Large racial/ethnic disparities exist between African Americans and Whites in HIV/AIDS diagnosis, treatment, and survival times. In 2006, the rate of HIV/AIDS diagnosis for African Americans was 68 per 100,000 and 8.2 per 100,000 for Whites.1 Among all racial/ethnic groups and both genders, the highest rates of HIV and AIDS diagnoses are among African American men.2 Moreover, in Los Angeles, the setting of the present study, in 2008, 19% of all male AIDS cases were African American men, although only 8% of men in the Los Angeles area were African American.3,4 Compared with their White counterparts, African Americans with HIV show lower rates of antiretroviral treatment utilization and adherence5-20 and worse survival times.21-24 Thus, uncovering reasons for nonadherence among African Americans with HIV is critical for designing culturally tailored adherence-promoting interventions.
Medical mistrust, including mistrust of HIV treatments, health care providers, and the medical system, is prevalent among African Americans25-27 and may influence health care behaviors.11,13,28 African Americans have reported lower satisfaction with health care;29-31 are skeptical about the efficacy of medications;32,33 and perceive that the US health care system is racist or discriminatory.31,34-41 Such feelings of mistrust are believed to stem from current and historical segregation, racism, and unjust treatment in the health care system and society in general.25,42-45
In the present study, we examined one form of medical mistrust as a potential barrier to treatment adherence-conspiracy beliefs about HIV (eg, HIV is a manmade virus). Prior research indicates that conspiracy beliefs are prevalent among African Americans.46-51 For example, substantial proportions of African Americans in a national random sample endorsed conspiracy beliefs about the origin and treatment of HIV: 48% believed that HIV is a manmade virus; 53% agreed that a cure for AIDS is being withheld from the poor; and 44% thought that people who take antiretroviral medications are human guinea pigs for the government.48 Research suggests that belief in conspiracies is higher among African Americans (vs. Whites), people of lower socioeconomic status, and men.49-55 Among people with HIV, conspiracy beliefs have been related to greater time since diagnosis and worse mental and physical health.55,56
HIV conspiracy beliefs have been associated with poor health behaviors related to HIV prevention and treatment, including lower levels of condom use among African American men in general public samples;48,57 lack of HIV testing among at-risk Black South Africans;58 and a greater number of emergency room visits among people with HIV.55 However, a cross-sectional study of 113 African Americans, Latinos, and Whites with HIV attending public treatment facilities did not find significant relationships between conspiracies and treatment nonadherence or engagement in care,56 although the majority (63%) of the sample endorsed at least 1 conspiracy belief. The authors suggested that conspiracies are common among patients with HIV but do not influence treatment behaviors. An alternate explanation may be that conflating responses across 3 racial/ethnic groups may have diluted any adherence effects; research suggests that beliefs indicative of medical mistrust may be more highly related to health behaviors among African Americans than Whites.11 Further work is needed to determine the relationship between belief in conspiracies and treatment adherence among African Americans in particular.
We tested the hypothesis that conspiracy beliefs are associated with nonadherence in a longitudinal sample of 214 African American men with HIV; conspiracy beliefs were assessed at baseline, and adherence was measured for 1 month postbaseline. We examined 2 types of conspiracy beliefs: those related to genocide (eg, “HIV is a manmade virus”) and those related to treatment mistrust (eg, “People who take the new medications for HIV are human guinea pigs for the government”). Although prior research in a general population sample suggested that conspiracy beliefs are a unidimensional construct,48 research has not yet tested the factor structure of such beliefs among people with HIV. Treatment-related beliefs are presumably more salient among people with HIV and therefore may need to be explored separately from other types of beliefs.
We were especially interested in assessing whether conspiracy beliefs had unique relationships with nonadherence, over and above variables related to adherence in prior research, including depression, substance use, sociodemographic and medical characteristics, and tangible and psychosocial barriers to health care access, such as lack of insurance.7,59-61 Such findings would suggest that conspiracy beliefs act as powerful barriers to adherence that need to be overcome in addition to mental health, substance use, and tangible structural barriers to improve treatment behaviors among African Americans with HIV. A significant multivariate effect of conspiracy beliefs, controlling for structural health care barriers, would suggest that interventions that ignore the influence of HIV conspiracy beliefs would not be successful even if tangible hurdles (eg, related to transportation, health insurance) were removed.
