Feature

State of the Science: The Efficacy of a Multicomponent Intervention for ART Adherence Among People Living With HIV Youngran Yang, PhD, MPH, BSN, RN Incorrect or inconsistent adherence to antiretroviral therapy (ART) compromises the effectiveness of medications and the patient’s chances of achieving viral suppression; near-perfect (.95%) compliance is required for both immediate and long-term clinical success. This report presents a systematic review of a multicomponent intervention to address adherence to ART and explores whether this intervention, when compared with standard care, resulted in improved ART adherence. Eleven randomized controlled trial studies published between 1999 and 2008 were reviewed. Seven of these demonstrated a beneficial effect from multicomponent intervention, which primarily incorporated individual education and one to three additional interventions. Interventions targeting the improvement of the patient’s medication management skills were particularly successful. However, because of incongruent results across studies, it could not be determined whether improved adherence extended to improved virologic or immunologic outcomes. There is a need for standardization and increased methodological rigor in the execution of adherence trials. (Journal of the Association of Nurses in AIDS Care, -, 1-12) Copyright Ó 2013 Association of Nurses in AIDS Care Key words: antiretroviral therapy, adherence, review, randomized controlled trial, intervention

Thanks to the availability and accessibility of antiretroviral (ARV) drugs, people living with HIV infection (PLWH) who adhere to their medications have experienced longer and healthier lives (Lucas,

2005). For short- and long-term clinical success, near-perfect adherence to ARV medication is required. In an observational study assessing the effects of different levels of adherence, individuals with 95% or greater ARV adherence rates had less virologic failure, greater increases in CD41 T cells, and lower rates of hospitalization than those having less than 95% adherence to ARV medications (Paterson et al., 2000). In addition to individual success, the importance of ARV adherence also must be emphasized from the perspective of public health; a person who has developed drug resistance due to poor practices in medication adherence may infect others with a drug-resistant virus (Wainberg & Friedland, 1998). Failure of ARV adherence is a major predictor of drug resistance. Unlike diabetes or hypertension medication, where one may recover the full benefit of medication by correcting partial adherence as soon as possible, the short half-lives of ARV drugs mean that even a few days of missed doses could adversely affect the opportunities for viral suppression and encourage the development of drug resistance (Funesti Esch & Frank, 2001; Williams, 2001). However, medication side effects, psychological factors, and the burden of taking large quantities of pills at regular intervals all have been shown to negatively impact adherence to antiretroviral therapy (ART), leading to a very low mean adherence rate (Miller et al., 2002). In one Youngran Yang, PhD, MPH, BSN, RN, is an assistant professor, Chonbuk National University College of Nursing, Jeonju-si, Jeollabuk-do, Republic of Korea.

JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. -, No. -, -/- 2013, 1-12 http://dx.doi.org/10.1016/j.jana.2013.08.003 Copyright Ó 2013 Association of Nurses in AIDS Care

2 JANAC Vol. -, No. -, -/- 2013

study of women living with HIV, the first month posted an adherence rate of 64%, which then dropped to 45% at the time of a 6-month follow-up measurement (Howard et al., 2002); in another study, the adherence rate over 1 week ranged from 53% to 60% among current and former drug users when measured by a medication event monitoring system (Arnsten et al., 2001). The objective of this paper was to review the state of the science of a multicomponent intervention designed to improve ART adherence and to explore whether this intervention resulted in higher success rates when compared with standard care. The multicomponent intervention is defined and evaluated, the conceptual model of the review is presented, the theoretical rationale for a multicomponent intervention addressing ART intervention is reviewed, and outcomes across studies are reviewed and synthesized. Implications for future research and implementation in clinical practice are discussed in the conclusion.

2 pilot test studies, were chosen for review. One article was published in Spanish, so only the abstract was reviewed (Knobel et al., 1999).

Definition of the Multicomponent Intervention The multicomponent intervention was defined as a program that incorporated an individual education component with between one and three additional interventions for the purpose of enhancing ART adherence among PLWH. Additional interventions might have included training in self-management skills, counseling, phone support, home visits, and/ or offering a variety of aids, such as pill-sorting boxes and medication planners. The programs were presented in a clinic or hospital setting and were facilitated by a trained health care professional.

Conceptual Model of the Review Literature Search Strategy Determining the state of the science of multicomponent interventions was undertaken by searching the computerized databases Medline, CINAHL, Cochrane CENTRAL, PsycINFO, EMBASE, and the National Guideline Clearinghouse, using the terms adherence, intervention, HIV or AIDS, randomized controlled trials, and antiretroviral* or ART. Manual searching for studies relevant to the intervention was also used. The inclusion of an education program as a primary component in the multicomponent intervention was emphasized as a requirement for an article to be selected. Preference was also given when this component was combined with additional interventions. Studies using only motivational interviewing or cognitive behavioral intervention without an education program and those targeting children were excluded. In order to examine the most rigorous research in this area of science, only randomized controlled trials (RCTs) were included. Although no restrictions were placed on publication dates, only articles published after 1997 appeared in the search results. Out of 224 RCT studies, 11 articles, all published between 1999 and 2008 and including

