Knowledge practice gap of nurses towards COVID-19 patients dead body care in a tertiary care hospital.
SAINI, G.; Panda, P. K.; Singh, M.; Maneesh, M.; Punjot, P.; Meshram, R.; Gupta, P. K.
Show abstract
AimTo know the dead body care of COVID-19 patients. ObjectiveO_LITo determine health care professionals, knowledge, attitude, and practice towards Covid-19 dead body care. C_LIO_LITo find the association of knowledge, attitude, practice with selected demographic variables. C_LI BackgroundCOVID-19 was a global pandemic and it was a serious note for health care professionals from many aspects. The virus was infective and causes serious infectionsto patients which were easily transmitted, hence specific dead body care is required for such kinds of patients. To keep this background in mind the study was conducted to identify the knowledge, practice and attitude towards COVID-19 dead body care among nurses. MethodologyA cross sectional survey based study was done on 282 samples.Quantitative research design with purposive sampling technique data was collected for knowledge,attitude, and practice. ResultKnowledge, attitude and practice were assessed and association was done with demographic profile. Hence the good knowledge, attitude and practicewere observed in experienced and trained nurses (p value<0.005. Whereas no significant changes were observed with age, gender and education qualification. ConclusionOverall knowledge, attitude and practice regarding COVID-19 dead body care were moderate to good. But it was important to identify the gap as it was a global pandemic and higher chances of spreading of infection.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Risk perceptions and preventive practices of COVID-19 among healthcare professionals in public hospitals in Ethiopia 97%
- Risk perceptions and preventive practices of COVID-19 among healthcare professionals in public hospitals in Ethiopia 97%
- The Patient Safety Curriculum: An Interventional Study on the Effectiveness of Patient Safety Education for Jordanian Nursing Students 97%
Similar papers in this journal
- Relationship Between Adverse Events Prevalence, Patient Safety Culture And Patient Safety Perception In A Single Sample Of Patients: A Cross-Sectional And Correlational Study 96%
- Clinical practice competencies for standard critical care nursing: Consensus statement based on a systematic review and Delphi survey 95%
- The preparedness and response to COVID-19 in a quaternary Intensive Care Unit in Australia: perspectives and insights from frontline critical care clinicians 95%
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 94%
- Using A Socio-Ecological System (SES) Framework to Explain Factors Influencing Countries’ Success Level in Curbing COVID-19 93%
- SARS-CoV-2 seroprevalence among healthcare workers in general hospitals and clinics in Japan 93%
Similar papers in this journal
- COVID-19: Knowledge, Perception of Risk, Preparedness and Vaccine Acceptability among Healthcare Workers in Kenya 97%
- Factors influencing intention to adhere to precautionary behavior in times of COVID- 19 pandemic in Sudan: an application of the Health Belief Model 96%
- Poor knowledge of COVID-19 and unfavourable perception of the response to the pandemic by healthcare workers at the Bafoussam Regional Hospital (West Region - Cameroon) 94%
Similar papers in this journal
- Burnout and sleep problems among nurses working in a tertiary hospital in Kathmandu, Nepal 97%
- Factors influencing the motivation of maternal health workers in conflict setting of Mogadishu, Somalia 96%
- Corona virus fear among health workers during the early phase of pandemic response in Nepal: a web-based cross-sectional study 96%
"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.