The present study was conducted among African American men with HIV in the Los Angeles, CA, area. We recruited 214 African American men with HIV on antiretroviral treatment using fliers disseminated and posted by staff at 3 HIV social service agencies and an HIV medical clinic. Individuals were eligible if they were African American, aged 18 years or older, and currently taking antiretroviral treatment. Interested individuals were screened for eligibility by telephone. Eligible participants were interviewed in confidential sound-proof rooms at the social service agencies. Study staff obtained informed consent before the interview. All study procedures were approved by the institutional review boards of Children's Hospital Boston, RAND Corporation, and Charles Drew University of Medicine and Science. Study procedures were in accordance with the Helsinki Declaration of 1975, as revised in 2000.
A total of 214 African American men with HIV were recruited and interviewed at baseline, of which 177 (83%) returned for the 1-month follow-up assessment. Four participants were lost to follow-up due to incarceration (n = 4), because we did not have institutional review board approval to survey prisoners; one participant died in between his baseline survey and 1-month follow-up appointment. Participants who did not complete the 1-month follow-up (n = 37) did not differ from other participants on sociodemographic factors, conspiracy beliefs, or treatment adherence (all P values > 0.05).
Participants completed a self-administered audio computer-assisted interview at baseline and at 1-month follow-up. At 1-month postbaseline, participants met with interviewers to download electronic medication adherence data (as described below).
HIV Conspiracy Beliefs
At baseline, participants were asked the extent to which they agreed or disagreed (1 = strongly disagree; 2 = slightly disagree; 3 = neutral; 4 = slightly agree; 5 = strongly agree) with 9 items assessing belief in specific HIV-related conspiracies and misconceptions (Table 1).48 Participants could also choose a “don't know” option (there was an average of 12 “don't know” responses per item); “don't know” responses were combined with “neutral” responses on the scale.
Exploratory factor analysis was performed using varimax rotation on the 9 conspiracy belief items. Based on an eigenvalue criterion of values greater than 1,62 2 factors were extracted: 1 representing “genocidal” conspiracies and 1 representing “treatment” conspiracies (as indicated in Table 1). We used a factor loading cut off of .60 (at least 36% overlapping variance) to determine items to retain;63 based on this criterion, we dropped only 1 item (“The medication used to treat HIV causes people to get AIDS”), which had a factor loading of 0.41. We then conducted a confirmatory factor analysis with the remaining 8 items to determine whether an overall 1-factor model fit the data better than the 2-factor model suggested by the exploratory factor analysis. Comparison of goodness-of-fit χ2 statistics indicated that the 2-factor solution (χ2 = 81.3, df = 20) was a better fit than the 1-factor solution (χ2 = 127.1, df = 19), Δχ2 = 45.8, df = 1, P < 0.0001. We therefore created 2 conspiracy beliefs subscales by averaging the 2 treatment beliefs (α = 0.78) and the 6 genocidal beliefs (α = 0.92).
Medication adherence was measured electronically for one month post-baseline using the Medication Event Monitoring System (MEMS; AARDEX, Inc, Zurich, Switzerland), which consists of bottle caps that record the times when medication bottles are opened. Electronic monitoring software yields detailed reports of daily medication-taking patterns and calculates the percentage of total scheduled doses actually taken in a format suitable for conversion to a statistical analysis package. We only monitored adherence to the antiretroviral medication with the most complex regimen because research indicates that rates of adherence do not differ significantly across medications.64 Participants were instructed to replenish the bottle when needed by refilling it after they removed the last pill.
At 1 month postbaseline, participants' MEMS data were downloaded, and participants completed a short questionnaire assessing whether (and how often) they (1) opened the bottle without removing a dose, (2) took a dose from a source other than the MEMS bottle, and (3) removed multiple doses from the bottle at a time (ie, pocketed doses) over the past month. We used these data to adjust electronic adherence scores to more accurately reflect actual pill-taking behavior-a strategy that has been previously validated.65 We adjusted the data for 13% of participants who reported using such strategies. We examined both continuous adherence (percentage of prescribed doses taken in past month) and the more conservative measure of dichotomous adherence. Because nearly perfect adherence is necessary for virological suppression, dichotomous adherence was defined as ≥95% of prescribed doses taken.66
We assessed date of birth, education (ie, highest degree earned), income, employment, sexual orientation, and housing status. Sociodemographic variables were dichotomized: education into high school diploma or less versus greater than high school; annual income into ≤$5000 per year versus >$5000 per year; employment into employed full/part time versus unemployed, on disability, retired, or in school; sexual orientation into heterosexual versus gay/same-gender loving, bisexual, not sure or in transition, something else, or don't know; and housing status into stable (rent or own home or apartment) versus unstable (homeless, residential treatment facility, temporary/transitional housing, living rent-free with friend/relative, subsidized housing).
