Expressed emotion as predictor of relapse in patients with comorbid psychoses and substance use disorder

Objective: Expressed emotion (EE) and substance use disorder predict relapse in psychosis, but there is little research on EE in comorbid samples. The current study addressed this issue. Method: Sixty inpatients with a DSM-IV psychosis and substance use disorder were recruited and underwent diagnostic and substance use assessment. Key relatives were administered the Camberwell Family Interview. Results: Patients were assessed on the initial symptoms and recent substance use, and 58 completed the assessment over the following 9 months. High EE was observed in 62% of households. Expressed emotion was the strongest predictor of relapse during follow up and its predictive effect remained in participants with early psychosis. A multivariate prediction of a shorter time to relapse entered EE, substance use during follow up Q1 and (surprisingly) an absence of childhood attention deficit hyperactivity disorder. Conclusions: Since high EE is a common and important risk factor for people with comorbid psychosis and substance misuse, approaches to address it should be considered by treating clinicians.

What measure of temperature is the best predictor of mortality?

Hot and cold temperatures significantly increase mortality rates around the world, but which measure of temperature is the best predictor of mortality is not known. We used mortality data from 107 US cities for the years 1987–2000 and examined the association between temperature and mortality using Poisson regression and modelled a non-linear temperature effect and a non-linear lag structure. We examined mean, minimum and maximum temperature with and without humidity, and apparent temperature and the Humidex. The best measure was defined as that with the minimum cross-validated residual. We found large differences in the best temperature measure between age groups, seasons and cities, and there was no one temperature measure that was superior to the others. The strong correlation between different measures of temperature means that, on average, they have the same predictive ability. The best temperature measure for new studies can be chosen based on practical concerns, such as choosing the measure with the least amount of missing data.

Commentaries and Responses to "The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis" [Commentaries lead by Anders af Wahlberg; Responses lead by J.C.F. de Winter]

The following discussion is in response to a 2010 article published in the Journal of Safety Research by J.C.F. de Winter and D. Dodou entitled “The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis” (Volume 41, Number 6, pp. 463-470, available on sciencedirect.com). The editors are pleased to provide a forum for this exchange and welcome further comments.

Clinical utility of mental state screening as a predictor of intellectual outcomes 6 months after diagnosis of type 1 diabetes

Background Screening tests of basic cognitive status or ‘mental state’ have been shown to predict mortality and functional outcomes in adults. This study examined the relationship between mental state and outcomes in children with type 1 diabetes. Objective We aimed to determine whether mental state at diagnosis predicts longer term cognitive function of children with a new diagnosis of type 1 diabetes. Methods Mental state of 87 patients presenting with newly diagnosed type 1 diabetes was assessed using the School-Years Screening Test for the Evaluation of Mental Status. Cognitive abilities were assessed 1 wk and 6 months postdiagnosis using standardized tests of attention, memory, and intelligence. Results Thirty-seven children (42.5%) had reduced mental state at diagnosis. Children with impaired mental state had poorer attention and memory in the week following diagnosis, and, after controlling for possible confounding factors, significantly lower IQ at 6 months compared to those with unimpaired mental state (p < 0.05). Conclusions Cognition is impaired acutely in a significant number of children presenting with newly diagnosed type 1 diabetes. Mental state screening is an effective method of identifying children at risk of ongoing cognitive difficulties in the days and months following diagnosis. Clinicians may consider mental state screening for all newly diagnosed diabetic children to identify those at risk of cognitive sequelae.

Deprivation is an independent predictor of 1-year mortality in outpatients with chronic obstructive pulmonary disease

Deprivation is linked to increased incidence in a number of chronic diseases but its relationship to chronic obstructive pulmonary disease (COPD) is uncertain despite suggestions that the socioeconomic gradient seen in COPD is as great, if not greater, than any other disease (Prescott and Vestbo).1 There is also a need to take into account the confounding effects of malnutrition which have been shown to be independently linked to increased mortality (Collins et al).2 The current study investigated the influence of social deprivation on 1-year survival rates in COPD outpatients, independently of malnutrition. 424 outpatients with COPD were routinely screened for malnutrition risk using the ‘Malnutrition Universal Screening Tool’; ‘MUST’ (Elia),3 between July and May 2009; 222 males and 202 females; mean age 73 (SD 9.9) years; body mass index 25.8 (SD 6.3) kg/m2. Each individual's deprivation was calculated using the index of multiple deprivation (IMD) which was established according to the geographical location of each patient's address (postcode). IMD includes a number of indicators covering economic, housing and social issues (eg, health, education and employment) into a single deprivation score (Nobel et al).4 The lower the IMD score, the lower an individual's deprivation. The IMD was assigned to each outpatient at the time of screening and related to1-year mortality from the date screened. Outpatients who died within 1-year of screening were significantly more likely to reside within a deprived postcode (IMD 19.7±SD 13.1 vs 15.4±SD 10.7; p=0.023, OR 1.03, 95% CI 1.00 to 1.06) than those that did not die. Deprivation remained a significant independent risk factor for 1-year mortality even when adjusted for malnutrition as well as age, gender and disease severity (binary logistic regression; p=0.008, OR 1.04, 95% CI 1.04 to 1.07). Deprivation was not associated with disease-severity (p=0.906) or body mass index, kg/m2 (p=0.921) using ANOVA. This is the first study to show that deprivation, assessed using IMD, is associated with increased 1-year mortality in outpatients with COPD independently of malnutrition, age and disease severity. Deprivation should be considered in the targeted management of these patients.

