SUMMARY STATEMENT OF IMPLICATIONS FOR PRACTICE 1 What does this research add to existing knowledge in gerontology? This study addresses the gaps in the level of prevention practices against COVID-19 among older people. This study provides information about the acceptance of the COVID-19 vaccine among older people. 2 What are the implications of this new knowledge for nursing care with older people? Males and lower educational level older people exhibited a lower level of prevention practices. Study found older people have positive attitudes towards COVID-19 vaccination. Study revealed recommendations from healthcare providers may increase vaccine acceptance 3 How could the findings be used to influence policy or practice or research or education? Intervention targeted at older males and lower education level should be carried out to enhance prevention practices. Raising awareness of COVID-19 prevention based on the Health Belief Model can be used as a framework for designing and implementing interventions to improve prevention practices among older people. Findings from this study can be used to inform healthcare professionals about their important role in enhancing COVID-19 vaccination intention among the older people. Owing to high COVID-19 vaccination acceptance, findings suggest that clinical trials represented by the older people are needed for conclusive results as to whether there is a benefit of vaccination among the older people population. 1 INTRODUCTION

The novel coronavirus disease (COVID-19) caused by SARS-CoV-2 that emerged in Wuhan, China at the end of 2019 has spread quickly around the world. The coronavirus has resulted in more than one million deaths in the first six months of the pandemic (Dong et al., 2020). By the end of October 2020, over 42 million cases and 1.1 million deaths had been reported globally (WHO, 2020a). COVID-19 has since caused a large-scale epidemic worldwide, including in Malaysia. Malaysia is currently faced with the third wave of COVID-19 cases. As of 31st October 2020, Malaysia had recorded over 30,000 cases of COVID-19 (Department of Statistics Malaysia, 2020a) since its first case on 25 January 2020.

COVID-19 is a threat to everyone's health and can be especially devastating to older individuals. Since the beginning of the COVID-19 pandemic, research evidence suggests that older people are at greater risk of severe illness from COVID-19 and fatal outcomes (Clark et al.,2020; Perrotta et al., 2020; Wang et al., 2020). The mortality rate in the age group 60–69 years is 3.6% and increases to 18% at 80 years and above (Meo et al., 2020). In the UK, individuals who are 65 and older comprise 92.5% of all confirmed COVID-19 deaths (Office for National Statistics, 2020). Similarly, in Malaysia, COVID-19 incidence is highest in those aged 55–69 years; the incidence rate per 100,000 population is 32.5 among those aged 60–64, followed by 31.5 in the 55–59 age group, and 26.8 in the 65–69 age group (CodeBlue, 2020). As of 31st October, 2020, 62.6% of fatalities involved those aged 60 and above (Astro Awani, 2020). Malaysia is expected to become an ageing nation by the year 2040, when the older people population will comprise 14.5% of the total population (Department of Statistics Malaysia, 2016). At present, the number of Malaysians aged 60 years and above is estimated to be 2.3 million (Department of Statistics Malaysia, 2020b) and is projected to increase to 3.8 million in the year 2040 (Kamaruddin, 2015). As such, the COVID-19 pandemic is causing unprecedented challenges in healthcare delivery and accessibility for the older adult population in Malaysia (Mustaffa et al., 2020).

As there is no specific treatment for COVID-19 and no vaccine to prevent the infection, preventive measures are the current most important step to prevent COVID-19. In the present era of the COVID-19 pandemic, older people may experience unique challenges in practising prevention measures against COVID-19. Digital technologies have been widely used in communication to confront COVID-19 pandemic. Unfortunately, older people are not currently well positioned to take advantage of social technologies (Moore & Hancockm, 2020; Schreurs et al., 2017). Deficiencies in digital literacy among the older people may lead to a lack of knowledge or misinformation about COVID-19 that may lead to disastrous consequences, such as lack of compliance to recommended prevention practices (Wolf et al., 2020). In addition to a greater risk of infection, COVID-19 is also exacerbating the mental health risk among older people. There is ample evidence showing mental health disorders in older people associated with self-isolation, social distancing and quarantine for COVID-19 (Armitage & Nellums, 2020; Santini et al., 2020; Sepulveda-Loyola et al., 2020), resulting in a greater challenge for older people having to practice quarantine and social distancing (Radwan et al., 2021).

