Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jul 6, 2021
Date Accepted: Dec 16, 2021

The final, peer-reviewed published version of this preprint can be found here:

Review of Mobile Apps for Women With Anxiety in Pregnancy: Maternity Care Professionals’ Guide to Locating and Assessing Anxiety Apps

Evans K, Donelan J, Rennick-Egglestone S, Cox S, Kuipers Y

Review of Mobile Apps for Women With Anxiety in Pregnancy: Maternity Care Professionals’ Guide to Locating and Assessing Anxiety Apps

J Med Internet Res 2022;24(3):e31831

DOI: 10.2196/31831

PMID: 35319482

PMCID: 8987965

A review of Mobile ‘Apps’ for women with anxiety in pregnancy: Maternity care professionals guide to locating and assessing Anxiety Apps.

  • Kerry Evans; 
  • Jasper Donelan; 
  • Stefan Rennick-Egglestone; 
  • Serena Cox; 
  • Yvonne Kuipers

ABSTRACT

Background:

Mental health and pregnancy Apps are widely available and have the potential to improve health outcomes and enhance women’s experience of pregnancy. Women frequently access digital information throughout their pregnancy. Healthcare providers and women have little information to guide them to potentially helpful or effective Apps.

Objective:

To develop a methodology to systematically search and evaluate commercially available Apps in order to assist maternity care professionals to identify resources to recommend to pregnant women with symptoms of anxiety.

Methods:

A stepwise systematic approach to identify, select, describe and assess the most popular and user rated Apps available in the UK from January – March 2021. This included developing a script-based search strategy and search process, developing evaluation criteria and conducting a narrative evaluation and description of the selected Apps.

Results:

Useful search terms were identified which included non-clinical, aspirational and problem-based phrases. There were 39 Apps selected for inclusion in the review. No Apps were located which specifically targeted women with anxiety in pregnancy. Of the 39 Apps included in the review, 33 focused solely on mind-body techniques to promote relaxation, stress reduction and psychological wellbeing. Only eight of the 39 Apps included in the review reported that healthcare professionals had contributed to the App development and only one provided empirical evidence on the effectiveness and acceptability of the App. The top 12 Apps were evaluated by two independent reviewers using the developed criteria and scores. The was a small negative correlation between the reviewers scores and App user rating scores, with higher user rating scores associated with lower reviewer scores.

Conclusions:

App developers, publishers and maternity care professionals should seek advice from women with lived experience of pregnancy anxiety symptoms to assist in locating, promoting and optimising the visibility of Apps for pregnant women. There is a lack of resources which provide coping strategies based on current evidence for the treatment of anxiety in pregnancy. Maternity Care Providers are hindered in their ability to locate and recommend acceptable and trustworthy Apps due to the lack of information on the evidence-base, development and testing of Apps. Maternity care professionals and women need access to libraries of trusted Apps which have been evaluated against relevant and established criteria.


 Citation

Please cite as:

Evans K, Donelan J, Rennick-Egglestone S, Cox S, Kuipers Y

Review of Mobile Apps for Women With Anxiety in Pregnancy: Maternity Care Professionals’ Guide to Locating and Assessing Anxiety Apps

J Med Internet Res 2022;24(3):e31831

DOI: 10.2196/31831

PMID: 35319482

PMCID: 8987965

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.