Using global positioning systems to study health-related mobility and participation

Behavioral activation for veterans with co-occurring alcohol use disorder and posttraumatic stress disorder: Basis and methodology for a pilot randomized controlled trial

BACKGROUND

Nearly 2 million U.S. veterans live with co-occurring alcohol use disorder and posttraumatic stress disorder (AUD/PTSD). Extant AUD/PTSD treatments emphasize symptom reduction, sometimes overlooking psychosocial functioning improvements, and have dropout rates as high as 50 %. Additionally, current approaches to measuring psychosocial functioning are limited to self-report. This study protocol describes a 1:1 parallel, two-arm, pilot randomized controlled trial comparing Behavioral Activation (BA) psychotherapy to Relapse Prevention (RP) psychotherapy for veterans with AUD/PTSD.

METHODS

Forty-six veterans with AUD/PTSD will be block-randomized to eight weekly, virtual, hour-long individual sessions of BA or RP. Clinical interview, self-report, and geospatial assessments will be administered at pre- and post-treatment. Select outcome and exploratory measures will be administered during treatment. Analyses will focus on trial feasibility, BA acceptability, and preliminary efficacy. Geospatial analyses will explore whether pre- to post-treatment changes in geospatial movement can be used to objectively measure treatment response. The study site and an independent Data and Safety Monitoring Board will monitor trial progress, safety, and quality. De-identified data from consenting participants will be submitted to a sponsor-designated data repository.

CONCLUSION

If successful, this trial could help to provide veterans with AUD/PTSD with a more acceptable treatment option. Positive findings would also lay groundwork for testing BA in civilians with AUD/PTSD. Finally, by incorporating novel geospatial methods and technologies, this study could potentially yield a new approach to objectively measuring AUD/PTSD recovery that could be used in other clinical trials. This study was registered in ClinicalTrials.gov (NCT06249386).

Using GPS and Self-Report Data to Examine the Relationship Between Community Mobility and Community Participation Among Autistic Young Adults

IMPORTANCE

Community participation of autistic adults is important for health and well-being. Many clinical efforts and interventions aim to enhance community participation in this population.

OBJECTIVE

To empirically examine the relationship between community participation and community mobility.

DESIGN

A randomized controlled trial using data from baseline and 4- to 6-wk follow-up.

SETTING

Community organizations serving autistic adults in Philadelphia.

PARTICIPANTS

Sixty-three autistic young adults with data on community mobility and participation from a prior study on public transportation use.

OUTCOMES AND MEASURES

Participants were tracked with GPS-enabled cell phones over a 2-wk period. A spatiotemporal data mining algorithm was used to compute the total number of destinations, nonhome destinations, unique destinations, percentage of time spent outside the home, and median daily activity space area from the GPS data. The Temple University Community Participation measure was used to collect self-report data in 21 different areas, and total amount, breadth, and sufficiency of participation were calculated.

RESULTS

Moderate and statistically significant associations were found between community mobility and participation variables at baseline and follow-up. However, changes in community mobility were not related to changes in community participation.

CONCLUSION

Health policymakers and providers should consider community mobility as a factor that can affect community participation in autistic individuals. Plain-Language Summary: Lower levels of community participation among autistic young adults affect health outcomes and overall quality of life. Community mobility is often a barrier to community participation. An understanding of the relationship between community mobility and community participation can lead to occupational therapists tailoring specific interventions and policies that support autistic young adults to engage in important life activities within the community.

Community Participation of Individuals with Mental Illnesses in Rural Areas: Stakeholder Perspectives on Barriers and Facilitators

Community inclusion and participation are social determinants of physical and mental health. This study examines activity preferences, barriers to engagement, and potential strategies for facilitating community participation for individuals with serious mental illness living in rural communities. Data for this qualitative study were collected in a series of focus groups with a stakeholders in rural Pennsylvania. Written responses to questions on activities, barriers, facilitators, and solutions were analyzed by members of the research team. The activities that are important to our participants included both those readily accessible in rural areas and those only accessible in more urban areas. Many of the barriers identified aligned with prior research (e.g., poverty, community mobility issues). A number of novel and feasible solutions to overcome barriers were provided at the policy, program, and practice levels, some of which that can be implemented immediately, to increase participation, and improve overall health of people with mental illnesses.

