Resilience Portfolios and Poly-Strengths: Identifying Strengths Associated with Wellbeing after Adversity
Bibliographic record
Abstract
Objectives: This study aimed to describe the prevalence of traumas and strengths in a representative sample of Quebec youth and to test whether poly-strengths were associated with low psychological distress, after controlling for poly-traumas. Method: Using data from the Quebec Youths’ Romantic Relationships survey (QYRRS), hierarchical logistic regressions were conducted to examine the relationship between poly-strengths and low levels of psychological distress, and to identify which strengths were associated with outcomes, after accounting for demographic variables and individuals’ experiences of traumas. Results: More than a third of the sample experienced 4 traumas or more (37.0%). The average number of experienced traumas was 3.04 out of 10 measured traumas. More than half of the sample had at least 5 strengths, the average number of strengths being 3.95 (out of 8). Two third (67.6%) of the sample did not suffer from psychological distress. Among poly-victims, half of the participants (49.6%) showed clinical symptoms of distress. Poly-strengths were uniquely associated with low of clinical distress. After accounting for demographics and poly-traumas, poly-strengths explained 24.2% of the variance of low levels of psychological distress. Self-esteem, optimism, parental support and attachment, number of sources of support, social support (seeking secure base), and capacity to adapt (resiliency) were uniquely associated with low levels of distress. Conclusion and Implications: The combination of strengths decreases the likelihood of experiencing clinical levels of psychological distress, which can contribute to healthy functioning in context of adversities. Findings highlight the importance of promoting multiple and diverse strengths among youth.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".