Traditional Mexican dietary pattern and cancer risk among women of Mexican descent.

PURPOSE: To examine the association of a traditional Mexican diet score with risk of total, breast, and colorectal cancer among women of Mexican ethnic descent in the Women's Health Initiative (WHI). METHODS: Participants were WHI enrollees who self-identified as being of Mexican descent. Data from food frequency questionnaires self-administered at study baseline were used to calculate the MexD score, with higher scores indicating greater adherence to an a priori-defined traditional Mexican diet (high in dietary fiber, vegetables, and legumes). Incident cancers were self-reported by participants from 1993 to 2020 and adjudicated by trained physicians. We used multivariable-adjusted Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Among 2,343 Mexican descent women (median baseline age: 59 years), a total of 270 cancers (88 breast, 37 colorectal) occurred during a mean follow-up of 14.4 years. The highest tertile of MexD score was associated with a lower risk of all-cancer incidence (HR: 0.67; 95% CI 0.49-0.91; p-trend: 0.01) and colorectal cancer (HR: 0.38; 95% CI 0.14-0.998; p-trend < 0.05), with each unit increase in the MexD score associated with a 6% lower risk of all-cancer incidence (HR: 0.94; 95% CI 0.88-0.99). There was no statistically significant association with risk of breast cancer. CONCLUSION: Consumption of a traditional Mexican diet was associated with a significantly lower risk of all-cancer incidence and colorectal cancer. Confirmation of these findings in future studies is important, given the prevalence of colorectal cancer and a growing U.S. population of women of Mexican descent.

Relative Efficacy of an Acceptance and Commitment Therapy-Based Smartphone App with a Standard US Clinical Practice Guidelines-Based App for Smoking Cessation in Dual Users of Combustible and Electronic Cigarettes: Secondary Findings from a Randomized Trial.

BACKGROUND: While smartphone apps for smoking cessation have shown promise for combustible cigarette smoking cessation, their efficacy in helping dual users of combustible and electronic cigarettes (e-cigarettes) to quit cigarettes remains unknown. This study utilized data from a randomized trial to determine if an Acceptance and Commitment Therapy (ACT)-based app (iCanQuit) was more efficacious than a US Clinical Practice Guidelines-based app (QuitGuide) for combustible cigarette smoking cessation among 575 dual users. METHODS: The primary cessation outcome was self-reported, complete-case 30-day abstinence from combustible cigarettes at 12 months. Logistic regression assessed the interaction between dual use and treatment arm on the primary outcome in the full trial sample (N = 2,415). We then compared the primary outcome between arms among dual users (iCanQuit: n = 297; QuitGuide: n = 178). Mediation analyses were conducted to explore mechanisms of action of the intervention: acceptance of cues to smoke and app engagement. Results: There was an interaction between dual use of combustible and e-cigarettes and treatment arm on the primary outcome (p = 0.001). Among dual users, 12-month abstinence from cigarettes did not differ between arms (23% for iCanQuit vs. 27% for QuitGuide, p = 0.40). Mediation analysis revealed a significant positive indirect effect of the iCanQuit app on 12-month abstinence from cigarettes through acceptance of emotions that cue smoking (p = 0.004). CONCLUSIONS: Findings from this study of dual users of combustible and e-cigarettes showed no evidence of a difference in quit rates between arms. Acceptance of emotions that cue smoking is a potential mechanism contributing to cigarette smoking abstinence among dual users.

Dietary inflammatory index and cardiovascular disease risk in Hispanic women from the Women's Health Initiative.

