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. Author manuscript; available in PMC: 2023 Mar 1.
Published in final edited form as: Addiction. 2021 Dec 9;117(3):760–771. doi: 10.1111/add.15721

Efficacy and utilization of an acceptance and commitment therapy-based smartphone application for smoking cessation among Black adults: secondary analysis of the iCanQuit randomized trial

Margarita Santiago-Torres 1, Kristin E Mull 1, Brianna M Sullivan 1, Diana Kwon 1,2, Nicolle L Nollen 3, Michael J Zvolensky 4,5,6, Jonathan B Bricker 1,2
PMCID: PMC9798432  NIHMSID: NIHMS1855396  PMID: 34890104

Abstract

Background and aims:

Black adults who smoke are less likely to seek treatment and to succeed in quitting compared with other racial groups. The lack of efficacious and engaging trials for smoking cessation further contributes to this disparity. This study explored whether an acceptance and commitment therapy (ACT)-based smartphone application (iCanQuit) was more efficacious for smoking cessation than a United States Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) among Black adults.

Design:

Secondary analysis of a two-arm randomized trial with 12-month follow-up.

Setting:

United States (US).

Participants:

A total of 554 Black adults who smoke daily were recruited from 34 US states and enrolled between May 2017 and September 2018.

Interventions:

Participants were randomized to receive iCanQuit (n = 274) or QuitGuide (n = 280) for 12 months.

Measurements:

Smoking cessation outcomes were measured at 3, 6, and 12 months. The primary outcome was self-reported complete-case 30-day point prevalence abstinence (PPA) at 12 months. Secondary outcomes were 7-day PPA, missing-as-smoking imputation, multiple imputation, prolonged abstinence, and cessation of all tobacco products at 12 months. Study retention, treatment engagement, and change in ACT-based processes were also compared between arms.

Findings:

Study retention was 89% at 12 months and did not differ by arm (P > 0.05). The complete-case 30-day PPA was 28% for iCanQuit versus 20% for QuitGuide at 12 months (odds ratio [OR] = 1.60; 95% confidence interval [CI] = 1.03, 2.46). Similar associations were observed for the missing-as-smoking imputation, although non-significant (25% iCanQuit vs 18% QuitGuide; OR = 1.50; 95% CI = 0.98, 2.30). iCanQuit vs QuitGuide participants were significantly more engaged with iCanQuit application as measured by the number of logins from baseline to 6 months (incidence rate ratio = 3.26; 95% CI = 2.58, 4.13). Increased acceptance of cues to smoke mediated the effect of treatment on cessation (indirect effect: OR = 0.20; 95% CI = 0.05, 0.29).

Conclusions:

Among Black adults, an acceptance and commitment therapy-based smartphone application appeared to be more efficacious and engaging for smoking cessation than the United States Clinical Practice Guidelines-based QuitGuide application.

Keywords: Acceptance and commitment therapy, black adults, digital interventions, iCanQuit, smartphone applications, smoking cessation

INTRODUCTION

Non-Hispanic Black or African American (referred to hereafter as Black) adults in the United States (US) are disproportionally affected by smoking-related morbidity and mortality [1–4]. Although cigarette smoking rates among Black adults are comparable to that of the general population (14.0% vs 14.9%), Black adults smoke fewer cigarettes per day and begin smoking later in life [2, 5–7]. Furthermore, Black adults who smoke evince greater levels of nicotine dependence and serum cotinine [8–10]. Although smoking fewer cigarettes per day should theoretically be associated with greater quit success, relative to the general population, Black adults are less likely to quit (63.9% vs 46.1%) [3] and experience more difficulty quitting [11].

There are multilevel factors contributing to cigarette smoking disparities among Black adults at the individual (e.g. beliefs, experienced and perceived racial discrimination, and stress), community (e.g. familial norms, neighborhood influences), and institutional levels (e.g. access to health care, cost) [12–18]. Furthermore, because of a history of institutionalized racism and discrimination, Black adults are less likely to seek treatment [19].

The growing field of digital interventions for smoking cessation has the potential to greatly enhance reach among Black adults [20, 21]. There are only a few digital intervention studies for smoking cessation that have been conducted in this population. All have been feasibility studies, and none have demonstrated efficacy. One study tested the effect of a culturally-sensitive cognitive behavioral theory (CBT) digital video disc (DVD)-based intervention for smoking cessation against a standard control DVD among 140 Black adults [22]. Although user acceptability was high, there were no group differences in quitting rates at the 1-month follow-up. Another feasibility study compared the effect of a smartphone application that uses machine learning to generate motivational messages to quit smoking among Black and non-Hispanic White adults [23]. The study showed that Black adults were two times more likely to engage with the application and quit smoking compared to their counterparts at the 1-month follow-up; however, the study was limited by short duration and lack of random assignment. This scarce evidence highlights the need to rigorously test digital interventions with long-term follow-ups aimed at helping Black adults quit smoking.

