Self-reported versus GPS-derived indicators of daily mobility in a sample of healthy older adults

Neighborhood Walkability Is Associated With Global Positioning System-Derived Community Mobility of Older Adults

BACKGROUND

Neighborhood walkability may encourage greater out-of-home travel (ie, community mobility) to support independent functioning in later life. We examined associations between a novel walkability audit index and Global Positioning System (GPS)-derived community mobility in community-dwelling older adults. We compared associations with the validated Environmental Protection Agency (EPA) National Walkability Index and further examined moderation by clinical walking speed.

METHODS

Participants were 146 older adults (Mean = 77.0 ± 6.5 years, 68% women) at baseline of a randomized trial to improve walking speed. A walkability index (range: 0-5; eg, land-use mix, crosswalks, and so on) was created using Google Street View audits within 1/8-mile of the home. Participants carried a GPS device for 5-7 days to derive objective measures of community mobility (eg, time spent out of home, accumulated distance from home).

RESULTS

Each 1 SD (~1.3-point) greater walkability audit score was associated with a median 2.16% more time spent out of home (95% confidence interval [95% CI]: 0.30-4.03, p = .023), adjusting for individual demographics/health and neighborhood socioeconomic status. For slower walkers (4-m walking speed <1 m/s), each 1 SD greater audit score was also associated with a median 4.54 km greater accumulated distance from home (95% CI: 0.01-9.07, p (interaction) = .034). No significant associations were found for the EPA walkability index.

CONCLUSIONS

Walkability immediately outside the home was related to greater community mobility, especially for older adults with slower walking speeds. Results emphasize the need to consider the joint influence of local environment and individual functioning when addressing community mobility in older populations.

Effects of a Physical Therapist Intervention on GPS Indicators of Community Mobility in Older Adults: A Secondary Analysis of a Randomized Controlled Trial

OBJECTIVE

The authors compared the effects of a standard strength and endurance intervention with a standard plus timing and coordination training intervention on community mobility measured using global positioning systems (GPS) among community-dwelling older adults in this secondary analysis of a randomized controlled trial.

METHODS

Participants were randomized to a standard or a standard plus timing and coordination training program. Community mobility was measured using the Life Space Assessment (LSA) and GPS indicators of community mobility at baseline, as well as at 12 (immediately after the intervention), 24, and 36 weeks. Linear mixed models were used for analysis.

RESULTS

There were 166 participants with GPS data at baseline, including 81 in the standard plus group and 85 in the standard group. The groups did not differ in participant characteristics or GPS measures at baseline. There were no significant within-group changes in GPS indicators of community mobility or LSA score over time, nor between-group differences of the same.

CONCLUSION

There were no significant changes in community mobility with either intervention or between-intervention differences. These findings suggest that interventions targeting physical function alone may not be sufficient to improve community mobility or participation in older adults. Future research should focus on the development of multifaceted interventions targeted to improve real-world participation.

IMPACT

The studied interventions did not significantly change community mobility measured using GPS-derived community mobility measures or self-report measures in older adults, suggesting that more comprehensive interventions may be needed to target improvements in community mobility.

Using GPS Technologies to Examine Community Mobility in Older Adults

BACKGROUND

Objective measures of community mobility are advantageous for capturing movement outside the home. Compared with subjective, self-reported techniques, global positioning system (GPS) technologies leverage passive, real-time location data to reduce recall bias and increase measurement precision. We developed methods to quantify community mobility among community-dwelling older adults and assessed how GPS-derived indicators relate to clinical measures of physical and cognitive performance.

METHODS

Participants (n = 149; M ± standard deviation [SD] = 77.1 ± 6.5 years) from the program to improve mobility in aging (PRIMA) study, a physical therapy intervention to improve walking ability, carried a GPS device for 7 days. Community mobility was characterized by assessing activity space, shape, duration, and distance. Associations between GPS-derived indicators and cognition and physical function were evaluated using Spearman correlations.

