Bariatric Surgical Practice and Patient Care

Body image concerns are common among individuals seeking bariatric surgery, though less is known about factors associated with positive body image in this population. Body appreciation has received limited attention in prebariatric samples, despite its potential relevance. The present study examined psychosocial correlates of body appreciation, with particular focus on overvaluation of shape and weight (OSW) and sociocultural appearance pressures.

Adults seeking bariatric surgery (N = 160) completed an online questionnaire following a psychological evaluation at a rural Midwestern hospital. Bivariate correlations and hierarchical linear regression analyses examined associations between body appreciation and psychosocial variables. Moderation analyses tested age as a potential moderator.

Body appreciation was negatively correlated with OSW and sociocultural appearance pressures from peers, family, and media but was not significantly correlated with age. In regression analyses controlling for age, gender, and body mass index, OSW and age emerged as significant negative predictors of body appreciation, whereas sociocultural appearance pressures did not uniquely predict body appreciation. Age did not moderate the associations of OSW or sociocultural appearance pressures with body appreciation.

OSW appears to be a key psychosocial correlate of low body appreciation among individuals seeking bariatric surgery, highlighting its potential relevance for presurgical psychosocial assessment and support.

Obesity is a major global health challenge with significant metabolic and cardiovascular consequences. Artificial intelligence (AI) offers novel opportunities for prediction, risk stratification, and management; however, the structural landscape of this research has not been comprehensively assessed.

We conducted a bibliometric analysis of 5893 unique articles from 2015 to July 15^th, 2025, indexed in Web of Science and Scopus. We used R (Bibliometrix and Biblioshiny) and VOSviewer to evaluate publication trends, citations, collaborations, and thematic clusters. Data integrity was verified by dual review of 5% of studies.

Scientific output rose steadily, with a marked acceleration after 2019. Citation activity peaked in 2020, reflecting increased focus on digital health during the Coronavirus Disease 2019 (COVID-19) pandemic. Thematic mapping identified four main clusters: (1) AI in surgical outcomes, including bariatric surgery and risk prediction; (2) digital health and remote care; (3) conversational technologies like natural language processing and chatbots; and (4) precision health, focusing on personalized medicine and predictive analytics. Collaboration networks were sparse, with few prolific authors.

AI research in obesity is expanding rapidly across diverse themes but remains fragmented. Strengthening interdisciplinary collaboration will be critical to maximize impact on obesity care and outcomes.