Bibliographic record
Abstract
Murray and Lopez1 estimated that, in 1990, unipolar major depression accounted for 13% of all years lived with disability, making it the leading cause of disability in developed regions of the world. They also estimated that, in the established market economies, only 35% of people with unipolar major depression were actually treated, even though treatment can reduce the disability by 50%.2 Primary care services have an essential role if the best public health outcome is to be achieved (that is, the best possible reduction in morbidity as a result of improved awareness, detection, diagnosis, and treatment) because this goal far exceeds what is feasible for existing secondary and specialist level services. Thus the questions raised in this In Review section by Busker et al3 and Kates and Mach4-how to define the responsibilities of primary care and construct the best interface between primary care and specialist services, what primary care should be able to manage, and what are the best methods for managing depression-are critical to improving both the system of care and patient outcomes. Primary health care is under considerable stress in Canada, as in other countries,5 owing to the overall low numbers of physicians and to particular problems regarding recruitment into primary care. Overall, Canada has 2.1 doctors per 1000 population. The figure is 3.5 per 1000 in the Euro area, 2.7 per 1000 in the United States, and 2.0 per 1000 in the United Kingdom. Clearly, Canada's ratio of physicians to population is considerably lower than the ratio in most Western European countries and in the United States, although higher than that in the United Kingdom.6 A further concern is that the level of expertise and the complexity of the work required in primary care has reached the stage where it may be beyond what can reasonably be expected from most individuals. This shortfall may be partly attributed to the short-sighted physician recruitment policies adopted in Canada a decade ago, which led to cutbacks in medical school enrolment; it may also be attributed to payment systems that financially disadvantage those who choose to work and provide services in teams of health care providers. Across the country, the problem is now being in addressed by various schemes to encourage and support primary care reform. About 30% of the population have symptoms of a mental disorder over a 1 -year period, and over 80% of the population see a family physician. A mental disorder is detected in about 14% of the population each year; about 3.4% will see a psychiatrist, 3% a psychologist, and fewer than 0.5% will be admitted to hospital. Less than one-half of those who have symptoms of a mental disorder within a given year actually get treatment.7 Bilsker et al3 show that the physician-treated prevalence of depression in British Columbia increased from 7.7% in 1991-1992 to 9.5% in 2000-2001. Consistently, however, more than 95% were seen by family physicians, and in the last year, only 7.5% were seen by psychiatrists. (Busker and colleagues are to be congratulated on accessing the British Columbia billing database, which that province has sensibly made available to researchers. …
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".