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Record W3035719199 · doi:10.1521/pedi_2020_34_483

Reciprocal Influences of Parent and Adolescent Borderline Personality Symptoms Over 3 Years

2020· article· en· W3035719199 on OpenAlexaff
Erin A. Kaufman, Sarah E. Victor, Alison E. Hipwell, Stephanie D. Stepp

Bibliographic record

VenueJournal of Personality Disorders · 2020
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsWestern University
FundersNational Institute of Mental Health
KeywordsPsychologyBorderline personality disorderDevelopmental psychologySocioeconomic statusPersonalityDepression (economics)Family aggregationClinical psychologyPsychopathologyEtiologyLongitudinal studyCohortOffspringPsychiatryDemographyPopulationMedicinePregnancySocial psychology

Abstract

fetched live from OpenAlex

Leading etiological theories implicate the family environment in shaping borderline personality disorder (BPD). Although a substantive literature explores familial aggregation of this condition, most studies focus on parent influence(s) on offspring symptoms without examining youth symptom influence on the parent. The current study investigated reciprocal relations between parent and adolescent BPD symptoms over time. Participants were 498 dyads composed of urban-living girls and their parents enrolled in a longitudinal cohort study (Pittsburgh Girls Study). The authors examined BPD severity scores assessed yearly when youth were ages 15-17 years in a series of cross-lagged panel models. After controlling for autoregressive effects, a measure of parent-child conflict, and an indicator of socioeconomic status, evidence of parental influence on adolescent symptoms did not emerge. However, adolescent BPD symptoms at age 16 predicted greater parent BPD symptoms at age 17 above the influence of depression. Results highlight the importance of considering the influence of youth BPD on parental symptoms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.332
Teacher spread0.299 · 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.

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

Citations10
Published2020
Admission routes1
Has abstractyes

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