Affective models of depression and anxiety: Extension to within-person processes in daily life

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

BACKGROUND: Affective models (e.g., tripartite model) delineate shared and unique components of depression and anxiety. Specifically, negative affect is broadly associated with these symptoms, whereas low positive affect is relatively specific to depression and social anxiety. However, it is unknown how affect relates to symptoms as they occur naturalistically in daily life or as a within-person dynamic process.

METHOD: 135 treatment-seeking adults completed a baseline assessment of trait affect and then rated current affect and symptoms (depression, social anxiety, panic, worry) three times per day for 10 days. Multilevel structural equation modeling was used, and prospective analyses held constant current symptoms.

RESULTS: Baseline trait negative affect and individual differences in momentary negative affect predicted all four symptoms in daily life, whereas low positive affect predicted greater depression only. Similar results were found for within-person concurrent analyses. Prospectively, momentary negative affect predicted increased depression up to 24 h later, and increased panic or worry up to 8-16 h later. Low momentary positive affect predicted greater depression only (8 h later).

LIMITATIONS: All data were self-reported, and some relevant anxiety and mood symptoms were excluded. The timing of reports was random and may have missed notable symptoms. Given the novelty of the study, replication is important.

CONCLUSIONS: Affective models of depression and anxiety derived from retrospective assessments demonstrated strong ecological validity. With the exception of PA and social anxiety, associations found at the between-person level generally applied to within-person processes, which may be amenable to tracking and targeting in therapy.

Original languageEnglish
Pages (from-to)241-248
Number of pages8
JournalJournal of Affective Disorders
Volume243
DOIs
Publication statusPublished - 15 Jan 2019
Externally publishedYes

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