Correction to: The Effect of Rating Scale Length on the Occurrence of Inappropriate Category Use for the Assessment of Job Satisfaction: an Experimental Online Study

A Correction to this paper has been published: 10.1007/s41543-021-00041-9

Difference in mood at work and home. An additional indicator of job satisfaction

New techniques for multiple moment assessment allow us to assess how people feel at different times of the day. These techniques are mostly used to assess how well people feel during particular activities, such as during work or childcare. In this paper we focus on the difference in how well people feel at work and at home. The following questions are addressed: 1) How large is the difference in mood at work and at home? 2) How much does the difference in mood at work and at home vary across kinds of people and occupations? 3) Is the difference in mood at work and at home associated with job satisfaction as measured using common general retrospective ratings or does it tap another aspect of job satisfaction? We explore answers to these questions, using data from a diary study in the Netherlands, done using an e-application of the Day Reconstruction Method (DRM) in which 1,410 people provided information about mood experienced in 32,000 episodes. We found that the average difference in mood at work and at home is small in this sample but that it varies across people and occupations. We found a low correlation of the difference in mood with the respondent’s retrospective ratings of their general job satisfaction, which suggests that there is more in the phenomena of job satisfaction than is measured using the usual questions on general job satisfaction. This, as yet unrecognized, aspect of job satisfaction is likely to add to information demands behind common measurements of job satisfaction, that is, to indicate the quality of the work conditions and estimate chances to improve worker performance and reduce turnover by making work more satisfying. We suggest an agenda for research in these areas of possible gains.

Unpacking the Quantifying and Qualifying Potential of Semi-Open Job Satisfaction Questions through Computer-Aided Sentiment Analysis

Despite their suitability for mitigating survey biases and their potential for enhancing information richness, open and semi-open job satisfaction questions are rarely used in surveys. This is mostly due to the high costs associated with manual coding and difficulties that arise when validating text measures. Recently, advances in computer-aided text analysis have enabled researchers to rely less on manual coding to construct text measures. Yet, little is known about the validity of text measures generated by computer-aided text analysis software and only a handful of studies have attempted to demonstrate their added value. In light of this gap, drawing on a sample of 395 employees, we showed that the responses to a semi-open job satisfaction question can reliably and conveniently be converted into a text measure using two types of computer-aided sentiment analysis: SentimentR, and Linguistic Inquiry and Word Count (LIWC) 2015. Furthermore, the substantial convergence between the LIWC2015 and, in particular, SentimentR measure with a closed question measure of job satisfaction and logical associations with closed question measures of constructs that fall within and outside job satisfaction’s nomological network, suggest that a semi-open question has adequate convergent and discriminant validity. Finally, we illustrated that the responses to our semi-open question can be used to fine-tune the computer-aided sentiment analysis dictionaries and unravel antecedents of job satisfaction.