Listening to Caregivers: Narratives of Health Seeking for Children Under Five with Pneumonia and Diarrhea: Insights from the NIGRAAN Trial in Pakistan
Bibliographic record
Abstract
Abstract Background Access to health services is an important way to reduce child mortality and is influenced by health-seeking behaviors of caregivers. There are numerous contextual factors that affect health-seeking behaviors, such as distance to health services, transportation, treatment cost, caregiver access to household finances, perceived quality of available health providers, availability and comprehension of health information, social and religious norms (including gender-based mobility), and perceived severity of illness. Objective The objective of this study (embedded in a larger trial called Nigraan) was to gather caregiver narratives in order to develop a comprehensive understanding of the context and process of care giving for children under five with pneumonia and diarrhea, in order to highlight the complexities and dynamics of health seeking in rural Sindh, Pakistan. Methods This study used a narrative interview approach gathering information in the form of stories from care givers of children under five with pneumonia and diarrhea. Twenty caregivers from 11 households participated in this exercise. All data collection was conducted privately in participants’ homes.Results The role of joint family households is integral in health seeking for pneumonia and diarrhea in children under five. Elders and female relatives, especially the child’s paternal grandmother, are an important and trusted source of knowledge regarding child sickness in the household. Furthermore, practice of home remedies is inherited from mother-in-law and older sisters-in-law in the household, and oftentimes their recommendations are taken as authority. Caregivers were generally dissatisfied with doctors in public sector who provide free consultation and associated higher quality care with private doctors who charge more and had shorter waiting times. Joint family households were generally observed to increase the support available to address the financial and practical considerations of health seeking and implementing treatment plans for pneumonia and diarrhea. Conclusions Policy and research on community-based health programs and interventions would be more comprehensive if a health education intervention considered the context of decision making and social influences at the household level rather than focusing on individual caregivers.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".