MétaCan
Menu
Back to cohort
Record W4390902178 · doi:10.1080/07448481.2023.2299397

Depression and help-seeking behaviors among college students: Findings from the Healthy Minds Study 2018-2019

2024· article· en· W4390902178 on OpenAlexaboutno aff
Madison E. Raposa, Daniel Smithers, Chad M. Coleman, Bernard L. Harlow

Bibliographic record

VenueJournal of American College Health · 2024
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCollege healthHelp-seekingDepression (economics)Mental healthClinical psychologySocial psychologyMedicinePsychiatryFamily medicine

Abstract

fetched live from OpenAlex

Objective To determine the likelihood of using formal and informal mental health services among college students according to prior history of depression diagnosis and presence of depression symptoms.Participants College students from 79 universities in the U.S. and Canada who participated in the Healthy Minds Study, 2018-2019.Methods Odds ratios and 95% confidence intervals via logistic regression were estimated for the likelihood of using informal and formal mental health services stratified by depression diagnosis and severity of depression symptoms and further stratified by race/ethnicity.Results We report increased odds of using formal mental health services with increasing depression severity symptoms and increased odds of using formal mental health services among students without a clinical depression diagnosis. The odds of service utilization varied by race/ethnicity.Conclusions The likelihood of seeking mental health services differs depending on the history of formal depression diagnosis, current symptoms, and race/ethnicity among college students.

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)0.002
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 score0.152
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.024
GPT teacher head0.399
Teacher spread0.375 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of American College HealthSame topicMental Health Treatment and AccessFrench-language works237,207