Evidence map›Paper›PMID 42712482›Full record

Articlenpj women's health2026

Decoding menstrual health across the lifespan: a scoping review of digital health tools in research.

Sarah C Johnson, Johanna O'Day, Emily Kraus, Scott L Delp, Jennifer L Hicks

Abstract read
In one paragraph

Article in npj women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Sarah C Johnson *Wu Tsai Human Performance Alliance, Stanford University, Stanford, CA USA.
Johanna O'Day *Wu Tsai Human Performance Alliance, Stanford University, Stanford, CA USA.
Emily KrausWu Tsai Human Performance Alliance, Stanford University, Stanford, CA USA.
Scott L DelpWu Tsai Human Performance Alliance, Stanford University, Stanford, CA USA.
Jennifer L HicksWu Tsai Human Performance Alliance, Stanford University, Stanford, CA USA.

Funding

TR&D Project 3: OpenSim for PredictionP41EB027060 · NIBIB · STANFORD UNIVERSITY · PI SCOTT L DELP · 2020 to 2026
$9.7M
NIBIB NIH HHS P41 EB027060
6 · The paper itself

Abstract

Digital health tools provide longitudinal physiological and behavioural data that can address knowledge gaps in women's health. This is particularly relevant for understanding hormone-driven physiological changes and symptoms, which impact health and performance across the lifespan. We conducted a scoping review of research using wearables or smartphone applications to identify insights about physiology, health behaviours, and symptoms throughout the menstrual cycle and menopausal transition. We identified 40 original articles. We summarise findings that reproduce lab-based results, giving confidence in the use of digital health tools for studying menstrual health, along with new insights gained. Given the importance of validation against gold standards, and the lack of a prior synthesis of wearable accuracy for women's health applications, we next report the accuracy of wearables that measure biometrics relevant to menstrual health. Finally, we discuss future research needs, including understanding physiological changes during perimenopause, and the role of health behaviours in symptom management.

Indexed as

Computational biology and bioinformaticsEngineeringHealth carePhysiology

Identifiers

PMID42712482
PMCPMC13549953

What OpenQuestion holds

Textmetadata
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.