Health and Health Care Variables
Participants were asked when they first tested HIV positive, from which we derived time since diagnosis. Participants were presented with a checklist of 13 tangible barriers to health care access in the past 6 months (Table 2). The number of barriers endorsed was summed.
Viral load (n = 114) was obtained from medical records for a subset of respondents to validate adherence measures against disease progression; we also asked participants whether their current viral load was “detectable” or “undetectable,” with a “don't know” option. (We were unable to obtain any medical records viral load data from 100 participants because their providers did not respond to multiple requests for the information.)
Depression was measured with the Medical Outcome Studies' brief depression screener.67 Screening positive for depression on this instrument indicates a high probability of current major depression.
Participants were asked the number of times they used 5 different substances in the past 30 days (ie, heroin, powder cocaine, crack cocaine, and amphetamine/methamphetamine). Responses were collapsed into “any” versus “no” substance use.
Descriptive statistics were computed on all study variables. Means and standard deviations were examined for continuous variables, and frequencies were examined for categorical variables. Using t tests for continuous outcomes and Fisher exact tests for categorical outcomes, we compared differences between participants who did, versus who did not, endorse at least 1 conspiracy belief (ie, strongly agree and slightly agree, versus strongly disagree, slightly disagree, and neutral/don't know).
Bivariate tests were conducted to examine whether the conspiracy belief subscales and potential covariates (sociodemographic characteristics, health and health care variables, depression, and substance use) were related to adherence. When bivariate relationships between the conspiracy beliefs subscales and adherence were significant, multivariate regression was used to predict adherence with the subscales; linear regression was used for continuous adherence (percentage of doses taken); and logistic regression was used for dichotomous adherence (≥95% of doses taken). Multivariate models were adjusted for any sociodemographic, health, health care, mental health, and substance use variables that were related to nonadherence at an alpha level of 0.10 in bivariate tests. Including these covariates in the model allowed us to determine whether conspiracies functioned as an additional unique barrier to medication adherence. To make results comparable across outcomes, we chose a common set of covariates for the continuous and dichotomous adherence outcomes.
Education and depression were each missing for 1 participant; age and time since diagnosis were each missing for 2 participants; sexual orientation and health care barriers were each missing for 3 participants; and income was missing for 4 participants. Because the amount of missing data was low, mean substitution methods were used to impute these data.
The average age of the sample was 44, and a substantial percentage had low socioeconomic status, with 85% not working, nearly 40% with very low incomes, and over a fifth with no more than a high school degree (Table 2). Over half (56%) were in unstable temporary housing situations (eg, homeless). Most (78%) identified as gay, bisexual, or another nonheterosexual category. On average, participants were diagnosed with HIV 13 years before the study. About 30% endorsed at least 1 health care barrier, with the most frequent being lack of or inadequate insurance. Nearly half (45%) screened positive for depression, and 27% engaged in drug use in the past month.
On average, participants took only 68% of the prescribed doses of their HIV antiretroviral medications during the month between the baseline and follow-up assessments (Table 2). Only 22% of participants demonstrated an optimal level of adherence (ie, ≥95% of doses). Greater adherence was significantly associated with undetectable viral load as measured by medical records (t = 2.33, P < 0.05, n = 104) and self-report (t = 2.75, P < 0.01, n = 174). (Electronic adherence data were missing for 10 participants for whom we had medical records.)
Endorsement of HIV Conspiracy Beliefs
Almost two-thirds (64%) agreed with at least 1 HIV conspiracy belief; about half (48%) agreed with 2 or more. Forty-four percent believed that HIV is manmade, 35% thought that AIDS was created in a government laboratory, and a third endorsed the genocidal belief related to a cure being withheld (Table 1). Conspiracy beliefs about medications were also substantially endorsed, with 22% believing that people who take the new HIV medications are human guinea pigs for the government and 17% believing that the medications are poison. Participants who screened positive for depression and who had higher incomes were more likely to endorse at least 1 conspiracy belief (Table 2).
