Validation of the Child and Youth Resilience Measure (CYRM-28) on a Sample of At-Risk New Zealand Youth
Bibliographic record
Abstract
Purpose: This article reports on an examination of the psychometric properties of the 28-item Child and Youth Resilience Measure (CYRM-28). Methods: Exploratory factor analysis, confirmatory factor analysis, Cronbach’s α, t-tests, correlations, and multivariate analysis of variance were applied to data collected via interviews from 593 at-risk adolescents (12–17 years) to identify the factor structure, internal consistency, test–retest reliability, construct validity, and floor and ceiling effects of the CYRM-28. Results: A four-factor structure was identified comprising two contextual factors, individual and family factors. The CYRM-28 and its factors show good internal reliability, stable test–retest properties, and no floor or ceiling effects. The measure also showed good construct validity. Discussion: The CYRM-28 shows good overall validity on this group of New Zealand youth, and researchers and social workers can have some confidence in its usefulness as a measure that can be used to assess resilience in youth from a range of ethnic backgrounds.
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 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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".