Eldin Dzubur

Development of a Smartphone Application to Measure Physical Activity Using Sensor-Assisted Self-Report

Introduction: Despite the known advantages of objective physical activity monitors (e.g., accelerometers), these devices have high rates of non-wear, which leads to missing data. Objective activity monitors are also unable to capture valuable contextual information about behavior. Adolescents recruited into physical activity surveillance and intervention studies will increasingly have smartphones, which are miniature computers with built-in motion sensors. Methods: This paper describes the design and development of a smartphone application (“app”) called Mobile Teen that combines objective and self-report assessment strategies through (1) sensor-informed context-sensitive ecological momentary assessment (CS-EMA) and (2) sensor-assisted end-of-day recall. Results: The Mobile Teen app uses the mobile phone’s built-in motion sensor to automatically detect likely bouts of phone non-wear, sedentary behavior, and physical activity. The app then uses transitions between these inferred states to trigger CS-EMA self-report surveys measuring the type, purpose, and context of activity in real-time. The end of the day recall component of the Mobile Teen app allows users to interactively review and label their own physical activity data each evening using visual cues from automatically detected major activity transitions from the phone’s built-in motion sensors. Major activity transitions are identified by the app, which cues the user to label that “chunk,” or period, of time using activity categories. Conclusion: Sensor-driven CS-EMA and end-of-day recall smartphone apps can be used to augment physical activity data collected by objective activity monitors, filling in gaps during non-wear bouts and providing additional real-time data on environmental, social, and emotional correlates of behavior. Smartphone apps such as these have potential for affordable deployment in large-scale epidemiological and intervention studies.

Investigating within-day and longitudinal effects of maternal stress on children's physical activity, dietary intake, and body composition: Protocol for the MATCH study

Parental stress is an understudied factor that may compromise parenting practices related to childrens dietary intake, physical activity, and obesity. However, studies examining these associations have been subject to methodological limitations, including cross-sectional designs, retrospective measures, a lack of stress biomarkers, and the tendency to overlook momentary etiologic processes occurring within each day. This paper describes the recruitment, data collection, and data analytic protocols for the MATCH (Mothers And Their Childrens Health) study, a longitudinal investigation using novel real-time data capture strategies to examine within-day associations of maternal stress with childrens physical activity and dietary intake, and how these effects contribute to childrens obesity risk. In the MATCH study, 200 mothers and their 8 to 12 year-old children are participating in 6 semi-annual assessment waves across 3 years. At each wave, measures for mother-child dyads include: (a) real-time Ecological Momentary Assessment (EMA) of self-reported daily psychosocial stressors (e.g., work at a job, family demands), feeling stressed, perceived stress, parenting practices, dietary intake, and physical activity with time and location stamps; (b) diurnal salivary cortisol patterns, accelerometer-monitored physical activity, and 24-hour dietary recalls; (c) retrospective questionnaires of sociodemographic, cultural, family, and neighborhood covariates; and (d) height, weight, and waist circumference. Putative within-day and longitudinal effects of maternal stress on childrens dietary intake, physical activity, and body composition will be tested through multilevel modeling and latent growth curve models, respectively. The results will inform interventions that help mothers reduce the negative effects of stress on weight-related parenting practices and childrens obesity risk.

Design of a smartphone application to monitor stress, asthma symptoms, and asthma inhaler use

