Evidence map›Paper›PMID 38106802›Full record

ArticleCureus2023

Factors Used by Mobile Applications to Predict Female Fertility Status and Their Reported Effectiveness: A Scoping Review.

Elaine E Saugar, Sabine Katsoulos, Hyun-Su Kim, Nazanin Fakharzadeh, Jacob Schaffer, Maubeen Ahmad, Caitlin Zeher, Meghan Benedict, Sarina Gupta, Gina Foster-Moumoutjis

Open access · diamondAbstract readScoping Review
In one paragraph

Article in Cureus, 2023. 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
0.6field-weighted citation impact, top 29% of its field
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, 2 citations in OpenAlex.

  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

10 authors at 1 institution in 1 country.

Elaine E SaugarDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, USA.
Sabine KatsoulosDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, USA.
Hyun-Su KimDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Clearwater, USA.
Nazanin FakharzadehDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Clearwater, USA.
Jacob SchafferDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Clearwater, USA.
Maubeen AhmadDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Clearwater, USA.
Caitlin ZeherDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, USA.
Meghan BenedictDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, USA.
Sarina GuptaDr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, USA.
Gina Foster-MoumoutjisDepartment of Family Medicine, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Davie, USA.
Nova Southeastern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Family planning, whether for pregnancy prevention or conception, is of pivotal importance to women of reproductive age. As hormonally driven methods, such as oral contraceptive pills, are widely used but have numerous side effects, women often seek alternative non-hormonal, non-invasive options, including fertility-tracking mobile applications (apps). However, the effectiveness of these apps as a method of contraception and conception planning has not been extensively vetted. The goal of this scoping review is to identify the various factors used by apps marketed as a method of contraception and/or family planning to predict a woman's fertility status, as well as their documented effectiveness. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines, a literature search was performed in CINAHL, MEDLINE, and Alt HealthWatch databases for articles published between October 1, 2017, and October 4, 2022. Quality assessment of eligible full-text articles was conducted using the Joanna Briggs Institute critical appraisal tools. A total of 629 articles were screened. Overall, 596 articles were excluded and the remaining 33 articles underwent full-text review. Seven articles were included in the final analysis, yielding data on the following five apps: Natural Cycles, Ava Fertility, Clearblue Connected, Ovia Fertility, and Dynamic Optimal Timing (DOT). Data supporting the effectiveness of these apps is limited. All apps provided predictions on fertility status throughout a woman's menstrual cycle using proprietary algorithms, biometric data, and self-reported menstrual cycle data. Further research, particularly independent research following a randomized controlled design, on the efficacy of these apps is needed to produce more robust results.

Indexed as

conceptiondigital health self-trackingfamily planningfemale contraceptionfemale sexual and reproductive healthfertilityfertility awareness-based methodfertility tracking appmobile applicationovulation

Identifiers

PMID38106802
PMCPMC10723623
OpenAlexW4388694261

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.