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BACKGROUND: Patients with diabetes experience worse health outcomes and greater health care expenditure. Improving diabetes outcomes requires involved self-management. Peer coaching programs can help patients engage in self-management while addressing individual and structural barriers. These peer coaching programs can be scaled with digital platforms to efficiently connect patients with peer supporters who can help with diabetes self-management. OBJECTIVE: This study aimed to evaluate the implementation of a technology-enabled peer coaching intervention to support diabetes self-management among patients with uncontrolled diabetes. METHODS: MetroPlusHealth, a predominant Medicaid health maintenance organization based in New York City, partnered with Pyx Health to enroll 300 Medicaid patients with uncontrolled diabetes into its 6-month peer coaching intervention. Pyx Health peer coaches conduct at least 2 evidence-based and goal-oriented coaching sessions per month with their assigned patients. These sessions are focused on addressing both behavioral and social determinants of health (SDoH) with the goal of helping patients increase their diabetes self-management literacy, implement self-management behaviors, and reduce barriers to ongoing self-care. Data analyzed in this study included patient demographic data, clinical data (patients hemoglobin A1c [HbA1c]), and program implementation data including types of behavioral determinants of health and SDoH reported by patients and types of interventions used by peer coaches. RESULTS: A total of 330 patients enrolled in the peer mentoring program and 2118 patients were considered to be on a waitlist group and used as a comparator. Patients who enrolled in the peer coaching program were older; more likely to be English speakers, female, and African American; and less likely to be White or Asian American or Pacific Islander than those in the waitlist condition, and had similar HbA1c laboratory results at baseline (intervention group 10.59 vs waitlist condition 10.62) Patients in the enrolled group had on average a -1.37 point reduction in the HbA1c score (n=70; pre: 10.99, post 9.62; P

BackgroundText messaging interventions can be an effective and efficient way to improve health behavioral changes. However, most texting interventions are neither tested nor designed with diverse end users, which could reduce their impact, and there is limited evidence regarding the optimal design methodology of health text messages tailored to low-income, low–health literacy populations and non-English speakers. ObjectiveThis study aims to combine participant feedback, crowdsourced data, and researcher expertise to develop motivational text messages in English and Spanish that will be used in a smartphone app–based texting intervention that seeks to encourage physical activity in low-income minority patients with diabetes diagnoses and depression symptoms. MethodsThe design process consisted of 5 phases and was iterative in nature, given that the findings from each step informed the subsequent steps. First, we designed messages to increase physical activity based on the behavior change theory and knowledge from the available evidence. Second, using user-centered design methods, we refined these messages after a card sorting task and semistructured interviews (N=10) and evaluated their likeability during a usability testing phase of the app prototype (N=8). Third, the messages were tested by English- and Spanish-speaking participants on the Amazon Mechanical Turk (MTurk) crowdsourcing platform (N=134). Participants on MTurk were asked to categorize the messages into overarching theoretical categories based on the capability, opportunity, motivation, and behavior framework. Finally, each coauthor rated the messages for their overall quality from 1 to 5. All messages were written at a sixth-grade or lower reading level and culturally adapted and translated into neutral Spanish by bilingual research staff. ResultsA total of 200 messages were iteratively refined according to the feedback from target users gathered through user-centered design methods, crowdsourced results of a categorization test, and an expert review. User feedback was leveraged to discard unappealing messages and edit the thematic aspects of messages that did not resonate well with the target users. Overall, 54 messages were sorted into the correct theoretical categories at least 50% of the time in the MTurk categorization tasks and were rated 3.5 or higher by the research team members. These were included in the final text message bank, resulting in 18 messages per motivational category. ConclusionsBy using an iterative process of expert opinion, feedback from participants that were reflective of our target study population, crowdsourcing, and feedback from the research team, we were able to acquire valuable inputs for the design of motivational text messages developed in English and Spanish with a low literacy level to increase physical activity. We describe the design considerations and lessons learned for the text messaging development process and provide a novel, integrative framework for future developers of health text messaging interventions.

BackgroundThe COVID-19 pandemic has propelled patient-facing research to shift to digital and telehealth strategies. If these strategies are not adapted for minority patients of lower socioeconomic status, health inequality will further increase. Patient-centered models of care can successfully improve access and experience for minority patients. ObjectiveThis study aims to present the development process and preliminary acceptability of altering in-person onboarding procedures into internet-based, remote procedures for a mobile health (mHealth) intervention in a population with limited digital literacy. MethodsWe actively recruited safety-net patients (English- and Spanish-speaking adults with diabetes and depression who were receiving care at a public health care delivery system in San Francisco, United States) into a randomized controlled trial of text messaging support for physical activity. Because of the COVID-19 pandemic, we modified the in-person recruitment and onboarding procedures to internet-based, remote processes with human support. We conducted a preliminary evaluation of how the composition of the recruited cohort might have changed from the pre–COVID-19 period to the COVID-19 enrollment period. First, we analyzed the digital profiles of patients (n=32) who had participated in previous in-person onboarding sessions prior to the COVID-19 pandemic. Next, we documented all changes made to our onboarding processes to account for remote recruitment, especially those needed to support patients who were not very familiar with downloading apps onto their mobile phones on their own. Finally, we used the new study procedures to recruit patients (n=11) during the COVID-19 social distancing period. These patients were also asked about their experience enrolling into a fully digitized mHealth intervention. ResultsRecruitment across both pre–COVID-19 and COVID-19 periods (N=43) demonstrated relatively high rates of smartphone ownership but lower self-reported digital literacy, with 32.6% (14/43) of all patients reporting they needed help with using their smartphone and installing apps. Significant changes were made to the onboarding procedures, including facilitating app download via Zoom video call and/or a standard phone call and implementing brief, one-on-one staff-patient interactions to provide technical assistance personalized to each patient’s digital literacy skills. Comparing recruitment during pre–COVID-19 and COVID-19 periods, the proportion of patients with digital literacy barriers reduced from 34.4% (11/32) in the pre–COVID-19 cohort to 27.3% (3/11) in the COVID-19 cohort. Differences in digital literacy scores between both cohorts were not significant (P=.49). ConclusionsPatients of lower socioeconomic status have high interest in using digital platforms to manage their health, but they may require additional upfront human support to gain access. One-on-one staff-patient partnerships allowed us to provide unique technical assistance personalized to each patient’s digital literacy skills, with simple strategies to troubleshoot patient barriers upfront. These additional remote onboarding strategies can mitigate but not eliminate digital barriers for patients without extensive technology experience. Trial RegistrationClinicaltrials.gov NCT0349025, https://clinicaltrials.gov/ct2/show/NCT03490253

