Skip to main content

ORIGINAL RESEARCH article

Front. Public Health, 07 March 2024
Sec. Aging and Public Health

Public perception on active aging after COVID-19: an unsupervised machine learning analysis of 44,343 posts

\r\nPeipei ChenPeipei ChenYuwei JinYuwei JinXinfang MaXinfang MaYan Lin
Yan Lin*
  • School of Foreign Language Studies, Wenzhou Medical University, Wenzhou, Zhejiang, China

Introduction: To analyze public perceptions of active aging in China on mainstream social media platforms to determine whether the “14th Five Year Plan for the Development of the Aging Career and Older Adult Care System” issued by the CPC in 2022 has fully addressed public needs.

Methods: The original tweets posted on Weibo between January 1, 2020, and June 30, 2022, containing the words “aging” or “old age” were extracted. A bidirectional encoder representation from transformers (BERT)-based model was used to generate themes related to this perception. A qualitative thematic analysis and an independent review of the theme labels were conducted by the researchers.

Results: The findings indicate that public perceptions revolved around four themes: (1) health prevention and protection, (2) convenient living environments, (3) cognitive health and social integration, and (4) protecting the rights and interests of the older adult.

Discussion: Our study found that although the Plan aligns with most of these themes, it lacks clear planning for financial security and marital life.

1 Introduction

According to China's seventh population census in 2020, there are now 264 million older Chinese adults, representing 18.7% of the population. By 2025, the population of China's older adults is expected to exceed 500 million, representing 38.81% of the total population, with over 10% of the population being over the age of 80 (1). The government, society, and individuals all face the crucial task of mitigating the negative impacts of an aging society and enhancing the social value of older adults. To address this challenge, the World Health Organization introduced the concept of “active aging” as a means to optimize health, social participation, and security to enhance the quality of life as people age (2). Active aging emphasizes not only the absence of disease or disability but also the ability to maintain physical and mental wellbeing, engage in social activities, and continue to contribute to society (3, 4). Unlike previous aging ideals such as “healthy aging,” active aging recognizes the pivotal role that social involvement plays in the lives of older individuals as they age (5).

In this context, the CPC Central Committee and the State Council released “The 14th Five-Year Plan for the Development of the National Aging Career and Older Adult Care System” (2022), which provides guidelines for actively responding to aging populations. These priorities include (1) improving older adult care services; (2) improving support systems; (3) developing multiple business models; (4) strengthening security capabilities; and (5) creating an age-friendly environment.

However, the COVID-19 pandemic has significantly altered public perceptions of aging, particularly among older adults, causing many of them to reevaluate their understanding of a fulfilling life. As a result of social distance, many older adults have become more dependent on their families, making communal living a difficult choice (6). Furthermore, social media has become a valuable tool for seniors to combat feelings of isolation and a lack of social support (7). In light of this, older adults are increasingly embracing a digital lifestyle and adapting their views on aging. To gain a better understanding of the public's perception of active aging, a study was conducted analyzing conversations about aging on mainstream Chinese social media platforms. Through BERT-based text topic mining analysis and qualitative thematic analysis, we identified key concerns related to active aging as discussed by the Chinese public. By comparing them to the priorities set forth in the Plan, we aim to improve the effectiveness of active aging policies by bridging the gap between public perception and government initiatives.

2 Materials and methods

The data for this study is collected from Sina Weibo, one of the most popular social media platforms in China with over 500 million registered users and around 200 million monthly active users in 2023. Tweets containing the following keywords (“aging” or “old age” or “active aging” or “healthy aging”) between January 1, 2020 and June 30, 2022. In order to focus on original tweets posted by individuals, we pre-processed the data by removing duplicate comments, noisy data, organizational tweets, and irrelevant comments. The final dataset for this study was 44,343.

