Supporting Student Success with the “Stress Stories Project” Pilot Intervention Study: An Integrated Approach to Regulating Stress and Enhancing Learning Management to Support Flourishing at School
Bibliographic record
Abstract
Elementary students can experience high levels of school-related stress, which can subsequently hinder learning and well-being. At this age and stage, students are still developing the skills to manage stress and academic demands, and benefit from additional support. Few studies have explored interventions that combine stress regulation with learning management or compared different learning consolidation methods. This study examined the effectiveness of the Stress Stories Project , an integrated intervention targeting two key stress appraisals linked to student success: (a) stress mindset and (b) coping self-efficacy. It also compared the effects of two consolidation strategies, memory reconsolidation and metacognitive reflection, on the appraisal outcomes. Grade 4 and 5 Canadian Public School students participated in the 2-week intervention and were assigned to either the memory reconsolidation or metacognitive reflection condition. Stress mindset and coping self-efficacy were measured before and after the intervention. A 2 (Time: pre, post) × 2 (Group: reflection, reconsolidation) repeated measures ANOVA assessed the impact of condition on outcomes. Results showed an overall increase in stress mindset scores, with more students adopting a “stress is enhancing” mindset. Coping self-efficacy did not change significantly. However, a significant time-by-group interaction revealed that memory reconsolidation was more effective than reflection in improving stress mindset over time. These findings suggest that addressing students’ past school stress experiences through memory reconsolidation may enhance stress mindset and offer greater psychological and motivational benefits.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".