Developing an international consensus Reporting guideline for intervention Fidelity in Non-Drug, non-surgical trials: The ReFiND protocol.

BACKGROUND: Inadequate reporting of fidelity to interventions in trials limits the transparency and interpretation of trial findings. Despite this, most trials of non-drug, non-surgical interventions lack comprehensive reporting of fidelity. If fidelity is poorly reported, it is unclear which intervention components were tested or implemented within the trial, which also hinders research reproducibility. This protocol describes the development process of a reporting guideline for fidelity of non-drug, non-surgical interventions (ReFiND) in the context of trials. METHODS: The ReFiND guideline will be developed in six stages. Stage one: a guideline development group has been formed to oversee the guideline methodology. Stage two: a scoping review will be conducted to identify and summarize existing guidance documents on the fidelity of non-drug, non-surgical interventions. Stage three: a Delphi study will be conducted to reach consensus on reporting items. Stage four: a consensus meeting will be held to consolidate the reporting items and discuss the wording and structure of the guideline. Stage five: a guidance statement, an elaboration and explanation document, and a reporting checklist will be developed. Stage six: different strategies will be used to disseminate and implement the ReFiND guideline. DISCUSSION: The ReFiND guideline will provide a set of items developed through international consensus to improve the reporting of intervention fidelity in trials of non-drug, non-surgical interventions. This reporting guideline will enhance transparency and reproducibility in future non-drug, non-surgical intervention research.

Behavioral Activation Mobile App to Motivate Smokers to Quit: Feasibility and Pilot Randomized Controlled Trial.

BACKGROUND: Behavioral activation (BA) is an evidence-based treatment for depression that fosters engagement in values-based activities to increase access to positive reinforcement. Depressed mood has been shown to hinder smoking cessation. OBJECTIVE: This study determined the feasibility and preliminary efficacy of a mobile app to motivate smokers to quit by using BA and integrating motivational messages to quit smoking. METHODS: Adult smokers (N=56; mean age 34.5, SD 9.52 years) who were not ready to quit smoking within 30 days were recruited from advertisements and randomized to either 8 weeks of the BA app (set 2 values-based activities per week+motivational messages+feedback on changes in smoking, mood, and values-based activities) or the control group (no app; received resources for quitting smoking). All participants completed the baseline and end-of-treatment web-based questionnaires. Controls also completed weekly web-based assessments, and BA app participants completed assessments through the app. RESULTS: There were no dropouts and only 2 participants in each condition did not complete the end-of-treatment questionnaire. The results demonstrated that it is feasible to recruit smokers who are unmotivated to quit into a smoking cessation induction trial: 86% (57/66) of eligible participants were randomized (BA app: n=27; control: n=29). Participants reported high levels of satisfaction: 80% (20/25) of participants said they would recommend the BA app, there were moderate-to-high scores on the Mobile App Rating Scale, and 88% (22/25) of participants rated the app 3 stars or higher (out of 5). There were high levels of BA app engagement: 96% (26/27) of participants planned activities, and 67% (18/27) of participants planned 7 or more activities. High engagement was found even among those who were at the highest risk for continued smoking (low motivation to quit, low confidence to quit, and high negative affect). The results provided support for the hypothesized relationships between BA constructs: greater pleasant activity completion was associated with greater positive affect (b=0.37, SE 0.21; 95% CI -0.05 to 0.79; P=.08), and greater positive affect tended to predict fewer cigarettes smoked the next day (b=-0.19, SE 0.10; 95% CI -0.39 to 0.01; P=.06). Additionally, a greater number of activities planned was associated with lower negative affect (b=-0.26, SE 0.15; 95% CI -0.55 to 0.04; P=.09). Overall, 16% (4/25) of BA app participants set a quit date versus 4% (1/27) among controls, and there were promising (but not significant) trends for motivation and confidence to quit. CONCLUSIONS: The findings suggest that a mobile app intervention can be made appealing to smokers who are unmotivated to quit by focusing on aspects most important to them, such as mood management. This theory-based intervention has shown some initial support for the underlying theoretical constructs, and further efficacy testing is warranted in a fully powered trial.

