Delwyn Catley

Introduction: We sought to evaluate preliminary efficacy and implementation outcomes of an e-cigarette and tobacco cessation intervention for hospitalised youth in the USA. Methods: We conducted a pilot randomised controlled trial at a paediatric hospital with 3-month follow-up from August 2023 to December 2024. Hospitalised youth (14–21 years) with self-reported past 30-day e-cigarette use were eligible. Exclusions included severe medical/psychiatric illness, cognitive impairment and inability to communicate in English. Intervention entailed health education, motivational interviewing counselling, quit planning, nicotine replacement therapy (NRT) and phone booster sessions. Control entailed brief advice and quit programme 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 hospitalised youth enrolled, the mean age was 16.2 years (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 OR of abstinence was OR 0.77 (95% CI 0.27 to 2.19, p=0.62) in the intervention versus 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 hospitalised youth. Future work is needed to enhance intervention efficacy in this population. Trial registration number: NCT05936099 .

Background: Mobile health (mHealth) interventions are growing in popularity, but less research has focused on low-income families, particularly interventions integrating wearable devices with automated personalized messages. Objective: We tested a preliminary wearable-integrated mHealth intervention with initial personalization elements among adults and youth from low-income urban communities, focusing on feasibility, acceptability, and preliminary evidence of physical activity behavior. Methods: Participants were 83 adults and 31 youth recruited through community health events held in low-income urban communities. Using a single-arm pre-post design, participants were enrolled into a 7-week beta-version mHealth intervention that integrated a Garmin activity monitor with automated text messages. Messages were sent 4 days/week and focused on increasing step counts using theory-based behavior change techniques related to goal setting, self-monitoring, reinforcement, contextual factors, and self-efficacy. Most messages were personalized by including calculations based on the step-count and step-goal data, using branching logic, and using 2-way question-and-response messages. Feasibility measures included enrollment, retention, fidelity of message delivery, and adherence to wearing the Garmin device. Acceptability measures included survey items and engagement with responding to 2-way messages. Changes in daily steps were explored using mixed-effects linear regression. Results: Enrollment and eligibility rates were 64% (84/132, adults) and 63% (31/49, youth), retention for physical activity measures was 84% (70/83) and 77% (24/31), and 99% (3910/3955) of the intended messages were delivered. Adults and youth adhered to wearing the Garmin on 82% (45/56) and 79% (44/56) of the study days, respectively. Overall acceptability ratings were 83% to 100%, with 97% (75/77) of adults and 100% (27/27) of youth indicating they would recommend the program. Adults and youth replied to a mean of 2.6 (SD 2.2) and 3.2 (SD 2.7) of the 7 text messages that asked for a reply, with higher engagement among adults who participated with their child. Pre-post changes in daily steps were β=240 (95% CI –387 to 866) for adults and β=413 (95% CI –877 to 1703) among youth, with larger changes observed among those in the highest tertile of engagement (adults: β=584, 95% CI –784 to 1952; n=19; youth: β=941, 95% CI –827 to 2709; n=11) and those who were meeting less than two-thirds of the physical activity guideline at baseline (adults: β=609, 95% CI –30 to 1247; n=47; youth: β=1406, 95% CI –94 to 2907; n=22). Conclusions: Personalized mHealth physical activity interventions integrating wearable step trackers with automated text messaging appear to be feasible and acceptable among adults and youth from low-income communities. Step-count findings show promise for the intervention’s ability to support individuals who are further from meeting physical activity guidelines and warrant more research among parent–child dyads. Overall, findings support additional research to optimize and evaluate similar interventions within this population group using fully powered randomized controlled trials. Trial Registration: ClinicalTrials.gov NCT05110508; https://clinicaltrials.gov/ct2/show/NCT05110508

