Mobile addiction treatment and harm reduction services as tools to address health inequities: a community case study of the Brockton Neighborhood Health Center mobile unit.

Opioid overdose deaths continue to increase in the US. Recent data show disproportionately high and increasing overdose death rates among Black, Latine, and Indigenous individuals, and people experiencing homelessness. Medications for opioid use disorder (MOUD) can be lifesaving; however, only a fraction of eligible individuals receive them. Our goal was to describe our experience promoting equitable MOUD access using a mobile delivery model. We implemented a mobile MOUD unit aiming to improve equitable access in Brockton, a racially diverse, medium-sized city in Massachusetts. Brockton has a relatively high opioid overdose death rate with increasingly disproportionate death rates among Black residents. Brockton Neighborhood Health Center (BNHC), a community health center, provides brick-and-mortar MOUD access. Through the Communities That HEAL intervention as part of the HEALing Communities Study (HCS), Brockton convened a community coalition with the aim of selecting evidence-based practices to decrease overdose deaths. BNHC leadership and coalition members recognized that traditional brick-and-mortar treatment locations were inaccessible to marginalized populations, and that a mobile program could increase MOUD access. In September 2021, with support from the HCS coalition, BNHC launched its mobile initiative - Community Care-in-Reach® - to bring low-threshold buprenorphine, harm reduction, and preventive care to high-risk populations. During implementation, the team encountered several challenges including: securing local buy-in; navigating a complex licensure process; maintaining operations throughout the COVID-19 pandemic; and finally, planning for sustainability. In two years of operation, the mobile team cared for 297 unique patients during 1,286 total visits. More than one-third (36%) of patients received buprenorphine prescriptions. In contrast to BNHC's brick-and-mortar clinics, patients with OUD seen on the mobile unit were more representative of historically marginalized racial and ethnic groups, and people experiencing homelessness, evidencing improved, equitable addiction care access for these historically disadvantaged populations. Offering varied services on the mobile unit, such as wound care, syringe and safer smoking supplies, naloxone, and other basic medical care, was a key engagement strategy. This on-demand mobile model helped redress systemic disadvantages in access to addiction treatment and harm reduction services, reaching diverse individuals to offer lifesaving MOUD at a time of inequitable increases in overdose deaths.

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (ß=-93.61, P<.001), increased sleep variability (ß=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: ß=0.55, P=.001; sleep offset: ß=1.12, P<.001; M10 onset: ß=0.73, P=.003; HR acrophase: ß=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (ß of PHQ-8 × spring = -31.51, P=.002) and summer (ß of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (ß of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

A data-driven approach to implementing the HPTN 094 complex intervention INTEGRA in local communities.

BACKGROUND: HIV burden in the US among people who inject drugs (PWID) is driven by overlapping syndemic factors such as co-occurring health needs and environmental factors that synergize to produce worse health outcomes among PWID. This includes stigma, poverty, and limited healthcare access (e.g. medication to treat/prevent HIV and for opioid use disorder [MOUD]). Health services to address these complex needs, when they exist, are rarely located in proximity to each other or to the PWID who need them. Given the shifting drug use landscapes and geographic heterogeneity in the US, we evaluate a data-driven approach to guide the delivery of such services to PWID in local communities. METHODS: We used a hybrid, type I, embedded, mixed method, data-driven approach to identify and characterize viable implementation neighborhoods for the HPTN 094 complex intervention, delivering integrated MOUD and HIV treatment/prevention through a mobile unit to PWID across five US cities. Applying the PRISM framework, we triangulated geographic and observational pre-implementation phase data (epidemiological overdose and HIV surveillance data) with two years of implementation phase data (weekly ecological assessments, study protocol meetings) to characterize environmental factors that affected the viability of implementation neighborhoods over time and across diverse settings. RESULTS: Neighborhood-level drug use and geographic diversity alongside shifting socio-political factors (policing, surveillance, gentrification) differentially affected the utility of epidemiological data in identifying viable implementation neighborhoods across sites. In sites where PWID are more geographically dispersed, proximity to structural factors such as public transportation and spaces where PWID reside played a role in determining suitable implementation sites. The utility of leveraging additional data from local overdose and housing response systems to identify viable implementation neighborhoods was mixed. CONCLUSIONS: Our findings suggest that data-driven approaches provide a contextually relevant pragmatic strategy to guide the real-time implementation of integrated care models to better meet the needs of PWID and help inform the scale-up of such complex interventions. This work highlights the utility of implementation science methods that attend to the impact of local community environmental factors on the implementation of complex interventions to PWID across diverse drug use, sociopolitical, and geographic landscapes in the US. TRIAL REGISTRATION: ClincalTrials.gov, Registration Number: NCT04804072 . Registered 18 February 2021.

