Dataset Information

Mapping urban greenspace use from mobile phone GPS data.

ABSTRACT: Urban greenspace is a valuable component of the urban form that has the potential to improve the health and well-being of residents. Most quantitative studies of relationships between health and greenspace to date have investigated associations only with what greenspace exists in the local environment (i.e. provision of greenspace), rather than to what extent it is used. This is due to the difficulty of obtaining usage data in large amounts. In recent years, GPS functionality integrated into mobile phones has provided a potential solution to this problem by making it possible to track which parts of the environment people experience in their day-to-day lives. In this paper, we demonstrate a method to derive cleaned, trip-level information from raw GPS data collected by a mobile phone app, then use this data to investigate the characteristics of trips to urban greenspace by residents of the city of Sheffield, UK. We find that local users of the app spend an average of an hour per week visiting greenspaces, including around seven trips per week and covering a total distance of just over 2.5 km. This may be enough to provide health benefits, but is insufficient to provide maximal benefits. Trip characteristics vary with user demographics: ethnic minority users and users from more socioeconomically deprived areas tend to make shorter trips than White users and those from less deprived areas, while users aged 34 years and over make longer trips than younger users. Women, on average, make more frequent trips than men, as do those who spent more time outside as a child. Our results suggest that most day-to-day greenspace visits are incidental, i.e. travelling through rather than to greenspace, and highlight the importance of including social and cultural factors when investigating who uses and who benefits from urban greenspace.

SUBMITTER: Mears M

PROVIDER: S-EPMC8262795 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAs successful malaria control programmes re-orientate towards elimination, the identification of transmission foci, targeting of attack measures to high-risk areas and management of importation risk become high priorities. When resources are limited and transmission is varying seasonally, approaches that can rapidly prioritize areas for surveillance and control can be valuable, and the most appropriate attack measure for a particular location is likely to differ depending on whether it exports or imports malaria infections.Methods/resultsHere, using the example of Namibia, a method for targeting of interventions using surveillance data, satellite imagery, and mobile phone call records to support elimination planning is described. One year of aggregated movement patterns for over a million people across Namibia are analyzed, and linked with case-based risk maps built on satellite imagery. By combining case-data and movement, the way human population movements connect transmission risk areas is demonstrated. Communities that were strongly connected by relatively higher levels of movement were then identified, and net export and import of travellers and infection risks by region were quantified. These maps can aid the design of targeted interventions to maximally reduce the number of cases exported to other regions while employing appropriate interventions to manage risk in places that import them.ConclusionsThe approaches presented can be rapidly updated and used to identify where active surveillance for both local and imported cases should be increased, which regions would benefit from coordinating efforts, and how spatially progressive elimination plans can be designed. With improvements in surveillance systems linked to improved diagnosis of malaria, detailed satellite imagery being readily available and mobile phone usage data continually being collected by network providers, the potential exists to make operational use of such valuable, complimentary and contemporary datasets on an ongoing basis in infectious disease control and elimination.

Project description:BackgroundMobile apps are a popular strategy for reducing mobile phone use and preventing maladaptive mobile phone use (MMPU). Previous research efforts have been made to understand the features of apps that have the potential to reduce mobile phone use and MMPU. However, there has been a lack of a comprehensive examination of the effectiveness of such apps and their features.ObjectiveThis paper investigated existing apps designed to reduce mobile phone use and prevent MMPU and examined the evidence of their effectiveness. The research aimed to provide a comprehensive analysis of app features that can reduce mobile phone use and MMPU, while also assessing their effectiveness. In addition, we explored users' perceptions of these apps and the various features the apps offer to understand potential adoption issues and identify opportunities.MethodsThis study used 3 methods: a review of scientific evidence, content analysis, and sentiment analysis.ResultsOur study comprehensively examine the common features of 13 apps designed to reduce mobile phone use. We extracted and classified the features into 7 types: self-tracking, social tracking, goal setting, blocking, gamification, simplification, and assessment. The effectiveness of these apps in reducing mobile phone use and MMPU varied from weak to strong. On the basis of content analysis, self-tracking and goal setting were the most frequently used features, whereas gamification and assessment were used the least frequently. The intervention strategies that effectively reduce mobile phone use and MMPU included using grayscale mode, app limit features, and mixed interventions. Overall, users tended to accept these apps, as indicated by sentiment scores ranging from 61 to 86 out of 100.ConclusionsThis study demonstrates that app-based management has the potential to reduce mobile phone use and MMPU. However, further research is required to evaluate the effectiveness of app-based interventions. Collaborations among researchers, app developers, mobile phone manufacturers, and policy makers could enhance the process of delivering, evaluating, and optimizing apps aimed at reducing mobile phone use and MMPU.

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Mapping urban greenspace use from mobile phone GPS data.

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