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Record W3037449640 · doi:10.2196/19100

Design and Implementation of a Multilevel Intervention to Reduce Hepatitis C Transmission Among Men Who Have Sex With Men in Amsterdam: Co-Creation and Usability Study

2020· article· en· W3037449640 on OpenAlexvenueno aff
Tamara Prinsenberg, Paul Zantkuijl, Wim Zuilhof, Udi Davidovich, Janke Schinkel, Maria Prins, Marc van der Valk

Bibliographic record

VenueJMIR Formative Research · 2020
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
FundersCilagGilead Sciences
KeywordsPsychological interventionMedicineStakeholderPopulationUsabilityIntervention (counseling)Context (archaeology)Environmental healthNursingPolitical scienceComputer sciencePublic relations

Abstract

fetched live from OpenAlex

BACKGROUND: In the Netherlands, transmission of hepatitis C virus (HCV) occurs primarily among men who have sex with men (MSM). Early HCV testing of at-risk MSM and immediate initiation of treatment will prevent onward transmission, but this may not be sufficient to eliminate HCV in a population with ongoing risk behaviors. Therefore, targeted socioculturally acceptable preventive measures, including behavioral interventions, are urgently needed. Currently, little contextually appropriate information about HCV or risk reduction interventions is available. OBJECTIVE: The objective of this project was to develop an intervention to reduce HCV transmission among MSM in Amsterdam through a co-creation process, with the input of men from the targeted community directly impacting intervention content, design, and implementation. METHODS: We developed a multilevel intervention targeting 6 levels: individual, community, professional, context, patient, and network. The intervention was developed in close cooperation between health professionals, gay community members, commercial stakeholders, and stakeholders from within the gay community. The co-creation process had 4 phases: a needs assessment, stakeholder engagement, co-creation, and implementation. The co-creation phase continued until consensus was reached between the researchers and community members on the intervention content and design. The final intervention, NoMoreC, was completed within 2 years, and implementation started in February 2018. RESULTS: NoMoreC includes web-based and face-to-face components as well as an anonymous HCV testing service. The NoMoreC website provides information about hepatitis C, HCV transmission routes, risk reduction strategies, testing and treatment options, and partner notification. The face-to-face component comprises a risk reduction toolbox, training for health professionals, and providing tailored advice to sex on premises venues. NoMoreC is promoted by an active voluntary campaign team. CONCLUSIONS: Involving the community and stakeholders in the creation of NoMoreC has been the main strength of this project. It has resulted in an intervention with various components that resonates with the gay community at risk of HCV infection. The uptake and acceptability of the described intervention will be evaluated in the future. The description of the co-creation process and implementation of the project may serve as a rich and useful source for others who want to develop culturally and context appropriate HCV interventions.

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)0.014
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.081
GPT teacher head0.474
Teacher spread0.394 · 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 designQualitative
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

Citations7
Published2020
Admission routes1
Has abstractyes

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