Figure 1 illustrates the conceptual model for the multicomponent intervention promoting ART adherence that was used by this review. Certain personal characteristics and environmental and social factors may act as moderating factors that influence health behaviors and ARV medications at an individual level (Fisher, Fisher, Amico, & Harman, 2006). Psychological health parameters, such as depression and substance use (e.g., alcohol, cocaine, heroin, or current intravenous drug use), when present at high levels, have consistently been found to negatively affect ART adherence (Holzemer, Henry, Portillo, & Miramontes, 2000; Murphy, Lu, Martin, Hoffman, & Marelich, 2002). Environmental and social factors include homelessness (Duran et al., 2001), childcare demands (Mellins et al., 2002), access to medical services (Murphy et al., 2002), and social support (Koenig et al., 2008). The multicomponent intervention is guided by the InformationMotivation-Behavioral Skills (IMB) model of adherence to ART to improve outcomes of adherence measurement, which is described in the following section. The intervention aspires to enhance ART adherence, increase CD41 T cell counts, and decrease HIV RNA viral loads.

Yang / Intervention for ART Adherence

People Living With HIV

3

Outcomes

Psychological factors Depression Substance use

ART adherence CD4+ T cells RNA viral load

Environmental & social factors Homelessness Childcare demands Social support Access to health services

Health Behavior

Intervention Multicomponent intervention guided by the IMB model of adherence to ART

ARV medication

Figure 1. Conceptual model of the review. Note. ARV 5 antiretroviral; IMB 5 Information-Motivation -Behavioral Skills model; ART 5 antiretroviral therapy; RNA 5 ribonucleic acid.

Theoretical Framework of the Multicomponent Intervention

Characteristics of 11 RCT Studies Study Setting

The IMB model of ART adherence was the best fit for reviewing the multicomponent intervention’s ability to help individuals achieve optimal levels of adherence (Fisher et al., 2006). The IMB model of adherence is comprised of three determinants— information, motivation, and behavioral skills—as prerequisites of consistent and correct use of therapy. Information about ART may facilitate adherence, as in the case of an individual who acquires comprehensive information about specific medications involved in his or her regimen, including when and how to take them, potential drug interactions, and side effects. An individual’s adherence is subject to his or her motivation to adhere, which is based on the individual’s personal and social beliefs about outcomes from therapy adherence. Lastly, behavioral skills are the individual’s abilities or perceived self-efficacy to deal with the complexities that occur during prescription adherence. These include skills such as selfadministering medications, incorporating a regimen into one’s daily life, acquiring social support as needed, and participating in adherence selfreinforcement over time (Fisher et al., 2006). The determinants of information and behavioral skills were used for the purposes of this review.

In general, participants in the reviewed studies were drawn from urban university-affiliated hospital settings, infectious disease departments, and sexually transmitted disease clinics. Five studies were conducted in the United States (Koenig et al., 2008; Rathbun, Farmer, Stephens, & Lockhart, 2005; Rawlings et al., 2003; Samet et al., 2005; Smith, Rublein, Marcus, Brock, & Chesney, 2003), two in Spain (Knobel et al., 1999; Tuldra et al., 2000), two in France (Goujard et al., 2003; Pradier et al., 2003), and two in Australia (Fairley et al., 2003; Levy et al., 2004). Length of time between intervention and follow-up surveys ranged from 3 months to 18 months, with the sessions occurring between October 1995 and September 2002. All studies were approved by ethics committees, and written informed consent was obtained from all participants. Participants Study participants were limited to PLWH on prescribed ART who were able to self-medicate. In most of the studies, people were eligible if they were at least 18 years of age and not planning to

4 JANAC Vol. -, No. -, -/- 2013

interrupt or change ART in the following 3 months. Some studies included additional specific eligibility criteria; examples included a history of alcohol problems (Samet et al., 2005) or being infected with HIV through injection drug use and possessing no opportunistic infections (Pradier et al., 2003). Five studies included participants who were either ARV na€ıve or switching to a new ARV regimen (Knobel et al., 1999; Rathbun et al., 2005; Rawlings et al., 2003; Smith et al., 2003; Tuldra et al., 2000). Study Design and Procedure All participants in the studies were randomized into an intervention group or a control group. Two studies used the stepped-wedge design, where individuals received the intervention in a random order over a 20-week study period (Fairley et al., 2003; Levy et al., 2004). This design implied the standard of a conventional RCT because all observations before the intervention were compared to those after the intervention during the analysis phase. In one study, participants were grouped based on medication frequency and regimen combination to reflect the types of regimens used and their potential tolerability (Rathbun et al., 2005). Intervention groups and control groups were offered the same questionnaires at enrollment and follow-ups, and two studies contacted participants monthly via telephone (Fairley et al., 2003; Levy et al., 2004). Level of CD41 T cell counts and plasma viral loads were recorded at baseline and at follow-ups as secondary outcomes. Outcome Measures Definitions of adherence varied across studies (Wise & Operario, 2008). Whereas some studies defined adherence in terms of meeting a minimum threshold (e.g., 80%) of pill-taking behavior, others used more conservative standards (100% pill taking; Pradier et al., 2003; Samet et al., 2005), and still others defined adherence by number of missed treatment doses (Fairley et al., 2003; Levy et al., 2004). Combinations of the measurement categories were employed. Of these studies, seven (Fairley et al., 2003; Goujard et al., 2003; Knobel et al., 1999;

