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Record W2991751336 · doi:10.1097/jan.0000000000000307

Perceptions and Experiences of Methadone Maintenance Treatment

2019· article· en· W2991751336 on OpenAlexaffabout
Courtney Pearson Jeske, Patrick O’Byrne

Bibliographic record

VenueJournal of Addictions Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMethadone maintenanceAffect (linguistics)MethadonePerspective (graphical)PerceptionPsychologyMedicineNursingPsychiatry

Abstract

fetched live from OpenAlex

Over the past 10 years, there has been a consistent increase in opioid use, which has resulted in an increase in methadone maintenance treatment (MMT). With retention in MMT being a key factor, to understand the process of retention, it is important to better understand individual perceptions and experiences. Little research in Ottawa, Ontario, has addressed the perspective of MMT from people enrolled in MMT; therefore, nursing-based research was undertaken. The objective was to understand the process and experiences associated with MMT from the perspective of persons who are enrolled in treatment. Twelve participants were engaged in semistructured interviews. These participants described that, although MMT can positively affect the people who use such a treatment option, multiple barriers, including social perceptions, physical environment, and healthcare delivery practices, continue to affect MMT initiation and delivery.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.308
Teacher spread0.288 · 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 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

Citations12
Published2019
Admission routes2
Has abstractyes

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Same venueJournal of Addictions NursingSame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207