Bibliographic record
Abstract
Abstract To inform future research, treatment, and policy decisions, this book traces the scientific and social developments that shaped the current treatment model for depression in primary care over the past half century. While new strategies for diagnosing and treating depression have improved millions of people’s lives, there is little evidence that the overall societal burden of depression has decreased. Most experts point to a gap between what psychiatrists know and what primary care doctors do to explain untreated depression. Callahan and Berrios argue, however, that the problem stems mainly from lack of a public health perspective, that prevailing etiologic models underestimate the roles of society and culture in causing depression and over-emphasize biological factors. The current conceptual model for depression is a scientific and social invention of the last quarter century. Such models are important because they shape how society views people with emotional symptoms, defines who is sick, and determines who should get care. Most parents who seek treatment for depression receive antidepressant medications in primary care. The authors show that although depressed patients’ help-seeking behaviour and primary care doctors’ clinical approach have changed little over the past half century, the field of primary care medicine has changed dramatically. They describe how the specific diagnoses and treatments developed by psychiatrists in the past 50 years have often collided with the non-specific approaches that dominate primary care practice. In examining the research seeking to close the gap between psychiatry and primary care, Callahan and Berrios offer public health models to explain the ongoing societal burden of depression. By exploring the history of depression in primary care, they open a pathway for improvements in the care of people with depression, where primary care physicians should play a greater leadership role in the future.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".