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- Title
Preferences for Updates on General Research Results: A Survey of Participants in Genomic Research from Two Institutions.
- Authors
Taylor, Casey Overby; Manov, Natalie Flaks; Crew, Katherine D.; Weng, Chunhua; Connolly, John J.; Chute, Christopher G.; Ford, Daniel E.; Lehmann, Harold; Rahm, Alanna Kulchak; Kullo, Iftikhar J.; Caraballo, Pedro J.; Holm, Ingrid A.; Mathews, Debra; Qureshi, Nadeem
- Abstract
There is a need for multimodal strategies to keep research participants informed about study results. Our aim was to characterize preferences of genomic research participants from two institutions along four dimensions of general research result updates: content, timing, mechanism, and frequency. Methods: We conducted a web-based cross-sectional survey that was administered from 25 June 2018 to 5 December 2018. Results: 397 participants completed the survey, most of whom (96%) expressed a desire to receive research updates. Preferences with high endorsement included: update content (brief descriptions of major findings, descriptions of purpose and goals, and educational material); update timing (when the research is completed, when findings are reviewed, when findings are published, and when the study status changes); update mechanism (email with updates, and email newsletter); and update frequency (every three months). Hierarchical cluster analyses based on the four update preferences identified four profiles of participants with similar preference patterns. Very few participants in the largest profile were comfortable with budgeting less money for research activities so that researchers have money to set up services to send research result updates to study participants. Conclusion: Future studies may benefit from exploring preferences for research result updates, as we have in our study. In addition, this work provides evidence of a need for funders to incentivize researchers to communicate results to participants.
- Subjects
PARTICIPANT observation; HUMAN research subjects; ELECTRONIC newsletters; HIERARCHICAL clustering (Cluster analysis); CLUSTER analysis (Statistics); EMAIL
- Publication
Journal of Personalized Medicine, 2021, Vol 11, Issue 5, p399
- ISSN
2075-4426
- Publication type
Article
- DOI
10.3390/jpm11050399