Psychometric properties of the Big Five Inventory in a Chinese sample of smokers receiving cessation treatment: A validation study
Bibliographic record
Abstract
Background : Some personality traits were found to be relevant to engagement in smoking. Examination of associations between personality traits and behaviours in smoking and cessation will guide the development of effective preventive and cessation interventions. The objective of this study was to evaluate the factor structure and reliability of a Chinese version of the Big Five Inventory (BFI) for assessing the five personality dimensions of extraversion, agreeableness, conscien- tiousness, neuroticism and openness to experience in adults who had a smoking habit. Methods : 1173 Chinese smokers who had received smoking cessation intervention at a smoking cessation health centre in Hong Kong from 21 August 2000 to January 2002 were followed-up by telephone between February and August 2008. Participants completed a questionnaire including the 44-item BFI and perceived health status. A total of 480 (41%) participants completed the survey and 439 questionnaires without missing were analysed. The factor structure of the BFI was assessed by confirmatory factor analysis, reliability by Cronbach alpha and concurrent validity by personality scores by gender and relationship with perceived health. The convergent and discriminant validity of the reduced version of BFI was compared to the original version using the mulittrait-multimethod matrix approach. Results : Confirmatory factor analyses revealed that the five-factor structure provided an acceptable fit after removing 15 items which did not contribute to their corresponding factors. The reduced 29-item BFI had internal reliability estimates ranged from 0.69 for agreeableness to 0.81 for neuroticism. Women scored significantly higher in neuroticism and lower in openness to experience. All the correlations of the five personality traits with perceived health were in the expected directions and statistically significant except openness to experience. The four requirements of convergent and discriminant validity of the reduced 29-item BFI were met. Conclusions : These results showed that the satisfactory psychometric properties of the Chinese version of BFI with modifications; suggesting that the Chinese translation of the abbreviated 29-item BFI could be a useful and practical tool in measuring personality traits among Chinese adults had a smoking habit.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".