Cause and effect: Optimizing the designs of longitudinal studies in occupational health psychology

According to the National Institute for Occupational Safety and Health, occupational health psychology (OHP) involves “the application of psychology to improving the quality of work life, and to protecting and promoting the safety, health and well-being of workers” (NIOSH, 2013). Although not everyone may agree with this definition (is OHPresearch only about the application of currently available psychological knowledge to working life, or does it also generate new and even fundamental insights? ), to make a difference in workers’ lives is certainly a key concern in our discipline. Achieving this aim requires in-depth knowledge of the causal processes that affect these desiderata: healthy work and healthy workers. In order to obtain such knowledge, we need longitudinal studies in which the same variables are measured at least twice across time for the same set of participants (e.g. Hassett & Paavilainen-Mäntymäki, 2013; Menard, 2007; Ployhart & Vandenberg, 2010). Although cross-sectional designs can tell us whether particular variables are associated in ways that are proposed by theories, longitudinal research designs can also provide us with information about the temporal order of the events underlying these associations, show how the presumed “outcomes” have changed across time and whether this change can be ascribed to (changes in) the alleged “independent” variables. Accordingly, over the last two decades the number of OHP studies examining causal processes through longitudinal research designs has increased steadily (see, for instance, Austin, Scherbaum, & Mahlmann, 2002; StoneRomero, 2011). A number of such studies are included in this special edition of Work & Stress, which is devoted to longitudinal research. An intriguing question is whether our understanding of the causal underpinnings of occupational safety, health and well-being has increased at a similar pace. To some extent it has: longitudinal studies have often confirmed and clarified relations that were previously mainly obtained in cross-sectional research. For example, by now we know that high job demands, low support and low control adversely affect well-being longitudinally and, by implication, causally (Häusser, Mojzisch, Niesel, & SchulzHardt, 2010). However, longitudinal studies have also produced unexpected and confusing findings, and sometimes have not replicated associations that had been firmly established cross-sectionally. We believe that this is at least partly due to poor a priori consideration of what exactly should be the right longitudinal design for studying the specific causal relations at hand. That is, researchers should carefully consider their choice of research design in the light of theories on the specific relations under study, previous empirical studies on these relations, and practical considerations, paying due attention to each of these three aspects. In this editorial we focus on two pivotal sets of issues that warrant more attention, namely (1) the length of the time intervals employed in longitudinal designs, and (2) the issue of reciprocal (i.e. bi-directional) effects. Work & Stress, 2014 Vol. 28, No. 1, 1–8, http://dx.doi. org/10.1080/02678373.2014. 878494