The Longitudinal Reciprocal Relationships of Tooth Brushing Behaviors Between Underserved Children and Their Caregivers.

BACKGROUND: Tooth brushing is effective in preventing early childhood caries. However, it is unclear how children's and caregiver's tooth brushing are reciprocally related. PURPOSE: The current study investigated whether the longitudinal relationships between children and caregiver tooth brushing are moderated by a caregiver-targeted child oral health intervention and caregiver depression. METHODS: Secondary analysis of a randomized clinical trial that tested whether caregiver-targeted oral health text messages (OHT) outperformed child wellness text messages (CWT) on pediatric dental caries and oral health behaviors (n = 754, mean child age = 2.9 years, 56.2% Black, 68.3%

Tooth brushing is effective in preventing dental cavities in children, but we do not know if or how children and caregiver brushing frequencies are related. This is important because interventions targeting children's oral health may also have the potential to benefit their caregiver's behaviors. Our study examined whether caregiver brushing of their own teeth and caregiver brushing of their young child's teeth positively influenced each other over time. We also explored whether this relationship was less likely if caregivers experienced depressive symptoms and more likely if caregivers participated in a text message program focused on improving their child's oral health. Results showed that caregiver and child tooth brushing behaviors positively influenced each other over time, but this relationship was observed only in caregivers who received the child oral health program (as opposed to the control group) and who reported low depressive symptoms (in contrast to caregivers with high depression symptoms). Our findings suggest that while caregivers and children positively influence each other's tooth-brushing behaviors over time, additional support is essential for caregivers experiencing depression to fully realize these reciprocal benefits.

Pain-Related Smoking Expectancies and Smoking Behavior Among U.S. Adult Cigarette Smokers with Chronic Pain.

BACKGROUND: This study investigated the factor structure of a measure of pain-smoking interrelations and expectancies (pain and smoking inventory (PSI)) and examined associations with risk factors for smoking maintenance among smokers with chronic pain (CP). METHOD: Participants (n = 504; M age = 46 ± 13 years; 58% female) completed an online survey about health-related factors and smoking characteristics. Data were analyzed using Horn's parallel analysis (PA) and multiple linear regression. RESULTS: PA indicated that a single-dimension structure was the best fit for the PSI. Our regression model accounted for 34% of the variance in PSI score. The PSI was associated with younger age, higher education, poorer physical functioning, greater pain severity and pain intensity, higher psychological distress, greater nicotine dependence, lower self-efficacy and greater perceived difficulty quitting, and lifetime use of behavioral treatment for quitting smoking. CONCLUSION: This research is the first step in identifying potential targets for smoking cessation approaches tailored to smokers with CP.

Perceptions about smartphone-based interventions to promote physical activity in inactive adults with knee pain - A qualitative study.

PURPOSE: Smartphone-based interventions offer a promising approach to address inactivity in people with knee osteoarthritis (OA). We explored perceptions towards smartphone-based interventions to improve physical activity, pain, and depressed mood in inactive people with knee pain. METHODS: This qualitative study included six focus groups at Boston University with inactive people with knee pain (n = 35). A smartphone app, developed by our team, using constructs of Social Cognitive Theory, was used to obtain participant feedback. RESULTS: Participants discussed wanting to use smartphone-based interventions for personalized exercise advice, for motivation (e.g., customized voice messages, virtual incentives), and to make exercise "less boring" (e.g., music, virtual gaming). Preferred app features included video tutorials on how to use the app, the ability to select information that can be viewed on the home screen, and the ability to interact with clinicians. Features that received mixed responses included daily pain tracking, daily exercise reminders, peer-interaction for accountability, and peer-competition for motivation. All participants discussed privacy and health data security concerns while using the app. CONCLUSIONS: Using a co-design approach, we report preferences and concerns related to using smartphone-based physical activity interventions in inactive people with knee pain. This information may help improve acceptability of such interventions in this population.

