Adolescent Resilience Assessment in Person-centered Medical Care
Bibliographic record
Abstract
Background. Acquiring resilience and psychological strength is central to adolescents' development and evolution from dependent child to autonomous adult, but is rarely addressed by physicians. Nevertheless, resilience, that is, positive adaptation to stress, predicts adult health and wellness. Objectives. We examined how to assess resilience in youth in a person-centered manner of merit to participants themselves. Our aim was to identify characteristics of resilience such as self-control and optimism, and foster these strengths at the same time. Method. Fifty-nine13-16 year-old adolescents from a small Canadian city, a remote town and one northern Ontario First Nations Reserve answered the 28-item Resilience Scale for Adolescents (READ) privately. Then they were asked semi-structured questions about their responses, family and social stresses, and strengths. Medical histories provided information about childhood adversities like poverty, abuse and family disruption. Results. We found READ scores to be statistically valid, comparable across gender, but lower among on-reserve indigenous youth. Results aligned loosely with subsequent interview information. However, the real merit of the resilience scale was as a door-opener to deeper, person-centered discussions. Only via interviews did we learn that youth had often adapted positively to the adversities identified in standard social/medical histories and named these as sources of strength and resilience rather than stress. Participants welcomed engaging as individuals rather than offspring of parents, and talked at length and with insight and enthusiasm. Conclusions. The positive response to and contextual understanding gained during interviews suggests that use of the READ followed by a qualitative discussion is a valuable and feasible clinical component of adolescent-centered medical care.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".