Aging and HIV are both risk factors for memory deficits and declines in real-world functioning. However, we know little about the profile of memory deficits driving instrumental activities of daily living (IADL) declines across the lifespan in HIV. This study examined 145 younger (<50 years) and 119 older (≥50 years) adults with HIV who completed the California Verbal Learning Test-Second Edition (CVLT-II), the Wechsler Memory Scale-Third Edition Logical Memory subtest (WMS-III LM), and a modified Lawton and Brody ADL questionnaire. No memory predictors of IADL dependence emerged in the younger cohort. In the older group, IADL dependence was uniquely associated with worse performance on all primary CVLT-II variables, as well as elevated recency effects. Poorer immediate and delayed recall of the WMS-III LM was also associated with IADL dependence, although recognition was intact. Findings suggest older HIV-infected adults with shallow encoding and forgetting are at risk for IADL dependence.

Introduction

The past decade has witnessed a progressive aging of the HIV/AIDS epidemic in developed countries, with an increase in both the prevalence and incidence of HIV among older adults (Centers for Disease Control and Prevention, 2008) due in part to reduced mortality associated with effective combination antiretroviral therapy (cART; Palella et al., 1998). It is estimated that in the near future approximately half of those persons living with HIV/AIDS in the USA will be 50 years of age and older (Smith, 2006; U.S. Senate Special Committee on Aging, 2013). Despite increased longevity in this population, older adults living with HIV are still at an increased risk for various detrimental health and cognitive outcomes relative to their younger counterparts (High et al., 2012), including poorer immunovirological and non-HIV-associated health outcomes (e.g., cardiovascular disease; Rodriguez-Penney et al., 2013). Of particular relevance to clinical neuropsychologists, HIV and aging appear to have additive (and possibly synergistic) adverse effects on central nervous system structure and function (e.g., Ernst & Chang, 2004; Green et al., 2005; Jernigan et al., 2005), including smaller caudate volumes (Ances, Ortega, Vaida, Heaps, & Paul, 2012), changes in the microstructure of cerebral white matter (e.g., Nir et al., 2014), and decreased resting state functional connectivity (Thomas et al., 2013). There is also evidence of an additive adverse effect of HIV and aging on neurocognitive functioning (e.g., Hardy & Vance, 2009; cf. Valcour, Paul, Neuhaus, & Shikuma, 2011), with some research showing that older adults are at threefold increased risk of HIV-associated neurocognitive disorders relative to their younger HIV-infected counterparts (Valcour et al., 2004). At the domain level, older HIV-infected adults appear to be particularly vulnerable to deficits in the areas of executive functions (e.g., Iudicello, Woods, Deutsch, Grant, & the HNRP Group, 2012) and episodic memory (e.g., Sacktor et al., 2007; Woods, Dawson, Weber, Grant, & the HNRC Group, 2010).

The increased neurocognitive burden of growing older with HIV infection may also translate into a disruption of normal everyday functioning. Research to date shows that older age and HIV infection confer additive detrimental effects on laboratory measures of functional capacity (Foley et al., 2013; Thames et al., 2011; Vance, Fazeli, & Gakumo, 2013; Vance, Wadley, Crowe, Raper, & Ball, 2011), including medication management, financial management, and automobile driving simulations. Outside the laboratory, older HIV-infected adults are also at elevated risk of poorer manifest real-world functioning, including dependence in instrumental activities of daily living (IADLs) (Morgan et al., 2012) and poorer health-related quality of life (Doyle et al., 2012; Morgan et al., 2012).

Neurocognitive impairment confers an increased risk of poor everyday functioning outcomes in younger, middle-aged, and older adults with HIV (e.g., Barclay et al., 2007; Iudicello, Woods, Deutsch, Grant, & the HNRP Group, 2012; Malaspina et al., 2011; Vance et al., 2011, 2013). Yet, older HIV-infected individuals with neurocognitive impairment appear to be at disproportionate risk for poorer everyday functioning (e.g., Barclay et al., 2007; Hinkin et al., 2004; Thames et al., 2011; cf. Doyle et al., 2012). A working hypothesis suggested by these laboratory findings is that the relative frailty of older HIV+ adults' successful daily functioning is more vulnerable to the disruptive influence of higher-order neurocognitive deficits, particularly in the absence of effective compensatory strategies (see Blackstone, Weber, Iudicello, & Woods, in press). Across this small but growing literature, deficits in episodic memory and executive functions are the most consistent and robust predictors of functional problems in older HIV-infected adults (e.g., Barclay et al., 2007; Hinkin et al., 2004; Iudicello, Woods, Deutsch, Grant, & the HNRP Group, 2012; Thames et al., 2011; cf. Foley et al., 2013). However, we know very little about the particular cognitive architecture of these two key neurocognitive functions that, when intact, appear to support successful real-world outcomes in older HIV-infected adults; indeed, very few studies have taken a component process approach to understanding the relationship between neurocognition and everyday functioning in HIV (e.g., Wright et al., 2011). Such an approach may be helpful for identifying at-risk individuals, offering practical clinical recommendations, and designing appropriate cognitive remediation strategies to help improve everyday functioning in older adults living with HIV (Woods, Moore, Weber, & Grant, 2009).

In the current study, we focus our attention on the profile of verbal episodic memory deficits that underlie declines in IADLs in HIV across the lifespan. Our exclusive focus on memory in this study allows for a deeper exploration of its component processes, which enables a more thorough analysis of the cognitive architecture of IADL dependence. Learning and memory deficits are a core feature of HIV-associated neurocognitive disorders (HAND; e.g., Carey et al., 2004; Heaton et al., 2010) and are an important predictor of poorer everyday functioning outcomes (e.g., Woods et al., 2009). Consistent with the prominent prefrontostriatal pathology of neuro-AIDS, the memory deficits observed in HIV, while heterogeneous (e.g., Murji et al., 2003), are broadly characterized by a mixed encoding and retrieval profile (e.g., Peavy et al., 1994). This profile includes poorer immediate and delayed free recall secondary to diminished use of higher-level encoding strategies (e.g., semantic clustering; Gongvatana et al., 2007), but only mild forgetting (e.g., Cattie et al., 2012) and generally intact recognition (e.g., Woods et al., 2005). Although controversy exists regarding whether older HIV-infected adults are at risk for a memory profile characterized by rapid forgetting and intrusions that is more akin to “cortical” disorders (e.g., Alzheimer's disease; Greenaway et al., 2006), the literature suggests that, while the severity of HIV-associated memory impairment is indeed exacerbated by older age, the pattern of deficits is not compellingly different from the classic frontostriatal mixed strategic encoding and retrieval profile evident in younger and middle-aged HIV-infected persons (Scott et al., 2011; Woods et al., 2013).

