scholarly journals Patients’, pharmacists’, and prescribers’ attitude toward using blockchain and machine learning in a proposed ePrescription system: online survey

JAMIA Open ◽  
2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Bader Aldughayfiq ◽  
Srinivas Sampalli

Abstract Objective To evaluate the attitudes of the parties involved in the system toward the new features and measure the potential benefits of introducing the use of blockchain and machine learning (ML) to strengthen the in-place methods for safely prescribing medication. The proposed blockchain will strengthen the security and privacy of the patient’s prescription information shared in the network. Once the ePrescription is submitted, it is only available in read-only mode. This will ensure there is no alteration to the ePrescription information after submission. In addition, the blockchain will provide an improved tracking mechanism to ensure the originality of the ePrescription and that a prescriber can only submit an ePrescription with the patient’s authorization. Lastly, before submitting an ePrescription, an ML algorithm will be used to detect any anomalies (eg, missing fields, misplaced information, or wrong dosage) in the ePrescription to ensure the safety of the prescribed medication for the patient. Methods The survey contains questions about the features introduced in the proposed ePrescription system to evaluate the security, privacy, reliability, and availability of the ePrescription information in the system. The study population is comprised of 284 respondents in the patient group, 39 respondents in the pharmacist group, and 27 respondents in the prescriber group, all of whom met the inclusion criteria. The response rate was 80% (226/284) in the patient group, 87% (34/39) in the pharmacist group, and 96% (26/27) in the prescriber group. Key Findings The vast majority of the respondents in all groups had a positive attitude toward the proposed ePrescription system’s security and privacy using blockchain technology, with 72% (163/226) in the patient group, 70.5% (24/34) in the pharmacist group, and 73% (19/26) in the prescriber group. Moreover, the majority of the respondents in the pharmacist (70%, 24/34) and prescriber (85%, 22/26) groups had a positive attitude toward using ML algorithms to generate alerts regarding prescribed medication to enhance the safety of medication prescribing and prevent medication errors. Conclusion Our survey showed that a vast majority of respondents in all groups had positive attitudes toward using blockchain and ML algorithms to safely prescribe medications. However, a need for minor improvements regarding the proposed features was identified, and a post-implementation user study is needed to evaluate the proposed ePrescription system in depth.

Vaccines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 411
Author(s):  
Anna Brodziak ◽  
Dawid Sigorski ◽  
Małgorzata Osmola ◽  
Michał Wilk ◽  
Angelika Gawlik-Urban ◽  
...  

Recently developed COVID-19 vaccines significantly reduce the risk of severe coronavirus disease, which is essential in the particularly vulnerable cancer patient population. There is a growing anti-vaccine concern that may affect the success of the fight against the SARS-CoV2 pandemic. To evaluate opinions and attitudes toward vaccination, we conducted an anonymous online survey among Polish patients diagnosed with cancer. We analyzed how socio-demographic factors, type of cancer, comorbidities, previous influenza vaccinations, and information sources affect the general willingness and opinions about vaccinations, emphasizing vaccination against COVID-19. Six hundred thirty-five patients (80.2% female) participated in the study. A positive attitude towards vaccination was presented by 73.7%, neutral by 17.8%, while negative by 8.5%. Willingness to get vaccinated was declared by 60.3%, 23.5% were unwilling, and 16.2% were undecided. Significant predictors of willingness were education, marital status, active anti-cancer treatment, previous influenza vaccination, and positive attitude towards vaccinations. Patients with cancer have concerns regarding safety, effectiveness, and the process of development of the COVID-19 vaccine. Overall, patients with cancer present positive attitudes towards COVID-19 vaccination but required sufficient information on its efficacy and side effects.


