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Record W2983705721 · doi:10.1111/eip.12894

Childhood adversity and depressive symptoms among young adults: Examining the roles of individuation difficulties and perceived social support

2019· article· en· W2983705721 on OpenAlexafffund
David Kealy, Simon Rice, Daniel W. Cox

Bibliographic record

VenueEarly Intervention in Psychiatry · 2019
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndividuationDepressive symptomsPsychologySocial supportDevelopmental psychologyClinical psychologyPsychiatryPsychotherapistCognition

Abstract

fetched live from OpenAlex

AIM: While childhood adversity is a known risk for depressive symptoms, little is known about the contributing role of individuation difficulties among young adults. The present study examined individuation difficulties and perceived social support-and their interaction-as moderators of the relationship between childhood adversity exposure and depressive symptoms. METHODS: Young adults (N = 119; M = 20.8 years) completed self-report assessments of childhood adversity, depressive symptoms, individuation difficulties, and perceived social support. Regression analyses were used to examine interaction effects regarding depressive symptom severity. RESULTS: A significant moderated moderation effect was found whereby individuation difficulties interacted with adversity exposure as perceived social support was reduced. Thus, at high levels of individuation difficulties, young adults with exposure to childhood adversity reported elevated depressive symptoms. This effect was buffered by social support such that when individuation difficulties were high, the association between adversity and depressive symptoms decreased from low to moderate and high support. CONCLUSION: Individuation difficulties and social support are important factors in the development of depressive symptoms from exposure to childhood adversity among young adults.

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 score0.042
Threshold uncertainty score0.437

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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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

Citations16
Published2019
Admission routes2
Has abstractyes

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