BackgroundSocial distancing is a crucial intervention to slow down person-to-person transmission of COVID-19. However, social distancing has negative consequences, including increases in depression and anxiety. Digital interventions, such as text messaging, can provide accessible support on a population-wide scale. We developed text messages in English and Spanish to help individuals manage their depressive mood and anxiety during the COVID-19 pandemic. ObjectiveIn a two-arm randomized controlled trial, we aim to examine the effect of our 60-day text messaging intervention. Additionally, we aim to assess whether the use of machine learning to adapt the messaging frequency and content improves the effectiveness of the intervention. Finally, we will examine the differences in daily mood ratings between the message categories and time windows. MethodsThe messages were designed within two different categories: behavioral activation and coping skills. Participants will be randomized into (1) a random messaging arm, where message category and timing will be chosen with equal probabilities, and (2) a reinforcement learning arm, with a learned decision mechanism for choosing the messages. Participants in both arms will receive one message per day within three different time windows and will be asked to provide their mood rating 3 hours later. We will compare self-reported daily mood ratings; self-reported depression, using the 8-item Patient Health Questionnaire; and self-reported anxiety, using the 7-item Generalized Anxiety Disorder scale at baseline and at intervention completion. ResultsThe Committee for the Protection of Human Subjects at the University of California Berkeley approved this study in April 2020 (No. 2020-04-13162). Data collection began in April 2020 and will run to April 2021. As of August 24, 2020, we have enrolled 229 participants. We plan to submit manuscripts describing the main results of the trial and results from the microrandomized trial for publication in peer-reviewed journals and for presentations at national and international scientific meetings. ConclusionsResults will contribute to our knowledge of effective psychological tools to alleviate the negative effects of social distancing and the benefit of using machine learning to personalize digital mental health interventions. Trial RegistrationClinicalTrials.gov NCT04473599; https://clinicaltrials.gov/ct2/show/NCT04473599 International Registered Report Identifier (IRRID)DERR1-10.2196/23592

BackgroundHealth care systems are rapidly deploying digital tools for disease management; however, few studies have evaluated their usability by vulnerable populations. To understand the barriers to app usage among vulnerable populations, we employed user-centered design (UCD) methods in the development of a new text messaging app. ObjectiveThe study aimed to describe variations in patients’ engagement in the app design process, focusing on limited health literacy (LHL), limited English proficiency (LEP), and limited digital literacy (LDL). MethodsWe conducted 20 in-depth semistructured interviews with primary care patients at a public health care system, used open-ended discussions and card sorting tasks to seek input about mobile phones and text messaging, and used open coding to categorize the patterns of mobile phone usage and to evaluate engagement in the card sorting process. We examined qualitative differences in engagement by examining the extensiveness of participant feedback on existing and novel text messaging content and calculated the proportion of patients providing extensive feedback on existing and novel content, overall and by health literacy, English proficiency, and digital literacy. ResultsThe average age of the 20 participants was 59 (SD 8) years; 13 (65%) were female, 18 (90%) were nonwhite, 16 (80%) had LHL, and 13 (65%) had LEP. All had depression, and 14 (70%) had diabetes. Most participants had smartphones (18/20, 90%) and regularly used text messaging (15/20, 75%), but 14 (70%) of them reported having difficulty texting because of inability to type, physical disability, and low literacy. We identified 10 participants as specifically having LDL; 7 of these participants had LEP, and all 10 had LHL. Half of the participants required a modification of the card sorting activity owing to not understanding it or not being able to read the cards in the allotted time. The proportion of participants who gave extensive feedback on existing content was lower in participants with limited versus adequate English proficiency (4/13, 30% vs 5/7, 71%), limited versus adequate health literacy (7/16, 44% vs 3/4, 75%), and limited versus adequate digital literacy (4/10, 40% vs 6/10, 60%); none of these differences were statistically significant. When examining the proportion of patients who gave extensive feedback for novel messaging content, those with LHL were less engaged than those with adequate health literacy (8/16, 50% vs 4/4, 100%); there were no statistical differences by any subgroup. ConclusionsDespite widespread mobile phone use, digital literacy barriers are common among vulnerable populations. Engagement in the card sorting activity varied among participants and appeared to be lower among those with LHL, LEP, and LDL. Researchers employing traditional UCD methods should routinely measure these communication domains among their end-user samples. Future work is needed to replicate our findings in larger samples, but augmentation of card sorting with direct observation and audiovisual cues may be more productive in eliciting feedback for those with communication barriers.

BackgroundAlthough psychotherapy is one of the most efficacious and effective treatments for depression, limited accessibility to trained providers markedly limits access to care. In an attempt to overcome this obstacle, several platforms seeking to provide these services using digital modalities (eg, video, text, and chat) have been developed. However, the use of these modalities individually poses barriers to intervention access and acceptability. Multimodal platforms, comprising those that allow users to select from a number of available modalities, may be able to provide a solution to these concerns. ObjectiveWe aimed to investigate the preliminary effectiveness of providing psychotherapy through a multimodal digital psychotherapy platform. In addition, we aimed to examine differential responses to intervention by gender, self-reported physical health status, and self-reported financial status, as well as how prior exposure to traditional face-to-face psychotherapy affected the effectiveness of a multimodal digital psychotherapy intervention. Finally, we aimed to examine the dose-response effect. MethodsData were collected from a total of 318 active users of BetterHelp, a multimodal digital psychotherapy platform. Data on physical health status, financial status, and prior exposure to psychotherapy were obtained using self-report measures. Effectiveness was determined by the extent of symptom severity change, which was measured using the Patient Health Questionnaire at Time 1 (time of enrollment) and Time 2 (3 months after enrollment). Intervention dosage was measured as the sum of individual therapist-user interactions across modalities. ResultsDepression symptom severity was significantly reduced after the use of the multimodal digital psychotherapy intervention (P

BACKGROUND: Limited English Proficiency (LEP) Latinxs experience a longer duration of untreated depression and anxiety. LEP Latinxs have difficulty accessing mental healthcare due to insufficient Spanish-speaking behavioral/mental health clinicians to meet demand. These under-resourced healthcare systems are less likely to be the site for the implementation of innovations. Digital interventions can provide an effective option for overcoming these barriers; yet, when digital evidence-based treatments are available, uptake and engagement is often low. This manuscript presents the protocol for the SUPERA (SUpport from PEeRs to expand Access) study which will evaluate the implementation of an evidence-based, Spanish language, digital cognitive-behavioral therapy (dCBT) intervention (i.e., SilverCloud) in safety-net primary care clinics for LEP Latinx patients with depression or anxiety. METHODS: We will conduct an effectiveness-implementation hybrid trial (Type 2) design comparing engagement and clinical outcomes in two modalities of dCBT delivery (peer-supported vs. unsupported). We will also compare provider-level outreach (using a clinic patient registry) versus inreach (traditional provider referral) to compare rates of initiation, completion, and cost. Participants will be 426 LEP Latinx adults ≥18 years of age, PHQ-9 ≥ 10 or GAD-7 ≥ 8, with access to the internet via smartphone, and not currently receiving individual psychotherapy. We will collect baseline, post-intervention (8 weeks), and follow up (3 months) data. CONCLUSION: The long-term goal of this research is to aid in the implementation of digital mental health interventions that can be sustainably implemented in low-resourced settings, while reducing the reliance on professionals, overcoming workforce deficits, and increasing relevance for diverse populations.

