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Record W3024290380 · doi:10.1177/0844562120924516

Experiences of Clients in Three Types of Methadone Maintenance Therapy in an Atlantic Canadian City: A Qualitative Study

2020· article· en· W3024290380 on OpenAlexaffvenueabout
Lillian MacNeill, Caroline Brunelle, Brittany Skelding, Enrico DiTommaso

Bibliographic record

VenueCanadian Journal of Nursing Research · 2020
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMethadoneMethadone maintenanceAddictionQualitative researchMedicineMental healthOpioid use disorderPsychologyPsychiatryOpioidInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Methadone maintenance therapy remains the most common form of substitution therapy for opioid use disorder in Canada. Effectiveness of methadone maintenance therapy has been established, but recently newer treatment delivery models have emerged. Differences across these treatment models have not been examined. PURPOSE: This descriptive qualitative study used semi-structured interviews to assess client experiences in three methadone maintenance therapy treatment delivery models: (a) comprehensive programs, (b) low-threshold/high-tolerance programs, and (c) fee-for-service programs. METHODS: = 12). Content analysis was performed on interview data to assess the frequency of relevant themes in the data. RESULTS: Participants from all groups stressed the importance of supportive staff and having access to some form of counselling. However, low-threshold/high-tolerance and fee-for-service clients voiced a need for more formal counselling and programming at their clinics. Methadone was reported as the most helpful aspect of the methadone maintenance therapy programs; however, participants also expressed negative views about the substance. CONCLUSIONS: These findings have important implications for the development and implementation of methadone maintenance therapy, specifically pertaining to further integration of addiction and mental health services.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.270
GPT teacher head0.479
Teacher spread0.209 · 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

Citations9
Published2020
Admission routes3
Has abstractyes

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