Determinants of COVID-19 vaccine acceptance in a high infection-rate country: a cross-sectional study in Russia.

BACKGROUND: COVID-19 vaccine development is proceeding at an unprecedented pace. Once COVID-19 vaccines become widely available, it will be necessary to maximize public vaccine acceptance and coverage. OBJECTIVE: This research aimed to analyze the predictors of COVID-19 vaccine acceptance in Russia. METHODS: A cross-sectional online survey was conducted among Russian adults from September 26th to November 9th, 2020. Predictors of the intent to take up COVID-19 vaccination were explored using logistic regression. RESULTS: Out of 876 participants, 365 (41.7%) would be willing to receive the vaccine if it became available. Acceptance increased for a vaccine with verified safety and effectiveness (63.2%). Intention to receive the COVID-19 vaccine was relatively higher among males (aOR=2.37, 95% CI 1.41-4.00), people with lower monthly income (aOR=2.94, 95%CI 1.32-6.57), and with positive trust in the healthcare system (aOR=2.73, 95% CI 1.76-4.24). The Russian people were more likely to accept the COVID-19 vaccine if they believed that the vaccine reduces the risk of virus infection (aOR=8.80, 95%CI 5.21-14.87) or relieves the complications of the disease (aOR=10.46, 95%CI 6.09-17.96). Other barriers such as being unconcerned about side-effects (aOR=1.65, 95%CI 1.03-2.65) and the effectiveness and safety of the vaccination (aOR=2.55, 95%CI 1.60-4.08), also affected acceptance. CONCLUSIONS: The study showed the usefulness of the health belief model constructs in understanding the COVID-19 vaccination acceptance rate in the Russian population. This rate was influenced by sociodemographic and health-related characteristics, and health beliefs. These findings might help guide future efforts for policymakers and stakeholders to improve vaccination rates by enhancing trust in the healthcare system.

Determinants of COVID-19 vaccine acceptance in a high infection-rate country: a cross-sectional study in Russia

BACKGROUND: COVID-19 vaccine development is proceeding at an unprecedented pace. Once COVID-19 vaccines become widely available, it will be necessary to maximize public vaccine acceptance and coverage. OBJECTIVE: This research aimed to analyze the predictors of COVID-19 vaccine acceptance in Russia. METHODS: A cross-sectional online survey was conducted among Russian adults from September 26th to November 9th, 2020. Predictors of the intent to take up COVID-19 vaccination were explored using logistic regression. RESULTS: Out of 876 participants, 365 (41.7%) would be willing to receive the vaccine if it became available. Acceptance increased for a vaccine with verified safety and effectiveness (63.2%). Intention to receive the COVID-19 vaccine was relatively higher among males (aOR=2.37, 95% CI 1.41-4.00), people with lower monthly income (aOR=2.94, 95%CI 1.32-6.57), and with positive trust in the healthcare system (aOR=2.73, 95% CI 1.76-4.24). The Russian people were more likely to accept the COVID-19 vaccine if they believed that the vaccine reduces the risk of virus infection (aOR=8.80, 95%CI 5.21-14.87) or relieves the complications of the disease (aOR=10.46, 95%CI 6.09-17.96). Other barriers such as being unconcerned about side-effects (aOR=1.65, 95%CI 1.03-2.65) and the effectiveness and safety of the vaccination (aOR=2.55, 95%CI 1.60-4.08), also affected acceptance. CONCLUSIONS: The study showed the usefulness of the health belief model constructs in understanding the COVID-19 vaccination acceptance rate in the Russian population. This rate was influenced by sociodemographic and health-related characteristics, and health beliefs. These findings might help guide future efforts for policymakers and stakeholders to improve vaccination rates by enhancing trust in the healthcare system

No disponible

Detecting Data Quality Issues in Clinical Trials: Current Practices and Recommendations.

BACKGROUND: Data quality issues in clinical trials can be caused by a variety of behaviors including fraud, misconduct, intentional or unintentional noncompliance, and significant carelessness. Regardless of how these behaviors are defined, they may compromise the validity of the study results. Reliable study results and quality data are needed to evaluate products for marketing approval and for decisions that are made on the use of medicine. This article focuses on detecting data quality issues, irrespective of origin or motive. Early detection of data quality issues are important so that corrective actions taken can be implemented during the conduct of the trial, recurrence can be prevented, and data quality can be preserved. METHODS: A survey was distributed to TransCelerate member companies to assess current strategies for detecting and mitigating risks involving fraud and misconduct in clinical trials. A review of literature across many industries from 1985 to 2014 was conducted using multiple platforms. RESULTS: Eighteen TransCelerate member companies anonymously responded to the survey. All of the respondents had one or more existing strategies for fraud and misconduct detection. The literature search identified current practices and methodologies across many industries. CONCLUSIONS: TransCelerate recommends the creation of an integrated, multifaceted approach to proactively detect data quality issues. Detection methods should include a strategy tailored to the characteristics of the study. Some sponsors are taking advantage of more advanced methods and integrated processes and systems to proactively detect and address issues, relying on advances in technology to more efficiently review data in real time. Further research is underway to assess statistical data quality detection methodology in clinical trials.