Knee Osteoarthritis (OA) is a leading cause of disability and chronic pain in middle- and older-age adults worldwide. Despite recommendations to be physically active, people with knee OA, especially those who experience depressive symptoms, are largely inactive.Smartphone-based interventions have the potential to improve physical activity in this population leading to improved pain, mood, and function. However, little is known about preferences for such interventions in individuals with knee pain who are inactive and who may also experience depressed mood. We examined the perceptions of inactive people with knee pain on using smartphone-based interventions to improve physical activity, pain, and mood, using an intervention framework grounded in Social Cognitive Theory as an example.We reported preferred app features in this population such as flexibility to view specific data, video tutorials on how to use the app, ability to interact with the clinician. We reported features that received mixed reviews such as daily pain tracking, daily reminders to exercise, peer-interaction and peer-competition for accountability and motivation respectively.Overall, people in our study wanted to use smartphone apps to improve motivation for exercise, to make exercise less boring, and to receive personalized exercise advise but they also had concerns related to privacy and health data security with using smartphone-based interventions.

Methods used to quit vaping among adolescents and associations with perceived risk, addiction, and socio-economic status.

Despite widespread evidence suggesting that e-cigarettes are harmful to youth, the prevalence of adolescent vaping continues to rise. The first aim of this cross-sectional study was to determine which methods adolescents have previously used to quit vaping and their interest in using various methods to quit vaping in the future. The second aim was to investigate the associations between vaping-related characteristics and (1) motivation to quit vaping and (2) previous use of pharmacological methods to quit vaping or previous use of unassisted quitting. Participants were 185 current or former vapers, aged 14-19 (M age = 16.9 years, SD = 1.1; 52% female), recruited online from different U.S. regions. Data were collected through online questionnaires. Most participants reported at least one prior attempt to quit vaping (81.3%). Unassisted quitting was the most prevalent method to quit vaping (78.4%), followed by "advice from a friend" (51.9%). Participants were interested in using a variety of methods for quitting vaping in the future, including medication (28.8%), and mobile apps (34.6%). Greater perceived harm of vaping was significantly associated with motivation to quit vaping, while greater perceived risk of addiction and higher SES were significantly associated with lifetimeuse of nicotine replacement to quit vaping. Adolescents may be open to trying methods to quit that are different from what they have used previously. These findings could help direct resources toward the development of vaping cessation programs that are acceptable to adolescents.

Association of Depressive Symptom Trajectory With Physical Activity Collected by mHealth Devices in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Few studies have examined the association between depressive symptom trajectories and physical activity collected by mobile health (mHealth) devices. OBJECTIVE: We aimed to investigate if antecedent depressive symptom trajectories predict subsequent physical activity among participants in the electronic Framingham Heart Study (eFHS). METHODS: We performed group-based multi-trajectory modeling to construct depressive symptom trajectory groups using both depressive symptoms (Center for Epidemiological Studies-Depression [CES-D] scores) and antidepressant medication use in eFHS participants who attended 3 Framingham Heart Study research exams over 14 years. At the third exam, eFHS participants were instructed to use a smartphone app for submitting physical activity index (PAI) surveys. In addition, they were provided with a study smartwatch to track their daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and physical activity including app-based PAI and smartwatch-collected step counts over a 1-year follow-up adjusting for age, sex, wear hour, BMI, smoking status, and other health variables. RESULTS: We identified 3 depressive symptom trajectory groups from 722 eFHS participants (mean age 53, SD 8.5 years; n=432, 60% women). The low symptom group (n=570; mean follow-up 287, SD 109 days) consisted of participants with consistently low CES-D scores, and a small proportion reported antidepressant use. The moderate symptom group (n=71; mean follow-up 280, SD 118 days) included participants with intermediate CES-D scores, who showed the highest and increasing likelihood of reporting antidepressant use across 3 exams. The high symptom group (n=81; mean follow-up 252, SD 116 days) comprised participants with the highest CES-D scores, and the proportion of antidepressant use fell between the other 2 groups. Compared to the low symptom group, the high symptom group had decreased PAI (mean difference -1.09, 95% CI -2.16 to -0.01) and the moderate symptom group walked fewer daily steps (823 fewer, 95% CI -1421 to -226) during the 1-year follow-up. CONCLUSIONS: Antecedent depressive symptoms or antidepressant medication use was associated with lower subsequent physical activity collected by mHealth devices in eFHS. Future investigation of interventions to improve mood including via mHealth technologies to help promote people's daily physical activity is needed.

