Optimization of a mHealth Physical Activity Promotion Intervention With Mindful Awareness for Young Adult Cancer Survivors: Design and Methods of Opt2Move Full Factorial Trial.

Background: Opt2Move is a theory-guided moderate and vigorous physical activity (MVPA) promotion trial that uses multiphase optimization strategy (MOST) methodology to evaluate the individual and combined effects of four intervention components in a full factorial experiment among young adult cancer survivors (YACS; N = 304). All participants will receive the core mHealth MVPA intervention, which includes a Fitbit and standard self-monitoring Opt2Move smartphone application. YACS will be randomized to one of 16 conditions to receive between zero and four additional components each with two levels (yes v. no): E-Coach, buddy, general mindfulness, and MVPA-specific mindfulness. Objective: The primary aim is to determine the individual and combined effects of the components on MVPA post-intervention (12-weeks) and at 24-week follow-up. The secondary aim is to examine how changes in MVPA are associated with patient-reported outcomes, light-intensity activity, sedentary time, and sleep duration and quality. Potential mediators and moderators of component effects will also be examined. Results: Results will support the selection of a package of intervention components optimized to maximize MVPA to be tested in a randomized controlled trial. Conclusion: Opt2Move represents the first systematic effort to use MOST to design an optimized, scalable mHealth MVPA intervention for YACS and will lead to an improved understanding of how to effectively change YACS' MVPA and ultimately, improve health and disease outcomes.

The moderating effect of access to food facilities and recreational activity space on mHealth multiple health behavior change intervention.

OBJECTIVE: To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity. METHODS: Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks. RESULTS: According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence. CONCLUSIONS: A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.

Feasibility and preliminary effects of the Fit2ThriveMB pilot physical activity promotion intervention on physical activity and patient reported outcomes in individuals with metastatic breast cancer.

PURPOSE: Physical activity research among patients with metastatic breast cancer (MBC) is limited. This study examined the feasibility and potential benefits of Fit2ThriveMB, a tailored mHealth intervention. METHODS: Insufficiently active individuals with MBC (n = 49) were randomized 1:1 to Fit2ThriveMB (Fit2ThriveMB app, Fitbit, and weekly coaching calls) or Healthy Lifestyle attention control (Cancer.Net app and weekly calls) for 12 weeks. Fit2ThriveMB aimed to increase daily steps via an algorithm tailored to daily symptom rating and step goal attainment. The primary outcome was feasibility defined as ≥ 80% completion rate. Secondary feasibility metrics included meeting daily step goal and wearing the Fitbit ≥ 70% of study days, fidelity, adherence to intervention features and safety. Secondary outcomes included physical activity, sedentary time, patient reported outcomes (PROs), health-related quality of life (QOL) and social cognitive theory constructs. A subsample (n = 25) completed functional performance tests via video conferencing. RESULTS: The completion rate was 98% (n = 1 died). No related adverse events were reported. Fit2ThriveMB participants (n = 24) wore the Fitbit 92.7%, met their step goal 53.1%, set a step goal 84.6% and used the app 94.1% of 84 study days. Intent-to-treat analyses indicated trends toward improvements in activity, QOL, and some PROs, social cognitive theory constructs, and functional performance tests favoring the Fit2ThriveMB group. Significant effects favoring Fit2ThriveMB were observed for self-efficacy and goal-setting. However, some PROs and functional performance improvements favored the control group (p-values > 0.05). CONCLUSIONS: Fit2ThriveMB is feasible and safe for patients with MBC and warrants further evaluation in randomized controlled trials with larger sample sizes. Registration Clinicaltrials.gov NCT04129346, https://clinicaltrials.gov/ct2/show/NCT04129346.

A Framework for Integrating Telehealth Equitably across the cancer care continuum.