Geographic intelligence to investigate community participation: a scoping review

PURPOSE

To understand the applicability and unique contributions of global positioning system (GPS) and geographic information system (GIS) technologies to investigate individuals' participation in the community.

METHODS

A scoping review was conducted to summarize studies that employed GPS and/or GIS to assess community participation. Systematic literature searches were performed using nine electronic databases, up to April 2022. Two independent reviewers screened studies for eligibility and extracted data from the selected studies.

RESULTS

The searches retrieved 628 articles, of which 36 met the inclusion criteria. In 31 studies, a GPS unit or GPS-enabled device monitored the community mobility of individuals with different health conditions. Tracking periods varied from five hours to 30 consecutive days. The spatiotemporal parameters obtained from satellite-based data provided information about individuals' presence in the community. Most studies combined GPS with other measuring tools (self-report diaries/questionnaires, qualitative interviews) to capture a broader description of community participation.

CONCLUSIONS

GPS and GIS are viable approaches for advancing research as they provide unique information about community participation not easily captured by other methods. The combination of available methods comprehensively address the physical and social dimensions of this construct.IMPLICATIONS FOR REHABILITATIONGlobal positioning system (GPS) and geographic information system (GIS) technology allows direct and real-time quantification of patterns of individuals' community mobility.The geographic area where individuals participate in daily living activities complements information from self-report diaries/questionnaires.Combining GPS technology with self-report diaries/questionnaires allows a broader description of individuals' community participation, addressing respectively both its physical and social dimensions.Knowledge of individuals' access to and involvement in community locations/situations may help therapists design interventions to improve community participation.

Sensory Processing and Community Participation in Autistic Adults

Background

Sensory processing differences have been shown to impact involvement in community activities. However, relatively little is known about how these differences affect community participation in autistic adults.

Objective

The objective of this study was to explore how sensory processing patterns of autistic adults impact community participation, including where people go, what they do, the amount of time in the community, and preferred locations.

Methods

We used data gathered from six autistic adults and their caregivers who participated in two studies. From Study 1, we reviewed results of the Adolescent and Adult Sensory Profile (AASP) and transcripts from interviews with caregivers. From Study 2, we reviewed GPS tracking data and transcripts from structured interviews with autistic adults focused on community participation. We read transcript data, identified quotes related to sensory processing and community participation and constructed individual participant narratives which linked findings from interviews, AASP, and GPS tracking.

Results

Participants included three males and three females ranging in age from 29 to 51. Each participant had a unique sensory processing profile that influenced where they went, the activities in which they engaged, how much time they spent in the community, and their preferred locations. Those whose sensory processing patterns indicated sensory sensitivity and sensory avoiding described the experience of certain environments as overwhelming and fatiguing and thus spent less time in the community and visited fewer places than those with other sensory processing patterns.

Conclusion

Results highlight the importance of sensory processing, especially as it impacts participation in the community. Sensory processing patterns should be considered along with other personal and contextual factors when assessing community participation and personal sensory processing patterns should be matched with activities and environmental demands.

Modeling Antimicrobial Prescriptions in Scotland: A Spatiotemporal Clustering Approach

In 2016, the British government acknowledged the importance of reducing antimicrobial prescriptions to avoid the long-term harmful effects of overprescription. Prescription needs are highly dependent on the factors that have a spatiotemporal component, such as bacterial outbreaks and urban densities. In this context, density-based clustering algorithms are flexible tools to analyze data by searching for group structures and therefore identifying peer groups of GPs with similar behavior. The case of Scotland presents an additional challenge due to the diversity of population densities under the area of study. We propose here a spatiotemporal clustering approach for modeling the behavior of antimicrobial prescriptions in Scotland. Particularly, we consider the density-based spatial clustering of applications with noise algorithm (DBSCAN) due to its ability to include both spatial and temporal data. We extend this approach into two directions. For the temporal analysis, we use dynamic time warping to measure the dissimilarity between time series while taking into account effects such as seasonality. For the spatial component, we propose a new way of weighting spatial distances with continuous weights derived from a Kernel density estimation-based process. This makes our approach suitable for cases with different local densities, which presents a well-known challenge for the original DBSCAN. We apply our approach to antibiotic prescription data in Scotland, demonstrating how the findings can be used to compare antimicrobial prescription behavior within a group of similar peers and detect regions of extreme behaviors.

