Mitigation of COVID-19 Risk Among Older Adults in Nursing Homes: A Public Survey

(1)

Mitigation of COVID-19 Risk Among Older Adults in Nursing Homes: A Public Survey

Wang Ling Lee, PhD, RN; Dorothy DeWitt, PhD; Ping Lei Chui, PhD, RN; Abdul Kadir Shah Sahibudeen, MBBS;

Mohd Said Nurumal, PhD, RN; Karuthan Chinna, PhD, MS; and Mei Chan Chong, PhD, RN

ABSTRACT

The current study examines the public’s perception on the mitigation of COVID-19 risk and knowledge of disease symptoms among older adults in nursing homes, with the intention to address gaps in knowledge using mobile technologies. An online survey questionnaire was completed by 611 adults residing in Malaysia. The four domains, derived from factor analysis, aﬃ rmed the supportive perception among the public (score range = 4.42 to 4.64/5.0). However, among the gaps identi- fi ed were the perception toward hand sanitizing and susceptibility of older adults to COVID-19. Public knowledge on symptoms of COVID-19 was limited (e.g., 41.4% to 53.4% incorrect responses to anosmia, diarrhea, confusion). Multivariate analysis of variance found that males and participants with less education had signifi cantly lower supportive perceptions (p < 0.05). With >86% of participants having access to internet communication technology, mobile interventions tailored to gender and educational level are recommended to promote long-term pandemic preparedness among stakeholders and the public. [Journal of Gerontological Nursing, 47(3), 23-28.]

T

he coronavirus disease, or COVID-19, poses an unprec- edented challenge to public health, specifi cally among the 962 million older adults worldwide (Unit- ed Nations, Department of Economic

and Social Aff airs, Population Divi- sion, 2017). Emerging data show that persons age ≥60 years have a higher risk of mortality, and this risk increas- es exponentially for those with co- morbidities such as frailty, dementia,

and chronic medical conditions (e.g., cardiovascular disease, diabetes, lung disease) (Pan et al., 2020). It is alarm- ing to hear that thousands of older adults and staff in nursing homes have lost their lives to COVID-19 (Werner et al., 2020). Th e COVID-19 infection rate in Malaysian nursing homes was <9%, with only fi ve deaths as of June 2020 (Hasmuk et al., 2020), and the latest rate during Malaysia’s spike of cases since October 2020 has yet to be reported. If the government and public fall back in the containment of COVID-19, the risk of transmission from communities to largely ill- prepared nursing homes will increase.

Two million older citizens are at risk, as 63% of coronavirus deaths in Malaysia were older adults (Ministry of Health Malaysia, 2020a).

A pandemic response plan for nursing homes was proposed more than 10 years ago to mitigate in- fl uenza outbreaks (Mody & Cinti, 2007), but fell short of implementation. Low-preparedness remains a major contributor to the high transmission rate of COVID-19 in nursing homes, whereas other factors (e.g., delayed recognition of cases, staff who work in more than one setting, visitors and staff who have been exposed to the virus due to their movement in communities with active cases) are also signifi cant (McMichael et

Dr. Lee is RN, Dr. Chui is RN, and Dr. Chong is Associate Professor and RN, Department of Nursing Science, Faculty of Medicine, Dr. DeWitt is Associate Professor, Department of Cur- riculum and Instructional Technology, Faculty of Education, University of Malaya, Kuala Lumpur, Dr. Sahibudeen is Medical Doctor, Hospital Queen Elizabeth, Kota Kinabalu, Sabah, Dr. Nurumal is Associate Professor and RN, Kulliyyah of Nursing, International Islamic University Malaysia, Pahang, and Dr. Chinna is Associate Professor, School of Medicine, Faculty of Health and Medi- cal Sciences, Taylor’s University, Subang Jaya, Selangor, Malaysia.

The authors have disclosed no potential confl icts of interest, fi nancial or otherwise.

The authors thank participants who completed the survey and Ng Bren Den who helped in preparation of the Google Form.

Address correspondence to Wan Ling Lee, PhD, RN, Department of Nursing Science, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia; email: [email protected].

Received: July 7, 2020 Accepted: October 2, 2020

doi:10.3928/00989134-20210209-04

(2)

al., 2020). Th e dire consequences of COVID-19 in long-term care facilities calls for concerted actions among government bodies and the public.

Supportive perception among the public may be one essential factor to drive and sustain initiatives in miti- gating COVID-19 risk among nursing home residents and staff . For ex- ample, individuals who perceive that wearing face masks is a good protec- tive measure for vulnerable popula- tions, such as nursing home residents, will likely adhere to the recommenda- tion or regulation. Public opinion on COVID-19–related issues pertinent to the older population is scarce, and most studies covered general aspects, such as impact of COVID-19 on public social life (Nelson et al., 2020) and public response to general policies and health measures of COVID-19 (Azlan et al., 2020).

