Evidence map›Paper›PMID 38323149›Full record

ArticlemHealth2024

Women's comfort with mobile applications for menstrual cycle self-monitoring following the overturning of

Gabrielle M Salvatore, Iris Bercovitz, Danielle Arigo

Abstract read
In one paragraph

Article in mHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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  5. 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

3 authors.

Gabrielle M SalvatoreDepartment of Psychology, Rowan University, Glassboro, NJ, USA.
Iris BercovitzDepartment of Psychology, Rowan University, Glassboro, NJ, USA.
Danielle ArigoDepartment of Psychology, Rowan University, Glassboro, NJ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The overturning of Methods: A total of 206 women aged 18-60 years who were identified as pre- or perimenopausal completed an anonymous, cross-sectional survey between August and November 2022. Results: Most respondents had experience using a MC app at the time of reporting; 53.4% (n=110) were current users, and an additional 48 participants had used MC tracking apps in the past. Over one-third of participants (38.3%; n=75) indicated that they had reconsidered using such an app because of current events; 30.3% (n=59) preferred methods of MC tracking that did not involve app-based technology, and 34.2% (n=67) reported that they are not willing to participate in research that involves daily tracking of the MC. Conclusions: Overall, the feasibility of menstruation-related research that includes mobile apps is fairly low, given women's current comfort with this technology compared to the Roe era, and there is a need to establish criteria and protections for use of mobile apps in women's health research.

Indexed as

electronic health (eHealth)healthcare policymenstrual cycle (MC)Mobile applications (mobile apps)mobile health (mHealth)

Identifiers

PMID38323149
PMCPMC10839505

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.