Community Mental Health Center Visits and Community Mobility of People with Serious Mental Illnesses: A Facilitator or Constraint?

Mental health services and interventions have increasingly focused on the importance of community participation and mobility for people with serious mental illnesses (SMI). This study examined the role that visits to community mental health centers (CMHCs) may play in increasing community mobility of people with SMI. Eighty-nine adults with SMI receiving services at three CMHCS were tracked with GPS-enabled phones over a 13-day period. Findings revealed that participants visited more destinations on days they went to a CMHC compared to days they did not. They also spent more time out of the home and traveled greater distances. Results suggest that the benefits of visiting a mental health center appear to go beyond treatment outcomes, but also point to the possibility that obligations, whether to a clinic appointment or possibly vocational, educational, leisure, faith, or social commitments, may be an important stepping stone to more mobility and intentional, sustained community participation.

The use of smartphone-derived location data to evaluate participation following critical illness: A pilot observational cohort study

BACKGROUND

Disability is common following critical illness, impacting the quality of life of survivors, and is difficult to measure. 'Participation' can be quantified as involvement in life outside of their home requiring movement from their home to other locations. Participation restriction is a key element of disability, and following critical illness, participation may be diminished. It may be possible to quantify this change using pre-existing smartphone data.

OBJECTIVES

The feasibility of extracting location data from smartphones of survivors of intensive care unit (ICU) admission and assessing participation, using location-based outcomes, during recovery from critical illness was evaluated.

METHODS

Fifty consecutively admitted, consenting adult survivors of non-elective admission to ICU of greater than 48-h duration were recruited to a prospective observational cohort study where they were followed up at 3 and 6 months following discharge. The feasibility of extracting location data from survivors' smartphones and creating location-derived outcomes assessing participation was investigated over three 28-d study periods: pre-ICU admission and at 3 and 6 months following discharge. The following were calculated: time spent at home; the number of destinations visited; linear distance travelled; and two 'activity spaces', a minimum convex polygon and standard deviation ellipse.

RESULTS

Results are median [interquartile range] or n (%). The number of successful extractions was 9/50 (18%), 12/39 (31%), and 13/33 (39%); the percentage of time spent at home was 61 [56-68]%, 77 [66-87]%, and 67 [58-77]% (P = 0.16); the number of destinations visited was 34 [18-64], 38 [22-63], and 65 [46-88] (P = 0.02); linear distance travelled was 367 [56-788], 251 [114-323], and 747 [326-933] km over 28 d (P = 0.02), pre-ICU admission and at 3 and 6 months following ICU discharge, respectively. Activity spaces were successfully created.

CONCLUSION

Limited smartphone ownership, missing data, and time-consuming data extraction limit current implementation of mass extraction of location data from patients' smartphones to aid prognostication or measure outcomes. The number of journeys taken and the linear distance travelled increased between 3 and 6 months, suggesting participation may improve over time.

Impact of COVID-19 on Community Participation and Mobility in Young Adults with Autism Spectrum Disorders

Transportation and mobility for community participation is difficult for persons with Autism Spectrum Disorders (ASD) under normal circumstances, but the impact of COVID-19 made access even more challenging. Researchers used a single-subject design to examine patterns of change from before and after the COVID-19 pandemic in community mobility and participation as measured by GPS and daily participation questionnaires. Participants were young adults with ASD between the ages of 21 and 27 (4 males, 2 females) who were enrolled in a subsequent study. Community mobility and participation decreased for all participants in both essential and non-essential activities. Additionally, the number of trips for participants decreased substantially in the after COVID-19 periods, as did the variability in modes of transit.

