Reliability and Validity of Noncognitive Ecological Momentary Assessment Survey Response Times as an Indicator of Cognitive Processing Speed in People's Natural Environment: Intensive Longitudinal Study.

BACKGROUND: Various populations with chronic conditions are at risk for decreased cognitive performance, making assessment of their cognition important. Formal mobile cognitive assessments measure cognitive performance with greater ecological validity than traditional laboratory-based testing but add to participant task demands. Given that responding to a survey is considered a cognitively demanding task itself, information that is passively collected as a by-product of ecological momentary assessment (EMA) may be a means through which people's cognitive performance in their natural environment can be estimated when formal ambulatory cognitive assessment is not feasible. We specifically examined whether the item response times (RTs) to EMA questions (eg, mood) can serve as approximations of cognitive processing speed. OBJECTIVE: This study aims to investigate whether the RTs from noncognitive EMA surveys can serve as approximate indicators of between-person (BP) differences and momentary within-person (WP) variability in cognitive processing speed. METHODS: Data from a 2-week EMA study investigating the relationships among glucose, emotion, and functioning in adults with type 1 diabetes were analyzed. Validated mobile cognitive tests assessing processing speed (Symbol Search task) and sustained attention (Go-No Go task) were administered together with noncognitive EMA surveys 5 to 6 times per day via smartphones. Multilevel modeling was used to examine the reliability of EMA RTs, their convergent validity with the Symbol Search task, and their divergent validity with the Go-No Go task. Other tests of the validity of EMA RTs included the examination of their associations with age, depression, fatigue, and the time of day. RESULTS: Overall, in BP analyses, evidence was found supporting the reliability and convergent validity of EMA question RTs from even a single repeatedly administered EMA item as a measure of average processing speed. BP correlations between the Symbol Search task and EMA RTs ranged from 0.43 to 0.58 (P<.001). EMA RTs had significant BP associations with age (P<.001), as expected, but not with depression (P=.20) or average fatigue (P=.18). In WP analyses, the RTs to 16 slider items and all 22 EMA items (including the 16 slider items) had acceptable (>0.70) WP reliability. After correcting for unreliability in multilevel models, EMA RTs from most combinations of items showed moderate WP correlations with the Symbol Search task (ranged from 0.29 to 0.58; P<.001) and demonstrated theoretically expected relationships with momentary fatigue and the time of day. The associations between EMA RTs and the Symbol Search task were greater than those between EMA RTs and the Go-No Go task at both the BP and WP levels, providing evidence of divergent validity. CONCLUSIONS: Assessing the RTs to EMA items (eg, mood) may be a method of approximating people's average levels of and momentary fluctuations in processing speed without adding tasks beyond the survey questions.

Glycemic Risk Index Profiles and Predictors Among Diverse Adults With Type 1 Diabetes.

BACKGROUND: The Glycemia Risk Index (GRI) was introduced as a single value derived from the ambulatory glucose profile that identifies patients who need attention. This study describes participants in each of the five GRI zones and examines the percentage of variation in GRI scores that is explained by sociodemographic and clinical variables among diverse adults with type 1 diabetes. METHODS: A total of 159 participants provided blinded continuous glucose monitoring (CGM) data over 14 days (mean age [SD] = 41.4 [14.5] years; female = 54.1%, Hispanic = 41.5%). Glycemia Risk Index zones were compared on CGM, sociodemographic, and clinical variables. Shapley value analysis examined the percentage of variation in GRI scores explained by different variables. Receiver operating characteristic curves examined GRI cutoffs for those more likely to have experienced ketoacidosis or severe hypoglycemia. RESULTS: Mean glucose and variability, time in range, and percentage of time in high, and very high, glucose ranges differed across the five GRI zones (P values < .001). Multiple sociodemographic indices also differed across zones, including education level, race/ethnicity, age, and insurance status. Sociodemographic and clinical variables collectively explained 62.2% of variance in GRI scores. A GRI score ≥84.5 reflected greater likelihood of ketoacidosis (area under the curve [AUC] = 0.848), and scores ≥58.2 reflected greater likelihood of severe hypoglycemia (AUC = 0.729) over the previous six months. CONCLUSIONS: Results support the use of the GRI, with GRI zones identifying those in need of clinical attention. Findings highlight the need to address health inequities. Treatment differences associated with the GRI also suggest behavioral and clinical interventions including starting individuals on CGM or automated insulin delivery systems.

