Exploring daily affective changes in university students with a mindful positive reappraisal intervention: A daily diary randomized controlled trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Brief and cost-effective interventions focused on emotion regulation techniques can buffer against stress and foster positive functioning. Mindfulness and positive reappraisal are two techniques that can mutually enhance one another to promote well-being. However, research testing the effectiveness of interventions combining mindfulness and reappraisal is lacking. The current pilot examined the effect of a combined mindful-reappraisal intervention on daily affect in a 5-day diary study with 106 university students. Participants were randomized to a mindful-reappraisal intervention (n = 36), a reappraisal-only intervention (n = 34), or an active control activity (n = 36). All participants described a negative event each day but only reappraised the event in the intervention conditions. Using multilevel growth modelling, results indicated that negative affect in both interventions declined over 5 days compared to the control; however, there were no differences in the growth of positive affect. Compared to reappraisal-only, the mindful-reappraisal group reported overall lower daily negative affect and marginally higher daily positive affect over the 5-day intervention. These findings suggest that brief daily practice combining mindfulness and positive reappraisal can be trained as a self-regulatory resource to promote positive affect and buffer negative affect above and beyond reappraisal practice alone.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it