Jenny Baker / Friday, September 23, 2022 / Categories: 602 SIOP Award Winners: Meet Christina Guthier, Christian Dormann, and Manuel Voelkle, the Schmidt-Hunter Meta-Analysis Award Winners Liberty J. Munson As part of our ongoing series to provide visibility into what it takes to earn a SIOP award or grant, we highlight a diverse class of award winners in each edition of TIP. We hope that this insight encourages you to consider applying for a SIOP award or grant because you are probably doing something amazing that can and should be recognized by your peers in I-O psychology! This quarter, we are highlighting SIOP’s 2022 Schmidt-Hunter Meta-Analysis Award winners: Christina Guthier, Christian Dormann, and Manuel Voelkle. They won the award for their paper “Reciprocal effects between job stressors and burnout: A continuous time meta-analysis of longitudinal studies,” published in Psychological Bulletin. Their analysis dealt with a societally important topic, and it revealed some novel findings. Share a little bit about who you are and what you do. My name is Christina Guthier. As a self-employed scientist and speaker, I am sharing all of my knowledge about burnout with organizations to foster change towards healthier work environments. I am also involved in research projects on topics like disability leadership, motivation, and work engagement as well as exhaustion. My name is Christian Dormann. I am a professor for business education and management at Johannes Gutenberg-University Mainz and adjunct research professor at the University of South Australia. Broadly speaking, my research is on longitudinal stress. My name is Manuel Voelkle. I am a professor for psychological research methods at Humboldt-Universitaet zu Berlin in Germany. Broadly speaking, my research and teaching revolves around the design and analysis of multivariate empirical studies with an emphasis on the use of structural equation models and/or the analysis of longitudinal data. Describe the research/work that you did that resulted in this award. What led to your idea? We reviewed all existing longitudinal studies that investigated workload and burnout. Workload is the most frequently investigated job stressor, and burnout the most frequently investigated outcome of job-related stress. We developed a new statistical method called COntinuous-TIme Meta-Analysis (CoTiMA). CoTiMA enables researchers to estimate the average effects among workload and burnout across all available longitudinal studies, irrespective of how many times workload and burnout were measured in these studies and of how long the time intervals between measurement occasions were. This was a distinct methodological innovation. The most important substantive result was that burnout increases workload in the future (strain effect) more strongly than workload increases future burnout (stressor effect). The stressor effect is proposed by all existing work stress theories whereas the strain effect is rarely included. What do you think was key to you winning this award? We think that the key to winning the award was a combination of three major points: (a) theoretical contribution, (b) first application of CoTiMA, and (c) additional analyses on replicability of effects. First, we propose the unexpected strain effect from burnout on workload to be a perception effect, which opens the avenue for a stream of new research addressing questions such as what kinds of job stressors are involved in strain effects or what kinds of mechanisms could buffer these effects to prevent severe stress symptoms in the long run. Second, the first application of the newly developed Continuous Time Meta-Analysis (CoTiMA) approach allowed us to take different time intervals into account that were used in the primary studies. Third, we provided extensive additional analyses on the replicability of the effects. These analyses show that the unexpected and stronger strain effects are less likely to be the result of publication bias and other sorts of questionable research practices than the weaker but usually predicted stressor effect. What did you learn that surprised you? Did you have an “aha” moment? What was it? Only a few authors assumed strain effects before, although the strain effect is indeed about twice as strong as the stressor effect. Overall, there is a vicious circle by which perceived workload and burnout mutually affect each other. The vicious circle might be broken by the moderating effects of job control and job support. However, moderation unexpectedly occurs for the strain effect and not the stressor effect. What do you see as the lasting/unique contribution of this work to our discipline? How can it be used to drive changes in organizations, the employee experience, and so on? Because the strain effect is stronger, our research puts an emphasis on the human experience of work as a starting point of developing new interventions or work environments where people are both healthy and productive. Conversations and actions need to focus more on making sure that individuals are equipped with the right resources to overcome burnout rather than avoiding workload and other stressful work conditions. Avoidance is not realistic, and it may even undermine individual self-efficacy beliefs that they are able to successfully deal with stressful conditions. Who would you say was the biggest advocate of your research/work that resulted in the award? How did that person become aware of your work? Many previous analyses (including our own) showed that results that align to major theories are more likely to be published. It is much more difficult to publish unexpected findings. This, however, does not mean that the scientific community does not appreciate unexpected findings. Once they are published, they are frequently appreciated, thought provoking, and very inspiring for many. Thus, the biggest advocate probably is the scientific community as a whole, who likes this sort of brain food. To what extent would you say this work/research was interdisciplinary? With regard to the content and data used in our research, it was not interdisciplinary. Indeed, one problem is that psychologists prefer longitudinal studies whereas researchers from the medical disciplines prefer prospective designs. We would have loved to include such studies, too, but some of their features prevented us from doing so (e.g., starting with only healthy people, measuring workload only at the first measurement occasion, etc.). With regard to the data analysis approach, our interdisciplinary collaboration with Manuel Voelkle, who is a methodological expert, was very beneficial to ensure analytical quality. Are you still doing work/research in the same area where you won the award? If so, what are you currently working on in this space? If not, what are you working on now, and how did you move into this different work/research area? Yes, we do, but we have now started to broaden our scope to include different sorts of working conditions and different sorts of possible outcomes. We do so in internationally composed teams, and we are still expecting the unexpected. What’s a fun fact about yourself (something that people may not know)? Christina Guthier: I can play three ukuleles (soprano, tenor, and bass) Christian Dormann: I started studying math first but was dissatisfied with the job prospects, which were either becoming a statistician or a teacher. Then moved to psychology. Ended up with a job involving lots of teaching and statistics. Manuel Voelkle: As a judo player, I enjoy wrestling with people just as much as wrestling with equations. Albeit lately, I primarily wrestle with my kids. What piece of advice would you give to someone new to I-O psychology? (If you knew then what you know now…) Christina Guthier: I think the most exciting research projects are either practitioner–scientist or interdisciplinary collaborations. So, I would recommend not only learning how to do valuable research but also starting to network broadly as early as possible. Christian Dormann: Do research on one broadly defined topic, identify important but under-researched issues, develop the most appropriate research design possible, in collaboration with other stakeholders, know what you are doing in your statistical analysis, and learn to know how to craft articles that are interesting to the reader. Writing articles is like crafting a story, there are standards that define excellent craftsmanship, and crafting can be learned. About the author: Liberty Munson is currently the director of Psychometrics of the Microsoft Worldwide Learning programs in the Worldwide Learning organization. She is responsible for ensuring the validity and reliability of Microsoft’s certification programs. Her passion is for finding innovative solutions to business challenges that balance the science of assessment design and development with the realities of budget, time, and schedule constraints. Most recently, she has been presenting on the future of testing and how technology can change the way we assess skills. Liberty loves to bake, hike, backpack, and camp with her husband, Scott, and miniature schnauzer, Apex. If she’s not at work, you’ll find her enjoying the great outdoors or in her kitchen tweaking some recipe just to see what happens. Her advice to someone new to I-O psychology? Statistics, statistics, statistics—knowing data analytic techniques will open A LOT of doors in this field and beyond! Print 129 Rate this article: No rating Comments are only visible to subscribers.