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.

Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals' everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants' extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Understanding Worker Well-Being Relative to High-Workload and Recovery Activities across a Whole Day: Pilot Testing an Ecological Momentary Assessment Technique.

Occupational health and safety is experiencing a paradigm shift from focusing only on health at the workplace toward a holistic approach and worker well-being framework that considers both work and non-work factors. Aligned with this shift, the purpose of this pilot study was to examine how, within a person, frequencies of high-workload and recovery activities from both work and non-work periods were associated with same day well-being measures. We analyzed data on 45 workers with type 1 diabetes from whom we collected activity data 5-6 times daily over 14 days. More frequent engagement in high-workload activities was associated with lower well-being on multiple measures including higher stress. Conversely, greater recovery activity frequency was mostly associated with higher well-being indicated by lower stress and higher positive affect. Overall, our results provide preliminary validity evidence for measures of high-workload and recovery activity exposure covering both work and non-work periods that can inform and support evaluations of worker well-being.

Cooking and Gardening Behaviors and Improvements in Dietary Intake in Hispanic/Latino Youth.

Background: School gardening interventions typically include cooking and gardening (CG) components; however, few studies have examined associations between CG psychosocial behaviors (attitudes, self-efficacy, and motivation), dietary intake, and obesity parameters. This study assessed the association between changes in CG behaviors with changes in dietary intake and obesity in participants of the LA Sprouts study, an after-school, 12-week, randomized controlled CG intervention conducted in four inner-city elementary schools in Los Angeles. Methods: Process analysis using data from 290 low-income, primarily Hispanic/Latino third through fifth-grade students who were randomized to either the LA Sprouts intervention (n = 160) or control group (n = 130). Height, weight, waist circumference, dietary intake via questionnaire, and CG behaviors were collected at baseline and postintervention. Linear regressions determined whether changes in CG behaviors predicted changes in dietary intake and obesity outcomes. Results: There were no differences in changes in CG psychosocial behaviors between intervention and control groups, therefore groups were combined. Participants were 49% male, 87% Hispanic/Latino, and an average age of nine. Increases in cooking behaviors significantly predicted increases in dietary fiber intake (p = 0.004) and increases in vegetable intake (p = 0.03). Increases in gardening behaviors significantly predicted increased intake of dietary fiber (p = 0.02). Changes in CG behaviors were not associated with changes in BMI z-score or waist circumference. Conclusions: Results from this study suggest that school-based interventions should incorporate CG components, despite their potentially costly and time-intensive nature, as these behaviors may be responsible for improvements in dietary intake of high-risk minority youth.

Psychosocial and Behavioral Correlates of A1C and Quality of Life Among Young Adults With Diabetes.

PURPOSE: The purpose of this study was to evaluate relationships between behavioral and psychosocial constructs, A1C, and diabetes-dependent quality of life (DQoL) among low-socioeconomic status, ethnically diverse young adults with diabetes. METHODS: Using baseline data of 81 participants in the Resilient, Empowered, Active Living (REAL) randomized controlled trial, behavioral, cognitive, affective, and experiential variables were correlated with A1C and DQoL while adjusting for demographic characteristics, and these relationships were examined for potential effect modification. RESULTS: The data indicate that depressive symptoms and satisfaction with daily activities are associated with both A1C and DQoL, while diabetes knowledge and participation in daily activities are associated with neither A1C nor DQoL. Two constructs, diabetes distress and life satisfaction, were associated with DQoL and were unrelated to A1C, while 2 constructs, self-monitoring of blood glucose and medication adherence, were associated with A1C but unrelated to DQoL. These relationships were largely unchanged by adjusting for demographic characteristics, while numerous effect modifications were found. CONCLUSION: The data suggest that when tailoring interventions, depressive symptoms and satisfaction with daily activities may be particularly fruitful intervention targets, as they represent modifiable risk factors that are associated with both A1C and DQoL.

