Quality evaluation of digital voice assistants for diabetes management

Background: Digital voice assistants (DVAs) are increasingly used to search for health information. However, the quality of information provided by DVAs is not consistent across health conditions. From our knowledge, there have been no studies that evaluated the quality of DVAs in response to diabetes-related queries. The objective of this study was to evaluate the quality of DVAs in relation to queries on diabetes management. Materials and methods: Seventy-four questions were posed to smartphone (Apple Siri, Google Assistant, Samsung Bixby) and non-smartphone DVAs (Amazon Alexa, Sulli the Diabetes Guru, Google Nest Mini, Microsoft Cortana), and their responses were compared to that of Internet Google Search. Questions were categorized under diagnosis, screening, management, treatment and complications of diabetes, and the impacts of COVID-19 on diabetes. The DVAs were evaluated on their technical ability, user-friendliness, reliability, comprehensiveness and accuracy of their responses. Data was analyzed using the Kruskal-Wallis and Wilcoxon rank-sum tests. Intraclass correlation coefficient was used to report inter-rater reliability. Results: Google Assistant (n = 69/74, 93.2%), Siri and Nest Mini (n = 64/74, 86.5% each) had the highest proportions of successful and relevant responses, in contrast to Cortana (n = 23/74, 31.1%) and Sulli (n = 10/74, 13.5%), which had the lowest successful and relevant responses. Median total scores of the smartphone DVAs (Bixby 75.3%, Google Assistant 73.3%, Siri 72.0%) were comparable to that of Google Search (70.0%, p = 0.034), while median total scores of non-smartphone DVAs (Nest Mini 56.9%, Alexa 52.9%, Cortana 52.5% and Sulli the Diabetes Guru 48.6%) were significantly lower (p < 0.001). Non-smartphone DVAs had much lower median comprehensiveness (16.7% versus 100.0%, p < 0.001) and reliability scores (30.8% versus 61.5%, p < 0.001) compared to Google Search. Conclusions: Google Assistant, Siri and Bixby were the best-performing DVAs for answering diabetes-related queries. However, the lack of successful and relevant responses by Bixby may frustrate users, especially if they have COVID-19 related queries. All DVAs scored highly for user -friendliness, but can be improved in terms of accuracy, comprehensiveness and reliability. DVA designers are encouraged to consider features related to accuracy, comprehensiveness, reliability and user-friendliness when developing their products, so as to enhance the quality of DVAs for medical purposes, such as diabetes management.

Research on Cold Chain Logistics Service Quality Evaluation Considering Product Freshness under Community Group Buying

In 2019, The outbreak of Corona Virus Disease 2019 (named COVID-19) has caused great changes in the living habits of residents, and the community group buying model has re-emerged. Under the background of community group buying mode, combined with the characteristics of fresh products, and based on the SEVRQUAL model and the national standard of "Logistics Enterprise Cold Chain Service Requirements and Capability Evaluation Indicators", an evaluation index system of cold chain logistics service quality for community group purchase of fresh products with 5 dimensions and 29 indicators is constructed from the perspective of users. Then a 5-level Likert scale was used to design relevant questionnaires, and Xingsheng Youxuan and Meituan Youxuan were used as empirical cases for sample research. Combined collected sample data, the validity and rationality of the index system were tested through reliability, validity testing and factor analysis. The data analysis also shows the problems and influencing factors of Xingsheng Youxuan and Meituan Youxuan in terms of fresh food cold chain logistics service quality, and further suggestions for the development of cold chain logistics services considering product freshness under community group buying is also provided. © 2022 ACM.

Twitter as research data Tools, costs, skill sets, and lessons learned.

Scholars increasingly use Twitter data to study the life sciences and politics. However, Twitter data collection tools often pose challenges for scholars who are unfamiliar with their operation. Equally important, although many tools indicate that they offer representative samples of the full Twitter archive, little is known about whether the samples are indeed representative of the targeted population of tweets. This article evaluates such tools in terms of costs, training, and data quality as a means to introduce Twitter data as a research tool. Further, using an analysis of COVID-19 and moral foundations theory as an example, we compared the distributions of moral discussions from two commonly used tools for accessing Twitter data (Twitter's standard APIs and third-party access) to the ground truth, the Twitter full archive. Our results highlight the importance of assessing the comparability of data sources to improve confidence in findings based on Twitter data. We also review the major new features of Twitter's API version 2.

Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic

The spread of the COVID-19 pandemic has resulted in the launch of contactless delivery services. This research integrates resource matching, service quality evaluation, and perceived value theories to explore the factors that promote the use contactless delivery services. The data was obtained through questionnaire surveys, and research hypotheses were verified through the structural equation modelling approach. With the exception of convenience, the results show that privacy, reliability, security, and flexibility have a significantly positive effect on consumers' intention to use "contactless” delivery services through consumers' perceived value. This study contributes to the literature by introducing theoretical frameworks from various paradigms and enriches the academic research on existing theoretical structure models. It also helps optimize resource allocation and realize the social environment related to coexisting with the COVID-19 pandemic. © 2023 Elsevier Ltd

Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic

The spread of the COVID-19 pandemic has resulted in the launch of contactless delivery services. This research integrates resource matching, service quality evaluation, and perceived value theories to explore the factors that promote the use contactless delivery services. The data was obtained through questionnaire surveys, and research hypotheses were verified through the structural equation modelling approach. With the exception of convenience, the results show that privacy, reliability, security, and flexibility have a significantly positive effect on consumers' intention to use "contactless” delivery services through consumers' perceived value. This study contributes to the literature by introducing theoretical frameworks from various paradigms and enriches the academic research on existing theoretical structure models. It also helps optimize resource allocation and realize the social environment related to coexisting with the COVID-19 pandemic.

The quantitative assessment of patient satisfaction in the COVID-19 epidemic compared to the epidemic-free period

Surveying patient satisfaction is considered an important part of any systematic program of quality assurance. Quality of healthcare service and patient satisfaction has been affected by the current COVID-19 epidemic. The purpose of the study was to determine how COVID-19 epidemic has affected patients in Slovenia as it is evident via permanently available questionnaire and from studying this data source to improve our response to future crises and to improve the resilience of healthcare systems. A secondary analysis of 12,756 completed questionnaires was performed via freely available patient satisfaction questionnaire in the period from October 2019 to June 2021. The number of completed questionnaires was significantly higher in the period before the COVID-19 outbreak than in the subsequent periods. Comparing COVID-19 period and epidemic-free period statistically significant differences in satisfaction assessment occurred in four variables. More patients recognized opportunities for improvement in the COVID-19 epidemic than in the epidemic-free period. This study can be upgraded with qualitative studies and implementation of systemic measures. © The Author(s), 2022.

Evaluation of quality and antimicrobial efficacy of locally manufactured alcohol-based hand sanitizers marketed in Addis Ababa, Ethiopia in the era of COVID-19.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has been rapidly spreading across the globe since the World Health Organization (WHO) has declared the disease outbreak as a global pandemic on March 11, 2020. Hand hygiene, via either regular handwashing with soap and water or using hand sanitizers, is among the various measures that need to be followed to control the outbreak of the disease. Alcohol-based hand sanitizers (ABHS) are the "gold standard" for hand disinfection because of their broad antimicrobial spectrum of activity, easy availability, better safety profile, and general acceptability to users. This study aimed at evaluating the physicochemical quality and antimicrobial efficacy of the locally manufactured ABHS marketed in Addis Ababa, Ethiopia. METHODS: A cross-sectional survey was used to collect ABHS from Addis Ababa marketplaces. A total of 25 sample products were randomly selected from different categories of hand sanitizer manufacturers. The physicochemical evaluation of the products was carried out as per the United States Pharmacopoeia and WHO standards. Escherichia coli, Klebsiella spp., Pseudomonas aeruginosa, Staphylococcus aureus, Salmonella spp., and Shigella spp clinical isolates were used for the antimicrobial efficacy test. RESULTS: The Fourier Transform Infrared result confirmed that all the test products met the identification test for ethanol. The majority (68%) of ABHS complied with the test for ethanol content (75-85% v/v). However, only 3 products fulfilled the hydrogen peroxide content (0.112-0.137% v/v). LPC307 showed the maximum zone of inhibition of 12 mm against Escherichia coli whereas MPC204 exhibited only 3 mm. LPC101 was found to be more sensitive to Shigella and Klebsiella Spp with minimum inhibitory concentration values of 20% and 10%, respectively. The sample product LPC101 showed a minimum bactericidal concentration of 20% against Escherichia coli, Pseudomonas aeruginosa, and Klebsiella spp. CONCLUSION: One-third of the tested ABHS did not comply with the WHO ethanol content limit and the majority of the products failed to meet the label claim for hydrogen peroxide content. Besides, nearly all products proved that they have activity against all the tested pathogenic microorganisms at a minimum concentration from 10 to 80%; though, they did not show 99.9% bacteriostatic or bactericidal activities as claimed. The study findings suggested regular monitoring of the quality of marketed ABHS considering the current wide use of these products.

