Sexual conversation networks and young adults' sexual health in a Southeast-European context.
Subject: Book publishing (Public opinion)
Social networks (Public opinion)
Teenagers (Public opinion)
Youth (Public opinion)
HIV (Viruses) (Public opinion)
Condoms (Public opinion)
Authors: Bozic, Jasmina
Bacak, Valerio
Stulhofer, Aleksandar
Pub Date: 12/22/2011
Publication: Name: The Canadian Journal of Human Sexuality Publisher: SIECCAN, The Sex Information and Education Council of Canada Audience: Academic Format: Magazine/Journal Subject: Psychology and mental health Copyright: COPYRIGHT 2011 SIECCAN, The Sex Information and Education Council of Canada ISSN: 1188-4517
Issue: Date: Winter, 2011 Source Volume: 20 Source Issue: 4
Topic: Event Code: 290 Public affairs
Product: Product Code: 2731000 Book Publishing; E121930 Youth; 3069770 Prophylactics & Diaphragms NAICS Code: 51113 Book Publishers; 326299 All Other Rubber Product Manufacturing SIC Code: 2731 Book publishing; 3069 Fabricated rubber products, not elsewhere classified
Organization: Company Name: Oxford University Press (Oxford, England)
Geographic: Geographic Scope: Croatia; United Kingdom; New York Geographic Code: 4EXCR Croatia; 1U2NY New York
Accession Number: 286557621
Full Text: Abstract: Social network approach has conceptually and empirically improved research on HIV/ AIDS by counterbalancing the individualized concepts of sexual decision-making. In the current study, associations between the structural characteristics of ego-centered networks and HIV-related knowledge, attitudes, and behaviours were examined in a population-based sample (n = 1005) of young Croatian adults aged 18-25 years. The findings suggested that the associations between the selected HIV-relevant outcomes and the structural properties of social networks were weak and markedly gender-specific. Among women, network-based religiosity predicted HIV-related knowledge, while network density was related to attitudes toward condoms. Age homophily and network history were correlated with condom use at last intercourse among men. Future studies may improve the understanding of the associations between social networks and HIV-relevant beliefs and behaviours by exploring the possibility that network effects are not invariant over time.

Introduction

Network analysis has been increasingly successful in improving our knowledge of the social dimensions of health (Luke & Harris, 2007; Smith & Christakis, 2008). We now know, for example, that sexual health-related behaviours, knowledge, and attitudes in particular are strongly shaped by the immediate social environment through peer influence and normative pressures. To date, a majority of population-based studies of social networks and sexuality have been carried out in North America (e.g., Bearman, Moody, & Stovel, 2004; Laumann, Gagnon, Michael, & Michaels, 1994) although the human-immunodeficiency virus (HIV) epidemic has motivated a number of innovative network studies in sub-Saharan Africa (e.g., Helleringer & Kohler, 2007; Kohler, 2001; Morris, 2004; Valente, Watkins, Jato, van der Straten, & Tsitsol, 1997). In contrast, similar studies of the social dimensions of sexuality and sexually transmitted infections (STIs) have yet to appear in other parts of the world, including Southeastern Europe.

The characteristics of social networks, including tie strength (Granovetter, 1983) and homophily (i.e., the tendency to create ties with similar people; McPherson, Smith-Lovin, & Cook, 2001), are crucial for explaining how individuals behave and understand the world around them. These and other dimensions of social connections have been associated with a range of sexual practices of young people, including contraceptive use (Choi & Gregorich, 2009; Tyler, 2008), timing of intercourse (Sieving, Eisenberg, Pettingell, & Skay, 2006), sexual debut (Adamczyk & Felson, 2006), and STI-related risks (Fichtenberg, Muth, Brown, Padian, Glass, & Ellen, 2009). There is also qualitative and quantitative evidence that, especially among women, informal conversations about topic such as family planning, family size, and HIV/AIDS are associated with fertility-related attitudes (Bernardi, 2003; Montgomery and Chung 1998; Smith & Watkins, 2005). Men engage in similar conversations when, for example, they seek sexual health information from each other or ask for advice about STI treatment (Watkins, 2004).

Personal networks and their properties influence individuals through a variety of social mechanisms (Luke & Harris, 2007) although two mechanisms, social learning and social influence, appear to be central (Christakis & Fowler, 2009; Valente, 2010). Individuals learn about health-related topics from the people around them and that is particularly so for topics dealing with sexual and reproductive health (Kohler, 2001). Social connections also influence people's beliefs and attitudes through social norms that exist in their environment. Such normative influences on sex-related issues are pronounced among young people who are more likely than adults to imitate what their peers are doing and thinking. In addition, the personal reputations of adolescents and young adults seem to be more dependent on the referent group opinion than is the case with adults, which further facilitates these normative pressures.

The present study

The aim of the present study was to examine the associations between Croatian young adults' personal networks and HIV-relevant attitudes, knowledge, and behaviours. The guiding assumption behind the study, based on the vast literature on youth sexuality, was that the basic structural characteristics of social networks, e.g., size, density, or homophily, would be related to a number of sexual and reproductive health outcomes. Given that sexual socialization of women and men still diverges, particularly in Southern Europe (cf. Traeen, Stulhofer, & Landripet, 2011), we also expected that the observed pattern of associations between network characteristics and outcomes would be gender-specific.

