Evidence map›Paper›PMID 41057189›Full record

ArticleBMJ open2025

Quantifying cross-sectional and longitudinal associations in mental health symptoms within families: network models applied to UK cohort data.

Yushi Bai, Archie Rayner, Kathryn M Abel, Sam Cartwright-Hatton, Ming Wai Wan, Matthias Pierce

Abstract read
In one paragraph

Article in BMJ open, 2025. 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
–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.

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2 · The registry

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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. Article
4 · The record

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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

6 authors.

Yushi BaiCentre for Women's Mental Health, Faculty of Biology, Medicine and Health Sciences, University of Manchester, Manchester, UK yushi.bai@manchester.ac.uk.ORCID http://orcid.org/0000-0002-4894-8779
Archie RaynerImperial College London, London, UK.
Kathryn M AbelCentre for Women's Mental Health, Faculty of Biology, Medicine and Health Sciences, University of Manchester, Manchester, UK.
Sam Cartwright-HattonSchool of Psychology, University of Sussex, Brighton, UK.
Ming Wai WanDivision of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health Sciences, The University of Manchester, Manchester, UK.
Matthias PierceCentre for Women's Mental Health, Faculty of Biology, Medicine and Health Sciences, University of Manchester, Manchester, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectivesFamilies offer promising targets for mental health interventions. Existing evidence investigates parent-child dyads or partners; we use an innovative approach to look at triads of parents and their children. This gives us more detail on mental health dimensions and individuals central to mental health transmission in families.

designBoth cross-sectional and longitudinal network models

settingWe identified triads of children (under age 16), mothers and fathers from the UK Household Longitudinal Study, between 2009 and 2022. PARTICIPANTS AND

methodsCross-sectional networks captured independent associations between family members' mental health (n=8795 families). Longitudinal networks examined directional temporal associations among family members' emotional symptoms (n=3757 families). PRIMARY OUTCOME MEASURES: Children's and parents' mental health dimensions were assessed using the Strengths and Difficulties Questionnaire and the General Health Questionnaire, respectively.

resultsMothers' mental health, particularly emotional symptoms, was linked to children's mental health, while fathers' symptoms showed no independent association. In the longitudinal network, maternal feelings of being overwhelmed were associated with children's future worry, affecting symptoms of nervousness and unhappiness, which then fed back into worsening maternal emotional symptoms.

conclusionsInvestigating family mental health using network models highlights mothers' central role. The longitudinal relationship between maternal feelings of being overwhelmed and children's anxiety, and the subsequent feedback into maternal anxiety, indicates a promising target for intervention.

Indexed as

FathersMental DisordersMental HealthMothersParentsAdolescentAdultChildChild, PreschoolCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleParent-Child RelationsSurveys and QuestionnairesChild & adolescent psychiatryFamilyMENTAL HEALTHPublic health

Identifiers

PMID41057189
PMCPMC12506059

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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.