Development and Implementation of Liposomal Encapsulated Micronutrient Fortified Body Oil Intervention for Infant Massage: An Innovative Concept to Prevent Micronutrient Deficiencies in Children
Bibliographic record
Abstract
Indian communities have the ancient cultural practice of gentle oil massage for infants which has been shown to play a beneficial role in neuro-motor development. The concept of incorporating nanosized liposomes of micronutrients (i.e., iron, folate, vitamin B12, and vitamin D) in the body oil leverages this practice for transdermal supplementation of essential micro-nutrients. This paper describes the experience of developing an intervention in the form of body oil containing nanosized liposomes of iron and micro-nutrients built on the social context of infant oil massage using a theory of change approach. The process of development of the intervention has been covered into stages such as design, decide and implement. The design phase describes how the idea of nanosized liposomal encapsulated micronutrient fortified (LMF) body oil was conceptualized and how its feasibility was assessed through initial formative work in the community. The decide phase describes steps involved while scaling up technology from laboratory to community level. The implementation phase describes processes while implementing the intervention of LMF oil in a community-based randomized controlled study. Overall, the theory of change approach helps to outline the various intermediate steps and challenges while translating novel technologies for transdermal nutrient fortification to community level. In our experience, adaptation in the technology for large scale up, formative work and pilot testing of innovation at community level were important processes that helped in shaping the innovation. Meticulous mapping of these processes and experiences can be a useful guide for translating similar innovations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".