Evidence map›Paper›PMID 37728974›Full record

ArticleJournal of medical Internet research2023

Differing Behaviors Around Adult Nonmedical Use of Prescription Stimulants and Opioids: Latent Class Analysis.

Karilynn M Rockhill, Richard Olson, Richard C Dart, Janetta L Iwanicki, Joshua C Black

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 36% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
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

5 authors at 1 institution in 1 country.

Karilynn M RockhillRocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, United States.ORCID 0000-0003-2831-4055
Richard OlsonRocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, United States.ORCID 0000-0002-4587-7637
Richard C DartRocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, United States.ORCID 0000-0001-5989-9354
Janetta L IwanickiRocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, United States.ORCID 0000-0001-9608-391X
Joshua C BlackRocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, United States.ORCID 0000-0002-7329-2740
Denver Health Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe availability of central nervous system stimulants has risen in recent years, along with increased dispensing of stimulants for treatment of, for example, parent-reported attention-deficit/hyperactivity disorder in children and new diagnoses during adulthood. Typologies of drug use, as has been done with opioids, fail to include a sufficient range of behavioral factors to contextualize person-centric circumstances surrounding drug use. Understanding these patterns across drug classes would bring public health and regulatory practices toward precision public health.

objectiveThe objective of this study was to quantitatively delineate the unique behavioral profiles of adults who currently nonmedically use stimulants and opioids using a latent class analysis and to contrast the differences in findings by class. We further evaluated whether the subgroups identified were associated with an increased Drug Abuse Screening Test-10 (DAST-10) score, which is an indicator of average problematic drug use.

methodsThis study used a national cross-sectional web-based survey, using 3 survey launches from 2019 to 2020 (before the COVID-19 pandemic). Data from adults who reported nonmedical use of prescription stimulants (n=2083) or prescription opioids (n=6127) in the last 12 months were analyzed. A weighted latent class analysis was used to identify the patterns of use. Drug types, motivations, and behaviors were factors in the model, which characterized unique classes of behavior.

resultsFive stimulant nonmedical use classes were identified: amphetamine self-medication, network-sourced stimulant for alertness, nonamphetamine performance use, recreational use, and nondiscriminatory behaviors. The drug used nonmedically, acquisition through a friend or family member, and use to get high were strong differentiators among the stimulant classes. The latter 4 classes had significantly higher DAST-10 scores than amphetamine self-medication (P<.001). In addition, 4 opioid nonmedical use classes were identified: moderate pain with low mental health burden, high pain with higher mental health burden, risky behaviors with diverse motivations, and nondiscriminatory behaviors. There was a progressive and significant increase in DAST-10 scores across classes (P<.001). The potency of the opioid, pain history, the routes of administration, and psychoactive effect behaviors were strong differentiators among the opioid classes.

conclusionsA more precise understanding of how behaviors tend to co-occur would improve efficacy and efficiency in developing interventions and supporting the overall health of those who use drugs, and it would improve communication with, and connection to, those at risk for severe drug outcomes.

Indexed as

Central Nervous System StimulantsCOVID-19Opioid-Related DisordersAdultAmphetamineAnalgesics, OpioidChildCross-Sectional StudiesDiethylaminesFluorineHumansLatent Class AnalysisPandemicsAmphetamineAnalgesics, OpioidCentral Nervous System StimulantsDiethylaminesdiethylaminosulfur trifluorideFluorineadulthooddrug overdosedrugsdrug use patterngeneral populationhigh-dimensional analysislatent class analysisnonmedical use of prescription stimulantopioidopioid misusestimulant misusesubstance abuse

Identifiers

PMID37728974
PMCPMC10551786
OpenAlexW4386887436

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.