Assessing the Intention to Provide Human Genetic Resources: An Explanatory Model

Abstract

Background: Human genetic resources are an important material component for life science research and have strategic significance for medical science and technological innovation. In this study, we employ frameworks from social psychology and the science of human behavior to study human genetic resource providers. Aims: We used structural equation techniques to explain factors affecting the intention to provide human genetic resources and the mechanisms for providing such resources. Methods: We conducted an online survey with respondents from ethnic minorities (n = 912). Our model integrates key variables informed by the theory of planned behavior (TPB), the theory of benefit and risk assessment (BRA), as well as variables that represent the policy and political system. Results: Our results show that the factors affecting the intention to provide human genetic resources, ranked from highly influential to less influential, are perceived benefits, privacy risk, attitudes toward providing human genetic resources, perceived behavioral efficacy, psychological risk, subjective norms, and physical risk. The variables informed by the TPB all have a significant positive effect on the intention to provide human genetic resources. With the exception of physical risk, the variables informed by the theory of BRA have a significant effect on the intention to provide human genetic resources. Respondents with different health conditions have significantly different levels of physical risk. Conclusions: The results of our study provide insights into how to improve people's intention to provide human genetic resources. We also proposed ways to protect such resources globally.

Quantitative Evaluation of China’s Biogenetic Resources Conservation Policies Based on the Policy Modeling Consistency Index Model

“…In recent years, scholars in China have usually combined another policy analysis method in addition to the PMC index model to carry out quantitative evaluation of the policy, which, from a comprehensive point of view, mainly includes policy tools, semantic network analysis, knowledge mapping, and text analysis [31]. Taken together, this type of research mainly explores the traditional research methods in the field of policy evaluation [32][33][34], the integration of the PMC index model with other research methods [35][36][37].…”