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Record W4402990418 · doi:10.1177/10731911241283908

Understanding the Within- and Between-Person Structure of Daily Psychopathology Among Adolescents and Young Adults

2024· article· en· W4402990418 on OpenAlexafffundabout
Hao Zheng, Yao Zheng

Bibliographic record

VenueAssessment · 2024
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaKillam TrustsWomen and Children's Health Research InstituteMitacsChildren's Health Research Institute
KeywordsPsychopathologyPsychologySet (abstract data type)Clinical psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Previous investigations on the underlying structure of psychopathology symptoms primarily focused at the between-person level and among adult samples. This study used two independent Canadian samples with month-long daily diary designs to investigate daily psychopathology structure at both within- and between-person level among adolescents ( n = 99, 2,132 daily reports) and young adults ( n = 313, 6,431 and 4,018 daily reports at each wave). Four mainstream types of psychopathology structure were compared based on a comprehensive set of standards. The results suggest that the general factor of psychopathology ( p factor) derived from the higher-order and bifactor models performed similarly well at both within- and between-person levels, while the specific factors estimated in the bifactor models demonstrated low reliability and consistency over time. Psychopathology manifests as multidimensional at the within-person level but unidimensional at the between-person level. The current findings inform the development of future prevention and intervention programs by supporting the adoption of transdiagnostic treatment that addresses multiple psychopathology symptoms with a holistic approach.

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 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.307
Teacher spread0.271 · 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 teacher head, 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

Citations6
Published2024
Admission routes3
Has abstractyes

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