Dataset Information

Messaging to Increase Public Support for Naloxone Distribution Policies in the United States: Results from a Randomized Survey Experiment.

ABSTRACT:

Background

Barriers to public support for naloxone distribution include lack of knowledge, concerns about potential unintended consequences, and lack of sympathy for people at risk of overdose.

Methods

A randomized survey experiment was conducted with a nationally-representative web-based survey research panel (GfK KnowledgePanel). Participants were randomly assigned to read different messages alone or in combination: 1) factual information about naloxone; 2) pre-emptive refutation of potential concerns about naloxone distribution; and 3) a sympathetic narrative about a mother whose daughter died of an opioid overdose. Participants were then asked if they support or oppose policies related to naloxone distribution. For each policy item, logistic regression models were used to test the effect of each message exposure compared with the no-exposure control group.

Results

The final sample consisted of 1,598 participants (completion rate: 72.6%). Factual information and the sympathetic narrative alone each led to higher support for training first responders to use naloxone, providing naloxone to friends and family members of people using opioids, and passing laws to protect people who administer naloxone. Participants receiving the combination of the sympathetic narrative and factual information, compared to factual information alone, were more likely to support all policies: providing naloxone to friends and family members (OR: 2.0 [95% CI: 1.4 to 2.9]), training first responders to use naloxone (OR: 2.0 [95% CI: 1.2 to 3.4]), passing laws to protect people if they administer naloxone (OR: 1.5 [95% CI: 1.04 to 2.2]), and passing laws to protect people if they call for medical help for an overdose (OR: 1.7 [95% CI: 1.2 to 2.5]).

Conclusions

All messages increased public support, but combining factual information and the sympathetic narrative was most effective. Public support for naloxone distribution can be improved through education and sympathetic portrayals of the population who stands to benefit from these policies.

SUBMITTER: Bachhuber MA

PROVIDER: S-EPMC4488484 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Messaging to Increase Public Support for Naloxone Distribution Policies in the United States: Results from a Randomized Survey Experiment.

Bachhuber Marcus A MA McGinty Emma E EE Kennedy-Hendricks Alene A Niederdeppe Jeff J Barry Colleen L CL

PloS one 20150701 7

<h4>Background</h4>Barriers to public support for naloxone distribution include lack of knowledge, concerns about potential unintended consequences, and lack of sympathy for people at risk of overdose.<h4>Methods</h4>A randomized survey experiment was conducted with a nationally-representative web-based survey research panel (GfK KnowledgePanel). Participants were randomly assigned to read different messages alone or in combination: 1) factual information about naloxone; 2) pre-emptive refutatio ...[more]

PMID: 26132859

Similar Datasets

Project description:ImportanceTo mitigate the opioid overdose crisis, states have implemented a variety of legal interventions aimed at increasing access to the opioid antagonist naloxone. Recently, Virginia and Vermont mandated the coprescription of naloxone for potentially at-risk patients.ObjectiveTo assess the association between naloxone coprescription legal mandates and naloxone dispensing in retail pharmacies.Design, setting, and participantsThis was a population-based, state-level cohort study. The sample included all prescriptions dispensed for naloxone in the retail pharmacy setting contained in IQVIA's national prescription audit, which represents 90% of all retail pharmacies in the United States. The unit of observation was state-month and the study period was January 1, 2011, to December 31, 2017.ExposuresState legal intervention mandating naloxone coprescription.Main outcomes and measuresNumber of naloxone prescriptions dispensed. State rates of naloxone prescriptions dispensed per month per 100 000 standard population were calculated.ResultsThe rate of naloxone dispensing increased after implementation of legal mandates for naloxone coprescription. An estimated 88 naloxone prescriptions per 100 000 were dispensed in Virginia and 111 prescriptions per 100 000 were dispensed in Vermont during the first full month the legal requirement was effective. In comparison, 16 naloxone prescriptions per 100 000 were dispensed in the 10 states (including the District of Columbia) with the highest opioid overdose death rates and 6 prescriptions per 100 000 were dispensed in the 39 remaining states. The number of naloxone prescriptions dispensed was associated with the legal mandate for naloxone coprescription (incidence rate ratio [IRR], 7.75; 95% CI, 1.22-49.35). Implementation of the naloxone coprescription mandate was associated with an estimated 214 additional naloxone prescriptions dispensed per month in the period following the mandates, holding all other variables constant. Among covariates, naloxone access laws (IRR, 1.37; 1.05-1.78), opioid overdose death rates (IRR, 1.06; 95% CI, 1.04-1.08), the percentage of naloxone prescriptions paid by third-party payers (IRR 1.009; 1.008-1.010), and time (IRR, 1.06; 95% CI, 1.05-1.07) were significantly associated with naloxone prescription dispensing.Conclusions and relevanceThese study findings suggest that legally mandated naloxone prescription for those at risk for opioid overdose may be associated with substantial increases in naloxone dispensing and further reduction in opioid-related harm.

Dataset Information

Messaging to Increase Public Support for Naloxone Distribution Policies in the United States: Results from a Randomized Survey Experiment.

Background

Methods

Results

Conclusions

Publications

Messaging to Increase Public Support for Naloxone Distribution Policies in the United States: Results from a Randomized Survey Experiment.

Similar Datasets

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