One way to improve the odds of quitting in this population is to leverage the reach of digital interventions with theory-based behavioral approaches proven to be efficacious for smoking cessation. Acceptance and commitment therapy (ACT) is a contextual CBT that has shown promise for long-term smoking cessation [24–27]. ACT-based interventions for smoking cessation teach people to observe, acknowledge, and accept their cravings to smoke rather than avoid them, and use life values instead of expectations as motivation to quit [28, 29]. Quitting smoking may be particularly difficult for Black adults if cigarette smoking functions as a way to cope with highly stressful environments [30, 31]. Stressful environments (e.g. socioeconomic adversities, racism) are known barriers for cessation and a risk for relapse in this population [32]. Given that ACT-based interventions specifically target acceptance of stressful triggers to smoke, this behavioral approach could be particularly helpful to Black adults attempting to quit smoking.

Another key component of ACT-based interventions that may be beneficial to Black adults is the focus on taking actions in accordance with life values. Culturally specific interventions for smoking cessation among Black adults are well accepted, in part because of an emphasis on cultural values that are relevant to the population (e.g. religion, spirituality, family, and community) [33–35]. ACT-based interventions for smoking cessation may be helpful to Black adults because they focus on cultivating the ability to persist in or change behavior when doing so serves one’s values. Indeed, in the related domain of weight loss, ACT has been helpful to Black adults [36].

Bricker et al. developed iCanQuit, an ACT-based smartphone application for smoking cessation [37]. In a two-arm randomized trial, iCanQuit was compared to QuitGuide, a US Clinical Practice Guidelines (USCPG)-based smartphone application. At the 12-month follow-up, iCanQuit was 1.5 times more efficacious than QuitGuide for smoking cessation among 2415 adults from all 50 US states [37]. Unknown is whether iCanQuit is efficacious for smoking cessation among Black adults.

To address this gap, in a secondary analysis of the iCanQuit trial data, the current study explored the efficacy of iCanQuit against QuitGuide for smoking cessation among Black adults. iCanQuit may be efficacious among Black adults because of its focus on two ACT-based processes of smoking cessation: (i) it addresses triggers to smoke with acceptance rather than avoidance among those who may have greater susceptibility to smoking in response to stressful environments; and (ii) it encourages the enactment of life values such as religiosity, spirituality, family, and collectivism as motivators to quit smoking.

Compared to the QuitGuide arm, we explored whether Black adults in the iCanQuit arm would have higher rates of smoking cessation, engagement and satisfaction, and greater increases in ACT-based processes of acceptance of cues to smoke and valued living. We further explored the extent to which smoking cessation outcomes were mediated by changes in ACT-based processes. Results are aimed at informing the development of ACT-based interventions for Black adults who smoke.

METHODS

Overview

Data for this secondary analysis were from adults ( ≥ 18 years) who self-identified as Black, either alone or in combination with other races, enrolled in the two-arm randomized iCanQuit parent trial. Eligibility criteria included daily smoking, smartphone access, and wanting to quit smoking. Exclusion criteria included being unable to read English, receiving smoking cessation treatment, having used QuitGuide in the past, or having a household member already enrolled in the study. Participants were recruited and screened for eligibility online. Details on the 12-month parent trial have been previously described [37]. In brief, a racially/ethnically diverse sample of 2415 adults from all 50 US states were randomized 1:1 to receive an ACT-based smartphone application (iCanQuit) or a USCPG-based smartphone application (QuitGuide) for 12 months. Randomization by permuted blocks of size 2, 4, and 6 was stratified by daily smoking frequency (≤20 vs ≥21 cigarettes/day), minority race/ethnicity, education level (≤high school vs ≥some college), and positive screening for depression (Center for Epidemiological Studies-Depression [CESD]-20 scale score ≤15 vs ≥16) [38]. Study procedures were approved by the Fred Hutchinson Cancer Research Center Institutional Review Board. All participants were compensated to up to $105 for completing study data collection.