The StayWell at Home intervention, a 60-day text-messaging program based on Cognitive Behavioral Therapy (CBT) principles, was developed to help adults cope with the adverse effects of the global pandemic. Participants in StayWell at Home were found to show reduced depressive and anxiety symptoms after participation. However, it remains unclear whether the intervention improved mood and which intervention components were most effective at improving user mood during the pandemic. Thus, utilizing a micro-randomized trial (MRT) design, we examined two intervention components to inform the mechanisms of action that improve mood: 1) text messages delivering CBT-informed coping strategies (i.e., behavioral activation, other coping skills, or social support); 2) time at which messages were sent. Data from two independent trials of StayWell are included in this paper. The first trial included 303 adults aged 18 or older, and the second included 266 adults aged 18 or older. Participants were recruited via online platforms (e.g., Facebook ads) and partnerships with community-based agencies aiming to reach diverse populations, including low-income individuals and people of color. The results of this paper indicate that participating in the program improved and sustained self-reported mood ratings among participants. We did not find significant differences between the type of message delivered and mood ratings. On the other hand, the results from Phase 1 indicated that delivering any type of message in the 3 pm-6 pm time window improved mood significantly over sending a message in the 9 am-12 pm time window. The StayWell at Home program increases in mood ratings appeared more pronounced during the first two to three weeks of the intervention and were maintained for the remainder of the study period. The current paper provides evidence that low-burden text-message interventions may effectively address behavioral health concerns among diverse communities.

BACKGROUND: Women are less physically active, report greater perceived barriers for exercise, and show higher levels of depressive symptoms. This contributes to high global disability. The relationship between perceived barriers for physical activity and depressive symptoms in women remains largely unexplored. The aims of this cross-sectional analysis were to examine the association between physical activity barriers and depressive symptoms, and identify types of barriers in physically inactive community-dwelling women. METHODS: Three hundred eighteen physically inactive women aged 25-65 years completed the Barriers to Being Active Quiz (BBAQ) developed by the Centers for Disease Control and Prevention, and the Center for Epidemiological Studies Depression Scale at the baseline visit of the mobile phone-based physical activity education trial. The BBAQ consists of six subscales (lack of time, social influence, lack of energy, lack of willpower, fear of injury, lack of skill, and lack of resources). We used multivariate regression analyses, correcting for sociodemographics. RESULTS: Higher physical activity barriers were associated with greater depressive symptoms scores (linear effect, estimate = 0.75, 95% confidence interval [CI]: 0.39-1.12, p

BackgroundAutomatically tracking mental well-being could facilitate personalization of treatments for mood disorders such as depression and bipolar disorder. Smartphones present a novel and ubiquitous opportunity to track individuals’ behavior and may be useful for inferring and automatically monitoring mental well-being. ObjectiveThe aim of this study was to assess the extent to which activity and sleep tracking with a smartphone can be used for monitoring individuals’ mental well-being. MethodsA cohort of 106 individuals was recruited to install an app on their smartphone that would track their well-being with daily surveys and track their behavior with activity inferences from their phone’s accelerometer data. Of the participants recruited, 53 had sufficient data to infer activity and sleep measures. For this subset of individuals, we related measures of activity and sleep to the individuals’ well-being and used these measures to predict their well-being. ResultsWe found that smartphone-measured approximations for daily physical activity were positively correlated with both mood (P=.004) and perceived energy level (P

BackgroundYouth in the child welfare system (child welfare-involved [CWI] youth) have high documented rates of mental health symptoms and experience significant disparities in mental health care services access and engagement. Adolescence is a developmental stage that confers increased likelihood of experiencing mental health symptoms and the emergence of disorders that can persist into adulthood. Despite a high documented need for evidence-based mental health services for CWI youth, coordination between child welfare and mental health service systems to increase access to care remains inadequate, and engagement in mental health services is low. Navigator models developed in the health care field to address challenges of service access, fragmentation, and continuity that affect the quality of care provide a promising approach to increase linkage to, and engagement in, mental health services for CWI youth. However, at present, there is no empirically supported mental health navigator model to address the unique and complex mental health needs of CWI youth and their families.ObjectiveUsing a randomized controlled trial, this study aims to develop and test a foster care family navigator (FCFN) model to improve mental health service outcomes for CWI adolescents (aged 12-17 years).MethodsThe navigator model leverages an in-person navigator and use of adjunctive digital health technology to engage with, and improve, care coordination, tracking, and monitoring of mental health service needs for CWI youth and families. In total, 80 caregiver-youth dyads will be randomized to receive either the FCFN intervention or standard of care (clinical case management services): 40 (50%) to FCFN and 40 (50%) to control. Qualitative exit interviews will inform the feasibility and acceptability of the services received during the 6-month period. The primary trial outcomes are mental health treatment initiation and engagement. Other pre- and postservice outcomes, such as proportion screened and time to screening, will also be evaluated. We hypothesize that youth receiving the FCFN intervention will have higher rates of mental health treatment initiation and engagement than youth receiving standard of care.ResultsWe propose enrollment of 80 dyads by March 2024, final data collection by September 2024, and the publication of main findings in March 2025. After final data analysis and writing of the results, the resulting manuscripts will be submitted to journals for dissemination.ConclusionsThis study will be the first to produce empirically driven conclusions and recommendations for implementing a family mental health navigation model for CWI youth with long-standing and unaddressed disparities in behavioral health services access. The study findings have potential to have large-scale trial applicability and be feasible and acceptable for eventual system implementation and adoption.Trial registrationClinicalTrials.gov NCT04506437; https://www.clinicaltrials.gov/study/NCT04506437.International registered report identifier (irrid)DERR1-10.2196/49999.

Background: Community health centers (CHCs) pivoted to remote chronic care services during the COVID-19 pandemic. While care continuity is associated with improved care quality and patients’ experiences, telehealth’s impact on these relationships is unclear. Objective: We aimed to examine the association among care continuity, telehealth use, and quality of diabetes or hypertension care in CHCs before and during the COVID-19 pandemic. Methods: We collected electronic health record data from a cohort of 20,792 patients with diabetes or hypertension with ≥2 visits per year from March to December 2019 and 2020 among 166 California CHCs in the OCHIN Accelerating Data Value Across a National Community Health Center Network Collaborative. Logistic regression models estimated the association between care continuity (modified, modified continuity index [MMCI]) and telehealth adoption and blood pressure or hemoglobin A1c (HbA1c) testing. Generalized linear regression models for 2019 and 2020 estimated the association between MMCI and blood pressure or HbA1c, exploring telehealth as a mediator. Results: Patients experienced reduced care continuity (2019: MMCI=0.71, SD 0.28; 2020: MMCI=0.63, SD 0.36; P

ObjectiveTo assess the magnitude of racial-ethnic disparities in pandemic-related social stressors and examine frontline work's moderating relationship on these stressors.Data sourcesEmployed Californians' responses to the Institute for Governmental Studies (IGS) poll from April 16-20, 2020, were analyzed. The Pandemic Stressor Scale (PSS) assessed the extent to which respondents experienced or anticipated problems resulting from the inability to pay for basic necessities, job instability, lacking paid sick leave, unavailability of childcare, and reduced wages or work hours due to COVID-19.Study designMixed-effects generalized linear models estimated (1) racial-ethnic disparities in pandemic stressors among workers during the first COVID-19 surge, adjusting for covariates, and (2) tested the interaction between race-ethnicity and frontline worker status, which includes a subset of essential workers who must perform their job on-site, to assess differential associations of frontline work by race-ethnicity.Data collectionThe IGS poll data from employed workers (n = 4795) were linked to the 2018 Centers for Disease Control and Prevention Social Vulnerability Index at the zip code level (N = 1068).Principal findingsThe average PSS score was 37.34 (SD = 30.49). Whites had the lowest PSS score (29.88, SD = 26.52), and Latinxs had the highest (50.74, SD = 32.61). In adjusted analyses, Black frontline workers reported more pandemic-related stressors than White frontline workers (PSS = 47.73 vs. 36.96, p

