Knowledge, attitudes and practices towards COVID-19 among multiethnic elderly Asian residents in Singapore: a mixed-methods study

Adherence to COVID-19 measures and the associated factors: evidence from a two-wave longitudinal study in Singapore

BACKGROUND

At the onset of the Coronavirus disease (COVID-19) pandemic when pharmaceutical interventions were not readily available, governments relied on public health mandates and social distancing measures to counter rising infection rates. In order to address the dearth of longitudinal studies, this study sought to identify factors associated with continued adherence to COVID-19 preventive behaviours in Singapore.

METHODS

Data were from a two-wave longitudinal cohort study; baseline study was conducted from May 2020 to June 2021 and follow-up study from October 2021 to September 2022. Participants (n = 858) were Singapore residents, aged 18 and above, and able to speak English, Chinese or Malay. Weighted multivariable logistic regressions were conducted to identify factors associated with adherence to the COVID-19 measures.

RESULTS

Adherence rates of 'avoid dining out', 'crowded places', 'people with flu symptoms' and 'small group gatherings' at baseline were 39.41%, 60.82%, 79.82%, and 44.82% respectively. All measures had a decrease in adherence rates across the two-waves. Older age groups were associated with greater adherence to 'avoid dining out' and 'avoid crowded places'. Having high trust in local public health experts was associated with greater adherence to 'avoid crowded places' and 'avoid people with flu symptoms'. Fear of family and friends getting infected with COVID-19 was associated with 'avoid dining out' and 'avoid crowded places'.

CONCLUSIONS

Soft interventions like nudges can be implemented at crowded places to remind the public of the ease of transmitting the virus to their loved ones. Increasing media presence of public health experts can be a viable alternative to improve adherence.

Diverse pathways to permanent childlessness in Singapore: A latent class analysis

The proportions of adults reaching midlife without having children have been rising rapidly across the globe, particularly in Asia. However, little is known about the pathways to permanent childlessness within the region's childless population. This study utilized latent class analysis (LCA) to typologize pathways to childlessness based on dynamic characteristics of multiple life domains (i.e., partnership, education, and occupation) among 489 childless Singaporeans aged 50 and above from a 2022 nationwide survey. Additionally, we utilized multinomial logistic regressions to examine the sociodemographic correlates of pathway profiles and Shannon's entropy index to assess the heterogeneity in pathways to childlessness among successive cohorts. Results revealed five distinct profiles of pathways to childlessness: the Never-Married Semi-Professionals, the Low-Flex Blue-Collars, the Highly Educated Professionals, the Ever-Married Semi-Professionals, and the Flexible Blue-Collars. These pathway profiles were significantly associated with sociodemographic characteristics such as gender and family background. Women's pathways to childlessness were more standardized and heavily influenced by partnership characteristics, compared to those of men. The childless from privileged family background were less likely to follow pathways characterized by disadvantageous education and occupational status. There were also rising trends of voluntary childlessness among married childless individuals and increasing heterogeneity in pathways to childlessness across successive birth cohorts. In sum, our findings are consistent with some of the predictions of the Second Demographic Transition theory, suggesting that Singapore may be experiencing a demographic transition characterized by rising childlessness, decoupling of marriage and childbearing, and de-standardization of the life course.

Using search trends to analyze web-based users' behavior profiles connected with COVID-19 in mainland China: infodemiology study based on hot words and Baidu Index

Background

Mainland China, the world's most populous region, experienced a large-scale coronavirus disease 2019 (COVID-19) outbreak in 2020 and 2021, respectively. Existing infodemiology studies have primarily concentrated on the prospective surveillance of confirmed cases or symptoms which met the criterion for investigators; nevertheless, the actual impact regarding COVID-19 on the public and subsequent attitudes of different groups towards the COVID-19 epidemic were neglected.

Methods

This study aimed to examine the public web-based search trends and behavior patterns related to COVID-19 outbreaks in mainland China by using hot words and Baidu Index (BI). The initial hot words (the high-frequency words on the Internet) and the epidemic data (2019/12/01-2021/11/30) were mined from infodemiology platforms. The final hot words table was established by two-rounds of hot words screening and double-level hot words classification. Temporal distribution and demographic portraits of COVID-19 were queried by search trends service supplied from BI to perform the correlation analysis. Further, we used the parameter estimation to quantitatively forecast the geographical distribution of COVID-19 in the future.

Results

The final English-Chinese bilingual table was established including six domains and 32 subordinate hot words. According to the temporal distribution of domains and subordinate hot words in 2020 and 2021, the peaks of searching subordinate hot words and COVID-19 outbreak periods had significant temporal correlation and the subordinate hot words in COVID-19 Related and Territory domains were reliable for COVID-19 surveillance. Gender distribution results showed that Territory domain (the male proportion: 67.69%; standard deviation (SD): 5.88%) and Symptoms/Symptom and Public Health (the female proportion: 57.95%, 56.61%; SD: 0, 9.06%) domains were searched more by male and female groups respectively. The results of age distribution of hot words showed that people aged 20-50 (middle-aged people) had a higher online search intensity, and the group of 20-29, 30-39 years old focused more on Media and Symptoms/Symptom (proportion: 45.43%, 51.66%; SD: 15.37%, 16.59%) domains respectively. Finally, based on frequency rankings of searching hot words and confirmed cases in Mainland China, the epidemic situation of provinces and Chinese administrative divisions were divided into 5 levels of early-warning regions. Central, East and South China regions would be impacted again by the COVID-19 in the future.