Evidence map›Paper›PMID 26510886›Full record

ArticleJMIR mHealth and uHealth2015

Views of Women and Health Professionals on mHealth Lifestyle Interventions in Pregnancy: A Qualitative Investigation.

Jane C Willcox, Paige van der Pligt, Kylie Ball, Shelley A Wilkinson, Martha Lappas, Elizabeth A McCarthy, Karen J Campbell

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 4 pooled it
15.2field-weighted citation impact, top 1% 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

52 citing papers in PubMed, 4 syntheses or guidelines pooled it, 110 citations in OpenAlex.

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  10. Person-Generated Health Data in Women's Health: Scoping Review.Journal of medical Internet research · 2024
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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

7 authors at 3 institutions in 1 country.

Jane C WillcoxCentre for Nutrition and Physical Activity Research, School of Nutrition and Exercise Sciences, Deakin University, Burwood, Australia. jwillcox@deakin.edu.au.ORCID http://orcid.org/0000-0002-6306-5333
Deakin University · AUThe University of Melbourne · AUThe University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvidence suggests that women are failing to meet guidelines for nutrition, physical activity, and weight gain during pregnancy. Interventions to promote a healthy lifestyle in pregnancy demonstrate mixed results and many are time and resource intensive. mHealth-delivered interventions offer an opportunity to provide trusted source information in a timely and cost-effective manner. Studies regarding women's and health professionals' views of mHealth in antenatal care are limited.

objectiveThis study aimed to explore women's and health professionals' views regarding mHealth information sources and interventions to assist women to eat well, be physically active, and gain healthy amounts of weight in pregnancy.

methodsA descriptive qualitative research approach employed focus groups and in-depth interviews with 15 pregnant or postpartum women and 12 in-depth interviews with health professionals including two from each category: obstetricians, general practitioners, midwives, dietitians, physiotherapists, and community pharmacists. All interviews were transcribed verbatim and thematically analyzed.

resultsWomen uniformly embraced the concept of mHealth information sources and interventions in antenatal care and saw them as central to information acquisition and ideally incorporated into future antenatal care processes. Health professionals exhibited varied views perceiving mHealth as an inevitable, often parallel, service rather than one integrated into the care model. Four key themes emerged: engagement, risk perception, responsibility, and functionality. Women saw their ability to access mHealth elements as a way to self-manage or control information acquisition that was unavailable in traditional care models and information sources. The emergence of technology was perceived by some health professionals to have shifted control of information from trusted sources, such as health professionals and health organizations, to nontrusted sources. Some health professionals were concerned about the medicolegal risks of mHealth (incorrect or harmful information and privacy concerns), while others acknowledged that mHealth was feasible if inherent risks were addressed. Across both groups, there was uncertainty as to who should be responsible for ensuring high-quality mHealth. The absence of a key pregnancy or women's advocacy group, lack of health funds for technologies, and the perceived inability of maternity hospitals to embrace technology were seen to be key barriers to provision. Women consistently identified the functionality of mHealth as adding value to antenatal care models. For some health professionals, lack of familiarity with and fear of mHealth limited their engagement with and comprehension of the capacity of new technologies to support antenatal care.

conclusionsWomen exhibited positive views regarding mHealth for the promotion of a healthy lifestyle in antenatal care. Conversely, health professionals expressed a much wider variation in attitudes and were more able to identify potential risks and barriers to development and implementation. This study contributes to the understanding of the opportunities and challenges in developing mHealth lifestyle interventions in antenatal care.

Indexed as

attitudemHealthpregnancyqualitative research

Identifiers

PMID26510886
PMCPMC4704935
OpenAlexW1836486152

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.