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Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study.
Vesel, Claudia; Rashidisabet, Homa; Zulueta, John; Stange, Jonathan P; Duffecy, Jennifer; Hussain, Faraz; Piscitello, Andrea; Bark, John; Langenecker, Scott A; Young, Shannon; Mounts, Erin; Omberg, Larsson; Nelson, Peter C; Moore, Raeanne C; Koziol, Dave; Bourne, Keith; Bennett, Casey C; Ajilore, Olusola; Demos, Alexander P; Leow, Alex.
Afiliação
  • Vesel C; Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Rashidisabet H; Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Zulueta J; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Stange JP; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Duffecy J; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Hussain F; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Piscitello A; Department of Computer Science, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Bark J; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Langenecker SA; Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA.
  • Young S; Sage Bionetworks, Seattle, Washington, USA.
  • Mounts E; Sage Bionetworks, Seattle, Washington, USA.
  • Omberg L; Sage Bionetworks, Seattle, Washington, USA.
  • Nelson PC; Department of Computer Science, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Moore RC; Department of Psychiatry, University of California, San Diego, San Diego, California, USA.
  • Koziol D; Arbormoon Software, Inc, Ann Arbor, Michigan, USA.
  • Bourne K; Arbormoon Software, Inc, Ann Arbor, Michigan, USA.
  • Bennett CC; College of Computing and Digital Media, DePaul University, Chicago, Illinois, USA.
  • Ajilore O; School of Intelligence, Hanyang University, Seoul, Korea.
  • Demos AP; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Leow A; Department of Psychology, University of Illinois at Chicago, Chicago, Illinois, USA.
J Am Med Inform Assoc ; 27(7): 1007-1018, 2020 07 01.
Article em En | MEDLINE | ID: mdl-32467973
OBJECTIVE: Ubiquitous technologies can be leveraged to construct ecologically relevant metrics that complement traditional psychological assessments. This study aims to determine the feasibility of smartphone-derived real-world keyboard metadata to serve as digital biomarkers of mood. MATERIALS AND METHODS: BiAffect, a real-world observation study based on a freely available iPhone app, allowed the unobtrusive collection of typing metadata through a custom virtual keyboard that replaces the default keyboard. User demographics and self-reports for depression severity (Patient Health Questionnaire-8) were also collected. Using >14 million keypresses from 250 users who reported demographic information and a subset of 147 users who additionally completed at least 1 Patient Health Questionnaire, we employed hierarchical growth curve mixed-effects models to capture the effects of mood, demographics, and time of day on keyboard metadata. RESULTS: We analyzed 86 541 typing sessions associated with a total of 543 Patient Health Questionnaires. Results showed that more severe depression relates to more variable typing speed (P < .001), shorter session duration (P < .001), and lower accuracy (P < .05). Additionally, typing speed and variability exhibit a diurnal pattern, being fastest and least variable at midday. Older users exhibit slower and more variable typing, as well as more pronounced slowing in the evening. The effects of aging and time of day did not impact the relationship of mood to typing variables and were recapitulated in the 250-user group. CONCLUSIONS: Keystroke dynamics, unobtrusively collected in the real world, are significantly associated with mood despite diurnal patterns and effects of age, and thus could serve as a foundation for constructing digital biomarkers.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Ritmo Circadiano / Afeto / Smartphone Tipo de estudo: Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Am Med Inform Assoc Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Ritmo Circadiano / Afeto / Smartphone Tipo de estudo: Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Am Med Inform Assoc Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos