“I would have said ‘bad news’ but now I say ‘different news”: Mixed methods evaluation of a communication skills training for healthcare professionals in the first 1000 days of life
Bibliographic record
Abstract
BACKGROUND: Receiving a diagnosis of congenital anomalies in the first 1000 days of life can have significant implications for a family's emotional and mental wellbeing. We refer to this as different news. We evaluated a communications skills training to improve how healthcare professionals deliver different news using a train-the-trainer (Champions) model. METHODS: We recruited 22 healthcare professionals from 6 NHS trusts in England and trained them as Champions. They delivered 17 training sessions to healthcare professional colleagues. Data were collected on knowledge, skills and attitudes to different news communication using a bespoke questionnaire and the Self-Efficacy Scale (SE-12) at pre-training, straight after training and four weeks post-training. We conducted 19 interviews with healthcare professionals, four managers and eight parents. Data were analysed using Framework analysis guided by the Theoretical Domains Framework. RESULTS: A total of 204 healthcare professionals completed pre-training questionnaires, 187 completed post-training questionnaires immediately after training, and 109 completed the questionnaires four weeks post-training. A total of 179 healthcare professionals completed the SE-12 scale immediately after training and 102 completed it at four weeks follow-up. The training improved healthcare professionals' confidence and skills to deliver different news. There were statistically significant differences in confidence levels between pre-/post-training SE-12 scores in delivering different news. Scores were significantly higher post-training. The estimated difference in mean scores post-training was 18.3 (95% confidence interval 15.7-20.9 p < 0.001), and one-month post-training 16.9 (95% confidence interval 13.7-20.2; p < 0.001) more than three times larger than the difference in SE-12 in the validation sample. There was a statistically significant difference between SE-12 scores for the Champions and the healthcare professionals they trained. SE-12 scores were higher for Champions and their improvement from pre-training was greater. Overall, participants reported that the training provided the skills to structure different news conversations, use the right language and pace the provision of information and support. CONCLUSIONS: The results suggest that the training equips healthcare professionals to deliver different news to families sensitively and compassionately which can potentially prevent mental ill-health across the life course.
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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 | 0.049 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".