General practitioner identification and retention for people with spinal cord damage: establishing factors to inform a general practitioner satisfaction measure
Bibliographic record
Abstract
People with spinal cord damage (SCD) report a high level of GP use. There is a dearth of research investigating factors that contribute to GP identification and retention for people with SCD. Furthermore, a GP satisfaction measure developed specifically for people with SCD is non-existent. This preliminary study sought to identify factors contributing to GP identification and retention. A total of 266 people with SCD primarily based in Queensland, Australia, completed a cross-sectional survey that aimed to fill these knowledge gaps. Descriptive statistics and correlational analyses clarified the factors contributing to GP identification and GP retention respectively. An exploratory factor analysis utilising the principal components analysis method clarified a set of items that could underpin key domains for a SCD-specific GP satisfaction measure. The findings confirm that knowledge about SCD, physically accessible services, and trust are seminal considerations aligned with GP identification and retention for people with SCD.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".