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Record W2982194199 · doi:10.2991/jegh.k.190929.001

What Constitutes Health Care Seeking Pathway of TB Patients: A Qualitative Study in Rural Bangladesh

2019· article· en· W2982194199 on OpenAlexaff
Tanvir Shatil, Nusrat Khan, Fakir Md Yunus, Anita Sharif Chowdhury, Saifur Reza, Shayla Islam, Akramul Islam, Mahfuzar Rahman

Bibliographic record

VenueJournal of Epidemiology and Global Health · 2019
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Saskatchewan
FundersGlobal Fund to Fight AIDS, Tuberculosis and Malaria
KeywordsMedicineNonprobability samplingSnowball samplingQualitative researchTuberculosisPsychological interventionPublic healthMilestoneSocial determinants of healthHealth careSocioeconomic statusFamily medicineNursingEnvironmental healthPopulationEconomic growthPathology

Abstract

fetched live from OpenAlex

Given the targeted 4-5% annual reduction of tuberculosis (TB) cure cases to reach the "End TB Strategy" by 2020 milestone globally set by WHO, exploration of TB health seeking behavior is warranted for insightful understanding. This qualitative study aims to provide an account of the social, cultural, and socioeconomic breadth of TB cases in Bangladesh. We carried out a total of 32 In-depth Interviews (IDIs) and 16 Key Informant Interviews (KIIs) in both rural and urban areas of Bangladesh. We covered both BRAC [a multinational Non-governmental Organization (NGO)] and non-BRAC (other NGOs) TB program coverage areas to get an insight. We used purposive sampling strategy and initially followed "snowball sampling technique" to identify TB patients. Neuman's three-phase coding system was adopted to analyze the qualitative data. Underestimation of TB knowledge and lack of awareness among the TB patients along with the opinions from their family members played key roles on their TB health seeking behavior. Quick decision on the treatment issue was observed once the diagnosis was confirmed; however, difficulties were in accepting the diseases. Nevertheless, individual beliefs, intrinsic ideologies, financial abilities, and cultural and social beliefs on TB were closely inter-connected with the "social perception" of TB that eventually influenced the care seeking pathways of TB patients in various ways. Individual and community level public health interventions could increase early diagnosis; therefore, reduce recurrent TB.

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)0.010
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.464
Teacher spread0.416 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2019
Admission routes1
Has abstractyes

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