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Record W3144896785 · doi:10.1177/10497323211003063

Conversations About Opioids: Impact of the Opioid Overdose Epidemic on Social Interactions for People Who Live With Chronic Pain

2021· article· en· W3144896785 on OpenAlexafffundabout
Lise Dassieu, Angela Heino, Élise Develay, Jean‐Luc Kaboré, M. Gabrielle Pagé, Maria Hudspith, Gregg Moor, Manon Choinière

Bibliographic record

VenueQualitative Health Research · 2021
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsPositive Living Society of British ColumbiaCentre Hospitalier de l’Université de Montréal
FundersRéseau québécois de recherche sur la douleur
KeywordsChronic painThematic analysisOpioid overdoseStigma (botany)MedicineOpioidPsychiatrySocial stigmaPsychologyQualitative researchFamily medicineSociology

Abstract

fetched live from OpenAlex

The objective of this study was to understand the impact of the opioid overdose epidemic on the social lives of people suffering from chronic pain, focusing on interactions within their personal and professional circles. The study was based on 22 in-depth interviews with people living with chronic pain in Canada. Using thematic analysis, we documented three main impacts of the opioid overdose epidemic: (a) increased worries of people in pain and their families regarding the dangers of opioids; (b) prejudices, stigma, and discrimination faced during conversations about opioids; and (c) stigma management attempts, which include self-advocacy and concealment of opioid use. This study represents important knowledge advancement on how people manage stigma and communicate about chronic disease during everyday life interactions. By showing negative effects of the epidemic's media coverage on the social experiences of people with chronic pain, we underscore needs for destigmatizing approaches in public communication regarding opioids.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.227
GPT teacher head0.567
Teacher spread0.340 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations27
Published2021
Admission routes3
Has abstractyes

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