Understanding Sexual Risk Behaviors Among Persons Living

UNDERSTANDING SEXUAL RISK BEHAVIORS AMONG PERSONS LIVING

WITH HIV/AIDS IN ABIDJAN, COTE D’IVOIRE

FATOUMATA TRAORE

Submitted in partial fulfillment of the requirements

For the degree of Doctor of Philosophy

Dissertation Adviser: Dr. Mendel Singer

Department of Epidemiology and Biostatistics

Case Western Reserve University

May, 2005 CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the dissertation of

______

candidate for the Ph.D. degree *.

(signed)______(chair of the committee)

______

(date) ______

*We also certify that written approval has been obtained for any proprietary material contained therein. DEDICATION

To my late parents, Sollo and Moussokoro TRAORE, and my family: I would not be here without their sacrifices, support and encouragement. Being where I am and having them in my life were true Blessings from God! 1

TABLES OF CONTENTS

List of Tables ------2

List of Figures ------4

Acknowledgments ------5

Abstract ------6

I. Research Question and Specific Aims ------8

II. Background and Significance ------11 1 Overview of the HIV epidemic ------11 2 Current Issues: Continued sexual risk-taking among HIV patients - 14 3 HIV prevention research among HIV infected persons ------18 4 Shortcomings of previous research in HIV/AIDS patients ------37 5 Putting everything together: Towards an integrative model ------43

III. Methods ------45 1 Study design, Setting, and Population ------45 2 Training of the Interviewers and Pilot Study ------46 3 Data Collection ------48 4 Measures ------50 5 Data Management and Quality Control ------52 6 Analytic Plans ------52

IV. Results ------60 1 Descriptive Analysis ------60 2 Bivariate Analysis ------71 3 Multivariate Analysis ------76 4 Post Hoc Analyses 91

V. Discussion ------107

VI. Appendix ------127 Questionnaire ------158

VII. Bibliography ------

LIST OF TABLES

Description Page

Table 1. The Major Factors and their Utility in HIV Primary and Secondary 33 Prevention ------

Table 2. Summary table for the study variables ------51

Table 3. Socio-demographic information for the study sample ------61

Table 4. Health information for the study participants ------62

Table 5. Association between the demographic and psychological distress 64 variables and the variable ‘lifestyle changes’ ------

Table 6. Study participants’ sexual risk behaviors 66

Table 7. Descriptive statistics and Cronbach’s alpha for the measured 69 scales ------

Table 8. Classification into the high-risk group ------72

Table 9. Association between demographic/health status variables and 74 sexual risk behavior ------

Table 10. Association between the measured scales and sexual risk 75 behavior ------

Table 11. Socio-demographic information for the study groups ------76

Table 12. Perceived health and sexual risk behaviors for the study groups 78

Table 13. Factor loadings and factor structure for the measured scales ---- 79

Table 14. Inter-factor correlations ------81

Table 15. Goodness of fit indices for the measurement model ------85

Table 16. Properties of the estimated measurement model ------87

Table 17. Goodness of fit indices for the estimated structural models ------89

Table 18. Factor loadings and factor structure for the women ------91

Table 19. Factor loadings and factor structure for the men ------92

Table 20. Goodness of fit indices for the estimated measurement models - 94

Table 21. Properties of the revised measurement models ------96

Table 22. Goodness of fit indices for the women’s structural models ------98

Table 23. Goodness of fit indices for the men’s structural models ------100

Table 24. Goodness of fit indices for the measurement models ------103

Table 25. Goodness of fit indices for the structural model ------105

LIST OF FIGURES

Description Page

Figure 1. The Health Belief Model (HBM) ------21

Figure 2. Overview of the AIDS Risk-Reduction Model Stages ------28

Figure 3. Proposed Conceptual Model ------44

Figure 4. Hypothesized Conceptual Model ------55

Figure 5. The initial measurement model ------84

Figure 6. The initial structural model ------88

Figure 7. Final structural model and standardized estimates ------89

Figure 8. The initial measurement model for the women ------93

Figure 9. The initial measurement model for the men ------85

Figure 10.The initial structural model for the women ------97

Figure 11.Final structural model and standardized estimates for women ---- 98

Figure 12.The initial structural model for the men ------99

Figure 13.Final structural model and standardized estimates for men ------101

Figure 14.Initial overall measurement model ------102

Figure 15. Final overall structural model and standardized estimates ------106

ACKNOWLEDGMENTS

I would like to express my sincere thanks to my advisor, Dr. Mendel

Singer for his motivation, his support at critical times, and his guidance throughout this work. It was a real pleasure and honor working with him and I will forever be indebted to him.

I would like to thank my committee members, Dr. Phil Allen, Dr. Kathy

Smyth and Dr. Sana Loue for their dedicated assistance. Their insightful comments made this work better than it otherwise would have been.

Next, I would like to thank my family for their support, most importantly my husband Serge whose tireless encouragement and unconditional love helped me keep going, and my sister-in-law Gisele Toure, who helped me get the approval to conduct my study at the USAC clinic.

Finally, I am grateful to a number of individuals for their help: my friends

Lamine, Tina and Fatou for their encouragement at critical times; my friend

Achilles who contributed by reviewing the final work and encouraging me at all times; Drs. Constance Kanga and Alex Ani from the USAC clinic for all their help during the data collection; all the interviewers (Olga, Edith, Sekongo and Zehi) whose effort had made this work possible; and last but not least to all the patients at USAC (specifically Yolande), who spontaneous agreed to participate. Thanks also to everyone who contributed in any way towards completion of this work. 6

Understanding Sexual Risk Behaviors among Persons Living with HIV/AIDS in Abidjan, Cote d’Ivoire

Abstract

FATOUMATA TRAORE

Background: Recent studies have found that as many as one in three HIV infected persons may continue to engage in unprotected sex, sexual contact often occurring with seronegative or unknown status partners. While the issue of prevention has received greater attention in developed countries, little is known about the extent to which persons living with HIV/AIDS (PLWHA) might continue to engage in high-risk sexual behaviors in sub-Saharan Africa.

Objectives: Propose and test a conceptual model explaining sexual-risk behaviors among PLWHA in terms of cognitive and situational factors.

Methods: Cross-sectional study conducted in Abidjan, Cote d’Ivoire (West

Africa). The study sample consisted of HIV-positive men and women at various stages of their illness and currently attending one of the largest outpatient clinics for HIV patients. All the data were collected through face-to-face structured interviews.

Results: Three hundred forty-nine (349) valid questionnaires were completed.

Fifty percent (50%) of the study sample reported one regular partner; 10% reported casual partners and 7% reported multiple partners. Over one-third of the respondents had engaged in high-risk sexual behaviors during the previous 6 months. As posited, two cognitive factors (an internal and external) emerged from the factor analysis process. Although only a small to moderate variance 7

was explained by the model, most of the hypothesized effects were statistically

significant: the internal cognitive and the situational factors were inversely related

to sexual risk behaviors; the internal cognitive factor also partially mediated the

relationship between situational factor and sexual risk-taking. The external

cognitive had no significant effect on the outcome. Different models were found

for the men and women.

Conclusions: The present study indicates that the behavior of a sizable number of HIV patients may continue to increase the burden of the disease at the population. Because access to care is still very limited in sub-Saharan Africa, secondary prevention should be an important part of the routine care for persons

living with HIV/AIDS. Moreover, findings suggest that merely encouraging individuals to engage in safe sex behaviors in order to protect others may not be as efficient as appealing to their moral norms and self-confidence for condom use.

Chapter 1. Research Question and Specific Aims

1. Research Question

How well do situational and cognitive factors, in combination, explain sexual decision-making of persons living with HIV/AIDS in Abidjan, Cote d’Ivoire?

2. Specific Aims and Hypotheses

Past research has demonstrated the importance of cognitive factors for predicting individual health behaviors [1]. The present study will expand previous findings and propose that for persons living with HIV/AIDS, the cognitive processes involved in sexual decision-making may be separated into two major factors: internal cognitive factor (Moral Norms, Self-efficacy, Outcome

Expectancies, and Religious Norms) representing individuals’ personal values/thoughts about a given situation or action, and external cognitive factor

(Anticipated Regrets, Outcome Value, HIV Treatment Beliefs, and Social Norms) representing their beliefs or concerns about others (e.g. motivation to protect others). In order to achieve the above objective, the following specific aims will be carried out:

Specific aim 1

Validate the constructs of external and internal cognitive factors involved in the sexual decision making of persons living with HIV/AIDS (PLWHA).

Research hypothesis 1.1: Two major factors (external and internal) will underline

the cognitive processes influencing sexual decision-making in persons living with

HIV/AIDS.

Research hypothesis 1.2: Moral Norms, Perceived Self-Efficacy, Outcome

Expectancies, and Religious Norms will load on the internal cognitive factor.

Research hypothesis 1.3: Anticipated Regrets, Perceived Social Norms,

Outcome value, and Beliefs about HIV Treatment will load on the external

cognitive factor.

In addition to the cognitive factors, previous studies have demonstrated that due to their nature, sexual behaviors are likely to be influenced by situational factors

(e.g. substance use, presence of negative mood states) that may distract individuals from acting rationally, in the sense of always practicing safe sex.

However, studies examining direct relationships between risky sexual behaviors and situational factors such as alcohol use and depression have had inconsistent findings, indicating that other types of relationships between situational factors and behavior might exist. For example, rather than being direct, the relationship between negative mood states and high-risk behaviors might be mediated by cognitive factors: being infected may affect people’s mood states, which, in turn, might affect their ability to consistently engage in a rational decision-making about safe sex, thus leading them to high-risk sexual behaviors at times.

Likewise, the relationship between substance use and sexual behaviors may be mediated by cognitive factors: substance use may affect the individual’s cognitive 10 ability, leading him/her to more likely engage in high-risk behaviors. Thus, the following specific aim will be carried out:

Specific aim 2

Test a proposed conceptual model explaining the continued sexual risk-taking in

HIV-infected persons in terms of cognitive and situational factors.

Research hypothesis 2.1: The external and internal cognitive factors will have a direct effect on individuals’ safe sex practices.

Research hypothesis 2.2: The external and internal cognitive factors will mediate the relationship between situational factor and sexual risk behavior.

Research hypothesis 2.3: The relationship between each cognitive factor and sexual behavior will depend on the value of the situational factor.

Chapter 2. Background and Significance

1. Overview of the AIDS epidemic

Nearly two decades after the first case was diagnosed, HIV/AIDS remains a major public health problem. There are an estimated 40 million people currently living with HIV worldwide. Of those, over 70% live in developing countries [2]. Recent estimates indicate that HIV/AIDS is now the fourth biggest killer worldwide, and the number one killer in Sub-Saharan Africa [3]. In West

Africa, Cote-d’Ivoire is the country most affected by HIV. Out of a population of

17 million, an estimated 570, 000 people were living with HIV or AIDS as

December 2003 [4]. Fifty-three (53%) were estimated to be women, and 7% estimated to be children under the age of 15. Recent surveillance data from

UNAIDS estimate the burden adult HIV prevalence (i.e. 15-49 years old) to be around 7% (range 5%-10%), down from prevalence rates around 13% (range

9%-14%) in 1998 [5]. The drop in the national prevalence rates was mainly due to the strong and growing action taken by the national government against

HIV/AIDS, including large scales programs dealing with issues such as safety of blood transfusions, control of sexually transmitted infections including HIV/AIDS within the military and civilians, availability of condoms, and access to medication for HIV-infected persons. Unfortunately, there are new concerns as recent political conflicts in the country have slowed down the fight against HIV/AIDS [6].

Three major factors generally account for the rapid spread of the epidemic: sexual contact with an infected person, parenteral transmission 12

(including injection drug use and blood transfusion), and perinatal transmission from an infected mother to her child [7]. Of the three modes, sexual transmission is by far the most prevalent globally. In developing countries in sub-Saharan

Africa and Asia, heterosexual sexual contact is the predominant route of transmission, accounting for over 80% of all new HIV infections. By contrast, in

US and other high-income countries, male-to-male transmission of HIV accounts for the biggest share, followed by heterosexual transmission and injection drug use [2, 8]. As in other sub-Saharan countries, heterosexual contacts account for the majority of the infections in Cote d’Ivoire, and an array of factors contributes to the epidemic including cultural, economic, and social circumstances. Similar factors have been shown as significant determinants of the spread of HIV infection in other parts of Africa, where higher numbers of sexual partners, sexual contact with commercial sex workers, young age of women at marriage, age difference between spouses, the presence of sexually transmitted infections have been recognized as driving factors of the epidemic [2].

Because of the recognition that HIV is predominantly spread through risky behaviors that are largely avoidable, efforts directed towards changing individual sexual behaviors and attitudes in relation to HIV/AIDS has been promoted as an essential approach to curb the epidemic [9]. In developing countries, biomedical

(e.g. condom use, treatment of other STDs), and behavioral (through behavioral change to reduce high-risk practices) approaches have been recognized as “the only hope for reducing the mortality, morbidity, and social trauma associated with

HIV infection” [10]. Many success stories have provided evidence that strong 13

national commitments can result in lowering the prevalence (cf. encouraging

trends reported in Ethiopia and Uganda) [5]. Unfortunately, reports also indicate

that HIV infection rates are still on the rise in other parts of world. Worldwide, an estimated 38 million persons are now living with HIV, compared to 35 million in

2001 [5]. In Sub-Saharan Africa, high numbers of new HIV infections continue to

be reported annually in many parts of the continent (e.g. Southern Africa), with

the large majority of cases affected through unprotected heterosexual contact.

Moreover, only a small fraction of those already infected can presently afford

treatment [5]. More disturbing is the recent increase in various sexually

transmitted infections rates, especially among persons already infected with HIV.

This issue raises new concerns since persons with HIV not only place

themselves at risk for other sexually transmitted diseases including re-infection with new strains of the virus, but also place others at risk for HIV infection, thus

sustaining the global epidemic.

2. Current issues in epidemic: Continued sexual risk-taking in HIV Patients

The issue of prevention of HIV transmission from persons living with

HIV/AIDS (PLWHA) had received little research attention until recently, when

reports of increasing rates of sexually transmitted disease in persons with known

HIV seropositive status indicated that sexual risk behaviors might be occurring in

this group [2, 11]. Evidence supporting the findings that a substantial number of

HIV-infected persons may still be engaging in high-risk sexual behaviors has

been growing over the past few years, as illustrated by the following data (by

chronological order):

• In their study of 215 HIV-infected women living in New Jersey, Kline and

VanLandingham found that only 48% were using condoms consistently with their

primary partner [12].

• A study of HIV-positive persons in Switzerland reported that 26% of the

sample had engaged in unprotected vaginal or anal intercourse within the

previous 6 months [13].

• In a report from a population-based HIV risk-behavior study conducted in Los

Angeles County, as many as 29% of a cohort of HIV-infected men reported

engaging in unprotected sexual intercourse over the previous 12 months [14].

• A study examining contraceptive use and pregnancy decision-making among a group of women with HIV found that 21.1% of the women aware of their

positive serostatus never used condoms with HIV-negative sex partners or

partners of unknown serostatus [15]. 15

• A study conducted among a sample of 203 HIV-positive men and 129 HIV-

positive women living in the US found that 42% of men and 42% of women

reported at least one episode of unprotected sex in the preceding 6 months [16].

• In Tunisia, a study by Tiouiri and colleagues found that over 28% of a sample of HIV-positive men and women (N= 60) were still engaging in unprotected sexual intercourse [17].

• A study conducted in Tanzania and that examined whether care and support was associated with preventive behavior among people with HIV revealed 56% of condom use a last intercourse after 3 months of follow-up compared with only

16% of condom use at baseline [18].

• A study of sexual risk behaviors among heterosexual HIV discordant couples,

conducted in California, found that over two-thirds of couple members surveyed reported unprotected sex with their partner in the previous 6 months [19].

• After several years of steady decline, a report from the Center for Diseases

Prevention and Control (CDC) indicated a substantial increase in the number of reported syphilis cases among MSM, a high proportion of whom were also HIV-

infected, [20].

• A cross-sectional study conducted in New York found that among HIV-

positive women who were sexually active, 32% reported inconsistent condom

use. Of those, only 37% reported that all their sexual partners were HIV-positive

[21]. 16

• A study examining correlates inconsistent condom use in HIV-discordant heterosexual couples found that as much as 45% of the couples reported having had unprotected sexual intercourse in the previous 6 months [22].

• A study in Denmark reported a higher incidence of gonorrhea (a six-fold increase) in HIV-seropositive men who have sex with men (MSM) compared with other men, suggesting a relapse in high-risk sexual behaviors among this group

[23].

• In US, a study by Ostrow and colleagues found that more than 50% of a sample of HIV-positive and HIV-negative homosexual men reported recently engaging in unprotected anal intercourse [24].

• A large survey conducted between 1999 and 2001 in San Francisco,

California, found that the proportion reporting unprotected anal sex with 2 or more partners of unknown serostatus increased from 19% to 25% for HIV- positive MSM, compared to an increase from 10% to 15% for HIV-negative respondents [25]. The increases were comparable to those reported by a Elford and colleagues [26] in a study conducted in London between 1998 and 2001, and which found that the percentage of HIV-positive MSM reporting high-risk unprotected with a casual partner of unknown or discordant HIV status increased from 15.3% to 38.8% (from 6.8% to 12.1% from HIV negative).

• A study in France found that the proportion of HIV-positive patients reporting sexual behavior at risk for HIV transmission increased from 5.1% in 1998 to

21.1% in 2001-2002 [27]. 17

• In a study examining the sexual behavior of HIV discordant couples after HIV counseling and testing in Zambia, 80% of the study sample reported condom use. However, over-reporting of condom use was very common as 50% of semen, 32% of pregnancies and HIV transmissions were detected among couples who had reported consistent condom use [28]

• Twenty-two percent (22%) of HIV positive MSM reported engaging in unprotected anal intercourse with one or more new partners one month prior to the study [29].

The above findings illustrate the disturbing evidence of continued sexual risk-taking among HIV-positive patients. The majority of the reported studies were conducted in developed countries where the issue has received greater attention because recent advances in HIV treatment have resulted in increased survival, better quality of life, and possibly lesser concerns about the disease among those living with HIV/AIDS [21, 30]. Indeed, a number of studies have found that as many as one in three HIV infected persons may continue to engage in unprotected sex, with sexual contact often occurring with seronegative or unknown status partners [31-33]. In sub-Saharan Africa, little is known about the extent to which PLWHA might continue to engage in unprotected sex. There are compelling reasons, however, to conduct further research with regards to HIV risk and prevention behaviors in PLWHA in such areas. Indeed, although the use of highly active antiretroviral therapy (HAART) is still very limited in the majority of the sub-Saharan African countries and sexual activity is likely to be reduced 18

due to the infection, higher prevalence of HIV combined with the fact that, without

treatment, an HIV-infected person might live as long as 7 to 11 years [2] make it

imperative to focus on prevention issues among those living with HIV/AIDS as well. Thus, studies are needed to uncover barriers specific to PLWHA that might undermine their ability to adopt and maintain safer sex behaviors over time, in order to ensure that they not only avoid placing themselves at risk for sexually transmitted diseases including reinfection with HIV, but also avoid placing others at risk for HIV infection [21]. As observed by DiClemente and colleagues,

“Indeed, it should be axiomatic that prevention does not stop with HIV infection.

Quite the contrary, prevention efforts should be intensified for those individuals living with HIV as, ultimately, only infected individuals can transmit HIV” [32].

3. HIV prevention research in HIV infected persons

Many studies have investigated the persistence of high-risk sexual practices (i.e. unprotected vaginal and/or anal intercourse, sexual acts with multiple partners, sex without disclosure of one’s HIV status) and its correlates among HIV patients, generally in the context of a psychosocial framework. While a vast number of these studies were done outside of any theoretical models, a few studies employed some of the most widely used social cognitive models as their framework for understanding and identifying potential determinants of HIV- related sexual risk behaviors in PLWHA. 19 a. Review of studies using a social cognitive model as their framework

Social cognitive models (SCM) represent a widely used approach for understanding individual decision-making in adopting given health behaviors.

The models assume that individual social and health behaviors are largely a function of cognitive processes such as knowledge, attitudes, beliefs, and norms

[1]. They have been applied to a wide range of health behaviors, including

HIV/AIDS preventive behaviors. Some of the most commonly used models in

HIV prevention for PLWHA (secondary HIV prevention) include the health belief model (HBM), the aids-risk reduction theory (ARRM), the social cognitive theory

(SCT), and the transtheoretical model of behavior change (TTM).

The Health Belief Model

Description of the model

The HBM was originally developed in the1950s in an effort to understand people’s preventive health behavior; that is, the behaviors undertaken in absence of all symptoms, for the purpose of avoiding getting ill [34, 35]. According to the

HBM, an individual compliance with a given health behavior can be explained by four major cognitive factors: 1) perceived susceptibility (the individual subjective risks of contracting a given condition); 2) perceived severity (the individual convictions of the seriousness of contracting a condition or leaving it untreated);

3) perceived benefits (the individual beliefs of the effectiveness of the available courses of action in reducing his/her personal susceptibility to and severity of the illness); and 4) perceived barriers (i.e. the major costs believed to be associated 20

with actually complying with the available course of action). Over the years, new

elements have been added to the model. Factors that serve as cues to action

were believed to be necessary to trigger the appropriate behavior. Additionally,

various demographics, socio-psychological, and structural believed to have an

indirect affect on the individual’s perceptions were also added (Figure 1).

Background Action Perceptions

Cues to Action •Perceived Susceptibility •Media (or acceptance of diagnosis) •Personal influence •Perceived Severity of ill-health •Reminders condition

•Demographic factors (e.g. age, education, sex, race, Behavior to reduce ethnicity) threat based on •Sociopsychological variables expectations (personality, social class, peer and reference group pressure, etc…) •Structural variables (knowledge about the disease, prior contact with the disease, etc…)

•Perceived Benefits of action (minus)

•Perceived Barriers to action

•Perceived self-efficacy to perform action

Figure 1. The health belief model. Adapted from “The health belief model and HIV risk behavior change”, [35].

Described as the most widely used model in studies of health behavior,

the HBM has been applied, with moderate success, to numerous health behaviors including smoking, exercise, diet, compliance with therapy (high blood pressure, diabetes, asthma), compliance with preventive health behaviors 21

(influenza vaccine, breast self-examination), and primary HIV prevention, i.e. prevention in samples of uninfected population (see [36, 37] for a more complete review). Its utility, however, has generally been limited with regard to the latter.

Because of lack of a clear specification of the relationships between the variables, the conceptualization and operationalization of the model has greatly varied across studies, which may explain in part the inconsistency in the research findings [1]. Second, a number of researchers have commented that the tests of the model have been inadequate because they have studied the

HBM as a collection of variables, rather than examining the model as an entity, thus failing to account for potential complex and indirect relationships between the different constructs [1, 37]. Third, although the predictive utility of the model has been greatly improved by the addition of self-efficacy, the HBM still ignores a number of other variables found to be highly predictive of behavior changes such social pressure and behavior intentions [1]. Finally, a number of researchers have suggested that both perceived severity and perceived susceptibility might have limited power for discriminating between those who do and do not adopt

HIV-risk reduction behaviors because of a floor and ceiling effect for the variables: awareness of HIV/AIDS as a serious health threat is almost universal

(ceiling effect), yet most individuals still generally fail to perceive themselves as susceptible because of its low infectiousness and delayed manifestation (floor effect) [1, 38].

A. The Health Belief Model and Secondary HIV prevention

Very few studies have used the HBM as their conceptual framework for examining the HIV transmission sexual behaviors among PLWHA. Huebner and

Gerend [39] used two constructs from the HBM (perceived susceptibility and severity to HIV/AIDS) to explore the mechanisms underlying the relationships between specific beliefs about HIV treatment (Health Improvement,

Complications, Limited Efficacy, and Prevention Transmission beliefs) and sexual risk behaviors in a sample of HIV-positive and HIV-negative men. Perceived susceptibility was positively correlated to Transmission Prevention beliefs, and it partially mediated the relationship between these and sexual risk behaviors, suggesting that the beliefs may be the result of past risky behaviors, rather than cause the sexual behaviors. However, these findings were true for HIV-negative men only. The hypothesized mediating role of perceived severity between the

Health Improvement and Complications beliefs could not be explored because the two variables were unrelated to sexual risk behaviors as predicted.

Social Cognitive Theory

Description of the model

The socio cognitive theory (SCT) postulates that human behavior results

from the “continuous reciprocal” interaction between personal characteristics,

environmental factors, and the behavior itself [40, 41]. Three key cognitive

factors determine the personal factors: the individual’s belief that a given

behavior will lead to certain outcomes (Outcome Expectation), the perceived

values of those outcomes (Outcome Expectancy), and the individual’s conviction

of his/her ability to successfully perform the behavior required to influence those

outcomes (Perceived Self-Efficacy, PSE).

SCT variables (Self-efficacy and Outcome Expectancies i.e. the

combination of Outcome Expectation and Outcome Expectancy) have been

widely used across studies and found to be good predictors of various health

behaviors including the adoption of healthy behaviors (diet, exercise, seatbelt

use), the cessation of unhealthy ones (abstinence from smoking or drinking), and

compliance with preventive recommendations (diabetic regimens, breast self-

examination, management of asthma, epilepsy, and sleep apnea) [42-56]. PSE has also been extensively used in the area of HIV/AIDS prevention studies, and has emerged as one of the most important predictors of HIV preventive behaviors: the lower the PSE, the higher the probability for people to engage in high-risk sexual practices for HIV [1, 57-60]. Over the years, self-efficacy has been incorporated to other psychosocial models such as the HBM, the Theory of

Reasoned Action (TRA), and the Protection Motivation Theory (PMT), and has 24

been shown to significantly enhance the predictive utility of those models [1, 57,

61]. Outcome Expectancies have been used to a lesser extent compared to

PSE. Outcome Expectancies refer to the individual’s beliefs about the

consequences (physical, social and self-evaluative) of engaging in a given

behavior [41]. In the area of HIV/AIDS, for example, condom use expectancies

have included such beliefs as reduced sexual pleasure, negative partner reaction

(negative outcome expectancies), protection against HIV/AIDS, and social

approval (positive outcome expectancies). Outcome expectancies have also

been found to be good predictors in the area of HIV/AIDS prevention in the general population, with more favorable outcome expectancies associated with safer sex behaviors [58, 62-68].