Integrating community participation in the transition of older adults from hospital to home: a scoping review

INTRODUCTION

Benefits of community participation and physical activity for the health and wellbeing of older adults are well documented. This review aims to answer the question; "How is community participation considered for older adults in the transition from hospital to home?"

MATERIALS AND METHODS

This scoping review searched key databases using subject headings and keywords. Two independent reviewers selected studies based on a systematic procedure. Inclusion criteria were adults aged ≥60 years, transitioning from hospital to home, reporting on community participation, inclusive of leisure activities, social activities, and physical activity.

RESULTS

Of 2206 initial unique articles, 19 met inclusion criteria. Articles covered a range of diagnoses, most frequently stroke, hip replacement, or fracture. Numerous measures of community participation were reported, identifying "low" and "reduced" community participation in ten studies. Measures of physical activity, health-related quality of life, sleep quality, and loneliness were variable. Five studies reported interventions and four reported improved components of community participation. Numerous barriers to community participation were identified, with recommendations for future transition care services considered.

CONCLUSION

There are considerable barriers to promoting community participation in transition care services for older people. Older adults need information to prepare for returning home from hospital and to regain valued leisure and social activities for health-related quality of life.IMPLICATIONS FOR REHABILITATIONCommunity participation is an important component of healthy ageing which health professionals should consider beyond discharge.Levels of mobility and endurance should be considered in terms of facilitating community participation for older adults.Transition care services should provide adequate information to prepare individuals expectations of returning home following hospital stay, whilst attempting to maintain valued leisure and social activities.

A GPS-Based Framework for Understanding Outdoor Mobility Patterns of Older Adults with Dementia: An Exploratory Study

INTRODUCTION

An active lifestyle may protect older adults from cognitive decline. Yet, due to the complex nature of outdoor environments, many people living with dementia experience decreased access to outdoor activities. In this context, conceptualizing and measuring outdoor mobility is of great significance. Using the global positioning system (GPS) provides an avenue for capturing the multi-dimensional nature of outdoor mobility. The objective of this study is to develop a comprehensive framework for comparing outdoor mobility patterns of cognitively intact older adults and older adults with dementia using passively collected GPS data.

METHODS

A total of 7 people with dementia (PwD) and 8 cognitively intact controls (CTLs), aged 65 years or older, carried a GPS device when travelling outside their homes for 4 weeks. We applied a framework incorporating 12 GPS-based indicators to capture spatial, temporal, and semantic dimensions of outdoor mobility.

RESULTS

Despite a small sample size, the application of our mobility framework identified several significant differences between the 2 groups. We found that PwD participated in more medical-related (Cliff's Delta = 0.71, 95% CI: 0.34-1) and fewer sport-related (Cliff's Delta = -0.78, 95% CI: -1 to -0.32) activities compared to the cognitively intact CTLs. Our results also suggested that longer duration of daily walking time (Cliff's Delta = 0.71, 95% CI: 0.148-1) and longer outdoor activities at night, after 8 p.m. (Hedges' g = 1.42, 95% CI: 0.85-1.09), are associated with cognitively intact individuals.

CONCLUSION

Based on the proposed framework incorporating 12 GPS-based indicators, we were able to identify several differences in outdoor mobility in PwD compared with cognitively intact CTLs.

Community participation of community dwelling older adults: a cross-sectional study

BACKGROUND

With the advancing age of the population, and increasing demands on healthcare services, community participation has become an important consideration for healthy ageing. Low levels of community participation have been linked to increased mortality and social isolation. The extent to which community participation has been measured objectively in older adults remains scarce. This study aims to describe where and how older adults participate in the community and determine the feasibility of measurement methods for community participation.

METHODS

This observational cross-sectional study obtained data from 46 community dwelling older adults. A combination of Global Positioning Systems (GPS), accelerometry, and self-reported diaries were used over a 7-day monitoring period. Feasibility of methods were determined by calculating the loss of GPS data, questionnaires, and comparison of self-reported locations with GPS co-ordinates. Relationships between community participation, physical activity, social interactions, health related quality of life, sleep quality and loneliness were explored.

