Making flow happen: The effects of being recovered on work-related flow between and within days.

• DOI: 10.1037/a0035881
• Publication Date: 2014-02-10T11:51:55Z
• Authors: Maike E. Debus; Sabine Sonnentag; Werner Deutsch; Fridtjof W. Nussbeck
• Keywords: curvilinear effects; Adult; Employment; Time Factors; 10093 Institute of Psychology; 05 social sciences; 150; 3202 Applied Psychology; Workflow; flow experiences; Task Performance and Analysis; Humans; 0501 psychology and cognitive sciences; 150 Psychology; experience sampling study

This article examines variations of work-related flow both between and within days. On the basis of the effort-recovery model (Meijman & Mulder, 1998), we hypothesized that a person's relative day-specific state of being recovered (i.e., feeling refreshed) in the morning is positively related to subsequent day-level flow experiences during work. Taking into account research on circadian rhythms of human functioning, we further hypothesized that flow experiences follow a U-shaped pattern within the working day and that feeling recovered will affect this pattern. One hundred and twenty-one software professionals provided data on recovery at the start of the working day and on flow at 3 occasions during the day, for a period of 5 consecutive working days (resulting in 493 day-level and 1,340 occasion-level data points). Three-level multilevel models showed that relative day-level state of being recovered predicted day-level flow experiences in the hypothesized direction. The data did not support a general curvilinear, U-shaped main effect of flow experiences within the day. However, people in a relatively high state of being recovered in the morning experienced the predicted U-shaped pattern, whereas poorly recovered people experienced a gradual decrease in flow experiences over the course of the working day. This study emphasizes the importance of recovery during nonwork time for flow experiences within the entire working day, thereby extending research on task characteristics with personal resources when examining predictors of flow.