Advances in the treatment and prevention of asthma have curtailed deaths, hospitalizations, and increases in prevalence rates over the past thirty years.1 Nevertheless, the effectiveness of long-term asthma management is mediated by behavioral factors such as adherence to medication and psychosocial stress. In a study using ecological momentary assessment to monitor asthma inhaler use, half of all non-adherence cases occurred while participants were with their peers.2 However, the study relied on subjective reports of adherence. Associations between stress and asthma symptoms have been observed, but these have relied on retrospective self-report, potentially introducing recall bias. Laboratory studies have demonstrated causal relationships between stress and biological markers of immune responses related to asthma.3, 4 However, these settings may not represent real-world situations. Furthermore, both laboratory and longitudinal studies to date have not captured the effect of daily variations in adherence, stress, and symptoms. Advancements in technology have led to commercial availability of low-cost personal computing devices (smartphones) capable of executing advanced health-related applications (“apps”) and communicating with external sensors via short-wave radio signals (Bluetooth).5 Ecological momentary assessment (EMA) using smartphones is a method of capturing real-time data that maintains ecological validity, reduces recall bias, preserves within-day changes, and captures objective data from external devices to reduce social desirability bias.6 This letter describes the design of a smartphone application that integrates EMA and Bluetooth-enabled sensors for asthma inhalers. This technology can measure real-time asthma symptomology, social and physical context, behavior, stress, and inhaler use. Development of the application was a collaborative effort from a multidisciplinary team of researchers and computer scientists. The application was installed on Samsung Galaxy Y (Model S5460) smartphones running the latest available version of Google’s Android operating system and loaned to participants. Study personnel conducted iterative development (alpha) testing before initiating pilot (beta) testing using a small (N=20) English-speaking convenience sample of Hispanic middle and high school students (ages 12–17) enrolled in a mobile asthma management clinic for low-income families.7 Written parental consent and child assent were obtained at enrollment; the study was approved by the Institutional Review Board at the University of Southern California. Physicians assisted at enrollment to inform participants that the application was not a replacement for treatment. The application uses signal-contingent (i.e, randomly-timed) and event-contingent (i.e., context-sensitive) EMA sampling triggered by asthma inhaler use. Inhaler use is detected when the phone receives a signal from a Bluetooth sensor on the participant’s quick-relief and controller medications. The signal-contingent EMA component of the software prompts the user with an electronic survey at a random time within each of seven designated time windows: 7–9 AM, 9–11 AM, 11 AM–1 PM, 1 – 3 PM, 3 – 5 PM, 5–7 PM, and 7–9 PM. No surveys are deployed prior to 3 PM on weekdays (during school time). After receiving a prompt (eFigure 1), the participants are presented with a set of questions querying current levels of positive and negative affect, stress, energy, and fatigue, as well as the type of activity currently being performed, and information about social and physical contexts (eTable 1). Additionally, participants are asked to recall stressful events, asthma symptoms, and asthma coping-related behaviors occurring since the last survey (or in the past four hours if the last survey was completed more than four hours prior) (eTable 1).8,9,10 The event-contingent (i.e., context-sensitive) EMA component of the application runs a background service that monitors all incoming Bluetooth connections. Participants are provided with two small, button-like devices that attach to the tops of quick relief (i.e., rescue) and controller metered dose inhalers (Propeller sensor, provided at no cost by Propeller Health; Madison, WI) designed to transmit a Bluetooth signal to the phone when the inhaler is actuated. Approximately 5 minutes after the background service captures a Bluetooth sensor signal, the app initiates a real-time self-report survey. The first question in this survey asks whether the participant used a rescue inhaler, control inhaler, or neither (i.e., inhaler actuated unintentionally). If a participant reports any inhaler usage, the survey subsequently queries the severity of asthma symptoms experienced, the type of activity performed, and social and physical contexts encountered just before the inhaler use. Questions also ask about stressful events experienced since the last survey (or in the past four hours if the last survey was completed more than four hours prior) (eTable 1). To reduce burden on participants, EMA surveys contain logical question branching for question subsets. With the exception of questions related to performed activity type, a randomized selection algorithm was used for signal-contingent question subsets such that each subset had a 60% chance of appearing on any given survey. Data from all surveys are uploaded to a secure file transfer protocol (SFTP) server at the end of the day. At the completion of testing, the phones are retrieved from participants and the phone features are restored to factory settings. During pilot testing, participants received a daily average of 3.2 (SD = 0.9, range = 1 – 4.57) signal-contingent and 2.1 (SD= 2.6, range = 0.1 – 7.8) event-contingent prompts across all seven days. EMA prompt adherence rates ranged from 20% to 100% (M = 51.4%, SD = 21.8%). Users reported general satisfaction and ease of use, while some reported difficulty with answering surveys that interrupted them in the middle of the night (Table 1). Table 1 Sample Demographics and Usage Satisfaction in Pilot Testing (N=20) Once rigorously tested, the EMA portion of the application (source code) will be made publicly available (at no cost) to researchers. Open-source Android applications allow for localization to languages other than English and installation on participant-owned devices or loaned phones, thereby reducing cost. Furthermore, the application also allows for monitoring using other sensors (e.g. built in motion and location sensors, external personal ozone monitors). Future studies should seek to improve adherence rates, generalize to non-Hispanic sub-populations, and assess health adolescent health literacy. This application has the potential to assist researchers and clinicians to better understand real-time experiences of adolescent patients with asthma, increase adherence to asthma treatment regimens, tailor treatments to their specific needs, and enhance patient-provider communication.

