Trait Mindfulness, Self-Compassion, and Self-Talk: A Correlational Analysis of Young Adults
Bibliographic record
Abstract
This research explores the relationships between trait mindfulness, self-compassion, self-talk frequency, and experience with mindful practice. We expected to find that positive self-talk would be positively related to mindfulness and self-compassion, and negative self-talk would be negatively related to these variables. Participants (N = 342) were recruited through a university research pool, as well as via social media posting. The participants completed two measures of trait mindfulness (the 15-item Five Facet Mindfulness Questionnaire and the Trait Toronto Mindfulness Scale), two measures of self-talk (the Self-Talk Scale and the Automatic Thoughts Questionnaire—Revised), and the Self-Compassion Scale short form. The results showed moderate positive correlations between (1) positive self-talk and trait mindfulness and (2) positive self-talk and self-compassion. A significant negative correlation also emerged between negative self-talk and trait mindfulness. Additional analyses indicated no moderating effects of mindfulness experience on self-talk or self-compassion in predicting trait mindfulness. We discuss implications for the significance of the relationship between self-talk and mindfulness for the effective implementation in future treatment methodologies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".