Background: Smoking continues to be a leading cause of preventable morbidity and mortality, and more than 480,000 Americans die annually due to smoking-related illness attributable to smoking and secondhand smoke. More advanced, responsive, and tailored digital interventions using machine learning and artificial intelligence may be a valuable tool for successful smoking cessation referrals. Objective: This study used the dynamic systems development method to incorporate patient and consumer sources of conversational data to develop a technology-assisted motivational interviewing (TAMI) chatbot, a digital agent using machine learning models to deliver motivational interviewing (MI) for tobacco cessation. Methods: During the functional model iteration phase, user-centered design interviews with smokers (n=3) informed the creation of TAMI. The design and build phase involved the use of existing datasets to guide the incorporation of MI-consistent utterances, language recognition, and topic classification to guide a discussion about smoking, and providing a tailored quit plan if indicated. During the implementation phase, user experience interviews with randomly selected participants (n=9) in a pilot trial discussed their experiences with TAMI. Results: User-centered design interviews indicated a desire for a chatbot that was engaging and adaptable to personal interests in quitting smoking. Inductive analysis of user experience interviews revealed that anonymity, regular reminders, and a humanized experience facilitated engagement with TAMI, but technical glitches, chatbot misunderstandings, and issues with rapport were barriers to engagement. Conclusions: Informed by user input and patient and consumer datasets, TAMI can use MI skills to elicit change talk and/or accurately evaluate readiness for tobacco cessation. Further development will enhance TAMI’s ability to seamlessly engage with users when discussing behavior change and assist underserved populations achieve improvements in a variety of health behavior goals.

BACKGROUND Mobile health (mHealth) interventions are growing in popularity, but less research has focused on low-income families, particularly interventions integrating wearable devices with automated personalized messages. OBJECTIVE We tested a preliminary wearable-integrated mHealth intervention with initial personalization elements among adults and youth from low-income urban communities, focusing on feasibility, acceptability, and preliminary evidence of physical activity behavior. METHODS Participants were 83 adults and 31 youth recruited through community health events held in low-income urban communities. Using a single-arm pre-post design, participants were enrolled into a 7-week beta-version mHealth intervention that integrated a Garmin activity monitor with automated text messages. Messages were sent 4 days/week and focused on increasing step counts using theory-based behavior change techniques related to goal setting, self-monitoring, reinforcement, contextual factors, and self-efficacy. Most messages were personalized by including calculations based on the step-count and step-goal data, using branching logic, and using 2-way question-and-response messages. Feasibility measures included enrollment, retention, fidelity of message delivery, and adherence to wearing the Garmin device. Acceptability measures included survey items and engagement with responding to 2-way messages. Changes in daily steps were explored using mixed-effects linear regression. RESULTS Enrollment and eligibility rates were 64% (84/132, adults) and 63% (31/49, youth), retention for physical activity measures was 84% (70/83) and 77% (24/31), and 99% (3910/3955) of the intended messages were delivered. Adults and youth adhered to wearing the Garmin on 82% (45/56) and 79% (44/56) of the study days, respectively. Overall acceptability ratings were 83% to 100%, with 97% (75/77) of adults and 100% (27/27) of youth indicating they would recommend the program. Adults and youth replied to a mean of 2.6 (SD 2.2) and 3.2 (SD 2.7) of the 7 text messages that asked for a reply, with higher engagement among adults who participated with their child. Pre-post changes in daily steps were β=240 (95% CI –387 to 866) for adults and β=413 (95% CI –877 to 1703) among youth, with larger changes observed among those in the highest tertile of engagement (adults: β=584, 95% CI –784 to 1952; n=19; youth: β=941, 95% CI –827 to 2709; n=11) and those who were meeting less than two-thirds of the physical activity guideline at baseline (adults: β=609, 95% CI –30 to 1247; n=47; youth: β=1406, 95% CI –94 to 2907; n=22). CONCLUSIONS Personalized mHealth physical activity interventions integrating wearable step trackers with automated text messaging appear to be feasible and acceptable among adults and youth from low-income communities. Step-count findings show promise for the intervention’s ability to support individuals who are further from meeting physical activity guidelines and warrant more research among parent–child dyads. Overall, findings support additional research to optimize and evaluate similar interventions within this population group using fully powered randomized controlled trials. CLINICALTRIAL ClinicalTrials.gov NCT05110508; https://clinicaltrials.gov/ct2/show/NCT05110508

