Comparing two domain scoring methods for the Personality Inventory for DSM-5.

The Personality Inventory for Diagnostic and Statistical Manual of Mental Disorders-5 (PID-5) has become a popular measure of personality pathology, with widespread usage extending beyond its original purpose to aid in the diagnosis of personality disorders. There are 2 methods for scoring the 5 higher order domain scales (Negative Affect, Detachment, Antagonism, Disinhibition, Psychoticism) of this instrument, both of which are used with similar frequency. Krueger, Derringer, Markon, Watson, and Skodol (2012) initially used a scoring method for the 5 domains that included all 25 of the lower order facets. In contrast, the American Psychiatric Association (2013) copyright and publicly available version instructs users to score the domain scales using only 15 of the 25 facets. Our aim in the current study was to compare these 2 scoring methods across various analyses by quantifying the magnitude of any differences in results. The results from both clinical (N = 388) and undergraduate (N = 492) samples supported that the results produced by the 2 domain scoring methods are more similar than different with respect to mean differences, convergent and discriminant correlations with external criteria, and intraclass correlations comparing the consistency between profiles of correlations produced by each scoring method. In contrast, the domain scale profiles for 2 individuals with a borderline personality diagnosis revealed substantive differences for 3 of the 5 domain scales across scoring methods, which has implications for clinical utility. Given these results, we recommend using the 15-facet domain scoring method for research contexts and that more research is needed to determine the optimal scoring method for clinical contexts. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Clarifying the interstitial nature of facets from the Personality Inventory for DSM-5 using the five factor model of personality.

Although the higher order structure of the Personality Inventory for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (PID-5; Krueger, Derringer, Markon, Watson, & Skodol, 2012), is well-established, the lower order structure and facet-to-domain assignment is inconsistent across studies. Some studies used the five-factor model of adaptive personality (FFM) as a framework to evaluate and characterize this lower order structure; however, findings have been limited in various respects including the use of primarily Caucasian and nonclinical samples. The goal of the current investigation was to clarify and extend knowledge of the lower order structure of the PID-5 through joint PID-5/FFM analysis using an ethnically diverse undergraduate sample (N = 492) and psychiatric patient sample (N = 388). Our findings revealed an optimal five-factor structure in the undergraduate sample (in which Openness facets did not load on any factor) and a six-factor structure in the clinical sample (in which Openness formed its own factor). Domains displayed good convergent validity with the domains of the personality psychopathology five model, except for Disinhibition/Conscientiousness, in which the lack of convergence was explained by Conscientiousness. Furthermore, we evaluated six specific PID-5 facets with respect to interstitiality and optimal PID-5 domain placement, where results supported several recommendations for model modification of the PID-5 structure. These include moving Restricted Affectivity to Detachment from Negative Affectivity, moving Hostility to Antagonism from Negative Affectivity, moving Suspiciousness to Negative Affectivity from Detachment, and removing Submissiveness from the PID-5 measure and the alternative model of personality disorders. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Meta-analysis to derive an empirically based set of personality facet criteria for the alternative DSM-5 model for personality disorders.

The alternative model for personality disorders (AMPD) is outlined in Section III of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. This model includes 25 dimensional trait facets that are used as criteria for six personality disorders in addition to impairment in functioning. Numerous previous studies have examined the degree to which the proposed trait facets converge with the Section II personality disorders (PDs) they are meant to capture, but the results from these various studies have been inconsistent. The current investigation sought to provide a meta-analysis of published and unpublished data, and in particular, to develop empirically derived trait criterion profiles for each of the six AMPD PDs. A total of 25 independent data sets utilizing diverse samples and methods that included measurement of AMPD traits and at least one Section II PD derived from both published and unpublished work were considered for this review. The findings indicated general support for the traits proposed for each of the six PDs within the AMPD, with obsessive-compulsive PD the notable exception. The discriminant validity, however, was questionable for several of the PDs; several nonproposed traits also correlated with the Section II PD counterparts at moderate to large degrees. Intraclass correlations used to model the agreement across the empirically derived trait profiles for each of the six PDs, however, revealed that most of the disorders were relatively distinct from one another. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A meta-analysis of the five-factor internal structure of the Personality Inventory for DSM-5.

