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Study of Complexity Systems in Public Health for Evaluating the Correlation between Mental Health and Age-Related Demographic Characteristics: A General Health Study

Study of Complexity Systems in Public Health for Evaluating the Correlation between Mental Health... Hindawi Journal of Healthcare Engineering Volume 2022, Article ID 2117031, 8 pages https://doi.org/10.1155/2022/2117031 Research Article Study of Complexity Systems in Public Health for Evaluating the Correlation between Mental Health and Age-Related Demographic Characteristics: A General Health Study 1 2 3,4 4 4 Fereshte Haghi, Shadi Goli, Rana Rezaei, Fatemeh Akhormi, Fatemeh Eskandari, 1,4 and Zeinab Nasr Isfahani Shahid Beheshti OB&GYN Hospital Isfahan University of Medical Sciences, Isfahan, Iran Nursing and Midwifery Sciences Development Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran Department of Midwifery, Shoushtar Faculty of Medical Sciences, Shoushtar, Iran Department of Midwifery, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran Correspondence should be addressed to Zeinab Nasr Isfahani; nasrisfahani.z@ajums.ac.ir Received 28 December 2021; Revised 8 February 2022; Accepted 3 March 2022; Published 6 April 2022 Academic Editor: Mohsen Ahmadi Copyright © 2022 Fereshte Haghi et al. ,is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ,e main objective of this study is to evaluate the quality of nurses’ work lives and mental health during outbreaks. We also use the General Health Questionnaire–28 and Walton’s QWL technique to assess the association between these two and their dimensions with demographic variables and each other. First, 165 nurses from COVID-19 medical centers in Iran filled surveys for this research. In an SPSS program, the data were examined. ,ere was a strong link between mental health and age-related de- mographic factors. ,ere was no evidence of a link between the quality of nurses’ work life and their psychological health. However, there was a strong link between somatic symptoms and fair and appropriate compensation, as well as constitutionalism. ,e worst situations for work life quality were linked to the whole living area dimension. In contrast, the worst conditions for mental health were linked to the somatic symptoms dimension. on the working community, active in various business 1. Introduction sectors [3]. COVID-19 has attracted special international In December 2019, an acute respiratory syndrome caused by attention as a serious threat to global public health. ,e SARS-CoV-2 caused a global pandemic in Wuhan, China, increasing prevalence of this disease and the prolongation of where almost the entire human community has been directly the disease process have made the activities of the medical affected by the disease or associated safety social restrictions. staff exhaustive [4]; ,us, with the over-admission of pa- Numerous studies have been published on the mechanism of tients in medical centers, the availability and readiness of the medical staff is a determining factor in overcoming the crisis action of this coronavirus and its individual and social effects and consequences, which indicate the occurrence of physical [5]. Considering that various studies and reports indicate the disease in the form of clinical complications and manifes- effect of health care providers’ satisfaction on patient sat- tations such as fever, chills, sore throat, contusion, cough, isfaction [6–11] and on the other hand, job satisfaction has a respiratory problems, vomiting, and diarrhea [1], as well as two-way relationship with the mental and psychological psychological complications such as fear and anxiety [2]. Of condition of employees [12], it is essential to consider course, clinical complications have affected patients, and psychological conditions and their improvement methods in psychological complications have affected both patients and the medical center. nonpatients. ,e pandemic has had a tremendous impact on According to the World Health Organization definition, various occupations. It has imposed different consequences mental health is “a state of wellbeing in which the individual 2 Journal of Healthcare Engineering ,ese strategies may vary even concerning the nurses’ realizes his or her abilities, can cope with the normal stresses of life, can work productively and fruitfully, and can make a workplace. From this point of view, it is necessary to conduct the necessary research. According to the explanations contribution to his or her community.” Good mental health is one of the pillars of health and is necessary for a useful, provided, it can be said that this study seeks to answer the effective, and satisfying life [13]. Quality of work life (QWL) following questions: is essential for attracting and retaining employees. When an (i) What are the most important problems and inad- organization provides a good QWL for employees, it intends equacies related to the quality of work life? to retain employees [14]. Quality of work life is one issue that (ii) What are the most important problems and mental affects almost all people regardless of the situation. In disorders? hospitals and medical centers, the quality of hospital services will not be guaranteed without the participation of nurses (iii) What is the correlation between the aspects of [15]. Various factors such as incompatibility and dissatis- quality of work life and mental disabilities? faction with work, stress, fatigue, illness, and lack of leisure time of nurses affect their behavior [16]. Nurses who have 2. Literature Review dealt with patients for a more extended period are more likely to be vulnerable. Critical and painful patients, dying Numerous studies have been conducted on mental health patients, complex equipment, inappropriate behaviors of and QWL and their relationship. A significant part of these patient companions, patients’ reactions, and many other studies goes back to nurses working in medical centers. issues give different aspects to nurses’ work, and such Javadi-Pashaki and Darvishpour [24] in their study on stress conditions affect burnout, job satisfaction, and the tendency and coping strategies to predict the general health of nursing of nurses to continue working [17]. ,ese characteristics in staff considered 318 nurses working in health centers of the workplace increase stress and the risk of mental dis- Guilan University of Medical Sciences [24]. ,e results orders [18]. Nursing is one of the 130 most stressful oc- showed that stress and coping strategies could explain about cupations and is ranked 27th among 130 occupations with a 2.5% of the variance in public health. However, the results high prevalence of mental disorders [19]. Nurses face several showed that coping strategies are significantly more pre- stressful sources such as time, long-term work, change of dictive of public health. Accordingly, attention to coping work shift, insomnia, death observation, malignancy, high strategies to predict general health in nurses has been patient expectations of nurses, and a low tolerance for error highlighted. Mahmoudi [3] studied the economic effect of [20]. Job stress can lead to disorders