Data-Driven Wellness: A Deep Dive into Mobile Health using Apple
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| Natura: | Recurso digital |
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2025
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| _version_ | 1866901733299453952 |
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| author | Jain, Teesta Sefton, Zoe Natarajan, Vijayalakshmi |
| author_facet | Jain, Teesta Sefton, Zoe Natarajan, Vijayalakshmi |
| contents | <p><span>Smartphones and their respective applications are utilized by millions at astronomical rates [1]. This pilot study, a component of the larger project, investigated the relationship between physical activity and sleep [4] in young adults by employing the Apple Watch, one of the most common smart devices on the market [1,3], highlighting its positive impact on student equity through increased accessibility, diverse representation, student empowerment, and equal opportunity for research experience.<span> </span>By doing so socioeconomic and geographical barriers to research involvement are removed [2], actively encouraging the inclusion of participants from diverse backgrounds by focusing on identifying health disparities within specific communities. <a name="_Hlk190686116"></a>Students are empowered through data-driven decision-making, learning to analyze personal health metrics and making informed lifestyle choices as physical activity influences sleep through various biological mechanisms, including decreased insulin resistance, reduced inflammation, and regulation of cardiac rhythm. Conversely, sleep deprivation can negatively impact physical and academic performance. Data collected from five young adults (n=5) over a seven-day period both day and night, tracking both step count and sleep duration using Apple Health data. Preliminary results indicated a complex relationship (R<sup>2</sup>=0.818). While no direct correlation was found between daily step count and total sleep time across all participants, some individuals exhibited a connection between total sleep time and next-day step count (R<sup>2</sup>=0.6728). This suggests that while overall activity levels may not directly influence sleep duration, the quality of sleep might play a role in subsequent activity levels. Students are empowered through data-driven decision-making, learning to analyze personal health metrics thus making informed lifestyle choices.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15595966 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Data-Driven Wellness: A Deep Dive into Mobile Health using Apple Jain, Teesta Sefton, Zoe Natarajan, Vijayalakshmi <p><span>Smartphones and their respective applications are utilized by millions at astronomical rates [1]. This pilot study, a component of the larger project, investigated the relationship between physical activity and sleep [4] in young adults by employing the Apple Watch, one of the most common smart devices on the market [1,3], highlighting its positive impact on student equity through increased accessibility, diverse representation, student empowerment, and equal opportunity for research experience.<span> </span>By doing so socioeconomic and geographical barriers to research involvement are removed [2], actively encouraging the inclusion of participants from diverse backgrounds by focusing on identifying health disparities within specific communities. <a name="_Hlk190686116"></a>Students are empowered through data-driven decision-making, learning to analyze personal health metrics and making informed lifestyle choices as physical activity influences sleep through various biological mechanisms, including decreased insulin resistance, reduced inflammation, and regulation of cardiac rhythm. Conversely, sleep deprivation can negatively impact physical and academic performance. Data collected from five young adults (n=5) over a seven-day period both day and night, tracking both step count and sleep duration using Apple Health data. Preliminary results indicated a complex relationship (R<sup>2</sup>=0.818). While no direct correlation was found between daily step count and total sleep time across all participants, some individuals exhibited a connection between total sleep time and next-day step count (R<sup>2</sup>=0.6728). This suggests that while overall activity levels may not directly influence sleep duration, the quality of sleep might play a role in subsequent activity levels. Students are empowered through data-driven decision-making, learning to analyze personal health metrics thus making informed lifestyle choices.</span></p> |
| title | Data-Driven Wellness: A Deep Dive into Mobile Health using Apple |
| url | https://doi.org/10.5281/zenodo.15595966 |