The COVID-19 pandemic placed a spotlight on the potential to dramatically increase the use of telehealth across the cancer care continuum, but whether and how telehealth can be implemented in practice in ways that reduce, rather than exacerbate, inequities are largely unknown. To help fill this critical gap in research and practice, we developed the Framework for Integrating Telehealth Equitably (FITE), a process and evaluation model designed to help guide equitable integration of telehealth into practice. In this manuscript, we present FITE and showcase how investigators across the National Cancer Institute's Telehealth Research Centers of Excellence are applying the framework in different ways to advance digital and health equity. By highlighting multilevel determinants of digital equity that span further than access alone, FITE highlights the complex and differential ways structural determinants restrict or enable digital equity at the individual and community level. As such, achieving digital equity will require strategies designed to not only support individual behavior but also change the broader context to ensure all patients and communities have the choice, opportunity, and resources to use telehealth across the cancer care continuum.

Scalable Telehealth Cancer Care: integrated healthy lifestyle program to live well after cancer treatment.

Northwestern University's Center for Scalable Telehealth Cancer Care (STELLAR) is 1 of 4 Cancer Moonshot Telehealth Research Centers of Excellence programs funded by the National Cancer Institute to establish an evidence base for telehealth in cancer care. STELLAR is grounded in the Institute of Medicine's vision that quality cancer care includes not only disease treatment but also promotion of long-term health and quality of life (QOL). Cigarette smoking, insufficient physical activity, and overweight and obesity often co-occur and are associated with poorer treatment response, heightened recurrence risk, decreased longevity, diminished QOL, and increased treatment cost for many cancers. These risk behaviors are prevalent in cancer survivors, but their treatment is not routinely integrated into oncology care. STELLAR aims to foster patients' long-term health and QOL by designing, implementing, and sustaining a novel telehealth treatment program for multiple risk behaviors to be integrated into standard cancer care. Telehealth delivery is evidence-based for health behavior change treatment and is well suited to overcome access and workflow barriers that can otherwise impede treatment receipt. This paper describes STELLAR's 2-arm randomized parallel group pragmatic clinical trial comparing telehealth-delivered, coach-facilitated multiple risk behavior treatment vs self-guided usual care for the outcomes of reach, effectiveness, and cost among 3000 cancer survivors who have completed curative intent treatment. This paper also discusses several challenges encountered by the STELLAR investigative team and the adaptations developed to move the research forward.

An Adaptive Behavioral Intervention for Weight Loss Management: A Randomized Clinical Trial.

Importance: Lifestyle interventions for weight loss are difficult to implement in clinical practice. Self-managed mobile health implementations without or with added support after unsuccessful weight loss attempts could offer effective population-level obesity management. Objective: To test whether a wireless feedback system (WFS) yields noninferior weight loss vs WFS plus telephone coaching and whether participants who do not respond to initial treatment achieve greater weight loss with more vs less vigorous step-up interventions. Design, Setting, and Participants: In this noninferiority randomized trial, 400 adults aged 18 to 60 years with a body mass index of 27 to 45 were randomized in a 1:1 ratio to undergo 3 months of treatment initially with WFS or WFS plus coaching at a US academic medical center between June 2017 and March 2021. Participants attaining suboptimal weight loss were rerandomized to undergo modest or vigorous step-up intervention. Interventions: The WFS included a Wi-Fi activity tracker and scale transmitting data to a smartphone app to provide daily feedback on progress in lifestyle change and weight loss, and WFS plus coaching added 12 weekly 10- to 15-minute supportive coaching calls delivered by bachelor's degree-level health promotionists viewing participants' self-monitoring data on a dashboard; step-up interventions included supportive messaging via mobile device screen notifications (app-based screen alerts) without or with coaching or powdered meal replacement. Participants and staff were unblinded and outcome assessors were blinded to treatment randomization. Main Outcomes and Measures: The primary outcome was the between-group difference in 6-month weight change, with the noninferiority margin defined as a difference in weight change of -2.5 kg; secondary outcomes included between-group differences for all participants in weight change at 3 and 12 months and between-group 6-month weight change difference among nonresponders exposed to modest vs vigorous step-up interventions. Results: Among 400 participants (mean [SD] age, 40.5 [11.2] years; 305 [76.3%] women; 81 participants were Black and 266 were White; mean [SD] body mass index, 34.4 [4.3]) randomized to undergo WFS (n = 199) vs WFS plus coaching (n = 201), outcome data were available for 342 participants (85.5%) at 6 months. Six-month weight loss was -2.8 kg (95% CI, -3.5 to -2.0) for the WFS group and -4.8 kg (95% CI, -5.5 to -4.1) for participants in the WFS plus coaching group (difference in weight change, -2.0 kg [90% CI, -2.9 to -1.1]; P < .001); the 90% CI included the noninferiority margin of -2.5 kg. Weight change differences were comparable at 3 and 12 months and, among nonresponders, at 6 months, with no difference by step-up therapy. Conclusions and Relevance: A wireless feedback system (Wi-Fi activity tracker and scale with smartphone app to provide daily feedback) was not noninferior to the same system with added coaching. Continued efforts are needed to identify strategies for weight loss management and to accurately select interventions for different individuals to achieve weight loss goals. Trial Registration: ClinicalTrials.gov Identifier: NCT02997943.

