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Record W4200041631 · doi:10.2196/28141

A Digital Health Innovation to Prevent Relapse and Support Recovery in Youth Receiving Specialized Services for First-Episode Psychosis: Protocol for a Pilot Pre-Post, Mixed Methods Study of Horyzons-Canada (Phase 2)

2021· article· en· W4200041631 on OpenAlexafffundvenueabout
Shalini Lal, John Gleeson, Simon D’Alfonso, Geraldine Etienne, Ridha Joober, Martín Lepage, Hajin Lee, Mario Álvarez‐Jiménez

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversité de MontréalMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health ResearchNational Health and Medical Research CouncilCanada Research ChairsMedical Research CouncilBrain and Behavior Research Foundation
KeywordsPsychosocialIntervention (counseling)Mental healthFocus groupMedicinePsychiatryAgency (philosophy)PsychologyFamily medicineGerontologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Psychotic disorders are among the most disabling of all mental disorders. The first-episode psychosis (FEP) often occurs during adolescence or young adulthood. Young people experiencing FEP often face multiple barriers in accessing a comprehensive range of psychosocial services, which have predominantly been delivered in person. New models of service delivery that are accessible, sustainable, and engaging are needed to support recovery in youth diagnosed with FEP. OBJECTIVE: In this paper, we describe a protocol to implement and evaluate the acceptability, safety, and potential efficacy of an online psychosocial therapeutic intervention designed to sustain recovery and prevent relapses in young adults diagnosed with FEP. This intervention was originally developed and tested in Australia and has been adapted for implementation and evaluation in Canada and is called Horyzons-Canada (HoryzonsCa). METHODS: This cohort study is implemented in a single-center and applies a pre-post mixed methods (qualitative-quantitative convergent) design. The study involves recruiting 20 participants from a specialized early intervention program for psychosis located in Montreal, Canada and providing them with access to the HoryzonsCa intervention for 8 weeks. Data collection includes interview-based psychometric measures, self-reports, focus groups, and interviews. RESULTS: This study received funding from the Brain and Behavior Research Foundation (United States), the Quebec Health Research Funding Agency (Canada), and the Canada Research Chairs Program. The study was approved by the Research Ethics Board of the Centre intégré universitaire de santé et de services sociaux de l'Ouest-de-l'Île-de-Montréal on April 11, 2018 (#IUSMD 17-54). Data were collected from August 16, 2018, to April 29, 2019, and a final sample of 20 individuals participated in the baseline and follow-up interviews, among which 9 participated in the focus groups. Data analysis and reporting are in process. The results of the study will be submitted for publication in 2021. CONCLUSIONS: This study will provide preliminary evidence on the acceptability, safety, and potential efficacy of using a digital health innovation adapted for the Canadian context to deliver specialized mental health services to youth diagnosed with FEP. TRIAL REGISTRATION: ISRCTN Registry ISRCTN43182105; https://www.isrctn.com/ISRCTN43182105. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/28141.

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)0.026
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.922
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.015
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0030.003
Science and technology studies0.0070.003
Scholarly communication0.0030.002
Open science0.0050.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0380.004

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 head0.263
GPT teacher head0.617
Teacher spread0.354 · 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 designNon-randomized trial
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

Citations7
Published2021
Admission routes4
Has abstractyes

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