In this study, we utilized a bidirectional encoder representation from transformers (BERT)-based model. A widely recognized state-of-the-art deep machine learning approach for natural language processing (NLP), BERT employs unsupervised masked language models (MLM) and the next sentence prediction (NSP) for text deep pretraining and fine-tuning (8). This algorithm has demonstrated impressive performance in multiple NLP tasks, including machine reading comprehension and sentiment analysis (9). MLM involves randomly masking or replacing certain words or phrases in a sentence, and predicting the words that are missing. NSP, on the other hand, trains the model to determine the contextual relationship between two randomly presented sentences. In contrast to traditional word embedding techniques such as Word2Vec or Glove, BERT takes into account each word's contextual significance and the varying meanings of expressions in different contexts. As its name suggests, BERTopic is a topic modeling algorithm that generates topic clusters using BERT word vectors, Transformer, and c-TF-IDF (10). In this method, the topics are explained clearly while preserving the important words in the topic descriptions. We selected BERTopic for our study because existing studies have demonstrated BERTopic to be significantly more effective than traditional topic models such as LDA when it comes to depth of topic words, specialization, clear-inter-word relationships, and retention of contextual semantic information (11, 12).

For this study, we used the Chinese pre-training model provided by BERT and integrated it into our own text classification system. The BERT model was called using the BERT-as-service open-source service provided by Tencent AI Lab. This allowed us to convert microblog posts into 768-dimensional sentence vectors and extract the topics for the analysis of the later text. The researchers conducted a qualitative thematic analysis, independently reviewing labels and themes. They familiarized themselves with keywords and sample tweets, customized and refined themes, and sought consensus on coding through group discussions.

3 Results

Data were collected from 287,942 original tweets containing keywords such as “aging” or “old age” or “healthy aging” or “active aging” posted on Weibo between January 1, 2020 and June 30, 2022. After removing duplicate posts as well as tweets by organizations, the study included a final total of 44,343 posts.

Figure 1 displays the annual distribution of posts, revealing a consistent focus on “aging” and related subjects on Weibo throughout the years 2020 to 2022. This phenomenon aligns with the present circumstances, considering the disproportionate impact of COVID-19 on older adult populations since its emergence in December 2019.

Figure 1
www.frontiersin.org

Figure 1. Tweet count by year.

The current study generated 20 prominent topics related to the public views regarding health and aging issues (Table 1). The most prominent topic, Topic 1, focused on COVID-19 confirmation and infection. To analyze the data, the researchers manually grouped the topics into four main themes using thematic analysis. This process involved individual familiarization with the data, theme generation and review, and naming of the themes during offline meetings (13, 14).

Table 1
www.frontiersin.org

Table 1. Themes related to public perceptions of active aging, along with the respective topics and sample tweets (N = 44,343).

According to Table 1, theme 1 (health prevention and protection) holds the highest prevalence, accounting for 20.23% of the total. Among the topics within this theme, topic 1 (COVID-19 prevention) is the most prominent, representing 12.13% of the total, while topic 4 (maintaining healthy skin) has the lowest share at 0.5%. The second most prominent theme is Theme 4 (the rights and interests of the older adult), comprising 10.3% of the total. Within this theme, topic 6 (fertility policy adjustment) stands out the most prominent, accounting for 5.2%, while topic 14 (inheritance and post mortem arrangements) ranks the least prominent at 0.6%. Theme 2 (a safe and convenient living environment) has a prevalence of 6.3%, with topic 19 (living convenience) being the most prominent at 3.8% and topic 18/12 (eating convenience, wandering prevention) both the least prominent at 0.6%. Theme 3 (cognitive health and social integration) has a prevalence of 8.3%. Topic 13 (retirement life) emerges as the most prominent topic within this theme, representing 3.4% of the total. Conversely, topic 11 (maintaining cognitive and mental health) ranks the least prominent, accounting for only 0.8%.

In addition to topic 1, the survey also identified three other prominent topics that have sparked considerable public discussions. These topics include topic 16 (fertility policy adjustment, accounting for 5.2% of the discussion), topic 19 (living convenience, accounting for 3.8% of the discussion), and topic 13 (retirement life, accounting for 3.4% of the discussion). Interestingly, topics that were traditionally considered to be of greater concern to Chinese seniors, such as topic 18 (eating convenience), received relatively less attention in this survey, only accounting for 0.8% of the discussion.