Feasibility and Performance Test of a Real-Time Sensor-Informed Context-Sensitive Ecological Momentary Assessment to Capture Physical Activity

Background Objective physical activity monitors (eg, accelerometers) have high rates of nonwear and do not provide contextual information about behavior. Objective This study tested performance and value of a mobile phone app that combined objective and real-time self-report methods to measure physical activity using sensor-informed context-sensitive ecological momentary assessment (CS-EMA). Methods The app was programmed to prompt CS-EMA surveys immediately after 3 types of events detected by the mobile phone’s built-in motion sensor: (1) Activity (ie, mobile phone movement), (2) No-Activity (ie, mobile phone nonmovement), and (3) No-Data (ie, mobile phone or app powered off). In addition, the app triggered random (ie, signal-contingent) ecological momentary assessment (R-EMA) prompts (up to 7 per day). A sample of 39 ethnically diverse high school students in the United States (aged 14-18, 54% female) tested the app over 14 continuous days during nonschool time. Both CS-EMA and R-EMA prompts assessed activity type (eg, reading or doing homework, eating or drinking, sports or exercising) and contextual characteristics of the activity (eg, location, social company, purpose). Activity was also measured with a waist-worn Actigraph accelerometer. Results The average CS-EMA + R-EMA prompt compliance and survey completion rates were 80.5% and 98.5%, respectively. More moderate-to-vigorous intensity physical activity was recorded by the waist-worn accelerometer in the 30 minutes before CS-EMA activity prompts (M=5.84 minutes) than CS-EMA No-Activity (M=1.11 minutes) and CS-EMA No-Data (M=0.76 minute) prompts (P’s<.001). Participants were almost 5 times as likely to report going somewhere (ie, active or motorized transit) in the 30 minutes before CS-EMA Activity than R-EMA prompts (odds ratio=4.91, 95% confidence interval=2.16-11.12). Conclusions Mobile phone apps using motion sensor–informed CS-EMA are acceptable among high school students and may be used to augment objective physical activity data collected from traditional waist-worn accelerometers.

Momentary Assessment of Psychosocial Stressors, Context, and Asthma Symptoms in Hispanic Adolescents:

The current study used a novel real-time data capture strategy, ecological momentary assessment (EMA), to examine whether within-day variability in stress and context leads to exacerbations in asthma symptomatology in the everyday lives of ethnic minority adolescents. Low-income Hispanic adolescents (N = 20; 7th-12th grade; 54% male) with chronic asthma completed 7 days of EMA on smartphones, with an average of five assessments per day during non-school time. EMA surveys queried about where (e.g., home, outdoors) and with whom (e.g., alone, with friends) participants were at the time of the prompt. EMA surveys also assessed over the past few hours whether participants had experienced specific stressors (e.g., being teased, arguing with anyone), asthma symptoms (e.g., wheezing, coughing), or used an asthma inhaler. Multilevel models tested the independent relations of specific stressors and context to subsequent asthma symptoms adjusting for age, gender, and chronological day in the study. Being outdoors, experiencing disagreements with parents, teasing, and arguing were associated with more severe self-reported asthma symptoms in the next few hours (ps < .05). Being alone and having too much to do were unrelated to the experience of subsequent self-reported asthma symptoms. Using a novel real-time data capture strategy, results provide preliminary evidence that being outdoors and experiencing social stressors may induce asthma symptoms in low-income Hispanic children and adolescents with chronic asthma. The results of this preliminary study can serve as a basis for larger epidemiological and intervention studies.

