No Evidence of Bias in Sexual Partnership Corroboration by Race and Ethnicity Among a Diverse Cohort of Young Men Who Have Sex with Men and Transgender Women

Patrick Janulis*, Balint Neray, Michelle Birkett, Gregory Phillips, Brian Mustanski

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Black men who have sex with men (MSM) continue to experience disproportionately high HIV incidence rates relative to their white peers. Yet, Black MSM do not report higher levels of sexual risk behavior, and contextual factors such as access to care and sexual networks only partially explain these disparities. However, risk misclassification could help explain this paradox, if measurement biases systematically underestimate sexual risk behavior among Black MSM relative to their peers. The current study examined variation in sexual partnership corroboration in the RADAR study, a large and diverse cohort of young MSM and transgender women. Network data were elicited regarding all sexual partners in the prior 6 months, including instances where participants reported other participants as sexual partners. Using these data, anal and condomless anal sex partners were separately examined using a series of exponential random graph models to estimate the rate of corroboration of sexual connections between participants and examine whether this parameter varied by race/ethnicity. For both types of behavior, providing separate estimates for corroboration across race/ethnicity groups reduced model fit and did not significantly vary across groups. Accordingly, we found no evidence of measurement bias by race/ethnicity in the current data. However, overall rates of corroboration (41.2–50.3%) were low, suggesting substantial levels of measurement error. Accordingly, it is vital that researchers continue to improve upon methods to measure risk behavior in order to maximize their validity. We discuss the implications of these findings, including potential alternative causes of risk misclassification (e.g., sampling bias) and future directions to reduce measurement error.

Original languageEnglish (US)
Pages (from-to)267-274
Number of pages8
JournalArchives of Sexual Behavior
Volume49
Issue number1
DOIs
StatePublished - Jan 1 2020

Fingerprint

Transgender Persons
Risk-Taking
Sexual Behavior
Sexual Partners
Selection Bias
Research Personnel
HIV
Incidence
Cohort
Corroboration
Ethnic Groups
Sexual

Keywords

  • Measurement bias
  • Men who have sex with men
  • Racial disparities
  • Sexual networks
  • Sexual orientation

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Psychology(all)

Cite this

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title = "No Evidence of Bias in Sexual Partnership Corroboration by Race and Ethnicity Among a Diverse Cohort of Young Men Who Have Sex with Men and Transgender Women",
abstract = "Black men who have sex with men (MSM) continue to experience disproportionately high HIV incidence rates relative to their white peers. Yet, Black MSM do not report higher levels of sexual risk behavior, and contextual factors such as access to care and sexual networks only partially explain these disparities. However, risk misclassification could help explain this paradox, if measurement biases systematically underestimate sexual risk behavior among Black MSM relative to their peers. The current study examined variation in sexual partnership corroboration in the RADAR study, a large and diverse cohort of young MSM and transgender women. Network data were elicited regarding all sexual partners in the prior 6 months, including instances where participants reported other participants as sexual partners. Using these data, anal and condomless anal sex partners were separately examined using a series of exponential random graph models to estimate the rate of corroboration of sexual connections between participants and examine whether this parameter varied by race/ethnicity. For both types of behavior, providing separate estimates for corroboration across race/ethnicity groups reduced model fit and did not significantly vary across groups. Accordingly, we found no evidence of measurement bias by race/ethnicity in the current data. However, overall rates of corroboration (41.2–50.3{\%}) were low, suggesting substantial levels of measurement error. Accordingly, it is vital that researchers continue to improve upon methods to measure risk behavior in order to maximize their validity. We discuss the implications of these findings, including potential alternative causes of risk misclassification (e.g., sampling bias) and future directions to reduce measurement error.",
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T1 - No Evidence of Bias in Sexual Partnership Corroboration by Race and Ethnicity Among a Diverse Cohort of Young Men Who Have Sex with Men and Transgender Women

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AU - Phillips, Gregory

AU - Mustanski, Brian

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N2 - Black men who have sex with men (MSM) continue to experience disproportionately high HIV incidence rates relative to their white peers. Yet, Black MSM do not report higher levels of sexual risk behavior, and contextual factors such as access to care and sexual networks only partially explain these disparities. However, risk misclassification could help explain this paradox, if measurement biases systematically underestimate sexual risk behavior among Black MSM relative to their peers. The current study examined variation in sexual partnership corroboration in the RADAR study, a large and diverse cohort of young MSM and transgender women. Network data were elicited regarding all sexual partners in the prior 6 months, including instances where participants reported other participants as sexual partners. Using these data, anal and condomless anal sex partners were separately examined using a series of exponential random graph models to estimate the rate of corroboration of sexual connections between participants and examine whether this parameter varied by race/ethnicity. For both types of behavior, providing separate estimates for corroboration across race/ethnicity groups reduced model fit and did not significantly vary across groups. Accordingly, we found no evidence of measurement bias by race/ethnicity in the current data. However, overall rates of corroboration (41.2–50.3%) were low, suggesting substantial levels of measurement error. Accordingly, it is vital that researchers continue to improve upon methods to measure risk behavior in order to maximize their validity. We discuss the implications of these findings, including potential alternative causes of risk misclassification (e.g., sampling bias) and future directions to reduce measurement error.

AB - Black men who have sex with men (MSM) continue to experience disproportionately high HIV incidence rates relative to their white peers. Yet, Black MSM do not report higher levels of sexual risk behavior, and contextual factors such as access to care and sexual networks only partially explain these disparities. However, risk misclassification could help explain this paradox, if measurement biases systematically underestimate sexual risk behavior among Black MSM relative to their peers. The current study examined variation in sexual partnership corroboration in the RADAR study, a large and diverse cohort of young MSM and transgender women. Network data were elicited regarding all sexual partners in the prior 6 months, including instances where participants reported other participants as sexual partners. Using these data, anal and condomless anal sex partners were separately examined using a series of exponential random graph models to estimate the rate of corroboration of sexual connections between participants and examine whether this parameter varied by race/ethnicity. For both types of behavior, providing separate estimates for corroboration across race/ethnicity groups reduced model fit and did not significantly vary across groups. Accordingly, we found no evidence of measurement bias by race/ethnicity in the current data. However, overall rates of corroboration (41.2–50.3%) were low, suggesting substantial levels of measurement error. Accordingly, it is vital that researchers continue to improve upon methods to measure risk behavior in order to maximize their validity. We discuss the implications of these findings, including potential alternative causes of risk misclassification (e.g., sampling bias) and future directions to reduce measurement error.

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