Preliminary Psychometric Evaluation of the Vancouver Index of Acculturation ( <scp>VIA</scp> ) in a <scp>UK</scp> ‐Based East‐Asian Sample
Bibliographic record
Abstract
ABSTRACT This study aimed to evaluate the psychometric properties and acceptability of the Vancouver Index of Acculturation (VIA) in a sample of UK‐based East‐Asian adults. Although widely used in cross‐cultural research, relatively few studies have assessed the factor structure, validity, and user acceptability of the VIA in non‐North American samples. A total of 236 East‐Asian participants (mean age = 26.8, 47.06% female) completed the 20‐item VIA and demographic questions. Confirmatory factor analysis (CFA) was conducted using AMOS with maximum likelihood estimation and robust standard errors. Exploratory factor analysis (EFA) using principal axis factoring and varimax rotation was also performed. Internal consistency, convergent and discriminant validity, and acceptability were evaluated. CFA showed poor model fit for the original two‐factor VIA structure: χ 2 (169) = 367.12, p < 0.001; CFI = 0.84; RMSEA = 0.089. The Mainstream factor showed weak and mostly nonsignificant loadings, while the Heritage factor demonstrated strong loadings. Internal consistency was high for Heritage ( α = 0.91) and acceptable for Mainstream ( α = 0.81). EFA supported a refined 17‐item two‐factor model, excluding three low‐loading Mainstream items. Discriminant validity was supported, but convergent validity was only partially established. Acceptability data indicated that while most items were well received, several were perceived as culturally ambiguous. Findings support the VIA's bidimensional structure but suggest that cross‐cultural adaptation may be needed to improve measurement accuracy in UK‐based East Asian populations. The study highlights the importance of further validation in culturally diverse samples.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".