Client involvement in psychotherapy: a literature review and evaluation of an involvement measure
Bibliographic record
Abstract
This thesis has three primary objectives and is organized into two separate but related manuscripts: In the first manuscript, entitled A Review of Client Involvement in Psychotherapy, the goal is to provide a thorough review of the involvement literature and to present a theoretical conceptualization of client involvement that could clarify our understanding of involvement. Specifically, it is argued that client involvement is composed of two facets, the internal and external processes which guide whether a client will participate in therapy. The goal of the second manuscript, which is entitled Factor Analysis and Construct Validity of a Measure of Client Involvement, is to evaluate a factor model of client involvement based on empirical data. The client involvement measure is the Comprehensive Scale of Psychotherapy Session Constructs Client Involvement subscale (CSPSC-CI; Eugster & Wampold, 1996), and it has not previously been independently evaluated. The psychometric properties of this measure were examined. Factor analysis of the CSPSC-CI revealed three interpretable factors: a Client factor, an Active Therapist factor, and a Disengaged Therapist factor. Discriminant and convergent construct validity was also evaluated; the results of the study provide preliminary support for the construct validity of the measure.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".