How Often Do Individuals with Major Depression Receive Minimally Adequate Treatment? A Population-Based, Data Linkage Study
Bibliographic record
Abstract
Objective: Depression is usually treated with antidepressants, psychotherapy, or both. In this study, we examined the extent to which individuals with depression receive minimally adequate treatment with regard to the use of antidepressants and psychotherapy. Method: Using population-based administrative data, we identified individuals with inpatient or outpatient diagnoses of depression and tracked their use of publicly funded mental health services within a 12-month period. We used mixed-effects logistic regression to assess the influence of patient-level characteristics and physician-level variations on the receipt of minimally adequate treatment. Results: A total of 108 101 individuals, predominantly women (65%) and urban residents (89%), were diagnosed with depression in 2010–2011. Of these, 13% received minimally adequate counseling/psychotherapy with higher proportions observed among men, younger individuals, and urban residents. In contrast, there were more who received minimally adequate antidepressant therapy (48%), with women, older individuals, and rural residents having the highest proportions. Overall, about 53% received either type of treatment, and the pattern of use was similar to that of antidepressant therapy. Mixed-effects logistic regression results indicate that these factors remain independent predictors of the receipt of minimally adequate depression care. Significant practice variations also exist, which determine patients’ receipt of minimally adequate care, particularly with respect to counseling or psychotherapy. Conclusions: Only about half of those with depression receive either minimally adequate counseling/psychotherapy or minimally adequate antidepressant therapy. Disparities also persist, affecting mostly men and younger individuals. A multifactorial approach is needed to improve access to and reduce variations in receipt of minimally adequate depression care.
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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 | 0.012 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".