Teaching home-visitors to support responsive caregiving: A cluster randomized controlled trial of an online professional development program in Brazil
Bibliographic record
Abstract
Background Home-visiting programs are a common and effective public health approach to promoting parent and child well-being, including in low-and middle-income countries.The World Health Organization and UNICEF have identified responsive caregiving as one key component of the nurturing care children need to survive and thrive.Nonetheless, the importance of responsive caregiving and how to coach it is often overlooked in trainings for staff in home-visiting programs.Methods To determine whether it is possible to enhance home-visitors' understanding of responsive caregiving and how to coach it, we conducted a cluster randomized controlled trial with 181 staff working in Brazil's national home-visiting program.We used a computerized random number generator to randomly assign half of participants to take an online professional development course about responsive caregiving immediately and the other half to a waitlist.Individuals assessing outcome data were blind to group assignment. ResultsCompared to those in the control group (N = 90, both randomized and analyzed), participants assigned to take the course (N = 91, both randomized and analyzed) were more knowledgeable about responsivity (Cohen's d = 0.64, 95% Confidence Interval (CI) = 0.34, 0.94) and its importance for children's socioemotional (odds ratio (OR) = 1.88, 95% CI = 1.00, 3.50) and cognitive (OR = 2.57, 95% CI = 1.15, 5.71) development, better able to identify responsive parental behaviors in videotaped interactions (d = 1.86, 95% CI = 1.51, 2.21), and suggested more effective strategies for coaching parents on responsivity (d = 0.51, 95% CI = 0.21, 0.80) and tracking goal implementation (OR = 3.20, 95% CI = 1.28, 7.99).There were no significant changes in participants' tendency to encourage goal setting and reflection, or their perspective-taking skills.Participants were very satisfied with the course content and mode of delivery and there was no drop-out from the program.Conclusions A short, online professional development program created moderate to large improvements in home-visitors' knowledge and intended coaching practices.This suggests that such programs are feasible, even in low-income and rural areas, and provide a low-cost, scalable option for possibly maximizing the impact of home-visiting programs -particularly with regard to parental responsivity, and in turn, child outcomes.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".