Evidence for measurement bias of the short form health survey based on sex and metropolitan influence zone in a secondary care population
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The 12-item Short Form Health Survey (SF-12) is a widely used measure of health related quality of life, but has been criticized for lacking an empirically supported model and producing biased estimates of mental and physical health status for some groups. We explored a model of measurement with the SF-12 and explored evidence for measurement invariance of the SF-12. RESEARCH DESIGN AND METHODS: The SF-12 was completed by 429 caregivers who accompanied patients with cognitive concerns to a memory clinic designed to service rural/remote-dwelling individuals. A multi-group confirmatory factor analysis was used to compare the theoretical measurement model to two empirically identified factor models reported previously in general population studies. RESULTS: A model that allowed mental and physical health to correlate, and some items to cross-load provided the best fit to the data. Using that model, measurement invariance was then assessed across sex and metropolitan influence zone (MIZ; a standardized measure of degree of rurality). DISCUSSION: Partial scalar invariance was demonstrated in both analyses. Differences by sex in latent item intercepts were found for items assessing feelings of energy and depression. Differences by MIZ in latent item intercepts were found for an item concerning how current health limits activities. IMPLICATIONS: The fitting model was one where the mental and physical health subscales were correlated, which is not provided in the scoring program offered by the publishers. Participants' sex and MIZ should be accounted for when comparing their factor scores on the SF-12. Additionally, consideration of geographic residence and associated cultural influences is recommended in future development and use of psychological measures with such populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.084 | 0.230 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".