Exploratory factor analysis of PROMIS-29 V1.0, PROMIS Global Health and the RAND SF-36 from chiropractic responders attending care in a practice-based research network
Bibliographic record
Abstract
BACKGROUND: The SF-36 questionnaire is perhaps the most widely used quality of life instrument in the world today, while the PROMIS instruments continue to gain popularity. Given their continued use in chiropractic research and practice, we examined their latent domain structure using exploratory factor analysis (EFA). METHODS: To uncover latent structures of a large series of measured variables from the PROMIS-29, PROMIS Global Health and RAND SF-36 domains, we defined a factor analysis model represented by the equation [Formula: see text], where [Formula: see text] is the matrix of random vectors corresponding to the domains with a mean of [Formula: see text] and the covariance matrix [Formula: see text] [Formula: see text] denotes the matrix of factor loadings, [Formula: see text] denotes the matrix of unobserved latent variables that influence the collection of domains and [Formula: see text] is the vector of latent error terms. The matrix of item responses X was the only observed quantity with restrictions such that variable scores were uncorrelated and of unit variance with the latent errors being independent with the variance vector [Formula: see text]. The inherited structure of X was expressed simply by [Formula: see text]. Orthogonal and oblique rotations were performed on the [Formula: see text] matrix with this equation to improve clarity of the latent structure. Model parameters [Formula: see text] were optimized using the method of minimum residuals. Each EFA model was constructed with Pearson and Polychoric correlation. RESULTS: For the PROMIS-29, domains were confirmed to be strongly correlated with Factor 1 (i.e., mental health) or Factor 2 (i.e., physical health). Satisfaction with participation in social roles was highly correlated with a 3rd factor (i.e., social health). For the PROMIS Global Health Scale, a 2-factor EFA confirmed the GPH and GMH domains. For the RAND SF-36, an apparent lack of definable structure was observed except for physical function which had a high correlational relationship with Factor 2. The remaining domains lacked correlation with any factors. CONCLUSION: Distinct separation in the latent factors between presumed physical, mental and social health domains were found with the PROMIS instruments but relatively indistinguishable domains in the RAND SF-36. We encourage continued efforts in this area of research to improving patient reported outcomes.
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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 | 0.043 | 0.128 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".