As the aging trend intensifies, the Chinese government prioritizes technological innovation in smart elderly care services to enhance quality and efficiency, catering to the diverse needs of the elderly. This study examines the acceptance and usage behavior of smart elderly care services among elderly individuals in Xi’an, using a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model that includes digital literacy as a moderating variable. Data were collected via a survey of 299 elderly individuals aged 60 and above in Xi’an. The study aims to identify factors influencing the acceptance and usage behavior of smart elderly care services and to understand how digital literacy moderates the relationship between these factors and usage behavior. Regression analysis assessed the direct effects of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) on usage behavior. These dimensions were then integrated into a comprehensive index Service Acceptance to evaluate their overall impact on usage behavior, with behavioral intention examined as a potential mediating variable. Results indicate that EE and SI significantly impact the adoption of smart elderly care services, whereas PE and FC do not. Behavioral intention mediates the relationship between these variables and usage behavior. Additionally, gender, age, and digital literacy significantly moderate the impact of service acceptance on usage behavior. This study provides valuable theoretical and practical insights for designing and promoting smart elderly care services, emphasizing the importance of usability and social promotion to enhance the quality of life for the elderly.
The current examines the influence of Islamic values on smoking behaviors among undergraduate students at Yarmouk University in Irbid, Jordan (N: 334). Tobacco use, in religious and cultural terms, is viewed as abhorrent; it is a significant concern for this population group. The study intends to identify how Islamic values affect the perception of students on smoking and, consequently, their smoking behavior. A self-administered questionnaire assessed sociodemographic data and the past 30 days of cigarette use. Descriptive statistics, such as frequencies and percentages, midpoint and standard deviation, and inferential statistics, such as chi-square tests, t-tests, ANOVA, Pearson correlation, and hierarchical regression, were used to analyze smoking behaviors, Islamic values, and demographic attributes. The study shows that Islamic values have a strong negative attitude towards smoking; students attributed smoking to religion, family and social expectations and perceptions, health and economic implications. Further, the hierarchical regression analysis revealed that cigarette use, hookah and e-cigarette, gender, and attitude towards Islamic values were suitable predictors for cigarette use. This study advances knowledge regarding smoking behaviors from the cultural-religious perspective. It highlights the importance of historically and culturally informed gender-sensitive prevention programs that address smoking-related beliefs, attitudes, and practices. Collaboration with the Ministry of Health and media outlets to integrate Islamic values into public health campaigns can reduce smoking among university students by aligning cultural and religious beliefs with health messaging.
The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.
This study employed the theory of planned behavior to examine how green urban spaces influence walking behaviors, with a focus on Chongqing’s Jiefangbei Pedestrian Street. Using structural equation modelling to analyse survey data from 401 respondents, this study assessed the relationships between attitudes, subjective norms, perceived behavioral control, walking intentions, and actions. The results revealed that attitudes toward walking (β = 0.335, p < 0.001) and subjective norms (β = 0.221, p < 0.001) significantly predict walking intentions, which strongly determine actual walking behavior (β = 0.379, p < 0.001). Moreover, perceived behavioral control exerts a direct significant impact on walking actions (β = 0.332, p < 0.001), illustrating that both environmental and social factors are crucial in promoting pedestrian activity. These findings suggest that enhancing the appeal and accessibility of urban green spaces can significantly encourage walking, providing valuable insights for urban planning and public health policy. This study can guide city planners and health professionals in creating more walkable and health-conducive urban environments.
Sports competition is one of the important contents and forms of sports activities and physical education. It plays a full range of valuable functions in promoting the all-round development of college students. Specifically, it can better help college students enjoy fun, enhance their physique, and improve their physical fitness during physical exercise. Personality and tempering the will. Countries around the world attach great importance to youth sports competitions, and use national strategies as the top-level design and sports events as activity carriers to create a series of youth sports competitions such as graded competitions, championships, and campus events, providing more opportunities for young people to watch and participate in sports. Opportunities and platforms for competition. College student sports competitions are an important part of youth sports competitions and shoulder multiple missions such as physical health promotion, competitive talent training, and sports industry development. In recent years, the development of college sports competitions around the world has achieved remarkable results, and the scale and quality of Chinese college sports competitions have also been significantly improved. However, compared with developed countries, overall, there is still a weak awareness of participation, poor competition experience, and competitive competition. Prominent problems such as low levels and high activity withdrawal rates have, to a certain extent, restricted the high-quality development of college student sports competitions. In fact, it is not as easy as imagined for college students to participate in sports competitions regularly for a long time. In addition to requiring college students to possess certain basic conditions such as time, energy, and skills, it also requires support and promotion from all walks of life, especially It is inseparable from the material, spiritual and technical support provided by family, friends, coaches and other important groups. Just as the social ecological model believes that individual physical activity behavior is closely related to social support at the interpersonal level, especially social support from important groups such as family and friends has a positive impact on individual physical activity behavior. At the same time, although social support is very important, not all social support received can promote college students to form good sports competition behaviors. Self-determination theory emphasizes that only effective social support can regulate and optimize individual sports motivation by meeting the individual’s basic psychological needs, and ultimately promote the formation of positive, long-term sports behavior. However, most of the current sports academic circles continue the research context of traditional college student sports management, focusing on the contemporary value, practical issues, system construction, etc. of college student sports competitions. They are more subjective qualitative theoretical research and relatively lack the influence of social support. Empirical research on the sports competition behavior of college students, so that the internal mechanism of social support affecting the sports competition behavior of college students is not clear enough and understood. Therefore, from the perspective of social ecology, this study explores the internal mechanism of social support affecting college students’ sports competition behavior, in order to provide certain theoretical reference for improving the level of college students’ sports competition behavior.
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