Thus, while we now know that older HIV-infected adults are at elevated risk for deficits in episodic memory and corresponding declines in everyday functioning, the component processes of memory that drive this important clinical association have not previously been described. The current study therefore aimed to elucidate profiles of memory dysfunction that are associated with dependence in IADLs in younger and older adults with HIV. We hypothesized that verbal memory indices from standard clinical tasks reflecting a mixed strategic encoding and retrieval profile (e.g., immediate and delayed free recall, semantic clustering), but not measures of consolidation (e.g., savings scores), would be more strongly associated with IADL declines in older HIV-infected adults as compared with their younger counterparts.

Method

Participants and Procedure

Two hundred and sixty-four participants with HIV infection were recruited into an NIMH-funded memory and aging study at the UCSD HIV Neurobehavioral Research Program. Inclusion criteria required that participants were aged 18 or older, had confirmed HIV infection diagnosis (determined via enzyme-linked immunosorbent assays and confirmatory Western blot test or MedMira Multiplo rapid test [MedMira Inc., Nova Scotia, Canada]), and were able to provide informed consent. Exclusion criteria included presence of a psychotic disorder (e.g., schizophrenia), or a neurological condition known to affect neurocognitive functioning (e.g., stroke, closed head injury, seizure disorder). In order to examine the study hypotheses, the sample was classified on the basis of both age (i.e., ≥50 years and <50 years) and IADL dependence (i.e., dependent and independent). The use of age 50 to classify “older” adults is based on the current standing of the HIV epidemic (Centers for Disease Control and Prevention, 2008) and NIH guidelines on aging research in clinical neuro-AIDS (Stoff, Khalsa, Monjan, & Portegies, 2004). IADL status was determined via a revised version of the Lawton and Brody (1969) self-report measure of activities of daily living (Heaton et al., 2004; Woods et al., 2008). Participants were classified as IADL dependent if their self-reported current functioning level was lower than their highest for at least two of the following: (i) finances, (ii) social activities, (iii) buying groceries, (iv) using the telephone; (v) transportation, (vi) child care, (vii) understanding written material/TV, (viii) shopping, (ix) cooking, (x) medication management, and (xi) working. Consistent with Frascati criteria (Antinori et al., 2007), this approach reflects both perceived declines from previous functioning as well as a need for assistance in performing activities. This classification system yielded four groups of HIV-infected persons: Older IADL Dependent (n = 43), Older IADL Independent (n = 76), Younger IADL Dependent (n = 37), and Younger IADL Independent (n = 108). Dichotomizing IADL dependence was deemed as a more appropriate approach rather than continuous examination because: (i) this classification maps on to the clinical diagnosis of HAND (i.e., presence of functional impairment) as well as other diagnostic approaches to determining functional dependence, and (ii) the non-normal nature of the continuous IADL measure (Shapiro-Wilk = .72, p < .01). Table 1 displays descriptive data regarding the number of IADL domains in which the various groups reported having experienced declines, the severity of declines across domains, and frequencies for percentage of participants in each group reporting a decline across each IADL domain.

Table 1.

Sample descriptives on IADL domain-specific decline

Variable Y+ IADL Dep. (n = 37) Y+ IADL Indep. (n = 108) O+ IADL Dep. (n = 43) O+ IADL Indep. (n = 76) 
IADL domain declinesa 3.0 (2.0–5.0) 0.0 (0.0–0.0) 3.0 (2.0–5.0) 0.0 (0.0–1.0) 
IADL decline severitya 4.0 (3.0–6.5) 0.0 (0.0–0.0) 4.0 (3.0–7.0) 0.0 (0.0–1.0) 
IADL individual domain declines 
 Finances (% yes) 12 (32) 5 (5) 12 (28) 0 (0) 
 Social activities (% yes) 25 (68) 10 (9) 28 (65) 11 (14) 
 Buying groceries (% yes) 14 (38) 0 (0) 15 (35) 1 (1) 
 Using the telephone (% yes) 8 (22) 0 (0) 11 (26) 0 (0) 
 Transportation (% yes) 2 (5) 0 (0) 2 (5) 0 (0) 
 Child care (% yes) 5 (14) 0 (0) 4 (9) 0 (0) 
 Understanding written material/TV (% yes) 20 (54) 3 (3) 29 (67) 6 (8) 
 Shopping (% yes) 16 (43) 1 (<1) 19 (44) 0 (0) 
 Cooking (% yes) 13 (35) 1 (<1) 13 (30) 0 (0) 
 Medication management (% yes) 7 (19) 2 (2) 9 (21) 0 (0) 
 Working (% yes)* 14 (39) 1 (1) 11 (27) 3 (4) 
Variable Y+ IADL Dep. (n = 37) Y+ IADL Indep. (n = 108) O+ IADL Dep. (n = 43) O+ IADL Indep. (n = 76) 
IADL domain declinesa 3.0 (2.0–5.0) 0.0 (0.0–0.0) 3.0 (2.0–5.0) 0.0 (0.0–1.0) 
IADL decline severitya 4.0 (3.0–6.5) 0.0 (0.0–0.0) 4.0 (3.0–7.0) 0.0 (0.0–1.0) 
IADL individual domain declines 
 Finances (% yes) 12 (32) 5 (5) 12 (28) 0 (0) 
 Social activities (% yes) 25 (68) 10 (9) 28 (65) 11 (14) 
 Buying groceries (% yes) 14 (38) 0 (0) 15 (35) 1 (1) 
 Using the telephone (% yes) 8 (22) 0 (0) 11 (26) 0 (0) 
 Transportation (% yes) 2 (5) 0 (0) 2 (5) 0 (0) 
 Child care (% yes) 5 (14) 0 (0) 4 (9) 0 (0) 
 Understanding written material/TV (% yes) 20 (54) 3 (3) 29 (67) 6 (8) 
 Shopping (% yes) 16 (43) 1 (<1) 19 (44) 0 (0) 
 Cooking (% yes) 13 (35) 1 (<1) 13 (30) 0 (0) 
 Medication management (% yes) 7 (19) 2 (2) 9 (21) 0 (0) 
 Working (% yes)* 14 (39) 1 (1) 11 (27) 3 (4) 

Notes: IADL = instrumental activities of daily living; Dep. = dependent; Indep. = independent; yes = % reporting a decline in the specific domain.

aFor IADL domain declines and IADL decline severity, median (IQR) is reported. *Eight subjects missing data in O+ cohort (two in IADL Dep. group and six in IADL Indep. group); 11 subjects missing data in Y+ cohort (one in IADL Dep. group and 10 in IADL Indep. group).

