The Influence of Social Support on Smoking Cessation Treatment Adherence Among HIV+ Smokers

Abstract

Introduction:

The high prevalence of smoking among people living with HIV is a significant problem. Nonadherence to smoking cessation pharmacotherapy is a barrier for successfully quitting. The current study investigated the extent to which social support variables impact adherence and cessation.

Methods:

Participants were 444 HIV+ smokers who provided data on nicotine patch adherence, social support, and smoking. We conducted a path analysis to estimate (1) the effects of six social support indicators at baseline on nicotine patch adherence; (2) the effect of patch adherence on 7-day point prevalence smoking at 6-month follow-up; and (3) the indirect effects of social support indicators on 7-day point prevalence smoking at 6-month follow-up via patch adherence.

Results:

The tested model demonstrated good fit as indicated by the comparative fit index, root mean square error of approximation, and weighted root mean square residual (0.94, 0.02, and 0.51, respectively). Path analysis results indicated greater social support network contact was associated with higher levels of nicotine patch adherence (β = .13, P = .02), greater patch adherence was associated with a lower probability of 7-day point prevalence smoking at 6-month follow-up (β = −.47, P < .001) and greater social support network contact (β = −.06, P = .03) had a significant indirect effect on 7-day point prevalence smoking at 6-month follow-up via patch adherence.

Conclusions:

Findings have implications for smoking cessation interventions that seek to capitalize on the beneficial effects of social support. Such efforts should account for the role that frequency of contact may have on nicotine patch use and other treatment-related mechanisms.

Introduction

In the past 25 years, highly active antiretroviral therapies (HAART) have transformed the treatment of HIV/AIDS in the United States. In fact, HAART’s effectiveness in slowing the progression of HIV has led to a shift in the US public perception of the disease. Experts in the field have noted that the perception of HIV has gone from a “death sentence” in the 1980’s towards a growing view of the disease as a chronic and manageable condition. ¹ HIV clinical research has also been transformed by the effectiveness of HAART. In addition to the continued advances made in the pharmacological realm, there has also been a greater emphasis on improving the quality of life of people living with HIV (PLWH) and addressing comorbid conditions and psychosocial problems. ^{2 , 3}

As compared with the general population, PLWH are known to be under greater economic and psychological stress and have higher rates of substance use and other psychiatric conditions. ^{4 , 5} Not surprisingly, addressing these comorbid conditions and problems is now an integral part of the treatment of PLWH. One area that is gaining greater research and clinical attention is the implementation of tobacco cessation interventions to address the high level of tobacco use among PLWH. ⁶ Estimates of smoking prevalence among PLWH range as high as 70% which is 2–3 times greater than the prevalence rate (20%–25%) among the non-HIV population. ^7–9 The health consequences of tobacco use in the general population are well known and it has been implicated in a variety of diseases including lung cancer, pneumonia, bronchitis, and cardiovascular diseases. ¹⁰ Among PLWH, tobacco use is associated with a greater incidence and progression of tobacco-related diseases as well as an increased risk for developing HIV-related peripheral artery disease, cardio-metabolic syndrome and renal disease; all of which are significant causes of mortality among PLWH. ^11–15 Furthermore, smoking among PLWH is associated with a higher incidence of periodontal disease, oral candidiasis, and oral hairy leukoplakia. ^16–22

Despite the availability of efficacious treatments for smoking cessation, ²³ smoking prevalence remains high among PLWH and there is a limited amount of research focusing on smoking cessation with PLWH. ^{6 , 24} Lloyd-Richardson and colleagues ²⁵ tested a motivational enhancement behavioral intervention against a brief standard care intervention with both arms of the trial receiving 8 weeks of nicotine replacement therapy (NRT) patches. Findings from this study showed that there were no significant difference between groups on 7-day point prevalence rates of biochemically verified smoking at 2-, 4- and 6-month follow-up. Lloyd-Richardson and colleagues also found that at the 6-month follow-up, only 60% of participants reported using any nicotine patches. This level of NRT use is well below the level typically seen in smoking cessation trials ²⁶ and may point to a likely mechanism underlying the poor smoking cessation treatment success rate; that is, poor adherence to smoking cessation treatment which is known to impede cessation in the general population. ²⁷