Text messaging interventions are increasingly used to help people manage depression and anxiety. However, little is known about the effectiveness and implementation of these interventions among U.S. Latinxs, who often face barriers to using mental health tools. The StayWell at Home (StayWell) intervention, a 60-day text messaging program based on cognitive behavioral therapy (CBT), was developed to help adults cope with depressive and anxiety symptoms during the COVID-19 pandemic. StayWell users (n = 398) received daily mood inquiries and automated skills-based text messages delivering CBT-informed coping strategies from an investigator-generated message bank. We conduct a Hybrid Type 1 mixed-methods study to compare the effectiveness and implementation of StayWell for Latinx and Non-Latinx White (NLW) adults using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Effectiveness was measured using the PHQ-8 depression and GAD-7 anxiety scales, assessed before starting and after completing StayWell. Guided by RE-AIM, we conducted a thematic text analysis of responses to an open-ended question about user experiences to help contextualize quantitative findings. Approximately 65.8% (n = 262) of StayWell users completed pre-and-post surveys. On average, depressive (-1.48, p = 0.001) and anxiety (-1.38, p = 0.001) symptoms decreased from pre-to-post StayWell. Compared to NLW users (n = 192), Latinx users (n = 70) reported an additional -1.45 point (p

Current digital health approaches have not engaged diverse end users or reduced health or health care inequities, despite their promise to deliver more tailored and personalized support to individuals at the right time and the right place. To achieve digital health equity, we must refocus our attention on the current state of digital health uptake and use across the policy, system, community, individual, and intervention levels. We focus here on (a) outlining a multilevel framework underlying digital health equity; (b) summarizingfive types of interventions/programs (with example studies) that hold promise for advancing digital health equity; and (c) recommending future steps for improving policy, practice, and research in this space.

BackgroundCommunity health centers (CHCs) pivoted to using telehealth to deliver chronic care during the coronavirus COVID-19 pandemic. While care continuity can improve care quality and patients' experiences, it is unclear whether telehealth supported this relationship.ObjectiveWe examine the association of care continuity with diabetes and hypertension care quality in CHCs before and during COVID-19 and the mediating effect of telehealth.Research designThis was a cohort study.ParticipantsElectronic health record data from 166 CHCs with n=20,792 patients with diabetes and/or hypertension with ≥2 encounters/year during 2019 and 2020.MethodsMultivariable logistic regression models estimated the association of care continuity (Modified Modified Continuity Index; MMCI) with telehealth use and care processes. Generalized linear regression models estimated the association of MMCI and intermediate outcomes. Formal mediation analyses assessed whether telehealth mediated the association of MMCI with A1c testing during 2020.ResultsMMCI [2019: odds ratio (OR)=1.98, marginal effect=0.69, z=165.50, P

University students have low levels of physical activity and are at risk of mental health disorders. Mobile apps to encourage physical activity can help students, who are frequent smartphone-users, to improve their physical and mental health. Here we report students' qualitative feedback on a physical activity smartphone app with motivational text messaging. We provide recommendations for the design of future apps. 103 students used the app for 6 weeks in the context of a clinical trial (NCT04440553) and answered open-ended questions before the start of the study and at follow-up. A subsample (n = 39) provided additional feedback via text message, and a phone interview (n = 8). Questions focused on the perceived encouragement and support by the app, text messaging content, and recommendations for future applications. We analyzed all transcripts for emerging themes using qualitative coding in Dedoose. The majority of participants were female (69.9%), Asian or Pacific Islander (53.4%), with a mean age of 20.2 years, and 63% had elevated depressive symptoms. 26% felt encouraged or neutral toward the app motivating them to be more physically active. Participants liked messages on physical activity benefits on (mental) health, encouraging them to complete their goal, and feedback on their activity. Participants disliked messages that did not match their motivations for physical activity and their daily context (e.g., time, weekday, stress). Physical activity apps for students should be adapted to their motivations, changing daily context, and mental health issues. Feedback from this sample suggests a key to effectiveness is finding effective ways to personalize digital interventions.

BackgroundMobile health interventions are often standardized and assumed to work the same for all users; however, we may be missing cultural differences in the experiences of interventions that may impact how and if an intervention is effective. ObjectiveThe objective of the study was to assess qualitative feedback from participants to determine if there were differences between Spanish speakers and English speakers. Daily text messages were sent to patients as an adjunct to group Cognitive Behavioral Therapy (CBT) for depression. MethodsMessages inquired about mood and about specific themes (thoughts, activities, social interactions) of a manualized group CBT intervention. There were thirty-nine patients who participated in the text messaging pilot study. The average age of the participants was 53 years (SD 10.4; range of 23-72). ResultsQualitative feedback from Spanish speakers highlighted feelings of social support, whereas English speakers noted increased introspection and self-awareness of their mood state. ConclusionsThese cultural differences should be explored further, as they may impact the effect of supportive mobile health interventions. Trial RegistrationTrial Registration: Clinicaltrials.gov NCT01083628; http://clinicaltrials.gov/ct2/show/study/NCT01083628 (Archived by WebCite at http://www.webcitation.org/6StpbdHuq).

BackgroundInternet interventions have the potential to address many of the health problems that produce the greatest global burden of disease. We present a study illustrating this potential. The Spanish/English San Francisco Stop Smoking Internet site, which yielded quit rates of 20% or more at 12 months in published randomized controlled trials (RCTs), was modified to make it accessible to Spanish- and English-speaking smokers 18 years of age or older anywhere in the world. ObjectiveTo illustrate that Internet interventions designed to conduct RCTs can be adapted to serve as universal health care resources. We also examine quit rates obtained in the current participant preference study (in which users could choose from all elements tested in previous RCTs) to determine whether they differ from the quit rates found in the RCTs. MethodsWe modified the San Francisco Stop Smoking Internet site so that, instead of being randomly assigned to a specific intervention, participants could personalize the site by choosing among nine site elements (eg, stop smoking guide, reminder emails, journal, mood management intervention, or virtual group). Participants completed a baseline assessment, and reported smoking and mood data at 1-, 3-, 6-, and 12-month follow-ups. We assessed the modified website’s reach and outcomes (quit rates), and compared the quit rates of the current participant preference study with those of the previous RCTs. ResultsIn the first year of recruitment, 94,158 individuals from 152 countries and territories visited the site; 13,488 participants left some data; 9173 signed consent; 7763 completed the baseline survey; and 1955, 1362, 1106, and 1096 left 1-, 3-, 6-, and 12-month data, respectively. Observed quit rates were 38.1% (n = 668), 44.9% (n = 546), 43.6% (n = 431), and 45.4% (n = 449), respectively. The current participant preference study yielded higher observed quit rates (odds ratio 1.30) than the previous RCT when controlling for individuals’ demographic and smoking characteristics. ConclusionsAfter strict RCTs are completed, Internet intervention sites can be made into worldwide health intervention resources without reducing their effectiveness. Trial RegistrationClinicaltrials.gov NCT00721786; http://clinicaltrials.gov/ct2/show/NCT00721786 (Archived by WebCite at http://www.webcitation.org/66npiZF4y)

