ObjectivesTo identify factors influencing COVID-19 preventive behaviors among the Thai population.MethodsA cross-sectional web-based survey was used. A total of 6,521 Thai people completed the survey. The multiple linear regression analysis was performed to identify factors that influenced coronavirus disease 2019 (COVID-19) preventive behaviors. The Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation (PRECEDE) model was applied to propose factors influencing COVID-19 preventive behaviors.ResultsThe factors that mostly influenced COVID-19 prevention behaviors when controlling for the other variables are social support (β = 0.173, p < 0.001) follow by age (β = 0.162, p < 0.001), flu-like symptoms (β = 0.130, p < 0.001), gender (β = −0.084, p < 0.001), perceived risk of exposure (β = 0.035, p < 0.05), lock down policy (β = 0.029, p < 0.05), and residential area (β = −0.027, p < 0.05), respectively. These factors explained 52% of the COVID-19 preventive behaviors in Thai population.ConclusionThe result of this study was a foundation for further studies on different groups of people to develop different strategies to adopt preventive behaviors to reduce the spread of the COVID-19.

ObjectivesFace mask wearing is a standard preventive measure, in addition to handwashing and physical distancing. Individuals may find that wearing a face mask protects their physical health and prevents viral transmission. However, none of the studies in Thailand identified factors associated with face mask-wearing behaviors among Thai people. Therefore, this study aims to determine factors affecting face mask-wearing behaviors to prevent COVID-19.MethodsThis research is analytical survey research. The data used in this study were under the project title “The assessment of psychosocial and behavioral response and compliance to restriction measures to prevent and control COVID-19: A series of the rapid survey.” A total of 6,521 people participated in an online survey by multi-stage sampling. Bivariate logistic regression analysis was used to examine the factors associated with face mask-wearing behaviors.ResultsAfter adjusting for independent variables (i.e., gender, age, education, career, smoking, and comorbidity disease), the bivariate logistic regression analysis revealed that gender, age, and career were statistically significant to the face mask-wearing behaviors (p < 0.05). Level of education, smoking, and comorbidity disease were not statistically significant with face mask-wearing behaviors among Thai people.ConclusionFurther study should explore broader on individual face mask perceptions and wearing in the continuing of COVID-19 across gender, age, and careers to better understand their health behaviors and to inform further policy. In addition, the development of an intervention to promote face mask wearing should target men who age below 30 yrs. and did not work in government services careers as this group of the population was likely not to wear a face mask outside the home.

In Thailand, the elderly club is a public organization that plays an important role in developing the well-being of the elderly in the community. The aim of this study was to 1) examine the management of the elderly club and the characteristics of elderly well-being development activities, 2) investigate the management of the elderly club in developing elderly well-being, and 3) determine the factors affecting the successful management of the elderly clubs and the activities that improve well-being of the elderly. The employed research method was a form of phenomenological research, with data collection conducted via six focus group discussions and in-depth interviews. The participants were club committee members who met the inclusion criteria. Data was analyzed using the content analysis method and its reliability was verified by examining information against relevant literature, view of informants, and experts. Results found most of activities improving elderly well-being focused on health promotion and elder education. There were eight important factors affecting the successful management of the elderly club, i.e. competency of the leader and club committees, committee and member participation, regular activities, support from public health officers, financial self-reliance, external financial support, network partners, and social participation. The research also suggests five important factors affecting the activities that improve elderly well-being, i.e. external financial support, network partners, committee and member participation, social participation, and support from public health officers.

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Healthcare systems worldwide continue to face shortages of nursing professionals due to the increasing demands of the nursing field. At the same time, the existing workforce continues to age and retire (Aluttis et al., 2014;Sirisub et al., 2019). Thailand's demographic structure has changed into an ageing society (Rojpaisarnkit & Rodjarkpai, 2021). According to the United Nations' World Population Prospects 2019, the number of Thai senior citizens aged 65 or older will more than double from 9.0 million people, or 13.0 per cent of the total population in 2020, to 19.5 million people, or 29.6 per cent of the total population, by 2050. Furthermore, this figure is forecasted to reach 35.1 per cent by 2095 (Akaraphanth, 2015;Manakitsomboon, 2021), meaning one out of every three Thai people will be a senior citizen (Udomkerdmongkol, 2021). In addition, the number of older adults living alone appears to be increasing.For example, 8.7% of older adults lived alone in 2014, while older adults who lived alone increased to 12% in 2021 (Foundation of