4 Discussion

In our study, unsupervised machine learning was employed to analyze a total of 44,343 posts from a major social media platform. And arising 20 broad topics were further categorized into four themes through thematic analysis. These four themes are health prevention and protection, a safe and convenient living environment, cognitive health and social integration; and the rights and interests of the older adult (as shown in Figure 2).

Figure 2
www.frontiersin.org

Figure 2. Classification of themes and topics uncovered in the current study (percentages represent the prevalence of the individual topics).

Health prevention and protection (theme 1) is of utmost importance for the older adult population, especially during and after the COVID-19 epidemic. It is worth noting that the average age of COVID-19-related deaths in China was 80.3 years, with a significant proportion of the population being 65 years or older (90.1%), and 80 years or older (56.5%) (15). This study, conducted from January 2020 to June 2023, observed a consistent public interest in COVID-19 prevention (Topic 1), which aligns with the current social conditions. Additionally, the remaining topics within this theme emphasize the importance of enabling older individuals to maintain normal physical function, which is crucial for their active engagement in society as outlined in the Plan. This includes addressing various aspects of health, such as sleep quality (Topic 5), cancer prevention (Topic 3), hearing impairment (Topic 10), bone health (Topic 9), and skin health (Topic 4). These areas play a significant role in older people's sense of self-worth and independence (16).

Specifically, sleep quality (Topic 5) and cancer prevention (Topic 3) have received substantial attention. Previous studies have highlighted that poor sleep quality in older adults can have detrimental effects on cognitive function (17), increase the risk of neurological and psychiatric disease (18), and contribute to social isolation and feelings of loneliness (19). Notably, sleep disorders are highly prevalent among Chinese older adults in both rural and urban areas (20, 21). As to cancer prevention, it has always been a top priority for the Chinese government to promote a healthy and active aging society. To reduce the burden of cancer, collaborative efforts from various sectors have been implemented to mitigate factors such as environmental pollution, tobacco use, occupational carcinogens, excessive alcohol consumption, dietary deficiencies, and obesity (22, 23).

Themes 2 focuses on promoting a safe and convenient living environment. This aligns perfectly with the goals of creating an active and livable aging environment. Living and eating convenience (Topic 19 and Topic 18) are in line with the requirements of the Plan. Additionally, the prevention of wandering and hazards at home (Topic 12 and Topic 17) is essential for family care, especially considering that older adults are more susceptible to issues such as declining muscle strength and reduced adaptability to environmental changes (24). However, it is worth noting that Chinese households generally lack the necessary assistive technologies (25) to effectively prevent falls, wondering, and accidents (26, 27).

The importance of cognitive health and social integration (theme 3) for active aging cannot be overstated enough. An active and healthy social integration (Topic 16) and a well-planned retirement life (Topic 13) contribute to good physical, psychological, and cognitive wellbeing in seniors (28, 29). There is increasing public awareness in this area, as it has been proven to enhance the overall wellbeing and life expectancy of older adults (30). However, contemporary older adults in China faces a new set of challenges that are distinct from traditional ones. These challenges include the consequences of the two-child policy and the substantial financial losses caused by financial fraud (31). Senior citizens' universities (Topic 15) have also become a hot topic of discussion on social media. With over 70,000 senior colleges in China, these institutions provide gerontological education and cater to the diverse spiritual and cultural needs of the older adult population. They offer a wide range of educational resources, alleviating the pressure of population aging and achieving the goal of “learning and enjoyment for the older adult” (32) as set in the Plan for active aging.

The Plan focuses on improving the support systems to safeguard the rights and interests of the older adult (theme 4). It acknowledges the importance of healthcare services (Topic 20 Medical companion) in promoting healthy aging, such as establishing family hospital beds and facilitating home visits. However, our analysis reveals that the public's needs encompass a broader range of concerns beyond medical care. These include adapting to the negative impact brought by fertility policy adjustment (topic 6), ensuring financial security (topic 2 scam prevention), addressing marital life issues (topic 8 marriage), and managing inheritance and post-mortem arrangements (topic 14).