As ageism exists in many societ- ies (Offi cer & de la Fuente-Núñez, 2018), more research is needed to assess the public’s readiness to support and interact with older adults during outbreaks. It is also important to assess public perception on risk mitigation for older adults in nursing homes. In Malaysia, some nursing home residents receive many visitors and have small gatherings with family members, relatives, and friends, thus increasing their risk of infection.

Identifying misperceptions among the public could inform relevant stakeholders of gaps that exist for remedia- tion and public health education or interventions.

Health education during the pandemic has relied heavily on digital and internet technology as delivery chan- nels to avoid risks of COVID-19 transmission. Suitable training and support in technology applications (apps) during pandemics can assist older adults in self-management of disease (Tarte & Amirehsani, 2019), promote social connectedness to reduce loneliness (Mullins et al., 2020), and enable access to necessities, such as home delivery of meals, groceries, medications, and remote health care

services (Banskota et al., 2020). How- ever, studies on implementation of technology for caregivers and nursing homes are rare (Krick et al., 2019), and none seem to be conducted in Malaysian settings. As smartphones and social media predominate even in emerging and developing countries, the potential of mobile technologies can be explored (Pew Research Cen- ter, 2019). Social media platforms on mobile phones have the capacity to facilitate education and support for those in marginalized or remote areas (Chipps et al., 2015). In view of the fact that Malaysia has a mobile pen- etration rate of 130.2% (42.4 million mobile/cellular subscriptions) to a population of 32.6 million at the end of 2018 (Malaysian Communications and Multimedia Commission, 2018), mobile technologies could be further harnessed and studied (e.g., mobile support or informal training for caregivers and nursing home staff ).

To date, little is known about mobile technologies’ eff ects and use among informal caregivers of older adults in communities and nursing homes. Th e current study investigates the public’s perception on risk mitigation in nursing homes and their knowledge of COVID-19 symptoms among older adults with an intention to identify gaps in public health education and assist in the planning for optimization of social media apps.

METHOD Study Design

A cross-sectional study was conducted online from May 4 to May 23, 2020, during the enforcement of movement control order in Malaysia.

Th e survey questionnaire was designed in Google Forms and was aimed to gather swift information needed for prompt planning of a needs-based educational program targeted for nursing homes.

Ethical Consideration

Ethics clearance was obtained from the Institutional Review Board of University Malaya Medical Centre.

Study procedures were conducted according to the Declaration of Helsin- ki and in adherence to the Caldicott principles. Participants were advised to read the standardized study information sheet and click the button in- dicating consent.

Sampling and Procedure

Based on 80% power, alpha of 0.05, and modest eff ect size of 0.04, G*Power software (version 3.1.9.4) was used to calculate sample size for multivariate analysis of variance; the estimate obtained was congruent with the minimum sample of 300 as a rule of thumb (Bujang et al., 2017). Th e study aimed for >480 online responses after a 40% response rate was factored in. All adults (age ≥18 years) residing in Malaysia were eligible to partici- pate. By relying on professional and personal networks of researchers, the online survey was circulated on popular social media platforms among Ma- laysian individuals (i.e., WhatsApp™, Telegram, and Facebook®), and the posts were shared to facilitate snowball sampling.

Study Instrument

During the study’s conception, there were no specifi c questionnaires being distributed on public perception of COVID-19 risk among older residents of nursing homes. A list of pertinent items related to mitigation measures for nursing homes was derived from the literature and interim guidelines on the websites of the World Health Organization [WHO], Centers for Disease Control and Pre- vention [CDC], Ministry of Health Malaysia, and Malaysian Society of Geriatric Medicine. Overlapping items were removed and relevance of items was assessed by a physician and senior nurse from a local COVID-19 task force in a large medical center.

Th ree lay persons pretested the questionnaire and affi rmed that the items could be understood by lay persons and that the online form was user-friendly.

Perception on four domains (i.e., susceptibility of older adults, preven-

(3)

tive practices, visitation policy, and management role of nursing homes during a pandemic) was assessed using items scored on a 5-point Likert scale, where 1 = strongly disagree and 5 = strongly agree. For each participant, item scores were averaged ac- cordingly to compute domain scores, ranging from 1 to 5. A domain score

≥4 indicated positive or supportive perception. Item score ≤3 and domain score <4 were taken as indicators of a non-supportive perception, as these responses did not fall in the continu- um of agreeing to the item statement.