Advances and Controversies in Diet and Physical Activity Measurement in Youth.

Technological advancements in the past decades have improved dietary intake and physical activity measurements. This report reviews current developments in dietary intake and physical activity assessment in youth. Dietary intake assessment has relied predominantly on self-report or image-based methods to measure key aspects of dietary intake (e.g., food types, portion size, eating occasion), which are prone to notable methodologic (e.g., recall bias) and logistic (e.g., participant and researcher burden) challenges. Although there have been improvements in automatic eating detection, artificial intelligence, and sensor-based technologies, participant input is often needed to verify food categories and portions. Current physical activity assessment methods, including self-report, direct observation, and wearable devices, provide researchers with reliable estimations for energy expenditure and bodily movement. Recent developments in algorithms that incorporate signals from multiple sensors and technology-augmented self-reporting methods have shown preliminary efficacy in measuring specific types of activity patterns and relevant contextual information. However, challenges in detecting resistance (e.g., in resistance training, weight lifting), prolonged physical activity monitoring, and algorithm (non)equivalence remain to be addressed. In summary, although dietary intake assessment methods have yet to achieve the same validity and reliability as physical activity measurement, recent developments in wearable technologies in both arenas have the potential to improve current assessment methods. THEME INFORMATION: This article is part of a theme issue entitled Innovative Tools for Assessing Diet and Physical Activity for Health Promotion, which is sponsored by the North American branch of the International Life Sciences Institute.

Compliance With Mobile Ecological Momentary Assessment Protocols in Children and Adolescents: A Systematic Review and Meta-Analysis.

BACKGROUND: Mobile device-based ecological momentary assessment (mobile-EMA) is increasingly used to collect participants' data in real-time and in context. Although EMA offers methodological advantages, these advantages can be diminished by participant noncompliance. However, evidence on how well participants comply with mobile-EMA protocols and how study design factors associated with participant compliance is limited, especially in the youth literature. OBJECTIVE: To systematically and meta-analytically examine youth's compliance to mobile-EMA protocols and moderators of participant compliance in clinical and nonclinical settings. METHODS: Studies using mobile devices to collect EMA data among youth (age ≤18 years old) were identified. A systematic review was conducted to describe the characteristics of mobile-EMA protocols and author-reported factors associated with compliance. Random effects meta-analyses were conducted to estimate the overall compliance across studies and to explore factors associated with differences in youths' compliance. RESULTS: This review included 42 unique studies that assessed behaviors, subjective experiences, and contextual information. Mobile phones were used as the primary mode of EMA data collection in 48% (20/42) of the reviewed studies. In total, 12% (5/42) of the studies used wearable devices in addition to the EMA data collection platforms. About half of the studies (62%, 24/42) recruited youth from nonclinical settings. Most (98%, 41/42) studies used a time-based sampling protocol. Among these studies, most (95%, 39/41) prompted youth 2-9 times daily, for a study length ranging from 2-42 days. Sampling frequency and study length did not differ between studies with participants from clinical versus nonclinical settings. Most (88%, 36/41) studies with a time-based sampling protocol defined compliance as the proportion of prompts to which participants responded. In these studies, the weighted average compliance rate was 78.3%. The average compliance rates were not different between studies with clinical (76.9%) and nonclinical (79.2%; P=.29) and studies that used only a mobile-EMA platform (77.4%) and mobile platform plus additional wearable devices (73.0%, P=.36). Among clinical studies, the mean compliance rate was significantly lower in studies that prompted participants 2-3 times (73.5%) or 4-5 times (66.9%) compared with studies with a higher sampling frequency (6+ times: 89.3%). Among nonclinical studies, a higher average compliance rate was observed in studies that prompted participants 2-3 times daily (91.7%) compared with those that prompted participants more frequently (4-5 times: 77.4%; 6+ times: 75.0%). The reported compliance rates did not differ by duration of EMA period among studies from either clinical or nonclinical settings. CONCLUSIONS: The compliance rate among mobile-EMA studies in youth is moderate but suboptimal. Study design may affect protocol compliance differently between clinical and nonclinical participants; including additional wearable devices did not affect participant compliance. A more consistent compliance-related result reporting practices can facilitate understanding and improvement of participant compliance with EMA data collection among youth.

