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Record W4314935518 · doi:10.1097/nmd.0000000000001619

The Effect of Mindfulness-Based Stress Reduction (MBSR) on Emotional Flexibility and Ambivalence Over Emotional Expression in Divorced Women

2023· article· en· W4314935518 on OpenAlexaff
Rasoul Heshmati, Bassam Khoury, Shahin Abdollahi Fakhim, Masoumeh Zerang, Isabel Sadowski

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2023
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsMcGill University
Fundersnot available
KeywordsMindfulnessMindfulness-based stress reductionAmbivalenceFlexibility (engineering)PsychologyStress reductionClinical psychologyEmotional expressionAnalysis of varianceDevelopmental psychologyMedicineSocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT: The present study was developed to evaluate the effects of mindfulness-based stress reduction (MBSR) on the level of emotional flexibility and ambivalence related to emotional expression of divorced women. A general community sample of 30 divorced women was recruited and randomly assigned to experimental and control groups. The experimental group received MBSR for 8 weeks, and the control group was placed on a waiting list. The Emotional Flexibility Questionnaire (EFQ) and the Ambivalence Over the Expression of Emotion Questionnaire (AEQ) were administered to both groups before (pre) and after (post) the treatment. Data were analyzed using two-way mixed repeated-measures analyses of variance. The results showed that women in the treatment group had a significant increase in the total score of the EFQ and its components. In addition, the MBSR group had a significant decrease in the total score of the AEQ and its components. MBSR intervention shows potential for use with divorced women to help with emotion regulation and subsequent better adjustment to separation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations3
Published2023
Admission routes1
Has abstractyes

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