BackgroundSmoking is one of the largest contributors to the global burden of disease. Internet interventions have been shown to reduce smoking rates successfully. However, improved methods of evaluating effectiveness need to be developed for large-scale Internet intervention trials. ObjectiveTo illustrate a method to interpret outcomes of large-scale, fully automated, worldwide Internet intervention trials. MethodsA fully automated, international, Internet-based smoking cessation randomized controlled trial was conducted in Spanish and English, with 16,430 smokers from 165 countries. The randomized controlled trial replicated a published efficacy trial in which, to reduce follow-up attrition, 1000 smokers were followed up by phone if they did not provide online follow-up data. ResultsThe 7-day self-reported abstinence rates ranged from 36.18% (2239/6189) at 1 month to 41.34% (1361/3292) at 12 months based on observed data. Given high rates of attrition in this fully automated trial, when participants unreachable at follow-up were presumed to be smoking, the abstinence rates ranged from 13.63% (2239/16.430) at 1 month to 8.28% (1361/16,430) at 12 months. We address the problem of interpreting results with high follow-up attrition rates and propose a solution based on a smaller study with intensive phone follow-up. ConclusionsInternet-based smoking cessation interventions can help large numbers of smokers quit. Large-scale international outcome studies can be successfully implemented using automated Internet sites. Interpretation of the studies’ results can be aided by extrapolating from results obtained from subsamples that are followed up by phone or similar cohort maintenance methods. Trial RegistrationClinicalTrials.gov NCT00721786; http://clinicaltrials.gov/ct2/show/NCT00721786 (Archived by WebCite at http://www.webcitation.org/63mhoXYPw)

The Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TranS-C) was implemented in a community mental health center (CMHC) setting. The goal of TranS-C is to improve sleep and circadian dysfunction among people with severe mental illness. The present study uses the Theoretical Domains Framework (TDF) to uncover barriers and facilitators to changing behaviors learned in TranS-C. Adults with severe mental illness who completed TranS-C (n = 14) were given a semi-structured interview based on the TDF. Interview transcripts were independently coded using inductive and deductive coding. The most commonly coded TDF domains were Behavior Regulation, Beliefs about Consequences, Knowledge and Beliefs about Capabilities. Action planning was the most discussed facilitator and compromising sleep health in favor of time spent with loved ones was the most discussed barrier. These findings suggest that TranS-C has promising strengths and raise important barriers that can be addressed in TranS-C to improve its fit within CMHCs.

BackgroundLow physical activity is an important risk factor for common physical and mental disorders. Physical activity interventions delivered via smartphones can help users maintain and increase physical activity, but outcomes have been mixed.PurposeHere we assessed the effects of sending daily motivational and feedback text messages in a microrandomized clinical trial on changes in physical activity from one day to the next in a student population.MethodsWe included 93 participants who used a physical activity app, "DIAMANTE" for a period of 6 weeks. Every day, their phone pedometer passively tracked participants' steps. They were microrandomized to receive different types of motivational messages, based on a cognitive-behavioral framework, and feedback on their steps. We used generalized estimation equation models to test the effectiveness of feedback and motivational messages on changes in steps from one day to the next.ResultsSending any versus no text message initially resulted in an increase in daily steps (729 steps, p = .012), but this effect decreased over time. A multivariate analysis evaluating each text message category separately showed that the initial positive effect was driven by the motivational messages though the effect was small and trend-wise significant (717 steps; p = .083), but not the feedback messages (-276 steps, p = .4).ConclusionSending motivational physical activity text messages based on a cognitive-behavioral framework may have a positive effect on increasing steps, but this decreases with time. Further work is needed to examine using personalization and contextualization to improve the efficacy of text-messaging interventions on physical activity outcomes.Clinicaltrials.gov identifierNCT04440553.

IntroductionDigital health, the use of apps, text-messaging, and online interventions, can revolutionize healthcare and make care more equitable. Currently, digital health interventions are often not designed for those who could benefit most and may have unintended consequences. In this paper, we explain how privacy vulnerabilities and power imbalances, including racism and sexism, continue to influence health app design and research. We provide guidelines for researchers to design, report and evaluate digital health studies to maximize social justice in health.MethodsFrom September 2020 to April 2021, we held five discussion and brainstorming sessions with researchers, students, and community partners to develop the guide and the key questions. We additionally conducted an informal literature review, invited experts to review our guide, and identified examples from our own digital health study and other studies.ResultsWe identified five overarching topics with key questions and subquestions to guide researchers in designing or evaluating a digital health research study. The overarching topics are: 1. Equitable distribution; 2. Equitable design; 3. Privacy and data return; 4. Stereotype and bias; 5. Structural racism.ConclusionWe provide a guide with five key topics and questions for social justice digital health research. Encouraging researchers and practitioners to ask these questions will help to spark a transformation in digital health toward more equitable and ethical research. Future work needs to determine if the quality of studies can improve when researchers use this guide.

ObjectiveProviding behavioral health interventions via smartphones allows these interventions to be adapted to the changing behavior, preferences, and needs of individuals. This can be achieved through reinforcement learning (RL), a sub-area of machine learning. However, many challenges could affect the effectiveness of these algorithms in the real world. We provide guidelines for decision-making.Materials and methodsUsing thematic analysis, we describe challenges, considerations, and solutions for algorithm design decisions in a collaboration between health services researchers, clinicians, and data scientists. We use the design process of an RL algorithm for a mobile health study "DIAMANTE" for increasing physical activity in underserved patients with diabetes and depression. Over the 1.5-year project, we kept track of the research process using collaborative cloud Google Documents, Whatsapp messenger, and video teleconferencing. We discussed, categorized, and coded critical challenges. We grouped challenges to create thematic topic process domains.ResultsNine challenges emerged, which we divided into 3 major themes: 1. Choosing the model for decision-making, including appropriate contextual and reward variables; 2. Data handling/collection, such as how to deal with missing or incorrect data in real-time; 3. Weighing the algorithm performance vs effectiveness/implementation in real-world settings.ConclusionThe creation of effective behavioral health interventions does not depend only on final algorithm performance. Many decisions in the real world are necessary to formulate the design of problem parameters to which an algorithm is applied. Researchers must document and evaulate these considerations and decisions before and during the intervention period, to increase transparency, accountability, and reproducibility.Trial registrationclinicaltrials.gov, NCT03490253.

