MétaCan
Menu
Back to cohort
Record W2183694794

Professional and informal mental health support reported by Canadians aged 15 to 24.

2014· article· en· W2183694794 on OpenAlexaffabout
Leanne Findlay, Adam Sunderland

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsMental healthQuarter (Canadian coin)AnxietyOddsMoodPsychiatryDistressMedicineYoung adultPsychologyMental distressClinical psychologyGerontologyLogistic regression
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of mental health problems in Canada is highest among youth and young adults. Relatively little is known about where they seek support and the factors related to help-seeking. DATA AND METHODS: Based on the 2012 Canadian Community Health Survey-Mental Health, this study describes professional and informal mental health support reported by Canadians aged 15 to 24. RESULTS: In 2012, 12% of 15- to 24-year-olds reported that, in the previous 12 months, they had consulted health professionals about emotional, mental or substance use problems; 27% reported consulting informal sources such as family and friends. Young Canadians with mood, anxiety or substance disorders, one or more chronic physical conditions, higher levels of distress, or who had a traumatic childhood experience were more likely than their contemporaries who did not have these risk factors to report contact with professional and informal sources of support. Those with multiple needs-related factors had significantly higher odds of reporting contact with professional and informal sources. INTERPRETATION: More than one in ten young Canadians consulted professionals and about a quarter sought informal support for mental health problems in the past year. The percentages were higher among those with multiple risk factors.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.013
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.334
Teacher spread0.303 · 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

Citations29
Published2014
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicMental Health Treatment and AccessFrench-language works237,207