The Alternative Model for Personality Disorders (AMPD) in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition, Section III, presents a new approach to conceptualizing personality psychopathology and diagnosing personality disorders. The Personality Inventory for DSM-5 (PID-5) was designed to measure Criterion B of the AMPD and is composed of 25 lower-order facet trait scales that form 5 higher-order domain trait scales. Although the PID-5 has mostly adequate to strong psychometric qualities, the lower-order factor structure of PID-5 facet scales has shown considerable variability across studies, and several PID-5 facets scales show evidence of interstitiality-the cross-loading of facets onto more than 1 domain. This interstitiality is neither unexpected nor especially problematic because complex models of personality have traits that are by nature interstitial. What is problematic, however, is that the factor loadings of these interstitial facets vary across samples, suggesting that some PID-5 facet scales are likely susceptible to sampling error and sampling variability. Moreover, the magnitude of some cross-loadings in some studies is substantive (i.e., ≥ .30). The objective of the current study was to conduct a meta-analysis of the internal structure of the PID-5 to offset potential variability associated with sampling error and gain a clearer picture of the lower-order structure of PID-5 facet scales. This was accomplished using weighted mean factor loadings of the PID-5 facet scales across 14 independent samples (N = 14,743). Results supported that the level of interstitiality decreased when multiple samples were combined, and a clearer picture of the internal structure of the PID-5 facet scales emerged. (PsycINFO Database Record

An Examination of the Topology and Measurement of the Alexithymia Construct Using Network Analysis.

There is some ongoing controversy surrounding the definition and measurement of the alexithymia construct. Whereas most researchers describe 4 components comprising the construct (difficulty identifying feelings, difficulty describing feelings, restricted fantasizing, and externally oriented thinking), some include a 5th component, which is defined as "reduced experiencing of emotional feelings." This study examined the topology and measurement of alexithymia using the method of network analysis with data from a heterogeneous multilanguage sample (N = 1,696) that had completed the Bermond-Vorst Alexithymia Questionnaire (BVAQ; Vorst & Bermond, 2001 ). The BVAQ includes an Emotionalizing subscale for assessing the purported 5th component; we compared the network analyses conducted both with and without the Emotionalizing items. The results revealed strong associations between Emotionalizing and Analyzing (externally oriented thinking) items, but Emotionalizing items had almost as many negative as positive connections with items assessing the other components of the construct. A comparison of communities identified by modularity analyses of the 2 networks failed to support emotionalizing as a distinct component of the construct. In addition, network metrics revealed that Fantasizing items were particularly weak within both networks, suggesting that reduced fantasizing might be a peripheral component of the alexithymia construct. Implications for the measurement and treatment of alexithymia are discussed.

Illuminating the theoretical components of alexithymia using bifactor modeling and network analysis.

Alexithymia is a multifaceted personality construct that reflects deficits in affect awareness (difficulty identifying feelings, DIF; difficulty describing feelings, DDF) and operative thinking (externally oriented thinking, EOT; restricted imaginal processes, IMP), and is associated with several common psychiatric disorders. Over the years, researchers have debated the components that comprise the construct with some suggesting that IMP and EOT may reflect constructs somewhat distinct from alexithymia. In this investigation, we attempt to clarify the components and their interrelationships using a large heterogeneous multilanguage sample (N = 839), and an interview-based assessment of alexithymia (Toronto Structured Interview for Alexithymia; TSIA). To this end, we used 2 distinctly different but complementary methods, bifactor modeling and network analysis. Results of the confirmatory bifactor model and related reliability estimates supported a strong general factor of alexithymia; however, the majority of reliable variance for IMP was independent of this general factor. In contrast, network analysis results were based on a network comprised of only substantive partial correlations among TSIA items. Modularity analysis revealed 3 communities of items, where DIF and DDF formed 1 community, and EOT and IMP formed separate communities. Network metrics supported that the majority of central items resided in the DIF/DDF community and that IMP items were connected to the network primarily through EOT. Taken together, results suggest that IMP, at least as measured by the TSIA, may not be as salient a component of the alexithymia construct as are the DIF, DDF, and EOT components. (PsycINFO Database Record

Cross-cultural examination of measurement invariance of the Beck Depression Inventory-II.

