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Record W2599349352

Borderline Personality Disorder: Examining Trajectories Of Development Among Adolescents

2016· article· en· W2599349352 on OpenAlexaboutno aff
Valbona Semovski

Bibliographic record

VenueMacSphere (McMaster University) · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyDevelopmental psychologyPersonalityPersonality developmentPoison controlAdolescent developmentBorderline personality disorderClinical psychologySocial psychologyMedicineMedical emergency
DOInot available

Abstract

fetched live from OpenAlex

Title: Borderline personality disorder: examining trajectories of development among adolescents Background: Borderline personality disorder (BPD) tends to be highly comorbid with other disorders. In adolescence, information about the classification and development of BPD is in its early stages. There is limited empirical research available that investigates predictors of clinically significant symptom trajectories of the disorder using data collected in childhood. Given the enormous personal and societal costs associated with BPD, early detection and prevention is important. Clinical implications of this research include an improved understanding of risk factors and possible mechanisms for development of BPD symptomatology. Objectives: To identify trajectories of BPD symptomatology in a Canadian sample of adolescents (N = 703) assessed at ages 13, 14, 15 and 16, while examining predictors of trajectory group membership assessed at age 12. Methods: Data from the McMaster Teen Study was used to examine trajectories of BPD symptoms using group-based trajectory modeling. The influence of gender, depression, ADHD, family functioning and various sociodemographic variables as predictors of an individual’s group membership was tested. Chi-square, analysis of variance and multinomial logistic regression was used to analyze the data. Results: A four-group trajectory model was most robust at describing BPD symptomatology in this age group. Univariate analyses supported female gender, depression and ADHD at baseline, parental age, marital status, education, and income as significant predictors of group membership. Female gender, depression and ADHD severity at baseline were significant predictors of group membership when adopting a multivariate approach. There is a greater prevalence of girls with higher depression and ADHD scores in the high-increasing features and BPD group. Conclusion: Findings demonstrate four various developmental trajectories of BPD features. Results further the understanding of the factors associated with development of the disorder across time.

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)0.004
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 score0.225
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.023
GPT teacher head0.243
Teacher spread0.220 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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