Reducing Anger and Enhancing Moral Engagement through Cognitive Functioning Workshops
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to evaluate the effectiveness of cognitive functioning workshops in reducing anger and moral disengagement among adults. By integrating cognitive-behavioral techniques, mindfulness practices, and social skills training, the intervention seeks to enhance participants' emotional regulation and ethical decision-making capabilities. A randomized controlled trial design was employed, involving 30 participants randomly assigned to either the intervention group (n=15) or the control group (n=15). The intervention group attended twelve 60-minute sessions over three months. Assessments were conducted at baseline, immediately post-intervention, and at a three-month follow-up, using the State-Trait Anger Expression Inventory-2 (STAXI-2) and the Moral Disengagement Scale (MDS). Data were analyzed using analysis of variance (ANOVA) with repeated measurements and Bonferroni post-hoc tests in SPSS-27. The intervention group showed significant reductions in anger and moral disengagement scores compared to the control group. ANOVA results indicated a significant interaction effect between time and group for both anger (p < .05) and moral disengagement (p < .05), with post-hoc tests confirming sustained improvements at the three-month follow-up. The intervention was effective in enhancing cognitive control, emotional regulation, and ethical behavior among participants. Cognitive functioning workshops are an effective intervention for reducing anger and moral disengagement. The combination of cognitive-behavioral techniques, mindfulness, and social skills training provides a comprehensive approach to improving emotional and ethical functioning. These findings support the integration of such workshops in therapeutic settings to enhance psychological well-being and promote ethical behavior.
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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) | 0.000 | 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