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Record W4404559615 · doi:10.2196/63376

Community Versus Facility-Based Services to Improve the Screening of Active Hepatitis C Virus Infection in Cambodia: The ANRS 12384 CAM-C Cluster Randomized Controlled Trial—Protocol for a Mixed Methods Study

2024· article· en· W4404559615 on OpenAlexvenueno aff
Émilie Mosnier, Olivier Ségéral, Neth Sansothy, Luis Sagaon‐Teyssier, Dyna Khuon, Chan Leakhena Phoeung, Sovatha Mam, Chhingsrean Chhay, Kimeang Heang, Jean‐Charles Duclos‐Vallée, Vonthanak Saphonn

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychological interventionReferralPopulationRandomized controlled trialPublic healthEnvironmental healthHepatitis CProtocol (science)Cluster randomised controlled trialFamily medicineImmunologyAlternative medicineNursingInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: In Cambodia, hepatitis C constitutes a significant public health challenge, particularly among older adults (>45 years) for whom prevalence is estimated to be 5%. To facilitate the elimination of hepatitis C among the general population, enhancing access to screening and treatment is imperative. In this regard, the evaluation of community-based screening programs emerges as a crucial step toward improving health care accessibility. OBJECTIVE: This study aims to assess the comparative efficacy of a community-based versus a facility-based approach in enhancing the uptake of hepatitis C antibody testing among the general population older than 40 years of age in Cambodia. METHODS: The CAM-C (Community Versus Facility-Based Services to Improve the Screening of Active Hepatitis C Virus Infection in Cambodia) study uses a cluster-randomized controlled trial design across two Cambodian provinces to compare community-based and facility-based hepatitis testing interventions. Sampling involves a multistage cluster approach, targeting individuals older than 40 years of age due to their higher prevalence and risk of chronic hepatitis complications. This study incorporates a qualitative analysis of acceptability and a cost-effectiveness comparison. Interventions include facility-based testing with subsequent referral and community-based testing with direct in-home assessments. Follow-up for positive cases involves comprehensive management and potential direct-acting antiviral treatment. This study aims to identify a significant increase in testing uptake, requiring the screening of 6000 individuals older than 40 years of age, facilitated by a structured sampling and intervention approach to minimize contamination risks. RESULTS: The final protocol including the quantitative, qualitative, and cost-effectiveness part of the study was registered and was approved in 2019 by the National Ethical Cambodian for Health Research. Inclusions were completed by mid-2024, with analyses starting in May 2024. CONCLUSIONS: Using a mixed methods approach that combines a robust methodology (cluster-randomized controlled trial) with a cost-effectiveness analysis and qualitative research, such a study should provide invaluable information to guide the Ministry of Health in its hepatitis C virus screening strategy and move toward elimination. TRIAL REGISTRATION: ClinicalTrials.gov NCT03992313; https://clinicaltrials.gov/study/NCT03992313. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63376.

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)0.024
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.024
Meta-epidemiology (narrow)0.0060.002
Meta-epidemiology (broad)0.0120.007
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0390.005

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 head0.263
GPT teacher head0.609
Teacher spread0.346 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations1
Published2024
Admission routes1
Has abstractyes

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