Detecting short-term change and variation in health-related quality of life: within- and between-person factor structure of the SF-36 health survey
Bibliographic record
Abstract
BACKGROUND: A major goal of much aging-related research and geriatric medicine is to identify early changes in health and functioning before serious limitations develop. To this end, regular collection of patient-reported outcome measure (PROMs) in a clinical setting may be useful to identify and monitor these changes. However, existing PROMs were not designed for repeated administration and are more commonly used as one-time screening tools; as such, their ability to detect variation and measurement properties when administered repeatedly remain unknown. In this study we evaluated the potential of the RAND SF-36 Health Survey as a repeated-use PROM by examining its measurement properties when modified for administration over multiple occasions. METHODS: To distinguish between-person (i.e., average) from within-person (i.e., occasion) levels, the SF-36 Health Survey was completed by a sample of older adults (N = 122, M age = 66.28 years) daily for seven consecutive days. Multilevel confirmatory factor analysis (CFA) was employed to investigate the factor structure at both levels for two- and eight-factor solutions. RESULTS: Multilevel CFA models revealed that the correlated eight-factor solution provided better model fit than the two-factor solution at both the between-person and within-person levels. Overall model fit for the SF-36 Health Survey administered daily was not substantially different from standard survey administration, though both were below optimal levels as reported in the literature. However, individual subscales did demonstrate good reliability. CONCLUSIONS: Many of the subscales of the modified SF-36 for repeated daily assessment were found to be sufficiently reliable for use in repeated measurement designs incorporating PROMs, though the overall scale may not be optimal. We encourage future work to investigate the utility of the subscales in specific contexts, as well as the measurement properties of other existing PROMs when administered in a repeated measures design. The development and integration of new measures for this purpose may ultimately be necessary.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".