Theory-based psychosocial factors that discriminate between weight-loss success and failure over 6 months in women with morbid obesity receiving behavioral treatments
- 338 Downloads
To improve success rates of behavioral weight-loss treatments, a better understanding of psychosocial factors that discriminate between weight-loss success and failure is required. The inclusion of cognitive–behavioral methods and manageable amounts of exercise might induce greater improvements than traditional methods of education in healthy eating practices.
Women with morbid obesity [body mass index (BMI) ≥40 kg/m2] were recruited for a treatment of supported exercise paired with either a cognitive–behavioral or an educational approach to eating change over 6 months. They were classified as either successful with (i.e., at least 5 % loss; n = 40) or failed at (no loss, or weight gain; n = 43) weight loss. Discriminate function analysis incorporated theory-based models of 1 (self-efficacy), 5 (self-efficacy, self-regulation, mood, physical self-concept, body satisfaction), and 3 (self-efficacy, self-regulation, mood) psychosocial predictors at both month 6, and change from baseline–month 6.
All three models significantly discriminated weight-loss success/failure (66, 88, and 87 % for success; and 81, 87, and 88 % for failure, respectively). Self-regulation had the strongest correlations within the multi-predictor models (0.90–0.96), and all variables entered were above the standard of 0.30 set for relevance. Participants in the cognitive–behavioral nutrition group demonstrated significantly greater improvements in all psychosocial variables and success with weight loss. Completing at least two sessions of exercise per week predicted success/failure with weight loss better than overall volume of exercise.
New and relevant findings regarding treatment-induced psychosocial changes might be useful in the architecture of more successful behavioral weight-loss interventions.
KeywordsObesity Weight loss Psychological factors Behavioral theory
We acknowledge Ms. Kristin McEwen for her role in data collection within this study.
Conflict of interest
For this study the authors declare no conflict of interest.
- 9.Baker CW, Brownell KD (2000) Physical activity and maintenance of weight loss: physiological and psychological mechanisms. In: Bouchard C (ed) Physical activity and obesity. Human Kinetics, Champaign, pp 311–328Google Scholar
- 11.Buckworth J, Dishman RK (2002) Exercise psychology. Human Kinetics, ChampaignGoogle Scholar
- 19.Anderson ES, Winett RA, Wojcik JR, Williams DM (2010) Social cognitive mediators of change in a group randomized nutrition and physical activity intervention: social support, self-efficacy, outcome expectations, and self-regulation in the guide-to-health trial. J Health Psychol 15:21–32. doi: 10.1177/1359105309342297 CrossRefPubMedGoogle Scholar
- 25.Palmiera AL, Markland DA, Silva MN, Branco TL, Martins SC, Minderico CS, et al. (2009) Reciprocal effects among changes in weight, body image, and other behavioral factors during behavioral obesity treatment: a mediation analysis. Int J Behav Nutr Phys Act 6:9. doi: 10.1186/1479-5868-6-9. http://www.ijbnpa.org/content/6/1/9
- 31.Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice Hall, Englewood CliffsGoogle Scholar
- 32.Bandura A (1997) Self-efficacy: the exercise of control. Freeman, GordonsvilleGoogle Scholar
- 44.McNair DM, Heuchert JWP (2005) Profile of Mood States technical update. Multi-Health Systems, North TonawandaGoogle Scholar
- 45.Fitts WH, Warren WL (1996) Tennessee Self-Concept Scale manual, 2nd edn. Western Psychological Services, Los AngelesGoogle Scholar
- 47.Cash TF (1994) The Multidimensional Body-Self Relations Questionnaire users’ manual. Old Dominion University, NorfolkGoogle Scholar
- 48.Godin G (2011) The Godin–Shephard Leisure-Time Physical Activity Questionnaire. Health Fit J Can 4(1):18–22Google Scholar
- 52.Miller DJ, Freedson PS, Kline GM (1994) Comparison of activity levels using Caltrac accelerometer and five questionnaires. Med Sci Sport Exerc 26:376–382Google Scholar
- 53.Kaiser Permanente Health Education Services (2008) Cultivating health weight management kit, 8th edn. Kaiser Permanente Northwest, PortlandGoogle Scholar
- 56.Grimm LG, Yarnold PR (eds) (1995) Reading and understanding multivariate statistics. American Psychological Association, Washington DCGoogle Scholar
- 58.Tabachnick BG, Fidell LS (1996) Using multivariate statistics. Harper Collins, New YorkGoogle Scholar
- 59.Diekhoff GM (1992) Statistics for the social and behavioral sciences: univariate, bivariate, multivariate. Brown, DubuqueGoogle Scholar
- 64.Morgan WP (1997) Methodological considerations. In: Morgan WP (ed) Physical activity and mental health. Taylor & Francis, Washington DCGoogle Scholar
- 65.Nunally JC, Bernstein IH (1994) Psychometric theory, 2nd edn. McGraw-Hill, New YorkGoogle Scholar