Green,

KY (non-Appalachian county) site. By the fourth weekly session, the attrition rates of

Appalachian county and non-Appalachian county participants were 56.2% and 18.2% respectively (Figure 4).

Figure 3. Retention of PIOKIO participants across 15 weekly sessions

Figure 4. Retention across sessions by residents of Appalachian and non-Appalachian county participants

Calculation of weekly session’s attrition rates shows high attrition, and

differences between the two-program delivery sites. Six (22.2%) of the 27 participants

attended 12 weekly sessions (80% of sessions). Only one (3.7%) of the 27 participants

attended all 15 sessions (Table 4). There is a statistically significant difference (p=0.029)

in the weekly session attendance between the Appalachian county (mean=5.08;

median=3) and the non-Appalachian county (mean=8.78; median=9) participants (Table

5). The attrition rate across all 15 sessions was 74%, with 20 participants dropping out at

some point. Almost twice as many participants dropped out from the Appalachian county

site, with an attrition rate of 81.3% (13), compared to 63.6% (7) for the non-Appalachian county site (Figure 4)

Table 4. Participant Attrition

Smoking status at Posttest (20th All Resident of week) Participants Did Not Quit non- Number of Sessions Attended (N=27) Quit Smoking Appalachian Smoking Appalachian (n=6) county (n=16) (n=21) county (n=11) N (%) N (%) N (%) N (%) N (%) 0 sessions (0% of Sessions) 5 (18.5) 5 (23.8) 0 (0.0) 3 (18.8) 2 (18.2) 3 sessions (20% of Sessions) 16 (59.3) 10 (47.6) 6 (100.0) 7 (43.8) 9 (81.8) 6 sessions (40% of Sessions) 11 (40.7) 5 (23.8) 6 (100.0) 4 (25.0) 7 (63.6) 9 sessions (60% of Sessions) 8 (29.6) 2 (9.5) 6 (100.0) 3 (18.8) 5 (45.5)

46 12 sessions (80% of Sessions) 6 (22.2) 1 (4.8) 5 (83.3) 3 (18.8) 3 (27.3) 15 sessions (100% of Sessions) 1 (3.7) 0 (0.0) 1 (16.7) 1 (6.3) 0 (0.0)

Table 5. Study participants weekly session attendance

Smoking status at Posttest (20th week) Residents of All Participants Did Not Quit Smoking Quit Smoking P Appalachian county non- Appalachian county p (N=22) Characteristics (n=16) (Mann (n=13) (n=9) (Mann (n=6) - - Whitn Whitn Mean SD Mean SD Median Mean SD Median ey) Mean SD Median Mean SD Median ey)

Weekly 6.59 4.68 4.44 3.35 3.5 12.33 1.97 12.5 0.001 5.08 4.82 3 8.78 3.67 9 0.029 Sessions 47

Descriptive data of the continuous variables between early dropouts, late dropouts and pilot study completers is presented in Table 6. Study participants who dropped out early tended to be younger in age and have higher expired air carbon monoxide values.

Table 6. Comparison of continuous baseline variables by early dropouts, late dropouts and pilot study completers (N=27)

Early Dropout (before 4th Late Dropout (after 4th week) Completed Study (n=7) p (Mann- Variable week) (n=11) (n=9) Whitney) Mean SD Median Mean SD Median Mean SD Median

Age (years) 37 10.38 38 42.56 9.63 41 54.71 8.88 58 0.010

Weight (pounds) 227.61 50.52 227 223.44 70.29 189.40 182.54 46.20 178.00 0.178 Hours worked 10.22 17.55 0 26.39 25.83 37.5 24.29 22.99 40.00 0.153 per week

49 Body Mass 38.54 10.16 37.48 34.91 10.22 29.66 31.24 6.33 32.55 0.277 Index Waist Circumference 44.27 7.57 44.00 43.89 8.31 41.50 42.14 8.03 45.00 0.913 (inches) Cigarettes 22.63 9.41 20.00 20.67 9.70 20.00 17.00 9.29 20.00 0.588 Smoked Per Day Fagerström Test of Nicotine 6.27 2.28 7.00 6.44 1.42 6.00 5.28 1.89 6.00 0.459 Dependence Expired air carbon 38.63 15.36 40.00 27.89 15.60 32.00 21.57 9.43 21.00 0.059 monoxide (parts per million)

