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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 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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
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 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

Citations12
Published2019
Admission routes2
Has abstractyes

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