AIDS

Journal of Psychosomatic Research 54 (2003) 271 – 278

Personality, quality of life and HAART adherence among men and women living with HIV/AIDS Frank J. Penedoa,*, Jeffrey S. Gonzaleza, Jason R. Dahna, Mike Antonia,b, Robert Malowb, Paul Costac, Neil Schneidermana,b b

a Department of Psychology, University of Miami, P.O. 248185, Coral Gables, FL 33134, USA Department of Psychiatry and Behavioral Sciences, University of Miami, Coral Gables, FL, USA c National Institute on Aging, Baltimore, MD, USA

Received 21 July 2001; accepted 7 June 2002

Abstract Very few studies have documented relations between personality traits and quality of life among individuals living with human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS). Some have shown that poor perceived quality of life as determined by a sense of purpose may be associated with inadequate adherence to highly active antiretroviral treatment (HAART) in this population. Although adequate HAART adherence is critical to achieve the full therapeutic effects of newly and highly effective regimens, very little is known of how both personality factors and HIV-specific quality of life may impact adherence to these medication regimens. This study evaluated relations among personality traits, quality of life and HAART adherence among 116 men and women living with HIV/

AIDS. Results showed that personality traits such as neuroticism were significantly associated with poorer quality of life, whereas conscientiousness and extraversion were associated with better quality of life. In contrast, personality traits were not directly related to HAART adherence. Both higher overall functioning and lower medication worries scores were significantly associated with HAART adherence. Findings suggest that personality traits are associated with HIV-specific quality of life on the one hand, and that HIV-specific quality of life is related to HAART adherence on the other. Future studies assessing the efficacy of psychosocial interventions in improving quality of life and HAART adherence should consider the role of personality traits in promoting better quality of life. D 2003 Elsevier Science Inc. All rights reserved.

Keywords: HIV; AIDS; Personality; Quality of life; HAART adherence

Introduction HIV/AIDS and HAART adherence The acquired immune deficiency syndrome (AIDS) caused by the human immunodeficiency virus (HIV) continues to be among the leading causes of death among Americans between the ages of 25 and 44 [5]. Once infected with the virus, HIV+ individuals must endure a debilitating and unpredictable clinical course that can impact all facets of their life. HIV disease is characterized by a progressive depletion of CD4 T-lymphocytes, a subset of white blood cells responsible for coordinating and regulating immune

* Corresponding author. E-mail address: [email protected] (F.J. Penedo).

responses [16,17]. This condition eventually leads to impairment of immunologic function leaving the infected individual susceptible to opportunistic infections such as pneumocystis carinii pneumonia and other diseases normally prevented by the immune system [12]. The chronic and debilitating course associated with living with HIV/AIDS (e.g., fear, social stigma, uncertain disease course, complex regimens and medical costs) has been associated with increased depression and anxiety, and poor quality of life [25,30,32]. These challenges may overwhelm an individual’s capacity to effectively cope with the stressful demands associated with HIV/AIDS and compromise not only psychological well being, but also physical health [7,6,24,26]. Since the development of highly active antiretroviral treatment (HAART) for HIV/AIDS, more individuals are coping with the chronic, complex and unpredictable course of this disease [29,31,33]. These medication regimens,

0022-3999/03/$ – see front matter D 2003 Elsevier Science Inc. All rights reserved. PII: S 0 0 2 2 - 3 9 9 9 ( 0 2 ) 0 0 4 8 2 - 8

