Managing Editor
@ShahidNShah
@ShahidNShah
Personalizing a Weight Loss Program Using Cognitive-Behavioral Phenotypes to Improve Engagement and Weight Loss in Adults With Overweight or Obesity
Obesity affects more than one-quarter of adults in the United Kingdom and is a leading cause of preventable disease and health care costs. Digital behavior change programs can provide scalable weight management support, but maintaining engagement is challenging, and engagement is strongly associated with weight loss success. Tailoring interventions to cognitive-behavioral phenotypes, distinct patterns of thinking and behavior, offers one strategy to improve adherence. Although such approaches show promise in controlled settings, evidence from real-world digital programs is limited.
Medigy Insights
A stand-alone digital intervention designed to increase physical activity among office workers showed promising usability and moderate engagement, suggesting digital tools can support workplace health behavior change. However, sustained participation remains a challenge, highlighting the need for more engaging and personalized content to maintain long-term activity improvements.
Continue reading at formative.jmir.org
Make faster decisions with community advice
- Bridging The Digital Health Divide: Digital Endowment, Informal Social Participation, And Health Inequality Among Older Adults
- Comparing ChatGPT and DeepSeek for Assessment of Multiple-Choice Questions in Orthopedic Medical Education
- Effectiveness of ChatGPT, Google Gemini, and Microsoft Copilot in Answering Thai Drug Information Queries: Cross-Sectional Study
- Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study
- Observer-Independent Assessment of Content Overlap in Mental Health Questionnaires: Large Language Model–Based Study
Next Article
-
Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study
Large language models (LLMs) have been shown to answer patient questions in ophthalmology similar to human experts. However, concerns remain regarding their use, particularly related to patient …