Development of a Just-in-Time Adaptive Intervention for Smoking Cessation Among Korean American Emerging Adults

PurposeCigarette smoking is a preventable risk factor that contributes to unnecessary lung cancer burden among Korean Americans and there is limited research on effective smoking cessation strategies for this population. Smartphone-based smoking cessation apps that leverage just-in-time adaptive interventions (JITAIs) hold promise for smokers attempting to quit. However, little is known about how to develop and tailor a smoking cessation JITAI for Korean American emerging adult (KAEA) smokers.MethodThis paper documents the development process of MyQuit USC according to design guidelines for JITAI. Our development process builds on findings from a prior ecological momentary assessment study by using qualitative research methods. Semi-structured interviews and a focus group were conducted to inform which intervention options to offer and the decision rules that dictate their delivery.ResultsQualitative findings highlighted that (1) smoking episodes are highly context-driven and that (2) KAEA smokers believe they need personalized cessation strategies tailored to different contexts. Thus, MyQuit USC operates via decision rules that guide the delivery of personalized implementation intentions, which are contingent on dynamic factors, to be delivered “just in time” at user-scheduled, high-risk smoking situations.ConclusionThrough an iterative design process, informed by quantitative and qualitative formative research, we developed a smoking cessation JITAI tailored specifically for KAEA smokers. Further testing is under way to optimize future versions of the app with the most effective intervention strategies and decision rules. MyQuit USC has the potential to provide cessation support in real-world settings, when KAEAs need them the most.

Daily Associations of Stress and Eating in Mother–Child Dyads

Background and Aims. This study used Ecological Momentary Assessment (EMA) in mother–child dyads to examine the day-level associations of stress and eating. Method. Mothers and their 8- to 12-year-old children (N = 167 dyads) completed between three (weekday) and eight (weekend) EMA survey prompts per day at random nonschool times across 8 days. EMA measured perceived stress, and past 2-hour healthy (i.e., fruit and vegetables) and unhealthy (e.g., pastries/sweets, soda/energy drinks) eating. Results. Children reported more healthy and unhealthy eating on days when their mothers also engaged in more healthy and unhealthy eating, respectively. On days when mothers’ perceived stress was greater than usual, they reported more healthy eating. Discussion and Conclusions. Eating behaviors were coupled between mothers and children at the day level. Mothers’ stress was related to their own eating but not to children’s eating.

An Electronic Ecological Momentary Assessment Study to Examine the Consumption of High-Fat/High-Sugar Foods, Fruits/Vegetables, and Affective States Among Women

Objective: To examine the associations between high‐fat/high‐sugar foods (HFHS) and fruit and vegetable (FV) consumption and affective states in women. Methods: The researchers used electronic ecological momentary assessment to capture HFHS and FV consumption in the past 2 hours (predictor) and current affective states (outcome) across 1 week among 202 women. Multilevel linear regression was conducted. Weight status was tested as a moderator. Results: Consumption of FV in the past 2 hours was positively associated with feeling happy (P < .05). Women who consumed more HFHS or fewer FV than others in the study reported higher average sadness (both P < .05). Overweight or obese women who reported more frequent HFHS consumption than others had higher average stress than normal weight women (P < .05). Conclusions and Implications: The association between HFHS consumption and stress might be stronger in overweight or obese than normal weight women. Future studies could further enhance the electronic ecological momentary assessment method to explore other time‐varying moderators and mediators of food consumption and affect.