Inequalities in the Ability for People With Type 2 Diabetes and Prediabetes to Adapt to the Reduction in In-Person Health Support and Increased Use of Digital Support During the COVID-19 Pandemic and Beyond: Qualitative Study.

BACKGROUND: The COVID-19 pandemic created unprecedented challenges for people with type 2 diabetes (T2D) and prediabetes to access in-person health care support. Primary care teams accelerated plans to implement digital health technologies (DHTs), such as remote consultations and digital self-management. There is limited evidence about whether there were inequalities in how people with T2D and prediabetes adjusted to these changes. OBJECTIVE: This study aimed to explore how people with T2D and prediabetes adapted to the reduction in in-person health support and the increased provision of support through DHTs during the COVID-19 pandemic and beyond. METHODS: A purposive sample of people with T2D and prediabetes was recruited by text message from primary care practices that served low-income areas. Semistructured interviews were conducted by phone or video call, and data were analyzed thematically using a hybrid inductive and deductive approach. RESULTS: A diverse sample of 30 participants was interviewed. There was a feeling that primary care had become harder to access. Participants responded to the challenge of accessing support by rationing or delaying seeking support or by proactively requesting appointments. Barriers to accessing health care support were associated with issues with using the total triage system, a passive interaction style with health care services, or being diagnosed with prediabetes at the beginning of the pandemic. Some participants were able to adapt to the increased delivery of support through DHTs. Others had lower capacity to use DHTs, which was caused by lower digital skills, fewer financial resources, and a lack of support to use the tools. CONCLUSIONS: Inequalities in motivation, opportunity, and capacity to engage in health services and DHTs lead to unequal possibilities for people with T2D and prediabetes to self-care and receive care during the COVID-19 pandemic. These issues can be addressed by proactive arrangement of regular checkups by primary care services and improving capacity for people with lower digital skills to engage with DHTs.

The Efficacy of the Smartphone App for the Self-Management of Low Back Pain: A Systematic Review and Assessment of Their Quality through the Mobile Application Rating Scale (MARS) in Italy.

Smartphone apps for self-management are valuable tools to help manage low back pain (LBP) patients. The purposes of this systematic review were to (a) summarize the available studies on the efficacy of smartphone apps for self-management of LBP and (b) identify free applications available in Italy that offer strategies for LBP self-management and provide a qualitative assessment using the Mobile Application Rating Scale (MARS). According to the Prisma Checklist, six bibliographic databases were searched with the keywords 'low back pain', 'mobile application', 'smartphone', and 'telemedicine'. In total, 852 records were screened, and 16 were included in the systematic review. Of the six RCTs included, four reported a statistically significant decrease in pain in favor of the app group, and two RCTs did not. Only in a non-RCT was there an increase in the disability score. In the application research conducted on mobile stores, we identified and rated 25 applications through MARS. The overall scores ranged from 1.93 to 3.92 for the IOS app and 1.73 to 4.25 for the Play Store app. The findings suggest that few apps meet satisfying quality, content, and functionality criteria for LBP self-management.

Feasibility and Acceptability of a Mobile App-Based TEAM-CBT (Testing Empathy Assessment Methods-Cognitive Behavioral Therapy) Intervention (Feeling Good) for Depression: Secondary Data Analysis.