RESULTS

In adjusted models, a larger activity space, greater duration (eg, time out-of-home), and greater distance traveled from home were correlated with better 6-Minute Walk Test performance (ρ = 0.17-0.23, p's < .05). A more circular activity shape was related to poorer performance on the Trail Making Test, Part A (ρ = 0.18, p < .05). More time out-of-home and a larger activity space were correlated with faster times on the Trail Making Test, Part B (ρ = -0.18 to -0.24, p's < .05). Community mobility measures were not associated with global cognition, skilled walking, or usual gait speed.

CONCLUSION

GPS-derived community mobility indicators capture real-world activity among older adults and were correlated with clinical measures of executive function and walking endurance. These findings will guide the design of future interventions to promote community mobility.

Charting everyday activities in later life: Study protocol of the mobility, activity, and social interactions study (MOASIS)

Prominent theories of aging emphasize the importance of resource allocation processes as a means to maintain functional ability, well-being and quality of life. Little is known about which activities and what activity patterns actually characterize the daily lives of healthy older adults in key domains of functioning, including the spatial, physical, social, and cognitive domains. This study aims to gain a comprehensive understanding of daily activities of community-dwelling older adults over an extended period of time and across a diverse range of activity domains, and to examine associations between daily activities, health and well-being at the within- and between-person levels. It also aims to examine contextual correlates of the relations between daily activities, health, and well-being. At its core, this ambulatory assessment (AA) study with a sample of 150 community-dwelling older adults aged 65 to 91 years measured spatial, physical, social, and cognitive activities across 30 days using a custom-built mobile sensor ("uTrail"), including GPS, accelerometer, and audio recording. In addition, during the first 15 days, self-reports of daily activities, psychological correlates, contexts, and cognitive performance in an ambulatory working memory task were assessed 7 times per day using smartphones. Surrounding the ambulatory assessment period, participants completed an initial baseline assessment including a telephone survey, web-based questionnaires, and a laboratory-based cognitive and physical testing session. They also participated in an intermediate laboratory session in the laboratory at half-time of the 30-day ambulatory assessment period, and finally returned to the laboratory for a posttest assessment. In sum, this is the first study which combines multi-domain activity sensing and self-report ambulatory assessment methods to observe daily life activities as indicators of functional ability in healthy older adults unfolding over an extended period (i.e., 1 month). It offers a unique opportunity to describe and understand the diverse individual real-life functional ability profiles characterizing later life.

Psychometric properties of the MOBITEC-GP mobile application for real-life mobility assessment in older adults

Aim of this study was to test the reliability and validity of the life-space measures and walking speed delivered by the MOBITEC-GP app. Participants underwent several supervised walking speed assessments as well as a 1-week life-space assessment during two assessment sessions 9 days apart. Fifty-seven older adults (47.4% male, mean age= 75.3 (±5.9) years) were included in the study. The MOBITEC-GP app showed moderate to excellent test-retest reliability (ICCs between 0.584 and 0.920) and validity (ICCs between 0.468 and 0.950) of walking speed measurements of 50 meters and above and of most 1-week life-space parameters, including life-space area, time spent out-of-home, and action range. The MOBITEC-GP app for Android is a reliable and valid tool for the assessment of real-life walking speed (at distances of 50 metres and above) and life-space parameters of older adults. Future studies should look into technical issues more systematically in order to avoid invalid measurements.

Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences

Background

Behavioral science researchers are increasingly collecting detailed location data such as second-by-second GPS tracking on participants due to increased ease and affordability. While intraindividual variability has been discussed in the travel literature for decades, traditional methods designed for studying individual differences in central tendencies limit the extent to which novel questions about variability in lived experiences can be answered. Thus, new methods of quantifying behavior that focus on intraindividual variability are needed to address the context in which the behavior occurs and the location tracking data from which behavior is derived.

Methods

We propose deviations from typical paths as a data processing technique to separate individual-level typical travel behavior from a location tracking data set in order to highlight atypical travel behavior as an outcome measure.

Results

A simulated data example shows how the method works to produce deviation measures from a location dataset. Analysis of these deviations offers additional insights compared to traditional measures of maximum daily distance from home.

Conclusions

This process can be integrated into larger research questions to explore predictors of atypical behavior and potential mechanisms of behavior change.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00305-4.

