Reciprocal associations between positive emotions and resilience predict flourishing among adolescents
Bibliographic record
Abstract
INTRODUCTION: The broaden and build theory of positive emotions maintains that positive emotions serve to broaden individuals' thoughts and behaviours, resulting in the accrual of resources (e.g. resilience) that catalyze upward spirals of well-being. However, there is a relative dearth of research examining the upward spiral hypothesis in the context of adolescence. METHODS: Adolescents (n = 4064) in participating Canadian high schools were surveyed annually for three years as part of the COMPASS study. Reciprocal associations between positive emotions and resilience were examined as predictors of flourishing. RESULTS: Adolescents who experienced positive emotions more frequently than usual reported higher levels of resilience one year later. Similarly, adolescents who had higher levels of resilience than usual reported more positive emotions the following year. Higher than usual levels of resilience and positive emotions positively predicted flourishing. CONCLUSION: Positive emotions result in a cascade of beneficial outcomes including increased resilience and enhanced well-being, catalyzing an upward spiral towards flourishing. Opportunities to enhance positive emotions early on in adolescence may help build resources that can set students on the path towards increased well-being.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".