Work addiction in Chinese white-collar workers: the psychometric properties of its measure and its comorbidity with general anxiety in network analysis

Abstract

Background Work addiction (WA) threatens occupation-related health in many countries including China. This research aims to evaluate the psychometric properties of the Chinese version of Bergen Work Addiction Scale (BWAS), the most common measure of WA, to facilitate relevant studies in Chinese workers. A network analysis was further conducted to identify central and bridge symptoms within the WA-anxiety network to improve intervention practices. Methods A total of 694 Chinese white-collar workers completed an online questionnaire survey in March of 2022, and the responses to BWAS from a subsample of 50 participants one month after this survey were also collected. Results The unidimensionality of BWAS was supported by results of exploratory factor analysis, exploratory graph analysis, and confirmatory factor analysis and we found satisfactory internal consistency and acceptable test-retest reliability. Multiple-group factor analyses confirmed the measurement invariance of BWAS across genders, districts (i.e., central China, eastern China, western China, and northeastern China), and age groups (i.e., young and middle-aged adults) while the convergent validity of BWAS was demonstrated by its significant correlations with Dutch Work Addiction Scale (r = 0.62, p < 0.001) and its criterion validity was indicated by its significant correlations with general anxiety, weekly work hours, and health status (r = -0.16 to 0.31, p < 0.001–0.01). Network analysis further revealed two central symptoms (WA-tolerance and WA-problems) and three bridge symptoms (WA-problems, WA-mood modification, and mouth dryness of general anxiety) maintaining the WA-anxiety comorbidity. Conclusions Our findings suggest that BWAS is a valid measure of WA in Chinese workers and interventions should put special attention to the identified central and bridge symptoms underlying the WA-anxiety network.

Network Approach to Work Addiction: A Cross-Cultural Study

“…Taking into account feedback loops, it can be expected that increasing problems may increase mood modification needs and aggravate tolerance, withdrawal, and relapse symptoms. These assumptions seem to find support in previous research (Atroszko et al, 2017; Bellali et al, 2023; Denizci Nazlıgül et al, 2022; Falco et al, 2022; Fekih-Romdhane et al, 2022; Molino et al, 2022; Sun et al, 2023). Therefore, we argue that work addiction could be conceptualized as a network of direct relationships between its symptoms.…”

“…In light of previous research, it is important to point out that eight of the strongest edges in this study overlap with two out of the five strongest edges observed by Sun et al (2023), and five out of seven correlations between residuals in previous research grounded in the latent variable framework (two of them overlapping with Sun et al, 2023; see Table 1). These results seem to indicate that both previous network studies and latent variable studies may constitute a valid source of hypotheses for future network studies of work addiction.…”

“…However, the support for each of the assumptions seems to be scattered across the literature. Out of the five strongest edges found by Sun et al (2023), only two were found in the latent variable framework studies, and only one of these was found in more than a single study (i.e., the edge between salience and tolerance). While acknowledging the necessity for a confirmatory approach in behavioral sciences (Wagenmakers et al, 2012), we argue that, in the case of a complex network of interrelationships, imposing specific predictions in the context of vague and heterogeneous premises from previous studies as well as lack of solid theories may be impossible.…”

“…Two of them were direct extensions of this work (Bereznowski, Atroszko, & Konarski, 2023; Bereznowski, Bereznowska, et al, 2023) and, as such, do not constitute a valid source of hypotheses for the present study; thus, they will not be discussed here. The third study was conducted by Sun et al (2023) and investigated the network of symptoms of work addiction and general anxiety in Chinese white-collar workers. Sun et al (2023) showed that the five strongest edges in the estimated network were (a) Salience (1)—Tolerance (2), (b) Tolerance (2)—Problems (7), (c) Mood modification (3)–Withdrawal (5), (d) Salience (1)—Conflict (6), and (e) Mood modification (3)—Relapse (4), consecutively.…”

“…The BWAS has been developed as a measure of a single latent factor of work addiction, which showed an acceptable fit to the data in the original study in Norway (RMSEA = 0.077; Andreassen et al, 2012) and a recent study in China (RMSEA = 0.063; Sun et al, 2023). However, other studies showed that there are some non-trivial relationships between the symptoms of work addiction, which could not be explained by a single latent variable of work addiction.…”