The Chinese government has recently relaxed its birth control policy, allowing couples to have two or three children instead of the previous limit of one. This adjustment reflects a change in their fertility policy. However, our survey has revealed a significant amount of attention on social media (2,309 posts, 5.2%) toward the negative impact of this policy change on older adults, yet it has not been adequately addressed in the Plan. Due to Confucian family culture, Chinese older adults often take on the role of providing intergenerational care for their grandchildren, a practice that is nearly 10 times more prevalent compared to South Korea (33). While some studies suggest that intergenerational caregiving can have positive effects on older adults' physical and mental health (34, 35), it is generally acknowledged that excessive intergenerational caregiving can result in increased physical exhaustion (36), a higher risk of mental and physical ailments (37), and a decrease in socialization opportunities (38).

Thus, we believe that the Chinese government should address the societal perception that raising a second child is a burden, particularly for grandparents, by transforming child-rearing support into a welfare system. To achieve this, they can draw inspiration from European countries' childcare welfare systems, such as the UK's “Specified Adult Childcare credits,” “Major New Extensions of Shared Parental Leave,” and “Tax-free Children” (39). Additionally, the government should increase fiscal investment and lower the age limit for children entering kindergartens (40). By implementing these policies, grandparents would receive necessary support, thereby reducing their long-term responsibilities in caring for their grandchildren and alleviating the pressure on families.

Moreover, the government should address two other pressing issues concerning the wellbeing of older individuals: their financial security (Topic 2) and their marriages (Topic 8). In China, Internet scams have become the main form of fraud, with older adults being the primary victims of this crime due to their limited ability to discern online information and lack of immediate assistance (41, 42). Surprisingly, the Plan appears to overlook any specific initiatives aimed at safeguarding the financial assets of older people. Existing research indicates a direct correlation between the level of family contact, the prevalence of depression, and the vulnerability to deception among older adults (31, 42). Therefore, it is crucial for families to enhance their companionship with relatives of older adults, for the government to promote financial literacy and anti-fraud measures to enhance older people's fraud awareness, and for financial institutions to develop tailored financial products that help the older adult rationally plan for retirement finances (42).

Furthermore, older adults often encounter intricate challenges in their marital lives due to various factors such as financial constraints and social pressures. The loss of a spouse, known as widowhood, is a common struggle that can result in physical health deterioration, increased mortality rates, and psychological symptoms like depression and anxiety (43). Remarriage can be an effective way to restore the benefits of a marital relationship (44). However, in Chinese society, remarriages are often influenced by financial considerations, societal opinions, age-related issues, and inheritance matters. As older individuals seek solutions to address their feelings of spiritual emptiness and inheritance problems, non-traditional forms of remarriages, such as “cohabitation without marriage” and “contract marriage,” emerged. This social phenomenon has generated discussions on mainstream social media in China, yet there are currently no specific plans or measures in place to safeguard older people's marriages.

Given the increasing prevalence of non-marital cohabitation, it would be wise for the Chinese government to enhance the existing marriage law system by incorporating elements from the legislative model of the foreign non-marital cohabitation system (45). Additionally, the establishment of a contractual system for non-marital cohabitation (46) could be put in place. By doing so, a comprehensive legal framework can be established to address these dynamics and provide a foundation for safeguarding the interests of both partners and their offspring, while also ensuring the protection of the more vulnerable party involved.

