Affective Events Theory

Affect-driven behaviors flow directly from a person's current emotional state with little deliberation — helping a colleague because you feel good, withdrawing or lashing out because you feel bad, momentary bursts of effort or expressions of emotion. Judgment-driven behaviors flow from evaluative judgments such as job satisfaction, which are cognitive appraisals that build up over time, partly from accumulated affective experiences. This distinction is AET's key contribution because it explains a long-standing puzzle: job satisfaction predicts deliberate, considered decisions like turnover reasonably well but predicts spontaneous, in-the-moment behaviors poorly, whereas momentary affect predicts those spontaneous behaviors. Recognizing two pathways means researchers should match the predictor (affect versus attitude) to the type of behavior they want to explain.

Because its core claims are about processes that unfold within a single person over time: an event happens, it triggers an emotional reaction, and that reaction influences behavior, all moment by moment. A between-person, cross-sectional survey can only tell you whether people who report more events also report different average attitudes, which is not the same as showing that an event changed a person's affect and behavior. Weiss and Beal stressed that testing AET properly requires experience-sampling or daily-diary designs that repeatedly measure events, affect, and behavior in the same people, analyzed with multilevel models that separate within-person dynamics from stable between-person differences. This methodological demand is a large part of why AET drove the adoption of intensive longitudinal methods.

Not in one step. AET is a broad macro-framework — a structure that organizes how events, dispositions, affect, attitudes, and behavior relate — rather than a single falsifiable hypothesis. To test it, researchers derive specific predictions from it: for example, that a particular type of negative event will produce negative affect that increases counterproductive behavior the same day, moderated by trait negative affectivity. Each such derived model is testable with appropriate within-person data, and the accumulation of supported predictions is what gives the framework empirical credibility. Critics note this breadth makes AET hard to disconfirm as a whole, which is why disciplined use means specifying and testing concrete event-affect-behavior chains rather than invoking the framework loosely.