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Engagement Phenotypes in a Real-World Tirzepatide-Based Dig-Ital Weight-Loss Program: Unsupervised Clustering of Self-Tracking, Human Coaching, and AI Conversational Support

2026-06-29

Abstract excerpt

<h4>Background: </h4> and Objectives: Real-world adherence to medication-supported weight management programs is often low. While digital weight loss services (DWLS) provide multi-modal digital supports to improve engagement and counter attrition, existing literature frequently relies on unidimensional or binary classifications of user engagement. This study used unsupervised machine learning to identify distinct...

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Literature Corpus work
15187b83-9f2f-5ca1-8bde-5b226827133d
DOI
10.20944/preprints202606.2106.v1
Open publication

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Engagement Phenotypes in a Real-World Tirzepatide-Based Dig-Ital Weight-Loss Program: Unsupervised Clustering of Self-Tracking, Human Coaching, and AI Conversational SupportDOI 10.20944/preprints202606.2106.v1
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