Data sharing intentions of neuroscience researchers: A consequentialist theory perspective

Understanding the intentions of neuroscience researchers to share data is crucial for promoting data sharing within the field. Key determinants of data sharing intentions are explored using structural equation modeling (SEM) based on consequentialist theory. A survey was conducted among 552 Chinese neuroscience researchers using convenience sampling and several scales, including the Egoism Scale, Utilitarianism Scale, and the Chinese versions of the Research Ethics Scale and Data Sharing Intention Scale. SEM analysis revealed a good fit (χ 2 /df = 1.637, RMSEA = 0.025, CFI = 0.960, GFI = 0.979). Egoism influenced data sharing intentions indirectly through research ethics (β = 0.333, p < 0.001), showing complete mediation. Utilitarianism had a strong direct effect (β = 0.813, p < 0.01) and a significant indirect effect (β = 0.0735, p < 0.001) on data sharing intentions. Practice norms had a weaker influence (β = 0.225, p < 0.01). Valuable insights into the data sharing intentions of neuroscience researchers are offered, highlighting the strong influence of utilitarianism on their decisions. Promoting awareness of the collective benefits through education and outreach is crucial for encouraging extensive data sharing among researchers.