Levy et al., 2004; Pradier et al., 2003; Samet et al., 2005; Tuldra et al., 2000) used self-reporting measures of adherence, while the remaining four (Koenig et al., 2008; Rathbun et al., 2005; Rawlings et al., 2003; Smith et al., 2003) used objective (pill count, electronic monitoring) measures. Adherence outcomes were also calculated as continuous variables, using a percentage range based on those reaching a pre-determined threshold of adherence, such as 90% (Knobel et al., 1999), 95% (Tulda et al., 2000), or 100% (Pradier et al., 2003; Samet et al., 2005). The efficacy of the program sessions was examined in the following ways: (a) the comparison of the mean difference in adherence levels from baseline to end of study (Goujard et al., 2003; Koenig et al., 2008; Rathbun et al., 2005; Rawlings et al., 2003; Smith et al., 2003); (b) the number of missed doses of medication during the previous 4, 7, and 28 days; and (c) the Morsky score concerning adherence perceptions and practice (Fairley et al., 2003; Levy et al., 2004). Characteristics of the Multicomponent Intervention The duration of the interventions ranged from a single session to multiple sessions delivered over the course of 1 year. The single-session program incorporated an education package, individualized counseling, and the use of adherence tools; it required about 2–3 hours per participant (Fairley et al., 2003; Levy et al., 2004). In cases of multisession interventions, initial sessions lasted as long as 1–3 hours, while the rest of the sessions lasted between 15–30 minutes and 1–2 hours. Some interventions were offered on a regular schedule, such as weekly (Rawlings et al., 2003), monthly (Smith et al., 2003), or bi-monthly (Pradier et al., 2003). All multicomponent interventions reviewed included individual education as a primary component. The component’s objective was to improve the participants’ fundamental knowledge about HIV infection and its treatment, the importance of therapy adherence, food restrictions, and adverseevent management strategies. Participants were prepared for problems they might encounter in real-life situations (Goujard et al., 2003; Koenig et al., 2008) and taught to manage their

Yang / Intervention for ART Adherence

medications as well as tackle issues such as delayed or missed medications, side effects, and changes in daily routine (Koenig et al., 2008; Pradier et al., 2003; Smith et al., 2003; Tuldra et al., 2000). Tailored interventions were also delivered for specific circumstances, such as homelessness, limited access to refrigeration, or nondisclosure of HIV status (Samet et al., 2005). As an additional component in some studies, a counseling approach focusing on the cognitive, emotional, social, and behavioral factors affecting medication adherence was combined with education. Trained nurses delivered the means and strategies for remembering dosage schedules. In addition, potential barriers affecting ability to regularly take medication, such as social stigma, availability of supportive significant others, and personal economic concerns were addressed in the sessions (Pradier et al., 2003). Monitoring nonadherence by using a calendar diary, setting one’s own goal of adherence, and using incentives for attaining goals were presented as part of skills development (Smith et al., 2003). In some studies, educational intervention was combined with a variety of aids designed to improve adherence to ART, such as computer-generated medication planners and short message services (Fairley et al., 2003; Levy et al., 2004) or planning cards with self-adhesive stickers and pill boxes (Goujard et al., 2003). For some studies, a phone number for an intervention specialist was provided in case additional questions arose between interviews (Tuldra et al., 2000), or a follow-up phone call was held with participants between intervention sessions (Koenig et al., 2008; Rathbun et al., 2005). Of the 11 studies reviewed, 3 interventions were delivered by study nurses only (Fairley et al., 2003; Pradier et al., 2003; Samet et al., 2005), 1 by nurses together with staff physicians (Goujard et al., 2003), 1 by a psychologist (Tuldra et al., 2000), 1 by a pharmacist (Rathbun et al., 2005), and 2 by nurses and pharmacists (Levy et al., 2004; Smith et al., 2003). The nurse involved in an intervention for individuals with alcohol problems was specifically trained in motivational interviewing to address substance abuse and HIV medication adherence (Samet et al., 2005). One study provided well-organized ways to minimize intervener effect by having written intervention scripts for each

5

session and a clinical supervisor to regularly review the delivery (Pradier et al., 2003). Control Groups Participants randomized to control groups received standard care for HIV infection. Standard care was defined as a consultation by one’s primary provider during regular medical visits. Some participants were exposed to a single additional assistance component in addition to standard care, such as a therapeutic planning card (Goujard et al., 2003) or counseling (Koenig et al., 2008; Rawlings et al., 2003; Smith et al., 2003).

