Personality pathology predicting future impairment
Creators: name: Coifman, Karin
name: Richmond, Julia
Publisher: name: Open Science Framework
Year: 2023
Subjects: subject: Clinical Psychology
subject: Psychology
subject: FOS: Psychology
subject: Social and Behavioral Sciences

description: Description: These are pre-registration of planned analyses for an existing dataset. Data were collected from Winter 2020 to Fall 2022. These analyses will be conducted on all participants who completed the study and the follow-up data collection (N = 110). The primary goal of this investigation is to test whether self-reported interpersonal personality pathology predicts future psychiatric symptoms and functional impairment, as well as how well interpersonal personality pathology predicts future impairment above and beyond self-reported affective symptoms. This research is proposed because much of the literature on predicting future psychopathology utilizes self-report measures of current affective symptoms (i.e., depression, anxiety). However, we propose that self-reported affective symptoms may be more difficult to accurately report than self-reported interpersonal symptoms, which therefore may be useful in predicting future psychopathology. This work builds on prior research conducted by our team and others. Hypotheses: Based on prior research investigating predictors for psychopathology and impairment, we hypothesize that self-reported interpersonal difficulties (i.e., specific personality pathology) will predict current and future psychopathology as well as future functional impairment above and beyond self-reported affective symptoms. Design and Data Collection: The present study is a longitudinal design and part of a larger study designed to investigate the trajectories of risk and resilience in adults following PTSD criterion A accidents. Approximately 4 months following a criterion A traumatic event, participants completed self-report measures of depression symptoms and anxiety symptoms (Inventory of Depression and Anxiety Symptoms), posttraumatic stress disorder symptoms (PTSD Checklist for DSM-5, personality pathology (Structured Clinical Interview for DSM-5 Personality Questionnaire, SCID-5-SPQ), and were assessed for presence or absence of psychopathology (SCID-5). Then, approximately 18 months after the event, participants completed a follow-up SCID-5, as well as self-report measures of functioning (Subjective Impressions of Functioning) and wellbeing (Subjective Vitality Scale). Independent Variables: Interpersonal difficulties: Participants completed the SCID-5-SPQ, which is a 119-item self-report scale used to screen for possible presence of personality disorders. Participants respond to each item dichotomously (yes/no), and then trained clinical interviewers reviewed the questionnaire with participants and asked follow-up questions to determine presence/absence. These items will be summed to create a continuous measure of interpersonal personality psychopathology. Use of continuous measures of personality psychopathology have been used in many previous research designs (Bach et al., 2017; Gratz et al., 2008; Wright et al., 2012). The present study will use 2 methods of determining which items to use as a measure of interpersonal personality pathology. First, several raters will sort the items into interpersonal or non-interpersonal categories. Items that are sorted into the interpersonal category more than 70% of the time will be included (CITE; XX). Further, we will utilize factor analysis to explore which items load together to form an interpersonal dimension. Both methods will be compared to one another if significantly different. For both approaches, these items will be summed (yes = 1, no = 0) to create an index of self-reported interpersonal difficulties. Higher scores indicate greater self-reported interpersonal dysfunction. Affective symptoms: Participants completed several measures of affective symptoms (IDAS, PCL-5). The IDAS (Watson et al., 2007) is a 95-item measure of depression and anxiety symptoms rated on a 5-point scale. For the current study, we will examine depression symptoms using the 20-item general depression subscale. The PCL-5 (Weathers et al., 2013) is a 20-item measure of PTSD symptoms rated on a 5-point scale. These two measures will be correlated in order to determine how to analyze them. If they correlate at .70 or above, we will standardize and aggregate these measures. If they are correlated below .70, we will include them as independent measures. Primary Outcome Variables: Psychiatric diagnoses: Participants completed the SCID-5 with a trained doctoral-level student approximately 4 months after experiencing a severe incident/injury and then again 18 months after injury. Each diagnostic category was dichotomously coded as either present or absent. Analyses will utilize the 4-month and 18-month assessments in separate models. The variable used in each analysis will be a dichotomous variable indicating either the presence or absence of psychopathology. Wellbeing: Participants completed a self-report measure of well-being approximately 18 months after injury. This measure is a 8-item subscale of the Inventory of Depression and Anxiety Symptoms (Watson et al., 2007) that is summed to create a total score. This summed score will be used in analyses. Functioning: Either a friend/romantic partner/family member completed a partner-report measure of functioning 18 months after injury (Subjective Impressions of Functioning; Bonanno et al., 2005), which contains 5 items assessing current levels of health and general functioning. These 5 items will be summed and used in analyses. Key Covariates: Demographic characteristics including age (continuous), sex (dichotomous, coded as male vs not male) will be considered as covariates, given the association between these demographic variables and variability in affect conceptualization and reporting. Each will be entered into models initially but will be dropped if they do not exert any significant or meaningful (i.e., impact any other key associations) effects in the interest of parsimony. Findings will be reported with and without these covariates. Data analysis plan: Preliminary analyses: We will test for differences in outcomes across demographic variables indicated above. Demographics with significant correlations with outcome variables will be entered into relevant models as covariates. We will check assumptions of normality and transform if needed. We will also run bivariate correlations for all key variables. Primary analyses: We will test the predictive ability of self-reported interpersonal personality pathology (compared to self-reported affective symptoms) on future psychopathology, functioning, and wellbeing by conducting a series of regression models. Multiple regression models will be used to analyze continuous outcomes (e.g., wellbeing, functioning), while logistic regression will be used when the outcomes are dichotomous (e.g., current &amp; future psychopathology). One regression model will be conducted for each outcome. Self-reported affective symptoms will be included in the first step and self-reported interpersonal personality symptoms will be included in the second step. The incremental prediction of affective and interpersonal personality symptoms will be compared using ΔR2. Analyses will be conducted in SPSS version 27. Exploratory analysis: Finally, we will explore the impact of self-reported treatment history on outcomes and their associations with personality and affective symptoms. This will be done using a dichotomous response (yes/no) to one question “Have you ever seen a mental health provider?”.