A Survey of the Perceptions, Knowledge, and Use of Core Outcome Sets in Parkinson’s Disease (PD) Trials: A Cross-Sectional Study

Background: Parkinson’s Disease (PD) is a neurodegenerative condition affecting more than 10 million individuals globally, with an increasing annual incidence and profound, multifactorial consequences. Quality medical decision-making for PD patients is guided by clinical trials. Given the importance of clinical trials, Core Outcome Sets (COS) were created to provide standardized recommendations for trial measurements so trial efficacy could be more accurately compared. However, the PD COS have been poorly implemented in clinical trials since its publication in 2018. As funding for PD research increases, it becomes increasingly critical to comprehend the factors impacting the adoption of PD COS, ensuring the supported research holds clinical significance. This cross-sectional study aims to identify these factors by gathering trialists’ insights in a web-based survey. Our primary objective is to gain a more robust understanding of trialists’ perception, awareness, and experience with the current PD COS to identify its implementation barriers.

Methods: In a previous study, we extracted clinical trial measurement tools from PD trials before and after COS publication to evaluate PD COS uptake. For this study, we screened this set of trials to include clinical trialists who have participated in the design, implementation, or analysis of PD trials within the past five years. We then extracted the contact information of 1000 trialists to serve as survey recipients. The survey is designed to be comprehensive and will consist of a set of 20 questions. Participants will have informed consent and maintain complete anonymity. The participants' familiarity with the COS will determine their navigation through the survey. Surveys will be developed and distributed to trialists via REDCap (Research Electronic Data Capture), a secure web-based application designed for research data collection. Data analysis may include both descriptive and inferential statistics. Qualitative data will also be obtained from open-ended questions.

Results: Data is currently in the collection phase of this study. Analysis of survey responses will include:
1) Descriptive statistics: summarizes patient demographics and responses to close-ended questions.
2) Inferential statistics: examples include chi-square tests and t-tests which may be used to identify relationships between variables or differences among subgroups.
3) Qualitative data: derived from responses to open-ended questions, which will undergo thematic analysis to discern recurring themes and patterns.

Conclusion: Upon completion of this project, our data will inform us of the use and knowledge of COS by clinical trialists. The insight gained from this study may serve as a foundation for future initiatives and interventions aimed at enhancing the utilization of COS among clinical trialists. These outcomes may promote uniformity in clinical COS reporting, ultimately, improving patient outcomes with PD.