Relationship of HIV Conspiracy Beliefs With Adherence
In bivariate analyses, stronger genocidal and treatment-related conspiracy beliefs were associated with a lower percentage of doses taken over the past month (genocidal beliefs: b = −0.06, SE = 0.02, P < 0.01; treatment-related beliefs: b = −0.07, SE = 0.02, P < 0.01). Stronger treatment-related beliefs were related to a lower likelihood of optimal adherence in the past month (≥95% of doses taken) (odds ratio = 0.66, 95% confidence interval = 0.45 to 0.96, P < 0.05), whereas genocidal beliefs were not (odds ratio = 0.90, 95% confidence interval = 0.66 to 1.23, P > 0.10).
Of the potential covariates, in bivariate tests, both age and health care barriers were significantly related to continuous adherence, and only age was related to dichotomous adherence; thus, both were retained for the multivariate models, which tested the effects of both genocidal and treatment-related conspiracy beliefs simultaneously. The multivariate logistic regression of dichotomous adherence scores indicated that participants who more strongly endorsed conspiracy beliefs at baseline had a lower likelihood of optimal treatment adherence over the following month; odds ratio = 0.60, 95% confidence interval = 0.37 to 0.96, P < 0.05 (Table 3). In the multivariate linear regression of continuous adherence scores, the effect for treatment-related conspiracies was marginally significant, b (SE) = −0.04 (0.03), P < 0.10, and the effect for genocidal conspiracies was nonsignificant, b (SE) = −0.02 (0.02), P > 0.10).
In our sample of 214 African American men with HIV on antiretroviral treatment, many of whom were men who have sex with men (MSM), we found high levels of mistrust about HIV treatment and the governments' role in the HIV epidemic. Adherence rates were generally low, with less than a quarter of participants adhering to their regimens at high enough levels to be effective against virological failure and the development of drug-resistant strains of the virus. The mean adherence level observed in the present study (68%) is similar to average adherence levels reported in other studies using objective adherence measures.68,69
In an extension of prior research, we examined 2 distinct types of conspiracy beliefs: genocidal and treatment-related. Both types of beliefs were associated with nonadherence in bivariate models. In multivariate models, only belief in treatment-related HIV conspiracies was associated with nonadherence. The association between treatment-related conspiracy beliefs and nonadherence was significant controlling for age and structural and tangible health care barriers such as lack of insurance or transportation to the clinic.
Other research has similarly shown that beliefs about treatment, including efficacy, are related to acceptance of and adherence to antiretroviral therapy,13,70-72 and that African American men hold misconceptions about HIV treatment73,74 (eg, treatment optimism beliefs that HIV treatment reduces transmission risk). The present research demonstrates that suspicion of treatments may contribute to nonadherence and that clinicians need to address mistrust in addition to providing basic education about treatment efficacy.
In contrast to other samples, we did not find that sociodemographic factors contributed to nonadherence, possibly due to the relatively high homogeneity of the sample (ie, all were African American and men, and most were very low income). Moreover, depression and substance use, key predictors of adherence in other research, were not significantly related to adherence in this sample. Further research on similar samples is needed before conclusions can be drawn regarding these null results.
Our research differs from prior work in critical ways. Prior research using the scale items in a general African American population sample indicated that conspiracy beliefs are unidimensional,48 whereas the current research (on African Americans with HIV) showed 2 unique dimensions (related to genocide and treatment), possibly because of the relevance of treatment to participants' daily lives. Further, levels of conspiracy beliefs seemed to be higher than those found in a random US sample of African Americans. For example, genocidal beliefs about the role of the government and the CIA in creating and spreading HIV were endorsed by a higher percentage of participants in our sample than in the US sample. These findings are not unexpected, given that men and those with greater risk for HIV were more likely to endorse genocidal conspiracies in the national sample, and the present study sample is composed of high-risk men. Nevertheless, the current study was a convenience sample and therefore, these percentages are not representative of African American men with HIV as a whole. Moreover, all men in our study were on antiretroviral treatment, which limits generalizability to individuals who have been tested for HIV, who have become engaged in care, who have a usual health care provider, and who have accepted treatment. People with HIV who have more extreme levels of conspiracy beliefs may have been less likely to be included in our study because they may be too mistrustful of the health care system to have advanced through these multiple stages of the HIV care continuum.
