A Pilot Study of Defenses in Adults with Personality Disorders Entering Psychotherapy
Bibliographic record
Abstract
This study examined defensive functioning in adults entering open-ended dynamic psychotherapy and determined whether defenses predict retention at 1 year. Beginning at about the fifth session, 14 adults with personality and or depressive disorders entering open-ended dynamic psychotherapy had five therapy sessions audiotaped. The sessions were rated according to the Defense Mechanism Rating Scales, quantitative method. Interrater reliability of overall defensive functioning (ODF) and the number of defenses used per session were intraclass R = .85 and .83, respectively, whereas that of seven defense levels yielded a median of .625 (range .52 to .80). Stability of ODF across the five sessions was intraclass R = .48. The 11 subjects with personality disorders (PDs) used predominantly lower immature (49.3%) and neurotic (40.8%) level defenses. Subjects with borderline PD had significantly lower ODF than those with other PD types. Higher ODF was associated with remaining in treatment at 1 year, although this was confounded with a higher frequency of weekly sessions. Quantitative assessment of defenses demonstrated fair to excellent reliability and indicated that in the short term approximately half of defensive functioning reflects a stable repertoire, whereas the remaining variation may be due to occasion and error. PDs and especially BPD are characterized by a predominance of lower defenses. Higher defensive functioning was associated with twice-weekly sessions and retention in therapy at 1 year. In therapy, adjusting technique to the patient's defenses may improve retention and outcome.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".