Predictors of Patient Engagement in Telehealth-Delivered Tobacco Cessation Treatment during the COVID-19 Pandemic.

Smoking causes one in three cancer deaths and may worsen COVID-19 outcomes. Telehealth tobacco cessation treatment is offered as a covered benefit for patients at the Stanford Cancer Center. We examined predictors of engagement during the COVID-19 pandemic. Data were abstracted from the Electronic Health Record between 3/17/20 (start of pandemic shelter-in-place) and 9/20/22, including patient tobacco use, demographics, and engagement in cessation treatment. Importance of quitting tobacco was obtained for a subset (53%). During the first 2.5 years of the pandemic, 2595 patients were identified as recently using tobacco, and 1571 patients were contacted (61%). Of the 1313 patients still using tobacco (40% women, mean age 59, 66% White, 13% Hispanic), 448 (34%) enrolled in treatment. Patient engagement was greater in pandemic year 1 (42%) than in year 2 (28%) and year 3 (19%). Women (41%) engaged more than men (30%). Patients aged 36-45 (39%), 46-55 (43%), 56-65 (37%), and 66-75 (33%) engaged more than patients aged 18-35 (18%) and >75 (21%). Hispanic/Latinx patients (42%) engaged more than non-Hispanic/Latinx patients (33%). Engagement was not statistically significantly related to patient race. Perceived importance of quitting tobacco was significantly lower in pandemic year 1 than year 2 or 3. Nearly one in three cancer patients engaged in telehealth cessation treatment during the COVID-19 pandemic. Engagement was greater earlier in the pandemic, among women, Hispanic/Latinx individuals, and patients aged 36 to 75. Sheltering-in-place, rather than greater perceived risk, may have facilitated patient engagement in tobacco cessation treatment.

Acceptability and Utility of a Smartphone App to Support Adolescent Mental Health (BeMe): Program Evaluation Study.

BACKGROUND: Adolescents face unprecedented mental health challenges, and technology has the opportunity to facilitate access and support digitally connected generations. The combination of digital tools and live human connection may hold particular promise for resonating with and flexibly supporting young people's mental health. OBJECTIVE: This study aimed to describe the BeMe app-based platform to support adolescents' mental health and well-being and to examine app engagement, usability, and satisfaction. METHODS: Adolescents in the United States, aged 13 to 20 years, were recruited via the web and enrolled between September 1 and October 31, 2022. App engagement, feature use, clinical functioning, and satisfaction with BeMe were examined for 30 days. BeMe provides content based on cognitive behavioral therapy, dialectical behavior therapy, motivational interviewing, and positive psychology; interactive activities; live text-based coaching; links to clinical services; and crisis support tools (digital and live). RESULTS: The average age of the sample (N=13,421) was 15.04 (SD 1.7) years, and 56.72% (7612/13,421) identified with she/her pronouns. For the subsample that completed the in-app assessments, the mean scores indicated concern for depression (8-item Patient Health Questionnaire mean 15.68/20, SD 5.9; n=239), anxiety (7-item Generalized Anxiety Disorder Questionnaire mean 13.37/17, SD 5.0; n=791), and poor well-being (World Health Organization-Five Well-being Index mean 30.15/100, SD 16.1; n=1923). Overall, the adolescents engaged with BeMe for an average of 2.38 (SD 2.7) days in 7.94 (SD 24.1) sessions and completed 11.26 (SD 19.8) activities. Most adolescents engaged with BeMe's content (12,270/13,421, 91.42%), mood ratings (13,094/13,421, 97.56%), and interactive skills (10,098/13,421, 75.24%), and almost one-fifth of the adolescents engaged with coaching (2539/13,421, 18.92%), clinical resources (2411/13,421, 17.96%), and crisis support resources (2499/13,421, 18.62%). Overall app engagement (total activities) was highest among female and gender-neutral adolescents compared with male adolescents (all P<.001) and was highest among younger adolescents (aged 13-14 years) compared with all other ages (all P<.001). Satisfaction ratings were generally high for content (eg, 158/176, 89.8% rated as helpful and 1044/1139, 91.66% improved coping self-efficacy), activities (5362/8468, 63.32% helpful and 4408/6072, 72.6% useful in coping with big feelings), and coaching (747/894, 83.6% helpful and 747/894, 83.6% improved coping self-efficacy). Engagement (total activities completed) predicted the likelihood of app satisfaction (P<.001). CONCLUSIONS: Many adolescents downloaded the BeMe app and completed multiple sessions and activities. Engagement with BeMe was higher among female and younger adolescents. Ratings of BeMe's content, activities, and coaching were very positive for cognitive precursors aimed at reducing depression and anxiety and improving well-being. The findings will inform future app development to promote more sustained engagement, and future evaluations will assess the effects of BeMe on changes in mental health outcomes.