Typically, HIV risk-reduction interventions using the SCT as their conceptual framework provide participants with skills training (mostly through role playing or modeling) in order to enhance their self-efficacy to adopt safer sex behaviors. Overall, such interventions have been successful, resulting in adoption of self-protective behaviors both concurrently and longitudinally [57, 68-

75].

The SCT and Secondary HIV Prevention

The SCT has not been widely applied in HIV preventive behaviors among

PLWHA. Semple and colleagues [76] used constructs from the SCT (self-

efficacy and outcome expectancies) to examine the relationship between partner

type and sexual risk behavior in a sample of HIV-positive men. Outcome 25

expectancies for negotiation of safer sex were inversely related to high-risk

sexual practices (unprotected anal intercourse) with steady partners, whereas

self-efficacy for condom use and negotiation were inversely related to

unprotected sex with casual partners. Likewise, Kalichman and colleagues [77]

used the SCT to develop an HIV-transmission risk reductions intervention in a

sample of 230 men and 98 women living with HIV/AIDS in Atlanta, Georgia.

Compared to the control group, the intervention group reported greater self- efficacy for suggesting condom use with new partners, being satisfied in practicing safer sexual behaviors, and having stronger intentions for considering the costs and benefits of disclosing HIV status to partners and practicing safer sex with partners who were unaware of their status. This in turn resulted in significantly less unprotected sex and greater condom use at follow-up. Finally,

Semple et al. [33] used the SCT to examine the determinants of unprotected sex among 322 HIV-positive men who reported having unprotected sexual intercourse with at least one HIV-negative or unknown status partner in the four

months period prior to the study. Self-efficacy and outcome expectancies in

relation to condom use and negotiation of safer sex practices, two constructs of

the model, were found to make a small (2%) and non-significant contribution to

the prediction of sexual behavior among the study sample.

Stage models: the AIDS-Risk Reduction and Transtheoretical Models

Description of the model

In contrast with the two previous models, which primarily look at the

relationship between various psychosocial factors and risk behaviors, the AIDS- 26

Risk Reduction Model (ARRM) [78] and the Transtheoretical Model (TTM) [79] examine the actual process through which people change their behavior. The

ARRM postulates that three major stages characterize the change process: (1) recognition and labeling of one’s sexual behavior as high risk for contracting HIV,

(2) making a strong commitment to changing those high risk behaviors, finally,

(3) seeking and enacting strategies to meet these goals (Figure 2). Similarly, the

TTM postulates a series of five stages individuals go through in their efforts to change or adopt a given health behaviors: a precontemplation phase (period in which they are not yet thinking about engaging in the behavior); contemplation phase (when individuals are seriously thinking about changing or adopting the health behaviors in the near future, i.e. at least in the next 6 months), preparation

(period in which they are making small steps toward the behavior); action (the period ranging from 0 to 6 months after individuals have engaged in the behavior of interest); and maintenance (period beyond 6 months after action has started). 27

Labeling No action No

Yes

Commitment Resignation No

Yes

Resignation No Enactment Self-Help

Enacting Help Solutions

Figure 2. Overview of the ARRM stages. [78].

ARRM and TTM integrate many of the constructs discussed in other psychosocial models. For example in the ARRM, three factors (knowledge of the modes of HIV transmission, perceived susceptibility to HIV, and social influences) are hypothesized to affect people’s recognition and labeling of their sexual behaviors as problematic. Likewise, perceived costs and benefits, self- efficacy and perceived social norms and social support are important factors for the commitment stage. Finally, social factors and sexual communication skills are postulated as being in the help-seeking and enacting stage. The TTM includes the constructs of self-efficacy and two decisional balance measures: individuals’ beliefs about the pros and cons of the target behavior. The balance 28

between the 2 measures is postulated to vary according to the stages where the

individual is currently at. For example, the pros will outweigh the cons in the precontemplation phase; the opposite will be true in the action and maintenance phase, with the crossover between the measures happening in the contemplation and preparation stages.

Studies looking at the relationship between the ARRM and AIDS preventive behaviors have generally found results that are consistent with the model assumptions. Catania et al. [80] found that heterosexuals that were using condoms regularly were more likely to label their behaviors as problematic, make commitments about condoms use, and indicate higher perceived benefits and sexual communication skills. Sheeran and colleagues [81] conducted a large meta-analysis to identify the psychosocial determinants of condom use among heterosexual adults using the ARRM as a framework for organizing the variables of interest. Consistent with the model, several commitment and enactment stage variables had good average correlations with condom use, whereas labeling stage variables had small correlations with the actual behavior. A number of

AIDS prevention programs have also used the ARRM as the guiding framework.

However, these studies have produced mixed results with regards to the effectiveness of the model [82-85].

The TTM has also been widely applied to numerous health behaviors including smoking cessation, weight control, diet, substance abuse, delinquent behaviors, sunscreen use, radon gas exposure, mammography, exercise, and HIV risk behaviors (see [86-100] more recent reviews of the TTM). . With regards to 29 primary HIV intervention, programs based on the model usually assess stages in which participants are at baseline and tailor the interventions according to their readiness of change. Overall, such interventions have been successful, resulting in significant reductions in HIV risk behaviors among the intervention groups, significant progression across stages for participants, and support for the various constructs for the model [87, 101-106].

The stages models and Secondary HIV Prevention

Few studies have also based their research on the ARRM or the TTM.

For example, Kline and VanLandingham [12] used the constructs of the ARRM to examine the patterns of condom use in a sample of 215 HIV-infected women.

The study found that the change process for adopting safe sex behaviors was as outlined in the model. Six factors, representing each of the constructs from the

ARRM, were all related to consistent condom use; four factors were partner- related variables (e.g. conflicts with partner, partner’s HIV status or desire to have children) and only two factors reflected attitudes and beliefs independent of their partners (perceived barriers about condom use and the women’s own substance use). An important point from the authors was that partner-related factors seemed to be particularly important for HIV-infected women, suggesting that further research was needed to examine issues specifically relevant to preventive decision-making among this group.

Using the TTM as their conceptual framework, Fogarty et al. [107] developed an intervention for HIV prevention for a group of HIV-positive women 30

(n= 322) from Baltimore and a group of HIV-negative women at high risk for HIV

(n= 1289) from Philadelphia. The study outcomes were three target behaviors: consistent condom use with a main partner, condom use with other male partners, and contraceptive use. Among HIV positive women, the intervention influenced both the women’s self-efficacy and their perceived advantages for consistent condom use. Those changes, in turn, resulted in positive changes in

HIV+ women’s risk behaviors. Although the differences were not statistically significant at all transitions, women in the intervention group were, overall, more likely than those in the control group to show more progress toward long-term condom use and report consistent condom use at their last interview.

Butler and colleagues [89] also used the TTM to develop a series of four stage-based interventions for promoting safer sex behaviors among HIV-positive adolescents with hemophilia. The participants demonstrated significant increases in self-efficacy for and knowledge about safer sex, and they were significantly more likely to engage in safer sex behaviors following the interventions.

However, there was no control group, making it difficult to evaluate the effectiveness of the intervention. Similar results were reported by Parsons et al.

[90] in their sample of HIV-positive men with hemophilia and their HIV-negative partners. Their intervention, also based on the TTM, was associated with significant beneficial effects for safer sex behaviors, communication about safer sex and self-efficacy for condom use among men who received the full intervention. Unfortunately, the effectiveness of the interventions was hard to evaluate for a number of reasons: participants self-selected the level of 31 intervention they wanted to be assigned to, the majority of them were already in maintenance for safer sex behaviors at baseline, and no randomization was used for assigning participants to the different groups.

Table 1 summarizes the findings for each SCM with regard to both primary and secondary HIV prevention.

Table 1. Major social cognitive models and their utility in primary and secondary HIV prevention

Factors Models Findings for Primary HIV prevention (References) Findings for Secondary HIV prevention (References) Perceived Susceptibilty HBM/ ARRM Mixed results across studies Negative finding about hypothesized mediating role of (Rosenstock et al., 1994; Catania et al., 1990; Perceived Susceptibility between HIV treatment beliefs Maddux, 1995) and sexual risk behaviors (Huebner and Gerend, 2001)

Perceived Severity HBM Relatively weak predictor predictor of HIV-protective Hypothesized mediating role of Perceived Severity s behaviors(Rosenstock , 1974; Rosenstock et al., 1994; betweencould HIV not treatmentbe explored beliefs and sexual risk behavior Conner and Norman, 1996)

Perceived Benefits/ Barriers HBM/ ARRM Good and consistent predictors of AIDS- Perceived barriers related to consistent condom use protective behaviors (Rosenstock et al., 1994; Catania et al., 1990; Maddux, 1995)

Self-efficacy SCT/ ARRM/TTM Strongest and most consistent predictor of behavior Mixed results across studies change (Bandura, 1994; Conner and Norman, 1996) Outcome expectancies SCT Good predictor of HIV-protective behavior Mixed results across studies (Jemmot and Jemmot, 1992; O’Leary et al., 1992; Fishbein et al., 1993; Wulfert and Wan, 1993; Murphy et al., 1998; Dilorio et al., 2000; Bowen et al., 2001; Dilorio et al., 2002)

Change process ARRM/ TTM In general, stages of changes as outlined in models In general, stages of changes as outlined in models (Catania et al., 1990; Sheeran et al., 1999; (Kline and VanLandingham, 1994; Fogarty et al; 2001; Prochaska et al.,1994; Redding, 1994;Stevens et al. Butler et al., 2003; Parsons et al., 2000) 1996; Jamner et al., 1997; Evers et al.,1998; Harlow et al., 1998; Cabral et al., 2004 ) HBM= Health Belief Model; ARRM= The AIDS Risk Reduction Model; SCT= Social Cognitive Theory; TTM= Transtheoretical Model of Change

b. Review of studies done outside of a theoretical/conceptual framework

Besides the few studies that were explicitly based on already established

theories, a vast number of others have examined the sexual risk practices of

PLWHA and its correlates outside of any given theory. The studied predictors

can be classified into two broad categories: HIV-related (initiation of antiretroviral

therapy) and non HIV-related (including situational variables, individuals’

personal characteristics, and individuals’ general attitudes about sexual risk

behaviors) variables.

HIV-related factors

The use of antiretroviral therapy has been the most consistently studied

correlate of high-risk sexual behavior among HIV/AIDS patients. Because the

sudden increase in HIV-related risk behavior has coincided with the widespread

use of with highly active antiretroviral therapy (HAART) for HIV/AIDS patients,

many researchers have suggested that such increase in unsafe sexual practices

among HIV patients might be directly related to HAART. Treatment with HAART

has been associated with many beneficial effects including increased survival,

improved quality of life, substantial decrease in viral load, and increase in CD4

count [39, 108, 109]. These positive effects might have given individuals a “false

sense of security”, and subsequently decreased their compliance with

recommended protective behaviors [24, 39]. Unfortunately, studies relating

HAART to increased unprotected sex have had mixed results. While some

studies have reported a positive relationship between use of HAART and high 34 risk sexual practices among HIV positive men and women [29, 110], others have failed to report such findings [24, 111, 112].

Non-HIV related factors

Personal characteristics of the individual such as age, sex, race, and economic condition have generally been found to be poor predictors of high-risk sexual behaviors among HIV positive patients [16, 113].

Studies that have examined the relationship between situational factors and sexual risk taking among PLWHA have had mixed findings. Situational or contextual variables correspond to social or environmental “circumstances” that can inhibit or motivate behavior, and may include factors such as substance use and negative mood states [76]. Studies investigating the role of substance use on sexual risk behavior have had modest findings [13, 16].

Negative emotional states such as anxiety and depression, as well as poor coping strategies have been shown to be common in patients with

HIV/AIDS, and to be related to increased high-risk behavior (Angelino, 2002;

Beck et al., 2003). However, studies relating negative mood states and sexual practices in HIV patients have had inconsistent findings [16]. Finally, attitudes towards sexual risk behaviors, in particular safe sex fatigue or burnout, have been demonstrated to be associated to sexual risk taking, and may be consistent with “cognitive escape” approache, which posit that individuals may engage in unprotected sex because being consistently aware of HIV and engaging in safe sex behavior become aversive over time [108, 114]. 35

4. Shortcomings of previous research in HIV/AIDS Patients

Overall, the vast majority of research on correlates of safe sex practices in

HIV infected persons has explored the role of a limited set of factors that are

sociocognitive in nature. Those variables may be grouped into four main

constructs: self-efficacy, outcome expectancy (e.g. attitudes towards high-risk

sexual behavior), outcome values (e.g. reduced concern about HIV), and the

individual’s beliefs about HIV treatment. Each of the constructs has been related

to HIV-risk behaviors in at-risk populations; however, they have had limited

validity in HIV-infected persons (see Table 1). This limitation may stem from several reasons. First, a number of other sociocognitive variables that have not been examined may offer better prediction of sexual risk behavior with regards to protective decision-making of seropositive individuals. Second, social cognitive approaches generally emphasize the rationality of individual decision-making process. This emphasis on rationality in the area of sexual behavior has been criticized on various grounds. A number of researchers have suggested the importance of other types of factors, such as situational factors, which may allow for non-rational influences on individual sexual decision-making process.

a. Additional Sociocognitive variables

Social cognitive theories traditionally assume that “people weight expected costs against expected benefits and make decisions based on what they think will best serve their self-interest and personal well-being”. Little emphasis is placed on “people’s morals or obligations to their fellow human beings” [115]. In 36 the case of PLWHA, however, the motivation to adopt and maintain safer sex behaviors is somewhat obscured by the interpretation of the benefits versus the costs of behavior. Indeed, given that they are already infected, the costs of engaging in unprotected sex (e.g. perceived threat for contracting HIV) may appear lower or nonexistent compared to the benefits (e.g. increased spontaneity and pleasure) of unprotected sexual intercourse. For example, a number of studies have found that the most common self-justification for unprotected sex among HIV-infected persons was that “they felt they had nothing to lose” [11,

116-118]. Thus, self-protection, previously shown to be one of the best motivating factors for engaging in protected sex among seronegative individuals, will probably be less relevant in the present context. By contrast, the individual’s motive for protecting his/her sexual partner so as to avoid subsequent feelings of guilt might be a relevant factor to consider. Three such constructs are moral norms, religious/spiritual beliefs, and anticipated regrets.

Moral norms refer to the individual’s conviction of the moral correctness or incorrectness of certain forms of behavior, regardless of their personal or social consequences [1, 119]. A number of studies have demonstrated that moral norms are likely to have an important impact on behaviors with a moral or ethical dimension [1]. Engaging in high-risk sexual behavior is one of such behaviors since it has the potential to transmit HIV to healthy individuals.

Similarly, individuals’ level of religious/spiritual beliefs may be an important factor with regards to sexual decision-making of PLWHA. Past research has documented the beneficial effects of religiousness, spirituality or both on a 37 number of health risk-behaviors including alcohol, drug, or tobacco use, violence, poor nutrition and lack of exercise [120, 121]. With regards to HIV prevention, having strong religious beliefs (e.g. degree of personal devotion and involvement) has been consistently and positively associated with less sexual risk-taking, fewer sexual partners, more positive attitudes toward condom use, and higher sexual communication self-efficacy and greater perception for HIV risk [122, 123]. Moreover, a small number of studies with those with HIV/AIDS indicate that religiousness and spirituality are associated with increased survival and decreased high-risk behaviors. Arnold and colleagues [124] conducted an exploratory study with 21 HIV-positive drug users and found that altruism/protection of others, a component of spirituality, was associated with HIV harm reduction behaviors, including not sharing drug paraphernalia and not engaging in unsafe sexual practices. Similarly, Ironson and colleagues [125], in a study that involved 279 HIV-seropositive patients, concluded that both religiousness and spirituality were important factors in the lives of those living with HIV, and were related to a number of beneficial outcomes including long survival, less affective distress, and more preventive behaviors. More specifically, compassionate view of others, a dimension that captures both spirituality and religiousness, was strongly related to very long survival, helping others and more willingness to disclose one’s HIV status to sexual partners.

While some authors have argued for a net differentiation between religiousness and spirituality, others have argued that both spirituality and religiousness should be considered together, as studies have showed that individuals’ 38 conceptualization of spirituality often varied from beliefs in God or a higher power, to practice of an organized religion, attending worship services, to an inner source of strength and altruism [124, 126].

Just as with moral norms and religiousness/spirituality, anticipated regrets may exert an important influence on sexual decision making of people living with

HIV/AIDS. A number of authors have demonstrated that for situations where the consequences of performing or not performing a given behavior are unpleasant, the anticipation of such negative feelings might make the individual less likely to perform it. For example, Richard and van der Plight [127] demonstrated that anticipated regret was an important predictor of condom use among adolescents.

Likewise, Richard et al. [128] found that anticipated negative reactions were related to subsequent condom use among their study participants. The concept, however, has yet to be evaluated in HIV-seropositive individuals.

Finally, a measure of social influences might be important with regards to sexual decision-making of HIV-infected persons. Although numerous studies have successfully examined the concept of perceived norms in at-risk populations, it has been relatively less studied in HIV-infected persons. However, social norms are likely to be an important determinant of sexual behaviors in this group.

Indeed, as protecting others rather than oneself against HIV infection is the key objective, the extent to which the individual cares about his or her partner is likely to influence sexual decision-making. Moreover, the degree to which the person feels able to make/negotiate sexual decisions within the relationship is expected to relate to his/her ability to adopt and maintain safe sex practices over time. 39

Relationship power or “the ability to make sexual decisions within the

relationship” [129] has received increasing research attention over the years.

Among women in particular, the lack of power or perceived lack of control in

relationships has been associated with more unprotected sex [129].

b. Importance of situational factors

Additional situational barriers, likely to operate in HIV-infected individuals

and impact their ability to consistently act rationally, need to be taken into account for a full understanding of high-risk sexual behaviors among HIV-positive

individuals. First, research with patients seeking care at HIV primary care clinics

or preventive health services have reported a fairly high prevalence of negative

mood states including depression, anxiety, and hostility [11, 30, 130-133]. For

example, a study by Cohen and colleagues [133] found that over 70% of the

patients had high anxiety and 46% had depression. Negative mood states, in

turn, have been shown to influence sexual-risk taking [11, 16, 117, 134].

However, studies of the relationship between emotional distress and unsafe

sexual practices have had inconsistent findings. Some studies have failed to find

any relationship [16], while others have found a negative relationship between emotional distress and sexual risk-taking [135]. This inconsistency in the findings may be related to the fact that the exact link between HIV disease and psychological distress is (still) not clear-cut. For example, depressive symptoms may lead patients to engage in higher-risk behavior (e.g. injection drug use) to begin with, subsequently leading them to become HIV infected [30, 136]. On the 40 other hand, rather than being direct, the relationship between negative mood states and high-risk behaviors might be mediated by cognitive factors: being infected may affect people’s mood states, which, in turn, might affect their ability to consistently engage in a rational decision-making about safe sex, thus leading them to high-risk sexual behaviors at times [11, 130].

Finally, another situational barrier that may operate in HIV-infected persons is substance use. The variable has been consistently related to sexual risk-taking across different population subgroups from adolescents [137], to women [12], and heterosexual and gay men [13]. The exact nature of the relationship between substance use and unsafe sexual practices, however, has yet to be elucidated. Substance use might have a direct effect on unsafe sex.

On the other hand, an HIV-infected person might “strategically” use substances as a means to “escape” from self-awereness of HIV, creating a state of “cognitive disengagement” where behavior is less under internal or external pressure, and thus leading the individual to more likely engage in high-risk behaviors [114].

Because a pilot study revealed a very low prevalence of substance use in the study population, we were not able to examine the effect of substance use in the present study.

5. Putting everything together: Towards an integrative model

The model depicted in Figure 3 follows from the literature review and integrates cognitive and situational factors that may help explain sexual decision- making among HIV-infected persons. First, the model postulates that two distinct 41 constructs will underlie the cognitive factors involved in PLWHA sexual decision- making: internal factor (Moral Norms, Outcome Expectancies, Religious Norms, and Self-efficacy) representing individuals’ own/internal value system or as related to their self-interest (e. g. motivation to satisfy their own physical or emotional needs), and external factor (Anticipated Regrets, Outcome Value, HIV

Treatment Beliefs, and Social Norms) representing values oriented towards others (e.g. their motivation to protect others). 42

Cognitive Factors Situational Factor Behavior

• Negative Affective States (Depression/Anxiety/Stress)

Internal Factor •Moral Norms •Self-Efficacy •Outcome Expectancies •Religious/Spiritual Norms

Sexual Risk Behavior External Factor •Anticipated Regrets •Social Norms •Outcome Value •HIV Treatment Beliefs

Figure 3. Proposed conceptual model: Integrated model for explaining HIV-infected persons sexual decision-making

Second, both cognitive factors will be postulated to be strong motivators for

PLWHA to engage in responsible sexual practices. Third, because sexual

decision-making is likely to be influenced by emotions, the model postulates that

a number of situational variables (negative affective states such as anxiety,

depression, or stress) will interfere with the individual’s ability to make a rational decision. Moreover, the model posits that rather than being direct, external and internal cognitive factors will mediate the relationship between situational factor and sexual behavior.

Chapter 3. Methods

1. Study Population, Setting and Design

The current study was conducted among men and women living with

HIV/AIDS in Abidjan, Cote d’Ivoire (West Africa). Cote d’Ivoire is currently the most affected country by HIV in West Africa and one the few countries providing antiretroviral therapy (ARV) at subsidized prices (between 50 to 95% subsidy) to patients who meet certain economic conditions. The sample comprises HIV- infected men and women who were currently attending an outpatient HIV clinic

(Unites des Soins Ambulatoires et de Conseils - USAC) in Abidjan. USAC is one of the six (and the largest) treatment centers in Abidjan. The present study employed a cross-sectional design and was conducted between January and

September 2004. The study protocol was approved by the clinic’s review board

and the Institutional Review Board (IRB) of the University Hospitals of Cleveland,

Ohio.

Subjects were enrolled in the study if they met the following inclusion

criteria and none of the exclusion criteria.

Inclusion criteria

• Age greater or equal to 18 years

• Having a known HIV positive status for at least 6 months as of the time

of the interview

• Primary school or higher education level 44

Exclusion criteria

• Too physically ill to sit through the interview process

• Unable or unwilling to give informed consent to participate

• Poor cognitive status (Mini-Mental State Exam score of 22 or lower)

In Abidjan, most people speak French, including those with no formal education. However, to make sure that the study only included subjects who had a good understanding of the questionnaires (and thus, were likely to give valid answers), the study included only people who had attained primary or higher education.

A convenience sampling method was used to select the study sample.

Eligible participants were informed about the study by the attending clinician or nurse during their regular medical visit. Next, each subject was actively approached at the end of his/her visit by one of the trained interviewers to explain the goals of the study and request her/his consent to participate. Although a convenience sampling was used, almost all the patients who were approached and were eligible agreed to participate.

2. Training of the interviewers and Pilot study

Four interviewers were initially recruited to help with data collection. We advertised for interviewers who were fluent in French, had at least graduated from high-shool, and had previous experience in conducting surveys. The training of the interviewers took 1 day (divided up into 3 sessions). During the 45

first session, a general presentation of the study was provided (i.e. goal of the

study, plan for recruitment of subjects and consent process), as well as a

discussion about the ethical principles of research involving human subjects.

More specifically, the sensitive nature and ethical implications of the current study were stressed, including the increased requirement of confidentiality of all the information to be collected and the privacy of the participants. The second

session included a general discussion of the questionnaires (description of the

different sections and instructions pertaining to each section; overview of the individual questions and answer codes; suggestions and recommendations for editing completed questionnaires and answering respondent’s questions). Any ambiguity in the questions was solved. Finally during the third session, each

interviewer had a chance to conduct a practice interview with an actual respondent. The session was followed by a review of the interviewer’s

performance, some general recommendations, and work planning issues.

During data collection, the interviewers were routinely provided feedback

about their performance. In the first week of the initial data collection, a meeting

was held at the end of each data collection day to go over the collected data and

discuss any issues and/or difficulties they might have encountered during the

interviews. As the data collection went along, the meetings were held on a

weekly basis. In addition, the completed questionnaires were routinely checked

for mistakes and any concern was immediately discussed with all the

interviewers.

All the data collected during the initial data collection period (N=144) were used as a pilot test for assessing the feasibility of the study, and pretesting the questionnaire. All the collected data were analyzed at the end of the pilot study.

Basis descriptive statistics (frequency distributions and measures of central tendency) were generated for all the major study variables of interest. Patterns of missing values and variability for each variable were noted. The psychometric properties of the measured scales were also evaluated by examining the following characteristics: the item means, item-total correlations, overall

Cronbach’s alpha value, and Cronbach’s alpha value after item deletion.

Anticipated Regrets, Outcome Value, Outcome Expectancies scales had unacceptably low Cronbach’s alpha coefficients. Thus, these scales were revised for the second round of data collection. Finally, an exploratory factor analysis was also conducted (principal axis factoring followed by a varimax prerotation and a promax rotation) to assess the hypothesized factor structure of the scales. Modifications were made to the instrument as appropriate prior to the final round of data collection.

3. Data Collection

All the data were collected through face-to-face interviews by three trained interviewers using an instrument constructed specifically for this study. The translated versions of the various measures were used whenever available. For example, the French version of the Mini-Mental State Examination (Version consensuelle du GRECO) and the French version of the Hospital Anxiety and 47

Depression Scale were used. In cases where the French version was not

available, the English version of the items were first translated in French by the

investigator and back-translated to English by a graduate student from the

department of Languages at the University of Abidjan, Cote d’Ivoire. There were

few discrepancies between the 2 versions, and the ones that arise were mainly

due to difficulty in translating some ‘technical’ terms (e.g. Outcome Expectancies,

Outcome Value). In such cases, discrepancies were resolved by language experts at the university.

The majority of the established scales had not been previously used in the target population. Consequently, the translated instrument was extensively evaluated prior to its use by a group that consisted of a staff physician from the

clinic, the 3 interviewers and the investigator. Each item was carefully reviewed

for the adequacy of the language and cultural sensitivity for the study population.

