Are non-attenders a concern for primary care practice?
Bibliographic record
Abstract
The article by Eshel et al. describes major differences, in terms of demography and health status, between elderly patients who did and those who did not visit primary care physicians for general health check-ups. The authors conclude that non-attenders are not at risk for developing health conditions.While this study by Eshel et al. provides a better understanding of the primary care population, the conclusion (no need for reaching out to the non-attenders) should be viewed with caution. In this study, non-attenders 'have a higher probability of being women, older, not married and from a lower socio-economic' segment of the population, a population that is known to be at higher risk for chronic disease. In addition, outreach programs in primary care would be key in providing essential preventive measures for this vulnerable population (e.g., osteoporosis prevention, vaccination, lifestyle, etc.).This is a commentary on http://www.ijhpr.org/content/2/1/7.
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.
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 | 0.011 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.042 | 0.039 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".