Should CRISPR-Cas9 Be Used in Human Embryos to Eliminate Genetic Diseases? Public Attitudes and Benefit–Risk Analysis

Abstract

CRISPR-Cas9 is one of the most extraordinary biotechnologies of the twenty-first century, and its possible application to editing human embryos to cure hereditary diseases still brings up some ethical, social, and technical questions. The current research examines the survey-based public perceptions and probabilistic benefits and risks trades-offs using a mixture of the primary survey data and mathematical model. A questionnaire that was structured and given to 320 participants; mostly students aged 16 and above, was used to measure demographic variables, risk perception, and trust in science and support of CRISPR in the event of severe disease, mild disease, and enhancement. It was found that there was high ranking of acceptance with the strongest support going to the severe cases of therapeutic application, moderate to mild disease cases having moderate and slight support respectively and enhancement hardly receiving support. The results of statistical testing proved the significant difference between severe disease and enhancement support. Contrary to the expectations, risk perception was not a significant predictor of support and such a result suggests that the aspect of humanitarian may override the aspect of technical in the sampled population. Probabilistic modelling of cystic fibrosis and Huntington’s disease demonstrated that expected net benefits remained positive across reported ranges of editing efficiency and off-target probabilities, with high-burden diseases offering substantially greater margins of acceptable risk. Demographic variables, including age, field of study, and prior knowledge, were not significant predictors of support, suggesting that ethical reasoning exerts more influence than background characteristics. The findings provide evidence that therapeutic necessity dominates public acceptance of embryo editing among the sampled academic population and that quantitative models can reinforce the case for carefully regulated medical applications. Limitations include the use of a nonrepresentative sample, primarily students, which may not fully reflect broader public attitudes.