Results Sample size and participant demographics varied across studies. The reported number of participants per study ranged from 17 to 367, and characteristics of participants varied widely. However, participants tended toward being male (63–100%), non-White (42–82%), unemployed (53–71%), men who have sex with men (22–91%), and injection drug users (15–60%); the mean age per study averaged between 37 and 43 years. Effect on Adherence Outcomes As shown in Table 1, when using a significance p level less than .05, seven studies (Fairley et al., 2003; Goujard et al., 2003; Knobel et al., 1999; Koenig et al., 2008; Levy et al., 2004; Pradier et al., 2003; Smith et al., 2003) demonstrated the multicomponent intervention as having a beneficial effect on ART adherence; four studies (Rathbun et al., 2005; Rawlings et al., 2003; Samet et al., 2005; Tuldra et al., 2000) failed to demonstrate an improved level of adherence resulting from the intervention. Of these four studies, two showed adherence improvements when using a 90% confidence interval (Rathbun et al., 2005; Tuldra et al., 2000), while another study analyzed only patients who had completed all procedures (known as an as-treated analysis; Tuldra et al., 2000). A number of intervention features were examined to identify recurring characteristics that might be linked to successful adherence outcomes.

Studies Using Multicomponent Intervention for Adherence to ART Results

Study Goujard et al. (2003) (France)

Fairley et al. (2003) (Australia)

Levy et al. (2004) (Australia)

Tuldra et al. (2000) (Spain)

Sample EX: n 5 188 UC: n 5 179 Male: 80%

Stepped wedge design Pre-intervention: n 5 43 Post-intervention: n 5 37 Male: 95–100% MSM: 90–91%

Stepped wedge design n 5 68 Male: 81–88% MSM: 38–58% IDU: 21–25%

EX : n 5 55 UC: n 5 61 Male: 75% MSM: 38% IDU: 38%

Intervention

Usual Care

Therapeutic plan Education program ning cards of 4 individual 1-hour sessions  Pill boxes and therapeutic planning cards provided over 12 months  Education program of 1 individual 2–3 hour session  Regimen analysis, computer-generated medication planner  Medication dosette box, medication alarm, SMS text message  Education program of 1 individual 2–3 hour session  Regimen analysis, computer-generated medication planner  Medication dosette box, medication alarm, SMS text message  Psycho-educational program  Medical management skills  Phone support  Follow-up visits

Delay in receiving the education program

Delay in receiving the education program

Outcome Measures Primary: changes in self-reported adherence score (14) Secondary: concordant changes in CD41 T cell and VL Primary: changes of number of selfreported missed doses over 5 months Secondary: Morisky Score (0–4)a Mean CD41 T cell Mean HIV RNA

Time Point/ RR$OR

EX

UC

p-Value

M0-M6 M0-M12 M0-M18

0.25 0.22 0.29

20.19 20.05 0.27

.020 .220 .750

M0-M6

56%

50%

NS

Last 4 days Last 7 days Last 28 days

Primary: Changes of Last 4 days Last 7 days number of selfLast 28 days reported missed doses over 5 months Secondary: Morisky Score (0–4)a Mean CD41 T cell Mean HIV RNA

Standard assessment Primary: % with and a follow-up visit $95% adherence at 48 weeks (selfreported; ITT) Secondary: % with RNA VL #400 copies/mL (ITT)

0.38 6 0.9 0.76 6 1.5 0.74 6 1.5 1.5 6 2.5 2.5 6 6.3 2.5 6 4.1

.030 .005 .960

2.9 6 0.9

3.3 6 0.8

.006

513 6 247 551 6 309 5,108 10,228

.800 .960

1.0 6 2.6 1.8 6 3.7 4.2 6 8.3

1.9 6 3.0 3.0 6 4.1 7.4 6 11.5

,.001 ,.001 ,.001

0.5 6 0.8

1.3 6 1.3

,.001

406 6 256 382 6 254 21,801 17,587

.701 .393

At 4 wks At 24 wks At 48 wks

67% 51% 58%

57% 39% 41%

NS NS .064

At 4 wks At 24 wks At 48 wks

22% 40% 58%

25% 28% 45%

NS NS .062

6 JANAC Vol. -, No. -, -/- 2013

Table 1.

Knobel et al. (1999) (Spain)

Samet et al. (2005) (USA)

Pradier et al. (2003) (France)

Rathbun et al. (2005) (USA)

EX: n 5 60 UC: n 5 110 Male: 73% IDU: 48–50%

 Individual advice  Supportive counseling

EX: n 5 74 UC: n 5 77 Male: 78–84% AA: 42–52% MSM: 22–25% IDU: 57–60%

 4 (15–60 min) education sessions over 3 months  2 home visits

Conventional dispensing of pills every 2 months

Verbal or written instructions

Usual clinical  3 individual educafollow-up every tion/counseling combination sessions 2–3 months at M0, M2, M4 (45–60 min/session)

EX: n 5 16 UC: n 5 17 Male: 85% MSM: 63–76% IDU: 6–19%

 Individual education sessions (Initial visit: 1–1.5 hour, follow-up: 30 minutes)  Visual aids and reminder devices  Additional visits/ phone follow-up through week 12

