Evidence map›Paper›PMID 32546131›Full record

ArticleBMC pregnancy and childbirth2020

Supporting perinatal anxiety in the digital age; a qualitative exploration of stressors and support strategies.

Virginia Harrison, Donna Moore, Lisa Lazard

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07223736 (Postpartum Education Via Artificial Intelligence for Recovery and Loneliness), which is not on this map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 4% 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.

NCT07223736 narecruitingnot on this mapstarted 2026, after this paper: background citation

Postpartum Education Via Artificial Intelligence for Recovery and Loneliness (PEARL): A Randomized Controlled Trial

TypeinterventionalSponsorUniversity of California, San DiegoRan2026 to 2026Enrolled130ConditionsPelvic Floor Disorder, Loneliness, Postpartum, Mental HealthArmsGenerative artificial intelligence (genAI) postpartum chatbot, Standard of Care (SOC)
3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

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  20. Trends of Perinatal Stress, Anxiety, and Depression and Their Prediction on Postpartum Depression.International journal of environmental research and public health · 2021
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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

3 authors at 1 institution in 1 country.

Virginia HarrisonSchool of Psychology and Counselling, Faculty of Arts and Social Sciences, Open University, Milton Keynes, MK7 6AA, UK. gini.harrison@open.ac.uk.ORCID http://orcid.org/0000-0001-7668-4574
Donna MooreSchool of Psychology and Counselling, Faculty of Arts and Social Sciences, Open University, Milton Keynes, MK7 6AA, UK.
Lisa LazardSchool of Psychology and Counselling, Faculty of Arts and Social Sciences, Open University, Milton Keynes, MK7 6AA, UK.
The Open University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe period surrounding childbirth is one of profound change, which can often be experienced as stressful and overwhelming. Indeed, around 20% of women may experience significant levels of anxiety in the perinatal period. However, most women experiencing perinatal anxiety (PNA) go unrecognised and untreated. The Internet offers a potentially scalable solution to improve access to support, however a dearth of research in this area means that work is needed to better understand women's experience of PNA, so that potential targets for intervention can be identified and possible barriers to support overcome. This study aimed to qualitatively explore women's experience of anxiety triggers and support in the perinatal period; and gain insight into what online support is acceptable for women with PNA.

methodsWomen who were either pregnant or within one-year postpartum were invited to participate in focus groups across the UK. Focus groups were used to allow a diversity of perspectives to be heard, while simultaneously promoting the identification and prioritisation of important support needs and solutions. Interviews were transcribed and thematically analysed.

resultsFive key themes emerged in relation to women's experience with PNA: holding unrealistic expectations of birth and motherhood; stigma; the importance of peer support; uncertainty and poor maternal confidence; and a lack of mental health support and knowledge. Perinatal women felt under-supported and poorly prepared for motherhood. A mismatch between their expectations and the reality of their experience, alongside a pressure to be the 'perfect mum' was the primary source of their anxiety. Furthermore, stigma associated with PNA may have exacerbated these issues and led to help-seeking avoidance. Overall, women felt these issues could be addressed via online support, through the delivery of more realistic information, providing psychoeducation about PNA symptoms and management, and the inclusion of authentic peer experiences. Thus, delivering evidence-based information and interventions online may provide a solution that is acceptable to this cohort.

conclusionsThis work provides unique insight into potential sources of anxiety for women in the perinatal period, while also offering potential internet-based support solutions that are likely to be acceptable and helpful for women with PNA.

Indexed as

Internet-Based InterventionAdultAnxietyFemaleFocus GroupsHumansMental HealthMiddle AgedParturitionPerinatal CarePostpartum PeriodPregnancyPregnancy ComplicationsQualitative ResearchanxietyFemaleMood disorderPerinatalpostpartum

Identifiers

PMID32546131
PMCPMC7298791
OpenAlexW3034599076

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.