Nighttime Sleep Quality and Daytime Sleepiness Predicts Suicide Risk in Adults Admitted to an Inpatient Psychiatric Hospital.

As sleep problems have been identified as an important, yet understudied, predictor of suicide risk, the present study analyzed the relationship between daytime sleepiness and nighttime sleep disturbance in a high-risk population of adults admitted to an inpatient psychiatric hospital. Objectives were to (1) examine the time course of subjective daytime sleepiness, nighttime sleep disturbance, and suicide risk throughout inpatient psychiatric treatment, (2) examine pre- to post-treatment changes in sleep disturbance with treatment as usual in an inpatient psychiatric setting, and (3) investigate whether daytime sleepiness and nighttime sleep disturbance predicted suicide risk above and beyond anxiety and depression. Participants were 500 consecutively admitted adults admitted to an intermediate length of stay (4-6 weeks) inpatient psychiatric hospital (47% female; 18-87 years of age). Measures of sleep, suicide risk, depression, and anxiety were completed at admission, weeks 1 through 4, and at discharge. Latent growth curve modeling (LGM) and hierarchal linear modeling (HLM) were conducted. The LGM analysis demonstrated that daytime sleepiness, nighttime sleep disturbance, and suicide risk all improved throughout inpatient treatment. Further, HLM showed that daytime sleepiness predicted suicide risk above and beyond symptoms of anxiety, depression, major sleep medications, and prior suicidal ideation and attempts, while nighttime sleep disturbance predicted suicide risk above and beyond symptoms of anxiety, major sleep medications, and prior suicidal ideation and attempts. Findings indicate the need to reevaluate safety protocols that may impact sleep, particularly that may increase daytime sleepiness, and to develop evidence-based sleep interventions for individuals admitted to inpatient psychiatric hospitals.

Predicting depression outcomes throughout inpatient treatment using the general and specific personality disorder factors.

BACKGROUND: Clinical intuition suggests that personality disorders hinder the treatment of depression, but research findings are mixed. One reason for this might be the way in which current assessment measures conflate general aspects of personality disorders, such as overall severity, with specific aspects, such as stylistic tendencies. The goal of this study was to clarify the unique contributions of the general and specific aspects of personality disorders to depression outcomes. METHODS: Patients admitted to the Menninger Clinic, Houston, between 2012 and 2015 (N = 2352) were followed over a 6-8-week course of multimodal inpatient treatment. Personality disorder symptoms were assessed with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th edition Axis II Personality Screening Questionnaire at admission, and depression severity was assessed using the Patient Health Questionnaire-9 every fortnight. General and specific personality disorder factors estimated with a confirmatory bifactor model were used to predict latent growth curves of depression scores in a structural equation model. RESULTS: The general factor predicted higher initial depression scores but not different rates of change. By contrast, the specific borderline factor predicted slower rates of decline in depression scores, while the specific antisocial factor predicted a U shaped pattern of change. CONCLUSIONS: Personality disorder symptoms are best represented by a general factor that reflects overall personality disorder severity, and specific factors that reflect unique personality styles. The general factor predicts overall depression severity while specific factors predict poorer prognosis which may be masked in prior studies that do not separate the two.

Clinical utility of the DSM-5 alternative model for borderline personality disorder: Differential diagnostic accuracy of the BFI, SCID-II-PQ, and PID-5.