Standard care

Primary: % with 100% adherence Secondary: Mean difference RNA VL Difference CD41 T cell increase Primary: Mean adherence rate (measured by MEMS) Secondary: % with HIV-1 RNA ,400 copies/mL Median CD41 T cell increase

At 6 months RR: 1.45

76.7%

52.7%

.002

RR: 1.19

65.0%

54.5%

.180

At 6 months At 12 months

65% 71%

63% 62%

.860 .390

At 6 months At 12 months

63% 67%

62% 64%

1.000 .830

At 6 months At 12 months At 6 months At 12 months At 6 months OR: 2.5 M0-M6

479 512 2.0 2.7 75%

374 362 2.4 2.5 61%

NS NS .29 .44 .04

20.22 6 log 0.86

0.12 6 log 0.90

.002

37 + 157

43 + 142

.75

At 4 wks At 16 wks At 28 wks

86 6 27% 77 6 28% 74 6 31%

73 6 32% 56 6 39% 51 6 41%

.23 .08 .08

At 4 wks At 16 wks At 28 wks

63% 100% 94% 142

29% 71% 65% 97

NS .04 NS NS

M0-M6

(Continued )

Yang / Intervention for ART Adherence

EX: n 5 123 UC: n 5 121 Male: 87–91% Single: 64–70% IDU: 30–33% ART na€ıve: 28.5%

Primary: % with $90% adherence (self-reported) Secondary: % with detectable VL (,50 copies/mL) Primary: % with 100% in previous 3 days (selfreported) % with $95% in previous 30 days (self-reported) Secondary: CD41 T cell Log HIV RNA

7

(Continued ) Results

Study Rawlings et al. (2003) (USA)

Smith, et al. (2003) (USA)

Koenig et al. (2008) (USA)

Sample EX: n 5 96 UC: n 5 99 Male: 65% AA: 71% IDU: 20%

Intervention

Usual Care

 4 individual modules Routine counseling of education sessions per week  Routine counseling

EX: n 5 22 UC: n 5 21 Male: 91% MSM: 21–33% Non-White: 74% Unemployed: 53%



EX: n 5 110 UC: n 5 116 Male: 63% Black/nonHispanic: 82% Unemployed: 71%



 





Outcome Measures

Primary: Mean adherence rate (measured by MEMS) Secondary: Median change from baseline in CD41 T cell HIV RNA ,40 copies/mL HIV RNA ,400 copies/mL Primary: Mean Individual education a) education, b) adherence rate and medication self- assistance with (measured by management session scheduling of doses, MEMS) c) electronic 3 follow-ups Secondary: % with monitoring Monthly individual HIV RNA ,400 counseling copies/mL Primary: % with 3 sessions of assess- 2 adherence coun$90% adherence ment and education, seling sessions Secondary: Odds of occurring at weeks 2, achieving an 4, 8, and 1 session at undetectable VL 6 months Difference in CD41 5 total phone calls, T cell increase occurring at weeks 1, 6, 10, and at 4 months 2 group education sessions to occur at any time

Time Point/ RR$OR

EX

UC

p-Value

At 24 wks

70%

74%

..05

At 24 wks

78.3

104.8

.498

At 24 wks

60%

55%

.529

At 24 wks

80%

80%

.689

At 12 wks OR 5 7.8

96%

37%

.001

64%

38%

.22

40.2%

27.6%

.02

At 6 months OR 5 1.69 OR 5 1.65

.04

203.9

198.2

.73

Note. EX 5 experimental group; UC 5 usual care (control group); IDU 5 injecting drug user; VL 5 viral load; MSM 5 men who have sex with men; AA 5 African American; MEMS 5 medication event monitoring system; NS 5 not significant; ITT 5 intention to treat; M 5 month; wks 5 weeks; ART 5 antiretroviral therapy; RNA 5 ribonucleic acid. a. Higher score indicates low levels of adherence.

8 JANAC Vol. -, No. -, -/- 2013

Table 1.

Yang / Intervention for ART Adherence

Above all, interventions targeting improvement in the individual’s medication management skills were successful (Fairley et al., 2003; Goujard et al., 2003; Levy et al., 2004; Smith et al., 2003). Two studies showed that combining the strategies of individualized education, the use of adherence tool devices, and the development of ways to address common adherence barriers significantly decreased the number of missed doses and the patient’s Morisky score (Fairley et al., 2003; Levy et al., 2004). In the Smith et al. (2003) study, the medication self-management group was 7.8 times more likely to take 80% or more of their pill doses each week compared to the control group. The program consisted of medication counseling, written medication information, monthly visits for medication consultations, and the use of electronic monitors. The findings from Koenig et al. (2008) emphasized social support to help individuals overcome medication barriers. However, a study focused on participants with a past history of alcoholism was not successful at improving adherence through four education sessions and two home visits (Samet et al., 2005). That study’s authors discussed the fact that the treatment group did not receive the full intervention as designed. Effect on Virologic and Immunologic Outcomes The studies were not able to determine whether improved adherence extended to improved virologic or immunologic outcomes. Nine studies included both virologic and immunologic outcomes such as HIV RNA viral load and CD41 T cells, while two studies included virologic outcomes only (Knobel et al., 1999; Tuldra et al., 2000). Three studies found that the intervention produced a statistically significant effect associated with a decrease in RNA viral load (Koenig et al., 2008; Pradier et al., 2003; Rathbun et al., 2005). Of these three, one study reported statistically significant findings for only specific points in time over the course of 16 weeks rather than continuously throughout the intervention program (Rathbun et al., 2005). Similar to its reported adherence outcomes, the study by Tuldra et al. (2000) reported a significant finding when using only an as-treated analysis. For immunologic outcomes, all studies compared the differ-

