Evidence map›Paper›PMID 28185717›Full record

ArticleAnnals of epidemiology2017

Biomarker validation of self-reported sex among middle-aged female sex workers in China.

Jennifer Guida, Ami Fukunaga, Hongjie Liu

Abstract readValidation Study
In one paragraph

Article in Annals of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jennifer GuidaSchool of Public Health, University of Maryland, College Park. Electronic address: jlguida@umd.edu.
Ami FukunagaSchool of Public Health, University of Maryland, College Park.
Hongjie LiuSchool of Public Health, University of Maryland, College Park.

Funding

Social network and sexual risk for HIV/STIs among older female sex workersR01HD068305 · NICHD · VIRGINIA COMMONWEALTH UNIVERSITY · PI LIU, HONGJIE · 2011 to 2014
$1.6M
NICHD NIH HHS R01 HD068305
6 · The paper itself

Abstract

purposeThe objective of this study was to examine information bias arising from self-reported sexual activity and its association with syphilitic infections among female sex workers (FSWs) aged 35 years and older in China.

methodsA questionnaire was administered to 1245 middle-aged FSWs. Respondents self-reported sexual intercourse in the past 48 hours. The prostate-specific antigen test was used to verify self-reported sexual activity. FSWs were considered discordant if they indicated no sexual intercourse in the past 48 hours on the questionnaire and had a positive prostate-specific antigen test. Logistic regression was used to assess the associations between discordance and syphilis.

resultsThree hundred twenty FSWs self-reported no engagement in sexual intercourse in the past 48 hours. One-fourth of respondents (25%) were discordant. Twenty-two percent and 35.8% of discordant FSWs tested positive for active and prevalent syphilis, respectively. After adjusting for confounders, discordant FSWs had 3.8 times the odds of active syphilis (95% confidence interval: 1.52-9.30) and 2.6 times the odds of prevalent syphilis (95% confidence interval: 1.37-5.02), compared with concordant FSWs.

conclusionsFSWs who had active or prevalent syphilis were more likely to be discordant. Data collected via self-reported questionnaire may not be a valid tool to assess sexual behavior.

Indexed as

AdultBiomarkersChinaCondomsFemaleHumansMiddle AgedPrevalenceProstate-Specific AntigenRisk-TakingSelf ReportSexual BehaviorSex WorkersSyphilisUnsafe SexBiomarkersProstate-Specific AntigenHIVSelf-reported measuresSex workerSTIValidity

Identifiers

PMID28185717
PMCPMC5359020

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.