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What are we modeling? An evaluation of depressive symptom trajectory models from adolescence to early midlife in the Add Health cohort

2025· article· en· W4408990072 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Science Research · 2025
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversity of North Carolina WilmingtonNational Institute on AgingNational Institutes of Health
KeywordsCohortPsychologyDepressive symptomsTrajectoryGerontologyCohort studyClinical psychologyDevelopmental psychologyMedicinePsychiatryAnxiety

Abstract

fetched live from OpenAlex

It is critical to understand the development of depressive symptoms across life stages. Existing research has primarily explored this from a life course perspective, yielding inconsistent depressive trajectories, and raising questions as to whether life course processes best characterize the evolution of depressive symptoms across life stages. This study compares ten longitudinal models from four theoretical perspectives ( life course , enduring , autoregressive , and hybrid ) to identify the best-fitting, theoretically-informed model of depressive symptom development from adolescence to early midlife. Results indicate a hybrid model that combines enduring and autoregressive perspectives outperforms traditional life course models and best fits the data. This hybrid model suggests depressive symptom levels at baseline remain relatively stable across life stages, with past symptom levels predicting future levels. Additionally, it reveals racial/ethnic and gender differences in symptom levels in early adolescence, as well as racial/ethnic differences in longitudinal patterns. These findings advance theoretical understanding of depressive symptom development among US young adults across early portions of the life course. • This study compares life course, enduring, autoregressive, and hybrid models of depressive symptoms in the Add Health cohort. • A hybrid model which combines enduring and autoregressive perspectives outperforms life course models of depressive development. • This model suggests baseline depressive levels stay stable across life stages, with past levels predicting future levels. • There are racial/ethnic and gender differences in depressive symptom levels in early adolescence. • There are racial/ethnic differences in the longitudinal patterns of depressive development from adolescence to early midlife.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.432
GPT teacher head0.602
Teacher spread0.170 · 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