Items assessing knowledge on nine symptoms of COVID-19 were scored as 1 point for correct and 0 points for incorrect responses. Knowledge scores were totaled, and percentages were computed. Other information obtained included participants’ sociode- mographics, living arrangement with older parents, and access to internet communication technology (ICT).

Statistical Analysis

All data analyses were performed using IBM SPSS version 26. Descrip- tive analysis, exploratory factor analysis, and general linear model procedures were used. For all tests, the level of signifi cance was set at 0.05.

RESULTS

A total of 611 respondents partici- pated. As shown in Table A (available in the online version of this article), the four domains of perception were supported in the factor analyses. All domains had adequate item loadings (λ = 0.64 to 0.86) and good internal consistency reliability (Cronbach’s α = 0.649 to 0.863). An item on the use of hand sanitizer failed to load on any of the factors, hence it was ex- cluded from analysis. A sizable 42.1%

(n = 257) of participants disagreed and 17% (n = 104) were uncertain of the statement “Th e use of hand sanitizer on soiled hands is not eff ective to kill the virus.”

Participants’ sociodemographic characteristics are shown in Table B (available in the online version of this

article). Most participants resided in Selangor (46.8%) and Federal Terri- tory of Kuala Lumpur (19.5%). Th ese two states had the highest number of COVID-19 cases and also a large proportion of nursing homes (De- partment of Social Welfare, 2018).

Most participants had access to ICT;

86.9% owned a computer (e.g., desk- top, laptop, tablet) and 88.1% owned a smartphone. Approximately 89% of participants used more than one social media platform; 99% used WhatsApp and 81.5% had Facebook. Other popular platforms included Instagram™

(61%), Telegram (49.6%), and WeChat (29.8%).

Assessment of the Public’s View Table A describes participants’ responses to the 16 items and four domains. All domain scores were high.

Participants showed highest supportive perception toward visitation policy (domain score = 4.64) and least supportive perception on susceptibility of older adults (domain score = 4.42).

It is still noteworthy to look at item scores ≤3, although the percentages are low. Th ere were participants who disagreed or were unsure on items, such as older adults are at risk of COVID-19 in nursing homes (18%);

asymptomatic children and adults can spread the virus to residents (6.5%);

and infected persons who do not wear a face mask can spread the virus (5.6%). Th e uncertainty on practices related to hand hygiene was 3.6% to 4% and face mask use was 6%. Assess- ment on knowledge shows that 15%

to 53% of participants were unsure or did not know that fatigue, fl u-like symptoms, body aches/pain, anosmia, diarrhea, and confusion were also symptoms of COVID-19. A small number of participants (n = 13, 2.1%) had a score of 0 for total knowledge.

Factors Associated With the Public’s Perception

Associations between demographic characteristics of participants and domain scores were tested using multivariate analysis of variance. Th e re-

sults are shown in Table B. Among the variables tested, only level of education and gender were signifi cant (p < 0.05). Participants with a tertiary level of education had higher mean scores in all four domains compared to those with only a secondary level of education. Females had higher mean scores in the domains of preventive practices, visitation policy, and management role compared to males.

DISCUSSION

Participants in general were supportive in their perception toward COVID-19 mitigation measures recommended for the protection and care of older adults in nursing homes during the pandemic. Th e highly supportive perception could have resulted from a heightened awareness among the Malaysian public from coordinated eff orts undertaken by government agencies (i.e., Ministry of Health and the National Security Council).

Th e initial COVID-19 misinforma- tion leading to misperception among the public was aggressively tackled with multiple strategies since the na- tion’s lockdown began on March 18, 2020. Th e Malaysian government dis- seminated daily COVID-19 reports and educated the public on mitigation measures with simple materials, including short video clips and infographics designed for the level of understanding among lay persons. In addition to government websites and mainstream media, popular social media platforms were also used for wider information dissemination. Th ose ob- servations imply that coordinated and timely eff orts using appropriately designed material and suitable delivery modes are several factors to be con- sidered in promoting and enhancing perception levels.

Th e current study found gender and educational level to be associated with perception. Females demonstrat- ed higher supportive perception than males. Th is diff erence in perception between genders could be attributed to women being generally more pro- active and concerned about the im-

(4)

pact of COVID-19 (Frederiksen et al., 2020). Participants with tertiary education had higher positive perceptions compared to those with only secondary education. By and large, participants educated at the tertiary level had higher literacy skills, en- abling them to acquire and compre- hend the fl ood of information, and had better fi nancial status to aff ord internet technology, which kept them well-informed. Two implications from these fi ndings are as follows.

