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Record W4281382690 · doi:10.15273/hpj.v2i1.11236

Clarifying the concept of mental health literacy: Protocol for a scoping review

2022· review· en· W4281382690 on OpenAlexaff
Emma C. Coughlan, Lindsay K. Heyland, Taylor G. Hill

Bibliographic record

VenueHealthy Populations Journal · 2022
Typereview
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsMount Saint Vincent UniversityDalhousie University
Fundersnot available
KeywordsMental healthMental health literacyConceptualizationGrey literatureCLARITYPsychological interventionHealth literacyPsychologyMedicinePublic relationsMental illnessMEDLINEPolitical sciencePsychiatryHealth careComputer science

Abstract

fetched live from OpenAlex

This scoping review will map the peer-reviewed and grey literature, to clarify the concept of mental health literacy (MHL). MHL is an emerging area of study within mental health promotion, as programming and policy efforts devoted to promoting mental health emerge. Enhancing MHL in the general population is a strategy for promoting mental health by reducing stigma and empowering individuals to recognize, interpret, and understand their mental health, and know when to seek help for themselves and others. Despite the positive outcomes associated with MHL, conceptualization varies in scope, purpose, process, and outcome; there is little consensus of what “counts” as MHL. A clearly defined conceptualization of MHL is needed to support research, programing, and policy in mental health promotion. Papers on the theoretical and conceptual principles underlying MHL and primary studies documenting MHL initiatives, and methods, will be included. A scoping literature search will be performed following the search protocol for scoping reviews by the Joanna Briggs Institute (JBI) to identify all relevant literature on MHL. Searches will be conducted in three scientific databases; there will be no time limit imposed, although all sources must be written in English. Identifying the conceptualizations of MHL in the literature that is guiding mental health interventions will provide conceptual clarity ultimately advancing knowledge of mental health literacy.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.609
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0120.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.630
GPT teacher head0.679
Teacher spread0.049 · 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.

Study designSystematic review
Domainnot available
GenreReview

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
Published2022
Admission routes1
Has abstractyes

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