BACKGROUND: The Feeling Good App is an automated stand-alone digital mobile mental health tool currently undergoing beta testing with the goal of providing evidence-informed self-help lessons and exercises to help individuals reduce depressive symptoms without guidance from a mental health provider. Users work through intensive basic training (IBT) and ongoing training models that provide education regarding cognitive behavioral therapy principles from a smartphone. OBJECTIVE: The key objective of this study was to perform a nonsponsored third-party academic assessment of an industry-generated data set; this data set focused on the safety, feasibility, and accessibility of a commercial automated digital mobile mental health app that was developed to reduce feelings associated with depression. METHODS: The Feeling Good App development team created a waitlist cohort crossover design and measured symptoms of depression and anxiety using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and an app-specific measure of negative feelings called the 7 Dimension Emotion Slider (7-DES). The waitlist cohort crossover design divided the participants into 2 groups, where 48.6% (141/290) of the participants were given immediate access to the apps, while 51.4% (149/290) were placed on a 2-week waitlist before being given access to the app. Data collected by the Feeling Good App development team were deidentified and provided to the authors of this paper for analysis through a nonsponsored university data use agreement. All quantitative data were analyzed using SPSS Statistics (version 28.0; IBM Corp). Descriptive statistics were calculated for demographic variables. Feasibility and acceptability were descriptively assessed. All participants included in the quantitative data were given access to the Feeling Good App; this study did not include a control group. RESULTS: In terms of safety, there was no statistically significant change in suicidality from preintervention to postintervention time points (t288=0.0; P>.99), and there was a statistically significant decrease in hopelessness from preintervention to postintervention time points (F289=30.16; P<.01). In terms of acceptability, 72.2% (166/230) of the users who started the initial 2-day IBT went on to complete it, while 34.8% (80/230) of the users who started IBT completed the entirety of the apps' 4-week protocol (150/230, 65.22% dropout rate over 4 weeks). CONCLUSIONS: This study is the first reported proof-of-concept evaluation of the Feeling Good App in terms of safety, feasibility, and statistical trends within the data set. It demonstrates a feasible and novel approach to industry and academic collaboration in the process of developing a digital mental health technology translated from an existing evidence-informed treatment. The results support the prototype app as safe for a select nonclinical population. The app had acceptable levels of engagement and dropouts throughout the intervention. Those who stay engaged showed reductions in symptom severity of depression warranting further investigation of the app's efficacy.

Assessment of Heart Failure Post-discharge Management Strategies, Needs and Acceptance of Mobile Application-based Remote Patient Management in South India.

The demand for digital platforms in managing heart failure (HF) is expected to increase with promising effects on readmission and health expenditure. The study aims to explore current post-discharge management strategies and identify the need and acceptance of digital platforms, to ensure the development of a user-friendly mobile application for HF patients. Using a cross-sectional analytical research design, 90 consecutive patients diagnosed with HF who were discharged from a Tertiary Care Center were enrolled. Tele-interview was conducted using a self-developed and validated tool. The mean age of participants was 55.54 ± 10.33 years. The participants' adherence to HF management strategies was low in terms of physical exercise and weight monitoring. More than one-third were willing to self-record their measurements and use a mobile application. The common mobile application features requested were medication information/reminder (88.6%), health education (84.3%), chat with nurses (84.3%), physical activity (81.4%), symptoms (78.6%), diet (78.6%) and weight management (72.9%). The findings from this initial phase of mobile development are expected to help leverage better development of digital interventions for HF patients.

Accuracy of the Apple Watch Series 4 and Fitbit Versa for Assessing Energy Expenditure and Heart Rate of Wheelchair Users During Treadmill Wheelchair Propulsion: Cross-sectional Study.