Table 6 (continued) Early Dropout (before 4th Late Dropout (after 4th week) Completed Study (n=7) p (Mann- Variable week) (n=11) (n=9) Whitney) Mean SD Median Mean SD Median Mean SD Median Mean of Support 66.12 25.90 68.42 80.70 12.42 78.95 84.21 8.66 87.37 0.250 Index Mean of 0 to 57.66 32.38 60.53 75.88 15.53 73.68 80.26 10.82 84.21 0.250 100 Scale

Qualitative data from participant feedback indicated that the most common

retention and attendance problems were a change in their employment status or working

hours/scheduling conflicts, problems with childcare, and/or transportation issues. Both

smoking cessation and weight loss are challenging, and it was anticipated that attempting

both behavior modifications simultaneously would be difficult for some individuals. Four

participants indeed expressed that the combined challenge had been overwhelming and

that they needed a support group to maintain a non-smoking status. Three participants

also expressed that the duration of the intervention was long, and attending 15 weekly

sessions was burdensome.

3.4 Acceptability

All seven participants who completed the intervention demonstrated acceptability

by stating in the posttest participant feedback form that there was a high likelihood of

recommending PIOKIO to a friend, family member, or coworker. Their responses to

items on the number of sessions, length of each session, frequency of each session, and

assignments between sessions were unanimous: “[It was] just right”. All participants

expressed a high level of satisfaction (chose 5 “A lot” on a 5-point scale) with the program’s group-based approach, the facilitators, and with the social support they received from other participants. Participant satisfaction with the PIOKIO program overall and the course materials was positive (100% marked 4 or 5 on the 5-point scale, with 86% of them giving the highest rating). Additional information provided in table 7

and table 8.

Table 7. Participant Feedback Evaluation (N=7) - How satisfied were you with……

Very Very Dissatisfied Satisfied How satisfied were you Dissatisfied Satisfied with…… % (N) % (N) % (N) % (N) overall comfort level of 0 (0) 0 (0) 43 (3) 57 (4) the room? length of each class? 0 (0) 0 (0) 14 (1) 86 (6) day of the week class 0 (0) 0 (0) 0 (0) 100 (7) held? time of day class held? 0 (0) 14 (1) 0 (0) 86 (6) time allowed for open 0 (0) 0 (0) 14 (1) 86 (6) discussion?

Table 8. Participant Feedback Evaluation (N=7) - How much did PIOKIO help you to do the following?

1 3 5 The PIOKIO 2 4 Not at all A little A lot program… % (N) % (N) % (N) % (N) % (N)

motivated me to quit 0 (0) 0 (0) 0 (0) 14 (1) 86 (6) and stay smoke free informed me about what to expect when I 0 (0) 0 (0) 0 (0) 29 (2) 71 (5) quit provided me with ideas about how to create a 0 (0) 0 (0) 0 (0) 29 (2) 71 (5) positive environment for myself

taught me skills for 0 (0) 0 (0) 0 (0) 14 (1) 86 (6) how to quit

helped me to relax and not think about 0 (0) 0 (0) 0 (0) 29 (2) 71 (5) smoking after each of the sessions helped me postpone smoking the next 0 (0) 0 (0) 0 (0) 14 (1) 86 (6) cigarette after each session helped me maintain or 0 14 (1) 29 (2) 14 (1) 43 (3) lose weight

helped me increase my 0 (0) 43 (3) 0 (0) 0 (0) 57 (4) physical activity

3.5 Outcomes

For this pilot study, two primary indicators of efficacy were used for participant

outcomes at the end of the program: (1) participants would quit smoking completely and

maintain a non-smoking status, and (2) participants would at least maintain their original

weight.

3.5.1 Smoking Quit Rates Outcome

Seven (31.8%) of the 22 participants who attended at least one session had quit

smoking by the end of the intervention. Three (23.1%) of the 13 Appalachian county

participants and 4 (44.4%) of the 9 non-Appalachian county participants had completed

the program. Three (23%) of the 13 Appalachian county residents and 3 (33%) of the 9

non-Appalachian county residents quit smoking. All six of them were females. Four of

them were White and two of them were African Americans. Four (67%) of the six self-

reported having fair health and two (33%) of the six self-reported to be in good health.

