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Is Child Maltreatment a Risk Factor for Borderline Personality Disorder? A Systematic Review of Prospective Longitudinal Studies

2022· review· en· W4292099806 on OpenAlexaff
Marie-Sarah Girard, Julien Morizot

Bibliographic record

VenueCurrent Psychiatry Research and Reviews · 2022
Typereview
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBorderline personality disorderPsychologyNeglectLongitudinal studyProspective cohort studyClinical psychologySexual abuseEtiologyRisk factorPsychological abusePhysical abuseChild abusePsychiatryDevelopmental psychologyPoison controlInjury preventionMedicineMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

Background: Borderline personality disorder (BPD) is a clinical condition associated with numerous individual and collective negative consequences. According to several etiological theories and retrospective research, child maltreatment (CM) may be considered a central factor explaining BPD development. Objectives: In order to verify this hypothesis, a systematic review of prospective longitudinal studies was conducted. Methods: Following searches in five electronic databases, 19 articles that examined the relationship between CM (i.e., physical, sexual and emotional abuse; physical and emotional neglect) and BPD (i.e., diagnosis or severity score) were selected. Results: Overall, the results only partly confirm the hypothesis that CM is a risk factor for BPD. Evidence for a prospective relationship between CM and later BPD is stronger in studies using a symptom count compared to a categorical diagnosis. However, the small number of studies precludes assessing the differential impacts between CM types and BPD. Conclusion: Available prospective longitudinal studies do not unequivocally support the idea that CM is a robust risk factor for BPD. Future research needs are discussed.

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)0.006
metaresearch head score (Gemma)0.001
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.300
GPT teacher head0.531
Teacher spread0.231 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2022
Admission routes1
Has abstractyes

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