scholarly journals Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0258348
Author(s):  
Nguyen Tien Huy ◽  
R. Matthew Chico ◽  
Vuong Thanh Huan ◽  
Hosam Waleed Shaikhkhalil ◽  
Vuong Ngoc Thao Uyen ◽  
...  
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Healthcare Workers ◽  
Management Training ◽  
Mean Difference ◽  
Rule Mining ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Training Courses ◽  
High Level

Background Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. Methods This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. Results We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0–14.0) and the median awareness score was 29.6 (IQR = 26.6–32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a ’great-extent-of-confidence’ in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. Interpretation There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type.

scholarly journals Filipino Nurses in Cebu City Reveal High Level of Knowledge, Attitudes, Practices and Willingness in Providing Care to COVID-19 Patients: A Cross-Sectional Analysis

2021 ◽  
Author(s):  
Brian Denney ◽  
Alexandra Astor ◽  
Joanna Cabrilles ◽  
Kristiane Codera ◽  
Edzil Marice Forteza ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
The Philippines ◽  
Survey Method ◽  
Local Health ◽  
Limited Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Mean Values ◽  
Filipino Nurses ◽  
High Level

Abstract Background: COVID-19 is a rapidly spreading illness and has resulted in a global pandemic. In the Philippines, active cases of COVID-19 are rising and have threatened both local health and healthcare workers given the limited information on this new disease. Despite several studies conducted to assess the awareness, knowledge, attitude, practices, and willingness of nurses to provide care during this pandemic, there are scarce reports regarding Filipino nurses. Thus, our study assessed such criteria in staff nurses across different Cebu hospitals.Methods: This study utilized a descriptive research design using the cross-sectional survey method. A web-based survey and convenience sampling method was adopted to collect the data from Filipino nurses from any hospital in Cebu, of which, 137 participated in the study. A 43-item questionnaire was developed, which was spread out into 5 parts that comprised of the demographic profile, knowledge (15 items), attitude (10 items), practices (9 items), and willingness to care for patients with COVID-19 (9 items). The data was processed and analyzed using inferential statistical tools.Results: Majority of the nurses were females (70.80%), whose ages were 20-25 years old (54.01%), single (89.78%), mostly college degree holder (90.51%), and employed in hospitals for 1-3 years (64.96%). They also rely on the internet (99.27%) as a source of information related to COVID-19. They also displayed an overall knowledge of 65% especially about the COVID-19 causative agent, its transmission, and pathogenesis. Furthermore, the respondents were generally knowledgeable of the various information regarding COVID-19 at a rate of 79.56%. The mean values for attitude, practices, and willingness to provide care were 4.45 (very favorable), 4.65 (always), and 4.52 (very willing) respectively.Conclusions: Generally, the results of our study were favorable across the 5 parts of the survey. Overall knowledge and extent of practice was high, which can be attributed to government efforts of educating healthcare workers and observance of the mandated protocols. In addition, attitude significantly affected the willingness of the nurses to provide care. However, knowledge and practice did not affect the nurses’ willingness as the drawbacks and demands of their occupation outweighed and decreased their willingness.

scholarly journals OPTIMIZATION OF ASSOCIATION RULES FOR TUBERCULOSIS USING GENETIC ALGORITHM

2014 ◽  
pp. 151-159
Author(s):  
T. Asha ◽  
S. Natarajan ◽  
K.N.B. Murthy
Keyword(s):  
Genetic Algorithm ◽  
Association Rule ◽  
Association Rule Mining ◽  
Solution Space ◽  
Current Approach ◽  
Experimental Result ◽  
Rule Mining ◽  
Human Immuno Deficiency Virus ◽  
Small Set ◽  
High Level

Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium Tuberculosis which usually spreads through the air and attacks low immune bodies. Human Immuno deficiency Virus (HIV) patients are more likely to be attacked by TB. It is an important health problem around the world including India. Association Rule Mining is the process of discovering interesting and unexpected rules from large sets of data. This approach results in huge quantity of rules where some are interesting and others are repetitive. It also limits the quality of rules to only two measures support and confidence. In this paper we try to optimize the rules generated by Association Rule Mining for Tuberculosis using Genetic Algorithm. Our approach is to extract only a small set of high quality Tuberculosis rules among the larger set using Genetic Algorithm. In the current approach datatypes such as discrete, continuous and categorical items have been handled. The proposed experimental result includes a small set of converged TB rules that helps doctors in their diagnosis decisions. The main motivation for using Genetic Algorithms in the discovery of high-level prediction rules is that they are robust, use adaptive search techniques that perform a global search on the solution space and cope better with attribute interaction than the greedy rule induction algorithms often used in data mining.

