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Existing eCoaching systems largely focus on personalized feedback without incorporating social reinforcement or group-level motivation, creating a gap in leveraging community influence for sustained health behaviors. Our system combines real-time activity tracking through wearable sensors and advice-based collaborative filtering to deliver adaptive recommendations. We collected data from 31 participants (16 using MOX2-5 sensors and 15 from a public Fitbit-based dataset), targeting daily activity levels to generate actionable guidance. Through decision tree classification and SHAP-based interpretability, we achieved a model accuracy of 99.8%, with F1, precision, recall, and MCC metrics confirming robustness across both balanced and imbalanced datasets. Ethical considerations, including privacy, bias mitigation, and informed consent, were integral to our design and implementation. Limitations include potential biases due to sample size and data imbalances, suggesting the need for future validation on independent datasets. This system demonstrates the potential to integrate with real-world healthcare initiatives, offering trust, transparency, and user engagement opportunities to meet public health objectives.<\/jats:p>","DOI":"10.1007\/s11042-025-21116-2","type":"journal-article","created":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T10:39:21Z","timestamp":1758105561000},"page":"50001-50035","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Designing an ethical and explainable automatic coaching (eCoach) system for community based, persuasive recommendations"],"prefix":"10.1007","volume":"84","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0407-7702","authenticated-orcid":false,"given":"Ayan","family":"Chatterjee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael\u00a0A.","family":"Riegler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P\u00e5l","family":"Halvorsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,17]]},"reference":[{"key":"21116_CR1","unstructured":"https:\/\/www.who.int\/news\/item\/04-04-2002-physical-inactivity-a-leading-cause-of-disease-and-disability-warns-who. 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Therefore, ethical bodies, such as SIKT and REK, approved all experimental protocols. In this study, participation has been voluntary. Informed consent was obtained from all participants included in the study. Moreover, we have not disclosed any identifiable data of the participants in the form of numbers, text, or figures. We used two separate tables - a. Table-1 to store personal information (e.g., email, name, surname, address, unique id, and bcrypted password), and b. Table\n                      \n                      for data collection (Unique id, and all data fields). We created separate access-control list for both the tables. Therefore,\n                      informed consent form as directed by ethical bodies to participate was obtained from all the participants in the study. All experiments were performed by relevant REK and SIKT guidelines and regulations.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval and Consent to Participate"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interests"}}]}}