First, additional qualitative research is recommended to explore gender per- spectives on COVID-19 issues. Sec- ond, assessment should be performed using current educational materials to determine the extent to which their design and delivery are tailored to gender and educational level. It is be- yond the scope of the current article to elaborate on the ever-growing literature describing the diff erent learning behaviors and diff erent approaches according to gender and educational level (CDC, 2009; Cuadrado-Garcia et al., 2010).

A non-supportive perception of 62% was observed on an item pertinent to application of hand sanitizer to soiled hands. Th is fi nding warrants attention regardless of reasons to the item failing to load in factor analysis.

As hand sanitizers are widely used in public premises, more emphasis on their proper application should be in- corporated in the current educational campaign on COVID-19. Th e 6%

non-supportive perception on wearing face masks for nursing home visitors is open to diff ering views. Interim guidelines on public use of face masks are subject to change according to the latest evidence or debate. One fact remains—the fl uid-resistance proper- ty of surgical face masks forms a good physical barrier between wearer and the immediate environment; thus, face masks off er added protection for older adults and nursing home staff from asymptomatic infected visitors.

The misperception surround- ing susceptibility of older adults to COVID-19 is concerning, as public

education heavily promotes containment and mitigation measures for the general population, with a much lesser extent on measures for older adults in nursing homes. Despite an offi cial report on a cluster case from aged- care facilities in Selangor state (Min- istry of Health Malaysia, 2020b), 18% of participants, albeit low, were uncertain that older adults in nursing homes also were at risk of contract- ing COVID-19. Th e public’s knowledge on COVID-19 symptoms was minimal, with many unaware of the development of confusion, anosmia, fatigue, diarrhea, body aches, and pain in infected older adults (WHO, 2020). Such defi ciency in knowledge among caregivers may lead to delayed recognition of COVID-19, as older adults may be incapable of verbalizing symptoms due to cognitive impair- ment or fear. Hence, targeted strategies to promote awareness should be explored, such as the development of more materials addressing the misperception and knowledge gaps found in the current study.

According to Mody and Cinti (2007), a preparedness plan to coun- ter outbreaks should include a detailed educational program for nursing home staff , residents and family members, and visitors and members of the public who provide care and services to nursing homes. Th e current study supports the value of surveying the public’s perception to highlight gaps for consideration in the execution of national preparedness plans among government agencies, health authori- ties, relevant sectors, and members of the public. Although positive cases in Malaysia were low at 0.2% in June (Ministry of Health Malaysia, 2020c), more eff orts for mitigation and strategies for interventions should be rolled out to benefi t the 350 registered and >1,000 unregistered residential aged-care facilities operated by non- governmental organizations and pri- vate entities (Hasmuk et al., 2020).

Initiatives proposed should aim to draw participation from all operators of aged-care facilities, especially

unregistered facilities, by off ering the kind of support needed, and bridging the gaps of cooperation between all stakeholders, including members of the public.

NURSING IMPLICATIONS To combat current and future outbreaks, gerontological nursing cur- riculum and practices must explore greater involvement of nursing home operators, staff , and informal caregivers of older adults in fostering cooperation that promotes continuity of quality geriatric care. More research by nursing scholars is needed to explore solutions and interventions to improve care models, skilled nursing care, and infection control practices in nursing homes. Th e current study proposes the use of mobile technologies to address knowledge gaps or information needs, despite the country’s digital divide (e.g., poor internet connectivity in rural areas, lack of internet access) (Foo et al., 2017). Although traditional methods (e.g., pamphlets, posters) are still applicable, low-band- width modalities, such as low-cost social media apps, can be used. So- cial media apps can be harnessed to deliver various forms of mobile interventions, such as education, training, or support services. Mobile interventions could be delivered across the geographical divide and at the user’s convenience (McKenna et al., 2019) to meet the needs of caregivers among the public and nursing home operators, who often depend on foreign domestic workers and need frequent staff training due to high staff turn- over.

LIMITATIONS

Th e snowball sampling method of disseminating the online survey through contacts and social media has a limitation as it may not reach the disadvantaged public (e.g., those with low education, low socioeco- nomic status, no internet access). On the other hand, this survey portrays the viewpoint of targeted respondents with older parents (age >65 years).

(5)

Although items in the perception questionnaire are dependent on the interim guidelines, there is no major deviation of current policies that invalidates the fi ndings. Th e inher- ent socially desirable response bias of self-reported questionnaires was mini- mized due to anonymous response to the online survey.

