Beş Faktörlü Bilgece Farkındalık Ölçeği-Kısa Formu’nun (BFBFÖ-K) Türkçe Uyarlaması
Bibliographic record
Abstract
In recent years, mindfulness has been acknowledged as an important factor for physical and psychological well-being. At the same time, it is conceptualized as a personality characteristic as well as an intervention technique. Several assessment instruments were developed to measure mindfulness. Among these, Toronto Mindfulness Scale (TMS), Mindful Attention Awareness Scale (MAAS) and Five Facet Mindfulness Questionnaire (FFMQ) were adapted to Turkish language and culture. In the meantime, a short form of the Five Facet Mindfulness Questionnaire (FFMQ) was developed. The aim of the current study is to conduct a Turkish adaptation study for this short form. The other scales used in the study included Demo-graphic Information and Personal Evaluation Questionnaire, Toronto Mindfulness Scale (TMS), Difficulties in Emotion Regulation Scale (DERS), and the Brief Symptom Inventory (BSI). The study sample consisted of 268 participants (165 women and 99 men), with an age range of 18-75 (M = 25.59, SD = 9.99). The analyses revealed that the five-factor structure of the original form was preserved and other psychometric properties such as validity and reliability were found to be appropriate in the Turkish adaptation of the short form of the scale. In the light of the findings obtained, it is proposed that the Short Form of the Five Facet Mindfulness Questionnaire (FFMQ - Short Form) can be used with confidence in mindfulness-related research in Turkey
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".