Abstract
Introduction
We sought to evaluate preliminary efficacy and implementation outcomes of an e-cigarette and tobacco cessation intervention for hospitalized youth in the United States.
Methods
We conducted a pilot randomized controlled trial at a pediatric hospital with 3-month follow-up, from 08/2023-12/2024. Hospitalized youth (14-21 years) with self-reported past-30-day e-cigarette use were eligible. Exclusions included severe medical/psychiatric illness, cognitive impairment, inability to communicate in English. Intervention entailed health education, motivational interviewing counseling, quit planning, nicotine replacement therapy (NRT), and phone booster sessions. Control entailed brief advice and quit program referral. The primary outcome was self-reported past-30-day e-cigarette abstinence at 3-months with biochemical confirmation with intention-to-treat (ITT) sensitivity analysis. Implementation outcomes included acceptability, feasibility and fidelity.
Results:
In 144 hospitalized youth enrolled, the mean age was 16.2 years (standard deviation SD: 1.3) and 62% were female. At 3-months there was no difference in past-30-day e-cigarette abstinence between arms (intervention 43% vs control 42%; p=0.91). In ITT analysis we found the odds ratio of abstinence was OR 0.77 (95% CI 0.27 – 2.19, p = 0.62) in the intervention vs. control. Mean fidelity score was 43 (SD: 3; out of 50). All intervention participants (n=96) completed the initial in-person intervention, 49% made a quit plan, of those 23% were prescribed NRT. Most (89%) were somewhat/very satisfied with the intervention.
Conclusions:
Our study is among the first to demonstrate promising implementation but not efficacy of an e-cigarette cessation intervention in hospitalized youth. Future work is needed to enhance intervention efficacy in this population.
Introduction
E-cigarette use among youth is linked with adverse health outcomes and increased use of tobacco, cannabis, and alcohol.1,2 E-cigarettes can deliver extremely high nicotine doses, increasing risk for nicotine dependence which can have negative effects on attention, learning, anxiety and mood disorders.3,4 Nearly half of adolescent e-cigarette users want to quit, and a quarter have attempted quitting in the past year.5 Barriers to successfully quitting include confidentiality concerns, influence of peer pressure, unaddressed mental health disorders and nicotine dependence.5 Nearly two-thirds of youth who attempt to quit do so unassisted, thus are far less likely to quit successfully.6-8
To date, most tobacco use cessation studies in clinical settings focus on primary care.9,10 Youth with mental health and substance use disorders, may lack primary care access making the hospital a potentially important setting for intervention.11 Hospitalized youth are at increased risk for nicotine-related poor health outcomes due to underlying comorbidities (e.g., mental health disorders, asthma),1,4 but tobacco use cessation studies in hospitalized adolescents and young adults (AYAs) are lacking.12,13
The limited evidence of e-cigarette cessation interventions for youth suggest behavioral and pharmacological interventions show promise. A recent study found a community-based text message program "This is Quitting," significantly increased self-reported 30-day point-prevalence e-cigarette abstinence among AYAs, highlighting the promise of behavioral interventions in this age group.7 Pharmacotherapy evidence is evolving with a recent community-based randomized controlled trial for AYAs finding significantly greater biochemically verified abstinence in varenicline vs. placebo arm at 6-months.8 Studies of nicotine replacement therapy (NRT) in youth are limited but so far have shown minimal evidence of long-term efficacy.14Nonetheless, current pediatric guidelines recommend off-label NRT use for moderate to severely nicotine dependent youth.9,15 It is unknown whether e-cigarette cessation interventions incorporating behavioral support and pharmacotherapy when indicated are feasible and efficacious for youth in the hospital setting.
This study evaluated preliminary efficacy and implementation outcomes (acceptability, feasibility, and fidelity) of an e-cigarette cessation intervention for hospitalized AYAs.
Methods
Setting
We conducted a single site pilot randomized controlled trial (RCT) at a US free-standing tertiary care Midwestern pediatric hospital. The study was approved by the institutional review board (Children's Mercy Hospital, Kansas City MO; STUDY00002116) and a Data Safety Monitoring Board was established to ensure safety. See our previously published protocol paper for further study details.16 This study followed the CONSORT reporting guidelines for randomized trials.
