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Multi-modal data collection for measuring health, behavior, and living environment of large-scale participant cohorts.
Wu, Congyu; Fritz, Hagen; Bastami, Sepehr; Maestre, Juan P; Thomaz, Edison; Julien, Christine; Castelli, Darla M; de Barbaro, Kaya; Bearman, Sarah Kate; Harari, Gabriella M; Cameron Craddock, R; Kinney, Kerry A; Gosling, Samuel D; Schnyer, David M; Nagy, Zoltan.
Affiliation
  • Wu C; Department of Psychology, University of Texas at Austin, 108 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Fritz H; Department of Civil, Environmental, and Architectural Engineering, University of Texas at Austin, 301 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Bastami S; Department of Civil, Environmental, and Architectural Engineering, University of Texas at Austin, 301 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Maestre JP; Department of Civil, Environmental, and Architectural Engineering, University of Texas at Austin, 301 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Thomaz E; Department of Electrical and Computer Engineering, University of Texas at Austin, 2501 Speedway, Austin, Texas, 78712, USA.
  • Julien C; Department of Electrical and Computer Engineering, University of Texas at Austin, 2501 Speedway, Austin, Texas, 78712, USA.
  • Castelli DM; Department of Kinesiology and Health Education, University of Texas at Austin, 2109 San Jacinto Blvd, Austin, Texas, 78712, USA.
  • de Barbaro K; Department of Psychology, University of Texas at Austin, 108 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Bearman SK; Department of Educational Psychology, University of Texas at Austin, 1912 Speedway, Austin, Texas, 78712, USA.
  • Harari GM; Department of Communication, Stanford University, 450 Serra Mall, Stanford, California, 94305, USA.
  • Cameron Craddock R; Department of Diagnostic Medicine, University of Texas at Austin, 1601 Trinity St, Austin, Texas, 78712, USA.
  • Kinney KA; Department of Civil, Environmental, and Architectural Engineering, University of Texas at Austin, 301 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Gosling SD; Department of Psychology, University of Texas at Austin, 108 E Dean Keeton St, Austin, Texas, 78712, USA.
  • Schnyer DM; Melbourne School of Psychological Sciences, University of Melbourne, Grattan Street, Parkville, Victoria, 3010, Australia.
  • Nagy Z; Department of Psychology, University of Texas at Austin, 108 E Dean Keeton St, Austin, Texas, 78712, USA.
Gigascience ; 10(6)2021 06 21.
Article in En | MEDLINE | ID: mdl-34155505
ABSTRACT

BACKGROUND:

As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes.

RESULTS:

To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants' mood, sleep, behavior, and living environment.

CONCLUSIONS:

We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Smartphone Type of study: Etiology_studies / Incidence_studies / Observational_studies / Risk_factors_studies Aspects: Patient_preference Limits: Humans Language: En Journal: Gigascience Year: 2021 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Smartphone Type of study: Etiology_studies / Incidence_studies / Observational_studies / Risk_factors_studies Aspects: Patient_preference Limits: Humans Language: En Journal: Gigascience Year: 2021 Document type: Article Affiliation country: United States