Investigating Mindfulness, Borderline Personality Traits, and Well-Being in a Nonclinical Population
Bibliographic record
Abstract
A growing body of literature has revealed that mindfulness-based interventions consistently have positive outcomes, suggesting that increased mindfulness is related to decreases in psychological symptoms and increases in well-being. In a sample of 110 Mount Royal University undergraduate students, we explored the intercorrelations between mindfulness, borderline personality traits, and subjective well-being (SWB). We hypothesized a negative correlation between mindfulness and borderline personality traits, a positive correlation between mindfulness and SWB, and a negative correlation between borderline personality traits and SWB. To examine, a battery of questionnaire containing four measures was used: Mindful Attention Awareness Scale (MAAS), Five Facet of Mindfulness Questionnaire (FFMQ), Personal Well-being Index (PWI), and Borderline Personality Questionnaire—revised (BPQ). Pearson’s correlation and multiple regression analysis results were consistent with our hypotheses. As predicted, higher degrees of mindfulness are associated with less borderline personality traits and greater well-being, whereas the presence of borderline personality traits is linked to lower degrees of well-being. The findings of the present study have significant clinical implications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".