Background

As is the case with a number of its neighbouring countries, Croatia has witnessed significant political, socio-economic, and cultural changes in the last 20 years triggered by the process of post-communist transition (Stulhofer & Sandfort, 2005). The unemployment level remains high and the GDP per capita is substantially lower than in Western European countries. According to the Croatian National Bank, GDP per capita in 2011 was 18,300 USD, and the unemployment rate was 17.9%. In addition, the effects of the current global recession have had severe consequences on the public sector prompting cuts in social services, including investment in HIV prevention programs. In the sphere of sexuality, this social change has been marked by the competing influences of rising sexual permissiveness on the one hand and politically motivated efforts at retraditionalization on the other. While popular media and increasing Internet usage have stimulated the former, the Catholic Church has played an important role in the latter (Bijelic, 2008). In such a tumultuous social context, it can be argued that social networks may reflect clashing normative pressures by mediating their influence on what young people know and believe about sexrelated topics. For example, the stigma attached to HIV and its association with socially marginalized groups such as homosexual men, could have distorted the type of information that young people have available about the infection. In addition, the moral discourse surrounding contraception as reflecting a "promiscuous lifestyle" may have discouraged some young men and women from developing positive attitudes towards condom use.

Sexual knowledge, attitudes and behaviours

Recent studies among young adults in Croatia suggest that a majority hold positive attitudes toward condoms. In a 2005 population-based study of men and women aged 18-24, between 78-85% of respondents agreed with positive statements about condom use such as "people who use condoms are very responsible" (Stulhofer, Graham, Bozicevic, Kufrin, & Ajdukovic, 2009). In the same study, a third of the respondents answered correctly to all seven questions assessing elementary HIV knowledge. It is important to note that women scored higher on the knowledge scale than men. A longitudinal study of youth sexuality carried out in three waves between 1998 and 2008 among first-year university students in the capital city of Zagreb revealed that sexual literacy scores (indicating basic knowledge of reproductive and sexual health topics) remained stable throughout the period (Landripet, Sevic, Car, Bacak, Mamula, & Stulhofer, 2010). With respect to behaviour, recent studies have pointed to a substantial, but rather stable, prevalence of risky sexual behaviours such as multiple sexual partners and mostly inconsistent condom use, among Croatian young adults (Landripet et al., 2010; Stulhofer, Graham, Bozicevic, Kufrin, & Ajdukovic, 2007). The most recent analysis of the association between religiosity and sexual behaviour among youth suggests that the effects of religion tend to be sporadic and present primarily among women (Puzek, Stulhofer, & Bozicevic, in press).

Study objectives

In order to gain a better understanding of HIV-related sexual behaviours, knowledge and attitudes among young people, we examined here the associations between risky sexual behaviours, HIV knowledge and attitudes toward condom use and a number of characteristics of ego-centered social networks (ESN) related to communication about sexuality in a population-based sample of Croatian young adults aged 18-25. Considering that sex-related norms are often gender-specific (Ricardo, Barker, Pulerwitz, & Rocha, 2006), particularly in more traditional settings, we explored whether the associations that we found would reflect this traditional difference between women and men. Our analysis emerges from the theoretical notion that network-based approaches provide a more socially embedded (and therefore, more realistic) understanding of HIV-relevant attitudes and knowledge than do individualistic, socially atomized approaches (Boyce, Huang Soo, Jenkins, Mohamed, Overs et al., 2007; Obermayer, 2004; Rhodes, 1997; Rhodes, Singer, Bourgois, Friedman, & Strathdee, 2005).

Methods

Participants and data collection

In February and March 2010, a national probability study of sexuality-related knowledge, attitudes, and behaviors was carried out among 1,005 Croatian young adults aged 18-25. The study procedures were approved by the Ethical Review Board of the Faculty of Humanities and Social Sciences at the University of Zagreb and informed consent was obtained from all participants. The sample was stratified according to region (n = 6), county (n = 21), settlement size ([less than or equal to] 2,000; 2,001 - 10,000; 10,001 - 100,000; > 100,000), and gender. The survey was completed by 495 women and 510 men who were surveyed in their homes. The overall participation rate was 32%. An analysis of reasons given for refusal showed that 24% of those who refused to participate declined to discuss the subject of the study (HIV-related issues), while an additional 4% mentioned parents' opposition to their participation. Around three quarters of participants (74.1% of women and 71.6% of men) described their family socioeconomic status as average, while about one fifth of women (22.6%) and one fourth of men (24.3%) assessed it as better than average. A majority of participants (54.8%) reported spending most of their life in settlements with less than 10,000 inhabitants (54.8%). Religious background was almost invariably Catholic (most participants stated that they were raised in a religious spirit in their families), but only 28.3% of women and 25.7% of men who reported this upbringing strictly followed religious norms. At the time of the survey, 9.3% of women and 4.9% of men were married, while 51.9% of women and 43.3% of men reported being in a relationship. The mean age at first sexual intercourse was 16.9 years (SD = 1.86) for men and 17.4 years (SD = 1.59) for women. Median age was 17 for both genders. A majority of participants were currently sexually active (85.7%). On average, men reported 7.3 lifetime sexual partners (SD = 9.97) and women 3.7 (SD = 4.35).

Questionnaire

The first part of the questionnaire was administered by a trained interviewer. Information on sociodemographic characteristics, HIV knowledge, gender roles, and ESN was collected. The second part of the questionnaire, which focused on sexual behaviours, was self-administered to maximize confidentiality.

The network questions were fashioned according to the General Social Survey measures designed by Burt (1984). We used the following name generator for eliciting personal networks: "Many people occasionally talk about sexuality with their friends and other close persons; please list the persons with whom you talk about your own sexual life most often--excluding your parents." Participants were allowed to name up to five individuals (alters) and were then asked about the age, sex, education, and religiosity of the alters cited, and also how long the participant (ego) had known each of the alters. In addition, relationships among the alters were assessed. Only 59 participants (5.9%) reported no alters. The questionnaire was piloted for comprehensiveness and completion time among 103 students from two metropolitan secondary schools and 132 university students.