Study Design
Hospitalized AYAs with current (past-30-day) e-cigarette use were enrolled and randomized 2:1 to receive the intervention or control (described below) with 3-month follow-up to evaluate preliminary efficacy and implementation outcomes from 08/2023-12/2024. There were no protocol deviations from our clinical trials record (NCT05936099). Our study design drew from the ORBIT framework for intervention development through formative testing and iterative refinement and subsequent feasibility pilot testing.17
Participant Recruitment and Randomization
AYAs (ages 14-21) admitted (from any setting, including the emergency department, other healthcare facility, or home) to any service (e.g., general pediatrics, surgery) were potentially eligible. Exclusions included severe medical or psychiatric illness based on the medical team assessment (i.e., too ill or impaired to participate), cognitive impairment, and inability to communicate in English based on chart review or medical team assessment. There were no exclusions based on quit motivation. Parental consent was waived based on best AYA practices.18 The health educator monitored the electronic health record (EHR) to identify potential eligible participants within the age range and were deemed medically stable to approach. The health educator approached these participants, gave parents/guardians brief study information including that the study topic was focused on adolescent health behaviors, such as substance use, and requested to meet confidentially with the potential participant who were s then asked to complete a confidential screening survey to identify those who self-reported past 30-day e-cigarette use. For those who met our eligibility criteria and reported past 30-day e-cigarette use, the health educator then privately reviewed the informed consent and randomized consented participants using the sealed envelope method.19 It was not possible to conceal allocation, therefore participants and the study team were not blinded. All participants then completed a demographic and baseline survey based on validated surveys (see Supplemental).20 The EHR was reviewed for health insurance status and documented diagnosis of a mental health and non-nicotine substance use disorder.
Intervention Design and Delivery
The intervention based in the Clinical Practice Guidelines “5As” framework21 incorporated health education, MI counseling, and behavioral skills quit training (e.g., craving management) for both e-cigarette and tobacco use cessation. The intervention was designed with formative testing and iterative refinement from key stakeholders including the youth research advisory board (YRAB) and hospital staff. The intervention content and procedures were presented to the YRAB and based on feedback changes were made x including using youth-friendly terminology, tailoring health education to include peer pressure, social media, and e-cigarettes impacts on mental health, and intervention elements emphasizing theperceived benefits vs. harms of youth vaping. Additionally, three YRAB members provided ongoing feedback on study procedures and intervention content during formative testing and refinement.
The intervention was delivered by a health educator with a Master’s in Public Health and trained in MI for e-cigarette and tobacco cessation (see Supplemental Intervention Manual and Survey Questions). Intervention participants received an initial in-person session in the hospital and subsequent brief booster phone sessions, once weekly for four weeks. Booster sessions entailed brief support for those attempting to quit or brief MI for those not ready to quit. Participants completed an initial assessment regarding their e-cigarette use behaviors in the past 7 days, willingness to quit, and nicotine dependence. The health educator then delivered tailored recommendations and MI counseling for those not ready to quit and skill-based counseling for those ready to quit (e.g., anticipated challenges, coping strategies).22 For those reporting e-cigarette and traditional cigarette use, the health educator offered tailored cessation counseling and health education on both e-cigarette and cigarette use. The health educator assisted those interested in quitting to create a Quit Plan and encouraged enrollment into a text message-based quit program referral (i.e., This is Quitting).7 Participants were eligible for NRT if they created a quit plan and scored medium to highly nicotine dependent;15 for those interested in NRT the health educator connected the participant to the physician (Masonbrink) who offered brief quit advice, NRT counseling and prescription free of charge based on the AAP guidelines.15 A computerized decision support (CDS) system guided these intervention delivery procedures and data collection via a tablet that was used by the health educator and the participant. Participants completed self-report survey questions while the health educator followed counseling and survey prompts related to intervention delivery. The CDS system included branching logic based on participant responses to provide the appropriate health education and MI counseling prompts as well as prompts related to the quit plan and NRT prescription. Participants who indicated they also used cannabis were given a referral information for an adolescent addiction clinic.
The control group received brief advice that entailed general health education about e-cigarette and tobacco use including a recommendation to consider quitting and a printed referral to the text message-based quit program (i.e., This is Quitting)7 provided by the health educator.
Data Collection and Outcome Measures
Participant demographics, e-cigarette use and nicotine dependence were assessed by confidential self-report of previously developed survey items (see Supplemental Intervention Manual and Survey Questions).20 Participants responded to 11-point Likert-type scale items with one survey item to assess knowledge, one to assess motivation, and one to assess confidence to quit (0=no to 10=extreme motivation, confidence, and knowledge; motivation questions added mid-study due to technical error leading to higher rates of missing data for this item; see Supplement for survey items).23
Consistent with our intervention development aim and the ORBIT model framework we assigned our primary outcome as preliminary efficacy assessed via self-reported 30-day continuous e-cigarette abstinence at 3-month follow-up (based on date of enrollment).24For those who self-reported abstinence at follow-up, biochemical verification was requested via mailed point-of-care salivary specimen tests with pre-paid packages for return.17 Due to low return rates, we added the option for confidential video or photo-observed at home saliva cotinine testing mid-study. We also assessed secondary preliminary efficacy including self-reported increased motivation, knowledge and confidence to quit using single item 5-point Likert scale survey questions compared from baseline to immediately post-intervention (intervention only) and 3-month follow up.25 For the intervention group, an exploratory efficacy of early self-report 7-day abstinence was collected during each Booster session survey.
