Current Status and Associated Factors of Health Information Literacy Among the Community Elderly in Central China in the COVID-19 Pandemic: A Cross-Sectional Study

Introduction

The COVID-19 pandemic has profoundly impacted all aspects of society, including the mental and physical health of its residents.1–3 According to the Organisation for Economic Co-operation and Development (OECD), from March 2020 onwards, the prevalence of anxiety and depression increased and even doubled in some countries.4 Not only is there tremendous pressure on our health care system, but also the HIL of our old population is facing serious challenges.5 Good health information literacy could guide people to adopt scientific protection and choose medical measures, meanwhile, the correct health information awareness and health information behavior are particularly important and even life-relating during the epidemic.6,7

The Medical Library Association (MLA) defined Health information literacy (HIL) as a series of abilities that can help individuals identify health information needs, recognize possible information sources, use them to retrieve relevant information, assess the quality of information and its specific application scenarios, and make rational health decisions.8 It is the reflection of an individual’s ability to access, evaluate, and apply health information, and its level is related to the effectiveness of health education and the state of health engagement in a given region.9

According to the results of the seventh national census of China, the population of China aged 60 and above was 264.02 million (18.70%), and the proportion of the population aged 65 and above was 13.5%.10 At present, China has become the country with the largest elderly population with the fastest aging rate in the world.11 Previous studies found that the most important information needs of the elderly in their daily lives are health information needs because the elderly have a higher concern for health issues than other age populations.12,13 However, it is worth worrying that the elderly in both developed and developing countries have common dilemmas in understanding, identifying, accessing and using health information to solve health problems. Studies have reported that the elderly in both South Korea and the United States are used to accessing health-related information through medical staff and have lower usage of the Internet.14,15 Huvila et al found that the elderly have difficulties understanding health terms, drug packaging labels, and so on. When comparing information from multiple sources, it is difficult for them to determine their own health information needs.16 Mcnutt et al found that when faced with health-related decisions, elderly patients have to deal with a large amount of complex treatment information in a short time, which causes great stress.17 This indicates that the elderly, who are not skilled at analyzing and understanding health information, will be inflicted with a negative mood harming their mental health. During the pandemic of COVID-19, fewer opportunities to go outside reduce the accessibility of traditional means for older adults to obtain health information (eg, by borrowing health books, participating in community healthcare activities, or consulting medical staff at hospitals) and transfer to need to use the social media, such as television, cell phones, and the Internet.18,19 The elderly often do not provide the health knowledge needed to meet their needs because of their inadequate knowledge and use of information technology.20,21 On the other hand, the integration of digital applications into life has become a trend in response to national epidemic prevention and control normalization.22 While the Internet has granted unprecedented convenience and efficiency to people in modern times, the elderly have gradually become a marginal group in the Internet era because they cannot keep up with the rhythm of information updates—like “digital refugees” cut off from the rest of the world.23,24 Due to the distance between the elderly and digital technology, they cannot quickly keep up with the rhythm of information technology—for example, they have difficulties using health codes and Internet medical care.25–27 In the face of a huge amount of information on epidemics, improving HIL is key to ensuring that the elderly can effectively access, understand, analyze, screen, and correctly utilize epidemic information.28 Therefore, it has become an urgent social problem to understand the current situation of HIL among the community elderly and to study the path to improving this literacy among them.

In the literature, a number of studies have explored the status of HIL and its influence factors, and the targeted participants included the public, university students and the medical staff population,29–31 but less attention focused on the elderly of the community. Further, although nationwide surveys have conducted in China, information on specific regions remains limited. The major objective of this study was to assess the HIL levels of community elderly in Central China and identify the influence factors.

Materials and Methods Study Design

A descriptive cross-sectional design was used in a survey study conducted from April 2021 to July 2021.

Participants and Sample

After receiving ethical approval from Xiangnan University’s committee, six communities in Chenzhou, Central China, were first selected by random sampling. Then, we contacted the managers of these communities, all of whom expressed their willingness to participate in this study. They were, therefore, assigned as representatives of their communities and acted primarily as contractors and liaisons between the communities and our research team. Finally, a convenience sampling method was used to select 120 older adults aged 60 years and more from each community, who were surveyed using the Chinese residents’ HIL self-rated scale,28 and a self-made sociodemographic questionnaire. The participants were recruited by researchers and community workers based on a questionnaire distributed according to the following inclusion criteria: 1) be aged ≥ 60 years; exhibit consciousness and no language impairment; 3) have inhabited the community for at least one year; and 4) agree to participate in the study. The elderly who refused or were unable to cooperate with the researchers and withdrew in the middle were excluded. The sample size in this study using G * Power resulted in a required minimum sample size of 160 (effect size = 0.15; P = 0.05; Power = 0.95). Assuming a loss of 20% in the sample, the necessary sample size was determined to be at least 200 cases.

