Factors Affecting Acceptance of Participating in Clinical Trials of New Drugs: A National Cross-Sectional Study

Clinical trials are regarded as an essential method for developing new treatments and giving patients access to potentially effective medications that are still being studied. This study aimed to evaluate acceptance of participating in clinical trials of new drugs and to further explore the associated factors.

A population-based cross-sectional study was conducted in China from June 20 to August 31, 2022. We collected demographic data and used visual analog scale scores to assess the public's willingness to accept clinical trials of new drugs (range 0-100). Linear regression analysis was adopted to evaluate the factors related to attitudes toward clinical trials of new drugs.

This survey contained 19,710 valid questionnaires to investigate acceptance of participating in clinical trials of new drugs. Participants showed low willingness to accept clinical trials of new drugs, with a mean score of 44.69 out of 100. The results showed that rural residence (β = 3.00), western China (β = 3.15), being married (β = 2.93), older age (31-59 years [β = 3.84], ≥60 years [β = 7.71]), having cancer or rare diseases (β = 5.15), higher monthly household income (>6000 yuan [β = 1.76]), medical-related occupations (β = 8.01), anxiety status (moderate anxiety [β = 1.83]), moderate to severe anxiety [β = 2.66]), perceived stress (β = 0.51), health literacy (β = 0.21), self-efficacy (β = 0.34), and media use (β = 0.42) were associated with higher acceptance of participating in clinical trials of new drugs. However, central China (β = -1.65), female sex (β = -2.29), chronic diseases (β = -2.45), and medical insurance (β = -3.78) were associated with lower acceptance of participating in clinical trials of new drugs. Subgroup analysis demonstrated consistent trends across age and chronic disease subgroups.

This reveales low public willingness to accept clinical trials of new drugs. The willingness is affected by marital status, occupation, area of residence, income, health insurance, physical and mental health status, media use, and health literacy.