BACKGROUND: To evaluate the association between the dietary inflammatory index (DII®) and incident cardiovascular disease (CVD) in Hispanic women from the Women's Health Initiative (WHI), and to determine if body mass index (BMI) interacted with the DII scores. METHODS: Secondary analysis of baseline dietary data and long-term CVD outcomes among 3,469 postmenopausal women who self-identified as Hispanic enrolled in WHI. DII scores were calculated from self-administered food frequency questionnaires. The CVD outcomes included coronary heart disease (CHD) and stroke. Stratified Cox regression models were used to assess the relationship between DII scores and CVD in women with and without obesity. Models were adjusted for age, lifestyle risk factors, known risk factors, and neighborhood socioeconomic status. RESULTS: The incidence of CHD was 3.4 and 2.8% for stroke after a median follow-up of 12.9 years. None of the DIIs were associated with CVD risk in this sample of Hispanic women. BMI interacted with the DII (p < 0.20) and stratified models showed that the associations between the DII and CVD were only significant in women with overweight (p < 0.05). In this group, higher DII scores were associated with a higher risk of CHD (HR 1.27; 95% CI: 1.08, 1.51) and a higher risk of stroke (HR 1.32; 95% CI: 1.07, 1.64). CONCLUSION: Among postmenopausal Hispanic women with overweight, greater adherence to pro-inflammatory diets was associated with higher risk of CVD. Additional research is needed to understand how to promote long-term heart-healthy dietary habits to reduce inflammation and prevent CVD in at-risk Hispanic women.

Role of perceived discrimination and anxiety sensitivity in cigarette smoking among english-speaking latinx adults living in the United States.

OBJECTIVE: The Latinx/Hispanic (hereafter, Latinx) population in the United States (US) experiences significant tobacco-related health disparities. Extant work suggests social determinants of health (SDoH) such as perceived discrimination is an individual differences factor for cigarette smoking behavior among Latinx individuals who smoke cigarettes. Other research has suggested sensitivity to internal cues, referred to as anxiety sensitivity, is related to smoking among Latinx adults, but this work has not explored whether anxiety sensitivity may moderate the association between perceived discrimination and smoking behavior. METHOD: Therefore, the present investigation sought to explore the main and interactive association of perceived discrimination and anxiety sensitivity in relation to cigarettes smoked per day, severity of problems experienced when quitting, and perceived barriers for smoking cessation among 338 English-speaking Latinx individuals living in the US (Mage = 35.5 years; SD = 8.65; age range 18-61; 37.3% female) who smoke cigarettes. RESULTS: Results supported statistically significant main effects for perceived discrimination and anxiety sensitivity in relation to increased severity of problems experienced when quitting and perceived barriers for smoking cessation. These associations were evident after adjusting for a sociodemographic covariates. CONCLUSION: Overall, the present investigation suggests that both perceived discrimination and anxiety sensitivity are important constructs relevant to understanding smoking processes among Latinx adults who smoke cigarettes and should be integrated in theoretical models of smoking among this population.

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials.

BACKGROUND: A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods. OBJECTIVE: This study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529). METHODS: Standard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction. RESULTS: The AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold). CONCLUSIONS: Logistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes.

Acceptance and Commitment Therapy-Based Smartphone Applications for Cessation of Tobacco Use among Adults with High Nicotine Dependence: Results from the iCanQuit Randomized Trial.

Background: With 1 in 2 adult tobacco users being highly dependent on nicotine, population-based interventions specifically designed for this group are urgently needed. This study used data from a randomized trial to evaluate whether (1) Acceptance and Commitment Therapy (ACT) delivered via a smartphone application (iCanQuit) would be more efficacious for cessation of nicotine-containing tobacco products than the US Clinical Practice Guidelines (USCPG)-based application (QuitGuide) among highly nicotine-dependent adults, (2) the effect of treatment on cessation was mediated by increases in acceptance of cravings to smoke, and (3) treatment utilization and satisfaction differed by arm. Methods: A total of 1452 highly nicotine-dependent adults received the iCanQuit or QuitGuide application for 12-months. Cessation outcomes were self-reported complete-case 30-day abstinence of nicotine-containing tobacco products (e.g., combustible cigarettes, e-cigarettes, chewing tobacco, snus, hookahs, cigars, cigarillos, tobacco pipes, and kreteks) at 3, 6, and 12-month post-randomization timepoints, missing-as-smoking, and multiple imputation analyses. Acceptance of cues to smoke and satisfaction with the applications was also reported. Results: Participants who received iCanQuit were significantly more likely to report 30-day abstinence of nicotine-containing tobacco products than those who received QuitGuide at 12-months (24% vs. 17%; OR = 1.47 95% CI: 1.11, 1.95). iCanQuit participants utilized their application more frequently and reported greater satisfaction than those who received QuitGuide. Increases in participants' acceptance of cues to smoke mediated the intervention effect on cessation of nicotine-containing tobacco products. Conclusions: Among nicotine-dependent adults, an application-delivered ACT-based intervention was more engaging and efficacious than a USCPG-based intervention for cessation of nicotine-containing tobacco products.

