Trust in the Food and Drug Administration: A National Survey Study.

Building trust in public health agencies like the US Food and Drug Administration (FDA) has become a key government priority. Understanding the roots of FDA mistrust is important if the agency is to develop targeted messaging and reforms aimed at building confidence in the agency. We conducted a survey of 2,021 respondents in the US probing attitudes toward the FDA. The primary outcome was FDA trust, defined as the mean score that each respondent assigned to the FDA across four prespecified axes: (1) competence and effectiveness; (2) commitment to acting in the best interests of the American public; (3) abiding by the rules and regulations set forth by policy or law; and (4) expertise in health, science, and medicine. On multivariable ordinal logistic regression, FDA mistrust was associated with female gender (odds ratio [OR] = 0.74, 95% confidence interval [CI] 0.62-0.88), rural community (OR 0.85, 95% CI 0.75-0.96), conservative political views (OR 0.77, 95% CI 0.74-0.81), worse self-reported health (OR 0.89, 95% CI 0.80-0.98), lower satisfaction with health care received (OR 0.63, 95% CI 0.56-0.71), less attention to health and science news (OR 0.72, 95% CI 0.64-0.80), and not having children under the age of 18 (OR 0.72, 95% CI 0.60-0.86). These findings underscore the challenges faced by US political leaders in convincing a heterogeneous American public to trust the FDA. The FDA should develop and deploy targeted outreach strategies to populations with lower levels of trust and strengthen internal processes that minimize biases and ensure sound decision-making.

Excess Fatal Overdoses in the United States During the COVID-19 Pandemic by Geography and Substance Type: March 2020-August 2021.

Objectives. To assess heterogeneity in pandemic-period excess fatal overdoses in the United States, by location (state, county) and substance type. Methods. We used seasonal autoregressive integrated moving average (SARIMA) models to estimate counterfactual death counts in the scenario that no pandemic had occurred. Such estimates were subtracted from actual death counts to assess the magnitude of pandemic-period excess mortality between March 2020 and August 2021. Results. Nationwide, we estimated 25 668 (95% prediction interval [PI] = 2811, 48 524) excess overdose deaths. Specifically, 17 of 47 states and 197 of 592 counties analyzed had statistically significant excess overdose-related mortality. West Virginia, Louisiana, Tennessee, Kentucky, and New Mexico had the highest rates (20-37 per 100 000). Nationally, there were 5.7 (95% PI = 1.0, 10.4), 3.1 (95% PI = 2.1, 4.2), and 1.4 (95% PI = 0.5, 2.4) excess deaths per 100 000 involving synthetic opioids, psychostimulants, and alcohol, respectively. Conclusions. The steep increase in overdose-related mortality affected primarily the southern and western United States. We identified synthetic opioids and psychostimulants as the main contributors. Public Health Implications. Characterizing overdose-related excess mortality across locations and substance types is critical for optimal allocation of public health resources. (Am J Public Health. 2024;114(6):599-609. https://doi.org/10.2105/AJPH.2024.307618).

Leah Z. Rand, Daniel P. Carpenter, Aaron S. Kesselheim, Anushka Bhaskar, Jonathan J. Darrow, and William B. Feldman Reply.

The authors respond to a letter by Mitchell Berger in the March-April 2024 issue of the Hastings Center Report concerning their essay "Securing the Trustworthiness of the FDA to Build Public Trust in Vaccines."

Securing the Trustworthiness of the FDA to Build Public Trust in Vaccines.

The Covid-19 pandemic highlighted the need to examine public trust in the U.S. Food and Drug Administration (FDA) vaccine approval process and the role of political influence in the FDA's decisions. Ensuring that the FDA is itself trustworthy is important for justifying public trust in its actions, like vaccine approvals, thereby promoting public health. We propose five conditions of trustworthiness that the FDA should meet when it reviews vaccines, even during emergencies: consistency with rules, proper expert or political decision-makers, proper decision-making and noninterference, connection to public preference, and transparency of both reasons and procedures. The five conditions provide a road map of procedural and substantive requirements, which the FDA has variably implemented, focused on ensuring appropriate influence of political interests. While being a trustworthy agency cannot guarantee the public's trust, implementing these conditions builds a groundwork for public trust.

What Should Be Clinicians' Roles in Regulatory Assessment of Prospective Interventions' Risks of Exacerbating Inequity?

When there is an evidence base that could be used credibly to justify expedited US Food and Drug Administration review, emergency use authorization, or approval, interventions-in-development must be evaluated in terms of their possible downstream influence on public trust and confidence in regulatory processes during a national public health crisis. When regulatory decisions express overconfidence about a prospective intervention's success, there is risk that the costliness of or misinformation about the intervention will exacerbate health inequity. A converse risk is regulators' underestimation of an intervention's value in treating populations at risk for inequitable care. This article considers the nature and scope of clinicians' roles in regulatory processes in which such risks must be considered and balanced to promote public safety and public health.

Screening of Parkinson's Disease Using Geometric Features Extracted from Spiral Drawings.

Conventional means of Parkinson's Disease (PD) screening rely on qualitative tests typically administered by trained neurologists. Tablet technologies that enable data collection during handwriting and drawing tasks may provide low-cost, portable, and instantaneous quantitative methods for high-throughput PD screening. However, past efforts to use data from tablet-based drawing processes to distinguish between PD and control populations have demonstrated only moderate classification ability. Focusing on digitized drawings of Archimedean spirals, the present study utilized data from the open-access ParkinsonHW dataset to improve existing PD drawing diagnostic pipelines. Random forest classifiers were constructed using previously documented features and highly-predictive, newly-proposed features that leverage the many unique mathematical characteristics of the Archimedean spiral. This approach yielded an AUC of 0.999 on the particular dataset we tested on, and more importantly identified interpretable features with good promise for generalization across diverse patient cohorts. It demonstrated the potency of mathematical relationships inherent to the drawing shape and the usefulness of sparse feature sets and simple models, which further enhance interpretability, in the face of limited sample size. The results of this study also inform suggestions for future drawing task design and data analytics (feature extraction, shape selection, task diversity, drawing templates, and data sharing).

Lag time between state-level policy interventions and change points in COVID-19 outcomes in the United States.

State-level policy interventions have been critical in managing the spread of the new coronavirus. Here, we study the lag time between policy interventions and change in COVID-19 outcome trajectory in the United States. We develop a stepwise drifts random walk model to account for non-stationarity and strong temporal correlation and subsequently apply a change-point detection algorithm to estimate the number and times of change points in the COVID-19 outcome data. Furthermore, we harmonize data on the estimated change points with non-pharmaceutical interventions adopted by each state of the United States, which provides us insights regarding the lag time between the enactment of a policy and its effect on COVID-19 outcomes. We present the estimated change points for each state and the District of Columbia and find five different emerging trajectory patterns. We also provide insight into the lag time between the enactment of a policy and its effect on COVID-19 outcomes.