TY - JOUR
T1 - Methods for the design and analysis of relationship and partner effects on sexual health
AU - Mustanski, Brian
AU - Starks, Tyrel
AU - Newcomb, Michael E.
N1 - Funding Information:
Acknowledgments During the preparation of this manuscript, Brian Mustanski was supported as a Principal Investigator on a grant for research on relationships and the health of YMSM from the National Institute of Mental Health (R21MH095413). He was also supported for research on LGBT Health from the William T. Grant Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health, the National Institutes of Health, or the William T. Grant Foundation. This article was an output of a meeting on male couples and sexual health co-organized by Drs. Jeffrey Parsons and Brian Mustanski. We thank anonymous reviewers for their helpful comments on drafts of the article.
PY - 2014/1
Y1 - 2014/1
N2 - Sexual intercourse involves two people and many aspects of sexual health are influenced by, if not dependent on, interpersonal processes. Yet, the majority of sexual health research involves the study of individuals. The collection and analysis of dyadic data present additional complexities compared to the study of individuals. The aim of this article was to describe methods for the study of dyadic processes related to sexual health. One-sided designs, including the PLM, involve a single individual reporting on the characteristics of multiple romantic or sexual relationships and the associations of these factors with sexual health outcomes are then estimated. This approach has been used to study how relationship factors, such as if the relationship is serious or casual, are associated with engagement in HIV risk behaviors. Such data can be collected cross-sectionally, longitudinally or through the use of diaries. Two-sided designs, including the actor-partner interdependence model, are used when data are obtained from both members of the dyad. The goal of such approaches is to disentangle intra- and inter-personal effects on outcomes (e.g.; the ages of an individual and his partner may influence sexual frequency). In distinguishable datasets, there is some variable that allows the analyst to differentiate between partners within dyads, such as HIV status in a serodiscordant couple. When analyzing data from these dyads, effects can be assigned to specific types of partners. In exchangeable dyadic datasets, no variable is present that distinguishes between couple members across all dyads. Extensions of these approaches are described.
AB - Sexual intercourse involves two people and many aspects of sexual health are influenced by, if not dependent on, interpersonal processes. Yet, the majority of sexual health research involves the study of individuals. The collection and analysis of dyadic data present additional complexities compared to the study of individuals. The aim of this article was to describe methods for the study of dyadic processes related to sexual health. One-sided designs, including the PLM, involve a single individual reporting on the characteristics of multiple romantic or sexual relationships and the associations of these factors with sexual health outcomes are then estimated. This approach has been used to study how relationship factors, such as if the relationship is serious or casual, are associated with engagement in HIV risk behaviors. Such data can be collected cross-sectionally, longitudinally or through the use of diaries. Two-sided designs, including the actor-partner interdependence model, are used when data are obtained from both members of the dyad. The goal of such approaches is to disentangle intra- and inter-personal effects on outcomes (e.g.; the ages of an individual and his partner may influence sexual frequency). In distinguishable datasets, there is some variable that allows the analyst to differentiate between partners within dyads, such as HIV status in a serodiscordant couple. When analyzing data from these dyads, effects can be assigned to specific types of partners. In exchangeable dyadic datasets, no variable is present that distinguishes between couple members across all dyads. Extensions of these approaches are described.
KW - Dyadic relationships
KW - Gay
KW - HIV
KW - MSM
KW - Romantic relationships
KW - Sexual health
KW - Sexual orientation
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U2 - 10.1007/s10508-013-0215-9
DO - 10.1007/s10508-013-0215-9
M3 - Article
C2 - 24243003
AN - SCOPUS:84892670611
SN - 0004-0002
VL - 43
SP - 21
EP - 33
JO - Archives of Sexual Behavior
JF - Archives of Sexual Behavior
IS - 1
ER -