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Record W2733546598 · doi:10.1093/heapol/czx074

Migrant tuberculosis patient needs and health system response along the Thailand–Myanmar border

2017· article· en· W2733546598 on OpenAlexafffund
Naomi Tschirhart, François Nosten, Angel M. Foster

Bibliographic record

VenueHealth Policy and Planning · 2017
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Ottawa
FundersUniversity of OxfordOntario Ministry of Health and Long-Term CareWellcomeUniversity of OttawaInternational Development Research CentreWellcome Trust
KeywordsPsychological interventionFocus groupTuberculosisBusinessEconomic growthHealth careMedicineEnvironmental healthNursingMarketing

Abstract

fetched live from OpenAlex

This article aims to identify how the health system in Tak province, Thailand has responded to migrants' barriers to tuberculosis (TB) treatment. Our qualitatively driven multi-methods project utilized focus group discussions, key informant interviews, and a survey of community health volunteers to collect data in 2014 from multiple perspectives. Migrants identified legal status and transportation difficulties as the primary barriers to seeking TB treatment. Lack of financial resources and difficulties locating appropriate and affordable health services in other Thai provinces or across the border in Myanmar further contributed to migrants' challenges. TB care providers responded to barriers to treatment by bringing care out into the community, enhancing patient mobility, providing supportive services, and reaching out to potential patients. Interventions to improve migrant access and adherence to TB treatment necessarily extend outside of the health system and require significant resources to expand equitable access to treatment. Although this research is specific to the Thailand-Myanmar border, we anticipate that the findings will contribute to broader conversations around the inputs that are necessary to address disparities and inequities. Our study suggests that migrants need to be provided with resources that help stabilize their financial situation and overcome difficulties associated with their legal status in order to access and continue TB treatment.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.435
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2017
Admission routes2
Has abstractyes

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