Older adults who smoke: Do they engage with and benefit from web-based smoking cessation interventions?

Quitting smoking at any age increases life expectancy, but older adults face barriers to receiving cessation services. Despite the promise of web-based smoking cessation interventions to help address access barriers, whether older adults who participate in smoking cessation programs engage with and benefit from these tools at the same rate as younger adults remains unknown. In this secondary analysis, we compared engagement and satisfaction with two web-based smoking cessation interventions and quit rates between older, middle-aged, and young adults in the United States enrolled in the WebQuit trial between March 2014 and August 2015. Participants were divided into age groups: older (60 years and older, n = 439/2637), middle-aged (40-59 years, n = 1308/2637), and young adults (18-39 years, n = 890/2637). Treatment engagement and satisfaction, and 12-month quit rates (self-reported complete-case 30-day PPA and missing-as-smoking) were compared between groups. Older adults engaged more with the websites than young adults through multiple indicators of intervention engagement (i.e., number of sessions, unique days of use, and time spent on the site), and older adults spent more time on the site per session than their counterparts. Satisfaction with websites was high (81%) and non-differential between groups. Older and middle-aged adults quit smoking at a similar rate as younger adults (24%, 24%, 27%, respectively, p = 0.905). Older and middle-aged adults who participated in a web-delivered smoking cessation intervention engaged more with the intervention than their younger counterparts and they quit smoking at a similar rate, thereby demonstrating high acceptability and potential of digital interventions to help older adults quit smoking. Trial registration:ClinicalTrials.gov Identifier: NCT1166334.

Efficacy of an acceptance and commitment therapy-based smartphone application for helping rural populations quit smoking: Results from the iCanQuit randomized trial.

Limited access to evidence-based smoking cessation interventions among rural populations contributes to high rates of cigarette smoking and poor cessation outcomes. Yet, accessible digital interventions for cessation focusing on rural populations are lacking. In a secondary analysis, we determined the acceptability and efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) relative to a U.S. Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) for smoking cessation among rural participants enrolled in the two-arm randomized iCanQuit trial. Participants were enrolled between May 2017 and September 2018 and randomized to either receive iCanQuit or QuitGuide for 12-months. Rural residence was determined by sub-county level Rural-Urban Commuting Area codes. A total of 550 rural participants were recruited from 43 U.S. states. Self-reported complete-case 30-day point-prevalence abstinence was 15% (33/226) for iCanQuit vs. 9% (22/253) for QuitGuide at 3-months (OR = 1.83; 95% CI: 1.03, 3.25) and 29% (66/231) for iCanQuit vs. 25% (64/288) for QuitGuide at 12-months (OR = 1.19 95% CI: 0.80, 1.79). Retention rate was 89% at 12-months and did not differ by arm. iCanQuit vs. QuitGuide participants were significantly more engaged and satisfied with the iCanQuit application. Increased acceptance of internal cues to smoke mediated the effect of treatment on cessation. Findings suggest that iCanQuit had significantly higher short-term quit rates, descriptively higher long-term quit rates, and operated through its hypothesized mechanisms of action relative to QuitGuide. Future larger studies are needed to further evaluate the efficacy of and methods for disseminating the iCanQuit application for smoking cessation among U.S. rural adults nationwide. Trial registrationClinicalTrials.gov Identifier: NCT02724462.

Efficacy and Utilization of Smartphone Applications for Smoking Cessation Among American Indians and Alaska Natives: Results From the iCanQuit Trial.