5 Conclusion

In conclusion, this study analyzed the key public perceptions of active aging, as represented by Weibo users from January 1, 2020, to June 30, 2022, to see if the “14th Five Year Plan for the Development of the Aging Career and Older Adult Care System” issued by the CPC in 2022 has fully addressed public needs. The research findings show that the Pan for active aging appears to align well with the future objectives and work priorities, as it covers many prominent topics of public concern. However, there are certain topics that have not been adequately addressed in the Plan, such as fertility policy adjustment, financial security, social integration, and marital life. These topics have gained public attention, indicating that the concerns of older adults in China have expanded beyond basic healthcare and daily life needs. They now encompass a broader and more complex range of psychological and social needs. In line with these findings, it is important for future government efforts to prioritize not only the existing topics in the Plan but also consider additional areas such as fertility policy adjustment, financial security, marital life, and social integration. These findings may provide the government and organizations with valuable insights for better active-aging initiatives.

6 Limitations and future work

However, it is important to consider the limitations of this study. Firstly, the findings may not be representative of the entire population as they primarily reflect the views of the Chinese public expressed on Weibo, a major social platform, but not the only one. It is important to include perspectives from other platforms such as TikTok, an emerging micro-video sharing app that has gained popularity among older adults. Future research should aim to capture and analyze the voices of the aging population on TikTok thus providing a more comprehensive understanding of their perceptions. Secondly, participation on Weibo requires a certain level of literacy, which means that illiterate older adults may be excluded from expressing their opinions on this social platform. To overcome this limitation, future researchers could consider incorporating methods such as surveys and interviews to obtain the perceptions of older adults who may not be active on social media platforms. By combining multiple data sources, researchers can strive for multiple verifications of their research findings. Last, it is worth noting that some tweets seemed to be advertisements or product placements, which may have influenced the accuracy of the findings. Although we excluded organizational tweets, we couldn't exclude individual tweets promoting products for commercial gain. Future research could explore additional techniques, such as Zipf's law (47) to reduce statistic noise and improve accuracy. Additionally, novel topic modeling approaches like GPT 4.0 and WuDao 2.0 could be employed to further improve the analysis.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

PC: Writing – original draft, Writing – review & editing. YJ: Conceptualization, Investigation, Writing – review & editing. XM: Software, Writing – review & editing. YL: Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was supported by 2023 Wenzhou Philosophy and Social Science Planning Annual Project (23WSK121YBM) and 2021 The Educational Science Planning Project of Zhejiang Province (2021SCG166).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. World Population Prospects 2022 Online Edition. Population (2022). Available online at: https://population.un.org/wpp/ (accessed August 12, 2023).

Google Scholar

2. World Health Organization [WHO]. Active ageing: a policy framework. Aging Male. (2002). 5:1–37. doi: 10.1080/tam.5.1.1.37

Crossref Full Text | Google Scholar

3. Cosco TD, Howse KR, Brayne C. Healthy ageing, resilience and wellbeing. Epidemiol Psychiatr Sci. (2017) 26:579–83. doi: 10.1017/S2045796017000324

PubMed Abstract | Crossref Full Text | Google Scholar

4. Walker A. A strategy for active ageing. Labor. (2002) 246:118. doi: 10.1111/1468-246X.00118

Crossref Full Text | Google Scholar

5. Lin K, Ning Y, Mumtaz A, Li H. Exploring the relationships between four aging ideals: a bibliometric study. Front Public Health. (2022) 9:762591. doi: 10.3389/fpubh.2021.762591

PubMed Abstract | Crossref Full Text | Google Scholar

6. Manli Y. Research on Emergency Policies of Home-based Elderly Care Services in Shanghai Community Based on Epidemic Prevention and Control. Beijing: China National Conditions and Strength (2022). p. 56–60.

Google Scholar

7. Martínez-Alcalá CI, Rosales-Lagarde A, Pérez-Pérez YM, Lopez-Noguerola JS, Bautista-Díaz ML, Agis-Juarez RA. The effects of COVID-19 on the digital literacy of the elderly: norms for digital inclusion. Front Educ. (2021) 6:716025. doi: 10.3389/feduc.2021.716025

Crossref Full Text | Google Scholar

8. Ng QX, Lim SR, Yau CE, Liew TM. Examining the prevailing negative sentiments related to COVID-19 vaccination: unsupervised deep learning of twitter posts over a 16 month period. Vaccines. (2022) 10:91457. doi: 10.3390/vaccines10091457

PubMed Abstract | Crossref Full Text | Google Scholar

9. Devlin J, Chang MW, Lee K, Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. North American Chapter of the Association for Computational Linguistics (2019).

