Improving social functioning and life satisfaction among patients with personality dysfunction: Connectedness and engagement in integrative group treatment
Bibliographic record
Abstract
Reduced social impairment and improved life satisfaction are important objectives in group treatment for patients with personality dysfunction. Knowledge regarding patient characteristics and group treatment processes that contribute to these outcomes, however, remains limited. Dispositional connectedness, the valuing of interpersonal connections, may be an important patient factor that influences patients' experience of group treatment in ways that facilitate therapeutic benefits. The present study investigated the roles of dispositional connectedness and group engagement in contributing to improvement in social functioning and life satisfaction through integrative group treatment for personality dysfunction. Seventy-nine patients who completed an integrative group treatment programme were assessed for dispositional connectedness at baseline and social functioning and life satisfaction at pretreatment and posttreatment; each also provided ratings of group engagement during treatment. Regression analyses using bootstrap confidence intervals found significant indirect effects for dispositional connectedness regarding improvement in both social functioning and life satisfaction, through the mediating effect of group engagement. Thus, patients who entered treatment with tendencies towards interpersonal connectedness perceived a higher level of engagement in the group environment. Group engagement in turn contributed to greater improvement in social functioning and to greater improvement in life satisfaction following treatment. The findings indicate dispositional connectedness as a salient characteristic in selecting patients for group treatment and highlight the role of an engaged interpersonal climate in facilitating improvement in social functioning and life satisfaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".