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Contribution of media on knowledge generation about tuberculosis in Palpa district, Nepal

2018· article· en· W2898559917 on OpenAlexaboutno aff
Deelip Kumar Karki, Birendra Kumar Singh, Pravin Kumar Khanal

Bibliographic record

VenueInternational Journal of Community Medicine and Public Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDiverse Scientific Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperTuberculosisQuarter (Canadian coin)MedicineTransmission (telecommunications)Mass mediaFamily medicineAdvertisingGeographyTelecommunicationsPathology

Abstract

fetched live from OpenAlex

Background: Media is the means of communication, as radio, television and newspaper that reach or influence people widely. It is a tool for the transfer of information and ideas to audiences. The media plays the crucial role in instructing, motivating and guiding the public for control of tuberculosis. The objectives of the study were to study the knowledge and the source of information regarding tuberculosis.Methods: A cross sectional study was conducted whereas multistage sampling was adopted.Results: Around half of respondents (46.5%) were 15-24 years of age and 63.9 per cent were female. Overwhelming number of the respondents (95.1%) had radio and more than one fourth (76.4%) had television at home. More than three quarter (88.9%) respondents said droplet infection is the mode of transmission of tuberculosis but 11.1 per cent said sharing common utensil. 97.2 per cent respondents had good behaviour towards TB patient. In respect to knowledge score, 18.1 per cent had high level of knowledge followed by 56.2 per cent had medium and 25.7 per cent had low level. Fifty per cent respondents said television, 46.5 percent said radio were the source of information for tuberculosis.Conclusions: The study found that majority of the respondents had satisfactory knowledge level about tuberculosis. The results exemplify the contribution of media on improving TB related knowledge. Most of the respondents ranked media, i.e., radio and television is the number one source of information.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.276
GPT teacher head0.523
Teacher spread0.247 · 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
Published2018
Admission routes1
Has abstractyes

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