A relational agent for treating substance use in adults: Protocol for a randomized controlled trial with a psychoeducational comparator.

BACKGROUND: Substance use disorders (SUDs) are prevalent and compromise health and wellbeing. Scalable solutions, such as digital therapeutics, may offer a population-based strategy for addressing SUDs. Two formative studies supported the feasibility and acceptability of the relational agent Woebot, an animated screen-based social robot, for treating SUDs (W-SUDs) in adults. Participants randomized to W-SUDs reduced their substance use occasions from baseline to end-of-treatment (EOT) relative to a waitlist control. OBJECTIVE: To further develop the evidence base, the current randomized trial extends follow-up to 1-month post-treatment and will test the efficacy of W-SUDs relative to a psychoeducational control. METHODS: This study will recruit, screen, and consent 400 adults online reporting problematic substance use. Following baseline assessment, participants will be randomized to 8 weeks of W-SUDs or a psychoeducational control. Assessments will be conducted at weeks 4, 8 (EOT), and 12 (1-month post-treatment). Primary outcome is past-month number of substance use occasions, summed across all substances. Secondary outcomes are number of heavy drinking days, the percent of days abstinent from all substances, substance use problems, thoughts about abstinence, cravings, confidence to resist substance use, symptoms of depression and anxiety, and work productivity. If significant group differences are found, we will explore moderators and mediators of treatment effects. CONCLUSIONS: The current study builds upon emerging evidence of a digital therapeutic for reducing problematic substance use by examining sustained effects and testing against a psychoeducational control condition. If efficacious, the findings have implications for scalable mobile health interventions for reducing problematic substance use. TRIAL REGISTRATION: NCT04925570.

Traditional Heart-Healthy Diet and Medication Adherence in the Norton Sound Region: An 18-Month Telehealth Intervention.

INTRODUCTION: Innovations are needed for preventing cardiovascular disease (CVD) and for reaching diverse communities in remote regions. The current study reports on a telemedicine-delivered intervention promoting a traditional heart-healthy diet and medication adherence with Alaska Native men and women residing in the Norton Sound region of Alaska. METHODS: Participants were 299 men and women with high blood pressure or high cholesterol smoking daily who were randomized to receive telemedicine-delivered counseling and printed materials on diet and medication adherence or on smoking and physical activity. Intervention contacts were at baseline and 3-, 6-, and 12-months follow-up, with a final assessment at 18 months. Nutrition outcomes were the ratio of heart-healthy foods and traditional heart-healthy foods relative to all foods reported on a 34-item food frequency questionnaire. Recent and typical adherence for heart medications were self-reported. RESULTS: Intervention effects were significant for the heart-healthy foods ratio at 6 months only (p = 0.014) and significant for the traditional heart-healthy foods ratio at 6 months only for those aged 47+ (p = 0.031). For recent and typical medication adherence, there were no significant group differences by time. DISCUSSION: In a remote region of Alaska, telemedicine proved feasible and acceptable for engaging Alaska Native men and women in counseling on CVD risk behaviors. The findings indicate that more touchpoints may be necessary to impart comprehensive lasting change in heart-healthy eating patterns. Medication adherence group differences were not significant; however, medication adherence was high overall.

Associations Between Substance Use Problems and Stress During COVID-19.

OBJECTIVE: The COVID-19 pandemic has produced major life disruptions and increased stress. We explored associations between pandemic-related stress and substance use problems. METHOD: Adults (N = 180; 65% female) with problematic substance use (CAGE-AID > 1) were recruited online June-August 2020. Measures included the 15-item Short Inventory of Problems-Alcohol and Drugs (SIP-AD), Generalized Anxiety Disorder-7 (GAD-7) seven-item anxiety measure, Patient Health Questionnaire-8 (PHQ-8) eight-item depression measure, a three-item measure of pandemic life disruptions, a six-item measure of pandemic-related mental health effects, and a five-item measure of pandemic-related personal growth. Participants reported whether they frequented bars and attended large gatherings. Participants with children (<18 years of age) in the home completed a four-item measure of pandemic-related worry about children's well-being. Pandemic-related measures with significant bivariate associations with SIP-AD, GAD, and PHQ scores were tested in multivariable linear regression, adjusting for sex, age, and race/ethnicity. RESULTS: Participants who struggled with responsibilities at home, had greater mental health impacts, had greater personal growth, and frequented bars or large gatherings had higher SIPAD scores (all ps < .05). Participants who struggled with responsibilities at home, had difficulty getting necessities, had greater mental health impacts, and worried more about their children had higher GAD-7 and PHQ-8 scores (all ps < .05). Participants who lost a job or income during the pandemic had higher PHQ-8 scores (p = .015). In multivariable analyses, greater mental health impacts were associated with higher SIP-AD, PHQ-8, and GAD-7 scores (all ps < .05). CONCLUSIONS: Experiencing worsened mental health symptoms during COVID-19 was associated with more substance use problems and symptoms of depression and anxiety. Pandemic disruptions may exacerbate preexisting substance use problems.

