ArticleHeliyon2023
Evaluation of a smartphone-based methodology that integrates long-term tracking of mobility, place experiences, heart rate variability, and subjective well-being.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study presents MyGävle, a smartphone application that merge long-term tracking of mobility data, heart rate variability and subjective and objective well-being records. Developed to address the challenges faced in researching healthy and sustainable lifestyles, this app serves as a pioneering implementation of Real-life Long-term Methodology (ReaLM). After eight months' use by 257 participants from Gävle (Sweden), we evaluate the completeness, accuracy, validity, and consistency of all data collected. MyGävle produced remarkable results as a ReaLM method. On average, it precisely tracked participants daily locations for approximately 8 h and accurately collected heart-rate variability values throughout the day (12 h) and night (6 h). Participants reported 5115 subjective place experiences (ranging from 160 to 120 per week) and seasonal participation, although declining, is accurate. Our findings indicate that the amount of data collected through smartphone sensors, fitness wristbands and in-app questionnaires is consistent enough to be leveraged for integrated assessments of habits, environmental exposure, and subjective and physiological well-being. Yet, considerable variation exists across individuals; thus diagnostic analysis must precede use of these datasets in any particular research endeavors. By doing so we can maximise the potential of ReaLM research to delve into real life conditions conducive to healthy living habits while also considering broader sustainability goals.
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