Instrumentos de evaluación de la autolesión no suicida en adolescentes 1990-2016: una revisión sistemática
Bibliographic record
Abstract
The purpose of this systematic review was to identify the instruments created or adapted to assess non-suicidal self-injury (NSSI) among adolescents. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) methodology was used. Two individual reviewers analyzed the psychometric properties of instruments published in English or Spanish from 1990 to 2016 considering standardized quality criteria. The PsycINFO, PubMed, ISI Web of Knowledge, Scopus, SciELO, ScienceDirect, and EBSCO databases were consulted. Eighteen studies that created or adapted 11 instruments were selected. Most were developed in the United States or Canada, and none were developed in Latin America. Several studies presented no evidence of the psychometric properties of their instruments. Seven of the 18 studies obtained at least one positive score. The Alexian Brothers Urge to Self-Injure Scale (ABUSI) and the Impulse, Self-harm, and Suicide Ideation Questionnaire for Adolescents (ISSIQ-A) obtained the highest positive scores. The limitation of this study is that only seven databases were employed for the literature search in English and Spanish. The reporting of the psychometric properties of NSSI instruments among adolescents should be improved, and adaptations to Latin American countries should be developed for international comparisons.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.024 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".