Intervention research is needed on effective methods to address culturally specific factors among African American men, including myths and misconceptions about HIV, and likely roots of mistrust, including African American men's experiences with discrimination from HIV status, race, and homophobia (among MSM).75 African American MSM with HIV are marginalized in mainstream, African American, and gay communities due to the intersection of 3 stigmatized characteristics.76 Marginalization due to such stigmas can lead to suspicion and mistrust of established mainstream entities related to the public health and a vulnerability to HIV denialism (of which HIV conspiracies are one form).
Adherence interventions designed to address culturally specific roots of nonadherence may help to overcome medical mistrust. One recent example is an intervention developed with strong community input that included one-on-one discussions with peer treatment advocates who were enmeshed in the community and who understood cultural barriers to adherence, such as community stigma and myths about HIV.77 At least 2 HIV prevention interventions for African American MSM have included such culturally tailored components, which could also be adapted for adherence interventions. A community-level intervention for African American MSM involved popular opinion leaders (POLs) in 3 cities spreading prevention messages; in 1 session, popular opinion leaders were taught facts and discussed myths about HIV.78 The Many Men, Many Voices Project included a component addressing the effects of racism and homophobia on sexual risk.79 However, in neither of these articles did the authors report intervention effects on mistrust, conspiracies, and/or stigma. Further research is needed to understand the ways in which such intervention components can reduce such key mediators of sexual risk and nonadherence.
Given the high levels of conspiracies found in our research and other studies, social network research is warranted to understand how myths about HIV are spread throughout African American communities. Such research could help to identify key people in networks to whom African Americans turn for HIV-related information (both accurate and inaccurate). A POL approach (that targets individuals who are central to the flow of HIV-related information in the network) may be helpful in dispelling such beliefs (and changing norms about HIV-related information) at a community level. Social network analysis could be used to identify POLs who are their community's primary source for HIV-related information and through whom a high volume of HIV-related information travels. Interventions could focus on engaging trusted community members (eg, community leaders such as ministers) to disseminate accurate messages about HIV (and directly dispel myths) to existing groups of people with HIV in community settings (eg, support groups or educational groups sponsored by trusted community organizations).
Medical providers can also play a fundamental role in dispelling conspiracies, especially when discussing treatment options. Patients' trust in their providers and health care satisfaction are key correlates of HIV treatment adherence.13,71,80 Qualitative research suggests that African American MSM who are not satisfied with their provider relationship may turn to sources of misinformation about HIV that feed on their treatment-related skepticism.81 Providers who are open to dialogue about patients' treatment-related concerns have an opportunity to address and overcome mistrust-related barriers to adherence, improve patient relationships, and counteract inaccurate information patients hear in the community.
Given the prevalence of beliefs found in this and other studies, HIV conspiracies cannot be dismissed as rare or extreme. Such beliefs can ultimately contribute to decreased survival time (and further disparities) by discouraging appropriate treatment behavior. Adherence-promoting interventions that openly address and acknowledge HIV misconceptions, and identify and then target sources of misconceptions in communities, may contribute to overcoming such mistrust.
We would like to thank Kellii Trombacco, E. Michael Speltie, Charisma Acey, PhD, for their contributions to data collection; David Klein, MS, for data management and analysis; and Charles Hilliard, PhD, and the staff and clients of SPECTRUM for their support of this research.
1. Centers for Disease Control and Prevention. HIV/AIDS Surveillance Report, 2006
. Atlanta, GA: US Department of Health and Human Services; 2006.
2. Centers for Disease Control and Prevention. HIV and AIDS in the United States: a Picture of Today's Epidemic
. Atlanta, GA: Department of Health and Human Services; 2008.
3. HIV Epidemiology Program. HIV/AIDS Semi-Annual Surveillance Summary
. Los Angeles, CA: Los Angeles County Department of Public Health; 2009.
