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Record W2032841824 · doi:10.1002/jcop.20406

Adolescent knowledge of schizophrenia and social distancing: a province‐wide survey

2010· article· en· W2032841824 on OpenAlexaffabout
Guy Faulkner, Hyacinth Irving, Angela Paglia‐Boak, Edward M. Adlaf

Bibliographic record

VenueJournal of Community Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
Fundersnot available
KeywordsSocial distanceDistancingSchizophrenia (object-oriented programming)PsychologyStigma (botany)Psychological interventionMental healthMental illnessSocial stigmaClinical psychologyPsychiatryDevelopmental psychologyCoronavirus disease 2019 (COVID-19)MedicineHuman immunodeficiency virus (HIV)Family medicineDisease

Abstract

fetched live from OpenAlex

Abstract Stigma is a significant barrier to the improvement of the lives of people with schizophrenia. Little is known about the emergence of stigmatizing attitudes developmentally. The purpose of this study was to provide a provincial assessment of adolescent knowledge about schizophrenia and to identify the relationship between adolescent knowledge and social distance toward people with schizophrenia. Data were derived from the 2005 cycle of the Ontario Student Drug Use and Health Survey. In total, 3,117, 7th‐ to 12th‐graders completed self‐administered questionnaires that included a measure of schizophrenia knowledge and social distancing. Results indicated that the majority of adolescents had some knowledge about schizophrenia and low social distancing toward people with schizophrenia. Greater knowledge, increasing age, being female, and lower parental education were associated with less distancing attitudes. Educational campaigns to reduce stigma may still be warranted as one component of broader multilevel interventions to overcome mental illness stigma. © 2010 Wiley Periodicals, Inc.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.394
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.090
GPT teacher head0.430
Teacher spread0.340 · 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 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

Citations26
Published2010
Admission routes2
Has abstractyes

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