CONCLUSION

A lesser supportive perception observed among men and those with less education may require information to be designed and delivered according to gender and educational level. Find- ings also advocate for more attention to be given to educating the public on proper use of hand sanitizer, the risk of transmission, and symptoms of COVID-19 among older adults in nursing homes. Low-cost modalities using existing social media apps could be explored to design and deliver mobile interventions off ering a wide range of services and supports to caregivers of older adults in the community and nursing homes.

REFERENCES

Azlan, A. A., Hamzah, M. R., Sern, T. J., Ayub, S. H., & Mohamad, E. (2020).

Public knowledge, attitudes and practices towards COVID-19: A cross-sectional study in Malaysia. PLoS One, 15(5), e0233668. https://doi.org/10.1371/journal.

pone.0233668 PMID:32437434

Banskota, S., Healy, M., & Goldberg, E. M.

(2020). 15 smartphone apps for older adults to use while in isolation during the COVID-19 pandemic. Th e Western Journal of Emergency Medicine, 21(3), 514–525. https://doi.org/10.5811/

westjem.2020.4.47372 PMID:32302279 Bujang, M. A., Sa’at, N., Ikhwan, T. M., &

Sidik, T. A. B. (2017). Determination of minimum sample size requirement for multiple linear regression and analysis of covariance based on experimental and non- experimental studies. Epidemiology, Biosta- tistics, and Public Health, 14(3). https://doi.

org/10.2427/12117

Centers for Disease Control and Prevention.

(2009). Simply put: A guide for creating easy- to-understand materials. https://www.cdc.

gov/healthliteracy/pdf/simply_Put.pdf Chipps, J., Pimmer, C., Brysiewicz, P., Walters,

F., Linxen, S., Ndebele, T., & Gröhbiel, U. (2015). Using mobile phones and social media to facilitate education and sup-

port for rural-based midwives in South Africa. Curationis, 38, 1500. https://

doi.org/10.4102/curationis.v38i2.1500 PMID:26842093

Cuadrado-Garcia, M., Ruiz-Molina, M., &

Montoro-Pons, J. (2010). Are there gender diff erences in e-learning use and assessment?

Evidence from an interuniversity online project in Europe. Procedia: Social and Be- havioral Sciences, 2, 367–371. https://doi.

org/10.1016/j.sbspro.2010.03.027

Department of Social Welfare. (2018). Table 14.1: Number of registered care centres, number of carer and residents by state and category, 2018. In Department of Social Wel- fare statistics report (p. 168).

Foo, L. N., Lai, W. K., & Elamzazuthi, C.

(2017). 12/13). Narrowing the digital divide in Malaysia: Issues and initiatives. ASEAN Journal on Science and Technology for Devel- opment, 19, 97. https://doi.org/10.29037/

ajstd.342

Frederiksen, B., Gomez, I., Salganicoff , A., &

Ranji, U. (2020, March 20). Coronavirus:

A look at gender diff erences in awareness and actions. https://www.kff .org/coronavirus- covid-19/issue-brief/coronavirus-a-look-at- gender-diff erences-in-awareness-and-actions Hasmuk, K., Sallehuddin, H., Tan, M. P.,

Cheah, W. K., Rahimah, I., & Chai, S.

T. (2020, October 2). Th e long-term care COVID-19 situation in Malaysia. https://

ltccovid.org/wp-content/uploads/2020/10/

Malaysia-LTC-COVID-situation-report- 2-October-2020-1.pdf

Krick, T., Huter, K., Domhoff , D., Schmidt, A., Rothgang, H., & Wolf-Ostermann, K.

(2019). Digital technology and nursing care: A scoping review on acceptance, ef- fectiveness and effi ciency studies of informal and formal care technologies. BMC Health Services Research, 19(1), 400. https://

doi.org/10.1186/s12913-019-4238-3 PMID:31221133

Malaysian Communications and Multimedia Commission. (2018). Internet users survey 2018: Statistical brief number twenty-three.

https://www.mcmc.gov.my/skmmgovmy/

m e d i a / G e n e r a l / p d f / In t e r n e t - Us e r s - Survey-2018.pdf

McKenna, P., Babughirana, G., Amponsah, M., Egoeh, S. G., Banura, E., Kanwagi, R., &

Gray, B. (2019). Mobile training and support (MOTS) service: Using technology to increase Ebola preparedness of remotely- located community health workers (CHWs) in Sierra Leone. mHealth, 5, 35–35. https://

doi.org/10.21037/mhealth.2019.09.03 PMID:31620462

McMichael, T. M., Clark, S., Pogosjans, S., Kay, M., Lewis, J., Baer, A., Kawakami, V., Lukoff , M. D., Ferro, J., Brostrom-Smith, C., Riedo, F. X., Russell, D., Hiatt, B., Montgomery, P., Rao, A. K., Currie, D. W., Chow, E. J., Tobolowsky, F., Bardossy, A. C., . . . Duchin, J. S., & the Public Health –

Seattle & King County, EvergreenHealth, and CDC COVID-19 Investigation Team.

