Introduction:Fifty-three percent of Indian under-5 deaths occur during the neonatal age group. Recognizing that there is a lack of illustrated district-level data on neonatal mortality in India, we mapped this to visually highlight districts where neonatal health issues require the most attention.Methods:District-level estimates of 596 Indian districts were used to generate maps and to illustrate neonatal mortality rates (NMRs), absolute numbers of neonatal deaths; the best and worst performing districts (positive and negative deviants) in each Indian state; the neonatal female/male death ratio; and district lag in NMR reductions.Results:The NMR ranged from 4.3 (Kannur, Kerala) to 65.1 (Datia, Madhya Pradesh), with the mean NMR being 29.8. Almost two-thirds of the districts (n = 380, 63.7%) had NMRs between 20 and 40. The top third of neonatal deaths could be accounted for by just 71 districts of a total of 596.Conclusion:There is an urgent need for up-to-date data on district-level neonatal mortality in India.
Bland-Altman analysis is a very commonly used method in the biomedical research. This method is used to study the agreement between two measurements that are in continuous scale. Although this method is commonly used in medical research, the statistical software packages do not have the menu-driven operation for the Bland-Altman analysis. Hence this paper intends to provide an R function (BA.plot) for Bland-Altman analysis.
A
bstract
Background
Coronavirus disease-2019 (COVID-19) pandemic has exposed healthcare workers (HCWs) to a unique set of challenges and stressors. Our frontline workers are under tremendous psychological pressure because of the ever-rising crisis. This study was done to assess the magnitude of the psychological impact of the COVID-19 pandemic on clinical and nonclinical HCWs in India.
Materials and methods
It was a cross-sectional, online survey that was done from June 1, 2020, to July 4, 2020. A total of 313 clinical and nonclinical HCWs, who were directly or indirectly involved in patient care, participated in the study. The psychological impact was assessed in terms of four variables: insomnia, anxiety, depression, and stress. Insomnia was assessed by the Insomnia Severity Index (ISI). Anxiety and depression were assessed via the Patient Health Questionnaire-4 (PHQ-4), which included a 2-item anxiety scale and a 2-item depression scale (PHQ-2). Stress was assessed via the Perceived Stress Scale (PSS). We also compared the psychological impact of this pandemic between clinical and nonclinical HCWs.
Results
7.3% of HCWs were having moderate insomnia, 3.8% had severe insomnia, and 20.8% were having subthreshold insomnia. Severe anxiety and depression were found in 6.7% of respondents. 8.0 and 32.3% of the respondents had moderate and mild anxiety–depression, respectively. 6.4% had high perceived stress. 47.6 and 46.0% of the respondents had moderate and low stress, respectively. There was a statistically significant difference in severe insomnia between clinical and nonclinical HCWs, whereas no significant difference in anxiety, depression, and stress between clinical and nonclinical HCWs.
Conclusion
This study suggests that psychological morbidity is prevalent among both clinical and nonclinical HCWs and both males and females. Early intervention may be beneficial to prevent this issue.
How to cite this article
Sunil R, Bhatt MT, Bhumika TV, Thomas N, Puranik A, Chaudhuri S,
et al.
Weathering the Storm: Psychological Impact of COVID-19 Pandemic on Clinical and Nonclinical Healthcare Workers in India. Indian J Crit Care Med 2021;25(1):16–20.
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