272

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278

although highly effective, must be strictly followed (i.e., > 95% adherence) in order to (a) obtain the therapeutic gains from the medications and (b) prevent viral mutations and drug resistance to HAART regimens [26]. Several studies have documented that adequate adherence to HAART is associated with clinically significant reductions in viral load, improved immune function and decreased mortality [2,4,8,11]. The extent to which personality factors and quality of life may be related to adequate adherence to complex HAART regimens remains to be determined. Axis I– II psychopathology and quality of life in HIV/AIDS The role of personality in secondary prevention efforts in HIV/AIDS has received limited attention in the extant literature. The few studies that have examined personality and quality of life among HIV/AIDS populations consistently show a higher prevalence of Axes I and II disorders among individuals living with HIV/AIDS (e.g., Refs. [23,34,38]). In general, these studies suggest that individuals reporting personality traits associated with character pathology (e.g., neuroticism and impulsiveness) tend to express attitudes and behaviors that are commonly associated with risk behaviors and poor health habits [1]. Furthermore, individuals endorsing these traits are likely to experience more depression and psychological distress (e.g., anxiety and anger), greater social conflict and poorer overall functioning [23]. In fact, Johnson et al. [23] suggested that as many as one-third of individuals living with HIV/AIDS may meet criteria for a personality disorder and may have a concurrent Axis I disorder, with a mood disorder being the most commonly diagnosed Axis I condition in this population. This rate of individuals living with HIV/AIDS meeting criteria for a personality disorder is in stark contrast to the estimated rate of 6% in the general adult population; however, these rates should be interpreted with caution given limitations in using pre-morbid personality traits to predict subsequent health adjustment [37]. Nonetheless, these studies suggest that personality traits such as neuroticisms are related to higher psychological distress in individuals living with HIV/AIDS. Personality traits, quality of life and HIV/AIDS The relationship between personality factors and quality of life in disease populations is far less clear. In other chronic illnesses such as cancer, certain personality traits such as neuroticism have been significantly associated with poorer health-related quality of life, while traits such as extraversion have been associated with better quality of life [40]. Few studies, however, have assessed the relationship between personality and quality of life in HIV/AIDS. In a recent study, the role of personality in quality of life among individuals living with HIV/AIDS was assessed among men who have sex with men (MSM) and injection drug users (IDUs). Findings showed that neuroticism, a personality

factor characterized by a high degree of depression, anxiety, anger and low self-confidence, was associated with poor health-related quality of life [3]. Although this is among the first studies to relate personality style to quality of life among individuals living with HIV/AIDS, the extent to which better quality of life was related to health behaviors such as HAART adherence was not assessed. Quality of life and HAART adherence Very few published research studies have related quality of life to HAART adherence. For example, among asthma patients, greater reported quality of life in social, psychological and physical domains was significantly associated with greater medication adherence over a 1-year period [18]. On the other hand, fewer studies have examined the relationship between quality of life and HAART adherence. Among individuals living with HIV/AIDS, reporting a meaningful life, feeling cared for and perceiving the ability to use time wisely were each related to greater adherence to HAART [22]. This finding suggests that perceptions of better functioning in several quality of life domains might lead to improved HAART adherence but because this was not a prospective study, it is possible that better adherence may have been related to better health and thus more sense of meaning in life. Furthermore, limited research is available relating issues specifically relevant to HIV/AIDS (e.g., physical limitations, HIV/AIDS medication worries, etc.). The present study This study sought to assess the relationship between personality, general and HIV-specific quality of life (e.g., HIV mastery and medication worries) and HAART adherence using a comprehensive personality instrument that measures intrapsychic, interpersonal, experiential and motivational components of personality. We hypothesized that higher neuroticism and lower extraversion would be associated with lower overall and HIV-specific quality of life, as well as more medication and medical worries. Furthermore, we expected that higher extraversion and agreeableness would be associated with higher HIV mastery; moreover, better overall functioning and HIV-specific quality of life was hypothesized to be related to better HAART adherence.

Method Inclusion criteria All participants were required to be symptomatic HIV+ men and women with or without AIDS who had been on HAART for at least 30 days prior to assessment. Furthermore, participants were required to be free of cognitive impairment as indicated by as score greater than 25 (i.e., 1 S.D. below the established mean for HIV+ individuals) on

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278

the Folstein Mini Mental Status Exam [15], fluent in English and have completed at least a ninth grade education. Exclusion criteria Individuals who displayed signs of cognitive impairment such as AIDS dementia complex as shown by deficits in motor speed, concentration and memory on the HIV Dementia Scale (HDS [36]) were excluded from participation. Furthermore, individuals who reported a history of intravenous drug use or substance abuse/dependency within the past 6 months were excluded. Participants were also excluded if they had a current major psychiatric disorder (e.g., bipolar affective disorder) or a diagnosis of antisocial or borderline personality disorder.

