Converted Patients and Clinic Patients as Control Cases: a Comparison With Implications for Psychoanalytic Training
Bibliographic record
Abstract
All twenty-eight respondents to a recent poll of the thirty institutes affiliated with the American Psychoanalytic Association reported that they now accept cases converted from psychotherapy to psychoanalysis as control cases. This study was designed to compare converted cases to clinic cases systematically with respect to patient characteristics, treatment, and the educational experience of the treating candidate. The study followed twenty-four candidates entering analytic training between 1992 and 1995, who treated thirty-four clinic cases and forty-three converted cases between February 1993 and July 2000. Clinic and converted patients were comparable with regard to demographics, prior treatment histories, structural diagnoses, and Axis I diagnoses. In addition, the two groups of cases were indistinguishable with respect to the rate at which candidates received credit toward graduation requirements. Candidates treating converted cases earned approximately dollars 7,600 per patient per year, compared to candidates treating clinic cases, who earned nothing. Eighty-four percent of converted patients diagnosed with a mood disorder by the treating candidate were on medication, in contrast to only 20% of clinic patients with the same diagnosis. Similar differences were seen in the case of anxiety disorders. Given the prevalence of affective and anxiety disorders in control cases and the availability of a variety of medications and psychotherapies with documented efficacy in treating these disorders, candidates should be trained to discuss treatment options with patients who present with Axis I disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".