We assessed implementation outcomes using Proctor’s model,26 including acceptability (i.e., satisfaction) and feasibility (i.e., ease of administration) and intervention fidelity.26 Acceptability was assessed via enrollment, intervention element completion rates (i.e., uptake of resources) and surveys of intervention participants and via Likert-scale survey items (e.g., “how satisfied were you with the intervention?”) immediately post-intervention.26 The health educator completed acceptability questions, including whether participants made a quit plan, were prescribed NRT, enrolled in the text-to-quit program at the completion of the index session. Feasibility was assessed via intervention duration (minutes) from CDS system and health educator survey (see Supplemental “Health Educator Field Notes.” Fidelity of intervention delivery was assessed by intervention audio recording review and scoring (by Masonbrink, Catley) from 0 (never/very poor) to 5 (always/very good) of 10 fidelity rating questions (e.g., “How well or often did the health educator… explore perceptions related to vaping”) adapted from previously validated scales with a maximum possible score of 50 (see Supplement) with the target of 75% fidelity based on literature on fidelity monitoring of behavioral intervention interventions.27,28
Retention strategies used included multiple contact and follow-up methods (i.e. email, text). AYA participants received completion incentives including $15 visa card (baseline), a $20 visa card (3-month follow up) and a $25 visa card (salivary cotinine test; added mid-study due to low completion rates).
Statistical Analysis
Descriptive statistics (means, frequencies, percentages) were used to summarize the data. Following the CONSORT guidelines, baseline characteristics were not compared between arms. To assess preliminary efficacy, between-arm differences in 3-month follow up in self-reported past-30-day continuous abstinence (primary outcome) and biochemically verified (salivary cotinine level <=30 ng/mL; secondary outcome)29 were compared by Fisher’s exact test and using logistic regression adjusting for demographic and comorbidity covariates. Following the intention-to-treat (ITT) principle, missing values were imputed 10 times using random forest algorithm within the Multiple Imputation by Chained Equations and results pooled according to Rubin’s rule. Cohen’s d effect size was converted from the pooled odds ratio (OR).30 As sensitivity analyses, missing outcomes were imputed as all abstinent (best-case) and all not abstinent (worst-case scenario). Motivation, knowledge and confidence to quit were compared by Wilcoxon rank-sum test and by linear mixed-effects models (LMM) where the fixed-effects included arm, timepoint, arm-by-time interaction, and covariates, including age, sex, race and ethnicity, insurance type, past history of mental health and substance use disorders. The between-arm comparison of pre-to-3-month change was the inference of interest. We then used the sum of random intercept variance and residual variance to derive Cohen’s d.31 For acceptability, descriptive statistics were used to calculate study enrollment, intervention completion and the proportion of AYA intervention participants with ratings of acceptability on 5-point Likert scale survey items. For feasibility descriptive analyses were used to summarize survey items and calculate intervention length (median, standard deviation [SD]). Fidelity was summarized utilizing similar descriptive analyses of the fidelity ratings (from 1 to 5) calculate mean (SD) scores from 10 questions adapted from previously validated scales (maximum possible score 50; score ≥75% or 37.5 deemed adequate). Exploratory analyses were conducted: (1) logistic regression was used to evaluate for an association between the number of booster session completion and 30-day abstinence adjusting demographic variables in the intervention arm; (2) and generalized linear regression was used to assess the effects of secondary efficacy including motivation, knowledge and confidence to quit measures on 30-day abstinence at 3-months and and 7-day abstinence at 1 month, controlling for arm (for pre-intervention and 3-month follow-up) and demographics. . Following recommendations for behavioral intervention pilot trials17 our sample size [n=144 (96 treatment, 48 control)] was based on feasible to recruit, capturing a representative sample, and being sufficient to evaluate preliminary efficacy in a behavioral trial. Although this pilot study was not intended to be a fully powered randomized trial with respect to our primary outcome our sample size was calculated a priori to be sufficient to determine the cessation rate within a margin of error of 10% and 14% (if the proportion was 50%) in the intervention and the control arm, respectively.9,32,33
Results
Of 1,331 AYAs eligible for pre-screening via the EHR based on being hospitalized and in the age range (14-21 years old), 816 (61%) who did not meet exclusion criteria and were deemed medically stable were approached by the health educator, 670 (82%) agreed to respond to the screening survey, of which 149 (22%) met inclusion criteria, 144 (21%) consented to participate, with 96 (67%) randomized to the intervention and 48 (33%) to the control arm, and 96 (67%) completed the 3 month follow up survey (see Figure 1). Of 144 participants enrolled, the mean age was 16 years (SD: 1.3), 62% were female, 58% were white, 49% were government insured. Participant characteristics, overall and by group, are shown in Table 1. Seventy-six (53%) had an EHR-documented non-nicotine substance use disorder and 83 (58%) had a documented mental health disorder. At baseline 56 (39% 95% confidence interval [CI]: 31, 47) participants reported frequent (≥20 days in past 30 days) e-cigarette use, 35 (25%, 95% CI 18, 32) were highly nicotine dependent and 113 (79%) reported ever use of cannabis (Table 2).
