ArticlemHealth2025
Development, validation, adherence, self-efficiency and satisfaction of a mobile health application for women with primary dysmenorrhea.
Article in mHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Self-management strategies for menstrual cycle symptoms: a systematic review.BMC women's health · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Primary dysmenorrhea (PD) is a prevalent gynecological condition characterized by menstrual pain. Women with PD often experience functional disability, absenteeism, and presenteeism, leading to increased healthcare costs. Health education is a proven strategy for improving self-management behaviors, and mobile health (mHealth) technologies, such as smartphone applications (apps), offer a promising avenue for delivering educational interventions. However, existing menstrual cycle apps have limited functionality and do not focus on PD self-management. We aimed to develop and validate a health education app-ColicApp-to improve knowledge and self-management of PD and to assess adherence, self-efficacy, and satisfaction among users. Methods: This was a descriptive technology development study. The content of the app was designed based on a literature review, incorporating scientific evidence on PD self-management. A prototype was developed following structured guidelines and included sections on the definition, prevalence, pathophysiology, symptoms, self-care strategies, and pain management techniques. The content was reviewed for accessibility and comprehension by a group of women from the community. The app was validated by women's health physiotherapists and women with PD using the content validity index (CVI) and percentage of absolute agreement. Adherence, self-efficacy, and satisfaction were assessed over three menstrual cycles using standardized instruments. Data were collected online using Google Forms. Results: The content of the app was evaluated by 22 women's health physiotherapists and 17 women with PD. The experts rated the app with a CVI greater than 0.76, while women with PD rated it greater than 0.80, with overall agreement levels of 96% and 94%, respectively. Participants provided suggestions for improvement, including the addition of explanatory videos for women with low literacy. Among 99 women who used the app, adherence rates were 76.8% in the first cycle, 68.7% in the second cycle, and 55.6% in the third cycle. A significant correlation was observed between adherence in the third cycle and pain reduction. Self-efficacy scores were high, indicating improved confidence in managing PD symptoms. Most participants reported high satisfaction with the app's design, functionality and educational content of the app. Conclusions: ColicApp was successfully developed and validated as an educational tool for PD self-management. High levels of adherence, self-efficacy, and satisfaction ratings suggest strong clinical applicability. This mHealth intervention has the potential to enhance self-care practices among women with PD and could serve as a valuable resource for both individuals and healthcare professionals. Future studies should evaluate the performance of the app when integrated into operating system platforms.
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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 Socratic graph.