273

as well as time since HIV diagnosis were assessed during a physical examination. CD4+ T-lymphocyte cell counts were assessed using peripheral venous blood samples drawn by a phlebotomist following standard procedures that included using sterile evacuated tubes containing sodium heparin (Vacutainer-sodium heparin, Becton-Dickinson, Rutherford, NJ). Cell counts were established using standard methods described by Fletcher, Baron, Ashman, Fischl and Klimas [14]. HIV viral load (i.e., the number of copies of HIV RNA) was assessed by measuring the number of HIV virions per ml of peripheral blood plasma using an AMPLICOR assay using reverse transcriptase polymerase chain reaction (RT-PCR; Roche Laboratories, US #83088). These levels indicate the magnitude of HIV replication and its associated rate of CD4+ T-lymphocyte destruction. Assessment of personality and quality of life

Procedures Participants were recruited through various methods including distribution of flyers advertising the study in local newspapers and HIV-related community events, presentation of study aims at local community organizations and informing local physicians known to treat HIV+ individuals. Initial eligibility screening was conducted by phone interview to assess exclusion criteria such as gross psychopathology based on self-report and presence of advanced HIV/ AIDS disease state that would impede participation. Individuals meeting initial eligibility criteria were given an appointment for a psychiatric interview to detect more subtle signs of psychopathology. During this interview, the Hamilton Rating Scale for Depression (HRS-D [19]) and the Structured Clinical Interview for DSM-III-R-non-patientHIV version (SCID-NP-HIV [39]) were administered. The SCID-NP-HIV was used to identify psychotic and mood disorders, substance use, anxiety and adjustment disorders related to HIV. Furthermore, the SCID-II [13] was administered to identify personality disorders, particularly antisocial and borderline personality disorder. Participants who met inclusion criteria signed an informed consent and were scheduled for a blood draw, a physical examination and a psychosocial battery lasting about 60 min. Participants received monetary compensation (US$50) for their psychosocial and medical assessments.

Personality The NEO-PI-R [10], a 240-item self-reported personality measure, was used to assess five major personality factors — neuroticism, extraversion, openness, agreeableness and conscientiousness. There are six facet scales for each factor designed to capture more specific personality traits. Each item is answered on a five-point Likert scale ranging from strongly disagree to strongly agree. The NEO-PI-R has shown adequate internal consistency (ranging from .59 to .92), test – retest reliability (ranging from .68 to .73), and has been cross-validated in studies with other personality selfreports [9,28,35]. Quality of life The HIV/AIDS-Targeted Quality of Life (HAT-QoL) Instrument was used to assess quality of life issues relevant to HIV/AIDS populations [20,21]. The HAT-QoL is a 42item Likert scale that assesses nine dimensions of quality of life including overall function, life satisfaction, medical worries, financial worries, medication worries, hiv mastery, disclosure worries, provider trust and sexual functioning. Participants were asked to rate on a Likert scale ranging from all of the time to none of the time the degree to which they experienced satisfaction or difficulty in each dimension over the past 4 weeks. Assessment of HAART adherence

Sociodemographic and HIV/AIDS-related measures Sociodemographics measures Gender, age, ethnic group membership, years of formal education, yearly income and current employment status (i.e., full-time, part-time and not employed) were assessed using a standard self-report demographics questionnaire. HIV/AIDS disease status HIV and AIDS clinical conditions (e.g., night sweats, fatigue, lymphadenopathy, diarrhea and Kaposi’s Sarcoma),

The Adherence to Combination Therapy Guide (ACTG [6]), a self-report adherence interview questionnaire, was used to assess HAART adherence. Participants were asked to list their prescribed HAART medications and (a) recorded how many doses were prescribed for each day and (b) how many pills were prescribed for each dose. Participants were then asked to recall each of the 4 previous days (one at a time) and remember if he/she had missed any doses/pills of each specific medication in their regimen. For the present study, an overall indicator of adherence was computed by

274

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278

summing the number of pills taken during the previous four days and dividing this number by the sum of pills prescribed for that same period. This resulting adherence ratio represents the percentage of HAART pills taken as prescribed.

