Adapting the spillover–crossover model to the context of eldercare, we employed a 5-week weekly diary method in a sample of 82 Chinese dual-earner heterosexual couples to examine the relationships between family eldercare demands, family-to-work conflict, and time theft. Results from multilevel path modeling analyses found that family eldercare demands (as a shared/common stressor) were positively related to each partner’s family-to-work conflict and that the weekly family-to-work conflict of each partner was positively related. Furthermore, family eldercare demands were positively related to each partner’s time theft at the week level, and this relationship was mediated by weekly family-to-work conflict. Thus, this is one of the first studies to show that family eldercare demands can explain the interindividual crossover of family-to-work conflict between partners at the week level and this can spill over intraindividually to impact time theft at work. These findings enhance the field’s understanding of the process by which eldercare demands relate to time theft among dual-earner couples within a focused temporal framework.
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Description of Supplemental Data Set and Measures Used to Evaluate Construct Validity of the Shortened Eldercare Demands and Time Theft Measures
Participants and Procedure
For the purposes of providing additional construct validity information for the eldercare demands and time theft measures used in this study, a separate heterogeneous sample of 243 working U.S. eldercare providers was recruited from TurkPrime (Litman et al., 2017) to complete an online survey for a financial compensation of $.50. Prior research argued that researchers can recruit diverse samples from such channels and can acquire very acceptable quality of data for academic research (Buhrmester, Talaifar, & Gosling, 2018). Respondents had to be organizationally employed at least 35 hours per week and be caring a loved one (i.e., family member, relative, friend, neighbor) who had to be 50 years and older. Initially, 510 individuals from a TurkPrime panel who are currently providing eldercare completed a prescreening survey, 301 of whom met the criteria and were invited to complete the full survey, and 292 responded to the full survey. Five validation questions were embedded to ensure effortful responding (e.g., “Select often if you are paying attention to this item”). Respondents who failed to correctly complete at least 4 of the 5 questions were excluded. After data cleaning, 243 individuals were retained. The majority of the sample was female (58%) and White/non-Hispanic (69%) and was caring for a parent/parent-in-law and grandparent/grandparent-in-law (85%). Sixty-two percent had at least a 4-year college degree and 62% worked in nonsupervisory positions. Hours worked per week ranged from 35 to 90 (M = 41.32 h, SD = 5.69). Hours devoted to elder caregiving per week ranged from 1 to 80 (M = 23.29 h, SD = 15.29). Participants’ ages ranged from 20 to 69 (M = 37.93 years, SD = 11.26). Eldercare recipients’ ages ranged from 50 to 99 (M = 75.09 years, SD = 11.29). Average job tenure was 6.52 years (SD = 6.10).
Eldercare demands were measured with all 22 items developed by Zarit et al. (1985). We followed the recommendation of Bédard et al. (2001) and computed the average score of the 4-item version, which has been used in the weekly diary study. Furthermore, following the editor’s and reviewers’ suggestion, we eliminated two conceptually overlapping items (i.e., do not have enough time for yourself, stressed between caring for elders and trying to meet other responsibilities) and computed the average score of the remaining two items. Family-to-work conflict was measured by using the same 3-item subscale of family-to-work conflict (Grzywacz et al., 2006). Time theft was measured by the same 6 items used in the weekly diary study (Bennett & Robinson, 2000; Dalal et al., 2009; Henle et al., 2010; Lorinkova & Perry, 2017). Following the editor’s and reviewers’ suggestion, we eliminated two conceptually overlapping items (i.e., worked on a personal matter instead of working for your employer, surfed the Internet to deal with personal matters at your workplace) and computed the average score of the remaining four items. Organizational deviance was measured by using the 12-item subscale of organizational deviance developed by Bennett and Robinson (2000). Time banditry was measured using the 31-item questionnaire developed by Brock et al. (2013). This measure contains three subscales measuring classic time banditry (18 items), technology-related time banditry (7 items), and socially oriented time banditry (5 items). Production deviance (3 items) and withdrawal (4 items) were measured by using the two subscales from the 32-item Counterproductive Work Behavior Checklist (CWB-C; Spector et al., 2006).
Appendix Table 2 provides Cronbach’s alphas and correlations among all measured variables. All other descriptive statistics are available from the first author. The 4-item eldercare demands measure (r = .87, p < .01) and the 2-item eldercare demands measure (r = .82, p < .01) were significantly correlated with the full 22-item eldercare demands measure. The 4-item eldercare demands measure and the 2-item eldercare demands measure were significantly correlated (r = .90, p < .01). Furthermore, a similar pattern of relationships with all other measured variables was observed, and the magnitudes of these correlations were quite similar.
The 6-item time theft measure and the 4-item time theft measure were significantly correlated (r = .98, p < .01). Moreover, the 6-item time theft measure and the 4-item time theft measure were similarly correlated with production deviance (r = .58, p < .01; r = .59, p < .01), withdrawal (r = .74, p < .01; r = .74, p < .01), overall time banditry (r = .78, p < .01; r = .75, p < .01), classic time banditry (r = .78, p < .01; r = .77, p < .01), technology-related time banditry (r = .51, p < .01; r = .44, p < .01), socially oriented time banditry (r = .64, p < .01; r = .60, p < .01), organizational deviance (r = .73, p < .01; r = .75, p < .01), and family-to-work conflict (r = .54, p < .01; r = .53, p < .01).
The short measures of eldercare demands were strongly correlated with the full measure of eldercare demands. The short measures of time theft were also strongly correlated with other established measures, including time banditry, production deviance, and organizational deviance. These results suggest that the short measures used in the weekly diary study are valid measures of their respective constructs.
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Peng, Y., Jex, S., Zhang, W. et al. Eldercare Demands and Time Theft: Integrating Family-to-Work Conflict and Spillover–Crossover Perspectives. J Bus Psychol 35, 45–58 (2020). https://doi.org/10.1007/s10869-019-09620-3
- Time theft
- Family-to-work conflict
- Spillover–crossover model