Google Scholar

10. Grootendorst MR. BERTopic: neural topic modeling with a class-based TF-IDF procedure. ArXiv. (2022). doi: 10.48550/arXiv.2203.05794

Crossref Full Text | Google Scholar

11. Egger R, Yu J. A topic modeling comparison between LDA, NMF, Top2Vec, and BERTopic to demystify twitter posts. Front Sociol. (2022) 7:886498. doi: 10.3389/fsoc.2022.886498

PubMed Abstract | Crossref Full Text | Google Scholar

12. Guangqing T, Yao J, Rui T. Comparative study on domain knowledge evolution based on multiple data source dimensions: taking graphene field research in the United States as an example. Inform Document Serv. (2023) 44:61–70. doi: 10.12154/j.qbzlgz.2023.06.007

Crossref Full Text | Google Scholar

13. Clarke V, Braun V. Successful qualitative research: A practical guide for beginners. London: Sage (2013). p. 382.

Google Scholar

14. Kiger ME, Varpio L. Thematic analysis of qualitative data: AMEE Guide No. 131. Medical Teacher. (2020) 42:846–54. doi: 10.1080/0142159X.2020.1755030

PubMed Abstract | Crossref Full Text | Google Scholar

15. Feng P. Elderly people are a priority population for protection against new coronavirus infections. China Medical Herald. (2023) 20:1–3.

Google Scholar

16. Adams KE, Tyler JM, Calogero RM, Lee J. Exploring the relationship between appearance-contingent self-worth and self-esteem: the roles of self-objectification and appearance anxiety. Body Image. (2017) 23:176–82. doi: 10.1016/j.bodyim.2017.10.004

PubMed Abstract | Crossref Full Text | Google Scholar

17. Casagrande M, Forte G, Favieri F, Corbo I. Sleep quality and aging: a systematic review on healthy older people, mild cognitive impairment and Alzheimer's disease. Int J Environ Res Public Health. (2022) 19:148457. doi: 10.3390/ijerph19148457

PubMed Abstract | Crossref Full Text | Google Scholar

18. Amorim L, Magalhães R, Coelho A, Moreira PS, Portugal-Nunes C, Castanho TC, et al. Poor sleep quality associates with decreased functional and structural brain connectivity in normative aging: a MRI multimodal approach. Front Aging Neurosci. (2018) 10:375. doi: 10.3389/fnagi.2018.00375

PubMed Abstract | Crossref Full Text | Google Scholar

19. Yu B, Steptoe A, Niu K, Ku P-W, Chen L-J. Prospective associations of social isolation and loneliness with poor sleep quality in older adults. Qual Life Res. (2018) 27:683–91. doi: 10.1007/s11136-017-1752-9

PubMed Abstract | Crossref Full Text | Google Scholar

20. Luo J, Zhu GX, Zhao Q, Guo Q, Meng H, Hong Z, et al. Prevalence and risk factors of poor sleep quality among Chinese elderly in an urban community: results from the Shanghai Aging Study. PLoS ONE. (2013) 8:1261. doi: 10.1371/journal.pone.0081261

PubMed Abstract | Crossref Full Text | Google Scholar

21. Wang P, Song L, Wang K, Han X, Cong L, Wang Y, et al. Prevalence and associated factors of poor sleep quality among Chinese older adults living in a rural area: a population-based study. Aging Clin Exp Res. (2019) 32:125–31. doi: 10.1007/s40520-019-01171-0

PubMed Abstract | Crossref Full Text | Google Scholar

22. Bode AM, Dong Z, Wang H. Cancer prevention and control: alarming challenges in China. Natl Sci Rev. (2016) 31:117–27. doi: 10.1093/nsr/nwv054

