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Record W4292657466 · doi:10.31234/osf.io/vfxwe

Self-Reported Trait Mindfulness and Couples’ Relationship Satisfaction: A Meta-Analysis

2022· preprint· en· W4292657466 on OpenAlexafffund
Christopher Quinn‐Nilas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMindfulnessTraitPsychologyAssociation (psychology)Meta-analysisRomanceSocial psychologyClinical psychologyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

Objectives: New theoretical perspectives have begun to shift the study of trait mindfulness beyond individual processes to interpersonal romantic relationships. Viability of these pursuits is perhaps contingent on the basic assumption that higher trait mindfulness is associated with beneficial outcomes like relationship satisfaction. Moreover, if this association is not consistent across sample characteristics or if the available knowledge appears tainted by publication bias, then the basic assumption of this emerging research may not be tenable. Methods: Twenty-eight samples of studies correlating trait mindfulness and relationship satisfaction were collected. Results: The average effect size was small (.24) and publication bias was not evident. The effect size was consistent across age, gender, marital status, meditation status, and mindfulness dimensionality. Conclusions: This study supports emerging theoretical perspectives linking trait mindfulness to romantic relationship outcomes. The association between trait mindfulness and relationship satisfaction does not appear sensitive to a publication bias mechanism.

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)0.018
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.033
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.028
Bibliometrics0.0080.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.151
GPT teacher head0.379
Teacher spread0.228 · 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 designMeta-analysis
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

Citations1
Published2022
Admission routes2
Has abstractyes

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