Assessment of psychological predictors of weight loss: How and what for?

Abstract

Obesity is a multifactorial disease and the prominent factors playing a role in its pathogenesis are biological, environmental and psychological. There is a growing interest in understanding psychological functioning of obese subjects and the influence of psychological factors on treatment outcome. The aim of the present narrative review is to critically analyze the current literature, in order to point out the most common psychological constructs studied in obesity and to give an overview of the main existing tools investigating psychological features which have been considered significant for the prediction of success in weight loss and maintenance programs in obese patients. In this framework, the most common psychological constructs studied are: self-motivation, self-efficacy, locus of control, health related quality of life, self-esteem, self-control, concerns about body image, outcome expectations, and personality traits. These features have been explored through a wide variety of psychometric instruments. However, as an overall, studies evaluating the association between psychological features and treatment outcome failed to give consistent results. A possible explanation may consist on the fact that many tools widely used to explore psychological features were not specifically designed for obese patients and none of them was comprehensive of all possible psychological features involved. The identification of well-defined subgroups of patients and the validation of more reliable and comprehensive tools, specifically designed for obese subjects, should be forecasted in order to reach a better knowledge of psychological functioning of obese individuals and to improve the outcome of weight loss programs.

Evolving self view and body image concerns in female postoperative bariatric surgery patients

“…BSQ scores indicate how the individual views herself and incorporates a perceptual, attitudinal and behavioural component and thus may or may not be rooted in reality. It is a concept that is extremely relevant to research in obesity, as 74% of obese individuals have body image dissatisfaction and distortion (Lazzeretti et al., ). A study by Pona, Heinberg, Lavery, Ben‐Porath, and Rish () found that patients with pre‐existing mental health issues, such as depression or ideas of persecution were more likely to report body image concerns in the first 3 months after bariatric surgery, despite weight loss.…”

“…The data show that slightly more than half of women who report a low concern about their body image also view themselves as "I-ex-obese" (n = 7, 58%). If we view as (Lazzeretti et al, 2015). A study by Pona, Heinberg, Lavery, Ben-Porath, and Rish (2016) found that patients with pre-existing mental health issues, such as depression or ideas of persecution were more likely to report body image concerns in the first 3 months after bariatric surgery, despite weight loss.…”

“…Lazzeretti et al. () says: “The BSQ is one of the most valid psychometric instruments for the assessment of distress related to body image and weight in obese individuals seeking weight reduction” (p. 62).…”

“…The body is the external self that we present to the world, and as a result, the opinions and support of others may impact the postsurgical adjustment and ultimate weight loss (Livhits et al., ). Therefore, recovery and adaptation should be viewed through a holistic lens (Lazzeretti, Rotella, Pala, & Rotella, ).…”

The Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Project: Rationale and Approach

“…There is a growing understanding that this variability in response is rooted in the inherent variability of behavioral, biological, environmental, and psychosocial factors ; however, at present, we lack data sets that allow a comprehensive examination of how these multiple factors and their interactions influence treatment response. Some explanatory factors have emerged as potential predictors of treatment response and are summarized elsewhere , but few have been replicated across trials . Several reasons for this have been suggested, including heterogeneous study populations and treatments, imprecisely defined factors and the lack of common measures to assess them, insufficient frequency of longitudinal assessments, insufficient statistical power, and inadequate statistical modeling and analytic approaches .…”