Long-Term Changes in Defense Styles With Psychodynamic Psychotherapy for Depressive, Anxiety, and Personality Disorders
Bibliographic record
Abstract
OBJECTIVE: This study examined 1) whether patients with chronic and recurrent anxiety and depressive disorders and/or personality disorders demonstrate improvement in their defense styles with long-term dynamic psychotherapy and 2) what the relationship is between defense style change and symptomatic change. METHOD: Measures of defense (Defense Style Questionnaire) and symptoms and functioning were administered at regular intervals over the course of 3-5 years to adults who entered a naturalistic study of long-term psychodynamic psychotherapy. With hierarchical linear regression, the relative contributions of change in variables on the Defense Style Questionnaire to change in other outcome variables were calculated. RESULTS: Those with high initial scores on the maladaptive and self-sacrificing defense styles improved, with effect sizes of 0.80 and 0.67, while overall defensive functioning improved, with an effect size of 0.43. The effect size of the change in score on the Global Assessment of Functioning scale was 0.82. Depressed subjects improved their scores significantly on the Hamilton Depression Rating Scale, and there was a significant improvement in distress, as measured by the SCL-90-R. Changes in score on the Defense Style Questionnaire added substantially to the prediction of variance in these three outcomes above their initial levels. A higher level of defensive functioning also predicted a better self-reported therapeutic alliance. CONCLUSIONS: Defense styles became more adaptive and symptoms improved over time in patients who started with scores in the clinical range. Change in defense style predicts symptomatic change, but causation has not been established.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".