BACKGROUND: The Apple Watch (AW) Series 1 provides energy expenditure (EE) for wheelchair users but was found to be inaccurate with an error of approximately 30%, and the corresponding error for heart rate (HR) provided by the Fitbit Charge 2 was approximately 10% to 20%. Improved accuracy of estimated EE and HR is expected with newer editions of these smart watches (SWs). OBJECTIVE: This study aims to assess the accuracy of the AW Series 4 (wheelchair-specific setting) and the Fitbit Versa (treadmill running mode) for estimating EE and HR during wheelchair propulsion at different intensities. METHODS: Data from 20 manual wheelchair users (male: n=11, female: n=9; body mass: mean 75, SD 19 kg) and 20 people without a disability (male: n=11, female: n=9; body mass: mean 75, SD 11 kg) were included. Three 4-minute wheelchair propulsion stages at increasing speed were performed on 3 separate test days (0.5%, 2.5%, or 5% incline), while EE and HR were collected by criterion devices and the AW or Fitbit. The mean absolute percentage error (MAPE) was used to indicate the absolute agreement between the criterion device and SWs for EE and HR. Additionally, linear mixed model analyses assessed the effect of exercise intensity, sex, and group on the SW error. Interclass correlation coefficients were used to assess relative agreement between criterion devices and SWs. RESULTS: The AW underestimated EE with MAPEs of 29.2% (SD 22%) in wheelchair users and 30% (SD 12%) in people without a disability. The Fitbit overestimated EE with MAPEs of 73.9% (SD 7%) in wheelchair users and 44.7% (SD 38%) in people without a disability. Both SWs underestimated HR. The device error for EE and HR increased with intensity for both SWs (all comparisons: P<.001), and the only significant difference between groups was found for HR in the AW (-5.27 beats/min for wheelchair users; P=.02). There was a significant effect of sex on the estimation error in EE, with worse accuracy for the AW (-0.69 kcal/min; P<.001) and better accuracy for the Fitbit (-2.08 kcal/min; P<.001) in female participants. For HR, sex differences were found only for the AW, with a smaller error in female participants (5.23 beats/min; P=.02). Interclass correlation coefficients showed poor to moderate relative agreement for both SWs apart from 2 stage-incline combinations (AW: 0.12-0.57 for EE and 0.11-0.86 for HR; Fitbit: 0.06-0.85 for EE and 0.03-0.29 for HR). CONCLUSIONS: Neither the AW nor Fitbit were sufficiently accurate for estimating EE or HR during wheelchair propulsion. The AW underestimated EE and the Fitbit overestimated EE, and both SWs underestimated HR. Caution is hence required when using SWs as a tool for training intensity regulation and energy balance or imbalance in wheelchair users.

Response Rate Patterns in Adolescents With Concussion Using Mobile Health and Remote Patient Monitoring: Observational Study.

Background: A concussion is a common adolescent injury that can result in a constellation of symptoms, negatively affecting academic performance, neurobiological development, and quality of life. Mobile health (mHealth) technologies, such as apps for patients to report symptoms or wearables to measure physiological metrics like heart rate, have been shown to be promising in health maintenance. However, there is limited evidence about mHealth engagement in adolescents with a concussion during their recovery course. Objective: This study aims to determine the response rate and response rate patterns in concussed adolescents reporting their daily symptoms through mHealth technology. It will also examine the effect of time-, demographic-, and injury-related characteristics on response rate patterns. Methods: Participants aged between 11-18 years (median days since injury at enrollment: 11 days) were recruited from the concussion program of a tertiary care academic medical center and a suburban school's athletic teams. They were asked to report their daily symptoms using a mobile app. Participants were prompted to complete the Post-Concussion Symptom Inventory (PCSI) 3 times (ie, morning, afternoon, and evening) per day for 4 weeks following enrollment. The primary outcome was the response rate pattern over time (by day since initial app use and the day since injury). Time-, demographic-, and injury-related differences in reporting behaviors were compared using Mann Whitney U tests. Results: A total of 56 participants were enrolled (mean age 15.3, SD 1.9 years; n=32, 57% female). The median response rate across all days of app use in the evening was 37.0% (IQR 27.2%-46.4%), which was significantly higher than the morning (21.2%, IQR 15.6%-30.5%) or afternoon (26.4%, IQR 21.1%-31.5%; P<.001). The median daily response was significantly different by sex (female: 53.8%, IQR 46.2%-64.2% vs male: 42.0%, IQR 28.6%-51.1%; P=.003), days since injury to app use (participants starting to use the app >7 days since injury: 54.1%, IQR 47.4%-62.2% vs starting to use the app ≤7 days since injury: 38.0%, IQR 26.0%-53.3%; P=.002), and concussion history (participants with a history of at least one prior concussion: 57.4%, IQR 44.5%-70.5% vs participants without concussion history: 42.3%, IQR 36.8%-53.5%; P=.03). There were no significant differences by age. Differences by injury mechanism (sports- and recreation-related injury: 39.6%, IQR 36.1%-50.4% vs non-sports- or recreation-related injury: 30.6%, IQR 20.0%-42.9%; P=.04) and initial symptom burden (PCSI scores greater than the median score of 47: 40.9%, IQR 35.2%-53.8% vs PCSI scores less than or equal to the median score: 31.9%, IQR 24.6%-40.6%; P=.04) were evident in the evening response rates; however, daily rates were not statistically different. Conclusions: Evening may be the optimal time to prompt for daily concussion symptom assessment among concussed adolescents compared with morning or afternoon. Multiple demographic- and injury-related characteristics were associated with higher daily response rates, including for female participants, those with more than 1 week from injury to beginning mHealth monitoring, and those with a history of at least one previous concussion. Future studies may consider incentive strategies or adaptive digital concussion assessments to increase response rates in populations with low engagement.

