Evidence map›Paper›PMID 42832707›Full record

ArticleJMIR research protocols2026

Reminder Strategies to Improve Meal-Logging Adherence: Protocol for a Microrandomized Trial.

Magdalena Fuchs, Victoria Brügger, Qiuhan Jin, Benjamin Wirth, Stefan Bilz, Florian von Wangenheim, Michael Brändle, Tobias Kowatsch, Mia Jovanova

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Magdalena FuchsDepartment of Management, Technology and Economics, ETH Zurich, Weinbergstrasse 56/58, Zürich, Zurich, 8006, Switzerland, +41 446321111.ORCID http://orcid.org/0009-0003-5621-1560
Victoria BrüggerSchool of Medicine, University of St. Gallen, St. Gallen, Switzerland.ORCID http://orcid.org/0000-0002-8294-2370
Qiuhan JinSchool of Medicine, University of St. Gallen, St. Gallen, Switzerland.ORCID http://orcid.org/0009-0004-4151-3889
Benjamin WirthDepartment of Endocrinology, HOCH Health Ostschweiz, St. Gallen, Switzerland.ORCID http://orcid.org/0000-0001-7006-0410
Stefan BilzDepartment of Endocrinology, HOCH Health Ostschweiz, St. Gallen, Switzerland.ORCID http://orcid.org/0000-0002-7716-2791
Florian von WangenheimDepartment of Management, Technology and Economics, ETH Zurich, Weinbergstrasse 56/58, Zürich, Zurich, 8006, Switzerland, +41 446321111.ORCID http://orcid.org/0000-0003-3964-2353
Michael BrändleDepartment of Endocrinology, HOCH Health Ostschweiz, St. Gallen, Switzerland.ORCID http://orcid.org/0000-0002-3228-0313
Tobias KowatschDepartment of Management, Technology and Economics, ETH Zurich, Weinbergstrasse 56/58, Zürich, Zurich, 8006, Switzerland, +41 446321111.ORCID http://orcid.org/0000-0001-5939-4145
Mia JovanovaDepartment of Management, Technology and Economics, ETH Zurich, Weinbergstrasse 56/58, Zürich, Zurich, 8006, Switzerland, +41 446321111.ORCID http://orcid.org/0000-0003-3634-4449

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Objective: The study aims to examine the effects of 2 theory-driven reminder strategies-loss-framing and logging consistency-on adherence to repeated, image-based meal logging. Methods: We conducted a microrandomized trial embedded within a 4-week observational lifestyle phenotyping study in Switzerland (N=200, age ≥45 y, BMI ≥25 kg/m²). 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 ("loss-framing"), (2) a reminder providing feedback on recent logging consistency ("logging consistency"), or (3) a neutral reminder ("active control"). 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 2025-00972). Results: 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. Conclusions: 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.

Indexed as

MealsPatient ComplianceReminder SystemsAdherence InterventionsFemaleHumansMaleMiddle AgedMobile ApplicationsSwitzerlandadherencehabit formationloss aversionmHealthmicrorandomized trialmobile healthnutrition trackingpush notifications

Identifiers

PMID42832707
PMCPMC13637989

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.