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Record W2801875520 · doi:10.5206/uwomj.v86i2.2027

Wait times for psychiatric care in Ontario

2017· article· en· W2801875520 on OpenAlexvenueaboutno aff
Rachel Loebach, Sasha Ayoubzadeh

Bibliographic record

VenueUniversity of Western Ontario Medical Journal · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMandateMental healthGovernment (linguistics)Nova scotiaMental health careMedicineHealth careMental illnessPsychiatryPolitical scienceGeography

Abstract

fetched live from OpenAlex

Mental illness is a prevalent and costly health care issue. Lengthy wait times for psychiatric services in Ontario are a barrier to adequate mental health care for adults, children and youth. The objective of this paper is to highlight the current state of psychiatric wait times in Ontario by looking at provincial policies and comparing data to physical health services, as well as between provinces and other developed nations. The Ontario government has successfully implemented mandatory reporting of wait-time data for many medical and surgical services. However, such policies have yet to be implemented for psychiatric services. As a result, availability of current data for comparison is limited. Nova Scotia is currently the only province to government mandate reporting of wait times for mental health. Furthermore, The Organisation for Economic Co-operation and Development ranks Canada below average on measures related to accessibility of psychiatric inpatient services compared to other developed nations. While Ontario has implemented new initiatives to address the issue of timely mental health care, there is still insufficient evidence to determine if they are effective. Continued advocacy for mandatory wait-time reporting at the provincial level and further analysis of current initiatives worldwide are essential steps toward reducing wait times.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.041
GPT teacher head0.361
Teacher spread0.320 · 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.

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

Citations14
Published2017
Admission routes2
Has abstractyes

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