Mediators of a smoking cessation intervention for persons living with HIV/AIDS

Vidrine, Damon J.; Kypriotakis, George; Li, Liang; Arduino, Roberto C.; Fletcher, Faith E.; Tamí-Maury, Irene; Gritz, Ellen R.

doi:10.1016/j.drugalcdep.2014.12.003

Cited by 28 publications

(15 citation statements)

References 48 publications

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“…Increasing smokers’ confidence in their ability to quit was the best mediator. This finding is in line with research on telephone counseling and cellphone interventions that have highlighted the importance of self‐efficacy in achieving abstinence . It extends existing evidence by showing that self‐efficacy plays a key role in text‐messaging interventions, and that utilization of outside resources was not important as a meditational pathway, with the possible exception of the use of medications.…”

Section: Discussionsupporting

confidence: 87%

“…The clear result of psychosocial processes playing a key role in conferring the benefit of Text2Quit notwithstanding, much of the variance remains unexplained, similar to other studies of treatment mechanisms underlying smoking cessation . With 65% of the effect still unaccounted for, there are still other ways in which text‐messaging confers benefit.…”

Section: Discussionmentioning

confidence: 72%

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How do text‐messaging smoking cessation interventions confer benefit? A multiple mediation analysis of Text2Quit

Hoeppner

Abroms

2016

Addiction

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Aims To determine the degree to which the observed benefit of Text2Quit was accounted for by psychosocial mechanisms derived from its quit smoking messaging versus from the use of extra-programmatic smoking cessation treatments and services. Design Prospective, multiple mediation model of a randomized controlled trial (RCT). Setting USA nationwide. Participants 409 adult daily smokers. Participants were on average 35 years of age, predominantly female (68%), White (79%), lacked a college degree (70%), had medium nicotine dependence (average FTND score of 5.2), and more than half (62%) had made a previous quit attempt. Intervention Adult daily smokers browsing the web for smoking cessation support (n=409; recruited5/19/2011–7/10/2012) were randomized to receive smoking cessation support via Text2Quit versus a smoking cessation material. Measurements Mediators (i.e., changes in psychosocial constructs of health behavior change, use of extra-programmatic treatment) were assessed at 1-month using single-item measures, and outcome (i.e., self-reported 7-day point prevalence abstinence) at 6-month follow-up. Findings Mediators accounted for 35% of the effect of Text2Quit on smoking cessation. Only psychosocial mechanisms had complete mediational paths, with increases in self-efficacy (b=0.10 [0.06–0.15]), quitting know-how (b=0.07 [0.03–0.11]), and the sense that someone cared (b=0.06 [0.01–0.11]) partially explaining the conferred benefit of Text2Quit. Use of outside resources, including treatments explicitly promoted by Text2Quit (i.e., medication (b=0.001 [−0.01–0.01]), quitline (b=−0.002 [−0.01–0.04])) and treatments and resources not promoted by Text2Quit (i.e., online forums (b=0.01 [−0.01–0.04]), self-help materials (b=−0.01 [−0.04–0.02])) did not have complete mediational paths. An interaction effect existed for medication use that suggested that for participants not using medication, Text2Quit conferred substantial benefit, but not for participants using medication. Conclusions Text-messaging programs for smoking cessation appear primarily to confer benefit by promoting improvements in the psychosocial processes related to quitting rather than through the use of extra-programmatic smoking cessation treatments and services.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 72%

How do text‐messaging smoking cessation interventions confer benefit? A multiple mediation analysis of Text2Quit

Hoeppner

Abroms

2016

Addiction

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“…Mobile-based smoking cessation programs were conducted in eight studies for adult smokers, 7 – 11 , 105 – 107 nine studies for young smokers, 108 – 116 and five interventions (seven reports) for HIV-positive patients or pregnant smokers. 117 – 123 Among 22 mHealth interventions, the significant effect on smoking abstinence was confirmed in five studies among adults, 7 , 9 , 105 – 107 six studies among young smokers, 109 , 111 – 114 , 116 and three smoking interventions for pregnant woman and HIV-positive patients. 118 , 119 , 123 However, due to high heterogeneity ( I 2 >81%), the effect of the study sample was not pooled by the meta-analysis.…”

Section: Resultsmentioning

confidence: 88%

Which eHealth interventions are most effective for smoking cessation? A systematic review

