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Record W1976870548 · doi:10.1111/sltb.12037

Assessing Motivations for Suicide Attempts: Development and Psychometric Properties of the Inventory of Motivations for Suicide Attempts

2013· article· en· W1976870548 on OpenAlexaff
Alexis M. May, E. David Klonsky

Bibliographic record

VenueSuicide and Life-Threatening Behavior · 2013
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntrapersonal communicationPsychologyInterpersonal communicationConvergent validitySuicide preventionClinical psychologyInterpersonal relationshipPoison controlPsychometricsSocial psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

This study describes the psychometric properties of the Inventory of Motivations for Suicide Attempts (IMSA). The IMSA was designed to comprehensively assess motivations for suicide emphasized by major theories of suicidality. The IMSA was administered to two samples of recent suicide attempters, undergraduates (n = 66) and outpatients (n = 53). The IMSA exhibited a reliable two-factor structure in which one factor represented Intrapersonal motivations related to ending emotional pain, and the second represented Interpersonal motivations related to communication or help-seeking. Convergent validity and divergent validity of IMSA scales were supported by expected patterns of correlations with another measure of suicide motivations. In addition, the IMSA scales displayed clinical utility, in which greater endorsement of intrapersonal motivations was associated with greater intent to die, whereas greater endorsement of interpersonal motivations was associated with less lethal intent and greater likelihood of rescue. Findings suggest the IMSA can be of use for both research and clinical purposes when a comprehensive assessment of suicide motivations is desired.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.157
GPT teacher head0.355
Teacher spread0.199 · 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.

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

Citations101
Published2013
Admission routes1
Has abstractyes

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