Advancing Models and Theories for Digital Behavior Change Interventions.

To be suitable for informing digital behavior change interventions, theories and models of behavior change need to capture individual variation and changes over time. The aim of this paper is to provide recommendations for development of models and theories that are informed by, and can inform, digital behavior change interventions based on discussions by international experts, including behavioral, computer, and health scientists and engineers. The proposed framework stipulates the use of a state-space representation to define when, where, for whom, and in what state for that person, an intervention will produce a targeted effect. The "state" is that of the individual based on multiple variables that define the "space" when a mechanism of action may produce the effect. A state-space representation can be used to help guide theorizing and identify crossdisciplinary methodologic strategies for improving measurement, experimental design, and analysis that can feasibly match the complexity of real-world behavior change via digital behavior change interventions.

A Longitudinal Analysis of the Effects of Socioeconomic Factors, Foreign Media, and Attitude toward Appearance on General and Central Adiposity in Chinese Adolescents.

OBJECTIVE: This paper explores the longitudinal effects of socioeconomic factors (i.e., parent education and family income level), foreign media, and attitude toward appearance on general and central adiposity among Chinese adolescents. METHOD: A longitudinal analysis was performed using data from the China Seven Cities Study, a health promotion and smoking prevention study conducted in seven cities across Mainland China between 2002 and 2005. Participants included 5,020 middle and high school students and their parents. Explanatory variables included foreign media exposure, attitude toward appearance, parent education, and family income. Three-level, random-effect models were used to predict general adiposity (i.e., body mass index) and central adiposity (i.e., waist circumference). The Generalized Estimating Equation approach was utilized to determine the effect of explanatory variables on overweight status. RESULTS: Among girls, foreign media exposure was significantly negatively associated with general adiposity over time (ß=-0.06, p=0.01 for middle school girls; ß=-0.06, p=0.03 for high school girls). Attitude toward appearance was associated with lesser odds of being overweight, particularly among high school girls (OR=0.86, p<0.01). Among boys, parental education was significantly positively associated with general adiposity (ß=0.62, p<0.01 for middle school boys; ß=0.37, p=0.02 for high school boys) and associated with greater odds of being overweight (OR=1.55, p<0.01 for middle school boys; OR=1.26, p=0.04 for high school boys). Across all gender and grade levels, family income was significantly negatively associated with central adiposity over time. CONCLUSION: Interventions addressing Chinese adolescent overweight/obesity should consider these factors as potential focus areas.

Momentary assessment of affect, physical feeling states, and physical activity in children.

