Children’s health-related experiences in India: A scoping review
Bibliographic record
Abstract
Background & Objectives: The perspectives of children have becoming increasingly emphasized in healthcare research and practice in order to facilitate children’s inclusion, participation, and decision-making in matters related to their health. In India, however, little is known about children’s views regarding their health despite the various health challenges and ethical concerns they may face, such as poverty, malnutrition, and gender inequalities. The aim of this scoping review is to explore children’s health-related experiences from their own perspectives in India from 2000 to 2020. Methods: Five online databases were searched. Three independent reviewers screened articles for inclusion. Included texts were analyzed using thematic synthesis, which involved extracting and descriptively coding data, categorizing/grouping codes by similar topics, and comparing and contrasting topics to generate descriptive themes. The scoping review was reported using the PRISMA-ScR checklist. Results: Fifty-two articles were included, and five descriptive themes were identified. The articles typically overlapped in themes, which related to children’s health-related experiences (n=38), emotions (n=19), and knowledge (n=15); the impact of illness on children’s lives (n=41); and children’s ability to communicate their needs (n=12). Interpretation & Conclusions: We identified the need to tailor research designs to better elicit children’s perspectives and provide comprehensive health education for children and families in India. This scoping review helped to highlight gaps in healthcare policy, practice, and research, providing a starting point for more focused investigation into children’s health-related experiences in India.
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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.021 | 0.028 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".