Phuc¹,

Tran²,

Pham³

et al. 2018

PPA

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PurposeTo synthesize evidence of the effects and potential effect modifiers of different electronic health (eHealth) interventions to help people quit smoking.MethodsFour databases (MEDLINE, PsycINFO, Embase, and The Cochrane Library) were searched in March 2017 using terms that included “smoking cessation”, “eHealth/mHealth” and “electronic technology” to find relevant studies. Meta-analysis and meta-regression analyses were performed using Mantel–Haenszel test for fixed-effect risk ratio (RR) and restricted maximum-likelihood technique, respectively. Protocol Registration Number: CRD42017072560.ResultsThe review included 108 studies and 110,372 participants. Compared to nonactive control groups (eg, usual care), smoking cessation interventions using web-based and mobile health (mHealth) platform resulted in significantly greater smoking abstinence, RR 2.03 (95% CI 1.7–2.03), and RR 1.71 (95% CI 1.35–2.16), respectively. Similarly, smoking cessation trials using tailored text messages (RR 1.80, 95% CI 1.54–2.10) and web-based information and conjunctive nicotine replacement therapy (RR 1.29, 95% CI 1.17–1.43) may also increase cessation. In contrast, little or no benefit for smoking abstinence was found for computer-assisted interventions (RR 1.31, 95% CI 1.11–1.53). The magnitude of effect sizes from mHealth smoking cessation interventions was likely to be greater if the trial was conducted in the USA or Europe and when the intervention included individually tailored text messages. In contrast, high frequency of texts (daily) was less effective than weekly texts.ConclusionsThere was consistent evidence that web-based and mHealth smoking cessation interventions may increase abstinence moderately. Methodologic quality of trials and the intervention characteristics (tailored vs untailored) are critical effect modifiers among eHealth smoking cessation interventions, especially for web-based and text messaging trials. Future smoking cessation intervention should take advantages of web-based and mHealth engagement to improve prolonged abstinence.

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“…Self-efficacy has been found to buffer the negative effects of core belief disruption following adversity 61 and to mediate relationships between literacy and medication adherence 23 and between a phone intervention and smoking cessation for HIV+ individuals. 62 It also predicts adjustment to illness and treatment, 63 longevity, 64 and positive mental health outcomes. 65 In a recent study in which patients with HIV were interviewed about their reasons for leaving care (associated with higher viral load), the three most frequent reasons included the perception that they felt well and therefore did not need treatment, loss of interest in treatment, and not being ready to deal with an HIV diagnosis/avoidance, 66 all of which suggest limited self-efficacy and self-awareness about adaptive healthcare behaviors.…”

Section: Discussionmentioning

confidence: 99%

Life Lessons from Women with HIV: Mutuality, Self-Awareness, and Self-Efficacy

Brody

Jack

Bruck-Segal

et al. 2016

AIDS Patient Care and STDs

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Women with HIV in the United States cope with multiple traumas that influence adherence to antiretroviral therapy (ART) and well-being. Narrative themes from three life turning points and a projective story task were compared for two groups of women with HIV (HIV well-managed vs. HIV not well-managed, matched on demographics and narrative word count) to understand predictors of successful outcomes. The well-managed group (n = 10) was virally suppressed and reported ≥95% ART adherence; the not well-managed group (n = 10) had detectable viral load and reported <95% ART adherence. Women were predominantly African American with low socioeconomic status and averaged 46.51 years. A three-stage coding process (with coders blind to group status in stages 1 and 2) involved (1) line by line thematic analyses that generated 155 subthemes reflecting six content areas (interpersonal relationships; culture and community; sense of self; relationship to past, present, and future experiences; self-care; and motivators for change); (2) absence/presence of the 155 subthemes was compared for the two groups; the frequency of 37 subthemes was found to significantly differ; and (3) the 37 differentiating subthemes were conceptually integrated, revealing that the well-managed group's narratives more frequently reflected (a) mutuality (growth-fostering relationships involving reciprocal care and empathy); (b) self-awareness (recognition of personal strengths and weaknesses and multiple factors contributing to life choices and trajectories); and (c) self-efficacy (active coping, self-advocacy, and utilizing resources). Implications for treatment and interconnections among themes are discussed, emphasizing the factors that enable women to care for themselves and others.

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Mediators of a smoking cessation intervention for persons living with HIV/AIDS

Cited by 28 publications

References 48 publications

How do text‐messaging smoking cessation interventions confer benefit? A multiple mediation analysis of Text2Quit

How do text‐messaging smoking cessation interventions confer benefit? A multiple mediation analysis of Text2Quit

Which eHealth interventions are most effective for smoking cessation? A systematic review

Life Lessons from Women with HIV: Mutuality, Self-Awareness, and Self-Efficacy

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