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Record W4395681576 · doi:10.30574/wjarr.2024.22.1.1233

Screening for risk factors for type 2 diabetes mellitus using the Canadian Diabetes Risk Questionnaire (CANRISK) in the East Java Provincial Health Service, Indonesia

2024· article· en· W4395681576 on OpenAlexaboutno aff
Fifta Hayu Ananda, Asma Azzahra, Izzah Nur Shabrina

Bibliographic record

VenueWorld Journal of Advanced Research and Reviews · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetes mellitusMedicineJavaType 2 diabetesService (business)Environmental healthType 2 Diabetes MellitusFamily medicineGerontologyBusinessEndocrinologyComputer science

Abstract

fetched live from OpenAlex

Diabetes Mellitus remains a serious and growing global challenge for public health. Early identification of cases prevents delays in treating diabetes mellitus, which often causes various complications in the body. Diabetes Mellitus screening includes anamnesis for family and personal history of the disease, measurement of height, weight, abdominal circumference, blood pressure examination, and examination of sugar levels. One instrument that can be used to assess the risk of developing type 2 diabetes mellitus is the Canadian Diabetes Risk Questionnaire (CANRISK). The aim of this research is to find out the characteristics of respondents and the risk categories of respondents suffering from type 2 diabetes mellitus in the next 10 years using CANRISK. This research uses quantitative methods. Based on the type of research, this research uses descriptive observational research. The research design used was cross sectional. The results showed that 78% of respondents had a low-moderate risk of developing type 2 DM, 6% had a high risk of developing type 2 DM, and 16% had a very high risk of developing type 2 DM. The conclusion of this study was that the risk factors for developing Type 2 DM 2 are age, BMI, waist circumference, physical activity habits, vegetable and fruit consumption habits, history of high blood pressure and high blood sugar, history of giving birth to a baby more than 4.1 kg, family history of diabetes, parents' ethnic group, and level of education.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.096
GPT teacher head0.389
Teacher spread0.293 · 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 designOther design
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of Advanced Research and ReviewsSame topicDiabetes, Cardiovascular Risks, and LipoproteinsFrench-language works237,207