Review of the use of digital therapeutics (DTx) for obesity treatment: towards a psychological phenotyping?

Digital therapeutics (DTx) offer an innovative opportunity for the prevention and treatment of obesity. However, their efficacy remains limited by a standardized approach that often does not adequately consider interindividual differences in eating behavior, motivation, mental comorbidities and emotional regulation. Currently, many DTx rely primarily on physical indicators such as BMI and blood pressure, overlooking psychological factors that influence adherence and intervention success. Given that obesity is a multifactorial pathology, it is crucial to develop a more personalized approach including psychological phenotyping. This method involves the categorization of patients according to key psychological dimensions: personality, eating behavior, psychological burden, emotional regulation, motivation, health literacy, body image, and social support. Such classification may enable optimization of DTx relevance and clinical impact, contingent on algorithm validation and integration with clinical oversight. This narrative review explores the psychological dimensions involved in obesity and how they may be used to inform personalization strategies in digital therapeutics (DTx). Through an analysis of existing studies, we identify underexplored psychological dimensions and suggest the integration in DTx to enhance patient assessment and monitoring. Finally, we discuss the clinical and methodological implications of psychological phenotyping, highlighting its value for healthcare professionals, who could achieve greater efficiency through better-tailored recommendations and optimizing patient care. STATEMENT OF SIGNIFICANCE: Current digital therapeutics for obesity largely overlook psychological heterogeneity among patients, relying primarily on physiological indicators. This review is the first to propose psychological phenotyping as a structured framework, identifying eight key psychological dimensions and five DTx-specific personalization mechanisms to improve engagement and clinical outcomes.

• Publication year

  2026

• Venue

  Advances in Nutrition

• Publication date

  2026-03-01

• Fields of study

  Medicine, Psychology

• Identifiers
  DOI 10.1016/j.advnut.2026.100613PMID 41780892PMCID PMC13022612
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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