Journal of child psychology and psychiatry, and allied disciplines · 2020
Determining the key childhood and adolescent risk factors for future BPD symptoms using regularized regression: comparison to depression and conduct disorder.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Beeney Joseph E, Forbes Erika E, Hipwell Alison E, Nance Melissa, Mattia Alexis, Lawless Joely M, Banihashemi Layla, Stepp Stephanie D
Аннотация
OBJECTIVE: Research has yielded factors considered critical to risk for borderline personality disorder (BPD). Yet, these factors overlap and are relevant to other disorders, like depression and conduct disorder (CD). Regularized regression, a machine learning approach, was developed to allow identification of the most important variables in large datasets with correlated predictors. We aimed to identify critical predictors of BPD symptoms in late adolescence (ages 16-18) and determine the specificity of factors to BPD versus disorders with putatively similar etiology.
METHOD: We used a prospective longitudinal dataset (n = 2,450) of adolescent girls assessed on a range of clinical, psychosocial, and demographic factors, highlighted by previous research on BPD. Predictors were grouped by developmental periods: late childhood (8-10) and early (11-13) and mid-adolescence (14-15), yielding 128 variables from 41 constructs. The same variables were used in models predicting depression and CD symptoms.
RESULTS: The best-fitting model for BPD symptoms included 19 predictors and explained 33.2% of the variance. Five constructs - depressive and anxiety symptoms, self-control, harsh punishment, and poor social and school functioning - accounted for most of the variance explained. BPD was differentiated from CD by greater problems with mood and anxiety in BPD and differences in parenting risk factors. Whereas the biggest parenting risk for BPD was a punitive style of parenting, CD was predicted by both punitive and disengaged styles. BPD was differentiated from MDD by greater social problems and poor behavioral control in BPD.
CONCLUSIONS: The best predictors of BPD symptoms in adolescence are features suggesting complex comorbidity, affective activation, and problems with self-control. Though some risk factors were non-specific (e.g., inattention), the disorders were distinguished in clinically significant ways.
METHOD: We used a prospective longitudinal dataset (n = 2,450) of adolescent girls assessed on a range of clinical, psychosocial, and demographic factors, highlighted by previous research on BPD. Predictors were grouped by developmental periods: late childhood (8-10) and early (11-13) and mid-adolescence (14-15), yielding 128 variables from 41 constructs. The same variables were used in models predicting depression and CD symptoms.
RESULTS: The best-fitting model for BPD symptoms included 19 predictors and explained 33.2% of the variance. Five constructs - depressive and anxiety symptoms, self-control, harsh punishment, and poor social and school functioning - accounted for most of the variance explained. BPD was differentiated from CD by greater problems with mood and anxiety in BPD and differences in parenting risk factors. Whereas the biggest parenting risk for BPD was a punitive style of parenting, CD was predicted by both punitive and disengaged styles. BPD was differentiated from MDD by greater social problems and poor behavioral control in BPD.
CONCLUSIONS: The best predictors of BPD symptoms in adolescence are features suggesting complex comorbidity, affective activation, and problems with self-control. Though some risk factors were non-specific (e.g., inattention), the disorders were distinguished in clinically significant ways.