Association Between Self-Reported and Objective Activity Levels by Demographic Factors: Ecological Momentary Assessment Study in Children

Background To address the limitations of the retrospective self-reports of activity, such as its susceptibility to recall bias, researchers have shifted toward collecting real-time activity data on mobile devices via ecological momentary assessment (EMA). Although EMA is becoming increasingly common, it is not known how EMA self-reports of physical activity and sedentary behaviors relate to the objective measures of activity or whether there are factors that may influence the strength of association between these two measures. Understanding the relationship between EMA and accelerometry can optimize future instrument selection in studies assessing activity and health outcomes. Objective The aim of this study was to examine the associations between EMA-reported sports or exercise using the accelerometer-measured moderate-to-vigorous physical activity (MVPA) and EMA-reported TV, videos, or video games with the accelerometer-measured sedentary time (ST) in children during matched 2-h windows and test potential moderators. Methods Children (N=192; mean age 9.6 years; 94/192, 49.0% male; 104/192, 54.2% Hispanic; and 73/192, 38.0% overweight or obese) wore an accelerometer and completed up to 7 EMA prompts per day for 8 days during nonschool time, reporting on past 2-h sports or exercise and TV, videos, or video games. Multilevel models were used to assess the relationship between the accelerometer-measured ST and EMA-reported TV, videos, or video games. Given the zero-inflated distribution of MVPA, 2-part models were used assess the relationship between the accelerometer-measured MVPA and EMA-reported sports or exercise. Results EMA-reported TV, videos, or video games were associated with a greater accelerometer-measured ST (beta=7.3, 95% CI 5.5 to 9.0, P<.001). This relationship was stronger in boys (beta=9.9, 95% CI 7.2 to 12.6, P<.001) than that in girls (beta=4.9, 95% CI 2.6 to 7.2, P≤.001). EMA-reported sports or exercise was associated with a greater accelerometer-measured MVPA (zero portion P<.001; positive portion P<.001). This relationship was stronger on weekends, in older children, and in non-Hispanic children (zero portion all P values<.001; positive portion all P values<.001). Conclusions EMA reports highly relate to accelerometer measures. However, the differences in the strength of association depending on various demographic characteristics suggest that future research should use both EMA and accelerometers to measure activity to collect complementary activity data.

Investigating health risk environments in housing programs for transition-aged youth using geographically explicit ecological momentary assessments (Preprint)

Background Young adults who experience homelessness are exposed to environments that contribute to risk behavior. However, few studies have examined how access to housing may affect the health risk behaviors of young adults experiencing homelessness. Objective This paper describes the Log My Life study that uses an innovative, mixed-methods approach based on geographically explicit ecological momentary assessment (EMA) through cell phone technology to understand the risk environment of young adults who have either enrolled in housing programs or are currently homeless. Methods For the quantitative arm, study participants age 18-27 respond to momentary surveys via a smartphone app that collects geospatial information repeatedly during a 1-week period. Both EMAs (up to 8 per day) and daily diaries are prompted to explore within-day and daily variations in emotional affect, context, and health risk behavior, while also capturing infrequent risk behaviors such as sex in exchange for goods or services. For the qualitative arm, a purposive subsample of participants who indicated engaging in risky behaviors are asked to complete an in-depth qualitative interview using an interactive, personalized geospatial map rendering of EMA responses. Results Recruitment began in June of 2017. To date, 170 participants enrolled in the study. Compliance with EMA and daily diary surveys was generally high. In-depth qualitative follow-ups have been conducted with 15 participants. We expect to recruit 50 additional participants and complete analyses by September of 2019. Conclusions Mixing the quantitative and qualitative arms in this study will provide a more complete understanding of differences in risk environments between homeless and housed young adults. Furthermore, this approach can improve recall bias and enhance ecological validity. International Registered Report Identifier (IRRID) DERR1-10.2196/12112