Quantifying the Persistence of Daily Routines

TL;DR

This paper introduces a framework to quantify and analyze the stability and individuality of daily routines using passive sensing data from over a thousand participants, revealing consistent personal patterns across diverse populations.

Contribution

The study develops a novel method to identify and characterize recurring daily routines and their persistence, validated on large-scale longitudinal sensing data.

Findings

Approximately eight routine types capture dominant daily behaviors.

Individuals maintain stable, person-specific distributions over routine types.

Routine patterns are consistent across different populations and correlate modestly with personality traits.

Abstract

Daily life is structured by recurring routines that coordinate biological rhythms with social and occupational demands. Individual differences in work schedules, family obligations, and social commitments produce distinctive ways of organizing activities throughout the day. Do people have typical days with certain arrangement of activities? How often do these typical days or routines occur and does this differ from person to person? We introduce a framework for quantifying such recurring routines, their persistence over time and their distinctiveness for different people. We model consecutive days in one's life as a sequence of different types of typical days, i.e. routines. Characterizing each day through patterns of activities common among all people - sleep, movement, and device use - we identify a small set of routine types that capture the dominant structure of everyday behavior. We then test whether individuals maintain stable, person-specific distributions over these types and transition between them in characteristic ways. Validating this framework with passive sensing data from 1,086 participants across 153,000 person-days in three longitudinal studies, we find that daily life typically resolves into approximately eight routine types and each person maintains a characteristic distribution over these types. Both the time allocation across routine types and the day-to-day transition dynamics are substantially more similar within individuals than between them, remaining stable across observation windows spanning weeks to months and across populations differing in age, occupation, and health status. Routine persistence shows modest associations with personality traits such as conscientiousness, but is broadly similar across age and gender. Our findings establish routine patterns as stable, person-specific behavioral fingerprints with applications in personalized health monitoring.