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      A preregistered vignette experiment on determinants of health data sharing behavior : Willingness to donate sensor data, medical records, and biomarkers

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          Abstract

          The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data types and recipients, we argue that established social norms shape the acceptance of novel practices of data collection and use. To investigate the willingness to share health data, we conducted a preregistered vignette experiment. The scenarios experimentally varied the vignette dimensions by data type, recipient, and research purpose. While some findings contradict our hypotheses, the results indicate that all three dimensions affected respondents’ data sharing decisions. Additional analyses suggest that institutional and social trust, privacy concerns, technical affinity, altruism, age, and device ownership influence the willingness to share health data.

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          Most cited references60

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          Fitting Linear Mixed-Effects Models Usinglme4

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            G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

            G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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              lmerTest Package: Tests in Linear Mixed Effects Models

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                Author and article information

                Journal
                Politics and the Life Sciences
                Polit. life sci.
                Cambridge University Press (CUP)
                0730-9384
                1471-5457
                2022
                September 15 2022
                2022
                : 41
                : 2
                : 161-181
                Article
                10.1017/pls.2022.15
                9a0fc272-32f5-46b7-848e-f065e17578a0
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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