Physical activity (PA) is an effective depression treatment. However, knowledge on how variation in day-to-day PA relates to depression in women is lacking. The purposes of this study were to 1) compare overall objectively measured baseline daily steps and duration of moderate to vigorous PA (MVPA) and 2) examine differences in steps and MVPA on days of the week between women aged 25-65 years, who were physically inactive, with high and low depressive symptoms, enrolled in a run-in period of the mobile phone based physical activity education (mPED) trial. The Center for Epidemiological Studies Depression Scale was used to categorize low/high depressive symptom groups. We used linear mixed-effects models to examine the associations between steps and MVPA and depression-status overall and by day of the week, adjusting for selected demographic variables and their interactions with day of the week. 274 women were included in the final analysis, of which 58 had high depressive symptoms. Overall physical activity levels did not differ. However, day of the week modified the associations of depression with MVPA (p = 0.015) and daily steps (p = 0.08). Women with high depression were characterized by reduced activity at the end of the week (Posthoc: Friday: 791 fewer steps, 95% CI: 73-1509, p = 0.03; 8.8 lower MVPA, 95% CI: 2.16-15.5, p = 0.0098) compared to women with low depression, who showed increased activity. Day of the week might be an important target for personalization of physical activity interventions. Future work should evaluate potential causes of daily activity alterations in depression in women.

BackgroundLow physical activity is an important risk factor for common physical and mental disorders. Physical activity interventions delivered via smartphones can help users maintain and increase physical activity, but outcomes have been mixed.PurposeHere we assessed the effects of sending daily motivational and feedback text messages in a microrandomized clinical trial on changes in physical activity from one day to the next in a student population.MethodsWe included 93 participants who used a physical activity app, "DIAMANTE" for a period of 6 weeks. Every day, their phone pedometer passively tracked participants' steps. They were microrandomized to receive different types of motivational messages, based on a cognitive-behavioral framework, and feedback on their steps. We used generalized estimation equation models to test the effectiveness of feedback and motivational messages on changes in steps from one day to the next.ResultsSending any versus no text message initially resulted in an increase in daily steps (729 steps, p = .012), but this effect decreased over time. A multivariate analysis evaluating each text message category separately showed that the initial positive effect was driven by the motivational messages though the effect was small and trend-wise significant (717 steps; p = .083), but not the feedback messages (-276 steps, p = .4).ConclusionSending motivational physical activity text messages based on a cognitive-behavioral framework may have a positive effect on increasing steps, but this decreases with time. Further work is needed to examine using personalization and contextualization to improve the efficacy of text-messaging interventions on physical activity outcomes.Clinicaltrials.gov identifierNCT04440553.

Introduction: Cognitive behavioral therapy (CBT) is an established treatment for depression, but its success is often impeded by low attendance. Supportive text messages assessing participants' mood in between sessions might increase attendance to in-clinic CBT, although it is not fully understood who benefits most from these interventions and how. This study examined (1) user groups showing different profiles of study engagement and (2) associations between increased response rates to mood texts and psychotherapy attendance. Methods: We included 73 participants who attended Group CBT (GCBT) in a primary care clinic and participated in a supportive automated text-messaging intervention. Using unsupervised machine learning, we identified and characterized subgroups with similar combinations of total texting responsiveness and total GCBT attendance. We used mixed-effects models to explore the association between increased previous week response rate and subsequent week in-clinic GCBT attendance and, conversely, response rate following attendance. Results: Participants could be divided into four clusters of overall study engagement, showing distinct profiles in age and prior texting knowledge. The response rate to texts in the week before GCBT was not associated with GCBT attendance, although the relationship was moderated by age; there was a positive relationship for younger, but not older, participants. Attending GCBT was, however, associated with higher response rate the week after an attended session. Conclusion: User groups of study engagement differ in texting knowledge and age. Younger participants might benefit more from supportive texting interventions when their purpose is to increase psychotherapy attendance. Our results have implications for tailoring digital interventions to user groups and for understanding therapeutic effects of these interventions.

Introduction: Digital technologies, including text messaging and mobile phone apps, can be leveraged to increase people's physical activity and manage health. Chatbots, powered by artificial intelligence, can automatically interact with individuals through natural conversation. They may be more engaging than one-way messaging interventions. To our knowledge, physical activity chatbots have not been developed with low-income participants, nor in Spanish-the second most dominant language in the U.S. We recommend best practices for physical activity chatbots in English and Spanish for low-income women. Methods: We designed a prototype physical activity text-message based conversational agent based on various psychotherapeutic techniques. We recruited participants through SNAP-Ed (Supplemental Nutrition Assistance Program Education) in California (Alameda County) and Tennessee (Shelby County). We conducted qualitative interviews with participants during testing of our prototype chatbot, held a Wizard of Oz study, and facilitated a co-design workshop in Spanish with a subset of our participants. Results: We included 10 Spanish- and 8 English-speaking women between 27 and 41 years old. The majority was Hispanic/Latina (n = 14), 2 were White and 2 were Black/African American. More than half were monolingual Spanish speakers, and the majority was born outside the US (>50% in Mexico). Most participants were unfamiliar with chatbots and were initially skeptical. After testing our prototype, most users felt positively about health chatbots. They desired a personalized chatbot that addresses their concerns about privacy, and stressed the need for a comprehensive system to also aid with nutrition, health information, stress, and involve family members. Differences between English and monolingual Spanish speakers were found mostly in exercise app use, digital literacy, and the wish for family inclusion. Conclusion: Low-income Spanish- and English-speaking women are interested in using chatbots to improve their physical activity and other health related aspects. Researchers developing health chatbots for this population should focus on issues of digital literacy, app familiarity, linguistic and cultural issues, privacy concerns, and personalization. Designing and testing this intervention for and with this group using co-creation techniques and involving community partners will increase the probability that it will ultimately be effective.

Abstract BACKGROUND Patients with lower grade (2 and 3) gliomas (LrGG) are living longer, but often with cognitive impairments from their tumor and treatments. However, cognitive assessments and access to cognitive rehabilitation are not a standard part of care. We present preliminary results of a pilot study investigating feasibility and efficacy of three cognitive rehabilitation strategies for stable LrGG patients – in-person manualized cognitive rehabilitation; iPad based cognitive rehabilitation program of retraining and compensation strategies (ReMind); or daily instructional text messages (Healthy SMS). METHODS Eligible patients were adults with clinically and radiologically stable LrGG, > 6 months from last treatment, and ≥1 standard deviation (SD) below normal on ≥ 2 domains of neuropsychological assessments. Patients were first offered in-person cognitive rehabilitation or randomized to ReMind or Healthy SMS if unable to attend in-person. Interventions lasted 3 months. Neuropsychological and HRQOL assessments, using PROMIS NeuroQOL, were conducted at baseline, 3, and 6 months post-intervention. Feasibility was defined as attending ≥80% of in-person sessions; completing ≥80% of ReMind tasks; or not opting out of Healthy SMS texts. RESULTS To date 23/60 patients have enrolled: 11 in-person and 12 randomized to ReMind (5) or Healthy SMS (7). Demographic and clinical characteristics were similar between cohorts. Median age at testing was 46 years, with 65% female, and 78% having received prior radiation (median 4.1 years, range 3.2 – 11.5). At baseline, processing speed was the most common domain of impairment with 43% ≥ 1.5 SD below normal and 36% patients reporting subjective cognitive impairment on HROQL assessment. Feasibility was 71% for in-person rehabilitation; 50% for ReMind; and 100% for Health SMS. CONCLUSION These preliminary results demonstrate that stable LrGG patients with subjective and objective cognitive impairments can reasonably engage in cognitive rehabilitation interventions. Updated data including post-intervention neuropsychological and HROQL related changes will be presented.

