Is it all about Depression? Determinants of Burnout among Employees Referred for Inpatient Treatment of Job-Related Stress Disorders

Evaluating an Autistic Burnout Measurement in Women

This study evaluated the suitability of an unpublished autistic burnout assessment tool, focusing on autistic women. Distinguishing autistic burnout from conditions like depression or anxiety is crucial for effective interventions, emphasizing the need for nuanced research and refined measures in understanding and addressing autistic burnout. The Dutch version of the AASPIRE Autistic Burnout Measure (AABM-NL) was evaluated within a sample of 45 autistic women from the Autism Expertise Center. Preliminary findings of the AABM-NL scores demonstrated promising evidence of good internal consistency and convergent validity. Positive associations were observed between AABM-NL scores and a Likert scale assessing identification with autistic burnout, as well as with an instrument measuring physical and psychological complaints (SCL-90-R; Symptom Checklist-90-Revised). Specifically, anxiety, somatization, cognitive-performance deficits, and depression were correlated with the severity of autistic burnout. There was no significant difference between work status and the severity of autistic burnout, implying no employment-related connection. The AABM-NL effectively differentiated between women with and without autistic burnout, with 62 points as a suitable cut-off point. However, these results may not be generalized to women requiring daily living support, individuals beyond outpatient psychiatric settings, or those in institutionalized populations. The preliminary findings provide empirical evidence supporting the use of the AABM-NL as a potential tool for assessing autistic burnout in women receiving outpatient psychiatric care. Its implementation may contribute to programs aimed at recognizing and preventing autistic burnout in women. Further research is needed to enhance intervention strategies for mitigating the risk of autistic burnout.

Mediating effect of sleep quality on the association between job stress and health-related productivity loss among workers in R&D enterprises in Shanghai

Background

Past research indicates that occupational stress negatively predicts health-related productivity. Simultaneously, sleep problem among workers may stem from job stress, subsequently leading to a decline in sleep quality and resulting in reduced health productivity. Therefore, this study aims to idenitify whether the sleep quality of employees functions as a mediator in the process through which job stress impacts health productivity.

Objectives

This study aimed to assess the status and analyze differences in quality of sleep, job stress, and health-related productivity loss (HRPL) among workers in research and development (R&D) enterprises in Minhang District, Shanghai. We also assessed the mediating effect of sleep quality on the relationship between job stress and HRPL.

Methods

A total of 3,216 workers in R&D firms aged between 18 and 60 years participated in this study (mean age 35.15 years; standard deviation 8.44; male-to-female ratio≈2:1). The Nakata Insomnia Questionnaire, the Chinese version of the Brief Job Stress Questionnaire revised edition, and the Chinese version of the Work Productivity and Activity Impairment Questionnaire were used in this study. And the Kruskal-Wallis test, Hierarchical Multiple Regression Analysis, and Path Analysis were utilized for data analysis in this study.

Results

There were significant differences in the positive detection rate of insomnia among participants according to age, educational level, marital status, position, length of service, and level of financial difficulties (all P < 0.05). We also found significant differences in the positive detection rate of HRPL among participants according to age, marital status, length of service, and level of financial difficulties (all P < 0.05); participants with insomnia scored higher for HRPL than those without insomnia (6.00 vs. 4.20, P < 0.001). Additionally, participants with job stress problems had higher HRPL than those without these issues (7.00 vs. 4.20, P < 0.001). Our findings suggest that sleep quality plays a mediating role between job stress and HRPL (all P < 0.05).

Conclusions

Occupational health professionals must pay particular attention to job stress, sleep quality, and their influencing factors to positively influence the wellbeing of workers while improving productivity.

Should Burnout Be Conceptualized as a Mental Disorder?

Burnout is generally acknowledged by researchers, clinicians, and the public as a pervasive occupational difficulty. Despite this widespread recognition, longstanding debates remain within the scientific community regarding its definition and the appropriateness of classifying burnout as its own pathological entity. The current review seeks to address whether burnout should (or could) be characterized as a distinctive mental disorder to shed light on this debate. After briefly reviewing the history, theoretical underpinnings, and measurement of burnout, we more systematically consider the current evidence for and against its classification as a mental disorder within existing diagnostic systems. Stemming from a lack of conceptual clarity, the current state of burnout research remains, unfortunately, largely circular and riddled with measurement issues. As a result, information regarding the unique biopsychosocial etiology, diagnostic features, differential diagnostic criteria, and prevalence rates of burnout are still lacking. Therefore, we conclude that it would be inappropriate, if not premature, to introduce burnout as a distinct mental disorder within any existing diagnostic classification system. We argue, however, that it would be equally premature to discard burnout as a psychologically relevant phenomenon and that current evidence does support its relevance as an important occupational syndrome. We finally offer several avenues for future research, calling for cross-national collaboration to clarify conceptual and measurement issues while avoiding the reification of outdated definitions. In doing so, we hope that it one day becomes possible to more systematically re-assess the relevance of burnout as a distinctive diagnostic category.

