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Record W3136183903 · doi:10.3389/fpsyg.2021.648087

A Self-Compassion and Mindfulness-Based Cognitive Mobile Intervention (Serene) for Depression, Anxiety, and Stress: Promoting Adaptive Emotional Regulation and Wisdom

2021· article· en· W3136183903 on OpenAlexaff
Mohamed Al-Refae, Amr Al-Refae, Melanie Munroe, Nicole Sardella, Michel Ferrari

Bibliographic record

VenueFrontiers in Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMindfulnessPsychologySelf-compassionAnxietyClinical psychologyPsychological interventionCognitionCognitive reappraisalPsychotherapistRandomized controlled trialCoping (psychology)PsychiatryMedicine

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.322
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations74
Published2021
Admission routes1
Has abstractyes

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