Humfleet and colleagues ²⁸ also noted low rates of NRT patch use in their RCT that tested three smoking cessation treatments among PLWH. Findings from this study showed no statistically significant difference among the three treatment groups [(1) individual counseling + NRT; (2) computer based counseling + NRT; and (3) self-help + NRT] on biochemically verified 7-day smoking point prevalence at follow-up. All 209 participants in the three conditions were offered 10 weeks (70 daily patches) of NRT patches which they used at a fairly low rate ranging from a mean of 44.7 patches in the computer-based counseling condition to a mean of 51.5 patches in the individual counseling condition.

Vidrine, Gritz, and colleagues ^{29 , 30} showed very promising smoking cessation treatment outcomes among HIV+ smokers. At 3-month follow-up the cell phone delivered intervention group was found to have significantly higher quit rates as compared to standard care treatment. However, the effect diminished by the 6- and 12-month follow-up assessments. Moreover, NRT was not directly provided to participants and thus, rates of NRT use were not reported. However, Vidrine, Gritz and colleagues ³⁰ note that NRT adherence was a significant problem in their sample and an important area for future research.

Moadel and colleagues ³¹ tested a group counseling intervention versus standard care among 145 PLWH that were smokers. The group counseling intervention showed a 19.2% quit rate at 3-month follow-up which was significantly higher than that of the standard care condition (9.7%). Data on adherence to smoking cessation pharmacotherapy was not collected in this trial and both the control and randomization of pharmacotherapy were not a part of the study design. Lastly, in the most recent smoking cessation trial of PLWH, Shuter and colleagues ³² tested a web-based intervention against standard care among 138 PLWH and found a greater odd of cessation at 3-month follow-up among participants randomized to the web-based intervention. Most strikingly, all participants were offered a prescription for 3 months of NRT and only 55% accepted the prescription and of those, only 31.9% reported using any of the patches during the 12 weeks of treatment. Undoubtedly, the development and testing of smoking cessation interventions for PLWH has advanced. However, adherence to pharmacotherapy, particularly NRT, continues to be a significant barrier.

Social Support and Smoking Cessation

Given the noted challenges of achieving optimal adherence to smoking cessation interventions among PLWH, adherence to smoking cessation treatments may be an important target for improving cessation rates. There has been a considerable amount of research focused on adherence to HAART among PLWH which can undoubtedly inform the topic of adherence to smoking cessation treatment. Social support has also emerged as a key factor in the area of general medication adherence among PLWH. ^33–35 Broadly delineated, social support can be thought of as having two domains—structural and functional. ³⁶ The structural domain refers to the individual’s number and patterns of social ties. Functional support refers to the type of resources an individual receives from social ties. Findings have supported the notion that a greater level of social support is beneficial to adherence due to the fact that individuals with greater support have access to “tangible” social resources that can impact medication adherence. ³⁷ Such tangible resources include medication reminders as well as assistance with refilling prescriptions and attending medical visits. ^{33 , 34 , 37} In addition, social support is more generally known to positively impact overall mental health and well-being, ³⁸ which can influence crucial cognitive factors related to treatment adherence such as motivation and self-efficacy. ³⁹

A number of studies have demonstrated the beneficial effects of social support on smoking cessation treatment. ^40–44 This has been an area of considerable emphasis within the field of smoking cessation due to the fact that social support is a domain that is particularly amenable to a variety of enhancement approaches. For example, studies have aimed to enhance social support through treatments involving romantic partner dyads, ⁴² supportive peers, ^{43 , 44} group interventions, ⁴² and web-based interventions with peer support. ⁴¹ Overall, such treatments have demonstrated efficacy and social support is regarded as a well-established treatment element associated with greater rates of cessation. ⁴⁰

Given the known association between social support domains and smoking cessation, the current study aims to investigate the (1) effects of social support domains on adherence to NRT and smoking cessation treatment outcome, and (2) examine if the adherence to NRT mediates the effects of social support domains on smoking cessation outcomes. The current investigation will examine data from the Lloyd-Richardson and colleagues’ trial ²⁵ in order to test a hypothesized path model where social support domains predict NRT use, which in turn predicts smoking cessation treatment outcome.

