Change in Defense Mechanisms During Long-Term Dynamic Psychotherapy and Five-Year Outcome
Bibliographic record
Abstract
OBJECTIVE: Research suggests that defense mechanisms may underlie other aspects of functioning and psychiatric symptoms. The authors examined whether defenses change in accordance with the hierarchy of defense adaptation during long-term dynamic psychotherapy and whether such change is associated with long-term outcomes on other measures. METHOD: Twenty-one adults with depressive, anxiety, and/or personality disorders entered long-term dynamic psychotherapy (mean=248 weeks) and subsequent follow-along (mean duration, 5.1 years). Measures of functioning and symptoms were gathered in periodic follow-along interviews, external to the therapy. A median of eight psychotherapy sessions over 2.5 years for each participant were rated using the Defense Mechanism Rating Scales quantitative method. RESULTS: Overall, the lowest (action) and highest (high adaptive) defense levels in the hierarchy of defenses improved significantly, as did overall defensive functioning (median effect size=0.71, 95% CI=0.01-1.83). Overall defensive functioning still remained below the healthy-neurotic range. A higher number of axis I disorders and childhood histories of sexual abuse and witnessing violence were associated with a slower rate of improvement in defenses. Change in defenses within therapy by 2.5 years was highly associated with significant levels of change at 5 years in external measures of both functioning (rs=0.60) and symptoms (rs=0.58), controlling for initial levels. CONCLUSIONS: Change in defensive functioning in long-term psychotherapy largely follows the hierarchy of defense adaptation. The relationship to long-term improvement in outcomes suggests that defenses be considered candidates for mediating improvement in functioning and symptoms.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| 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".