
Realist synthesis techniques can be used to assess complex interventions by extracting and synthesizing configurations of contexts, mechanisms, and outcomes found in the literature. Our novel and multi‐pronged approach to the realist synthesis of workplace harassment interventions describes our pursuit of theory to link macro and program level theories. After discovering the limitations of a dogmatic approach to realist synthesis, we adapted our search strategy and focused our analysis on a subset of data. We tailored our realist synthesis to understand how, why, and under what circumstances workplace harassment interventions are effective. The result was a conceptual framework to test our theory‐based interventions and provide the basis for subsequent realist evaluation. Our experience documented in this article contributes to an understanding of how, under what circumstances, and with what consequences realist synthesis principles can be customized.
Bullying, Health Care Sector, Sexual Harassment, Research Design, Humans, Health Services Research, Diffusion of Innovation, Workplace, Algorithms, Problem Solving
Bullying, Health Care Sector, Sexual Harassment, Research Design, Humans, Health Services Research, Diffusion of Innovation, Workplace, Algorithms, Problem Solving
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