A randomized controlled trial of a therapeutic relational agent for reducing substance misuse during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic disrupted access to treatment for substance use disorders (SUDs), while alcohol and cannabis retail sales increased. During the pandemic, we tested a tailored digital health solution, Woebot-SUDs (W-SUDs), for reducing substance misuse. METHODS: In a randomized controlled trial, we compared W-SUDs for 8 weeks to a waitlist control. U.S. adults (N = 180) who screened positive for substance misuse (CAGE-AID>1) were enrolled June-August 2020. The primary outcome was the change in past-month substance use occasions from baseline to end-of-treatment (EOT). Study retention was 84%. General linear models tested group differences in baseline-to-EOT change scores, adjusting for baseline differences and attrition. RESULTS: At baseline, the sample (age M = 40, SD = 12, 65% female, 68% non-Hispanic white) averaged 30.2 (SD = 18.6) substance occasions in the past month. Most (77%) reported alcohol problems, 28% cannabis, and 45% multiple substances; 46% reported moderate-to-severe depressive symptoms. Treatment participants averaged 920 in-app text messages (SD = 892, Median = 701); 96% of completed lessons were rated positively; and 88% would recommend W-SUDs. Relative to waitlist, W-SUDs participants significantly reduced past-month substance use occasions (M = -9.1, SE = 2.0 vs. M = -3.3, SE = 1.8; p = .039). Secondary substance use and mood outcomes did not change significantly by group; however, reductions in substance use occasions correlated significantly with increased confidence and fewer substance use problems, cravings, depression and anxiety symptoms, and pandemic-related mental health effects (p-value<.05). CONCLUSIONS: W-SUDs was associated with significant reductions in substance use occasions. Reduction in substance use occasions was associated with better outcomes, including improved mental health. W-SUDs satisfaction was high.

A Therapeutic Relational Agent for Reducing Problematic Substance Use (Woebot): Development and Usability Study.

BACKGROUND: Misuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Woebot is a mental health digital solution informed by cognitive behavioral therapy and built upon an artificial intelligence-driven platform to deliver tailored content to users. In a previous 2-week randomized controlled trial, Woebot alleviated depressive symptoms. OBJECTIVE: This study aims to adapt Woebot for the treatment of substance use disorders (W-SUDs) and examine its feasibility, acceptability, and preliminary efficacy. METHODS: American adults (aged 18-65 years) who screened positive for substance misuse without major health contraindications were recruited from online sources and flyers and enrolled between March 27 and May 6, 2020. In a single-group pre/postdesign, all participants received W-SUDs for 8 weeks. W-SUDs provided mood, craving, and pain tracking and modules (psychoeducational lessons and psychotherapeutic tools) using elements of dialectical behavior therapy and motivational interviewing. Paired samples t tests and McNemar nonparametric tests were used to examine within-subject changes from pre- to posttreatment on measures of substance use, confidence, cravings, mood, and pain. RESULTS: The sample (N=101) had a mean age of 36.8 years (SD 10.0), and 75.2% (76/101) of the participants were female, 78.2% (79/101) were non-Hispanic White, and 72.3% (73/101) were employed. Participants' W-SUDs use averaged 15.7 (SD 14.2) days, 12.1 (SD 8.3) modules, and 600.7 (SD 556.5) sent messages. About 94% (562/598) of all completed psychoeducational lessons were rated positively. From treatment start to end, in-app craving ratings were reduced by half (87/101, 86.1% reporting cravings in the app; odds ratio 0.48, 95% CI 0.32-0.73). Posttreatment assessment completion was 50.5% (51/101), with better retention among those who initially screened higher on substance misuse. From pre- to posttreatment, confidence to resist urges to use substances significantly increased (mean score change +16.9, SD 21.4; P<.001), whereas past month substance use occasions (mean change -9.3, SD 14.1; P<.001) and scores on the Alcohol Use Disorders Identification Test-Concise (mean change -1.3, SD 2.6; P<.001), 10-item Drug Abuse Screening Test (mean change -1.2, SD 2.0; P<.001), Patient Health Questionnaire-8 item (mean change 2.1, SD 5.2; P=.005), Generalized Anxiety Disorder-7 (mean change -2.3, SD 4.7; P=.001), and cravings scale (68.6% vs 47.1% moderate to extreme; P=.01) significantly decreased. Most participants would recommend W-SUDs to a friend (39/51, 76%) and reported receiving the service they desired (41/51, 80%). Fewer felt W-SUDs met most or all of their needs (22/51, 43%). CONCLUSIONS: W-SUDs was feasible to deliver, engaging, and acceptable and was associated with significant improvements in substance use, confidence, cravings, depression, and anxiety. Study attrition was high. Future research will evaluate W-SUDs in a randomized controlled trial with a more diverse sample and with the use of greater study retention strategies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04096001; http://clinicaltrials.gov/ct2/show/NCT04096001.

