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Record W4413398353 · doi:10.1186/s13033-025-00683-9

Evaluating provider training in stepped care 2.0 and one-at-a-time services among mental health and addiction providers

2025· article· en· W4413398353 on OpenAlexafffund
Kaitlyn N. Mahon, Laura M. Harris-Lane, Alesha C. King, Monte Bobele, AnnMarie Churchill, Peter Cornish, Bernard Goguen, Sheila N. Garland, Alexia Jaouich, Joshua A. Rash

Bibliographic record

VenueInternational Journal of Mental Health Systems · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsGovernment of New BrunswickMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsMental healthHealth administrationAddictionHealth informaticsMental health careTraining (meteorology)Health careNursingPsychologyPublic healthPsychiatryMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Stepped Care 2.0 (SC2.0) and One-at-a-Time (OAAT) approaches can help address challenges related to accessing effective addiction and mental health (A&MH) services. OAAT services, available by walk-in or appointment, were implemented in New Brunswick (NB) as the first step in developing a provincial stepped care framework in alignment with NB's A&MH action plan. This study sought to evaluate the impact of online training courses in SC2.0 and OAAT service delivery on providers' knowledge, readiness, and capabilities to implement OAAT services in A&MH clinics, within the broader context of the provincial SC2.0 model. METHODS: Providers employed with A&MH services (e.g., social workers, nurses, psychologists) across NB completed asynchronous training courses in SC2.0 and OAAT services as part of a provincial implementation initiative. Over 400 providers volunteered to complete questionnaires related to this training (N = 401). Knowledge acquisition questionnaires were developed based on SC2.0 course content and administered pre- and post-training. Providers also completed a post-training knowledge acquisition questionnaire on OAAT services. Providers completed questionnaires on acceptability, appropriateness and feasibility of training courses, and self-efficacy post-training. Qualitative interviews were conducted with 28 providers to further understand their experiences with training courses in SC2.0 (n = 12) and OAAT services (n = 16). RESULTS: Mean percentage of correct responses at post-course for SC2.0 and OAAT services was 67.2% (SD = 15.9%) and 75.7% (SD = 15.7%), respectively. A modest, but significant, increase in knowledge of SC2.0 was observed post-training. Courses were deemed acceptable, appropriate and feasible, and resulted in favorable outcome expectancies. Moreover, providers reported modest self-efficacy to enact SC2.0 following training. Providers made recommendations to receive additional resources and training in SC2.0 and OAAT services to further enhance confidence to integrate key principles into practice. CONCLUSIONS: Asynchronous training courses in SC2.0 and OAAT services supported the provincial practice change initiative in NB. In line with the COM-B model of behavior change, course barriers and facilitators were identified and provide insights into ways in which these courses, and related implementation projects involving training healthcare professionals, could be adapted to help create and sustain change.

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)0.022
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.050
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.386
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations1
Published2025
Admission routes2
Has abstractyes

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