BACKGROUND: With the publication of DSM 5 alternative model for personality disorders it is critical to assess the components of the model against evidence-based models such as the five factor model and the DSM-IV-TR categorical model. This study explored the relative clinical utility of these models in screening for borderline personality disorder (BPD). METHODS: Receiver operator characteristics and diagnostic efficiency statistics were calculated for three personality measures to ascertain the relative diagnostic efficiency of each measure. A total of 1653 adult inpatients at a specialist psychiatric hospital completed SCID-II interviews. Sample 1 (n=653) completed the SCID-II interviews, SCID-II Questionnaire (SCID-II-PQ) and the Big Five Inventory (BFI), while Sample 2 (n=1,000) completed the SCID-II interviews, Personality Inventory for DSM5 (PID-5) and the BFI. RESULTS: BFI measure evidenced moderate accuracy for two composites: High Neuroticism+ low agreeableness composite (AUC=0.72, SE=0.01, p<0.001) and High Neuroticism+ Low+Low Conscientiousness (AUC=0.73, SE=0.01, p<0.0001). The SCID-II-PQ evidenced moderate-to-excellent accuracy (AUC=0.86, SE=0.02, p<0.0001) with a good balance of specificity (SP=0.80) and sensitivity (SN=0.78). The PID-5 BPD algorithm (consisting of elevated emotional lability, anxiousness, separation insecurity, hostility, depressivity, impulsivity, and risk taking) evidenced moderate-to-excellent accuracy (AUC=0.87, SE=0.01, p<0.0001) with a good balance of specificity (SP=0.76) and sensitivity (SN=0.81). CONCLUSIONS: Findings generally support the use of SCID-II-PQ and PID-5 BPD algorithm for screening purposes. Furthermore, findings support the accuracy of the DSM 5 alternative model Criteria B trait constellation for diagnosing BPD. Limitations of the study include the single inpatient setting and use of two discrete samples to assess PID-5 and SCID-II-PQ.

A Novel Approach to Identifying a Neuroimaging Biomarker for Patients With Serious Mental Illness.

Serious mental illness (SMI) is disabling, and current interventions are ineffective for many. This exploratory study sought to demonstrate the feasibility of applying topological data analysis (TDA) to resting-state functional connectivity data obtained from a heterogeneous sample of 235 adult inpatients to identify a biomarker of treatment response. TDA identified two groups based on connectivity between the prefrontal cortex and striatal regions: patients admitted with greater functional connectivity between these regions evidenced less improvement from admission to discharge than patients with lesser connectivity between them. TDA identified a potential biomarker of an attenuated treatment response among inpatients with SMI. Insofar as the observed pattern of resting-state functional connectivity collected early during treatment is replicable, this potential biomarker may indicate the need to modify standard of care for a small, albeit meaningful, percentage of patients.

A Systematic Analysis of Treatment Effects on Depressive Symptom Severity by Level of Coercion.

Few studies examine the effect of interpersonal, regulatory or legal coercion on the treatment of depressive symptoms. This retrospective case-control study compared the recovery rates of 574 adults whose level of coercion was scored on a 0-3 scale from fully voluntary to severe coercion when admitted to the Menninger Clinic between 2009 and 2014. The change in Patient Health Questionnaire-9 (PHQ-9) scores (measuring depression severity) from admission to discharge served as the primary outcome measure. Level of coercion was not associated with a difference in rate of improvement in PHQ-9 score. Greater improvement in PHQ-9 scores was associated with (a) older age, (b) lack of a psychotic spectrum disorder diagnosis, (c) stronger working alliance with treatment team, and (d) less difficulty with emotional regulation [lower Difficulties in Emotion Regulation Scale (DERS) scores]. DERS scores were the most impactful factor. This study suggests that licensure boards can continue to mandate treatment despite concerns that coercion may decrease treatment effectiveness.

A dimensional approach to assessing personality functioning: examining personality trait domains utilizing DSM-IV personality disorder criteria.

