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Record W2524621393 · doi:10.1093/ajcp/aqw138

Effect of On-Site Support on Laboratory Practice for Human Immunodeficiency Virus, Tuberculosis, and Malaria Testing

2016· article· en· W2524621393 on OpenAlexaff
Sarah Burnett, Martin Mbonye, Robert K. Martin, Allan Ronald, Stella Zawedde‐Muyanja, Kelly Willis, Robert Colebunders, Yukari C. Manabe, Marcia R. Weaver

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2016
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMalariaSputumMedicineTuberculosisHuman immunodeficiency virus (HIV)Medical laboratoryImmunologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the effect of on-site support in improving human immunodeficiency virus (HIV) rapid testing, tuberculosis (TB) sputum microscopy, and malaria microscopy among laboratory staff in a low-resource setting. METHODS: This cluster randomized trial was conducted at 36 health facilities in Uganda. From April to December 2010, laboratory staff at 18 facilities participated in monthly on-site visits, and 18 served as control facilities. After intervention, 128 laboratory staff were observed performing 587 laboratory tests across three diseases: HIV rapid testing, TB sputum microscopy, and malaria microscopy. Outcomes were the proportion of laboratory procedures correctly completed for the three laboratory tests. RESULTS: Laboratory staff in the intervention arm performed significantly better than the control arm in correctly completing laboratory procedures for all three laboratory tests, with an adjusted relative risk (95% confidence interval) of 1.18 (1.10-1.26) for HIV rapid testing, 1.29 (1.21-1.40) for TB sputum microscopy, and 1.19 (1.11-1.27) for malaria microscopy. CONCLUSIONS: On-site support significantly improved laboratory practices in conducting HIV rapid testing, TB sputum microscopy, and malaria microscopy. It could be an effective method for improving laboratory practice, without taking limited laboratory staff away from health facilities for training.

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)0.011
metaresearch head score (Gemma)0.070
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.070
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.457
Teacher spread0.411 · 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 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

Citations8
Published2016
Admission routes1
Has abstractyes

Explore more

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