Perceived Stress and Psychological (Dis)Stress among Indian Endodontists During COVID19 Pandemic Lock down
Nair, A. K. R.; Chellaswamy, K. S.; Kattula, D.; Thavarajah, R.; Mohandoss, A. A.
Show abstract
ASBTRACTO_ST_ABSBackgroundC_ST_ABSThe novel 2019 coronavirus(COVID-19) spreads by respiratory and aerosols. COVID19 driven pandemic causes panic, fear and stress among all strata of society. Like all other medical professions, dentists, particularly endodontists, who are highly exposed to aerosols would be exposed to stress. The aim of this study was to assess the (dis)stress among Indian endodontists and the factors that could influence the (dis)stress. MethodsFrom 8th April to 16th April 2020, we conducted an online survey in closed endodontic social media using snowball sampling technique, collecting basic demographic data, practice setting and relevant data. Psychological stress and perceived distress were collected through COVID-19 Peri-traumatic Distress Index (CPDI) and Perceived stress scale (PSS). Multinomial regression analysis was performed to estimate relative risk rate and P[≤]0.05 was considered significant. ResultsThis study had 586 Indian endodontists completing this survey across India. Of these, 311 (53.07%) were males, 325(55%) in the age group of 25-35 years, 64%in urban areas, 13.14% in solo-practice and a fourth of them were residents. Female endodontists had high perceived stress (RRR=2.46,P=0.01) as compared to males, as measured by PSS. Younger endodontists<25 years(RRR=9.75;P=0.002) and 25-35years (RRR=4.60;P=0.004) as compared with >45 years age-group had more distress. Exclusive consultants had RRR= 2.90, P=0.02, for mild-to-moderate distress as compared to normal. Factors driving this phenomenon are considered. ConclusionsDuring the lock down due to COVID-19, 1-in-2 Indian endodontists had distress, as measured by CPDI and 4-in-5 of them had perceived stress, as indicated by PSS. Our model identified certain factors driving the (dis)stress, which would help policy framers to initiate appropriate response.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Silicone toothbrushes: A scoping review of an underutilized tool in global oral health 92%
- Factors influencing the motivation of maternal health workers in conflict setting of Mogadishu, Somalia 92%
- Patient knowledge, attitudes and practices on chronic wound infections in Tanga Regional Referral Hospital, Tanzania; a qualitative study 92%
Similar papers in this journal
- Knowledge and aptitude of early childhood, primary and/or secondary education teachers referred to first aid measures in dental trauma in the province of Seville (Spain.) 95%
- Different features of cholera in malnourished and non-malnourised children: analysis of 10-year surveillance data from a large diarrheal disease hospital in urban Bangladesh 90%
- Cine phase contrast magnetic resonance imaging of calf muscle contraction in pediatric patients with cerebral palsy and healthy children: comparison of voluntary motion and electrically evoked motion 85%
Similar papers in this journal
- Projecting trends in the disease burden of adult edentulism in China between 2020 and 2030: a systematic study based on the global burden of disease 92%
- Knowledge, attitudes, and practices among the general population during COVID-19 outbreak in Iran: A national cross-sectional survey 92%
- Profiles of bacteria isolates and their antimicrobial resistance pattern among housemaids working in communal living residences in Jimma City, Ethiopia 92%
Similar papers in this journal
- Assessment of Experiences of Preventive Measures Practice including Vaccination History and Health Education among Umrah Pilgrims in Saudi Arabia, 1440H-2019 92%
- Using A Socio-Ecological System (SES) Framework to Explain Factors Influencing Countries’ Success Level in Curbing COVID-19 91%
- Quality assessment of studies included in Cochrane oral health systematic reviews 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.