Given substantial rates of major depressive disorder among college and university students, as well as the growing cultural diversity on many campuses, establishing the cross-cultural validity of relevant assessment tools is important. In the current investigation, we examined the Beck Depression Inventory-Second Edition (BDI-II; Beck, Steer, & Brown, 1996) among Chinese-heritage (n = 933) and European-heritage (n = 933) undergraduates in North America. The investigation integrated 3 distinct lines of inquiry: (a) the literature on cultural variation in depressive symptom reporting between people of Chinese and Western heritage; (b) recent developments regarding the factor structure of the BDI-II; and (c) the application of advanced statistical techniques to the issue of cross-cultural measurement invariance. A bifactor model was found to represent the optimal factor structure of the BDI-II. Multigroup confirmatory factor analysis showed that the BDI-II had strong measurement invariance across both culture and gender. In group comparisons with latent and observed variables, Chinese-heritage students scored higher than European-heritage students on cognitive symptoms of depression. This finding deviates from the commonly held view that those of Chinese heritage somatize depression. These findings hold implications for the study and use of the BDI-II, highlight the value of advanced statistical techniques such as multigroup confirmatory factor analysis, and offer methodological lessons for cross-cultural psychopathology research more broadly.

Bringing psychosocial support to headache sufferers using information and communication technology: lessons learned from asking potential users what they want.

BACKGROUND: Headaches are a major concern for which psychosocial interventions are recommended. However, headache sufferers do not always have ready access to these interventions. Technology has been used to improve access, especially in young people. OBJECTIVES: To examine user preferences to inform the development of an Internet-based psychosocial intervention including smartphone technology, referred to as the Wireless Headache Intervention. METHODS: The methodology followed a participatory design cycle, including 25 headache sufferers (14 to 28 years of age) who informed the prototype design. All participants were familiar with smartphones and the Internet. Through two iterative cycles of focus groups stratified according to age, qualitative data were collected by asking user preferences for the different planned components of the intervention (ie, smartphone pain diary, Internet-based self-management treatment, social support) and other relevant aspects (ie, smartphone versus computer delivery, and ways of reaching target audience). NVivo 8 with content analysis was used to analyze data and reflect themes as guided by the thematic survey. RESULTS: Participants reported a preference for completing the smartphone pain diary on a daily basis. Participants believed that the program should facilitate easy access to information regarding headaches and management strategies. They also wanted access to other headache sufferers and experts. Participants believed that the program should be customizable and interactive. They reinforced the need and value of an integrated smartphone and Internet-based application. CONCLUSIONS: The results provide insight into a participatory design to guide design decisions for the type of intervention for which success relies largely on self-motivation. The results also provide recommendations for design of similar interventions that may benefit from the integration of mobile applications to Internet-based interventions. The present research contributes to the theoretical frameworks that have been formulated for the development of Internet-based applications.

The internet administration version of the 20-item Toronto alexithymia scale.

Researchers are increasingly administering tests developed and validated in paper format via the Internet. Yet, the equivalence between paper and Internet concerning administration of tests is not typically demonstrated. We evaluated the reliability, factorial and external validity, and measurement equivalency of the Internet version of the 20-item Toronto Alexithymia Scale (TAS-20; Bagby, Parker, & Taylor, 1994; Bagby, Taylor, & Parker, 1994; Lumley et al., 2007) vis-à-vis the paper version. Participants (N = 621) completed the TAS-20 either on the Internet or on paper. Reliability and item-to-scale homogeneity were evaluated for each format. We used confirmatory factor analyses (CFAs) to evaluate factorial validity and used CFA-based factorial invariance procedures to determine measurement equivalency. Alpha coefficients and mean interitem correlations (MICs) were adequate for the full-scale TAS-20 Internet and paper versions and the difficulty identifying feelings (DIF) and difficulty describing feelings (DDF) factor scale test scores; in both formats, alpha and MICs were poorer for externally oriented thinking (EOT) factor test scores compared to scores for the DIF and DDF. The fit of the 3-factor structure of the TAS-20 was adequate for both formats. Factorial invariance across formats was also demonstrated; mean scores for the total scale and each factor scale were not different across formats. Correlations with the domain and facet scales of the Revised NEO Personality Inventory (Costa & McCrae, 1992b) were mostly similar across formats. The Internet and paper versions of the TAS-20 are comparably reliable and valid. An Internet version of the TAS-20 expands opportunities to collect data and permits generalizing of results across studies using the different modes of administration.

Remote population-based intervention for disruptive behavior at age four: study protocol for a randomized trial of Internet-assisted parent training (Strongest Families Finland-Canada).

