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Record W955694826

Healthcare-Seeking Behaviour in Anyigba, North-Central, Nigeria

2009· article· en· W955694826 on OpenAlexaboutno aff
M. Akande Tanimola, Julius Olugbenga Owoyemi

Bibliographic record

VenueResearch Journal of Medical Sciences · 2009
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsNigeriansMedicineHealth carePublic healthQuarter (Canadian coin)PopulationEnvironmental healthBenin cityHealth facilitySocioeconomicsFamily medicineNursingEconomic growthHealth servicesTeaching hospital
DOInot available

Abstract

fetched live from OpenAlex

2 Abstract: This study of health seeking behaviour of household members in Anyigba, North Central Nigeria. Total 333 respondents were randomly selected and self-administered structured questionnaires were used to collect data on household health seeking behaviour. Descriptive and inferential methods were used to analyze the data. The mean age of respondents was 39.65±11.12 years, >3 quarter were married. The mean, median and mode delay time before seeking treatment were 9.89±46.03, 3.0 and 2.0 days, respectively. The major reason for the delay in seeking treatment as reported by 56.9% was the thought that they would get over the ailment without treatment and 25.4% of respondents delayed because of lack of money for treatment. Less than half (44.7%) of those who sought treatment patronized public health facility. The study showed that significantly higher proportion of the low income than high income people patronize drug sellers for treatment and higher proportion of the high income people than low income patronize private health facilities. Delay in receiving care for health problems can be costly and dangerous, it is necessary to increase awareness and to health educate people on this problem. Generally, more people in the study population patronize private health facilities, people's confidence in public health facilities need to be improved in Nigeria and should be made more accessible to people for improvement in the health status of Nigerians.

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)0.008
metaresearch head score (Gemma)0.001
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 score0.141
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
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 science0.0010.000
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 head0.113
GPT teacher head0.472
Teacher spread0.359 · 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

Citations31
Published2009
Admission routes1
Has abstractyes

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