Survey Tools

The questionnaire employed in this study consisted of three parts: a general information questionnaire, the Chinese residents’ HIL self-rated scale, and the reliability evaluation form.

General Information

The general information questionnaire included age, gender, education, religion, annual family income, living arrangements, chronic disease status, and self-care ability.

The Chinese Residents’ HIL Self-Rating Scale

This scale was developed by Wang et al,32 was used to assess the HIL level of the elderly in the community and included the five dimensions of health information cognition (HIC), health information search (HIS), health information evaluation (HIE), health information application (HIA), and health information moral (HIM), which comprised 29 items and was scored on a 5-Likert scale (“very disagreed” = 1, “disagreed” =2, “unclear” =3, “agreed” =4, and “very agreed” =5 points), and a total score of 145 points. The overall Cronbach’s alpha coefficient of this scale was 0.847, and Cronbach’s alpha coefficient for the HIC, HIS, HIE, HIA and HIM sub-dimensions were 0.783, 0.917, 0.832, 0.874, and 0.872, respectively. The higher the score gained by the participants, the higher the level of HIC. The scale has good validity and reliability, with Cronbach’s alpha coefficient > 0.75.

Reliability Evaluation

A self-made reliability evaluation form was further used to evaluate common health information access sources. All investigators were required to receive training before they began their investigations. First, they obtained some basic health information about the elderly in the community, and after confirming who met the requirements of the study’s subjects, they explained the purpose of the survey, precautions, and the technique of filling out the questionnaire in detail. They also assured participants that their privacy would be protected. Some of the participants filled out the questionnaires by themselves on the spot, and the family members or investigators provided those who could not do so independently with the necessary assistance.

A total of 720 questionnaires were distributed. Subsequently, after removing 103 invalid questionnaires that contained continuous repetitions, regular answers, and logical contradictions, among others, 617 valid questionnaires were included in this study, which had an efficiency rate of 85.69% (617/720).

Statistical Analysis

Statistical data were analyzed using SPSS 23.0. Frequencies and percentages were used to describe the basic profile of the elderly in the community and to evaluate the reliability of various health information access channels. An independent two-sample t-test and analysis of variance (ANOVA) were used to test the differences between HIL and the demographic characteristics of the community elderly. This was followed by multiple linear regression to identify factors influencing HIL, and the significance level was set at 0.05 (two-sided) for all analyses.

Results Demographic Characteristics

The sample comprised 617 participants with an average age of 67.45 ± 10.06 years (range: 60–85 years); the majority of the participants were 60–70 years old (58.51%). Further, there were 302 males (48.95%) and 315 females (51.05%). More than two-thirds of the participants (63.86%) had been through middle or high school education, and over four-fifths of them (84.60%) had no religious beliefs. Nearly half of the annual family Income was around 30,000 to 50,000 RMB (49.27%). Almost half of the participants lived with their spouses (46.84%); more than half of the participants reported chronic diseases (58.51%), and nearly two-thirds of the participants had the ability to completely take care of themselves (64.34%). More demographic details are presented in Table 1.

Table 1 Demographic Characteristics of the Community Elderly (n=617)

Differences Between the HIL and the Community Elderly’s Demographics

In order to represent the results more intuitively, the scores of HIL were processed using the 100-point system. There were 519 people with HIL scores < 60, accounting for 84.12% (519/617). Additionally, among the remaining 98 people, the highest scores did not exceed 75, which shows that the overall level of HIL in the community elderly’s population in our city is low. Meanwhile, the HIC score (70.7 points) of the subjects in this study was higher than that of the other four dimensions: HIS (38.38 points), HIE (60.97 points), HIA (55.29 points), and HIM (58.0 points), among which the HIS score was the lowest.

After the t-test and ANOVA, the results show there are significant differences in the comparison of HIL total scores and 5 sub-dimensions scores among the community elderly with education, family income, living arrangements, and a chronic disease status (P < 0.05). And the elderly with an education level above senior high school, an annual family income > 50,000 yuan, living with children, or without chronic diseases achieved higher scores.