2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Aliaa M. Alabdali

With the growing need of technology into varied fields, dependency is getting directly proportional to ease of user-friendly smart systems. The advent of artificial intelligence in these smart systems has made our lives easier. Several Internet of Things- (IoT-) based smart refrigerator systems are emerging which support self-monitoring of contents, but the systems lack to achieve the optimized run time and data security. Therefore, in this research, a novel design is implemented with the hardware level of integration of equipment with a more sophisticated software design. It was attempted to design a new smart refrigerator system, which has the capability of automatic self-checking and self-purchasing, by integrating smart mobile device applications and IoT technology with minimal human intervention carried through Blynk application on a mobile phone. The proposed system automatically makes periodic checks and then waits for the owner’s decision to either allow the system to repurchase these products via Ethernet or reject the purchase option. The paper also discussed the machine level integration with artificial intelligence by considering several features and implemented state-of-the-art machine learning classifiers to give automatic decisions. The blockchain technology is cohesively combined to store and propagate data for the sake of data security and privacy concerns. In combination with IoT devices, machine learning, and blockchain technology, the proposed model of the paper can provide a more comprehensive and valuable feedback-driven system. The experiments have been performed and evaluated using several information retrieval metrics using visualization tools. Therefore, our proposed intelligent system will save effort, time, and money which helps us to have an easier, faster, and healthier lifestyle.


Author(s):  
Vijaya Ravindra Wankhade

Abstract: In recent years, the emergence of blockchain technology (BT) has become a novel, most disruptive, and trending technology. The redistributed database in BT emphasizes data security and privacy. Also, the consensus mechanism makes positive that data is secured and bonafide. Still, it raises new security issues like majority attacks and double-spending. To handle the said problems, data analytics is required on blockchain-based secure knowledge. Analytics on these data raises the importance of arising technology Machine Learning (ML). ml involves the rational quantity of data to create precise selections. data reliability and its sharing are terribly crucial in ml to enhance the accuracy of results. the combination of those two technologies (ML and BT) provide give highly precise results. in this paper, present gift a detailed study on ml adoption we BTbased present applications additional resilient against attacks. There area unit varied ancient ML techniques, for example, Support Vector Machines (SVM), clustering, bagging, and Deep Learning (DL) algorithms like Convolutional Neural Network (CNN) and Long STM (LSTM) are often used to analyze the attacks on a blockchain-based network. Further, we tend to embody however each the technologies are often applied in many sensible applications like unmanned Aerial Vehicle (UAV), sensible Grid (SG), healthcare, and sensible cities. Then, future analysis problems and challenges are explored. At last, a case study is presented with a conclusion. Keywords: Blockchain, machine learning, smart grid, data security and privacy, data analytics, smart applications.


2020 ◽  
Vol 162 (12) ◽  
pp. 3081-3091 ◽  
Author(s):  
Victor E. Staartjes ◽  
Vittorio Stumpo ◽  
Julius M. Kernbach ◽  
Anita M. Klukowska ◽  
Pravesh S. Gadjradj ◽  
...  

Abstract Background Recent technological advances have led to the development and implementation of machine learning (ML) in various disciplines, including neurosurgery. Our goal was to conduct a comprehensive survey of neurosurgeons to assess the acceptance of and attitudes toward ML in neurosurgical practice and to identify factors associated with its use. Methods The online survey consisted of nine or ten mandatory questions and was distributed in February and March 2019 through the European Association of Neurosurgical Societies (EANS) and the Congress of Neurosurgeons (CNS). Results Out of 7280 neurosurgeons who received the survey, we received 362 responses, with a response rate of 5%, mainly in Europe and North America. In total, 103 neurosurgeons (28.5%) reported using ML in their clinical practice, and 31.1% in research. Adoption rates of ML were relatively evenly distributed, with 25.6% for North America, 30.9% for Europe, 33.3% for Latin America and the Middle East, 44.4% for Asia and Pacific and 100% for Africa with only two responses. No predictors of clinical ML use were identified, although academic settings and subspecialties neuro-oncology, functional, trauma and epilepsy predicted use of ML in research. The most common applications were for predicting outcomes and complications, as well as interpretation of imaging. Conclusions This report provides a global overview of the neurosurgical applications of ML. A relevant proportion of the surveyed neurosurgeons reported clinical experience with ML algorithms. Future studies should aim to clarify the role and potential benefits of ML in neurosurgery and to reconcile these potential advantages with bioethical considerations.


