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Record W4402567687 · doi:10.1080/10615806.2024.2403437

Dynamic links between daily anxiety symptoms and young adults’ daily well-being

2024· article· en· W4402567687 on OpenAlexafffund
Kehan Li, Eric M. Cooke, Yao Zheng

Bibliographic record

VenueAnxiety Stress & Coping · 2024
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsAnxietyPsychologyActivities of daily livingWell-beingClinical psychologyDevelopmental psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Anxiety disorders are prevalent among youth and adults. Increasing studies examined the dynamic associations between momentary fluctuations of anxiety and well-being, primarily focusing on the severity of general anxiety. Scant research has explored the co-fluctuations between different anxiety symptoms and mental health outcomes. METHOD: = 271, Mage = 18 years, 72% female, 68% non-White) who participated in a 30-day daily diary study. RESULTS: Between persons, GAD, SP, and PD were positively correlated with depressive symptoms, stress, as well as emotional and peer problems. Within persons, both SP and PD were positively associated with stress, peer and emotional problems on the same day. Across days, there was positive reciprocal relation between PD and stress, whereas negative reciprocal link was observed between SP and emotional problems. CONCLUSIONS: Current findings showed dynamic and distinct patterns in the associations between different anxiety symptoms and several mental health outcomes, which emphasizes the need to disentangle between- and within-person variation of anxiety symptoms with intensive longitudinal designs.

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)0.003
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.012
GPT teacher head0.303
Teacher spread0.291 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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