INTRODUCTION: There is tremendous need for efficacious and accessible interventions for smoking cessation among American Indians and Alaska Natives. We tested the efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) versus US Clinical Practice Guidelines-based smartphone application (QuitGuide) for smoking cessation among American Indians and Alaska Natives. AIMS AND METHODS: We compared cessation, changes in ACT-based processes, engagement and satisfaction between American Indian and Alaska Native iCanQuit (n = 89) and QuitGuide (n = 80) participants enrolled in the iCanQuit trial. The primary outcome was self-reported, complete-case, 30-day point-prevalence abstinence. Follow-up timepoints were 12, 6, and 3 months. RESULTS: Randomized American Indians and Alaska Natives from 31 US states (70% urban, 30% rural, with 25% of participants residing on tribal land). The outcome data retention rates were 93%, 92%, and 90% at the 12-, 6-, and 3-month follow-ups, respectively, with no differential retention between arms. The 30-day point-prevalence abstinence for iCanQuit versus QuitGuide was 30% versus 18% at 12 months (odds ratio [OR] = 1.96; 95% confidence interval [CI]: 0.90 to 4.26) 25% versus 11% at 6 months (OR = 2.62; 95% CI: 1.06 to 6.45), and 15% versus 6% at 3 months (OR = 2.93; 95% CI: 0.90 to 9.59). Increases in acceptance of internal cues to smoke mediated the effect of treatment on smoking cessation at 12 months. iCanQuit arm participants were also significantly more engaged and satisfied with their assigned application. CONCLUSIONS: In a nationwide sample with high data retention and participant engagement, this is the first study to show that a digital intervention may be efficacious for helping American Indians and Alaska Natives quit smoking. IMPLICATIONS: This is the first study to provide evidence of an efficacious, accessible, and engaging treatment for helping American Indians and Alaska Natives quit smoking. Compared to a US Clinical Practice Guidelines-based smartphone application (QuitGuide), an ACT-based smartphone application (iCanQuit) was more efficacious, engaging, and satisfactory among American Indians and Alaska Natives nationwide. Our results will inform the tailoring of the iCanQuit smartphone application for American Indian and Alaska Native tribal communities and organizations with potential for broad dissemination and high impact.

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial.

BACKGROUND: Little is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes. OBJECTIVE: In the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership. METHODS: Functional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app. RESULTS: For iCanQuit, participants were clustered into 3 groups: "1-week users" (610/1069, 57.06%), "4-week users" (303/1069, 28.34%), and "26-week users" (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P<.001). For QuitGuide, participants were clustered into 2 groups: "1-week users" (695/1064, 65.32%) and "3-week users" (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app. CONCLUSIONS: Patterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful.

Structural equation modeling of the associations between the home environment and obesity-related cardiovascular fitness and insulin resistance among Hispanic children.

Hispanic children are disproportionally affected by obesity-related risk of metabolic disease. We used the structural equation modeling to examine the associations between specific diet and physical activity (PA) behaviors at home and Hispanic children's metabolic health. A total of 187 Hispanic children and their parents from an urban community in Wisconsin participated in the study. Exposure variables included, children's daily intake of sugar-sweetened beverages (SSB) and PA; home availability of SSB and PA areas/equipment; and parents' intake of SSB and PA, assessed through self-administered questionnaires. Outcome variables for children's metabolic health included, measured anthropometrics; cardiovascular fitness assessed using the Progressive Aerobic Cardiovascular Endurance Run (PACER); and insulin resistance determined with the homeostasis model assessment of insulin resistance (HOMAIR). We found that children's daily intake of SSB was positively associated with BMI z-score, which in turn, was positively associated with HOMAIR (P < 0.05). Specific diet behaviors at home associated with children's intake of SSB, included home availability of SSB, which mediated the association between parents' and children's intake of SSB (P < 0.05). Children's PA was positively associated with PACER z-score, which in turn, was inversely associated with HOMAIR (P < 0.05). Specific PA behaviors at home associated with children's PA, included home availability of PA areas/equipment, which mediated the association between parents' and children's PA (P < 0.05). The structural equation model indices suggested a satisfactory model fit (Chi-square, X(2) = 53.1, comparative fix index = 0.92, root-mean-squared error associated = 0.04). The findings confirm the need for interventions at the family level that promotes healthier home environments by targeting poor diet and low levels of PA in all family members.

Development and Use of a Traditional Mexican Diet Score in Relation to Systemic Inflammation and Insulin Resistance among Women of Mexican Descent.

