scholarly journals Association of work performance and interoceptive awareness of ‘body trusting’ in an occupational setting: a cross-sectional study

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e044303
Author(s):  
Chisato Tanaka ◽  
Kenta Wakaizumi ◽  
Shizuko Kosugi ◽  
Shintaro Tanaka ◽  
Ko Matsudaira ◽  
...  

ObjectivesWork performance has been known to be influenced by both psychological stress (mind) and physical conditions (body). The aim of this study was to investigate the association between work performance and ‘body trusting’, which is a dimension of interoceptive awareness representing mind–body interactions.MethodsA cross-sectional study was conducted among a sample of workers in an industrial manufacturing company in Japan. Participants were assessed with a self-reported questionnaire including evaluations of work performance, body trusting, psychological distress, pain persistence, workplace and home stressors, and workaholism. Participants’ sociodemographic, health and lifestyle characteristics were collected from their annual health check data. The association between work performance and body trusting was examined using multivariable regression analyses in the overall sample and in a subsample of people with pain.ResultsA total of 349 workers participated in the study. A significant association between work performance and body trusting was observed, with higher body trusting representing higher work performance. The association was significant after controlling for psychological distress, workplace and home stress, workaholism and participants’ characteristics (p<0.001). Compared with people without pain (n=126, 36.1%), people with pain (n=223, 63.9%) showed less body trusting, which was associated with decreased work performance after controlling for pain-related variables (p<0.001).ConclusionsWorkers with higher body trusting showed higher work performance, even after controlling for various influencing factors. Body trusting may be an important target to promote work performance and to prevent loss of performance induced by health problems.

2021 ◽  
Vol 5 (1) ◽  
pp. e000958
Author(s):  
Merel M Nap-van der Vlist ◽  
Geertje W Dalmeijer ◽  
Martha A Grootenhuis ◽  
Kors van der Ent ◽  
Marry M van den Heuvel-Eibrink ◽  
...  

ObjectiveTo determine: (1) which biological/lifestyle, psychological and/or social factors are associated with fatigue among children with a chronic disease and (2) how much each of these factors contributes to explaining variance in fatigue.Design and settingThis was a cross-sectional study across two children’s hospitals.PatientsWe included children aged 8–18 years who visited the outpatient clinic with cystic fibrosis, an autoimmune disease or postcancer treatment.Main outcome measuresFatigue was assessed using the PedsQL Multidimensional Fatigue Scale. Generic biological/lifestyle, psychological and social factors were assessed using clinical assessment tools and questionnaires. Multiple linear regression analyses were used to test the associations between these factors and fatigue. Finally, a multivariable regression model was used to determine which factor(s) have the strongest effect on fatigue.ResultsA total of 434 out of 902 children were included (48% participation rate), with a median age of 14.5 years; 42% were male. Among these 434 children, 21.8% were severely fatigued. Together, all biopsychosocial factors explained 74.6% of the variance in fatigue. More fatigue was uniquely associated with poorer physical functioning, more depressive symptoms, more pressure at school, poorer social functioning and older age.ConclusionsFatigue among children with a chronic disease is multidimensional. Multiple generic biological/lifestyle, psychological and social factors were strongly associated with fatigue, explaining 58.4%; 65.8% and 50.0% of the variance in fatigue, respectively. Altogether, almost three-quarters of the variance in fatigue was explained by this biopsychosocial model. Thus, when assessing and treating fatigue, a transdiagnostic approach is preferred, taking into account biological, psychological and social factors.


BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e046265
Author(s):  
Shotaro Doki ◽  
Shinichiro Sasahara ◽  
Daisuke Hori ◽  
Yuichi Oi ◽  
Tsukasa Takahashi ◽  
...  

ObjectivesPsychological distress is a worldwide problem and a serious problem that needs to be addressed in the field of occupational health. This study aimed to use artificial intelligence (AI) to predict psychological distress among workers using sociodemographic, lifestyle and sleep factors, not subjective information such as mood and emotion, and to examine the performance of the AI models through a comparison with psychiatrists.DesignCross-sectional study.SettingWe conducted a survey on psychological distress and living conditions among workers. An AI model for predicting psychological distress was created and then the results were compared in terms of accuracy with predictions made by psychiatrists.ParticipantsAn AI model of the neural network and six psychiatrists.Primary outcomeThe accuracies of the AI model and psychiatrists for predicting psychological distress.MethodsIn total, data from 7251 workers were analysed to predict moderate and severe psychological distress. An AI model of the neural network was created and accuracy, sensitivity and specificity were calculated. Six psychiatrists used the same data as the AI model to predict psychological distress and conduct a comparison with the AI model.ResultsThe accuracies of the AI model and psychiatrists for predicting moderate psychological distress were 65.2% and 64.4%, respectively, showing no significant difference. The accuracies of the AI model and psychiatrists for predicting severe psychological distress were 89.9% and 85.5%, respectively, indicating that the AI model had significantly higher accuracy.ConclusionsA machine learning model was successfully developed to screen workers with depressed mood. The explanatory variables used for the predictions did not directly ask about mood. Therefore, this newly developed model appears to be able to predict psychological distress among workers easily, regardless of their subjective views.


Author(s):  
Marion J. Wessels‐Bakker ◽  
Eduard A. van de Graaf ◽  
Johanna M. Kwakkel‐van Erp ◽  
Harry G. Heijerman ◽  
Wiepke Cahn ◽  
...  

2018 ◽  
Vol 154 (1) ◽  
pp. S49
Author(s):  
Shmuel Odes ◽  
Vered Slonim-Nevo ◽  
Ruslan Sergienko ◽  
Michael Friger ◽  
Doron Schwartz ◽  
...  

Author(s):  
Ana Cebrián-Cuenca ◽  
José Joaquín Mira ◽  
Elena Caride-Miana ◽  
Antonio Fernández-Jiménez ◽  
Domingo Orozco-Beltrán

Abstract Background: The COVID-19 pandemic is affecting people worldwide. In Spain, the first wave was especially severe. Objectives: This study aimed to identify sources and levels of distress among Spanish primary care physicians (PCPs) during the first wave of the pandemic (April 2020). Methods: A cross-sectional study was conducted using a survey that included sociodemographic data, a description of working conditions related to distress [such as gaps in training in protective measures, cleaning, and hygiene procedures in work setting, unavailability of personal protective equipments (PPEs) and COVID-19 RT-PCR test, and lack of staff due to be infected] and a validated scale, the ‘Self-applied Acute Stress Scale’ (EASE). The survey was answered by a non-probability sampling of PCPs working in family healthcare centres from different regions of Spain. Analysis of variance and multivariate linear regression analysis were performed. Results: In all, out of 518 PCP participants, 123 (23.7%) obtained high psychological distress scores. Only half of them had received information about the appropriate use of PPE. PCP characteristics associated with higher levels of distress include female gender [1.69; 95% confidence interval (CI) 0.54, 2.84]; lack of training in protective measures (1.96; 95% CI 0.94, 2.99); unavailable COVID-19 RT-PCR for health care workers after quarantine or COVID-19 treatment (−0.77 (−1.52, −0.02). Reinforcing disinfection of the work environment (P < 0.05), availability of PPEs (P < 0.05), and no healthcare professional was infected (P < 0.05) were related to the lowest distress score. Conclusions: A better understanding of the sources of distress among PCPs could prevent its effect on future outbreaks.


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