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Record W4396929834 · doi:10.1111/pere.12546

Mindfulness networks: Analyzing associations with self‐compassion, other‐compassion, need fulfillment, and satisfaction in midlife married Canadians

2024· article· en· W4396929834 on OpenAlexafffund
Christopher Quinn‐Nilas, Robin R. Milhausen

Bibliographic record

VenuePersonal Relationships · 2024
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMindfulnessCompassionSelf-compassionPsychologyClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Interest in mindfulness in the field of romantic relationships is growing. Drawing from a Self‐Determination Theory (SDT) perspective—which proposes that the basic psychological needs for autonomy, competence, and relatedness are foundational for well‐being—we attempted to map out the complex associations between mindfulness, self‐compassion, other‐compassion, basic need fulfillment in relationships, and increased relationship and sexual satisfaction. A sample of 640 midlife (40–59‐year‐old) married Canadians was recruited from a national panel. To test the associations at a systems‐level, we utilized psychological network analysis based on the premise that the relational and sexual effects of mindfulness are understood as part of a dynamic and multivariate network of associations with other variables. Need fulfillment in relationships (particularly relatedness needs) occupied a central position in the model, connecting mindfulness and self‐compassion with relationship satisfaction and sexual satisfaction. The findings underscored the major importance of SDT in relationships, and the overall structure of the network was consistent with growing theories of mindfulness in relationships. Future research employing longitudinal network models will aid in elucidating this system's operation over time.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.294
Teacher spread0.263 · 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.

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

Citations1
Published2024
Admission routes2
Has abstractyes

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