Figure 1.
Consort Diagram
Table 1:
Participant Characteristicsa
| Demographics | Overall n=144 N (%) |
Control n=48 N (%) |
Intervention n=96 N (%) |
|---|---|---|---|
| Age (mean, SD) | 16.2 (1.3) | 16.2 (1.3) | 16.2 (1.3) |
| Sex, Male | 50 (35) | 17 (35) | 33 (34) |
| Gender Identity | |||
| Female | 89 (62) | 30 (63) | 59 (62) |
| Male | 49 (34) | 17 (35) | 32 (33) |
| Non-binary | 1 (1) | 0 (0) | 1 (1) |
| Trans Female | 1 (1) | 0 (0) | 1 (1) |
| Trans Male | 2 (1) | 1 (2) | 1 (1) |
| Not Listed/Prefer Not to Answer | 2 (1) | 0 (0) | 2 (2) |
| Race | |||
| White | 83 (58) | 27 (56) | 56 (58) |
| Mixed Race | 25 (17) | 9 (19) | 16 (17) |
| Black or African American | 24 (17) | 7 (15) | 17 (18) |
| American Indian or Alaska Native | 2 (1) | 0 (0) | 2 (2) |
| Native Hawaiian or Other Pacific Islander | 1 (1) | 0 (0) | 1 (1) |
| Prefer Not to Answer | 4 (3) | 2 (4) | 2 (2) |
| Unknown/Unsure | 5 (4) | 3 (6) | 2 (2) |
| Ethnicity | |||
| Not Hispanic | 115 (80) | 35 (73) | 80 (83) |
| Hispanic | 25 (17) | 10 (21) | 15 (16) |
| Prefer Not to Answer | 4 (3) | 3 (6) | 1 (1) |
| Insurance Type | |||
| Medicaid or Other Government | 71 (49) | 23 (48) | 48 (50) |
| Private | 44 (31) | 16 (33) | 28 (29) |
| None | 19 (13) | 7 (15) | 12 (13) |
| Other | 10 (7) | 2 (4) | 8 (8) |
| Mental Health Disorder b | 83 (58) | 29 (60) | 54 (56) |
| Depression | 48 (58) | 12 (41) | 36 (67) |
| Anxiety | 37 (45) | 11 (38) | 26 (48) |
| Suicidal Thoughts | 13 (16) | 5 (17) | 8 (15) |
| Suicide Attempt | 48 (58) | 17 (59) | 31 (57) |
| Bipolar Disorder | 3 (4) | 1 (3) | 2 (4) |
| Attention Deficit Hyperactivity Disorder | 23 (28) | 7 (24) | 16 (30) |
| Autism Spectrum Disorder | 1 (1) | 0 (0) | 1 (2) |
| Other Diagnosis | 12 (15) | 3 (10) | 9 (17) |
| Substance Use Disorder c | 76 (53) | 23 (48) | 53 (55) |
| Cannabis | 66 (76) | 20 (74) | 46 (77) |
| Alcohol | 18 (21) | 8 (30) | 10 (17) |
| Opioid | 2 (2) | 0 (0) | 2 (3) |
| Other Substance | 14 (16) | 5 (19) | 9 (15) |
All values are n (%) unless otherwise noted
% out of those with any mental health diagnosis, can have multiple diagnoses
% out of those with any substance use disorder, can have multiple diagnoses
Table 2:
Baseline Substance Use Behaviors (N (%) [95% CI])
| Substance Use Behavior | Overall N=144 |
Control N=48 |
Intervention N=96 |
|---|---|---|---|
| E-cigarette use in the past 30 days | |||
| 0 days | 0 (0) [0, 3.2] | 0 (0) [0, 9.2] | 0 (0) [0, 4.8] |
| 1-5 (occasional) | 49 (34) [26, 42] | 18 (38) [24, 53] | 31 (32) [23, 43] |
| 6-19 (intermittent) | 36 (25) [18, 33] | 12 (25) [14, 40] | 24 (25) [17, 35] |
| 20+ (frequent) | 56 (39) [31, 47] | 16 (33) [21, 49] | 40 (42) [32, 52] |
| Missing | 3 (2.1) [0.54, 6.4] | 2 (4.2) [0.72, 15] | 1 (1.0) [0.05, 6.5] |
| E-cigarette Penn State Nicotine Dependence Category | |||
| None | 36 (25) [18, 33] | 18 (38) [24, 53] | 18 (19) [12, 28] |
| Low | 40 (28) [21, 36] | 9 (19) [9.4, 33] | 31 (32) [23, 43] |
| Medium | 32 (22) [16, 30] | 10 (21) [11, 35] | 22 (23) [15, 33] |
| High | 35 (24) [18, 32] | 11 (23) [13, 38] | 24 (25) [17, 35] |
| Missing | 1 (0.7) [0.04, 4.4] | 0 (0) [0.00, 9.2] | 1 (1.0) [0.05, 6.5] |
| Cigarette ever use | |||
| No | 70 (49) [40, 57] | 25 (52) [37, 66] | 45 (47) [37, 57] |
| Yes | 55 (38) [30, 47] | 16 (33) [21, 49] | 39 (41) [31, 51] |