Characterizing Longitudinal Patterns in Cognition, Mood, And Activity in Depression With 6-Week High-Frequency Wearable Assessment: Observational Study.

BACKGROUND: Cognitive symptoms are an underrecognized aspect of depression that are often untreated. High-frequency cognitive assessment holds promise for improving disease and treatment monitoring. Although we have previously found it feasible to remotely assess cognition and mood in this capacity, further work is needed to ascertain the optimal methodology to implement and synthesize these techniques. OBJECTIVE: The objective of this study was to examine (1) longitudinal changes in mood, cognition, activity levels, and heart rate over 6 weeks; (2) diurnal and weekday-related changes; and (3) co-occurrence of fluctuations between mood, cognitive function, and activity. METHODS: A total of 30 adults with current mild-moderate depression stabilized on antidepressant monotherapy responded to testing delivered through an Apple Watch (Apple Inc) for 6 weeks. Outcome measures included cognitive function, assessed with 3 brief n-back tasks daily; self-reported depressed mood, assessed once daily; daily total step count; and average heart rate. Change over a 6-week duration, diurnal and day-of-week variations, and covariation between outcome measures were examined using nonlinear and multilevel models. RESULTS: Participants showed initial improvement in the Cognition Kit N-Back performance, followed by a learning plateau. Performance reached 90% of individual learning levels on average 10 days after study onset. N-back performance was typically better earlier and later in the day, and step counts were lower at the beginning and end of each week. Higher step counts overall were associated with faster n-back learning, and an increased daily step count was associated with better mood on the same (P<.001) and following day (P=.02). Daily n-back performance covaried with self-reported mood after participants reached their learning plateau (P=.01). CONCLUSIONS: The current results support the feasibility and sensitivity of high-frequency cognitive assessments for disease and treatment monitoring in patients with depression. Methods to model the individual plateau in task learning can be used as a sensitive approach to better characterize changes in behavior and improve the clinical relevance of cognitive data. Wearable technology allows assessment of activity levels, which may influence both cognition and mood.

Combining anchoring with financial incentives to increase physical activity: a randomized controlled trial among college students.

The purpose of this study was to: (1) compare the relative efficacy of different combinations of three behavioral intervention strategies (i.e., personalized reminders, financial incentives, and anchoring) for establishing physical activity habits using an mHealth app and (2) to examine the effects of these different combined interventions on intrinsic motivation for physical activity and daily walking habit strength. A four-arm randomized controlled trial was conducted in a sample of college students (N = 161) who had a self-reported personal wellness goal of increasing their physical activity. Receiving cue-contingent financial incentives (i.e., incentives conditional on performing physical activity within ± one hour of a prespecified physical activity cue) combined with anchoring resulted in the highest daily step counts and greatest odds of temporally consistent walking during both the four-week intervention and the full eight-week study period. Cue-contingent financial incentives were also more successful at increasing physical activity and maintaining these effects post-intervention than traditional non-cue-contingent incentives. There were no differences in intrinsic motivation or habit strength between study groups at any time point. Financial incentives, particularly cue-contingent incentives, can be effectively used to support the anchoring intervention strategy for establishing physical activity habits. Moreover, mHealth apps are a feasible method for delivering the combined intervention technique of financial incentives with anchoring.

Feasibility and acceptability of measuring prenatal stress in daily life using smartphone-based ecological momentary assessment and wearable physiological monitors.