Treating tobacco dependence to aid re-employment among job-seekers: A randomized controlled trial.

INTRODUCTION: U.S. reductions in smoking have not been experienced equally. Smoking prevalence is greater among persons of lower education, lower income, and unemployed. We evaluated whether a cessation intervention for job-seekers would result in significantly fewer cigarettes smoked per day and a greater likelihood of tobacco abstinence and re-employment, compared to the control condition at 6-months follow-up. METHODS: Unemployed, job-seekers who smoked daily were recruited from five employment development departments in the San Francisco Bay Area, October 2015 to February 2018. Intention to quit smoking was not required. Participants were randomized to a brief motivationally-tailored, computer-assisted counseling intervention or referred to a toll-free quitline. Midstudy, 8-weeks of combination nicotine replacement was added to the intervention. Expired carbon monoxide and cotinine testing verified abstinence. Data were analyzed fall 2019. RESULTS: Participants (N = 360; 70% men; 43% African American, 27% non-Hispanic Caucasian; 19% unhoused) averaged 12 cigarettes/day (SD = 6), 67% smoked within 30 min of wakening; 27% were in preparation stage to quit. During the 6-month study period, intervention participants were more likely to make a quit attempt (71% vs. 58%, p = .021) and reported significantly greater reduction in cigarettes/day than control participants (median reduction: 6.9 vs. 5.0, p = .038); however, bioconfirmed abstinence (3%) and re-employment (36%) did not differ by treatment group. CONCLUSIONS: In a diverse sample with economic hardships, quit attempts and smoking reduction were greater in the intervention group; however, few achieved abstinence, and neither abstinence nor re-employment differed by condition. A priority group, further research is needed on smoking and re-employment.

Discretionary spending priorities of unemployed, job-seeking adults who smoke cigarettes.

OBJECTIVE: Tobacco use is detrimental to physical and financial wellbeing. Smoking is associated with unemployment and a harder time finding re-employment. The current study examined job-seekers' prioritization of smoking over other discretionary items. METHODS: Adult, unemployed job-seekers smoking daily ranked items from 1 (highest) to 13 (lowest) for prioritization of their discretionary spending. The online survey randomly ordered the presentation of items. The Heaviness of Smoking Index (HSI, time to first cigarette and cigarettes per day) assessed severity of nicotine addiction. RESULTS: The sample (N = 290) was 70% men, 42% African American and 30% non-Hispanic Caucasian, with mean age of 43 (SD = 11), smoking an average of 12 cigarettes per day (SD = 6), and 67% smoking within 30 min of waking. Overall, cigarettes (M = 4.7, SD = 3.1) ranked second in importance behind only food (M = 2.5, SD = 2.7); 45% of the sample ranked tobacco in their top 3 spending priorities, and 26% ranked cigarettes as a higher priority than food. Cellular charges, transportation, grooming, and clothing ranked third through sixth, respectively. Higher HSI scores significantly correlated with greater prioritization of cigarettes (r = -0.25), and lower prioritization of food (r = 0.16) and transportation (r = 0.13), p's < 0.05. CONCLUSIONS: Findings indicate cigarettes were highly prioritized, second only to food among job-seekers who smoke. Cigarettes were prioritized over job-seeking resources and health care, particularly among those who were more heavily addicted. Tobacco addiction can preempt basic life needs and reduce resources for finding re-employment.

Online Patient-Provider E-cigarette Consultations: Perceptions of Safety and Harm.