Instruments

HIV knowledge

Knowledge of HIV was assessed with seven questions about the modes of HIV transmission (including widespread misconceptions) and the modes of protection from HIV infection, which were recommended as United Nations General Assembly Special Session indicators (UNAIDS, 2007): (1) Can the risk of HIV transmission be reduced by having sex with only one uninfected partner who has no other partners? (2) Can a person reduce the risk of getting HIV by using a condom every time they have sex? (3) Can a healthy-looking person have HIV? (we used the variety "Can one get HIV by having sex with a healthy-looking person?") (4) Can a person get HIV by sharing food with someone who is infected? (5) Can a person get HIV from mosquito bites'? (6) Can a person get HIV by using a public toilet? and (7) Can a person get HIV by using a glass after someone who is infected? Correct answers were coded 1 and others 0 giving a score range from 0 to 7 with higher results indicating more knowledge.

Attitudes toward condoms

Participants' perspectives on condom use were addressed on a four item scale that included observations such as "Those who suggest condom use frequently change sexual partners" and "Individuals who insist on condom use mistrust their partners". Answers for each item were recorded on a 5-point Likert-type scale with higher results reflecting higher acceptance of condom use. The items were summed into a composite scale with satisfactory reliability ([alpha] =.80).

Indicators of sexual risk taking

Two items were used to assess sexual risk-taking: (a) condom use at most recent sexual intercourse and (b) the number of sexual partners in the last 12 months (sexual partner was defined as someone with whom the participant had sexual intercourse). The second indicator was dichotomized into 0 = one or no sexual partners and 1 = two or more sexual partners in the past year.

Characteristics of ego-centered social networks

Six characteristics of ego-centered social networks were assessed: network size (0 - 1,2 - 3, [greater than or equal to] 4); network density; network-based religiosity; age; gender homophily; and network history. Network density assessed the level of interpersonal connectedness (number of dyadic ties) within ego-centered networks. The indicator was dichotomized into 0 = less than the maximum number of ties between pairs of alters, and 1 = maximum number of ties. Network-based religiosity refers to the number of alters that the ego classified as attending religious services regularly. According to the answers to that question, we compiled three categories: 1 = no religious alters, 2 = some alters are religious and 3 = all alters are religious. Age homophily (1 = on average, alters are younger than ego, 2 = alters are of the same age as ego, and 3 = alters are older than ego) and gender homophily (1 = not all alters of the same gender as ego, and 2 = all alters of the same gender as ego) assessed age and gender composition of one's social network. Only one participant reported a social network with all alters of the opposite gender. Finally, network history, which indicated the average duration of ego's relationships with alters, was recoded into 1 = 1 - 5 years, 2 = 5.1 - 10 years, and 3 = [greater than or equal to] 10.1 years of knowing alters.

Socio-demographic indicators

Socio-demographic indicators were age, the size of settlement where the participant spent most of his/ her life ([less than or equal to] 2,000 inhabitants; 2,001 - 10,000; 10,001 100,000; [greater than or equal to] 100,000), parents' education, sexual experience, and frequency of church attendance. Parents' education consisted of summed mother's and father's education (1 = primary education or less, 2 = secondary and 3 = tertiary education). Sexual experience was defined as having had sexual intercourse. Frequency of church attendance was measured on a 6-point scale (1 = never to 6 = daily or almost daily).

Statistical procedures

Gender differences in basic characteristics of ESN, as well as associations between ESN characteristics and risky sexual behaviours, were assessed with chi-square tests. One-way ANOVA was used to test bivariate associations between ESN characteristics one the one hand, and HIV knowledge and attitudes toward condom use on the other. Finally, multivariate OLS and logistic regression analyses were carried out to verify statistically significant bivariate ties by controlling for selected sociodemographic characteristics (age, settlement size, parents' education, frequency of attending religious services, and--in two of the three analyses--sexual experience). All data analyses were carried out using SPSS 16 statistical software. All analyses were conducted separately for women and men to assess the likely effects of gender-specific sexual socialization.

Results

The basic characteristics of personal network are presented by gender in Table 1. Male and female personal networks differed significantly with respect to network religiosity and age homophily. Women reported more religious alters in their social networks than men. In addition, women had proportionately more older alters than did men, while the opposite was found in reporting younger alters.

Bivariate analyses

Bivariate associations between ego-centered network characteristics and HIV-related knowledge, attitudes toward condoms, and HIV risk behaviours are presented in Table 2. Among men, the largest networks were associated with lowest HIV knowledge, but also with most accepting attitudes toward condom use. With regard to HIV-risk behaviours, network age homophily and network history were significantly related to condom use at most recent sexual intercourse. Among the men who used a condom at most recent intercourse, those who reported younger alters were significantly less prevalent than others. Interestingly, the highest proportion of participants who reported condom use was found among men with the shortest personal network history (up to five years).

Among women, HIV knowledge was found to be associated with network-based religiosity. Women who reported only religious alters were significantly less informed about HIV than other female participants. The female participants' attitudes toward condom use were related to three network characteristics. Women who reported the smallest and least dense networks had the least positive attitudes toward condom use. The least positive attitudes toward condoms were also observed among women who discussed their sex life only with religious alters. In the female subsample, risky sexual behaviours were related only to personal network size. Women who reported the smallest network size were significantly under-represented among those who reported that a condom was used at their most recent intercourse. The association with the second indicator of sexual risk taking (partners in the last 12 months) was in the opposite direction. The highest proportion of women with a single sexual partner (or no partners) in the past 12 months was observed among those with the smallest personal networks.