Analyzing GPS Data for Psychological Research: A Tutorial

The ubiquity of location-data-enabled devices provides novel avenues for psychology researchers to incorporate spatial analytics into their studies. Spatial analytics use global positioning system (GPS) data to assess and understand mobility behavior (e.g., locations visited, movement patterns). In this tutorial, we provide a practical guide to analyzing GPS data in R and introduce researchers to key procedures and resources for conducting spatial analytics. We show readers how to clean GPS data, compute mobility features (e.g., time spent at home, number of unique places visited), and visualize locations and movement patterns. In addition, we discuss the challenges of ensuring participant privacy and interpreting the psychological implications of mobility behaviors. The tutorial is accompanied by an R Markdown script and a simulated GPS data set made available on the OSF.

Sarcopenia and its association with objectively measured life-space mobility and moderate-to-vigorous physical activity in the oldest-old amid the COVID-19 pandemic when a physical distancing policy is in force

Introduction

The oldest-old are highly vulnerable to sarcopenia. Physical distancing remains a common and effective infection-control policy to minimize the risk of COVID-19 transmission during the pandemic. Sarcopenia is known to be associated with impaired immunity. Moderate-to-vigorous physical activity (MVPA) and life-space mobility (LSM) are potential strategies for minimizing the risk of sarcopenia. However, a physical distancing policy might jeopardize the practice of MVPA and LSM. The purposes of this study were to identify the prevalence of sarcopenia and examine the association between MVPA and LSM with sarcopenia in the community-dwelling oldest-old during the COVID-19 pandemic.

Methods

This study employed a cross-sectional and observational design. The study was conducted in 10 community centres for older people in Hong Kong during the period of the COVID-19 pandemic (September to December 2020). Eligible participants were the oldest-old people aged ≥85 years, who were community-dwelling and had no overt symptoms of cognitive impairment or depression. Key variables included sarcopenia as measured by SARC-F, LSM as measured by a GPS built into smartphones, and MVPA as measured by a wrist-worn ActiGraph GT3X+. Variables were described by mean and frequency. A multiple linear regression was employed to test the hypotheses. The dependent variable was sarcopenia and the independent variables included LSM and MVPA.

Results

This study recruited 151 eligible participants. Their mean age was 89.8 years and the majority of them were female (n = 93/151, 61.6%). The prevalence of sarcopenia was 24.5% (n = 37/151) with a margin of error of 6.86%. MVPA was negatively associated with sarcopenia in older people (β = − 0.002, SE = 0.001, p = 0.029). However, LSM was not associated with sarcopenia.

Conclusion

The prevalence of sarcopenia in the community-dwelling oldest-old population is high. MVPA is negatively associated with sarcopenia. LSM is unrelated to sarcopenia. Sarcopenia should be recognized and the oldest-old with sarcopenia should be accorded priority treatment during the COVID-19 pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02861-7.

Mobility enhancement among older adults 75 + in rural areas: Study protocol of the MOBILE randomized controlled trial

BACKGROUND

Maintaining mobility in old age is crucial for healthy ageing including delaying the onset and progress of frailty. However, the extent of an individuals´ mobility relies largely on their personal, social, and environmental resources as outlined in the Life-Space Constriction Model. Recent studies mainly focus on facilitating habitual out-of-home mobility by fostering one type of resources only. The MOBILE trial aims at testing whether tablet-assisted motivational counselling enhances the mobility of community-dwelling older adults by addressing personal, social, and environmental resources.

METHODS

In the MOBILE randomized controlled trial, we plan to enrol 254 community-dwelling older adults aged 75 and older from Havelland, a rural area in Germany. The intervention group will receive a tablet-assisted motivational counselling at the participant´s home and two follow-up telephone sessions. Main focus of the counselling sessions lays on setting and adapting individual mobility goals and applying action planning and habit formation strategies by incorporating the personal social network and regional opportunities for engaging in mobility related activities. The control group will receive postal general health information. The primary mobility outcome is time out-of-home assessed by GPS (GPS.Rec2.0-App) at three points in time (baseline, after one month, and after three months for seven consecutive days each). Secondary outcomes are the size of the GPS-derived life-space convex hull, self-reported life-space mobility (LSA-D), physical activity (IPAQ), depressive symptoms (GDS), frailty phenotype, and health status (SF-12).