Method

Participants

Data for this investigation were drawn from a larger RCT ²⁵ involving 444 HIV-positive smokers recruited from eight immunology clinics in the Northeastern United States. Participants were recruited from six outpatient HIV clinics and two primary care clinics in Massachusetts and Rhode Island. Recruitment consisted of study physicians identifying potential participants in their clinical caseload and referring them to the study. Participants were eligible if they were: (1) seropositive for HIV, (2) 18+ years of age, (3) currently smoking (≥5 cigarettes/d for the past 3 months), (4) English or Spanish speaking, and (5) available through the 6-month study period. Participants were not required to quit smoking or to use the nicotine patch. Exclusion criteria consisted of: (1) suffering from any unstable medical condition precluding use of the nicotine patch (eg, uncontrolled hypertension) or an active skin condition (eg, psoriasis, eczema), (2) currently using smokeless tobacco, NRT or involvement in other smoking cessation treatment, and (3) pregnant or nursing.

Participants that were eligible and willing to participate met with a study research assistant to provide informed consent and complete a battery of assessments at baseline.

Participants were then randomized (block randomization stratified by gender and motivation to quit) to one of two treatment conditions, (1) Standard Care counseling plus NRT (SC) or (2) motivationally enhanced treatment plus nicotine replacement (motivational enhancement) (treatments described further below). Follow-up assessments occurred at baseline, 2, 4, and 6 months and participants were given monetary compensation (gift cards ranging in value from $20–$50) for attending study visits. In total 599 participants were screened, and 155 were deemed ineligible to participate. Four-hundred forty-four participants were randomized to either the Standard Care condition ( n = 232) or the motivational enhancement condition ( n = 212). A total of 318 participants returned for the 6-month follow-up assessment (72% in both groups). A complete description of this clinical trial including the full CONSORT flow diagram appears in Lloyd-Richardson and colleagues. ²⁵ The study was approved by the participating hospitals and clinics.

Measures

Smoking Status

Our primary outcome variable was smoking at the 6-month follow-up. This variable was operationalized as any self-reported tobacco use in the past 7 days (even one puff) verified using a 24-hour biochemical measure of smoking via carbon monoxide exhalation testing with less than 10 parts per million (ppm) considered nonsmoking. ^{45 , 46} Carbon monoxide testing was measured using standard and calibrated monitors.

Social Support

Six social support domains were measured using a modified version of the Important People and Activities Instrument. ^{47 , 48} The IPA was originally designed to assess the relationship of social support and social network variables to alcohol use. ⁴⁷ The measure can be modified so that alcohol use is replaced with smoking. ⁴⁸ The IPA asks participants to name up to 10 important people in their lives. For each named individual, participants use a six-point scale (ranging from “ extremely supportive ” to “ not at all ”) to rate each named individual on their level of general supportiveness and quitting support (ie, “How would/does this person feel about you quitting smoking?”). Respondents are also asked to use a seven point scale (ranging from “ once in the last 6 months ” to “ daily ”) to assess the frequency of contact with each member in the social network. The IPA asks respondents to also rate the “importance” of each individual in the social network on a 6-point Likert scale ranging from “ extremely important ” to “ not at all important ”. Lastly, respondents also rated the overall reaction to smoking by each member of the social network using the following scale ( 1 = left/made you leave ; 2 = didn’t accept ; 3 = neutral ; 4 = accepts ; 5 = encourages ).

With the exception of the reaction to smoking variable, all of the IPA variables were coded so that a higher value represented a greater level of support, frequency, and importance. Since the “encouragement to smoke” is not necessarily indicative of support, the reaction to smoking variable was not recoded and the response scale described above was used. Data from the IPA were used to derive the following variables used in the analyses: network size (a count of the number of individuals named); mean level of contact, mean level of general support from all social network members; mean level of quitting support from all social network members; mean level of “importance” of all network members, mean reaction to smoking by all members of the social network.