OBJECTIVE: Most research on the interplay of affective and physical feelings states with physical activity in children has been conducted under laboratory conditions and fails to capture intraindividual covariation. The current study used Ecological Momentary Assessment (EMA) to bidirectionally examine how affective and physical feeling states are related to objectively measured physical activity taking place in naturalistic settings during the course of children's everyday lives. METHODS: Children (N = 119, ages 9-13 years, 52% male, 32% Hispanic) completed 8 days of EMA monitoring, which measured positive affect (PA), negative affect (NA), feeling tired, and feeling energetic up to 7 times per day. EMA responses were time-matched to accelerometer assessed moderate-to-vigorous physical activity (MVPA) in the 30 min before and after each EMA survey. RESULTS: Higher ratings of feeling energetic and lower ratings of feeling tired were associated with more MVPA in the 30 min after the EMA prompt. More MVPA in the 30 min before the EMA prompt was associated with higher ratings of PA and feeling energetic and lower ratings of NA. Between-subjects analyses indicated that mean hourly leisure-time MVPA was associated with less intraindividual variability in PA and NA. CONCLUSIONS: Physical feeling states predict subsequent physical activity levels, which in turn, predict subsequent affective states in children. Active children demonstrated higher positive and negative emotional stability. Although the strength of these associations were of modest magnitude and their clinical relevance is unclear, understanding the antecedents to and consequences of physical activity may have theoretical and practical implications for the maintenance and promotion of physical activity and psychological well-being in children.

Current mHealth technologies for physical activity assessment and promotion.

CONTEXT: Novel mobile assessment and intervention capabilities are changing the face of physical activity (PA) research. A comprehensive systematic review of how mobile technology has been used for measuring PA and promoting PA behavior change is needed. EVIDENCE ACQUISITION: Article collection was conducted using six databases from February to June 2012 with search terms related to mobile technology and PA. Articles that described the use of mobile technologies for PA assessment, sedentary behavior assessment, and/or interventions for PA behavior change were included. Articles were screened for inclusion and study information was extracted. EVIDENCE SYNTHESIS: Analyses were conducted from June to September 2012. Mobile phone-based journals and questionnaires, short message service (SMS) prompts, and on-body PA sensing systems were the mobile technologies most utilized. Results indicate that mobile journals and questionnaires are effective PA self-report measurement tools. Intervention studies that reported successful promotion of PA behavior change employed SMS communication, mobile journaling, or both SMS and mobile journaling. CONCLUSIONS: mHealth technologies are increasingly being employed to assess and intervene on PA in clinical, epidemiologic, and intervention research. The wide variations in technologies used and outcomes measured limit comparability across studies, and hamper identification of the most promising technologies. Further, the pace of technologic advancement currently outstrips that of scientific inquiry. New adaptive, sequential research designs that take advantage of ongoing technology development are needed. At the same time, scientific norms must shift to accept "smart," adaptive, iterative, evidence-based assessment and intervention technologies that will, by nature, improve during implementation.

Mobile health technology evaluation: the mHealth evidence workshop.

Creative use of new mobile and wearable health information and sensing technologies (mHealth) has the potential to reduce the cost of health care and improve well-being in numerous ways. These applications are being developed in a variety of domains, but rigorous research is needed to examine the potential, as well as the challenges, of utilizing mobile technologies to improve health outcomes. Currently, evidence is sparse for the efficacy of mHealth. Although these technologies may be appealing and seemingly innocuous, research is needed to assess when, where, and for whom mHealth devices, apps, and systems are efficacious. In order to outline an approach to evidence generation in the field of mHealth that would ensure research is conducted on a rigorous empirical and theoretic foundation, on August 16, 2011, researchers gathered for the mHealth Evidence Workshop at NIH. The current paper presents the results of the workshop. Although the discussions at the meeting were cross-cutting, the areas covered can be categorized broadly into three areas: (1) evaluating assessments; (2) evaluating interventions; and (3) reshaping evidence generation using mHealth. This paper brings these concepts together to describe current evaluation standards, discuss future possibilities, and set a grand goal for the emerging field of mHealth research.

Sociocultural and socioeconomic influences on type 2 diabetes risk in overweight/obese African-American and Latino-American children and adolescents.