As shown in Table 2, preliminary analyses examining IADL group differences within each age cohort on demographic, medical, and psychiatric variables revealed that the Younger IADL Dependent group had significantly lower nadir CD4 counts and higher rates of current major depressive disorder (MDD; as determined by the Composite International Diagnostic Interview; World Health Organization, 1998) than the Younger IADL Independent group (ps < .05). Within the older cohort, the IADL Dependent group had significantly higher rates of hepatitis C virus (HCV) co-infection and current MDD than the IADL Independent group (ps < .05). As noted subsequently, these variables that differed between IADL groups were entered as covariates into subsequent statistical models.

Table 2.

Sample descriptives

Variable Y+ IADL Dep. (n = 37) Y+ IADL Indep. (n = 108) O+ IADL Dep. (n = 43) O+ IADL Indep. (n = 76) 
Demographics 
 Age (years) 39.0 (6.5) 36.7 (7.7) 56.0 (6.1) 56.3 (5.6) 
 Education (years) 13.1 (2.8) 13.1 (2.4) 13.7 (2.6) 14.3 (2.7) 
 Sex (men, %) 32 (86) 98 (91) 34 (79) 63 (83) 
 Race (Caucasian, %) 22 (59) 62 (57) 33 (77) 50 (66) 
Medical 
 Current CD4 542.6 (279.5) 605.9 (297.5) 584.8 (302.0) 583.9 (325.5) 
 Nadir CD4Y+ 176.7 (123.6) 266.0 (205.7) 209.5 (202.3) 187.0 (158.6) 
 log PL viral load 2.4 (1.2) 2.3 (1.3) 2.1 (1.0) 1.9 (0.7) 
 AIDS (with, %) 23 (62) 47 (44) 29 (67) 47 (62) 
 ARV (on, %) 31 (84) 91 (84) 35 (82) 66 (87) 
 Estimated duration of infection (months) 137.5 (94.1) 113.4 (82.8) 195.3 (95.7) 196.2 (82.7) 
 HCV (pos, %) O+ 2 (5) 9 (8) 18 (43) 14 (19) 
 Diabetes Mellitus (with, %) 1 (3) 2 (2) 3 (7) 13 (18) 
 Hypertension (with, %) 6 (17) 9 (8) 15 (35) 26 (35) 
 High cholesterol (with, %) 2 (6) 1 (<1) 11 (26) 16 (22) 
Psychiatric 
 Current MDD (%)Y+, O+ 8 (22) 9 (9) 12 (28) 5 (7) 
 Lifetime MDD (%)O+ 24 (65) 52 (49) 35 (81) 31 (41) 
 Lifetime sub dependence (%) 19 (51) 54 (50) 27 (63) 36 (47) 
Cognitive     
 WTAR verbal IQ 102.3 (11.1) 101.8 (11.7) 100.2 (12.3) 102.8 (11.6) 
 HDS total 14.1 (2.7) 14.7 (1.9) 13.1 (3.5) 13.7 (2.7) 
Variable Y+ IADL Dep. (n = 37) Y+ IADL Indep. (n = 108) O+ IADL Dep. (n = 43) O+ IADL Indep. (n = 76) 
Demographics 
 Age (years) 39.0 (6.5) 36.7 (7.7) 56.0 (6.1) 56.3 (5.6) 
 Education (years) 13.1 (2.8) 13.1 (2.4) 13.7 (2.6) 14.3 (2.7) 
 Sex (men, %) 32 (86) 98 (91) 34 (79) 63 (83) 
 Race (Caucasian, %) 22 (59) 62 (57) 33 (77) 50 (66) 
Medical 
 Current CD4 542.6 (279.5) 605.9 (297.5) 584.8 (302.0) 583.9 (325.5) 
 Nadir CD4Y+ 176.7 (123.6) 266.0 (205.7) 209.5 (202.3) 187.0 (158.6) 
 log PL viral load 2.4 (1.2) 2.3 (1.3) 2.1 (1.0) 1.9 (0.7) 
 AIDS (with, %) 23 (62) 47 (44) 29 (67) 47 (62) 
 ARV (on, %) 31 (84) 91 (84) 35 (82) 66 (87) 
 Estimated duration of infection (months) 137.5 (94.1) 113.4 (82.8) 195.3 (95.7) 196.2 (82.7) 
 HCV (pos, %) O+ 2 (5) 9 (8) 18 (43) 14 (19) 
 Diabetes Mellitus (with, %) 1 (3) 2 (2) 3 (7) 13 (18) 
 Hypertension (with, %) 6 (17) 9 (8) 15 (35) 26 (35) 
 High cholesterol (with, %) 2 (6) 1 (<1) 11 (26) 16 (22) 
Psychiatric 
 Current MDD (%)Y+, O+ 8 (22) 9 (9) 12 (28) 5 (7) 
 Lifetime MDD (%)O+ 24 (65) 52 (49) 35 (81) 31 (41) 
 Lifetime sub dependence (%) 19 (51) 54 (50) 27 (63) 36 (47) 
Cognitive     
 WTAR verbal IQ 102.3 (11.1) 101.8 (11.7) 100.2 (12.3) 102.8 (11.6) 
 HDS total 14.1 (2.7) 14.7 (1.9) 13.1 (3.5) 13.7 (2.7) 

Notes: IADL = instrumental activities of daily living; Dep. = dependent; Indep. = independent; PL = plasma; ARV = antiretroviral medications; HCV = Hepatitis C virus; MDD = major depressive disorder; WTAR = Wechsler test of adult reading; HDS = HIV Dementia Scale. Y+ = Younger HIV+ IADL groups differ, p < .05; O+ = Older HIV+ IADL groups differ, p < .05.