Nicotine Patch Adherence

Nicotine patch adherence was measured using retrospective self-reports of NRT patch collected at each follow-up visit. Participants were prompted to recall the number of days that they used the dispensed NRT patches during the corresponding follow-up interval. Responses for all the follow-up time points were combined and corroborated resulting in a variable that characterized each participant’s maximum number of patches used throughout the active treatment phase of participation. This variable was further collapsed into a nine-item scale, which corresponds to the 8 weeks of NRT patches dispensed (0 = no patches used; 1= 7 days of patch use; 2 = 8–14 days; 3 = 15–21 days; 4 = 22–28 days; 5 = 29–35 days; 6 = 36–42 days; 7 = 43–49 days; 8 = 50–56; and 9 = greater than 56 days of patches use).

Several variables were used as a covariates in the analytic models including nicotine dependence which was measured using the Fagerström Test for Nicotine Dependence. ⁴⁹ The Fagerström Test for Nicotine Dependence is a reliable and well-validated six-item measure of nicotine dependence that is scored on a 10-point scale, with higher scores indicating greater levels of dependence. Lastly, participants completed a self-reported sociodemographic questionnaire. Variables such as age, gender, employment, and marital status (married and/or “living with a partner” vs. not) were obtained using this questionnaire.

Analytic Plan

The current study used a path analysis ( Figure 1 ) to estimate the following parameters: (1) effects of the six social support indicators at baseline on nicotine patch adherence at 2-month follow-up, (2) the effect of nicotine patch adherence at 2-month follow-up on 7-day point prevalence smoking at 6-month follow-up, and (3) the indirect effects of social support indicators on 7-day point prevalence smoking at 6-month follow-up via nicotine patch adherence. All of the predictors were included in one model to minimize Type I error risk.

Figure 1.

Conceptual model guiding the present study.

The model was estimated using mean and variance adjusted weighted least squares because it produces standard fit indices for models with categorical outcomes and probit regression coefficients. ⁵⁰ Probit regression assumes that the probability of the dependent-variable event occurring is normally distributed; therefore, a standardized probit regression coefficient is comparable to a standardized linear regression coefficient (with the exception that the outcome is the probability of an event occurring). The model was evaluated using four model fit indices ^{51 , 52} : (1) chi-square test of model fit (χ ² ) > .05, (2) comparative fit index ≥ .90, (3) root mean square error of approximation ≤ .05, and (4) weighted root mean square residual ≤ 1.0. All effects associated with the smoking outcome controlled for nicotine dependence, age, gender, treatment group, marital status, and employment status.

To examine if gender influenced the direction and/or strength of the associations tested we conducted a moderation analysis using PROCESS v2.10. ⁵³ The moderation analysis controlled for all demographic variables used in the path analysis.

Results

Preliminary Analysis

Table 1 presents the frequencies, means and standard deviations for all the variables used in the study. The sample was primarily male ( n = 281, 63%) and the mean age was 42.5 ( SD = 7.67). A total of 349 individuals (78%) were unemployed and 101 (22.7) were either married or lived with a significant other. The mean level of nicotine dependence was 6.72 ( SD = 1.95) which falls within the “moderate dependence” range. At 6-month follow-up a total of 405 individuals (91.3%) did not smoke and the mean number of patches was 3.93 which corresponds to approximately 22 days of patches used. The mean social network size (number of individuals in the network) was 6.41 and the mean level of importance of social network members (4.80) was in the moderate range; the reaction to smoking was within the neutral range (3.14), the mean level of quitting support was within the “supportive” range (5.33); general social support was within the “very” supportive range (4.70); and mean level of contact with social support network members was 5.34 which falls within the “once or twice a week range.

Table 1.