The Health4Life e-health intervention for modifying lifestyle risk behaviours of adolescents: secondary outcomes of a cluster randomised controlled trial.

OBJECTIVES: To investigate the effectiveness of a school-based multiple health behaviour change e-health intervention for modifying risk factors for chronic disease (secondary outcomes). STUDY DESIGN: Cluster randomised controlled trial. SETTING, PARTICIPANTS: Students (at baseline [2019]: year 7, 11-14 years old) at 71 Australian public, independent, and Catholic schools. INTERVENTION: Health4Life: an e-health school-based multiple health behaviour change intervention for reducing increases in the six major behavioural risk factors for chronic disease: physical inactivity, poor diet, excessive recreational screen time, poor sleep, and use of alcohol and tobacco. It comprises six online video modules during health education class and a smartphone app. MAIN OUTCOME MEASURES: Comparison of Health4Life and usual health education with respect to their impact on changes in twelve secondary outcomes related to the six behavioural risk factors, assessed in surveys at baseline, immediately after the intervention, and 12 and 24 months after the intervention: binge drinking, discretionary food consumption risk, inadequate fruit and vegetable intake, difficulty falling asleep, and light physical activity frequency (categorical); tobacco smoking frequency, alcohol drinking frequency, alcohol-related harm, daytime sleepiness, and time spent watching television and using electronic devices (continuous). RESULTS: A total of 6640 year 7 students completed the baseline survey (Health4Life: 3610; control: 3030); 6454 (97.2%) completed at least one follow-up survey, 5698 (85.8%) two or more follow-up surveys. Health4Life was not statistically more effective than usual school health education for influencing changes in any of the twelve outcomes over 24 months; for example: fruit intake inadequate: odds ratio [OR], 1.08 (95% confidence interval [CI], 0.57-2.05); vegetable intake inadequate: OR, 0.97 (95% CI, 0.64-1.47); increased light physical activity: OR, 1.00 (95% CI, 0.72-1.38); tobacco use frequency: relative difference, 0.03 (95% CI, -0.58 to 0.64) days per 30 days; alcohol use frequency: relative difference, -0.34 (95% CI, -1.16 to 0.49) days per 30 days; device use time: relative difference, -0.07 (95% CI, -0.29 to 0.16) hours per day. CONCLUSIONS: Health4Life was not more effective than usual school year 7 health education for modifying adolescent risk factors for chronic disease. Future e-health multiple health behaviour change intervention research should examine the timing and length of the intervention, as well as increasing the number of engagement strategies (eg, goal setting) during the intervention. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12619000431123 (prospective).

Design of experiments with sequential randomizations on multiple timescales: the hybrid experimental design.