RESULTS

Older adults took a median (IQR) of 15 (9.25-18.75) trips out of home over the 7-day monitoring period, most frequently visiting commercial and recreational locations. In-home activities were mainly sedentary in nature, with out of home activities dependent on location type. Self-reported and GPS measures of trips out of home and the locations visited were significantly correlated (self-report 15.7 (5.6) GPS 14.4 (5.8) (r = 0.94)). Significant correlations between both the number of trips taken from home, with social interactions (r = 0.62) and the minutes of moderate to vigorous physical activity (MVPA) (r = 0.43) were observed. Daily MVPA was higher in participants who visited local walk/greenspaces (r = 0.48).

CONCLUSION

Participants performed more activities with social interactions out of home and visited commercial locations most frequently. The combination of GPS, accelerometry and self-report methods provided a detailed picture of community participation for older adults. Further research is required with older adults of varying health status to generalise the relationships between community participation, location and physical activity.

TRIAL REGISTRATION

Ethical approval was gained from the Flinders University Social and Behavioural Research Ethics Committee (protocol no. 8176).

Applying Environmental Context to Rehabilitation Research Using Geographic Information Systems and Global Positioning Systems Geospatial Technologies

Background

The International Classification of Functioning, Disability, and Health includes important considerations of environmental context in understanding disability, but the environmental impact is often difficult to measure.

Purpose

Demonstrates the use of Geographic Information Systems (GIS) and Global Positioning Systems (GPS) in rehabilitation research in assessing accessibility and participation; describes how to use these methods, and presents several considerations in using GIS and GPS in research.

Method

Using methods from public health and medical geography, this article describes how to apply GIS and GPS technologies to rehabilitation research to measure community participation and accessibility to resources.

Findings

Directions for using ArcGIS functions and case examples joining these mapping technologies with rehabilitation measures are provided.

Conclusions

Together with traditional measures, these technologies may provide rehabilitation researchers a more comprehensive approach to assessing accessibility and participation.

Examining the relationship between community mobility and participation using GPS and self-report data

Higher levels of community mobility have been shown to be associated with better physical health, mental health, and quality of life. The ability to move about one's community is also expected to facilitate community participation, which is an aspect of health functioning. This study uses Global Positioning Systems (GPS) technology to track various dimensions of community mobility, such as destinations, time outside the home, and distance traveled, and examine the relationship between these variables and community participation in a sample of individuals with serious mental illnesses (SMI). This population was selected because they are known to have diminished health functioning in terms of their community participation, and the goal is to explore the extent to which mobility limitations may account for this. A total of 103 individuals with serious mental illnesses were recruited from mental health agencies and consented to having their mobility tracked using GPS for 13 days and answering questions about their community-based activities. Greater amount of participation was associated with having more destinations and spending more time out of the house, but not with traveling larger distances and having a greater activity space. None of the mobility variables were related to the number of important participation areas or sufficiency of participation. The findings support the hypothesis that greater mobility is related to more participation, although satisfaction with the degree to which one participates does not appear to be impacted, suggesting that other factors need to be accounted for. Health policymakers and providers should pay attention to community mobility as a factor that affects health outcomes such as participation, in individuals with serious mental illnesses, and other populations. In particular, attending to access to personal transport, public transportation, and other mobility options appears to be important, as well as interventions aimed at encouraging greater community mobility.

Inferring Destinations and Activity Types of Older Adults From GPS Data: Algorithm Development and Validation

Background

Outdoor mobility is an important aspect of older adults’ functional status. GPS has been used to create indicators reflecting the spatiotemporal dimensions of outdoor mobility for applications in health and aging. However, outdoor mobility is a multidimensional construct. There is, as of yet, no classification algorithm that groups and characterizes older adults’ outdoor mobility based on its semantic aspects (ie, mobility intentions and motivations) by integrating geographic and domain knowledge.

Objective

This study assesses the feasibility of using GPS to determine semantic dimensions of older adults’ outdoor mobility, including destinations and activity types.