In addition to comprehensive psychiatric and medical evaluations, all participants completed a neurocognitive battery that included two standard clinical measures of verbal episodic memory: (i) CVLT-II (Delis, Kramer, Kaplan, & Ober, 2000) and (ii) Wechsler Memory Scale-Third Edition (WMS-III) Logical Memory (LM) subtest (Wechsler, 1997). Given the importance of age to the study hypotheses, raw scores were used in all analyses (but normative scores are displayed for graphical purposes in Fig. 1). The CVLT-II is a well-validated list-learning episodic verbal memory measure. The following indices were used in the current study: five list learning trials (i.e., list A) including total correct on trial 1, total correct on trials 1–5, total correct on a distractor list trial (i.e., list B), short- and long-delay free recall trials, long-delay savings (i.e., percentage of words recalled on trial 5 that are recalled on the long-delay free recall), and recognition discriminability (d′). We also examined several learning style component process measures of the CVLT-II, including primacy (i.e., percentage of words recalled from trials 1–5 that are from the first four words of list A), recency (i.e., percentage of words recalled from trials 1–5 that are from the last four words of list A), middle effects (i.e., percentage of words recalled from trials 1–5 that are from the interior eight words of list A), semantic clustering (i.e., ratio of list A words from the same category recalled together over chance), serial clustering (i.e., ratio of list A words in the same order as they were presented over chance), learning slope (i.e., average number of new correct words recalled per trial for list A), repetitions, and intrusions. All scores were calculated by the CVLT-II program software (Delis et al., 2000).

Fig. 1.

CVLT-II Normative Z-scores by IADL Group in the Older HIV+ Sample. Notes: CVLT-II = California Verbal Learning Test-Second Edition; IADL = instrumental activities of daily living; Indep. = independent; Dep. = dependent; T = trial; SDFR = short-delay free recall; LDFR = long-delay free recall; d′ = Recognition Discrimination Index.

Fig. 1.

CVLT-II Normative Z-scores by IADL Group in the Older HIV+ Sample. Notes: CVLT-II = California Verbal Learning Test-Second Edition; IADL = instrumental activities of daily living; Indep. = independent; Dep. = dependent; T = trial; SDFR = short-delay free recall; LDFR = long-delay free recall; d′ = Recognition Discrimination Index.

The WMS-III LM subtest is a widely used passage recall episodic memory task in which participants are read two short stories (i.e., A and B, the latter of which is read twice to the participant) and asked to recall each both immediately and after a 25- to 35-min delay. The current study used the following indices from this measure: LM-I unit total (i.e., immediate recall of story A plus both immediate recalls of story B), LM-II unit total (i.e., delayed recalls of story A plus story B), percent retention (i.e., LM-II unit total divided by LM-I story A plus the second recall of story B in LM-I), learning slope (i.e., the second immediate recall of story B minus the first immediate recall from LM-I), and a yes/no recognition trial (i.e., recognition total).

In addition, participants completed measures of semantic memory (i.e., Boston Naming Test [Kaplan, Goodglass, & Weintraub, 1983]; Kaufman Adolescent and Adult Intelligence Test [KAIT] Famous Faces subtest; [Kaufman & Kaufman, 1993]) and working memory/attention (i.e., WMS-III Digit Span [Wechsler, 1997]). Furthermore, given the role of executive functions in both HIV-associated memory deficits and IADL declines, we also included Action Fluency (Piatt, Fields, Paolo, & Tröster, 1999), Trail Making Test B (Reitan & Wolfson, 1985), and the Tower of London (total moves; Culbertson & Zillmer, 2001). All of these measures were administered and scored according to their respective published standardized procedures. As with the episodic memory measures, raw composite scores were used for all analyses.

Data Analytic Plan

All statistical analyses were performed using JMP software (Version 10.0, SAS Institute, Cary, NC). The critical alpha was set at the standard level of .05 for all analyses. A series of multivariable logistic regressions were conducted predicting IADL status from the primary memory variables separately in the Older and Younger cohorts. In this way, conducting separate models in the Younger and Older samples provided a more tailored and conservative approach to determining the role of memory in IADL declines across the lifespan. Clinical variables that differed between groups split by IADL status within the Older (i.e., HCV and current MDD) and Younger (i.e., nadir CD4 count and current MDD) samples were entered as covariates. Note that, exclusion of the covariates from the models did not alter the study findings. Results within the Younger cohort showed that no indices from the CVLT-II or WMS-III LM were significant predictors of IADL dependence (all ps > .10). In contrast, examination within the Older cohort revealed several significant associations between primary episodic memory measures and IADL dependence, which are reported in detail subsequently (see Table 3 for means, SDs, and effect sizes).

Table 3.

Means and SDs for memory and executive variables by IADL dependence within the older cohort