Linear and logistic multivariate regression analyses

As the final step, linear (Table 3) and logistic (Table 4) multivariate regression analyses were carried out with sociodemographic indicators and selected network characteristics as correlates of HIV knowledge and attitudes toward condoms. As shown in Table 3, HIV knowledge among men was significantly predicted by their parents' education ([beta] =. 15, p <.01) and by their own frequency of church attendance ([beta] = -. 15, p < .01). Frequency of church attendance was also found to be negatively associated with male participants' attitudes toward condom use ([beta] = -. 15, p <.01).

In the female subsample, HIV knowledge was significantly related to parents' education ([beta] =. 14, p <.01) and network-based religiosity ([beta] = -. 13, p < .05) (Table 3). Women who reported only religious alters were significantly less knowledgeable about HIV than those with no religious alters. Women's attitudes toward condom use were associated with settlement size ([beta] =. 14, p <.01), personal religiosity ([beta] = -.17, p <.01), and network density ([beta] =.12, p < .05). Female participants living in the largest urban settings and those with the highest network density held more positive attitudes toward condom use than others. Women with a higher frequency of church attendance were less accepting of condom use.

All four linear regression models explained marginal proportions of the dependent variables' variance.

The correlates of sexual risk behaviours are shown in Table 4. Among men, two personal network characteristics were significantly related to condom use at most recent sexual intercourse. Men who reported younger alters were substantially less likely to have used a condom at most recent intercourse (OR =.58, p <.05) than other male participants. In addition, those with the shortest network history were 1.7 times more likely to have used a condom than men with the longest network history (OR = 1.71, p <.05). Reporting multiple sexual partners in the past 12 months was correlated only with age (OR =.88, p <.05). In the male subsample, the logistic regression analysis correctly predicted 59% of cases when the outcome was condom use at most recent sexual intercourse, which is a marginal improvement over chance. Only 54% of correctly classified cases were observed when predicting the number of sexual partners in the past 12 months.

Among women, parents' education increased the odds of condom use at most recent sexual intercourse (OR = 1.25, p <.05), while women with higher church attendance were significantly less likely to report having had two or more partners in the past year (OR =.78, p <.05). For women, the regression model correctly predicted only 57% of cases when condom use at most recent intercourse was the dependent variable. The prediction was somewhat better in the case of the number of sexual partners (76% of correctly classified cases).

Discussion

Through social influence and social learning, peers have been identified as playing an important role in the context of youth sexuality (Maxwell, 2002). For most young men and women, talking about sex with friends is more common and more comfortable than discussing it either with parents or health-care providers (Lefkowitz, Boone, & Shearer, 2004). In this study, we assessed peer influence on HIV-related knowledge, attitudes, and behaviours by analyzing young adults' ESN. The finding that a majority of young Croatian adults talk about their sex life with a number of friends (the sex-talk networks appear to be relatively large, with 30% of participants reporting four or more confidants) confirmed the feasibility of approaching the question of peer influence on sexuality-related issues by social network analysis.

Significant gender differences in the composition of personal networks emerged only with regard to network religiosity and age homophily. Unlike male participants, female participants reported that they discuss their sex life with alters who are on average older than themselves. In addition, female networks included more religious alters than male networks. Adjusted for participants' sociodemographic characteristics, only a few network characteristics were significantly correlated with the outcomes. Among women, network-based religiosity predicted HIV-related knowledge, while network density was associated with attitudes toward condoms. No significant associations were found between ESN characteristics and risky sexual behaviours. In contrast, among men age homophily and network history were correlated with condom use at last sexual intercourse.

The fact that female networks were more religious then male ones corresponds to the finding that a negative association between network-based religiosity and HIV-related knowledge was found only among women. The relationship, however, was significant only when all alters were religious, not in the case when ESN included both religious and non-religious alters. This corroborates the results of a previous Croatian study, which showed that religiosity is negatively related to how much young women know about sexuality (Stulhofer, Soh, Jelaska, Bacak, & Landripet, 2010). Although it seems possible that discussing one's sex life only with religious peers may limit the scope of topics and information young women can receive, network-based religiosity did not seem to be associated with attitudes toward condom use. This is in contrast to a recent study carried out in the United States, which found that religious young adults discussed abstinence more than their peers and that discussing abstinence was associated with having more negative attitudes toward condoms (Lefkowitz et al., 2004). It is plausible that the interactions between social networks, religiosity, and sexuality among young female adults are culture-specific--moderated by religious affiliations and/or mediated by the prevalence of religious fundamentalism.

Network density was positively associated with attitudes toward condoms among female participants, similar to some other studies that have examined related aspects of female contraceptive use (e.g., Kohler, Berman, & Watkins, 2001). It is important to note here that in this study density was a binary variable where dense networks were defined as those in which all alters were mutually connected. Such networks are likely to exhibit stronger normative pressure on their members--either due to homophilic selection or emotionally enhanced members' influence (see Billy & Udry, 1985). As condom use is a normatively loaded subject, the finding that network density was related to attitudes toward condom use among women is not surprising. The direction of this relationship is, however, less self-evident. The predominantly positive attitude toward condom use observed in this study suggests that more dense personal networks are more efficient in solidifying this viewpoint among young adults than less dense networks.