9

ence in CD41 T cell counts from baseline between the intervention group and the control group and failed to demonstrate a beneficial effect on CD41 T cells from the intervention.

Discussion Given the fairly large number of intervention studies for HIV medication adherence, a relative few studies were selected for this review. Most studies were observational studies, which indicated that conducting a well-designed RCT of an HIV medication adherence program is a challenge. Each study provided different levels of description about the intervention. For example, Samet et al. (2005) provided an accurate description of the intervention implemented during each visit and session, which is encouraged in RCT reporting. Patients in the control group were also found to receive substantial care to maintain ART. The concept of standard care varies widely between studies, from only receiving planning cards to participating in three components of an intervention, one of which could be an education session. Overall, evidence from 7 of the 11 studies reviewed supported the efficacy of a multicomponent intervention that incorporated individual education with additional components to improve ART adherence when rigorously evaluated with a high standard (e.g., intention-to-treat analysis and p-value , .05). Seven studies concluded that individual-level interventions were successful, and those interventions directly targeting practical medication management skills demonstrated better outcomes when compared to cognitive behavioral or motivational approaches (Rueda et al., 2006). The researcher was unable to determine whether the advantages associated with adherence outcomes translated to improved virologic or immunologic outcomes. This finding may be partially attributable to participant selection because laboratory responses may be more difficult to demonstrate in people using ARV drugs at study baseline, or due to time factors, as virologic and immunologic responses may lag behind improved adherence. Studies of adequate power and duration are required to resolve this question.

10 JANAC Vol. -, No. -, -/- 2013

Some recommendations to improve the design of studies focused on multicomponent intervention arise from this review. For example, failure at improving adherence among individuals with a past history of alcoholism suggested the need to develop a different approach, such as teaching marginalized populations management skills for their drinking problems (Samet et al., 2005). Results showing poorer adherence for persons with depression suggested that individual psychological states and physical conditions also needed to be taken into consideration (Paterson et al., 2000). In other words, it may not be possible to develop a general multicomponent intervention that works for all populations with HIV. Within the studies reviewed, simple revisions may have resulted in a significant effect. In the study conducted by Rawlings et al. (2003), the use of devices such as pill boxes or therapeutic planning cards by the treatment group, in combination with education sessions, may have resulted in a significant effect because both groups received a certain amount of information through routine counseling. In seven studies, the treatment effect lasted as long as 6 months. The authors discussed that the result of no impact from the intervention at 12 months and 18 months was attributed to a diffusion or Hawthorne effect, leading to an improved adherence in the control group (Goujard et al., 2003). This could have resulted in different outcomes if participants were not allowed to receive education sessions after month 12; however, withholding knowledge from patients for a long period of time is an ethical issue. Thus, when evaluating the efficacy of an intervention as planned, the study needs to be carefully designed to minimize Type III error by enhancing the integrity of intervention implementation (Sidani & Braden, 1998). One study also discussed the loss of a fairly large number of patients due to their moving or changing hospitals (Tuldra et al., 2000), while another addressed the fact that 25% of the participants in the treatment group received either a partial intervention or none (Samet et al., 2005). More than 25% attrition in RCTs can cause an inaccurate treatment effect and decrease statistical power (Leon et al., 2006). Sustainable retention strategies such as monitoring participants’ intentions about attendance at each visit or offering

incentives to reduce attrition bias are needed. Using imputation strategies or mixed-effects models can be alternative statistical approaches as well (Leon et al., 2006). There were several limitations to this review. It was not possible to pool the features of interventions because of significant heterogeneity in the combinations of interventions and care given to control groups. Additionally, it was impossible to assess the clinical significance of the reported adherence outcomes from the literature, and some studies included unvalidated adherence measures (e.g., an ordinal score ranging from 1 to 4). Such concerns may be particularly important for future studies as the understanding of optimal adherence evolves.

Conclusion A systematic review of 11 RCTs was conducted in order to define the state of science for a multicomponent intervention aimed at improving ARV adherence among PLWH. The multicomponent intervention was defined as a package including an individual education session and one to three complementary aids. A conceptual model illustrating the individual, environmental, and social factors influencing ART for individuals was designed and presented for the review. The IMB model of ART adherence guided the review of each study’s program. The review concluded that seven studies presented evidence in favor of the feasibility and efficacy of a multicomponent intervention to increase ARV adherence based on using a significance of p , .05 and intention to treat. The multicomponent program focused on enhancing knowledge about and management skills of ARV medication in order to promote ART adherence among the participants. However, improved adherence did not extend to lowering the HIV RNA viral load and elevating CD41 T cell counts. Further studies need to include a focus on the evaluation of cost to implement multicomponent interventions. More reliable, valid, and objective methods to measure adherence, such as electronic monitoring, also should be considered, rather than relying on pill count or self-reported measures.