High levels of stress during pregnancy can have lasting effects on maternal and offspring health, which disproportionately impacts families facing financial strain, systemic racism, and other forms of social oppression. Developing ways to monitor daily life stress during pregnancy is important for reducing stress-related health disparities. We evaluated the feasibility and acceptability of using mobile health (mHealth) technology (i.e., wearable biosensors, smartphone-based ecological momentary assessment) to measure prenatal stress in daily life. Fifty pregnant women (67% receiving public assistance; 70% Black, 6% Multiracial, 24% White) completed 10 days of ambulatory assessment, in which they answered smartphone-based surveys six times a day and wore a chest-band device (movisens EcgMove4) to monitor their heart rate, heart rate variability, and activity level. Feasibility and acceptability were evaluated using behavioral meta-data and participant feedback. Findings supported the feasibility and acceptability of mHealth methods: Participants answered approximately 75% of the surveys per day and wore the device for approximately 10 hours per day. Perceived burden was low. Notably, participants with higher reported stressors and financial strain reported lower burden associated with the protocol than participants with fewer life stressors, highlighting the feasibility of mHealth technology for monitoring prenatal stress among pregnant populations living with higher levels of contextual stressors. Findings support the use of mHealth technology to measure prenatal stress in real-world, daily life settings, which shows promise for informing scalable, technology-assisted interventions that may help to reduce health disparities by enabling more accessible and comprehensive care during pregnancy.

Poor Rhinitis and Asthma Control Is Associated With Decreased Health-Related Quality of Life and Utilities: A MASK-air Study.

BACKGROUND: Allergic rhinitis (AR) and asthma may affect health-related quality of life. However, national estimates on the quality of life of patients with AR or asthma are lacking. OBJECTIVE: To provide estimates for utility scores and EuroQoL five-dimension (EQ-5D) visual analog scale (VAS) for patients with AR or asthma. METHODS: We conducted a cross-sectional study using direct patient data from the MASK-air app on European MASK-air users with self-reported AR or asthma. We used a multi-attribute instrument (EQ-5D) to measure quality of life (as utility scores and EQ-5D VAS values). Mean scores were calculated per country and disease control level using multilevel regression models with poststratification, accounting for age and sex biases. RESULTS: We assessed data from 7905 MASK-air users reporting a total of up to 82,737 days. For AR, utilities ranged from 0.86 to 0.99 for good control versus 0.72 to 0.85 for poor control; EQ-5D VAS levels ranged from 78.9 to 87.9 for good control versus 55.3 to 64.2 for poor control. For asthma, utilities ranged from 0.84 to 0.97 for good control versus 0.73 to 0.87 for poor control; EQ-5D VAS levels ranged from 68.4 to 81.5 for good control versus 51.4 to 64.2 for poor control. Poor disease control was associated with a mean loss of 0.14 utilities for both AR and asthma. For the same control levels, AR and asthma were associated with similar utilities and EQ-5D VAS levels. However, lower values were observed for asthma plus AR compared with AR alone. CONCLUSIONS: Poor AR or asthma control are associated with reduced quality of life. The estimates obtained from mobile health data may provide valuable insights for health technology assessment studies.

Momentary Factors and Study Characteristics Associated With Participant Burden and Protocol Adherence: Ecological Momentary Assessment.