Network characteristics were significantly related to sexual behaviour only among men. Similar to the finding of Ford, Sohn, and Lepkowski (2001) that having older sexual partners decreases the likelihood of condom use, we found that men in our study who reported alters younger, on average, than themselves were less likely to report condom use at most recent sexual intercourse. This age discrepancy may be suggestive of a unidirectional path of social influence on sexual behaviour. Younger network members may themselves be more likely not to use condoms due to less experience and a lower likelihood that they have already experienced an adverse consequence of unprotected sex. Through social influence, this may impact ego's practices. If some alters are also ego's sexual partners, an alternative consideration would be that younger partners may have less power to negotiate condom use.

Men who knew their alters for a shorter period of time were more likely to report using a condom at most recent sexual intercourse than those who reported having networks which were 10 or more years-old. Although more information is required to explain this intriguing finding, it could be that more recently formed networks are less homogenous and, thus, allow for more diverse information and experiences to be shared than more restrictive (more homogenous) long-term networks. Alternatively, it could be that the association reflects the effect of education, as more educated participants are often more socially "mobile" (and more likely to use condoms), i.e. more likely to change social circles throughout their educational career.

Overall, the associations between young adults' HIV-related knowledge, attitudes and behaviors on the one hand and the structural properties of their social networks on the other were few and weak. (All multivariate regression models were characterized by a marginal proportion of explained variance.) This is a departure from studies which have found relatively strong independent effects of social network structure on sexual risk taking (Avogo & Agadjanian, 2008; Choi & Gregorich, 2009; Valente, 2010). A possible reason may be that the name generator used in this study was not entirely adequate or that it was too general (we discuss this below). Another possibility to be considered is a timing effect. The importance of personal networks may not be invariant over time. It seems plausible that the influence of alters is more pronounced at some critical stages or moments, such as the onset of partnered sexual activity (or an emotional crisis caused, for example, by a traumatic break up or being diagnosed with an STI), and becomes less important in more steady periods. Although our data do not allow us to test this hypothesis, a timing effect, if it exists, would almost certainly result in weak and inconsistent associations between network characteristics and the outcomes analyzed in this study.

Study limitations

Several study limitations should be briefly discussed. The low response rate may have affected the generalizability of the findings. It likely introduced some selection bias, favouring more sexually open and liberal individuals. Considering that one in four non-participants stated the study subject as their reason for refusing to participate, it may be that individuals who were more likely to discuss their sex life with their friends and acquaintances were overrepresented in our sample. Whether this may have reduced the variability of personal network characteristics or otherwise affected the associations between the characteristics of ESN and HIV-related issues remains unknown, but it cautions against an uncritical extrapolation of the findings to the respective population. It also needs to be emphasized that the findings are not generalizable outside of the South-Eastern European context due to distinct social and cultural influences on youth sexuality in the region.

The name generator used in this study focused on the individual's sex life rather than on discussions regarding sexuality in general or HIV-related issues. Such a strategy likely underestimated the role of social networks in the peer dissemination of HIV knowledge and the social construction of HIV-related attitudes. As HIV risks remain low in Croatia, especially for members of the general population, it is likely that focusing on more personal aspects of sexuality has overlooked some of the peer exchange on HIV-related topics and issues. It is, however, reasonable to expect that those alters with whom ego feels comfortable enough to talk about his/her sex life would also qualify for discussions about HIV risks. In addition, some of the reasons for the weak association between social networks and the HIV-related outcomes examined in this study may lie in a substantial role-topic dependency in conversational networks (Bearman & Parigi, 2004). Future studies should consider collecting more information about alters' roles (e.g., romantic partner, best friend or colleague at work) and the topics of sex-related conversations.

Concluding observations

The social network approach has been conceptually and empirically fruitful in research on HIV/ AIDS. It has provided an analytically important counterbalance to the individualized concepts of sexual decision-making, emphasizing the role of social interactions and in-group influences. In the current study, associations between the structural characteristics of ego-centered networks based on conversations about the ego's sex life and HIV-related knowledge, attitudes and behaviours were examined in a population-based sample of young Croatian adults. According to the findings, the associations between the selected HIV-relevant outcomes and the structural properties of social networks were weak and gender-specific. Improving the understanding of likely mechanisms behind network effects seems dependent on collecting more detailed information about the content of network-embedded sexual conversations and on the assessment of the possibility that network influences are not invariant over time.

Acknowledgements: The authors would like to thank Damir Soh and Ivan Puzek for their valuable input during the drafting of the study questionnaire and assistance in the initial phase of data analysis. The research was funded by the Croatian Ministry of Science, Education and Sports, and UNDP Croatia.

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Jasmina Bozic, Valerio Bacak (1), (2), and Aleksandar Stulhofer (1)

(1) Department of Sociology, Faculty of Humanities and Social Sciences, University of Zagreb, Croatia

(2) Department of Sociology, University of Pennsylvania, Philadelphia, United States

Correspondence concerning this article should be addressed to Jasmina Bozic, Ph. D., Department of Sociology, Faculty of Humanities and Social Sciences, University of Zagreb, I. Lucica 3, 10000 Zagreb, Croatia. E-mail: jasmina.bozic@ffzg.hr
Table 1 Basic characteristics of personal networks by gender *

                                            Men         Women
                                            n(%)         n(%)

Network size
  [less than or equal to] 1 alters       136 (26.7)   118 (23.8)
  2 - 3 alters                           221 (43.3)   221 (44.6)
  [greater than or equal to] 4 alters    153 (30.0)   156 (31.5)

Network density
  less than max. number of ties          341 (66.9)   333 (67.3)
   between alters
  maximum number of ties                 169 (33.1)   162 (32.7)