BACKGROUND: This study compared a dimensional, trait domain approach to characterizing personality pathology with the traditional polythetic approach with respect to their associations with interpersonal functioning and personality traits from the five factor model. METHODS: Psychiatric inpatients (N=1476) were administered the Structured Clinical Interview for DSM-IV Axis II personality disorders. Dimensional representations of trait domains were derived from reorganizing DSM-IV criteria into personality trait domains from DSM-5 Alternative Model. Dimensional scores and personality disorder (PD) total criterion scores served as independent variables in predicting interpersonal profile clusters, as well as extraversion, agreeableness conscientiousness, neuroticism and openness from the five factor model traits. RESULTS: Trait domain scores and PD criteria totals were significantly correlated with submissive interpersonal style yet none proved significant in regression analyses. Avoidant and borderline PD total criteria were negatively associated with a normative interpersonal style. Combined trait domain of detachment and avoidant PD total criteria predicted a hostile/withdrawn interpersonal style. The trait domain of detachment was negatively associated with five factor traits of extroversion, whereas borderline PD total criteria were negatively associated with conscientiousness. Avoidant and borderline PD total criteria were positively associated with neuroticism. CONCLUSIONS: The cross-cutting dimensional approach provided useful information in predicting a hostile/withdrawn interpersonal style as well as extroversion. Importantly, PD criterion scores and dimensional trait scores combined to predict this interpersonal style providing support to the alternative model of personality diagnosis in DSM-5. Clinicians are encouraged to assess dimensions of personality traits as these are related to interpersonal problems frequently encountered in psychiatric settings. While potentially useful, the dimensional approach articulated here did not yield substantial prediction of behavior.

Impact of personality dysfunction on interdisciplinary treatment team working alliance in an inpatient psychiatric population.

Cluster B personality disorders (PDs) share specific traits that can result in interpersonal conflict. As therapeutic working alliance has a strong relationship with improved outcomes, there is interest in understanding the relationship between PDs, working alliance, and clinical outcomes. This is especially compelling in inpatient populations, where symptoms are severe, and patients are working with a treatment team. The aims of this study were to (a) assess whether higher team working alliance is associated with lower depressive symptoms, (b) assess whether patients with Cluster B PD traits have worse working alliance with their team than patients without those Cluster B PD traits, and (c) assess whether higher team working alliance is associated with lower depressive symptoms when Cluster B PD traits are present. Team working alliance was measured at baseline and at discharge for 3,406 inpatients at a psychiatric hospital. Improved team working alliance was associated with lower depression scores at discharge. Patients with borderline personality disorder traits had worse team working alliance, whereas patients with narcissistic personality disorder and antisocial personality disorder traits had similar working alliance scores as other patients. Borderline personality disorder and antisocial personality disorder traits moderated the association between team working alliance and depressive symptoms differently. Findings suggest that team working alliance works similarly to therapist working alliance. Of clinical importance is the finding that team working alliance and its relationship with depression symptoms differ based on Cluster B PD traits, and the importance of strong working alliance regardless of interpersonal challenges due to personality pathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Personality trait domains predict psychiatric symptom and functional outcomes.

A review of high intensity, high dose mentalization-based inpatient psychiatric treatment indicated large effect-size reductions in symptoms of depression, anxiety, somatization, and improving emotion-regulation functioning (Allen et al., 2017). This study examined the impact of pathological personality traits has on baseline symptoms and functioning, as well as their impact on the longitudinal course in a large cohort of adult inpatient psychiatric sample (N = 804). The Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012) was used to assess trait domains impact on longitudinal outcomes (anxiety, depression, somatic symptoms, and functional impairment) using hierarchical repeated measures modeling. Results indicate Negative Affectivity and Detachment were related to higher admission severity in all four outcome domains. Psychoticism was related to somatic symptoms, while Antagonism and Disinhibition were related to functional impairment. Paradoxically, when symptoms were plotted over 2-week intervals during hospitalization, patients with higher admission PID-5 trait scores exhibited greater improvement over time. The PID-5 appears to contribute to prediction of treatment outcome response above and beyond demographic and burden of illness. Importantly, the findings add to a growing body of literature indicating that impairments in personality traits do not preclude positive treatment response, particularly when treatments target pathological personality features. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Diagnostic accuracy of DSM-5 borderline personality disorder criteria: Toward an optimized criteria set.