5. Johnson MO, Catz SL, Remien RH, et al. Theory-guided empirically supported avenues for intervention on HIV medication nonadherence: findings from the Healthy Living Project. AIDS Patient Care STDS
6. Stall R, Pollack L, Mills TC, et al. Use of antiretroviral therapies among HIV-infected men who have sex with men: a household-based sample of 4 major American cities. Am J Public Health
7. Halkitis P, Palamar J, Mukherjee P. Analysis of HIV medication adherence in relation to person and treatment characteristics using hierarchical linear modeling. AIDS Patient Care STDS
8. Johnson MO, Chesney MA, Neilands TB, et al. Disparities in reported reasons for not initiating or stopping antiretroviral treatment among a diverse sample of persons living with HIV. J Gen Intern Med
9. Gebo KA, Fleishman JA, Conviser R, et al. Racial and gender disparities in receipt of highly active antiretroviral therapy persist in a multistate sample of HIV patients in 2001. J Acquir Immune Defic Syndr
10. Lazo M, Gange SJ, Wilson TE, et al. Patterns and predictors of changes in adherence to highly active antiretroviral therapy: longitudinal study of men and women. Clin Infect Dis
11. Bogart LM, Bird ST, Walt LC, et al. Association of stereotypes about physicians to health care satisfaction, help-seeking behavior, and adherence to treatment. Soc Sci Med
12. Kleeberger CA, Buechner J, Palella F, et al. Changes in adherence to highly active antiretroviral therapy medications in the Multicenter AIDS Cohort Study. AIDS
13. Mostashari F, Riley E, Selwyn PA, et al. Acceptance and adherence with antiretroviral therapy among HIV-infected women in a correctional facility. J Acquir Immune Defic Syndr Hum Retrovirol
14. Shapiro MF, Morton SC, McCaffrey DF, et al. Variations in the care of the HIV-infected adults in the United States: results from the HIV Cost and Services Utilization Study. J Am Med Assoc
15. Singh N, Berman SM, Swindells S, et al. Adherence of human immunodeficiency virus-infected patients to antiretroviral therapy. Clin Infect Dis
16. Bright PE, Arnett DK, Blair C, et al. Gender and ethnic differences in survival in a cohort of HIV positive clients. Ethn Health
17. Halkitis PN, Parsons JT, Wolitski RJ, et al. Characteristics of HIV antiretroviral treatments, access and adherence in an ethnically diverse sample of men who have sex with men. AIDS Care
18. Lucas GM, Chaisson RE, Moore RD. Highly active antiretroviral therapy in a large urban clinic: risk factors for virologic failure and adverse drug and reactions. Ann Intern Med
19. Palacio H, Shiboski CH, Yelin EH, et al. Access to and utilization of primary care services among HIV-infected women. J Acquir Immune Defic Syndr
20. Sorvillo F, Kerndt P, Odem S, et al. Use of protease inhibitors among persons with AIDS in Los Angeles County. AIDS Care
21. Mugavero MJ, Lin HY, Willig JH, et al. Missed visits and mortality among patients establishing initial outpatient HIV treatment. Clin Infect Dis
22. Hall HI, Byers RH, Ling Q, et al. Racial/ethnic and age disparities in HIV prevalence and disease progression among men who have sex with men in the United States. Am J Public Health
23. Lima VD, Harrigan R, Murray M, et al. Differential impact of adherence on long-term treatment response among naive HIV-infected individuals. AIDS
24. Schackman BR, Ribaudo HJ, Krambrink A, et al. Racial differences in virologic failure associated with adherence and quality of life on efavirenz-containing regimes for initial HIV therapy: results of ACTG A5095. J Acquir Immune Defic Syndr
25. Landrine H, Klonoff EA. Cultural diversity and health psychology. In: Baum A, Revenson TA, Singer JE, eds. Handbook of Health Psychology
. Mahwah, NJ: Erlbaum; 2001:851-891.
26. Brandon DT, Isaac LA, LaVeist TA. The legacy of Tuskegee and trust in medical care: is Tuskegee responsible for race differences in mistrust of medical care? J Natl Med Assoc
27. Armstrong K, McMurphy S, Dean LT, et al. Differences in the patterns of health care system distrust between blacks and whites. J Gen Intern Med
28. Maly RC, Stein JA, Umezawa Y, et al. Racial/ethnic differences in breast cancer outcomes among older patients: effects of physician communication and patient empowerment. Health Psychol
29. Blendon RJ, Aiken LH, Freeman HE, et al. Access to medical care for black and white Americans. A matter of continuing concern. J Am Med Assoc
30. Burke JK, Cook JA, Cohen MH, et al. Dissatisfaction with medical care among women with HIV: dimensions and associated factors. AIDS Care
31. LaVeist TA, Nickerson KJ, Bowie JV. Attitudes about racism, medical mistrust, and satisfaction with care among African American and white cardiac patients. Med Care Res Rev
. 2000;57(Suppl 1):146-161.