that put nurses at COVID-19. ,is model is enhanced with additional char- serious risk of mental disorders [21]. acteristics to assess the economic impact of COVID-19 on From December 2019 onward, medical staff, especially the labor market. ,e findings indicate that the US gov- nurses, are under severe pressure. Various waves of COVID- ernment might employ a straightforward technique to 19 have swept across many countries, including Iran. In this mitigate the harmful effects of COVID-19. situation, not only do medical staff rescue infected patients Zhang et al. [22] in their study of the mental health status but they also oversee the entire process of combating health of Chinese healthcare-related infection control specialists events. In addition to the stress of the job itself, they are during the coronavirus outbreak investigated data from involved in a conflict between their safety needs and job 9,228 cases from 3,776 hospitals across China in the form of requirements. ,ey may be exposed to anxiety, depression, an online questionnaire. A 12-item Chinese version of the insomnia, and other psychological disorders [22]. High- General Health Questionnaire and a Chinese version of the sensitivity patient care imposes significant physical and Psychological Capital Questionnaire suitable for medical emotional burdens, exacerbated by increased workload, staff personnel were used as tools in this study. By performing shortages, and equipment shortages. Direct contact with the univariate and multivariate analysis, it was found that the patient increases the risk of infection [23]. Meanwhile, the risk of mental health problems is higher with more self- measures taken by the government, especially with an sufficiency and working in a public hospital. Working in a emphasis on social distance and restricting communication second-degree rather than a third-degree hospital poses a and travel outside the workplace, are also significant. significantly lower risk. However, fewer psychological ,erefore, it is impossible to take many common strategies problems have been observed in single people than in to reduce stress and anxiety, which increases the respon- married ones. In addition, fewer working hours per week, sibility of medical centers to take the initiative and create the hope, and optimism played a role in reducing risk. Har- appropriate conditions to compensate for the shortcomings. diyono [25] in their study on burnout of nurses working in Paying attention to the QWL and improving it is one of the the hospital for the treatment of patients with COVID-19 approaches used by organizations. However, the QWL in- concluded that burnout is present in nurses who were ex- cludes several aspects, and consequently, a variety of solu- posed to a large number of patients with the virus [25]. ,e tions in this area is considerable. high workload, and at the same time, the worry of trans- It is necessary to properly understand the psychological mitting the virus to themselves and their family members is problems of nurses in the context of the COVID-19 pan- one of the most important factors that put them under demic, the relationship between various problems and psychological pressure and lead to burnout. Quchan et al., in mental disorders with different aspects of work life, and to their study, compared the mental health of nurses working create the right mentality to adopt an appropriate solution. in COVID-19 referral hospitals and regular hospitals [2]. 60 Journal of Healthcare Engineering 3 and energy following COVID-19. According to Chen et al. [34], nurses related to the COVID-19 wards and 62 non-COVID- 19 nurses participated in the study. A standard public health a Markov chain position predictions model based on multilevel correction was presented. ,is approach is also helpful in de- questionnaire was provided to them online. ,ere was no statistically significant difference between the two groups. termining the correlation between the variables in the COVID- However, both groups had poor mental health, which the 19 dataset. Ala et al. [35] studied how the whale optimization researchers said was probably due to the pandemic. Sade- algorithm and the NSGA-II can be used to optimize appoint- ghipoor and Moradisabzevar [26] developed a smart toy car ment scheduling for healthcare systems based on the quality of to screen children for autism. ,e findings indicate that the fairness service provided. According to Hankir et al. [36]; a study system has an accuracy rate of 85 percent, a sensitivity of 93 protocol is being developed to study an anti-stigma program and long-term reductions in mental health stigma among medical percent, and a specificity of 76 percent. ,e findings are same for boys and girls, indicating that this approach may be students. Abbas [37] drew on data on coronavirus infections obtained from the Ministry of Health and National Institute of widely used by all youngsters. Dehkordi et al. [27] conducted a study on the effect of Health Pakistan to conduct his research. ,is study evaluation includes data provided by the National Institutes of Health, and COVID-19 disease on anxiety, quality of work life, and fatigue of health care providers in health centers in southwestern Iran. ,e responses were from all areas of Pakistan, limiting the gener- statistical population includes 181 people directly related to alizability of the findings to empirical evidence. patients and 261 employees in other wards who had no direct contact with patients with COVID-19 [27]. ,ey concluded that 3. Methodology both groups’ work life quality had decreased, and fatigue and anxiety caused by COVID-19 had increased. However, there is In the present study, data collection has been performed no statistically significant difference between the fatigue caused based on 250 General Health Questionnaire – 28 (GHQ-28) by the anxiety of the staff involved with COVID-19 and the of Goldberg and Hillier [38] and Walton’s QWL ques- personnel of other departments. In terms of QWL, no significant tionnaire [39] distributed among nurses of ten hospitals in difference was observed in other components except for human Iran with surgical, orthopedic, COVID-19, intensive care resource development. ,e results also showed a statistically units, emergency, cardiology, and neurology wards. ,e significant relationship between the level of component anxiety validity and reliability of both questionnaires have been with QWL and fatigue. Kelbiso et al. [28] have identified and repeatedly reviewed and found appropriate for screening the analyzed the determinants of QWL among nurses working in QWL and job-related factors [40, 41]. public health facilities in Hawassa, Ethiopia [28]. In this study, ,e GHQ-28 questionnaire is multiple choice and has 253 nurses from two hospitals and nine health centers partic- four dimensions: somatic symptoms, anxiety and insomnia, ipated. Findings showed that at least 60% of nurses were dis- social dysfunction, and severe depression. Its scoring method satisfied with their quality of work life. ,is study showed that is in the form of Likert, which has a number between zero and independent predictors of QWL among the study population 3 (never � zero, sometimes � 1, most of the time � 2, and were educational status, monthly income, position, and work always � 3). Each dimension consists of 7 questions. ,e environment. Abadi et al. [29] used a unique hybrid salp swarm maximum score in each dimension is 21, and the person’s technique and genetic algorithm to schedule nurses to care for total score is from zero to 84. A higher score indicates lower COVID-19 patients. Zhang et al. [30] expected that perceived health. On the other hand, the Walton’s QWL questionnaire social distance would positively buffer the effect of anger on trust has eight dimensions in the following order: fair and adequate and that gender would moderate the effect of perceived social payment (questions 1, 2, 3), safe and healthy working envi- distance on trust. According to the findings, female participants, ronment (questions 4, 5, 6), opportunities for continuous but not male participants, sent more money to their counterparts growth, and security (questions 7, 8, 9), constitutionalism in the low social distance than in the control condition. (questions 10, 11, 12, 13), social dependence of working life Women’s optimistic risk assessment and consequently greater (questions 14, 15, 16), the total living space (questions 17, 18, trust in others may be triggered by the high certainty, higher 19), social integration and cohesion in the organization individual control, and approach motivation associated with (questions 20, 21, 22, 23), and development of human ca- anger, according to the findings of both studies. ,is is due to pabilities (questions 24, 25, 26, 27). ,is questionnaire is also women’s perception of a smaller social distance. Public trans- based on the Likert scale from very low to very high, 1 to 5. portation networks, mobile operators, and mobile phone ap- ,e questionnaire does not have a reverse question. plications were taken as the three key sources of mobility data by Hu et al. [31]. Sadeghipour et al. (2016) concentrated on facial 4. Results recognition with the use of an enhanced SIFT algorithm. ,e results demonstrate that the suggested method outperforms the Ultimately, 165 nurses working in different wards provided SIFT. ,e suggested approach is evaluated by applying it to the their answers, which the summarized results and related ORL database and then comparing it to existing face identifi- parameters are shown in Table 1. Based on Table 1, ,e cation techniques [32]. In order to assess human mobility, four reliability of GHQ-28 based on Cronbach’s alpha coefficient following ways are typically used: public transit-based flow, is 0.922. ,e QWL Questionnaire is 0.933, which is excellent. societal activity patterns, index-based movement data, and social Table 2 shows the significance of the difference between media-derived movement data. Sharifi et al. [33] studied the mental health and QWL for respondents based on their impact of artificial intelligence and digital style on the industry demographic characteristics. As can be seen in this table, 4 Journal of Healthcare Engineering Table 1: Summary of information about the respondents and their status in terms of mental health (MH) and QWL. Number Mean Std. dev. Max Min Median Mode % Age 165 33 7 54 24 32 25 100.0 Work experience 165 9 7 27 0 8 3 100.0 MH 11 20.27 7.73 30.00 11.00 18.00 30.00 6.7 Orthopedic QWL 11 100.45 16.80 122.00 77.00 99.00 82.00 6.7 MH 14 18.71 8.16 38.00 8.00 18.50 19.00 8.5 Emergency QWL 14 103.43 8.99 119.00 92.00 102.00 93.00 8.5 MH 10 30.00 23.90 63.00 6.00 17.50 54.00 6.1 Surgical QWL 10 106.10 9.00 114.00 83.00 106.50 105.00 6.1 MH 15 24.27 14.27 52.00 9.00 19.00 9.00 9.1 Ward Cardiology QWL 15 107.93 14.78 133.00 72.00 109.00 117.00 9.1 MH 89 27.44 9.25 71.00 9.00 27.00 31.00 53.9 COVID-19 QWL 89 91.67 11.13 124.00 68.00 93.00 91.00 53.9 MH 15 25.67 15.62 60.00 9.00 22.00 9.00 9.1 Intensive care units QWL 15 98.27 19.05 121.00 64.00 100.00 118.00 9.1 MH 11 25.36 14.08 57.00 9.00 21.00 9.00 6.7 Neurology QWL 11 104.45 17.60 135.00 78.00 105.00 78.00 6.7 MH 18 31.50 9.37 54.00 18.00 30.00 27.00 10.9 Associate degree QWL 18 97.61 10.34 121.00 81.00 97.00 97.00 10.9 MH 128 25.03 11.67 63.00 6.00 23.50 31.00 77.6 Education Bachelor’s degree QWL 128 96.20 14.91 135.00 64.00 96.00 94.00 77.6 MH 19 25.47 15.66 71.00 7.00 21.00 11.00 11.5 Master’s degree QWL 19 102.32 11.95 121.00 81.00 101.00 96.00 11.5 MH 39 21.28 11.65 54.00 6.00 18.00 9.00 23.6 Conscription QWL 39 100.10 13.83 121.00 71.00 101.00 118.00 23.6 MH 27 29.52 12.55 71.00 11.00 28.00 31.00 16.4 Temp-to-perm QWL 27 96.11 13.07 124.00 64.00 96.00 91.00 16.4 Employment status MH 34 25.09 8.66 40.00 10.00 25.50 32.00 20.6 Contractual QWL 34 92.65 15.44 121.00 66.00 92.50 92.00 20.6 MH 65 27.31 13.00 63.00 7.00 25.00 30.00 39.4 Permanent QWL 65 97.94 14.01 135.00 70.00 97.00 93.00 39.4 MH 64 23.75 11.47 57.00 6.00 23.50 9.00 38.8 Male QWL 64 98.47 13.89 135.00 70.00 99.50 82.00 38.8 Gender MH 101 27.08 12.31 71.00 9.00 26.00 16.00 61.2 Female QWL 101 96.17 14.45 133.00 64.00 96.00 93.00 61.2 MH 42 24.95 13.24 71.00 9.00 21.50 17.00 25.5 Single QWL 42 95.17 13.54 124.00 69.00 96.00 92.00 25.5 MARSTA MH 123 26.07 11.68 63.00 6.00 25.00 30.00 74.5 Married QWL 123 97.71 14.46 135.00 64.00 97.00 91.00 74.5 Table 2: Significance of mean difference for mental health and QWL based on demographic characteristics. Demographic classification Significance of mean difference for mental health Significance of mean difference for QWL Ward 0.112 Less than 0.001 Education 0.102 0.215 Employment status 0.026 0.143 Gender 0.084 0.313 MARSTA 0.605 0.319 according to the medical department, the difference in the Table 3: Significance of correlation between mental health and mean QWL at the error level of one percent is significant. QWL with age and work experience. At the 5% error level, the difference in the mean for mental Mental health QWL health based on employment status is significant. ,ere is no Pearson correlation 0.276 0.050 significant mean difference at the 5% error level in other cases. Age Significance 0.000 0.527 Additionally, to examine the relationship between age Pearson correlation 0.242 -0.026 and work experience with mental health and QWL, the Work experience Significance 0.002 0.744 Pearson correlation coefficient was used, the result of which Journal of Healthcare Engineering 5 Table 4: Significance of mean rank difference for mental health disorders. Mental health disorder Mean Std. dev. Mean rank Significant Somatic symptoms 7.70 4.07 2.96 1 Social dysfunction 7.50 2.85 2.95 2 Anxiety and insomnia 6.99 4.42 2.65 3 Severe depression 3.59 3.95 1.44 4 Chi-square statistics for the significance of the difference in mean rank 162.6 Probability of error Less than 0.001 Table 5: Significance of mean rank difference for QWL disorders. Mental health disorder Mean Std. dev. Mean rank Significant ,e total life space 10.42 2.21 2.92 1 Social dependence of working life 10.53 2.17 3.02 2 Opportunities for continuous growth and security 10.61 2.18 3.04 3 Safe and healthy working environment 10.67 2.32 3.19 4 Fair and adequate payment 10.87 2.14 3.44 5 Social integration and cohesion in the organization 14.20 2.54 6.48 6 Constitutionalism 14.12 2.43 6.56 7 Development of