Behavior Analytic Approach to Increase Exercise Behavior in Overweight and Obese Adults Contemporary Developments in Behavior Analysis Boston, March 12th, 2011 Gretchen A. Dittrich Michael Cameron What is behavioral medicine? • Behavioral medicine involves the application of behavior analytic principles to the prevention, treatment, and rehabilitation of medical and health disorders. • Behavioral medicine evaluates the relation between behavior and biology, and provides methods to shift these relations to improve overall health in individuals, populations, and communities. A sizeable epidemic: • 2 out of 3 Americans are overweight (BMI ≥ 25) • 1 out of 3 Americans are obese (BMI ≥ 30) • Obesity prevalence is accelerating in the U.S. (Ogden, & Carroll, 2010) • Prevalence of extreme morbid obesity has increased by 75% (Sturm, 2007) • The epidemic is not limited to America, but is also spreading across the world (Malnick, & Knobler, 2006) Normal-weight obesity syndrome • Normal weight (BMI of 18.5 - 24.9) • Body fat mass similar to obese – Women ≥ 30% – Men ≥ 20 – 25% • More than 50% of normal weight Americans are normal-weight obese (Mayo Clinic) • People with normal weight obesity are at risk for developing the same health problems as those who are overweight or obese Collateral effects of obesity: • Physiological complications: – Hypertension, dyslipidemia, cardiovascular disease, stroke, sleep disorders, gallbladder disease, gastroesophageal reflux disease, liver and kidney disease, cancer, metabolic syndrome, Type II diabetes, osteoarthritis, etc. (Malnick, & Knobler, 2006; Mokdad, et al., 2003) • Psychological complications: – depression (Malnick, & Knobler, 2006) • Health care costs : – $147 billion per year (Finkelstein, Trogdon, Cohen, & Dietz, 2009) Treatments: • Pharmacological • Dietary or nutritional changes, naturopathic treatment • Surgical – Lap Band, gastric bypass surgery, gastric reduction duodenal switch (GRDS), cervical vagus nerve stimulation (VNS), jaw fixation, etc. • Exercise • Behavioral • Many treatments result in immediate reinforcement with minimal response effort Behavior analysis and weight loss • There is a direct relationship between the environment and healthy or unhealthy behavior – Eating – Exercising • These behaviors are amenable to a behavior analytic approach to treatment – – – – Quantifiable Measurable Can be analyzed Are susceptible to conditioning Effective behavior analytic interventions include: • • • • • • • • Self-monitoring Goal setting Caloric restrictions Stimulus control Behavior substitution Relapse prevention Social support systems Exercise Exercise • Exercise facilitates weight loss through caloric expenditure • However, studies that incorporated exercise also noticed ancillary improvements in: – Adherence to reduced calorie diet (Jakicic, Wing, & Winters-Hart, 2002) – Feelings of well being (Hansen, Stevens, & Coast, 2001) • From a behavioral perspective, these findings may be explained by way of stimulus-stimulus pairing – Changes in neurotransmitter levels and rate of transfer during and immediately following exercise – Exercise becomes conditioned reinforcer – Behaviors associated with accessing reinforcement increase • Exercise has been demonstrated to improve overall health in normal weight, overweight, and obese individuals, and these changes can occur without weight loss • In addition, research suggests that exercise plays an important role in weight loss maintenance – People who continue to exercise post treatment at levels similar to those during treatment were more successful at maintaining weight loss for at least 1 year (Gorin, Phelan, Wing, & Hill, 2004; Elfhag, & Rössner, 2005; Miller, Koceja, & Hamilton, 1997; Ryan, & Kushner, 2010; and Annesi, & Whitaker, 2010) Recommendations for exercise • Cardiorespiratory – 150 min per week (moderate-intensity) – 75 min per week (vigorous-intensity) – Combination of both • Strength training – At least 2 days per week • Few Americans meet exercise targets • Exercising frequency is declining • Behavior analytic programs can increase exercise behavior Purpose • To evaluate the efficacy of a behavior analytic treatment package on exercise behavior in overweight or obese adults. Method • Participants: – – – – – – 4 Adults: 3 female, 1 male Age range: 26 - 48 years old 3 met criteria for overweight or obese status (BMI ≥ 25) 1 was struggling to lose weight after pregnancy All participants in a 10-stage weight loss program All participants had a release from PCP • Materials: – Caloric burn calculator (http://www.healthstatus.com/calculator/cbc) – Wi-Fi Scale – Video Conference equipment (headset, webcam, ooVoo®) • Setting: – Weekly video group meetings occurred online via ooVoo®, within the participants’ homes – All exercise activities occurred in locations determined by participants (e.g., gym, home, park, etc.) • Data collection: – Exercise data were calculated via the caloric burn calculator – Weight and body fat composition were transmitted electronically daily via the Wi-Fi scale – Goal and self-monitoring logs were emailed weekly – Baseline and current