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Record W4389001918 · doi:10.31234/osf.io/ub27f

Youth Self-Harm and the Role of Reasons for Living and Hope: A Secondary Analysis from a Randomized Controlled Trial

2023· preprint· en· W4389001918 on OpenAlexafffund
Sarina Rain, Marissa Williams, Rachel Mitchell, Rabia Zaheer, Craig J. Bryan, Ayal Schaffer, Vera Yu Men, Neal Westreich, Janet Ellis, Benjamin I. Goldstein, Amy Cheung, Steven Selchen, Mark Sinyor

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental HealthSunnybrook Health Science CentreHealth Sciences CentreQueen's University
FundersUniversity of Toronto
KeywordsRandomized controlled trialHarmPsychologyLogistic regressionMedicineSuicide preventionClinical psychologyPoison controlPsychiatryEnvironmental healthInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

Self-harm (SH) is one of the strongest predictors of eventual death by suicide. This study examines the potential protective role of reasons for living (RFL) and hope in youth with a history of self-harm using data from a randomized control trial (RCT) of brief cognitive behavioural therapy (BCBT). A single-blind, pilot RCT examined the efficacy of BCBT for suicide prevention versus an attentional control in youth aged 15-25 admitted to hospital following self-harm. Subjects’ reasons for living and hope were measured weekly by the Reasons for Living Scale (RFL) and Adult Hope Scale (AHS), respectively, for 10 weeks of acute treatment. Logistic regression was performed to evaluate whether baseline RFL and AHS scores predicted repeat self-harm. Mann-Whitney U tests were used to compare median RFL and AHS scores. Our study did not find associations between reasons for living or hope and repeat self-harm in youth. Treatment with BCBT was also not associated with improved scores on either measure.

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)0.011
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.025
GPT teacher head0.302
Teacher spread0.277 · 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 designRandomized trial
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
Published2023
Admission routes2
Has abstractyes

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