PURPOSE: It is unclear whether sociocultural and socioeconomic factors are directly linked to type 2 diabetes risk in overweight/obese ethnic minority children and adolescents. This study examines the relationships between sociocultural orientation, household social position, and type 2 diabetes risk in overweight/obese African-American (n = 43) and Latino-American (n = 113) children and adolescents. METHODS: Sociocultural orientation was assessed using the Acculturation, Habits, and Interests Multicultural Scale for Adolescents (AHIMSA) questionnaire. Household social position was calculated using the Hollingshead Two-Factor Index of Social Position. Insulin sensitivity (SI), acute insulin response (AIRG) and disposition index (DI) were derived from a frequently sampled intravenous glucose tolerance test (FSIGT). The relationships between AHIMSA subscales (i.e., integration, assimilation, separation, and marginalization), household social position and FSIGT parameters were assessed using multiple linear regression. RESULTS: For African-Americans, integration (integrating their family's culture with those of mainstream white-American culture) was positively associated with AIRG (ß = 0.27 ± 0.09, r = 0.48, P < 0.01) and DI (ß = 0.28 ± 0.09, r = 0.55, P < 0.01). For Latino-Americans, household social position was inversely associated with AIRG (ß = -0.010 ± 0.004, r = -0.19, P = 0.02) and DI (ß = -20.44 ± 7.50, r = -0.27, P < 0.01). CONCLUSIONS: Sociocultural orientation and household social position play distinct and opposing roles in shaping type 2 diabetes risk in African-American and Latino-American children and adolescents.

Psychosocial determinants of participation in moderate-to-vigorous physical activity among Hispanic and Latina middle school-aged girls.

We examined physical activity (PA)-related psychosocial factors, weight status, and self-reported participation in moderate-to-vigorous physical activity (MVPA) in Latina middle school-aged girls. Baseline data from a middle school-based health behavior study (N = 326) was used. Contrasting activity-level groups were identified (81 most active, 144 least active) and compared. More active girls had significantly greater social support for PA, motivation to exercise, and positive meanings of PA than their less active peers. There was no significant difference in body mass index (BMI) percentile, barriers to PA, or negative meanings of PA between groups. Less active girls reported more screen time activities than the highly active girls. Positive psychosocial factors may be predictive of participation in MVPA for middle school-aged Latina youth. However, BMI may not be directly related to PA participation in this population.

Does community type moderate the relationship between parent perceptions of the neighborhood and physical activity in children?

PURPOSE: To examine whether residing in a community designed to promote physical activity moderates the relationship between parent perceptions of the neighborhood and general physical activity or active commuting to school in their children. DESIGN: Cross-sectional. SETTING: San Bernardino County, California. SUBJECTS: Three hundred sixty-five families (one parent and one child in grades four through eight). Eighty-five reside in a smart growth community designed to be more conducive to physical activity. MEASURES: Parent perceptions assessed using the Neighborhood Environment Walkability Scale (NEWS). General child physical activity was measured using accelerometers, and active commuting was self-reported by children. ANALYSIS: Two sets of regressions were performed: one for general physical activity, and one for active commuting. Separate models were run in the two sets for each of the 14 NEWS factors, while controlling for demographics. RESULTS: For general physical activity, walking infrastructure, lack of cul-de-sacs, and social interaction had significant main effect associations (p ≤ .05). No factors were moderated by community. The relationships between active commuting to school and perceived crime, traffic hazards, hilliness, physical barriers, cul-de-sac connectivity, aesthetics, and walking infrastructure were significant for those in the smart growth community only (p ≤ .05). CONCLUSIONS: Living in an activity-friendly environment is associated with positive relationships between parent perceptions and active commuting behaviors in children. Future interventions should account for both the perceived neighborhood environment and available physical activity infrastructure.

Determining energy expenditure from treadmill walking using hip-worn inertial sensors: an experimental study.

