Case Studies in Clinical Psychology: Are We Giving up a Publication Type and Methodology in Research on and Teaching of Psychopathology and Psychotherapy?
Bibliographic record
Abstract
Scientometric results on publication trends in clinical psychology, which refer to publication type and methodology of case studies/reports, are presented. Absolute and relative frequencies of clinical case studies are identified for the segment “mental and behavioral disorders” in MEDLINE (ICD-10 Chapter V [F]) as well as for clinical psychology publications documented in PsycINFO and PSYNDEX in 40 publication years (1975-2014). Results show an increase of the absolute number of published case studies documented in MEDLINE and PsycINFO (but not in PSYNDEX), which is highly correlated with the total increase of clinical psychology publications in both databases. Relative frequencies show another picture, namely a drop of the percentage of case studies on mental and behavioral disorders in MEDLINE, and a sharp drop in PSYNDEX since the 1980s. The trend for the relative frequency of case studies within all publications on clinical psychology documented in PsycINFO is V-shaped with 6% in the 1970s, 3% in the early 1990s, and 4-5% after the millennium. Pros and cons of case studies in clinical psychology research and education are discussed. Qualitative and quantitative case study methodologies are distinguished with respect to the phases of clinical trials and observational studies in evidence-based and empirically supported psychotherapy. Subsequently, methodological constraints are balanced with specific values in clinical training, applied research, and innovative research on the symptomatology, etiology, and classification of mental disorders as well as on combined and/or integrative treatment techniques and methods.
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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 | 0.265 | 0.668 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.049 | 0.093 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.024 | 0.032 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".