BACKGROUND: Women of Mexican descent are disproportionally affected by obesity, systemic inflammation, and insulin resistance (IR). Available approaches used to give scores to dietary patterns relative to dietary guidelines may not effectively capture traditional diets of Mexicans, who comprise the largest immigrant group in the United States. OBJECTIVES: We characterized an a priori traditional Mexican diet (MexD) score high in corn tortillas, beans, soups, Mexican mixed dishes (e.g., tamales), fruits, vegetables, full-fat milk, and Mexican cheeses and low in refined grains and added sugars and evaluated the association of the MexD score with systemic inflammation and IR in 493 postmenopausal participants in the Women's Health Initiative (WHI) who are of Mexican ethnic descent. METHODS: The MexD score was developed from the baseline (1993-1998) WHI food frequency questionnaire, which included Hispanic foods and was available in Spanish. Body mass index (BMI) was computed from baseline measured weight and height, and ethnicity was self-reported. Outcome variables were high sensitivity C-reactive protein (hsCRP), glucose, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), and triglyceride concentrations measured at follow-up (2012-2013). Multivariable linear and logistic regression models were used to test the associations of the MexD score with systemic inflammation and IR. RESULTS: The mean ± SD MexD score was 5.8 ± 2.1 (12 maximum points) and was positively associated with intakes of carbohydrates, vegetable protein, and dietary fiber and inversely associated with intakes of added sugars and total fat (P < 0.01). Women with high compared with low MexD scores, consistent with a more-traditional Mexican diet, had 23% and 15% lower serum hsCRP (P < 0.05) and insulin concentrations, respectively (P < 0.05). Baseline BMI modified these associations such that lower MexD scores were associated with higher insulin and HOMA-IR in overweight/obese women (P-interaction <0.05). CONCLUSION: These findings suggest that greater adherence to a traditional Mexican diet could help reduce the future risk of systemic inflammation and IR in women of Mexican descent.

Conversational Chatbot for Cigarette Smoking Cessation: Results From the 11-Step User-Centered Design Development Process and Randomized Controlled Trial.

BACKGROUND: Conversational chatbots are an emerging digital intervention for smoking cessation. No studies have reported on the entire development process of a cessation chatbot. OBJECTIVE: We aim to report results of the user-centered design development process and randomized controlled trial for a novel and comprehensive quit smoking conversational chatbot called QuitBot. METHODS: The 4 years of formative research for developing QuitBot followed an 11-step process: (1) specifying a conceptual model; (2) conducting content analysis of existing interventions (63 hours of intervention transcripts); (3) assessing user needs; (4) developing the chat's persona ("personality"); (5) prototyping content and persona; (6) developing full functionality; (7) programming the QuitBot; (8) conducting a diary study; (9) conducting a pilot randomized controlled trial (RCT); (10) reviewing results of the RCT; and (11) adding a free-form question and answer (QnA) function, based on user feedback from pilot RCT results. The process of adding a QnA function itself involved a three-step process: (1) generating QnA pairs, (2) fine-tuning large language models (LLMs) on QnA pairs, and (3) evaluating the LLM outputs. RESULTS: We developed a quit smoking program spanning 42 days of 2- to 3-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing Food and Drug Administration-approved cessation medications, coping with triggers, and recovering from lapses and relapses. In a pilot RCT with 96% three-month outcome data retention, QuitBot demonstrated high user engagement and promising cessation rates compared to the National Cancer Institute's SmokefreeTXT text messaging program, particularly among those who viewed all 42 days of program content: 30-day, complete-case, point prevalence abstinence rates at 3-month follow-up were 63% (39/62) for QuitBot versus 38.5% (45/117) for SmokefreeTXT (odds ratio 2.58, 95% CI 1.34-4.99; P=.005). However, Facebook Messenger intermittently blocked participants' access to QuitBot, so we transitioned from Facebook Messenger to a stand-alone smartphone app as the communication channel. Participants' frustration with QuitBot's inability to answer their open-ended questions led to us develop a core conversational feature, enabling users to ask open-ended questions about quitting cigarette smoking and for the QuitBot to respond with accurate and professional answers. To support this functionality, we developed a library of 11,000 QnA pairs on topics associated with quitting cigarette smoking. Model testing results showed that Microsoft's Azure-based QnA maker effectively handled questions that matched our library of 11,000 QnA pairs. A fine-tuned, contextualized GPT-3.5 (OpenAI) responds to questions that are not within our library of QnA pairs. CONCLUSIONS: The development process yielded the first LLM-based quit smoking program delivered as a conversational chatbot. Iterative testing led to significant enhancements, including improvements to the delivery channel. A pivotal addition was the inclusion of a core LLM-supported conversational feature allowing users to ask open-ended questions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03585231; https://clinicaltrials.gov/study/NCT03585231.

