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Record W2953174619 · doi:10.1101/589051

Knowledge of Chagas disease in Latin American migrant population living in Japan and factors associated with knowledge level

2019· preprint· en· W2953174619 on OpenAlexaff
Inés María Iglesias-Rodríguez, Shusaku Mizukami, Đào Huy Mạnh, Thuan Minh Tieu, Hugo Alberto Justiniano, Sachio Miura, George Ito, Nguyen Tien Huy, Kenji Hirayama

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLatin AmericansDiseaseChagas diseasePopulationPsychologyGerontologyDemographyEnvironmental healthMedicinePolitical scienceSociologyImmunologyPathology

Abstract

fetched live from OpenAlex

Abstract Background Chagas disease (CD), typically confined to the Latin America (LA) region, is emerging as a global health problem. In Japan, as in the rest of world, the under-diagnose rate of CD is alarmingly high. Various studies have highlighted the importance of informed knowledge in the seeking behavior. Educational integrative activities, with consideration for socio-cultural factors, can help increase the knowledge of the participants. There has been no studies that analyze the difference in knowledge, before and after these educational activities. This study aimed to qualitatively and quantitatively investigate the knowledge, behavior and attitude toward CD among LA migrants in Japan and to evaluate the effectiveness of the community educational activity in increasing knowledge of CD. Methodology This cross-sectional study involved two questionnaires to analyze the knowledge of the LA migrant participants before and after the community activity (CA) in four cities in Japan (Oizumi, Suzuka, Hadano, and Nagoya). Principal Findings A total of 75 participants were enrolled, predominantly Bolivians from hyperendemic areas. The baseline knowledge of CD was low. However, most of them were familiar with the disease although less than 10% of them had been tested for CD before. Living in Japan for more than 10 years and previously being tested for CD were the factors associated with better knowledge. The conducted CA significantly improved the knowledge of the participants. They associated the term “Chagas” mostly with fear and concern. In contrast to other studies, the level of stigmatization was low. The barriers in care seeking behavior were language, migration process and difficulties to access to the healthcare system. Conclusion Educational activities with integrative approach are useful to increase knowledge of CD. The activity brings the possibility to explore not only the level of knowledge, but also to reveal the experience and to understand the needs of the people at risk. Author Summary Though the incident rate of Chagas disease (CD) has fallen, more than 7 million people are affected worldwide. The CD prevalence is under-estimated because just 1% of these affected people can access to the diagnosis and treatment. This situation is maintaining mainly for the lack of implication of socio-cultural factors in the interventions to decrease the burden of the disease. Educational activities with integral approach are useful to increase the knowledge of the people at risk. People that have being tested for CD before or living in Japan for more than 10 years have better knowledge about the disease, suggesting the importance of knowledge in the seeking behavior. The authors recommend the implementation of educational activities with integral approach as a strategy to improves the knowledge of Chagas disease among Latin America migrants in Japan.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.282
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2019
Admission routes1
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