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Record W4321495501 · doi:10.1177/02698811221144635

We need to talk: The urgent conversation on chronic pain, mental health, prescribing patterns and the opioid crisis

2023· review· en· W4321495501 on OpenAlexaff
Marco Battaglia, Cornelius B. Groenewald, Fiona Campbell, Simona Scaini, Yves De Koninck, Jennifer Stinson, Patrick D. Quinn

Bibliographic record

VenueJournal of Psychopharmacology · 2023
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsHospital for Sick ChildrenUniversité LavalUniversity of TorontoSickKids FoundationCentre for Addiction and Mental Health
FundersNational Heart, Lung, and Blood Institute
KeywordsMental healthConversationPsychiatryChronic painMedicineMultidisciplinary approachPopulationOpioidPsychological interventionPsychologyPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

The opioid crisis' pathways from first exposure onwards to eventual illnesses and fatalities are multiple, intertwined and difficult to dissect. Here, we offer a multidisciplinary appraisal of the relationships among mental health, chronic pain, prescribing patterns worldwide and the opioid crisis. Because the opioid crisis' toll is especially harsh on young people, emphasis is given on data regarding the younger strata of the population. Because analgesic opioid prescription constitute a recognised entry point towards misuse, opioid use disorder, and ultimately overdose, prescribing patterns across different countries are examined as a modifiable hazard factor along these pathways of risk. Psychiatrists are called to play a more compelling role in this urgent conversation, as they are uniquely placed to provide synthesis and lead action among the different fields of knowledge and care that lie at the crossroads of the opioid crisis. Psychiatrists are also ideally positioned to gauge and disseminate the foundations for diagnosis and clinical management of mental conditions associated with chronic pain, including the identification of hazardous and protective factors. It is our hope to spark more interdisciplinary exchanges and encourage psychiatrists worldwide to become leaders in an urgent conversation with interlocutors from the clinical and basic sciences, policy makers and stakeholders including clients and their families.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.674
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.048
GPT teacher head0.394
Teacher spread0.347 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2023
Admission routes1
Has abstractyes

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