BACKGROUND: Oppositional Defiant Disorder (ODD) is characterized by angry and noncompliant behaviour. It is the most common disruptive behaviour disorder (DBD), with prevalence estimates of 6-9% for preschoolers and is closely linked to several long-term difficulties, including disorders of conduct, mood, anxiety, impulse-control, and substance abuse. ODD in children is related to parental depression, family dysfunction, and impairments in parental work performance. Children displaying early DBDs exhibit more symptoms of greater severity, more frequent offences, and commit more serious crimes later in life. The goal of the Strongest Families Finland Canada (SFFC) Smart Website intervention research program is to develop and evaluate an affordable, accessible, effective secondary prevention parent training program for disruptive behaviour in preschoolers to prevent the negative sequelae of ODD. Strongest Families is an 11-session program with two booster sessions that focuses on teaching skills to: strengthen parent-child relationships; reinforce positive behaviour; reduce conflict; manage daily transitions; plan for potentially problematic situations; promote emotional regulation and pro-social behaviour and decrease antisocial behaviour. METHODS/DESIGN: This protocol paper describes an ongoing population-based randomized controlled trial (RCT) of high-risk 4 year-olds attending well-child clinics in Turku, Finland and environs to examine the effectiveness of the Strongest Families Smart Website intervention compared to an Education Control condition. Randomization consists of a 1:1 ratio for intervention versus the education group, stratified by the child's sex. The participants randomized to the intervention group receive access to the Strongest Families Smart Website and weekly telephone coaching sessions. The participants randomized to the Education Control condition receive access to a static website with parenting tips. Children are followed using parental and daycare teacher measures at 6 and 12 months after randomization. DISCUSSION: The Strongest Families Smart Website intervention is hypothesized to improve parenting skills, reduce child disruptive behaviour, reduce parental distress and improve family functioning. These results will likely inform subsequent investigations, public policy, and early treatment of childhood disruptive behaviour problems. TRIAL REGISTRATION: ClinicalTrials.gov # NCT01750996.

Telephone-based mental health interventions for child disruptive behavior or anxiety disorders: randomized trials and overall analysis.

OBJECTIVE: Most children with mental health disorders do not receive timely care because of access barriers. These initial trials aimed to determine whether distance interventions provided by nonprofessionals could significantly decrease the proportion of children diagnosed with disruptive behavior or anxiety disorders compared with usual care. METHOD: In three practical randomized controlled trials, 243 children (80 with oppositional-defiant, 72 with attention-deficit/hyperactivity, and 91 with anxiety disorders) were stratified by DSM-IV diagnoses and randomized to receive the Strongest Families intervention (treatment) or usual care (control). Assessments were blindly conducted and evaluated at 120, 240, and 365 days after randomization. The intervention consisted of evidence-based participant materials (handbooks and videos) and weekly telephone coach sessions. The main outcome was mental health diagnosis change. RESULTS: Intention-to-treat analysis showed that for each diagnosis significant treatment effects were found at 240 and 365 days after randomization. Moreover, in the overall analysis significantly more children were not diagnosed as having disruptive behavior or anxiety disorders in the treatment group than the control group (120 days: χ(2)(1) = 13.05, p < .001, odds ratio 2.58, 95% confidence interval 1.54-4.33; 240 days: χ(2)(1) = 20.46, p < .001, odds ratio 3.44, 95% confidence interval 1.99-5.92; 365 days: χ(2)(1) = 13.94, p < .001, odds ratio 2.75, 95% confidence interval 1.61-4.71). CONCLUSIONS: Compared with usual care, telephone-based treatments resulted in significant diagnosis decreases among children with disruptive behavior or anxiety. These interventions hold promise to increase access to mental health services. CLINICAL TRIAL REGISTRATION INFORMATION: Strongest Families: Pediatric Disruptive Behaviour Disorder, http://www.clinicaltrials.gov, NCT00267579; Strongest Families: Pediatric Attention-Deficit/Hyperactivity Disorder, http://www.clinicaltrials.gov, NCT00267605; and Strongest Families: Pediatric Anxiety, http://www.clinicaltrials.gov, NCT00267566.

Filtering for medical news items using a machine learning approach.

We address the problem of filtering medical news articles for targeted audiences. The approach is based on terms and one of the difficulties is extracting a feature set appropriate for the domain. This paper addresses the medical news-filtering problem using a machine learning approach. We describe the application of two supervised machine learning techniques, Decision Trees and Naïve Bayes, to automatically construct classifiers on the basis of a training set, in which news articles have been pre-classified by a medical expert and four other human readers. The goal is to classify the news articles into three groups: non-medical, medical intended for experts, and medical intended for other readers. While the general accuracy of the machine learning approach is around 78%, the accuracy of distinguishing non-medical articles from medical ones is shown to be 92%.