MétaCan
Menu
Back to cohort
Record W4389625339 · doi:10.1186/s13011-023-00586-3

An environmental scan of residential treatment service provision in Ontario

2023· article· en· W4389625339 on OpenAlexaffabout
Farihah Ali, Justine Law, Cayley Russell, Nikki Bozinoff, Brian Rush

Bibliographic record

VenueSubstance Abuse Treatment Prevention and Policy · 2023
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoMental Health Research CanadaCentre for Addiction and Mental Health
FundersNational Institute on Drug Abuse
KeywordsBusinessPsychological interventionGovernment (linguistics)Service (business)PopulationAddictionIndigenousAddiction treatmentEnvironmental healthMedicineEnvironmental planningGeographyNursingMarketingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Ontario has one of the highest rates of substance-related harms in Canada. Residential treatment programs in the province provide a variety of in-house treatment services to support the needs of individuals with substance use disorders (SUD). However, these programs are not standardized, often varying in the type, quality, and availability of services offered, including evidence-based interventions such as Opioid Agonist Treatment (OAT). Local treatment systems are also rather fragmented and complex to navigate, creating barriers for potential services users to identify and make informed choices on available treatment options. METHODS: Between May to August 2023, we conducted an environmental scan to capture available information on all publicly-funded residential treatment programs in Ontario using the ConnexOntario service portal, a government-funded, health services information platform. Data were captured on organization name, geographical location, program description, program type (residential addictions treatment or supportive recovery programs), eligibility criteria, target population, the program's OAT policies, number of available beds, minimum and maximum length of stay, projected wait times, funding source, and associated fees for program admission. Data were extracted and organized by geographic region, and findings were presented descriptively. RESULTS: A total of 102 residential addiction treatment programs and 36 residential supportive recovery programs in Ontario were identified. The scan noted substantial regional variations in program availability and wait times, along with a lack of programs tailored to unique populations such as women, youth, and Indigenous peoples. There is also a paucity of publicly-available information on program offerings, including detailed specifics on OAT policies within residential treatment programs that are crucial to ensuring that the services being offered are safe and grounded in evidence-based practice. CONCLUSIONS: Findings from the scan highlight notable gaps in program types, offerings, and availability among residential treatment programs in the province, including a lack of standardization on OAT policies across programs. Efforts should be made to ensure access to treatment-specific program information relevant to potential service users and to enhance coordinated access to residential treatment services in the province.

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)0.001
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.031
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.021
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.031
GPT teacher head0.317
Teacher spread0.286 · 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".

Quick stats

Citations7
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueSubstance Abuse Treatment Prevention and PolicySame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207