Psychological interventions, especially those leveraging mobile and wireless technologies, often include multiple components that are delivered and adapted on multiple timescales (e.g., coaching sessions adapted monthly based on clinical progress, combined with motivational messages from a mobile device adapted daily based on the person's daily emotional state). The hybrid experimental design (HED) is a new experimental approach that enables researchers to answer scientific questions about the construction of psychological interventions in which components are delivered and adapted on different timescales. These designs involve sequential randomizations of study participants to intervention components, each at an appropriate timescale (e.g., monthly randomization to different intensities of coaching sessions and daily randomization to different forms of motivational messages). The goal of the current manuscript is twofold. The first is to highlight the flexibility of the HED by conceptualizing this experimental approach as a special form of a factorial design in which different factors are introduced at multiple timescales. We also discuss how the structure of the HED can vary depending on the scientific question(s) motivating the study. The second goal is to explain how data from various types of HEDs can be analyzed to answer a variety of scientific questions about the development of multicomponent psychological interventions. For illustration, we use a completed HED to inform the development of a technology-based weight loss intervention that integrates components that are delivered and adapted on multiple timescales.

Delivering COVID-19 Vaccine via Trusted Social Services: Program Evaluation Results from the Chicagoland CEAL Program.

To describe the reach, implementation, and sustainability of COVID-19 vaccination programs delivered by social service community organizations. Five academic institutions in the Chicagoland CEAL (Community Engagement Alliance) program partnered with 17 community organizations from September 2021-April 2022. Interviews, community organizations program implementation tracking documents, and health department vaccination data were used to conduct the evaluation. A total of 269 events were held and 5,432 COVID-19 vaccines delivered from May 2021-April 2022. Strategies that worked best included offering vaccinations in community settings with flexible and reliable hours; pairing vaccinations with ongoing social services; giving community organizations flexibility to adjust programs; offering incentives; and vaccinating staff first. These strategies and partnership structures supported vaccine uptake, community organization alignment with their missions and communities' needs, and trust. Community organizations delivering social services are local community experts and trusted messengers. Pairing social service delivery with COVID-19 vaccination built individual and community agency. Giving COs creative control over program implementation enhanced trust and vaccine delivery. When given appropriate resources and control, community organizations can quickly deliver urgently needed health services in a public health crisis.

Community engagement through social media: A promising low-cost strategy for rural recruitment?

PURPOSE: For the same reasons that rural telehealth has shown promise for enhancing the provision of care in underserved environments, social media recruitment may facilitate more inclusive research engagement in rural areas. However, little research has examined social media recruitment in the rural context, and few studies have evaluated the feasibility of using a free social media page to build a network of rural community members who may be interested in a research study. Here, we describe the rationale, process, and protocols of developing and implementing a social media approach to recruit rural residents to participate in an mHealth intervention. METHODS: Informed by extensive formative research, we created a study Facebook page emphasizing community engagement in an mHealth behavioral intervention. We distributed the page to local networks and regularly posted recruitment and community messages. We collected data on the reach of the Facebook page, interaction with our messages, and initiations of our study intake survey. FINDINGS: Over 21 weeks, our Facebook page gained 429 followers, and Facebook users interacted with our social media messages 3,080 times. Compared to messages that described desirable study features, messages that described community involvement resulted in higher levels of online interaction. Social media and other recruitment approaches resulted in 225 people initiating our in-take survey, 9 enrolling in our pilot study, and 26 placing their names on a waiting list. CONCLUSIONS: A standalone social media page highlighting community involvement shows promise for recruiting in rural areas.

Home-Based Walking Exercise and Supervised Treadmill Exercise in Patients With Peripheral Artery Disease: An Individual Participant Data Meta-Analysis.