Do medications increase the efficacy of digital interventions for smoking cessation? Secondary results from the iCanQuit randomized trial.

BACKGROUND AND AIMS: iCanQuit is a smartphone application (app) proven efficacious for smoking cessation in a Phase III randomized controlled trial (RCT). This study aimed to measure whether medications approved by the US Food and Drug Administration (FDA) for smoking cessation would further enhance the efficacy of iCanQuit, relative to its parent trial comparator-the National Cancer Institute's (NCI's) QuitGuide app. DESIGN: Secondary analysis of the entire parent trial sample of a two-group (iCanQuit and QuitGuide), stratified, doubled-blind RCT. SETTING: United States. PARTICIPANTS: Participants who reported using an FDA-approved cessation medication on their own (n = 619) and those who reported no use of cessation medications (n = 1469). INTERVENTIONS: Participants were randomized to receive iCanQuit app or NCI's QuitGuide app. MEASUREMENTS: Use of FDA-approved medications was measured at 3 months post-randomization. Smoking cessation outcomes were measured at 3, 6 and 12 months. The primary outcome was 12-month self-reported 30-day point prevalence abstinence (PPA). FINDINGS: The data retention rate at the 12-month follow-up was 94.0%. Participants were aged 38.5 years, 71.0% female, 36.6% minority race/ethnicity, 40.6% high school or less education, residing in all 50 US States and smoking 19.2 cigarettes/day. The 29.6% of all participants who used medications were more likely to choose nicotine replacement therapy (NRT; 78.8%) than other cessation medications (i.e. varenicline or bupropion; 18.3 and 10.5%, respectively) and use did not differ by app treatment assignment (all P > 0.05). There was a significant (P = 0.049) interaction between medication use and app treatment assignment on PPA. Specifically, 12-month quit rates were 34% for iCanQuit versus 20% for QuitGuide [odds ratio (OR) = 2.36, 95% confidence interval (CI) = 1.59, 3.49] among participants reporting any medication use, whereas among participants reporting no medication use, quit rates were 28% for iCanQuit versus 22% for QuitGuide (OR = 1.41, 95% CI = 1.09, 1.82). Results were stronger for those using only NRT: 40% quit rates for iCanQuit versus 18% quit rates for QuitGuide (OR = 3.57, 95% CI = 2.20, 5.79). CONCLUSIONS: The iCanQuit smartphone app for smoking cessation was more efficacious than the QuitGuide smartphone app, regardless of whether participants used medications to aid cessation. Smoking cessation medications, especially nicotine replacement therapy, might enhance the efficacy of the iCanQuit app.

Emotional dysregulation among English-speaking Hispanic persons who smoke living in the United states.

Hispanic/Latinx (hereafter Hispanic) individuals in the United States (US) experience serious tobacco-related disparities and factors contributing to such disparities need to be adequately identified and clinically addressed. Emotion dysregulation is a key transdiagnostic relevant to smoking. The present cross-sectional investigation sought to test if emotion dysregulation was related to more severe problems during smoking quit attempts (e.g., irritability, weight gain), perceptions of difficulty about quitting, as well as negative and positive beliefs about smoking abstinence in a sample of English-speaking Hispanic adults residing in the US who smoke. Participants included 332 Hispanic adults who engaged in daily cigarette smoking (35.46 years old, 37 % identified as female). Emotion dysregulation was significantly related to more severe problems when quitting and perceived barriers for quitting, as well as negative beliefs about smoking abstinence. Additionally, emotion dysregulation was significantly and negatively related to positive outcomes about smoking abstinence. The amount of change in the various smoking criterion variables accounted for by emotion dysregulation was small (sr2 range: 0.028-0.085), but evident in adjusted models that accounted for a wide range of factors (e.g., depression, drug use severity). Overall, this investigation found consistent empirical evidence that individual differences in emotion dysregulation in Hispanic individuals were associated with several clinically significant smoking processes, suggesting this construct may represent an important factor involved in the maintenance and relapse of smoking among this ethnic population.

Do Smartphone Apps Impact Long-Term Smoking Cessation for Sexual and Gender Minority Adults? Exploratory Results from a 2-Arm Randomized Trial Comparing Acceptance and Commitment Therapy with Standard US Clinical Practice Guidelines.