human capabilities 15.65 2.34 7.36 8 Chi-square statistics for the significance of the difference in mean rank 755.64 Probability of error Less than 0.001 is shown in Table 3. As can be seen, the respondents’ mental distributed questionnaires. On the other hand, because it health has a significant positive correlation with their age seeks to understand the correlation relationships based on the opinions and desires of individuals, it is considered and work experience. ,e ranking of mental health disorders and disorders correlational. ,e researcher has no role in the relationship related to QWL using the Friedman test indicates that Chi- between different factors and only uses questionnaires with square statistics to evaluate the significance of the difference validity and reliability. In terms of time, it is a cross-sectional in the mean rank for mental health and QWL are 162.6 and study that refers to the experiences and perceptions of nurses 755.6, respectively, with an error probability of less than up to a specific period. It is also qualitative in terms of data 0.001. ,e results of this analysis are presented in Tables 4 type. and 5. Further investigation in this regard by focusing on Pearson correlation was also used to examine the rela- nurses with associate degrees shows that at the level of five tionship between the dimensions of mental health and the percent error, there is a significant correlation between dimensions of QWL. ,e degree of correlation and their fair and adequate payment with depressive symptoms, opportunities for continuous growth and security with significance are shown in Table 6. Even at the 10% error level, there is no significant correlation between QWL and di- social dysfunction, and the total living space with somatic mensions of mental health. Also, there is no significant symptoms. Another essential point in this study is the correlation between mental health and dimensions of QWL significant correlation between age and work experience at the same level of error. At the 1% error level, only the with the mental health of nurses. Due to the negative correlation between fair and adequate payment and somatic mental health index, as the age of nurses increases, their symptoms is significant. However, at the 10% error level, the mental health deteriorates. However, the correlation be- correlations between somatic symptoms with constitu- tween age and work experience with QWL is not signif- tionalism, anxiety symptoms, and insomnia with the de- icant. ,erefore, older nurses are more likely to be velopment of human capabilities and social dysfunction with psychologically vulnerable and need more support. ,ese opportunities for continuous growth and security are results can be delegated by the type of activity or re- significant. sponsibility, which requires further consideration. Re- garding the dimensions of mental health, the worst conditions are related to somatic symptoms, and the best 5. Discussion conditions are related to depressive symptoms. Regarding ,e present study is descriptive correlational in terms of the QWL, the worst conditions are related to the total purpose and applied in terms of the type of use. It attempts living space, and the best conditions are related to the to understand a specific situation in the real world to apply development of human capabilities. It has been investi- the findings to provide solutions for development and gated whether specific pandemic protocols have put more improvement. ,erefore, in terms of purpose, it is consid- pressure on nurses and resulted in fatigue or boredom of ered practical. ,is research is conducted from a descriptive the overall living space and confirmed by Sun et al. [42]. point of view conducted in the field using the data of ,e correlation between fair and adequate payment and 6 Journal of Healthcare Engineering Table 6: Degree of correlation and their significance. Somatic Anxiety and Social Severe Total mental symptoms insomnia dysfunction depression health Pearson −0.097 0.015 −0.051 0.017 −0.034 correlation Total QWL Significant 0.217 0.844 0.514 0.833 0.669 error Pearson −0.207 −0.089 0.034 0.113 −0.057 correlation Fair and adequate payment Significant 0.008 0.258 0.668 0.147 0.467 error Pearson −0.100 0.025 −0.055 −0.022 −0.045 Safe and healthy working correlation environment Significant 0.199 0.746 0.485 0.775 0.567 error Pearson −0.032 0.067 −0.141 −0.054 −0.037 Opportunities for continuous correlation growth and security Significant 0.687 0.393 0.070 0.491 0.635 error Pearson −0.150 −0.040 −0.027 −0.051 −0.089 correlation Constitutionalism Significant 0.054 0.608 0.732 0.512 0.257 error Pearson −0.077 −0.049 0.042 0.043 −0.020 correlation Social dependence of working life Significant 0.326 0.529 0.595 0.587 0.797 error Pearson −0.044 0.002 −0.094 −0.037 −0.049 correlation ,e total life space Significant 0.572 0.985 0.228 0.634 0.533 error Pearson −0.091 0.038 −0.079 0.022 −0.028 Social integration and cohesion in correlation the organization Significant 0.246 0.632 0.314 0.777 0.719 error Pearson 0.099 0.133 0.008 0.095 0.115 correlation Development of human capabilities Significant 0.208 0.089 0.915 0.224 0.141 error constitutionalism in QWL with the dimension of somatic 6. Conclusion symptoms in mental health is significant, indicating that nurses’ fatigue is more pronounced concerning the soft In the present study, nurses’ mental health status and QWL aspects of QWL. Consequently, establishing appropriate during the COVID-19 pandemic were evaluated to a limited performance appraisal systems and performance-based extent. As expected, the reliability of both questionnaires pay and rewards can be considered a vital decision- was acceptable. ,e study found that if mental health was making option. Other issues such as symptoms of anxiety considered a criterion, the pandemic affected almost all and insomnia and their significant negative relationship nurses with different demographic conditions. ,is did not with the development of human capabilities are also depend solely on the ostensibly involved departments, such debatable. Perhaps, more awareness of the pandemic as the emergency or COVID-19. However, the study shows that nurses with associate degrees have significantly less situation has somehow led to anxiety. In this case, reapplying appropriate safety systems by hospitals and mental health. medical centers to build trust and confidence in invul- ,is study did not identify a significant relationship nerability can be a desirable option for decision making. between age and QWL, same as [43], which is not consistent Social dysfunction also significantly correlates with op- with the study of [44], stating that there is a close correlation portunities for continuous growth and security. Perhaps, between age and QWL of nurses. ,e findings of this study individuals will show more social dysfunction if they have are in good agreement with the findings of Bakhshi et al. [14] the opportunity to grow and develop in their jobs and that there is no significant difference in the mean QWL in professions. different wards of hospitals and medical centers. 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Study of Complexity Systems in Public Health for Evaluating the Correlation between Mental Health and Age-Related Demographic Characteristics: A General Health Study