| Missing | 19 (13) [8.3, 20] | 7 (15) [6.5, 28] | 12 (13) [6.9, 21] |
| Cigarette use in the past 30 days a | |||
| 0 days | 57 (40) [32, 48] | 15 (31) [19, 46] | 42 (44) [34, 54] |
| 1-5 days (occasional) | 9 (6.3) [3.1, 12] | 4 (8.3) [2.7, 21] | 5 (5.2) [1.9, 12] |
| 6-19 days (intermittent) | 2 (1.4) [0.24, 5.4] | 1 (2.1) [0.11, 12] | 1 (1.0) [0.05, 6.5] |
| 20+ (frequent) | 1 (0.7) [0.04, 4.4] | 0 (0) [0, 9.2] | 1 (1.0) [0.05, 6.5] |
| Missing | 75 (52) [44, 60] | 28 (58) [43, 72] | 47 (49) [39, 59] |
| Cannabis ever use (yes) | 113 (78) [71, 85] | 39 (81) [67, 91] | 74 (77) [67, 85] |
| Cannabis use in the past 30 days a,b | |||
| 0 days | 0 (0) [0, 3.2] | 0 (0) [0, 9.2] | 0 (0) [0, 4.8] |
| 1-5 (occasional) | 16 (11) [6.7, 18] | 9 (19) [9.4, 33] | 7 (7.3) [3.2, 15] |
| 6-19 (intermittent) | 18 (13) [7.8, 19] | 9 (19) [9.4, 33] | 9 (9.4) [4.6, 17] |
| 20+ (frequent) | 9 (6.3) [3.1, 12] | 3 (6.3) [1.6, 18] | 6 (6.3) [2.6, 14] |
| Missing | 75 (52) [44, 60] | 22 (46) [32, 61] | 53 (55) [45, 65] |
| Nicotine pouch ever use c | |||
| No | 24 (17) [11, 24] | 13 (27) [16, 42] | 11 (11) [6.1, 20] |
| Yes | 8 (5.6) [2.6, 11] | 4 (8.3) [2.7, 21] | 4 (4.2) [1.3, 11] |
| Missing | 86 (60) [51, 68] | 26 (54) [39, 68] | 60 (63) [52, 72] |
| Nicotine pouch use in the past 30 days c | |||
| 0 | 28 (19) [14, 27] | 15 (31) [19, 46] | 13 (14) [7.7, 22] |
| 1-5 | 3 (2.1) [0.54, 6.4] | 2 (4.2) [0.72, 15] | 1 (1.0) [0.05, 6.5] |
| 6-19 | 0 (0) [0, 3.2] | 0 (0) [0, 9.2] | 0 (0) [0, 4.8] |
| 20+ | 1 (0.7) [0.04, 4.4] | 0 (0) [0, 9.2] | 1 (1.0) [0.05, 6.5] |
| Missing | 86 (60) [51, 68] | 26 (54) [39, 68] | 60 (63) [52, 72] |
Past 30-day use only asked of those who answered yes to ever use
Question added mid-study, only asked of n=59 (control n=29; intervention n=30)
Question added mid-study, only asked of n=32 (control n=17; intervention n=15)
E-cigarette Abstinence (Primary Outcome)
At 3-month follow-up, the response rate was lower in the intervention than control arm (60% vs. 79%, p = 0.039), with 48 (33%; control: n=10 (21%) vs intervention n=38 (40%); p=0.024)) lost to follow up. Among respondents, 25 (43%) intervention participants and 16 (42%) control participants reported past 30-day e-cigarette abstinence (primary outcome; OR 1.06, 95% CI 0.39–2.89, p=0.91; Table 3). Thirty-six participants (control n=14, intervention n=22) were eligible to complete biochemical verification via mailed cotinine test, 26 declined (control n=10, intervention n=16) and 10 were mailed at home cotinine tests. Biochemical confirmation was completed in 3 (2 control and 1 intervention) participants which were all verified as abstinent (cotinine < 30ng/ml). There was no increase from baseline in past 30-day cigarette use and no difference between control and intervention participants at 3-months (Control 39% vs intervention 25%; p-value=0.48). In our intent-to-treat sensitivity analysis multiple imputation results found the odds ratio (OR) of abstinence was OR 0.77 (95% CI 0.27 – 2.19,p = 0.62) in the intervention as compared to the control arm. Assuming all lost-to-follow-up and non-responders remained e-cigarette and/or tobacco users (i.e., worst-case scenario) demonstrated an OR 0.64 (95%CI 0.21,1.95,p=0.43). On the other hand, the best-case scenario found an OR 1.00 (95%CI 0.45,2.23,p=1.00) in intervention compared to control arms.