Methods

A total of 5 healthy individuals, aged 65 years or older, carried a GPS device when traveling outside their homes for 4 weeks. The participants were also given a travel diary to record details of all excursions from their homes, including date, time, and destination information. We first designed and implemented an algorithm to extract destinations and infer activity types (eg, food, shopping, and sport) from the GPS data. We then evaluated the performance of the GPS-derived destination and activity information against the traditional diary method.

Results

Our results detected the stop locations of older adults from their GPS data with an F1 score of 87%. On average, the extracted home locations were within a 40.18-meter (SD 1.18) distance of the actual home locations. For the activity-inference algorithm, our results reached an F1 score of 86% for all participants, suggesting a reasonable accuracy against the travel diary recordings. Our results also suggest that the activity inference’s accuracy measure differed by neighborhood characteristics (ie, Walk Score).

Conclusions

We conclude that GPS technology is accurate for determining semantic dimensions of outdoor mobility. However, further improvements may be needed to develop a robust application of this system that can be adopted in clinical practice.

Validating a GPS-based approach to detect health facility visits against maternal response to prompted recall survey

Introduction

Common approaches to measure health behaviors rely on participant responses and are subject to bias. Technology-based alternatives, particularly using GPS, address these biases while opening new channels for research. This study describes the development and implementation of a GPS-based approach to detect health facility visits in rural Pune district, India.

Methods

Participants were mothers of under-five year old children within the Vadu Demographic Surveillance area. Participants received GPS-enabled smartphones pre-installed with a location-aware application to continuously record and transmit participant location data to a central server. Data were analyzed to identify health facility visits according to a parameter-based approach, optimal thresholds of which were calibrated through a simulation exercise. Lists of GPS-detected health facility visits were generated at each of six follow-up home visits and reviewed with participants through prompted recall survey, confirming visits which were correctly identified. Detected visits were analyzed using logistic regression to explore factors associated with the identification of false positive GPS-detected visits.

Results

We enrolled 200 participants and completed 1098 follow-up visits over the six-month study period. Prompted recall surveys were completed for 694 follow-up visits with one or more GPS-detected health facility visits. While the approach performed well during calibration (positive predictive value (PPV) 78%), performance was poor when applied to participant data. Only 440 of 22 251 detected visits were confirmed (PPV 2%). False positives increased as participants spent more time in areas of high health facility density (odds ratio (OR) = 2.29, 95% confidence interval (CI) = 1.62-3.25). Visits detected at facilities other than hospitals and clinics were also more likely to be false positives (OR = 2.78, 95% CI = 1.65-4.67) as were visits detected to facilities nearby participant homes, with the likelihood decreasing as distance increased (OR = 0.89, 95% CI = 0.82-0.97). Visit duration was not associated with confirmation status.

Conclusions

The optimal parameter combination for health facility visits simulated by field workers substantially overestimated health visits from participant GPS data. This study provides useful insights into the challenges in detecting health facility visits where providers are numerous, highly clustered within urban centers and located near residential areas of the population which they serve.

Out-of-Home Mobility and Social Participation of Older People: a Photo-Based Ambulatory Assessment Study

Research has shown that social participation contributes to older people’s healthy ageing. Out-of-home mobility may promote higher levels of social participation among older people. However, mobility and social participation are sophisticated constructs. Social participation can be distinguished among different levels, such as being alone, being alone surrounded by others, interacting with others or engaging in activities together. Social participation and time spent in out-of-home-mobility can be difficult to remember and therefore difficult to assess. Picture-based ambulatory assessment provides valid and reliable information about people’s mobility as well as their level of participation with high ecological validity. The aim of the study was to investigate older people’s level of social participation and its association with high or low out-of-home mobility. In sum, 23072 pictures (mean per person = 2307; SD = 686.7) involving ten older people (mean age = 75.4 years; SD = 7.5 years) living in southwestern Germany were analysed. They were asked to wear a wearable camera for two consecutive days. Images were automatically captured every 15 seconds. Image analysis shows that study participants spent most of their time alone (at approximately 35% of analysed time). Out-of-home mobility was associated with higher levels of social participation, such as helping others (chi2 = 200,664, df = 5, p < .001). Picture-based ambulatory assessment can assist in the gathering of necessary sophisticated information that is difficult to assess via questionnaires or other similar methods.