Response to comments on "Productivity is a poor predictor of plant species richness"

Pan et al. claim that our results actually support a strong linear positive relationship between productivity and richness, whereas Fridley et al. contend that the data support a strong humped relationship. These responses illustrate how preoccupation with bivariate patterns distracts from a deeper understanding of the multivariate mechanisms that control these important ecosystem properties.

Craving as a predictor of treatment outcomes in heavy drinkers with comorbid depressed mood

Alcohol and depression comorbidity is high and is associated with poorer outcomes following treatment. The ability to predict likely treatment response would be advantageous for treatment planning. Craving has been widely studied as a potential predictor, but has performed inconsistently. The effect of comorbid depression on craving's predictive performance however, has been largely neglected, despite demonstrated associations between negative affect and craving. The current study examined the performance of craving, measured pretreatment using the Obsessive subscale of the Obsessive Compulsive Drinking Scale, in predicting 18-week and 12-month post-treatment alcohol use outcomes in a sample of depressed drinkers. Data for the current study were collected during a randomized controlled trial (Baker, Kavanagh, Kay-Lambkin, Hunt, Lewin, Carr, & Connolly, 2010) comparing treatments for comorbid alcohol and depression. A subset of 260 participants from that trial with a Timeline Followback measure of alcohol consumption was analyzed. Pre-treatment craving was a significant predictor of average weekly alcohol consumption at 18 weeks and of frequency of alcohol binges at 18 weeks and 12months, but pre-treatment depressive mood was not predictive, and effects of Baseline craving were independent of depressive mood. Results suggest a greater ongoing risk from craving than from depressive mood at Baseline.

To what extent is the Mayer and Salovey (1997) model of emotional intelligence a useful predictor of leadership style and perceived leadership outcomes in Australian educational institutions?

Researchers have found that transformational leadership is related to positive outcomes in educational institutions. Hence, it is important to explore constructs that may predict leadership style in order to identify potential transformational leaders in assessment and selection procedures. Several studies in non-educational settings have found that emotional intelligence is a useful predictor of transformational leadership, but these studies have generally lacked methodological rigor and contextual relevance. This project, set in Australian educational institutions, employed a more rigorous methodology to answer the question: to what extent is the Mayer and Salovey (1997) model of emotional intelligence a useful predictor of leadership style and perceived leadership outcomes? The project was designed to move research in the field forward by using valid and reliable instruments, controlling for other predictors, obtaining an adequately sized sample of current leaders and collecting multiple ratings of their leadership behaviours. The study (N = 144 leaders and 432 raters) results indicated that emotional intelligence was not a useful predictor of leadership style and perceived leadership outcomes. In contrast, several of the other predictors in the study were found to predict leadership style.

Validating a novel, low cost, automated malnutrition screening system as a predictor of nutritional risk in the Oncology Day Care Unit

Background Cancer-related malnutrition is associated with increased morbidity, poorer tolerance of treatment, decreased quality of life, increased hospital admissions, and increased health care costs (Isenring et al., 2013). This study’s aim was to determine whether a novel, automated screening system was a useful tool for nutrition screening when compared against a full nutrition assessment using the Patient-Generated Subjective Global Assessment (PG-SGA) tool. Methods A single site, observational, cross-sectional study was conducted in an outpatient oncology day care unit within a Queensland tertiary facility, with three hundred outpatients (51.7% male, mean age 58.6 ± 13.3 years). Eligibility criteria: ≥18 years, receiving anticancer treatment, able to provide written consent. Patients completed the Malnutrition Screening Tool (MST). Nutritional status was assessed using the PG-SGA. Data for the automated screening system was extracted from the pharmacy software program Charm. This included body mass index (BMI) and weight records dating back up to six months. Results The prevalence of malnutrition was 17%. Any weight loss over three to six weeks prior to the most recent weight record as identified by the automated screening system relative to malnutrition resulted in 56.52% sensitivity, 35.43% specificity, 13.68% positive predictive value, 81.82% negative predictive value. MST score 2 or greater was a stronger predictor of nutritional risk relative to PG-SGA classified malnutrition (70.59% sensitivity, 69.48% specificity, 32.14% positive predictive value, 92.02% negative predictive value). Conclusions Both the automated screening system and the MST fell short of the accepted professional standard for sensitivity (80%) or specificity (60%) when compared to the PG-SGA. However, although the MST remains a better predictor of malnutrition in this setting, uptake of this tool in the Oncology Day Care Unit remains challenging.