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Record W3013179097 · doi:10.1503/cmaj.190603

Trends in objectively measured and perceived mental health and use of mental health services: a population-based study in Ontario, 2002–2014

2020· article· en· W3013179097 on OpenAlexafffundvenueabout
Maria Chiu, Abigail Amartey, Xuesong Wang, Simone N. Vigod, Paul Kurdyak

Bibliographic record

VenueCanadian Medical Association Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsWomen's College HospitalUniversity of TorontoCentre for Addiction and Mental Health
FundersOntario Ministry of Health and Long-Term Care
KeywordsMental healthMedicinePopulationDistressPsychiatryConfidence intervalMental illnessPatient Health QuestionnairePublic healthMental distressDepression (economics)Cross-sectional studyClinical psychologyAnxietyDepressive symptomsEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Mental illness is widely perceived to be more of a public health concern now than in the past; however, it is unclear whether this perception is due to an increase in the prevalence of mental illness, an increase in help-seeking behaviours or both. We examined temporal trends in use of mental health services as well as objectively measured and perceived mental health. METHODS: We conducted a repeat cross-sectional study of Ontario residents who participated in Statistics Canada’s Canadian Community Health Survey (2002–2014). We assessed temporal trends in objectively measured past-year major depressive episode (based on criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, and International Classification of Diseases, 10th Revision) and past-month psychological distress (Kessler Psychological Distress Scale–6 score ≥ 8) and perceived, self-rated mental health. We also examined use of mental health services, including service use among those with a need for mental health care. RESULTS: A total of 260 090 survey participants were included. The age- and sex-standardized prevalence of a major depressive episode (4.8%, 95% confidence interval [CI] 4.2%–5.3% in 2002 v. 4.9%, 95% CI 4.2%–5.7% in 2012; p = 0.9) and psychological distress (7.0%, 95% CI 6.3%–7.6% in 2002 v. 6.5%, 95% CI 5.7%–7.5% in 2012; p = 0.4) did not change significantly over time. However, self-rated fair or poor mental health status increased from 4.9% in 2003–2005 to 6.5% in 2011–2014 (ptrend < 0.001), as did the use of mental health services (7.2% to 12.8%, ptrend < 0.001). The percentage of individuals who had subjective or objectively measured mental health problems and did not access mental health services decreased significantly over time. INTERPRETATION: Given the stable prevalence of objectively measured psychiatric symptoms, the increase in use of mental health services appears to be, at least partly, explained by an increase in perceived poor mental health and help-seeking behaviours.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
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 score0.022
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.327
Teacher spread0.292 · 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

Labeled directly by 2 models reading the full record.

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

Citations53
Published2020
Admission routes4
Has abstractyes

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