Population, recruitment, and enrollment

A total of 554 Black adults were selected [37]. Black adults were recruited via Facebook ads (489/554, 88%), a survey sampling company (33/554, 6%), search engine results (16/554, 3%), and word of mouth (16/554, 3%). Tailored recruitment efforts to enroll Black adults included using Facebook ads featuring photos of Black community members and selecting parameters corresponding to Black organizations, professional associations, and magazines (e.g. Black Lives Matter, National Society of Black Engineers, Vibe) along with parameters of cigarette smoking and smoking control initiatives (e.g. Marlboro, smoking ban). Facebook ads specifically tailored to Black adults’ cost per click were $0.41 and cost per randomized participant was $8.16. The total number of impressions was 78 910. Participants were enrolled between May 2017 and September 2018. Participants were given unique access to their assigned application and were sent unique links to study surveys online at the 3-, 6-, and 12-month follow-ups. Follow-up data collection was between August 2017 and December 2019.

Interventions

iCanQuit

Participants randomized to the iCanQuit arm received access to download the iCanQuit smartphone application (version 1.2.1). iCanQuit teaches ACT skills for coping with smoking urges, staying motivated, and preventing relapse [37]. The content is delivered in eight levels, including on-demand help in coping with smoking urges, tracking daily number of cigarettes smoked, and urges passed without smoking. The program is self-paced, and content is unlocked in a sequential manner. If a participant lapses, the program encourages them to set a new quit date and return to the first five levels for preparation. iCanQuit did not contain content specifically tailored to Black adults.

QuitGuide

Participants randomized to the QuitGuide arm received access to download the QuitGuide smartphone application (version 1.2.2). QuitGuide content is delivered in four main sections: (i) “Thinking about quitting”, which focuses on motivations to quit by using reason and logic and providing information on the health consequences of smoking and quitting; (ii) “Preparing to Quit”, which helps users develop a quit plan, identify smoking behaviors, triggers, and reasons for being smoke-free, and social support for quitting; (iii) “Quitting”, which teaches skills for avoiding cravings to smoke; and (iv) “Staying Quit”, which presents tips, motivations, and actions to stay smoke-free and skills for coping with slips. No quit smoking medications, coaching, or any other intervention was provided in either arm [37].

Study Measures

Baseline characteristics

Baseline data included age, gender, ethnicity, education, employment, income, marital status, sexual orientation, and zip codes. Study participants completed positive screening tools to assess mental health, including depression [38], panic [39], and post-traumatic stress (PTSD) disorders [40]. Alcohol consumption was assessed via the Quick Drinking Screen [41]. Smoking behavior variables included nicotine dependence (measured by Fagerström Test for Nicotine Dependence) [42], number of cigarettes smoked per day, years of smoking, use of e-cigarettes, quit attempts, confidence to quit smoking, and relationships with other people who smoke.

Smoking cessation outcomes

Smoking cessation outcomes were measured at the 3-, 6-, and 12-month follow-ups. Consistent with the iCanQuit parent trial, [37] primary analysis was performed on a complete-case basis, with intent-to-treat missing-as-smoking and multiple imputation sensitivity analyses. Complete-case analysis is appropriate in studies with low attrition and when baseline covariates related to the outcome are included in the analysis [43, 44]. The primary smoking cessation outcome was self-reported 30-day point-prevalence abstinence (PPA) at 12 months. Secondary smoking cessation outcomes were: 7-day PPA, missing-as-smoking imputation, multiple imputation, prolonged abstinence defined as no smoking at all in the 9-month period of 3 to 12 months post-randomization, and cessation of all nicotine and tobacco products (e-cigarettes or vaping, chewing tobacco, snus, hookahs, cigars, cigarillos, tobacco pipes, and kreteks) at 12 months.

ACT-based processes

Change from baseline to 3 months post-randomization in ACT-based processes, including acceptance of internal cues to smoke and valued living, were measured using validated tools. Acceptance of internal cues to smoke was measured via the Avoidance and Inflexibility Scale (AIS-27 adapted from Gifford et al.) [45], which includes three sub-scales that assess one’s willingness to experience sensations, emotions, and thoughts that cue smoking. The 27 items are rated on a 5-point scale from (1) “Not at all” to (5) “Very willing” and averaged, with higher scores indicating greater acceptance. Valued living was measured via the 10-item Valuing Questionnaire [46] designed to assess the extent of personal values (e.g. spirituality, family, and health) enactment. Each item is rated on a 7-point scale ranging from (0) “Not at all true” to (6) “Completely true”. Scores were averaged and two distinct factors were derived, progress and obstruction with higher scores indicating either greater progress or greater obstruction toward valued living, respectively.

Treatment engagement and satisfaction

Utilization of the assigned application was objectively measured by Google Analytics, including number of times the application was opened, the time spent per session, and the number of unique days of use. Data on satisfaction was self-reported at the 3-month follow-up via an 11-item treatment satisfaction scale.