DISCUSSION

The MOBILE trial will test the effect of a motivational counselling intervention on out-of-home mobility in community-dwelling older adults. Novel aspects of the MOBILE trial include the preventive multi-level intervention approach in combination with easy-to-use technology. The ecological approach ensures low-threshold implementation, which increases the benefit for the people in the region.

TRIAL REGISTRATION

The MOBILE trial is prospectively registered at DRKS (Deutsches Register Klinischer Studien, German Registry of Clinical Trials) DRKS00025230 . Registered 5 May 2021.

Can probability neglect bias promote social distancing during the COVID-19 pandemic?

The effectiveness of a stay-at-home order depends on the speed of behavioral changes that are triggered by risk perception. Probability neglect bias, one of the cognitive biases, may lead people to engage in social distancing. However, there is no empirical evidence of the relationship between probability neglect bias and social distancing. This study aims to examine the relationship between individual differences in susceptibility to probability neglect bias and the level of social distancing practice during the early stages of the COVID-19 outbreak in Japan. The level of engagement in social distancing was defined as the narrowing of life-space mobility. We conducted a web-based questionnaire survey among 1000 adults living in central Tokyo, Japan, at the beginning of the pandemic outbreak. Our results show that people had a strong fear of infection in the early pandemic stages. Approximately 60% of our subjects were influenced by probability neglect bias. People susceptible to probability neglect bias engaged in social distancing more intensely than those who were not susceptible after the state of emergency was lifted.

Wearable GPS and Accelerometer Technologies for Monitoring Mobility and Physical Activity in Neurodegenerative Disorders: A Systematic Review

Neurodegenerative disorders (NDDs) constitute an increasing global burden and can significantly impair an individual's mobility, physical activity (PA), and independence. Remote monitoring has been difficult without relying on diaries/questionnaires which are more challenging for people with dementia to complete. Wearable global positioning system (GPS) sensors and accelerometers present a cost-effective and noninvasive way to passively monitor mobility and PA. In addition, changes in sensor-derived outcomes (such as walking behaviour, sedentary, and active activity) may serve as potential biomarkers of disease onset, progression, and response to treatment. We performed a systematic search across four databases to identify papers published within the past 5 years, in which wearable GPS or accelerometers were used to monitor mobility or PA in patients with common NDDs (Parkinson's disease, Alzheimer's disease, motor neuron diseases/amyotrophic lateral sclerosis, vascular parkinsonism, and vascular dementia). Disease and technology-specific vocabulary were searched singly, and then in combination, identifying 4985 papers. Following deduplication, we screened 3115 papers and retained 28 studies following a full text review. One study used wearable GPS and accelerometers, while 27 studies used solely accelerometers in NDDs. GPS-derived measures had been validated against current gold standard measures in one Parkinson's cohort, suggesting that the technology may be applicable to other NDDs. In contrast, accelerometers are widely utilised in NDDs and have been operationalised in well-designed clinical trials.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

Geographical life-space and subjective wellbeing in later life

Geographical life-space is an important factor to consider when studying subjective wellbeing of older adults. The purpose of this article is twofold: to provide an in-depth understanding of 1) the geographical life-spaces in which the lives of older adults take place and 2) the relation between life-space and experienced levels of subjective wellbeing. Seventy-six older adults (aged 65 and older) participated in our qualitative study. We applied a qualitative research approach, through combining indepth-interviews with visual life-space diagrams. Our findings show that most older adults continue to experience a high level of subjective wellbeing, regardless of the extent of their life-space. We conclude that the possibility to fulfill one's needs, even in a restricted life-space, is more conducive to maintaining subjective wellbeing than the extent of life-space itself.

Psychological Reactance to Mobility Restrictions Due to the COVID-19 Pandemic: A Japanese Population Study

In Japan, mobility restrictions were enforced by the government to abate the spread of COVID-19. The current study examined whether experiences of such mobility restrictions affected motivation for future going-out activities. To this end, we conducted a one-time online survey of 1,000 adults in Tokyo to measure going-out activities in four different time periods at once: before the spread of infection, during and after the emergency declaration, and after the end of the pandemic (future desire). In addition, to examine the impact of preferences for online services that make it easier to stay home, we measured the usage history of online services to obtain food during the mobility restriction period. Results indicated that desire for going-out activities after the end of the pandemic increased compared with those before the pandemic, particularly for leisure-related purposes. In addition, the use of online services to obtain food tended to suppress the increased desire for future going-out activities, although this effect was not significant. In conclusion, mobility restrictions resulted in motivational arousal for going-out activities after the end of the pandemic. Our findings indicate that psychological reactance plays a role in determining going-out activities in the future.