Three (50%) of the six were unemployed. No participants who reported having less than

12 years of formal education were able to quit smoking. The mean weekly number of

sessions attended was 4.4 (29.3%, range from 1 to 13 sessions) for participants who did

not quit smoking and 12.3 (82%, range from 9 to 15 sessions) for those who were able to

quit smoking. The increase in number of sessions attended (OR = 2.03, 95% CI = 1.12–

3.7) and age (OR = 1.17, 95% CI = 1.02–1.34) was associated with a higher odds of

smoking cessation. The mean and median initial weight (230.41 lbs. and 219 lbs.) of

participants in the “Did Not Quit Smoking” group was statistically significant and higher

than the mean and median initial weight (175.6 lbs. and 160.2 lbs.) of participants in the

“Quit Smoking” group (p= 0.047). The mean and median BMI (36.83 and 34.57) of

participants in the “Did Not Quit Smoking” group was higher than the mean and median initial BMI (30.84 and 29.83) of participants in the “Quit Smoking” group. However, they were not statistically significant (p=0.210). Six (85.7%) of the seven participants who completed the program had maintained abstinence from smoking at the 20-week posttest assessment session. Objective measurements utilizing the breath CO monitor matched the self-reported smoking status provided on the TLFB logs.

3.5.2 Weight Change Outcome

Among participants attempting to stop smoking, the second major program goal was a lack of weight gain. Changes in participant weight ranged from losing 8 lbs. to gaining 11.4 lbs. The average and median weight gain among those who quit smoking was 4.5 and 7.3 lbs. respectively. Only one of the six participants who had quit smoking had lost weight or maintained the initial weight by the 20-week posttest assessment session. The median weight gain among Appalachian and non-Appalachian county participants was 10 and 11.4 lbs. respectively. Change in the participants’ calculated BMI ranged from a decrease in BMI of 1.4 to an increase in BMI of 2.0. The average and median increase in BMI among those who quit smoking was 0.8 and 1.6 respectively.

The median BMI increase among Appalachian and non-Appalachian county participants was 1.9 and 0.6 respectively. Additional information is presented in Table 9, Figure 5 and

Figure 6.

Table 9. Outcome of participants that completed the program at the 20-week evaluation session

Baseline Posttest Difference in p-value for Outcome results (Median) (Median) the Median Difference All participants (N=7) Physical Health Component Score 40.3 49.5 9.2 0.043 Mental Health Component Score 52.3 40.9 -11.4 0.063 Weight (lbs.) 178 185 7 0.128 BMI 32.6 33.8 1.2 0.128 56

Waist Circumference (inches) 45 43.5 -1.5 0.891 Quit smoking (N=6) Physical Health Component Score 39.8 49.2 9.4 0.075 Mental Health Component Score 52.7 41.2 -11.5 0.116 Weight (lbs.) 160.2 167.5 7.3 0.173 BMI 29.8 31.4 1.6 0.173 Waist Circumference (inches) 40.8 40.3 -0.5 0.713

Table 9 (continued) Baseline Posttest Difference in p-value for Outcome results (Median) (Median) the Median Difference Appalachian county residents

(N=3) Physical Health Component Score 39.3 56.9 17.6 0.109 Mental Health Component Score 42.2 35.9 -6.3 0.285 Weight (lbs.) 140 150 10 0.593 BMI 27.1 29 1.9 0.593 57

Waist Circumference (inches) 34 35 1 0.18 non-Appalachian county residents

(N=3) Physical Health Component Score 40.3 36.9 -3.4 0.285 Mental Health Component Score 53.5 48.7 -4.8 0.109 Weight (lbs.) 226.4 237.8 11.4 0.109 BMI 37.1 37.7 0.6 0.109 Waist Circumference (inches) 48 43.5 -4.5 0.655

Figure 5. Weekly weight change (Median) based on outcome smoking status at program completion (week 20-Posttest)

Figure 6. Weekly weight change (Median) based on Appalachian and non-Appalachian county of residence for those who stay quit (week 20-Posttest)

3.5.3 Waist Circumference Outcome

Change in waist circumference ranged from reducing 4.5 inches to increasing 1 inch. The average and median decrease in waist circumference among those who quit smoking was 0.4 and 0.5 inches respectively. The median waist circumference change among Appalachian and non-Appalachian county participants was 1 and -4.5 inches respectively. Additional information is presented in table 9.

The median physical health component score for participants who completed the program increased by 9.2 (p=0.043).

CHAPTER 4. DISCUSSION

Health behavior change may serve as an individual’s pathway to a healthier lifestyle, and has the potential to result in better quality of life and increased life expectancy.45 From a public health perspective, there is an urgent need for development of an acceptable and effective smoking cessation program with a weight control component.

