Evidence map›Paper›PMID 38547079›Full record

ArticlePloS one2024

Developing medical simulations for opioid overdose response training: A qualitative analysis of narratives from responders to overdoses.

G Franklin Edwards, Cassandra Mierisch, Brock Mutcheson, Allison Strauss, Keel Coleman, Kimberly Horn, Sarah Henrickson Parker

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

G Franklin EdwardsGraduate Program in Translational Biology, Medicine, and Health, Virginia Tech, Blacksburg, Virginia, United States of America.ORCID 0000-0002-5071-5288
Cassandra MierischDepartment of Basic Science Education, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, United States of America.
Brock MutchesonOffice of Assessment and Program Evaluation, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, United States of America.
Allison StraussVirginia Tech Carilion School of Medicine, Roanoke, Virginia, United States of America.
Keel ColemanDepartment of Emergency Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, United States of America.
Kimberly HornDepartment of Population Health Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, Virginia, United States of America.
Sarah Henrickson ParkerFralin Biomedical Research Institute at VTC, Roanoke, Virginia, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical simulation offers a controlled environment for studying challenging clinical care situations that are difficult to observe directly. Overdose education and naloxone distribution (OEND) programs aim to train potential rescuers in responding to opioid overdoses, but assessing rescuer performance in real-life situations before emergency medical services arrive is exceedingly complex. There is an opportunity to incorporate individuals with firsthand experience in treating out-of-hospital overdoses into the development of simulation scenarios. Realistic overdose simulations could provide OEND programs with valuable tools to effectively teach hands-on skills and support context-sensitive training regimens. In this research, semi-structured interviews were conducted with 17 individuals experienced in responding to opioid overdoses including emergency department physicians, first responders, OEND program instructors, and peer recovery specialists. Two coders conducted qualitative content analysis using open and axial thematic coding to identify nuances associated with illicit and prescription opioid overdoses. The results are presented as narrative findings complemented by summaries of the frequency of themes across the interviews. Over 20 hours of audio recording were transcribed verbatim and then coded. During the open and axial thematic coding process several primary themes, along with subthemes, were identified, highlighting the distinctions between illicit and prescription opioid overdoses. Distinct contextual details, such as locations, clinical presentations, the environment surrounding the patient, and bystanders' behavior, were used to create four example simulations of out-of-hospital overdoses. The narrative findings in this qualitative study offer context-sensitive information for developing out-of-hospital overdose scenarios applicable to simulation training. These insights can serve as a valuable resource, aiding instructors and researchers in systematically creating evidence-based scenarios for both training and research purposes.

Indexed as

Drug OverdoseOpiate OverdoseOpioid-Related DisordersAnalgesics, OpioidHumansNaloxoneNarcotic AntagonistsQualitative ResearchAnalgesics, OpioidNaloxoneNarcotic Antagonists

Identifiers

PMID38547079
PMCPMC10977769

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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.