BACKGROUND: Ecological momentary assessment (EMA) has become a popular mobile health study design to understand the lived experiences of dynamic environments. The numerous study design choices available to EMA researchers, however, may quickly increase participant burden and could affect overall adherence, which could limit the usability of the collected data. OBJECTIVE: This study quantifies what study design, participant attributes, and momentary factors may affect self-reported burden and adherence. METHODS: The EMA from the Phase 1 Family Matters Study (n=150 adult Black, Hmong, Latino or Latina, Native American, Somali, and White caregivers; n=1392 observation days) was examined to understand how participant self-reported survey burden was related to both design and momentary antecedents of adherence. The daily burden was measured by the question "Overall, how difficult was it for you to fill out the surveys today?" on a 5-item Likert scale (0=not at all and 4=extremely). Daily protocol adherence was defined as completing at least 2 signal-contingent surveys, 1 event-contingent survey, and 1 end-of-day survey each. Stress and mood were measured earlier in the day, sociodemographic and psychosocial characteristics were reported using a comprehensive cross-sectional survey, and EMA timestamps for weekends and weekdays were used to parameterize time-series models to evaluate prospective correlates of end-of-day study burden. RESULTS: The burden was low at 1.2 (SD 1.14) indicating "a little" burden on average. Participants with elevated previous 30-day chronic stress levels (mean burden difference: 0.8; P=.04), 1 in 5 more immigrant households (P=.02), and the language primarily spoken in the home (P=.04; 3 in 20 more non-English-speaking households) were found to be population attributes of elevated moderate-high burden. Current and 1-day lagged nonadherence were correlated with elevated 0.39 and 0.36 burdens, respectively (P=.001), and the association decayed by the second day (ß=0.08; P=.47). Unit increases in momentary antecedents, including daily depressed mood (P=.002) and across-day change in stress (P=.008), were positively associated with 0.15 and 0.07 higher end-of-day burdens after controlling for current-day adherence. CONCLUSIONS: The 8-day EMA implementation appeared to capture momentary sources of stress and depressed mood without substantial burden to a racially or ethnically diverse and immigrant or refugee sample of parents. Attention to sociodemographic attributes (eg, EMA in the primary language of the caregiver) was important for minimizing participant burden and improving data quality. Momentary stress and depressed mood were strong determinants of participant-experienced EMA burden and may affect adherence to mobile health study protocols. There were no strong indicators of EMA design attributes that created a persistent burden for caregivers. EMA stands to be an important observational design to address dynamic public health challenges related to human-environment interactions when the design is carefully tailored to the study population and to study research objectives.

Impact of Digital Interventions on the Treatment Burden of Patients With Chronic Conditions: Protocol for a Systematic Review.

BACKGROUND: There is great potential for delivering cost-effective, quality health care for patients with chronic conditions through digital interventions. Managing chronic conditions often includes a substantial workload required for adhering to the treatment regimen and negative consequences on the patient's function and well-being. This treatment burden affects adherence to treatment and disease outcomes. Digital interventions can potentially exacerbate the burden but also alleviate it. OBJECTIVE: The objective of this review is to identify, summarize, and synthesize the evidence of how digital interventions impact the treatment burden of people with chronic conditions. METHODS: The search, selection, and data synthesis processes were designed according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015. A systematic search was conducted on October 16, 2023, from databases PubMed, Scopus, Web of Science, ACM, PubMed Central, and CINAHL. RESULTS: Preliminary searches have been conducted, and screening has been started. The review is expected to be completed in October 2024. CONCLUSIONS: As the number of patients with chronic conditions is increasing, it is essential to design new digital interventions for managing chronic conditions in a way that supports patients with their treatment burden. To the best of our knowledge, the proposed systematic review will be the first review that investigates the impact of digital interventions on the treatment burden of patients. The results of this review will contribute to the field of health informatics regarding knowledge of the treatment burden associated with digital interventions and practical implications for developing better digital health care for patients with chronic conditions. TRIAL REGISTRATION: PROSPERO CRD42023477605; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=477605. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54833.

Use of Ecological Momentary Assessment to Measure Dyspnea in COPD.

Dyspnea is an unpredictable and distressing symptom of chronic obstructive pulmonary disease (COPD). Dyspnea is challenging to measure due to the heterogeneity of COPD and recall bias associated with retrospective reports. Ecological Momentary Assessment (EMA) is a technique used to collect symptoms in real-time within a natural environment, useful for monitoring symptom trends and risks of exacerbation in COPD. EMA can be integrated into mobile health (mHealth) platforms for repeated data collection and used alongside physiological measures and behavioral activity monitors. The purpose of this paper is to discuss the use of mHealth and EMA for dyspnea measurement, consider clinical implications of EMA in COPD management, and identify needs for future research in this area.

Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study.