Author(s):  
Mohamed Ali Alzain ◽  
Najm Eldinn Elsser ◽  
Collins Otieno Asweto ◽  
Mohammed Mohamoud Alsese ◽  
Mohammed Ismail Humaida ◽  
...  

Background: The awareness and belief of people on coronavirus disease 2019 (COVID-19) prevention often influence their practices toward the disease. Therefore, it is essential to assess people's knowledge, attitude, and practice towards COVID-19 prevention; to inform policymakers.Methods: An online survey was conducted on 1455 Sudanese adults using a pretested questionnaire. Chi-square test, spearman’s correlation, and logistic regression were used to analyse the data using statistical package for social sciences (SPSS) version-25.Results: The study found relatively good knowledge, attitude, and practice on COVID-19 prevention with overall correct rates of 84.6%, 88.8 %, and 78.6%, respectively. Furthermore, knowledge was positively correlated with attitude (r=0.355, P<0.001). Participants with good knowledge were more likely to have a positive attitude and practice (OR=1.36; 95%CI:1.08-1.71; OR=1.52; 95%CI:1.36-1.71), respectively than those with insufficient knowledge. While participants with a positive attitude were more than two times (OR=2.36; 95%CI:1.86-2.99) more likely to have good practice than a negative attitude. Moreover, females and married were more likely to have good practice (OR=1.37; 95%CI:1.10-1.69; OR=1.26; 95%CI:1.02-1.55), and positive attitudes (OR=1.39; 95%CI: 1.10-1.77; OR=1.45; 95% CI:1.15-1.84), respectively than their corresponding targeted counterparts. Furthermore, certain occupations (housewife, no worker, and employed) were more likely to have positive attitude and practice than the student (p<0.05). Besides, considerable participants had misconceptions regarding; effectiveness of antibiotics in combating COVID-19 (32%); almost two-thirds of participants either never wearing masks or sometimes.Conclusions: The finding concluded that relatively good knowledge, positive attitude, and desired practices against prevention of COVID-19. Therefore, a great emphasis on health awareness campaigns should focus on risk-taking practice and remove misconceptions.   


2021 ◽  
Vol 11 (4) ◽  
pp. 288-292
Author(s):  
Sheetal Aurangabadkar ◽  
Asmita Karajgi

The Coronavirus (COVID-19) outbreak was declared a public health emergency of international concern by the World Health Organisation. Pandemics can lead to increased level of stress and anxiety. This is especially true for COVID -19 when there is speculation surrounding the mode and rate of transmission, with the disease spreading at such a magnitude all around the globe. This online survey, related to the knowledge, attitude and anxiety about the novel Corona virus, was conducted among the urban population of Mumbai, India. A total of 155 responses were obtained. All the participants were above 18 years and of Indian origin. Among the participants, 74.2% were females and 25.8% were males. A majority of responders were aware of the basic knowledge of the disease COVID 19. About 65.2% participants reported that Corona virus can spread through touching, sneezing, kissing and food. Most of the participants had positive attitude towards the disease and the social practises related to the COVID 19. Majority of the participants complained of high anxiety and stress related to their personal hygiene, keeping a stock of all the essentials in their home and a constant fear of getting infected. Conclusion – There is moderate level of awareness about the knowledge related to the mode and spread of COVID 19 among the study population due to their high level of education and internet access. Though there is a positive attitude towards the practise of COVID protocol like isolation and the need for avoiding crowded places, there is still fear of getting infected among the study population. Key words: Corona virus, Knowledge, Attitude, Anxiety, World Health Organisation.