Research on University Teaching Quality Evaluation and Guarantee System Based on Block Chain Technology

Influenced by the COVID-19 epidemic in the past two years, colleges and universities at home and abroad have adopted a combination of online and offline teaching reform, education informatization and intelligent talent training methods, which have become the focus of research for educators. The teaching quality is related to the quality of talent cultivation, and the intelligence, fairness and accuracy of the teaching evaluation system are particularly important. And block chain technology is decentralized and safe and reliable features, so the development of the technology based on big data and chain blocks obeys the law of education development of teaching evaluation system, to solve the shortage of the current appraisal system, and realize the sharing of teaching resources, integrate and optimize the teaching resources, promoting the standardization and standardization of teaching resources construction, To promote the construction and better development of disciplines in colleges and universities. © 2022 IEEE.

Formulation, process optimization, and quality evaluation of barnyard millet (Echinochloa frumentacea)-based ready-to-eat (RTE) extruded snack

COVID-19 pandemic has increased the demand for antioxidant and micronutrient-rich foods that are easy to prepare, consume, and require less handling. In this research, we worked on the development of nutritious extruded snack made from barnyard millet, defatted soy flour, Indian gooseberry powder, and rice flour. Box–Behnken Design of Response Surface Methodology was utilized to determine the influence of process variables viz;blend ratio of barnyard millet and defatted soy flour, extruder barrel temperature, and Indian gooseberry powder on nutritional and organoleptic properties of snack. Optimized extruded snack were attained at blend ratio (6:1), barrel temperature (115°C), and Indian gooseberry (12.25 g/100 g of total flour). Extruded snack presented good overall acceptability along with high fiber (16.84 g/100 g), protein (18.91 g/100 g), total phenol (67.51 mg GAE/100 g), and total flavonoid (153.61 mg RE/100 g) content. Microbial analysis indicates that extruded snack can be stored for up to 60 days without microbial contamination. Novelty impact statement: The pandemic has made people refocus on the foods that are nutritious, yet take less time to prepare and handle. In the present research, we explored the use of locally available and low-cost barnyard millet and defatted soy flour coupled with Indian gooseberry powder—a rich source of antioxidants and rice flour for the preparation of nutritious snack. Extrudates developed with a higher blend ratio at higher barrel temperature and enriched with Indian gooseberry content displayed excellent nutritional, bioactive, and dimensional characteristics. The study will help formulate extruded snack with high protein, antioxidants, as well as fiber content. © 2022 Wiley Periodicals LLC.

Integration of Hospital Therapeutic Gardens into the Green Frame of Sevastopol

The past decade has witnessed a series of major international events dedicated to the “return of nature to cities.” The modern processes of urban development and planning are associated with creation of comfortable and safe urban environments, the quality of life being the main criterion of the effectiveness of urban planning strategies. To the foreground come the tasks of providing the population with an urban environment that would contribute to longer lifespan and greater comfort of living for all categories of citizens. Healthy ageing is increasingly seen as the main element in urban environment quality evaluation. The comfortable urban setting with increased health improvement opportunities is an important tool to mitigate the negative consequences of urbanization, burdened by globalization and COVID-19. The urban planning and development strategies are currently undergoing changes. The green frames of urban localities, destroyed in the 1990s by unregulated development of various functional purpose, are regaining their role as the key marker of the balanced urban development and spatial planning approach. The study has been conducted within the framework of Grant 29/06-31. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Web-based Intelligent Update Design of Sports Comprehensive Quality Evaluation Support System (CQESS) with Aptana Studio under COVID-19

