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Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Integrating human support with chatbot-based behavior change interventions raises three challenges: (1) attuning the support to an individual\u2019s state (e.g., motivation) for enhanced engagement, (2) limiting the use of the concerning human resources for enhanced efficiency, and (3) optimizing outcomes on ethical aspects (e.g., fairness). Therefore, we conducted a study in which 679 smokers and vapers had a 20% chance of receiving human feedback between five chatbot sessions. We find that having received feedback increases retention and effort spent on preparatory activities. However, analyzing a reinforcement learning (RL) model fit on the data shows there are also states where not providing feedback is better. Even this \u201cstandard\u201d benefit-maximizing RL model is value-laden. It not only prioritizes people who would benefit most, but also those who are already doing well and want feedback. We show how four other ethical principles can be incorporated to favor other smoker subgroups, yet, interdependencies exist.<\/jats:p>","DOI":"10.1038\/s41746-025-01701-3","type":"journal-article","created":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T10:15:14Z","timestamp":1748686514000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Psychological, economic, and ethical factors in human feedback for a chatbot-based smoking cessation intervention"],"prefix":"10.1038","volume":"8","author":[{"given":"Nele","family":"Albers","sequence":"first","affiliation":[]},{"given":"Francisco S.","family":"Melo","sequence":"additional","affiliation":[]},{"given":"Mark A.","family":"Neerincx","sequence":"additional","affiliation":[]},{"given":"Olya","family":"Kudina","sequence":"additional","affiliation":[]},{"given":"Willem-Paul","family":"Brinkman","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,31]]},"reference":[{"key":"1701_CR1","doi-asserted-by":"publisher","first-page":"e45111","DOI":"10.2196\/45111","volume":"25","author":"YE Fang","year":"2023","unstructured":"Fang, Y. 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