Results Participant characteristics A total of 145 participants responded to our recruitment efforts. Twenty-nine participants were excluded for various reasons with the most common exclusionary criteria met being current drug abuse, followed by cognitive impairment and major psychiatric disorder. Eligible participants were 116 individuals (55% men and 45% women) living with HIV/AIDS who were undergoing HAART. The majority of participants were Black (37%) followed by Hispanics (33%) and non-Hispanic Whites (23%). The mean age of the sample was 39.2 years (S.D. = 8.7). The majority of participants reported an annual income less than US$20,000 (69%) and most participants were unemployed or disabled (53%). Participants reported taking an average of 42.3 (S.D. = 25.3) HIV-related pills (i.e., nucleoside reverse transcriptase [NRT] and non-nucleoside reverse transcriptase [NNRT] inhibitors, and protease inhibitors [PI]) in the last 4 days. The most common HAART regimen among participants (45%) involved taking a NNRT inhibitor in combination with a NRT inhibitor. About 34% of all participants were on PI/NRT inhibitor combination, while about 13% were on a regimen that involved a combination of all three types of drugs. Only about 4% of participants reported taking a PI in combination with a NNRT. Participants had received an HIV seropositive diagnosis an average 5.5 years prior to assessment (M = 67.3 months, S.D. = 48.2). The average CD4 T-lymphocyte cell count was 408.5 cell/mm3 (S.D. = 259.6) and the mean HIV viral load (log 10) was 2.6 copies/ml of peripheral blood (S.D. = 1.4). Participant characteristics and HIV-related measures are detailed in Table 1. Associations among sociodemographic and HIV/AIDSrelated measures, and HAART adherence Examination of sociodemographic measures and HAART adherence showed that only age was significantly associated with adherence (r = .21, P < .05) such that older age was significantly associated with greater HAART adherence. Quality of life and adherence to HAART did not vary as a function of prescribed regimen. Associations between personality, quality of life and HAART adherence Pearson zero-order correlations were conducted to assess the extent to which personality factors were related

to quality of life in our sample. As hypothesized, neuroticism scores were significantly associated with all quality of life subscales with the exception of provider trust. Higher scores on the neuroticism dimension were significantly associated with poorer overall function, life satisfaction, medical worries, financial worries, medication worries, HIV mastery, disclosure worries and sexual functioning. In contrast, higher scores on the extraversion and conscientiousness dimensions were significantly associated with better overall function, life satisfaction, HIV mastery and sexual functioning. Furthermore, greater extraversion was significantly associated with less medical, financial and disclosure worries, and sexual functioning,

Table 1 Sociodemographic and HIV-related variables Mean Age Months since HIV diagnosis Total HIV medications (total pills last 4 days) Total CD4+ T-cells/mm3 HAART adherencea Adherent ( > 95%) Nonadherent ( < 95%) Total HIV viral load (log 10) Gender Male Female Ethnicity Black Non-Hispanic White Hispanic American Indian Mixed Other Not reported Education Grades 7 to 12 High school Some college Graduated college Some graduate Graduate degree Annual income < US$5000 US$5001 – 10,000 US$10,001 – 20,000 US$20,001 – 30,000 US$30,001 – 40,000 US$40,001 – 50,000 Over US$50,000 Unknown Employment status Full-time Part-time Student Unemployed Disabled Unknown a

S.D.

39.2 67.3 42.3

8.7 48.2 25.3

408.53

259.6

72% (n = 84) 28% (n = 32) 2.6

1.4

55% 45% 37% 23% 33% 1% 2% 1% 3% 20% 19% 23% 19% 9% 10% 22% 27% 20% 7% 5% 3% 6% 10% 23% 11% 3% 21% 32% 10%

Adherence rate calculated as ratio of pills taken/pills prescribed over past 4 days.

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278

275

Table 2 Correlations among personality and quality of life variables Neuroticism Overall function Life satisfaction Medical worries Financial worries Medication worries HIV mastery Disclosure worries Provider trust Sexual functioning

Extraversion

Openness

.30** .30** .31** .20* .14 .33** .28** .03 .31**

.12 .01 .04 .01 .05 .13 .19* .04 .06

.39** .45** .45** .23** .35** .28** .27** .07 .27**

Agreeableness

Conscientiousness

.11 .05 .19* .07 .18* .37** .16 .08 .02

.20* .26** .24** .05 .13 .25** .08 .10 .22*

* P < .05. ** P < .01.