Mobility impact and well-being in later life: A multidisciplinary systematic review

In modern societies, the understanding of how active mobility affects the elderly's psycho-physical well-being is crucial to design ageing-friendly transport measures. From a multidisciplinary perspective, this systematic review points out the mobility impact on three elements of the EU Active Ageing Index: health, independence and social connectedness. By scanning four databases (Scopus, Web of Science, PubMed, and TRID), 3727 peer-reviewed papers published in the last decade were found, of which 57 met the inclusion criteria. The screening process was conducted following the PRISMA protocol and registered to the database PROSPERO, while the quality assessment was done using the Mixed Methods Appraisal Tool. More than 80% of the papers showed that an active mobility prevents psycho-physical harms, while only few papers study the relation of mobility with independence and social inclusion, to reduce the need for assistance and the related public expenditures. The findings of this review give important information both to transportation researchers and policymakers and companies, underlining the need for further research as well as investments in targeted age-friendly transport systems. The Covid-19 emergency has further underlined the importance of this issue, being the elderly one of the more disadvantaged and frailer social group.

Change in GPS-assessed walking locations following a cluster-randomized controlled physical activity trial in older adults, results from the MIPARC trial

This study employed novel GPS methods to assess the effect of a multilevel physical activity (PA) intervention on device-measured walking locations in 305 community dwelling older adults, ages 65+ (mean age = 83, 73% women). Retirement communities were randomized to a 1-year PA intervention that encouraged neighborhood walking, or to a healthy aging control condition. Total time and time spent walking in four life-space domains were assessed using GPS and accelerometer devices. The intervention increased the time spent walking as a proportion of total time spent in the Campus, Neighborhood and Beyond Neighborhood domains. Intervention effects on walking location were observed in both genders and across physical and cognitive functioning groups. Results demonstrate that an intervention providing individual, social and environmental support for walking can increase PA in larger life-space domains for a broad spectrum of older adults.

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.

Comparing GPS-Based Community Mobility Measures with Self-report Assessments in Older Adults with Parkinson's Disease

BACKGROUND

Real-life community mobility (CM) measures for older adults, especially those with Parkinson's disease (PD), are important tools when helping individuals maintain optimal function and quality of life. This is one of the first studies to compare an objective global positioning system (GPS) sensor and subjective self-report CM measures in an older clinical population.

METHODS

Over 14 days, 54 people in Ontario, Canada with early to mid-stage PD (mean age = 67.5 ± 6.3 years; 47 men; 46 retired) wore a wireless inertial measurement unit with GPS (WIMU-GPS), and completed the Life Space Assessment and mobility diaries. We assessed the convergent validity, reliability and agreement on mobility outcomes using Spearman's correlation, intraclass correlation coefficient, and Bland-Altman analyses, respectively.

RESULTS

Convergent validity was attained by the WIMU-GPS for trip frequency (rs = .69, 95% confidence interval [CI] = 0.52-0.81) and duration outside (rs = .43, 95% CI = 0.18-0.62), but not for life space size (rs = .39, 95% CI = 0.14-0.60). The Life Space Assessment exhibited floor and ceiling effects. Moderate agreements were observed between WIMU-GPS and diary for trip frequency and duration (intraclass correlation coefficients = 0.71, 95% CI = 0.51-0.82; 0.67, 95% CI = 0.42-0.82, respectively). Disagreement was more common among nonretired individuals.

CONCLUSIONS

WIMU-GPS could replace diaries for trip frequency and duration assessments in older adults with PD. Both assessments are best used for retired persons. However, the Life Space Assessment may not reflect actual mobility.

