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Record W6893631439 · doi:10.5281/zenodo.4009931

Health Seeking Behaviour among Adults in Malaysia During Times of Illness

2020· article· en· W6893631439 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Health careDescriptive statisticsDescriptive researchNational Health Interview SurveyPublic healthCluster (spacecraft)

Abstract

fetched live from OpenAlex

introduction Health-seeking behaviour influences healthcare services utilisation and self-care. Delay in timely and appropriate care when one is ill may lead to rise in morbidity and mortality. This study aimed to describe the health-seeking behaviour among adults in Malaysia with acute illness and oral health problems. Materials and Methods We analysed data of adults aged 18 years and over from the National Health and Morbidity Survey 2019. This cross-sectional survey used a complex study design with a two-stage stratified cluster sampling. Face-to-face interviews were conducted using a validated questionnaire. Descriptive analysis was performed using STATA Version 14.0 software. Results [Refer to Poster]. Discussion / Conclusion Our findings revealed that more than one-third of the adults did not seek care when ill despite a quarter of them perceiving care was needed. Promoting responsible self-medication is important(4) to empower people in self-care. Nevertheless, seeking appropriate care when needed is equally important.

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)0.001
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.268
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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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