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Association of Childhood Externalizing, Internalizing, and Comorbid Symptoms With Long-term Economic and Social Outcomes

2023· article· en· W4313880112 on OpenAlexafffundabout
Francis Vergunst, Melissa Commisso, Marie‐Claude Geoffroy, Caroline E. Temcheff, Martine Poirier, Jungwee Park, Frank Vitaro, Richard E. Tremblay, Sylvana M. Côté, Orri Massimilliano

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsStatistics CanadaMcGill UniversityDouglas Mental Health University InstituteConcordia UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health Research
KeywordsSocioeconomic statusPsychologyAssociation (psychology)DemographyCohortSocial supportMedicinePsychiatryClinical psychologyPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Importance: Little is known about the long-term economic and social outcomes for children with longitudinally assessed comorbid externalizing and internalizing symptoms, especially compared with children with externalizing symptoms or internalizing symptoms only. Objective: To examine the association between childhood trajectories of externalizing, internalizing, and comorbid symptoms and long-term economic and social outcomes. Design, Setting, and Participants: A 32-year prospective cohort study linked with administrative data was conducted in school-aged participants aged 6 to 12 years in the Québec Longitudinal Study of Kindergarten Children (N = 3017) followed up from 1985 to 2017. Data analysis was conducted between August 1, 2021, and March 31, 2022. Exposures: Teacher-rated behavioral symptoms were used to categorize children from age 6 to 12 years into developmental profiles using group-based trajectory modeling. Main Outcomes and Measures: Multivariable regression models were used to test the association between childhood symptom profile group and adult employment earnings, welfare receipt, intimate partnership status, and having children living in the household. Participant sex, IQ, and socioeconomic background were adjusted for. Results: Of 3017 participants in this sample, 1594 (52.8%) were male and 1423 (47.2%) were female. Per confidentiality rules established by Statistics Canada, income variables were rounded to base 100 and count variables were rounded to base 10; the mean (SD) age was 37 (0.29) years at follow-up. Four symptom profiles were identified: no/low (n = 1369 [45.4%]), high externalizing (882 [29.2%]), high internalizing (354 [11.7%]), and comorbid (412 [13.7%]) symptoms. Compared with the no/low symptom profile, participants in the high externalizing-only profile earned $5904 (95% CI, -$7988 to -$3821) less per year and had 2.0 (95% CI, 1.58-2.53) times higher incidence of welfare receipt, while participants in the high internalizing group earned $8473 (95% CI, -$11 228 to -$5717) less per year, had a 2.07 (95% CI, 1.51-2.83) higher incidence of welfare receipt, and had a lower incidence of intimate partnership (incident rate ratio [IRR], 0.89; 95% CI, 0.80-0.99). Participants in the comorbid profile fared especially poorly: they earned $15 031 (95% CI, -$18 030 to -$12 031) less per year, had a 3.79 (95% CI, 2.75-5.23) times higher incidence of annual welfare receipt, and were less likely to have an intimate partner (IRR, 0.71; 95% CI, 0.63-0.79) and children living in the household (IRR, 0.86; 95% CI, 0.80-0.92). Estimated lost earnings over a 40-year working career were $140 515 for the high externalizing, $201 657 for the high internalizing, and $357 737 for the comorbid profiles. Conclusions and Relevance: In this cohort study, children exhibiting sustained childhood high externalizing, high internalizing, or comorbid symptoms were at increased risk of poor economic and social outcomes into middle age. These findings suggest that children exhibiting comorbid problems were especially vulnerable and that early detection and support are indicated.

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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)0.004
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 score0.204
Threshold uncertainty score0.405

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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".

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Citations108
Published2023
Admission routes3
Has abstractyes

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