Personalized predictions to identify individuals most likely to achieve 10% weight loss with a lifestyle intervention

URN to cite this document:: urn:nbn:de:bvb:355-epub-777165
DOI to cite this document:: 10.5283/epub.77716

Kuhlemeier, Alena

; Van Horn, David J. ; Jaki, Thomas

; Wilson, Dawn K. ; Resnicow, Ken

; Jimenez, Elizabeth Y. ; Van Horn, M. Lee

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 22 Sep 2025 05:26

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Abstract

Objective: The objective of this study is to generate an algorithm for making predictions about individual treatment responses to a lifestyle intervention for weight loss to maximize treatment effectiveness and public health impact. Methods: Using data from Action for Health in Diabetes (Look AHEAD), a national, multisite clinical trial that ran from 2001 to 2012, and machine-learning ...