The differential predictive utility of two caregiver-targeted self-efficacy measures to promote oral health of underserved children.

OBJECTIVE: Oral health self-efficacy is a modifiable determinant of early childhood caries, which is one of the most prevalent childhood diseases. Yet, two common measures of self-efficacy (i.e., context-specific and behavior-specific) lack validation and clarity in the prediction of children's oral health behaviors. This study examined the psychometric properties of two caregiver oral health self-efficacy measures and investigated the predictive ability and age-varying effects of caregiver oral health self-efficacy on child oral health behaviors. METHOD: In this secondary data analysis of caregiver-child dyads (n = 754, Mchild age = 2.4, 56.2% Black or African American, 68.3% below poverty level), caregivers reported their oral health self-efficacy and their child's tooth brushing frequency, diet, and sugar-sweetened beverage (SSB) consumption at baseline and 4, 12, and 24 months. Psychometrics were examined with confirmatory factor analyses (CFAs) and the predictive ability and age-varying effects of caregiver self-efficacy on child oral health behaviors were examined with time-varying effect models (TVEMs). RESULTS: The context- and behavior-specific oral health self-efficacy CFA models indicated mixed model fit. In the predictive TVEM models, greater behavior-specific, but not context-, oral health self-efficacy predicted greater child tooth brushing across all ages. Greater context-specific oral health self-efficacy predicted healthier child diet throughout childhood, but greater behavior-specific self-efficacy only predicted healthier child diet in older children. Greater behavior-specific self-efficacy predicted lower SSB consumption throughout childhood while greater context-specific self-efficacy only predicted lower SSB consumption in younger children. CONCLUSIONS: Both caregiver oral health self-efficacy measures were psychometrically comparable and differentially predicted oral health behaviors across varying childhood ages. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Greater engagement in valued activities is associated with less barriers to quitting smoking among smokers with mobility impairments.

BACKGROUND: Individuals with mobility impairments (MI; use equipment to ambulate) have a high prevalence of both smoking and depression. Behavioral activation (BA) purports that depressed mood is remediated through valued activity engagement and may facilitate smoking cessation in MI populations. OBJECTIVE: We examined cross-sectional associations between activity engagement and variables important for smoking cessation among a high-risk group of smokers (people with MIs) and also describe a smoking cessation intervention based on BA, given the lack of studies on smokers with MIs. METHODS: This study used data from a smoking cessation trial enrolling smokers with MIs (n = 263). We assessed valued activities, activity type, activity restriction due to MI, and replacement of restricted activities. Motivation and confidence to quit smoking, number of cigarettes per day, and mood were also assessed. Analysis was performed with generalized linear (or logistic) regression models adjusted for age and physical functioning using aggregated data at baseline. RESULTS: Greater number and frequency of valued activities was associated with less smoking, depression, negative affect, and stress and higher positive affect and self-efficacy to quit. Activity restriction was associated with greater odds of major depression, and activity replacement with lower odds of major depression, lower stress, and higher positive affect and self-efficacy. Strength of associations varied by activity type. CONCLUSIONS: Consistent with our theoretical model, BA activity constructs were associated with several mediators of smoking outcomes in the expected directions. Smokers engaging in valued activities have more favorable profiles for smoking cessation and mood management.

Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis.

BACKGROUND: Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk. OBJECTIVE: The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF. METHODS: Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m2), as well as the relation between self-reported physical activity and predicted 5-year AF risk. RESULTS: We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk. CONCLUSIONS: Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.

Behavioural and social oral health intervention research: Looking to the future.

Behavioural and social oral health intervention has made great strides in intervention development and testing. Future research should focus on applying successful methods and interventions of disciplines outside oral health to oral health research and practice as well as focus on raising the visibility of oral health research by applying our established methods and interventions to outside domains. Behavioural and social oral health is strategically positioned to be a leader across several research domains, perhaps most prominently in digital health, disparities and developing and testing theories and frameworks, given the progress that has already been made, and significant investment in these areas from funders like the National Institute for Craniofacial Research.

