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Record W3087168243 · doi:10.9734/jpri/2020/v32i2230777

TB Infection Control in TB/HIV Settings in Cross River State, Nigeria: Policy Vs Practice

2020· article· en· W3087168243 on OpenAlexaff
Michael Odo, Kingsley Ochei, Emmanuel Ifeanyi Obeagu, Barinaadaa Afirima, Ugobo Emmanuel Eteng, Mabel Ikpeme, Jonah Offor Bassey, Andrew Ogar Paul

Bibliographic record

VenueJournal of Pharmaceutical Research International · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsMedicineInfection controlEnvironmental healthHuman immunodeficiency virus (HIV)Health carePublic healthPopulationFamily medicineNursingSurgeryEconomic growth

Abstract

fetched live from OpenAlex

TB and HIV remain a dangerous duo of significant public health concern across the globe. Both diseases require significant community and health system activities to be successfully managed. TB infection control is an important disease prevention strategy among the general population and among people living with HIV, in cost and management. We undertook to assess the situation of TB infection control at three levels of health care in Cross River State of Nigeria. A qualitative method was used to assess TB infection control (TBIC) knowledge, attitudes, and practices of the health care workers at each of the purposefully selected facilities using a semi-structured questionnaire - University of Calabar Teaching hospital, Calabar; Infectious disease Hospital, Calabar and primary Health Centre, Calabar Municipal, between 15th to 31st November, 2019 in the first phase, and an extension to February, 2020 due to delayed ethical clearance from the University of Calabar Teaching hospital. Data was collected and entered on an excel template and cleaned by trained data entry clerks. Charts and color diagrams were developed to compare specific descriptive data. There is wide variation between the written policies of TB infection control and the practices among health workers. Even though there are strong administrative protocols to support TB infection control in the higher levels of care, it is better practiced in the lower level PHC where the protocols were not spelt out.

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)0.004
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.098
GPT teacher head0.547
Teacher spread0.449 · 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.

Study designNot applicable
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

Citations25
Published2020
Admission routes1
Has abstractyes

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