Affect, behavior, and severity of psychopathological symptoms do not remain
static throughout the life of an individual, but rather they change over time.
Since the rise of the smartphone, longitudinal data can be obtained at higher
frequencies than ever before, providing new opportunities for investigating
these person-specific changes in real-time. Since 2019, researchers have started
using the exponentially weighted moving average (EWMA) procedure, as a
statistically sound method to reach this goal. Real-time, person-specific change
detection could allow (a) researchers to adapt assessment intensity and strategy
when a change occurs to obtain the most useful data at the most useful time and
(b) clinicians to provide care to patients during periods in which this is most
needed. The current paper provides a tutorial on how to use the EWMA procedure
in psychology, as well as demonstrates its added value in a range of potential
applications.