Evidence map›Paper›PMID 37996896›Full record

ArticleTrials2023

Effectiveness and cost-effectiveness of an electronic mindfulness-based intervention to improve maternal mental health in the peripartum: study protocol for a randomised controlled trial.

Grace Branjerdporn, Kerri Gillespie, Elizabeth Martin, Vivianne Kissane, Alex De Young, Tatjana Ewais, Kathleen Goldsmith, Susan Wilson, Sam Adhikary, Greg McGahan and 2 more

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

12 authors at 4 institutions in 1 country.

Grace BranjerdpornMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia. Grace.branjerdporn@mater.org.au.ORCID http://orcid.org/0000-0001-6578-2718
Kerri GillespieMater Research Institute - University of Queensland, Whitty Building (Ground Floor), Annerley Road, Mater Hill, South Brisbane, QLD, 4101, Australia.
Elizabeth MartinMater Research Institute - University of Queensland, Whitty Building (Ground Floor), Annerley Road, Mater Hill, South Brisbane, QLD, 4101, Australia.
Vivianne KissanePeach Tree Perinatal Wellness Inc, 293 Ellison Rd, Geebung, QLD, 4034, Australia.
Alex De YoungQueensland Centre for Perinatal and Infant Mental Health, Children's Health Queensland - Queensland Health, Nundah, QLD, 4012, Australia.
Tatjana EwaisMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia.
Kathleen GoldsmithMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia.
Susan WilsonChildren's Health Queensland, Queensland Health, 501 Stanley St, South Brisbane, QLD, 4101, Australia.
Sam AdhikaryMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia.
Greg McGahanMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia.
Constanze SchulzMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia.
Michael BeckmannMater Health, Annerley Road Campus, South Brisbane, QLD, 4101, Australia.
Mater Health Services · AUQueensland Health · AUThe University of Queensland · AUGriffith University · AU

Funding

Mater Foundation 2809
6 · The paper itself

Abstract

backgroundPerinatal women are highly vulnerable to developing mental health issues and particularly susceptible to a recurrence of psychiatric illness. Poor mental health during the perinatal period can have long-term impacts on the physical and psychiatric health of both mother and child. A potentially useful strategy to improve women's mental health is through a mobile application teaching mindfulness, an evidence-based technique helping individuals focus on the present moment.

methodsA mixed method, prospective randomised controlled trial. The study group comprise women aged 18 years and over, who are attending the public and private maternity clinics at Mater Mothers' Hospital. A sample of 360 prenatal women will be randomised into the intervention group (with the use of the mindfulness app) or usual care. Participants will remain in the study for 11 months and will be assessed at four timepoints for changes in postnatal depression, mother-infant bonding, and quality of life. A cost-effectiveness evaluation will also be conducted using quality-adjusted life year (QALY) calculations. A random selection of intervention participants will be invited to attend focus groups to give feedback on the mindfulness app. DISCUSSION: Previous studies have found mindfulness interventions can reduce stress, anxiety, depression, and sleep disturbances in a prenatal population. The risks of the intervention are low, but could be of significant benefit for women who are unable to attend face-to-face appointments due to geographical, financial, or time barriers; during endemic or pandemic scenarios; or due to health or mobility issues.

trial registrationThis study was approved by the Mater Misericordiae Human Research Ethics Committee (83,589). Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12622001581752 ( https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=385107&isReview=true ). Registered on 22 Dec. 2022.

Indexed as

Mental HealthMindfulnessAdolescentAdultAustraliaCost-Benefit AnalysisFemaleHumansInfant, NewbornPeripartum PeriodPregnancyProspective StudiesQuality of LifeRandomized Controlled Trials as TopicInterventionMaternal mental healthMaternityMindfulnessPeripartum

Identifiers

PMID37996896
PMCPMC10666349
OpenAlexW4388945457

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.