GPS mobility as a digital biomarker of negative symptoms in schizophrenia: a case control study

Mobility is an important correlate of physical, cognitive, and mental health in chronic illness, and can be measured passively with mobile phone global positional satellite (GPS) sensors. To date, GPS data have been reported in a few studies of schizophrenia, yet it is unclear whether these data correlate with concurrent momentary reports of location, vary by people with schizophrenia and healthy comparison subjects, or associate with symptom clusters in schizophrenia. A total of 142 participants with schizophrenia (n = 86) or healthy comparison subjects (n = 56) completed 7 days of ecological momentary assessment (EMA) reports of location and behavior, and simultaneous GPS locations were tracked every five minutes. We found that GPS-derived indicators of average distance travelled overall and distance from home, as well as percent of GPS samples at home were highly correlated with EMA reports of location at the day- and week-averaged level. GPS-based mobility indicators were lower in schizophrenia with medium to large effect sizes. Less GPS mobility was related to greater negative symptom severity, particularly diminished motivation, whereas greater GPS mobility was weakly associated with more community functioning. Neurocognition, depression, and positive symptoms were not associated with mobility indicators. Therefore, passive GPS sensing could provide a low-burden proxy measure of important outcomes in schizophrenia, including negative symptoms and possibly of functioning. As such, passive GPS sensing could be used for monitoring and timely interventions for negative symptoms in young persons at high risk for schizophrenia.

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

BACKGROUND

GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.

METHODS

With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.

RESULTS

The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.

CONCLUSION

This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

A Time-Based Objective Measure of Exposure to the Food Environment

Exposure to food environments has mainly been limited to counting food outlets near participants’ homes. This study considers food environment exposures in time and space using global positioning systems (GPS) records and fast food restaurants (FFRs) as the environment of interest. Data came from 412 participants (median participant age of 45) in the Seattle Obesity Study II who completed a survey, wore GPS receivers, and filled out travel logs for seven days. FFR locations were obtained from Public Health Seattle King County and geocoded. Exposure was conceptualized as contact between stressors (FFRs) and receptors (participants’ mobility records from GPS data) using four proximities: 21 m, 100 m, 500 m, and ½ mile. Measures included count of proximal FFRs, time duration in proximity to ≥1 FFR, and time duration in proximity to FFRs weighted by FFR counts. Self-reported exposures (FFR visits) were excluded from these measures. Logistic regressions tested associations between one or more reported FFR visits and the three exposure measures at the four proximities. Time spent in proximity to an FFR was associated with significantly higher odds of FFR visits at all proximities. Weighted duration also showed positive associations with FFR visits at 21-m and 100-m proximities. FFR counts were not associated with FFR visits. Duration of exposure helps measure the relationship between the food environment, mobility patterns, and health behaviors. The stronger associations between exposure and outcome found at closer proximities (<100 m) need further research.

Digital technologies for social inclusion of individuals with disabilities

Information technology can be an important facilitator of social inclusion for people with disabilities into society. However, the goals specified in this area by organizations such as the European Commission have not yet been achieved in their totality. The aim of this paper is to explore which types of information communication technology-based applications and/or digital services have been suggested to facilitate the social integration of people who suffer from different types of disabilities. We performed a literature review that included studies published during a period of 6 years (2010–2016). The results show that, in the data we have had access to, no concrete patterns can be identified regarding the type of technology or technological trends that can be used to support the social integration of individuals with disabilities. This literature review is of relevance to the identification of further research areas and to the identification of issues which have to be considered in the context of the development and implementation of technological innovations that are aimed at promoting or facilitating social inclusion of individuals with disabilities.

