The Intention of Retail Stores in Taiwan to Cooperate with the Government in the Establishment of IT Measures for Pandemic Prevention.

This study focuses on the cooperative attitude and intention of retail stores in Taiwan to cooperate with the government's related pandemic prevention measures. The study is based on the Theory of Planned Behavior (TPB). The study includes factors such as perceived risk of infection, job stress, pandemic prevention IT (information technology) convenience, pandemic prevention attitude, and pandemic prevention intention. Pandemic prevention attitude is used as a mediating variable to establish the research framework. This study collected research data through a questionnaire survey. A total of 457 valid questionnaires were collected through an electronic questionnaire platform. The findings showed that perceived risk of infection and pandemic prevention IT convenience had a positive and significant effect on pandemic prevention attitude (ß = 0.567; ß = 0.422) and pandemic prevention intention (ß = 0.424; ß = 0.296). Job stress has a significant negative effect on attitude (ß = -0.173). In addition, job stress influenced intention through attitudes. Finally, perceived risk, job stress, and IT convenience had high explanatory power (R2 = 0.706) on attitudes. Perceived risk, IT convenience, and attitude also had moderate explanatory power (R2 = 0.588) on prevention intention. The study also suggests practical recommendations to improve and cooperate with pandemic prevention intention.

Integrating the Public Health Services Model into Age-Friendly Pharmacies: A Case Study on the Pharmacies in Taiwan.

Taiwan is expected to become a superaged society by 2026. Community pharmacies have recently joined Taiwan's primary care system; they have great potential to provide professional healthcare services. This study examined whether the services provided by community pharmacists enhance medication adherence, enable the identification and solution of drug therapy problems, and are accepted by community residents. The Department of Public Health, Taoyuan City, collaborated with the Taoyuan Pharmacist Association over 11 months in 2018 in enabling pharmacists to dispense prescriptions and provide medication adherence consultations, cognitive services, and home and institutional medical care services. This study designed four satisfaction questionnaires to assess the feasibility and performance of these services. Regarding the services related to medication knowledge and adherence, 92.10% of the patients reported overall satisfaction, and all understanding and ability scores were improved in more than 95% of patients. The number of patients highly cooperative regarding their medication had risen from 14 to 234 after the intervention, and the number with low medication adherence had dropped from 533 to 33. More than 90% of respondents indicated that the institutional medical care services had significantly improved their medication knowledge and behaviors. The feasibility of the incorporation of integrated the public health services model into age-friendly pharmacies was confirmed by this study.

Feature Selection Based on a Large-Scale Many-Objective Evolutionary Algorithm.

The feature selection problem is a fundamental issue in many research fields. In this paper, the feature selection problem is regarded as an optimization problem and addressed by utilizing a large-scale many-objective evolutionary algorithm. Considering the number of selected features, accuracy, relevance, redundancy, interclass distance, and intraclass distance, a large-scale many-objective feature selection model is constructed. It is difficult to optimize the large-scale many-objective feature selection optimization problem by using the traditional evolutionary algorithms. Therefore, this paper proposes a modified vector angle-based large-scale many-objective evolutionary algorithm (MALSMEA). The proposed algorithm uses polynomial mutation based on variable grouping instead of naive polynomial mutation to improve the efficiency of solving large-scale problems. And a novel worst-case solution replacement strategy using shift-based density estimation is used to replace the poor solution of two individuals with similar search directions to enhance convergence. The experimental results show that MALSMEA is competitive and can effectively optimize the proposed model.