We describe an experimental study to estimate energy expenditure during treadmill walking using a single hip-mounted inertial sensor (triaxial accelerometer and triaxial gyroscope). Typical physical-activity characterization using commercial monitors use proprietary counts that do not have a physically interpretable meaning. This paper emphasizes the role of probabilistic techniques in conjunction with inertial data modeling to accurately predict energy expenditure for steady-state treadmill walking. We represent the cyclic nature of walking with a Fourier transform and show how to map this representation to energy expenditure (VO(2), mL/min) using three regression techniques. A comparative analysis of the accuracy of sensor streams in predicting energy expenditure reveals that using triaxial information leads to more accurate energy-expenditure prediction compared to only using one axis. Combining accelerometer and gyroscope information leads to improved accuracy compared to using either sensor alone. Nonlinear regression methods showed better prediction accuracy compared to linear methods but required an order of higher magnitude run time.

Influences of social support, perceived barriers, and negative meanings of physical activity on physical activity in middle school students.

BACKGROUND: A profound decline in physical activity occurs in puberty. This phenomenon is not well understood. Therefore, the purpose of this study is to examine associations between family/friend social support for physical activity, negative meanings of physical activity (NMPA), and internal /external barriers to physical activity with moderate to vigorous physical activity (MVPA), and sedentary and light behavior (SLB) in youth. METHODS: A total of 350 participants from 7 Los Angeles County middle schools participated in the study (62% Latina, 79% females). Hypothesized pathways were examined using structural equation modeling. Psychosocial variables and participation in MVPA and SLB were assessed by self-reported questionnaires. RESULTS: NMPA were related to lower levels of family/friend social support and greater internal/external barriers. Family social support was the only significant indicator of MVPA (ß=0.79). Low family social support was related to higher SLB (ß=-0.25). CONCLUSIONS: Family social support seems crucial to promote MVPA and reduce SLB in adolescents and might be influenced by child's feelings about physical activity. Future research should consider the interrelationship between psychosocial correlates of physical activity.

Investigating children's physical activity and sedentary behavior using ecological momentary assessment with mobile phones.

The risk of obesity during childhood can be significantly reduced through increased physical activity and decreased sedentary behavior. Recent technological advances have created opportunities for the real-time measurement of these behaviors. Mobile phones are ubiquitous and easy to use, and thus have the capacity to collect data from large numbers of people. The present study tested the feasibility, acceptability, and validity of an electronic ecological momentary assessment (EMA) protocol using electronic surveys administered on the display screen of mobile phones to assess children's physical activity and sedentary behaviors. A total of 121 children (ages 9-13, 51% male, 38% at risk for overweight/overweight) participated in EMA monitoring from Friday afternoon to Monday evening during children's nonschool time, with 3-7 surveys/day. Items assessed current activity (e.g., watching TV/movies, playing video games, active play/sports/exercising). Children simultaneously wore an Actigraph GT2M accelerometer. EMA survey responses were time-matched to total step counts and minutes of moderate-to-vigorous physical activity (MVPA) occurring in the 30 min before each EMA survey prompt. No significant differences between answered and unanswered EMA surveys were found for total steps or MVPA. Step counts and the likelihood of 5+ min of MVPA were significantly higher during EMA-reported physical activity (active play/sports/exercising) vs. sedentary behaviors (reading/computer/homework, watching TV/movies, playing video games, riding in a car) (P < 0.001). Findings generally support the acceptability and validity of a 4-day EMA protocol using mobile phones to measure physical activity and sedentary behavior in children during leisure time.

Energy-efficient multihypothesis activity-detection for health-monitoring applications.

Multi-hypothesis activity-detection using a wireless body area network is considered. A fusion center receives samples of biometric signals from heterogeneous sensors. Due to the different discrimination capabilities of each sensor, an optimized allocation of samples per sensor results in lower energy consumption. Optimal sample allocation is determined by minimizing the probability of misclassification given the current activity state of the user. For a particular scenario, optimal allocation can achieve the same accuracy (97%) as equal allocation across sensors with an energy savings of 26%. As the number of samples is an integer, further energy reduction is achieved by developing an approximation to the probability of misclassification which allows for a continuous-valued vector optimization. This alternate optimization yields approximately optimal allocations with significantly lower complexity, facilitating real-time implementation.