Using Geospatial Research Methods to Examine Resource Accessibility and Availability as it Relates to Community Participation of Individuals with Serious Mental Illnesses

Greater community participation among individuals with serious mental illnesses is associated with better psychosocial and health outcomes. Typically, studies examining community participation have utilized self-report measures and been conducted in limited settings. The introduction of methodological advances to examining community participation of individuals with serious mental illnesses has the potential to advance the science of community mental health research and invigorate the work of community psychologists in this area. This study employed an innovative geospatial approach to examine the relationship between community participation and resource accessibility (i.e., proximity) and availability (i.e., concentration) among 294 individuals utilizing community mental health services throughout the United States. Findings suggest small but significant associations between community participation and the accessibility and availability of resources needed for participation. Furthermore, findings demonstrate the importance of car access for individuals residing in both urban and non-urban settings. The methods and results presented in this study have implications for community mental health research and services and provide an illustration of ways that geospatial methodologies can be used to investigate environmental factors that impact community inclusion and participation of individuals with serious mental illnesses.

Kids in space: Measuring children's residential neighborhoods and other destinations using activity space GPS and wearable camera data

INTRODUCTION

Defining the boundary of children's 'neighborhoods' has important implications for understanding the contextual influences on child health. Additionally, insight into activities that occur outside people's neighborhoods may indicate exposures that place-based studies cannot detect. This study aimed to 1) extend current neighborhood research, using data from wearable cameras and GPS devices that were worn over several days in an urban setting; 2) define the boundary of children's neighborhoods by using leisure time activity space data; and 3) determine the destinations visited by children in their leisure time, outside their neighborhoods.

METHOD

One hundred and fourteen children (mean age 12y) from Wellington, New Zealand wore wearable cameras and GPS recorders. Residential Euclidean buffers at incremental distances were paired with GPS data (thereby identifying time spent in different places) to explore alternative definitions of neighborhood boundaries. Children's neighborhood boundary was at 500 m. A newly developed software application was used to identify 'destinations' visited outside the neighborhood by specifying space-time parameters. Image data from wearable cameras were used to determine the type of destination.

RESULTS

Children spent over half of their leisure time within 500 m of their homes. Children left their neighborhood predominantly to visit school (for leisure purposes), other residential locations (e.g. to visit friends) and food retail outlets (e.g. convenience stores, fast food outlets). Children spent more time at food retail outlets than at structured sport and in outdoor recreation locations combined.

CONCLUSION

Person-centered neighborhood definitions may serve to better represent children's everyday experiences and neighborhood exposures than previous methods based on place-based measures. As schools and other residential locations (friends and family) are important destinations outside the neighborhood, such destinations should be taken into account. The combination of image data and activity space GPS data provides a more robust approach to understanding children's neighborhoods and activity spaces.

Wide Disagreement Between Alternative Assessments of Premorbid Physical Activity: Subjective Patient and Surrogate Reports and Objective Smartphone Data

OBJECTIVES

Surrogate-decision maker and patient self-reported estimates of the distances walked prior to acute illness are subjective and may be imprecise. It may be possible to extract objective data from a patient's smartphone, specifically, step and global position system data, to quantify physical activity. The objectives were to 1) assess the agreement between surrogate-decision maker and patient self-reported estimates of distance and time walked prior to resting and daily step-count and 2) determine the feasibility of extracting premorbid physical activity (step and global position system) data from critically ill patients.

DESIGN

Prospective cohort study.

SETTING

Quaternary ICU.

PATIENTS

Fifty consecutively admitted adult patients who owned a smartphone, who were ambulatory at baseline, and who remained in ICU for more than 48 hours participated.

MEASURMENTS AND MAIN RESULTS

There was no agreement between patients and surrogates for all premorbid walking metrics (mean bias 108% [99% lower to 8,700% higher], 83% [97% to 2,100%], and 71% [96% to 1,080%], for distance, time, and steps, respectively). Step and/or global position system data were successfully extracted from 24 of 50 phones (48%; 95% CI, 35-62%). Surrogate-decision makers, but not patient self-reported, estimates of steps taken per day correlated with smartphone data (surrogates: n = 13, ρ = 0.56, p < 0.05; patients: n = 13, ρ = 0.30, p = 0.317).

CONCLUSION

There was a lack of agreement between surrogate-decision maker and patient self-reported subjective estimates of distance walked. Obtaining premorbid physical activity data from the current-generation smartphones was feasible in approximately 50% of patients.