Descriptive Statistics for Study Variables

Variable	n (%)
Smoking status (biochemically verified)
Not smoking at 6-month follow-up	39 (8.6)
Gender
Female	163 (36.0)
Partner status
Married or living with partner	101 (22.7)
Employment status
Employed full-time	60 (13.5)
Employed part-time	34 (7.7)
Unemployed	349 (78.4)
Treatment group
Motivational enhancement	232 (51.2)

Variable	M (SD )
Age	42.45 (7.67)
Nicotine dependence	6.72 (1.95)
Nicotine patch adherence	3.93 (3.51)
Number of Members in SS network	6.41 (3.15)
Importance of all SS members	4.80 (.75)
Reaction to smoking	3.14 (.68)
SS from all network members	4.70 (.87)
SS frequency	5.34 (.98)

SS = social support.

Table 2 shows the bivariate correlations of the variables used in the path analysis. Results indicate that 7-day point prevalence smoking at follow-up had statistically significant correlations with nicotine patch adherence ( r = −.26, P = .01) and nicotine dependence ( r = .14, P = .01). Also male gender was significantly associated with greater nicotine dependence ( r = .13, P = .01) as expected.

Table 2.

Bivariate Correlations of Variables Used in Path Analysis ( n = 444)

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13
1. Smoking status	1
2. Age	−0.7	1
3. Gender	0.06	−0.16**	1
4. Partner status	0.06	−0.16**	0.03	1
5. Employment status	0.03	0.17**	0.16**	−0.17**	1
6. Treatment group	−0.04	−0.11*	0.1*	−0.01	0.02	1
7. Nicotine dependence	0.14**	−0.07	0.13**	−0.04	0.08	−0.02	1
8. Nicotine patch adherence	−0.26**	0.06	−0.01	−0.04	0.07	0.01	−0.06	1
9. Number of members in SS network	0.00	0.01	0.06	0.06	−0.08	0.02	−0.02	0.16**	1
10. Importance of all SS members	0.06	−0.08	0.17**	0.09	−0.03	−0.01	0.13*	0.12*	−0.1	1
11. Reaction to smoking	0.02	−0.09	−0.03	0.001	0.03	−0.02	0.03	−0.1	0.02	−0.1	1
12. SS from all network members	−0.07	−0.01	0.01	0.004	−0.01	−0.03	0.08	0.06	−0.12*	0.15**	−0.13**	0.28**	1
13. SS frequency	−0.09	−0.07	0.12*	0.02	0.08	−0.02	0.04	0.07	−0.14**	0.13*	−0.19**	0.23**	0.59**

SS = social support.

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

Path Analysis

Chi-square test of model fit was not statistically significant, suggesting that the model did fit the data, χ ² ( n = 374, df = 6) = 7.29, P > .05. The comparative fit index, root mean square error of approximation, and weighted root mean square residual (0.94, 0.02, and 0.51, respectively) all indicated adequate model fit.

Highlighted below are the direct effects that were statistically significant. Higher scores of social support frequency were associated with higher nicotine patch adherence (β = .13, P = .02), greater nicotine patch adherence was associated with a lower probability of 7-day point prevalence smoking (β = −.47, P < .001), and higher scores of nicotine dependence were associated with a higher probability of 7-day point prevalence smoking (β = .25, P = .02). The other covariates in the model were not found to be significant.

Indirect Effects

Mediation analyses with 100 000 bootstrap iteration indicated that social support contact frequency (β = −.06, P = .03) had a statistically significant indirect effect on 7-day point prevalence smoking via nicotine patch adherence.

Moderation Analysis

A moderation analysis with 100 000 bootstrap iteration indicated that gender did not have a statistically significant interaction with any of the direct or indirect effects.

Moderated Mediation Analysis

A post hoc moderated mediation analysis was also conducted using PROCESS v2.10 (Hayes, 2013) to examine if the number of members in the social support network moderated the effects between (1) social support frequency and nicotine patch adherence and (2) nicotine patch adherence and 7-day point prevalence smoking. This analysis controlled for age, nicotine dependence, gender, treatment group, marital status, employment status, mean level of social support from network members, mean level of reaction to smoking, and mean level of quitting support. Findings from this analysis indicated that the number of members in the social support network did not moderate either of the two associations.

