A systematic review of the psychology literature addressing hospital practice.
Bibliographic record
Abstract
Hospitals, with their unique practice constraints and opportunities, are one of the most important arenas wherein the field of clinical psychology has developed throughout its history. However, there have been few efforts to comprehensively examine the literature on this topic. This is a literature worth examining, not only out of historical interest but also in the effort to provide direction for the field. Accordingly, systematic, scoping review methods were used to address the question: What does the psychology literature tell us about the nature and evolution of psychology practice in hospitals? The review identified 115 papers on this topic dating from 1916-2017, primarily in the form of practice commentaries and case studies. Analysis of the papers revealed 2 broad themes. One involved the nature of hospital practice, which concentrated on the major domains of assessment, psychotherapy and research activities along with issues related to training. The second involved structural and policy-related considerations such as cost-effectiveness and reimbursement models, leadership, the structure of practice, relationship to physicians, and hospital privileges. Implications of the review include the need for better data on the hospital practices of psychologists and continued work on role definition and the unique value of psychology. Other implications include direction for training models, practice models such as stepped care and a compromise between program and department-based management, privileges, and mental health reform. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.010 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".