In the aspect of the sub-dimensions score, the bivariate analysis revealed that age and gender were correlated with HIC, HIS, HIE, and HIA dimensions and the total HIL score (P < 0.05), and who aged 60–70 years old or the female achieved high scores. It should be highlighted here that the comparison between the HIM dimension was the only exception, yielding no statistically significant difference (P > 0.05) (see Table 2).

Table 2 Differences Between the HIL and the Community Elderly’s Demographics

Multivariate Linear Regression Analysis of the Community Elderly

The results of the multiple linear regression analysis show that age, gender, education, annual family income, living arrangement, and chronic disease status were all associated factors for HIL among older adults in the community (P < 0.05), as shown in Table 3. (Independent variable assignment rule: age: 1=60–70 years old, 2=70–80 years old, 3≤80 years old; Gender: 1=male, 2=female; Education level: 1=primary school or below, 2=junior high school/senior high school, 3=senior high school or above; Annual family income: 1=less than 30,000 yuan, 2=3~50,000 yuan, 3=above 50,000 yuan; Living arrangement: 1=alone, 2=living with spouse, 3=living with children; Chronic diseases status: 1=yes, 2=no.)

Table 3 Multivariate Linear Regression Analysis of the Community Elderly

Reliability Evaluation of Common Health Information Access Sources

The values of respondents’ reliability evaluations are ranked from the highest to the lowest, in the following order: doctor consultations (90.28%), health-related TV programs (69.37%), family and friends (54.13%), books and newspapers (49.43%), the Internet (8.59%), and pharmaceutical advertisements (7.29%), as shown in Table 4.

Table 4 Reliability Evaluation of Common Health Information Access Sources (n/%)

Discussion

The results of this study show that the overall level of HIL in the community elderly population during the COVID-19 pandemic was low, with 84.12% of them scoring < 60, compare to another study using the same scale, which is below the 83.26% of the result obtained by Luo et. al,33 may be related to the difficulties of access reliable health information have increased because of the range of outdoor activities for the elderly is limited by the background of the COVID-19.

From the dimension perspective, the score of HIC of the elderly in the community is higher than their HIS, HIE, and HIA (70.7 points VS 38.38, 60.97, and 55.29 points). This is probably because they live in communities which have more opportunities to participate in traditional community activities and to learn about the importance of health information and its relation to the maintenance of health from this social participation, so they have developed good health information cognitive. However, they are not skilled at searching for health information from social media, and the limitation of their possibility to participate in outdoor activities because of the COVID-19 pandemic, and the exposure to health information reduced by older adults makes it more difficult to make appropriate health decisions. Meanwhile, a good ability to search for health information is contributed to making correct health evaluations and applications.34,35 Combined with the results of this study, the community elderly have the lowest score on HIS, we strongly recommend that the community should organize centralized health education programs targeting to teach how to use information technology to search for health-related information and to solve the difficulties encountered in the learning process face to face in time, and ensure the community elderly master the information acquisition ability. This is the basis to improve their evaluation and application abilities about health information, and beneficial to cultivate their ability to apply the health knowledge found on the Internet or social media to their self-management of health.

Our study showed that age, gender, education, annual family income, living arrangement, and chronic disease status were associated with the HIL level of the community elderly. Wang et al36 reported the highest HIL levels in low-age elderly (60–69 years), followed by the group of 70–79 years, and the lowest in >80 years, which is consistent with the results of our study. The possible explanation could be that as their age increases, their receptiveness and understanding of health information gradually decrease, and they do not have active memory and enough energy to learn and accept new knowledge and skill. Consequently, the ways of accessing health information become limited, resulting in a low level of HIL.37 This study found that women’s health knowledge level is higher than that of men of the same age (β= 0.296; P<0.001), which is consistent with the research results of Aponte et al.38 This may be related to the fact that women always play a caretaker role in the family and need to take care of daily affairs. Therefore, they may pay more attention to the health status of their families and tend to more actively obtain health information to promote their health management. The impact of educational level on HIL has been previously demonstrated, and participants with a higher level of education achieved higher HIL levels.39 The elderly who has received a good education show high ability in learning awareness, understanding and communication, they are more active and valid in acquiring health information through communication with the staff of community service centre and hospital and accordingly adjust bad behaviour during their daily lives. Furthermore, those with higher annual family incomes have more ways to access health information and are willing to take medical physician examinations regularly. This may result in them having a good HIL level.40,41 The elderly who live with their children are meticulously cared for by them and can broaden their access to health information through their children’s help. This living arrangement is good for developing a higher level of HIL.42,43 In addition, the community elderly with chronic diseases have reduced physical functions and are confronted with the difficulty of obtaining health information.44 On the one hand, elderly people should maintain an open and positive attitude, show initiative to find health information, and focus on their physician and mental health. On the other hand, their children and communities should also offer correct guidance to improve their HIL level, give support to them in their daily lives, help them strengthen their attention toward major public health emergencies, and assist them with taking preventive measures.