scholarly journals Filipino Nurses in Cebu City Reveals High Level of Knowledge, Attitudes, Practices and Willingness in Providing Care to COVID-19 Patients: A Cross-Sectional Analysis

2021 ◽  
Author(s):  
Brian Denney ◽  
Alexandra Astor ◽  
Joanna Cabrilles ◽  
Kristiane Codera ◽  
Edzil Marice Forteza ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
The Philippines ◽  
Survey Method ◽  
Local Health ◽  
Limited Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Mean Values ◽  
Filipino Nurses ◽  
High Level

Abstract Background: COVID-19 is a rapidly spreading illness and has resulted in a global pandemic. In the Philippines, active cases of COVID-19 are rising and have threatened both local health and healthcare workers given the limited information on this new disease. Despite several studies conducted to assess the awareness, knowledge, attitude, practices, and willingness of nurses to provide care during this pandemic, there are scarce reports regarding Filipino nurses. Thus, our study assessed such criteria in staff nurses across different Cebu hospitals.Methods: This study utilized a descriptive research design using the cross-sectional survey method. A web-based survey and convenience sampling method was adopted to collect the data from Filipino nurses from any hospital in Cebu, of which, 137 participated in the study. A 43-item questionnaire was developed, which was spread out into 5 parts that comprised of the demographic profile, knowledge (15 items), attitude (10 items), practices (9 items), and willingness to care for patients with COVID-19 (9 items). The data was processed and analyzed using inferential statistical tools.Results: Majority of the nurses were females (70.80%), whose ages were 20-25 years old (54.01%), single (89.78%), mostly college degree holder (90.51%), and employed in hospitals for 1-3 years (64.96%). They also rely on the internet (99.27%) as a source of information related to COVID-19. They also displayed an overall knowledge of 65% especially about the COVID-19 causative agent, its transmission, and pathogenesis. Furthermore, the respondents were generally knowledgeable of the various information regarding COVID-19 at a rate of 79.56%. The mean values for attitude, practices, and willingness to provide care were 4.45 (very favorable), 4.65 (always), and 4.52 (very willing) respectively.Conclusions: Generally, the results of our study were favorable across the 5 parts of the survey. Overall knowledge and extent of practice was high, which can be attributed to government efforts of educating healthcare workers and observance of the mandated protocols. In addition, attitude significantly affected the willingness of the nurses to provide care. However, knowledge and practice did not affect the nurses’ willingness as the drawbacks and demands of their occupation outweighed and decreased their willingness.

scholarly journals Obesity Management Education Needs Among General Internists: A Survey

2021 ◽  
Vol 12 ◽  
pp. 215013272110132
Author(s):  
Sanjeev Nanda ◽  
Jayanth Adusumalli ◽  
Ryan T. Hurt ◽  
Karthik Ghosh ◽  
Karen M. Fischer ◽  
...  
Keyword(s):  
Weight Management ◽  
Healthcare Workers ◽  
Medical Training ◽  
Management Training ◽  
Primary Care Providers ◽  
Obese Patients ◽  
Care Providers ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
General Internal

Objective The purpose of this study was to determine self-reported knowledge, attitudes, prior experience, and perceived needs for the management of overweight and obese patients within a General Internal Medicine Practice. Patients and Methods An emailed cross-sectional survey was sent between June 20, 2019 and September 12, 2019 to 194 healthcare workers (93 primary care providers (PCPs) and 101 nurses) which focused on management of patients with weight issues. Results In total, 80 of the eligible 194 participants completed the survey (nurses = 42, PCPs = 38). Up to 87% were white, 74.7% female (74.7%). Most of the responders were either in the age group of 30’s (30%) or 50’s (30%). Among the responders, 48.8% reported some type of specialty training in weight management since their medical training with lectures being the most common form of training (36%). When asked about their interest in either weight management training or strategies to initiate weight conversations, 79% of the respondents reported an interest in education on weight management or strategies to initiate weight conversations, while 65.8% indicated they would be interested in both topics. Conclusion Our study suggests that healthcare workers have a self-reported need for further training in management of overweight and obese patients, irrespective of previous training in this area.

scholarly journals A New Privacy Preserving Association Rule Mining Algorithm Based on Hybrid Partial Hiding Strategy