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Copyright © 2022 Fereshte Haghi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

Hindawi Journal of Healthcare Engineering Volume 2022, Article ID 2117031, 8 pages https://doi.org/10.1155/2022/2117031 Research Article Study of Complexity Systems in Public Health for Evaluating the Correlation between Mental Health and Age-Related Demographic Characteristics: A General Health Study 1 2 3,4 4 4 Fereshte Haghi, Shadi Goli, Rana Rezaei, Fatemeh Akhormi, Fatemeh Eskandari, 1,4 and Zeinab Nasr Isfahani Shahid Beheshti OB&GYN Hospital Isfahan University of Medical Sciences, Isfahan, Iran Nursing and Midwifery Sciences Development Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran Department of Midwifery, Shoushtar Faculty of Medical Sciences, Shoushtar, Iran Department of Midwifery, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran Correspondence should be addressed to Zeinab Nasr Isfahani; nasrisfahani.z@ajums.ac.ir Received 28 December 2021; Revised 8 February 2022; Accepted 3 March 2022; Published 6 April 2022 Academic Editor: Mohsen Ahmadi Copyright © 2022 Fereshte Haghi et al. ,is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ,e main objective of this study is to evaluate the quality of nurses’ work lives and mental health during outbreaks. We also use the General Health Questionnaire–28 and Walton’s QWL technique to assess the association between these two and their dimensions with demographic variables and each other. First, 165 nurses from COVID-19 medical centers in Iran filled surveys for this research. In an SPSS program, the data were examined. ,ere was a strong link between mental health and age-related de- mographic factors. ,ere was no evidence of a link between the quality of nurses’ work life and their psychological health. However, there was a strong link between somatic symptoms and fair and appropriate compensation, as well as constitutionalism. ,e worst situations for work life quality were linked to the whole living area dimension. In contrast, the worst conditions for mental health were linked to the somatic symptoms dimension. on the working community, active in various business 1. Introduction sectors [3]. COVID-19 has attracted special international In December 2019, an acute respiratory syndrome caused by attention as a serious threat to global public health. ,e SARS-CoV-2 caused a global pandemic in Wuhan, China, increasing prevalence of this disease and the prolongation of where almost the entire human community has been directly the disease process have made the activities of the medical affected by the disease or associated safety social restrictions. staff exhaustive [4]; ,us, with the over-admission of pa- Numerous studies have been published on the mechanism of tients in medical centers, the availability and readiness of the medical staff is a determining factor in overcoming the crisis action of this coronavirus and its individual and social effects and consequences, which indicate the occurrence of physical [5]. Considering that various studies and reports indicate the disease in the form of clinical complications and manifes- effect of health care providers’ satisfaction on patient sat- tations such as fever, chills, sore throat, contusion, cough, isfaction [6–11] and on the other hand, job satisfaction has a respiratory problems, vomiting, and diarrhea [1], as well as two-way relationship with the mental and psychological psychological complications such as fear and anxiety [2]. Of condition of employees [12], it is essential to consider course, clinical complications have affected patients, and psychological conditions and their improvement methods in psychological complications have affected both patients and the medical center. nonpatients. ,e pandemic has had a tremendous impact on According to the World Health Organization definition, various occupations. It has imposed different consequences mental health is “a state of wellbeing in which the individual 2 Journal of Healthcare Engineering ,ese strategies may vary even concerning the nurses’ realizes his or her abilities, can cope with the normal stresses of life, can work productively and fruitfully, and can make a workplace. From this point of view, it is necessary to conduct the necessary research. According to the explanations contribution to his or her community.” Good mental health is one of the pillars of health and is necessary for a useful, provided, it can be said that this study seeks to answer the effective, and satisfying life [13]. Quality of work life (QWL) following questions: is essential for attracting and retaining employees. When an (i) What are the most important problems and inad- organization provides a good QWL for employees, it intends equacies related to the quality of work life? to retain employees [14]. Quality of work life is one issue that (ii) What are the most important problems and mental affects almost all people regardless of the situation. In disorders? hospitals and medical centers, the quality of hospital services will not be guaranteed without the participation of nurses (iii) What is the correlation between the aspects of [15]. Various factors such as incompatibility and dissatis- quality of work life and mental disabilities? faction with work, stress, fatigue, illness, and lack of leisure time of nurses affect their behavior [16]. Nurses who have 2. Literature Review dealt with patients for a more extended period are more likely to be vulnerable. Critical and painful patients, dying Numerous studies have been conducted on mental health patients, complex equipment, inappropriate behaviors of and QWL and their relationship. A significant part of these patient companions, patients’ reactions, and many other studies goes back to nurses working in medical centers. issues give different aspects to nurses’ work, and such Javadi-Pashaki and Darvishpour [24] in their study on stress conditions affect burnout, job satisfaction, and the tendency and coping strategies to predict the general health of nursing of nurses to continue working [17]. ,ese characteristics in staff considered 318 nurses working in health centers of the workplace increase stress and the risk of mental dis- Guilan University of Medical Sciences [24]. ,e results orders [18]. Nursing is one of the 130 most stressful oc- showed that stress and coping strategies could explain about cupations and is ranked 27th among 130 occupations with a 2.5% of the variance in public health. However, the results high prevalence of mental disorders [19]. Nurses face several showed that coping strategies are significantly more pre- stressful sources such as time, long-term work, change of dictive of public health. Accordingly, attention to coping work shift, insomnia, death observation, malignancy, high strategies to predict general health in nurses has been patient expectations of nurses, and a low tolerance for error highlighted. Mahmoudi [3] studied the economic effect of [20]. Job stress can lead to disorders that put nurses at COVID-19. ,is model is