Affective Dynamics in Psychopathology

Abstract

We discuss three varieties of affective dynamics (affective instability, emotional inertia, and emotional differentiation). In each case, we suggest how these affective dynamics should be operationalized and measured in daily life using time-intensive methods, like ecological momentary assessment or ambulatory assessment, and recommend time-sensitive analyses that take into account not only the variability but also the temporal dependency of reports. Studies that explore how these affective dynamics are associated with psychological disorders and symptoms are reviewed, and we emphasize that these affective processes are within a nexus of other components of emotion regulation.

A systematic review of the psychometric properties, usability and clinical impacts of mobile mood-monitoring applications in young people

“…Given the evidence from the adult literature, research on the possible harmful effects of app use in youths is needed before these tools are routinely used in clinical practice. Part of this endeavour should seek to identify the optimal balance between a monitoring schedule, which accurately captures affective dynamic processes, while minimising respondent workload (Bolger et al 2003;Trull et al 2015). This is particularly important, not only because it affects participation rates, but also because the responsibility of self-monitoring could impose a burden on young people (Shiffman et al 2008), might result in unnecessary pressure (Lupton, 2013;Seko et al 2014) and exacerbate mental health problems (Conner & Reid, 2012;Faurholt-Jepsen et al 2015).…”

“…Problems with regulating mood can play a key role in the development and trajectory of a range of psychopathologies (Paris, 2004;Crowell et al 2009;Marwaha et al 2015). Traditionally, mood has been assessed with retrospective measures (Trull et al 2015). This can increase the risk of recall bias subsequently reducing accuracy (Schwartz et al 1999;Reid et al 2009).…”

“…Mood is an affective dynamic, which naturally varies across time and contexts (Trull et al 2015). Problems with regulating mood can play a key role in the development and trajectory of a range of psychopathologies (Paris, 2004;Crowell et al 2009;Marwaha et al 2015).…”

An Objective, Comprehensive and Flexible Statistical Framework for Detecting Early Warning Signs of Mental Health Problems

“…material) with KCP to test for significant change points before relapse. As these statistics quantify affective dynamics linked to psychopathology [9, 10], it makes indeed sense to expect that change points in them can serve as EWS of an upcoming depressive episode.…”

Modeling Affect Dynamics: State of the Art and Future Challenges

“…This implies that-depending on the process we are interested in-we may need day-to-day, moment-to-moment, or even second-to-second measurements, which can be obtained using a daily diary, ambulatory assessment, experience sampling, observations, or laboratory measurements (Bolger, Davis, & Rafaeli, 2003;Trull & Ebner-Priemer, 2013). Recent technological developments such as smartphones, accelerometers, and smart shirts have made gathering ILD relatively easy, and as a result intensive longitudinal studies have become a reasonable alternative to our more traditional research methods, such as cross-sectional and panel research.…”