Healthcare Access Experiences Among Indigenous Women in Northern Rural Thailand: A Focused Ethnographic Study
Bibliographic record
Abstract
INTRODUCTION: Persistent inequities in health and access to healthcare services for indigenous women living in Thailand remain a significant challenge. This study provides narrative accounts of Indigenous women's experiences accessing healthcare in northern and rural Thailand and explores the complexity of culture and its interaction with multiple intersecting influences on health behaviours. METHODS: A focused ethnographic study was conducted to understand and describe the culture of health behaviors and other cultural phenomena. We recruited 21 female participants aged 20-41 years between March and April of 2017. In-depth semi-structured interviews conducted in Thai were used to explore the experiences of the participants living in a northern rural village. Data analysis was informed and guided by Roper and Shapira's framework for ethnographic analysis. RESULTS: Seven themes presented across three phases of experience (pre-access, making choices, and encountering difficulties) revealed an in-depth understanding of the Indigenous women's lives, the broader sociocultural context in which they lived, and the challenges they faced when accessing healthcare. Analysis of data showed that the participants did not have equal access to healthcare and often disproportionately experienced discriminatory practices and negative attitudes of mainstream healthcare providers. CONCLUSIONS: This is the only study to date that discusses healthcare access challenges experienced by Indigenous women living in a northern rural Thai village. There is an urgent need to focus on citizenship, employment, and general health conditions; gender, familial, and labor roles; specific health conditions, wellness, and cultural practices; the seeking of healthcare services; healthcare provider relationships; the ability to access needed care; and optimization of self-care. Future efforts to improve healthcare access and reduce disease burden might benefit from these findings and allow for the development of more effective strategies, programs, and policies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".