Development, Implementation, and Process Evaluation of Bukhali: An Intervention from Preconception to Early Childhood
Bibliographic record
Abstract
Abstract The Healthy Life Trajectories Initiative, an international consortium developed in partnership with the World Health Organization, is addressing childhood obesity from a life-course perspective. It hypothesises that an integrated complex intervention from preconception, through pregnancy, infancy and early childhood, will reduce childhood adiposity and non-communicable disease risk, and improve child development. As part of the Healthy Life Trajectories Initiative in South Africa, the Bukhali randomised controlled trial is being conducted with 18–28-year-old women in Soweto, where young women face numerous challenges to their physical and mental health. The aims of this paper were to describe the intervention development process (including adaptations), intervention components, and process evaluation; and to highlight key lessons learned. Intervention materials have been developed according to the life-course stages: preconception (Bukhali), pregnancy (Bukhali Baby), infancy (Bukhali Nana; birth—2 years), and early childhood (Bukhali Mntwana, 2–5 years). The intervention is delivered by community health workers, and includes the provision of health literacy resources, multi-micronutrient supplementation, in-person health screening, services and referral, nutrition risk support, SMS-reminders and telephonic contacts to assist with behaviour change goals. A key adaption is the incorporation of principles of trauma-information care, given the mental health challenges faced by participants. The Bukhali process evaluation is focussing on context, implementation and mechanisms of impact, using a mixed methods approach. Although the completion of the trial is still a number of years away, the documentation of the intervention development process and process evaluation of the trial can provide lessons for the development, implementation, and evaluation of such complex life-course trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".