Table 3:
3 Month Follow up Assessmenta
| Overall n=96 N (%) |
Control n=38 N (%) |
Intervention n=58 N (%) |
p-value | |
|---|---|---|---|---|
| E-cigarette use in past 30 days | ||||
| 0 days (Abstinence) | 41 (43) | 16 (42) | 25 (43) | 0.91 |
| 2 to 10 days (occasional) | 24 (25) | 12 (32) | 12 (21) | |
| 11 to 19 days (intermittent) | 14 (15) | 5 (13) | 9 (16) | |
| >= 20 days (Frequent) | 17 (18) | 5 (13) | 12 (21) | |
| Salivary cotinine test | ||||
| Declined test | 26 (27) | 10 (26) | 16 (28) | 1 |
| Salivary kit mailedb | 10 (28) | 4 (29) | 6 (27) | |
| Results receivedc | 3 (30) | 2 (20) | 1 (10) | |
| Confirmed abstinentc | 3 (30) | 2 (20) | 1 (10) | |
| Craving to use e-cigarette | 0.623 | |||
| No | 59 (62) | 25 (66) | 34 (59) | |
| Yes | 37 (39) | 13 (34) | 24 (41) | |
| Cigarette use in past 30 days | ||||
| Yes | 15 (30) | 7 (39) | 8 (25) | 0.479 |
| No | 35 (70) | 11 (61) | 24 (75) | |
| NRT use in past 30 days | 0.117 | |||
| No | 83 (87) | 36 (95) | 47 (81) | |
| Yes | 12 (13) | 2 (5) | 10 (17) | |
| Missing | 1 (1) | 0 (0) | 1 (2) |
Out of n=96 who completed the 3-month follow up survey (Control n=38; Intervention n=58)
Out of n=36 (Control n=14; Intervention n=22) who reported past abstinence and no NRT use in past 30 days
Out of n=10 (control n=4; intervention n=6) who were eligible and agreed to complete the salivary cotinine test
Psychological Quit Indicators: Knowledge, Confidence and Motivation (Secondary Efficacy Outcomes)
Our secondary preliminary efficacy outcomes were psychological indicators including knowledge, motivation (questions only asked of n=71 due to technical error) and confidence to quit (eFigure 1,eTable 1) at baseline and 3-months. LMM demonstrated the intervention arm saw a non-significant increase in knowledge (mean score change: 0.38, 95%CI −0.06,0.81,p=0.09), and confidence (mean score change: 0.35, 95%CI0.11,0.80,p=0.13) but no change in motivation (mean score change: −0.01,95%CI −0.64,0.62, p=0.97).
Implementation Outcomes: Acceptability, Feasibility and Fidelity
Acceptability
Of 816 eligible participants 146 (18%) declined study participation and all (n=96) intervention participants completed the index intervention session in the hospital (Figure 1). Forty-seven (49%) made a quit plan, of those 14 (30%) were interested in NRT, 11 (23%) were prescribed NRT, 13 (28%) enrolled in a text-to-quit program (This is Quitting) and 67 (91%) were provided addiction resources (Table 4). Fifty (52%) intervention participants completed all four booster sessions. Among intervention participants 85 (89%) were somewhat/very satisfied with the intervention and 72 (75%) were likely/extremely likely to recommend the intervention to friends or family.
Table 4:
Intervention Characteristics
| N=96 (%) | |
|---|---|
| Duration, mins, Median (IQR) c | 32 (28, 39) |
| Interruptions during intervention, mins, Median (IQR) c | 0 (0, 5) |
| Intervention acceptability | |
| Satisfied with the intervention b | |
| A little | 3 (3) |
| Not sure | 8 (8) |
| Somewhat | 34 (35) |
| Very | 51 (53) |
| Likely to recommend the intervention to your friends and family b | |
| Extremely unlikely | 1 (1) |
| Unlikely | 3 (3) |
| Neutral | 20 (21) |
| Likely | 37 (39) |
| Extremely likely | 35 (37) |
| Likely to stop using e-cigarettes in next 30 days b | |
| Extremely unlikely | 4 (4) |
| Unlikely | 15 (16) |
| Neutral | 22 (23) |
| Likely | 26 (27) |
| Extremely likely | 29 (30) |
| Fidelity score, Mean (SD), 5-point Likert score from 10 items (Maximum 50), n=13d | 43 (3) |
| Made quit plan c | 47 (49) |
| Interested in NRT a b | 14 (30) |
| Nicotine replacement therapy prescribed a c | 11 (23) |
| Enrolled in quit program (This is Quitting) a c | 13 (28) |
| Addiction Clinic information provided (yes) c | 67 (91) |
Out of n=47 intervention participants who made a quit plan
Data collected from participant
Data collected from health educator
Data collected by study team review for fidelity monitoring
Feasibility
The median index in-person index intervention session duration was 32 minutes (IQR:28,39) with a mean of 0 minutes of interruptions (IQR0,5). The health educator agreed that the intervention was easy to deliver for a majority of participants (n=95, 99%) and there was enough time for intervention completion (n=94, 98%).
