‘Friendly’ and ‘noisy surveillance’ through MapMyRun during the COVID-19 pandemic

Fletcher, Olivia

doi:10.1016/j.geoforum.2022.05.004

Cited by 6 publications

(3 citation statements)

References 45 publications

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“…As Pink and Fors argue in cultural geographies : “while self‐tracking technologies might appear on the surface to belong to a quantified world of measurement … they participate considerably in how people ‘feel’ or sense in their everyday environments” (2017, p. 376). Moreover, for some runners, studies show how this numerical data has a ‘social afterlife’ on social media platforms designed specifically for exhibiting ‘running sessions’ but also for sustaining social bonds, connections and surveillance, friendly or otherwise (Fletcher, 2022; Little, 2017).…”

Section: Technology and Objectsmentioning

confidence: 99%

Geographies of running cultures and practices

Simon

Larsen

2022

Geography Compass

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Running is inherently geographical, with spaces, places, movement and bodies central to the practice. Running has captured the geographical imagination over the last decade and this paper reaches across such work to provide a state‐of‐the‐art synthesis of the geographies of running. The review is structured around six key themes that characterise contemporary running geographies and demonstrate the value geography and running bring to each other: (1) different running practices; (2) theorising and researching running; (3) senses, experiences and embodiment; (4) running, space and place; (5) events; and (6) technologies and objects. The paper concludes by considering what is next for running geographies by highlighting three new avenues: (1) further engagement with digital geographies; (2) the runnability of places; and (3) diversifying who does running geography and who it studies.

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Section: Technology and Objectsmentioning

confidence: 99%

Geographies of running cultures and practices

Simon

Larsen

2022

Geography Compass

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“…Currently, there are many popular apps that focus on these lifestyle behaviors and have gained tremendous popularity including MapMyRun that focuses on tracking physical activity and MyFitnessPal, another fitness app focused on tracking diet and calorie intake [ 19 , 20 ]. Although these apps address a number of the lifestyle behaviors (mentioned in the previous paragraphs) that have been linked to the likelihood of developing dementia, few apps have been designed to target these functions specifically for persons with or at risk of developing dementia.…”

Section: Introductionmentioning

confidence: 99%

mHealth Apps for Dementia, Alzheimer Disease, and Other Neurocognitive Disorders: Systematic Search and Environmental Scan

Ali,

Alizai,

Hagos

et al. 2024

JMIR Mhealth Uhealth

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Background: Lifestyle behaviors including exercise, sleep, diet, stress, mental stimulation, and social interaction have been shown to have a significant impact on the likelihood of developing dementia. mHealth apps have been valuable tools in addressing these lifestyle behaviors for general health and wellbeing, and there is growing recognition of their potential use as a tool focusing on brain-health and dementia prevention. In order to design effective apps that are both evidence-based and safeguard user data, app creators must address the gaps observed in the current state of dementia-related mHealth apps.Objective: Describe the scope of available apps intended for use by the general public relating to dementia prevention and risk factors, highlighting gaps and suggesting a path forward for future development.Methods: A systematic search of mobile app stores and environmental scan of peer-reviewed literature, dementia/Alzheimer's association/advocacy websites, and websites accessed using a browser search was conducted from October 19, 2022 to November 2, 2022. A total of 1044 mHealth apps were retrieved across this comprehensive array of sources. After screening, 152 apps met the inclusion criteria and were coded by two independent reviewers using an extraction framework. The extraction framework was adapted using the Silberg scale, other scoping reviews of mHealth apps for similar populations, and background research of modifiable dementia risk factors. Coded elements included: evidence-based and expert credibility, app features, lifestyle element(s) of focus, and privacy/security. Results:Of the final selection of apps that met final selection criteria, 88 (57.9%) addressed the modifiable lifestyle behaviors associated with reducing dementia risk. However, the majority of these apps only addressed one lifestyle behavior-with mental stimulation being the most frequently addressed of the lifestyle behaviors investigated in this study. The majority of apps scored 2 points out of 9 on the Silberg scale, with a mean score of 2.4 points. App information was not disclosed by the majority of the 152 apps, as 120 apps did not disclose expert consultation (78.9%), 125 did not disclose evidence-based information (82.2%), 146 did not disclose author credentials (96.1%), and 134 apps did not disclose their information sources (88.2%). Moreover, 105 apps (69.2%) did not disclose adherence to data privacy/security practices or lack thereof. Conclusions:There is an opportunity for mHealth apps to support individuals in regularly engaging in behaviors linked to reducing dementia risk. While there is a market for these products, there is a lack of dementia-related apps focused on multiple lifestyle behaviors. There are currently gaps in rigor of app development regarding evidence-base and credibility of apps, as well as adherence to data privacy/security standards. Addressing these observed gaps-such as through following established and validated guidelines-will be necessary for dementia-related apps to be effective and adva...

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“…2 | SELF-TRACKING, AUTO -NETNOGRAPHY AND FAT STUDIES 2.1 | Materialities of self-tracking Key work on self-tracking has explored people's experiences of using self-tracking technologies to track their health for self-optimisation (Lupton, 2017;Sanders, 2017). This has been theorised in relation to quantified health targets and the role of self and social surveillance (Ajana, 2017;Fletcher, 2022;Fotopoulou & O'Riordan, 2017). The embodied and sensorial experiences of self-tracking have emerged as a theme within self-tracking research (Thorpe et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Blurring boundaries: Researching self‐tracking and body size through auto‐netnography

Olivia

2023

Area

Self Cite

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In this paper, I use auto‐netnography data to explore my experiences of self‐tracking with my Apple watch to uncover some of the ways in which the materiality of self‐tracking led me to experience an intensified form of surveillance around my body. The paper contributes to literature within digital geographies which considers the blurring of online and offline boundaries. I consider this in relation to auto‐netnography and auto‐ethnography to question the distinction between the two. I contribute to debates in fat studies around the blurring of the personal and researcher identity when supporting the Health at Every Size Approach, furthering these debates by exemplifying how the materiality of self‐tracking can intensify feelings of guilt and shame when researching the body. The paper concludes with some ethical recommendations for self‐care in the research process, arguing that future research should consider how the researcher should hold space to deal with the unintended emotional consequences that may come from research.

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‘Friendly’ and ‘noisy surveillance’ through MapMyRun during the COVID-19 pandemic

Cited by 6 publications

References 45 publications

Geographies of running cultures and practices

Geographies of running cultures and practices

mHealth Apps for Dementia, Alzheimer Disease, and Other Neurocognitive Disorders: Systematic Search and Environmental Scan

Blurring boundaries: Researching self‐tracking and body size through auto‐netnography

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