ArticleContemporary clinical trials2022
Development of opioid rapid response system: Protocol for a randomized controlled trial.
Article in Contemporary clinical trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Developing and Testing the Opioid Rapid Response System
Reducing High School Athletes' Prescription Opioids Misuse and Diversion Through the Student Athlete Wellness Portal
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Effects of Online Naloxone Training for Laypersons: An Extended-Baseline Assessment.Substance use & misuse · 2024Trial
- Developing the Opioid Rapid Response System™ for Lay Citizen Response to the Opioid Overdose Crisis: a Randomized Controlled Trial.Prevention science : the official journal of the Society for Prevention Research · 2023Trial
- Article
- Usability of Mixed Reality for Naloxone Training: Iterative Development and Field Testing of ReviveXR.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundOpioid overdoses require a rapid response, but emergency responders are limited in how quickly they can arrive at the scene for administering naloxone. If laypersons are trained to administer naloxone and are notified of overdoses, more lives can be saved.
objectiveThis study aimed to examine the feasibility of the Opioid Rapid Response System (ORRS) that recruits, trains, and links citizen responders to overdose events in their community in real-time to administer naloxone. Aim of this paper is to present the protocols for recruiting participants through multiple communication channels; developing and evaluating the online training which has both interactive and asynchronous modules; randomly assigning laypersons to either online naloxone training or waitlist control group; measuring participants' knowledge, skills, and attitudes before and after the training; and distributing intranasal naloxone kits to participants for use in events of overdose in their community.
methodsSampling: Utilizing a combination of purposive sampling methods, laypersons from across five Indiana counties who did not self-identify as current first responders were invited to participate.
designIn this two-arm randomized waitlist-controlled study (N = 220), individuals were assigned into either online training or waitlist control that received the training two weeks later. ANALYSIS: A linear mixed model will be used for determining the changes in targeted outcomes in the training group and accommodate for fixed and random effects. IMPLICATIONS: While ORRS can become a community-engaged, cost-effective model for technology-based emergency response for opioid overdoses, study protocols can be useful for other emergency response programs that involve laypersons. CLINICALTRIALS: gov Registration Number: NCT04589676.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.