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Record W3217785166 · doi:10.1136/bmjopen-2020-045726

Interventions to reduce stigma towards mental disorders in young people: protocol for a systematic review and meta-analysis

2021· review· en· W3217785166 on OpenAlexaff
Daniel Núñez, Pablo Martínez, Francesca Borghero, Susana Campos, Vania Martínez

Bibliographic record

VenueBMJ Open · 2021
Typereview
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversité de Sherbrooke
FundersAgencia Nacional de Investigación y DesarrolloUniversidad de Talca
KeywordsMedicineMeta-analysisPsychological interventionStigma (botany)Mental healthProtocol (science)PsychiatrySystematic reviewAlternative medicineMEDLINEPathology

Abstract

fetched live from OpenAlex

Introduction The stigma towards mental disorders can limit the use and effectiveness of available mental health interventions for young people. We aim to systematically review effectiveness of interventions to reduce stigma towards mental disorders in young people, as evidence has not been recently and systematically synthesised on this topic. Methods and analysis We will conduct a systematic review and meta-analysis of randomised or controlled clinical trials of interventions to reduce stigma towards mental disorders in people aged 10–24 years. Studies involving a comparison group, post intervention and/or follow-up assessments of knowledge, attitudes and/or behaviours towards mental disorders (including help-seeking behaviours), will be included. The Cochrane Central Register of Controlled Trials (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, PubMed and PsycINFO databases will be searched, without time limits, for eligible studies in English or Spanish, and with results available. Databases will be searched from July 2020 to April 2021. The study selection process, the data extraction and the critical evaluation—with the Cochrane risk-of-bias tool—of included studies will be performed independently and in duplicate by teams of reviewers, with the assistance of a third party, until reaching a high degree of agreement. In the presence of substantial heterogeneity (I 2 >75%), a narrative synthesis of the study results will be used. If feasible, we will also conduct a quality effects model for the statistical synthesis of results. If sufficient data are available, subgroup analyses will be performed to assess potential sources of heterogeneity. Doi plots and the Luis Furuya-Kanamori index will be used to assess publication bias. The Grades of Recommendation, Assessment, Development and Evaluation approach will be used to assess the confidence in the evidence reviewed. Ethics and dissemination Results are expected to be published in a peer-reviewed journal in the field of adolescent and/or youth mental health. PROSPERO registration number CRD42020210901.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.088
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.089
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0880.115
Meta-epidemiology (narrow)0.0090.007
Meta-epidemiology (broad)0.0250.037
Bibliometrics0.0120.012
Science and technology studies0.0030.004
Scholarly communication0.0090.008
Open science0.0060.006
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0890.010

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 head0.423
GPT teacher head0.632
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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

Citations2
Published2021
Admission routes1
Has abstractyes

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