Importance: Few people with lower extremity peripheral artery disease (PAD) participate in supervised treadmill exercise covered by the Center for Medicare and Medicaid Services. In people with PAD, the benefits of home-based walking exercise, relative to supervised exercise, remain unclear. Objective: To study whether home-based walking exercise improves 6-minute walk (6MW) more than supervised treadmill exercise in people with PAD (defined as Ankle Brachial Index ≤0.90). Data Sources: Data were combined from 5 randomized clinical trials of exercise therapy for PAD using individual participant data meta-analyses, published from 2009 to 2022. Study Selection: Of the 5 clinical trials, 3 clinical trials compared supervised treadmill exercise to nonexercise control (N = 370) and 2 clinical trials compared an effective home-based walking exercise intervention to nonexercise control (N = 349). Data Extraction and Synthesis: Individual participant-level data from 5 randomized clinical trials led by 1 investigative team were combined. The 5 randomized clinical trials included 3 clinical trials of supervised treadmill exercise and 2 effective home-based walking exercise interventions. Main Outcomes and Measures: Change in 6MW distance, maximum treadmill walking distance, and Walking Impairment Questionnaire at 6-month follow-up. The supervised treadmill exercise intervention consisted of treadmill exercise in the presence of an exercise physiologist, conducted 3 days weekly for up to 50 minutes per session. Home-based walking exercise consisted of a behavioral intervention in which a coach helped participants walk for exercise in or around home for up to 5 days per week for 50 minutes per session. Results: A total of 719 participants with PAD (mean [SD] age, 68.8 [9.5] years; 46.5% female) were included (349 in a home-based exercise clinical trial and 370 in a supervised exercise trial). Compared with nonexercise control, supervised treadmill exercise was associated with significantly improved 6MW by 32.9 m (95% CI, 20.6-45.6; P < .001) and home-based walking exercise was associated with significantly improved 6MW by 50.7 m (95% CI, 34.8-66.7; P < .001). Compared with supervised treadmill exercise, home-based walking exercise was associated with significantly greater improvement in 6MW distance (between-group difference: 23.8 m [95% CI, 3.6, 44.0; P = .02]) but significantly less improvement in maximum treadmill walking distance (between-group difference:-132.5 m [95% CI, -192.9 to -72.1; P < .001]). Conclusions and Relevance: In this individual participant data meta-analyses, compared with supervised exercise, home-based walking exercise was associated with greater improvement in 6MW in people with PAD. These findings support home-based walking exercise as a first-line therapy for walking limitations in PAD.

An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study.

BACKGROUND: Predicting the likelihood of success of weight loss interventions using machine learning (ML) models may enhance intervention effectiveness by enabling timely and dynamic modification of intervention components for nonresponders to treatment. However, a lack of understanding and trust in these ML models impacts adoption among weight management experts. Recent advances in the field of explainable artificial intelligence enable the interpretation of ML models, yet it is unknown whether they enhance model understanding, trust, and adoption among weight management experts. OBJECTIVE: This study aimed to build and evaluate an ML model that can predict 6-month weight loss success (ie, ≥7% weight loss) from 5 engagement and diet-related features collected over the initial 2 weeks of an intervention, to assess whether providing ML-based explanations increases weight management experts' agreement with ML model predictions, and to inform factors that influence the understanding and trust of ML models to advance explainability in early prediction of weight loss among weight management experts. METHODS: We trained an ML model using the random forest (RF) algorithm and data from a 6-month weight loss intervention (N=419). We leveraged findings from existing explainability metrics to develop Prime Implicant Maintenance of Outcome (PRIMO), an interactive tool to understand predictions made by the RF model. We asked 14 weight management experts to predict hypothetical participants' weight loss success before and after using PRIMO. We compared PRIMO with 2 other explainability methods, one based on feature ranking and the other based on conditional probability. We used generalized linear mixed-effects models to evaluate participants' agreement with ML predictions and conducted likelihood ratio tests to examine the relationship between explainability methods and outcomes for nested models. We conducted guided interviews and thematic analysis to study the impact of our tool on experts' understanding and trust in the model. RESULTS: Our RF model had 81% accuracy in the early prediction of weight loss success. Weight management experts were significantly more likely to agree with the model when using PRIMO (χ2=7.9; P=.02) compared with the other 2 methods with odds ratios of 2.52 (95% CI 0.91-7.69) and 3.95 (95% CI 1.50-11.76). From our study, we inferred that our software not only influenced experts' understanding and trust but also impacted decision-making. Several themes were identified through interviews: preference for multiple explanation types, need to visualize uncertainty in explanations provided by PRIMO, and need for model performance metrics on similar participant test instances. CONCLUSIONS: Our results show the potential for weight management experts to agree with the ML-based early prediction of success in weight loss treatment programs, enabling timely and dynamic modification of intervention components to enhance intervention effectiveness. Our findings provide methods for advancing the understandability and trust of ML models among weight management experts.