while higher agreeableness scores were associated with less medical and medication worries and greater HIV mastery (all P’s < .01; see Table 2). There were no significant relationships between the personality dimensions and HAART adherence. Quality of life as a correlate of HAART adherence To determine whether quality of life was related to HAART adherence, Pearson zero-order correlations were conducted. Higher scores on overall functioning were significantly associated with higher percentage of HAART medications taken (r =.29, P < .01). Similarly, lower medication worries was related to a lower percentage of HAART medication taken (r = .26, P < .01). There were no significant relationships among other quality of life indices and HAART adherence (see Table 3). A hierarchical logistic regression including age was then conducted to determine whether quality of life was a significant correlate of HAART adherence above and beyond demographic factors. We first divided our sample into  95% (i.e., adherent) versus < 95% adherence (i.e., nonadherent) following previous work showing that adherence rates  95% are necessary for optimal virologic response to HAART [33]. To test the validity of this approach, independent samples t-tests were conducted to

determine if physiological determinants of adherence differed across both groups. As expected, results showed that participants in the adherent group had significantly lower HIV viral load (log 10 HIV viral load 3.13 in nonadherent vs. 2.14 in adherent [t (92) = 2.47, P < .05]). We then tested whether both groups differed in any of our sociodemographic or HIV/AIDS-related measures and found that participants in the nonadherent group were significantly younger [35.6 (S.D. = 8.7) vs. 40.7 (8.8); t(89) = 2.59, P < .05]. There were no other significant differences between both groups. A hierarchical logistic regression controlling for age was conducted with age in the first block and both overall functioning and medication worries in the second block. After controlling for age, both age and overall functioning remained significant correlates of HAART adherence accounting for 18% of the variance in adherent versus nonadherent group membership [c2 = 12.87(2,1), P < .01]. Each standard deviation unit increase in age was associated with a 1.08 increase in the odds of a participant being in the adherent group. Similarly, each standard deviation unit increase in overall functioning was associated with a 1.11 increase in the odds of a participant being in the adherent group (see Table 4).

Discussion

Table 3 Correlations between quality of life subscales and HAART adherence

In this study, we sought to evaluate the relationship between personality, HIV-specific quality of life and HAART

HAART adherence Overall function Life satisfaction Medical worries Financial worries Medication worries HIV mastery Disclosure worries Provider trust Sexual functioning * P < .01.

.29* .06 .14 .15 .26* .05 .05 .11 .03

Table 4 Hierarchical logistic regression analysis of variables significantly associated with HAART adherence Variable Block 1 Age Block 2 Overall function

Odds ratio

95% CI

P value

1.08

1.02 – 1.15

.007

1.11

1.02 – 1.19

.004

276

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278

adherence among men and women living with HIV/AIDS. As we hypothesized and consistent with prior work [3], higher neuroticism was consistently associated with poorer overall quality of life and all HIV-specific domains (e.g., medication worries and HIV mastery) with the exception of provider trust. This finding suggests that individuals reporting personality traits associated with tendencies to experience greater depression, anxiety and fearfulness report poorer overall and HIV-specific quality of life. We also expected that traits such as conscientiousness, agreeableness and extraversion would be associated with better HIV-specific quality of life. As hypothesized, individuals with personality scores higher in assertiveness, trust and competence reported better quality of life, particularly in overall functioning, medical worries and HIV mastery. Although prior work has shown that neuroticism is associated with poor quality of life in HIV, these findings are among the first to suggest that more adaptive dispositional traits among men and women living with HIV/AIDS may contribute to the extent to which these individuals are able to manage the multiple demands associated with living with this disease. Furthermore, these findings underscore the importance of assessing variables such as personality traits when evaluating quality of life in this population. Given the limited literature available relating HIV-specific quality of life and HAART adherence, a primary aim of this study was to examine to what extent HIV-specific quality of life was related to adherence. In contrast to prior work [22], the present study used a more specific and direct measure of HIV-specific quality of life with domains relevant to living with HIV/AIDS [21]. This allowed us to tap into more HIV-specific functioning areas relevant to managing this disease. We hypothesized that better self-reported quality of life would be associated with better HAART adherence. As expected, better overall functioning and less medication worries were significantly related to better adherence. In contrast, other HIV-specific quality of life domains such as medical worries, HIV mastery and more general areas such as life satisfaction and financial worries were not related. These findings are among the first to suggest that quality of life as determined by overall functioning (e.g., physical activity, job-related activity and social activity), as well as HIV medication worries (e.g., concerns over side effects and regimen burden) is related to the extent to which individuals adhere to HAART. That other HIVspecific quality of life domains were not related to HAART adherence suggests that more global indices of quality of life and medication concerns may be more prognostic of adherence to HAART. In the present study, we measured adherence as the ratio of HAART pills taken over pills prescribed. In a logistic regression with adherent versus nonadherent group (i.e., >95% vs. < 95%) membership as the dependent factor, both age and overall functioning remained significant correlates of group membership. More specifically, older age and better overall functioning were significantly associated with

