Specialized Nutritious Food Combined With Cash Transfers and Social and Behavior Change Communication to Prevent Stunting Among Children Aged 6 to 23 Months in Pakistan: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: In Pakistan, the prevalence of stunting in children younger than 5 years has remained above global critical levels over the past two decades, with the stunting rate being 40.2% in 2018. Children living in rural areas and in the poorest households suffer the most from stunting across the country-43.2% in rural areas and 51.4% in the lowest wealth quintile. As a continuing public health concern, it is essential that stunting prevention is a national priority in order to ensure human capital development, especially among the poorest households. OBJECTIVE: The primary objective of this study is to determine the effect of a medium quantity of a lipid-based nutrient supplement (LNS) combined with unconditional cash transfers and social and behavior change communication (SBCC) on reduction of stunting in children aged 6 to 23 months. METHODS: A 5-arm cluster randomized controlled trial will be conducted in the district of Rahim Yar Khan in Punjab, Pakistan. The intervention packages will be (1) cash only, (2) cash with LNS, (3) cash with SBCC, and (4) cash with SBCC and LNS. The control arm will receive routine standard of care. We will enroll children at 6 months of age and follow up on a monthly basis up to 24 months of age. A total of 2000 children, 400 in each arm, will be enrolled to detect a 20% reduction in the prevalence of stunting among children aged 24 months. Length, weight, food intake, compliance to interventions, morbidities, and other relevant data will be collected at enrollment and on a monthly basis over the period of 18 months. The process evaluation will assess acceptability of the interventions and potential barriers to implementation through focus group discussions and in-depth interviews with the target population and relevant stakeholders. Furthermore, a cost analysis will be conducted to assess the cost-effectiveness of each intervention package. RESULTS: The study protocol was approved by the Ethics Review Committee of Aga Khan University in Pakistan on January 4, 2017. Data collection began in May 2017 and was completed in July 2019. Data analyses are yet to be completed. This study will explore the effectiveness of intervention packages comprised of cash transfers from Benazir Income Support Programme with or without additional LNS and SBCC in preventing childhood stunting. We expect the results to be published in peer-reviewed journals by autumn of 2020. CONCLUSIONS: The findings of this trial will provide robust evidence as to which intervention packages can have significant effects on linear growth of children and design effective intervention packages to prevent stunting in children aged 6 to 23 months. TRIAL REGISTRATION: ClinicalTrials.gov NCT03299218; https://clinicaltrials.gov/ct2/show/NCT03299218. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/19001.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.064 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".