The role of the therapeutic alliance in psychotherapy with sexual offenders
Bibliographic record
Abstract
The present study investigated which components of the therapeutic alliance were predictive of positive therapeutic outcomes in psychotherapy with a population of male sexual offenders.Measured elements of the alliance included: therapist empathy, unconditionality, positive regard, and congruence; the client-therapist bond; and clienttherapist collaboration on the tasks and goals of treatment.Outcome indices included: global functioning; attainment of specific treatment goals; healthy intimacy development; and reduction in cognitive distortions.Participants were 44 men participating in either community-or institutionally-based treatment.Hierarchical regression analyses, guided by an exploratory factor analysis, indicated that the quality of the therapeutic alliance was significantly predictive of indices of treatment outcome, producing medium to large effect sizes.ln particular, therapist empathy was significantly associated with most outcome indices, accounting for up to 28o/o of the variability in outcome.The findings were robust, and generally unaffected by ancillary variables such as risk level and treatment duration.Quantitative results were largely consistent with qualitative data, which indicated that participants attributed treatment success to factors associated with therapeutic style, instillation of hope, social corurectedness, and healthy skill development.Results are consistent with the general psychotherapy literature and suggestive of a fundamental role for the therapeutic alliance in the treatment of sexual offender populations.Implications are discussed with regard to the treatment of sexual offender populations.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".