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Recommendations as Challenges: Estimating Required Effort and User Ability for Health Behavior Change Recommendations

, and . 27th International Conference on Intelligent User Interfaces, page 106-119. ACM, (March 2022)
DOI: 10.1145/3490099.3511118

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Towards a User Integration Framework for Personal Health Decision Support and Recommender Systems., and . UMAP, page 65-76. ACM, (2021)Mobile Mood Tracking: An Investigation of Concise and Adaptive Measurement Instruments., and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (4): 155:1-155:30 (2020)Recommendations as Challenges: Estimating Required Effort and User Ability for Health Behavior Change Recommendations., and . IUI, page 106-119. ACM, (2022)Exploring chatbot user interfaces for mood measurement: a study of validity and user experience., and . UbiComp/ISWC Adjunct, page 135-138. ACM, (2020)Mood Measurement on Smartphones: Which Measure, Which Design?. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 7 (1): 29:1-29:35 (March 2023)Fifth International Workshop on Health Recommender Systems (HealthRecSys 2020)., , , and . RecSys, page 611-612. ACM, (2020)How can they know that?: a study of factors affecting the creepiness of recommendations., , and . RecSys, page 423-427. ACM, (2019)STRETCH: Stress and Behavior Modeling with Tensor Decomposition of Heterogeneous Data., , and . WI/IAT, page 453-462. ACM, (2021)Fourth international workshop on health recommender systems (HealthRecSys 2019)., , , , , and . RecSys, page 554-555. ACM, (2019)Health Recommender Systems for Mental Health Promotion. Essen University, Germany, (2022)base-search.net (ftunivessen:oai:duepublico2.uni-due.de:duepublico_mods_00076050).