Inequities and oral health: A behavioural sciences perspective.

OBJECTIVES: The importance of tackling ongoing dental health inequities, observed both within and across countries, cannot be overstated. Alarmingly, health inequities in some areas are widening, resulting in an urgent need to act. The objective of this commentary is to explore oral health inequities through the lens of behavioral science and discuss adapting evidence based interventions for populations experiencing health inequities. METHOD/RESULTS: The first section of this paper aims to describe the role of health disparities and inequities within oral health, with a specific focus on behaviours. The determinants, from upstream to downstream, and the interplay between these levels of intervention are discussed. This is followed by an overview of oral health promotion interventions, again with a focus on behaviours, which could potentially improve oral health while also taking into account oral health inequities. It is essential to translate evidence-based interventions (EBIs) to populations that have the greatest burden of disease. The second section of this paper discusses the rationale for cultural adaption of EBIs, criteria to justify EBIs and considers different cultural adaptation strategies necessary for the development and testing of effective, engaging, equitable and culturally relevant interventions. CONCLUSIONS: We conclude with future directions for the development of theory-based multi-level interventions, guided by extent evidence-based interventions, and transdisciplinary approaches to science and key stakeholders such as patients, providers and payers.

Theoretical and methodological approaches in designing, developing, and delivering interventions for oral health behaviour change.

Oral health behaviour change interventions are gaining momentum on a global scale. After lagging behind other disciplines, oral health behaviour change is becoming an area of fast and important development. Theories used in medicine and healthcare more generally are now being applied to oral health behaviour change with varying results. Despite the importance of using theories when designing and developing interventions, the variety and variation of theories available to choose from create a series of dilemmas and potential hazards. Some theories, like the COM-B (Capability, Opportunity, Motivation-Behaviour) model, and frameworks, like the Behaviour Change Wheel might represent areas of opportunity for oral health behaviour change interventions with careful consideration vital. Different methodological approaches to intervention development are actively utilized in oral health with a wide host of potential opportunities. The issue of co-designing and co-developing interventions with intended users and stakeholders from the start is an important component for successful and effective interventions, one that oral health behaviour change interventions need to consistently implement. Oral health behaviour change interventions are utilizing technology-based approaches as a major vehicle for intervention delivery and, innovative solutions are implemented across a wide host of oral health behaviour change interventions. With multiple options for designing, developing, and delivering interventions, careful selection of appropriate, user-inclusive, and adaptable approaches is essential. With a lot of available information and evidence from other disciplines, oral health behaviour change interventions need to reflect on lessons learned in other fields whilst also maximizing the potential of the wide variety of theories, frameworks, methodologies, and techniques available at present.

Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial.

BACKGROUND: Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited. OBJECTIVE: This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data. METHODS: We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant's name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary). RESULTS: Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%; P=.006), but no significant differences were observed for HR data transmission (212/324, 65.4% vs 209/327, 63.9%; P=.69). Personalized notifications were associated with increased BP and HR data transmission versus standard at 6 months (BP: 107/291, 36.8% vs 66/295, 22.4%; difference=14.4%, 95% CI 7.1- 21.7%; P<.001; HR: 186/281, 66.2% vs 158/281, 56.2%; difference=10%, 95% CI 2%-18%; P=.02). For BP and HR primary or secondary outcomes, there was no evidence of differences in data transmission for notifications sent on weekend versus weekday or morning versus evening. CONCLUSIONS: Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research. TRIAL REGISTRATION: ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019.

Factors associated with long-term use of digital devices in the electronic Framingham Heart Study.