32. Schrimshaw EW, Siegel K, Lekas HM. Changes in attitudes toward antiviral medical: a comparison of women living with HIV/AIDS in the pre-HAART and HAART. AIDS Behav
33. Siegel K, Karus D, Schrimshaw EW. Racial differences in attitudes toward protease inhibitors among older HIV-infected men. AIDS Care
34. Bird ST, Bogart LM. Perceived race-based and socioeconomic status (SES)-based discrimination in interactions with health care providers. Ethn Dis
35. Hausmann LR, Jeong K, Bost JE, et al. Perceived discrimination in health care and health status in a racially diverse sample. Med Care
36. Fowler-Brown A, Ashkin E, Corbie-Smith G, et al. Perception of racial barriers to health care in the rural South. J Health Care Poor Underserved
37. Chen FM, Fryer GEJ, Phillips RLJ, et al. Patients' beliefs about racism, preferences for physician race, and satisfaction with care. Ann Fam Med
38. Malebranche DJ, Peterson JL, Fullilove RE, et al. Race and sexual identity: perceptions about medical culture and healthcare among Black men who have sex with men. J Natl Med Assoc
39. Blendon RJ, Scheck AC, Donelan K, et al. How white and African Americans view their health and social problems. Different experiences, different expectations. J Am Med Assoc
40. Finnegan JR Jr, Meischke H, Zapka JG, et al. Patient delay in seeking care for heart attack symptoms: findings from focus groups conducted in five U.S. regions. Prev Med
41. Lillie-Blanton M, Brodie M, Rowland D, et al. Race, ethnicity, and the health care system: public perceptions and experiences. Med Care Res Rev
42. Krieger N. Discrimination and health. In: Berkman LF, Kawachi I, eds. Social Epidemiology
. Oxford, United Kingdom: Oxford University Press; 2000:36-75.
43. Gamble VN. Under the shadow of Tuskegee: African Americans and health care. Am J Public Health
44. Jones JH. Bad Blood: The Tuskegee Syphilis Experiment, New and Expanded Edition
. New York, NY: The Free Press; 1993.
45. Thomas SB, Quinn SC. The Tuskegee Syphilis Study, 1932 to 1972: implications for HIV education and AIDS risk education programs in the Black community. Am J Public Health
46. Bird ST, Bogart LM. Conspiracy beliefs about HIV/AIDS and birth control among African Americans: implications for the prevention of HIV, other STDs, and unintended pregnancy. J Soc Issues
47. Bogart LM, Bird ST. Exploring the relationship of conspiracy beliefs about HIV/AIDS to sexual behaviors and attitudes among African-American adults. J Natl Med Assoc
. 2003;95:1057-1065. PMC2594665.