Appropriate changes were made. Additional feedback was obtained from the

first 10 interviewees with regard to any difficulties in understanding the

questionnaires, and modifications were also made as needed.

Each interview lasted approximately 50 minutes and was conducted in

French. Interviews were conducted at the clinic in separate rooms in order to

protect the privacy of the subject and the confidentiality of the collected data.

Participants’ mental status was evaluated using the Mini-Mental State Exam, a

tool developed by Folstein and colleagues [138] and used to screen for cognitive

impairment in clinical settings as well as in epidemiological studies [138]. Higher 48

scores indicate higher cognitive ability. Subjects with a score of 22 or lower (total

possible scores of 30) were subsequently excluded from the study.

4. Measures

The dependent variable was a measure of the participant’s sexual

practices in the preceding 6 months, obtained using a series of questions (4 to 6)

designed to measure the frequency of various sexual practices determined to increase or decrease the risk of HIV transmission. Measures included participants’ reported condom use with regular and/or casual partners, and the extent to which they disclose their HIV status to their partner(s) prior to sexual intercourse. The independent variables included 8 sociocognitive variables

(Anticipated Regrets, Moral Norms, Religious Norms, Perceived Social Norms,

Outcome Expectancies, Outcome Values, Beliefs about HIV/AIDS Treatment, and Sexual Self-efficacy) and 3 psychological distress variables (Anxiety,

Depression, and Perceived Stress) (see Appendix 1 for more details). The items for the measured scales were selected or adapted from previous studies [26,

119, 128, 139-143]. In addition, information on participants’ socio-demographic background and health status were recorded. Table 2 summarizes the variables measured in the study. 49

Table 2. Summary table for the study variables Level of Concept measurement Source Coding Rule Sexual Risk Behaviors High-risk sexual behaviors (Sexually active (6 questions) Dichotomous AND inconsistent/no condom use inconsistent status diclosure) 1, 2. Have regular or casual sexual3. Frequency partner(s) of condom use 1="yes"; 2="No" 1="Always" and/or to 4="Never" VERSUS Low-risk sexual behaviors with regular partner 4. Frequency of condom use 1="Always" to 4="Never" with casual partners 5,6. Disclosure/Frequency of status disclosure 1="Always" to 4="Never"/ prior to sexual intercourse to regular/casual partners 1="yes"; 2="No"

Moral Norms (6 items) Ordinal Terry and Hogg, 2000 1="Str. disagree" to 4="Str. agree" Summary scores (higher scores= higher moral norms) Sexual Self-Efficacy (7 items) Ordinal Dilorio et al., 1997 1="Not sure at all"; 4="Very sure" Summary scores (higher scores= higher self-efficacy) Anticipated Regrets (8 items) Ordinal Richard et al. 1995 1="No regrets at all"; Summary scores (higher scores= higher 3="Lots of regrets" anticipated regrets) Religious Norms (4 items) Ordinal Krause, 2003 1="Str. agree" to 4= "Str. disagree" Summary scores (higher scores= higher 1="Several times a week/day"; religious/spiritual beliefs) 8-9="Never" Outcome Expectancies (6 items) Ordinal Sherman et al. 2003; 1="Str. disagree" to 4= "Str. agree" Summary scores (higher scores= higher Dilorio et al., 1997 1="Very confident";4="Don't know" positive outcome expectancies) Outcome Values (4 items) Ordinal 1="Str. agree" to 4= "Str. disagree" Summary scores (higher scores= higher outcome values) Social Norms (7 items) Ordinal 1="Str. disagree" to 4= "Str. agree" Summary scores (lower scores= higher social norms) Beliefs about HIV treatment (5 items) Ordinal Elford et al. 2001 1="Str. agree" to 4= "Str. disagree" Summary scores (higher scores= less optimistic beliefs about HIV treatment)

Anxiety/Depression Presence of anxiety (score >= 7) or (14 items) Ordinal Zigmund & Snaith, 1983 depression (score >= 7)

Perceived stress Summary scores (higher scores= higher (14 items) Ordinal Cohen et al., 1983 1="Never"; 5="Very often" higher perceived stress) Str.= Strongly 50

5. Data Management/ Quality Control

At end of the interview, each questionnaire was first sight-checked in order

to resolve any discrepancy while the respondent was still present. Second, the

collected data were entered using a data entry form specifically developed for the

study using the survey software Snap [144]. During their entry, the data were

edited via computerized range and logic checks to flag any missing, inconsistent

or out-of-range values. Any detected error was corrected whenever possible.

The cleaned data were then stored on computer drives at two different locations, with access restricted to the investigators, and were routinely backed-up on

floppy disks and cd-roms. Hard copies of the questionnaires are kept at the

investigator’s residence, and will be archived for several years as required by the

study regulatory board.

6. Analytic plan

a. Descriptive analyses

The study sample was described by its demographic characteristics (age,

sex, education, marital status, occupation, religious preference) and by all of

the main outcome (i.e. health risk behaviors) variables. Means and standard

deviations were used for normally distributed continuous/ordinal variables;

medians and ranges for non-normally distributed ones. Categorical variables

were described using actual number and percentages. In addition, the

psychometric properties of all the measured scales were evaluated.

51 b. Bivariate analyses

To examine the demographic, cognitive and situational variables associated with HIV transmission and reinfection risk due to unsafe sex, participants were classified into two groups based on their answers to the four questions assessing their sexual behaviors. Participants who had multiple sexual partners, and/or engaged in unprotected sex, and/or inconsistently disclosed their HIV-status to their partner(s) were defined as being at high risk for

HIV transmission or reinfection. In contrast, those who did not engage in any of those behaviors were defined as being at low or no risk for HIV transmission or reinfection. Differences between the two groups were examined using Student’s t-test for normally distributed continuous/ordinal variables (Wilcoxon-rank tests for non-normally distributed ones), and chi-square/ Fisher’s exact test for categorical variables. Two-tailed p values of less than 0.05 were considered statistically significant.

c. Multivariate analyses

Specific aim 1: Validate the constructs of external and internal cognitive factors involved in the sexual decision making of PLWHA

Research hypothesis 1.1: Two major factors (external and internal) will

underline the cognitive processes influencing sexual decision-making in

persons living with HIV/AIDS. 52

Research hypothesis 1.2: Anticipated Regrets, Outcome Value, Beliefs about

HIV Treatment, and Perceived Social Norms will load on the external

cognitive factor.

Research hypothesis 1.3: Moral Norms, Self-Efficacy, Outcome

Expectancies, and Religious/Spiritual Beliefs will load on the internal cognitive

factor.

An exploratory factor analysis (principal axis method followed by a

varimax prerotation and a promax rotation) was used to verify the factor structure

of the measured scales. The goal of the principal axis factoring was to maximize the amount of variance extracted from the variables with each succeeding factor.

After extraction, an oblique rotation (Promax) was used to obtain factors that were correlated with one another, unambiguous and that achieved simple structure (i.e. each variable loads only on one factor). The following criteria were used for determining the number of factors to retain: (1) The scree test, a graph that plots the eigenvalues (i.e. the amount of variance that is accounted for by a given factor) against the number of factors, and that recommends retaining only factors located on the initial portion of the plot through visual inspection; (2) The total amount of variance accounted for by each factor (20% or higher); (3) The size of the factor loadings, which measure the relationship between the factor and the variable (loadings under 0.40 are usually considered less meaningful) and (4) The interpretability of the factor solutions. Where the obtained factor solution did not fit the hypothesized factor solution, the following steps were 53

taken: (1) comparisons between the hypothesized factors and the factor solution

were made; (2) the most parsimonious solution was selected, interpreted conceptually, and submitted to the confirmatory factor analysis to test whether the theoretical number of factors adequately fit the data.

Specific aim 2: Test a proposed conceptual model explaining the continued

sexual risk-taking in HIV-infected persons in terms of cognitive and situational

factors

Moral Norms Outcome Self - Religious Norms Expectancies Efficacy

Internal Cognitive Factor

Anxiety

Depression Situational Factor Sexual Behavior

Perceived Stress

External Cognitive Factor

Anticipated Outcome Beliefs about Social Regrets Value HIV Treatment Norms

Figure 4. Hypothesized conceptual model

Structural equation modeling (SEM) using SAS CALIS procedure (SAS

Institute, 1989) was used to address the second study aim. This statistical

technique was appropriate for several reasons: (1) As a multivariate technique, it 54 allows examination of a set of complex relationships between one or more

(continuous or discrete ) independent variables and one or more (continuous or discrete) dependent variables (Ullmann, in Tabachnick and Fidell, 2001); (2) Both the independent and dependent variables can be measured (observed) variables or latent variables (factors), which are not directly measured but rather assessed through multiple indicator (or manifest) variables; (3) It is the only technique that allows the testing of models OVERALL rather than of coefficients individually; (4)

The estimated relationships are free of measurement error since the error terms are specifically modeled; and finally, (5) It is a powerful technique which can take into account difficult data (e.g. correlated independent variables, non-normal data, and multicollinearity).

A two-stage modeling procedure was used to test the proposed conceptual model. First, a confirmatory factor analysis (CFA) was performed to develop the measurement model, i.e. the part of the model that describes the relationships between the latent constructs and their indicator or manifest variables. Then, in the second stage, the structural model (the part of the model that specifies the causal relationships between the latent constructs) was evaluated. Prior to the analyses, all the key assumptions for the SEM approach were checked. More specifically, all the measured variables were assessed for normality and appropriate transformations were performed when necessary to improve normality. However, as a number of variables still departed from a normal distribution and the study sample size was relatively small, we followed the recommendations of West and colleagues for using SEM in such instances. 55

Thus, because none of our data substantially departed from non-normality according to the recommended criteria (i.e. none of the univariate skewness was above 2 and none of the univariate kurtosis exceeded 7), the maximum likeliwood (ML) method was used to estimate all the models. Four goodness-of- fit indices were used for evaluating each model: the chi-square goodness-of-fit test, the comparative fit index (CFI; Bentler, 1990), Bollen’s incremental fit index

(IFI; Bollen, 1989), and the root mean square error of approximation (RMSEA;

Browne and Cudeck, 1993). The model chi-square fit index tests the null hypothesis that the model fits the data (i.e. the estimated covariance matrix is not different from the observed covariance matrix), with a non-significant p value (p greater than 0.05 and preferably closer to 1) indicative of a good model fit.

However, because the test is very sensitive to sample size and departures from multivariate normality, a significant p value on the chi-square test in itself does not generally result in the rejection of the model. Instead, a chi-square/degree of freedom (df) ratio of less than 2 is usually used as a more liberal criterion for a good model fit. Bentler’s CFI and Bollen’s IFI have been particularly recommended for smaller sample sizes under substantial departure from non- normality (West and al.; in Hoyle, 2000). The CFI compares the observed covariance matrix with the null model (covariance matrix of 0s) to estimate the percentage of lack of fit accounted for by going from the null model to the hypothesized model. Values of CFI greater or equal to 0.9 are generally viewed as acceptable, indicating that “90% of the covariation in the data can be reproduced by the measured model” [145]. Bollen’s IFI also compares the fit of 56 the hypothesized model to the fit of the null model. For example, a value of 0.50 indicates that the postulated model improves the fit by 50% compared to the null model. IFI may assume values between 0 and 1, with values above 0.9 and close to 1 indicative of a good model fit. In the present analysis, the Bollen’s delta

2, an equivalent to the IFI that is printed by the SAS output and that more clearly adjusts for sample size influences, will be reported. Finally, the RMSEA estimates the lack of fit in a model compared to a perfect (saturated) model [146].

In general, values of 0.06 or less are indicative of a good model fit, whereas values larger than 0.1 indicates a poor-fitting model.

d. Sample size requirement

The sample size calculation for the study was based on the

multivariate model. In order to obtain stable parameters, large samples are

generally required for SEM. As a rule of thumb, the larger of 150

observations or 5 observations per parameter to be estimated are

recommended [147]. There were 28 parameters to be estimated in the

hypothesized model, leading to a minimum sample size of 140.

More formal methods for determining the necessary sample size to

achieve a desired power have also been developed. MacCallum, Browne,

and Sugawara [148] provide tables for estimating the minimum sample size

needed for the goodness of fit based on the RMSEA, and taking into account

the model’s degrees of freedom and the effect size. In the present study,

there were 12 measured variables, 12*(12+1)/2 (i.e. 78) data points, 28 57 parameters to be estimated (11 variances, 11 factor loadings, 2 covariances between latent constructs, and 4 regression coefficients), and 50 degrees of freedom (78 data points – 28 parameters). Thus, with 50 degrees of freedom, a power of 0.80 for a RMSEA close to 0.05 can be achieved with a minimum sample size of approximately 214 [148] (page 144). 58

Chapter 4. Results

1. Descriptive Analysis

a. Characteristics of the study participants

A convenient sampling procedure was used for recruiting the participants.

Clinic attendants were actively approached at the end of their visit and asked to participate in the study. Three-hundred ninety (390) individuals completed interviews, of which 51 subjects were excluded (after data collection) because of cognitive impairment or inadequate level of education, leaving 349 subjects as the final study sample. We were unable to calculate an accurate refusal rate because, to protect patients’ confidentiality, the names of those approached were not recorded and non-participants may have been approached more than once.

However, the majority of those approached were willing to participate. The most frequently cited reason for refusal was lack of time.

The socio-demographic characteristics for the 349 participants are presented in Table 3. The sample was evenly split with regards to sex (49.7% male and 50.3% male). The proportion of participants who were married or living with a partner was quite similar to that of participants who were single/never married (41% each). The majority of the study sample was between the ages of

25 and 44 years and currently employed. Over 82% of the respondents had education beyond primary school, and more people (42%) described their income level as fair. Religious affiliation was as follows: 57% Christian, 29.8%

Muslim and 13.2% other. 59

Table 3. Socio-demographic information for the study group

Variables (N=349) Sex Female 50.3 % Male 49.7

Age in years 18-24 3.2 % 25-34 36.9 35-44 48.1 45-54 10.7 55 and over 1.2

Marital status Married or Living with a partner 40.9 % Widowed, separated, or divorced 18.2 Single/Never married 40.6 Refused 0.3

Highest educational level attained Primary 16.9 % Secondary 51.9 Beyond secondary 30.9 Refused 0.3

Currently employed Yes 66.2 % No 33.8

Religious affiliation Christian 57.0 % Muslim 29.8 Other or refused 13.2

Perceived income adequacy Very good/good 26.5 % Fair 42.4 Poor 31.1

60 b. Health status and Sexual behaviors of the participants

The length of time since testing seropositive varied widely, with mean disease duration of 50 months (approximately 4 years) and a range of 7 months to 20 years. When asked about their overall health status in the previous 6 months, the majority (66.8%) rated their health status as very good or good.

Over three quarters of the respondents were currently receiving antiretroviral therapy and the majority reported always taking their medications as prescribed

(Table 4).

Table 4. Health information for the study participants Variables (N= 349) 1 Perceived health in previous 6 months or since the diagnosis Very good or good 66.8 % Fair or poor 31.2 Don't Know 2.0

How much HIV infection has made you change your lifestyle

A lot 26.9 % Some 11.5

Not at all 56.5 Refused or don’t know 5.1

Currently taking treatment for HIV Yes 78.9 % No 2 21.1

Self-reported adherence to antiretroviral therapy Always as prescribed 80 % Very often 7 Fairly often 5 Sometimes/never 8 1 Unless otherw ise indicated 2 Included those w ho said No "Are you aw are of treatments currently available for treating people w ith HIV/AIDS?" and those w ho said N o to "Are you currently taking any treatment for HIV/AIDS?" 61

Most respondents (56.5%) reported that knowledge of their HIV status didn’t make them change their lifestyles. For those who indicated that they have made some changes as a result of testing positive for HIV, the most frequently cited changes were general behavioral changes (e.g. quit drinking and smoking, avoid strenuous activities and going out; 63.4%), better compliance with health care professionals’ recommendations in term of diet and medical follow-up

(47.0%), safer sex (e.g. more condom use, fewer partners, sexual abstinence;

34.3%), and general social changes (e.g. more reserved, more spiritual; fewer social interactions; 17.9%). Most subjects reported multiple changes. Compared to those who indicated no lifestyles changes due their HIV serostatus, respondents who reported one or multiple lifestyles changes were less likely to describe their health status as good or very good (72% versus 61% respectively, p = 0.04) and more likely to report higher level of anxiety (23% versus 37% respectively, p = 0.009). There were no significant differences between the two groups with regards to any other demographic or health-related variables (Table

5).

Table 5. Association between the demographic and psychological distress variables and 1 the variable 'lifestyle changes'

Variables Lots of/Some Changes No Changes P-value 2 (N=133) (N=196) Sex Female 53.4 % 47.7 % 0.31 Male 46.6 52.3

Age in years 18-44 88.7 % 88.3 % 0.90 45 and over 11.3 11.7 Marital status

Married or Living with a partner 43.1 % 38.3 % 0.38 Widowed, separated, divorced, 56.9 61.7 single or never married

Highest educational level attained Primary 19.6 % 14.2 % 0.20 Secondary or beyond 80.4 85.8

Employment status Employed 67.9 % 67.0 % 0.68 Unemployed 32.1 33.0

Perceived income adequacy Very good or good 28.6 % 26.5 % 0.68 Fair or Poor 71.4 73.5

Perceived health Very good or good 61.2 % 71.9 % 0.04 Fair or Poor 38.8 28.1

Anxiety Possible anxiety case 36.6 % 23.3 % 0.009 No anxiety 63.4 76.7

Depression Possible depressive case 32.1 % 22.8 % 0.06 No depression 67.9 77.2

Perceived stress High perceived stress 53 % 48.7 % 0.45 Low perceived stress 47 51.3 1 Some respondents had missing information on the variable 2 Chi-square test used unless specified 63

Findings about the respondents sexual risk behaviors during the past 6 months are presented in Table 6. Fifty-seven percent (56.7%) of the participants reported having a regular partner and 16.9% reported having casual partners.

Among those with a regular partner, 24% did not know the HIV status of their partners, while 21% reported that their partner was HIV-negative. The majority

(55.2%) of those reporting casual partners did not know the HIV status of those partners, while only 24% knew that their partners were HIV-positive. The frequency of unprotected sex with both regular and casual partners was fairly high among the group. Thirty-five percent of the respondents with a regular partner and 28% of those with a casual partner reported inconsistent or no condom use at all.

The pattern of HIV status disclosure differed greatly by relationship status.

Seventy-seven percent of the respondents with a regular partner had disclosed their HIV status to their sex partner in the previous 6 months, while only 24% of those with casual sexual partners reported consistently disclosing their HIV status to their sex partners (Table 6).

Table 6. Study participants' sexual risk behaviors Variables (N= 349) 1

Had a regular sexual partner 57.6 %

Had casual partners 16.9 No partner 32.7

HIV status of regular partner (n= 201) Positive 54.5 % Negative 21.0 Unknown 24.5

HIV status of casuals partners (n= 59) All Negative 5.2 %

Some positive 15.5 All Positive 24.1

Unknown 55.2

Frequency of condom use with regular partner (n=191) Always 62.8 % Sometimes, rarely or never 35.1 Refused/Don't know 1.6 Not applicable (sexual abstinence) 0.5

Frequency of condom use with casual partners (n= 58) Always 70.7 % Sometimes, rarely or never 27.6

Don't know 1.7

Disclosed HIV status to regular partner (n= 201) 77.5 %

Frequency of HIV status disclosure to casual partners (n= 58) Always 24.1 % Sometimes, rarely or never 75.9 1 Unless otherw ise indicated 65 c. Psychometric evaluation of the measured scales

A total of 11 scales were measured in the study: Moral Norms, Self-

Efficacy, Anticipated Regrets, Outcome Expectancies, HIV Treatment Beliefs,

Outcome Value, Social Norms, Religious Norms, Anxiety, Depression and

Perceived Stress. Each scale was evaluated by examining the following characteristics: the item means, item-total correlations, overall Cronbach’s alpha value, and Cronbach’s alpha value after item deletion. All the psychometric analyses were based on individuals who provided an answer to all items for the given scale.

The results of the psychometric evaluation of the individual scales are presented in detail in Appendix 1. One criterion for a good scale is to have all items highly intercorrelated. This was particularly true for 5 of the 11 scales. The correlation coefficients for the items on each of these 5 scales (Moral Norms,

Outcome Value, Social Norms, Religious Norms and Depression) were all statistically significant at the 0.05 alpha level , and ranged from 0.11 to 0.90 (see

Appendix 1). There were some exceptions. On the Self-Efficacy scale, item 7 had several low correlations with the other items on the scale. The same was true for items 1, 2 and 6 on the Anticipated Regrets scale, items 5 and 6 of the

Outcome Expectancies scale, item 1 on HIV Treatment Beliefs scale, item 6 on the Anxiety scale and items 10 and 12 on the Perceived Stress scale (see Tables

B.1, C.1, D.1, F.1, I.1, and K.1- Appendix 1).

Appendix 1 also shows the descriptive statistics and reliability data for all the scales. Overall, the scales showed good reliability. The distribution of the 66 item means for the majority of the scales were either close to their expected values (i.e. near the center of the range of possible scores for each item) or only off by half point. The only exception was with items 4, 6, and 8 of the Outcome

Expectancies scale, item 13 on the Perceived Stress scale, the items on the HIV

Treatment Beliefs scale, the Religious Norms scale, the Anxiety scale, the

Depression scale, and the Self-Efficacy and Anticipated Regrets scales. Most of the item-total correlations were 0.20 or greater, indicating that each item correlated substantially with the set of remaining items. Again, the only exceptions were with some of the previously mentioned items, i.e. item 7 on the

Self-efficacy scale, item 6 on the Anxiety scale, and item 12 on the Perceived

Stress scale. Examination of the Cronbach’s alpha values if the items were deleted from their respective scales showed that the only internal consistency reliabilities that greatly improved after item deletion was that of the Outcome

Expectancies where deletion of items 5 and 6 increased the Cronbach’s alpha from 0.6 to 0.7, and that of the Self-Efficacy scale, where deletion of item 7 changed the alpha coefficient from 0.84 to 0.89. The 3 items were subsequently deleted from their respective scales, leaving 4 items in the final Outcome

Expectancies scale and 6 items in the Self-Efficacy scale. Table 7 shows the descriptive statistics and the Cronbach’s alpha for the 11 scales. The computed coefficients ranged from 0.70 to 0.93, indicating high internal consistency for each scale. 67

Table 7. Descriptive statistics and Cronbach's alpha for the measured scales

# correlated Number items over Coefficient Variables N of items Mean Std Range total alpha Moral Norms 348 6 20.0 3.3 11-24 6 /6 0.86 Self-Efficacy* 348 6 20.1 4.5 0-24 6 /6 0.89 Anticipated Regrets* 345 8 16.9 2.6 0-24 5 /8 0.74 Outcome Expectancies 336 4 7.5 1.5 4-13 4 /4 0.70 Outcome Value 348 4 10.3 2.2 4-16 4 /4 0.86 HIV Treatment Beliefs 308 5 16.4 2.2 7-20 4 /5 0.81 Social Norms 345 7 13.8 2.7 7-22 7 /7 0.78 Religious Beliefs 344 4 21.4 5.0 6-25 4 /4 0.77 Anxiety 343 7 5.3 3.6 0-16 6 /7 0.78 Depression 343 7 4.2 4.9 0-20 7 /7 0.93 Perceived Stress 338 14 22.0 10.0 4-52 12 /14 0.91 * Those answering "Don't Know" have been given a score of "0"

The mean scores for the vast majority of the sociocognitive scales were fairly high, indicating that participants generally endorsed higher (i.e. more positive) beliefs on these scales. The Hospital Anxiety and Depression Scale

(HADS) was used to assess the level of depressive symptoms (7 items) and anxiety (7 items) among the participants during the past 6 months [141]. On the original scale, a score of 7 or greater on the anxiety or the depression subscale is used to identify potential clinical cases of depression or anxiety. In our sample,

29% of the participants had a score of at least 7 on either subscale. The

Perceived Stress Scale was used to measure the degree to which respondents perceived the situations in their life as stressful [142]. The mean total score was 68

22.0, SD= 10.0, median= 21, and range= 4-52, indicating that all participants endorsed at least some symptoms in the previous 6 months. Using the median as the cut-off point for classification purposes, 51% scored above the median, indicating a fairly high prevalence of perceived stress in our sample.

The normality of the 8 continuous variables (Moral Norms, Self-Efficacy,

Anticipated Regrets, Outcome Expectancies, Outcome Value, HIV Treatment

Beliefs, Social Norms, and Religious Norms) was assessed by inspecting histograms and computing the skewness and kurtosis for each variable. Three variables showed a marked departure from normality. A strong negative skewness was noted for Self-Efficacy, Anticipated Regrets, and Religious Norms, indicating a tendency for respondents to choose higher values on these scales.

Self-Efficacy and Anticipated Regrets also had a high kurtosis. Because data transformation did not improve the normality of these variables, non-parametric statistical tests were used in subsequent analyses to examine the relationship between these variables and participants’ sexual risk behavior.

2. Bivariate Analyses: Factors associated with Sexual Risk Behaviors

To examine the demographic, cognitive and situational variables associated with HIV transmission and reinfection risk due to unsafe sex, participants were classified into two groups. Table 8 summarizes the classification criteria and the frequency distribution for those in the high-risk category. High-risk group was defined as being sexually active AND inconsistently or not disclosing one’s HIV status to regular and/or casual partner(s) and inconstantly or not using condoms with regular and/or casual partner(s).

Table 8. Classification into the high-risk group

Categories n(%) Overlapping* Total (%) ** categories

Regular partner and inconsistent condom use (n=191) 70 (36.6)

Casual partners and inconsistent condom use (n=58) 17 (29.3)

Regular AND Casual partners AND inconsistent condom use 5

Regular partner and non-disclosure of HIV serostatus (n=200) 45 (22.5)

Casual partners and inconsistent disclosure of HIV serostatus (n=58) 44 (75.9)

Regular AND Casual partners AND inconsistent/nondisclosure of serostatus 7

Regular partner AND inconsistent condom use AND nondisclosure of serostatus 25

Casual partners AND inconsistent condom use AND nondisclosure of serostatus 12

Total (n=349) 176 49 127 (36.4) * Numbers in this column represent respondents who were in multiple categories, and thus were "double-counted" ** Actual number of respondents classified as high-risk group

Thirty-six percent (36%) of the participants (127 subjects out of 349) were classified into the high-risk group, leaving 222 (64%) in the low-risk group.