Long-term use of digital devices is critical for successful clinical or research use, but digital health studies are challenged by a rapid drop-off in participation. A nested e-cohort (eFHS) is embedded in the Framingham Heart Study and uses three system components: a new smartphone app, a digital blood pressure (BP) cuff, and a smartwatch. This study aims to identify factors associated with the use of individual eFHS system components over 1-year. Among 1948 eFHS enrollees, we examine participants who returned surveys within 90 days (n = 1918), and those who chose to use the smartwatch (n = 1243) and BP cuff (n = 1115). For each component, we investigate the same set of candidate predictors for usage and use generalized linear mixed models to select predictors (P < 0.1, P value from Z test statistic), adjusting for age, sex, and time (app use: 3-month period, device use: weekly). A multivariable model with the predictors selected from initial testing is used to identify factors associated with use of components (P < 0.05, P value from Z test statistic) adjusting for age, sex, and time. In multivariable models, older age is associated with higher use of all system components. Female sex and higher education levels are associated with higher completion of app-based surveys whereas higher scores for depressive symptoms, and lower than excellent self-rated health are associated with lower use of the smartwatch over the 12-month follow-up. Our findings show that sociodemographic and health related factors are significantly associated with long-term use of digital devices. Future research is needed to test interventional strategies focusing on these factors to evaluate improvement in long-term engagement.

Integrating Social Determinants of Health With Tobacco Treatment for Individuals With Opioid Use Disorder: Feasibility and Acceptability Study of Delivery Through Text Messaging.

BACKGROUND: Individuals with opioid use disorder (OUD) have a high prevalence of smoking and frequently experience unmet social determinants of health (SDOH), which may be barriers to smoking cessation. Hospitalization is an opportunity to encourage smoking cessation. Unfortunately, many clinicians do not provide tobacco treatment to support the maintenance of cessation achieved during hospitalization. Interventions are required to support these high-risk individuals after hospital discharge. OBJECTIVE: This study aimed to test the feasibility and acceptability of a 28-day SMS text messaging program tailored to individuals with OUD, which provides smoking cessation support and addresses unmet SDOH needs. METHODS: From July to December 2019, we enrolled 25 individuals who were hospitalized with tobacco dependence and OUD at our large safety net hospital. The SMS text messaging program was initiated during hospitalization and continued for 28 days. Participants were enrolled in either the ready to quit within 30 days or the not ready to quit within 30 days program based on their readiness to quit. Automated SMS text messages were sent twice daily for 4 weeks. The topics included health and cost benefits of quitting, both general and opioid specific (16 messages); managing mood and stress (8 messages); motivation, coping strategies, and encouragement (18 messages); addressing medication misconceptions (5 messages); links to resources to address substance use (2 messages providing links to the Massachusetts Substance Use Helpline and Boston Medical Center resources), tobacco dependence (1 message providing a link to the Massachusetts Quitline), and unmet SDOH needs (6 messages assessing SDOH needs with links to resources if unmet SDOH needs were identified). Questionnaires and interviews were conducted at baseline and at 2 and 4 weeks after enrollment. RESULTS: The participants were 56% (14/25) female, 36% (9/25) African American, 92% (23/25) unemployed, and 96% (24/25) Medicaid insured. Approximately 84% (21/25) activated the program, and none of the participants unsubscribed. Approximately 57% (12/21) completed either the 2- or 4-week questionnaires. Program satisfaction was high (overall mean 6.7, SD 0.8, range 1-7). Many perceived that the SMS text messaging program provided social support, companionship, and motivation to stop smoking. Messages about the health benefits of quitting were well received, whereas messages on how quitting cigarettes may prevent relapse from other substances had mixed views, highlighting the importance of tailoring interventions to patient preferences. CONCLUSIONS: SMS text messaging to promote smoking cessation and address SDOH needs may be an effective tool for improving quit rates and health outcomes in individuals with tobacco dependence and OUD. Our study adds to the growing body of evidence that SMS text messaging approaches are feasible and acceptable for providing tobacco treatment to all individuals who smoke, even among low-income populations who have OUD and are not ready to quit.

Self-Determination Theory and Preventive Medication Adherence: Motivational Considerations to Support Historically Marginalized Adolescents With Asthma.

