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Record W4414845259 · doi:10.30834/kjp.38.1.2025.502

Mental Health Awareness Campaigns: Experiment with Exhibition and Public Participatory Training

2025· article· en· W4414845259 on OpenAlexaff
Saleem TK, Shahul Ameen, Dayal Narayan

Bibliographic record

VenueKerala Journal of Psychiatry · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMental healthContext (archaeology)ExhibitionPerceptionCitizen journalismPublic healthMental illnessCredibility

Abstract

fetched live from OpenAlex

A multifaceted approach to mental health education is needed to mould the public's perception of mental disorders. The campaign aimed at the accurate portrayal of mental health issues, particularly in the context of media representation and public understanding. The demonstration of modified Electroconvulsive Therapy (ECT) on a human replica sparked significant interest among visitors, facilitating discussions about shock therapy and its misconceptions. A dedicated module on substance use served as a platform to discuss the harmful effects of drugs and alcohol, mainly targeting adolescents and young adults. The evolution of mental health care over the past 250 years was presented through interactive biographical slides, fostering a deeper understanding of the historical context and the importance of positive mental health practices. The need to refrain from harmful stereotypes and misrepresentations in media, which can shape societal views, often portraying individuals with mental disorders as violent or unpredictable, was highlighted. The creation of a makeshift mini-theater for public awareness video shows and individual sessions conducted by trained volunteers was an effective strategy for engaging the community in mental health discussions. These initiatives aimed to educate stakeholders on the importance of accurate mental health representations and the detrimental effects of stigma. There is a necessity for comprehensive mental health education that addresses misconceptions, promotes positive behaviors, and encourages open dialogue within the community.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.449
GPT teacher head0.598
Teacher spread0.149 · 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 designQualitative
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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