Rheumatoid arthritis (RA) is a chronic, systemic, inflammatory disorder of unknown etiology. It is characterized by symmetric, polyarticular pain, swelling, morning stiffness, and fatigue. RA has a variable course, often with periods of exacerbations and, less frequently, true remissions. Outcomes are also variable, ranging from the rarely seen remitting disease to severe disease that brings disability and in some patients premature death. Without treatment, the majority of patients will experience progressive joint damage and, in some patients, this results in significant disability within just a few years. Improvement in health related quality of life is one of the most important goals in the management of rheumatoid arthritis and therefore must be pursued as a crucial aim in clinical practice. This paper draws from 49 qualitative interviews conducted with RA patients, before starting a program of Spa Therapy and aims to get an overview of their main RA related difficulties, worries, and overall understanding of quality of life. Information on the patients’ physical function was also obtained by means of the Stanford Health Assessment Questionnaire Disability Index (HAQ). Patients present a mean HAQ score of 1.42 (SD=0.69). Main findings from the interviews highlight the importance given to being autonomous and feeling independent and healthy. In addition, underlying psychological problems (e.g. depressive signs; coping with progressive dependence) and concerns with social relationships (e.g. perceived support, loneliness) emerged as significant facets of living with the disease. Despite different treatments, RA still has many deleterious consequences which from the patients’ perspective include, among other, persistent pain, functional disability, fatigue, and depression. Along with treating RA signs and associated medical evolution, medical staff should consider and deeply understand the patients’ needs, expectations and main perceived determinants of their quality of life.

Background: Psychosocial risks are increasingly a type of risk analyzed in organizations beyond chemical, physical, and biological risks. To this type of risk, a greater attention has been given following the update of ISO 9001: 2015, more precisely the requirement 7.1.4 for the process operation environment. The update of this normative reference was intended to approximate OHSAS 18001: 2007 reference updated in 2018 with the publication of ISO 45001. Thus, the organizations are increasingly committed to achieving and demonstrating good occupational health and safety performance. Methods: The aim of this study was to characterize the psychosocial risks in a cryopreservation laboratory and to develop a predictive model for psychosocial risk management. The methodology followed to collect the information was the inquiry by questionnaire that was applied to a sample comprising 200 employees. Results: The results show that most of the respondents are aware of the psychosocial risks, identifying interpersonal relationships and emotional feelings as the main factors that lead to this type of risks. Furthermore, terms such as lack of resources, working hours, lab equipment, stress, and precariousness show strong correlation with psychosocial risks. The model presented in this study, based on artificial neural networks, exhibited good performance in the prediction of the psychosocial risks. Conclusion This work presents the development of an intelligent system that allows identifying the weaknesses of the organization and contributing to the enhancement of the psychosocial risks management.

Background: Psychosocial risks are increasingly a type of risk analyzed in organizations beyond chemical, physical, and biological risks. To this type of risk, a greater attention has been given following the update of ISO 9001: 2015, more precisely the requirement 7.1.4 for the process operation environment. The update of this normative reference was intended to approximate OHSAS 18001: 2007 reference updated in 2018 with the publication of ISO 45001. Thus, the organizations are increasingly committed to achieving and demonstrating good occupational health and safety performance. Methods: The aim of this study was to characterize the psychosocial risks in a cryopreservation laboratory and to develop a predictive model for psychosocial risk management. The methodology followed to collect the information was the inquiry by questionnaire that was applied to a sample comprising 200 employees. Results: The results show that most of the respondents are aware of the psychosocial risks, identifying interpersonal relationships and emotional feelings as the main factors that lead to this type of risks. Furthermore, terms such as lack of resources, working hours, lab equipment, stress, and precariousness show strong correlation with psychosocial risks. The model presented in this study, based on artificial neural networks, exhibited good performance in the prediction of the psychosocial risks. Conclusion This work presents the development of an intelligent system that allows identifying the weaknesses of the organization and contributing to the enhancement of the psychosocial risks management.