The Use of Antidepressant Medications in Substance Abuse Treatment: The Public-Private Distinction, Organizational Compatibility, and the Environment
Bibliographic record
Abstract
Many studies of innovation adoption in health care organizations focus either on organizational characteristics or the institutional environment, but not both. Furthermore, these perspectives are rarely employed simultaneously in both public and private health care organizations. This research considers the public-private distinction, organizational compatibility, and interorganizational referral relationships in the use of selective serotonin reuptake inhibitors (SSRIs) by substance abuse treatment organizations. Using data from nationally representative samples of 363 publicly funded and 403 privately funded substance abuse treatment centers, a four-category typology of public and private organizations initially predicted variation in SSRI use. However some differences were no longer significant once organizational and environmental characteristics were added to the statistical model. These data support hypotheses about the associations between organizational characteristics and SSRI use as well as hypotheses regarding the external environment. Future research should continue to integrate both internal and external factors in theoretical explanations of innovation adoption.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".