Decision quality instrument for treatment of hip and knee osteoarthritis: a psychometric evaluation
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.
Bibliographic record
Abstract
BACKGROUND: A high quality decision requires that patients who meet clinical criteria for surgery are informed about the options (including non-surgical alternatives) and receive treatments that match their goals. The aim of this study was to evaluate the psychometric properties and clinical sensibility of a patient self report instrument, to measure the quality of decisions about total joint replacement for knee or hip osteoarthritis. METHODS: The performance of the Hip/Knee Osteoarthritis Decision Quality Instrument (HK-DQI) was evaluated in two samples: (1) a cross-sectional mail survey with 489 patients and 77 providers (study 1); and (2) a randomized controlled trial of a patient decision aid with 138 osteoarthritis patients considering total joint replacement (study 2). The HK-DQI results in two scores. Knowledge items are summed to create a total knowledge score, and a set of goals and concerns are used in a logistic regression model to develop a concordance score. The concordance score measures the proportion of patients whose treatment matched their goals. Hypotheses related to acceptability, feasibility, reliability and validity of the knowledge and concordance scores were examined. RESULTS: In study 1, the HK-DQI was completed by 382 patients (79%) and 45 providers (58%), and in study 2 by 127 patients (92%), with low rates of missing data. The DQI-knowledge score was reproducible (ICC = 0.81) and demonstrated discriminant validity (68% decision aid vs. 54% control, and 78% providers vs. 61% patients) and content validity. The concordance score demonstrated predictive validity, as patients whose treatments were concordant with their goals had more confidence and less regret with their decision compared to those who did not. CONCLUSIONS: The HK-DQI is feasible and acceptable to patients. It can be used to assess whether patients with osteoarthritis are making informed decisions about surgery that are concordant with their goals.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it