enhanced with additional char- serious risk of mental disorders [21]. acteristics to assess the economic impact of COVID-19 on From December 2019 onward, medical staff, especially the labor market. ,e findings indicate that the US gov- nurses, are under severe pressure. Various waves of COVID- ernment might employ a straightforward technique to 19 have swept across many countries, including Iran. In this mitigate the harmful effects of COVID-19. situation, not only do medical staff rescue infected patients Zhang et al. [22] in their study of the mental health status but they also oversee the entire process of combating health of Chinese healthcare-related infection control specialists events. In addition to the stress of the job itself, they are during the coronavirus outbreak investigated data from involved in a conflict between their safety needs and job 9,228 cases from 3,776 hospitals across China in the form of requirements. ,ey may be exposed to anxiety, depression, an online questionnaire. A 12-item Chinese version of the insomnia, and other psychological disorders [22]. High- General Health Questionnaire and a Chinese version of the sensitivity patient care imposes significant physical and Psychological Capital Questionnaire suitable for medical emotional burdens, exacerbated by increased workload, staff personnel were used as tools in this study. By performing shortages, and equipment shortages. Direct contact with the univariate and multivariate analysis, it was found that the patient increases the risk of infection [23]. Meanwhile, the risk of mental health problems is higher with more self- measures taken by the government, especially with an sufficiency and working in a public hospital. Working in a emphasis on social distance and restricting communication second-degree rather than a third-degree hospital poses a and travel outside the workplace, are also significant. significantly lower risk. However, fewer psychological ,erefore, it is impossible to take many common strategies problems have been observed in single people than in to reduce stress and anxiety, which increases the respon- married ones. In addition, fewer working hours per week, sibility of medical centers to take the initiative and create the hope, and optimism played a role in reducing risk. Har- appropriate conditions to compensate for the shortcomings. diyono [25] in their study on burnout of nurses working in Paying attention to the QWL and improving it is one of the the hospital for the treatment of patients with COVID-19 approaches used by organizations. However, the QWL in- concluded that burnout is present in nurses who were ex- cludes several aspects, and consequently, a variety of solu- posed to a large number of patients with the virus [25]. ,e tions in this area is considerable. high workload, and at the same time, the worry of trans- It is necessary to properly understand the psychological mitting the virus to themselves and their family members is problems of nurses in the context of the COVID-19 pan- one of the most important factors that put them under demic, the relationship between various problems and psychological pressure and lead to burnout. Quchan et al., in mental disorders with different aspects of work life, and to their study, compared the mental health of nurses working create the right mentality to adopt an appropriate solution. in COVID-19 referral hospitals and regular hospitals [2]. 60 Journal of Healthcare Engineering 3 and energy following COVID-19. According to Chen et al. [34], nurses related to the COVID-19 wards and 62 non-COVID- 19 nurses participated in the study. A standard public health a Markov chain position predictions model based on multilevel correction was presented. ,is approach is also helpful in de- questionnaire was provided to them online. ,ere was no statistically significant difference between the two groups. termining the correlation between the variables in the COVID- However, both groups had poor mental health, which the 19 dataset. Ala et al. [35] studied how the whale optimization researchers said was probably due to the pandemic. Sade- algorithm and the NSGA-II can be used to optimize appoint- ghipoor and Moradisabzevar [26] developed a smart toy car ment scheduling for healthcare systems based on the quality of to screen children for autism. ,e findings indicate that the fairness service provided. According to Hankir et al. [36]; a study system has an accuracy rate of 85 percent, a sensitivity of 93 protocol is being developed to study an anti-stigma program and long-term reductions in mental health stigma among medical percent, and a specificity of 76 percent. ,e findings are same for boys and girls, indicating that this approach may be students. Abbas [37] drew on data on coronavirus infections obtained from the Ministry of Health and National Institute of widely used by all youngsters. Dehkordi et al. [27] conducted a study on the effect of Health Pakistan to conduct his research. ,is study evaluation includes data provided by the National Institutes of Health, and COVID-19 disease on anxiety, quality of work life, and fatigue of health care providers in health centers in southwestern Iran. ,e responses were from all areas of Pakistan, limiting the gener- statistical population includes 181 people directly related to alizability of the findings to empirical evidence. patients and 261 employees in other wards who had no direct contact with patients with COVID-19 [27]. ,ey concluded that 3. Methodology both groups’ work life quality had decreased, and fatigue and anxiety caused by COVID-19 had increased. However, there is In the present study, data collection has been performed no statistically significant difference between the fatigue caused based on 250 General Health Questionnaire – 28 (GHQ-28) by the anxiety of the staff involved with COVID-19 and the of Goldberg and Hillier [38] and Walton’s QWL ques- personnel of other departments. In terms of QWL, no significant tionnaire [39] distributed among nurses of ten hospitals in difference was observed in other components except for human Iran with surgical, orthopedic, COVID-19, intensive care resource development. ,e results also showed a statistically units, emergency, cardiology, and neurology wards. ,e significant relationship between the level of component anxiety validity and reliability of both questionnaires have been with QWL and fatigue. Kelbiso et al. [28] have identified and repeatedly reviewed and found appropriate for screening the analyzed the determinants of QWL among nurses working in QWL and job-related factors [40, 41]. public health facilities in Hawassa, Ethiopia [28]. In this study, ,e GHQ-28 questionnaire is multiple choice and has 253 nurses from two hospitals and nine health centers partic- four dimensions: somatic symptoms, anxiety and insomnia, ipated. Findings showed that at least 60% of nurses were dis- social dysfunction, and severe depression. Its scoring method satisfied with their quality of work life. ,is study showed that is in the form of Likert, which has a number between zero and independent predictors of QWL among the study population 3 (never � zero, sometimes � 1, most of the time � 2, and were