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Record W7074741994

Psychometric Validation and Demographic Differences in Two Recently Developed Trait Mindfulness Measures

2012· article· en· W7074741994 on OpenAlexaboutno aff

Bibliographic record

VenueResearchArchive–Te Puna Rangahau (Victoria University of Wellington) · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessTraitFacet (psychology)Context (archaeology)HappinessPsychometricsSelf-report studyDepression (economics)Construct validityYoung adult
DOInot available

Abstract

fetched live from OpenAlex

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.243
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2012
Admission routes1
Has abstractyes

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