A Survey on Differences in Implementing Evidence-Based Practice According to Five Psychotherapist Variables
Bibliographic record
Abstract
Given the divide between research and practice, there has been an increased focus on evidence-based practice (EBP) in psychology. EBP has been defined as the integration of three main components during clinical decision-making: (a) best available research evidence, (b) clinical expertise, and (c) client characteristics, cultures, and treatment preferences. However, little is known about the self-ratings of implementing EBP or its components among psychotherapy providers. Secondary data analyses of a survey of Canadian psychotherapy providers (Middleton et al., 2020) investigated differences in providers’ self-ratings of implementing EBP according to five psychotherapist variables. These psychotherapist variables included the primary therapeutic approach, the number of years of professional experience, the primary setting of practice, the level of education, and the professional capacity of practice. Results indicated significant results for many psychotherapist variables. Among other findings, while psychotherapy providers who were oriented primarily toward cognitive and/or behavioural approaches had significantly higher self-ratings of implementing EBP than did those with a psychoanalytic/psychodynamic approach, providers with a master’s degree had significantly lower self-ratings than did those with a Ph.D. or with postdoctoral training. Findings are discussed in relation to educational, research, and training initiatives in EBP.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".