scholarly journals The Unanticipated Challenges Associated With Implementing an Observational Study Protocol in a Large-Scale Physical Activity and Global Positioning System Data Collection (Preprint)

2017 ◽  
Author(s):  
Paul McCrorie ◽  
David Walker ◽  
Anne Ellaway
Keyword(s):  
Physical Activity ◽  
Data Collection ◽  
Global Positioning System ◽  
Large Scale ◽  
Gps Data ◽  
Positioning System ◽  
Consent Forms ◽  
Global Positioning ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity

BACKGROUND Large-scale primary data collections are complex, costly, and time-consuming. Study protocols for trial-based research are now commonplace, with a growing number of similar pieces of work being published on observational research. However, useful additions to the literature base are publications that describe the issues and challenges faced while conducting observational studies. These can provide researchers with insightful knowledge that can inform funding proposals or project development work. OBJECTIVES In this study, we identify and reflectively discuss the unforeseen or often unpublished issues associated with organizing and implementing a large-scale objectively measured physical activity and global positioning system (GPS) data collection. METHODS The SPACES (Studying Physical Activity in Children’s Environments across Scotland) study was designed to collect objectively measured physical activity and GPS data from 10- to 11-year-old children across Scotland, using a postal delivery method. The 3 main phases of the project (recruitment, delivery of project materials, and data collection and processing) are described within a 2-stage framework: (1) intended design and (2) implementation of the intended design. RESULTS Unanticipated challenges arose, which influenced the data collection process; these encompass four main impact categories: (1) cost, budget, and funding; (2) project timeline; (3) participation and engagement; and (4) data challenges. The main unforeseen issues that impacted our timeline included the informed consent process for children under the age of 18 years; the use of, and coordination with, the postal service to deliver study information and equipment; and the variability associated with when participants began data collection and the time taken to send devices and consent forms back (1-12 months). Unanticipated budgetary issues included the identification of some study materials (AC power adapter) not fitting through letterboxes, as well as the employment of fieldworkers to increase recruitment and the return of consent forms. Finally, we encountered data issues when processing physical activity and GPS data that had been initiated across daylight saving time. CONCLUSIONS We present learning points and recommendations that may benefit future studies of similar methodology in their early stages of development.

scholarly journals Concurrent Measurement of Global Positioning System and Event-Based Physical Activity Data: A Methodological Framework for Integration

2020 ◽  
pp. 1-14
Author(s):  
Anna M.J. Iveson ◽  
Malcolm H. Granat ◽  
Brian M. Ellis ◽  
Philippa M. Dall
Keyword(s):  
Physical Activity ◽  
Outcome Measures ◽  
Global Positioning System ◽  
Gps Data ◽  
Positioning System ◽  
Activity Data ◽  
Data Set ◽  
Physical Activity Data ◽  
Global Positioning ◽  
Event Based

Objective: Global positioning system (GPS) data can add context to physical activity data and have previously been integrated with epoch-based physical activity data. The current study aimed to develop a framework for integrating GPS data and event-based physical activity data (suitable for assessing patterns of behavior). Methods: A convenience data set of concurrent GPS (AMOD) and physical activity (activPAL) data were collected from 69 adults. The GPS data were (semi)regularly sampled every 5 s. The physical activity data output was presented as walking events, which are continuous periods of walking with a time-stamped start time and duration (to nearest 0.1 s). The GPS outcome measures and the potential correspondence of their timing with walking events were identified and a framework was developed describing data integration for each combination of GPS outcome and walking event correspondence. Results: The GPS outcome measures were categorized as those deriving from a single GPS point (e.g., location) or from the difference between successive GPS points (e.g., distance), and could be categorical, scale, or rate outcomes. Walking events were categorized as having zero (13% of walking events, 3% of walking duration), or one or more (52% of walking events, 75% of walking duration) GPS points occurring during the event. Additionally, some walking events did not have GPS points suitably close to allow calculation of outcome measures (31% of walking events, 22% of walking duration). The framework required different integration approaches for each GPS outcome type, and walking events containing zero or more than one GPS points.

scholarly journals Estimating experienced racial segregation in US cities using large-scale GPS data

2021 ◽  
Vol 118 (46) ◽  
pp. e2026160118
Author(s):  
Susan Athey ◽  
Billy Ferguson ◽  
Matthew Gentzkow ◽  
Tobias Schmidt
Keyword(s):  
Global Positioning System ◽  
Large Scale ◽  
Racial Segregation ◽  
Gps Data ◽  
Income Mobility ◽  
Positioning System ◽  
Global Positioning ◽  
Highly Correlated ◽  
Transit Use ◽  
Us Cities

We estimate a measure of segregation, experienced isolation, that captures individuals’ exposure to diverse others in the places they visit over the course of their days. Using Global Positioning System (GPS) data collected from smartphones, we measure experienced isolation by race. We find that the isolation individuals experience is substantially lower than standard residential isolation measures would suggest but that experienced isolation and residential isolation are highly correlated across cities. Experienced isolation is lower relative to residential isolation in denser, wealthier, more educated cities with high levels of public transit use and is also negatively correlated with income mobility.

scholarly journals Monitoring Mobility in Older Adults Using Global Positioning System (GPS) Watches and Accelerometers: A Feasibility Study

2009 ◽  
Vol 17 (4) ◽  
pp. 455-467 ◽  
Author(s):  
Sandra C. Webber ◽  
Michelle M. Porter
Keyword(s):  
Older Adults ◽  
Data Collection ◽  
Global Positioning System ◽  
Extended Period ◽  
Gps Data ◽  
Positioning System ◽  
Mobility Patterns ◽  
Community Mobility ◽  
Global Positioning ◽  
Indoor And Outdoor Environments

This exploratory study examined the feasibility of using Garmin global positioning system (GPS) watches and ActiGraph accelerometers to monitor walking and other aspects of community mobility in older adults. After accuracy at slow walking speeds was initially determined, 20 older adults (74.4 ± 4.2 yr) wore the devices for 1 day. Steps, distances, and speeds (on foot and in vehicle) were determined. GPS data acquisition varied from 43 min to over 12 hr, with 55% of participants having more than 8 hr between initial and final data-collection points. When GPS data were acquired without interruptions, detailed mobility information was obtained regarding the timing, distances covered, and speeds reached during trips away from home. Although GPS and accelerometry technology offer promise for monitoring community mobility patterns, new GPS solutions are required that allow for data collection over an extended period of time between indoor and outdoor environments.

