Comparison of the sustainability of the impact of team-based versus individual clinician-focused training of primary care professionals in serious illness conversations on caregiver burden of care: a secondary analysis of a cluster randomized trial
Bibliographic record
Abstract
BACKGROUND: Training health professionals in serious illness conversations is important for patients with serious illnesses and for their caregivers. However, most training focuses on individual clinicians rather than on healthcare teams. Caregivers of their patients are highly sensitive to changes in communication dynamics in the healthcare setting. We aimed to compare the impact of a team-based training program in serious illness conversations with that of an individual clinician-focused training program on the burden of care of caregivers of patients with serious illnesses, and the sustainability of these impacts over time. METHODS: We performed a secondary analysis of caregivers’ data from a preliminary cluster randomized trial in the USA and Canada in which 42 primary care clinics were randomized to an interprofessional team-based training arm (intervention) or an individual clinician-focused training arm (control). Seriously ill patients who had had a serious illness conversation with the trained clinicians were asked to refer a caregiver. We used the Zarit Burden Interview (range: 0–48) to assess caregiver burden immediately after the serious illness conversation (T1), six months later (T2) and 12 months later (T3). Statistical analyses using a linear mixed model were performed to compare caregiver burden between the two arms at the three times. RESULTS: We included 192 caregivers from 42 primary care clinics. Most were female (67.8%); aged 65–74 (28.6%). The mean caregiver burden scores were low, and similar in both the arms at the three times. The difference in mean burden between the two study arms was 1.05 (95% CI -1.47 to 3.59; p = 0.40), -0.24 (95% CI -2.57 to 2.08; p = 0.82), and 0.09 (95% CI -2.61 to 2.81; p = 0.94) at T1, T2 and T3 respectively. The p-value of the interaction term between study arm and time was p = 0.47. Mean difference between arms after performing a model with time effect and after adjusting was 0.90 (95% CI -0.76 to 2.57; p = 0.28). Various other factors such as caregivers feeling anxious or depressed were associated with caregiver burden. CONCLUSION: Analysis showed that there was no difference between perceived caregiver burden after the interprofessional team-based training approach and after the individual clinician-focused training approach. Our study did however underline the importance of recognizing other factors influencing caregiver well-being. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NCT03577002).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".