Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study

Abstract

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.

Naturalistic smartphone keyboard typing reflects processing speed and executive function

“…The change in significance may be due to the fact that typing speed explained the effect on dTMT‐B in place of age, especially considering the effect age had on typing speed reported by Vesel et al. ( 2020 ). Further, in our models, time of day was never a significant predictor of dTMT‐B performance.…”

“…Median IKD was calculated for time windows with at least 20 character‐to‐character transitions of less than 8 s. The time cutoff of 8 s was previously defined by Vesel et al. as the end of a typing session (Vesel et al., 2020 ). Time windows that did not meet these criteria were omitted from the analysis.…”

“…This approach has the potential to evolve into a form of personalized treatment medicine that focuses more on predicting and preventing symptoms based on the individual (Flores et al., 2013 ). To this end, several recent studies have found that passively collected naturalistic smartphone typing dynamics may be associated with mood state and cognition (Cao et al., 2017 ; Lam et al., 2020 ; Mastoras et al., 2019 ; Vesel et al., 2020 ; Zulueta et al., 2018 ).…”

Future directions for sleep and cognition research in at-risk older adults

“…A recent study using passively and unobtrusively obtained keystroke metadata (i.e. how you type, not what you type) from real-world daily smartphone keyboard interactions found an age effect and diurnal pattern with the keystroke data (Vesel et al, 2020). Results of the sample of 250 individuals demonstrated a nonlinear diurnal pattern for typing speed, wherein user's typing speed was fastest midday (12:00 pm to 3:00 pm) and their slowest typing was at night.…”

Using Absolutist Word Frequency from Online Searches to Measure Population Mental Health Dynamics

“…inclusion of question mark or not). This has led researchers to question the validity of measures based on online search data [27][28] . In comparison, the ATI's only assumption is that the way individuals typewrite is influenced by their mood, an uncontroversial assumption which has empirically been verified recently 29 .…”