Differences between the 2 groups were assessed using chi-square tests for categorical variables, Student’s t-test for normally distributed continuous variables, and Wilcoxon-rank test for non-normally distributed continuous variables. Results are displayed in Table 9 and 10 below. Means and standard deviations are reported for normally distributed continuous variables, medians and ranges for non-normally distributed continuous variables, and percentages for categorical variables.

Two-tailed p-values of 0.05 or less were considered as statistically significant. A number of demographic, health status, cognitive and situational variables were associated with high-risk sexual behaviors. HIV transmission and reinfection risk was more prevalent among men and women between the age of

18-44 compared to those 45 years or older (94% versus 85%; Χ2 (1, 347) =5.67, p = 0.02), those who were married or living with a partner compared to others

(51% versus 49%; Χ2 (1, 344) =7.73, p = 0.005), those who were not currently receiving antiretroviral therapy and those who reported less than perfect adherence to therapy (Table 9). With regard to the cognitive variables, compared to those in the low-risk group, participants in the high-risk group had lower sexual self-efficacy (p < .0001), lower religious norm (p = 0.01), but higher anticipated regrets (p = 0.002) (Table 10).

Table 9. Association between demographic and health status variables and sexual risk behavior

Variables High-risk Low-risk P-value 1 group (N=136) group (N=213) Sex Female 55.9 % 47.1 % 0.11 Male 44.1 52.9

Age in years 18-44 93.6 % 85.1 % 0.02

45 and over 6.4 14.9

Marital status Married or Living with a partner 50.8 % 35.4 % 0.005 Widowed, separated, divorced, 49.2 64.6 single or never married

Highest educational level attained Primary 14.2 % 18.6 % 0.29 Secondary or beyond 85.8 81.4

Employment status Employed 66.7 % 65.9 % 0.89 Unemployed 33.3 34.1

Perceived income adequacy Very good or good 31.2 % 23.9 % 0.14 Fair or Poor 68.8 76.1

Perceived health Very good or good 74.6 % 64.6 % 0.06 Fair or Poor 25.4 35.4

Currently taking antiretroviral therapy Yes 66.7 % 85.9 % < 0.0001 No 33.3 14.1

Self-reported adherence to therapy as prescribed Always/Very often 81.0 % 90.4 % 0.03 Fairly often/sometimes/never 19.0 9.6 1 Chi-square test used unless specified

Perceived health status, perceived stress, and depression were marginally related to sexual risk behaviors. Respondents in the high-risk group were marginally more likely than those in the low-risk group to perceive their health status as very good/good (75% versus 65%; Χ2 (1, 342) =3.65, p = 0.06), and to report lower level of perceived stress (55% versus 45%; Χ2 (1, 349) =2.99, p =

0.08). Finally, subjects in the high-risk group were less likely to be depressed compared to those in the low-risk group (23% versus 32%; Χ2 (1, 349) =3.32, p =

0.07).

Table 10. Association between measured scales and sexual risk behavior

Variables High-risk Low-risk P-value 1 group (N=136) group (N=213) Anxiety Possible anxiety case 26.8 % 30.2 % 0.50 No anxiety 73.2 69.8

Depression Possible depressive case 22.8 % 32.0 % 0.07 No depression 77.2 68.0

Perceived stress High perceived stress 44.9 % 54.5 % 0.08 Low perceived stress 55.1 45.5

Moral Norm, mean (SD) 19.5 (3.8) 20.2 (3.0) 0.08

Self-efficacy, median (Range) 19.0 (5-24) 21.0 (0-24) < 0.0001

Anticipated regrets, median (Range) 18.0 (5-20) 18.0 (0-24) 0.002

Outcome expectancies, mean (SD) 7.5 (1.7) 7.5 (1.4) 0.84

Outcome value, mean (SD) 10.3 (2.4) 10.2 (2.1) 0.64

HIV Treatment Beliefs, mean (SD) 16.6 (2.5) 16.3 (2.0) 0.32

Social Norm, mean (SD) 13.8 (3.0) 13.8 (2.5) 0.99

Religious Beliefs, median (Range) 24.0 (6-25) 24.0 (6-25) 0.01 1 Chi-square test used unless specified 74

3. Multivariate Analyses

The multivariate analyses were conducted only on subjects with complete data (288 out of the 349 participants). Incomplete data were mainly generated because the items on the HIV Treatment Beliefs scale were automatically skipped for participants who were not currently using or who were not aware of the availability of antiretroviral therapy. To verify whether those with missing data consistently differ from those with no missing data, we compared both groups with regards to selected demographic and risk behavior variables (see results in

Tables 11 and 12).

Table 11. Socio-demographic information for the study groups

Variables Total sample Complete data Incomplete data P-value (n=349) (n=288) (n=61) Gender Female 50.3 % 51.2 % 45.9 % 0.45 Male 49.7 48.8 54.1

Age in years 18-44 88.2 % 89.9 % 80.3 % 0.04 45 and over 11.8 10.1 19.7

Marital status Married or Living with a partner 41.0 % 40.7 % 42.4 % 0.81 Other 59.0 59.3 57.6

Highest educational level attained Primary 16.9 % 14.9 % 26.7 % 0.03 Secondary and beyond 83.1 85.1 73.3

Currently employed Yes 66.2 % 68.1 % 57.4 % 0.11 No 33.8 31.9 42.6

Religious affiliation Christian 57.0 % 59.0 % 47.5 % 0.04 Muslim 29.8 28.5 36.1 Other or refused 13.2 12.5 16.4

Perceived income adequacy Very good/good 26.5 % 27.6 % 21.3 % 0.31 Fair/Poor 73.5 72.4 78.7 75

The two samples slightly differed with regards to age, religious affiliation, and education level, with those with complete data more likely to have higher education compared to those in with incomplete data. Respondents in the complete dataset group were also more likely than those in the incomplete dataset group to report that knowledge of their HIV status didn’t make them change their lifestyle (60.2% versus 37.7 %, p < 0.0001). There was no difference between the 2 groups with regards to any of the sexual risk behaviors

(Table 12).

Table 12. Perceived health and sexual risk behaviors for the study groups

Variables Total sample Complete data Incomplete data P-value (n=349) (n=288) (n=61) Health Information

Perceived health last 6 months Very good or good 68.1 % 68.1 % 68.4 % 0.96 Fair or poor 31.9 31.9 31.6

Lifestyle changes due to HIV A lot 26.9 % 25.7 % 32.8 % < .0001 Some 11.5 11.8 9.8 Not at all 56.5 60.4 37.7 Refused or don’t know 5.1 2.1 19.7

Sexual behaviors last 6 months Had a regular sexual partner 57.6 % 58.7 % 52.5 % 0.37 Had casual partners 16.9 17.8 13.1 0.38 No partner 32.7 30.9 41.0 0.13

HIV status of regular partner (n= 201) Positive 54.5 % 55.4 % 50.0 % 0.13 Negative 21.0 22.6 12.5 Unknown 24.5 22.0 37.5

HIV status of casuals partners (n= 59) All Negative 5.2 % 6.0 % 0.0 % 0.21 Some positive 15.5 16.0 12.5 All Positive 24.1 28.0 0.0 Unknown 55.2 50.0 87.5

Condom use with regular partner (n=201) Always 59.7 % 61.5 % 50.0 % 0.10 Sometimes, rarely or never 33.3 30.8 46.9 Refused/Don't know/Missing 6.5 7.7 0.0 Not applicable (sexual abstinence) 0.5 0.0 3.1

Condom use with casual partners (n= 59) Always 69.5 % 68.6 % 75.0 % 0.12 Sometimes, rarely or never 27.1 29.4 12.5 Don't know/Missing 3.4 2.0 12.5

Disclosed HIV status to regular partner (n= 201) 77.5 % 79.2 % 68.7 % 0.19

HIV status disclosure to casual partners (n= 59) Always 24.1 % 28.0 % 0.0 % 0.27 Sometimes, rarely or never 75.9 72.0 100.0 1 Unless otherw ise indicated

Specific aim 1: Validate the constructs of external and internal cognitive factors involved in the sexual decision making of PLWHA

The factor structure of the measured scales was examined by performing an exploratory factor analysis (EFA) using SAS procedure. Three factors were extracted (Table 13).

Table 13. Factor loadings* and factor structure for the measured scales (N= 288) (order by size)

Scales** Factor 1 Factor 2 Factor 3 Moral Norms (I) -13 73 3 Self Efficacy (I) 7 64 -2 Outcome Expectancies (I) -10 0 70 Religious Norms (I) 9 24 26

Anticipated Regrets (E) 13 27 39 HIV Treatment Beliefs (E) -27 42 2 Social Norms (E) 3 -4 73 Outcome Value (E) -12 10 -16 Anxiety (S) 78 7-6 Depression (S) 81 33 Perceived Stress (S) 52 -16 10

* Factor loadings represent standardized regressions coefficients; Printed values are multiplied by 100 and rounded to the nearest integer. ** (I) Hypothesized as representing an Internal Cognitive Factor; (E) Hypothesized as representing an External Cognitive Factor

With a factor loading of 0.35 as the cutoff level for inclusion of a variable on any factor, three scales loaded on factor 1: anxiety, depression, and perceived stress. Because all these variables were related to negative mood states, factor 1 was labeled as the situational factor (SF; hypothesis 4). Three scales also loaded on the second factor (Moral Norms, self efficacy, and HIV treatment beliefs), and three scales (anticipated regrets, Social Norms, and outcome expectancies) loaded on the third factor. Contrary to our expectations,

HIV treatment beliefs, hypothesized to be an indicator of the external cognitive factor, loaded with Moral Norms and self efficacy, both posited to represent an internal cognitive factor. However, because the 3 variables seemed to be related in general to the individual personal values/thoughts about given situations or scenarios, this factor was labeled as the internal cognitive factor (ICF; hypothesis

1). Likewise, outcome expectancies, originally hypothesized to be measuring an internal cognitive factor, loaded with social norms and anticipated regrets, both hypothesized to be measuring an external cognitive factor. This factor, however, was still labeled as the external cognitive factor since most of the scales heavily loading on it (anticipated regrets, Social Norms) were related to individual beliefs/concerns about others, and outcome expectancies were also mostly related to a person’s concerns about how his/her behavior may affect his/her partners (hypothesis 2). The three extracted factors explained approximately

97% of the variance in the set of original variables. In addition, the low correlations among the factors (r = 0.02 to 0.24) suggested that the 3 factors were indeed distinct from one another (Table 14). 79

Table 14. Inter-factor correlations

Factor 1 Factor 2 Factor 3 Situational Factor (SF) 1.00

Internal Cognitive Factor (ICF) 0.24 1.00

External Cognitive Factor (ECF) 0.02 -0.22 1.00

Specific aim 2: Test a conceptual model explaining sexual risk-taking in

HIV-infected persons in terms of cognitive and situational factors.

Structural equation modeling (SEM) using SAS CALIS procedure (SAS

Institute, 1989) was used to address the second study aim. The analysis involved a two-stage modeling procedure. First, a confirmatory factor analysis

(CFA) was performed to develop the measurement model, i.e. the part of the model that describes the relationships between the latent constructs and their indicator or manifest variables. Then, in the second stage, the structural model

(the part of the model that specifies the causal relationships between the latent constructs) was evaluated.

a. Evaluating the model assumptions

The key assumptions of the SEM techniques are large sample sizes (at least 5 observations per parameter to be estimated for a small to medium models), and indicator variables with a univariate and a multivariate normal distributions. There were 21 parameters to be estimated for the model, leading to a minimum sample size of 105. Therefore the sample size for this study (n=

288) was adequate for using the SEM techniques.

As previously indicated, three variables showed a marked departure from normality. A strong negative skewness was noted for Self-Efficacy (skewness= -

1.60), Anticipated Regrets (skewness= -3.29) and Religious Norm (skewness= - 81

1.78), indicating a tendency for respondents to generally endorse higher values on these scales. Self-Efficacy and Anticipated Regrets also had a high kurtosis

(4.0 and 16.2, respectively). Inspection of the 2 scales for outliers revealed 4 cases (2 for each scale) with an extremely low score. Those cases corresponded to those answering “don’t know” to the items on the self-efficacy and anticipated regrets scales and thus were given a score of 0, which markedly contributed to the overall skewness of the two scales. After deletion of the 4 cases, the kurtosis and skewness of the scales greatly improved (skewness= -

1.24 and kurtosis= 2.18 for Self-efficacy; skewness= -2.07 and kurtosis= 5.33 for

Anticipated Regrets). However, attempts to improve the normality of the 4 scales through data transformation were still not very successful. Two options are usually recommended for estimating models in case of non-normality and when dealing with a relatively small sample size [149]: robust maximum likelihood estimation (MLE) which adjusts the chi-square for the amount of kurtosis in the data (Satorra-Bentler scaled chi-square), or normal maximum likelihood estimation (MLE) if the data do not substantially depart from non-normal distribution (e.g. skewness < 2, and kurtosis < 7). The latter estimation approach was employed to test all the models since the necessary conditions were met and robust ML estimation is not available in the SAS program. The input dataset

(i.e. the intercorrelations and standard deviations for the measured variables) used for the analyses is presented in Appendix 2.

82 b. Evaluating the measurement model with confirmatory factor analysis

The measurement model investigated in this study consisted of 3 factors with 3 indicator variables each (see Figure 5). In SEM, only models that are identified (i.e. models that provide unique numerical solution for each parameter) can be estimated [146]. As a general rule of thumb, a model is identified if there are more data points than parameters to be estimated or if each factor is measured by at least three indicator variables. In the present measurement model, there were 3 measured variables per latent factor thus 9*(9+1)/2 (i.e. 45) data points, and 21 parameters (9 variances, 9 factor loadings, and 3 covariances between latent constructs) to be estimated. Therefore, the measurement portion of the hypothesized model could be identified since it had more data points than parameters to be estimated.

Moral Norms Self-Efficacy HIV Treatment Beliefs

Anxiety Depression Stress Internal Cognitive Factor

Situational Factor

External Cognitive Factor

Anticipated Regrets Outcome Expectancies Social Norms

Figure 5. The initial measurement model 83

Only a marginal support was found for the hypothesized measurement model. The model chi-square was significant, both the CFI and the IFI were below 0.9 and the RMSEA was above 0.10 (Table 15). Thus, additional modifications were attempted to improve the model. Two modification indices are routinely used for model revisions in SEM: the Lagrange Multipliers (LM) test

(a statistical test that estimates the improvement in the model chi-square that would result from adding a new path, i.e. a new factor loading or a new covariance to the model), and the Wald test, a statistical test that estimates the change in the model chi-square that would result from fixing to zero a parameter in the current model (i.e. deleting an ‘unnecessary’ path or covariance). Only suggested modifications that could be theoretically/reasonably interpreted were implemented. However, in the present analysis, no reasonable modification was suggested. Thus, the measurement model was used for tentatively developing the structural model.

Table 15. Goodness of fit indices for the measurement model

Model Chi-square df p CFI Delta2 RMSEA

Initial model 128.05 24 < 0.0001 0.86 0.87 0.12

The standardized factor loadings for the indicator variables are presented in Table 16. Factor loadings are equivalent to path coefficients, with a non- 84 significant loading indicating that the indicator variable is not doing a good job in measuring the underlying factor [147]. The obtained t values (testing the null hypothesis that the factor loading is equal to zero in the population) show that all the factor loadings were significant at the 0.001 level (t values greater than 3.29) and were all moderate to large in size, ranging from 0.49 to 0.96.

Table 16 also shows the reliabilities of each indicator along with the composite reliability index for each latent factor included in the model. The reliability of the indicator is the square of the standardized factor loading and indicates the percent of variation in the indicator that is captured by the underlying factor [147]. The composite reliability for the latent factor is similar to

Cronbach’s alpha. In the present analysis, all the indicator reliabilities, as well as all the composite reliabilities for the latent factors were moderate to large, indicating acceptable levels of reliability.

Finally, Table 16 presents the variance extracted estimates for the 3 latent factors. This measure indicates the amount of variance explained by the underlying factors in relation to the amount of variance due to measurement error. Estimates greater than 0.50 are generally recommended (indicating that variance explained by the model is larger than the variance due to random measurement error). Only the variance estimates for the situational factor and the internal cognitive factor were above 0.50.

Table 16. Properties of the estimated measurement model

Factors and Indicators Standardized t* Reliability Variance extracted loading estimate

F1. Internal Cognitive Factor 0.74 0.51

V1. Moral Norms 0.96 13.79 0.92 V2. Self-Efficay 0.60 9.48 0.36 V6. HIV Treatment Beliefs 0.49 7.77 0.24

F2. External Cognitive Factor 0.74 0.49 V3. Anticipated Regrets 0.56 8.91 0.31 V4. Outcome Expectancies 0.78 12.08 0.61 V7. Social Norms 0.75 11.78 0.56

F3. Situational Factor 0.78 0.56

V9 Anxiety 0.74 12.09 0.55

V10 Depression 0.95 15.29 0.90

V11 Perceived Stress 0.49 8.09 0.24 * All t values are significant at p < 0.001

c. Evaluating the structural model

The initial structural model is depicted in Figure 6. The model consisted of

3 latent independent factors and one manifest variable (sexual behavior) as the dependent variable. Because the two latent endogenous variables (the internal and cognitive factors) were not related to each other, the structural portion for the model was identifiable [146]. The models’ fit was evaluated using the Bentler’s

Comparative Fit Index (CFI), the Bollen’s Incremental Fit Index (IFI, equivalent to the Bollen’s Non-Normed Index Delta 2 printed by the SAS output), the root mean square error of estimation (RMSEA), and the model chi-square. 86

Moral Norms Self-Efficacy HIV Treatment Beliefs

Anxiety Depression Stress

Internal Cognitive Factor

Situational Factor Sexual Risk Behavior

External Cognitive Factor

Social Norms Anticipated Regrets Outcome Expectancies

Figure 6. The initial structural model

Only a marginal support was found for the initial model with a significant model, a CFI and IFI below 0.9 and a RMSEA above 0.10 (Table 17). Therefore, further evaluation of the model was postponed and the results of the analysis were examined for appropriate modifications. On the basis of the Lagrange

Multipliers test, a path relating F3 and V12 (suggesting a relationship between situational factor and sexual behavior) was added. Adding this path improved the model’s fit, however, the overall fit was still marginal (Table 17). 87

Table 17. Goodness of fit indices for the estimated structural models

Model Chi-square df p CFI Delta2 RMSEA

Initial model 192.25 32 < 0.0001 0.80 0.81 0.13

Revised Model 183.89 31 < 0.0001 0.81 0.81 0.13 Path added: F3* to V12**

*F3: situational factor; **V12: sexual risk behavior

The revised structural model with all the standardized path coefficients is depicted in Figure 7.

Moral Norms Self-Efficacy HIV Treatment Beliefs

0.94 0. 62*** 0.49*** Anxiety Depression Stress

Internal Cognitive Factor 0. 94 0. 49*** -0. 29*** 0. 74*** -0. 14*

-0. 19** Situational Factor Sexual Risk Behavior

-0. 05 -0. 03 External Cognitive Factor

0. 53*** 0. 79 0. 76***

Anticipated Regrets Outcome Expectancies Social Norms Figure 7. Final structural model and standardized estimates. *p <= 0.05; **p <= 0.01; ***p <= 0.001

The model only explained 4% of the variance in sexual risk behavior. The

ICF was significantly related to sexual risk-taking, indicating that the lower the internal cognitive values, the higher the reported sexual risk behavior. Contrary to our hypothesis, the ECF did not affect the outcome. The SF, however, directly affected the sexual risk behavior (standardized path coefficient= -0.19), suggesting that having fewer situational barriers were related to more sexual risk taking. The SF also negatively affected the ICF. However, because the overall model failed to meet the minimally required statistical criteria for a satisfactory model, the hypothesized nonlinear effects (the mediating and interactive effects of the situational and cognitive factors on the outcome) were not examined. 89

4. Post-Hoc Analyses

Post-hoc model fitting are customary conducted in SEM in order to identify and correct for misspecified parameters [150]. Because the fit of the hypothesized model was very marginal, a number of post-hoc modifications were conducted in an attempt to find a better fitting model. The EFA conducted separately by sex had revealed a different factor structure for men and women.

Table 18. Factor loadings* and factor structure for the women (N= 147)

Scales Factor 1 Factor 2 Factor 3 Moral Norms (I) -20 8 64

Self Efficacy (I) 13 -4 68

Outcome Expectancies (I) -20 65 -3 Religious Norms (I) 10 55 9 Anticipated Regrets (E) 15 33 32 HIV Treatment Beliefs (E) -38 1 40 Social Norms (E) 3 69 -2 Outcome Value (E) -13 -32 26 Anxiety (S) 77 -6 4

Depression (S) 79 -1 5

Perceived Stress (S) 62 12 -3 * Factor loadings represent standardized regressions coefficients; Printed values are multiplied by 100 and rounded to the nearest integer. ** (I) Hypothesized as representing an Internal Cognitive Factor; (E) Hypothesized as representing an External Cognitive Factor

The factor structure for the men was similar to that of the overall sample

(Table 19). The factor solution for the women, however, slightly differed (Table

18). One variable, HIV treatment beliefs cross-loaded on factor 1 and 3 and was 90 not used in interpreting the factors. Similar to the previous model, three factors emerged: anxiety, depression, and perceived stress loaded on the first factor labeled as the situational factor since all 3 variables were related to individual negative mood states. Two of the variables loading on factor 2 (outcome expectancies and religious norm) and factor 3 (Moral Norms and self efficacy) were hypothesized to be measuring an internal cognitive factor. However, variables loading on factor 2 seemed to deal in general with a person’s concerns about how his/her behavior may affect his/her partner. It therefore seemed appropriate to label this factor the external cognitive factor. Variables on factor 3, on the other hand, dealt with people personal values about given actions or situations. Thus, this factor was named internal cognitive factor.

Table 19. Factor loadings* and factor structure for the men (N= 140)

Scales Factor 1 Factor 2 Factor 3 Moral Norms (I) 87 21

Self Efficacy (I) -2 8 68 Outcome Expectancies (I) 0 81 -2 Religious Norms (I) 31 2 2 Anticipated Regrets (E) 18 56 11 HIV Treatment Beliefs (E) 47 2-12 Social Norms (E) -10 83 -3 Outcome Value (E) -2 -2 -11

Anxiety (S) 4 -2 79

Depression (S) -2 4 83 Perceived Stress (S) -34 -1 40 * Factor loadings represent standardized regressions coefficients; Printed values are multiplied by 100 and rounded to the nearest integer. ** (I) Hypothesized as representing an Internal Cognitive Factor; (E) Hypothesized as representing an External Cognitive Factor 91 a. Evaluating the measurement models for men and women

The input datasets (i.e. the intercorrelations and standard deviations for the measured variables) used for the analyses are presented in Appendix 2. The fit for the women’s initial measurement model was very good (Figure 8 and Table

20). However, the large standardized coefficient for the variable Moral Norms

(greater than 1) suggested a problem with the reliability of the model. Thus, additional modifications for the women were considered. Examination of the

Wald test revealed no substantial change in the model fit to be introduced from the elimination of the variance of Moral Norms. Deletion of the parameter improved the model and no further modifications were considered.

Moral Norms Self- Efficacy

Anxiety Depression Stress Internal Cognitive Factor

Situational Factor

External Cognitive Factor

Outcome Expectancies Social Norms Religious Norms

Figure 8. The initial measurement model for the women 92

Table 20. Goodness of fit indices for the estimated measurement models

Model Chi-square df p CFI Delta2 RMSEA Women

Model 1 Initial model (Fig. 8) 28.16 17 0.04 0.96 0.96 0.07

Model 2 Variance of V1 dropped * 29.26 18 0.04 0.96 0.96 0.07

Men

Model 1 Initial model (Fig. 9) 66.2 24 < 0.0001 0.90 0.91 0.11

Model 2 V11 dropped * 29.5 17 0.03 0.97 0.97 0.07 Model 3 Variances of V1 and V10 dropped * 36.1 19 0.01 0.96 0.96 0.08

* As a reminder: V1: Moral Norms; V11: Stress; V10: Depression

The fit indexes for the men’s initial measurement model were rather marginal (Figure 9 and Table 20). Thus, additional modifications were attempted in order to improve the model. The pattern of normalized residuals, the factor loadings and the Lagrange Multiplier tests suggested that V11 (perceived stress) could be a multidimensional indicator, affected by both F1 (the internal cognitive factor) and F3 (the situational factor). Because loading perceived stress on the internal cognitive factor would lead to an ambiguous specification, the variable was eliminated and the model reevaluated. Deletion of V11 significantly improved the model with (CFI = 0.97, and IFI = 0.97; Table 19), however, a warning code in the SAS output indicated a problem with model’s convergence. 93

Thus, additional modification indices were evaluated in an attempt to solve this problem. On the basis of the Wald test, the variances of self-efficacy and depression were successively dropped. Deletion of the 2 variances removed the warning code and model3 was accepted as the final measurement model for the men.

Moral Norms Self-Efficacy HIV Treatment Beliefs

Anxiety Depression Stress Internal Cognitive Factor

Situational Factor

External Cognitive Factor

Anticipated Regrets Social Norms Outcome Expectancies

Figure 9. The initial measurement model for the men

Additional reliability information provided adequate support for the two final measurement models (Table 21). All the factor loadings were significant at the 0.001 level (t values greater than 3.29) and were all moderate to large in size.

Likewise, all the indicator reliabilities, as well as all the composite reliabilities for the latent factors were all moderate to large, indicating acceptable levels of 94 reliability. Finally, except for the ECF in the women’s model, all the variances extracted estimates were larger than 0.50.

Table 21. Properties of the Revised Measurement Models

Factors and Indicators Standardized loading t* Reliability Variance extracted estimate Women F1 Internal Cognitive Factor 0.78 0.66 V1 Moral Norms 1.00 16.85 1.00 V2 Self-Efficay 0.57 7.42 0.32

F2 External Cognitive Factor 0.70 0.45 V4 Outcome Expectancies 0.64 6.84 0.41 V7 Social Norms 0.81 8.21 0.66 V8 Religious Norms 0.52 5.67 0.27

F3 Situational Factor 0.78 0.55 V9 Anxiety 0.71 8.47 0.50 V10 Depression 0.92 11.05 0.85 V11 Perceived Stress 0.56 6.58 0.31

Men F1 Internal Cognitive Factor 0.84 0.65 V1 Moral Norms 1.00 16.67 1.00 V2 Self-Efficay 0.63 8.33 0.40 V6 HIV Treatment Beliefs 0.49 6.13 0.24

F2 External Cognitive Factor 0.88 0.71 V3 Anticipated Regrets 0.55 6.53 0.30 V4 Outcome Expectancies 0.87 10.50 0.75 V7 Social Norms 0.86 10.4 0.73

F3 Situational Factor 0.87 0.78 V9 Anxiety 0.75 10.4 0.56 V10 Depression 1.00 16.7 1.00

* Significant at p < 0.001

95 b. Evaluating the structural models

Only marginal support was found for the women’s initial model with a significant model chi-square (24, N = 147) = 73.02, p < 0.0001, a CFI = 0.85, and an IFI = 0.85 (Figure 10 and Table 22). Therefore, further evaluation of the model was postponed and the results of the analysis were examined for appropriate modifications. On the basis of the LM and the Wald tests, 2 paths were added and one path deleted. The model fit greatly improved: the model’s chi-square test was no longer significant (17, N = 147) = 27.64, p =0.06, the CFI and delta2 were both over 0.95, and the RMSEA was equal to 0.07 (Table 22).

Self-Efficacy Moral Norms

Anxiety Depression Stress Internal Cognitive Factor

Situational Factor Sexual Risk Behavior

External Cognitive Factor

Outcome Expectancies Social Norms Religious Norms

Figure 10. The initial structural model for the women

Table 22. Goodness of fit indices for the women's structural models

Model Chi-square df CFI Delta2 RMSEA Model 1 Initial model (Fig. 10) 73.02 24 0.85 0.85 0.12

Revised Model 2 Path added: F3 to V12 * 59.70 23 0.89 0.88 0.11

Revised Model3 V2 to V12 added; F1 dropped * 27.64 17 0.95 0.96 0.07

* As a reminder: F3: Situational Factor; V12: Sexual Risk Behaviors; V2: Self-Efficacy; F1: Internal Cognitive Factor

The final model showed a reasonable fit, accounting for 23% of the variance in women’s sexual risk behaviors (Figure 11). Neither the ICF nor the

ECF were related to the outcome. The SF, however, directly affected the sexual risk behavior (standardized path coefficient= -0.31), suggesting that having fewer situational barriers were related to more sexual risk taking. Likewise, one observed variable, Self-Efficacy was significantly related to sexual risk behavior

(standardized coefficient = -0.40) indicating that lower self-efficacy was associated with higher sexual risk taking.

Anxiety Depression Stress Self-Efficacy .95 -. 16 -.40 *** .69*** .54 ***

-.31 *** Situational Factor Sexual Risk Behavior

-.10 -. 01 External Cognitive Factor

.66 *** .80 .53***

Outcome Expectancies Social Norms Religious Norms

Figure 11. Final structural model and standardized estimates for women *p<= 0.05; ** p <= 0.01; p <= 0.001 *** 97

Similar steps were followed for evaluating the structural model for the men. The initial model provided an acceptable though marginal fit to the data with values around 0.9 on the delta2 (0.92) and CFI (0.92) and a significant model chi-square (Figure 12 and Table 23). Thus, post hoc modifications were performed in an attempt to develop a better fitting model (Table 23 presents the description and fit indices of the models tested). The final model provided an excellent overall fit to the data. The chi-square was no longer significant

(p=0.38), the RMSEA was less than 0.05, and values of 1 were obtained for the

CFI and delta2, indicating that the final model was definitely better than the null model.

Moral Norms Self-Efficacy HIV Treatment Beliefs

Anxiety Depression Internal Cognitive Factor

Situational Factor Sexual Risk Behavior

External Cognitive Factor

Anticipated Regrets Outcome Expectancies Social Norms

Figure 12. The initial structural model for the men

Table 23. Goodness of fit indices for the men's structural models

Model Chi-square df CFI Delta2 RMSEA Model 1 Initial model (Fig. 12) 52.61 24 0.93 0.93 0.09

Revised Model 2 V6 to V12 added; F1 to V12 dropped 12.78 12 1.00 1.00 0.02

Revised Model 3 Variance of V10 dropped * 12.88 13 1.00 1.00 0.00 As a reminder: V6: HIV Treatment Beliefs; F1: Internal Cognitive Factor; V12: Sexual Risk Behaviors; V10: Depression

The men’s final model (Figure 13) only explained 6% of the variance in sexual risk behavior. Similar to the women’s model, neither the ECF nor the ICF were significantly related to the outcome. Instead, only one indicator variable from the ICF (HIV treatment beliefs) significantly affected the men’s sexual behavior (standardized coefficient = 0.25), suggesting that this variable, rather than the whole latent factor, directly affected sexual risk-taking in this group. The relationship suggested that the more positive beliefs respondents endorsed about antiretroviral treatment, the higher the reported sexual risk behavior. SF did not affect any of the latent factors.

HIV Treatment Beliefs Anxiety Depression -.14 .25 ** 1.00 0.75 ***

Situational Factor Sexual Risk Behavior

.03 External Cognitive Factor

.54 *** .86 *** .86 ***

Anticipated Regrets Outcome Expectancies Social Norms

Figure 13. Final structural model and standardized estimates for men. *p <= 0.05; **p <= 0.01; ***p <= 0.001

c. Formulating a single overall model for men and women

In the final stage of our analyses, the 2 best structural models for men and women were integrated into a single overall model in order to obtain a model that would be both more parsimonious and statistically more powerful for detecting any meaningful relationships between the relevant variables. The initial combined measurement model (Figure 14) included 3 manifest variables (Sex,

Self-Efficacy, and HIV Treatment Beliefs), and 2 latent variables: External

Cognitive Factor (with outcome expectancies, anticipated regrets, social norms, and Religious Norms as indicators) and Situational Factor (with anxiety, depression, and perceived stress as indicators). Sex was as a moderator variable to asses the sex-specific influences on all the other variables. Because the internal cognitive factor failed to achieve statistical significant in all the prior analyses, the construct was dropped from the integrative model and self-efficacy and HIV treatment beliefs were included, instead, as separate manifest variables. 100

The correlation matrix used as input dataset is presented in Appendix 2 (Table

2.4).

HIV Treatment Beliefs V6 Anxiety V9

Situational Factor Depression Sex F3 V10 Self-Efficacy V2 Stress V11

External Cognitive Factor F2 Ant. regrets V3

Outcome Social Norms Religious Norms Expectancies V7 V8 V4

Figure 14. Initial Measurement Model

101

Only marginal support was found for the initial measurement model: the chi-square test was significant, both the CFI and delta2 were below their recommended values of 0.9 and the root mean square of error (RMSEA) was above the recommended value of 0.05 (see Table 24). Thus, the results of the analysis were examined for appropriate modifications. On the basis of the

Lagrange Multipliers (LM) tests, 5 paths were successively added to the model

(see Table 24 for the summary of all the tested models).

Table 24. Goodness of fit indices for the measurement models

Model Chi-square df p CFI Delta2 RMSEA Model 1 Initial model (Fig. 12) 120.69 28 < 0.0001 0.85 0.85 0.11

Model 2 Path added: V2 to V3 * 81.88 27 < 0.0001 0.91 0.91 0.08

Model 3 Path added: V6 to V11 * 66.68 26 < 0.0001 0.93 0.94 0.07

Model 4 Path added: V2 to V8 * 54.12 25 0.0006 0.95 0.95 0.06

Model 5 Path added: F3 to V4 * 45.25 24 0.005 0.96 0.97 0.06

Model 6 Path added: V12 to V9 * 37.38 23 0.03 0.98 0.98 0.05 * As a reminder: V2: Self-Efficacy; V3: Anticipated Regrets; V4: Outcome Expectancies; V6: HIV Treatment Beliefs; V8: Religious Norms; V9: Anxiety; V12: Sex; F3: Situational Factor

102

First, the LM suggested that adding a path relating V3 (anticipated regrets) to V2 (self-efficacy) would significantly improve the model. Because the suggested path was a reasonable parameter to add (it may be that individuals who reported higher anticipated regrets were also more likely to report higher self-efficacy), the path was added and the model re-evaluated. On the next run, a path relating V11 (perceived stress) to V6 (HIV treatment beliefs) was added suggesting that individuals’ level of perceived stress was likely to affect their beliefs about the benefits of the available therapy against HIV. Finally, three reasonable parameters were added using the next rounds of LM tests: a path relating self-efficacy (V2) to Religious Norms (suggesting that individuals who reported higher Religious Norms were also more likely to report higher perceived self-efficacy), a path relating situational factor and outcome expectancies and a path relating sex to anxiety (suggesting a differential effect of sex with regards to anxiety). Addition of the 5 parameters significantly improved the model’s fit: although the model’s chi-square was significant, the chi-square/df ratio was below the suggested value of 2 (ratio=1.63). Both the CFI and delta2 exceeded

0.97, and the RMSEA was at the recommended value of 0.05 (Table 23). All the factor loadings were significant at the 0.01 or 0.001 level. Thus, the model was accepted as the final measurement model and the structural portion of the model was examined next.

The initial structural model was rejected on the basis of the 4 goodness-of- fit indices (Table 25). Thus, several additional models were tested in an attempt to develop a better fitting model (see Table 25 for a summary). On the basis of 103 the LM test, 2 parameters were successively added: a path relating anxiety to

HIV treatment beliefs, and a path relating self-efficacy to HIV treatment beliefs

(suggesting that individuals who reported higher HIV treatment beliefs were also more likely to report higher self-efficacy). The final model provided an excellent fit to the data: the Χ2 /df ratio was under 2, both the CFI and delta were above

0.95 and the RMSEA was at 0.05. Figure 15 depicts the final structural model with all the estimated standardized coefficients.

Table 25. Goodness of fit indices for the structural models

Model Chi-square df p CFI Delta2 RMSEA Model 1 Initial model 96.47 36 < 0.0001 0.91 0.91 0.08

Model 2 Path added: V9 to V6 * 72.49 35 0.0002 0.94 0.94 0.06

Model 3 Path added: V2 to V6 * 54.25 34 0.02 0.97 0.97 0.05 * As a reminder: V2: Self-Efficacy; V6: HIV Treatement Beliefs; V9: Anxiety

104

-0.13 ** HIV Treatment Beliefs (V6) -0.24 *** 0.12 * -0.28 *** 0.24 *** 0.42*** -0.17 ** Stress (V11) -0.21 *** Situational Factor Sexual Risk F3 1.00 -0.33 *** Behavior (V13) Sex Dep. (V10) 0. 09 -0.14 ** 0.67*** Self-Efficacy (V2) -0.08 Anxiety (V9)

0.21 *** -0.10 ** 0.10 0.35*** External Cognitive Factor 0.07 F2 0.76 0.79*** 0.27*** 0.52*** Outcome Social Norms Religious Norms Ant. regrets Expectancies V7 V8 V3 V4

Figure 15. Final Overall Structural Equation Model and Standardized Estimates; *p <= 0.05; **p <= 0.01; ***p <= 0.001

The final structural model provided a reasonable fit to the data, accounting for 14% of the variance in self-reported sexual risk behaviors. Three variables were significantly related to the outcome. Self-efficacy and the situational factor were inversely related to sexual risk taking, whereas HIV treatment beliefs were positively associated with risk behavior (the more positive/optimistic beliefs respondents held about the effects of the HIV therapy, the higher the reported sexual risk behavior). The external cognitive factor was not significant. Finally, the analysis also revealed the significant influences of self-efficacy and situational factor such as anxiety on many other variables (including outcome expectancies, anticipated regrets, religious norms, and HIV treatment beliefs). 105

Chapter 5. Discussion

More than two decades after the first case was diagnosed, HIV/AIDS remains a major public health problem. Recent advances in HIV treatment have resulted in dramatic declines in the number of AIDS deaths and have slowed the progression of the disease from HIV infection to AIDS. However, there is still no cure for the disease and an effective vaccine has yet to be found. Thus, prevention remains the best strategy to reduce the spread of the disease.

Unfortunately, HIV prevention had been neglected for those living with HIV/AIDS until recently, when reports indicated an increase in various sexually transmitted infections rates among persons already infected with HIV [2]. The issue is, however, important since ultimately, the epidemic can only be sustained by the transmission of the virus from infected individuals to non-infected ones.

While there has been a multitude of studies with regards to HIV prevention among the non-infected population, HIV prevention research among PLWHA

(secondary prevention) has been more limited. The few studies of HIV- transmission prevention that have been conducted in PLWHA have had inconsistent findings, suggesting that factors other than the ones previously investigated might be involved. The objective of this research was to examine the sexual risk practices of men and women living with HIV/AIDS in a developing country, Cote d’Ivoire, and test a conceptual model explaining their sexual decision-making in terms of social cognitive and situational factors.

Our data revealed a high rate of risky sexual practices among the study sample. One-third of our sample reported engaging in unprotected sex, often 106 with partners that had a negative or unknown HIV status. Similar results have been reported in studies conducted in the US and other industrialized countries

[16, 27, 151-155]. Studies conducted in developing countries also have reported comparable prevalence rates [17, 18]. A number of reasons have been suggested for these findings. Because the sudden increase in HIV-related risk behavior has coincided with the widespread use of antiretroviral therapy for

HIV/AIDS patients, many researchers have suggested that the positive effects associated with the treatment might have given individuals a “false sense of security” and somewhat reduced their concern about HIV infection. The above results provide evidence that risk reduction counseling remains important, despite improvements in the treatment of HIV infection.

Our results also revealed that married participants or those living with a partner were more likely than others to engage in high-risk sexual behaviors.

The partner HIV status might offer a potential explanation for this finding. Indeed in our sample, over 90% of the respondents who were married or living with a partner reported that their partner was also HIV-positive. Thus, it is likely that individuals in HIV-seroconcordant relationships may perceive protected sex as less necessary when their partner is also HIV-positive. This result would be consistent with other research findings that have indicated a higher prevalence of high-risk sexual behaviors among individuals who were members of HIV- seroconcordant relationships compared to those in HIV-discordant couples [156-

158]. Reduced concern about HIV has been suggested as a potential explanation for this finding. There are still a lot of controversies concerning the 107 extent to which continued unprotected sex among those in HIV-seroconcordant relationships may lead to more rapid disease progression or reinfection with new or drug-resistant HIV strains [156, 158-164]. Nonetheless, our finding deserves special attention in terms of future research and in terms of secondary prevention of HIV. Indeed, continued unprotected sex among HIV-seroconcordant couples may still result in unwanted pregnancies (leading to a potential perinatal transmission of HIV), or in high risk of secondary HIV transmission in instances where at least one member of the couples may continue to engage in unprotected sex outside of the primary relationships.

We proposed a conceptual model to explain sexual decision-making of persons living with HIV/AIDS in terms of social cognitive and situational factors.

Although the proposed model failed to meet the standard statistical criteria for a good model fit, a number of the hypothesized effects were statistically significant.

Two out of 3 proposed factors (the internal cognitive and the situational factors) directly affected sexual risk behavior in our sample. In addition, the situational factor significantly related to the internal cognitive factor. However, contrary to our hypothesis, the external cognitive factor had no significant effect on the outcome. There may be some methodological explanations for this finding.

Almost all the respondents exhibited higher scores, i.e. more positive beliefs on the scales (i.e. almost all the respondents felt strongly that putting others at risk for HIV infection would be related to lots of regrets, and had positive attitudes about condom use). Such ceiling effects may have limited our ability to find a 108 relationship between the external cognitive factor and sexual risk behaviors in this sample.

Specific aim 1

The first aim of the study was to validate the constructs of external and internal cognitive factors involved in the sexual decision making of PLWHA.

As posited, two factors emerged from the factor analyses procedure.

Although the results were not entirely consistent with the pre-specified factors, two out of three indicators consistently loaded on their expected factors. Moral

Norms and Self-Efficacy consistently grouped with the same factor, labeled internal cognitive factor (ICF). Anticipated Regrets and Social Norms also grouped on the same factor, labeled external cognitive factor (ECF). Contrary to our hypothesis, Religious Norms and Outcome Expectancies, both intended to load with the ICF, grouped with the ECF. Careful examination of both scales later on revealed that most items on the two scales were in fact related to respondents’ concerns about how their own behaviors might affect their partners or others. Therefore, it was not surprising to see the two variables load on the

ECF. Likewise, HIV Treatment Beliefs loaded with the ICF, although intended to group with the ECF. This finding might be in part due to the fact that items on the

HIV Treatment Beliefs scale assessed respondent’s perceived beliefs, rather than their actual knowledge, about the benefits of the antiretroviral therapy.

Thus, the variable was more related to their personal values. 109

The ICF and ECF were only moderately correlated, suggesting they were indeed two distinct factors and that each provided unique and non-overlapping information. These results confirm that social cognitive variables related to sexual risk behaviors are complex, multidimensional constructs. Previous studies have mainly focused on sociocognitive variables with an emphasis on self-interest (Self-efficacy, Outcome Expectancies, and Outcome Value).

Although such constructs have generally been found to be good predictors in the non-infected population, they have had limited predictive utility for those already living with HIV/AIDS. However, it may be that other dimensions of these variables are more relevant for the latter group. Thus, to the extent the two factors exhibit differential impacts on sexual risk taking among PLWHA, distinguishing between the two factors might be important for prevention purposes. For example, they may require different types of intervention programs.

A different factor structure was found for men and women. HIV Treatment

Beliefs was significant for men only, while Religious Norms was significant for women only. These results may simply indicate that men and women may tend to base their decisions on different factors. For example, women may be more likely to consider faith as particularly important in their decision-making, while men may emphasize more objective values (such as benefits of antiretroviral therapy) in their decision-making process. Indeed, women in our sample were more likely than men to report attending religious services once or several times a week (79% versus 66%, p = 0.007) whereas men were more likely than women 110 to report perfect or near perfect adherence to therapy in our study (93% versus

83%, p = 0.01). Alternatively, as men and women in our sample were very similar with respect to all measured demographic characteristics and sociocognitive variables (the only difference was with regards to educational attainment and employment status with men more likely to have higher education and to be employed- see Tables 3.1 and 3.2, Appendix 3), another potential explanation for the sex differences is that our results may have been confounded by unexplored social, cultural or behavioral factors. Examples of these unmeasured variables may include size and composition of social network, social support, cultural norms, HIV transmission knowledge, and other social constraints (e.g. women’s lack of adherence may be a function economic conditions and/or time and role conflicts that they may face as caretakers for their children and partner).

Specific aim 2

We tested a proposed conceptual model to explain the continued sexual risk- taking in HIV-infected persons in terms of cognitive and situational factors.

The purpose of the second aim was to evaluate a conceptual model that uses a set of socio-cognitive and situational variables for understanding high-risk sexual behaviors in persons living with HIV/AIDS. Such evaluation is essential for identifying variables and/or constructs that work in HIV-transmission prevention with PLWHA, and for ultimately planning and designing intervention programs targeting this group. The statistical method utilized in the present 111 study was adequate as it allowed us to test the utility of the model as a whole rather than examine the relationship between individual variables. Although the model was not statistically supported by the data, this study (both through the primary and secondary analyses) revealed a number of significant relationships between the study variables, and sexual risk behaviors.

A number of indicators of the ICF had significant effect on the sexual risk- taking. Self-efficacy was found to significantly affect AIDS-risk behaviors, with higher perceived self-efficacy (PSE) negatively related to high-risk sexual behaviors. Similar findings have been reported by previous studies conducted with PLWHA [76, 77]. However, PSE was significant only for women in our sample, not for men. Interestingly, Semple and colleagues also reported self- efficacy to make a small and non significant contribution to safer sex behavior in a sample of HIV positive men [33]. Are these results suggesting a differential effect of self-efficacy on sexual-risk behaviors across sex, at least for those living with HIV/AIDS? One potential explanation is that this finding may have been an artifact from the restricted variability in self-efficacy among the men in our study, as virtually all of them reported high self-efficacy. Alternatively, as women in sub-Sahara Africa very often lack sexual decision-making power for cultural, economic, and social reasons, it may be that for those of them who strongly believe in their ability to influence their sexual partners to use condoms, PSE is likely to play a major role in wether or not they engage in safer sex behaviors.

This hypothesis would be consistent with previous research findings that perceived behavioral control (i.e. one’s perceptions of control over the 112 performance of a given behavior, a construct from the Theory of Planned

Behavior that has been very closely related to the self-efficacy construct) generally correlated more strongly to condom use in populations that lack power to actually implement or negotiate condom use, including women, ethnic minorities, adolescents or individuals with lower SES [165-169].

HIV treatment related beliefs also significantly affected sexual risk behaviors, after controlling for all other variables. This result is consistent with previous findings showing an association between perceptions about antiretroviral therapy and prevalence of unprotected sex [24, 170-177]. A recent meta-analytic review by Crepaz and colleagues showed that HIV-patients’ beliefs about antiretroviral therapy (e.g. taking antiretroviral therapy reduces the risk of transmitting HIV), rather than the initiation of the treatment or the therapeutic response to the drugs (e.g. undetectable viral load) were the major determinants of unsafe sex in this group [171]. In fact, in the studies they reviewed, the prevalence of unprotected sex was not higher among HIV patients receiving treatment compared to those not receiving treatment. Similar to the previous review, the current study also found that receiving treatment did not increased risky sexual behaviors among the participants. The prevalence of high-risk sexual behaviors was actually lower among those taking treatment versus those not yet receiving any treatment (30.8% versus 57.5%; p < 0.0001). In studies examining the association of sexual behavior with antiretroviral therapy, risky sexual behavior was related to the simple initiation of therapy or to the perceived response to therapy but not the actual response to therapy (e.g. reduced viral 113 load) [172, 177]. Thus, although regular and correct use of antiretroviral therapy has been linked with less infectiousness of HIV patients [178], most individuals engaging in high-risk behaviors do so without actually being on treatment or without knowledge of the therapeutic response. Thus, many PLWHA engaging in high-risk sexual behaviors may continue to pose a great risk to themselves as well as to their partners.

Situational factor (SF) had both a direct and indirect effect (through partial mediation with the internal cognitive factor) on sexual risk behaviors. The

Situational Factor was negatively related to the outcome, with more situational barriers leading to less sexual risk taking. Studies investigating the role of psychological distress (including anxiety, depression and stress) in the sexual risk taking among HIV-infected persons have generally had conflicting results, with a very few studies finding a negative or no relationship between sex risk behavior and affective mood states [16, 135], and many others finding a positive relationship [151, 155, 179-183]. This inconsistency across studies has been previously attributed to sampling differences, positive findings generally occurring with studies conducted with subjects already at higher risk for emotional distress

(e.g. patients attending mental health facilities or enrolled in prevention programs) [16]. Likewise, other methodological (e.g. measurement of the variables) or population (age, gender) characteristics may help explain the inconsistencies in findings.

The relationship between situational factor and sexual risk behavior was also mediated by the internal cognitive factor: situational factor negatively 114 affected the internal cognitive factor, which in turn negatively related to sexual risk behaviors. It is not clear why the factor failed to the external cognitive factor as hypothesized. The restricted variability in the respondent’s scores on the external cognitive factor may offer a potential explanation for this negative finding. Nonetheless, the partial mediation has important implications in terms of possible secondary prevention interventions. Indeed, our result suggests that situational factor may also in fact affect individuals’ cognitive norms, leading them to more likely engage in high-risk sexual behaviors. Thus, assessing psychological distress and providing appropriate support for those in need may offer an additional means to prevent sexual risk-taking among PLWHA.

Our study also found a difference by sex for the relationship between situational factor and sexual risk taking, in that situational factors were only significant for women. Further examination of the data revealed that women were significantly more likely than men to show high levels of anxiety (40.6% versus 17.3%, p< 0.0001) and depression (36.6% versus 20.8%, p= 0.001).

Thus, the failure of the situational factor to be related to the outcome among men may be due to the fact that the large majority of the men in our study (close to

80%) reported no anxiety or depression. Sex differences in the prevalence and clinical presentations of anxiety and depression have been well documented.

Studies have shown that women are twice as likely as men to experience major depression and anxiety disorders [184-192]. Furthermore, the clinical presentations and features of anxiety and depression have also been shown to differ in men and women [185-187, 193-196]. For example, women are more 115 likely to report more somatic symptoms of anxiety such as more sleep changes

[194, 197], higher anxiety-related physical concerns [198], more vegetative and severe depressive symptoms [190, 193], more psychomotor retardation [194], and more emotional distress [189]. In the other hand, men are more likely to exhibit anxiety-related social concerns, atypical depressive symptoms such as anger irritability, aggressiveness or abusive behavior, and a more gradual

(masked) development of depression [193, 198, 199]. Other studies, however have failed to find any differences between men and women with regards to the presentation of depressive symptoms (1f, 6). Thus, our result that women in our sample may carry an additional burden of dealing with high levels of anxiety and depression might be either a true finding, or an artifact of the assessment tools used in our study (i.e. our instruments may have failed to adequately assess the extent of psychological distress among men).

Self-efficacy was significantly related to a number of other study variables.

Higher self-efficacy was associated with more optimistic beliefs about antiretroviral treatment, higher anticipated regrets toward engaging in unsafe sex for a PLWHA, and higher religious/spiritual beliefs. Previous studies have reported a relationship between self-efficacy and religiosity/spirituality.

Schneider (2004) found significant negative correlations between self-efficacy and religiosity (defined in the study as the frequency of prayer and church attendance) in a sample of 134 adults living in Germany. However, in contrast with our study sample, the previous sample was mostly comprised of participants reporting praying “never” or only “sometimes”. In another study, McCree et al. 116

(2003) also found that adolescent females with higher religious/spiritual scores were also more likely to exhibit higher self-efficacy for condom use negotiation.

