Evidence map›Paper›PMID 34647898›Full record

ReviewJMIR mHealth and uHealth2021

Characteristics and Quality of Mobile Apps Containing Prenatal Genetic Testing Information: Systematic App Store Search and Assessment.

Ko-Lin Wu, Rebeca Alegria, Jazzlyn Gonzalez, Harrison Hu, Haocen Wang, Robin Page, Patricia Robbins-Furman, Ping Ma, Tung-Sung Tseng, Lei-Shih Chen

Abstract readReview
In one paragraph

Review in JMIR mHealth and uHealth, 2021. 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. Trial
  2. Review
  3. Article
  4. Article
  5. Review
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.

Ko-Lin WuGraduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States.ORCID 0000-0003-3739-0762
Rebeca AlegriaDepartment of Health and Kinesiology, Texas A&M University, College Station, TX, United States.ORCID 0000-0002-0956-3067
Jazzlyn GonzalezCollege of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, TX, United States.ORCID 0000-0002-7971-2363
Harrison HuCollege of Science, Texas A&M University, College Station, TX, United States.ORCID 0000-0003-2279-0210
Haocen WangDepartment of Health and Kinesiology, Texas A&M University, College Station, TX, United States.ORCID 0000-0001-5173-7051
Robin PageCollege of Nursing, Texas A&M University, College Station, TX, United States.ORCID 0000-0001-7223-412X
Patricia Robbins-FurmanDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States.ORCID 0000-0001-6100-2358
Ping MaDepartment of Health Promotion & Community Health Sciences, School of Public Health, Texas A&M University, College Station, TX, United States.ORCID 0000-0002-0585-7885
Tung-Sung TsengBehavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, United States.ORCID 0000-0001-6266-9891
Lei-Shih ChenDepartment of Health and Kinesiology, Texas A&M University, College Station, TX, United States.ORCID 0000-0001-5320-6350

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrenatal genetic testing is an essential part of routine prenatal care. Yet, obstetricians often lack the time to provide comprehensive prenatal genetic testing education to their patients. Pregnant women lack prenatal genetic testing knowledge, which may hinder informed decision-making during their pregnancies. Due to the rapid growth of technology, mobile apps are a potentially valuable educational tool through which pregnant women can learn about prenatal genetic testing and improve the quality of their communication with obstetricians. The characteristics, quality, and number of available apps containing prenatal genetic testing information are, however, unknown.

objectiveThis study aims to conduct a firstreview to identify, evaluate, and summarize currently available mobile apps that contain prenatal genetic testing information using a systematic approach.

methodsWe searched both the Apple App Store and Google Play for mobile apps containing prenatal genetic testing information. The quality of apps was assessed based on the criteria adopted from two commonly used and validated mobile app scoring systems, including the Mobile Application Rating Scale (MARS) and the APPLICATIONS evaluation criteria.

resultsA total of 64 mobile apps were identified. Of these, only 2 apps were developed for a specific prenatal genetic test. All others were either pregnancy-related (61/64, 95%) or genetics-related (1/64, 2%) apps that provided prenatal genetic testing information. The majority of the apps (49/64, 77%) were developed by commercial companies. The mean quality assessment score of the included apps was 13.5 (SD 2.9), which was equal to the average of possible theoretical score. Overall, the main weaknesses of mobile apps in this review included the limited number of prenatal genetic tests mentioned; incomprehensiveness of testing information; unreliable and missing information sources; absence of developmental testing with users (not evidence based); high level of readability; and the lack of visual information, customization, and a text search field.

conclusionsOur findings suggest that the quality of mobile apps with prenatal genetic testing information must be improved and that pregnant women should be cautious when using these apps for prenatal genetic testing information. Obstetricians should carefully examine mobile apps before referring any of them to their patients for use as an educational tool. Both improving the quality of existing mobile apps, and developing new, evidence-based, high-quality mobile apps targeting all prenatal genetic tests should be the focus of mobile app developers going forward.

Indexed as

Mobile ApplicationsText MessagingDelivery of Health CareFemaleGenetic TestingHumansPregnancyPregnant Peopleevaluationmobile applicationspregnancyprenatal genetic testingreview

Identifiers

PMID34647898
PMCPMC8554671

What OpenQuestion holds

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LicenceCC BY
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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.