Memory variable IADL Dep. (n = 43) IADL Indep. (n = 76) Cohen's d 
Primary CVLT-II variables 
 Trial 1* 5.02 (1.79) 5.88 (1.98) 0.45 
 Trials 1–5* 43.86 (9.50) 47.84 (10.29) 0.40 
 Trial B* 4.00 (1.56) 4.83 (1.75) 0.49 
 Short-delay free recall* 8.71 (3.18) 9.56 (3.48) 0.25 
 Long-delay free recall* 8.71 (3.77) 9.96 (3.53) 0.35 
 Long-delay savings (% change)* −23.22 (26.31) −16.72 (20.30) 0.29 
 Recognition discriminability* 2.62 (0.73) 2.97 (0.87) 0.43 
Component process CVLT-II variables 
 Primacy (% recall from) 27.55 (7.42) 28.15 (5.70) 0.09 
 Middle (% recall from) 40.81 (7.18) 43.28 (7.54) 0.33 
 Recency (% recall from)* 31.64 (8.94) 28.71 (7.98) 0.35 
 Semantic clustering 0.64 (1.66) 1.16 (2.06) 0.27 
 Serial clustering 0.76 (0.91) 0.58 (1.06) 0.18 
 Learning slope 1.42 (0.68) 1.40 (0.55) 0.03 
 Repetitions 4.43 (4.48) 5.68 (5.40) 0.25 
 Intrusions 5.43 (5.85) 6.52 (7.53) 0.16 
WMS-III logical memory 
 Logical Memory-I unit total* 35.63 (10.70) 42.30 (9.97) 0.65 
 Logical Memory-II unit total* 20.37 (7.87) 25.89 (7.07) 0.75 
 Retention (%)* 77.23 (16.60) 85.01 (14.21) 0.51 
 Learning Slope 4.16 (2.79) 4.39 (2.55) 0.09 
 Recognition 24.51 (3.06) 25.37 (2.60) 0.31 
Semantic Memory 
 Boston Naming Test 54.17 (4.95) 55.33 (5.27) 0.22 
 KAIT famous faces 13.12 (4.41) 14.16 (3.92) 0.25 
Executive functioning 
 Action fluency total words* 13.44 (4.41) 16.08 (4.88) 0.56 
 Trail making test B total time* 112.84 (64.95) 75.95 (38.09) 0.75 
 Tower of London total moves 33.90 (24.67) 32.64 (23.53) 0.05 
Compositesa 
 Encoding* −0.34 (0.81) 0.20 (0.73) 0.71 
 Consolidation* −0.25 (0.85) 0.14 (0.74) 0.50 
 Recognition* −0.23 (0.78) 0.13 (0.82) 0.45 
 Executive function* −0.28 (0.83) 0.15 (0.65) 0.60 
Memory variable IADL Dep. (n = 43) IADL Indep. (n = 76) Cohen's d 
Primary CVLT-II variables 
 Trial 1* 5.02 (1.79) 5.88 (1.98) 0.45 
 Trials 1–5* 43.86 (9.50) 47.84 (10.29) 0.40 
 Trial B* 4.00 (1.56) 4.83 (1.75) 0.49 
 Short-delay free recall* 8.71 (3.18) 9.56 (3.48) 0.25 
 Long-delay free recall* 8.71 (3.77) 9.96 (3.53) 0.35 
 Long-delay savings (% change)* −23.22 (26.31) −16.72 (20.30) 0.29 
 Recognition discriminability* 2.62 (0.73) 2.97 (0.87) 0.43 
Component process CVLT-II variables 
 Primacy (% recall from) 27.55 (7.42) 28.15 (5.70) 0.09 
 Middle (% recall from) 40.81 (7.18) 43.28 (7.54) 0.33 
 Recency (% recall from)* 31.64 (8.94) 28.71 (7.98) 0.35 
 Semantic clustering 0.64 (1.66) 1.16 (2.06) 0.27 
 Serial clustering 0.76 (0.91) 0.58 (1.06) 0.18 
 Learning slope 1.42 (0.68) 1.40 (0.55) 0.03 
 Repetitions 4.43 (4.48) 5.68 (5.40) 0.25 
 Intrusions 5.43 (5.85) 6.52 (7.53) 0.16 
WMS-III logical memory 
 Logical Memory-I unit total* 35.63 (10.70) 42.30 (9.97) 0.65 
 Logical Memory-II unit total* 20.37 (7.87) 25.89 (7.07) 0.75 
 Retention (%)* 77.23 (16.60) 85.01 (14.21) 0.51 
 Learning Slope 4.16 (2.79) 4.39 (2.55) 0.09 
 Recognition 24.51 (3.06) 25.37 (2.60) 0.31 
Semantic Memory 
 Boston Naming Test 54.17 (4.95) 55.33 (5.27) 0.22 
 KAIT famous faces 13.12 (4.41) 14.16 (3.92) 0.25 
Executive functioning 
 Action fluency total words* 13.44 (4.41) 16.08 (4.88) 0.56 
 Trail making test B total time* 112.84 (64.95) 75.95 (38.09) 0.75 
 Tower of London total moves 33.90 (24.67) 32.64 (23.53) 0.05 
Compositesa 
 Encoding* −0.34 (0.81) 0.20 (0.73) 0.71 
 Consolidation* −0.25 (0.85) 0.14 (0.74) 0.50 
 Recognition* −0.23 (0.78) 0.13 (0.82) 0.45 
 Executive function* −0.28 (0.83) 0.15 (0.65) 0.60 

Notes: IADL = instrumental activities of daily living; Dep. = dependent; Indep. = independent; CVLT-II = California Verbal Learning Test-Second Edition; WMS-III = Wechsler Memory Scale-Third Edition; KAIT = Kaufman Adolescent and Adult Intelligence Test.

aFor all Z-score composites higher scores reflect better performance.

*p < .05.

Results

The California Verbal Learning Test-Second Edition

In the Older cohort, analyses of all primary CVLT-II indices showed significant effects on IADL dependence (all logistic regression model p-values < .05), with the Older IADL Dependent group exhibiting lower scores than the Older IADL Independent group on trial 1 (χ2 = 6.78; p = .009), total trials 1–5 (χ2 = 6.16; p = .013), total trial B (χ2 = 4.83; p = .028), short-delay free recall (X2 = 4.77; p = .029), long-delay free recall (χ2 = 7.07; p = .008), long-delay savings (χ2 = 6.80; p = .009), and recognition discriminability (d′) (χ2 = 5.35; p = .021). Demographically adjusted scores on the full array of CVLT-II learning and memory variables for the IADL Independent and Dependent Older groups are displayed for the reader in Figure 1.

In order to further examine the nature of the association between the CVLT-II and IADL dependence in the Older cohort, follow-up unadjusted univariate analyses were conducted using select component process variables. Results revealed that the Older IADL Dependent group demonstrated elevated recency effects (χ2 = 5.30; p = .02) relative to the Older IADL Independent group. Semantic clustering, serial clustering, learning slope, repetitions, and intrusions were not significantly associated with IADL dependence (ps > .10).

WMS-III Logical Memory

Results from the WMS-III LM were broadly consistent with those observed on the CVLT-II. Specifically, the Older IADL Dependent group demonstrated significantly worse performance on LM-I unit total (χ2 = 6.77, p = .009), LM-II unit total (χ2 = 11.13, p = .001), and percent retention (χ2 = 9.18, p = .002), with no differences on learning slope (p > .10). However, in contrast to the CVLT-II, the WMS-III LM recognition total was not significantly different between the Older IADL Dependent and Independent groups (p > .10).

