Educational interventions to train healthcare professionals in end-of-life communication: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Practicing healthcare professionals and graduates exiting training programs are often ill-equipped to facilitate important discussions about end-of-life care with patients and their families. We conducted a systematic review to evaluate the effectiveness of educational interventions aimed at providing healthcare professionals with training in end-of-life communication skills, compared to usual curriculum. METHODS: We searched MEDLINE, Embase, CINAHL, ERIC and the Cochrane Central Register of Controlled Trials from the date of inception to July 2014 for randomized control trials (RCT) and prospective observational studies of educational training interventions to train healthcare professionals in end-of-life communication skills. To be eligible, interventions had to provide communication skills training related to end-of-life decision making; other interventions (e.g. breaking bad news, providing palliation) were excluded. Our primary outcomes were self-efficacy, knowledge and end-of-life communication scores with standardized patient encounters. Sufficiently similar studies were pooled in a meta-analysis. The quality of evidence was assessed using GRADE. RESULTS: Of 5727 candidate articles, 20 studies (6 RCTs, 14 Observational) were included in this review. Compared to usual teaching, educational interventions to train healthcare professionals in end-of-life communication skills were associated with greater self-efficacy (8 studies, standardized mean difference [SMD] 0.57;95% confidence interval [CI] 0.40-0.75; P < 0.001; very low quality evidence), more knowledge (4 studies, SMD 0.76;95% CI 0.40-1.12; p < 0.001; low quality evidence), and improvements in communication scores (8 studies, SMD 0.69; 95% CI 0.41-0.96; p < 0.001; very low quality evidence). There was insufficient evidence to determine whether these educational interventions affect patient-level outcomes. CONCLUSION: Very low to low quality evidence suggests that end-of-life communication training may improve healthcare professionals' self-efficacy, knowledge, and EoL communication scores compared to usual teaching. Further studies comparing two active educational interventions are recommended with a continued focus on contextually relevant high-level outcomes. TRIAL REGISTRATION: PROSPERO CRD42014012913.
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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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".