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Record W4220652983 · doi:10.1177/00220426221083655

Chronic Pain and Prescription Opioid Use Among Socially Marginalized Nigerian Women: Exploring Supply Channels and Pathways to Misuse

2022· article· en· W4220652983 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Drug Issues · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedical prescriptionChronic painMedicinePsychiatryOpioidPrescription Drug MisuseDistressCoping (psychology)Opioid use disorderSubstance abuseClinical psychologyNursing

Abstract

fetched live from OpenAlex

This study explores pathways to prescription opioid misuse and supply channels based on in-depth interviews with 16 socially marginalized Nigerian women suffering chronic pain. The pathways identified were medical pain treatment, prior substance use and opioid use for recreation and coping with psychological distress. Facing barriers to prescription opioids due to prescribing restrictions and provider stigma, many resorted to unlicensed chemist stores and street drug dealers for opioid analgesics, including fake and potentially harmful products. Patterns of prescription opioid misuse were woven into multiple and overlapping dynamics of marginalization shaping the lives of these women, including homelessness, sex work, substance use and intimate partner violence. Findings show a need to improve access to prescription opioids and other evidence-based approaches, framed within a trauma-informed approach to pain management. Further, integrating substance abuse treatment and pain management could make services responsive to the inter-related problems of chronic pain and prescription opioid misuse.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.264
Teacher spread0.234 · 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