OBJECTIVE: The polythetic system used by the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) for diagnosing borderline personality disorders (BPD) is far from optimal; however, accumulated research and clinical data are strong enough to warrant ongoing utilization. This study examined diagnostic efficiency of the nine DSM-IV BPD criteria, then explored the feasibility of an optimized criteria set in classifying BPD. METHODS: Adults (N=1,623) completed the Structured Clinical Interviews for DSM-IV Axis II Disorders resulting in a BPD group (n=352) and an inpatient psychiatric control group (PC) with no personality disorders (n=1,271). Receiver operator characteristics and diagnostic efficiency statistics were calculated to ascertain the relative diagnostic efficiency of each DSM-5 BPD criterion in classifying BPD cases. RESULTS: Affective instability (Criterion 6) evidenced the strongest capacity to differentiate the groups (AUC = .84, SE = .01, p < .0001). Abandonment fears (Criterion 1), unstable relationships (Criterion 2), identity disturbance (Criterion 3), impulsivity (Criterion 4), and chronic emptiness (Criterion 7) yielded good-to-moderate discrimination (AUC range = .75-.79). A composite index of these six criteria yielded excellent accuracy (AUC = .98, SE = .002, p < .0001), sensitivity (SN=.99), and specificity (SP=.90). CONCLUSIONS: The current findings add to evidence that affective instability is a useful gate criterion for screening, and the optimized criteria set evidences equivalent accuracy to the original 9 criteria, with a substantial reduction in estimated heterogeneity (from 256 combinations with the original set to 42 combinations with the optimized set).

Lifetime and prospective associations among personality trait domains and suicide-related behaviors in patients with severe mental illness.

BACKGROUND: Despite extensive research and clinical efforts, the suicide rate in the United States continues to rise, driving the need for more research to identify latent factors that increase risk for suicide and to guide treatment decision-making. METHODS: The current study examined a large cohort (N = 1,219) of high-risk psychiatric inpatients to explore associations between personality traits and suicide-related variables measured retrospectively (lifetime history prior to hospital admission) and prospectively (at discharge and 12-month follow-up). RESULTS: Lifetime suicide-related behavior (SRB: combination of ideational severity, aborted, interrupted, actual attempts, and non-suicidal self-injury) was associated with age (younger), gender (female), and elevated scores on the Personality Inventory for DSM-5 (PID-5) negative affectivity, borderline trait composite score, and five-factor model traits of conscientiousness and neuroticism. Patients who manifested persistent suicidal ideation throughout a 6-8 week inpatient treatment (n = 162; 16.9%) tended to be younger, female, and to have elevated PID-5 borderline trait composite scores. Twelve-month post-discharge SRB was predicted by elevated PID-5 borderline trait composite scores. LIMITATIONS: Personality traits accounted for a small amount of variance in the overall model, thus limiting prediction based on individual traits. CONCLUSIONS: This large sample of high-risk inpatients with longitudinal outcomes provides a rare assessment of proximal personality traits in predicting lifetime SRB, persistent suicidal ideation observed during the course of a 6-8-week intensive inpatient treatment, and SRB outcomes within 12 months after discharge from hospitalization. Personality traits should be included in future attempts to create predictive algorithms that include relevant biological data (neuroimaging, genetic, microbiome).

Time in treatment: Examining mental illness trajectories across inpatient psychiatric treatment.

Early discharge or reduced length of stay for inpatient psychiatric patients is related to increased readmission rates and worse clinical outcomes including increased risk for suicide. Trajectories of mental illness outcomes have been identified as an important method for predicting the optimal length of stay but the distinguishing factors that separate trajectories remain unclear. We sought to identify the distinct classes of patients who demonstrated similar trajectories of mental illness over the course of inpatient treatment, and we explore the patient characteristics associated with these mental illness trajectories. We used data (N = 3406) from an inpatient psychiatric hospital with intermediate lengths of stay. Using growth mixture modeling, latent mental illness scores were derived from six mental illness indicators: psychological flexibility, emotion regulation problems, anxiety, depression, suicidal ideation, and disability. The patients were grouped into three distinct trajectory classes: (1) High-Risk, Rapid Improvement (HR-RI); (2) Low-Risk, Gradual Improvement (LR-GI); and (3) High-Risk, Gradual Improvement (HR-GI). The HR-GI was significantly younger than the other two classes. The HR-GI had significantly more female patients than males, while the LR-GI had more male patients than females. Our findings indicated that younger females had more severe mental illness at admission and only gradual improvement during the inpatient treatment period, and they remained in treatment for longer lengths of stay, than older males.