The results of this reliability evaluation show that 90.28% of the community elderly members believe consulting a doctor is a highly reliable way of acquiring health information. This reflects the fact that most elderly people regard doctors as a trustworthy source of health information, and the establishment of effective doctor-patient communication can enable patients to obtain more effective health information and meet their health needs. In addition, related studies have shown that the Internet, an important channel for disseminating health information in modern society, can contribute to the improvement of HIL.45,46 However, only 8.59% of older adults in this study considered the Internet reliable. This may be because of the lack of ability to identify the authenticity of information on the Internet among older adults which led most older adults to consider the Internet unreliable.47,48 This suggests that the benefits of Internet health services and developing risk-avoidance skills should be further promoted in the future.

Conclusion

In summary, the overall level of HIL among the elderly in the community in the context of COVID-19 is low. And low-age elderly who have higher education and annual family income tended to show good HIL levels. In our study, the elderly showed a low score in 3 aspects of HIS, HIE and HIA, therefore, it’s necessary to provide health education training based on information technology and targeted to strengthen their health information search, evaluation, and application skills to upgrade their HIL levels. This is of positive significance in terms of improving medical compliance, reducing treatment costs, relieving social medical pressure, and preparing for future responses to major public health emergencies.

Abbreviations

COVID-19, coronavirus disease 2019; HIL, health information literacy; HIC, health information cognition; HIS, health information search; HIE, health information evaluation; HIA, health information application; HIM, health information moral; MLA, Medical Library Association; OECD, Organization for Economic Cooperation and Development; ANOVA, analysis of variance.

Ethics Approval and Informed Consent

The study was conducted in strict accordance with the Helsinki Declaration. The study protocol was approved by the Ethics Committee of Xiangnan University. All participants who met the inclusion criteria received a questionnaire and provided informed consent. The questionnaires-maintained anonymity and described how confidentiality was ensured.

Acknowledgments

The authors would like to thank the support by the Subject of Hunan Provincial “14th Five-Year Plan” Education Science Research Key Cultivation Base (Lifelong Education Research Base (Basic Theoretical Direction)) (grant no. XJK22ZDJD58), the participants, all the researchers in the research team, and the staff of the communities.

Funding

This study was supported by the Subject of the Hunan Provincial Social Science Achievement Committee (grant no. XSP22YBC215) and the National-level College Student Innovation and Entrepreneurship Training Program (grant no. 202210545023).

Disclosure

The authors declare that they have no conflicts of interest in this work.

References

1. Torales J, O’Higgins M, Castaldelli-Maia JM, et al. The outbreak of COVID-19 coronavirus and its impact on global mental health. Int J Soc Psychiatry. 2020;66(4):317–320. doi:10.1177/0020764020915212

2. Holmes EA, O’Connor RC, Perry VH, et al. Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry. 2020;7(6):547–560. doi:10.1016/S2215-0366(20)30168-1

3. Bao Y, Sun Y, Meng S, et al. 2019-nCoV epidemic: address mental health care to empower society. Lancet. 2020;395(10224):e37–e38. doi:10.1016/S0140-6736(20)30309-3

4. Organisation for Economic Cooperation and Development. Tackling the mental health impact of the COVID-19 crisis: an integrated, whole-of-society response. Available from: https://oecd.org/coronavirus/policy-responses/tackling-The-mental-health-impact-of-The-covid-19-crisis-an-integrated-whole-of-society-response-0ccafa0b/. Accessed August23, 2022.