Statistical Analysis

Baseline characteristics are described overall and by treatment arm. Zip codes were tied to geographic location using the R library “zipcode” [47] and were categorized as urban or rural using rural–urban commuting area (RUCA) codes (1–3 urban, 4–10 rural) [48–52]. To assess study outcomes, logistic regression models were used to compare binary cessation outcomes and data retention measures between arms, and Bayes factors for non-significant cessation outcomes were calculated. Second, multiple imputation was used to estimate missing 30-day PPA at 12 months. Effect sizes and standard errors from ten imputed datasets were pooled using Rubin’s rules [53] to generate a single OR and 95% CI. Third, changes in measures of ACT-based processes and treatment engagement and satisfaction were compared between arms. Generalized linear models were used for continuous outcomes, negative binomial models were used to compare arms on right-skewed count outcomes (e.g. number of application openings), and logistic regression models were used for binary satisfaction outcomes. All regression models were adjusted for the factors used in stratified randomization to avoid losing power and obtaining incorrect CI [54]. Hayes’ PROCESS macro for SAS was used to assess mediation of the treatment effect on the primary smoking cessation outcome by changes from baseline to 3 months in the acceptance subscales, mean acceptance, and valued living [55]. This method uses the regression-based product of coefficients with bootstrapping to estimate indirect effects. There was no evidence for confounding of the relationships between treatment and outcome, treatment and mediator, or mediator and outcome. Therefore, after adjusting mediation models for factors used in stratified randomization and baseline values of proposed mediators, no unmeasured confounding was assumed. The empirical distribution of the indirect effect was estimated with 5000 bootstrapped samples, which provided the estimated mediation effect and 95% CI. Mediation effects were considered statistically significant when confidence intervals did not include zero [54]. All statistical tests were 2-sided, with α = 0.05. Based on recommendations for exploratory analyses [56,57], we did not adjust for multiple comparisons, because this study aims to inform the development of ACT-based interventions for Black adults who smoke. Regression analyses were completed using R, version 4.0.3, and libraries “mice” for multiple imputation [58], and “MASS” for negative binomial regression [59, 60]. Bayes factors were calculated with R library “BFpack” [61], using uninformative priors to provide posterior probabilities for exploratory tests of the treatment effect on non-significant cessation outcomes [62].

RESULTS

Participant characteristics

Figure 1 illustrates the flow of participants through the study, and Figure 2 illustrates the geographical location of trial participants recruited from 34 US states, with 14% residing in rural areas. Study retention, defined as the proportion of participants who provided cessation outcome data, was high with 89%, 91%, and 89% of study participants retained at the 3-, 6-, and 12-month follow-ups, respectively, and no differential retention rates between arms (all P > 0.05). On average, participants were 37 years old, 22% male, 5% Hispanic (Table 1). Slightly more than half (52%) were employed and 48% had annual household incomes <$20 000. More than half (52%) of study participants screened positive for depression, 25% screened positive for panic disorder, and 50% screened positive for PTSD. The majority (79%) reported having smoked for 10 years or longer and 58% had high nicotine dependence.

FIGURE 1.

FIGURE 1

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CONSORT diagram. a To increase enrollment of American Indians or Alaska Natives and men, some Black individuals who were eligible for study enrollment were randomly selected to be excluded during a period when only American Indians or Alaska Natives were recruited. To increase enrollment of men, some women who were eligible for study enrollment, were randomly selected to be excluded. b Phone did not meet the version requirements or was unable to receive text messages

FIGURE 2.

FIGURE 2

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Geographic location of Black trial participants

TABLE 1.