Network religiosity
  no religious alters                    284 (60.4)   239 (50.2)
  some alters are religious              112 (23.8)   141 (29.6)
  all alters are religious                74 (15.7)    96 (20.2)

Network age homophily
  alters are younger than ego            204 (40.0)   137 (27.7)
  alters are of the same age as ego       96 (18.8)   103 (20.8)
  alters are older than ego              210 (41.2)   255 (51.5)

Network gender homophily
  not all alters are of the              226 (48.1)   217 (45.6)
   same gender as ego
  all alters are of the same             244 (51.9)   259 (54.4)
   gender as ego

Network history
  [less than or equal to] 5 years        136 (28.9)   130 (27.3)
   of knowing alters
  5.1 - 10 years of knowing alters       196 (41.7)   201 (42.2)
  [greater than or equal to] 10.1        138 (29.4)   145 (30.5)
   years of knowing alters

                                         [chi square]

Network size                             1.08
  [less than or equal to] 1 alters
  2 - 3 alters
  [greater than or equal to] 4 alters

Network density                          0.02
  less than max. number of ties
   between alters
  maximum number of ties

Network religiosity                      10.01 **
  no religious alters
  some alters are religious
  all alters are religious

Network age homophily                    17.55 ***
  alters are younger than ego
  alters are of the same age as ego
  alters are older than ego

Network gender homophily                 0.59
  not all alters are of the
   same gender as ego
  all alters are of the same
   gender as ego
                                         0.33
Network history
  [less than or equal to] 5 years
   of knowing alters
  5.1 - 10 years of knowing alters
  [greater than or equal to] 10.1
   years of knowing alters

(a) Due to missing cases not all percentages add up to 100

* p<.05; ** p<.01, *** p<.01

Table 2 Means, analysis of variance and [chi square] for HIV-
related knowledge, attitudes and behaviour across social network
characteristics by gender

                                          HIV knowledge

                                       Men          Women

                                               F

                                             M (SD)

Network size                          3.40 *        0.71
  [less than or equal to] 1        5.36 (l.64)   5.46 (l.67)
  2-3                              5.54 (l.47)   5.49 (1.50)
  [greater than or equal to] 4     5.13 (l.45)   5.30 (l.47)

Network density                        .21           .00
  <. 9 (< max. no. of ties btw.    5.35 (l.52)   5.42 (l.56)
    alters)
  max. no. of ties between         5.41 (1.52)   5.42 (l.49)
    alters

Network religiosity                   1.08         4.18 *
  no religious alters              5.45 (l.53)   5.51 (1.57)
  some alters are religious        5.39 (1.38)   5.49 (l.45)
  all alters are religious         5.16 (1.54)   5.00 (l.53)

Network age homophily                 1.81          0.33
  alters younger than ego          5.22 (l.56)   5.44 (l.53)
  alters of the same age as ego    5.56 (l.53)   5.51 (1.41)
  alters older than ego            5.42 (l.47)   5.37 (l.59)

Network gender homophily               .14           .63
  not all alters of the same
    gender
  as ego                           5.36 (l.46)   5.34 (l.64)
  all alters of the same gender
    as ego                         5.41 (1.53)   5.45 (l.45)

Network history                        .19          1.31
  [less than or equal to] 5        5.45 (l.52)   5.58 (l.38)
    years of knowing alters
  5.1-10 years of knowing alters   5.38 (l.53)   5.36 (l.60)
  [greater than or equal to]       5.34 (l.43)   5.30 (l.59)
    10.1 years of knowing alters

                                   Attitudes toward condom use

                                       Men           Women

                                               F

                                             M (SD)

Network size                          5.69 **        4.80 **
  [less than or equal to] 1        13.15 (4.21)   14.85 (4.18)
  2-3                              14.36 (3.86)   15.74 (3.51)
  [greater than or equal to] 4     14.61 (3.77)   16.21 (3.27)

Network density                         .40           5.61 *
  <. 9 (< max. no. of ties btw.    14.03 (3.95)   15.41 (3.86)
    alters)
  max. no. of ties between         14.27 (4.00)   16.23 (3.07)
    alters

Network religiosity                    1.97          3.10 *
  no religious alters              14.54 (3.79)   16.03 (3.53)
  some alters are religious        14.17 (3.89)   15.96 (3.43)
  all alters are religious         13.55 (4.20)   15.01 (3.57)

Network age homophily                   .20           .54
  alters younger than ego          13.80 (4.07)   15.42 (3.83)
  alters of the same age as ego    14.50 (4.10)   15.66 (3.82)
  alters older than ego            14.24 (3.78)   15.82 (3.46)

Network gender homophily               .72            .68
  not all alters of the same
    gender
  as ego                           14.45 (4.02)   15.66 (3.26)
  all alters of the same gender
    as ego                         14.15 (3.76)   15.93 (3.73)

Network history                        2.12           1.64
  [less than or equal to] 5        14.44 (3.56)   15.36 (3.56)
    years of knowing alters
  5.1-10 years of knowing alters   14.59 (3.97)   16.07 (3.48)
  [greater than or equal to]       13.73 (4.03)   15.83 (3.53)
    10.1 years of knowing alters

                                           HIV risk behaviours

                                          Condom use during last
                                               intercourse

                                          Men               Women

                                     [chi square]        [chi square]

                                   yes (%)   no (%)   yes (%)   no (%)

Network size                             3.80              5.09 *
  [less than or equal to] 1         41.9     58.1      33.9      66.1
  2-3                               51.1     48.9      46.6      53.4
  [greater than or equal to] 4      52.3     47.7      42.3      57.7