Discussion

The findings of the current study illustrate the complex and nuanced relationship between social support and adherence to NRT among PLWH. The extent to which our participants utilized the 8 weeks of NRT patches in our study is worth noting. The mean number of days of patch use was approximately 22 out of 56 days. This is a relatively low amount ²⁶ which highlights the continued need for developing interventions that can address this problem.

Unexpectedly, only one of the social support domains—social support contact frequency, was found to be associated with adherence and to fit the path model. The post hoc analyses were conducted in order to account for the potential interaction of decreasing social support contact frequency levels with increasing social network sizes. As noted, the results of the post hoc analyses were statistically insignificant and thus, this possible explanation for our findings was not well supported.

PLWH are a unique subpopulation of smokers and the interpretation of our study findings require a cautious and thoughtful consideration of the unique characteristics of PLWH as well as the psychosocial contextual factors that may contribute to findings. In interpreting our findings we note that PLWH are known to be under greater economic and psychosocial stress and have higher rates of substance use and other psychiatric conditions. ^{4 , 5} Therefore, we speculate that social support domains may have a more distinct function among PLWH as compared to the non-HIV population. ⁴⁰ Most notably, the challenging economic and psycho-social circumstances of PLWH may increase the critical nature of tangible and emotional support. Under such conditions, individuals in the social network may be relied upon for basic needs as well as for emotional support relevant to PLWH. Thus, the beneficial effects of social support found among non-HIV smokers, ⁴⁰ may be differentially expressed among PLWH due to the high levels of psychosocial stressors overtaxing coping resources. Further research is needed in order to explore the unique mechanisms underlying stress buffering, smoking and quitting among PLWHV.

As noted in the review of the literature, social support is a highly complex construct often conceptualized as having two general domains—structural and functional. ⁵⁴ Based on this, we are sensitive to the fact that asking participants to rate the frequency of contact with social support members is relatively ambiguous with respect to this conceptual dichotomy. That is, frequency of contact certainly characterizes the structural domain of social support. However, frequency of contact also inherently mediates functional domains given the fact that functional support is most often provided in the context of contact and communication. Unfortunately, the current study did not collect data that would allow for an exploration of specific functional elements that occur during contacts with social support network members. Future research seeking to expand this work may consider utilizing electronic momentary assessment data collection methods which can potentially capture such data in a more “real-time” fashion.

There are potential implications for our findings with respect to the design of interventions targeting smokers who are PLWH. Interventions may be designed with an added aim of enhancing the frequency of contact with social network members. Group interventions in particular may offer both a mode of intervention delivery as well as an opportunity for greater social contact, support and interaction. As noted in the review of the literature, Moadel and colleagues ³¹ utilized a group format intervention which outperformed the standard care condition on smoking rates at 3-month follow-up. Considering this finding, as well as our current findings, the development and testing of group interventions may prove to be a fruitful area for continued research. Moreover, our sample descriptives indicated that the social support and network characteristics of our participants were generally in the range of what is considered supportive as well as adequate in terms of frequency of contact and size. This provides further support for the feasibility of developing interventions that aim to capitalize on existing social ties. Future research in this area must consider addressing design limitations of the Moedel study including adequate control of pharmacotherapies and a more expanded follow-up assessment schedule (ie, 6, 12 and 18 months).

Another key factor to consider in the interpretation of our findings is the extent to which HIV status disclosure may impact social relationships and adherence among PLWH. Unlike the general population of smokers, the social relations of PLWH are unique challenged by the issue of HIV disclosure. ⁵⁵ In fact, HIV disclosure is known to impact adherence to HAART treatment ⁵⁶ and can significantly alter social relationships. ⁵⁵ Thus, in our study, where participants were asked to rate their social relationships, HIV disclosure is a variable that was not assessed but could undoubtedly impact our findings. In future studies of PLWH, the Important People scale can possibly be altered so as to include items relating to disclosure to social network members with the aim of exploring how this factor is related to smoking cessation and adherence. Furthermore, the smoking of social support members is a variable that should also be considered given its possible role as a promoter or discourager of smoking among PLWH.