Post hoc Analyses

Taken together, findings from both the CVLT-II and the WMS-III LM suggest that both encoding and consolidation deficits are independent predictors of IADL dependence among Older HIV+ adults. To evaluate the potential independent contribution of these two oftentimes related aspects of memory, composites were created for encoding and consolidation by averaging the raw sample-based Z-scores for CVLT-II trial 1 and WMS-III LM unit I total (encoding), and CVLT-II long-delay savings and WMS-III LM percent retention (consolidation). Composites were also calculated in the same manner for recognition (i.e., CVLT-II recognition discriminability and WMS-III LM recognition) and executive functions (i.e., Action Fluency total words, Tower of London total number of moves, and Trail Making Test B total time). Note that reverse scoring was employed for Trail Making Test B and Tower of London, thus for all Z-score composites higher values reflect better performance. These encoding, consolidation, recognition, and executive function Z-score composites were entered into a logistic regression model predicting IADL dependence in the Older HIV+ group, along with covariates of HCV co-infection, current MDD, and WMS-III Digit Span Forward (the latter to rule out the influence of basic attention deficits). The overall model was significant (χ2 = 34.93, p < .0001), with independent, significant contributions from both the encoding (χ2 = 5.67, p = .02) and consolidation (χ2 = 5.16, p = .02) composites, whereas the recognition and executive composites were not significant predictors of IADL dependence (ps > .10).

Finally, given the importance of both shallow encoding and poorer consolidation in the IADL declines of Older HIV-infected subjects and the controversies regarding the “cortical” hypothesis of neuro-AIDS in the cART era as described earlier, we also examined the associations between IADL dependence and measures of semantic memory. Logistic regressions controlling for MDD and HCV showed that neither Boston Naming Test nor the KAIT Famous Faces Test significantly discriminated between those Older HIV+ adults with and without IADL dependence (ps > .10).

Discussion

Older adults infected with HIV are at heightened risk for verbal memory deficits and corresponding declines in real-world functioning. However, we know little about the specific profile of memory deficits that drives HIV-associated IADL declines and how such effects may differ across the lifespan in HIV. Thus, the current study investigated memory profiles associated with IADL dependence in younger and older adults with HIV. Although verbal episodic memory was not related to IADLs in younger HIV-infected persons, such deficits were independent and robust predictors of IADL dependence among older HIV+ adults. Specifically, nearly all of the primary immediate and delayed recall indices from the CVLT-II and WMS-III LM were associated with a greater likelihood of IADL dependence, with generally medium-to-large effect sizes. The memory associations with IADLs were independent of other established predictors of IADLs, including factors upon which the IADL groups were comparable (e.g., demographics, premorbid IQ, HIV disease severity, and histories of substance use disorders) and those that were included as covariates in the logistic regressions (i.e., depression, co-infection with HCV). As such, verbal episodic memory deficits appear to be a particularly important determinant of functional dependence in older versus younger adults living with HIV infection. Consistent with prior findings in the ARV adherence literature (e.g., Hinkin et al., 2004), these data suggest that the combined effects of older age and neurocognitive burden are particularly detrimental to poorer real-world outcomes in persons living with HIV infection.

The present study also advances our understanding of the profile of episodic memory impairment that may increase HIV-infected older adults' vulnerability to functional dependence. The consistency of effects across all major memory indices, including initial learning, savings scores, and recognition discriminability (on the CVLT-II), suggest that both encoding and consolidation play a role in IADL dependence in older HIV-infected adults. This interpretation was supported by a post hoc regression showing independent effects of encoding and consolidation composite scores on IADL dependence, even when accounting for the potential roles of recognition, executive functions, and basic attention (i.e., digit span). This finding was surprising given the general pattern of HIV-associated episodic memory deficits, which is predominated by a profile of mixed strategic encoding and retrieval impairments (e.g., Cattie et al., 2012; Delis et al., 1995) that are sensitive to non-adherence in middle-aged cohorts (e.g. Wright et al., 2011). Nevertheless, the profile of memory deficits in HIV is heterogeneous (Murji et al., 2003), and there is prior evidence for at least mild deficits in consolidation (Cattie et al., 2012; Woods et al., 2005) that are related to medial temporal lobe atrophy (Maki et al., 2009). The absence of recognition findings suggests that the mild forgetting observed may also be, at least in part, related to strategically demanding retrieval at free recall that is diminished upon presentation of the more structured recognition format; a finding that as described below is particularly relevant to the WMS-III Logical Memory subtest.

Analyses of the component process measures from the CVLT-II shed further light on the possible mechanisms of deficient encoding and consolidation observed in the current study. In particular, these analyses revealed that serial position effects, namely elevated recency recall, might be a marker of shallow encoding which could play an important role in the IADL dependence of older HIV+ adults. This passive, “parroting” style of recall in which one echoes words in their immediate auditory attention span tends to discourage deep encoding and may thereby exacerbate forgetting. Such recency effects have been previously observed in HIV-associated dementia (HAD; Scott et al. 2006), which is marked by moderate-to-severe functional decline and cognitive impairment. Of note, none of the subjects in the current study met Frascati criteria for HAD (Antinori et al., 2007), and thus the influence of such shallow encoding on IADLs is evident in the absence of severe cognitive and functional declines. In contrast, recall from the primacy region, intrusion errors, and semantic clustering were not significant predictors of IADL dependence, suggesting that the shallow encoding due to recency effects may be a primary source of the memory deficit associated with IADL dependence in older non-demented HIV-infected adults.

One possible interpretation of these data is that the encoding and consolidation problems underlying IADL declines are consistent with the profile found in aging-related neurodegenerative disorders involving “cortical” dysfunction (viz, medial temporal lobe) such as Alzheimer's disease. However, several lines of evidence also argue against this interpretation. First, IADL declines were not associated with semantic memory in the current study, although this argument is somewhat tempered by the notion that measures of semantic memory may not be sensitive to IADL problems across clinical conditions. Second, the majority of controlled cognitive studies that have examined the so-called cortical hypothesis in HIV infection have not yielded positive findings, including two studies from our group Iudicello, Woods, Deutsch, Grant, & the HNRP Group, 2012; Scott et al., 2011). Thus, it may be that the heterogeneity of HIV-associated memory profiles (Murji et al., 2003) is such that the subset of older HIV+ adults with shallow encoding and poorer consolidation are simply at higher risk of IADL dependence, and potentially future neurocognitive decline, including possibly progression to HAD (Scott et al., 2006).

