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Record W3135505713 · doi:10.1186/s12955-021-01725-9

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

2021· article· en· W3135505713 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth and Quality of Life Outcomes · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsCanadian Chiropractic Association
Fundersnot available
KeywordsAlgorithmComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.052
metaresearch head score (Gemma)0.291
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0520.291
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.757
GPT teacher head0.611
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it