Two strategies to increase adherence to HIV antiretroviral medication: Life-Steps and medication monitoring
Introduction
Since the advent of highly active antiretroviral therapy (HAART) for HIV, significant numbers of HIV-positive individuals have had prolonged and healthier lives, such that HAART has been defined as the standard of care (Carpenter et al., 1997). HAART, which typically involves a combination of one protease inhibitor and two nucleoside reverse transcriptase inhibitors, leads to reductions in viral load, greater immune system function, and less likelihood of clinical immune deficiency in patients with HIV infection (see Carpenter et al., 1997; Deeks, Smith, Holodniy & Kahn, 1997; Flexner, 1998, Goebel, 1995; Kelley, Otto-Salaj, Sikkema, Pinkerton & Bloom, 1998).
Despite these advances, HAART is not without problems. Almost perfect adherence to HIV medications is critical for successful treatment, particularly for prevention of viral replication (see Katzenstein, 1997, Carpenter et al., 1997, Deeks et al., 1997, Descamps et al., 2000). Partial adherence is not sufficient, with evidence of dramatic differences in viral suppression at levels of medication adherence that would be acceptable for a variety of other medical conditions. For example, Patterson et al. (1999) found that 81% of HIV positive individuals with greater than 95% adherence showed complete viral suppression, whereas only 64% of those with 90–95%, 50% of those with 80–90%, and 30% of those with less than 80% adherence showed viral suppression.
Typical predictors of poor adherence in chronic illnesses are longer illnesses, less severe or noticeable symptoms, complex treatment regimens, large numbers of medications or high frequency of dosing, a poor doctor–patient relationships, and substance use, depression, and patient beliefs (e.g. Becker, 1985, Chesney & Ickovicks, 1997, Griffith, 1990, Haynes, 1979, Ickovics & Meisler, 1997). Many of these features are present in individuals being treated for HIV (e.g. Chesney & Ickovicks, 1997, Kalichman, 1998; Safren, Otto & Worth, 1999).
HAART medications may require different dosing schedules (some at 12, 8, 6 or 4 h intervals), different food intake patterns (some should be taken on an empty stomach, others need to be taken with meals, some with fatty foods, some with non-fatty foods) and different storage requirements (some need to be refrigerated). Many of these medications cause side effects which necessitate further medication, and still other interventions may be required to treat secondary opportunistic infections (see Kelley et al., 1998). Patients on HAART are therefore required to adhere to a complex and frequently confusing combination of medications throughout an indefinite course of treatment.
HAART also requires patients to take pills for long periods of time, frequently in the absence of symptoms. Indeed, because of emergent side-effects, HAART medication may induce symptoms in HIV patients who may otherwise be relatively symptom free. Moreover, in the context of successful treatment, patients appear to face an especially difficult challenge remaining adherent. Clearly, strategies are needed to enhance adherence to HAART regimens for patients with HIV.
The present study had two major goals. First, we sought to examine psychosocial predictors of HIV medication adherence. Second we sought to evaluate two minimal-intervention approaches to increasing adherence to HIV-medication regimens in persons with less than perfect adherence. Specifically, we compared a single-session cognitive-behavioral intervention (Life-Steps; Safren et al., 1999) to a self-monitoring condition alone. The cognitive-behavioral intervention was based on a converging set of evidence that brief, cognitive-behavioral, problem-focused interventions were useful to improving medical adherence for problems ranging from diabetes (Kirkman et al., 1994, Mendez & Beledez, 1997) and asthma (Bailey et al., 1990) to psychiatric out-patient aftercare (Spooren, Van Heeringen & Jannes, 1998). Likewise, self-monitoring has received support as a minimal-intervention strategy for a variety of behavioral modification efforts (see Gambrill, 1977), and is typically used as an adherence intervention in clinical trials of medications. In the present study we conducted a randomized clinical trial to evaluate these minimal-intervention strategies, and examined potential predictors of adherence in a sample of HIV-positive individuals with documented difficulties adhering to their HIV medications.
Section snippets
Participants and setting
The study setting was a community health center which primarily serves a lesbian, gay, bisexual, and transgendered community, as well as persons infected with HIV. There were two parts to the present project: prediction of concurrent adherence, and a pilot efficacy study of two interventions in patients taking medications with less-than-perfect medication adherence. Participants in the predictors study were 76 men and 8 women with HIV who were considered at risk for adherence problems because
Psychosocial correlates of baseline adherence
Associations, as assessed by Pearson correlation coefficients, between psychosocial predictor variables and baseline adherence are presented in Table 2. For these analyses, the adherence outcome measure was percent of pills taken for the past 2 weeks using the adherence questionnaire. Four of the six correlations were significant beyond the 0.01 level and these were in the moderate (0.30–0.40) range (see Table 2). As expected, depression and punishment beliefs about HIV infection were
Discussion
Baseline adherence was significantly associated with depression, satisfaction with social support, punishment beliefs about HIV infection, and self adherence self-efficacy. Contrary to our hypothesis, baseline adherence was not associated with self-reported frequency of alcohol or other substance use. Of these variables, baseline depression scores offered non-reduction prediction of adherence scores. Greater depressed mood was associated with poorer adherence, accounting for a total of 13% of
Acknowledgements
This study was supported from a grant issued through Community Research Institute of Boston by the Massachusetts Department of Public Health to Fenway Community Health. Portions of these data were presented at the 1999 meeting of the Association for the Advancement of Behavior Therapy, Toronto, Canada, and at the 7th Conference on Retroviruses and Opportunistic Infections, 2000, San-Francisco, CA. The authors would like to thank Dr Rhonda Linde, Ms Phyllis Dixon, Ms Meredith Gard, Ms Amy
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