{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T20:50:54Z","timestamp":1791233454296,"version":"4.1.0"},"reference-count":51,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Res Protoc"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Accurate measurement of lifestyle factors is central to understanding how daily behaviors act as risk factors or protective buffers to noncommunicable diseases. While wearable devices enable passive monitoring of physical activity or sleep, nutritional intake still depends on active participant input, such as manual dietary logs or image-based recordings. Adherence to such logging tasks often declines rapidly, impacting data completeness and clinical utility. Theory-based reminders drawing on loss-framing or logging consistency feedback (ie, tracking streaks) can improve adherence to lifestyle data collection, but the effects of these strategies on repeated dietary logging remain unclear.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n The study aims to examine the effects of 2 theory-driven reminder strategies\u2014loss-framing and logging consistency\u2014on adherence to repeated, image-based meal logging.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We conducted a microrandomized trial embedded within a 4-week observational lifestyle phenotyping study in Switzerland (N=200, age \u226545 y, BMI \u226525 kg\/m\u00b2). Participants photographed their meals at each mealtime (breakfast, lunch, and dinner) using a mobile app over 28 days. A decision point was scheduled prior to participant-defined habitual mealtimes. Participants were randomly assigned with equal probability to (1) a reminder emphasizing loss of a daily financial reward for not logging (\u201closs-framing\u201d), (2) a reminder providing feedback on recent logging consistency (\u201clogging consistency\u201d), or (3) a neutral reminder (\u201cactive control\u201d). The proximal outcome is whether the participant logs a meal within 2 hours of receiving a reminder. Participants earned a daily financial reward contingent on meal-logging completion. To estimate intervention effects, we will use marginal excursion effect models for binary outcomes, adjusting time-varying covariates (eg, day in study) and baseline covariates (eg, age and gender). Ethics approval for this study was granted by the Cantonal Ethics Committee of Eastern Switzerland (BASEC ID 2025\u201000972).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Enrollment began in November 2025, and the study was initiated on December 8, 2025. As of August 2026, 130 participants have been recruited, 120 have been enrolled, and 76 participants have completed the study, with an anticipated completion date of January 2027. Data analysis has not yet begun, and study results are expected to be published in Q2 2027.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n By clarifying the proximal effects of loss-framed and consistency-based reminders, findings will inform the design of future digital health studies to improve meal-logging adherence in daily life. This work contributes to the development of scalable, theory-driven reminder strategies for enhancing dietary data quality in observational and interventional research.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/100239","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T07:35:07Z","timestamp":1788161707000},"page":"e100239-e100239","source":"Crossref","is-referenced-by-count":0,"title":["Reminder Strategies to Improve Meal-Logging Adherence: Protocol for a Microrandomized 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