Analytic strategies for understanding affective (in)stability and other dynamic processes in psychopathology.

• DOI: 10.1037/a0014868
• Publication Date: 2009-02-18T02:40:07Z
• Authors: Ulrich W. Ebner-P...; Michael Eid; Nikolaus Kleindienst; Simon Stabenow; Timothy J. Trull
• Keywords: ddc:796; Time Factors; Mood Disorders; Environment; Models, Biological; 796; 03 medical and health sciences; Athletic & outdoor sports & games; Cross-Sectional Studies; 0302 clinical medicine; Borderline Personality Disorder; Disease Progression; Humans; Interpersonal Relations; Factor Analysis, Statistical; info:eu-repo/classification/ddc/796

The dynamics of psychopathological symptoms as a topic of research has been neglected for some time, likely because of the inability of cross-sectional and retrospective reports to uncover the ebb and flow of symptoms. Data gathered with the experience sampling method (ESM) enable researchers to study symptom variability and instability over time as well as the dynamic interplay between the environment, personal experiences, and psychopathological symptoms. ESM data can illuminate these dynamic processes, if time is both considered and integrated into (a) the research question itself, (b) the assessment or sampling method, and (c) the data analytic strategy. The authors highlight the complexity of assessing affective instability and unstable interpersonal relationships and explore sampling and analytic methods. Finally, they propose guidelines for future investigations. For the assessment of affective instability, the authors endorse the use of time-contingent recordings and of instability indices that address temporal dependency. For the assessment of unstable interpersonal relationships, they advocate the use of event-contingent recordings and separate analyses within and across dyads.