Joint modeling the frequency and duration of accelerometer-measured physical activity from a lifestyle intervention trial.

Physical activity (PA) guidelines recommend that PA be accumulated in bouts of 10 minutes or more in duration. Recently, researchers have sought to better understand how participants in PA interventions increase their activity. Participants can increase their daily PA by increasing the number of PA bouts per day while keeping the duration of the bouts constant; they can keep the number of bouts constant but increase the duration of each bout; or participants can increase both the number of bouts and their duration. We propose a novel joint modeling framework for modeling PA bouts and their duration over time. Our joint model is comprised of two sub-models: a mixed-effects Poisson hurdle sub-model for the number of bouts per day and a mixed-effects location scale gamma regression sub-model to characterize the duration of the bouts and their variance. The model allows us to estimate how daily PA bouts and their duration vary together over the course of an intervention and by treatment condition and is specifically designed to capture the unique distributional features of bouted PA as measured by accelerometer: frequent measurements, zero-inflated bouts, and skewed bout durations. We apply our methods to the Make Better Choices study, a longitudinal lifestyle intervention trial to increase PA. We perform a simulation study to evaluate how well our model is able to estimate relationships between outcomes.

Study Design, Rationale, and Methodology for Promote Weight Loss in Patients With Peripheral Artery Disease Who Also Have Obesity: The PROVE Trial.

Background Overweight and obesity are associated with adverse functional outcomes in people with peripheral artery disease (PAD). The effects of weight loss in people with overweight/obesity and PAD are unknown. Methods The PROVE (Promote Weight Loss in Obese PAD Patients to Prevent Mobility Loss) Trial is a multicentered randomized clinical trial with the primary aim of testing whether a behavioral intervention designed to help participants with PAD lose weight and walk for exercise improves 6-minute walk distance at 12-month follow-up, compared with walking exercise alone. A total of 212 participants with PAD and body mass index ≥25 kg/m2 will be randomized. Interventions are delivered using a Group Mediated Cognitive Behavioral intervention model, a smartphone application, and individual telephone coaching. The primary outcome is 12-month change in 6-minute walk distance. Secondary outcomes include total minutes of walking exercise/wk at 12-month follow-up and 12-month change in accelerometer-measured physical activity, the Walking Impairment Questionnaire distance score, and the Patient-Reported Outcomes Measurement Information System mobility questionnaire. Tertiary outcomes include 12-month changes in perceived exertional effort at the end of the 6-minute walk, diet quality, and the Short Physical Performance Battery. Exploratory outcomes include changes in gastrocnemius muscle biopsy measures of mitochondrial cytochrome C oxidase activity, mitochondrial biogenesis, capillary density, and inflammatory markers. Conclusions The PROVE randomized clinical trial will evaluate the effects of exercise with an intervention of coaching and a smartphone application designed to achieve weight loss, compared with exercise alone, on walking performance in people with PAD and overweight/obesity. Results will inform optimal treatment for the growing number of patients with PAD who have overweight/obesity. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04228978.

U.S. Vietnamese parents' trusted sources of information and preferences for intervention messaging about HPV vaccination: A mixed methods study.

