The Biggest Loser Thinks Long-Term: Recency as a Predictor of Success in Weight Management.

Only a minority of participants in behavioral weight management lose weight significantly. The ability to predict who is likely to benefit from weight management can improve the efficiency of obesity treatment. Identifying predictors of weight loss can also reveal potential ways to improve existing treatments. We propose a neuro-psychological model that is focused on recency: the reliance on recent information at the expense of time-distant information. Forty-four weight-management patients completed a decision-making task and their recency level was estimated by a mathematical model. Impulsivity and risk-taking were also measured for comparison. Weight loss was measured in the end of the 16-week intervention. Consistent with our hypothesis, successful dieters (n = 12) had lower recency scores than unsuccessful ones (n = 32; p = 0.006). Successful and unsuccessful dieters were similar in their demographics, intelligence, risk taking, impulsivity, and delay of gratification. We conclude that dieters who process time-distant information in their decision making are more likely to lose weight than those who are high in recency. We argue that having low recency facilitates future-oriented thinking, and thereby contributes to behavior change treatment adherence. Our findings underline the importance of choosing the right treatment for every individual, and outline a way to improve weight-management processes for more patients.

Decision-making, sensitivity to reward and attrition in weight management.

OBJECTIVE: Attrition is a common problem in weight management. Understanding the risk factors for attrition should enhance professionals' ability to increase completion rates and improve health outcomes for more individuals. A model that draws upon neuropsychological knowledge on reward-sensitivity in obesity and overeating to predict attrition is proposed. METHODS: A total of 52 participants in a weight-management program completed a complex decision-making task. Decision-making characteristics-including sensitivity to reward-were further estimated using a quantitative model. Impulsivity and risk-taking measures were also administered. RESULTS: Consistent with the hypothesis that sensitivity to reward predicted attrition, program dropouts had higher sensitivity to reward than completers (P < 0.03). No differences were observed between completers and dropouts in initial BMI, age, employment status, or the number of prior weight-loss attempts (P ≥ 0.07). Completers had a slightly higher education level than dropouts, but its inclusion in the model did not increase predictive power. Impulsivity, delay of gratification, and risk taking did not predict attrition, either. CONCLUSIONS: Findings link attrition in weight management to the neural mechanisms associated with reward-seeking and related influences on decision-making. Individual differences in the magnitude of response elicited by rewards may account for the relative difficulty experienced by dieters in adhering to treatment.