Background The ability to identify and measure behaviors that are related to weight loss and
the prevention of weight regain is crucial to understanding the variability in response to …

Background Individual variability in response to multiple modalities of obesity treatment is
well documented, yet our understanding of why some individuals respond while others do …

Background Within the Accumulating Data to Optimally Predict obesity Treatment (ADOPT)
Core Measures Project, the psychosocial domain addresses how psychosocial processes …

Background The responses to behavioral, pharmacological, or surgical obesity treatments
are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment …

The identification of predictor variables in the treatment of obese patients can focus on four
separate albeit related facets: attrition during treatment; short-term weight loss, long-term …

The medical evaluation of an individual with obesity, described by Kumar and Aronne
(Chapter 15, this volume), should be complemented whenever possible by a behavioral …

Weight management is a dynamic process, with a pre‐treatment phase, a treatment
(including process) phase and post‐treatment maintenance, and where relapse is possible …

Objective To describe the development of the Oxford Food and Activity Behaviors (OxFAB)
taxonomy and questionnaire to explore the cognitive and behavioral strategies used by …

Behavioral treatment for obesity, also commonly referred to as comprehensive lifestyle
treatment, employs principles from learning and social–cognitive theories (Bandura, 1991; …

Obesity is a global epidemic, yet successful interventions are rare. Up to 60% of people fail
to achieve clinically meaningful, short-term weight loss (5–10% of start weight), whereas up …