Psychometric Validation and Demographic Differences in Two Recently Developed Trait Mindfulness Measures
Bibliographic record
Abstract
<p>Although in recent years an increasingly large body of mindfulness research has accrued, there continues to be a lack of information about how to measure trait mindfulness, as well as whether it varies across demographic variables such as age and gender. Four hundred and six participants from across New Zealand completed a battery of self-report measures in order to examine demographic differences in mindfulness, as well as to look at how mindfulness predicts outcome variables such as happiness and depression. Additionally, psychometric validation was undertaken on two new trait measures of mindfulness: the Toronto Mindfulness Scale, which did not demonstrate good psychometric validity, and the Five Facet Mindfulness Questionnaire, which did demonstrate good psychometric validity. This study found that females reported higher levels of mindfulness than males, though males demonstrated a stronger mediating relationship between mindfulness and happiness. In addition, higher levels of mindfulness were reported by older individuals; however, young adults manifested the strongest negative relationship between mindfulness and depression across the lifespan. These findings are then discussed in the context of clinical utility and future research.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 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 teacher head, 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".