Network density                          2.36               .07
  <. 9 (< max. no. of ties btw.     46.6     53.4      42.6      57.4
    alters)
  max. no. of ties between          53.8     46.2      41.4      58.6
    alters

Network religiosity                          1.44              1.76
  no religious alters               50.4     49.6      43.5      56.5
  some alters are religious         53.6     46.4      46.1      53.9
  all alters are religious          44.6     55.4      37.5      62.5

Network age homophily                    7.82 *            1.60
  alters younger than ego           41.7     58.3      38.0      62.0
  alters of the same age as ego     51.0     49.0      45.6      54.4
  alters older than ego             55.2     44.8      43.1      56.9

Network gender homophily                  .08               .41
  not all alters of the same
    gender
  as ego                            50.9     49.1      41.5      58.5
  all alters of the same gender
    as ego                          49.6     50.4      44.4      55.6

Network history                           4.81 *            .10
  [less than or equal to] 5         58.1     41.9      43.8      56.2
    years of knowing alters
  5.1-10 years of knowing alters    46.4     53.6      43.3      56.7
  [greater than or equal to]        47.8     52.2      42.1      57.9
    10.1 years of knowing alters

                                      HIV risk behaviours

                                     No. of sexual partners
                                      in the last 12 months

                                              Men

                                           [chi square]

                                   0-1(%)   [greater than or
                                            equal to] 2 (%)

Network size                               3.84
  [less than or equal to] 1         62.7          37.3
  2-3                               51.1          48.9
  [greater than or equal to] 4      52.9          47.1

Network density                            2.71
  <. 9 (< max. no. of ties btw.     57.3          42.7
    alters)
  max. no. of ties between          49.0          51.0
    alters

Network religiosity                         .80
  no religious alters               55.6          44.4
  some alters are religious         55.4          44.6
  all alters are religious          49.1          50.9

Network age homophily                       .68
  alters younger than ego           55.0          45.0
  alters of the same age as ego     57.9          42.1
  alters older than ego             52.5          47.5

Network gender homophily                   2.10
  not all alters of the same
    gender
  as ego                            58.2          41.8
  all alters of the same gender
    as ego                          51.0          49.0

Network history                                   3.90
  [less than or equal to] 5         52.5          47.5
    years of knowing alters
  5.1-10 years of knowing alters    50.9          49.1
  [greater than or equal to]        62.2          37.8
    10.1 years of knowing alters

                                      HIV risk behaviours

                                     No. of sexual partners
                                      in the last 12 months

                                                  Women

                                               [chi square]

                                   0-1(%)   [greater than or
                                            equal to] 2 (%)

Network size                               8.88 *
  [less than or equal to] 1         88.8          11.2
  2-3                               73.5          26.5
  [greater than or equal to] 4      74.1          25.9

Network density                            0.18
  <. 9 (< max. no. of ties btw.     77.6          22.4
    alters)
  max. no. of ties between          75.8          24.2
    alters

Network religiosity                        2.92
  no religious alters               76.7          23.3
  some alters are religious         72.2          27.8
  all alters are religious          83.3          16.7

Network age homophily                       .18
  alters younger than ego           75.9          24.1
  alters of the same age as ego     76.3          23.7
  alters older than ego             77.8          22.2

Network gender homophily                    .50
  not all alters of the same
    gender
  as ego                            78.0          22.0
  all alters of the same gender
    as ego                          75.0          25.0

Network history                             .70
  [less than or equal to] 5         74.0          26.0
    years of knowing alters
  5.1-10 years of knowing alters    76.4          23.6
  [greater than or equal to]        78.8          21.2
    10.1 years of knowing alters

* p<.05, ** p<.01

Table 3 Socio-demographic and network-based correlates of HIV related
knowledge and attitudes by gender

                                                HIV knowledge

                                                     Men
                                                  (n = 464)
                                                  F = 3.68 ***

                                             [beta] (SE)   [beta]

Age                                           .05 (.03)     .07

Settlement size
  [less than or equal to] 2,000 = referent
  2,001-10,000                               -.26 (.20)    -.06
  10,001-100,000                              .19 (.19)     .05
  [greater than or equal to] 100,001          .06 (.19)     .02

Parents' education                            .24 (.08)     .15 **
Sexual experience                            -.46 (.24)    -.09
Frequency of church attendance               -.18 (.06)    -.15 **

Network size
  [less than or equal to] 1 = referent
  2-3                                         .03 (.21)     .01
  [greater than or equal to] 4               -.40 (.22)    -.13

Network density
  <.9 = referent
  max. no. of ties between alters            -.06 (.17)    -.02

Network religiosity
  no religious alters = referent
  some alters are r.                          .18 (.18)     .05
  all alters are r.                          -.12 (.20)    -.03
[R.sup.2]                                              .09

                                                 HIV knowledge

                                                     Women
                                                  (n = 471)
                                                  F = 2.16 *

                                             [beta] (SE)   [beta]

Age                                           .05 (.03)     .08

Settlement size
  [less than or equal to] 2,000 = referent
  2,001-10,000                               -.10 (.21)    -.02
  10,001-100,000                              .00 (.19)     .00
  [greater than or equal to] 100,001         -.09 (.20)    -.02

Parents' education                            .21 (.07)     .14 **
Sexual experience                            -.36 (.21)    -.08
Frequency of church attendance               -.04 (.06)    -.04

Network size
  [less than or equal to] 1 = referent
  2-3                                         .00 (.23)     .00
  [greater than or equal to] 4               -.25 (.23)    -.08

Network density
  <.9 = referent
  max. no. of ties between alters             .02 (.17)     .01

