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Characteristics of shiftwork schedules have implications for off-shift well-being. We examined the extent to which several shift characteristics (e.g., shift length, working Sundays) are associated with three aspects of off-shift well-being: work-to-family conflict, physical well-being, and mental wellbeing. We also investigated whether these relationships differed in four nations. The Survey of Work and Time was completed by 906 healthcare professionals located in Australia, Brazil, Croatia, and the USA. Hierarchical multiple regression analyses supported the hypothesis that shiftwork characteristics account for significant unique variance in all three measures of well-being beyond that accounted for by work and family demands, and personal characteristics. The patterns of regression weights indicated that particular shiftwork characteristics have differential relevance to indices of work-to-family conflict, physical well-being, and mental well-being. Our findings suggest that healthcare organizations should carefully consider the implications of shiftwork characteristics for off-shift well-being. Furthermore, although our findings did not indicate national differences in the nature of relationships between shift characteristics and well-being, shiftwork characteristics and demographics for healthcare professionals differ in systematic ways among nations; as such, effective solutions may be context-specific.

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Insufficient effort responding (IER) is problematic in that it can add a systematic source of variance for variables with average responses that depart from the scale midpoints. We present a rationale for why IER is of particular importance to Work and Organisational Health Psychology (WOHP) researchers. We also demonstrate its biasing effects using several variables of interest to WOHP researchers (perceived work ability, negative affectivity, perceived disability, work-safety tension, accident/injury frequencies, and experienced and instigated incivility) in two datasets. As expected, IER was significantly correlated with the focal study variables. We also found some evidence that hypothesised bivariate correlations between these variables were inflated when IER respondents were included. Corroborating IERs potential confounding role, we further found significant declines in the magnitude of the hypothesised bivariate correlations after partialling out IER. In addition, we found evidence for biasing (under-estimation) effects for predictors not contaminated by IER in multiple regression models where some predictors and the outcome were both contaminated by IER. We call for WOHP researchers to routinely discourage IER from occurring in their surveys, screen for IER prior to analyzing survey data, and establish a standard practice for handling IER cases.