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Record W4404957209 · doi:10.1016/j.jad.2024.12.025

Exploring the associations between the presence, characteristics, and biopsychosocial covariates of pain and lifetime depression in adolescents: A cross-sectional ABCD study analysis

2024· article· en· W4404957209 on OpenAlexaff
Scott D. Tagliaferri, Josh Nguyen, Laura K. M. Han, Sue Cotton, Jana M Menssink, Aswin Ratheesh, Mélanie Noël, Lianne Schmaal

Bibliographic record

VenueJournal of Affective Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Calgary
FundersNational Institute of Mental HealthNational Institutes of HealthNational Health and Medical Research CouncilNederlandse Organisatie voor Wetenschappelijk OnderzoekMonash UniversityAction for Boston Community Development
KeywordsBiopsychosocial modelCross-sectional studyDepression (economics)CovariatePsychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Depression and pain co-occur, even during adolescence. However, there is limited knowledge on the association between pain and lifetime depression, and which biopsychosocial measures are associated with this co-occurrence. METHODS: Cross-sectional analysis of the Adolescent Brain and Cognitive Development (ABCD) two-year follow-up. We explored associations between the presence and characteristics of past month pain (intensity, duration, activity limitations, and number of pain sites) and lifetime depression using logistic regression. We explored associations of brain structure, physical, behavioural, emotional, social, and cognitive measures with lifetime depression and past month pain compared to having had one or neither condition using multinomial logistic regression. RESULTS: A total of 5211 adolescents (mean age = 12.0 years) who had: (1) no lifetime mental ill-health and no pain (n = 3327); (2) pain only (n = 1407); (3) lifetime depressive disorder but no pain (n = 272); and (4) lifetime depressive disorder and pain (n = 205) were included. Pain presence was associated with lifetime depression (OR[95%CI]: 1.76 [1.45, 2.13], p < 0.001). Pain-related activity limitations (1.13 [1.06, 1.21], p < 0.001) and the number of pain sites (1.06 [1.02, 1.09], p < 0.001) were associated with lifetime depression. Various behavioural, emotional, social, and cognitive, but not brain structure or physical measures, were associated with lifetime depression and past month pain. LIMITATIONS: Longitudinal analyses should validate prognostic markers for predicting co-occurring depression and pain. CONCLUSIONS: Results support an association between the presence and characteristics of pain and lifetime depression during adolescence and could indicate the need for more integrated recognition and clinical care of youth experiencing both depression and pain.

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)0.002
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.023
GPT teacher head0.324
Teacher spread0.301 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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