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      Policing in pandemic: Is perception of workload causing work–family conflict, job dissatisfaction and job stress?

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      1 ,
      Journal of Public Affairs
      John Wiley and Sons Inc.

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          Abstract

          Police employees have to work extra during uncertain situations as they are responsible to maintain law and order. Currently, this department is facing a similar situation because of COVID‐19. Therefore, this study aims at investigating how police employees' perceptions of workload imbalance their family roles and further increase their job stress and dissatisfaction. The study collected cross‐sectional data from 247 constables performing their duties during lockdown because of COVID‐19. Hypotheses were examined using structural equation modeling. The findings revealed that police constables' perception of workload cause work–family conflict, job stress and job dissatisfaction. In addition, work–family conflict mediates the associations of workload with job stress and job dissatisfaction. The study collected data from a single source, though Harman's single factor confirmed the absence of common method variance. This study extends the conservation of resource theory and has implications for the management and policymakers.

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          Most cited references48

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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              Social and psychological resources and adaptation.

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                Author and article information

                Contributors
                msadiq@alqasimia.ac.ae
                Journal
                J Public Aff
                J Public Aff
                10.1002/(ISSN)1479-1854
                PA
                Journal of Public Affairs
                John Wiley and Sons Inc. (Hoboken )
                1472-3891
                1479-1854
                21 September 2020
                : e2486
                Affiliations
                [ 1 ] Department of Economics and Finance, College of Economics and Management, Women Al Qasimia University Sharjah UAE
                Author notes
                [*] [* ] Correspondence

                Misbah Sadiq, Department of Economics and Finance, College of Economics and Management, Women, Al Qasimia University, Sharjah, UAE.

                Email: msadiq@ 123456alqasimia.ac.ae

                Author information
                https://orcid.org/0000-0003-0662-4335
                Article
                PA2486
                10.1002/pa.2486
                7536908
                33041655
                62b0e3a6-8a91-47f5-8dde-d42b9fe5152f
                © 2020 John Wiley & Sons Ltd

                This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

                History
                : 14 August 2020
                : 06 September 2020
                : 11 September 2020
                Page count
                Figures: 0, Tables: 3, Pages: 8, Words: 6732
                Categories
                Academic Paper
                Academic Papers
                Custom metadata
                2.0
                corrected-proof
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.2 mode:remove_FC converted:06.10.2020

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