(2020). COVID-19 in a long-term care fa- cility - King County, Washington, February 27-March 9, 2020. Morbidity and Mortal- ity Weekly Report, 69(12), 339–342. https://

doi.org/10.15585/mmwr.mm6912e1 PMID:32214083

Ministry of Health Malaysia. (2020a, April 16).

Current situation of coronavirus (COVID-19) infection in Malaysia [Press release]. http://

covid-19.moh.gov.my/terkini/042020/

situasi-terkini-16-april-2020

Ministry of Health Malaysia [@KKMPutrajaya].

(2020b, May 7). Gold Cluster (senior care center) in Klang and Petaling which has in- fected 36 people including 5 deaths [Tweet].

Twitter. https://twitter.com/KKMPutrajaya/

status/1258375117945450496

Ministry of Health Malaysia. (2020c, June 3). Updates on the coronavirus disease 2019 (COVID-19) situation in Malaysia [Press release]. http://covid-19.moh.gov.my/

terkini/062020/situasi-terkini-03-jun-2020 Mody, L., & Cinti, S. (2007). Pandemic in-

fl uenza planning in nursing homes: Are we prepared? Journal of the American Geriat- rics Society, 55(9), 1431–1437. https://doi.

org/10.1111/j.1532-5415.2007.01299.x PMID:17767687

Mullins, L. B., Skemp, L., Reed, D., & Emerson, M. (2020). Internet programming to reduce loneliness and social isolation in aging. Re- search in Gerontological Nursing, 13(6), 233–

243. https://doi.org/10.3928/19404921- 20200320-01

Nelson, L. M., Simard, J. F., Oluyomi, A., Nava, V., Rosas, L. G., Bondy, M., & Linos, E. (2020). US public concerns about the COVID-19 pandemic from results of a survey given via social media. JAMA Inter- nal Medicine, 180, 1020–1022. https://doi.

org/10.1001/jamainternmed.2020.1369 PMID:32259192

Offi cer, A., & de la Fuente-Núñez, V. (2018).

A global campaign to combat ageism. Bul- letin of the World Health Organization, 96(4), 295–296. https://doi.org/10.2471/

BLT.17.202424 PMID:29695887 Pan, A., Liu, L., Wang, C., Guo, H., Hao, X.,

Wang, Q., Huang, J., He, N., Yu, H., Lin, X., Wei, S., & Wu, T. (2020). Association of public health interventions with the epidemiology of the COVID-19 outbreak in Wuhan, China. Journal of the American Medical Association, 323(19), 1915–1923.

https://doi.org/10.1001/jama.2020.6130 PMID:32275295

Pew Research Center. (2019, March 7).

Mobile connectivity in emerging econo- mies. https://www.pewresearch.org/

internet/2019/03/07/use-of-smartphones- and-social-media-is-common-across-most- emerging-economies/

Tarte, V. P., & Amirehsani, K. A. (2019). Per- ceptions of mobile technology for heart fail-

(6)

ure education and self-management among middle-aged and older adults. Journal of Ge- rontological Nursing, 45(11), 30–38. https://

doi.org/10.3928/00989134-20191011-05 PMID:31651986

United Nations, Department of Economic and Social Aff airs, Population Division. (2017).

World population ageing 2017 - High-

lights (ST/ESA/SER.A/397). https://www.

un.org/en/development/desa/population/

publications/pdf/ageing/WPA2017_

Highlights.pdf

Werner, R. M., Hoff man, A. K., & Coe, N.

B. (2020). Long-term care policy after COVID-19: Solving the nursing home cri- sis. Th e New England Journal of Medicine,

383, 903–905. https://doi.org/10.1056/

NEJMp2014811 PMID:32459918 World Health Organization. (2020, May 13).