Yang / Intervention for ART Adherence

Key Considerations  Evidence was found to support the use of a combination of individual, structured education and one to three additional interventions to improve antiretroviral therapy (ART) adherence in individuals living with HIV.  Interventions targeting practical medication management skills demonstrated more enhanced ART adherence outcomes.  Whether improved adherence extended to improved virologic or immunologic outcomes has not been determined due to incongruent results across studies.

Disclosures The author does not have any actual or potential conflicts of interest relevant to the subject matter of the manuscript that have occurred over the previous 2 years, over the duration of the research being reported on, and/or that can reasonably be expected to occur in the foreseeable future.

Acknowledgments Dr. Cynthia M. Dougherty and Dr. Margaret M. Heitkemper, University of Washington School of Nursing, Biobehavioral Nursing and Health Systems, for their guidance, feedback, and encouragement on this paper. This paper would have not been completed without their support.

References Arnsten, J. H., Demas, P. A., Farzadegan, H., Grant, R. W., Gourevitch, M. N., Chang, C. J., . Schoenbaum, E. E. (2001). Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: Comparison of self-report and electronic monitoring. Clinical Infectious Disease, 33(8), 1417-1423. http://dx.doi.org/10.1086/323201 Duran, S., Spire, B., Raffi, F., Walter, V., Bouhour, D., Journot, V., . Moatti, J. P. (2001). Self-reported symptoms

11

after initiation of a protease inhibitor in HIV-infected patients and their impact on adherence to HAART. HIV Clinical Trials, 2, 38-45. http://dx.doi.org/10.1310/R8M7-EQ0MCNPW-39FC Fairley, C. K., Levy, R., Rayner, C. R., Allardice, K., Costello, K., Thomas, C., . Mijch, A. (2003). Randomized trial of an adherence programme for clients with HIV. International Journal of STD and AIDS, 14(12), 805-809. http:// dx.doi.org/10.1258/095646203322556129 Fisher, J. D., Fisher, W. A., Amico, K. R., & Harman, J. J. (2006). An information-motivation-behavioral skills model of adherence to antiretroviral therapy. Health Psychology, 25(4), 462-473. http://dx.doi.org/10.1037/0278-6133.25.4. 462 Funesti Esch, J., & Frank, S. V. (2001). HIV drug resistance and nursing practice. American Journal of Nursing, 101(6), 3035. quiz 36. Goujard, C., Bernard, N., Sohier, N., Peyramond, D., Lancon, F., Chwalow, J., . Delfraissy, J. F. (2003). Impact of a patient education program on adherence to HIV medication: A randomized clinical trial. Journal of Acquired Immune Deficiency Syndromes, 34(2), 191-194. Holzemer, W. L., Henry, S. B., Portillo, C. J., & Miramontes, H. (2000). The Client Adherence Profiling-Intervention Tailoring (CAP-IT) intervention for enhancing adherence to HIV/AIDS medications: A pilot study. Journal of the Association of Nurses in AIDS Care, 11(1), 36-44. http://dx.doi.org/ 10.1016/S1055-3290(06)60420-2 Howard, A. A., Arnsten, J. H., Lo, Y., Vlahov, D., Rich, J. D., Schuman, P., . Schoenbaum, E. E. (2002). A prospective study of adherence and viral load in a large multi-center cohort of HIV-infected women. AIDS, 16(16), 2175-2182. Knobel, H., Carmona, A., Lopez, J. L., Gimeno, J. L., Saballs, P., Gonzalez, A., . Diez, A. (1999). Adherence to very active antiretroviral treatment: Impact of individualized assessment. Enfermedades Infecciosas y Microbiologia Clinica, 17(2), 78-81. Koenig, L. J., Pals, S. L., Bush, T., Pratt Palmore, M., Stratford, D., & Ellerbrock, T. V. (2008). Randomized controlled trial of an intervention to prevent adherence failure among HIV-infected patients initiating antiretroviral therapy. Health Psychology, 27(2), 159-169. http://dx.doi.org/10. 1037/0278-6133.27.2.159 Leon, A. C., Mallinckrodt, C. H., Chuang-Stein, C., Archibald, D. G., Archer, G. E., & Chartier, K. (2006). Attrition in randomized controlled clinical trials: Methodological issues in psychopharmacology. Biological Psychiatry, 59(11), 1001-1005. http://dx.doi.org/10.1016/j. biopsych.2005.10.020 Levy, R. W., Rayner, C. R., Fairley, C. K., Kong, D. C., Mijch, A., Costello, K., & McArthur, C. (2004). Multidisciplinary HIV adherence intervention: A randomized study. AIDS Patient Care STDS, 18(12), 728-735. http:// dx.doi.org/10.1089/apc.2004.18.728 Lucas, G. M. (2005). Antiretroviral adherence, drug resistance, viral fitness and HIV disease progression: A tangled web is

