Physician Typing Performance and Mental Fatigue Study

Yu Fang's dataset contains 45,042 typing sessions from 366 first-year training physicians in the United States, collected over a two-month period. It examines the relationship between smartphone keyboard metrics and time awake to assess mental fatigue.

Use Cases

• Analyze the non-linear adjusted relationship between typing speed and time since waking to model mental fatigue patterns.
• Correlate SensorKit typing performance metrics with wearable-derived sleep episode data for ambulatory alertness monitoring.
• Validate typing speed peaks and declines against classical Psychomotor Vigilance Test findings on response lapses.

Strengths

• Contains 45,042 typing sessions, providing a substantial behavioral sample.
• Data from 366 first-year physicians offers a focused population for high-stakes workplace studies.
• Two-month collection period enables analysis of temporal patterns in mental fatigue.

Limitations

• Small sample size of 366 participants limits generalizability to broader populations.
• Geographic bias as data is exclusively from physicians in the United States.
• The 5.5 KB file size indicates a tiny, aggregated dataset, not raw session-level data.

Provenance

Source

figshare, author Yu Fang

Collection Method

Collected via smartphone SensorKit typing metrics and wearable sensors from first-year training physicians.

Time Range

Two-month period (specific dates unknown).

Freshness

null

Geography

United States