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The Early Burden of Disability in Individuals With Mood and Other Common Mental Disorders in Ontario, Canada

2020· article· en· W3093941852 on OpenAlexaffabout
Benício N. Frey, Simone N. Vigod, Taiane de Azevedo Cardoso, Diego Librenza‐Garcia, Lindsay Favotto, Flávio Kapczinski

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsInstitute for Clinical Evaluative SciencesWomen's College HospitalUniversity of TorontoMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMoodMood disordersPsychiatryCohortMedicineCohort studyPopulationBipolar disorderAnxietyEnvironmental health

Abstract

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Importance: Large population-based data on the trajectory to disability after the first diagnosis of a mood disorder are lacking. Objective: To assess the time between an incident mood disorder diagnosis and the receipt of disability services during a follow-up period of as long as 20 years. Design, Setting, and Participants: This cohort study used health administrative and social service data from ICES for 1 902 792 adults aged 18 to 59 years living in Ontario, Canada. A narrow cohort of individuals who had a new diagnosis of a mood disorder between October 1, 1997, and March 31, 2007, matched by sex and age to individuals with no history of mood disorder, included 278 296 participants. A broader cohort of individuals who had a new diagnosis of other common mental disorders during the same period, matched by sex and age to individuals with no history of mental disorder diagnosis, included 1 624 496 individuals. All individuals were followed up to a maximum end date of March 31, 2017. Data analysis was conducted from November 2017 to June 2018. Exposure: Incident diagnosis of mood or common mental disorder. Main Outcomes and Measures: Disability outcomes were as follows: (1) entry into the Ontario Disability Support Program (ODSP), signifying long-term inability to work because of a disability, and (2) admission into a long-term care (LTC) residence, signifying the inability to live in independent housing. Cox proportional hazards models were used. Results: In the full cohort of 1 902 792 individuals, 278 296 participants (14.6%) were included in the mood disorder cohort (mean [SD] age, 37.5 [11.9] years; 157 386 [56.6%] women), and 1 624 496 participants (85.4%) were included in the common mental disorder cohort (mean [SD], 36.5 [11.8] years; 932 545 [57.4%] women). The incidence of ODSP initiation was greater among individuals with mood disorders than those without (51.5 per 10 000 person-years vs 25.5 per 10 000 person-years; adjusted hazard ratio [aHR], 2.03; 95% CI, 1.95-2.11) and for those with common mental disorders (45.0 per 10 000 person-years vs 27.6 per 10 000 person-years; aHR, 1.57; 95% CI, 1.55-1.60). The aHR for admission to LTC was also higher among individuals with mood disorders compared with those without (aHR, 2.20; 95% CI, 1.80-2.69) and those with common mental disorders compared with those without (aHR, 1.21; 95% CI, 1.14-1.29). Individuals with bipolar disorders had greater ODSP rates than individuals with major depressive disorders (crude rate ratio: 4.31 [95% CI, 3.56-5.17] vs 1.82 [95% CI, 1.36-2.43]). Conclusions and Relevance: This cohort study found that mood disorders were associated with elevated and early rates of disability services. Effective early intervention strategies targeting functional impairment in this population are encouraged.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.266
Teacher spread0.249 · 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.

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

Citations37
Published2020
Admission routes2
Has abstractyes

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