data were collected to determine changes in fitness and health measures (endurance, heart rates, specific medical conditions) • Additional data collected: – Functional movement screen – Maximal strength – Blood pressure • Unique to this research: – The current research analyzed a rich array of dependent variables to determine changes in overall health. – Multiple independent variables were introduced simultaneously. • Experimental design: – Multiple baseline across participants Procedure • Baseline – Anthropometric, cardiovascular, strength, FMS, and exercise (variety, duration, frequency) data were collected prior to treatment – Preference assessment for movement and exercise behavior – Stimulus control evaluation • Previous exercise activities • Antecedents to exercise or sedentary behavior • Goals • General guidelines – – – – Record physical activity and calories burned daily Weigh in daily on Wi-Fi scale Submit self-monitoring reports weekly Weekly online group meetings via ooVoo® • Correspondence training – Self-monitoring • Participants self monitor exercise behavior daily – Public reporting • progress was reported daily via Twitter® to all members • Exercise easing (shaping) – Target successful activities – Begin with short durations of low intensity exercise – Goal was to establish exercise behaviors in daily routines • Exercise diversification – Increase the variety of activities in the weekly exercise routine to include: • Cardiorespiratory workouts • Flexibility • Strength training • Exercise intensity shaping – Increase the intensity, duration, and frequency of exercise – Focus on exercising within cardio zones • Medium • Moderate • Cardiovascular max • Establishment of kedge goals – Publicly posted (via Twitter ® within behavior health community) goals with deadlines – These goals encourage maintenance of exercising behavior Interobserver Agreement (IOA) • Second independent observer: – Endurance – Blood pressure – Recovery heart rate • Professionals: – FMS, strength – Blood work • Equipment: – Weight – % body fat 400 BL 300 Shaping 200 100 0 1 5 9 13 17 21 25 29 33 1 5 9 13 17 21 25 29 33 1 5 9 13 17 21 25 29 33 1 5 9 13 17 21 25 29 33 800 Weekly Duration (min) 600 400 200 0 800 600 400 200 0 300 250 200 150 100 50 0 Weeks Change in Fitness Measures Endurance Participant Phase 1 B 0 60 0 0 0 94 33 C 5 66 34 4.3 1216 79 36 B 2 25 10 2.7 303 66 35 C 7 33 28 6.3 2825 60 44 B 3 --- --- 3 773 --- --- C 7 25 21 5 3500 70 50 B 1 49 40 3 351 50 50 C 5 58 41 5.3 2380 48 70 3 4 Pushups Heart rate Different activities 2 Situps Weekly exercise Days Calories burned Resting Recovery Change in Categories of Exercise Cardiorespiratory Strength training Flexibility Participant Phase Frequency Duration Frequency Duration Frequency Duration 1 B 0 0 0 0 0 0 C 3.7 136 1 2 0 0 B 2.7 101 0 0 0 0 C 4.7 328 1 60 1 75 B 3 90 1 30 1 60 C 2.7 205 1 20 3 233 B 0 0 3 45 0 0 C 3 155 5 50 0 0 2 3 4 Change in Anthropometric Measures and Medical Conditions Participant Phase Age Weight BMI % Fat 1 B 26 171 31.3 36 C --- 152 27.9 34.7 --- B 48 206 37 45.4 Fatty liver: alk phos 122, sgot 155, sgpt 322 C --- 167 29.6 40 Healthy liver: alk phos 84, sgot 26, sgpt 45 B 35 143 23.2 26.7 Daily lower back and hip pain C --- 128 20.6 23.9 Reduced pain B 38 230 28.8 23.7 High blood pressure (on medication) C --- 208 25.8 19 Will be tested to go off of medication 2 3 4 Medical conditions No weight-related conditions Preliminary Results • The treatment package was effective in improving exercise behavior, in terms of: – Increased frequency and duration of exercise per week – Increased variety in exercise activities – Increased caloric burn • Participants experienced changes in their overall health, as measured by: – Decreased resting HR, increased recovery HR, decreased body fat composition, improved medical conditions • Participants demonstrated: – Increased endurance Review • Exercise program implemented within a 10-stage weight loss program • Combines stimulus control, shaping, goal setting, self-monitoring, public posting, and social support systems • Evaluates changes in multiple dependent variables • Demonstrates, rather than assumes, improved health Discussion • Research suggests that incorporating exercise into a weight loss program will result in improved health benefits and weight loss that maintains more than 2 years post treatment • Exercise improves overall health in overweight, obese, and normal weight individuals. • Furthermore, exercise has been demonstrated to reduce depression, and prevent age-related illnesses • We currently live in an obesogenic environment • The prevalence of obesity is accelerating and spreading world wide, and it affects all ages. • Behavior analytic weight loss treatments are effective and result in overall improved health • We need to utilize our knowledge of behavior, the mechanisms that change behavior, and the strategies to maintain such changes and apply it to this global problem Limitations • Results are preliminary • Changes in weight, body fat composition, and medical conditions are 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