educational status, monthly income, position, and work always � 3). Each dimension consists of 7 questions. ,e environment. Abadi et al. [29] used a unique hybrid salp swarm maximum score in each dimension is 21, and the person’s technique and genetic algorithm to schedule nurses to care for total score is from zero to 84. A higher score indicates lower COVID-19 patients. Zhang et al. [30] expected that perceived health. On the other hand, the Walton’s QWL questionnaire social distance would positively buffer the effect of anger on trust has eight dimensions in the following order: fair and adequate and that gender would moderate the effect of perceived social payment (questions 1, 2, 3), safe and healthy working envi- distance on trust. According to the findings, female participants, ronment (questions 4, 5, 6), opportunities for continuous but not male participants, sent more money to their counterparts growth, and security (questions 7, 8, 9), constitutionalism in the low social distance than in the control condition. (questions 10, 11, 12, 13), social dependence of working life Women’s optimistic risk assessment and consequently greater (questions 14, 15, 16), the total living space (questions 17, 18, trust in others may be triggered by the high certainty, higher 19), social integration and cohesion in the organization individual control, and approach motivation associated with (questions 20, 21, 22, 23), and development of human ca- anger, according to the findings of both studies. ,is is due to pabilities (questions 24, 25, 26, 27). ,is questionnaire is also women’s perception of a smaller social distance. Public trans- based on the Likert scale from very low to very high, 1 to 5. portation networks, mobile operators, and mobile phone ap- ,e questionnaire does not have a reverse question. plications were taken as the three key sources of mobility data by Hu et al. [31]. Sadeghipour et al. (2016) concentrated on facial 4. Results recognition with the use of an enhanced SIFT algorithm. ,e results demonstrate that the suggested method outperforms the Ultimately, 165 nurses working in different wards provided SIFT. ,e suggested approach is evaluated by applying it to the their answers, which the summarized results and related ORL database and then comparing it to existing face identifi- parameters are shown in Table 1. Based on Table 1, ,e cation techniques [32]. In order to assess human mobility, four reliability of GHQ-28 based on Cronbach’s alpha coefficient following ways are typically used: public transit-based flow, is 0.922. ,e QWL Questionnaire is 0.933, which is excellent. societal activity patterns, index-based movement data, and social Table 2 shows the significance of the difference between media-derived movement data. Sharifi et al. [33] studied the mental health and QWL for respondents based on their impact of artificial intelligence and digital style on the industry demographic characteristics. As can be seen in this table, 4 Journal of Healthcare Engineering Table 1: Summary of information about the respondents and their status in terms of mental health (MH) and QWL. Number Mean Std. dev. Max Min Median Mode % Age 165 33 7 54 24 32 25 100.0 Work experience 165 9 7 27 0 8 3 100.0 MH 11 20.27 7.73 30.00 11.00 18.00 30.00 6.7 Orthopedic QWL 11 100.45 16.80 122.00 77.00 99.00 82.00 6.7 MH 14 18.71 8.16 38.00 8.00 18.50 19.00 8.5 Emergency QWL 14 103.43 8.99 119.00 92.00 102.00 93.00 8.5 MH 10 30.00 23.90 63.00 6.00 17.50 54.00 6.1 Surgical QWL 10 106.10 9.00 114.00 83.00 106.50 105.00 6.1 MH 15 24.27 14.27 52.00 9.00 19.00 9.00 9.1 Ward Cardiology QWL 15 107.93 14.78 133.00 72.00 109.00 117.00 9.1 MH 89 27.44 9.25 71.00 9.00 27.00 31.00 53.9 COVID-19 QWL 89 91.67 11.13 124.00 68.00 93.00 91.00 53.9 MH 15 25.67 15.62 60.00 9.00 22.00 9.00 9.1 Intensive care units QWL 15 98.27 19.05 121.00 64.00 100.00 118.00 9.1 MH 11 25.36 14.08 57.00 9.00 21.00 9.00 6.7 Neurology QWL 11 104.45 17.60 135.00 78.00 105.00 78.00 6.7 MH 18 31.50 9.37 54.00 18.00 30.00 27.00 10.9 Associate degree QWL 18 97.61 10.34 121.00 81.00 97.00 97.00 10.9 MH 128 25.03 11.67 63.00 6.00 23.50 31.00 77.6 Education Bachelor’s degree QWL 128 96.20 14.91 135.00 64.00 96.00 94.00 77.6 MH 19 25.47 15.66 71.00 7.00 21.00 11.00 11.5 Master’s degree QWL 19 102.32 11.95 121.00 81.00 101.00 96.00 11.5 MH 39 21.28 11.65 54.00 6.00 18.00 9.00 23.6 Conscription QWL 39 100.10 13.83 121.00 71.00 101.00 118.00 23.6 MH 27 29.52 12.55 71.00 11.00 28.00 31.00 16.4 Temp-to-perm QWL 27 96.11 13.07 124.00 64.00 96.00 91.00 16.4 Employment status MH 34 25.09 8.66 40.00 10.00 25.50 32.00 20.6 Contractual QWL 34 92.65 15.44 121.00 66.00 92.50 92.00 20.6 MH 65 27.31 13.00 63.00 7.00 25.00 30.00 39.4 Permanent QWL 65 97.94 14.01 135.00 70.00 97.00 93.00 39.4 MH 64 23.75 11.47 57.00 6.00 23.50 9.00 38.8 Male QWL 64 98.47 13.89 135.00 70.00 99.50 82.00 38.8 Gender MH 101 27.08 12.31 71.00 9.00 26.00 16.00 61.2 Female QWL 101 96.17 14.45 133.00 64.00 96.00 93.00 61.2 MH 42 24.95 13.24 71.00 9.00 21.50 17.00 25.5 Single QWL 42 95.17 13.54 124.00 69.00 96.00 92.00 25.5 MARSTA MH 123 26.07 11.68 63.00 6.00 25.00 30.00 74.5 Married QWL 123 97.71 14.46 135.00 64.00 97.00 91.00 74.5 Table 2: Significance of mean difference for mental health and QWL based on demographic characteristics. Demographic classification Significance of mean difference for mental health Significance of mean difference for QWL Ward 0.112 Less than 0.001 Education 0.102 0.215 Employment status 0.026 0.143 Gender 0.084 0.313 MARSTA 0.605 0.319 according to the medical department, the difference in the Table 3: Significance of correlation between mental health and mean QWL at the error level of one percent is significant. QWL with age and work experience. At the 5% error level, the difference in the mean for mental Mental health QWL health based on employment status is significant. ,ere is no Pearson correlation 0.276 0.050 significant mean difference at the 5% error level in other cases. Age Significance 0.000 0.527 Additionally, to examine the relationship between age Pearson correlation 0.242 -0.026 and work experience with mental health and QWL, the Work experience Significance 0.002 0.744 Pearson correlation coefficient was used, the result of which Journal of Healthcare Engineering 5 Table 4: Significance of mean rank difference for mental health disorders. Mental health disorder Mean Std. dev. Mean rank Significant Somatic symptoms 7.70 4.07 2.96 1 Social dysfunction 7.50 2.85 2.95 2 Anxiety and insomnia 6.99 4.42 2.65 3 Severe depression 3.59 3.95 1.44 4 Chi-square statistics for the significance of the difference in mean rank 162.6 Probability of error Less than 0.001 Table 5: Significance of mean rank difference for QWL disorders. Mental health disorder Mean Std. dev. Mean rank Significant ,e total life space 10.42 2.21 2.92 1 Social dependence of working life 10.53 2.17 3.02 2 Opportunities for continuous growth and security 10.61 2.18 3.04 3 Safe and healthy working environment 10.67 2.32 3.19 4 Fair and adequate payment 10.87 2.14 3.44 5 Social integration and cohesion in the organization 14.20 2.54 6.48 6 Constitutionalism 14.12 2.43 6.56 7 Development of human capabilities 15.65 2.34 7.36 8 Chi-square