PubMed Abstract | Crossref Full Text | Google Scholar

23. Sun D, Li H, Cao M, He S, Lei L, Peng J, et al. Cancer burden in China: trends, risk factors and prevention. Cancer Biol Med. (2020) 17:879–95. doi: 10.20892/j.issn.2095-3941.2020.0387

PubMed Abstract | Crossref Full Text | Google Scholar

24. Rodrigues F, Monteiro AM, Forte P, Morouço P. Effects of muscle strength, agility, and fear of falling on risk of falling in older adults. Int J Environ Res Public Health. (2023) 20:4945. doi: 10.3390/ijerph20064945

PubMed Abstract | Crossref Full Text | Google Scholar

25. Brims L, Oliver K. Effectiveness of assistive technology in improving the safety of people with dementia: a systematic review and meta-analysis. Aging Ment Health. (2019) 23:942–51. doi: 10.1080/13607863.2018.1455805

PubMed Abstract | Crossref Full Text | Google Scholar

26. Baichuan R, Chen X. Design of intelligent anti-fall monitoring system based on Bluetooth. Laser J. (2019) 40:32–4. doi: 10.14016/j.cnki.jgzz.2019.07.032

Crossref Full Text | Google Scholar

27. Shuai L, Yi W, Zhiwen W, Hui Z, Shuangyue T, Liyue L. Investigation on the current situation of home environment security of elderly people with dementia. Chin Nurs Manag. (2019) 19:1860–4. doi: 10.3969/j.issn.1672-1756.2019.12.020

Crossref Full Text | Google Scholar

28. Roosa L, Mikhail S, Jaana P, Jussi V, Sari S. Physical activity and self-rated health during retirement transition: a multitrajectory analysis of concurrent changes among public sector employees. Br Med J Open. (2023) 13:73876. doi: 10.1136/bmjopen-2023-073876

PubMed Abstract | Crossref Full Text | Google Scholar

29. Sarabia-Cobo CM, Pérez V, Hermosilla C, de Lorena P. Retirement or no retirement? The decision's effects on cognitive functioning, well-being, and quality of life. Behav Sci. (2020) 10:151. doi: 10.3390/bs10100151

PubMed Abstract | Crossref Full Text | Google Scholar

30. Crawford R. Healthism and the medicalization of everyday life. Int J Health Ser. (1980) 10:365–88. doi: 10.2190/3H2H-3XJN-3KAY-G9NY

PubMed Abstract | Crossref Full Text | Google Scholar

31. Yuan-yuan L, Cheng-yun S. Study on the influencing factors of financial fraud of middle-aged and elderly people in China: an empirical analysis based on CHARLS 2015. South China Popul. (2020) 35:13–26.

Google Scholar

32. Qiu J, Liu D, Liu Z. Practice and exploration of composite space design for senior citizens' universities—a case study of park spring senior citizens' university renovation. BCP Soc Sci Human. (2022) 2022:992. doi: 10.54691/bcpssh.v18i.992

Crossref Full Text | Google Scholar

33. Ko P-C, Hank K. Grandparents caring for grandchildren in China and Korea: findings from CHARLS and KLoSA. J Gerontol Ser B. (2013) 69:646–51. doi: 10.1093/geronb/gbt129

PubMed Abstract | Crossref Full Text | Google Scholar

34. Notter IR. Grandchild care and well-being: gender differences in mental health effects of caregiving grandparents. J Gerontol Ser B. (2021) 77:1294–304. doi: 10.1093/geronb/gbab164

PubMed Abstract | Crossref Full Text | Google Scholar

35. Yan X, Wu W, Chen X, Xu G, Yu S, Li S. Intergenerational caregiving on mental health of middle-aged and older adults in China: empirical insights. Front Public Health. (2023) 11:1224062. doi: 10.3389/fpubh.2023.1224062