Network religiosity
  no religious alters = referent
  some alters are r.                          .09 (.18)     .03
  all alters are r.                          -.48 (.21)    -.13 *
[R.sup.2]                                              .05

                                                Attitudes toward
                                                   condom use

                                                      Men
                                                   (n = 465)
                                                   F = 1.85 *

                                             [beta] (SE)   [beta]

Age                                           .03 (.08)     .02

Settlement size
  [less than or equal to] 2,000 = referent
  2,001-10,000                               -.26 (.53)    -.03
  10,001-100,000                             -.25 (.51)    -.03
  [greater than or equal to] 100,001         -.35 (.50)    -.04

Parents' education                            .35 (.20)     .09
Sexual experience                             .56 (.65)     .05
Frequency of church attendance               -.44 (.15)    -.15 **

Network size
  [less than or equal to] 1 = referent
  2-3                                         .91 (.57)     .12
  [greater than or equal to] 4               1.06 (.57)     .13

Network density
  <.9 = referent
  max. no. of ties between alters            -.36 (.44)    -.04

Network religiosity
  no religious alters = referent
  some alters are r.                         -.31 (47)     -.03
  all alters are r.                          -.20 (.54)    -.02
[R.sup.2]                                              .05

                                                Attitudes toward
                                                  condom use

                                                    Women
                                                  (n = 471)
                                                  F=3.97 ***

                                             [beta] (SE)   [beta]

Age                                           .07 (.07)     .05

Settlement size
  [less than or equal to] 2,000 = referent
  2,001-10,000                               -.20 (.47)    -.02
  10,001-100,000                              .50 (.43)     .06
  [greater than or equal to] 100,001         1.14 (.44)     .14 *

Parents' education                            .32 (.16)     .09
Sexual experience                            -.13 (.48)    -.01
Frequency of church attendance               -.46 (.14)    -.17 **

Network size
  [less than or equal to] 1 = referent
  2-3                                        -.33 (.51)    -.05
  [greater than or equal to] 4                .33 (.51)     .04

Network density
  <.9 = referent
  max. no. of ties between alters             .87 (.38)     .12 *

Network religiosity
  no religious alters = referent
  some alters are r.                          .18 (.40)     .02
  all alters are r.                          -.13 (.47)    -.02
[R.sup.2]                                              .09

* p<.05, ** p<.01, *** p<.001

Table 4 Socio-demographic and network-based correlates of
HIV-related behaviour by gender

                             Condom use during last intercourse

                                    Men                  Women
                                   N=463                 N=471

                                OR (95% CI)           OR (95% CI)

Age                          1.04 (.96-1.14)       .98 (.90-1.07)
Settlement size
[less than or equal to]              1                     1
  2,000 = referent
2,001-10,000                 1.33 (.77-2.32)       .66 (.38-1.15)
[greater than or equal to]   1.34 (.82-2.38)       .70 (.42-1.18)
  10,001-100,000
> 100,001                    1.13 (.67-1.88)       .67 (.40-1.12)

Parents' education           1.17 (.94-1.44)      1.25 (1.03-1.5 1) *
Frequency of church           .96 (.82-1.11)       .90 (.77-1.05)
  attendance

Network size
[greater than or equal to]           1                     1
  4 (referent)
[less than or equal to] 1     .61 (.34-1.08)       .79 (.45-1.38)
2-3                           .91 (.59-1.41)      1.27 (.83-1.95)

Network age homophily
alters older than ego                1                     1
  (referent)
alters younger than ego       .58 (.38 -.90) *     .95 (.60-1.51)
alters of the same age as     .97 (.58-1.63)      1.18 (.73-1.91)
  ego

Network history
[greater than or equal to]           1                     1
  10.1 years of knowing
  alters (referent)
[less than or equal to] 5    1.71 (1.01-2.90) *   1.11 (.67-1.83)
  years of knowing alters
5.1-10 years of knowing       .94 (.59-1.48)      1.09 (.70-1.69)
  alters

                              No. of sexual partners in the last
                                           12 months

                                    Men                Women
                                   N=401               N=391

                                OR (95% CI)         OR (95% CI)

Age                           .88 (.80 -.97) *    .91 (.81-1.02)
Settlement size
[less than or equal to]              1                   1
  2,000 = referent
2,001-10,000                  .94 (.52-1.70)     1.28 (.61-2.67)
[greater than or equal to]   1.09 (.61-1.95)     1.39 (.71-2.72)
  10,001-100,000
> 100,001                    .98 (.56- 1.73)     1.70 (.87-3.31)

Parents' education            .10 (.79-1.26)      .98 (.76-1.27)
Frequency of church          1.00 (.85- 1.18)     .78 (.64 -.96) *
  attendance

Network size
[greater than or equal to]           1                   1
  4 (referent)
[less than or equal to] 1     .55 (.29- 1.04)     .43 (.19-1.01)
2-3                          1.00 (.63-1.58)     1.08 (.64-1.83)

Network age homophily
alters older than ego                1                   1
  (referent)
alters younger than ego      1.03 (.64-1.64)     1.31 (.73-2.35)
alters of the same age as     .75 (.42-1.33)     1.13 (.59-2.15)
  ego

Network history
[greater than or equal to]           1                   1
  10.1 years of knowing
  alters (referent)
[less than or equal to] 5    1.50 (.84-2.68)     1.18 (.61-2.29)
  years of knowing alters
5.1-10 years of knowing      1.58 (.95-2.61)     1.03 (.58-1.85)
  alters

* p<.05, ** p<.01, *** p<.001
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