Psychometric Properties of the Inventory of Attitudes Toward Seeking Mental Health Services (Chinese Version)
Bibliographic record
Abstract
ABSTRACTResearch on underutilization patterns of mental health services among older Chinese immigrants is limited, partly due to the absence of translated, psychometrically sound measures for assessing attitudes towards seeking help. In this study we interviewed 200 older Chinese Canadian immigrants using a translated version of the Inventory of Attitudes Toward Seeking Mental Health Services scale (IASMHS), and assessed mental health care utilization over the past 12 months and intentions to seek help. Confirmatory factor analysis failed to replicate the original three-factor structure; thus, we used exploratory factor analysis to create a 20-item Chinese version, the C-IASMHS. It had acceptable internal consistency and was positively correlated with intentions to seek help. The Help-Seeking Propensity subscale had the strongest psychometric properties whereas the Psychological Openness subscale performed poorly based on factor analysis results and unacceptable internal consistency. Future research should focus on the conceptual equivalence of psychological openness among Chinese older adults.
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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 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".