statistics for the significance of the difference in mean rank 755.64 Probability of error Less than 0.001 is shown in Table 3. As can be seen, the respondents’ mental distributed questionnaires. On the other hand, because it health has a significant positive correlation with their age seeks to understand the correlation relationships based on the opinions and desires of individuals, it is considered and work experience. ,e ranking of mental health disorders and disorders correlational. ,e researcher has no role in the relationship related to QWL using the Friedman test indicates that Chi- between different factors and only uses questionnaires with square statistics to evaluate the significance of the difference validity and reliability. In terms of time, it is a cross-sectional in the mean rank for mental health and QWL are 162.6 and study that refers to the experiences and perceptions of nurses 755.6, respectively, with an error probability of less than up to a specific period. It is also qualitative in terms of data 0.001. ,e results of this analysis are presented in Tables 4 type. and 5. Further investigation in this regard by focusing on Pearson correlation was also used to examine the rela- nurses with associate degrees shows that at the level of five tionship between the dimensions of mental health and the percent error, there is a significant correlation between dimensions of QWL. ,e degree of correlation and their fair and adequate payment with depressive symptoms, opportunities for continuous growth and security with significance are shown in Table 6. Even at the 10% error level, there is no significant correlation between QWL and di- social dysfunction, and the total living space with somatic mensions of mental health. Also, there is no significant symptoms. Another essential point in this study is the correlation between mental health and dimensions of QWL significant correlation between age and work experience at the same level of error. At the 1% error level, only the with the mental health of nurses. Due to the negative correlation between fair and adequate payment and somatic mental health index, as the age of nurses increases, their symptoms is significant. However, at the 10% error level, the mental health deteriorates. However, the correlation be- correlations between somatic symptoms with constitu- tween age and work experience with QWL is not signif- tionalism, anxiety symptoms, and insomnia with the de- icant. ,erefore, older nurses are more likely to be velopment of human capabilities and social dysfunction with psychologically vulnerable and need more support. ,ese opportunities for continuous growth and security are results can be delegated by the type of activity or re- significant. sponsibility, which requires further consideration. Re- garding the dimensions of mental health, the worst conditions are related to somatic symptoms, and the best 5. Discussion conditions are related to depressive symptoms. Regarding ,e present study is descriptive correlational in terms of the QWL, the worst conditions are related to the total purpose and applied in terms of the type of use. It attempts living space, and the best conditions are related to the to understand a specific situation in the real world to apply development of human capabilities. It has been investi- the findings to provide solutions for development and gated whether specific pandemic protocols have put more improvement. ,erefore, in terms of purpose, it is consid- pressure on nurses and resulted in fatigue or boredom of ered practical. ,is research is conducted from a descriptive the overall living space and confirmed by Sun et al. [42]. point of view conducted in the field using the data of ,e correlation between fair and adequate payment and 6 Journal of Healthcare Engineering Table 6: Degree of correlation and their significance. Somatic Anxiety and Social Severe Total mental symptoms insomnia dysfunction depression health Pearson −0.097 0.015 −0.051 0.017 −0.034 correlation Total QWL Significant 0.217 0.844 0.514 0.833 0.669 error Pearson −0.207 −0.089 0.034 0.113 −0.057 correlation Fair and adequate payment Significant 0.008 0.258 0.668 0.147 0.467 error Pearson −0.100 0.025 −0.055 −0.022 −0.045 Safe and healthy working correlation environment Significant 0.199 0.746 0.485 0.775 0.567 error Pearson −0.032 0.067 −0.141 −0.054 −0.037 Opportunities for continuous correlation growth and security Significant 0.687 0.393 0.070 0.491 0.635 error Pearson −0.150 −0.040 −0.027 −0.051 −0.089 correlation Constitutionalism Significant 0.054 0.608 0.732 0.512 0.257 error Pearson −0.077 −0.049 0.042 0.043 −0.020 correlation Social dependence of working life Significant 0.326 0.529 0.595 0.587 0.797 error Pearson −0.044 0.002 −0.094 −0.037 −0.049 correlation ,e total life space Significant 0.572 0.985 0.228 0.634 0.533 error Pearson −0.091 0.038 −0.079 0.022 −0.028 Social integration and cohesion in correlation the organization Significant 0.246 0.632 0.314 0.777 0.719 error Pearson 0.099 0.133 0.008 0.095 0.115 correlation Development of human capabilities Significant 0.208 0.089 0.915 0.224 0.141 error constitutionalism in QWL with the dimension of somatic 6. Conclusion symptoms in mental health is significant, indicating that nurses’ fatigue is more pronounced concerning the soft In the present study, nurses’ mental health status and QWL aspects of QWL. Consequently, establishing appropriate during the COVID-19 pandemic were evaluated to a limited performance appraisal systems and performance-based extent. As expected, the reliability of both questionnaires pay and rewards can be considered a vital decision- was acceptable. ,e study found that if mental health was making option. Other issues such as symptoms of anxiety considered a criterion, the pandemic affected almost all and insomnia and their significant negative relationship nurses with different demographic conditions. ,is did not with the development of human capabilities are also depend solely on the ostensibly involved departments, such debatable. Perhaps, more awareness of the pandemic as the emergency or COVID-19. However, the study shows that nurses with associate degrees have significantly less situation has somehow led to anxiety. In this case, reapplying appropriate safety systems by hospitals and mental health. medical centers to build trust and confidence in invul- ,is study did not identify a significant relationship nerability can be a desirable option for decision making. between age and QWL, same as [43], which is not consistent Social dysfunction also significantly correlates with op- with the study of [44], stating that there is a close correlation portunities for continuous growth and security. Perhaps, between age and QWL of nurses. ,e findings of this study individuals will show more social dysfunction if they have are in good agreement with the findings of Bakhshi et al. [14] the opportunity to grow and develop in their jobs and that there is no significant difference in the mean QWL in professions. different wards of hospitals and medical centers. 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Published: Apr 6, 2022

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