a greater likelihood of group membership in the adherent group. These findings suggest that older age and better overall functioning may favorably impact an individual’s capacity to adhere to the complexity of HAART regimens currently available. It is worth noting that after controlling for age, medication worries was no longer a significant correlate of adherence group membership thus suggesting that older participants may be more experienced and knowledgeable in the complexities associated with a medication regimen. Taken together, these findings underscore the significance of perceived overall functioning in determining HAART adherence, independent of other factors such as age. Earlier work has shown that conscientiousness was related to better adherence as reported in the ACTG and prospectively related to disease progression (i.e., CD4 cell counts [31]). Unlike expected, personality traits were not directly related to medication adherence in our sample. Several factors may be associated with the lack of direct personality –adherence relationships in our study. Because participants in this study were entering a large-scale intervention study designed to improve quality of life, participants with gross levels of psychopathology (e.g., meeting DSM-IV criteria for borderline or antisocial personality disorder) and a diagnosis of alcohol and/or drug dependence or abuse were excluded from the study. It is possible that our sample reflects a relatively psychologically healthy subgroup of individuals living with HIV/AIDS and that a higher degree of personality pathology may be necessary to establish any direct relationships between personality and HAART adherence. Another possible factor that may be related with lack of direct relationships between personality and HAART adherence may be associated with our measure of medication adherence. Although the ACTG [6] is the most widely used self-reported adherence measure in HIV/ AIDS, this measure only captures HAART adherence over a 4-day period. Consequently, a limitation of this study is that data from a more objective measure of adherence such as an electronic cap opening measuring device was not currently available. Furthermore, our study lacked a detailed history of prior HAART regimentation (e.g., prior failed regimens) and medication side effects, two factors that may be related to current adherence. Although this study illustrates that HIV-specific quality of life is associated with HAART adherence, other limitations need to be addressed. Our sample consisted primarily of Black, Hispanic and non-Hispanic White participants motivated to participate in a research study. This precludes generalizing these findings to other HIV+ populations (e.g., substance abusers and individuals with severe psychiatric histories). These populations may be exposed to different stressors, which may relate to personality, quality of life and HAART adherence in different ways. Furthermore, the cross-sectional nature of the study precludes any causal inferences from our findings. It is plausible to argue that adequate adherence may impact quality of life

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278

therefore limiting the implied directionality of our hypothesized relationships. That is, more adherent participants may be healthier and therefore experience better overall quality of life; however, a recent study reported that less favorable changes in quality of life over time a 24-month period were associated with discontinuation of HAART [30]. Similarly, several studies have shown that life events, including chronic illness, have limited impact on personality traits including neuroticism and extraversion (e.g., Ref. [27]). Future studies should longitudinally examine how personality and quality of life may impact HAART adherence. Intervention studies aimed at improving quality of life and HAART adherence should assess how dispositional traits may impact improvements in quality of life and the extent to which these improvements are associated with adequate adherence to HAART. Future work should also evaluate relationships between personality, quality of life and adherence among individuals with more severe states of psychopathology.

[7]

[8]

[9]

[10] [11] [12]

[13]

[14]

Acknowledgments [15]

This study was supported in part by National Institute of Mental Health Grant PO1 MH49548 awarded to Dr. Neil Schneiderman in the University of Miami Department of Psychology, Behavioral Medicine Research Center, Coral Gables, FL. The authors are grateful to Drs. Ron Duran, Gail Ironson, Mary Anne Fletcher and Jeff Herbst for their collaboration in this study; to Kate Weaver, Carlos Bedoya, Brenda Stoelb, Michelle Peak, Peter Theodore, Tammy Enos and Arnetta Phillips who contributed in the recruitment and assessment of study participants; and to the many men and women who participated in the study.