Sexual and gender minority (SGM) adults face unique challenges in accessing smoking cessation care due to stigma tied to their identities and smoking. While cessation apps show promise in the general population, their efficacy for SGM adults is unclear. This study utilized data from a randomized trial to compare two cessation apps, iCanQuit (Acceptance and Commitment Therapy-based) and QuitGuide (US Clinical Practice Guidelines-based) among 403 SGM adults. The primary outcome was self-reported complete-case 30-day abstinence from cigarette smoking at 12 months. Mediation analyses explored whether interventions operated through acceptance of cues to smoke and app engagement. At 12 months, quit rates did not differ between arms (26% iCanQuit vs. 22% QuitGuide, OR = 1.22; 95% CI: 0.74 to 2.00, p = .43). iCanQuit positively impacted cessation via acceptance of cues to smoke (indirect effect = 0.23; 95% CI: 0.06 to 0.50, p < .001) and demonstrated higher engagement (no. logins, 28.4 vs. 12.1; p < .001) and satisfaction (91% vs. 75%, OR = 4.18; 95% CI: 2.12 to 8.25, p < .001) than QuitGuide. Although quit rates did not differ between arms, acceptance of cues to smoke seemed to play a crucial role in helping SGM adults quit smoking. Future interventions should consider promoting acceptance of cues to smoke in this population.

Cook and Move for Your Life, an eHealth intervention for women with breast cancer.

We tested the feasibility and preliminary efficacy of an online diet and physical activity program for women with early-stage breast cancer who had completed surgery, chemotherapy, and radiation therapy (ongoing endocrine therapy allowed). Participants with low fruit and vegetable (F/V) consumption and/or low moderate-to-vigorous physical activity (MVPA) levels were randomized to one of two doses - low (one Zoom group session) or high (12 Zoom group sessions) - of an online lifestyle program with the goal of improving F/V intake and MVPA. All participants received eHealth communications (text messages, study website access), a Fitbit, and a WiFi-enabled scale. Primary objectives evaluated feasibility. Secondary objectives compared the 6-month change in F/V intake and MVPA between the two dose groups. Seventy-four women (mean age = 58.4 years; 87% non-Hispanic White; mean time since diagnosis = 4.6 years) were accrued. Among women in the low dose group, 94% attended the single session; among women in the high dose group, 84% attended at least 8 of the 12 sessions. Retention at 6 months was 93%. High relative to low dose participants consumed 1.5 more servings/day of F/V at 6 months (P = 0.007) but MVPA levels did not differ between groups. We successfully implemented an online lifestyle program for early-stage breast cancer survivors. The high dose intervention demonstrated preliminary efficacy in improving F/V consumption in early-stage breast cancer survivors. Future trials can test the intervention in a larger and more diverse population of breast cancer survivors.

Use of e-Cigarettes in Cigarette Smoking Cessation: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Many adults use e-cigarettes to help them quit cigarette smoking. However, the impact of self-selected use of e-cigarettes on cigarette smoking cessation, particularly when concurrently receiving app-based behavioral interventions, remains unexplored. OBJECTIVE: This study used data from a randomized trial of 2 smartphone apps to compare 12-month cigarette smoking cessation rates between participants who used e-cigarettes on their own (ie, adopters: n=465) versus those who did not (ie, nonadopters: n=1097). METHODS: The study population included all participants who did not use e-cigarettes at baseline. "Adopters" were those who self-reported the use of e-cigarettes at either 3- or 6-month follow-ups. "Nonadopters" were those who self-reported no use of e-cigarettes at either follow-up time point. The primary cessation outcome was self-reported, complete-case, 30-day point prevalence abstinence from cigarette smoking at 12 months. Secondary outcomes were missing-as-smoking and multiple imputation analyses of the primary outcome, prolonged abstinence, and cessation of all nicotine and tobacco products at 12 months. In logistic regression models, we first examined the potential interaction between e-cigarette use and treatment arm (iCanQuit vs QuitGuide) on the primary cessation outcome. Subsequently, we compared 12-month cigarette smoking cessation rates between adopters and nonadopters separately for each app. RESULTS: There was suggestive evidence for an interaction between e-cigarette use and treatment arm on cessation (P=.05). In the iCanQuit arm, 12-month cigarette smoking cessation rates were significantly lower among e-cigarette adopters compared with nonadopters (41/193, 21.2% vs 184/527, 34.9%; P=.003; odds ratio 0.55, 95% CI 0.37-0.81). In contrast, in the QuitGuide arm, 12-month cigarette smoking cessation rates did not differ between adopters and nonadopters (46/246, 18.7% vs 104/522, 19.9%; P=.64; odds ratio 0.91, 95% CI 0.62-1.35). CONCLUSIONS: The use of e-cigarettes while concurrently receiving an app-based smoking cessation intervention was associated with either a lower or an unimproved likelihood of quitting cigarette smoking compared to no use. Future behavioral treatments for cigarette smoking cessation should consider including information on the potential consequences of e-cigarette use. TRIAL REGISTRATION: ClinicalTrials.gov NCT02724462; https://clinicaltrials.gov/study/NCT02724462.