Background: Accurately assessing an individual's diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed. Adherence to image-based methods may be improved with appropriately timed prompting via text message. Objective: This study aimed to quantitatively examine the effect of prompt timing on adherence to an image-based dietary record and qualitatively explore the participant experience of dietary assessment in order to inform the design of a novel image-based dietary assessment tool. Methods: This study used a randomized crossover design to examine the intraindividual effect of 3 prompt settings on the number of images captured in an image-based dietary record. The prompt settings were control, where no prompts were sent; standard, where prompts were sent at 7:15 AM, 11:15 AM, and 5:15 PM for every participant; and tailored, where prompt timing was tailored to habitual meal times for each participant. Participants completed a text-based dietary record at baseline to determine the timing of tailored prompts. Participants were randomized to 1 of 6 study sequences, each with a unique order of the 3 prompt settings, with each 3-day image-based dietary record separated by a washout period of at least 7 days. The qualitative component comprised semistructured interviews and questionnaires exploring the experience of dietary assessment. Results: A total of 37 people were recruited, and 30 participants (11 male, 19 female; mean age 30, SD 10.8 years), completed all image-based dietary records. The image rate increased by 0.83 images per day in the standard setting compared to control (P=.23) and increased by 1.78 images per day in the tailored setting compared to control (P≤.001). We found that 13/21 (62%) of participants preferred to use the image-based dietary record versus the text-based dietary record but reported method-specific challenges with each method, particularly the inability to record via an image after a meal had been consumed. Conclusions: Tailored prompting improves adherence to image-based dietary assessment. Future image-based dietary assessment tools should use tailored prompting and offer both image-based and written input options to improve record completeness.

Examining the Perceptions of mHealth on Racial and Ethnic Disparities in Postpartum Health for Black Women: A Scoping Review.

Background. Several disparities exist for Black mothers during the postpartum period, including but not limited to increased maternal mortality and morbidity rates, decreased access to care, and limited access to resources. Given the racial discrepancies in attention to postpartum care, coupled with the critical importance of the postpartum period for preventing adverse maternal health outcomes, research is warranted to explore how mobile health (mHealth) applications may help to alleviate maternal health disparities by optimizing postpartum care and addressing barriers to care for postpartum Black women. Thus, this review examines the perceptions of mHealth applications and their utility in health outcomes among postpartum Black women. Methods. We undertook a comprehensive literature search using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We included peer-reviewed articles published between 2010 and 2022 that were written in English, utilized mHealth as a primary intervention, and focused on postpartum health and access to resources, primarily among Black women in the United States. Results. A total of eight articles were included in our synthesis, encompassing mobile phone-based interventions for Black women. Cultural tailoring was included in five studies. Interventions that incorporated tailored content and fostered interactions reported high rates of follow-up. Conclusions. Tailored mHealth interventions can effectively promote behavior change and improve health care outcomes for Black women. However, there is a critical need for more research to assess user engagement and retention and whether these improvements indicate long-term sustainability.

The information, control, and value models of mobile health-driven empowerment.

Mobile health tools are often said to empower users by providing them with the information they need to exercise control over their health. We aim to bring clarity to this claim, and in doing so explore the relationship between empowerment and autonomy. We have identified three distinct models embedded in the empowerment rhetoric: empowerment as information, empowerment as control, and empowerment as values. Each distinct model of empowerment gives rise to an associated problem. These problems, the Problem of Interpretation, the Value Alignment Problem, and the Priority Problem, show that mobile health tools in their current form are either insufficient for empowerment or are self-defeating. These digital health technologies encourage users to adopt an individualized conception of autonomy, one that may weaken the doctor-patient relationship and undermine practices in shared decision making, and ultimately may not deliver on improving the health outcomes for those that need it the most.

Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review.

BACKGROUND: There has been an increased interest in understanding social anxiety (SA) and SA disorder (SAD) antecedents and consequences as they occur in real time, resulting in a proliferation of studies using ambulatory assessment (AA). Despite the exponential growth of research in this area, these studies have not been synthesized yet. OBJECTIVE: This review aimed to identify and describe the latest advances in the understanding of SA and SAD through the use of AA. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search was conducted in Scopus, PubMed, and Web of Science. RESULTS: A total of 70 articles met the inclusion criteria. The qualitative synthesis of these studies showed that AA permitted the exploration of the emotional, cognitive, and behavioral dynamics associated with the experience of SA and SAD. In line with the available models of SA and SAD, emotion regulation, perseverative cognition, cognitive factors, substance use, and interactional patterns were the principal topics of the included studies. In addition, the incorporation of AA to study psychological interventions, multimodal assessment using sensors and biosensors, and transcultural differences were some of the identified emerging topics. CONCLUSIONS: AA constitutes a very powerful methodology to grasp SA from a complementary perspective to laboratory experiments and usual self-report measures, shedding light on the cognitive, emotional, and behavioral antecedents and consequences of SA and the development and maintenance of SAD as a mental disorder.