Impact of a team-based versus individual clinician-focused training approach on primary healthcare professionals’ intention to have serious illness conversations with patients: A theory-informed process evaluation embedded within a cluster randomized trial
Bibliographic record
Abstract
BACKGROUND: Cluster randomized trials (cRTs) on the effectiveness of training programs face complex challenges when conducted in real-world settings. Process evaluations embedded within cRTs can help explain their results by exploring possible causal mechanisms impacting training effectiveness. OBJECTIVE: To conduct a process evaluation embedded within a cRT by comparing the impact of team-based vs. individual clinician-focused SICP training on primary healthcare professionals' (PHCPs) intention to have serious illness conversations with patients. METHODS: The cRT involved 45 primary care practices randomized into a team-based (intervention) or individual clinician-focused (comparator) training program and measured primary outcomes at the patient level: days at home and goals of care. To perform this theory-informed mixed-methods process evaluation embedded within the cRT, a different outcome was measured at the level of the PHCPs, namely, PHCPs' intention to have serious illness conversations with patients as measured with CPD-Reaction. Barriers and facilitators to implementing the conversations were identified through open-ended questions and analyzed using the Theoretical Domains Framework. The COM-B framework was used to triangulate data. Results were reported using the CONSORT and GRAMMS reporting guidelines. RESULTS: Of 535 PHCPs from 45 practices, 373 (69.7%) fully completed CPD-Reaction (30.8% between 25-34 years old; 78.0% women; 54.2% had a doctoral degree; 50.1% were primary care physicians). Mean intention scores for the team-based (n = 223) and individual clinician-focused arms (n = 150) were 5.97 (standard error (SE): 0.11) and 6.42 (SE: 0.13), respectively. Mean difference between arms was 0.0 (95% CI -0.29; 0.30; p = 0.99) after adjusting for age, education and profession. The team-based arm reported barriers with communication, workflow, and more discomfort in having serious illness conversations with patients. CONCLUSIONS: Team-based training did not outperform individual clinician-focused in influencing PHCPs' intention to have serious illness conversations. This process evaluation suggests that team-based training could improve intervention effectiveness by focusing on interprofessional communication, better organized workflows, and better support and training for non-clinician team members. Registration: ClinicalTrials.gov (ID: NCT03577002).
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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 | 0.088 | 0.108 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".