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Record W3210990329 · doi:10.1136/oem-2021-epi.444

S-487 Young people’s depressive symptom trajectories and their education and employment. Comparing Canada and the United States

2021· article· en· W3210990329 on OpenAlexaffabout
Anita Minh, Ute Bültmann, Sijmen A. Reijneveld, Sander van Zon, Chris McLeod

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMultinomial logistic regressionDemographyDepressive symptomsOddsLogistic regressionMedicineLongitudinal studyPsychologyPsychiatryStatisticsCognitionMathematicsSociology

Abstract

fetched live from OpenAlex

Objective This study examines how trajectories of depressive symptoms from the age of 16–25 are related to early adult education and employment outcomes in Canada and the United States. Methods Data came from the Canadian National Longitudinal Survey of Children and Youth (n=2348) and the American National Longitudinal Survey of Youth 1979 Child/Young Adult Survey (n=3961). Depressive symptom trajectories from the age of 16–25 were identified separately for each country using growth-mixture modeling, and linked to respondents’ education and employment status (working with a post-secondary degree; working with no degree; working with a high school degree; in school; and, not in employment, education, or training i.e., NEET), and part/full-time employment (less than 30 hours/week, 30–40 hours/week, more than 40 hours/week). We assessed the association of depressive symptom trajectories with these outcomes using multivariable multinomial logistic regressions, calculating the adjusted predicted probability of each outcome using marginal standardization. Results In both countries four similar depressive symptom trajectories were identified: low-stable, increasing, decreasing, and first increasing then decreasing symptoms (i.e., mid-peak). In both countries, increasing, decreasing, and mid-peak trajectories were associated with higher odds of working with low educational credentials, and/or NEET relative to low-stable trajectories. In Canada, however, all trajectories had a higher predicted probability of either being in school or working with a post-secondary degree than the other outcomes; in the USA, all trajectory groups were most likely to be working with a high school degree. In the USA but not in Canada, increasing and decreasing trajectories were associated with higher odds of part-time work than full-time work. Conclusions Higher levels of depressive symptoms during the transition to adulthood are associated with working with no or low credentials, NEET, and working part-time in young adulthood. Country-level differences may modify the influence of depressive symptoms.

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 score0.010
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.284
Teacher spread0.270 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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