5. Wu D, Zhang C. A study on health information literacy of patients with COVID-19. Libr J. 2020;39(7):70–82.

6. Hua J, Shaw R. Corona virus (Covid-19) “infodemic” and emerging issues through a data lens: the case of China. Int J Environ Res Public Health. 2020;17(7):2309. doi:10.3390/ijerph17072309

7. Lloyd A, Hicks A. Saturation, acceleration and information pathologies: the conditions that influence the emergence of information literacy safeguarding practice in COVID-19-environments. J Doc. 2021;78(5):1008–1026. doi:10.1108/JD-08-2021-0162

8. Shipman JP, Kurtz-Rossi S, Funk CJ, et al. The health information literacy research project. J Med Libr Assoc. 2009;97(4):293–301. doi:10.3163/1536-5050.97.4.014

9. Luo AJ, Wang FZ, Xie WZ. Health information literacy status and influencing factors of elderly chronic disease patients in Changsha community. Chin J Gerontol. 2016;36(14):3554–3556.

10. Zheng Z. From the past to the future: what we learn from China’s 2020 census. China Popul Dev Stud. 2021;5:101–106. doi:10.1007/s42379-021-00084-8

11. Man W, Wang S, Yang H. Exploring the spatial-temporal distribution and evolution of population aging and social-economic indicators in China. BMC Public Health. 2021;21(1):966. doi:10.1186/s12889-021-11032-z

12. Niu YF. Study on the Improvement of Health Information Literacy Among the Elderly in Urban Areas. Hebei University; 2021.

13. Rubinelli S, Ort A, Zanini C, et al. Strengthening critical health literacy for health information appraisal. An approach from argumentation theory. Int J Environ Res Public Health. 2021;18(13):6764. doi:10.3390/ijerph18136764

14. Jeong SH, Kim HK. Health literacy and barriers to health information seeking: a nationwide survey in South Korea. Patient Educ Couns. 2016;99(11):1880–1887. doi:10.1016/j.pec.2016.06.015

15. Cutili CC, Simko LC, Collbert AM, et al. Health literacy, health disparities, and sources of health information in US older adults. Orthop Nurs. 2018;37(1):54–65. doi:10.1097/NOR.0000000000000418

16. Huvila I, Hirvonen N, Enwald H, et al. Differences in health information literacy competencies among older adults, elderly and younger citizens. In: Communications in Computer and Information Science. New York: Springe; 2019:136–143.

17. McNutt RA. Shared medical decision making: problems, process, progress. JAMA. 2004;292(20):2516–2518. doi:10.1001/jama.292.20.2516

18. Fan J, Smith AP. Information overload, wellbeing and covid-19: a survey in China. Behav Sci. 2021;11(5):62. doi:10.3390/bs11050062

19. Okan O, Bollweg TM, Berens EM, et al. Coronavirus-related health literacy: a cross-sectional study in adults during the COVID-19 infodemic in Germany. Int J Environ Res Public Health. 2020;17(15):5503. doi:10.3390/ijerph17155503

20. Seytre B, Barros C, Bona P, et al. Revisiting COVID-19 communication in Western Africa: a health literacy-based approach to health communication. Am J Trop Med Hyg. 2021;105(3):708–712. doi:10.4269/ajtmh.21-0013

21. Huang K, Guo M, Hao X, et al. A review of the literature on health information literacy in the context of public health crisis events. Libr J. 2020;39(07):59–69.

22. Gu XS, Zhang ZX. Analysis on intelligent management of human resources in urban community under normalized epidemic prevention and control. Procedia Comput Sci. 2021;199:924–928.

23. Lv Z, Chen D, Feng H, et al. Digital twins in unmanned aerial vehicles for rapid medical resource delivery in epidemics. IEEE trans Intell Transp Syst;2021. 1–9. doi:10.1109/TITS.2021.3113787

24. Chen W, Yao M, Dong L, et al. The application framework of big data technology during the COVID-19 pandemic in China. Epidemiol Infect. 2022;150:1–11. doi:10.1017/S0950268822001388

25. Martins VJG. The effects of COVID-19 among the elderly population: a case for closing the digital divide. Front Psychiatry. 2020;11:577427. doi:10.3389/fpsyt.2020.577427

26. Litchfield I, Shukla D, Greenfield S. Impact of COVID-19 on the digital divide: a rapid review. BMJ Open. 2021;11(10):e053440. doi:10.1136/bmjopen-2021-053440

27. Giansanti D, Veltro G. The digital divide in the era of covid-19: an investigation into an important obstacle to the access to the mHealth by the citizen. Healthcare. 2021;9(4):371. doi:10.3390/healthcare9040371

28. Karim HA. Health literacy among rural communities: issues of accessibility to information and media literacy. Malaysian J Commun. 2020;36:1.