INTRODUCTION: E-cigarettes are popular and unregulated. Patient-provider communications concerning e-cigarettes were characterized to identify patient concerns, provider advice and attitudes, and research needs. METHODS: An observational study of online patient-provider communications was conducted January 2011-June 2015 from a network providing free medical advice, and analyzed July 2014-May 2016. Patient and provider themes, and provider attitudes toward e-cigarettes (positive, negative, or neutral) were coded qualitatively. Provider attitudes were analyzed with cumulative logit modeling to account for clustering. Patient satisfaction with provider responses was expressed via a Thank function. RESULTS: An increase in e-cigarette-related questions was observed over time. Patient questions (N=512) primarily concerned specific side effects and harms (34%); general safety (27%); e-cigarettes as quit aids (19%); comparison of e-cigarette harms relative to combusted tobacco (18%); use with pre-existing medical conditions (18%); and nicotine-free e-cigarettes (14%). Half of provider responses discussed e-cigarettes as a harm reduction option (48%); 26% discussed them as quit aids. Overall, 47% of providers' responses represented a negative attitude toward e-cigarettes; 33% were neutral (contradictory or non-committal); and 20% were positive. Attitudes did not differ statistically by medical specialty; provider responses positive toward e-cigarettes received significantly more Thanks. CONCLUSIONS: Examination of online patient-provider communications provides insight into consumer health experience with emerging alternative tobacco products. Patient concerns largely related to harms and safety, and patients preferred provider responses positively inclined toward e-cigarettes. Lacking conclusive evidence of e-cigarette safety or efficacy, healthcare providers encouraged smoking cessation and recommended first-line cessation treatment approaches.

Likelihood of Unemployed Smokers vs Nonsmokers Attaining Reemployment in a One-Year Observational Study.

IMPORTANCE: Studies in the United States and Europe have found higher smoking prevalence among unemployed job seekers relative to employed workers. While consistent, the extant epidemiologic investigations of smoking and work status have been cross-sectional, leaving it underdetermined whether tobacco use is a cause or effect of unemployment. OBJECTIVE: To examine differences in reemployment by smoking status in a 12-month period. DESIGN, SETTING, AND PARTICIPANTS: An observational 2-group study was conducted from September 10, 2013, to August 15, 2015, in employment service settings in the San Francisco Bay Area (California). Participants were 131 daily smokers and 120 nonsmokers, all of whom were unemployed job seekers. Owing to the study's observational design, a propensity score analysis was conducted using inverse probability weighting with trimmed observations. Including covariates of time out of work, age, education, race/ethnicity, and perceived health status as predictors of smoking status. MAIN OUTCOMES AND MEASURES: Reemployment at 12-month follow-up. RESULTS: Of the 251 study participants, 165 (65.7) were men, with a mean (SD) age of 48 (11) years; 96 participants were white (38.2%), 90 were black (35.9%), 24 were Hispanic (9.6%), 18 were Asian (7.2%), and 23 were multiracial or other race (9.2%); 78 had a college degree (31.1%), 99 were unstably housed (39.4%), 70 lacked reliable transportation (27.9%), 52 had a criminal history (20.7%), and 72 had received prior treatment for alcohol or drug use (28.7%). Smokers consumed a mean (SD) of 13.5 (8.2) cigarettes per day at baseline. At 12-month follow-up (217 participants retained [86.5%]), 60 of 108 nonsmokers (55.6%) were reemployed compared with 29 of 109 smokers (26.6%) (unadjusted risk difference, 0.29; 95% CI, 0.15-0.42). With 6% of analysis sample observations trimmed, the estimated risk difference indicated that nonsmokers were 30% (95% CI, 12%-48%) more likely on average to be reemployed at 1 year relative to smokers. Results of a sensitivity analysis with additional covariates of sex, stable housing, reliable transportation, criminal history, and prior treatment for alcohol or drug use (25.3% of observations trimmed) reduced the difference in employment attributed to smoking status to 24% (95% CI, 7%-39%), which was still a significant difference. Among those reemployed at 1 year, the average hourly wage for smokers was significantly lower (mean [SD], $15.10 [$4.68]) than for nonsmokers (mean [SD], $20.27 [$10.54]; F(1,86) = 6.50, P = .01). CONCLUSIONS AND RELEVANCE: To our knowledge, this is the first study to prospectively track reemployment success by smoking status. Smokers had a lower likelihood of reemployment at 1 year and were paid significantly less than nonsmokers when reemployed. Treatment of tobacco use in unemployment service settings is worth testing for increasing reemployment success and financial well-being.