Objective: Assess trusted sources of information, perceived message effectiveness, and preferred dissemination strategies regarding adolescent HPV vaccination among U.S. Vietnamese parents. Methods: Data came from an observational, explanatory sequential mixed-methods study with U.S. Vietnamese parents of adolescents (408 survey participants; 32 interview participants). Surveys and interviews were conducted in both Vietnamese and English. Mixed-methods data were integrated and analyzed for confirmation, expansion, or discordance. Results: Both quantitative and qualitative findings confirm high trust in HPV vaccination information from providers, government agencies, and cancer organizations. Messages perceived as effective emphasize vaccine safety, experts' endorsement, importance of vaccination prior to HPV exposure, and preventable cancers. Qualitative findings expanded quantitative results, demonstrating a desire for evidence-based information in the Vietnamese language and addressing cultural concerns (e.g., effectiveness or potential side effects specific to Vietnamese adolescents, whether parents should delay HPV vaccination for Vietnamese adolescents). Quantitative and qualitative findings were incongruent about whether parents would trust information about HPV vaccination that is disseminated via social media. Conclusion: We identified credible messengers, feasible strategies, and elements of impactful messages for interventions to increase adolescent HPV vaccination for U.S. Vietnamese. Innovation: We focus on a high-risk, underserved population and integrate mixed-methods design and analysis.

What Chicago community organizations needed to implement COVID-19 interventions: lessons learned in 2021.

Introduction: As the COVID-19 pandemic placed a spotlight on the health inequities in the United States, this study aimed to determine the local programmatic needs of community organizations (CO) delivering COVID-19 interventions across Chicago. Methods: In the summer of 2021, the Chicagoland CEAL Program interviewed 34 COs that were providing education, testing, and/or vaccinations in communities experiencing poor COVID-19 outcomes. The interviews were analyzed thematically and organized around logistical challenges and funding/resource needs. Results: The COs routinely offered testing (50%) or vaccinations (74%), with most (56%) employing some programmatic evaluation. Programs utilizing trusted-messenger systems were deemed most effective, but resource-intensive. CO specific needs clustered around sustaining effective outreach strategies, better CO coordination, wanting comprehensive trainings, improving program evaluation, and promoting services and programs. Conclusion: The COs reached populations with low-vaccine confidence using trusted messengers to overcome mistrust. However, replenishment of the resources needed to sustain such strategies should be prioritized. Leveraging the Chicagoland CEAL Program to help negotiate community organizations' interorganizational coordination, create training programs, and provide evaluation expertise are deliverable supports that may bolster COVID-19 prevention. Policy implications: Achieving health justice requires that all institutions of power participate in meaningful community engagement, help build community capacity, and infuse health equity throughout all aspects of the research and program evaluation processes.

Rationale and design of the SenseWhy project: A passive sensing and ecological momentary assessment study on characteristics of overeating episodes.

Objectives: Overeating interventions and research often focus on single determinants and use subjective or nonpersonalized measures. We aim to (1) identify automatically detectable features that predict overeating and (2) build clusters of eating episodes that identify theoretically meaningful and clinically known problematic overeating behaviors (e.g., stress eating), as well as new phenotypes based on social and psychological features. Method: Up to 60 adults with obesity in the Chicagoland area will be recruited for a 14-day free-living observational study. Participants will complete ecological momentary assessments and wear 3 sensors designed to capture features of overeating episodes (e.g., chews) that can be visually confirmed. Participants will also complete daily dietitian-administered 24-hour recalls of all food and beverages consumed. Analysis: Overeating is defined as caloric consumption exceeding 1 standard deviation of an individual's mean consumption per eating episode. To identify features that predict overeating, we will apply 2 complementary machine learning methods: correlation-based feature selection and wrapper-based feature selection. We will then generate clusters of overeating types and assess how they align with clinically meaningful overeating phenotypes. Conclusions: This study will be the first to assess characteristics of eating episodes in situ over a multiweek period with visual confirmation of eating behaviors. An additional strength of this study is the assessment of predictors of problematic eating during periods when individuals are not on a structured diet and/or engaged in a weight loss intervention. Our assessment of overeating episodes in real-world settings is likely to yield new insights regarding determinants of overeating that may translate into novel interventions.

Effect of the Fit2Thrive Intervention on Patient-reported Outcomes in Breast Cancer Survivors: A Randomized Full Factorial Trial.