Differentiating bipolar disorder from borderline personality disorder: Diagnostic accuracy of the difficulty in emotion regulation scale and personality inventory for DSM-5.

BACKGROUND: Confusion abounds when differentiating the diagnoses of bipolar disorder (BD) from borderline personality disorder (BPD). This study explored the relative clinical utility of affective instability and self-report personality trait measures for accurate identification of BD and BPD. METHODS: Receiver operator characteristics and diagnostic efficiency statistics were calculated to ascertain the relative diagnostic efficiency of self-report measures. Inpatients with research-confirmed diagnoses of BD (n = 341) or BPD (n = 381) completed the Difficulty in Emotion Regulation Scale (DERS) and Personality Inventory for DSM-5 (PID-5). RESULTS: The total score for DERS evidenced relatively poor accuracy for differentiating the disorders (AUC = 0.72, SE = 0.02, p < .0001), while subscales of affective instability measures yielded fair discrimination (AUC range = 0.70-0.59). The PID-5 BPD algorithm (consisting of emotional lability, anxiousness, separation insecurity, hostility, depressivity, impulsivity, and risk taking) evidenced moderate-to-excellent accuracy (AUC = 0.83, SE = 0.04, p < .0001) with a good balance of specificity (SP = 0.79) and sensitivity (SN = 0.77). CONCLUSION: Findings support the use of the PID-5 algorithm for differentiating BD from BPD. Furthermore, findings support the accuracy of the DSM-5 alternative model Criteria B trait constellation for differentiating these two disorders with overlapping features.

Cumulative prevalence of personality disorders between adolescence and adulthood.

OBJECTIVE: To investigate the cumulative prevalence of personality disorder (PD) among adults in the community, based on prospective longitudinal data from a series of psychiatric interviews. METHOD: Psychiatric interviews were administered to a regionally representative community-based sample of 568 individuals in 1983 (mean age = 14), 1985-1986 (mean age = 16), 1991-1993 (mean age = 22), and 2001-2004 (mean age 33). RESULTS: The point prevalence of any current DSM-IV PD, including depressive PD and passive-aggressive PD, varied between 12.7% and 14.6% across the four diagnostic assessments. The cumulative prevalence of PD increased at each of the follow-up assessments. At mean age 33, the estimated lifetime prevalence of PD was 28.2%. CONCLUSION: The cumulative prevalence of PD, based on a series of interviews conducted during adolescence and adulthood, may be substantially higher than the point prevalence of current PD based on a single assessment interview.

When is antipsychotic polypharmacy supported by research evidence? Implications for QI.

BACKGROUND: Concurrent use of multiple standing antipsychotics (antipsychotic polypharmacy) is increasingly common among both inpatients and outpatients. Although this has often been cited as a potential quality-of-care problem, reviews of research evidence on antipsychotic polypharmacy have not distinguished between appropriate versus inappropriate use. METHODS: A MEDLINE search from 1966 to December 2007 was completed to identify studies comparing changes in symptoms, functioning, and/or side effects between patients treated with multiple antipsychotics and patients treated with a single antipsychotic. The studies were reviewed in two groups on the basis of whether prescribing was concordant with guideline recommendations for multiple-antipsychotic use. RESULTS: A review of the literature, including three randomized controlled trials, found no support for the use of antipsychotic polypharmacy in patients without an established history of treatment resistance to multiple trials of monotherapy. In patients with a history of treatment resistance to multiple monotherapy trials, limited data support antipsychotic polypharmacy, but positive outcomes were primarily found in studies of clozapine augmented with a second-generation antipsychotic. DISCUSSION: Research evidence is consistent with the goal of avoiding antipsychotic polypharmacy in patients who lack guideline-recommended indications for its use. The Joint Commission is implementing a core measure set for Hospital-Based Inpatient Psychiatric Services. Two of the measures address antipsychotic polypharmacy. The first measure assesses the overall rate. The second measure determines whether clinically appropriate justification has been documented supporting the use of more than one antipsychotic medication.