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Objective: The main purpose of this study was to investigate the factor structure of the Beck Depression Inventory - Second Edition (BDI-II) in a sample of adults. Specifically, we evaluated the BDI-II based on confirmatory factor analysis of different measurement models, and compared the optimal factor structure of the BDI-II by gender using measurement invariance analysis. Method: A cross-sectional survey with 717 community-dwelling adults was conducted. The Brazilian Portuguese version of the BDI-II was administered. Seven different models (one-, two-, three-factor models and their bifactor structures) were tested through CFA. CFA and multigroup analysis were executed with the software MPLUS (Weighted Least Squares Estimator - WLSMV). Results: Four bifactor models reached acceptable fit indices. A bifactor model with two specific factors (Cognitive-Affective, and Somatic-Affective) provided the best fit to the data. The multigroup analysis of this model demonstrated invariance by gender. Conclusions: Our findings support the use of the total BDI-II score to identify depressive symptoms, including gender comparisons. Since a bifactor structure fit the data better, the scores of the specific factors should not be used as the first choice, or at least should be used with caution. The analysis of the severity of depression, based on a total score, seems to be the most appropriate option.

Chronic kidney disease is decreasing glomerular filtration rate of less than 15mL/minute which causes someone to undergo a hemodialysis therapy that replaces kidney function. The course of chronic kidney disease is progressive and irreversible and may cause psychological problems in hemodialysis patients such as depression. This study aimed to describe to what extent patients under hemodialysis treatment at Jemursari Hospital, Surabaya experience depression symptoms in patients. This study was descriptive research with a cross-sectional approach. The simple random sampling technique was performed to select 72 patients who had scheduled hemodialysis treatment and been qualified for the inclusion criteria. Data were then analyed using a univariate analysis in variable frequency distribution. The results show that patients with depression symptoms were mostly men as many as 31 people (43.1%), and the majority were aged 46-65 years as many as 24 people (49%).  The latest formal education in most respondents was high school (23.6%). There were 38 respondents (77.5%) who got married, and most respondents were unemployed (77.5%) and had undergone hemodialysis for more than 12 months (77.5%). This study concludes that the patients under hemodialysis treatment at the hospital experienced mild depression symptoms. Keyword: hemodialysis, depression, Beck Depression Inventory.

DICER1 is an enzyme that generates mature microRNAs (miRNAs), which regulate gene expression post-transcriptionally in brain and other tissues and is involved in synaptic maturation and plasticity. Here, through genome-wide differential gene expression survey of post-traumatic stress disorder (PTSD) with comorbid depression (PTSD&Dep), we find that blood DICER1 expression is significantly reduced in cases versus controls, and replicate this in two independent cohorts. Our follow-up studies find that lower blood DICER1 expression is significantly associated with increased amygdala activation to fearful stimuli, a neural correlate for PTSD. Additionally, a genetic variant in the 3′ un-translated region of DICER1 , rs10144436, is significantly associated with DICER1 expression and with PTSD&Dep, and the latter is replicated in an independent cohort. Furthermore, genome-wide differential expression survey of miRNAs in blood in PTSD&Dep reveals miRNAs to be significantly downregulated in cases versus controls. Together, our novel data suggest DICER1 plays a role in molecular mechanisms of PTSD&Dep through the DICER1 and the miRNA regulation pathway. DICER1 is required for the maturation of miRNAs which regulate expression of thousands of genes. Here the authors show significantly reduced levels of DICER1 in individuals having post-traumatic stress disorder and comorbid depression suggestive of a role in the molecular mechanism of the condition.

ABSTRACT Introduction Depressive tendencies associated with difficulty in the treatment of type 1 diabetes (T1D) could hinder appropriate intervention. Factors related to depressive tendencies in Japan remain unclear, though recent advances in medication may have affected them. Materials and methods Three hundred and fifty‐two Japanese patients with T1D registered in the Juntendo‐Aso Type 1 Diabetes (JAT‐1) Cohort Study were divided into two groups based on depressive tendencies assessed with the Beck Depression Inventory‐II score. We compared background characteristics of the patients between the groups and also analyzed additional clinical factors and quality of life scores. Results The patients with a Beck Depression Inventory‐II score ≧14 (35.5%) are classified as having depressive tendencies. Compared to the individuals without depressive characteristics, those with depressive tendencies had significantly higher proportions of females, welfare recipients, and shift workers; a higher proportion of individuals with microvascular complications; higher diastolic pressure; eating out or taking out food more frequently for dinner; lower protein intake; and higher scores in the total score of diabetes‐related problem domains and Pittsburgh Sleep Quality Index. Multiple regression analysis revealed that diastolic blood pressure, welfare recipient status, total score of diabetes‐related problem domains (PAID), and Pittsburgh Sleep Quality Index were significantly associated factors with BDI‐II score, and the PAID score showed the strongest association. Conclusions This study revealed that diabetes‐specific psychological burden, evaluated with the PAID score, is strongly associated with depressive tendencies. Routine use of the PAID could support the strategies to prevent depression in people with type 1 diabetes by identifying those at risk. We are conducting the Juntendo‐Aso Type 1 Diabetes cohort study, which is a prospective, 5‐year observational study of 352 adults with T1D in Japan. We used baseline data from the Beck Depression Inventory‐II scores and various clinical factors to investigate the prevalence of depression tendencies and their correlates.

