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- W3032207452 abstract "Since more than five decades, the replication crisis taints the field of psychological science. Small sample sizes and low statistical power are the identified issues, resulting in a staggering amount of results from studies that can not be replicated. Combating this crisis requires new and scalable approaches that enable innovative testinginstruments. Gamification and Applied Games offer those crucial and innovative new ways to assess cognition in an online setting. On the basis of two original research objects, this thesis highlights the challenges, obstacles and benefits from utilizing gamification and applied games for large-scale phenotypic measurements on the basis of an online platform called COSMOS. First, we applied this concept in the form of our established platform COSMOS which we presented in a published paper. In this paper, we purposed a digital psychometric toolkit in the guise of applied games that enables automatized psychometric data collection while measuring a broad range of cognitive functions. Second, we conducted a pilot study that assessed the feasibility and acceptance of a gamified test of the N-back task called HoNk-Back. We showed that participants like the HoNk-Back more than the non-gamified N-back and are more likely to replay the HoNk-Back again. Both the paper and the pilot study point out the benefits of using gamification and applied games for large-scale neurocognitive phenotype cohort screenings for genetic and imaging studies. The challenges and hurdles for future studies regarding data protection, data security and ethics in the online acquisition of personal data are identified and discussed." @default.
- W3032207452 created "2020-06-05" @default.
- W3032207452 creator A5001955021 @default.
- W3032207452 date "2020-01-01" @default.
- W3032207452 modified "2023-09-27" @default.
- W3032207452 title "Applied Games for smart phenotypic data acquisition - challenges of a web platform with digital gamified testing instruments for online-based large scale phenotyping" @default.
- W3032207452 doi "https://doi.org/10.5451/unibas-007193697" @default.
- W3032207452 hasPublicationYear "2020" @default.
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