To our surprise, there were no unique episodic memory profiles associated with IADL dependence in the younger HIV+ cohort. Although we expected such associations would be weaker than those predicted to emerge in older HIV-infected adults, the strikingly null findings were not anticipated. These differential findings across the lifespan are unlikely to be an artifact of statistical power (e.g., the Younger HIV+ sample was actually larger than the Older group) or IADL decline severity (i.e., the Older and Younger HIV+ samples were comparable in that regard). One possibility is that Younger HIV+ adults are less likely to exhibit shallow encoding and forgetting than their older counterparts. It is also possible that the relative fragility of older HIV+ adults' daily lives are simply more vulnerable to even subtle encoding and consolidation deficits, especially if proper compensatory strategies are not in place. Questions thus remain regarding the neurocognitive mechanisms of IADL declines in Younger HIV+ adults, which may relate more strongly to executive dysfunction (e.g., planning, novel problem solving). This is particularly relevant to “emerging” HIV+ adults (i.e., 16–24 years of age), who are at high risk for neurocognitive impairment (Nichols et al., 2013) while developing fundamental daily functioning skills and routines upon which successful health outcomes depend.

A limitation of this study includes the use of a cross-sectional design, limiting causal inferences regarding the association between memory deficits and IADL declines. Longitudinal studies examining the trajectory of HIV-associated memory impairments and incident syndromic HAND are needed to understand the temporal course of episodic memory and functional declines. Moreover, it should be noted that the use of an age 50 cutpoint for “older” adults differs from the geropsychology literature, but is consistent with clinical research recommendations in neuro-AIDS (e.g., High et al., 2012). Future research is warranted to examine these associations in even older HIV+ cohorts (e.g., aged 60 and older), who may be at particular risk of HAND. Nevertheless, the relatively younger age of our older cohort would arguably increase our risk of Type II error, which is less of a concern in light of the current study findings showing strong, independent associations between verbal memory deficits and IADL declines. There are also limitations to using single test scores as indicators of broad higher-level memory constructs as we did in our final regressions to examine “encoding” and “consolidation”; nevertheless, we arrived at those particular scores by way of a full profile analysis, which helps to mitigate that limitation. We also did not have any measures of visual memory (e.g., Rey Complex Figure Test) in this study to determine the concurrent validity of the verbal memory profiles. Finally, this study did not include symptom validity tests, limiting our ability to rule out the effects of suboptimal effort on memory performance; nevertheless, prior work suggests that suboptimal effort is relatively uncommon in the context of clinical research in HIV (Slick, Hinkin, van Gorp, & Satz, 2001; Woods et al., 2003).

Despite these limitations, our data provide initial evidence that memory encoding and consolidation deficits are both important contributors to functional outcomes in older individuals with HIV infection, even after accounting for disease status and comorbid medical and psychiatric factors. Our results also provide important data for rehabilitation for clinicians and researchers working with aging HIV populations. For example, the WMS-III LM profile suggests that verbal information presented in context may be more amenable to robust encoding by older HIV+ adults with IADL problems. Although deficits were evident on both immediate and long-delayed free recall of LM, with some evidence of forgetting on retention scores, yes/no recognition performance was nonetheless spared. By way of contrast, IADL dependence was associated with recognition deficits on the CVLT-II, which is a less structured supraspan list learning and recall task, suggesting that the added context of passage recall provided some benefit to encoding and retention when assessed in a structured recognition format. This interpretation is consistent with prior data showing that passage recall tasks are inherently more organized than list recall tasks, which require greater self-initiated, active organization of the material to be learned (Tremont, Halpert, Javorsky, & Stern, 2000). Individuals with IADL dependence may have more trouble with acquiring and retaining everyday tasks involving novel, unorganized information (e.g., remembering a grocery list, recipe, or phone number), which may be enhanced by provision of structure and/or context. Indeed, several studies now show that self-initiated and/or clinically imposed structure enhances neurocognitive performance in HIV-infected individuals (Iudicello et al., 2012; Weber et al., 2012).

Future studies are needed to examine the efficacy of intervention approaches to deepen encoding and facilitate transfer of episodic memories into more secure long-term storage. Some potential intervention approaches include self-generation (Weber et al., 2012) and spaced retrieval (Neundorfer et al., 2004). For example, Weber and colleagues showed that self-generation greatly enhanced both immediate and delayed verbal memory for paired associates in persons living with HIV infection (Weber et al., 2012). Given the preliminary evidence of these promising interventions, further approaches targeting such compensatory strategies to reduce burden on dysfunctional memory systems may offer a non-invasive and feasible way to avoid or prolong the onset of functional problems associated with underlying cognitive problems in aging with HIV. Future research building off of findings in the gerontological literature may provide insights and future directions for the cognitive rehabilitation of neuro-AIDS as this population continues to age.

Funding

This research was supported by National Institutes of Health (NIH) grants R01-MH073419, T32-DA031098, P30-MH062512, F31-DA034510, F31-DA035708, L30-DA032120, and L30-DA034362. Dr. Fazeli is supported by R25-MH081482, R01-MH099987, L30-AG045921, and ID10-SD-057 from California HIV/AIDS Research Program (CHRP).

Conflict of Interest

None declared.

Acknowledgements

The views expressed in this article are those of the authors and do not reflect the official policy or position of the Department of the Navy, Department of Defense, or U.S. Government.

