Factor structure and psychometric properties of the Chinese version of the Odor Awareness Scale
Bibliographic record
Abstract
Background The Odor Awareness Scale (OAS) is a questionnaire that assesses individual differences in awareness of odors in the surrounding environment, which has been shown to be associated with affective symptoms in recent researches. To further research, A Chinese version of the OAS needs to be introduced. Objective To investigate the factor structure and validate the psychometric properties of the OAS. Methods A total of 978 participants from college were randomly allocated into two groups for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), respectively. Additionally, the study entailed item analysis and scrutinized internal consistency reliability, test-retest reliability, and concurrent validity. Test-retest reliability was assessed by having 214 participants complete the OAS twice at a one-week interval. Concurrent validity was measured using the Body Odor Sniffing Questionnaire (BOSQ), the Generalized Anxiety Disorder Scale (GAD-7), and the Toronto Alexithymia Scale (TAS-20). Results EFA identified three factors that best fit the data: odor sensitivity, odor impact, and odor attention. CFA validated a second-order factor model, yielding good fit indices: χ2 / Df = 2.326, RMSEA = 0.052, CFI = 0.911, TLI = 0.900, SRMR = 0.053. The final version of the OAS comprised 27 items and exhibited a commendable internal consistency reliability (Cronbach’s α = 0.913), and a good test-retest reliability, as evidenced by the high Pearson correlation coefficient (r = 0.940) and intraclass correlation coefficient (ICC = 0.940). The OAS was significantly correlated with BOSQ (r = 0.416), GAD-7 (r = 0.155), and TAS-20 (r = −0.081). Conclusion The Chinese version of the OAS demonstrated robust reliability and validity, rendering it a valuable instrument for evaluating odor awareness in the Chinese population.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".