Fidelity
The mean fidelity score was 43 (SD 3.1) out of a maximum of 50 (43/50=86%) well above our target threshold of 75%.28,34 At the individual item level, analysis indicated the lowest mean score was for reflective listening (mean score 3.9 out of 5 [SD1.4] or 78%) which also exceeded our target threshold for acceptable fidelity.
No serious adverse events were reported during the study.
Exploratory analyses
In exploratory analyses, post-intervention motivation (OR 5.3,p = 0.03;eTable 2) and motivation at 3-months (OR 2.7,p = 0.02), were both associated with higher odds of 30-day abstinence at 3 months after adjusting covariates. Pre-intervention knowledge was also associated with 3-month abstinence (OR 2.0,p = 0.007). In intervention participants only, motivation pre-intervention (OR 9.9;p = 0.001; eTable 3) and post-intervention (OR: 64.5,p=0.018) were associated with 7-day abstinence at 1 month. Knowledge post-intervention (OR: 3.83,p=0.026) was associated with higher odds of 7-day abstinence at 1 month in intervention participants. Participants who attended a higher median number of booster sessions demonstrated increased odds of past 30-day abstinence at 3 months (OR:1.5,p=0.08;eTable 2).
Discussion
In this pilot RCT in 144 hospitalized youth with current e-cigarette use and diverse demographics, including nearly 50% government insurance and >40% non-White race and ethnicity, we found strong acceptability, feasibility and fidelity but no evidence of efficacy of an e-cigarette cessation intervention. All intervention participants completed the index intervention, nearly half made a quit plan and a substantial proportion were interested in and prescribed NRT. Most intervention participants reported intervention satisfaction and the health educator reported ease of intervention delivery during the hospitalization. Previous studies of tobacco use treatment during adult hospitalizations have similarly demonstrated high rates of acceptability, feasibility and uptake, including increased quit attempts, use of pharmacotherapy, engagement in quit programs, however they also have been shown to impact long-term abstinence after discharge.12,13,35,36 The present study of youth was not fully powered to evaluate intervention efficacy, and we did not find any indication of a significant effect on efficacy (i.e., 30-day abstinence between arms at 3 month follow up). We saw minimal evidence of secondary preliminary efficacy among intervention participants based on non-significant positive shifts in psychological indicators of knowledge and confidence to quit. In exploratory analyses, motivation and knowledge to quit emerged as predictors of past 30-day and 7-day vaping abstinence. This study enrolled a heterogeneous mix of current e-cigarette users who were non-treatment seeking and at any stage of motivation and confidence to quit, which may have impacted our ability to detect a significant difference in past-30-day abstinence between arms.
Recent studies targeting youth with e-cigarette use and motivation to quit have demonstrated evidence of efficacy of varenicline and digital quit support applications, thus it is possible our intervention was not found to impact abstinence due to enrolling youth who were not necessarily motivated to quit.7,8 Based on current pediatric medicine guidelines, NRT was prescribed for eligible participants, however in light of recent promising evidence in support of varenicline, further consideration regarding best pharmacotherapy for vaping cessation is needed.8 Additionally, a higher proportion of baseline frequent e-cigarette use and follow-up attrition was observed in the intervention vs. control, which could have impacted findings . Given lack of intervention effect on abstinence, further work is needed to tailor treatment based on quit motivation, knowledge and use frequency and to incorporate based on the best recent evidence to enhance intervention efficacy in this population.
To our knowledge this is the first study to evaluate an e-cigarette cessation intervention for hospitalized youth. Consistent with past literature highlighting the increased risk for mental health and substance use disorders in hospitalized youth, a majority of our participants had documentation of an underlying comorbid mental health or substance use disorder in addition to high rates of frequent e-cigarette use, cannabis co-use, and nicotine dependence. 1,4 While we used purposeful sampling to prioritize enrolling AYAs with EHR documented e-cigarette use, our previous work has shown that EHR data likely underestimates substance use rates compared to self-report.37 Universal screening for substance use during an AYA hospitalization could offset risk for potential missed opportunities to identify hospitalized youth who desire treatment. Given high rates of cannabis co-use in our study, further work is needed to overcome the potential treatment challenges related to co-use of nicotine and cannabis use in this population. Encouragingly, in our study of youth who were not necessarily seeking treatment, we saw high rates of participation interest (only 17% declined), uptake of treatment support in our intervention participants and retention, and increased odds of abstinence based on booster session attendance, which previous youth cessation studies have demonstrated can be challenging.38
While biochemical verification remains the abstinence gold standard in nicotine cessation studies, similar to previous studies we experienced challenges with salivary cotinine test completion.39 Despite adding the option for a home cotinine test (in addition to pre-paid mail back saliva kits) and adding the completion incentive mid-study, few participants completed the salivary cotinine test. This may be due to lack of follow-up or potential hesitancy due to discrepancy between self-reported abstinence and salivary cotinine test results.40 Further, incorporation of intervention elements such as larger incentives and use of mobile health applications or incorporation into our CDS system could improve biochemical verification test completion in future cessation studies. Additionally, limits exist to use of cotinine as biochemical verification for e-cigarette cessation particularly for those using NRT.29 Future work is needed to develop and validate e-cigarette specific biomarkers for abstinence confirmation.
