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Record W2408331535 · doi:10.1177/0020764016650214

Childhood emotional support and borderline personality features in a sample of Canadian psychiatric outpatients

2016· article· en· W2408331535 on OpenAlexaffabout
David Kealy, Carlos A. Sierra-Hernandez, John S. Ogrodniczuk

Bibliographic record

VenueInternational Journal of Social Psychiatry · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsBorderline personality disorderPsychologyMental healthPsychopathologyClinical psychologyPsychiatryEmotional distressNeglectDistressEmotional dysregulationPersonalityAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: Despite links between early relational experiences and psychopathology, data regarding childhood emotional neglect among Canadian mental health services users are scarce. AIMS: To explore the absence of emotional support experiences reported by Canadian psychiatric outpatients, and to examine the relationship between childhood emotional support and borderline personality disorder (BPD) features. METHODS: A survey regarding childhood emotional support was completed by consecutively admitted adult outpatients, along with self-report assessments of symptom distress and BPD features. RESULTS: A substantial proportion of outpatients reported absent emotional support experiences. After controlling for the effects of age and symptom distress, childhood emotional support was found to be significantly negatively associated with BPD features. CONCLUSION: The findings add further support to the need for clinical attention to the early relational experiences of mental health service users.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.960
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.309
Teacher spread0.296 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

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