Transcultural Adaptation of and Theoretical Validation Models for the Spanish Version of the Nurses’ Global Assessment of Suicide Risk Scale: Protocol for a Multicenter Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: The use of validated instruments means providing health professionals with reliable and valid tools. The Nurses' Global Assessment of Suicide Risk (NGASR) scale has proven to be valid and reliable in supporting the nursing evaluation of suicide risk in different languages and cultural environments. OBJECTIVE: The aims of our study are to translate and adapt the NGASR scale for the Spanish population and evaluate its psychometric properties in patients with suicide risk factors. METHODS: The translation, adaptation, and modeling of the tool will be performed. The sample will include 165 participants. The psychometric analysis will include reliability and validity tests of the tool's internal structure. The tool's reliability will be assessed by exploring internal consistency and calculating the Cronbach α coefficient; significance values of .70 or higher will be accepted as indicators of good internal consistency. The underlying factor structure of the Spanish version of the NGASR scale will be assessed by performing an exploratory factor analysis. The Kaiser-Meyer-Olkin measure of sample adequacy and the Bartlett sphericity statistic will be calculated beforehand. For the latter, if P is <.05 for the null hypothesis of sphericity, the null hypothesis will be rejected. RESULTS: Participants will be recruited between April 2022 and December 2022. Our study is expected to conclude in the first quarter of 2023. CONCLUSIONS: We hope to find the same firmness that colleagues have found in other countries in order to consolidate and promote the use of the NGASR tool in the Spanish population. The prevention and treatment of suicidal behavior require holistic, multidisciplinary, and comprehensive management. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/39482.
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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 | 0.034 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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".