Baseline socio-demographic characteristics of Black trial participants

No. (%) or mean (SD)
Characteristic n Total (n = 523) QuitGuide (n = 257) iCanQuit (n = 266)
Age, mean (SD), y 523 37.7 (10.5) 37.9 (10.8) 37.6 (10.2)
Men 523 116 (22%) 59 (23%) 57 (21%)
Hispanic or Latino ethnicity 523 26 (5%) 14 (5%) 12 (5%)
High school or less education 523 232 (44%) 111 (43%) 121 (45%)
Employment
 Employed 523 274 (52%) 131 (51%) 143 (54%)
 Unemployed 523 77 (15%) 34 (13%) 43 (16%)
 Homemaker 523 81 (15%) 44 (17%) 37 (14%)
 Disabled 523 66 (13%) 36 (14%) 30 (11%)
 Retired 523 13 (2%) 8 (3%) 5 (2%)
 Other 523 12 (2%) 4 (2%) 8 (3%)
Income
 <$20 000/y 523 253 (48%) 124 (48%) 129 (48%)
 $20 000–$54 999/y 523 226 (43%) 112 (44%) 114 (43%)
 ≥$55 000/y 523 44 (8%) 21 (8%) 23 (9%)
Urban residence 523 452 (86%) 219 (85%) 233 (88%)
Married 523 100 (19%) 52 (20%) 48 (18%)
LGBT 523 92 (18%) 43 (17%) 49 (18%)
Mental health positive screening results
 Depressiona 520 269 (52%) 129 (51%) 140 (53%)
 Panicb 516 135 (26%) 59 (23%) 76 (29%)
 PTSDc 519 260 (50%) 120 (47%) 140 (53%)
Alcohol use
 Heavy drinker, no. (%)d 502 95 (19%) 46 (19%) 49 (19%)
 No. of drinks/drinking day, mean (SD) 502 2.4 (4.2)e 2.3 (3.9)e 2.4 (4.5)e
Smoking behavior
 FTND score, mean (SD) 523 5.8 (1.9) 5.8 (1.9) 5.8 (2.0)
 High nicotine dependence (FTND score ≥ 6) 523 303 (58%) 146 (57%) 157 (59%)
 Smokes more than one-half pack/d 523 307 (59%) 157 (61%) 150 (56%)
 Smokes more than 1 pack/d 523 62 (12%) 28 (11%) 34 (13%)
 First cigarette within 5 min of waking 523 286 (55%) 139 (54%) 147 (55%)
 Smoked for ≥10 y 523 415 (79%) 205 (80%) 210 (79%)
 Used e-cigarettes at least once in past month 523 94 (18%) 48 (19%) 46 (17%)
 Quit attempts in past 12 months, mean (SD) 494 1.4 (2.7)f 1.6 (3.1)f 1.2 (2.3)f
 Confidence to quit smoking, mean (SD)g 523 71.3 (27.1) 72.2 (26.4) 70.5 (27.7)
 Friend and partner smoking
 Close friends who smoke, mean (SD) 523 2.5 (1.8)h 2.4 (1.8)h 2.6 (1.8)h
 No. of adults in home who smoke, mean (SD) 523 1.3 (0.8)i 1.3 (0.8)i 1.4 (0.7)i
 Living with partner who smokes 523 152 (29%) 72 (28%) 80 (30%)
ACT-based measures
 Acceptancej
 Sensations 518 3.0 (0.6) 3.1 (0.6) 3.0 (0.6)
 Emotions 519 2.8 (0.4) 2.8 (0.5) 2.7 (0.4)
 Thoughts 521 2.7 (0.5) 2.8 (0.5) 2.7 (0.4)
 Acceptance mean score 517 2.8 (0.4) 2.9 (0.4) 2.8 (0.4)
 Valued livingk
 Progressl 519 20.6 (7.6) 21.0 (7.3) 20.2 (7.8)
 Obstructionm 515 12.5 (8.7) 11.9 (8.4) 13.0 (9.0)
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Abbreviations: ACT = acceptance and commitment therapy; FTND = Fagerström test for nicotine dependence; LGBT = lesbian, gay, bisexual, or transgender; PTSD = post-traumatic stress disorder.

a

Positive screening results for depression via the Center for Epidemiological Studies Depression Scale (CESD-20) cutoff ≥16.

b

Panic disorder via the 5-item Autonomic Nervous System Questionnaire (ANSQ).

c

PTSD via the six-item PTSD Checklist (PCL-6; scores of ≥14 indicate a positive screen).

d

Heavy drinking is defined as 4 or more drinks on a typical drinking day for women and 5 or more drinks on a typical drinking day for men within the past 30 days.

e

Median = 1.

f

Median = 0.

g

Range, 0–100, where 0 indicates not at all confident and 100 indicates extremely confident.

h

Median = 2.

i

Median = 1.

j

Avoidance and inflexibility scale. Range is 1–5. Higher scores indicate greater acceptance.

k

Valuing Questionnaire.

l

Range is 0–30. Higher scores indicate greater progression toward one’s values.

m

Range is 0–30. Higher scores indicate greater obstruction of one’s values.