Web-based intelligent update design of the sports comprehensive quality evaluation support system (CQESS) with Aptana Studio under COVID-19 is studied in the paper. According to the background research, it is found that the current research on access constraints mostly adopts the methods of dynamic communication scheduling, static communication scheduling and communication scheduling protocol, and often ignores the random characteristics of access constraints. Hence, the dynamic network model is chosen as the target. Due to the advantages of basic non-volatile, byte addressing and high performance of persistent memory, researchers have then made the in-depth exploration of it from various aspects and the Aptana Studio is considered as the implementation platform. The ntelligent update design of sports comprehensive quality evaluation support system is implemented, and the related testing is then conducted to present the systematic performance. © 2022 IEEE.

Distance education quality evaluation based on multigranularity probabilistic linguistic term sets and disappointment theory

Distance education quality evaluation is extremely important in improving the quality of education under COVID-19. As traditional teaching-quality evaluation methods are no longer applicable, it is crucial to construct effective evaluation methods. In the evaluation of distance education quality, decision-makers have different linguistic expression preferences, and the evaluation information may be biased due to an improper grasp of the problem. In addition, the correlation between the criteria of distance education quality evaluation is common, and the results of existing evaluation methods are quite different. In this paper, to compensate for these deficiencies, we utilize the multi-granularity probabilistic linguistic term set (MGPLTS), which can reflect the linguistic expression preference of decision-makers and the importance of linguistic terms, and propose a multi-criteria group decision-making (MCGDM) method. First, the dispersion and concentration degrees are proposed as the theoretical basis for judging the hesitancy of decision-makers’ evaluation information, and the decision-maker weight adjustment model is constructed. To reflect the importance and correlation of criteria, the SWARA method and the CRITIC method are constructed as criteria weight methods. To obtain reliable decision results, decision-makers’ psychological expectations are taken into account, the MULTIMOORA method is improved upon, and a new integration theory is proposed to improve its robustness. Finally, through an example case of distance education quality evaluation and comparison with other methods, the effectiveness, practicability and superiority of this method are verified.

Quality Evaluation of Image Dataset based on Label File

The quality of the dataset affects the accuracy of the artificial intelligence model, but it is a lot of work to manually detect errors related to the quality evaluation of the dataset, and it may not be possible to perform quality evaluation through simple viewing. Therefore, we propose an image dataset quality measurement model, including nine evaluation metrics, and analyze the evaluation metrics from three aspects: definition, calculation formula and description. Based on the label file, the quality of the dataset file and the content of the dataset is evaluated, and the evaluation standard is given to judge whether the quality of the dataset is qualified. The measurement model and evaluation criteria proposed in this article were verified against the Cifar-10 dataset and the COVID-CT dataset, and the problems of label accuracy and label category imbalance were found, which proved the effectiveness of the method in this paper. © 2021 IEEE.

Indoor air quality evaluation in naturally cross-ventilated buildings for education using age of air

Natural ventilation (NV) is a strategy of bioclimatic design to promote hygrothermal comfort and indoor air quality (IAQ). Nowadays, COVID-19 pandemic highlights the review of ventilation standards. In Mexico, the IAQ standard states a minimum of 6 ACH for educational buildings. ACH considers NV as an ideal piston flow and does not provide information of indoor airflow distribution. In this work, new age of air associated parameters are proposed, considering the indoor airflow distribution: the air renovation per hour (ARH) and the renovation parameter R. An isolated educational building located in a rural region is studied. Four window configurations of cross-ventilation are considered. All configurations have one windward window located at bottom. The configurations axial and upward have one leeward window at bottom and top, respectively. While, configurations corner and upward corner have one lateral side window at bottom and top, respectively. A CFD model of the educational building is validated with experiments. The axial configuration has the best performance according to ACH, nevertheless has the worst performance according to ARH and R. The results show that NV evaluation using ACH can lead to wrong decisions. An improvement of NV standard with the age of air associated parameters is recommended. © 2021 Institute of Physics Publishing. All rights reserved.

Comparison of lung image quality between CT Ark and Brilliance 64 CT during COVID-19.

