- Explaining the goals of human factors validation and what data are important
- Identifying the reasons behind human factors validation methods and how the data differ from other types of research
- Showing the different ways non-experts can interpret results and advice for better understanding study outcomes (e.g., raw data, reports)
- Relating human factors validation results to user needs validation
In a human factors validation study, “performance data” (use errors, close calls, and use difficulties) are the primary points of interest. Unlike many types of research, the performance data from human factors validation studies do not tell a complete story on their own. Once raw performance data from human factors validation are generated, there are several steps to understanding the results and their implications. These steps include: understanding participants’ subjective assessments of any findings, performing root cause analysis to identify why each finding occurred, and performing residual risk analysis. Only after these steps are completed can human factors experts draw conclusions on a product’s safety and effectiveness.
This presentation will provide non-human factors experts with a deeper understanding of human factors validation goals and how to interpret human factors validation results. The objective of this presentation is to help stakeholders shift their focus away from the raw data and understand that the complete context of the performance data is key to drawing conclusions from a human factors validation study.
Alexandra Benbadis, Usability Leader, Sanofi
