Evidence map›Paper›PMID 42553151›Full record

ArticleGlobal mental health (Cambridge, England)2026

Between leaves and lives: Maternal mental health among tea garden workers in Bangladesh and its association with children's behavioural difficulties.

Murad Ansary, Afsana Sultana, Maria Ferdousi, Md Saifur Rahman, Monaemul Islam Sizear, Kamal Uddin Ahmed Chowdhury, M Tasdik Hasan

Abstract read
In one paragraph

Article in Global mental health (Cambridge, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Murad AnsaryClinical Psychology, University of Rajshahi, Rajshahi, Bangladesh.ORCID https://orcid.org/0009-0004-5642-6999
Afsana SultanaMicrobiology, Bangladesh University of Health Sciences, Dhaka, Bangladesh.ORCID https://orcid.org/0009-0009-8049-6862
Maria FerdousiClinical Psychology, University of Rajshahi, Rajshahi, Bangladesh.
Md Saifur RahmanClinical Psychology, University of Rajshahi, Rajshahi, Bangladesh.
Monaemul Islam SizearPublic Health Foundation Bangladesh, Dhaka, Bangladesh.
Kamal Uddin Ahmed ChowdhuryDepartment of Clinical Psychology, University of Dhaka, Dhaka, Bangladesh.
M Tasdik HasanMonash University, Melbourne, Australia.ORCID https://orcid.org/0000-0002-3256-093X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite growing recognition of the intergenerational effects of maternal mental health, evidence from tea garden communities remains limited. This study assessed the mental health status of working mothers in tea gardens of Moulvibazar, Bangladesh, examined its association with children's well-being, and explored contextual factors shaping maternal mental health. A convergent cross-sectional mixed-methods study was conducted. Using a purposive and stratified random sampling technique, the quantitative data were collected from 451 working mothers with at least one child aged 2-7 years. Mothers' psychological well-being was assessed using the Depression, Anxiety, Stress Scale-21 and World Health Organisation-Five scales, while children's behavioural and emotional well-being was measured using the Strengths and Difficulties Questionnaire (SDQ). The qualitative component included 11 key informant interviews and two focus group discussions (FGDs) from Moulvibazar, Bangladesh. Quantitative data were analysed using descriptive and inferential statistics, and qualitative data were thematically analysed. A substantial proportion of mothers reported high levels of psychological distress, with 32.4%, 29.9% and 31.7% experiencing moderate to extremely severe depression, anxiety and stress, respectively, while 33.9% had poor well-being. Age was significantly associated with stress (

Indexed as

child well-beingmaternal mental healthmixed-methodspsychological well-beingtea garden workers

Identifiers

PMID42553151
PMCPMC13433331

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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.