INTRODUCTION: Using self-determination theory, we explored relationships between autonomous motivation (AM) and perceived competence (PC) with previously validated measures of motivation and adolescent-reported asthma medication adherence. METHOD: Data were from adolescents (n = 260) enrolled in the School-Based Asthma Care for Teens study and taking preventive medication at baseline. Eligible adolescents (aged 12-16 years) had physician-diagnosed persistent asthma or poor control. RESULTS: Adolescents taking daily preventive medicine reported higher AM and PC for adherence, whereas adolescents likely to miss ≥1 dose in the next 2 weeks had lower AM and PC. Adolescents taking medicines as prescribed, with plans to continue, and those feeling able to follow provider care plans, had higher AM and PC. Findings remained significant in regressions with control variables. DISCUSSION: Many factors interfere with adolescent medication-taking. Clinicians' efforts to build AM and PC with patients and caregivers may be key to promoting adherence in this group.

Mobile health plus community health worker support for weight management among public housing residents (Path to Health): A randomized controlled trial protocol.

Interventions delivered by mobile devices (mHealth interventions) have the potential to increase access to weight management treatment in low-income populations. However, little prior research has examined effects of mHealth programming plus phone-based community health worker (CHW) support for weight management among public housing residents. For our intervention, we first interacted with a community advisory board to collect feedback on proposed intervention components. Transcripts from 5 advisory board meetings were coded and qualitative data was organized into themes. We used these data to inform our ongoing trial, in which public housing residents are randomized to one of three different groups: phone text messaging and digital self-weighing (mHealth only); mHealth intervention plus CHW behavioral phone counseling (mHealth+CHW); or assessment only to evaluate their differential effects on weight loss at 6- and 12-month follow-up. We will examine changes in diet and physical activity behaviors as well as potential mediating and moderating factors. Results of this trial could provide support for technology-based weight management interventions which may have greater potential for scalability and long-term dissemination than face-to-face programming. Clinical Trial Registration Number: NCT04852042.

Text-messaging to promote smoking cessation among individuals with opioid use disorder: quantitative and qualitative evaluation.

INTRODUCTION: Individuals with opioid use disorder (OUD) who smoke cigarettes have high tobacco-related comorbidities, lack of access to tobacco treatment, lack of inclusion in smoking cessation trials, and remain understudied in the mobile health field. The purpose of this study was to understand patients' with OUD perceptions of 1) text message programs to promote smoking cessation, 2) content and features to include in such a program, and 3) how message content should be framed. METHODS: From December 2018 to February 2019, we recruited 20 hospitalized individuals with a concurrent diagnosis of OUD and tobacco dependence at Boston Medical Center (BMC), the largest safety-net hospital in New England. We surveyed participants' cell phone use, their interest in a text message program to promote smoking cessation, and their reactions to and ratings of a series of 26 prototype texts. We then conducted open-ended interviews to elicit content and suggestions on how text message interventions can improve motivation to increase smoking cessation among individuals with OUD. The interviews also included open-ended inquiries exploring message ratings and message content, inquiries about preferences for message duration, frequency, and personalization. RESULTS: Quantitative analysis of questionnaire data indicated that the majority of participants owned a cell phone (95%, 19/20). Most participants (60%, 12/20) reported that they would be interested or very interested in receiving text messages about smoking cessation. Text messages about the health benefits of quitting were rated the highest among various categories of text messages. Qualitative analysis showed that almost every participant felt that text messages would help motivate smoking cessation given the support it would provide. CONCLUSIONS: This study demonstrates that individuals with OUD who smoke cigarettes perceive that a text message program designed to promote smoking cessation would motivate and support smoking cessation efforts. Our findings demonstrate that such a program is feasible as participants own cell phones, frequently send and receive text messages, and have unlimited text message plans. Findings from this study provide valuable insight into content and features to include when developing text message programs to address barriers to smoking cessation in individuals who have OUD and smoke cigarettes.

Relations Between BMI Trajectories and Habitual Physical Activity Measured by a Smartwatch in the Electronic Cohort of the Framingham Heart Study: Cohort Study.

BACKGROUND: The prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear. OBJECTIVE: This study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS). METHODS: We used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts. RESULTS: We identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI -823 to -21) and 1437 (95% CI -2084 to -790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI -773 to 10) and group 3 took 1120 (95% CI -1766 to -475) fewer steps, compared with group 1. CONCLUSIONS: In this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.