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Record W2994658918 · doi:10.2196/16038

How Motivations for Using Buprenorphine Products Differ From Using Opioid Analgesics: Evidence from an Observational Study of Internet Discussions Among Recreational Users

2019· article· en· W2994658918 on OpenAlexvenueno aff
Stephen F. Butler, Natasha K Oyedele, Taryn Dailey Govoni, Jody L. Green

Bibliographic record

VenueJMIR Public Health and Surveillance · 2019
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
FundersIndivior
KeywordsObservational studyBuprenorphineRecreationThe InternetRecreational useOpioidInternet privacyPsychologyMedicineApplied psychologyAdvertisingWorld Wide WebComputer scienceBusinessInternal medicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Opioid use disorder (OUD) poses medical and societal concerns. Although most individuals with OUD in the United States are not in drug abuse treatment, buprenorphine is considered a safe and effective OUD treatment, which reduces illicit opioid use, mortality, and other drug-related harms. However, as buprenorphine prescriptions increase, so does evidence of misused, abused, or diverted buprenorphine. Users' motivations for extratreatment use of buprenorphine (ie, misuse or abuse of one's own prescription or use of diverted medication) may be different from the motivations involved in analgesic opioid products. Previous research is based on small sample sizes and use surveys, and none directly compare the motivations for using buprenorphine products (ie, tablet or film) with other opioid products having known abuse potential. OBJECTIVE: The aim of the study was to describe and compare the motivation-to-use buprenorphine products, including buprenorphine/naloxone (BNX) sublingual film and oxycodone extended-release (ER), as discussed in online forums. METHODS: Web-based posts from 2012 to 2016 were collected from online forums using the Web Informed Services internet monitoring archive. A random sample of posts was coded for motivation to use. These posts were coded into the following motivation categories: (1) use to avoid withdrawal, (2) pain relief, (3) tapering from other drugs, (4) opioid addiction treatment, (5) recreational use (ie, to get high), and (6) other use. Oxycodone ER, an opioid analgesic with known abuse potential, was selected as a comparator. RESULTS: Among all posts, 0.81% (30,576/3,788,922) discussed motivation to use one of the target products. The examination of query-selected posts revealed significantly greater discussion of buprenorphine products than oxycodone ER (P<.001). The posts mentioning buprenorphine products were more likely than oxycodone ER to discuss treatment for OUD, tapering down use, and/or withdrawal management (P<.001). Buprenorphine-related posts discussed recreational use (375/1020, 36.76%), although much less often than in oxycodone ER posts (425/508, 83.7%). Despite some differences, the overall pattern of motivation to use was similar for BNX sublingual film and other buprenorphine products. CONCLUSIONS: An analysis of spontaneous, Web-based discussion among recreational substance users who post on online drug forums supports the contention that motivation-to-use patterns associated with buprenorphine products are different from those reported for oxycodone ER. Although the findings presented here are not expected to reflect the actual use of the target products, they may represent the interests and motivations of those posting on the online forums. Buprenorphine-related posts were more likely to discuss treatment for OUD, tapering, and withdrawal management than oxycodone ER. Although the findings are consistent with a purported link between the limited availability of medication-assisted therapies for substance use disorders and use of diverted buprenorphine products for self-treatment, recreational use was a motivation expressed in more than one-third of buprenorphine posts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.182
GPT teacher head0.373
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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