BACKGROUND The COVID-19 pandemic has propelled patient-facing research to shift to digital and telehealth strategies. If these strategies are not adapted for minority patients of lower socioeconomic status, health inequality will further increase. Patient-centered models of care can successfully improve access and experience for minority patients. OBJECTIVE This study aims to present the development process and preliminary acceptability of altering in-person onboarding procedures into internet-based, remote procedures for a mobile health (mHealth) intervention in a population with limited digital literacy. METHODS We actively recruited safety-net patients (English- and Spanish-speaking adults with diabetes and depression who were receiving care at a public health care delivery system in San Francisco, United States) into a randomized controlled trial of text messaging support for physical activity. Because of the COVID-19 pandemic, we modified the in-person recruitment and onboarding procedures to internet-based, remote processes with human support. We conducted a preliminary evaluation of how the composition of the recruited cohort might have changed from the pre–COVID-19 period to the COVID-19 enrollment period. First, we analyzed the digital profiles of patients (n=32) who had participated in previous in-person onboarding sessions prior to the COVID-19 pandemic. Next, we documented all changes made to our onboarding processes to account for remote recruitment, especially those needed to support patients who were not very familiar with downloading apps onto their mobile phones on their own. Finally, we used the new study procedures to recruit patients (n=11) during the COVID-19 social distancing period. These patients were also asked about their experience enrolling into a fully digitized mHealth intervention. RESULTS Recruitment across both pre–COVID-19 and COVID-19 periods (N=43) demonstrated relatively high rates of smartphone ownership but lower self-reported digital literacy, with 32.6% (14/43) of all patients reporting they needed help with using their smartphone and installing apps. Significant changes were made to the onboarding procedures, including facilitating app download via Zoom video call and/or a standard phone call and implementing brief, one-on-one staff-patient interactions to provide technical assistance personalized to each patient’s digital literacy skills. Comparing recruitment during pre–COVID-19 and COVID-19 periods, the proportion of patients with digital literacy barriers reduced from 34.4% (11/32) in the pre–COVID-19 cohort to 27.3% (3/11) in the COVID-19 cohort. Differences in digital literacy scores between both cohorts were not significant (P=.49). CONCLUSIONS Patients of lower socioeconomic status have high interest in using digital platforms to manage their health, but they may require additional upfront human support to gain access. One-on-one staff-patient partnerships allowed us to provide unique technical assistance personalized to each patient’s digital literacy skills, with simple strategies to troubleshoot patient barriers upfront. These additional remote onboarding strategies can mitigate but not eliminate digital barriers for patients without extensive technology experience. CLINICALTRIAL Clinicaltrials.gov NCT0349025, https://clinicaltrials.gov/ct2/show/NCT03490253

Sexual minority populations experience disproportionately high rates of depression and anxiety relative to their heterosexual counterparts. Unfortunately, both sexual minority clients and their therapists experience difficulties in therapy. After conducting a review of the extant literature focused on approaches to treating depression and anxiety among sexual minority individuals in psychotherapy, this manuscript aims to: (1) Propose a taxonomy of existing practice models for treating sexual minority clients for depression and anxiety (protocol-based approaches, principles-based approaches, and relationship-based approaches); (2) Describe the current research findings of the evaluations of these practice models; (3) Offer recommendations for research and practice.

IntroductionDepression and diabetes are highly disabling diseases with a high prevalence and high rate of comorbidity, particularly in low-income ethnic minority patients. Though comorbidity increases the risk of adverse outcomes and mortality, most clinical interventions target these diseases separately. Increasing physical activity might be effective to simultaneously lower depressive symptoms and improve glycaemic control. Self-management apps are a cost-effective, scalable and easy access treatment to increase physical activity. However, cutting-edge technological applications often do not reach vulnerable populations and are not tailored to an individual's behaviour and characteristics. Tailoring of interventions using machine learning methods likely increases the effectiveness of the intervention.Methods and analysisIn a three-arm randomised controlled trial, we will examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. The adaptive intervention group receives messages chosen from different messaging banks by a reinforcement learning algorithm. The uniform random intervention group receives the same messages, but chosen from the messaging banks with equal probabilities. The control group receives a weekly mood message. We aim to recruit 276 adults from primary care clinics aged 18-75 years who have been diagnosed with current diabetes and show elevated depressive symptoms (Patient Health Questionnaire depression scale-8 (PHQ-8) >5). We will compare passively collected daily step counts, self-report PHQ-8 and most recent haemoglobin A1c from medical records at baseline and at intervention completion at 6-month follow-up.Ethics and disseminationThe Institutional Review Board at the University of California San Francisco approved this study (IRB: 17-22608). We plan to submit manuscripts describing our user-designed methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at (inter)-national scientific meetings.Trial registration numberNCT03490253; pre-results.

BackgroundElectronic health records (EHRs) have potential to improve quality, health outcomes, and efficiency, but little is known about the mechanisms through which these improvements occur.PurposeOne potential mechanism could be that EHRs improve care team communication and coordination, leading to better outcomes. To test this hypothesis, we examine whether ease of EHR use is associated with better relational coordination (RC), a measure of team communication and coordination, among primary care team members.MethodologySurveys of adult primary care team members (n = 304) of 16 practices of two accountable care organizations in Chicago and Los Angeles were analyzed. The survey included a validated measure of RC and a measure of ease of EHR use from a national survey. Linear regression models estimated the association of ease of EHR use and RC, controlling for care site and patient demographics and accounting for cluster-robust standard errors. An interaction term tested a differential association of ease of EHR use and RC for primary care providers (PCPs) versus non-PCPs.ResultsEase of EHR use (mean = 3.5, SD = 0.6, range: 0-4) and RC were high (mean = 4.0, SD = 0.7, range: 0-5) but differed by occupation. In regression analyses, a 1-point increase in ease of EHR use was associated with a 0.36 point higher RC score (p = .001). The association of ease of EHR and RC use was stronger for non-PCPs than PCPs.ConclusionEase of EHR use is associated with better RC among primary care team members, and the benefits accrue more to non-PCPs than to PCPs.Practice implicationsEnsuring that clinicians and staff experience EHRs as easy to use for accessing and integrating data and for communication may produce gains in efficiency and outcomes through high RC. Future studies should examine whether interventions to improve EHR usability can lead to improved RC and patient outcomes.