The magnitude and effect of work-life imbalance on cognition and affective range among the non-western population: A study from Muscat

The temporal relationship between work-life balance/imbalance, occupational burnout, and poor mental health outcomes have been widely explored. Little has been forthcoming on cognitive functioning among those with work-life imbalance. This study aimed to explore the rate of work-life imbalance and the variation in neuropsychological functioning. The relationship between affective ranges (anxiety and depressive symptoms) and work-life balance was also explored. The target population in this study are Omani nationals who were referred for psychometric evaluation. The study employs neuropsychology measures tapping into attention and concentration, learning and remembering, processing speed, and executive functioning. Subjective measures of cognitive decline and affective ranges were also explored. A total of 168 subjects (75.3% of the responders) were considered to be at a work-life imbalance. Multivariate analysis showed that demographic and neuropsychological variables were significant risk factors for work-life imbalance including age and the presence of anxiety disorder. Furthermore, participants indicating work-life imbalance were more likely to report cognitive decline on indices of attention, concentration, learning, and remembering. This study reveals that individuals with work-life imbalance might dent the integrity of cognition including attention and concentration, learning and remembering, executive functioning, and endorsed case-ness for anxiety.

Bio-Psycho-Socio-Spirito-Cultural Factors of Burnout: A Systematic Narrative Review of the Literature

Background: Burnout is a widespread, multifactorial, and mainly psychological phenomenon. The pathogenesis of burnout is commonly described within the bio-psycho-social model of health and disease. Recent literature suggests that the phenomenon of burnout may be broader so that the three dimensions might not reflect the multifaceted and complex nature of the syndrome. Consequently, this review aims to identify the diversity of factors related to burnout, to define overarching categories based on these, and to clarify whether the bio-psycho-social model adequately describes the pathogenesis of burnout-holistically and sufficiently. Method: Five online databases (PubMed, PubPsych, PsychARTICLES, Psychology and Behavioral Sciences Collection, and Google Scholar) were systematically searched using defined search terms to identify relevant studies. The publication date was set between January 1981 and November 2020. Based on the selected literature, we identified factors related to burnout. We aggregated these factors into a comprehensible list and assigned them to overarching categories. Then, we assigned the factors to the dimensions of an extended model of health and disease. Results: We identified a total of 40 burnout-related factors and 10 overarching categories. Our results show that in addition to biological, psychological, and socio-environmental factors, various factors that can be assigned to a spiritual and work cultural dimension also play an important role in the onset of burnout. Conclusion: An extended bio-psycho-socio-spirito-cultural model is necessary to describe the pathogenesis of burnout. Therefore, future studies should also focus on spiritual and work cultural factors when investigating burnout. Furthermore, these factors should not be neglected in future developments of diagnosis, treatment, and prevention options.

Performance Assessment of Certain Machine Learning Models for Predicting the Major Depressive Disorder among IT Professionals during Pandemic times

Major depressive disorder (MDD) is the most common mental disorder in the present day as all individuals' lives, irrespective of being employed or unemployed, is going through the depression phase at least once in their lifetime. In simple terms, it is a mood disturbance that can persist for an individual for more than a few weeks to months. In MDD, in most cases, the individuals do not consult a professional, and even if being consulted, the results are not significant as the individuals find it challenging to identify whether they are depressed or not. Depression, most of the time, cooccurs with anxiety and leads to suicide in few cases, among the employees, who are about to handle the pressure at work and home and mostly unnoticing such problems. This is why this work aims to analyze the IT employees who are mostly working with targets. The artificial neural network, which is modeled loosely like the brain, has proved in recent days that it can perform better than most of the classification algorithms. This study has implemented the multilayered neural perceptron and experimented with the backpropagation technique over the data samples collected from IT professionals. This study aims to develop a model that can classify depressed individuals from those who are not depressed effectively with the data collected from them manually and through sensors. The results show that deep-MLP with backpropagation outperforms other machine learning-based models for effective classification.

[Using endurance training in nature as a resource in inpatient psychotherapy]

Using endurance training in nature as a resource in inpatient psychotherapy Objectives: Although positive effects of nature on mental health are generally well-documented, clinical studies into the deliberate use of nature as a resource in in-patient psychotherapy are missing. The following study examined whether an endurance training intervention in psychosomatic rehabilitation showed differential effects on patients depending on its implementation in an indoor or outdoor nature setting. Methods: Endurance training indoors (ergometer) was compared to training outdoors in the nature (walking) in N = 88 in-patients of a psychosomatic rehabilitation clinic using a linear mixed effects model. Health effects were examined using a standardized questionnaire on somatic symptoms (Giessener Beschwerdebogen GBB-24) and a mood questionnaire (Aktuelle Stimmungsskala ASTS). Seasonal effects were assessed by testing half of the sample in summer and half in winter. Secondary analyses of the linear mixed effects model were run for depression as primary diagnosis which accounted for half of the sample. Results: A nature setting positively predicted improvements on the ASTS positive mood scale (B = 0.34; t(245) = 3.25; p = .001; p_Bonferroni = .052). No significant interaction was found between the effect of the training setting and depression as primary diagnosis (B = -0.05; t(245) = -0.30; p = .76) in secondary analyses. Conclusions: The results primarily point to an improvement in mood following endurance training in a nature setting. Improvements are independent of depression as the primary diagnosis.