Validation and Factor Analysis of the Child and Youth Resilience Measure for Indigenous Australian Boarding School Students
Bibliographic record
Abstract
Introduction: Resilience is a strengths-based approach that is useful for understanding differences in health and wellbeing among youth. There are a range of validated survey instruments available to measure resilience for Aboriginal and Torres Strait Islander (hereafter respectfully Indigenous ) youth. However, standard international instruments should only be used if they have been subjected to a rigorous cross-cultural adaptation process and psychometric evaluation in the target population to ensure their validity. The aim of the study was to validate an adapted Child and Youth Resilience Measure (CYRM-28) within a sample of Indigenous Australian boarding school students. Method: The CYRM-28, augmented with an additional 11 site specific items was administered to a purposive sample of Australian Indigenous boarding school students (n=233) as part of the broader T4S survey instrument that captures demographic information and measures resilience, psychological distress and risk, and service usage. Confirmatory factor analysis was undertaken to verify the relationship between the observed variables with the theoretical constructs of the CYRM-28 and previous findings on the factor structure. Cronbach alpha was also calculated to assess the internal consistency of the CYRM-28 within this sample. Results: Survey data from the study was not a good fit for any previously identified models of the CYRM-28, although the inclusion of a site-specific variable improved the overall fit statistics. Two separate scales were confirmed that capture the sources and expressions of resilience for Indigenous Australian boarding school students. This structure is different to previous findings in relation to the CYRM-28, but consistent with other conceptualisations of resilience as a dynamic process. Conclusions: The findings are useful in guiding the future use of the CYRM-28 instrument, explorations of Indigenous youth resilience, and for services working with Indigenous youth in out of home care situations. They highlight contextual differences in the measurement of resilience and the importance of validating standard scales that have been subjected to rigorous cross-cultural adaptation processes. The two scales offer practical guidance to human services working with Indigenous youth on strategies to build and monitor resilience in Indigenous Australian youth and contribute to the emergent understanding of their resilience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".