[16]

[17] [18]

[19] [20]

References [1] Ball SA, Schottenfeld RS. A five-factor model of personality and addiction, psychiatric, and AIDS risk severity in pregnant and postpartum cocaine misusers. Subst Use Misuse 1997;32(1):25 – 41. [2] Berry D, Kahn JB, Cooper R. Antiretroviral activity and safety of indinavir (IDV) along and in combination with zidovudine (ZDV) in ZDV-naı¨ve patients with CD4 cell counts of 50 – 500 cells/mm3. Paper presented at the XI International Conference on AIDS, Vancouver, British Columbia, Canada, 1996. [3] Burgess AP, Carretero M, Elkington A, Pasqual-Marsettin E, Lobaccaro C, Catalan J. The role of personality, coping style and social support in health-related quality of life in HIV infection. Qual Life Res 2000;9:423 – 37. [4] Cameron W, Heath-Choizzi M, Kravcik S. Prolongation of life and prevention of AIDS in advanced HIV immunodeficiency with ritonavir. Paper presented at the Third Conference on Retroviruses and Opportunistic Infections, Washington, DC, 1996. [5] Centers for Disease Control, CDC. 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. Morb Mort Wkly Rep 1992;41:1 – 19. [6] Chesney MA, Ickovics JR, Chambers DB, Gifford AL, Neidig J,

[21]

[22]

[23]

[24] [25] [26] [27]

[28] [29]

277

Zwickl B, Wu AW. Self-reported adherence to antiretroviral medications among participants in HIV clinical trials: the AACTG Adherence Instruments. AIDS Care 2000;12(3):255 – 66. Chesney M, Folkman S. Psychological impact of HIV disease and implications for intervention. Psychiatr Clin North Am 1994;17(1): 163 – 82. Collier AC, Coombs RW, Schoenfeld DA, Basset RL, Timpone J, Baruch A, Jones M, Facey K, Whitacre C, McAuliffe VJ, Friedman HM, Flerigan TC, Reichman RC, Hooper C, Carey L. Treatment of human immunodeficiency virus infection with sasquinavir, zidovudine, and zalcitabine. N Engl J Med 1996;334:1011 – 7. Costa PT, McCrae RR, Dye DA. Facet scales for agreeableness and conscientiousness: a revision of the NEO personality inventory. Pers Individ Differ 1991;12:887 – 98. Costa PT, McCrae RR. Revised NEO personality inventory: professional manual. Odessa (FL): Psychological Assessment Resources, 1992. Deeks S, Smith M, Holodniy M, Kahn J. HIV-1 protease inhibitors: a review for clinicians. J Am Med Assoc 1997;2:145 – 53. Fahey JL, Taylor JM, Detels R, Hofman B, Melmed R, Nishanian P, Giorgi J. The prognostic value of cellular and serologic markers in infection with human immunodeficiency virus type-1. N Engl J Med 1990;322:166 – 72. First MB, Spitzer RL, Gibbon M, Williams, Janet BW. The structured clinical interview for DSM-III-R personality disorders (SCID-II): I. Description. J Pers Disord 1995;9:83 – 91. Fletcher MA, Baron G, Ashman M, Fischl M, Klimas N. Use of whole blood methods in assessment of immune parameters in immunodeficiency states. Diagn Clin Immunol 1987;5:69 – 81. Folstein MF, Folstein SE, McHugh PR. ‘‘Mini-mental state.’’ A practical method for grading the cognitive state of patients for the clinician. J Psychiatry Res 1975;12:189 – 98. Gallo RC. HIV-the cause of AIDS: an overview on its biology, mechanisms of disease induction, and out attempts to control it. J Acquir Immunodeficiency Syndr 1988;1:521 – 35. Gallo RC. Virus hunting AIDS, cancer, and the human retrovirus: a story of scientific discovery. New York: Basic Books, 1991. Gupchup GV, Hubbard JH, Teel MA, Singhal PK, Tonrey L, Riley K, Rupp MT, Coultas DB. Developing a community specific healthrelated quality of life (HRQOL) questionnaire for asthma: the Asthma-Specific Quality of Life Questionnaire for Native American Adults (AQLQ-NAA). J Asthma 2001;38(2):169 – 78. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56 – 62. Holmes WC. HAT-QoL: HIV/AIDS-Targeted Quality of Life Instrument, 1999. Holmes WC, Shea JA. Two approaches to measuring quality of life in the HIV/AIDS population: HAT-QoL and MOS-HIV. Qual Life Res 1999;8:515 – 27. Holzemer WL, Corless IB, Nokes KM, Turner JG, Brown MA, Powell-Cope GM, Inouye J, Henry SB, Nicholas PK, Portillo CJ. Predictors of self-reported adherence in persons living with HIV disease. AIDS Patient Care STDs 1999;13(3):185 – 97. Johnson JG, Williams JBW, Rabkin JG, Goetz RR, Remien RH. Axis I psychiatric symptoms associated with HIV infection and personality disorder. Am J Psychiatry 1995;152(4):551 – 4. Kemppainen J. Predictors of quality of life in AIDS patients. J Assoc Nurses AIDS Care 2001;12(1):61 – 70. Linsk NL. HIV among older adults: age-specific issues in prevention and treatment. AIDS Read 2000;10(7):430 – 40. Lewin D. Protease inhibitors: HIV-1 summons a Darwinian defense. J NIH Res 1996;8:33 – 5. Magnus K, Diener E, Fujita F, Payot W. Extraversion and neuroticism as predictors of objective life events: a longitudinal analysis. J Pers Soc Psychol 1993;65(5):1046 – 53. McCrae RR, Costa PT. Discriminant validity of the NEO PI-R facet scales. Educ Psychol Meas 1992;52:229 – 37. Miners AH, Sabin CA, Mocroft A, Youle M, Fisher M, Johnson M.

