Capturing Resilience: Utilizing the Brief Child and Youth Resilience Measure with Sexual and Gender Minority Youth
Bibliographic record
Abstract
Abstract This study explores the relevance of the brief Child and Youth Resilience Measure (CYRM-12) for sexual and gender minority youth (SGMY) aged 14–23 (N = 4,810), compares their patterns of resilience with general youth populations, and explores distinctions between key subgroups of SGMY. SGMY reported significantly lower scores, indicating poorer outcomes, than non-SGMY in several CYRM-12 items, especially those addressing familial and community support. Older SGMY (aged 19–23) reported significantly higher CYRM-12 scores than younger SGMY (aged 14–18; t = 11.00, p < .001). Compared with their non-SGMY counterparts, SGMY reported significantly lower scores regarding supportive parental relationships, connection to offline community, and school belongingness yet reported higher scores regarding the importance of education. Three factors contributed to SGMY resilience: (1) peer and community belonging, (2) familial and cultural support, and (3) youth’s personal attributes and self-efficacy. The results of this study also suggest that measuring resilience in SGMY should incorporate online as well as offline sources. Recommendations to enhance the CYRM-12 to capture the experiences of SGMY for social work research and practice are provided.
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 | 0.003 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".