Participants and Procedure
Initially, we recruited 165 individuals who satisfied our eligibility criteria in the initial baseline survey. Of these, we excluded 12 participants who failed one or more of the three attention check items. We also omitted 33 participants who did not complete a minimum of two full days of daily surveys (i.e., four daily surveys). The final sample size was 120 individuals providing 1,161 observations (response rate = 92.49%). On average, participants were 32.93 years old (SD = 3.27), 32.03% of whom were female. They worked for an average of 3.39 years in their current jobs (SD = 0.58). A majority of participants had obtained a bachelor’s degree (55.56%) and were either Black/African American (58.17%) or White (40.52%).
We recruited full-time employees by posting an advertisement on Craigslist, an online community website (see https://www.craigslist.org/about) in multiple large cities in the United States (see Judge et al., 2014; Vogel et al., 2020, for examples using Craigslist). The advertisement contained information about the study procedures, eligibility criteria, and compensation, and was posted for approximately two weeks in June 2022.
Interested participants were requested to email the researchers and were subsequently invited to complete an initial baseline survey, which included informed consent and measures of demographic variables. In this survey, participants were first screened based on three eligibility criteria: (a) age (i.e., 18 + years old), (b) full-time employment status (i.e., 30 + work hours per week), and (c) work schedules (i.e., whether they had a traditional work schedule from 9:00 AM to 5:00 PM), the last of which was employed to ease scheduling of daily surveys. At the end of the baseline survey, we employed a commitment device that asked participants to explicitly commit to completing a minimum of 75% of the daily surveys (Gabriel et al., 2019). If respondents failed to commit to completing 75% or more of daily surveys, we kindly asked them to consider increasing their commitment to maximize the utility of their effort in participating in the research study. As a result, all participants chose to commit 75% or more of the daily surveys.
For 10 consecutive workdays (i.e., two consecutive workweeks), participants received two brief surveys per day, the first survey at 10:00 a.m. (Time 1 or T1) and the second survey at 1:00 p.m. (Time 2 or T2). In both surveys, we assessed momentary measures of job boredom and CWB. In exchange for participation, we provided a maximum possible amount of 55.00 U.S. dollars in the form of an Amazon gift card.
To ensure data quality, we followed best practice recommendations for convenience sampling. Specifically, we implemented such strategies as posting the advertisement in major metropolitan areas (Antoun et al., 2016), including attention check items in the initial survey (e.g., “Please select Never for this item.”; Meade & Craig, 2012), and tracking unique identifiers to assure only one survey was completed per participant (Mason & Suri, 2012). Additionally, to ensure that our study had sufficient statistical power, we followed Gabriel et al.’s (2019) sample size recommendations, which were based on their calculation of the mean sample size of the past experience sampling studies. Accordingly, we aimed to obtain a minimum Level 2 sample size of 83 and a minimum Level 1 sample size of 835 by administering three daily surveys for 10 consecutive workdays. This strategy of sampling for two weeks allowed us to capture a generally representative sample of a person’s daily experiences (Wheeler & Reis, 1991).
Measures
Job Boredom
Momentary job boredom was assessed using a 4-item measure (Park et al., 2019). On a 5-point Likert scale (1 = not at all to 5 = extremely), participants were asked to rate the extent to which they were feeling each of the following four emotion adjectives at the current moment: “bored,” “sluggish,” “dull,” and “lethargic.” We aggregated momentary job boredom assessed in T1 and T2 up to a morning measure of job boredom. Across the days of data collection, the average Cronbach’s alpha coefficient was .99.
Counterproductive Work Behavior
CWB was measured with 2 items from Dalal et al. (2009). Although the full scale originally contained 6 items, we only included 2 of them that may be likely to have greater within-person variability during one’s typical workday (Koopman et al., 2021). On a dichotomous scale (1 = yes, 0 = no), we asked participants to rate each item while thinking about the last two hours at work. Example items include “Did not work to the best of my ability” and “Spent time on tasks unrelated to work.” Across the days of data collection, the average Cronbach’s alpha coefficient was .91.
Data Analysis
To study within-person dynamics between job boredom and CWB, we used latent change score (LCS) modeling (see Matusik et al., 2021, for a review). In an LCS model (see Fig. 1), we used 10 daily measurements of both job boredom and CWB and specified constant change effect (i.e., whether and to what extent there is an overall increasing or decreasing trend for a given variable), proportional change effect (i.e., whether and to what extent a level of the variable influences subsequent change in that same variable), and autoregression of change scores for both boredom and CWB. Importantly, we specified a lagged coupling effect of job boredom on change in CWB, as well as lagged coupling effect of CWB on change in job boredom. The lagged coupling effects were the parameters of primary interest in this study. For instance, the lagged coupling effect of job boredom on change in CWB indicates whether and to what extent job boredom at Day i – 1 predicts increases (indicated by a significant, positive effect) or decreases (indicated by a significant, negative effect) in CWB between Day i – 1 and Day i. As is common when using LCS models, all estimates were assumed to be equal across time points (Matusik et al., 2021). The LCS model showed acceptable fit (CFI = .90, TLI = .91, RMSEA = .09, SRMR = .10).