48. Bogart LM, Thorburn ST. Are HIV/AIDS conspiracy beliefs a barrier to HIV prevention among African Americans? J Acquir Immune Defic Syndr
49. Crocker J, Luhtanen R, Broadmax S, et al. Belief in U.S. government conspiracies against African American and White college students: powerlessness or system blame? Pers Soc Psychol Bull
50. Herek GM, Capitanio JP. Conspiracies, contagion, and compassion: trust and public reactions to AIDS. AIDS Educ Prev
51. Hutchinson AB, Begley EB, Sullivan P, et al. Conspiracy beliefs and trust in information about HIV/AIDS among minority men who have sex with men. J Acquir Immune Defic Syndr
52. Bogart LM, Thorburn ST. Relationship of African Americans' sociodemographic characteristics to belief in conspiracies about HIV/AIDS and birth control. J Natl Med Assoc
53. Abalakina-Paap M, Stephan WG, Craig T, et al. Belief in conspiracies. Political Psychol
54. Goertzel T. Belief in conspiracy theories. Political Psychol
55. Whetten K, Leserman J, Whetten R, et al. Exploring lack of trust in care providers and the government as a barrier to health service use. Am J Public Health
56. Clark A, Mayben JK, Hartman C, et al. Conspiracy beliefs about HIV infection are common but not associated with delayed diagnosis or adherence to care. AIDS Patient Care STDS
57. Ross MW, Essien EJ, Torres I. Conspiracy beliefs about the origin of HIV/AIDS in four racial/ethnic groups. J Acquir Immune Defic Syndr
58. Bogart LM, Kalichman SC, Simbayi LC. Endorsement of genocidal HIV conspiracy as a barrier to HIV testing in South Africa. J Acquir Immune Defic Syndr
59. Catz SL, Kelly JA, Bogart LM, et al. Patterns, correlates, and barriers to medication adherence among persons prescribed new treatments for HIV disease. Health Psychol
60. Royal SW, Kidder DP, Patrabansh S, et al. Factors associated with adherence to highly active antiretroviral therapy in homeless or unstably housed adults living with HIV. AIDS Care
61. Safren SA, Otto MW, Worth JL, et al. Two strategies to increase adherence to HIV antiretroviral medication: life-steps and medication monitoring. Behav Res Ther
62. Kaiser HF. The application of electronic computers to factor analysis. Educ Psychol Meas
63. Comrey AL, Lee HB. A First Course in Factor Analysis
. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum; 1992.
64. Arnsten JH, Demas PA, Grant RW, et al. Impact of active drug use on antiretroviral therapy adherence and viral suppression in HIV-infected drug users. J Gen Intern Med
65. Bangsberg DR, Hecht FM, Charlebois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS
66. Pearson CR, Simoni JM, Hoff P, et al. Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues. AIDS Behav
67. Wells KB, Sturm R, Sherbourne CD, et al. Caring for Depression
. Cambridge, MA: Harvard University Press; 1996.
68. Bangsberg DR, Deeks SG. Is average adherence to HIV antiretroviral therapy enough? J Gen Intern Med
69. Bangsberg DR, Moss AR, Deeks SG. Paradoxes of adherence and drug resistance to HIV antiretroviral therapy. J Antimicrob Chemother
70. Schönnesson LN, Williams ML, Ross MW, et al. Three types of adherence to HIV antiretroviral therapy and their association with AIDS diagnosis, medication side-effects, beliefs about antiretroviral therapy, and beliefs about HIV disease. Int J STD AIDS
71. Gauchet A, Tarquinio C, Fischer G. Psychosocial predictors of medication adherence among persons living with HIV. Int J Behav Med
72. Gonzalez JS, Penedo FJ, Llabre MM, et al. Physical symptoms, beliefs about medications, negative mood, and long-term HIV medication adherence. Ann Behav Med
73. Kalichman SC, Eaton L, White D, et al. Beliefs about treatments for HIV/AIDS and sexual risk behaviors among men who have sex with men, 1997-2006. J Behav Med
74. Sullivan PS, Drake AJ, Sanchez TH. Prevalence of treatment optimism-related risk behavior and associated factors among men who have sex with men in 11 states, 2000-2001. AIDS Behav
75. Bing EG, Bingham T, Millett GA. Research needed to more effectively combat HIV among African-American men who have sex with men. J Natl Med Assoc
76. Jerome RC, Halkitis PN. Stigmatization, stress, and the search for belonging in black men who have sex with men who use methamphetamine. J Black Psychol
77. Raja S, McKirnan D, Glick N. The Treatment Advocacy Program-Sinai: a peer-based HIV prevention intervention for working with African American HIV-infected persons. AIDS Behav
78. Jones KT, Gray P, Whiteside YO, et al. Evaluation of an HIV prevention intervention adapted for Black men who have sex with men. Am J Public Health
79. Wilton L, Herbst JH, Coury-Doniger P, et al. Efficacy of an HIV/STI prevention intervention for black men who have sex with men: Findings from the Many Men, Many Voices (3MV) project. AIDS Behav
80. Schneider J, Kaplan SH, Greenfield S, et al. Better physician-patient relationships are associated with higher reported adherence to antiretroviral therapy in patients with HIV infection. J Gen Intern Med
81. Wheeler DP. Working with positive men: HIV prevention with black men who have sex with men. AIDS Educ Prev