This pilot study evaluated an innovative MHBC intervention that combines the use of two existing and proven interventions that can target smoking while also providing the tools and skills to avoid weight gain. The three objectives for PIOKIO pilot study were: (1) Assessment of the feasibility of PIOKIO for smokers living within the selected communities, including its appeal to them and the feasibility of program completion; (2)

Identification of barriers to implementation of PIOKIO while maintaining the integrity of both behavior change programs; and (3) Efficacy testing for intermediate outcomes of changes in smoking habits and in weight maintenance.

Seven (31.8%) of the 22 PIOKIO participants who attended at least one session had quit smoking by the end of the intervention. Six (85.7%) of the seven participants who completed the program had maintained abstinence from smoking at the 20-week posttest assessment session. Changes in participant weight ranged from losing 8 lbs. to gaining 11.4 lbs. with an average weight gain among those who quit smoking of only 4.5 lbs. Only one of the six participants who had quit smoking had lost weight or maintained their weight by the 20-week posttest assessment session. The average decrease in waist

circumference among those who quit smoking was 0.4 inches. Age and expired air

carbon monoxide were identified as predictors of study attrition.

Despite a very promising indication of community interest, pilot study results

show that PIOKIO as implemented was feasible in terms of recruitment, but not in

retention. Five (18.5%) individuals did not return after the informational session, and

participant retention rates were disappointing. Reported retention rates for smoking

cessation intervention programs range from 23% to 89.2%, based on the type of smoking

cessation intervention and the characteristics of the targeted population.113 Those

programs that combine both a behavioral and a pharmacological component (such as

nicotine replacement therapy) report retention rates between 23% and 84%.113 Though

the PIOKIO pilot study’s retention rate (31.8%) falls within that range, it is towards the

lower end of the spectrum. These results indicate that a staged simultaneous

implementation (3 weeks of smoking cessation, followed by 10 weeks of both smoking

cessation and weight control, followed by 2 weeks of only weight control) may have been

overwhelming to many participants, when a full fifteen weeks of group sessions are

required.

Researchers have reported that MHBC interventions that addressed more than one

health behavior are more effective than interventions that addressed only one targeted

behavior.46,123-125 Some interventional studies have incorporated weight control programs

and nicotine replacement therapy with smoking cessation programs, based on the

assumption that preventing post-cessation weight gain would improve smoking cessation rates.129 When implementing an MHBC intervention, the research seems to show little

difference in effectiveness between sequential and simultaneous approaches.46 However,

sequential intervention has been favored in studies for smoking cessation behavior.126,127

For post-cessation weight control, Spring et al. suggest that smoking cessation should be

addressed before initiating a weight control intervention.128

The added behavioral weight control programs are attractive to participants, but the outcomes of these studies are mixed. Pirie et al. showed that combined interventions did not detract from the smoking cessation outcome of the program. In fact, they demonstrated that participants who received the weight control treatments did as well as or better at smoking abstinence than those who received only the smoking cessation program. However, they did not produce the expected weight effect.130 Hall et al. found that adding a behavioral weight management program to the smoking cessation program might have been too complicated for participants to maintain abstinence. They postulated that the caloric restriction might have encouraged smoking.131 In contrast to Pirie et al

and Hall et al., Perkins et al. found this approach to be successful in suppressing post- cessation weight gain and enhancing abstinence.130,132,131 Spring et al. suggest in their

study that the participants in the “early diet” group may have felt overwhelmed by being

asked to change eating, physical activity, and smoking simultaneously at the outset of

intervention.128 Some PIOKIO participants did express that the combined intervention

had been overwhelming and that they needed a support group to maintain abstinence.

The PIOKIO pilot study design was based on face-to-face group meetings, to

provide social support as well as easily accessible education (including immediate

answers to questions). Research on smoking cessation by Stead et al. shows that a group-

based approach is beneficial, increasing the chance of quitting by 50% to 130%.80 Every

PIOKIO participant who completed the evaluation survey expressed satisfaction with the

group setting. Research on smoking cessation programs shows a compelling link between

group session attendance and successful smoking cessation: an increased number of

sessions attended is associated with a higher odds of quitting smoking.62,121,122 Those

PIOKIO participants who quit smoking through the 20-week posttest assessment session

were those who attended at least nine sessions.