12 JANAC Vol. -, No. -, -/- 2013 woven. Journal of Antimicrobial Chemotherapy, 55(4), 413416. http://dx.doi.org/10.1093/jac/dki042 Mellins, C. A., Havens, J. F., McCaskill, E. O., Leu, C. S., Brudney, K., & Chesney, M. A. (2002). Mental health, substance abuse and disclosure are significantly associated with the medical treatment of HIV-infected mothers. Psychology, Health and Medicine, 7, 451-460. http:// dx.doi.org/10.1080/1354850021000015267 Miller, L. G., Golin, C. E., Hays, R. D., Liu, H., Beck, C. K., Kaplan, A. H., & Wenger, N. S. (2002). Impact of antiretroviral regimen switches on adherence. HIV Clinical Trials, 3(5), 355-360. http://dx.doi.org/10.1310/NNK4-GAGD5C1Y-K9QT Murphy, D. A., Lu, M. C., Martin, D., Hoffman, D., & Marelich, W. D. (2002). Results of a pilot intervention trial to improve antiretroviral adherence among HIVpositive patients. Journal of the Association of Nurses in AIDS Care, 13(6), 57-69. http://dx.doi.org/10.1177/ 1055329002238026 Paterson, D. L., Swindells, S., Mohr, J., Brester, M., Vergis, E. N., Squier, C., . Singh, N. (2000). Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Annals of Internal Medicine, 133(1), 21-30. http://dx.doi.org/10.7326/0003-4819-133-1-20000 7040-00004 Pradier, C., Bentz, L., Spire, B., Tourette-Turgis, C., Morin, M., Souville, M., . Moatti, J. P. (2003). Efficacy of an educational and counseling intervention on adherence to highly active antiretroviral therapy: French prospective controlled study. HIV Clinical Trials, 4(2), 121-131. http://dx.doi.org/ 10.1310/BRBV-3941-H1PP-NDRY Rathbun, R. C., Farmer, K. C., Stephens, J. R., & Lockhart, S. M. (2005). Impact of an adherence clinic on behavioral outcomes and virologic response in treatment of HIV infection: A prospective, randomized, controlled pilot study. Clinical Therapeutics, 27(2), 199-209. http:// dx.doi.org/10.1016/j.clinthera.2005.02.010 Rawlings, M. K., Thompson, M. A., Farthing, C. F., Brown, L. S., Racine, J., Scott, R. C., . Shaefer, M. S. (2003). Impact of an educational program on efficacy and adherence with a twice-daily lamivudine/zidovudine/abacavir regimen in underrepresented HIV-infected patients. Journal of Acquired Immune Deficiency Syndromes, 34(2), 174-183. Rueda, S., Park-Wyllie, L. Y., Bayoumi, A. M., Tynan, A. M., Antoniou, T. A., Rourke, S. B., & Glazier, R. H. (2006). Patient support and education for promoting adherence to highly active antiretroviral therapy for HIV/AIDS. Cochrane Database Systematic Reviews, 3, CD001442. http:// dx.doi.org/10.1002/14651858.CD001442.pub2 Samet, J. H., Horton, N. J., Meli, S., Dukes, K., Tripps, T., Sullivan, L., & Freedberg, K. A. (2005). A randomized controlled trial to enhance antiretroviral therapy adherence in patients with a history of alcohol problems. Antiviral Therapy, 10(1), 83-93. Sidani, S., & Braden, C. J. (1998). Evaluating nursing interventions: A theory-driven approach. Thousand Oaks, CA: Sage.

Smith, S. R., Rublein, J. C., Marcus, C., Brock, T. P., & Chesney, M. A. (2003). A medication self-management program to improve adherence to HIV therapy regimens. Patient Education and Counseling, 50(2), 187-199. http:// dx.doi.org/10.1016/S0738-3991(02)00127-1 Tuldra, A., Fumaz, C. R., Ferrer, M. J., Bayes, R., Arno, A., Balague, M., . Clotet, B. (2000). Prospective randomized two-arm controlled study to determine the efficacy of a specific intervention to improve long-term adherence to highly active antiretroviral therapy. Journal of Acquired Immune Deficiency Syndromes, 25(3), 221-228. Wainberg, M. A., & Friedland, G. (1998). Public health implications of antiretroviral therapy and HIV drug resistance. Journal of the American Medical Association, 279(24), 1977-1983. http://dx.doi.org/10.1001/jama.279.24.1977 Williams, A. B. (2001). Adherence to HIV regimens: 10 vital lessons. American Journal of Nursing, 101(6), 37-43. quiz 44. Wise, J., & Operario, D. (2008). Use of electronic reminder devices to improve adherence to antiretroviral therapy: A systematic review. AIDS Patient Care STDS, 22(6), 495504. http://dx.doi.org/10.1089/apc.2007.0180