278

[30]

[31]

[32]

[33]

[34]

F.J. Penedo et al. / Journal of Psychosomatic Research 54 (2003) 271–278 Health-related quality of life in individuals infected with HIV in the era of HAART. HIV Clin Trials 2001;2(6):484 – 92. Nieuwkerk P, Gisolf E, Reijers M, Lange J, Danner S, Sprangers M, NATIVE Study Group, PROMETHEUS Study Group, ADAM Study Group. Long-term quality of life outcomes in three antiretroviral treatment strategies for HIV-1 infection. AIDS 2001;15:1985 – 91. O’Cleirigh C, Ironson G, Herbst J, Costa PT. Conscientiousness is related to disease progression (viral load and CD4 cell number) and adherence in patients living with HIV/AIDS. Manuscript in preparation, 2002. Palella F, Delaney K, Moorman A, Loveless MO, Fuhrer J, Satten GA, Aschman DJ, Holmberg SD. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. N Engl J Med 1998;338:853 – 60. Patterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, Wagener MM, Singh N. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med 2000; 133(1):21 – 30. Perkins DO, Davidson EJ, Leserman J, Liao D, Evans DL. Personality disorder in patients infected with HIV: a controlled study with implications for clinical care. Am J Psychiatry 1994;150(2):298 – 9.

[35] Piedmont RL, Weinstein HP. A psychometric evaluation of the new NEO PI-R facets scales for Agreeableness and Conscientiousness. J Pers Assess 1993;60:302 – 18. [36] Power C, Selnes O, Grim J, McArthur J. HIV Dementia Scale: a rapid screening test. J AIDS Hum Retroviruses 1995;8:273 – 8. [37] Samuels JF, Nestadt G, Romanoski AJ, Folstein MF, McHugh PR. DSM-III personality disorders in the community. Am J Psychiatry 1994;1055 – 62. [38] Sikkema KJ, Kochman A, DiFranceisco W, Bergholte J, Peterson M. Psychiatric co-morbidity in HIV secondary prevention. National HIV Prev. Conference, Medical College of Wisconsin, Milwaukee. Abstract no. 284, 1999. [39] Spitzer R, Williams J, Gibbon M, First M. Structured clinical interview for DSM-III-R: nonpatient version for HIV studies (SCID-NPHIV 6/1/88). New York (NY): Biometrics Research Department, New York Psychiatric Institute, 1988. [40] Yamakoa K, Shigehisa T, Ogoshi K, Haruyama K, Watanabe M, Hayashi F, Hayashi C. Health-related quality of life varies with personality types: a comparison among cancer patients, non-cancer patients and healthy individuals in a Japanese population. Qual Life Res 1998;7(6):535 – 44.