AIM: This study is to compare the lung image quality between shelter hospital CT (CT Ark) and ordinary CT scans (Brilliance 64) scans. METHODS: The patients who received scans with CT Ark or Brilliance 64 CT were enrolled. Their lung images were divided into two groups according to the scanner. The objective evaluation methods of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used. The subjective evaluation methods including the evaluation of the fine structure under the lung window and the evaluation of the general structure under the mediastinum window were compared. Kappa method was used to assess the reliability of the subjective evaluation. The subjective evaluation results were analyzed using the Wilcoxon rank sum test. SNR and CNR were tested using independent sample t tests. RESULTS: There was no statistical difference in somatotype of enrolled subjects. The Kappa value between the two observers was between 0.68 and 0.81, indicating good consistency. For subjective evaluation results, the rank sum test P value of fine structure evaluation and general structure evaluation by the two observers was ≥ 0.05. For objective evaluation results, SNR and CNR between the two CT scanners were significantly different (P<0.05). Notably, the absolute values ​​of SNR and CNR of the CT Ark were larger than Brilliance 64 CT scanner. CONCLUSION: CT Ark is fully capable of scanning the lungs of the COVID-19 patients during the epidemic in the shelter hospital.

Quality evaluation of stress, anxiety and depression apps for COVID-19.

BACKGROUND: COVID-19 has caused increased stress, anxiety and depression with increased barriers to treatment. Mobile apps offer a potential solution, but there is no information on the quality of such apps recommended for COVID-19. This study aims to evaluate the quality of stress, anxiety and depression apps recommended for COVID-19. METHODS: A search was conducted to identify relevant apps on the iOS and Android platforms. 44 apps were evaluated using the Mobile App Rating Scale (MARS), and the American Psychiatric Association's app evaluation model for data privacy and security. RESULTS: Overall quality scores of iOS and Android apps were 3.69 ± 0.43 and 3.66 ± 0.47. Thirty percent had good/excellent overall scores. In general, the iOS and Android versions of the apps scored best for functionality (4.21 ± 0.48, 4.12 ± 0.53), followed by aesthetics (3.84 ± 0.50, 3.78 ± 0.56), information (3.39 ± 0.54, 3.40 ± 0.60), and engagement (3.31 ± 0.81, 3.34 ± 0.84). Over half (59%) shared personal information with third parties and 14% were compliant with data protection standards. LIMITATIONS: Only free apps available in Singapore were evaluated. Our results are time sensitive due to addition, removal, and update of apps in the app stores, thus our results should be extrapolated with caution to apps from other countries and paid apps. CONCLUSION: Apps that addressed all three conditions had the highest overall quality scores. The top ranked apps (Sanvello, Woebot, Happify, Youper, Bloom) were of good quality, but majority were of acceptable quality and had room for improvement. App developers are encouraged to use our findings to improve and develop better quality apps.

Establishing quality evaluation system of nursing management in fever clinics: A Delphi method.

AIM: The aim of this study is to construct a quality evaluation system for fever clinic nursing management. BACKGROUND: Fever clinic is the first line of defence against the epidemic during COVID-19 in China. METHODS: Our study combines the Delphi method and the analytic hierarchy process. Delphi method was used to carry out two rounds of consultation for 18 experts, to select and revise indicators at all levels. Analytic hierarchy process was used to calculate the weight of indicators at all levels. RESULTS: A quality evaluation system of nursing management for fever clinics is built using Delphi method. It includes five first-level indexes, 14 second-level indexes and 82 third-level indexes. A two-round expert consultation is used to build the indicators. The recovery rates of expert questionnaires in the two rounds were, respectively, 100% and 94%, and expert authority coefficients were 0.925. The Kendall coefficients in the two rounds were, respectively, 0.205 and 0.162 (P < .001). The weight analysis shows that health management of nursing staff (0.2803) and disinfection isolation and treatment of medical waste (0.2803) are most important, followed by nursing post management and personnel training (0.1889), configuration and management of equipment (0.1427) and patient consultation management and nursing (0.1078). CONCLUSION: The quality evaluation system of nursing management in the constructed fever clinic is used to put forward a specific, objective and quantifiable evaluation criteria of nursing quality for fever clinic management, which can better meet the needs of epidemic prevention and control, and has a certain application and promotion value. IMPLICATIONS FOR NURSING MANAGEMENT: The establishment and improvement of a quality system for fever clinic care management will help to respond to outbreaks such as COVID-19.