s) Behavioral theories are essential in understanding physical activity and
developing effective intervention strategies, yet most theories have been
developed alongside common research methods available at their
inception. Traditional methods have included infrequent assessments,
capturing one's usual level of behavior or average score on a theoretical
construct at a small set of time points. More contemporary data
collection methods such as intensive longitudinal designs (e.g.,
Ecological Momentary Assessment; EMA) are beginning to facilitate
more advanced approaches to theorizing. One of the primary challenges
in applying traditional behaviour change theories, however, relates to
measurement, as traditional multi-item measures are not practical nor
may they accurately capture the dynamic elements of the construct
sought in intensive longitudinal sampling. The purpose of this
presentation is to provide a user's guide of measures of the Multi
Process Action Control (M-PAC) Framework for use in EMA, followed by
preliminary working examples. EMA offers opportunities to sample and
obtain real-time (or near real-time) information that include processes
that are more automatically or immediately activated in response to
environmental stimuli or informational cues. As a result, we propose a
slight re-operationalization of M-PAC as it relates to the interacting
psychological systems in determining physical activity. We outline some
of the measurement challenges with M-PAC using EMA, and the
opportunities to blend more traditional and contemporary real-time
approaches to advance theory and our understanding of physical activity
utilizing the M-PAC framework. Together, this presentation is intended to
be a starting point, acknowledging the need to adapt traditional
behavioral theories to incorporate the dynamic factors in determining
physical activity. By doing so, we can advance our understanding of
physical activity behaviors and develop more effective, and theory
based, interventions tailored to individual needs and contexts.