If provider or volunteer resources allow, it may be beneficial to reach out multiple times to absent participants after each group session via phone, text, and social

media. Adding this or a more intensive follow-up procedure to a full-scale research project on PIOKIO would be important, but challenging, as few PIOKIO participants would answer phone calls from study personnel after they had dropped out.

Given the challenges and strengths discussed here, the seven participants who did complete PIOKIO expressed a high level of satisfaction at the 20-week follow-up point.

Their feedback on the PIOKIO program itself was unanimously positive, with 86% of participants giving the program the highest rating. All of them stated that it was very likely that they would recommend PIOKIO to a friend, family member, or coworker.

Facilitators were not formally surveyed, but all were enthusiastic about the experience of combining two effective and currently-used public health programs for a stronger MHBC impact. It may be that additional pilot projects incorporating stronger explorations of retention issues would inform providers on ways to improve delivery of both individual programs as well as a PIOKIO combination.

This pilot study identified some implementation barriers and predictors of

success. It is important to find ways to maintain participation and keep participants

engaged, especially during the first few weeks of the pilot study. Considering that five

(18.5%) of the 27 participants did not attend any weekly sessions and 11 (40.7%) of the

27 participants dropped out before the fourth weekly session suggests that these participants were not committed or engaged with the intervention.

Age (in years) and expired air carbon monoxide (parts per million) were identified as predictors of PIOKIO study attrition. The mean age of participants dropping out early in the pilot study was younger than the mean age of participants completing the pilot study. Studies have shown that age is a predictor of attrition: older participants are less likely to drop out,111,114 and younger age is associated with attrition.115,116 The research is

not clear on why younger smokers drop out from smoking cessation programs, but some

explanations have been proposed. Younger smokers, even if they want to quit, may have

other competing demands in life (e.g. working hours/scheduling conflicts, problems with

childcare, etc.) that interfere with their attendance in the smoking cessation

program.115,117 Research has shown that the number of cigarettes smoked is a good

predictor of smoking cessation. Participants who smoke a higher number of cigarettes per

day are more likely to drop out as they find it harder to overcome their need for

nicotine.118 Expired air carbon monoxide concentration has been considered as an indirect measure of cigarette use.119 Participants of younger age and those whose reported or

measured smoking rate is heavy may need more support throughout the smoking

cessation program.

The disparity in attrition and weekly session attendance between Appalachian

county and non-Appalachian county participants is significant. Participant feedback included transportation and childcare problems among the most common barriers to

attendance. The Foundry Christian Community Center in Warren County had two

advantages over the site in Hazard, KY. It was located within a low-income

neighborhood of the city of Bowling Green, which has a limited bus service from some

lower-income neighborhoods to a nearby bus stop. The Foundry also has a

preschool/child care program, in which the children of some participants may have been

enrolled. Hazard is a much-smaller city within a highly rural area. The only intra-county

transportation service has a very limited program and would not likely have been useful

for PIOKIO participants. To address these challenges, it may be beneficial to collaborate

with local churches that may help with childcare and transportation.19,120

It may also be useful to explore session scheduling. Commonly reported barriers

to attendance were changes in employment status and/or work scheduling conflicts.

Evening or late afternoon hours may be helpful. On the other hand, participants who have

children and who are unemployed may prefer to attend the sessions during day time when

their children are in school.

It is common for people to gain weight during and after smoking cessation,133-135

but limited weight gain and decrease in waist circumference were positive outcomes of

PIOKIO. Smoking cessation is associated with an average weight gain of 8.8 to 11 lbs.

after 12 months of abstinence in quitters who did not receive any pharmacological

treatment or who were not on treatment to prevent weight gain.135 Aubin and colleagues

focused on weight gain in those who quit smoking as part of randomized clinical trials of

cessation treatment, including pharmacotherapy, exercise, and weight gain prevention

studies.27 They reported that the average weight gain among successful quitters was 2.4

lbs. at one month, 5.1 lbs. at two months, 6.4 lbs. at three months, 9.2 lbs. at six months,

and 10.3 lbs. at 12 months.135 Changes in weight for PIOKIO study participants who quit smoking ranged from losing 8 lbs. to gaining 11.4 lbs. with an average 20-week/5 month

posttest weight gain of only 4.5 lbs.