Because our study was cross-sectional, we can only speculate on the causal direction between the various variables and self-efficacy. Nonetheless, the results suggest that self-efficacy may be an important target for future interventions in this population. Indeed, as self-efficacy is a readily modifiable behavior (e.g. through skills training or modeling), changing individuals’ sexual self-efficacy may be likely to influence a number of other important variables

(Religious Norms, Anticipated Regrets, and HIV Treatment Beliefs).

Limitations

The present study has a number of limitations. First, all the collected data were based on self-report and thus, they may be subject to some reporting bias due to social desirability. To the extent that individuals tended to underreport their unsafe sex behaviors, the bias introduced might have reduced our statistical power to detect any group differences. On the other hand, because any bias introduced in that fashion would be towards the null value, all our statistically significant findings would actually be an underestimate rather than an overestimate of the detected association. In any case, self-report is the only feasible way to collect data on topics such as sexual behaviors. Moreover, to increase participants’ trust and decrease their concerns, interviews were conducted in privacy and each participant was assured about the confidentiality of the collected data. 117

Second, this study used a convenience sampling technique and the interviews were conducted in one site only. Furthermore, the men and women who were recruited for this study were currently seeking care at the clinic and may have had more resources available to them or may have been more willing to open up about their status and accept their disease compared to HIV patients not currently seeking care. Thus, the generalizability of our findings to all HIV patients currently living in Cote d’Ivoire, especially to those living in rural areas, is unknown. However, as one of the largest HIV outpatient clinic of the area, the

USAC clinic is likely to be attended by the majority of those living with HIV/AIDS both from a rural or an urban setting in Cote d’Ivoire, or even those from other surrounding countries in West Africa. Furthermore, the age and sex distribution of patients enrolled in our study was quite comparable to that of the country with the majority of the cases occurring below age 49 and 50% of the cases being females [2, 200]. Nevertheless, further research will be needed to ensure that the present findings can be generalized to the rest of the HIV-positive women and men in Cote d’Ivoire or in the region at large.

Another potential limitation for this study stems from the selective nature of our sample. One of the eligibility criteria was a minimum of primary school level; as such, our sample may not be representative of the general population of

HIV-positive men and women, many of whom may not have had any formal schooling. We have no data on the literacy level among men and women living with HIV/AIDS in Abidjan or Cote d’Ivoire. However, out of the 390 patients who completed a questionnaire, 28 were excluded from the primary analyses because 118 they had no formal schooling. When compared to participants with a primary or higher education level, these respondents were more likely to be female, unemployed, of Muslim faith, and exhibiting a higher level of anxiety (Tables 3.3. and 3.4, Appendix 3). Apart from these few factors, the 2 groups were very comparable with regards to all other variables including sexual risk behaviors, health status and measured cognitive variables. Thus, limiting our study to those with a formal schooling may not have introduced a substantial bias in our results.

However, a larger study would be needed to confirm these results.

Fourth, this study was cross-sectional and as such, we cannot accurately conclude whether the various proposed factors were predictive rather than reflective of individuals’ sexual behaviors as the various beliefs and factors may have been derived in part from behaviors already made by the individuals. This issue can be overcome by using a prospective cohort study that would enroll patients shortly after their diagnosis and follow them up for a defined study period. All the hypothesized predictor variables would be assessed at baseline and frequency of sexual risk behaviors would be assessed at the end of the study period. Such design would allow us to more adequately assess the causal and temporal relationship between the various predictor variables and sexual risk-taking among the study population and answer to the question whether the hypothesized independent variables truly preceded the outcome. Nonetheless, the current findings still have important implications for understanding the relative importance of various correlates of sexual risk behaviors among HIV patients and for needed interventions among the group. 119

Although our study revealed two cognitive factors as hypothesized, the results of the exploratory factor analysis were not consistent with our initial hypothesis as a number of variables loaded on factors other than the ones on which they were expected to load on, while other variables did not load on any factors. Although the resulting constructs were still labeled as internal/external cognitive factors, it is possible that the internal/external dichotomization was not the most appropriate, and other dimensions might underlie the measured factors.

Finally, this study must be considered as exploratory as a number of post- hoc modifications were made in order to obtain a better fitting model. More specifically, precautions must be taken in interpreting the significant level of the findings since the type I error (i.e. rejecting, by mistake, the null hypothesis that the estimated parameters are equal to 0) might be inflated by such iterative processes for findings a good model. One way to protect against inflated type I error might be to use a more stringent level of alpha. In the present study, most of the alpha levels were 0.01 or smaller. Furthermore, because the post- modifications were data–driven, the likelihood of replicating similar findings in another sample might be low, particularly for small samples. However, our sample size was fairly large, and the suggested modifications were only implemented if conceptually sound. Nonetheless, cross-validation of our findings in a different sample is highly recommended prior to making any generalization at the population level.

Study Implications 120

Over 29 millions men and women living with HIV/AIDS reside in sub-

Saharan Africa [5]. This corresponds to almost 70% of all individuals living with

HIV/AIDS, for a region that only accounts for 10% of the global population [7].

HIV/AIDS is particularly costly because associated to devastating effect on so many sectors including individual households, agriculture, businesses, education, and health. For example in Cote d’Ivoire, healthcare costs due to AIDS absorbed nearly 11% of the total public health system budget [2], and still, public health services meet less than 20% of the demand for HIV-related care [201].

Furthermore, the management of HIV/AIDS in sub-Saharan Africa is complicated by the scarcity of available resources. At present, only 7% of those who need treatment have access to antiretroviral therapy [5]. Roughly 1/3 of our sample had engaged in unprotected sex during the past 6 months. To the extent that this behavior has the potential of exposing the individuals themselves at risk of contracting other STDs (including the risk of reinfection with drug resistant HIV strains) but also transmitting the virus to others (thus increasing the burden of the disease), our findings have important implications for health services needs of those living with HIV/AIDS. Indeed, secondary prevention of HIV might be an important component in the routine health care management of PLWHA.

Moreover, findings from this study should direct the attention of policy-makers to the need of persons living with HIV/AIDS in term of prevention and routine medical care. The importance of assisting HIV patients with their day to day struggle with adopting and maintaining safer sex behaviors is often overlooked in outpatient clinics. If findings are confirmed, public health and public policy 121 programs that promote routine counseling of HIV patients as part of their medical follow-up and appropriate mental health care could lead to long term reductions of HIV transmission from infected to non-infected individuals. Until a definite cure can be found, prevention interventions targeting PLWHA will remain an essential strategy for curving the HIV/AIDS pandemic for regions with scarce resources.

Sub-Saharan is by far the region most affected by the HIV/AIDS epidemic.

Many reasons have been advanced for the high prevalence of the infection, including economic, political, cultural and behavioral factors. Of those, behavioral factors are by far the most easily amenable to change. Thus, knowledge from studies such as the present one are needed in order to be able to design effective intervention programs to enhance PLWHA’s skills and motivation to engage in safer sex behaviors. More specifically, a number of recommendations for future interventions could be drawn from our results. First, the fact that the internal cognitive factor and its individual indicator variables were the strongest determinant of sexual risk behavior suggests that educational programs that promote individuals’ confidence in their own skills, their sense of duty and responsibility, and their perceived beliefs about safe sex behaviors will be likely to be successful. On the other hand, the negative finding with the ECF might suggest that messages merely encouraging individuals to engage in safe sex behaviors in order to protect others may not be sufficient. Second, self- efficacy was related to a number of variables in our study, suggesting that changing individuals’ sexual self-efficacy may be likely to influence a number of other important variables, including HIV treatment beliefs, anticipated regrets and 122 religious norms. Thus, interventions designed to enhance individuals’ self- efficacy for condom use and/or safe sex negotiation (e.g. through skills training or role modeling) are likely to be successful.

Key innovations and future work

The main contribution of this research was to test a conceptual model explaining sexual decision-making among PLWHA in terms of selected cognitive and situational factors in combination, and assess whether the cognitive processes involved in their sexual decision-making may be separated into two major factors: an internal cognitive factor (representing their own values/beliefs) and an external cognitive factor (representing their values related to others).

This aim was met as the study did reveal two factors that were both internally consistent and seem to provide unique and non-overlapping information.

However, the overall explanatory power of the hypothesized model was modest.

This may suggest that either the model is lacking some important variables and/or the measurement of key variables was inadequate. The latter explanation is supported by the fact many indicator variables exhibited a rather low variability.

Thus, a future project will be to try developing better scales for the internal and external cognitive variables. Alternatively, the operationalization of the measured factors could be improved by performing the exploratory factor analysis using the individual items rather than the computed summary scales. Doing so would help create more homogenous factors by ensuring that only items that uniquely contribute to the factor are selected whereas items that overlap between the variables are likely dropped. 123

It was beyond the scope of the present study to explore cultural reasons that might be related to sexual risk behavior among persons living with HIV/AIDS in this population. However, future research might definitely benefit from addition of such variables.

This is the first study, to our knowledge, to specifically examine the prevalence and correlates of high risk sexual behaviors among persons living with HIV/AIDS in sub-Saharan Africa. Our study revealed that merely encouraging individuals to engage in safer sex behaviors in order to protect their partners may not be as promising as postulated. Thus, patient education and counseling remain important for secondary HIV prevention.

124

Appendix 1

A. Psychometric Evaluation for Moral Norms (6 items)

MoralObl='Person has moral obligation to protect sexual partners' (Item 1) UnpSexWr='Wrong for someone to have unprotected sex' (Item 2) UnpSexPL='Wrong for a PLWHA to have unprotected sex' (Item 3) TalkSafS='Person has moral obligation to talk about safe sex' (Item 4) TellHSta='Wrong to have sex without disclosing status' (Item 5) AskHSta='Wrong to have sex without asking about part status' (Item 6)

Table A.1 Pearson Correlation Coefficients (N = 348) ______Items moralobl unpsexwr unpsexpl talksafs tellhsta askhsta ______moralobl 1.00000 unpsexwr 0.47363 1.00000 <.0001 unpsexpl 0.37450 0.78154 1.00000 <.0001 <.0001 talksafs 0.71044 0.41645 0.41233 1.00000 <.0001 <.0001 <.0001 tellhsta 0.33814 0.61258 0.57343 0.30176 1.00000 <.0001 <.0001 <.0001 <.0001 askhsta 0.26826 0.62020 0.57021 0.28559 0.75318 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001 ______

Table A.2 Descriptive Statistics

Variable N Mean Std Dev Sum Minimum Maximum

moralobl 348 3.44540 0.52037 1199 2.00000 4.00000 unpsexwr 348 3.28161 0.74075 1142 1.00000 4.00000 unpsexpl 348 3.39943 0.71113 1183 1.00000 4.00000 talksafs 348 3.45690 0.51590 1203 2.00000 4.00000 tellhsta 348 3.22989 0.84131 1124 1.00000 4.00000 askhsta 348 3.14368 0.90279 1094 1.00000 4.00000

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Table A.3 Cronbach Coefficient Alpha with Deleted Variable

______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ moralobl 0.504255 0.853808 0.547180 0.850755 unpsexwr 0.781673 0.802438 0.771408 0.809104 unpsexpl 0.725007 0.814475 0.710729 0.820755 talksafs 0.493896 0.855197 0.536167 0.852703 tellhsta 0.710318 0.817452 0.669807 0.828452 askhsta 0.685977 0.825789 0.645059 0.833045 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.854417 Standardized 0.856889 126

B. Psychometric Evaluation for Self-efficacy (7 items)

BuyCdn='How confident are you to buy condom in a store' (Item 1) UseCdn='How sure to consistently use condoms during sex' (Item 2) askpcdn='How confident are you to get every partner use cdn' (Item 3) forcpcdn='How confident to get partner you had sex with before to use cdn' (Item 4) forcpcd2='How confident to get partner you had sex with before to newly use cdn' (Item 5) StopCdn='How sure to stop and put/use condoms' (Item 6) StopSex='How sure to completely stop having sex because of status' (Item 7)

Table B.1 Pearson Correlation Coefficients (N = 348) ______Items buycdn usecdn askpcdn forcpcdn forcpcd2 stopcdn stopsex ______buycdn 1.00000

usecdn 0.36185 1.00000 <.0001

askpcdn 0.39657 0.76533 1.00000 <.0001 <.0001

forcpcdn 0.39671 0.54029 0.56510 1.00000 <.0001 <.0001 <.0001

forcpcd2 0.36662 0.68820 0.68900 0.63636 1.00000 <.0001 <.0001 <.0001 <.0001

stopcdn 0.40170 0.74489 0.70095 0.63162 0.80515 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001

stopsex 0.00105 0.09232 0.11004 0.06754 0.13138 0.08585 1.00000 0.9844 0.0855 0.0402 0.2088 0.0142 0.1099

Table B.2 Descriptive Statistics ______Variable N Mean Std Dev Sum Minimum Maximum ______buycdn 348 3.58621 0.86630 1248 0 4.00000 usecdn 348 3.33333 0.96530 1160 0 4.00000 askpcdn 348 3.28161 0.96091 1142 0 4.00000 forcpcdn 348 3.45115 0.82149 1201 0 4.00000 forcpcd2 348 3.23563 0.97028 1126 0 4.00000 stopcdn 348 3.22126 0.95121 1121 0 4.00000 stopsex 348 1.22414 0.87310 426.00000 0 4.00000 ______*The score for those who answered ‘Don’t know’ was changed from ‘5’ to ‘0’ 127

Table B.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ buycdn 0.425210 0.853984 0.424969 0.848918 usecdn 0.760204 0.804867 0.753172 0.799361 askpcdn 0.767994 0.803668 0.762662 0.797835 forcpcdn 0.659229 0.822941 0.656514 0.814599 forcpcd2 0.791413 0.799555 0.787827 0.793763 stopcdn 0.808530 0.797212 0.802951 0.791297 stopsex 0.102653 0.894155 0.100963 0.892053 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.849778 Standardized 0.844600

Psychometric Evaluation for the reduced Self-Efficay Scale (6 items)

Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ usecdn 0.711495 0.855795 0.708977 0.855181 askpcdn 0.725885 0.851964 0.724551 0.851490 forcpcdn 0.601982 0.879450 0.602787 0.879669 forcpcd2 0.812606 0.830509 0.812043 0.830266 stopcdn 0.727007 0.851941 0.720882 0.852362 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.880445 Standardized 0.879952

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C. Psychometric Evaluation for Anticipated Regrets (8 items)

SexWODis='Sex without disclosure of HIV status' (Item 1) SexWOAsk='Sex without asking partner HIV status' (Item 2) SexNocdn='Sex without condom' (Item 3) SexWcdn='Sex with condom' (Item 4) NocdnHng='Sex without condom and HIV neg' (Item 5) CdnHng='Sex with condom and HIV neg' (Item 6) Nocdnhps='Sex without condom and HIV positive' (Item 7) CdnHps='Sex with condom and HIV positive' (Item 8)

Table C.1 Pearson Correlation Coefficients for Anticipated Regrets Scale (N = 345) ______Items sexwodis sexwoask sexnocdn sexwcdn nocdnhng cdnhng nocdnhps cdnhps ______sexwodis 1.00000 sexwoask 0.77389 1.00000 <.0001 sexnocdn 0.54825 0.59942 1.00000 <.0001 <.0001 sexwcdn 0.11539 0.08847 0.14245 1.00000 0.0321 0.1009 0.0081 nocdnhng 0.35879 0.36915 0.55408 0.19927 1.00000 <.0001 <.0001 <.0001 0.0002 cdnhng 0.03598 0.05385 0.16556 0.40211 0.16711 1.00000 0.5054 0.3186 0.0020 <.0001 0.0018 nocdnhps 0.51709 0.47204 0.41714 0.16407 0.36065 0.09557 1.00000 <.0001 <.0001 <.0001 0.0022 <.0001 0.0763 cdnhps 0.09285 0.03753 0.20909 0.42255 0.20693 0.53530 0.15898 1.00000 0.0851 0.4872 <.0001 <.0001 0.0001 <.0001 0.0031 ______

129

Table C.2 Descriptive Statistics

______Variable N Mean Std Dev Sum Minimum Maximum ______sexwodis 345 2.61159 0.74700 901.00000 0 3.00000 sexwoask 345 2.65507 0.70289 916.00000 0 3.00000 sexnocdn 345 2.88406 0.42918 995.00000 0 3.00000 sexwcdn 345 1.05217 0.33697 363.00000 0 3.00000 nocdnhng 345 2.89275 0.47321 998.00000 0 3.00000 cdnhng 345 1.05797 0.29942 365.00000 0 3.00000 nocdnhps 345 2.66087 0.68904 918.00000 0 3.00000 cdnhps 345 1.04058 0.31175 359.00000 0 3.00000 ______* The score for those who answered ‘Don’t know’ was changed from ‘5’ to ‘0’

Table C.3 Cronbach Coefficient Alpha with Deleted Variable

______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ sexwodis 0.667767 0.711067 0.565633 0.728602 sexwoask 0.658934 0.712050 0.553122 0.730842 sexnocdn 0.663376 0.724496 0.616954 0.719303 sexwcdn 0.265347 0.777228 0.339215 0.767484 nocdnhng 0.506748 0.745021 0.507111 0.738984 cdnhng 0.229022 0.780472 0.320553 0.770537 nocdnhps 0.548809 0.737917 0.499352 0.740343 cdnhps 0.275179 0.776283 0.370056 0.762389 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.773727 Standardized 0.770092

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D. Psychometric Evaluation for Outcome Expectancies Scale (6 items)

SthWrgCd2='Something wrong if use condoms' (Item 1) Responsi='Feel more responsible if use condoms' (Item 2) Trust='Using cdns help built trust with partner' (Item 3) Worry='Using cdns makes you less worried for your partner' (Item 4) Refuse2='How confident to refuse sex if partner not allow condom' (Item 5) Convince2='How confident to convince partner to use condoms from now on' (Item 6)

Table D.1 Pearson Correlation Coefficients for Outcome Expect. Scale (N = 335) ______Items sthwrgcd2 worry trust responsi refuse2 convince2 ______sthwrgcd2 1.00000

worry 0.21689 1.00000 <.0001 <.

trust 0.31044 0.54404 1.00000 <.0001 <.0001

responsi 0.34793 0.33014 0.42676 1.00000 - <.0001 <.0001 <.0001

refuse2 0.06079 0.09057 -0.02715 -0.07003 1.00000 0.2672 0.0979 0.6205 0.2010

convince2 0.02171 0.11373 0.06154 -0.00693 0.88573 1.00000 0.6922 0.0375 0.2613 0.8995 <.0001 ______

Table D.2 Descriptive Statistics Variable N Mean Std Dev Sum Minimum Maximum

sthwrgcd2 335 1.75224 0.47838 587.00000 1.00000 4.00000 worry 335 1.88060 0.49314 630.00000 1.00000 4.00000 trust 335 2.03284 0.63961 681.00000 1.00000 4.00000 responsi 335 1.85075 0.47870 620.00000 1.00000 4.00000 refuse2 335 3.26866 0.85440 1095 1.00000 4.00000 convince2 335 3.32239 0.79516 1113 1.00000 4.00000

131

Table D.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ sthwrgcd2 0.259712 0.604287 0.307567 0.605456 worry 0.384957 0.566996 0.431274 0.557214 trust 0.329491 0.580684 0.439002 0.554091 responsi 0.257490 0.604906 0.332493 0.596000 refuse2 0.411824 0.551330 0.301282 0.607820 convince2 0.488719 0.505882 0.349754 0.589374 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.617100 Standardized 0.629128

Psychometric Evaluation for the reduced Outcome Expectancies Scale (4 items)

Cronbach Coefficient Alpha with Deleted Variable

______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ sthwrgcd2 0.374562 0.698836 0.376001 0.700976 worry 0.507189 0.624986 0.485714 0.634793 trust 0.591351 0.566943 0.589537 0.567593 responsi 0.494686 0.633539 0.492979 0.630237 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.700569 Standardized 0.699656

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E. Psychometric Evaluation for Outcome Value (4 items)

Lessfear='In CI most people less worried about AIDS than before' (Item 1) AIDSThrt='In CI most people think AIDS is a less serious threat' (Item 2) NoBigDea='In CI most people think AIDS no longer big deal bc of treatments'(Item 3) AIDSTrt='In CI most people less worried about AIDS bc treatments now available' (Item 4)

Table E.1 Pearson Correlation Coefficients for Outcome Value (N = 348) ______Items lessfear aidsthrt nobigdea aidstrt ______lessfear 1.00000 aidsthrt 0.80241 1.00000 <.0001 nobigdea 0.46157 0.55046 1.00000 <.0001 <.0001 aidstrt 0.48626 0.52159 0.83134 1.00000 <.0001 <.0001 <.0001 ______

Table E.2 Descriptive Statistics Variable N Mean Std Dev Sum Minimum Maximum

lessfear 348 2.38506 0.67564 830.00000 1.00000 4.00000 aidsthrt 348 2.37644 0.65679 827.00000 1.00000 4.00000 nobigdea 348 2.75575 0.65361 959.00000 1.00000 4.00000 aidstrt 348 2.74713 0.66564 956.00000 1.00000 4.00000

Table E.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ lessfear 0.670522 0.838972 0.670855 0.838894 aidsthrt 0.734115 0.812600 0.731944 0.813853 nobigdea 0.715890 0.820145 0.716421 0.820295 aidstrt 0.712250 0.821545 0.714343 0.821153 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.861416 Standardized 0.861661 133

F. Psychometric Evaluation for HIV Treatment Beliefs (5 items)

NoAIDS='If take treatment AIDS epidemic over' (Item 1) LesInfec='Treatments make people less infectious' (Item 2) NoTrans='Treatments take away all risk of sexual transmission of HIV' (Item 3) DifInfec='More difficult to infect through sex if take treatments' (Item 4) SexWTrt='Sex with PLWHA on treatments safer' (Item 5)

Table F.1 Pearson Correlation Coefficients for HIV Treatment Beliefs (N = 308) ______Items noaids lesinfec notrans difinfec sexwtrt ______noaids 1.00000 lesinfec 0.09886 1.00000 0.0833 notrans 0.14372 0.59845 1.00000 0.0116 <.0001 difinfec 0.14442 0.54614 0.83943 1.00000 0.0112 <.0001 <.0001 sexwtrt 0.12646 0.49539 0.79430 0.88607 1.00000 0.0265 <.0001 <.0001 <.0001 ______

Table F.2 Descriptive Statistics Variable N Mean Std Dev Sum Minimum Maximum

noaids 308 2.80519 0.79147 864.00000 1.00000 4.00000 lesinfec 308 3.24675 0.53310 1000 1.00000 4.00000 notrans 308 3.45130 0.51767 1063 2.00000 4.00000 difinfec 308 3.47403 0.52554 1070 1.00000 4.00000 sexwtrt 308 3.45130 0.58835 1063 1.00000 4.00000

134

Table F.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ noaids 0.145997 0.899547 0.146286 0.900418 lesinfec 0.527206 0.731622 0.553512 0.792910 notrans 0.771937 0.656309 0.810428 0.712794 difinfec 0.790097 0.648503 0.828002 0.706941 sexwtrt 0.732661 0.657282 0.778648 0.723254 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.768533 Standardized 0.814353

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G. Psychometric Evaluation for Social Norm (7 items)

Anotherp='Partner is having sex with other partner asks to use cdn' (Item 1) Partmad='Partner will get mad if use cdn' (Item 2) PreferCd2='Sexual partners should want use of condoms' (Item 3) PartDeci='It is up to the partner whether cdn is to be used' (Item 4) Friends2='Important to talk about condoms or HIV with friends' (Item 5) Encourag2='Most people in community encourage condom use' (Item 6) CdnImpor2='Most people in community think condoms very important agains HIV' (Item 7)

Table G.1 Pearson Correlation Coefficients for Social Norm (N = 345) ______Items anotherp partmad prefercd2 partdeci friends2 encourag2 cdnimpor2 ______anotherp 1.00000 partmad 0.86664 1.00000 <.0001

prefercd2 0.11924 0.17016 1.00000 0.0268 0.0015

partdeci 0.41376 0.43233 -0.25292 1.00000 <.0001 <.0001 <.0001

friends2 0.26418 0.29924 0.37927 0.16739 1.00000 <.0001 <.0001 <.0001 0.0018

encourag2 0.48065 0.42255 0.26815 0.15353 0.26529 1.00000 <.0001 <.0001 <.0001 0.0043 <.0001

cdnimpor2 0.42561 0.46318 0.31808 0.25032 0.36339 0.83877 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 ______

136

Table G.2 Descriptive Statistics

______Variable N Mean Std Dev Sum Minimum Maximum ______anotherp 345 1.92174 0.59280 663.00000 1.00000 4.00000 partmad 345 1.90725 0.56299 658.00000 1.00000 4.00000 prefercd2 345 2.23768 0.71632 772.00000 1.00000 4.00000 partdeci 345 2.30435 0.73738 795.00000 1.00000 4.00000 friends2 345 1.62029 0.51506 559.00000 1.00000 3.00000 encourag2 345 1.93913 0.57497 669.00000 1.00000 4.00000 cdnimpor2 345 1.91304 0.53752 660.00000 1.00000 3.00000 ______

Table G.3 Cronbach Coefficient Alpha with Deleted Variable ______Cronbach Coefficient Alpha with Deleted Variable

Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ anotherp 0.660499 0.687971 0.661885 0.722466 partmad 0.693417 0.683480 0.687365 0.717084 prefercd2 0.200734 0.795209 0.234778 0.804693 partdeci 0.251841 0.786288 0.275304 0.797514 friends2 0.433122 0.737290 0.424976 0.769895 encourag2 0.604282 0.701576 0.619763 0.731242 cdnimpor2 0.683642 0.688262 0.688966 0.716744 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.757740 Standardized 0.781767

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H. Psychometric Evaluation for Religious Norms (4 items)

ReligSer2='How often attend religious service?' (Item 1) PrayHome2='How often pray by yourself?' (Item 2) ReligObl2='Putting someone at risk for HIV means failing relig obligations'(Item 3) ReligImp2='Religion plays large role in my daily life' (Item 4)

