Public Opinion about America’s Opioid Crisis: Severity, Sources, and Solutions in Context

ABSTRACT

The opioid crisis has claimed more than a half-million deaths over the past two decades and is one of the leading causes of injury deaths in the United States. The current study examines: 1) public opinion on the severity of the opioid crisis in terms of lives lost compared to other fatal social events, 2) opinions on who has been most affected by the opioid crisis, and the accuracy of these perceptions, 3) opinions on who is responsible or “to blame” for the crisis and who should fix it and 4) the individual and contextual characteristics that are related to these perceptions. Using data from an October 2019 Amazon Mechanical Turk (MTurk) survey, the Center for Disease Control, and the U.S. Census, we find that the public severely underestimates the death toll of the opioid crisis compared to other fatal events. We also find that public perception of who and where have been most affected is fairly accurate, and such views are highly consistent across different locations, contexts, and sociodemographic characteristics of places and respondents. Additionally, we find that the public collectively views pharmaceutical companies and doctors as responsible for contributing to and fixing the opioid overdose crisis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ We obtained overdose death rate measures from the Centers for Disease Control’s (Centers for Disease Control and Prevention (CDC) 2020b) Restricted-Access Multiple Cause of Death (MCOD) Mortality data. The MCOD Mortality data include all death records in the U.S. from 2014 to 2016 and details the underlying cause of death and contributing causes of death (e.g., specific substance type present in the deceased). Overdose death rates were population-adjusted for county age distributions (see Dwyer-Lindgren et al. 2016). Overdose death rates were also calculated using a 3-year average (2014–2016) to add stability to estimates and to reduce the influence of a single year fluctuation (see Steffensmeier et al. 2010), and rates were square root transformed to adjust for skewness in the measure.

² Multicollinearity was examined, and all variance inflation factors (VIF) were below the recommended thresholds (highest = 2.714) (Belsley, Kuh, and Welsch 1980), which suggest multicollinearity was not a concern.

³ The Washington Post Fatal Force Database is an online and publicly accessible data set (https://github.com/washingtonpost/data-police-shootings). For our study, we report police shooting deaths for year 2018 to correspond with the timing our survey data collection in October 2019. Police shooting deaths for year 2019 were not made available at the time of survey data collection. Other estimates for police shooting such as those provided by the CDC and the National Violent Death Reporting System (NVDRS) are much lower and estimated to be at 632 deaths.

⁴ The CDC figures are drawn from Wilson et al. (2020) Morbidity and Mortality Weekly Report (MMWR) that uses data from the National Vital Statistics System.

⁵ To fully exhaust the data and examine the robustness of our findings, we conducted a series of supplemental analyses using alternative overdose mortality variables. We replicated all models using (1) age adjusted natural opioid overdose death rates (square root transformed to adjust for skewness), and (2) age adjusted synthetic opioid overdose death rates (square root transformed to adjust for skewness). Results from the supplemental analyses yielded substantially the same findings with few slight differences. Some variable coefficients dropped in or out of significance, but the key findings remained the same (results available upon request). We also replicated all models using age adjusted total overdose death rates nontransformed and using the full sample (i.e., including the people who failed attention check questions). Results from both analyses remained substantially similar to our key findings.

⁶ Results from the post-stratification weight models were substantially similar to our main findings reported in the Results. A few additional effects did reach significance in the weighted multivariate models (results available upon request). For example, the county prescription rate and percent of insured individuals in a community had a significant and positive effect in predicting blameworthiness for lack of drug treatment programs. However, the overall findings remained largely the same.

Additional information

Funding

This material is based upon work supported by the National Science Foundation under Grant No. NSF 1849209. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation

Notes on contributors

Diana Sun

Diana Sun is an assistant professor in the School of Criminology and Criminal Justice at Florida Atlantic University. Her research interests include the effects of incarceration on white-collar offenders, healthcare fraud and negligence, and race/ethnicity and crime. [email protected]

Amanda Graham

Amanda Graham is an assistant professor in the Department of Criminal Justice and Criminology at Georgia Southern University. Her research interests focus on policing, fear of police brutality, the impact of race in police-community relationships, police legitimacy, and measurement. Her work appears in journals such as Criminology, Criminal Justice Review, Crime & Delinquency, Policing: An International Journal, and Victims & Offenders. [email protected]

Ben Feldmeyer

Ben Feldmeyer is an associate professor in the School of Criminal Justice at the University of Cincinnati. His research focuses on macro-level patterns of crime and punishment across demographic groups (race/ethnicity, gender, age) and community contexts. [email protected]

Francis T. Cullen

Francis T. Cullen is distinguished research professor emeritus and a senior research associate in the School of Criminal Justice at the University of Cincinnati. He is the recipient of The 2022 Stockholm Prize in Criminology, and he previously served as president of both the American Society of Criminology and the Academy of Criminal Justice Sciences. His current interests include developing the rehabilitation–redemption model of corrections, social support theory, racial attitudes and public policy, and the criminology of Donald Trump. [email protected]

Teresa C. Kulig

Teresa C. Kulig is an assistant professor in the School of Criminology and Criminal Justice at the University of Nebraska at Omaha. Her current interests include studying the nature and control of human trafficking, the measurement and theories of victimization, and the social construction of crime. [email protected]