A Self-Compassion and Mindfulness-Based Cognitive Mobile Intervention (Serene) for Depression, Anxiety, and Stress: Promoting Adaptive Emotional Regulation and Wisdom
Bibliographic record
Abstract
Introduction: Many individuals and families are currently experiencing a high level of COVID-19-related stress and are struggling to find helpful coping mechanisms. Mindfulness-based interventions are becoming an increasingly popular treatment for individuals experiencing depression and chronic levels of stress. The app (Serene) draws from scholarly evidence on the efficacy of mindfulness meditations and builds on the pre-existing apps by incorporating techniques that are used in some therapies such as cognitive behavioral therapy and mindfulness-based cognitive therapy. Methods: Participants were randomly assigned to a 4-week mindfulness and self-compassion-based cognitive smartphone intervention (Serene) or a wait-list control group. They were instructed to engage in self-compassion and mindfulness practices and a cognitive restructuring task. They also completed measures that evaluated their levels of depression, stress, anxiety, self-compassion, wisdom, psychological well-being, and subjective well-being. The intervention group was also instructed to track their weekly engagement with the app. Standardized effect sizes for between-group differences were calculated using Cohen's d for complete case analyses. Results: Complete case analyses from baseline to the end of this randomized controlled trial demonstrated significant moderate between-group differences for depressive symptoms ( d = −0.43) and decisiveness ( d = 0.34). Moderate between-group differences were also found for self-compassion ( d = 0.6) such that significant improvements in self-kindness, common humanity, mindfulness and decreases in self-judgement, isolation, and overidentification were observed. A small between-group difference was found for emotional regulation ( d = 0.28). Moreover, a significant moderate within-group decrease in stress ( d = −0.52) and anxiety symptoms ( d = −0.47) was also observed in the intervention group. Conclusions: Serene is an effective intervention that promotes increased levels of self-compassion and emotional regulation. Engaging with Serene may help reduce depressive symptoms through mindfulness, self-compassion, and cognitive restructuring which help reduce overidentification with one's negative emotions. As individuals rebalance their thinking through cognitive restructuring, they can identify the varying stressors in their life, develop action plans and engage in adaptive coping strategies to address them. Serene may promote greater self-understanding which may provide one with a more balanced perspective on their current upsetting situations to positively transform their challenges during the pandemic.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".