2021 ◽  
Vol 9 (E) ◽  
pp. 1238-1243
Author(s):  
Hotma Rumahorbo ◽  
Priyanto Priyanto ◽  
Atin Karjatin

BACKGROUND: The COVID-19 infection spreads quickly and easily, hence people are required to obey health protocols. Attitudes play an important role in building people’s readiness to use face masks and wash hands. AIM: The study aims at analyzing several factors influencing people’s attitudes towards wearing face masks and washing hands in Indonesia. METHODS: The study employs a cross-sectional online survey involving 400 adult respondents in the Java region from July to September 2020. RESULTS: Of 400 respondents, 54.3% showed positive attitudes toward wearing face masks and 59.3% towards washing hands. The multivariate analysis showed that people’s attitudes towards wearing face masks were influenced by age and knowledge. Respondents aged 36–45 years old had positive attitudes on wearing face masks 3.9 times (p = 0.038) and aged ≥46 years old 4.1 times (p = 0.039) compared to aged 18–35 years old. Furthermore, attitudes on washing hands were influenced by gender, age groups, and knowledge. Female had positive attitudes towards washing hands 1.7 times (p = 0.029) compared to male. Respondents aged 36–45 years old had positive attitudes on washing hands 5 times (p = 0.037) and aged ≥46 years old 4.8 times (p = 0.05) compared to aged 18–35 years old. Knowledge acted as the confounding factor. CONCLUSION: The age and knowledge factors influenced positive attitude of using masks and washing hands were influenced by gender, age, and knowledge. Health education programs are recommended to increase knowledge about COVID-19, this is very helpful for the young generation of Indonesia to have a positive attitude.


Crisis ◽  
2015 ◽  
Vol 36 (2) ◽  
pp. 135-141 ◽  
Author(s):  
Erin F. Ward-Ciesielski ◽  
Madeline D. Wielgus ◽  
Connor B. Jones

Background: Suicide-bereaved individuals represent an important group impacted by suicide. Understanding their experiences following the suicide of a loved one is an important research domain, despite receiving limited attention. Although suicide-bereaved individuals may benefit from mental health treatment, their attitudes toward therapy and therapists are poorly understood. Aims: The present study aimed to understand the extent to which bereaved individuals’ attitudes toward therapy and therapists are impacted by whether their loved one was in therapy at the time of death. Method: Suicide-bereaved individuals (N = 243) from the United States were recruited to complete an online survey about their experience with and attitudes toward therapy and therapists following the suicide of a loved one. Results: Bereaved individuals whose loved one was in therapy at the time of death (N = 48, 19.8%) reported more negative and less positive attitudes toward the treating therapist than those whose loved one was not in therapy at the time of death (N = 81, 33.3%) or whose loved one was never in therapy/the deceased’s therapy status was unknown (N = 114, 46.9%). Conclusion: The deceased’s involvement with a therapist appears to be an important factor impacting the experience of bereaved individuals and should be considered when attempting to engage these individuals in postvention.


2012 ◽  
Vol 2 (2) ◽  
pp. 72-81
Author(s):  
Christina M. Rudin-Brown ◽  
Eve Mitsopoulos-Rubens ◽  
Michael G. Lenné

Random testing for alcohol and other drugs (AODs) in individuals who perform safety-sensitive activities as part of their aviation role was introduced in Australia in April 2009. One year later, an online survey (N = 2,226) was conducted to investigate attitudes, behaviors, and knowledge regarding random testing and to gauge perceptions regarding its effectiveness. Private, recreational, and student pilots were less likely than industry personnel to report being aware of the requirement (86.5% versus 97.1%), to have undergone testing (76.5% versus 96.1%), and to know of others who had undergone testing (39.9% versus 84.3%), and they had more positive attitudes toward random testing than industry personnel. However, logistic regression analyses indicated that random testing is more effective at deterring AOD use among industry personnel.


2020 ◽  
Author(s):  
Shreya Reddy ◽  
Lisa Ewen ◽  
Pankti Patel ◽  
Prerak Patel ◽  
Ankit Kundal ◽  
...  

<p>As bots become more prevalent and smarter in the modern age of the internet, it becomes ever more important that they be identified and removed. Recent research has dictated that machine learning methods are accurate and the gold standard of bot identification on social media. Unfortunately, machine learning models do not come without their negative aspects such as lengthy training times, difficult feature selection, and overwhelming pre-processing tasks. To overcome these difficulties, we are proposing a blockchain framework for bot identification. At the current time, it is unknown how this method will perform, but it serves to prove the existence of an overwhelming gap of research under this area.<i></i></p>


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