Smoking quit rates

Participants in the iCanQuit vs QuitGuide arm had greater odds of quitting smoking across all time points (Table 2). The self-reported complete-case 30-day PPA was 28% for iCanQuit vs 20% for QuitGuide at 12 months (OR = 1.60; 95% CI = 1.03, 2.46), 28% vs 14% at 6 months (OR = 2.40; 95% CI = 1.50, 3.85), and 19% vs 11% at 3 months (OR = 1.99; 95% CI = 1.17, 3.37). Multiple imputation analysis of 30-day PPA at 12 months resulted in similar 12-month quit rates of 29% for iCanQuit vs 20% for QuitGuide (OR = 1.67; 95% CI = 1.06, 2.63). The imputed missing-as-smoking 30-day PPA at 12 months was 25% for iCanQuit vs 18% for QuitGuide, although non-significant (OR = 1.50; 95% CI = 0.98, 2.30). The Bayes factor for 30-day PPA with missing-as-smoking imputation was 0.49, indicating that data were insensitive to detect a treatment effect [63]. Results for 7-day PPA were very similar and showed slightly higher quit rates at all follow-up time points. However, the Bayes factor for 7-day PPA at 12 months was 0.19, suggesting support for the null hypothesis that treatment did not affect this outcome [63].

TABLE 2.

Smoking cessation outcome by follow-up time pointa

No. (%) or Mean (SD)
Smoking cessation outcomeb Overall (n = 523) QuitGuide (n = 257) iCanQuit (n = 266) OR (95% CI) P value
12-month outcomes
 30-d PPA 112/467 (24%) 46/234 (20%) 66/233 (28%) 1.60 (1.03, 2.46) 0.035
 30-d PPA, missing-as-smokingc 112/523 (21%) 46/257 (18%) 66/266 (25%) 1.50 (0.98, 2.30) 0.063
 7-d PPA 148/467 (32%) 68/234 (29%) 80/233 (34%) 1.27 (0.86, 1.89) 0.233
 Prolonged abstinenced 41/385 (11%) 12/194 (6%) 29/191 (15%) 2.86 (1.40, 5.82) 0.004
 30-d PPA of all tobacco productse 95/467 (20%) 36/233 (15%) 59/234 (25%) 1.83 (1.15, 2.91) 0.011
6-month outcomes
 30-d PPA 99/476 (21%) 33/236 (14%) 66/240 (28%) 2.40 (1.50, 3.85) <0.001
 7-d PPA 150/476 (32%) 64/236 (27%) 86/240 (36%) 1.50 (1.01, 2.23) 0.043
3-month outcomes
 30-d PPA 72/468 (15%) 26/231 (11%) 46/237 (19%) 1.99 (1.17, 3.37) 0.011
 7-d PPA 122/468 (26%) 43/231 (19%) 79/237 (33%) 2.26 (1.47, 3.48) <0.001
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Abbreviations: OR = odds ratio; PPA = point prevalence abstinence.

a

All models include the following covariates: education (high school diploma or less), heavy smoking (>20 cigs/day) and depression symptoms (CESD-20 ≥ 16).

b

All outcomes are complete case (i.e. exclusion of participants lost to follow-up) and were specified a priori, except where noted.

c

Missing-as-smoking imputation sensitivity analysis was specified a priori as a secondary outcome.

d

Defined as no smoking since 3 months post-randomization, using self-reported data of last cigarette.

e

Including any kind of e-cigarettes or vaping, chewing tobacco, snus, hookahs, cigars, cigarillos, tobacco pipes, and kreteks.

Change in ACT-based process mediators

Indirect effects of the treatment on cessation through ACT-based processes are shown in Supporting information Table S1. Note that indirect effects are reported as hypothesized rather than individual path coefficients. iCanQuit vs QuitGuide participants had greater baseline to 3-month increases in acceptance of sensations (P = 0.015), emotions (P = 0.016), and mean acceptance (P = 0.007), and descriptively greater increases in acceptance of thoughts that cue smoking (P = 0.097). Baseline to 3-month changes in valued living measures of progress and obstruction of values did not differ between arms (all P > 0.05). Increases in acceptance were in turn associated with greater odds of quitting smoking by 12 months. Increases in acceptance of sensations (indirect effect: 0.13; 95% CI = 0.02, 0.29; P < 0.05) and emotions (indirect effect: 0.16; 95% CI = 0.03, 0.33; P < 0.05) significantly mediated the treatment effect on 30-day PPA at 12 months, whereas increases in acceptance of thoughts did not (P > 0.05). Increases in mean acceptance significantly mediated the treatment effect on 30-day PPA at 12 months (indirect effect: 0.20; 95% CI = 0.05, 0.29; P < 0.05).