2013 ◽  
Vol 13 (Special-Issue) ◽  
pp. 41-50 ◽  
Author(s):  
Jian-Ming Zhu ◽  
Ning Zhang ◽  
Zhan-Yu Li
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Privacy Preservation ◽  
Original Data ◽  
Rule Mining ◽  
Data Set ◽  
Original Algorithm ◽  
Level Data ◽  
Frequent Items ◽  
High Level

Abstract Data mining is the progress of automatically discovering high level data and trends in large amounts of data that would otherwise remain hidden. In order to improve the privacy preservation of association rule mining, a hybrid partial hiding algorithm (HPH) is proposed. The original data set can be interfered and transformed by different random parameters. Then, the algorithm of generating frequent items based on HPH is presented. Finally, it can be proved that the privacy of HPH algorithm is better than that of the original algorithm.

scholarly journals Filipino Nurses in Cebu City Reveal High Level of Knowledge, Attitudes, Practices and Willingness in Providing Care to COVID-19 Patients: A Cross-Sectional Analysis

2021 ◽  
Author(s):  
Brian Mortejo Denney ◽  
Alexandra Astor ◽  
Joanna Cabrilles ◽  
Kristiane Codera ◽  
Edzil Marice Forteza ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
The Philippines ◽  
Survey Method ◽  
Local Health ◽  
Limited Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Mean Values ◽  
Filipino Nurses ◽  
High Level

Abstract Background COVID-19 is a rapidly spreading illness and has resulted in a global pandemic. In the Philippines, active cases of COVID-19 are rising and have threatened both local health and healthcare workers given the limited information on this new disease. Despite several studies conducted to assess the awareness, knowledge, attitude, practices, and willingness of nurses to provide care during this pandemic, there are scarce reports regarding Filipino nurses. Thus, our study assessed such criteria in staff nurses across different Cebu hospitals. Methods This study utilized a descriptive research design using the cross-sectional survey method. A web-based survey and convenience sampling method was adopted to collect the data from Filipino nurses from any hospital in Cebu, of which, 137 participated in the study. A 43-item questionnaire was developed, which was spread out into 5 parts that comprised of the demographic profile, knowledge (15 items), attitude (10 items), practices (9 items), and willingness to care for patients with COVID-19 (9 items). The data was processed and analyzed using inferential statistical tools. Results Majority of the nurses were females (70.80%), whose ages were 20–25 years old (54.01%), single (89.78%), mostly college degree holder (90.51%), and employed in hospitals for 1–3 years (64.96%). They also rely on the internet (99.27%) as a source of information related to COVID-19. They also displayed an overall knowledge of 65% especially about the COVID-19 causative agent, its transmission, and pathogenesis. Furthermore, the respondents were generally knowledgeable of the various information regarding COVID-19 at a rate of 79.56%. The mean values for attitude, practices, and willingness to provide care were 4.45 (very favorable), 4.65 (always), and 4.52 (very willing) respectively. Conclusions Generally, the results of our study were favorable across the 5 parts of the survey. Overall knowledge and extent of practice was high, which can be attributed to government efforts of educating healthcare workers and observance of the mandated protocols. In addition, attitude significantly affected the willingness of the nurses to provide care. However, knowledge and practice did not affect the nurses’ willingness as the drawbacks and demands of their occupation outweighed and decreased their willingness.

Prediksi Code Defect Perangkat Lunak Dengan Metode Association Rule Mining dan Cumulative Support Thresholds

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Rizal Setya Perdana ◽  
Umi Laili Yuhana
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining ◽  
Program Code

Kualitas perangkat lunak merupakan salah satu penelitian pada bidangrekayasa perangkat lunak yang memiliki peranan yang cukup besar dalamterbangunnya sistem perangkat lunak yang berkualitas baik. Prediksi defectperangkat lunak yang disebabkan karena terdapat penyimpangan dari prosesspesifikasi atau sesuatu yang mungkin menyebabkan kegagalan dalam operasionaltelah lebih dari 30 tahun menjadi topik riset penelitian. Makalah ini akandifokuskan pada prediksi defect yang terjadi pada kode program (code defect).Metode penanganan permasalahan defect pada kode program akan memanfaatkanpola-pola kode perangkat lunak yang berpotensi menimbulkan defect pada data setNASA untuk memprediksi defect. Metode yang digunakan dalam pencarian polaadalah memanfaatkan Association Rule Mining dengan Cumulative SupportThresholds yang secara otomatis menghasilkan nilai support dan nilai confidencepaling optimal tanpa membutuhkan masukan dari pengguna. Hasil pengujian darihasil pemrediksian defect kode perangkat lunak secara otomatis memiliki nilaiakurasi 82,35%.

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