ArticleBMC medical research methodology2025
Dropping out of a peripartum depression mHealth study: participants' motives and suggestions for improvement.
Article in BMC medical research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
Who cites it
3 citing papers in PubMed.
- Can reporting mood swings during oral contraceptive use predict peripartum depression? Results from the Swedish longitudinal cohort study Mom2B.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- Separation between mothers and newborns directly after birth: mothers' experiences of separation - a qualitative analysis from a cohort study.Archives of disease in childhood. Fetal and neonatal edition · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPeripartum depression is a common but potentially debilitating pregnancy complication. Mobile applications can be used to collect data throughout the pregnancy and postpartum period to improve understanding of early risk indicators.
aimThis study aimed to improve understanding of why women drop out of a peripartum depression mHealth study, and how we can improve the app design.
methodParticipants who dropped out of the Mom2B study (n = 134) answered closed and open questions on their motives for dropping out of the study, suggestions for improvement, and preferred timeframe of the study. A mix of quantitative and qualitative strategies was used to analyze the responses.
resultsThe most common reasons for discontinuation were lack of time, problems with or loss of the pregnancy, the use of other pregnancy applications, surveys being too lengthy, the app draining too much battery, and participants incorrectly believing that their answers were irrelevant for the study. Participants suggested fewer survey moments, more reminders, and a need for more unique content compared to commercially available apps.
conclusionsResearcher who want to use mHealth designs in peripartum studies need to ensure that their study designs are as time-efficient as possible, remind participants about the study, manage expectations about the study and what is expected of participants throughout the study, design their apps to be attractive in a competitive market, and follow-up with participants who are excluded from the study due to pregnancy complications.
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Registered trials
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.