Evidence map›Paper›PMID 39029689›Full record

ArticleJournal of affective disorders2024

The role of borderline personality disorder traits in predicting longitudinal variability of major depressive symptoms among a sample of depressed adults.

Emily A Kline, Damien Lekkas, Anastasia Bryan, Matthew D Nemesure, Tess Z Griffin, Amanda C Collins, George D Price, Michael V Heinz, Subigya Nepal, Arvind Pillai and 2 more

Abstract read
In one paragraph

Article in Journal of affective disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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

12 authors.

Emily A KlineCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Department of Psychology, Montclair State University, Montclair, NJ, United States of America; Department of Psychiatry, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States of America. Electronic address: emilyklinephd@gmail.com.
Damien LekkasCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH, United States of America.
Anastasia BryanCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
Matthew D NemesureCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH, United States of America; Digital Data Design Institute, Harvard Business School, Boston, MA, United States of America.
Tess Z GriffinCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
Amanda C CollinsCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
George D PriceCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH, United States of America.
Michael V HeinzCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Department of Psychiatry, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States of America.
Subigya NepalDepartment of Computer Science, Dartmouth College, Hanover, NH, United States of America.
Arvind PillaiDepartment of Computer Science, Dartmouth College, Hanover, NH, United States of America.
Andrew T CampbellCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Department of Computer Science, Dartmouth College, Hanover, NH, United States of America.
Nicholas C JacobsonCenter for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Quantitative Biomedical Sciences Program, Dartmouth College, Hanover, NH, United States of America; Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America; Department of Computer Science, Dartmouth College, Hanover, NH, United States of America.

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
Personalized Deep Learning Models of Rapid Changes in Major Depressive Disorder Symptoms using Passive Sensor Data from Smartphones and Wearable DevicesR01MH123482 · NIMH · DARTMOUTH COLLEGE · PI JACOBSON, NICHOLAS CHARLES · 2020 to 2024
$2.6M
NIDA NIH HHS P30 DA029926NIMH NIH HHS R01 MH123482
6 · The paper itself

Abstract

backgroundMajor depressive disorder (MDD) and borderline personality disorder (BPD) often co-occur, with 20 % of adults with MDD meeting criteria for BPD. While MDD is typically diagnosed by symptoms persisting for several weeks, research suggests a dynamic pattern of symptom changes occurring over shorter durations. Given the diagnostic focus on affective states in MDD and BPD, with BPD characterized by instability, we expected heightened instability of MDD symptoms among depressed adults with BPD traits. The current study examined whether BPD symptoms predicted instability in depression symptoms, measured by ecological momentary assessments (EMAs).

methodsThe sample included 207 adults with MDD (76 % White, 82 % women) recruited from across the United States. At the start of the study, participants completed a battery of mental health screens including BPD severity and neuroticism. Participants completed EMAs tracking their depression symptoms three times a day over a 90-day period.

resultsUsing self-report scores assessing borderline personality disorder (BPD) traits along with neuroticism scores and sociodemographic data, Bayesian and frequentist linear regression models consistently indicated that BPD severity was not associated with depression symptom change through time. LIMITATIONS: Diagnostic sensitivity and specificity may be restricted by use of a self-report screening tool for capturing BPD severity. Additionally, this clinical sample of depressed adults lacks a comparison group to determine whether subclinical depressive symptoms present differently among individuals with BPD only.

conclusionsThe unexpected findings shed light on the interplay between these disorders, emphasizing the need for further research to understand their association.

Indexed as

Borderline Personality DisorderEcological Momentary AssessmentMajor Depressive DisorderAdultBayes TheoremComorbidityDepressionFemaleHumansLongitudinal StudiesMaleMiddle AgedNeuroticismPsychiatric Status Rating ScalesSelf ReportSeverity of Illness IndexAffectBorderline personality disorderDepressionEcological momentary assessment

Identifiers

PMID39029689
PMCPMC12067186

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.