Evidence pointing toward invalidity of the SF-8 physical and mental scales: a fusion validity assessment
Bibliographic record
Abstract
BACKGROUND: The SF-8™ Short Form Health Survey creates physical and mental health scale scores from responses to eight survey questions. These widely used scales demonstrate reasonable reliablity, and some forms of validity but have not been assessed for fusion validity. We assess the fusion validity of the SF-8 physical and mental health scales, and provide comments assisting fusion validity assessment of other scales. METHODS: Checking the fusion validity of a scale requires including the scale and its constituent indicators in a structural equation model that has at least one variable causally downstream from the scale. We assessed fusion validity of the SF-8 physical and mental health scales in the context of work-related variables for care aides working in Canadian long-term care homes. Variables causally downstream from physical and mental health, such as work burnout, permit checking whether the SF-8 indicator items fuse to form cogent physical and mental scales, irrespective of whether those indicators share common-factor foundations. RESULTS: We found that the SF-8 physical and mental health scales did not function appropriately. The scales inappropriately claimed effects for several items that had no effects and provided biased estimates of other effects. These deficiencies seem grounded in the scales' developmental history, which implicitly bolstered selection of some causally ambiguous items and paid insufficient attention to component factor model testing. CONCLUSION: Our observations of causal incongruities question whether the SF-8 can provide valid assessments of physical and mental health. However, it would be imprudent to discontinue SF-8 use on the basis of a single study suggesting invalidity. This uncomfortable conclusion can be rechecked by re-analyzing data from any project that employed the SF-8 and recorded even one causal consequence of physical or mental health. The power of fusion validity assessment comes from connecting the recorded consequences simultaneously to both the scale and the items from which that scale is calculated.
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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 | 0.171 | 0.404 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".