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Record W4226017580 · doi:10.2196/36758

Insights About Cannabis and Psychosis Using Video Games for Young People With a First Episode of Psychosis, Particularly Those From Black Racialized Communities: Protocol for a Mixed Methods Study

2022· article· en· W4226017580 on OpenAlexafffundvenue
Suzanne Archie, Lena Palaniyappan, Andrew T Olagunju, Natasha Johnson, Nicole Kozloff, Elham Sadeh, Andrea Bardell, Alexandra Baines, Kelly K. Anderson, Oyedeji Ayonrinde, Manuela Ferrari

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsQueen's UniversityMcGill UniversityUniversity of OttawaUniversity of British ColumbiaRoyal Ottawa Mental Health CentreOttawa HospitalWestern UniversityUniversity of TorontoMcMaster UniversityRobarts Clinical TrialsChamplain Regional CollegeCentre for Addiction and Mental HealthLawson Health Research Institute
FundersCanadian Institutes of Health Research
KeywordsCannabisPsychosisPsychologyPsychiatryQualitative researchClinical psychologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Cannabis use disorder among young people with a first episode of psychosis contributes to relapse, hospitalization, and impaired functioning. However, few studies have examined what young people with early phase psychosis, particularly those from Black racialized communities, understand or appreciate about this relationship, even though they may be at risk. There are no formally tested knowledge translation strategies that disseminate these research findings for young people with emerging psychosis from Black racialized communities. OBJECTIVE: This study aims to conceptualize what young people with early phase psychosis/cannabis use disorder understand about the relationship between cannabis and psychosis, focusing on people from racialized backgrounds. This study also aims to assess whether the knowledge translation product, the "Back to Reality Series," increases awareness of the impact of cannabis use on psychosis from the perspectives of young people with emerging psychosis and cannabis use disorder from Black African and Caribbean communities. METHODS: Qualitative analysis will reveal themes from qualitative interviews about cannabis and psychosis from the perspectives of young people with emerging psychosis and cannabis use disorder from Black African and Caribbean communities. Perceptions before and after exposure to the Back to Reality Series will be qualitatively analyzed. A control game will be used for comparison, and scores on a quiz after playing the Back to Reality Series will be quantitatively analyzed to establish whether the Back to Reality Series raises awareness of the effects of cannabis on psychosis. An advisory council involving young people from Black communities, family members, and clinicians will bring community perspectives to this research. RESULTS: We began recruiting participants for this study in September 2021. We will complete data collection on demographic and clinical factors, qualitative interviews, and quantitative assessments of the Back to Reality Series. CONCLUSIONS: The voices of young people from racialized backgrounds will generate preliminary data to inform early psychosis programs, addressing cannabis use in this population. The findings may advance the use of a new knowledge translation product that deals with gaps in knowledge about cannabis use for people experiencing early phase psychosis, particularly those from racialized communities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36758.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.054
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.060
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.046
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0040.003
Science and technology studies0.0070.003
Scholarly communication0.0050.004
Open science0.0050.005
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0600.011

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 head0.192
GPT teacher head0.555
Teacher spread0.363 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2022
Admission routes3
Has abstractyes

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