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Related Concept Videos

The Influence of Cognition on Affect01:29

The Influence of Cognition on Affect

Cognition plays a pivotal role in shaping emotional experiences, as demonstrated by Schachter and Singer’s two-factor theory of emotion. According to this model, emotion arises from a combination of physiological arousal and cognitive interpretation. The body’s physiological response to stimuli is ambiguous and only gains emotional significance through cognitive labeling. For instance, an increased heart rate and adrenaline surge while standing near an attractive person may be interpreted as...

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Predicting cognitive functioning in mood disorders through smartphone typing dynamics.

Emma Ning1, Ryne Estabrook1, Theja Tulabandhula2

  • 1Department of Psychology, University of Illinois Chicago.

Journal of Psychopathology and Clinical Science
|September 4, 2025
PubMed
Summary
This summary is machine-generated.

Smartphone typing patterns can passively predict cognitive function in mood disorders. Keystroke dynamics show promise for assessing cognition, though utility varies by cognitive domain and population.

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Area of Science:

  • Digital phenotyping
  • Neuroscience
  • Psychiatry

Background:

  • Mood disorders (MDs) like depression and bipolar disorder cause significant cognitive impairments affecting daily life.
  • Objective, passive monitoring of cognitive function in MDs is needed for better management.
  • Smartphone typing dynamics offer a potential avenue for such monitoring.

Purpose of the Study:

  • To investigate the predictive power of smartphone typing dynamics for cognitive functioning in individuals with MDs.
  • To assess whether passive typing data can prospectively predict cognitive performance.
  • To compare the relationship between typing dynamics and cognition across MDs and healthy controls.

Main Methods:

  • 127 participants used the BiAffect keyboard for ~28 days, collecting typing metadata.
  • Neuropsychological assessments were conducted twice, at least 14 days apart.
  • Principal component analysis and structural equation modeling were used to analyze typing features and predict cognitive test performance.

Main Results:

  • Slower typing speeds predicted worse cognitive performance in healthy controls, but this relationship was weaker or more variable in individuals with MDs.
  • Keystroke dynamics equally predicted performance on the Trail-Making Test, Part B, across both MDs and healthy control groups.
  • Typing speed and other keystroke dynamics showed differential predictive utility depending on the cognitive test and participant group.

Conclusions:

  • Keystroke dynamics represent an ecologically valid, passive method for assessing cognitive function.
  • The utility of typing dynamics as a cognitive biomarker varies across different cognitive domains and populations.
  • Further research is warranted to refine the application of digital phenotyping for cognitive assessment in mental health.