Opinion paper: poor response to treatment of depression in people in high occupational levels

Voice Disorders and Mental health of Basic Education Teachers in a Brazilian Municipality

OBJECTIVE

To identify associations with voice disorders in elementary school teachers of a Brazilian municipality STUDY DESIGN: This was a quantitative cross-sectional and analytical study with probability sampling carried out in the 2016 school year METHOD: Self-report of vocal complaints was used for the dependent variable vocal disorder. The independent variables were sociodemographic and occupational characteristics, working conditions that generate discomfort, habits and behaviors, mental health and self-perception of health. For the evaluation of the Burnout Syndrome (BS), the questionnaire Cuestionário para la Evaluación del Syndrome de Quemarse por el Trabajo (CESQT) was used and, for depression, the Beck Depression Inventory (BDI) scale instrument. Multiple fit models were used applying the Binary Logistic Regression RESULTS: A total of 634 teachers participated in this study. There was a predominance of women (85.3%) with mean age 40.6 years (SD ±9.5); 62.1% were married, 70.2% had children and a mean teaching time of 12.9 years (SD ±8.4); 19.3% had voice disorders; 14.5% experienced BS and 24.0% depression. Voice disorders were associated with women (OR=2.30) working longer weekly hours (OR=1.75), with psycho-emotional problems, with burnout (OR=1.95) and depressive symptoms (OR=1.70), and were also associated with women who reported negative self-perception of health (OR= 1.97) CONCLUSION: Voice disorders appear to be strongly associated with mental health problems, mainly in women, in those with a longer working week and those who reported a negative perception of health. Public policies are required to prevent psycho-emotional problems and for vocal health promotion of the teaching category.

Prognosis and Improved Outcomes in Major Depression: A Review

(Reprinted from Transl Psychiatry. 2019 Apr 3; 9(1):127. Open access; is licensed under a Creative Commons Attribution 4.0 International License).

Social dysfunction in mood disorders and schizophrenia: Clinical modulators in four independent samples

INTRODUCTION

Social dysfunction is a common symptom of several neuropsychiatric disorders. However, only in the last few years research began to systematically investigate clinical aspects of this relevant outcome. Interestingly, its distribution and link with other clinical variables is still unclear. This study investigated social dysfunction in 4 different cohorts of patients affected by mood disorders and schizophrenia to evaluate 1) the degree of social dysfunction in these populations; 2) the associations among social dysfunction and socio-demographic and psychopathological features.

METHODS

Data from 4 independent studies (CATIE, GSRD ES1, ES2 and ES3, STAR*D, STEP-BD) were investigated. Behavioural and affective indicators of social dysfunction were derived and operationalized from scales or questionnaire items related to the interaction with relatives, friends and significant people in patients affected by schizophrenia (N = 765) and mood disorders (N = 2278 + 1954 + 1829). In particular the social dysfunction indicator was derived from Sheehan Disability Scale (SDS) for GSRD sample, from the Work and Social Adjustment Scale (WSAS) for STAR*D sample, from the Life-Range of Impaired Functioning Tool (LRIFT) for STEP-BD sample, and from the Quality of Life Scale (QOLS) for CATIE sample. The distribution of social dysfunction was described and association with socio-demographic and psychopathological characteristics were analysed.

RESULTS

Social dysfunction indicators showed a broad distribution in all samples investigated. Consistently across studies, social dysfunction was associated with higher psychopathological severity (all samples except CATIE) and suicide risk (GSRD ES1 and ES2, STAR*D, and STEP-BD) that explain up to 47% of the variance, but also to lower education level (GSRD ES2, STAR*D, CATIE, and STEP-BD), poorer professional/work status (GSRD ES2 and ES3, STAR*D, CATIE, and STEP-BD), marital status (STAR*D and CATIE), age (younger age in GSRD ES1 and STAR*D, older age in CATIE), higher BMI (GSRD ES2 and ES3, and STEP-BD), and smoking (GSRD ES2 and ES3).

CONCLUSION

Our results demonstrated that a significant percentage of patients affected by both mood disorders and schizophrenia shows relevant social dysfunction. Social dysfunction is related, but not completely explained by psychopathological severity. In several patients, it tends to persist also during remission state. Socio-demographic and lifestyle factors were also found to play a role and should therefore be taken into consideration in further studies investigating social dysfunction.

Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Despite several pharmacological options, the clinical outcomes of major depressive disorder (MDD) are often unsatisfactory. Personalized psychiatry attempts to tailor therapeutic interventions according to each patient's unique profile and characteristics. This approach can be a crucial strategy in improving pharmacological outcomes in MDD and overcoming trial-and-error treatment choices. In this narrative review, we evaluate whether sociodemographic (i.e., gender, age, race/ethnicity, and socioeconomic status) and clinical [i.e., body mass index (BMI), severity of depressive symptoms, and symptom profiles] variables that are easily assessable in clinical practice may help clinicians to optimize the selection of antidepressant treatment for each patient with MDD at the early stages of the disorder. We found that several variables were associated with poorer outcomes for all antidepressants. However, only preliminary associations were found between some clinical variables (i.e., BMI, anhedonia, and MDD with melancholic/atypical features) and possible benefits with some specific antidepressants. Finally, in clinical practice, the assessment of sociodemographic and clinical variables considered in our review can be valuable for early identification of depressed individuals at high risk for poor responses to antidepressants, but there are not enough data on which to ground any reliable selection of specific antidepressant class or compounds. Recent advances in computational resources, such as machine learning techniques, which are able to integrate multiple potential predictors, such as individual/ clinical variables, biomarkers, and genetic factors, may offer future reliable tools to guide personalized antidepressant choice for each patient with MDD.

CA, Kasper S. Prognosis and improved outcomes in major depression: a review

Treatment outcomes for major depressive disorder (MDD) need to be improved. Presently, no clinically relevant tools have been established for stratifying subgroups or predicting outcomes. This literature review sought to investigate factors closely linked to outcome and summarize existing and novel strategies for improvement. The results show that early recognition and treatment are crucial, as duration of untreated depression correlates with worse outcomes. Early improvement is associated with response and remission, while comorbidities prolong course of illness. Potential biomarkers have been explored, including hippocampal volumes, neuronal activity of the anterior cingulate cortex, and levels of brain-derived neurotrophic factor (BDNF) and central and peripheral inflammatory markers (e.g., translocator protein (TSPO), interleukin-6 (IL-6), C-reactive protein (CRP), tumor necrosis factor alpha (TNFα)). However, their integration into routine clinical care has not yet been fully elucidated, and more research is needed in this regard. Genetic findings suggest that testing for CYP450 isoenzyme activity may improve treatment outcomes. Strategies such as managing risk factors, improving clinical trial methodology, and designing structured step-by-step treatments are also beneficial. Finally, drawing on existing guidelines, we outline a sequential treatment optimization paradigm for selecting first-, second-, and third-line treatments for acute and chronically ill patients. Well-established treatments such as electroconvulsive therapy (ECT) are clinically relevant for treatment-resistant populations, and novel transcranial stimulation methods such as theta-burst stimulation (TBS) and magnetic seizure therapy (MST) have shown promising results. Novel rapid-acting antidepressants, such as ketamine, may also constitute a paradigm shift in treatment optimization for MDD.

High occupational level is associated with poor response to the treatment of depression: A replication study

Major depressive disorder (MDD) is a leading cause of disability and inability to work. There is evidence that occupational factors may precipitate a MDD episode and interfere with the recovery process. In a previous investigation, we found that those employed in high occupational levels had a worse outcome after treatment for depression (Mandelli et al., 2016). The aim of the present study was to further investigate response to treatments for depression according to occupational status on an independent sample of MDD patients. Six hundred and forty-seven (647) subjects with a stable working occupation were taken from a larger independent sample of MDD patients evaluated for response and resistance to treatment for depression, after at least one adequate treatment trial. Three broad occupational categories were considered: 'manager', 'white-collar', 'blue-collar' and 'self-employed'. Managers had the highest rate of non-response and resistance to treatments. White-collar workers also had high non-response and resistance rates. At the opposite, Blue-collar workers had significantly lower rates of non-response and resistance. Self-employed were in between White- and Blue-collar workers and did not significantly differ from the other occupational categories. The findings of this replication study substantially support our previous observations. MDD patients employed in high-middle occupations may have a less favorable outcome after standard treatments of depression. Working stressful condition and other psychosocial factors at work should be investigated more closely in relation to treatment outcomes in MDD.