title: Biases in Short-Term Mood Prediction in Individuals with Depression and Anxiety Symptoms.
abstract: We used ecological momentary assessment to explore depressive and anxious biases in within-day negative and positive mood predictions. Participants (N= 120) who were higher in depression symptoms demonstrated stronger biases (i.e., were more pessimistically biased) in the prediction of negative mood and weaker biases (i.e., were less optimistically biased) in the prediction of positive mood (b01= .002,SE= .001,p= .031 andb01= -.008, SE = .002,p< .001, respectively). Anxiety symptoms were not associated with short-term mood prediction biases (p's > .10). Such biases might influence daily decisions and experiences as well as impact longer-term outcomes. Limitations and future research directions are discussed.
authors.affiliation: American University, Washington, DC.
authors.forename: Susan J
authors.initials: SJ
authors.lastname: Wenze
authors.affiliation: American University, Washington, DC.
authors.forename: Kathleen C
authors.initials: KC
authors.lastname: Gunthert
authors.affiliation: American University, Washington, DC.
authors.forename: Anthony H
authors.initials: AH
authors.lastname: Ahrens
authors.affiliation: American University, Washington, DC.
authors.forename: T C
authors.initials: TC
authors.lastname: Taylor Bos
keywords: affective forecasting; anxiety; depression; experience sampling