Telehealth acceptance and commitment therapy for weight loss: Protocol of the WeLNES full scale randomized controlled trial.

Behavioral interventions delivered via one-on-one telephone coaching (hereafter referred to as telehealth) for weight loss have had great population-level reach but to date limited efficacy. Acceptance and Commitment Therapy (ACT) has promise to improve behavioral weight loss treatment efficacy by addressing the fundamental challenges of weight loss and maintenance: overeating in response to internal (e.g., stress) and external (e.g., high calorie foods) cues. Here we describe the Weight Loss, Nutrition, and Exercise Study (WeLNES) randomized controlled trial that is testing the efficacy of an ACT-based telehealth coaching intervention for weight loss in comparison to a Standard Behavioral Therapy (SBT)-based telehealth coaching intervention. A total of 398 adults with overweight or obesity are being recruited and randomized to either ACT or SBT telehealth coaching. Participants in both arms are offered twenty-five telehealth coaching sessions in year one and nine booster sessions in year two. All participants receive a Bluetooth-enabled scale to self-monitor weight and a Fitbit Inspire + Fitbit app for tracking diet and physical activity. The primary aim is to determine whether a greater proportion of ACT participants will achieve a clinically significant weight loss of ≥10% compared with SBT participants at 12-months. Secondary outcomes include change in weight from baseline to 6, 12, and 24-months. Whether the effect of ACT on weight loss is mediated by ACT processes and is moderated by baseline factors will also be examined. If ACT proves efficacious, ACT telehealth coaching will offer an effective, broadly scalable weight loss treatment-thereby making a high public health impact.

Efficacy of smartphone applications to help cancer patients quit smoking: Protocol of the Quit2Heal randomized controlled trial.

Cigarette smoking is highly prevalent among cancer patients in the United States (US), with up to half of cancer patients smoking at the time of their initial cancer diagnosis. However, evidence-based cessation programs are rarely implemented in oncology care, and smoking is not consistently treated in cancer treatment settings. Consequently, there is an urgent need for accessible and efficacious cessation treatments that are uniquely tailored to the needs of cancer patients. Here we describe the design and implementation of a randomized controlled trial (RCT) testing the efficacy of a smartphone app (Quit2Heal) versus a US Clinical Practice Guidelines-based app (QuitGuide) for smoking cessation among a planned sample of 422 cancer patients. Quit2Heal is designed to address cancer-related shame, stigma, depression, anxiety, and knowledge about the consequences of smoking/quitting. Quit2Heal is based on the principles of Acceptance and Commitment Therapy, a behavioral therapy that teaches skills for accepting cravings to smoke without smoking, values-driven motivation to quit, and preventing relapse. The primary aim of the RCT is to determine whether Quit2Heal has significantly higher self-reported 30-day point prevalence abstinence at 12 months relative to QuitGuide. The trial will also determine whether Quit2Heal's effect on cessation is (1) mediated by improvements in cancer-related shame, stigma, depression, anxiety, and knowledge about the consequences of smoking/quitting; and (2) moderated by baseline factors (e.g., cancer type, stage, time since diagnosis). If successful, Quit2Heal will offer a more efficacious, broadly scalable smoking cessation treatment that could be implemented alongside existing oncology care, thereby improving cancer outcomes.