ABSTRACTIntroductionDepression and diabetes are highly disabling diseases with a high prevalence and high rate of comorbidity, particularly in low-income ethnic minority patients. Though comorbidity increases the risk of adverse outcomes and mortality, most clinical interventions target these diseases separately. Increasing physical activity might be effective to simultaneously lower depressive symptoms and improve glycemic control. Self-management apps are a cost-effective, scalable and easy access treatment to increase physical activity. However, cutting-edge technological applications often do not reach vulnerable populations and are not tailored to an individual’s behavior and characteristics. Tailoring of interventions using machine learning methods likely increases the effectiveness of the intervention.Methods and analysisIn a three-arm randomized controlled trial we will examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. The adaptive intervention group receives messages chosen from different messaging banks by a reinforcement learning algorithm. The uniform random intervention group receives the same messages, but chosen from the messaging banks with equal probabilities. The control group receives a weekly mood message. We aim to recruit 276 adults from primary care clinics aged 18 to 75 years who have been diagnosed with current diabetes and show elevated depressive symptoms (PHQ-8 >5). We will compare passively collected daily step counts, self-report PHQ-8 and most recent HbA1c from medical records at baseline and at intervention completion at 6-month follow-up.Ethics and disseminationThe Institutional Review Board at the University of California San Francisco approved this study (IRB: 17-22608). We plan to submit manuscripts describing our User Designed Methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at (inter)-national scientific meetings.Registrationclinicaltrials.gov: NCT03490253; pre-resultsArticle SummaryStrengths and LimitationsNovel approach of targeting diabetes and depressive symptoms using a smartphone applicationAbility to compare adaptive messaging for increasing physical activity to messages delivered with equal probabilitiesTesting of a smartphone application integrated within primary care settings in a low-income vulnerable patient populationLongitudinal design with 6-month follow-up enables assessing intervention effects over timeChallenges of this trial include supporting users in key behavior change in an automated manner with minimal in-person support

BACKGROUND Text messaging interventions can be an effective and efficient way to improve health behavioral changes. However, most texting interventions are neither tested nor designed with diverse end users, which could reduce their impact, and there is limited evidence regarding the optimal design methodology of health text messages tailored to low-income, low–health literacy populations and non-English speakers. OBJECTIVE This study aims to combine participant feedback, crowdsourced data, and researcher expertise to develop motivational text messages in English and Spanish that will be used in a smartphone app–based texting intervention that seeks to encourage physical activity in low-income minority patients with diabetes diagnoses and depression symptoms. METHODS The design process consisted of 5 phases and was iterative in nature, given that the findings from each step informed the subsequent steps. First, we designed messages to increase physical activity based on the behavior change theory and knowledge from the available evidence. Second, using user-centered design methods, we refined these messages after a card sorting task and semistructured interviews (N=10) and evaluated their likeability during a usability testing phase of the app prototype (N=8). Third, the messages were tested by English- and Spanish-speaking participants on the Amazon Mechanical Turk (MTurk) crowdsourcing platform (N=134). Participants on MTurk were asked to categorize the messages into overarching theoretical categories based on the capability, opportunity, motivation, and behavior framework. Finally, each coauthor rated the messages for their overall quality from 1 to 5. All messages were written at a sixth-grade or lower reading level and culturally adapted and translated into neutral Spanish by bilingual research staff. RESULTS A total of 200 messages were iteratively refined according to the feedback from target users gathered through user-centered design methods, crowdsourced results of a categorization test, and an expert review. User feedback was leveraged to discard unappealing messages and edit the thematic aspects of messages that did not resonate well with the target users. Overall, 54 messages were sorted into the correct theoretical categories at least 50% of the time in the MTurk categorization tasks and were rated 3.5 or higher by the research team members. These were included in the final text message bank, resulting in 18 messages per motivational category. CONCLUSIONS By using an iterative process of expert opinion, feedback from participants that were reflective of our target study population, crowdsourcing, and feedback from the research team, we were able to acquire valuable inputs for the design of motivational text messages developed in English and Spanish with a low literacy level to increase physical activity. We describe the design considerations and lessons learned for the text messaging development process and provide a novel, integrative framework for future developers of health text messaging interventions.

This study examined the acceptability of the BabyText program, a Spanish and English textmessaging program adapted from a prevention of postpartum depression group intervention. Ten ethnically and racially diverse pregnant and postpartum women (mean age = 31.3, standard deviation = 5.25) recruited from a metropolitan, urban area of the United States received the BabyText program over a 69-day period (between October 2015 and April 2016). Each tip was assessed for the helpfulness of the content, and all women were invited to provide qualitative feedback about the program. Eighteen of the tips received a positive endorsement of helpfulness from 75 to 100 percent of the women, 12 tips received a positive endorsement of helpfulness from 50 percent of the women, and one tip was rated negatively by those who responded. Qualitative feedback described the need to personalize the tips to reflect the characteristics of women such as planned/unplanned pregnancy status, available economic resources, and current psychological distress. Women in this study favored tips that described stress management skills and emphasized caring for the self (vs only the baby). Data from this study are preliminary but add to the growing sentiment that digital tools should continue to be developed and tested, and personalization of intervention content is important to users.

Current technologies designed for mental health support often have low adoption rates and may not fit people's routines. However, recent literature demonstrates that individuals managing mental illness often incorporate a variety of technologies into their self-management routines, including texting, music, wearables, online communities, games, and social media. Therefore, adopting a perspective focused on understanding the technology ecosystem of mental health management may be a better approach than focusing on singular platforms and applications. In this CHI workshop, we will examine a constellation of digital and non-digital mental health support resources. We will discuss the needs and practices of individuals managing mental illness, how these needs relate to future ecosystems of technologies and services, and the potentials and repercussions of current technologies. By convening a group of interdisciplinary researchers and practitioners, we will collectively address these topics to create resources attentive to individuals' lived experiences with mental illness, goals with respect to management and recovery, and interactions with existing forms of resources, care, and technology.

Although group-level evidence supports the use of behavioral interventions to enhance cognitive and emotional well-being, different interventions may be more acceptable or effective for different people. N-of-1 trials are single-patient crossover trials designed to estimate treatment effectiveness in a single patient. We designed a mobile health (mHealth) supported N-of-1 trial platform permitting US adult volunteers to conduct their own 30-day self-experiments testing a behavioral intervention of their choice (deep breathing/meditation, gratitude journaling, physical activity, or helpful acts) on daily measurements of stress, focus, and happiness. We assessed uptake of the study, perceived usability of the N-of-1 trial system, and influence of results (both reported and perceived) on enthusiasm for the chosen intervention (defined as perceived helpfulness of the chosen intervention and intent to continue performing the intervention in the future). Following a social media and public radio campaign, 447 adults enrolled in the study and 259 completed the post-study survey. Most were highly educated. Perceived system usability was high (mean scale score 4.35/5.0, SD 0.57). Enthusiasm for the chosen intervention was greater among those with higher pre-study expectations that the activity would be beneficial for them (p < 0.001), those who obtained more positive N-of-1 results (as directly reported to participants) (p < 0.001), and those who interpreted their N-of-1 study results more positively (p < 0.001). However, reported results did not significantly influence enthusiasm after controlling for participants' interpretations. The interaction between pre-study expectation of benefit and N-of-1 results interpretation was significant (p < 0.001), such that those with the lowest starting pre-study expectations reported greater intervention enthusiasm when provided with results they interpreted as positive. We conclude that N-of-1 behavioral trials can be appealing to a broad albeit highly educated and mostly female audience, that usability was acceptable, and that N-of-1 behavioral trials may have the greatest utility among those most skeptical of the intervention to begin with.