Indirect effects of the treatment on cessation through ACT-based processes are shown in Supporting information Table S1. Note that indirect effects are reported as hypothesized rather than individual path coefficients. iCanQuit vs QuitGuide participants had greater baseline to 3-month increases in acceptance of sensations (P = 0.015), emotions (P = 0.016), and mean acceptance (P = 0.007), and descriptively greater increases in acceptance of thoughts that cue smoking (P = 0.097). Baseline to 3-month changes in valued living measures of progress and obstruction of values did not differ between arms (all P > 0.05). Increases in acceptance were in turn associated with greater odds of quitting smoking by 12 months. Increases in acceptance of sensations (indirect effect: 0.13; 95% CI = 0.02, 0.29; P < 0.05) and emotions (indirect effect: 0.16; 95% CI = 0.03, 0.33; P < 0.05) significantly mediated the treatment effect on 30-day PPA at 12 months, whereas increases in acceptance of thoughts did not (P > 0.05). Increases in mean acceptance significantly mediated the treatment effect on 30-day PPA at 12 months (indirect effect: 0.20; 95% CI = 0.05, 0.29; P < 0.05).

Treatment engagement and satisfaction

Engagement with iCanQuit was greater than with QuitGuide from baseline to 6 months (Supporting information Table S2). On average, iCanQuit vs QuitGuide participants opened the application 30.9 times vs 9.7 times (P < 0.001). Compared to QuitGuide participants, minutes spent per session (3.4 vs 2.3, P < 0.001) and the number of unique days of use (19.6 vs 7.4, P < 0.001) was higher among iCanQuit participants. Overall satisfaction with the assigned application was high in both arms (88% iCanQuit vs 86% QuitGuide, P = 0.537). Both arms also found their application to be useful for quitting (85% iCanQuit vs 83% QuitGuide, P = 0.536). iCanQuit vs QuitGuide participants were more likely to recommend the application (87% vs 79%, P = 0.025), and were more likely to report they felt the application was made for them (83% vs 73%, P = 0.010).

DISCUSSION

This study showed that a digital intervention for smoking cessation was efficacious and engaging among Black adults. Across all time points (3-, 6-, and 12-month follow-ups), the complete-case 30-day PPA rates were significantly higher in the iCanQuit than the QuitGuide arm, with OR ranging from 1.60 to 1.99. Quit rates were comparable to those found in the iCanQuit parent trial (ORs ranging from 1.49–2.20) [37]. Similar associations were observed for missing-as-smoking imputation, although non-significant (25% iCanQuit vs 18% QuitGuide (OR = 1.50 95% CI = 0.98, 2.30; P = 0.06). The odds of prolonged abstinence at 12 months were 2.86 times higher among iCanQuit than QuitGuide participants. iCanQuit participants were also significantly more engaged with their application relative to QuitGuide. Greater increases in acceptance of internal cues to smoke mediated the effect of treatment on smoking cessation.

Only a few feasibility trials have tested digital interventions for smoking cessation among Black adults, but these are limited by short duration (1-month follow up), no difference in quit rates between treatment and control groups, or lack of random assignment [22, 23]. In the absence of efficacious low-cost, low-burden, highly disseminable digital interventions for smoking cessation among Black adults, our study is an important step toward using an existing efficacious digital tool that could be culturally adapted to this population and tested in a larger subsequent trial.

Smartphone applications can be a valuable tool for increasing smoking quit rates among otherwise hard-to-reach populations because they can remotely teach users an evidence-based approach to quit smoking that is available 24/7 while incorporating interactive tools and features to keep the user engaged long-term [21]. As such, this study addressed many of the existing population-specific barriers associated with reach, retention, engagement, and satisfaction among Black adults. First, we successfully recruited individuals from 34 US states, of whom 14% resided in a rural area, thereby demonstrating the potential for dissemination and broad impact in hard-to-reach populations. Second, this study showed high rates of long-term engagement and satisfaction with smartphone applications. In comparison, culturally tailored group-based CBT for smoking cessation among Black adults that resulted in short term efficacy reported no differences in utilization or satisfaction between arms [64]. Similarly, a 1-month trial that tested the effects of a culturally tailored DVD for smoking cessation among Black adults reported no difference in utilization between arms [22]. In contrast, this study showed much higher utilization of iCanQuit vs QuitGuide, suggesting that smartphone applications for smoking cessation are engaging in this population. iCanQuit participants were also more likely to report that they felt the application was made for them, thereby demonstrating the potential for future cultural adaptation of iCanQuit for Black adults.