PubMed Abstract | Crossref Full Text | Google Scholar

36. Sampaio D. Caring by silence: how (un)documented Brazilian migrants enact silence as a care practice for aging parents. J Intergener Relatsh. (2020) 18:1787038. doi: 10.1080/15350770.2020.1787038

Crossref Full Text | Google Scholar

37. Zeng Y, Chen YC, Lum TYS. Longitudinal impacts of grandparent caregiving on cognitive, mental, and physical health in China. Aging Ment Health. (2020) 25:2053–60. doi: 10.1080/13607863.2020.1856779

PubMed Abstract | Crossref Full Text | Google Scholar

38. Whitley DM, Kelley SJ, Sipe TA. Grandmothers raising grandchildren: are they at increased risk of health problems? Health Soc Work. (2001) 26:105–14. doi: 10.1093/hsw/26.2.105

PubMed Abstract | Crossref Full Text | Google Scholar

39. Yun Z, Zihan S. Research on policy support for grandparents in the United Kingdom population and society. Am Soc Rev. (2023) 39:36–50. doi: 10.1177/0003122413489130

Crossref Full Text | Google Scholar

40. Zhang G, Shi Y. Alternative care, delayed retirement and the realization of the second child in an all-round way. J Anshun Univ. (2021) 23:112–6. doi: 10.3969/j.issn.1673-9507.2021.04.023

Crossref Full Text | Google Scholar

41. Yuxi S, Zhongxian W, Xiaoyu D, Yanbin J, Beibei M, Meihong C. The psychology of the internet fraud victimization of older adults: a systematic review. Front Psychol. (2022) 13:912242. doi: 10.3389/fpsyg.2022.912242

Crossref Full Text | Google Scholar

42. Zhihong D, Weicheng W, Dong Z. Research on the impact mechanism of financial literacy overconfidence on financial fraud of urban elderly. Lanzhou Acad J. (2024) 4:104–15.

Google Scholar

43. Jadhav A, Weir D. Widowhood and depression in a cross-national perspective: evidence from the United States, Europe, Korea, and China. J Gerontol Ser B. (2017) 73:e143–53. doi: 10.1093/geronb/gbx021

PubMed Abstract | Crossref Full Text | Google Scholar

44. Ayoubi-Mahani S, Eghbali-Babadi M, Farajzadegan Z, Keshvari M, Farokhzadian J. Active aging needs from the perspectives of older adults and geriatric experts: a qualitative study. Front Public Health. (2023) 11:21761. doi: 10.3389/fpubh.2023.1121761

PubMed Abstract | Crossref Full Text | Google Scholar

45. Scherpe JM. The Changing Concept of “Family” and Challenges for Domestic Family Law (2016).

Google Scholar

46. Deng R, Shi Y, Zhang R, Feng T. Research on legal issues of women's rights and interests protection in non-marital cohabitation. J Human Arts Soc Sci. (2023) 1:21. doi: 10.26855/jhass.2023.01.021

Crossref Full Text | Google Scholar

47. Banks GC, Woznyj HM, Wesslen R, Ross RL. A review of best practice recommendations for text analysis in R (and a User-Friendly App). J Bus Psychol. (2018) 33:445–59. doi: 10.1007/s10869-017-9528-3

Crossref Full Text | Google Scholar

Keywords: active aging, public perception, topic modeling, BERTopic, policy making

Citation: Chen P, Jin Y, Ma X and Lin Y (2024) Public perception on active aging after COVID-19: an unsupervised machine learning analysis of 44,343 posts. Front. Public Health 12:1329704. doi: 10.3389/fpubh.2024.1329704

Received: 29 October 2023; Accepted: 27 February 2024;
Published: 07 March 2024.

Edited by:

Toni P. Miles, Rosalynn Carter Institute for Caregivers, United States

Reviewed by:

Chong Zhang, University of Electronic Science and Technology of China, China
Alexis B. Manrique Guzman, Private Technical University of Loja, Ecuador

Copyright © 2024 Chen, Jin, Ma and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yan Lin, bGlueSYjeDAwMDQwO3dtdS5lZHUuY24=

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.