The Distribution of Hospitality Services in Uyo Urban, Nigeria

2018 ◽  
pp. 137-150
Author(s):  
Violet Bassey Eneyo
Keyword(s):  
Data Collection ◽  
Global Positioning System ◽  
Central Area ◽  
Positioning System ◽  
Nearest Neighbour ◽  
Global Positioning ◽  
Neighbour Analysis

This paper examines the distribution of hospitality services in Uyo Urban, Nigeria. GIS method was the primary tool used for data collection. A global positioning system (GPS) Garmin 60 model was used in tracking the location of 102 hospitality services in the study area. One hypothesis was stated and tested using the nearest neighbour analysis. The finding shows evidence of clustering of the various hospitality services. The tested hypothesis further indicated that hospitality services clustered in areas that guarantee a sustainable level of patronage to maximize profit. Thus, the hospitality services clustered in selected streets in the metropolis while limited numbers were found outside the city’s central area.

scholarly journals Parking Places to Moped-Style Scooter Sharing Services Using GIS Location-Allocation Models and GPS Data

2021 ◽  
Vol 10 (4) ◽  
pp. 230
Author(s):  
Onel Pérez-Fernández ◽  
Juan Carlos García-Palomares
Keyword(s):  
Global Positioning System ◽  
Catchment Area ◽  
Public Spaces ◽  
Gps Data ◽  
Positioning System ◽  
Urban Centers ◽  
Location Allocation ◽  
Global Positioning ◽  
The City

Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.

scholarly journals Associations between time spent in green areas and physical activity among late middle-aged adults

2016 ◽  
Vol 11 (3) ◽  
Author(s):  
Bart Dewulf ◽  
Tijs Neutens ◽  
Delfien Van Dyck ◽  
Ilse De Bourdeaudhuij ◽  
Steven Broekx ◽  
...  
Keyword(s):  
Physical Activity ◽  
Global Positioning System ◽  
Individual Characteristics ◽  
Positioning System ◽  
Accelerometer Data ◽  
Middle Aged ◽  
Physically Active ◽  
Global Positioning ◽  
Green Areas ◽  
Middle Aged Adults

Physical activity is an important facilitator for health and wellbeing, especially for late middle-aged adults, who are more susceptible to cardiovascular diseases. Physical activity performed in green areas is supposed to be particularly beneficial, so we studied whether late middle- aged adults are more active in green areas than in non-green areas and how this is influenced by individual characteristics and the level of neighbourhood greenness. We tracked 180 late middle-aged (58 to 65 years) adults using global positioning system and accelerometer data to know whether and where they were sedentary or active. These data were combined with information on land use to obtain information on the greenness of sedentary and active hotspots. We found that late middle-aged adults are more physically active when spending more time in green areas than in non-green areas. Spending more time at home and in non-green areas was found to be associated with more sedentary behaviour. Time spent in non-green areas was found to be related to more moderate-to-vigorous physical activity (MVPA) for males and to less MVPA for females. The positive association between time spent in green areas and MVPA was the strongest for highly educated people and for those living in a green neighbourhood. This study shows that the combined use of global positioning system and accelerometer data facilitates understanding of where people are sedentary or physically active, which can help policy makers encourage activity in this age cohort.

Evaluation of CORSIM Car-Following Model by Using Global Positioning System Field Data

2000 ◽  
Vol 1710 (1) ◽  
pp. 114-121 ◽  
Author(s):  
Sastry Chundury ◽  
Brian Wolshon
Keyword(s):  
Data Collection ◽  
Global Positioning System ◽  
Field Data ◽  
Goodness Of Fit ◽  
Positioning System ◽  
Goodness Of Fit Test ◽  
Distance Information ◽  
Car Following ◽  
Wide Range ◽  
Global Positioning

It has been recognized that CORSIM (and its constituent program, NETSIM) is one of the most widely used and effective computer programs for the simulation of traffic behavior on urban transportation networks. Its popularity is due in large part to the high level of detail incorporated into its modeling routines. However, the car-following models, used for the simulation of driver behavior in the program, have not been formally calibrated or validated. Since the model has performed well in a wide range of applications for so many years, it has always been assumed to have an implied validity. This study evaluated the NETSIM car-following models by comparing their results with field data. Car-following field data were collected using a new data collection system that incorporates new Global Positioning System and geographic information system technologies to improve the accuracy, ease, speed, and cost-effectiveness of car-following data collection activities. First, vehicle position and speed characteristics were collected under field conditions. Then simulated speeds and distances were based on identical lead vehicle actions using NETSIM car-following equations. Comparisons of simulated and field data were completed using both graphical and statistical methods. Although some differences were evident in the graphical comparisons, the graphs overall indicated a reasonable match between the field and simulated vehicle movements. Three statistical tests, including a goodness-of-fit test, appear to support these subjective conclusions. However, it was also found that definitive statistical conclusions were difficult to draw since no single test was able to compare the sets of speed and distance information on a truly impartial basis.

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