Evidence map›Paper›PMID 24885218›Full record

ArticleSubstance abuse treatment, prevention, and policy2014

Patterns of non-compliant buprenorphine, levomethadone, and methadone use among opioid dependent persons in treatment.

Alicia Casati, Daniela Piontek, Tim Pfeiffer-Gerschel

Open access · goldAbstract read
In one paragraph

Article in Substance abuse treatment, prevention, and policy, 2014. 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
1.6field-weighted citation impact, top 15% 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, 8 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

3 authors at 1 institution in 1 country.

Alicia CasatiInstitut für Therapieforschung, Parzivalstr, 25, 80804 Munich, Germany. casati@ift.de.
Daniela Piontek
Tim Pfeiffer-Gerschel
IFT Institut für Therapieforschung · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe non-compliant use of opioid substitution treatment (OST) medicines is widespread and well-documented. However, less is known about characteristics of non-compliant OST medicine use and the factors that predict it. The two main goals of this study are to compare characteristics of non-compliant levomethadone, methadone, and buprenorphine use and to explore factors that may differentially predict it among opioid dependent persons in treatment.

methodsData from 595 opioid dependent patients with non-compliant OST medicine use were analyzed. Characteristics of use between substances were compared using chi-squared tests and predictive factors were explored through multinomial logistic regressions.

resultsNon-compliant levomethadone and methadone use was characterized by more frequent parallel consumption of other psychoactive substances and intravenous use, whereas buprenorphine was more often procured without a prescription. Regarding predictive factors, methadone was perceived to relieve withdrawal symptoms better than buprenorphine and levomethadone was perceived as being better at modulating the effects of other substances and worst at enhancing mood.

conclusionsPatterns of non-compliant use differ according to OST medicine. These patterns are considered with the reduction of non-compliant use and the improvement of treatment in mind.

Indexed as

Medication AdherenceOpiate Substitution TreatmentAdultAnalgesics, OpioidBuprenorphineFemaleHumansMaleMethadoneNarcoticsOpioid-Related DisordersSurveys and QuestionnairesAnalgesics, OpioidBuprenorphineMethadoneNarcotics

Identifiers

PMID24885218
PMCPMC4035758
OpenAlexW2148117403

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.