Table H.1 Pearson Correlation Coefficients for Religious Norm (N = 344) ______Items religser2 prayhome2 religobl2 religimp2 ______religser2 1.00000 prayhome2 0.70456 1.00000 <.0001 religobl2 0.37984 0.38659 1.00000 <.0001 <.0001 religimp2 0.37399 0.28457 0.61284 1.00000 <.0001 <.0001 <.0001 ______

Table H.2 Descriptive Statistics

Variable N Mean Std Dev Sum Minimum Maximum religser2 344 6.82558 2.77827 2348 1.00000 9.00000 prayhome2 344 7.10465 2.10942 2444 1.00000 8.00000 religobl2 344 3.71512 0.61583 1278 1.00000 4.00000 religimp2 344 3.80233 0.39883 1308 3.00000 4.00000

Table H.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ religser2 0.718307 0.395200 0.618049 0.691812 prayhome2 0.706330 0.341022 0.574550 0.715117 religobl2 0.452058 0.655393 0.576387 0.714145 religimp2 0.419517 0.685569 0.521576 0.742677 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.652310 Standardized 0.771029 138

I. Psychometric Evaluation for the anxiety scale (7 items)

Tense='Were you tense or wound up?' (Item 1) WorrThou='Did you have worrying thoughts?' (Item 2) Frighten='Did you feel frightened' (Item 3) Panic='Did you panic' (Item 4) Awful='Did you have awful feelings' (Item 5) Relax='Could you sit and relax' (Item 6) Restless='Did you feel restless' (Item 7)

Table I.1 Pearson Correlation Coefficients for Anxiety Scale (N = 343) ______Items tense worrthou frighten panic awful relax restless ______tense 1.00000

worrthou 0.70254 1.00000 <.0001

frighten 0.53119 0.51749 1.00000 <.0001 <.0001

panic 0.46889 0.50818 0.71367 1.00000 <.0001 <.0001 <.0001

awful 0.45988 0.51105 0.77477 0.76332 1.00000 <.0001 <.0001 <.0001 <.0001

relax 0.01612 0.06401 -0.09333 -0.05929 -0.06226 1.00000 0.7662 0.2370 0.0843 0.2735 0.2501

restless 0.17543 0.11066 0.33669 0.30584 0.34053 0.07728 1.00000 0.0011 0.0405 <.0001 <.0001 <.0001 0.1532 ______

Table I.2 Descriptive Statistics

Variable N Mean Std Dev Sum Minimum Maximum ______tense 343 0.73469 0.76253 252.00000 0 3.00000 worrthou 343 0.89796 0.86082 308.00000 0 3.00000 frighten 343 0.42274 0.67474 145.00000 0 3.00000 panic 343 0.38484 0.71164 132.00000 0 3.00000 awful 343 0.41691 0.77494 143.00000 0 3.00000 relax 343 1.65306 1.05370 567.00000 0 3.00000 restless 343 0.76968 0.91894 264.00000 0 3.00000 ______

139

Table I.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ tense 0.581446 0.684983 0.595682 0.738971 worrthou 0.589795 0.678769 0.613190 0.735408 frighten 0.689195 0.669243 0.723620 0.712340 panic 0.665900 0.670474 0.699070 0.717558 awful 0.684964 0.660834 0.725729 0.711889 relax -.004294 0.833709 -.012712 0.847754 restless 0.313362 0.746801 0.320647 0.791662 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.742017 Standardized 0.783711

140

J. Psychometric Evaluation for the depression scale (7 items)

Cheerful='Did you feel cheerful' (Item 1) SlowDown='Did you feel slowed down?' (Item 2) Enjoy1='Did you look forward to things' (Item 3) GoodBook='Could you enjoy a good book' (Item 4) Enjoy2='Did you enjoy things you used to' (Item 5) Laugh='Could you laugh' (Item 6) Restless='Did you feel restless' (Item 7)

Table J.1 Pearson Correlation Coefficients for Depression scale (N = 343) ______Items cheerful slowdown enjoy1 goodbook enjoy2 laugh interest ______cheerful 1.00000

slowdown 0.64412 1.00000 <.0001

enjoy1 0.69485 0.63058 1.00000 <.0001 <.0001

goodbook 0.53619 0.55663 0.62885 1.00000 <.0001 <.0001 <.0001

enjoy2 0.68807 0.61139 0.69514 0.60180 1.00000 <.0001 <.0001 <.0001 <.0001

laugh 0.68328 0.65388 0.78078 0.60126 0.67957 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001

interest 0.62516 0.66558 0.70939 0.63505 0.61322 0.69746 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 ______

Table J.2 Descriptive Statistics

______Variable N Mean Std Dev Sum Minimum Maximum ______cheerful 343 0.74344 0.82260 255.00000 0 3.00000 slowdown 343 0.51020 0.70028 175.00000 0 3.00000 enjoy1 343 0.54519 0.81837 187.00000 0 3.00000 goodbook 343 0.43149 0.76880 148.00000 0 3.00000 enjoy2 343 0.88338 1.08866 303.00000 0 3.00000 laugh 343 0.52478 0.78647 180.00000 0 3.00000 interest 343 0.61808 0.88352 212.00000 0 3.00000 ______

141

Table J.3 Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ cheerful 0.768693 0.912632 0.766386 0.917881 slowdown 0.741152 0.916374 0.741541 0.920281 enjoy1 0.828833 0.906808 0.828159 0.911831 goodbook 0.697936 0.919367 0.696193 0.924612 enjoy2 0.770141 0.916919 0.770382 0.917493 laugh 0.817910 0.908290 0.818068 0.912827 interest 0.778067 0.911673 0.783355 0.916231 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.924653 Standardized 0.928325 142

K. Psychometric Evaluation for the perceived stress scale (14 items)

Upset='How often been upset' (Item 1) Control='How often felt unable to control important things in your life' (Item 2) Stressed='How often been stressed' (Item 3) Hassles='How often been able to deal with life daily hassles' (Item 4) Changes2='How often been able to deal with important changes in your life' (Item 5) Problems='How often felt capable to take care of personal problems' (Item 6) GoingUrW='How often felt things were going your way' (Item 7) Cope='How often felt unable to cope with things'(Item 8) Irritate='How often felt able to deal with irritations in your life' (Item 9) TopOfThg='How often felt on top of things' (Item 10) Angered='How often been angered' (Item 11) Thinking='How often been thinking about things you had to do' (Item 12) Time='How often been able to control your time' (Item 13) Difficul='How often felt difficulties were piling up' (Item 14)

Table K.1 Pearson Correlation Coefficients for perceived stress scale (N = 338)

(Items 1 to 7) ______Items upset control stressed cope angered thinking difficul ______upset 1.00000 control 0.39382 1.00000 <.0001 stressed 0.52412 0.39118 1.00000 <.0001 <.0001 cope 0.40305 0.62738 0.35689 1.00000 <.0001 <.0001 <.0001 angered 0.48454 0.48911 0.50648 0.54339 1.00000 <.0001 <.0001 <.0001 <.0001 thinking -0.02126 0.05059 0.12312 0.02073 0.03698 1.00000 0.6969 0.3538 0.0236 0.7041 0.4981 difficul 0.37510 0.64988 0.35665 0.69390 0.57692 0.00622 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001 0.9093 hassles 0.29687 0.52282 0.35306 0.55116 0.48238 0.07748 0.64772 <.0001 <.0001 <.0001 <.0001 <.0001 0.1552 <.0001 changes2 0.22813 0.53738 0.33351 0.56649 0.48708 0.13219 0.65250 <.0001 <.0001 <.0001 <.0001 <.0001 0.0150 <.0001 problems 0.25300 0.54064 0.31048 0.59753 0.44703 0.07437 0.65944 <.0001 <.0001 <.0001 <.0001 <.0001 0.1725 <.0001 goingurw 0.14451 0.47291 0.24946 0.53738 0.41861 0.18532 0.65118 0.0078 <.0001 <.0001 <.0001 <.0001 0.0006 <.0001 irritate 0.23472 0.58836 0.30312 0.56247 0.46329 0.08293 0.68701 <.0001 <.0001 <.0001 <.0001 <.0001 0.1281 <.0001 topofthg 0.07864 0.40079 0.13357 0.37292 0.35788 0.18022 0.57275 0.1491 <.0001 0.0140 <.0001 <.0001 0.0009 <.0001 time 0.17269 0.34116 0.23883 0.26771 0.19262 0.08406 0.36944 0.0014 <.0001 <.0001 <.0001 0.0004 0.1230 <.0001 ______

143

(Items 7 to 14) ______Items hassles changes2 problems goingurw irritate topofthg time ______upset 0.29687 0.22813 0.25300 0.14451 0.23472 0.07864 0.17269 <.0001 <.0001 <.0001 0.0078 <.0001 0.1491 0.0014

control 0.52282 0.53738 0.54064 0.47291 0.58836 0.40079 0.34116 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

stressed 0.35306 0.33351 0.31048 0.24946 0.30312 0.13357 0.23883 <.0001 <.0001 <.0001 <.0001 <.0001 0.0140 <.0001

cope 0.55116 0.56649 0.59753 0.53738 0.56247 0.37292 0.26771 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

angered 0.48238 0.48708 0.44703 0.41861 0.46329 0.35788 0.19262 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0004

thinking 0.07748 0.13219 0.07437 0.18532 0.08293 0.18022 0.08406 0.1552 0.0150 0.1725 0.0006 0.1281 0.0009 0.1230

difficul 0.64772 0.65250 0.65944 0.65118 0.68701 0.57275 0.36944 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

hassles 1.00000

changes2 0.76418 1.00000 <.0001

problems 0.68303 0.65695 1.00000 <.0001 <.0001

goingurw 0.71241 0.68981 0.73600 1.00000 <.0001 <.0001 <.0001

irritate 0.67920 0.68319 0.70127 0.70261 1.00000 <.0001 <.0001 <.0001 <.0001

topofthg 0.63596 0.61458 0.59337 0.70208 0.66627 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001

time 0.40030 0.27520 0.35535 0.40474 0.45190 0.37792 1.00000 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 ______

144

Table K.2 Descriptive Statistics ______Variable N Mean Std Dev Sum Minimum Maximum ______upset 338 1.73669 0.79607 587.00000 0 4.00000 control 338 1.41716 1.10861 479.00000 0 4.00000 stressed 338 1.67751 0.93379 567.00000 0 4.00000 cope 338 1.63018 1.10135 551.00000 0 4.00000 angered 338 1.96746 0.86241 665.00000 0 4.00000 thinking 338 2.69527 0.89776 911.00000 0 4.00000 difficul 338 1.55621 1.21737 526.00000 0 4.00000 hassles 338 1.38462 1.00739 468.00000 0 4.00000 changes2 338 1.34024 1.00129 453.00000 0 4.00000 problems 338 1.32544 1.08974 448.00000 0 4.00000 goingurw 338 1.63609 1.15072 553.00000 0 4.00000 irritate 338 1.52959 1.09789 517.00000 0 4.00000 topofthg 338 1.58284 1.32111 535.00000 0 4.00000 time 338 0.71598 1.05168 242.00000 0 4.00000 ______

Table K.3. Cronbach Coefficient Alpha with Deleted Variable ______Raw Variables Standardized Variables

Deleted Correlation Correlation Variable with Total Alpha with Total Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ upset 0.381132 0.915168 0.393517 0.912016 control 0.680184 0.905722 0.682989 0.901213 stressed 0.443911 0.913762 0.464553 0.909424 cope 0.691881 0.905274 0.694641 0.900764 angered 0.611355 0.908655 0.619736 0.903628 thinking 0.113911 0.923320 0.110569 0.921968 difficul 0.797900 0.900697 0.793716 0.896909 hassles 0.789717 0.901995 0.782164 0.897362 changes2 0.767657 0.902828 0.759006 0.898268 problems 0.767955 0.902346 0.757422 0.898330 goingurw 0.771887 0.901971 0.757242 0.898337 irritate 0.795027 0.901245 0.782137 0.897364 topofthg 0.655991 0.907291 0.644054 0.902703 time 0.441574 0.914402 0.435598 0.910485 ______

Cronbach Coefficient Alpha

Variables Alpha ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Raw 0.913823 Standardized 0.910036 145

Appendix 2 Table 2.1. Standard deviations and intercorrelations of the measured scales

Measures V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 N 284 284 284 284 284 284 284 284 284 284 284 284

STD 3.2 3.8 2.0 1.3 2.0 2.2 2.4 4.8 0.4 0.4 0.5 0.5

V1. Moral Norms 1.000

V2. Self-Efficacy 0.585 1.000 <.0001 V3. Anticipated Regrets 0.356 0.373 1.000 <.0001 <.0001 V4. Outcome Expectancies 0.154 0.100 0.418 1.000 0.009 0.092 <.0001 V5. Outcome Value 0.063 -.049 -.098 -.058 1.000 0.288 0.414 0.100 0.331 V6. HIV Treatment Beliefs 0.468 0.258 0.130 0.192 0.253 1.000 <.0001 <.0001 0.028 0.001 <.0001 V7. Social Norms 0.135 0.017 0.403 0.604 -.060 0.094 1.000 0.023 0.775 <.0001 <.0001 0.313 0.115 V8. Religious Norms 0.232 0.224 0.258 0.208 -.074 0.094 0.228 1.000 <.0001 <.0001 <.0001 0.004 0.215 0.112 <.0001 V9. Anxiety -.168 -.100 -.004 -.143 -.118 -.268 -.034 0.009 1.000 0.004 0.092 0.948 0.016 0.047 <.0001 0.572 0.877 V10. Depression -.242 -.146 0.089 -.068 -.012 -.187 0.025 -.005 0.703 1.000 <.0001 0.014 0.134 0.253 0.834 0.001 0.674 0.935 <.0001 V11. Stress -.320 -.104 0.048 -.069 -.096 -.321 0.056 0.018 0.342 0.462 1.000 <.0001 0.080 0.420 0.242 0.104 <.0001 0.348 0.759 <.0001 <.0001 V12. Sexual Risk Behavior -.069 -.276 -.266 0.017 0.092 0.070 -.050 -.153 -.068 -.146 -.119 1.000 0.247 <.0001 <.0001 0.778 0.121 0.241 0.403 0.010 0.403 0.013 0.044 146

Table 2.2. Standard deviations and intercorrelations of the measured scales for the women

Measures V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 N 143 143 143 143 143 143 143 143 143 143 143 143

STD 3.5 4.3 2.3 1.5 2.1 2.3 2.7 4.5 0.5 0.5 0.5 0.5

V1. Moral Norms 1.000 <.0001 V2. Self-Efficacy 0.570 1.000. <.0001 V3. Anticipated Regrets 0.423 0.473 1.000 <.0001 <.0001 V4. Outcome Expectancies 0.206 0.119 0.389 1.000 0.013 0.157 <.0001 V5. Outcome Value 0.112 0.019 -.097 -.116 1.000 0.184 0.824 0.251 0.166 V6. HIV Treatment Beliefs 0.452 0.284 0.226 0.255 0.315 1.000 <.0001 0.0006 0.007 0.002 <.0001 V7. Social Norms 0.233 0.037 0.361 0.529 -.059 0.126 1.000 0.005 0.660 <.0001 <.0001 0.480 0.133 V8. Religious Norms 0.184 0.246 0.427 0.345 -.201 0.045 0.418 1.000 0.028 0.003 <.0001 <.0001 0.016 0.593 <.0001 V9. Anxiety -.244 -.072 0.000 -.199 -.184 -.393 -.009 -.007 1.000 0.003 0.389 0.995 0.017 0.028 <.0001 0.916 0.935 V10. Depression -.336 -.154 0.125 -.123 -.017 -.230 0.051 0.014 0.656 1.000 <.0001 0.055 0.135 0.142 0.842 0.006 0.546 0.866 <.0001 V11. Stress -.250 -.069 0.102 -.090 -.149 -.335 0.115 0.117 0.394 0.508 1.000 0.003 0.410 0.225 0.285 0.075 <.0001 0.171 0.164 <.0001 <.0001 V12. Sexual Risk Behavior -.107 -.363 -.332 -.033 0.103 -.081 -.103 -.231 -.134 -.236 -.166 1.000 0.204 <.0001 <.0001 0.696 0.222 0.335 0.222 0.005 0.111 0.004 0.047 147

Table 2.3. Standard deviations and intercorrelations of the measured scales for the men

Measures V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 N 140 140 140 140 140 140 140 140 140 140 140 140

STD 3.0 3.2 1.7 1.1 1.9 2.0 2.0 5.0 0.3 0.4 0.5 0.5

V1. Moral Norms 1.000

V2. Self-Efficacy 0.632 1.000 >.0001 V3. Anticipated Regrets 0.260 0.167 1.000 0.002 0.048 V4. Outcome Expectancies 0.078 0.053 0.467 1.000 0.362 0.534 >.0001 V5. Outcome Value -.002 -.138 -.089 0.039 1.000 0.979 0.104 0.293 0.648 V6. HIV Treatment Beliefs 0.488 0.225 -.019 0.098 0.170 1.000 >.0001 0.007 0.825 0.248 0.045 V7. Social Norms -.005 -.048 0.471 0.743 -.048 0.050 1.000 0.965 0.569 >.0001 >.0001 0.576 0.579 V8. Religious Norms 0.278 0.220 0.066 0.053 0.054 0.146 0.014 1.000 0.001 0.009 0.436 0.537 0.524 0.086 0.866 V9. Anxiety -.010 -.080 0.048 -.016 -.075 -.110 0.002 -.005 1.000 0.242 0.344 0.571 0.855 0.378 0.197 0.979 0.953 V10. Depression -.136 -.082 0.073 0.052 -.041 -.144 0.041 -.052 0.746 1.000 0.109 0.333 0.393 0.544 0.632 0.089 0.632 0.538 >.0001 V11. Stress -.424 -.159 -.025 -.043 -.036 -.313 -.016 -.082 0.300 0.424 1.000 >.0001 0.060 0.772 0.617 0.671 0.0002 0.852 0.335 0.0003 >.0001 V12. Sexual Risk Behavior -.022 -.144 -.171 0.094 0.071 0.253 0.037 -.082 -.023 -.064 -.069 1.000 0.794 0.089 0.044 0.270 0.404 0.003 0.667 0.336 0.791 0.454 0.418 148

Table 2.4. Standard deviations and intercorrelations of the measured scales for men and women Measures V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 N 283 283 83 283 283 283 283 283 283 283 283 283 283

STD 3.2 3.8 2.0 1.3 2.0 2.2 2.4 4.8 0.4 0.4 0.5 0.5 0.5

V1. Moral Norms 1.000

V2. Self-Efficacy 0.583 1.000 >.0001 V3. Anticipated Regrets 0.355 0.372 1.000 >.0001 >.0001 V4. Outcome Expectancies 0.154 0.099 0.418 1.000 0.010 0.095 >.0001 V5. Outcome Value 0.066 -.047 -.097 -.057 1.000 0.269 0.432 0.104 0.335 V6. HIV Treatment Beliefs 0.468 0.257 0.130 0.192 0.254 1.000 >.0001 >.0001 0.029 0.001 >.0001 V7. Social Norms 0.136 0.017 0.403 0.604 -.060 0.094 1.000 0.022 0.773 >.0001 >.0001 0.313 0.116 V8. Religious Norms 0.230 0.223 0.258 0.208 -.072 0.094 0.228 1.000 >.0001 0.0002 >.0001 0.0004 0.224 0.114 0.0001 V9. Anxiety -.166 -.098 -.003 -.143 -.119 -.267 -.034 0.011 1.000 0.005 0.099 0.960 0.016 0.045 >.0001 0.571 0.857 V10. Depression -.240 -.144 0.090 -.067 -.014 -.187 0.025 -.003 0.702 1.000 >.0001 0.015 0.129 0.257 0.819 0.002 0.676 0.954 >.0001 V11. Stress -.326 -.108 0.046 -.071 -.095 -.323 0.056 0.016 0.345 0.465 1.000 >.0001 0.070 0.436 0.236 0.112 >.0001 0.346 0.792 >.0001 >.0001 V12. Sex -.052 0.094 0.066 0.042 -.058 -.024 0.101 -.058 -.283 -.207 -.032 1.000 0.379 0.116 0.268 0.477 0.327 0.691 0.087 0.333 >.0001 0.0005 0.589 V13. Sexual Risk Behavior -.066 -.274 -.266 0.017 0.091 0.070 -.050 -.151 -.070 -.148 -.117 -.050 1.000 0.270 >.0001 >.0001 0.770 0.127 0.237 0.403 0.011 0.241 0.013 0.049 0.397 149

Appendix 3

Table 3.1. Association between demographic/heatlh status variables and sex 1

2 Variables Female Male P-value (N=174) (N=172)

Age in years 18-44 87.9 % 88.4 % 0.90 45 and over 12.1 11.6

Marital status Married or Living with a partner 37.2 % 45.0 % 0.14 Widowed, separated, divorced, 62.8 55.0 single or never married Highest educational level attained Primary 25.7 % 8.1 % < .0001 Secondary or beyond 74.3 91.9

Employment status Employed 51.2 % 81.8 % < .0001 Unemployed 48.8 18.2

Perceived income adequacy Very good or good 22.9 % 30.4 % 0.11 Fair or Poor 77.1 69.6

Perceived health Very good or good 71.2 % 64.9 % 0.21 Fair or Poor 28.8 35.1 1 One respondent had missing information on sex 2 Chi-square test used unless specified

150

Table 3.2. Association between measured scales and sex 1

Variables Female Male P-value 2 (N=174) (N=172) Anxiety Possible anxiety case 40.6 % 17.3 % < .0001 No anxiety 59.4 82.7

Depression Possible depressive case 36.6 % 20.8 % 0.001 No depression 63.4 79.2

Perceived stress High perceived stress 51.4 % 50.3 % 0.83 Low perceived stress 48.6 49.7

Moral Norm, mean (SD) 3 20.1 (3.5) 19.8 (3.1) 0.35

Self-efficacy, median (Range) 4 19.0 (5-24) 21.0 (0-24) 0.07

4 Anticipated regrets, median (Range) 18.0 (0-24) 18.0 (5-24) 0.56

3 Outcome expectancies, mean (SD) 7.4 (1.7) 7.6 (1.4) 0.23

Outcome value, mean (SD) 3 10.3 (2.3) 10.2 (2.2) 0.92

HIV Treatment Beliefs, mean (SD) 3 16.5 (2.3) 16.4 (2.0) 0.69

Social Norm, mean (SD) 3 13.6 (2.9) 14.1 (2.6) 0.07

4 Religious Beliefs, median (Range) 24.0 (6-25) 24.0 (6-25) 0.13 2 Chi-square test used unless specified 3 Student's T-test 4 Wilcoxon Rank test

151

Table 3.3. Association between demographic/healthstatus variables and education level

Variables No formal Formal P-value 1 schooling (N=28) Schooling (N=349) Gender Female 75.0 % 50.3 % 0.01 Male 25.0 49.7

Age in years 18-44 81.5 % 88.2 % 0.31 45 and over 18.5 11.8

Marital status Married or Living with a partner 42.9 % 41.0 % 0.85

Widowed, separated, divorced, 57.1 59.0 single or never married

Employment status Employed 42.9 % 66.2 % 0.01 Unemployed 57.1 33.8

Religious affiliation Christian 39.3 % 57.0 % 0.02 Muslim 57.1 29.8 Other 3.6 13.2

Perceived income adequacy Very good or good 11.1 % 26.5 % 0.08

Fair or Poor 88.9 73.5

Mean disease duration (in months) 45.6 50.2 0.54

Perceived health Very good or good 73.1 % 68.1 % 0.60

Fair or Poor 26.9 31.9

Lifestyle changes due to HIV A lot/Some 50.0 40.5 0.38 Not at all 50.0 59.5 1 Chi-square test used unless otherw ise indicated

152

Table 3.4. Association between psychological distress variables/sexual risk behaviors and education level

Variables No formal Formal P-value 1 Schooling (N=28)Schooling (N=349) Anxiety Possible anxiety case 60.7 % 28.9 % 0.0005 No anxiety 39.3 71.1 Depression Possible depressive case 39.3 % 28.7 % 0.23 No depression 60.7 71.3

Perceived stress High perceived stress 57.1 % 51.0 % 0.53 Low perceived stress 42.9 49.0

Sexual behaviors last 6 months

Had a regular sexual partner 53.6 % 57.6 % 0.68 Had casual partners 17.9 % 16.9 % 0.90 No partner 39.3 % 32.7 % 0.47 High-risk sexual behavior 42.9 % 36.4 % 0.49

HIV status of regular partner (n= 216) Positive 35.7 % 54.5 % 0.11 Negative 14.3 21.0 Unknown 50.0 24.5

3 HIV status of casuals partners (n= 64) All Negative 0 % 5.2 % 0.002 Some/ All positive 0 39.7 Unknown/Refused 100 55.2

Condom use with regular partner (n=199) 2 Always 41.7 % 64.2 % 0.12 Sometimes, rarely or never 58.3 35.8 Condom use with casual partners (n= 60) 4 Always 100 % 71.9 % 0.28 Sometimes, rarely or never 0 28.1

Disclosed HIV status to regular partner (n= 216) 57.1 % 77.5 % 0.08

HIV status disclosure to casual partners (n= 64) Always 0 % 24.1 % 0.26 Sometimes, rarely or never 100 75.9 1 Chi-square test use unless otherw ise indicated 2 Excluding those w ith missing/refused/NA responses for condom used (N=17) 3 Chhi-square test may not be appropriate

153

Table 3.5. Association between demographic/health status variables/sexual risk behaviors and regular partner HIV status (N=201)

Variables Partner Partner Partner P-value HIV positive HIV negative HIV status unknown Sex Female 35.8 % 78.6 % 67.3 % < 0.0001 Male 64.2 21.4 32.7

Age in years 18-44 86.1 % 95.2 % 95.8 % 0.08 d 9.4 33.3 70.8 45 and over 13.9 4.8 4.2 single/never married Marital status Education level Married or Living with a partne 90.6 % 66.7 % 29.2 % < 0.0001 Primary school 14.7 % 9.5 % 10.2 % 0.59 Widowed, separated, divorce Secondary or beyond 85.3 90.5 89.8

Employment status Employed 82.6 % 71.4 % 56.2 % 0.002 Unemployed 17.4 28.6 43.8

Perceived income adequacy Very good or good 43.0 % 40.5 % 22.5 % 0.04 Fair or poor 57.0 59.5 77.5

Disclosed HIV statusPerceived to partner health status 96.3 % 95.2 % 20.4 % < .0001 Very good or good 76.4 % 90.5 % 85.4 % 0.10 Inconsistent or no condomFair use or poor 36.3 % 23.6 14.6 % 9.5 54.5 % 0.0006 14.5

Sexual risk behaviors 154

Table 3.6. Association between the measured scales and regular partner HIV status (N=201)

Variables Partner HIV Partner HIV Partner HIV status P-value positive negative unknown Anxiety Possible anxiety case 13.8 % 14.3 % 32.6 % 0.01 No anxiety 86.2 85.7 67.4

Depression Possible depressive case 14.7 % 7.1 % 26.5 % 0.04 No depression 85.3 92.9 73.5

Perceived stress High perceived stress 38.5 % 33.3 % 40.8 % 0.75 Low perceived stress 61.5 66.7 59.2

Moral Norms (mean, SD) 19.9 (3.3) 22.2 (2.8) 20.3 (4.3) 0.001 ) 7.4 (1.6) 7.8 (1.4) 7.8 (1.8) 0.26 Self-efficacy (mean, SD) 20.2 (3.4) 22.1 (3.7) 18.5 (6.1) 0.001 Outcome value (mean, SD) 10.1 (2.3) 9.6 (9.6) 10.6 (2.2) 0.11 Anticipated regrets (mean, SD) 16.5 (2.7) 17.2 (1.9) 16.7 (2.9) 0.37 HIV treatment beliefs (mean, SD) 16.7 (2.0) 17.3 (2.1) 16.9 (3.1) 0.46 Outcome expectancies (mean, SD

Social Norms (mean, SD) 13.5 (2.9) 14.0 (2.7) 14.5 (2.7) 0.11

Religious Norms (mean, SD) 21.7 (4.7) 22.9 (3.3) 21.8 (4.3) 0.30 155

Structural Model including Partner HIV Status as a control variable

Moral Norms Self-Efficacy HIV Treatment Beliefs

0.81 0. 72*** 0.45*** Anxiety Depression Stress

Internal Cognitive Factor 0 0 0 0 -0. 34*

Situational Factor 0 Sexual Risk Behavior

0. 37*** 0 0. 08

Partner HIV External Cognitive Factor status

0. 56*** 0. 86 0. 73***

Anticipated Regrets Outcome Expectancies Social Norms

Figure 3.1. Structural model and standardized estimates. *p <= 0.05; **p <= 0.01; ***p <= 0.001; R2=0.25 Delta2 and CFI <= 0.60; chi-square < 0.0001

156

Questionnaire

Q1 Interviewer's Initials Q3 Date of Interview ______

Q2 Participant's ID Number Q4 Participant's Sex (Check one) ______Female ...... 1 Male ...... 2

This questionnaire has been prepared for the study project I just told you about. All the information collected today is and will be kept strictly confidential.

