Evidence map›Paper›PMID 38228121›Full record

ArticlePsychopathology2024

Network Analysis of Borderline Personality Features in Adolescence Using a Screening Tool in a Chinese Community Sample.

Qian Wang, Zirong Li, Jie Zhong

Abstract read
In one paragraph

Article in Psychopathology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Qian WangBeijing Key Laboratory of Behavior and Mental Health, Clinical and Health Psychology Department, School of Psychological and Cognitive Sciences, Peking University, Beijing, China.
Zirong LiBeijing Key Laboratory of Behavior and Mental Health, Clinical and Health Psychology Department, School of Psychological and Cognitive Sciences, Peking University, Beijing, China, zirongli2028@u.northwestern.edu.
Jie ZhongBeijing Key Laboratory of Behavior and Mental Health, Clinical and Health Psychology Department, School of Psychological and Cognitive Sciences, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study investigated the structure of the borderline personality features (BPFs) network and the most central BPF in adolescence.

methodsCross-sectional self-report data from 4,866 Chinese adolescents (M = 13.96, SD = 1.64; 61.3% girls) were included in the network analysis models. BPFs were assessed with the McLean Screening Instrument for Borderline Personality Disorder.

resultsIdentity disturbance and affective instability emerged as the most central BPF in the current adolescent sample. In addition, chronic emptiness was also found with high centrality. The general networks of BPF were very similar between adolescent boys and girls, although some differences were detected. DISCUSSION: This study further supports the necessity of BPD assessment and diagnosis in adolescence and identifies the distinctive importance of identity and affective dysregulation in the early development of BPD. The findings provide empirical insights into the interconnections of BPF, which resonate with therapeutic mechanisms of evidence-based treatments for BPD. However, the research was limited in its use of a screening measurement rather than a diagnostic tool. Future studies can further explore BPD psychopathology in adolescence with longitudinal data and clinical interviews.

Indexed as

Borderline Personality DisorderAdolescentChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansMaleSelf ReportAdolescenceAffective instabilityBorderline personality featuresIdentity disturbanceNetwork analysis

Identifiers

PMID38228121
PMCPMC11152012

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.