Being in fair health may have motivated some of our study participants to quit

smoking. Four (67%) of the six participants who quit smoking had reported being in fair

health during the initial session. Researchers have shown that having a poor health

perception initially was a predictor of success in smoking cessation, perhaps due to a

higher motivation.136

4.1 Limitations

There are several important limitations of the study to consider. First, the study

lacks randomization or a comparable control group that may introduce potential biases.

Second, participants were a convenience sample from the two Kentucky counties

included in the pilot study. Most of these participants were highly self-motivated to enroll

in this pilot study and it may not be possible to generalize these results to smokers who

are less motivated to quit smoking. Third, the sample size was small at 22 participants.

Fourth, nicotine patches or lozenges were provided at no cost to the participants. The cost

of nicotine patches or lozenges may be a barrier for smokers in other communities who

wish to participate in a smoking cessation program that lacks the resources to provide

them to participants. Fifth, a priori criteria for feasibility and acceptability had not been

established. Sixth, the PIOKIO study design lacked a follow-up procedure for securing post-intervention data from individuals who did not complete the intervention.

4.2 Next steps

Additional pilot studies that are focused on implementation barriers and

challenges might help identify the delivery mode(s) that are most successful for an

MHBC intervention that combines existing successful programs. These pilot studies in

turn would provide information for the planning and justification of a full study. They

may, for example, help identify an implementation model that is cost effective for

delivery by budget-conscious public health agencies and community partners, yet able to

maintain the integrity of both CCMSS and DPP.

Additional studies would be useful to explore program retention barriers

specifically. A pilot study that incorporated follow-up interviews with participants who had dropped out, for example, might provide very valuable information for identifying and addressing retention barriers. Such pilot studies might also identify sub-populations by gender, age group, SES, etc. who are more likely to complete the PIOKIO program.

By first addressing this critical barrier of retention, a full study assessing the effectiveness of PIOKIO for achieving behavior and lifestyle change will be more meaningful.

CHAPTER 5. CONCLUSION

Results from the PIOKIO pilot study indicate that smokers wishing to quit are very hopeful about an MHBC intervention that may help them to quit without the common problem of weight gain. Both facilitators and the participants saw PIOKIO as having strong potential for meeting the preventive health needs of Kentucky communities. The public health practitioners who facilitated PIOKIO found this intervention practical to deliver. The major impediment to feasibility for implementation was participant retention. Poor retention is not surprising, given the duration of the intervention as well as the challenges of an intervention that addresses two of our most difficult health behavior changes of weight control and smoking.

APPENDIX 1. PARTICIPANT FEEDBACK FORM

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VITA

1. Educational institutions attended and degrees already awarded Western Kentucky University (Aug 2000-Dec 2002) - Master of Public Health Dr. B.R. Ambedkar Medical College, Bangalore, India (Aug 1991-July 1998) - Bachelor of Medicine and Bachelor of Surgery

2. Professional positions held 2018-Epidemiologist, Immunization Healthcare Division, Defense Health Agency, Falls Church, VA 2003-2018- Regional Epidemiologist, Barren River District Health Department (BRDHD), Bowling Green, KY 2002-2002- Health Educator, Tobacco Control Program, Watts Health Foundation, Inc. Inglewood, CA 2002-2002- Resource Center Intern, EPA division, California Family Health Council, Los Angeles, CA 2002-2002- Maternal, Child, and Adolescent Health Intern (Title X Intern)/Student Worker, Maternal Health & Family Planning Programs; Los Angeles Co. Department of Health Services, CA 2001-2001- Graduate Assistant, Department of Elementary Education, Western Kentucky University, Bowling Green, KY 1998-2000- Resident Medical Officer, Ahalia Hospital, Abu Dhabi, United Arab Emirates 1998-1998- Resident Physician, Venlakh Hospital, Bangalore, India 1997-1998- Intern, Dr. B.R. Ambedkar Medical College Hospital and K. C. General Hospital, Bangalore, India

3. Scholastic and professional honors Friend of Nursing, Sigma Theta Tau International, Honor Society of Nursing- 2014 E. “Al” Austin Jr., Career Achievement Award, Kentucky Public Health Association- 2012 Runner-Up for 2011 Balderson Leadership Project Award, National Public Health Leadership Development Network - 2011 Employee of the month, Barren River District Health Department, Bowling Green, KY – 2007.

4. Professional publications Trends in cigarette smoking and obesity in Appalachian Kentucky." Southern medical journal 108, no. 3 (2015): 170-177

5. Srihari Seshadri 84