BACKGROUND: Moderate to vigorous physical activity (MVPA) interventions improve patient-reported outcomes (PROs) of physical and psychological health among breast cancer survivors (BCS); however, the effects of specific intervention components on PROs are unknown. PURPOSE: To use the Multiphase Optimization Strategy (MOST) to examine overall effects of the Fit2Thrive MVPA promotion intervention on PROs in BCS and explore whether there are intervention component-specific effects on PROs. METHODS: Physically inactive BCS [n = 269; Mage = 52.5 (SD = 9.9)] received a core intervention (Fitbit + Fit2Thrive smartphone app) and were randomly assigned to one of 32 conditions in a full factorial experiment of five components ("on" vs. "off"): (i) support calls, (ii) deluxe app, (iii) text messages, (iv) online gym, and (v) buddy. Patient-Reported Outcomes Measurement Information System (PROMIS) questionnaires assessed anxiety, depression, fatigue, physical functioning, sleep disturbance and sleep-related impairment at baseline, post-intervention (12-week), and 24-week follow-up. Main effects for all components at each time point were examined using an intention to treat mixed-effects model. RESULTS: All PROMIS measures except sleep disturbance significantly improved (p's < .008 for all) from baseline to 12-weeks. Effects were maintained at 24-weeks. The "on" level of each component did not result in significantly greater improvements on any PROMIS measure compared to the "off" level. CONCLUSIONS: Participation in Fit2Thrive was associated with improved PROs in BCS, but improvements did not differ for "on" vs. "off" levels for any component tested. The low-resource Fit2Thrive core intervention is a potential strategy to improve PROs among BCS. Future studies should test the core in an RCT and examine various intervention component effects in BCS with clinically elevated PROs.

Health4Life eHealth intervention to modify multiple lifestyle risk behaviours among adolescent students in Australia: a cluster-randomised controlled trial.

BACKGROUND: Lifestyle risk behaviours are prevalent among adolescents and commonly co-occur, but current intervention approaches tend to focus on single risk behaviours. This study aimed to evaluate the efficacy of the eHealth intervention Health4Life in modifying six key lifestyle risk behaviours (ie, alcohol use, tobacco smoking, recreational screen time, physical inactivity, poor diet, and poor sleep, known as the Big 6) among adolescents. METHODS: We conducted a cluster-randomised controlled trial in secondary schools that had a minimum of 30 year 7 students, in three Australian states. A biostatistician randomly allocated schools (1:1) to Health4Life (a six-module, web-based programme and accompanying smartphone app) or an active control group (usual health education) with the Blockrand function in R, stratified by site and school gender composition. All students aged 11-13 years who were fluent in English and attended participating schools were eligible. Teachers, students, and researchers were not masked to allocation. Primary outcomes were alcohol use, tobacco use, recreational screen time, moderate to vigorous physical activity (MVPA), sugar-sweetened beverage intake, and sleep duration at 24 months, measured by self-report surveys, and analysed in all students who were eligible at baseline. Latent growth models estimated between-group change over time. This trial is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12619000431123). FINDINGS: Between April 1, 2019, and Sept 27, 2019, we recruited 85 schools (9280 students), of which 71 schools with 6640 eligible students (36 schools [3610 students] assigned to the intervention and 35 [3030 students] to the control) completed the baseline survey. 14 schools were excluded from the final analysis or withdrew, mostly due to a lack of time. We found no between-group differences for alcohol use (odds ratio 1·24, 95% CI 0·58-2·64), smoking (1·68, 0·76-3·72), screen time (0·79, 0·59-1·06), MVPA (0·82, 0·62-1·09), sugar-sweetened beverage intake (1·02, 0·82-1·26), or sleep (0·91, 0·72-1·14) at 24 months. No adverse events were reported during this trial. INTERPRETATION: Health4Life was not effective in modifying risk behaviours. Our results provide new knowledge about eHealth multiple health behaviour change interventions. However, further research is needed to improve efficacy. FUNDING: Paul Ramsay Foundation, the Australian National Health and Medical Research Council, the Australian Government Department of Health and Aged Care, and the US National Institutes of Health.