Using the Socioecological Model to Explore Barriers to Health Care Provision in Underserved Communities in the Philippines: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The Philippines' primary care is delivered via local health centers called barangay health centers (BHCs). Barangays are the most local government units in the Philippines. Designed to promote and prevent disease via basic health care, these BHCs are staffed mainly by barangay health workers (BHWs). However, there has been limited research on the social and environmental factors affecting underserved communities' access to health care in underserved areas of the Philippines. Given the importance of BHCs in disease prevention and health promotion, it is necessary to identify obstacles to providing their services and initiatives. OBJECTIVE: This study aimed to explore multilevel barriers to accessing and providing basic health care in BHCs. METHODS: We used a qualitative approach and the socioecological model as a framework to investigate the multilevel barriers affecting basic health care provision. A total of 18 BHWs from 6 BHCs nationwide participated in focus group interviews. Traditional thematic content analysis was used to analyze the focus group data. After that, we conducted individual semistructured interviews with 4 public health nurses who supervised the BHWs to confirm findings from focus groups as a data source triangulation. The final stage of thematic analysis was conducted using the socioecological model as the framework. RESULTS: Findings revealed various barriers at the individual (lack of staff motivation and misperceptions of health care needs), interpersonal (lack of training, unprofessional behaviors, and lack of communication), institutional (lack of human resources for health, lack of accountability of staff, unrealistic expectations, and lack of physical space or supplies), community (lack of community support, lack of availability of appropriate resources, and belief in traditional healers), and policy (lack of uniformity in policies and resources and lack of a functional infrastructure) levels. CONCLUSIONS: Examining individual-, interpersonal-, institutional-, community-, and policy-level determinants that affect BHCs can inform community-based health promotion interventions for the country's underserved communities. Given the multidimensional barriers identified, a comprehensive program must be developed and implemented in collaboration with health care providers, community leaders, local and regional health care department representatives, and policy makers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".