When Treatment Does Not Seem to Help: Identifying Interpersonal and Defensive Functioning in a Case with Borderline Personality Disorder
Bibliographic record
Abstract
Abstract Improvement in interpersonal and defensive functioning are considered central transtheoretical mechanisms that drive symptomatic change in clients with BPD. The current case study illustrates the treatment process and symptom changes in relation to interpersonal functioning, operationalized as the pervasiveness of conflictual relationship themes, and defensive functioning of a 22-year-old female client diagnosed with borderline personality disorder (BPD). The client underwent a 10-session General Psychiatric Management, a psychodynamically-oriented brief case management focusing on interpersonal hypersensitivity, as part of a larger Randomized Controlled Trial. The assessment involved three time points—intake, mid-treatment, and discharge—and comprised of a validated symptom scale, the Zanarini Rating Scale for BPD, along with two coding procedures, the Core Conflictual Relationship Theme method and the Defense Mechanisms Rating Scale-Q sort. While a decrease in the pervasiveness of conflictual relationship themes was observed, a worsening of defensive functioning was noted, which is posited to contribute to the increased symptom severity, particularly in affective and relational domains. Her prominent use of rationalization and passive aggression, along with irregular session attendance and low treatment dosage, are likely key factors influencing the mixed outcomes observed in borderline symptoms and defensive functioning, despite the reduction in the pervasiveness of interpersonal patterns.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".