Mini Mental State Examination Q7 Please count backwards from 500 (MMSE) Francs by 100 Francs 500 Francs...... 1 First, I would like to ask you a few 400 Francs...... 2 general questions. Some of the questions 300 Francs...... 3 are very simple, and some are more 200 Francs...... 4 difficult. Try to do your best in 100 Francs...... 5 answering them. Q8 What were the three objects I asked Q5 Orientation you to repeat and remember a few What is the year? ...... 1 minutes ago? What is the season? ...... 2 What is the month? ...... 3 Lemon...... 1 What is the date? ...... 4 Key ...... 2 What is the day of the week?...... 5 Ball...... 3 What hospital are we in? ...... 6 What city are we in? ...... 7 Q9 Show patient a wristwatch. What county are we in? ...... 8 What is this?...... 1 What country are we in?...... 9 What floor are we on? ...... 10 Q10 Show patient a pencil. What is this? ...... 1 Q6 I am going to name three objects. I want you to repeat them and Q11 Please listen carefully and repeat after remember what they are because me. later on, I am going to ask you to NO IFS, ANDS, OR BUTS ...... 1 repeat them again. The three objects are: Q12 Put a paper in front of patient and Lemon ...... 1 say: Listen carefully and do what I Key...... 2 am going to ask you to do. Ball...... 3 Take the paper in your right 1

hand...... Fold it in half ...... 2 157

Put it on the floor ...... 3 Q14 Ask patient: Please tell me any complete 1 Q13 Close eyes and ask patients: sentence...... Please do the same...... 1 Q15 Show patient a picture of 2 intersected pentagons and say: Please copy this picture just below... 1

Interviewers: Refer to the scoring manual and record the number of points obtained by the participant: ------If less than 22, ask questions Q16 through Q19 and end the interview. 158

Section I. Health Information

The following questions are about your health status since you were diagnosed with HIV/AIDS. Again, all answers are confidential.

Q16 How long has it been since you have Q18 In the past 6 months, or since you been diagnosed with HIV? have been diagnosed (if less than 6 Number of years.. ______months), how much would you say Number of months ______that your HIV status has caused you to change your lifestyle Q17 I would like you to think about the A lot...... 1 past 6 months,or about the time Some...... 2 since you have been diagnosed (if Not at all ...... 3 GO TO SECTION less than 6 months),in answering the II following question. Would you say Don't know .... 4 GO TO SECTION that in general your health has II been: Refused...... 5 GO TO SECTION Very good...... 1 II Good ...... 2 Fair ...... 3 Q19 What types of changes have you made Poor ...... 4 in your lifestyle in the past 6 months Don't know ...... 5 as a result of the HIV? Refused...... 6 ______

159

Section II. Sexual Risk Behaviors and HIV Disclosure

In this section, I am going to ask you about a few sexual practices that are important for us to learn about for this study. REMEMBER, ALL THE ANSWERS WILL BE KEPT CONFIDENTIAL.

Q20 Do you have a spouse or a regular Q24 Could you give me at least 3 reasons partner? why you did not tell your spouse (or Yes...... 1 regular partner) that you had No...... 2 GO TO Q26 HIV/AIDS? ______Q21 Is your spouse (or regular partner) ______HIV-positive? ______Yes...... 1 ______No...... 2 ______Don't know ...... 3 ______Q22 Did you tell your spouse (or regular partner) that you had Q25 How often, would you say, you use a HIV/AIDS? condom with your spouse (or Yes...... 1 GO TO Q23 regular partner) during sexual No...... 2 GO TO Q24 intercourse? Always...... 1 Q23 Could you give me at least 3 Sometimes (about half the 2 reasons why you told your spouse time) ...... (or regular partner) that you had Rarely (less than half the time) 3 HIV/AIDS? Never...... 4 ______Don't know ...... 5 ______Not applicable (no sexual 6 ______intercourse)...... ______Refused...... 7 ______Q26 Do you have occasional partner(s)? Yes...... 1 No...... 2 GO TO SECTION III

Q27 Thinking about the last 6 months, or since your diagnosis (if less than 6 months), how many of those partner(s) were HIV-positive? None of them ...... 1 Some of them ...... 2 All of them ...... 3 160

Don't know ...... 4 Rarely (less than half the time) ...... 3 Refused ...... 5 Never...... 4 Don't know ...... 5 Q28 Thinking about all the sexual Refused...... 6 encounters during those past 6 months , or since your diagnosis (if Q30People have different reasons for less than 6 months), how often was telling their sexual partner(s) that a condom used? they have HIV. Can you give me at Always ...... 1 least three reasons why you told your Sometimes (about half the 2 HIV status to your sexual partner(s) time) ...... before having sex/sexual intercourse? Rarely (less than half the time) 3 Never...... 4 ______Don't know ...... 5 ______Refused...... 6 ______

Q31 People have different reasons for telling their sexual partner(s) that they have HIV. Could you give me at least three reasons why you did not tell your HIV status to your sexual partner(s) before sexual intercourse? ______Q29 Thinking about all the sexual ______encounters during those past 6 ______months, or since your diagnosis (if less ______than 6 months), how often would you ______say you told a new partner that you had HIV/AIDS? Always ...... 1 Sometimes (about half the time)...... 2

161

Section III. Socio-Cognitive Factors

III.1 Moral Norms

Now I am going to read you a list of Strongly agree...... 4 statements and I would like you to tell me if you strongly agree, agree, Q35 A person has a moral obligation disagree, or strongly disagree with to talk about safe sex with his/her each of them. sexual partner Strongly disagree ...... 1 Disagree...... 2 Q32 A person has a moral obligation Agree...... 3 to protect his/her sexual partner Strongly agree...... 4 Strongly disagree ...... 1 Disagree ...... 2 Q36 It is wrong for someone to have Agree ...... 3 sexual intercourse without first Strongly agree ...... 4 telling his/her HIV status to his/her partner Q33 It is wrong for someone to have Strongly disagree ...... 1 unprotected sex (i.e. without a Disagree...... 2 condom) Agree...... 3 Strongly disagree ...... 1 Strongly agree...... 4 Disagree ...... 2 Agree ...... 3 Q37 It is wrong for someone to have Strongly agree ...... 4 sexual intercourse without first asking about his/her partner's HIV status Strongly disagree ...... 1 Disagree...... 2 Agree...... 3 Strongly agree...... 4

Q34 It is wrong for someone living with HIV/AIDS to have unprotected sex (i.e. without a condom) Strongly disagree ...... 1 Disagree...... 2 Agree...... 3

162

III.2 Sexual Self-Efficacy

Now I am going to read you a series Q41 How confident are you that you of actions and I would like you to tell could get every partner you've me how sure you are that you could ever had sex with before to use a do each of them. condom even if they didn't want to? Q38 How confident are you that you Not confident at all...... 1 could purchase a condom in a Not very confident...... 2 store? Fairly confident...... 3 Not confident at all...... 1 Very confident ...... 4 Not very confident ...... 2 Don't know ...... 5 Fairly confident...... 3 Very confident ...... 4 Q42 How confident are you that you Don't know ...... 5 could get every partner to use a condom even if you had not use Q39 How sure are you that you could them together in the past? use (ask your partner to use) a Not confident at all...... 1 condom during all sexual Not very confident...... 2 intercourse? Fairly confident...... 3 Not sure at all ...... 1 Very confident ...... 4 Not very sure...... 2 Don't know ...... 5 Fairly sure ...... 3 Very sure...... 4 Q43 How sure are you that you could Don't know ...... 5 stop (ask your partner to stop) in the middle of sex and put on a Q40 How confident are you that you condom? can get every partner to use a Not sure at all...... 1 condom even if they don't want to? Not very sure...... 2 Not confident at all ...... 1 Fairly sure...... 3 Not very confident...... 2 Very sure ...... 4 Fairly confident ...... 3 Don't know ...... 5 Very confident...... 4 Don't know ...... 5 Q44 How sure are you that could completely stop having sexual intercourse because of your HIV status? Not sure at all...... 1 Not very sure...... 2 Fairly sure...... 3 Very sure ...... 4 Don't know ...... 5

163

III.3 Anticipated Regrets

People sometimes regret things they Q48 Having had sexual intercourse have done. I am going to read to you a using a condom. She or he would series of situations. Please tell me how a feel: person living with HIV/AIDS would feel No regrets at all ...... 1 after: Some regrets...... 2 Lots of regrets ...... 3 Q45 Having had sexual intercourse Don't know ...... 4 without telling his or her HIV status to his or her partner. She Q49 Having had sexual intercourse or he would feel: without using a condom with a No regrets at all ...... 1 partner she or he knew was HIV- Some regrets...... 2 negative. She or he would feel: Lots of regrets ...... 3 No regrets at all ...... 1 Don't know ...... 4 Some regrets...... 2 Lots of regrets ...... 3 Q46 Having had sexual intercourse Don't know ...... 4 without asking his or her partner about his/her HIV status. She or Q50 Having had sexual intercourse he would feel: using a condom with a partner she No regrets at all ...... 1 or he knew was HIV-negative. She Some regrets...... 2 or he would feel: Lots of regrets ...... 3 No regrets at all ...... 1 Don't know ...... 4 Some regrets...... 2 Lots of regrets ...... 3 Q47 Having had sexual intercourse Don't know ...... 4 without using a condom. She or he would feel: Q51 Having had sexual intercourse No regrets at all ...... 1 using a condom with a partner she Some regrets...... 2 or he knew was HIV-positive. She Lots of regrets ...... 3 or he would feel: Don't know ...... 4 No regrets at all ...... 1 Some regrets...... 2 Lots of regrets ...... 3 Don't know ...... 4

164

Q52 Having had sexual intercourse Lots of regrets ...... 3 without using a condom with a Don't know ...... 4 partner she or he knew was HIV- positive. She or he would feel: No regrets at all ...... 1 Some regrets...... 2

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III.4 Outcome Expectancies

Q53 For each of the statements I am going to read to you next, please tell me if you strongly agree, agree, disagree, or strongly disagree. Strongly Agree Disagree Strongly agree disagree You feel like you are doing 1 2 3 4 something wrong if your partner and you don't use a condom*.

You feel more responsible if 1 2 3 4 you use a condom.

Using condoms will help build 1 2 3 4 trust between your partner and you.

Using condoms makes you less 1 2 3 4 worried about your partner. Very Somewhat Not Don't confident confident confident know How confident are you that you 1 2 3 4 could refuse to have sex if your partner won't allow use of a condom?

How confident are you that you 1 2 3 4 could convince your partner to use condoms from now on?

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III.5 Outcome Value

Q54 For each of the statements I am going to read to you next, please tell me if you strongly agree, agree, disagree, or strongly disagree. Strongly Agree Disagree Strongly agree disagree In Ivory Coast, most people are 1 2 3 4 less worried about HIV than they used to be.

In Ivory Coast, most people 1 2 3 4 think AIDS is a less serious threat than it used to be.

In Ivory Coast, most people 1 2 3 4 think that being HIV-positive isn't that of a big deal now that treatments are better.

In Ivory Coast, most people are 1 2 3 4 less worried about HIV infection now that treatments are available.

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III.6 Beliefs about HIV treatment

Q55 Are you aware of the treatments Q59 Thinking about the last 10 times that are currently available for you took your medications, how treating people living with often did you take your anti-HIV HIV/AIDS? drugs exactly as prescribed (i.e. the Yes...... 1 exact dose at exact time)? No...... 2 GO TO Q62 Always (10 times 1 GO TO Q61 (SECTION III.7) out of 10)...... Very often 2 Q56 Are you currently taking any (between 9 and 8 treatment for HIV/AIDS? times)...... Yes ...... 1 Fairly often 3 No ...... 2 GO TO Q61 (between 7 and 5 times)...... Q57 How much would you say you Sometimes (less 4 know about the treatments for than 5 times)... those living with HIV/AIDS? Never...... 5 Nothing...... 1 Don't know ..... 6 A little...... 2 Refused...... 7 Some ...... 3 A lot ...... 4 Q60 Sometimes people have difficulties for taking their medications exactly Q58 Approximately how long have you as prescribed. Can you give me at been receiving antiretroviral least three reasons why you did not therapy? take your anti-HIV drugs as Number of years ______prescribed? Number of months ______It is a well-known fact that many people who need to be on tablets for a long time have difficulties with taking them. We are trying to get a clear idea how common this is for people taking anti-HIV treatments.

168

Q61 I am going to read some statements. Please tell me if you strongly agree, agree, disagree, or strongly disagree.

Strongly Agree Disagree Strongly agree disagree If every HIV-positive person took 1 2 3 4 the treatments, the AIDS epidemic would be over.

The treatments for HIV make 1 2 3 4 people with HIV less infectious.

The treatments for HIV take away 1 2 3 4 all the risks for infecting someone through sexual intercourse.

It would be more difficult for an 1 2 3 4 HIV-positive person to infect a partner through unsafe sex if the HIV-positive person was taking the treatments for HIV.

Sex with someone who has 1 2 3 4 HIV/AIDS and is on the antiretroviral drugs is safer than with someone who has HIV/AIDS and is not on the drugs.

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III.7 Social Norms

Q62 For each of the statements I am going to read to you next, please tell me if you strongly agree, agree, disagree, or strongly disagree. Strongly Disagree Agree Strongly disagree agree If a person asks his/her partner to 1 2 3 4 use a condom, the partner will think the person is having sex with someone else.

If someone tells his/her partner 1 2 3 4 they ought to use a condom, the partner will get mad.

Sexual partners should want to use 1 2 3 4 condoms during sex.

Whether or not a condom is used 1 2 3 4 should be up to the sexual partner.

Friends usually think it is 1 2 3 4 important to talk about AIDS, condoms, and/or safe sex practices.

Most people in the community 1 2 3 4 encourage the use of condoms during sex.

Most people in the community 1 2 3 4 think that condoms are v of the HIV infection.

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Section IV. Situational Factors

IV.1 Negative Mood States: Anxiety and Depression

Now I am going to ask you some Q67 Did you feel a sort of frightened questions about feelings you may have feeling like "butterflies" in the experienced over the PAST 6 months stomach? (A) or since your diagnosis (if less than 6 Not at all ...... 1 months). (Interviewer: please read the Occasionally ...... 2 questions and answer categories at Quite often...... 3 each time) Very often...... 4

Q63 Did you feel tense or "wound Q68 Were you looking forward with up"? *(A) enjoyment to things? (D) Most of the time...... 1 As much as you ever did...... 1 A lot of the time ...... 2 Rather less than you used 2 From time to time, 3 to ...... occasionally...... Definitely less than you 3 Not at all...... 4 used to ...... Hardly at all...... 4 Q64 Did you have worrying thoughts go through your mind? * (A) A great deal of the time ...... 1 Q69 Did you have sudden feelings of A lot of the time ...... 2 panic? * (A) From time to time, but not too 3 Very often indeed ...... 1 often...... Quite often...... 2 Only occasionally...... 4 Not very often...... 3 Not at all ...... 4 Q65 Did you feel cheerful? * (D) Not at all...... 1 Q70 Did you feel you could enjoy a Not often...... 2 good book or radio or TV Sometimes...... 3 program? (D) Most of the time...... 4 Often...... 1 Sometimes ...... 2 Q66 Did you feel as if you were slowed Not often...... 3 down? * (D) Very seldom...... 4 Nearly all the time...... 1 Very often ...... 2 Q71 Did you feel you still enjoyed the Sometimes...... 3 things you used to enjoy? (D) Not at all...... 4 Definitely as much as usual..... 1 Not quite as much...... 2 Only a little...... 3 Hardly at all ...... 4 171

Q74 Did you feel you could sit at ease Q72 Did you feel a sort of frightened and feel relaxed? (A) feeling as if something awful were Definitely as much as usual...... 1 about to happen? * (A) Usually...... 2 Very definitely and quite 1 Not often ...... 3 badly...... Not at all...... 4 Yes, but not too badly...... 2 A little, but it didn't worry 3 Q75 Did you feel you had lost interest in you...... your appearance? * (D) Not at all...... 4 Definitely...... 1 You didn't take so care as you 2 Q73 Did you feel you could laugh and should have ...... see the funny side of things? (D) You might not have taken quite 3 As much as you always could. 1 as much care ...... Not quite so much...... 2 You took care just as much care 4 Definitely not so much...... 3 as ever ...... Not at all...... 4 Q76 Did you feel restless as if you had to be on the move? * (A) Very much indeed...... 1 Quite a lot ...... 2 Not very much ...... 3 Not at all ...... 4

* Items will be reversed scored; (A) Items measuring anxiety; (D) Items measuring depression

172

IV.2 Perceived Stress

Q77 In the last 6 months or since your Q81 In the last 6 months or since your diagnosis, how often have you been diagnosis, how often have you felt upset because of something that that you were effectively coping happened unexpectedly? with important changes that were Never...... 1 occurring in your life?* Almost never ...... 2 Never...... 1 Sometimes ...... 3 Almost never...... 2 Fairly often ...... 4 Sometimes ...... 3 Very often...... 5 Fairly often...... 4 Very often...... 5 Q78 In the last 6 months or since your diagnosis, how often have you felt Q82 In the last 6 months or since your that you were unable to control the diagnosis, how often have you felt important things in your life? confident about your ability to Never ...... 1 handle your personal problems ?* Almost never...... 2 Never...... 1 Sometimes...... 3 Almost never...... 2 Fairly often...... 4 Sometimes ...... 3 Very often ...... 5 Fairly often...... 4 Very often...... 5 Q79 In the last 6 months or since your diagnosis, how often have you felt Q83 In the last 6 months or since your nervous and “stressed”? diagnosis, how often have you felt Never...... 1 that things were going your way?* Almost never ...... 2 Never...... 1 Sometimes ...... 3 Almost never...... 2 Fairly often ...... 4 Sometimes ...... 3 Very often...... 5 Fairly often...... 4 Very often...... 5 Q80 In the last 6 months or since your diagnosis, how often have you dealt Q84 In the last 6 months or since your successfully with irritating life diagnosis, how often have you hassles?* found that you could not cope Never...... 1 with all the things that you had to Almost never...... 2 do? Sometimes ...... 3 Never...... 1 Fairly often...... 4 Almost never...... 2 Very often...... 5 Sometimes ...... 3 Fairly often...... 4 Very often...... 5 173

Q85 In the last 6 months or since your Q88 In the last 6 months or since your diagnosis, how often have you been diagnosis, how often have you found able to control irritations in your yourself thinking about things that life?* you have to accomplish? Never...... 1 Never...... 1 Almost never...... 2 Almost never...... 2 Sometimes ...... 3 Sometimes ...... 3 Fairly often...... 4 Fairly often...... 4 Very often...... 5 Very often...... 5

Q86 In the last 6 months or since your Q89 In the last 6 months or since your diagnosis, how often have you felt diagnosis, how often have you been that you were on top of things?* able to control the way you spend Never...... 1 your time?* Almost never ...... 2 Never...... 1 Sometimes ...... 3 Almost never...... 2 Fairly often ...... 4 Sometimes ...... 3 Very often...... 5 Fairly often...... 4 Very often...... 5 Q87 In the last 6 months or since your diagnosis, how often have you been Q90 In the last 6 months or since your angered because of things that diagnosis, how often have you felt happened that were outside of difficulties were piling up so high your control? that you could not overcome them? Never...... 1 Never...... 1 Almost never...... 2 Almost never...... 2 Sometimes ...... 3 Sometimes ...... 3 Fairly often...... 4 Fairly often...... 4 Very often...... 5 Very often...... 5

* Items will be reversed scored 174

Section V. Demographic/Background Information

The purpose of this section is to have some background information. No questions identifying you specifically will be asked. ALL ANSWERS ARE CONFIDENTIAL.

Q91 What is your age? (Interviewer: Q95 If currently married or living with please check the category a partner), what is the highest corresponding to the age given by grade or year of regular school the respondent) your spouse/partner has ever 18 - 24 ...... 1 completed? 25 - 34...... 2 None ...... 1 35 - 44...... 3 Elementary ...... 2 45 - 54...... 4 High school ...... 3 55+...... 5 University...... 4 Don't know ...... 6 Don't know ...... 5 Refused...... 7 Refused...... 6

Q92 What is your current marital Q96 Are you currently employed? status? Yes...... 1 GO TO Q98 Legally married...... 1 No...... 2 Married traditionally ...... 2 Living with a partner...... 3 Q97 Are you... Widowed...... 4 Retired ...... 1 Divorced...... 5 Disabled...... 2 Separated...... 6 A student ...... 3 SKIP TO Q101 Never married/Single ...... 7 Refused ...... 8 Keeping 4 SKIP TO Q101 house...... Q93 (If currently married legally or Unemployed 5 traditionally), is your because of spouse/partner living with you? your health Yes ...... 1 status...... No ...... 2 Refused...... 6 SKIP TO Q101 Refused ...... 3 Other...... 7 SKIP TO Q101 Q94 What is the highest grade or year of regular school you have ever Specify if ______completed? other ______None...... 1 Elementary...... 2 High school...... 3 University...... 4 Refused...... 5

175

Q98 What is (was) your profession? Q103 What is (was) her/his profession? ______

Q99 What kind of business or industry Q104 What kind of business or industry (is/was) that?i.e where do/did you (is/was) that? i.e. where do/did work? he/she work? ______

Q100 What (are/were) your most Q105 What (are/were) her/his most important job activities or important job activities or duties? duties? ______Q106 What is your religion? Christian...... 1 Q101 (If currently married or living Muslim...... 2 with a partner), is your Refused...... 3 spouse/partner currently Other ...... 4 employed? Specify if other ______Yes...... 1 GO TO Q103 ______No...... 2

Q102 Is he/she... Q107 How often do you attend religious Retired...... 1 service?* Disabled ...... 2 Several times a week ...... 1 Student...... 3 SKIP TO Every week ...... 2 Q106 Nearly every week ...... 3 Keeping a 4 SKIP TO 2-3 times a month...... 4 house ...... Q106 About once a month...... 5 Unemployed 5 Several times a year ...... 6 because of About once or twice a year ...... 7 his/her health Less than once a year...... 8 status ...... Never ...... 9 Refused...... 6 SKIP TO Q106 Q108 How often do you pray by Other ...... 7 SKIP TO yourself?* Q106 Several times a day ...... 1 specify if other ______Once a day ...... 2 ______A few times a week ...... 3 ______Once a week ...... 4 A few times a month ...... 5 Once a month ...... 6 Less than once a month...... 7 Never ...... 8 176

* Items will be reverse-scored

Q109 For each of the statements I am going to read to you next, please tell me if you strongly agree, agree, disagree, or strongly disagree. Strongly Agree Disagree Strongly agree disagree Putting somebody at risk for 1 2 3 4 HIV infection means that I have failed my obligations to God

Religion plays a large role in 1 2 3 4 my daily life.

Q110 How would you describe your Q111 We have come to the end of the overall financial situation? (read questionnaire. Do you have any categories to respondent) comments and/or questions you More than adequate ...... 1 would like me to answer? Adequate...... 2 ______Less than adequate...... 3 ______Refused...... 4 ______

Thank you very much for your participation. Data collected for this project will help identify a number of issues persons living with HIV/AIDS might face in their daily life. We hope the results can be used to design better programs to assist them in the future.

177

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