Autonomous and controlled motivation for interpersonal therapy for depression: Between-therapists and within-therapist effects.
Bibliographic record
Abstract
Differences between therapists in the average outcomes their patients achieve are well documented, and researchers have begun to try to explain such differences (Baldwin & Imel, 2013). Guided by Self-Determination Theory (Deci & Ryan, 2000), we examined the effects on outcome of differences between therapists in their patients' average levels of autonomous and controlled motivation for treatment, as well as the effects of differences among the patients within each therapist's caseload. Between and within-therapist differences in the SDT construct of perceived relational support were explored as predictors of patients' motivation. Nineteen therapists treated 63 patients in an outpatient clinic providing manualized interpersonal therapy (IPT) for depression. Patients completed the BDI-II at pretreatment, posttreatment, and each treatment session. The Impact Message Inventory was administered at the third session and scored for perceived therapist friendliness, a core element of relational support. We created between-therapists (therapist-level) scores by averaging over the patients in each therapist's caseload; within-therapist (patient-level) scores were computed by centering within each therapist's caseload. As expected, better outcome was predicted by higher levels of therapist-level and patient-level autonomous motivation and by lower levels of therapist-level and patient-level controlled motivation. In turn, autonomous motivation was predicted by therapist-level and patient-level relational support (friendliness). Controlled motivation was predicted solely by patient self-critical perfectionism. The results extend past work by demonstrating that both between-therapists and within-therapist differences in motivation predict outcome. As well, the results suggest that therapists should monitor their interpersonal impact so as to provide relational support. (PsycINFO Database Record
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".