Empirical evidence on the effectiveness of evidence-based treatments for adolescents with post-traumatic stress disorder (PTSD) in low-resource settings is needed.AimsTo evaluate the comparative effectiveness of prolonged exposure and supportive counselling in adolescents with PTSD. Sixty-three adolescents (13-18 years) with PTSD were randomly assigned to receive either of the interventions comprising 7-14 sessions of treatment (trial registration in the Pan African Clinical Trials Registry: PACTR201511001345372). The primary outcome measure was PTSD symptom severity, as independently assessed on the Child PTSD Symptom Scale at pre-treatment, post-treatment, and at 3- and 6-month follow-up. Participants receiving prolonged exposure experienced greater improvement on the PTSD symptom severity scale than those receiving supportive counselling (between group differences at post-intervention, mean 12.49, 95% CI 6.82-18.17, P<0.001; d = 1.22). A similar effect size was maintained at 3-month (d = 0.85) and 6-month (d = 1.02) follow-up assessments. Adolescents with PTSD experienced greater benefit from prolonged exposure treatment when provided by non-specialist health workers (nurses) in a community setting.Declaration of interestNone.

Although there is mounting evidence that greater PTSD symptoms are associated with reduced executive functioning, it is not fully understood whether this association is more global or specific to certain executive function subdomains, such as inhibitory control. We investigated the generality of the association between PTSD symptoms and executive function by administering a broad battery of sensitive executive functioning tasks to a cohort of returning Operation Enduring Freedom/Operation Iraqi Freedom Veterans with varying PTSD symptoms. Only tasks related to inhibitory control explained significant variance in PTSD symptoms as well as symptoms of depression, while measures of working memory, measures of switching, and measures simultaneously assessing multiple executive function subdomains did not. Notably, the two inhibitory control measures that showed the highest correlation with PTSD and depressive symptoms, measures of response inhibition and distractor suppression, explained independent variance. These findings suggest that greater posttraumatic psychological symptoms are not associated with a general decline in executive functioning but rather are more specifically related to stopping automatic responses and resisting internal and external distractions. (JINS, 2015, 21, 342–352)

Psychologists have used tests and carefully designed survey questions, such as Beck's Depression Inventory (BDI), to identify the presence of depression and to assess its severity level.On the other hand, methods for automatic depression detection have gained increasing interest since all the information available in social media, such as Twitter and Facebook, enables novel measurement based on language use.These methods learn to characterize depression through natural language use and have shown that, in fact, language usage can provide strong evidence in detecting depressive people.However, not much attention has been paid to measuring finer grain relationships between both aspects, such as how is connected the language usage with the severity level of depression.The present study is a first step towards that direction.We train a binary text classifier to detect ``depressed'' users and then we use its confidence value to estimate the user's clinical depression level.In order to do that, our system has to be able to fill the standard BDI depression questionnaire on users' behalf, based only on their posts in Reddit.Our proposal was publicly tested in the eRisk 2019 task obtaining the best and second-best performance among the other 13 submitted models.

COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson's coefficient =-0.371) and the BDI ( =0.620), both <0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables.

Objective: To assess apathy in patients with Parkinson’s disease and its relation to disability, mood, personality, and cognition. Methods: Levels of apathy in 45 patients with Parkinson’s disease were compared with a group of 17 similarly disabled patients with osteoarthritis. Additional neuropsychiatric data were collected concerning levels of depression, anxiety, and hedonic tone. Personality was assessed with the tridimensional personality questionnaire. Cognitive testing included the mini-mental state examination, the Cambridge examination of cognition in the elderly, and specific tests of executive functioning. Results: Patients with Parkinson’s disease had significantly higher levels of apathy than equally disabled osteoarthritic patients. Furthermore, within the Parkinson sample, levels of apathy appear to be unrelated to disease progression. The patients with Parkinson’s disease with the highest levels of apathy where not more likely to be depressed or anxious than those with the lowest levels of apathy, though they did show reduced hedonic tone. No differences in personality traits were detected in comparisons between patients with Parkinson’s disease and osteoarthritis, or between patients in the Parkinson group with high or low levels of apathy. As a group, the patients with Parkinson’s disease tended not to differ significantly from the osteoarthritic group in terms of cognitive skills. However, within the Parkinson’s disease sample, the high apathy patients performed significantly below the level of the low apathy patients. This was particularly evident on tests of executive functioning. Conclusions: Apathy in Parkinson’s disease is more likely to be a direct consequence of disease related physiological changes than a psychological reaction or adaptation to disability. Apathy in Parkinson’s disease can be distinguished from other psychiatric symptoms and personality features that are associated with the disease, and it is closely associated with cognitive impairment. These findings point to a possible role of cognitive mechanisms in the expression of apathy.

Cognitive models of posttraumatic stress disorder (PTSD) implicate interpretation biases as a maintaining factor of symptoms. Existing measures index symptoms and negative beliefs in PTSD patients, but not threatening interpretation of socially-ambiguous information, which would further inform cognitive models of PTSD. Here we describe the development of a measure of interpretation bias specific to individuals with PTSD. Studies 1 and 2 utilized analog samples to identify the smallest set of items capable of differentiating PTSD-specific interpretation biases. Study 3 utilized a clinical sample to examine the factor structure of the 9-item Interpretation Bias Index for PTSD (IBIP). A bifactor model fit the IBIP best, comprising a general PTSD factor and two subfactors. The IBIP was most strongly related to PTSD symptoms and demonstrated sensitivity and specificity to detecting true PTSD cases. The IBIP has potential clinical utility for tracking interpretation bias in PTSD, or even screening for PTSD diagnoses.