Appendix

The San Diego HIV Neurobehavioral Research Program (HNRP) group is affiliated with the University of California, San Diego, the Naval Hospital, San Diego, and the Veterans Affairs San Diego Healthcare System, and it includes: Director: Igor Grant; Co-Directors: J. Hampton Atkinson, Ronald J. Ellis, and J. Allen McCutchan; Center Manager: Thomas D. Marcotte; Jennifer Marquie-Beck; Melanie Sherman; Neuromedical Component: Ronald J. Ellis (P.I.), J. Allen McCutchan, Scott Letendre, Edmund Capparelli, Rachel Schrier, Debra Rosario, Shannon LeBlanc; Neurobehavioral Component: Robert K. Heaton (P.I.), Steven Paul Woods, Mariana Cherner, David J. Moore, Erin E. Morgan, Matthew Dawson; Neuroimaging Component: Terry Jernigan (P.I.), Christine Fennema-Notestine, Sarah L. Archibald, John Hesselink, Jacopo Annese, Michael J. Taylor; Neurobiology Component: Eliezer Masliah (P.I.), Cristian Achim, Ian Everall (Consultant); Neurovirology Component: Douglas Richman (P.I.), David M. Smith; International Component: J. Allen McCutchan (P.I.); Developmental Component: Cristian Achim (P.I.), Stuart Lipton; Participant Accrual and Retention Unit: J. Hampton Atkinson (P.I.); Data Management Unit: Anthony C. Gamst (P.I.), Clint Cushman (Data Systems Manager); Statistics Unit: Ian Abramson (P.I.), Florin Vaida, Reena Deutsch, Anya Umlauf.

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Woods
S. P.
Weber
E.
Dawson
M. S.
Bondi
M. W.
Grant
I.
the HNRP Group
Neurocognitive consequences of HIV infection in older adults: An evaluation of the “cortical” hypothesis
AIDS and Behavior
 
2011
15
1187
1196
Slick
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Hinkin
C. H.
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W. G.
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Base rate of a WMS-R malingering index in a sample of non-compensation-seeking men infected with HIV-1
Applied Neuropsychology
 
2001
8
3
185
189
Smith
G.
Aging hearing: HIV over fifty, exploring the new threat
 
2006
Washington, DC
Senate Committee on Aging
Stoff
D. M.
Khalsa
J. H.
Monjan
A.
Portegies
P.
Introduction: HIV/AIDS and aging
AIDS
 
2004
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Thames
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Medication and finance management among HIV-infected adults: The impact of age and cognition
Journal of Clinical and Experimental Neuropsychology
 
2011
33
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Thomas
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Brier
M. R.
Snyder
A. Z.
Vaida
F. F.
Ances
B. M.
Pathways to neurodegeneration: Effects of HIV and aging on resting-state functional connectivity
Neurology
 
2013
80
13
1186
1193
Tremont
G.
Halpert
S.
Javorsky
D. J.
Stern
R. A.
Differential impact of executive dysfunction on verbal list learning and story recall
The Clinical Neuropsychologist
 
2000
14
3
295
302
United States Senate Special Committee on Aging
Hearing: Older Americans: The Changing Face of HIV/AIDS in America
2013
One Hundred Thirteenth Congress, first session
September 18, 2013
Washington, DC
Valcour
V.
Paul
R.
Neuhaus
J.
Shikuma
C.
The effects of age and HIV on neuropsychological performance
Journal of the International Neuropsychological Society
 
2011
17
190
195
Valcour
V.
Shikuma
C.
Shiramizu
B.
Watters
M.
Poff
P.
Selnes
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et al.  
Higher frequency of dementia in older HIV-1 individuals: The Hawaii Aging with HIV-1 Cohort
Neurology
 
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63
822
827
Vance
D. E.
Fazeli
P. L.
Gakumo
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The impact of neuropsychological performance on everyday functioning between older and younger adults with and without HIV
Journal of the Association of Nurses in AIDS Care
 
2013
24
2
112
125
Vance
D. E.
Wadley
V. G.
Crowe
M. G.
Raper
J.
Ball
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Clinical Gerontologist
 
2011
34
5
413
426
Weber
E.
Woods
S. P.
Kellog
E. J.
Grant
I.
Basso
M. R.
the HNRP Group
Self-generation enhances verbal recall in individuals infected with HIV
Journal of the International Neuropsychological Society
 
2012
18
1
128
133
Wechsler
D.
Wechsler memory scale-third edition
 
1997
San Antonio, TX
The Psychological Corporation
Woods
S. P.
Conover
E.
Weinborn
M.
Rippeth
J. D.
Brill
R. M.
Heaton
R. K.
the HNRC Group
Base rate of Hiscock Digit Memory Test failure in HIV-associated neurocognitive disorders
Clinical Neuropsychology
 
2003
17
3
383
389
Woods
S. P.
Dawson
M. S.
Weber
E.
Gibson
S.
Grant
I.
Atkinson
J. H.
et al.  
the HNRC Group
Timing is everything: Antiretroviral nonadherence is associated with impairment in time-based prospective memory
Journal of the International Neuropsychological Society
 
2013
15
45
52
Woods
S. P.
Dawson
M.
Weber
E.
Grant
I.
the HNRC Group
The semantic relatedness of cue-intention pairings influences prospective memory failures in older adults with HIV infection
Journal of Clinical and Experimental Neuropsychology
 
2010
32
398
407
Woods
S. P.
Hoebel
C.
Pirogovsky
E.
Rooney
A.
Cameron
M. V.
Grant
I.
et al.  
the HNRP Group
Visuospatial temporal order memory deficits in older adults with HIV infection
Cognitive and Behavioral Neurology
 
2013
26
4
171
180
Woods
S. P.
Iudicello
J. E.
Moran
L. M.
Carey
C. L.
Dawson
M. S.
Grant
I.
et al.  
the HNRC Group
HIV-associated prospective memory impairment increases risk of dependence in everyday functioning
Neuropsychology
 
2008
22
1
110
117
Woods
S. P.
Moore
D. J.
Weber
E.
Grant
I.
Cognitive neuropsychology of HIV-associated neurocognitive disorders
Neuropsychology Review
 
2009
19
2
152
168
Woods
S. P.
Scott
J. C.
Dawson
M. S.
Morgan
E. E.
Carey
C. L.
Heaton
R. K.
the HNRC Group
Construct validity of Hopkins Verbal Learning Test-Revised component process measures in an HIV-1 sample
Archives of Clinical Neuropsychology
 
2005
20
8
1061
1071
World Health Organization
Composite international diagnostic interview (CIDI, version 2.1).
 
1998
Geneva, Switzerland
Wright
M. J.
Woo
E.
Foley
J.
Ettenhofer
M. L.
Cottingham
M. E.
Gooding
A. L.
et al.  
Antiretroviral adherence and the nature of HIV-associated verbal memory impairment
Journal of Neuropsychiatry and Clinical Neurosciences
 
2011
23
3
324
331

Author notes

The HIV Neurobehavioral Research Program (HNRP) Group is listed in Appendix.