Mindfulness networks: Analyzing associations with self‐compassion, other‐compassion, need fulfillment, and satisfaction in midlife married Canadians
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".