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Health recommender systems (HRSs) have the potential to effectively personalize well-being related behavior change interventions to the needs of individuals. However, personalization is often conducted with a narrow perspective, and the underlying user features are inconsistent across HRSs. Particularly, theory-based determinants of behavior and the variety of lifestyle domains influencing well-being are poorly addressed. We propose a comprehensive theory-based framework of user features, the virtual individual (VI) model, to support the extensive personalization of digital well-being interventions. We introduce a prototype HRS (With-Me HRS) with knowledge-based filtering, which recommends behavior change objectives and activities from several lifestyle domains. With-Me HRS realizes a minimum set of important VI model features related to well-being, lifestyle, and behavioral intention. We report the preliminary validity and usefulness of the HRS, evaluated in a real-life health-coaching program with 50 participants. The recommendations were used in decision-making for half of the participants and were hidden for others. For 73&#x0025; of the participants (85&#x0025; with visible vs. 62&#x0025; with hidden recommendations), at least one of the recommended activities was included into their coaching plans. The HRS reduced coaches&#x2019; perceived effort in identifying appropriate coaching tasks for the participants (effect size: Vargha-Delaney <inline-formula> <tex-math notation="LaTeX">$\hat {A}$ </tex-math></inline-formula> &#x003D; 0.71, 95&#x0025; CI 0.59-0.84) but not in identifying behavior change objectives. From the participants&#x2019; perspective, the quality of coaching improved (effect size for one of three quality metrics: <inline-formula> <tex-math notation="LaTeX">$\hat {A}$ </tex-math></inline-formula> &#x003D; 0.71, 95&#x0025; CI 0.57-0.83). These results provide a baseline for testing the influence of additional user model features on the validity of recommendations generated by knowledge-based multi-domain HRSs.

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A Comprehensive User Modeling Framework and a Recommender System for Personalizing Well-Being Related Behavior Change Interventions: Development and Evaluation