UNSTRUCTURED Interactions based in Motivational Interviewing (MI) [1], driven by machine learning, may provide an efficient way to evaluate readiness to quit, elicit behavior change preferences, and scalable flexibility to extend reach to more diversified target populations. This study used patient and public sources of conversational data to develop a Technology Assisted Motivational Interviewing chatbot (TAMI), a digital agent employing machine learning models to deliver MI for tobacco cessation. Consistent with the four tasks of MI (engagement, focusing, evocation, and planning), the creation of TAMI involved 1) utilization of existing de-identified datasets to identify specific smoking topics of interest; 2) incorporation of MI-Consistent utterances to enhance relational connection to TAMI and elicit language expressing interest in quitting (change talk); 3) instilling change talk recognition and topic classification to guide discussion with TAMI and 4) providing tailored treatment options if indicated. Informed by patient, provider, and public discussions about smoking, TAMI can explore motivation associated with tobacco use, and privately employ interventions to elicit change talk, or accurately evaluate readiness for tobacco cessation. TAMI is also scalable technology, which opens the possibility of having more tools for clinical assessment, delivering MI, and tailoring cessation referrals to underserved populations or those with other target behavior goals.

Lifestyle Africa is an adapted version of the Diabetes Prevention Program designed for delivery by community health workers to socioeconomically disadvantaged populations in low- and middle-income countries (LMICs). Results from the Lifestyle Africa trial conducted in an under-resourced community in South Africa indicated that the programme had a significant effect on reducing haemoglobin A1c (HbA1c). To estimate the cost of implementation and the cost-effectiveness (in cost per point reduction in HbA1c) of the Lifestyle Africa programme to inform decision-makers of the resources required and the value of this intervention. Interviews were held with project administrators to identify the activities and resources required to implement the intervention. A direct-measure micro-costing approach was used to determine the number of units and unit cost for each resource. The incremental cost per one point improvement in HbA1c was calculated. The intervention equated to 71 United States dollars (USD) in implementation costs per participant and a 0.26 improvement in HbA1c per participant. Lifestyle Africa reduced HbA1c for relatively little cost and holds promise for addressing chronic disease in LMIC. Decision-makers should consider the comparative clinical effectiveness and cost-effectiveness of this intervention when making resource allocation decisions. Trial registration is at ClinicalTrials.gov (NCT03342274).

Background: Latinos remain disproportionately underrepresented in clinical trials, comprising only 2%-3% of research participants. In order to address health disparities, it is critically important to increase enrollment of Latino smokers in smoking cessation trials. There is limited research examining effective recruitment strategies for this population. Objective: The purpose of this study was to compare the effectiveness of direct versus mass and high- versus low-effort recruitment strategies on recruitment and retention of Latino smokers to a randomized smoking cessation trial. We also examine how the type of recruitment might have influenced the characteristics of enrolled participants. Methods: Latino smokers were enrolled into Decídetexto from 4 states—New Jersey, Kansas, Missouri, and New York. Participants were recruited from August 2018 until March 2021. Mass recruitment strategies included English and Spanish advertisements to the Latino community via flyers, Facebook ads, newspapers, television, radio, church bulletins, and our Decídetexto website. Direct, high-effort strategies included referrals from clinics or community-based organizations with whom we partnered, in-person community outreach, and patient registry calls. Direct, low-effort strategies included texting or emailing pre-existing lists of patients who smoked. A team of trained bilingual (English and Spanish) recruiters from 9 different Spanish-speaking countries of origin conducted recruitment, assessed eligibility, and enrolled participants into the trial. Results: Of 1112 individuals who were screened, 895 (80.5%) met eligibility criteria, and 457 (457/895, 51.1%) enrolled in the trial. Within the pool of screened individuals, those recruited by low-effort recruitment strategies (both mass and direct) were significantly more likely to be eligible (odds ratio [OR] 1.67, 95% CI 1.01-2.76 and OR 1.70, 95% CI 0.98-2.96, respectively) and enrolled in the trial (OR 2.60, 95% CI 1.81-3.73 and OR 3.02, 95% CI 2.03-4.51, respectively) compared with those enrolled by direct, high-effort strategies. Among participants enrolled, the retention rates at 3 months and 6 months among participants recruited via low-effort strategies (both mass and direct) were similar to participants recruited via direct, high-effort methods. Compared with enrolled participants recruited via direct (high- and low-effort) strategies, participants recruited via mass strategies were less likely to have health insurance (44.0% vs 71.2% and 71.7%, respectively; P<.001), lived fewer years in the United States (22.4 years vs 32.4 years and 30.3 years, respectively; P<.001), more likely to be 1st generation (92.7% vs 76.5% and 77.5%, respectively; P=.007), more likely to primarily speak Spanish (89.3% vs 65.8% and 66.3%, respectively), and more likely to be at high risk for alcohol abuse (5.8 mean score vs 3.8 mean score and 3.9 mean score, respectively; P<.001). Conclusions: Although most participants were recruited via direct, high-effort strategies, direct low-effort recruitment strategies yielded a screening pool more likely to be eligible for the trial. Mass recruitment strategies were associated with fewer acculturated enrollees with lower access to health services—groups who might benefit a great deal from the intervention. Trial Registration: ClinicalTrials.gov identifier: NCT03586596; https://clinicaltrials.gov/ct2/show/NCT03586596 International Registered Report Identifier (IRRID): RR2-DOI: 10.1016/j.cct.2020.106188

