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Record W4415855059 · doi:10.1177/22799036251385275

Prevalence and associated factors for perceived stigma among caregivers of patients with mental illness in Ethiopia: A national based systematic review and meta-analysis

2025· article· en· W4415855059 on OpenAlexaboutno aff
A. de Wolde, Gezahegn Eshetu Mamed, Abubeker Alebachew Seid, Eshetu Chekole Tadesse, Aragaw Asfaw Hasen

Bibliographic record

VenueJournal of public health research · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsnot available
Fundersnot available
KeywordsStigma (botany)Mental illnessCINAHLMental healthSocial stigmaSocial distanceMEDLINE

Abstract

fetched live from OpenAlex

This study planned to assess the prevalence and associated factor of perceived stigma among caregiver of patient with mental illness in Ethiopia. The Design of this study is a systematic review and meta-analysis. We searched from database PubMed, Google Scholar, and CINAHL and studies available from inception to August 2024. The quality of eligible studies was assessed using Newcastle-Ottawa Scale (NOS). A DerSimonian-Laird random-effects meta-analysis was used to estimate the pooled effect size of the outcome measures with their 95% CI. Stata version 14.0 (StataCorp, College Station, Texas, USA) was used for statistical analysis. A total of five studies reported the prevalence of perceived stigma among caregivers of patients with mental illness. The pooled prevalence of perceived stigma was 65% (95% CI: 41%–88%), with high heterogeneity ( I ² = 99.6%, p < 0.001). Longer caregiving duration (2.08, 95% CI: 0.87–3.29), and poor social support (4.20, 95% CI: 2.30–6.11) were associated with perceived stigma. Perceived stigma among caregivers of patient with mental illness is high in Ethiopia. The prevalence of perceived stigma prevalence varies across regions. Addressing perceived stigma among caregivers of individuals with mental illness in Ethiopia should be a priority for mental health services and policy makers. PROSPERO registration number : CRD42024581201.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.195
GPT teacher head0.454
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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