Symptoms of coronavirus. https://www.cdc.

gov/coronavirus/2019-ncov/symptoms- testing/symptoms.html

(7)

Table A

Distribution of public’s responses to 16 items on perception towards mitigation of COVID-19 risk among older people in nursing homes and 9 items on knowledge of disease symptoms (N=611)

Item score Description on item

1= Strongly

disagree 2 = Disagree 3 = Not sure 4 = Agree 5 = Strongly agree λ parameters ^Other

n (%) n (%) n (%) n (%) n (%)

Domain 1: Susceptibility of older people in nursing homes

S1: COVID-19 infection among older people is more serious as compared to

adults of a younger age. 0 (0) 6 (1.0) 13 (2.1) 246 (40.3) 346 (56.6) .703

S2: OP in nursing home have risk of COVID-19 infection. 0 (0) 24 (3.9) 86 (14.1) 255 (41.7) 246 (40.3) .640

S3: Children and adults with COVID-19 infection but without symptom can

still spread the virus to OP. 0 (0) 8 (1.3) 32 (5.2) 245 (40.1) 326 (53.4) .751

S4: A person with COVID-19 infection without wearing facemask will

spread the virus when chatting with residents. 0 (0) 8 (1.3) 26 (4.3) 218 (35.7) 359 (58.8) .720

Cronbach alpha reliability (α) α=.649

Domain score mean (SD) 4.42 (0.48)

Domain 2: Preventive practices for nursing homes

P1: Hand must be washed with soap and water for 20 seconds frequently in a

day. 0 (0) 9 (1.5) 15 (2.5) 267 (43.7) 320 (52.4) .738

P2: Hand must be washed after coughing or sneezing into a tissue. 1 (0.2) 11 (1.8) 10 (1.6) 234 (38.3) 355 (58.1) .811

P3: Visitors, staff and older people need to keep 1-meter distancing at

nursing home. 0 (0) 6 (1.0) 10 (1.6) 222 (36.3) 373 (61.0) .804

Cronbach alpha reliability (α) α= .687

Domain 3: Visitation policy for nursing homes

V1: All visitors to nursing home must only wear surgical facemask (3-ply) at

all times. 2 (0.3) 13 (2.1) 22 (3.6) 218 (35.7) 356 (58.3) .695

V2: All visitors to nursing home must screened for body temperature and

unwell symptom including flu. 1 (0.2) 1 (0.2) 4 (0.7) 192 (31.4) 413 (67.6) .860

V3: Visitors with flu or cough must be stopped from entering nursing home. 1 (0.2) 3 (0.5) 7 (1.1) 159 (26.0) 441 (72.2) .822

V4: All visitors should record their name and phone number each time they

visit nursing homes for the purpose of contact tracing when needed. 3 (0.5) 0 (0) 8 (1.3) 173 (28.3) 427 (69.9) .857

V5: Visitors must inform nursing home staff if they develop fever or

symptoms consistent with COVID-19 within 14 days of visit. 2 (0.3) 1 (0.2) 6 (1.0) 165 (27.0) 437 (71.5) .836

(8)

Item score Description on item

1= Strongly

disagree 2 = Disagree 3 = Not sure 4 = Agree 5 = Strongly agree λ parameters ^Other

n (%) n (%) n (%) n (%) n (%)

Domain 4: Management role for nursing homes

M1: Post signs on visitor restriction at the entrance of nursing home. 1 (0.2) 1 (0.2) 7 (1.1) 215 (35.2) 387 (63.3) .703

M2: Management of nursing home should provide alternative methods for

visitation such as video call. 1 (0.2) 4 (0.7) 19 (3.1) 238 (39.0) 349 (57.1) .839

M3: Management of nursing home should schedule call to connect residents

with their family. .0 (0) 10 (1.6) 32 (5.2) 254 (41.6) 315 (51.6) .828

M4: Management of nursing home should provide regular counselling service

to the residents. 1 (0.2) 3 (0.5) 33 (5.4) 270 (44.2) 304 (49.8) .780

Knowledge on COVID-19 symptoms of OP Incorrect response Correct response

n (%) n (%)

1. Short of breath 39 (6.4%) 572 (93.6%)

2. Cough 41 (6.7%) 570 (93.3%)

3. Fever 47 (7.7%) 564 (92.3%)

4. Fatigue 94 (15.4%) 517 (84.6%)

5. Flu 144 (23.6%) 467 (76.4%)

6. Body aches dan pain 155 (25.4%) 456 (74.6%)

7. Loss of smell 253 (41.4%) 358 (58.6%)

8. Diarrhoea 302 (49.4%) 309 (50.6%)

9. Confused 326 (53.4%) 285 (46.6%)

Total knowledge score ≤ 50% 90 (14.7%)

Note. λ, factor loading in exploratory factor analysis; SD, standard deviation; OP, older people.

