The relationship between therapeutic engagement, cognitive errors, and coping action patterns: An exploratory study
Bibliographic record
Abstract
Abstract Aim: This exploratory study examined the relationship between clients’ involvement in therapy and their cognitive errors (CE) and coping action patterns (CAP). Method: Therapy sessions from N = 26 clients were rated for CE and CP using the CE and CAP methods. Client involvement was measured with the Positive and Negative Affect Schedule, as well as the . Results: The CEs’ ‘magnification of the negative or minimisation of the positive’ and ‘labelling’ were associated with measures of affective therapeutic engagement. The coping styles ‘negotiation’, ‘opposition’, ‘submission’, ‘isolation’, ‘support seeking’, ‘information seeking’, ‘delegation’, and ‘escape’ were found to be associated with affective and behavioural dimensions of therapeutic involvement. Conclusions: These findings provide preliminary supporting evidence that CE and CP are related to the extent to which clients engage in the work of therapy. Implications for researchers and therapists 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".