Our study had limitations. Due to practical limitations, the study was not blinded which may have led to bias in the assessment of outcomes by the research team and self-reported outcomes of the participants. Regarding outcome measures, we relied on self-report which is susceptible to social desirability bias and had very low biochemical verification completion rates to confirm our primary outcome despite satisfactory follow up survey completion (67%).41 It is possible that our primary outcome of 30-day abstinence at 3-months was too conservative for preliminary efficacy testing. Our study may have benefited from alternative primary outcome assessments such as past 7-day abstinence at 1- and 3-months to assess early abstinence, which we included in exploratory analyses.40,42,43 As a single site study there is limited generalizability of our findings to other hospitals and settings.
Conclusion
Our work is among the first to demonstrate promising implementation of an e-cigarette cessation intervention in the pediatric hospital where youth with mental health and substance use disorders are frequently cared for. While our intervention was deemed acceptable, feasible and successful at engaging and supporting e-cigarette use cessation in hospitalized AYAs, future adaptation of treatment components may be needed to enhance intervention efficacy.
Supplementary Material
What is Already Known on this topic
E-cigarette use among youth is linked with adverse health outcomes, nicotine dependence, and increased use of other substances including cannabis. Nearly half of adolescent e-cigarette users want to quit, but most attempt quitting unassisted and without pharmacotherapy support, thus are far less likely to quit successfully. E-cigarette cessation studies in youth have primarily focused on community and primary care settings, with limited studies to date focused on the pediatric hospital setting.
What this study adds
In this pilot randomized controlled trial in 144 hospitalized youth with current e-cigarette use and diverse demographics, we found strong acceptability, feasibility and fidelity but no evidence of efficacy of an e-cigarette cessation intervention. Among intervention participants, nearly half made a quit plan and a substantial proportion were interested in and prescribed NRT. These findings support the hospital as a promising setting to engage youth in vaping cessation and may inform future efficacy trials.
How this study might affect research, practice or policy
The hospital, where at-risk youth who may lack primary care access are commonly cared for, is a potentially important setting for youth nicotine vaping cessation intervention. This pilot randomized controlled trial demonstrated strong feasibility and acceptability of a nicotine vaping cessation intervention for hospitalized youth. These findings may inform future cessation interventions tailored to youth motivated to quit and that incorporate emerging pharmacotherapy evidence to optimize efficacy in this population.
Acknowledgements:
We would like to thank Kimber Richter, PhD and Troy Richardson, PhD who served as mentors on this grant for the first two years. We would also like to thank Kelli Behr for assistance with data collection and Cheryl Errichetti for help with data cleaning and creation of the consort diagram and figures. Drs. Richter and Richardson and Ms. Behr and Errichetti did not receive any compensation for their contributions and have no conflicts of interest to disclose.
Funding Source:
Research reported in this publication was supported by the National Institute On Drug Abuse of the National Institutes of Health under Award Number K23DA055736 (PI Masonbrink). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Role of Funder/Sponsor:
The NIH had no role in the design and conduct of the study
Abbreviations:
- AYAs
Adolescent and Young Adults
- MI
Motivational Interviewing
- AAP
American Academy of Pediatrics
- SBIRT
(Screening, Brief Intervention, Referral to Treatment)
- RCT
randomized controlled trial
- NRT
nicotine replacement therapy
- EHR
electronic health record
- CDS
computerized decision support
- SD
Standard deviation
- IQR
Interquartile range
- ED
Emergency department
- CM
Contingency management
Footnotes
Conflicts of Interests: The authors have no conflicts of interest to report and have no additional financial relationships related to this article to disclose.
Trial Registration NCT05936099
Data Sharing
We do not plan to share individual participant data but study protocol, analysis plan, informed consent forms and clinical study report will be made available upon request by any researchers who provide a methodologically sound proposal beginning 3 months and ending 5 years following article publication. Any researcher requiring more study information can contact the corresponding author of the manuscript (Masonbrink) to request sharing of study materials.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
We do not plan to share individual participant data but study protocol, analysis plan, informed consent forms and clinical study report will be made available upon request by any researchers who provide a methodologically sound proposal beginning 3 months and ending 5 years following article publication. Any researcher requiring more study information can contact the corresponding author of the manuscript (Masonbrink) to request sharing of study materials.