Background: Low- and middle-income countries (LMICs) are experiencing major increases in diabetes and cardiovascular conditions linked to overweight and obesity. Lifestyle interventions such as the United States National Diabetes Prevention Program (DPP) developed in high-income countries require adaptation and cultural tailoring for LMICs. The objective of this study was to evaluate the efficacy of “Lifestyle Africa,” an adapted version of the DPP tailored for an underresourced community in South Africa compared to usual care. Methods and findings: Participants were residents of a predominantly Xhosa-speaking urban township of Cape Town, South Africa characterized by high rates of poverty. Participants with body mass index (BMI) ≥ 25 kg/m² who were members of existing social support groups or “clubs” receiving health services from local nongovernmental organizations (NGOs) were enrolled in a cluster randomized controlled trial that compared Lifestyle Africa (the intervention condition) to usual care (the control condition). The Lifestyle Africa intervention consisted of 17 video-based group sessions delivered by trained community health workers (CHWs). Clusters were randomized using a numbered list of the CHWs and their assigned clubs based on a computer-based random allocation scheme. CHWs, participants, and research team members could not be blinded to condition. Percentage weight loss (primary outcome), hemoglobin A1c (HbA1c), blood pressure, triglycerides, and low-density lipoprotein (LDL) cholesterol were assessed 7 to 9 months after enrollment. An individual-level intention-to-treat analysis was conducted adjusting for clustering within clubs and baseline values. Trial registration is at ClinicalTrials.gov (NCT03342274). Between February 2018 and May 2019, 782 individuals were screened, and 494 were enrolled. Participants were predominantly retired (57% were receiving a pension) and female (89%) with a mean age of 68 years. Participants from 28 clusters were allocated to Lifestyle Africa (15, n = 240) or usual care (13, n = 254). Fidelity assessments indicated that the intervention was generally delivered as intended. The modal number of sessions held across all clubs was 17, and the mean attendance of participants across all sessions was 61%. Outcome assessment was completed by 215 (90%) intervention and 223 (88%) control participants. Intent-to-treat analyses utilizing multilevel modeling included all randomized participants. Mean weight change (primary outcome) was −0.61% (95% confidence interval (CI) = −1.22, −0.01) in Lifestyle Africa and −0.44% (95% CI = −1.06, 0.18) in control with no significant difference (group difference = −0.17%; 95% CI = −1.04, 0.71; p = 0.71). However, HbA1c was significantly lower at follow-up in Lifestyle Africa compared to the usual care group (mean difference = −0.24, 95% CI = −0.39, −0.09, p = 0.001). None of the other secondary outcomes differed at follow-up: systolic blood pressure (group difference = −1.36; 95% CI = −6.92, 4.21; p = 0.63), diastolic blood pressure (group difference = −0.39; 95% CI = −3.25, 2.30; p = 0.78), LDL (group difference = −0.07; 95% CI = −0.19, 0.05; p = 0.26), triglycerides (group difference = −0.02; 95% CI = −0.20, 0.16; p = 0.80). There were no unanticipated problems and serious adverse events were rare, unrelated to the intervention, and similar across groups (11 in Lifestyle Africa versus 13 in usual care). Limitations of the study include the lack of a rigorous dietary intake measure and the high representation of older women. Conclusions: In this study, we found that Lifestyle Africa was feasible for CHWs to deliver and, although it had no effect on the primary outcome of weight loss or secondary outcomes of blood pressure or triglycerides, it had an apparent small significant effect on HbA1c. The study demonstrates the potential feasibility of CHWs to deliver a program without expert involvement by utilizing video-based sessions. The intervention may hold promise for addressing cardiovascular disease (CVD) and diabetes at scale in LMICs. Trial registration: ClinicalTrials.gov NCT03342274.