(9)

Table B

Perception by demographic characteristics of participants (N=611)

Participant’s

Characteristics n (%)

Susceptibility of OP Preventive Practices Visitation Policy Management role

Mean (SE) p Mean (SE) p Mean (SE) p Mean (SE) p

Age groups (Missing =4)

<30 years 155 (25.5) 4.36 (0.07) 0.579 4.52 (0.08) 0.860 4.60 (0.07) 0.76 4.46 (0.08) 0.963

30 -49 years 172 (28.3) 4.35 (0.07) 4.52 (0.07) 4.56 (0.07) 4.48 (0.07)

50-65 years 220 (36.2) 4.30 (0.06) 4.49 (0.06) 4.61 (0.06) 4.46 (0.06)

< 65 years 60 (9.9) 4.24 (0.09) 4.44 (0.09) 4.64 (0.08) 4.43 (0.09)

Gender

Male 190 (31.1) 4.28 (0.06) 0.110 4.43 (0.06) 0.008 4.55 (0.06) 0.021 4.39 (0.06) 0.003

Female 421 (68.9) 4.35 (0.05) 4.55 (0.05) 4.65 (0.05) 4.52 (0.05)

Living with spouse (Missing=2)

Yes 360 (59.1) 4.29 (0.05) 0.419 4.51 (0.06) 0.507 4.60 (0.05) 0.992 4.46 (0.06) 0.907

No 249 (40.9) 4.33 (0.06) 4.47 (0.06) 4.60 (0.06) 4.45 (0.06)

Education level

Tertiary 530 (86.7) 4.44 (0.05) 0.000 4.55 (0.05) 0.045 4.66 (0.05) 0.046 4.55 (0.05) 0.003

Up to secondary 81 (13.3) 4.18 (0.07) 4.43 (0.07) 4.55 (0.07) 4.37 (0.07)

Ethnic group

Bumiputera 254 (41.6) 4.34 (0.06) 0.579 4.51 (0.06) 0.616 4.62 (0.06) 0.819 4.44 (0.06) 0.203

Chinese 279 (45.6) 4.31 (0.06) 4.47 (0.06) 4.59 (0.05) 4.41 (0.06)

Indians etc. 78 (12.8) 4.28 (0.07) 4.50 (0.07) 4.60 (0.07) 4.52 (0.07)

Formal employment

Yes 346 (56.6) 4.30 (0.06) 0.206 4.51 (0.06) 0.486 4.65 (0.06) 0.142 4.46 (0.06) 0.537

No 145 (23.7) 4.24 (0.07) 4.44 (0.07) 4.54 (0.07) 4.41 (0.07)

Retiree 120 (19.6) 4.39 (0.07) 4.53 (0.07) 4.62 (0.07) 4.50 (0.07)

(10)

Participant’s

Characteristics n (%)

Susceptibility of OP Preventive Practices Visitation Policy Management role

Mean (SE) p Mean (SE) p Mean (SE) p Mean (SE) p

Income group

B40 (≤RM3K) 124 (20.3) 4.28 (0.06) 0.377 4.47 (0.06) 0.870 4.60 (0.06) 0.982 4.43 (0.06) 0.727

M40 376 (61.5) 4.30 (0.05) 4.49 (0.05) 4.60 (0.05) 4.46 (0.05)

T20 (≥RM12K) 111 (18.2) 4.36 (0.07) 4.51 (0.07) 4.61 (0.07) 4.48 (0.07)

House area

Urban 382 (62.5) 4.31 (0.05) 0.911 4.48 (0.06) 0.532 4.58 (0.05) 0.397 4.43 (0.06) 0.229

Suburban, rural 229 (37.5) 4.31 (0.06) 4.51 (0.06) 4.62 (0.05) 4.48 (0.06)

Has parents aged ≥ 65 years

No 238 (39.0) 4.31 (0.06) 0.924 4.50 (0.06) 0.658 4.61 (0.06) 0.628 4.47 (0.06) 0.596

Yes 373 (61.0) 4.31 (0.05) 4.48 (0.06) 4.59 (0.05) 4.44 (0.06)

Has staying parents

No 367 (60.1) 4.34 (0.06) 0.176 4.50 (0.06) 0.887 4.62 (0.06) 0.467 4.48 (0.06) 0.319

Yes 244 (39.9) 4.28 (0.06) 4.49 (0.06) 4.58 (0.05) 4.43 (0.06)

Has parents in nursing home

No 578 (94.6) 4.30 (0.04) 0.887 4.45 (0.04) 0.391 4.58 (0.04) 0.586 4.43 (0.04) 0.541

Yes 33 (5.4) 4.32 (0.09) 4.53 (0.09) 4.63 (0.09) 4.49 (0.09)

Note. SE, standard error; Malaysia’s income classification is described as top 20% (T20), middle 40% (M40) and bottom 40% (B40); the currency of Malaysia is Ringgit Malaysia (RM), p values < 0.05 are in bold print.