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Record W4297670932 · doi:10.2196/40095

Factors Associated With Syphilis Transmission and Acquisition Among Men Who Have Sex With Men: Protocol for a Multisite Egocentric Network Study

2022· article· en· W4297670932 on OpenAlexvenueno aff
Casey E. Copen, Julie Rushmore, Alex de Voux, Robert D. Kirkcaldy, Yetunde Fakile, Carla Tilchin, Jessica Duchen, Jacky M. Jennings, Morgan Spahnie, Abigail Norris Turner, William C. Miller, Richard M. Novak, John A. Schneider, Andrew Trotter, Kyle Bernstein

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicSyphilis Diagnosis and Treatment
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsSyphilisMen who have sex with menGonorrheaDemographyMedicineChlamydiaTransmission (telecommunications)CohortEpidemiologyGerontologyFamily medicineHuman immunodeficiency virus (HIV)ImmunologyInternal medicine

Abstract

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BACKGROUND: In the United States, the rates of primary and secondary syphilis have increased more rapidly among men who have sex with men (MSM) than among any other subpopulation. Rising syphilis rates among MSM reflect changes in both individual behaviors and the role of sexual networks (eg, persons linked directly or indirectly by sexual contact) in the spread of the infection. Decades of research examined how sexual networks influence sexually transmitted infections (STIs) among MSM; however, few longitudinal data sources focusing on syphilis have collected network characteristics. The Centers for Disease Control and Prevention, in collaboration with 3 sites, enrolled a prospective cohort of MSM in 3 US cities to longitudinally study sexual behaviors and STIs, including HIV, for up to 24 months. OBJECTIVE: The Network Epidemiology of Syphilis Transmission (NEST) study aimed to collect data on the factors related to syphilis transmission and acquisition among MSM. METHODS: The NEST study was a prospective cohort study that enrolled 748 MSM in Baltimore, Maryland; Chicago, Illinois; and Columbus, Ohio. NEST recruitment used a combination of convenience sampling, venue-based recruitment, and respondent-driven sampling approaches. At quarterly visits, participants completed a behavioral questionnaire and were tested for syphilis, HIV, gonorrhea, and chlamydia. The participants also provided a list of their sexual partners and described their 3 most recent partners in greater detail. RESULTS: The NEST participants were enrolled in the study from July 2018 to December 2021. At baseline, the mean age of the participants was 31.5 (SD 9.1) years. More than half (396/727. 54.5%) of the participants were non-Hispanic Black, 29.8% (217/727) were non-Hispanic White, and 8.8% (64/727) were Hispanic or Latino. Multiple recruitment strategies across the 3 study locations, including respondent-driven sampling, clinic referrals, flyers, and social media advertisements, strengthened NEST participation. Upon the completion of follow-up visits in March 2022, the mean number of visits per participant was 5.1 (SD 3.2; range 1-9) in Baltimore, 2.2 (SD 1.6; range 1-8) in Chicago, and 7.2 (SD 2.9; range 1-9) in Columbus. Using a community-based participatory research approach, site-specific staff were able to draw upon collaborations with local communities to address stigma concerning STIs, particularly syphilis, among potential NEST participants. Community-led efforts also provided a forum for staff to describe the NEST study objectives and plans for research dissemination to the target audience. Strategies to bolster data collection during the COVID-19 pandemic included telehealth visits (all sites) and adaptation to self-collection of STI specimens (Baltimore only). CONCLUSIONS: Data from NEST will be used to address important questions regarding individual and partnership-based sexual risk behaviors among MSM, with the goal of informing interventions to prevent syphilis in high-burden areas. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/40095.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.082
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.172
GPT teacher head0.480
Teacher spread0.308 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2022
Admission routes1
Has abstractyes

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