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Record W3194207299 · doi:10.1186/s13722-021-00261-7

Improving Treatment Together: a protocol for a multi-phase, community-based participatory, and co-design project to improve youth opioid treatment service experiences in British Columbia

2021· article· en· W3194207299 on OpenAlexaffabout
Kirsten Marchand, Corinne Tallon, Christina Katan, Jill Fairbank, Oonagh Fogarty, Katrina Marie Pellatt, Roxanne Turuba, Steve Mathias, Skye Barbic

Bibliographic record

VenueAddiction Science & Clinical Practice · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsSpinal Cord Injury BCUniversity of British ColumbiaProvidence Health Care Research InstituteCentre for Advancing Health OutcomesCanadian Centre on Substance Use and AddictionProvidence Health Care
Fundersnot available
KeywordsOpioid use disorderBuprenorphineGeneral partnershipMedicineService (business)Participatory action researchCommunity-based participatory researchPublic healthNursingOpioidMedical educationPsychologyBusinessSociologyMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: Opioid use is one of the most critical public health issues as highly potent opioids contribute to rising rates of accidental opioid-related toxicity deaths. This crisis has affected people from all age groups, including youth (ages 15-24) who are in a critical developmental period where the stakes of opioid use are especially high. Efforts to reduce the significant harms of opioid use have focused on the expansion of evidence-based treatments, including medications for opioid use disorder (e.g. buprenorphine). While these treatments are unequivocally life saving, recent evidence suggests that they may not align with youths' needs. Accordingly, the 'Improving Treatment Together' (ITT) project has been designed with the aim to improve youths' opioid treatment service experiences and outcomes by co-developing, implementing, and measuring youth-centred opioid use treatment service innovations. This manuscript describes the protocol for this multi-phase project. METHODS: The ITT project follows community-based participatory research (CBPR) and strategically integrates co-design processes throughout its four phases. Upon establishing a project partnership between national, provincial and community-based organizations, Phase 1 follows four core elements of human-centred co-design (empathy, needs identification, ideation, prototyping) in nine separate workshops. These workshops will be held in four diverse communities with youth, caregivers and service providers who have accessed or delivered opioid treatment services. Phase 1 will culminate in the co-production of opioid treatment service innovations to be considered by the project's partners for further co-development, pilot testing, and wider implementation during the remaining phases of the project. Throughout each phase, the project will collect and analyse both qualitative and quantitative research and evaluation data to determine the project's impact. DISCUSSION: This protocol provides a detailed description of the ITT project, with an emphasis on the project's application of co-design and CBPR processes, the planned research and implementation procedures, and the establishment of a unique partnership. To our knowledge, this is one of the first projects to integrate these participatory processes to the design, implementation and measurement of youth-centred opioid treatment services. Embedding these processes throughout each phase of the project will strengthen the relevance and feasibility of the project's service delivery innovations.

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)0.111
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.962
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1110.053
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.003
Science and technology studies0.0150.007
Scholarly communication0.0070.003
Open science0.0080.008
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0450.006

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 head0.812
GPT teacher head0.718
Teacher spread0.094 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations11
Published2021
Admission routes2
Has abstractyes

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