Share,like, twitter,and connect: Ecological momentary assessment to examine the relationship between non-work social media use at work and work engagement |
| |
Authors: | Christine J. Syrek Jana Kühnel Tim Vahle-Hinz Jessica De Bloom |
| |
Affiliation: | 1. Department for Work and Organizational Psychology, University of Trier, Trier, Germany;2. Institute of Psychology and Education, Work and Organizational Psychology, Ulm University, Ulm, Germany;3. Institute for Occupational Health Psychology, Humboldt University of Berlin, Berlin, Germany;4. Institute for Advanced Social Research, University of Tampere, Tampere, Finland |
| |
Abstract: | Non-work social media use at work has seen a dramatic increase in the last decade and is commonly deemed counterproductive work behaviour. However, we examined whether it may also serve as a micro-break and improve work engagement. We used ecological momentary assessment across 1 working day with up to 10 hourly measurements in 334 white-collar workers to measure non-work social media use and work engagement, resulting in 2235 hourly measurements. Multilevel modelling demonstrated that non-work social media use was associated with lower levels of work engagement between persons. Within persons, non-work social media use was also associated with lower concurrent work engagement. However, non-work social media use was related to higher levels of work engagement 1 hour later. While more extensive non-work social media use at work was generally associated with lower work engagement, our advanced study design revealed that the longer employees used social media for non-work purposes during 1 working hour, the more work engaged they were in the subsequent working hour, suggesting that employees turn to social media when energy levels are low and/or when they (temporarily) lose interest in their work. This behaviour may serve as a break, which in turn increases work engagement later during the day. |
| |
Keywords: | Recovery work engagement ecological momentary assessment micro-break within-person fluctuations |
|
|