Treatment Compliance Among Patients with Personality Disorders Receiving Group Psychotherapy: What Are the Roles of Interpersonal Distress and Cohesion?
Bibliographic record
Abstract
It is often assumed that patients with personality disorders have worse compliance in psychotherapy (i.e., attend fewer sessions) than patients without personality disorders. Such an assumption can have negative consequences for the treatment of patients with personality disorders. It also denies the presence of variability in session attendance among patients with personality disorders. Research that attempts to identify the factors that are associated with variability in session attendance among patients with personality disorders is needed. The present study examined the role of interpersonal distress as a predictor of session attendance for patients with personality disorders (n = 72) in two different forms of group psychotherapy (interpretive, supportive). The study also investigated whether patients' cohesion to their group mediated the effect of interpersonal distress on attendance. Findings indicated that interpersonal distress had a strong, direct association with attendance in supportive group therapy, but minimal association in interpretive group therapy. High levels of interpersonal distress were associated with higher attendance in supportive therapy. Furthermore, cohesion to the group accounted for about two-thirds of the effect of interpersonal distress on attendance in supportive group therapy, thus providing compelling evidence for its role as a mediator. Possible explanations and clinical implications of these findings are discussed.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".