The current findings indicate that the efficacy of an ACT-based smartphone application was mediated by changes in acceptance of urges to smoke, in agreement with the theoretical model underlying ACT for smoking cessation [27, 65, 66]. Perhaps learning ACT-based acceptance skills to be present with the urges to smoke that could be triggered by life stressors resonates with Black adults. Such acceptance may have, in turn, contributed to achieving and maintaining long-term cessation outcomes and preventing relapse, as demonstrated by higher odds of prolonged abstinence in the iCanQuit than the QuitGuide arm at 12 months. That this effect was achieved without the provision of pharmacotherapy among a group with high nicotine dependence is noteworthy. Future research could test whether the cultivation of skills to accept stressful triggers to smoke in ACT-based interventions helps offset nicotine dependence and withdrawal, thereby enhancing abstinence [67].

The increased accessibility of smoking cessation treatment via smartphone applications could have further contributed to prolonged abstinence. Black adults make more attempts to quit smoking than other racial groups, yet are less likely to quit partly because of lower utilization of cessation treatments [68]. Given that experienced racism in medical institutions is an impediment for seeking treatment, smartphone applications may provide a viable alternative treatment delivery context [17, 32].

Quit rates were higher at 12 months than at 3 or 6 months. The total length of time participants used the application is unlikely to explain this fully, because participants used the application for a mean of 62 (SD = 66) days, and 68% of participants did not use it after 3 months (data not shown). Another possibility is whether the number of 24-hour quit attempts increased at each follow-up time point, because it may take many quit attempts to finally be successful [69]. Indeed, we found that the mean number of quit attempts at the 3-, 6-, and 12-month follow-ups were 5.0 (8.1), 9.4 (23.8), and 12.7 (41.7), respectively. Future studies on the nature of the association between quit attempts and quit success are needed.

There are several important strengths. First, this study had a rigorous randomized trial design with long-term follow-up and 89% retention. Our group’s methods for obtaining high retention rates are described elsewhere [70]. Second, the study was successful in recruiting a geographically diverse sample of Black adults, thereby demonstrating high reach, generalization of the results, and potential for broad dissemination. Third, this study showed high engagement and satisfaction of smartphone applications for smoking cessation among Black adults.

This study has several limitations. First, the results are from a secondary analysis of a two-arm randomized parent trial and as such, the results are exploratory, rather than definitive. Second, the study was not culturally tailored to Black adults. Third, the trial results may not be representative of the full study population, which in this context include the growing percentage of Black adults who do not smoke heavily [71, 72] or populations of Black adults with low prevalence of mental health symptomology. Nonetheless, this study is an important step in identifying an existing tool that could be culturally adapted and tested in a future trial [73]. Fourth, smoking status was not biochemically verified. The self-reported outcome was prespecified based on methodological problems with remote biochemical verification [74, 75]. Although previous studies have demonstrated strong agreement between self-reported and biochemically verified smoking status [76, 77], others showed evidence of significant discordance [78, 79]. Therefore, the external validity of the self-reported smoking status in this trial is not known. However, given the double blinding of the trial, we see no compelling reason why the false reporting rate would be higher in one arm versus the other. Finally, full treatment engagement data up to 12 months was not available because of a technical error by Google Analytics. For this reason, we reported engagement for participants who had full 6 months of data available (519/523, 99%). Because participants were unaware of the error, the missing engagement data after 6 months is unlikely to change the validity of the results [43].

CONCLUSIONS

The ACT-based iCanQuit application was more efficacious and engaging for smoking cessation among Black adults than the USCPG-based QuitGuide application, and testing in a full-scale study is warranted. Based on acceptance and commitment therapy, the efficacy of the iCanQuit application was mediated by increases in acceptance of cues to smoke.

Supplementary Material

Supplementary Tables

ACKNOWLEDGEMENTS

We appreciate the tireless contributions of the entire study staff, most notably, Eric Meier, Eric Strand, Carolyn Ehret, Alanna Boynton, the design services of Ayogo, and the development services of Moby. We are very appreciative of the Black study participants.

Study protocol can be found in the supplement content of the primary outcome published paper (Jonathan B. Bricker et al. JAMA Intern Med. 2020;180[11]: 1472–1480).

FUNDING

This study was funded by grant R01CA192849, awarded to Jonathan B. Bricker (J.B.B.), from the National Cancer Institute. Research reported in this publication was supported by the National Institute on Minority Health and Health Disparities (NIMHD) of the National Institutes of Health (NIH) to the University of Houston under Award Number U54MD015946. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding information

National Cancer Institute, Grant/Award Number: R01CA192849; National Institute on Minority Health and Health Disparities to the University of Houston, Grant/Award Number: U54MD015946

Footnotes

DECLARATION OF INTERESTS

None of the authors have declarations. None of the authors have a financial interest in the iCanQuit application.

SUPPORTING INFORMATION

Additional supporting information may be found in the online version of the article at the publisher’s website.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov Identifier, NCT02724462.

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