Evidence map›Paper›PMID 40437458›Full record

ArticleBMC women's health2025

An evaluation of menstrual health apps' functionality, inclusiveness, and health education information.

Emma Bucher, Callie Sharkey, Abby Henderson, Briette Basaran, Sarah Meyer, Chen X Chen

Abstract read
In one paragraph

Article in BMC women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

6 authors.

Emma BucherIndiana University School of Nursing, Indianapolis, IN, USA.
Callie SharkeyIndiana University School of Nursing, Indianapolis, IN, USA.
Abby HendersonIndiana University School of Nursing, Indianapolis, IN, USA.
Briette BasaranIndiana University School of Nursing, Indianapolis, IN, USA.
Sarah MeyerIndiana University School of Nursing, Indianapolis, IN, USA.
Chen X ChenUniversity of Arizona College of Nursing, Office 439, 1305 N Martin Ave, Tucson, AZ, 85721, USA. cxchen@arizona.edu.

Funding

Vaginal Microbiome, Inflammatory Mediators, Metabolome, and Dysmenorrhea Symptom-based PhenotypesR01HD110994 · NICHD · UNIVERSITY OF ARIZONA · PI Chen X Chen · 2023 to 2026
$2.5M
NIH HHS R01HD110994
6 · The paper itself

Abstract

backgroundMenstrual health apps have become increasingly popular, providing users with a tool to monitor and learn about menstrual cycles, symptoms, and management. While previous research examined different aspects of menstrual health apps (e.g., fertility tracking), few examined menstrual health apps comprehensively to examine the menstrual health apps' functionality, inclusiveness, and health education information. The purpose of this study was to evaluate menstrual health apps' functionality, inclusiveness, and health education information.

methodsIn this descriptive study, two reviewers independently searched, screened, and evaluated each app using a standardized tool. Three terms (i.e., "period pain," "period app," and "menstrual cramp") were used to search the Apple App Store. Apps were also cross-searched on the Google Play Store. We screened 60 apps. After excluding duplicates and apps that did not meet the inclusion criteria, 14 apps were evaluated on their functionality (user experience, internet and language accessibility, privacy, cycle-prediction, and symptom-tracking ability), inclusiveness (cycle lengths and regularities, fertility goals, and gender expressions and sexualities), and menstrual health education information (credibility and comprehensiveness, presence of additional health information, and information on when to seek care). We used a modified version of the Mobile App Rating Scale to score each app.

resultsFor functionality, half of the apps had third-party advertisements. Most (71.4%) did not require cellular connection to utilize menstrual symptom-tracking, and 71.4% shared user data with third parties. All had cycle-prediction and symptom-tracking functions. The mean number of relevant symptoms tracked was 17.5 (SD = 5.44). None of the apps used or cited validated symptom measurement tools. For inclusiveness, all apps could be tailored to cycle lengths other than 28 days, 85.7% had ovulation prediction functions, 50% had neutral or no pronouns, and 92.9% allowed users to input at least one contraceptive type. For health education information, 42.9% cited medical literature.

conclusionThis study suggests a lack of professional involvement and gender inclusivity in menstrual health app development. Healthcare professionals should educate themselves on apps' functionality, inclusiveness, and health education information before recommending apps. Additional research is needed to understand diverse users' perspectives on menstrual health apps.

Indexed as

Health EducationMenstrual CycleMenstruationMobile ApplicationsFemaleHumansDysmenorrheaMenstrual cycleMenstrual periodMenstrual symptomsMenstrual trackingMobile applications

Identifiers

PMID40437458
PMCPMC12117836

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.