Science-Informed Practice in Canadian Professional Psychology: Factors Associated with Clinicians' Scientific Skills and Attitudes
Bibliographic record
Abstract
Foundational to professional psychology, the scientist-practitioner model encourages a scientific approach to practice, strengthening clinical work with the best available research evidence. However, troubling research shows inadequate training in research and science, and low engagement with science-based practice among psychologists. Considering the myriad ways that unscientific practice can worsen outcomes for clients, the extent to which psychologists are scientifically literate and research-informed impacts responsible client care. Despite the rationale and codified ethical imperatives for science-informed practice, there appears to be little research on this topic among Canadian psychologists. The present research reviews the rationale for and components of science-informed practice and presents a self-developed survey instrument for measuring critical thinking skills, science-informed practice attitudes, and clinician demographics. Three hundred and thirty-one psychologists and counsellors from across Canada completed the survey. Training level, training type, and licensure type were associated with science-informed practice attitudes and critical thinking scores. Being a psychologist, being trained in clinical psychology, and having a doctorate all predicted higher critical thinking and attitude scores. Scientific attitude was the strongest predictor of critical thinking, followed by licensure type (i.e., psychologist or counsellor). Item-level results indicated various strengths and weaknesses in Canadian clinicians’ endorsements of science-informed practice attitude and embodiment of science-informed practice skills and knowledge. Professional identity among counsellors and psychologists may be less clear than often posited and may contain tensions that work against a robust scientific foundation. Results from this research have implications for clients, clinicians, training programs, regulatory bodies, and the public at large. This research calls for stronger ongoing research to assess the scientific literacy of Canadian clinicians. Moreover, this research encourages improvement in the robustness of training and regulatory mechanisms for producing science-informed professionals.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".