Prediction of human active mobility in rural areas: development and validity tests of three different approaches

BACKGROUND/AIM

Active mobility may play a relevant role in the assessment of environmental exposures (e.g. traffic-related air pollution, livestock emissions), but data about actual mobility patterns are work intensive to collect, especially in large study populations, therefore estimation methods for active mobility may be relevant for exposure assessment in different types of studies. We previously collected mobility patterns in a group of 941 participants in a rural setting in the Netherlands, using week-long GPS tracking. We had information regarding personal characteristics, self-reported data regarding weekly mobility patterns and spatial characteristics. The goal of this study was to develop versatile estimates of active mobility, test their accuracy using GPS measurements and explore the implications for exposure assessment studies.

METHODS

We estimated hours/week spent on active mobility based on personal characteristics (e.g. age, sex, pre-existing conditions), self-reported data (e.g. hours spent commuting per bike) or spatial predictors such as home and work address. Estimated hours/week spent on active mobility were compared with GPS measured hours/week, using linear regression and kappa statistics.

RESULTS

Estimated and measured hours/week spent on active mobility had low correspondence, even the best predicting estimation method based on self-reported data, resulted in a R² of 0.09 and Cohen's kappa of 0.07. A visual check indicated that, although predicted routes to work appeared to match GPS measured tracks, only a small proportion of active mobility was captured in this way, thus resulting in a low validity of overall predicted active mobility.

CONCLUSIONS

We were unable to develop a method that could accurately estimate active mobility, the best performing method was based on detailed self-reported information but still resulted in low correspondence. For future studies aiming to evaluate the contribution of home-work traffic to exposure, applying spatial predictors may be appropriate. Measurements still represent the best possible tool to evaluate mobility patterns.

The development and validation of a prototype mobility tracker for assessing the life space mobility and activity participation of older adults

BACKGROUND

There is increasing interest in examining the life space mobility and activity participation of older adults in the community using sensor technology. Objective data from these technologies may overcome the limitations of self-reported surveys especially in older adults with age-associated cognitive impairment. This paper describes the development and validation of a prototype hybrid mobility tracker for assessing life space mobility and out-of-home activities amongst 33 community-ambulant older adults in Singapore.

METHODS

A hybrid mobility tracker was developed by combining a passive Global Positioning System logger, tri-axial accelerometer and radio-frequency identification. Objective measures of life space, derived from 1 week of tracking data using Geographic Information Systems, were the maximum Euclidean distance from home (Max Euclid) and the area of the minimum convex polygon surrounding all GPS waypoints (MCP area). Out-of-home activities were quantified by visually identifying the total number of activity nodes, or places where participants spent ≥5 min, from mobility tracks. Self-reported measure of life space in 4 weeks was obtained using the University of Alabama at Birmingham Study of Life Space Assessment (UAB-LSA) questionnaire. Self-reported out-of-home activities were recorded daily in a travel diary for 1 week. Bivariate correlations were used to examine convergent validity between objective and subjective measures of life space and out-of-home activities.

RESULTS

The mean age of participants was 69.2 ± 7.1 years. The mean UAB-LSA total score was 79.1 ± 17.4. The median (range) Max Euclid was 2.44 km (0.26-7.50) per day, and the median (range) MCP area was 3.31 km² (0.03-34.23) per day. The UAB-LSA total score had good correlation with Max Euclid (r = 0.51, p = 0.002), and moderate correlation with MCP area (r = 0.46, p = 0.007). The median (range) total number of activity nodes measured by tracker of 20 (8-47) per week had a good correlation with the total activity count recorded in the travel diaries of 15 (6-40) per week (r = 0.52, p = 0.002).

CONCLUSIONS

The tracking system developed to understand out-of-home travel was feasible and reliable. Comparisons with the UAB-LSA and travel diaries showed that it provided reliable and valid spatiotemporal data to assess the life space mobility and activity participation of older adults.

