of our research, we focus on actor 19 who we will refer to as "Madonna." Although she is active in the network of sexual relations, her structural uniqueness and ...
CONNECTIONS 18(1):72-87 ©1995 INSNA
"Truth or Dare?": Sexual Networks, Friendship Networks, and Risk Behavior in an Informal Gay Group Jeffrey C. Johnson East Carolina University
Edie Schade East Carolina University
Susan C. Weller University of Texas Medical Branch at Galveston
Introduction Recent large studies of homosexual men have found specific sexual practices to be primary risk factors for seroconversion (Penkower et al. 1991). However, these practical risk factors have been found to be enhanced by heavy drinking, moderate to heavy drug use, and youth through an association with increased sexual contacts, increased frequency of anonymous sex, and failure to use condoms. However, it is difficult to determine whether seroconversion is due to additional immune parameters (other than CD4+ Cells), anxiety, poor nutrition, drug or alcohol induced risk behaviors, the influences of social support, or some combination (ibid). These larger epidemiological studies have contributed much to a general understanding of the association between risk behaviors and seroconversion, but have contributed little to our understanding of the underlying social processes associated with the observed relationships among variables. Social network research, on the other hand, has furthered our understanding of the spread of AIDS (Laumann et al. 1993, Morris 1994) through the development of improved methods for estimating the size of rare population events (Bernard et al. 1987,1988), as a means for tracking the epidemic across sociodemographic subgroups (Laumann et al. 1993), and as a method for better understanding and predicting diffusion of the disease through a given population (Morris 1994). In addition, and no less important, network studies have increased our understanding of the importance of social context, sociogeography, and underlying social and psychological processes associated with the epidemic (e.g., Wallace 1991, 1993; O'Brien et al. 1993; Pivnick et al. 1994). Most of these studies, however, have been ego-centered (the network characteristics of a single actor or individual, usually from a random sample) and have provided insights at a more macro-level (e.g., multiple regression approaches) in terms of the association between network variables and such things as psychological well-being and associated risk behaviors (O'Brien 1993).
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Generally missing are network studies that examine how the actual structure of relations among all actors in a population or whole networks (Johnson 1994) influence attitudes, behavior, and knowledge (Marsden and Friedken 1994; Boster, Johnson, and Weller 1987) or how role structures contribute to the presence or absence of risk behaviors. The idea of a social roles influence on both individual and group behavior has been evident in intervention strategies, for example, that have used "key opinion leaders" to reduce the prevalence of HIV risk behaviors in given groups (Kelley et al. 1991). Yet even with a recognition of the importance of certain social roles in influencing behavior, there has been little research on the network dynamics, particularly with regard to social structure and behavior, of high risk groups. It has been generally noted that sexual risk-takers are young (Trocki 1992). And although there appears to be indications that safer sex is becoming the norm among gay male communities in larger cities, there is renewed concern that younger gay males may be increasingly engaging in risky behavior (Ehrhardt 1992). Thus, an understanding of factors contributing to this trend is critically important. In pursuit of this goal both network and ethnographic approaches have the potential to provide greater detail on factors contributing to high risk behaviors, allowing for a better understanding of causal relationships among variables found to be associated in large statistical studies. This paper presents the findings of an ethnographic study of a small informal gay group on a college campus for the purpose of providing greater insights into the role of social relations and social context in understanding interactions among various risk factors associated with seroconversion among members of a high risk group, namely young gay males. Specifically we seek to explore two basic questions. First, what is the relationship between selected sociological, psychological, cognitive, and behavioral factors for understanding greater risks of HIV infection? Second, how do group relations and social roles contribute to the presence or absence of risk factors?
Methods Participant observation and formal survey approaches were used to understand the relationship between primary risk factors, such as anal receptive sex, and other factors seen to either inhibit or enhance these primary factors. These secondary risk factors include, for example, self perception, social support, peer perception, drugs and drinking, condom use, sexual preferences, HIV testing, and other sociological factors (e.g., parties). Eighteen men and one woman were interviewed over a period of 3 months. These nineteen individuals represented the core of an informal gay group that at one time had asked for official recognition by a moderate sized university in the Southeast US. Data were collected on demographics, sexual practices, sexual networks, friendship networks, cognition, and risk behaviors. Because of problems with reliability of recall frequency data, most questions were limited to either the presence or absence without an estimate of actual frequency. Because of the small size of the study group, questions measured qualitatively were primarily limited to a binary response. Table 1 provides definitions for the social and behavioral variables and their measurement scales. These variables are directed at both risk behaviors and elements of social perception. One other variable not included in the table concerns the sexual activity of actors ordinally dichotomized as either low or high. This variable was determined
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after the study on the basis of ethnographic observations as well as aspects of the quantitative analysis. Social networks were derived from questions concerning who each actor had had sex with in the group (unlimited choices) and who were the three people or actors "hung out" with in the group. The list of names from which to choose involved free listings of group members determinations of who belonged to the group. This exhaustive list of members were then interviewed and network selections were taken from the list. In addition, stimuli for a judged-similarity task were derived from this list. TABLE 1. VARIABLES O F INTEREST AND MEASUREMENT RESPONSES
Social
Sexual Behavior and Risk Behavior
Variable
Measurement
Care a great deal about my appearance
yes/no
Importance of social life
important/not important
Importance of popularity in group
important/not important
Important to have regular HIV testing
yes/no
Sex with someone who had been tested
yes/no
Regularly tested for HIV
yes/no
Always use protection when having sex
yes/no
Enjoy sex with a woman
enjoy/think I would enjoy/do not enjoy
Various forms of insertive and receptive sex
yes/no
Multiplexity of social relations, or the overlap of social relations from one network to another, will be determined with the use of the Quadratic Assignment Procedure (Hubert 1986). Network matrices are correlated to assess similarity in structures and statistical significance is based on a Monte Carlo estimate of P in which the observed statistic is compared to a distribution of statistics derived from comparisons of randomly permuted matrices. Another important network measure involves the density of network relations. The higher the network density, the higher the number of connections between actors in the network. the measure itself is simply the proportion of ties observed to the total number of possible ties and represents the percentage of all possible ties that exist in any given network. Density, for example, may be indicative of the intensity of interaction in a given social context and is particularly suited for comparisons among different kinds of networks (e.g., advice, friendship, kinship). One important aspect of the informal network properties is the extent to which an actor is active in the network (degree centrality) and the extent to which an actor controls the flow of information or other important resources through the network (betweenness centrality). The former measure is a simple indication of the amount of activity of an actor in the system and is defined as
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where n is the number of nodes and di is the degree (number of edges connected to node i) of node i (Freeman 1979). Thus an actor is dominant in the network to the extent he/she is connected to all other actors in the network. The latter measure has been shown in other studies to be associated with power, leadership, and influence (Freeman 1979). The betweenness centrality of CB (k) of node k is
where for all unordered triples i, j, k (i