29. Nie XQ, Li YH, Li L, et al. Health information literacy level of Chinese residents and its influencing factors from 2012–2017. China Health Educ. 2020;36(10):875–879+895.

30. Guo WL. Research on the Current Situation and Countermeasures of College Students’ Health Information Literacy Based on WeChat. Shanxi Med University; 2019.

31. Kahouei M, Roghani PS, Zadeh JM, et al. The determinants of nursing, allied health and non medical staff’ health literacy in hospitals of a developing country. Mater Sociomed. 2015;27(6):421–424. doi:10.5455/msm.2015.27.421-424

32. Wang FZ, Luo AJ, Xie WZ, et al. Preparation and reliability and validity test of health information literacy self-assessment scale. Chin J Mod Med. 2013;23(30):89–93.

33. Luo D, Chen XZ, Fu LG, et al. A study on the current situation and influencing factors of health information literacy among residents aged 45–60 years in rural communities in Anhui Province. J Taishan Med Coll. 2016;37(6):601–604.

34. Chen X, Li M, Kreps GL. Double burden of COVID-19 knowledge deficit: low health literacy and high information avoidance. MC Res Notes. 2022;15(1):27. doi:10.1186/s13104-022-05913-8

35. Orom H, Schofield E, Kiviniemi MT, et al. Low health literacy and health information avoidance but not satisficing help explain “don’t know” responses to questions assessing perceived risk. Med Decis Making. 2018;38(8):1006–1017. doi:10.1177/0272989X18799999

36. Wang L. Study on Factors Influencing Health Information Literacy of Older Adults. Zhengzhou University; 2021.

37. Kobayashi LC, Wardle J, Wolf MS, et al. Aging and functional health literacy: a systematic review and meta-analysis. J Gerontol B Psychol Sci Soc Sci. 2016;71(3):445–457. doi:10.1093/geronb/gbu161

38. Aponte J, Nokes KM. Validating an electronic health literacy scale in an older Hispanic population. J Clin Nurs. 2017;26(17–18):2703–2711. doi:10.1111/jocn.13763

39. Li S, Cui G, Yin Y, et al. Health-promoting behaviors mediate the relationship between eHealth literacy and healthrelated quality of life among Chinese older adults: a cross-sectional study. Qual Life Res. 2021;30(8):2235–2243. doi:10.1007/s11136-021-02797-2

40. Ruedin D, Probst J, Wanner P, et al. COVID-19-related health literacy of socioeconomically vulnerable migrant groups. Int J Public Health. 2022;67:1604664. doi:10.3389/ijph.2022.1604664

41. Patel JA, Nielsen FBH, Badiani AA, et al. Poverty, inequality and COVID-19: the forgotten vulnerable. Public Health. 2020;183:110–111. doi:10.1016/j.puhe.2020.05.006

42. Göransson C, Wengström Y, Hälleberg-Nyman M, et al. An app for supporting older people receiving home care – usage, aspects of health and health literacy: a quasi-experimental study. BMC Med Inform Decis Making. 2020;20(1):226. doi:10.1186/s12911-020-01246-3

43. Chen J, Zhou X, Lu N. Providing instrumental support to older parents of multi-child families in China: are there different within-family patterns? Ageing Soc. 2021;41:1770–1787. doi:10.1017/S0144686X21000283

44. Fan L, Yang YH, Luo JK, et al. Status quo and influencing factors of health information literacy of middle-aged and elderly patients with chronic diseases. J Med Inform. 2020;41(6):33–37.

45. Chen YRR, Schulz PJ. The effect of information communication technology interventions on reducing social isolation in the elderly: a systematic review. J Med Internet Res. 2016;18(1):e18. doi:10.2196/jmir.4596

46. Farooq A, Laato S, Najmul Islam AKM. Impact of online information on self-isolation intention during the COVID-19 pandemic: cross-sectional study. J Med Internet Res. 2020;22(5):e19128. doi:10.2196/19128

47. Siebenhaar KU, Köther AK, Alpers GW. Dealing with the COVID-19 infodemic: distress by information, information avoidance, and compliance with preventive measures. Front Psychol. 2020;11:567905. doi:10.3389/fpsyg.2020.567905

48. Chen AT, Ge S, Cho S, et al. Reactions to COVID-19, information and technology use, and social connectedness among older adults with pre-frailty and frailty. Geriatr Nurs. 2021;42(1):188–195. doi:10.1016/j.gerinurse.2020.08.001

留言 (0)

沒有登入
gif