Merging self-reported with technically sensed data for tracking mobility behavior in a naturalistic intervention study. Insights from the GISMO study

Sound exposure data are central for any intervention study. In the case of utilitarian mobility, where studies cannot be conducted in controlled environments, exposure data are commonly self‐reported. For short‐term intervention studies, wearable devices with location sensors are increasingly employed. We aimed to combine self‐reported and technically sensed mobility data, in order to provide more accurate and reliable exposure data for GISMO, a long‐term intervention study. Through spatio‐temporal data matching procedures, we are able to determine the amount of mobility for all modes at the best possible accuracy level. Self‐reported data deviate ±10% from the corrected reference. Derived modal split statistics prove high compliance to the respective recommendations for the control group (CG) and the two intervention groups (IG‐PT, IG‐C). About 73.7% of total mileage was travelled by car in CG. This share was 10.3% (IG‐PT) and 9.7% (IG‐C), respectively, in the intervention groups. Commuting distances were comparable in CG and IG, but annual mean travel times differ between x¯  = 8,458 min (σ = 6,427 min) for IG‐PT, x¯  = 8,444 min (σ = 5,961 min) for IG‐C, and x¯  = 5,223 min (σ = 5,463 min) for CG. Seasonal variabilities of modal split statistics were observable. However, in IG‐PT and IG‐C no shift toward the car occurred during winter months. Although no perfect single‐method solution for acquiring exposure data in mobility‐related, naturalistic intervention studies exists, we achieved substantially improved results by combining two data sources, based on spatio‐temporal matching procedures.

Assessing Older Adults' Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators

Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived from GPS data, despite lacking consensus regarding thresholds to be used to extract those as well as limited knowledge about their validity. Using 7 days of GPS and diary data of 35 older adults, we make the following three main contributions. First, we perform a sensitivity analysis to investigate how using spatial and temporal thresholds to compute TOH and #ALs affects the agreement between self-reported and GPS-based indicators. Second, we show how daily self-reported and GPS-derived mobility indicators are compared. Third, we explore whether the type and duration of self-reported activity events are related to the degree of correspondence between reported and GPS event. Highest indicator agreement was found for temporal interpolation (Tmax) of up to 5 h for both indicators, a radius (Dmax) to delineate home between 100 and 200 m for TOH, and for #ALs a spatial extent (Dmax) between 125 and 200 m, and temporal extent (Tmin) between 5 and 6 min to define an activity location. High agreement between self-reported and GPS-based indicators is obtained for TOH and moderate agreement for #ALs. While reported event type and duration impact on whether a reported event has a matching GPS event, indoor and outdoor events are detected at equal proportions. This work will help future studies to choose optimal threshold settings and will provide knowledge about the validity of mobility indicators.

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.

Location monitoring of physical activity and participation in community dwelling older people: a scoping review

Background: Community participation and physical activity are important for the health of older adults. This review aimed to identify studies which have measured physical activity and community participation in older adults using Global positioning systems.Materials and methods: This scoping review searched key databases using predetermined subject headings and keywords. Two independent reviewers selected studies based on a systematic procedure following current guidelines. Inclusion criteria for studies were: participants aged over 50 years living independently in the community that reported on physical activity and/or participation inclusive of physical and social activity, and including a quantitative measure of location. All searches were limited to English. The primary review question was; "What studies have monitored the location of physical activity in an older population?" with secondary enquiries investigating the types of global positioning system devices, barriers and facilitators for activity and community participation.Results: The search returned 3723 articles (following duplicate removal) and 45 met the inclusion criteria. Studies from 12 countries published over a 12-year period were included. Participants were mainly healthy (n = 23) followed by having a cognitive impairment (n = 10). There were 14 different global positioning system devices used, assessing a variety of outcomes (n = 24). Seventeen studies identified facilitators and barriers to participation and physical activity in an older population. The most common facilitators were safety, weather and access to multi-purpose facilities. The most common barriers were weather, safety, low income/high deprivation areas and use of motor vehicles.Conclusion: This scoping review identified a variety of locational monitoring of older people using global positioning devices. Global positioning systems are a valuable tool to obtain accurate activity locations of older people. There is a need for clear guidelines regarding the use of global positioning system devices and specified outcomes in primary research to enable comparison across studies.Implications for rehabilitationPhysical activity and community participation are vital for healthy ageing.The environment can act as a facilitator or barrier to physical activity and community participation for older adults.Interventions need to target facilitators (weather, safety, facility access and social components) to maximize physical activity and community participation in older people.Interventions should be designed to reduce the barriers (weather, safety, low income and motor vehicle dependency) that prevent older adults from actively participating in their community.