Also, the high proportion of individuals that identify as lesbian, gay, bisexual and transgender (LGBT) in the HIV community ⁵⁴ necessitates a careful consideration of how sexual orientation may relate to the current findings. In our study approximately 33% of participants identified as LGBT. Previous studies have shown that strong social support as well as LGBT community connectedness is associated with improved health behavior and psychosocial functioning. ⁵⁷ Investigators have proposed the idea that greater social support among LGBT may not only provide tangible resources but also there is an “identity affirming” process that can be health promoting. ⁵⁷ Given that adherence to smoking cessation treatment and smoking itself are health behavior related, this is an important factor to consider. Future research can potentially explore this area through the inclusion of measures that assess the identity promoting nature of social relationships in both LGBT and non-LGBT smokers that are PLWH.

The limitations of the current study must also be carefully weighed in considering our findings. First, our study relied heavily on self-reported measures of some of the key variables in the analyses—including adherence to NRT. Recall bias may have under or overrepresented participant’s adherence. The use of a more rigorous approach to capturing adherence data, for example, electronic pill bottles ⁵⁸ could have validated self-report measures. Moreover, our approach for assessing social support could be expanded to include a wider range of social support domains through the use of additional measures. For example, collecting data on the smoking status of social support members could offer greater insight in the role of smoking peers. Second, our sample was limited to PLWH that were smokers seeking to quit in our catchment area of the States of Rhode Island and Massachusetts in the United States. Thus, results may not be generalizable to other geographic areas in the United States or throughout the world. This is a particularly relevant limitation when one considers the fact that cultural and national factors may also have an influence on social relationships as well on views of medications, smoking and adherence. Furthermore, the reliability of carbon monoxide testing can be impacted by the time of day of carbon monoxide testing. ⁵⁹ Thus, our approach was limited by the fact that we did not account for the time of day. Also, the use of cigars, menthol cigarettes and other forms of tobacco products are important factors to consider with respect to carbon monoxide testing. ⁶⁰ Unfortunately, we did not collect data on other forms of tobacco which is certainly a limitation that can be addressed in future research. Furthermore, collecting a greater amount of data on HIV-related variables such as CD4 counts, duration and extent of HAART treatment, and years since HIV diagnosis would have offered a more comprehensive characterization of our sample. Such variables would have aided in the interpretation of findings and should be considered in future studies. Lastly, the significant relation between adherence and frequency of contact with social support network that was found may be attributed to a third underlying confounding variable that was not accounted for in our study. Thus, future studies seeking to expand upon our work should consider such variables when designing the assessment battery.

Despite our limitations, this study is unique in its emphasis on the relationship between social support domains and adherence to smoking cessation treatment. Given the increasing research and clinical interest in addressing both tobacco use and adherence in the HIV community, the findings of the current study may provide support for a greater emphasis on social support domains as a possible target for attaining higher levels of smoking cessation treatment adherence. The findings from the current study may have implications for the development of interventions that seek to harness the important role of social support in the PLWH community. In the broader tobacco literature, there have been several studies that have successfully developed and tested smoking cessation interventions that include a social support dimension. ⁴⁰ However, there has been less work in this area with PLWH and in order to truly confront the challenge of tobacco use among PLWH these relationships must be well-studied and integrated into existing treatment modalities.

Funding

This research was supported by grant R01-DA12344-06 from the National Institute of Drug Abuse (RN, PI), grant K01-CA160670 from the National Cancer Institute (MAD, PI), grant K23-HL069987 from the National Heart, Lung, and Blood Institute (EL-R, PI), grant K07-CA95623 from the National Cancer Institute (CAS, PI), an NIH-funded Transdisciplinary Tobacco Use Research Center (TTURC) Award (P50 CA084719), an NIH-funded Lifespan/Tufts/Brown Center for AIDS Research Award (P30 AI42853), and by the Robert Wood Johnson Foundation.

Declaration of Interests

None declared.