A COVID-19 vaccine is likely the most effective approach to sustainably control the spread of coronavirus SARS-CoV-2. Currently, developing a vaccine against SARS-CoV-2 is proceeding at an unprecedented pace. Vaccine candidates move through field trials with unparalleled speed, with some candidates beginning phase 3 studies within 4 months of the start of vaccine development (Hodgson et al., 2020). As of 19th October, 2020, the landscape of SARS-Cov2 vaccine development in the world shows that there are currently 154 candidate vaccines in preclinical evaluations (WHO, 2020b). The Joint Committee on Vaccination and Immunization (JCVI) reported that people older than 65 years of age, high-risk groups and healthcare workers are the groups on the priority list for COVID-19 vaccination (Hassan et al., 2020). Despite the fact that older people are the age demographic most in need of the COVID-19 vaccine, vaccination against COVID-19 among this group remains the greatest challenge. Due to age-related immunosenescence, people of old age may lose the ability to acquire immunity through vaccination resulting in the vaccine being not as effective in older people. Current researchers continue to test the vaccine for safety and effectiveness in older people (Nature, 2020). COVID-19 vaccine acceptance among older people in Malaysia is unknown. Therefore COVID-19 vaccine acceptance or hesitancy among the older people warrant investigation. As the battle against COVID-19 has to put together behavioural prevention practices along with providing a vaccination when one becomes available, this study aimed to determine the behavioural prevention practices against SARS-CoV-2 infection and the intention to vaccinate among older people.

2 METHOD

An anonymous Internet-based, cross-sectional survey was commenced on 14th July and 8th October 2020 (Figure 1). The inclusion criteria were that the respondents were from the general public of Malaysia, aged over 60 years old. The researchers used social network platforms (Facebook, Twitter, Instagram and WhatsApp) to disseminate and advertise the survey link to the public. Recipients of the survey link who were not in the inclusion criteria age were encouraged to assist older people's family members in answering the survey. The questionnaire was developed in English and translated into Bahasa Malaysia, the national language of Malaysia. Questions were presented in both English and Bahasa Malaysia in the survey link. A multidisciplinary team of researchers, clinicians and academicians validated the content of the questionnaire. Pilot-testing was performed with 30 participants for clarity of the items and also suggestions for improvement. A minor revision was made based on the results of the pilot. Subsequently, the revised questionnaire was further pretested before field administration.

COVID-19 cases trend in Malaysia and data collection period

The first section of the survey assessed demographic background and participants’ health status. A question on the source of COVID-19 information was also asked. The second section investigated attitudes towards COVID-19 based on the Health Belief Model (HBM) (Becker, 1974; Champion & Skinner, 2008; Rosenstock, 1974). Questions on perceived susceptibility (1 item) and severity (1 item) asked participants to rate their level of likelihood of becoming infected with SARS-CoV-2 and their level of worry over SARS-CoV-2 infection, respectively. Questions on perceived benefits (2 items) assessed participants’ perception of benefits in carrying out preventive measures and healthy adherence to healthy lifestyle habits. Perceived barrier (1 item) determined the difficulties in carrying out prevention measures against SARS-CoV-2 infection. Perceived self-efficacy (1 item) assessed one's capabilities to perform targeted preventive behaviours by reinforcing positive steps and the belief that one has the ability to overcome a given situation. Cues to action (1 item) was assessed in this study in order to better understand what participants perceived to have received motivating them to undertake mitigating actions.

The third section assessed anxiety level using the 6-item state version of the State-Trait Anxiety Inventory (STAI-6) (Hou et al., 2015; Marteau & Bekker, 1992). The six items of the STAI in Malaysia language was adapted from the validated full 20-item STAI (Hashim et al., 2018). Respondents rated the frequency of experiencing six emotional states, namely being calm, tense, upset, relaxed, content and worried, connected with the current COVID-19 outbreak. A four-point scale was used (1, not at all; 2, somewhat; 3, moderately; 4, very much). The scores on the three positively worded items were reverse coded. The total summed scores were pro-rated (multiplied by 20/6) to obtain scores that were comparable with those from the full 20-item STAI (giving a range of 20–80) (Marteau & Bekker, 1992). A cut-off score of 44 was used to indicate moderate to severe symptoms (Knight et al., 1983; Leung et al., 2005).

The fourth section of the questionnaire queried participants' practice towards measures in preventing SARS-CoV-2 infection (five items), which include the use of a face mask, the practice of hand hygiene, social distancing, healthy lifestyles and avoiding crowds. A four-point scale was used (0, not at all; 1, rarely; 2, sometimes; 3, all the time). The scores on the preventive practices range from 0 to 15, with a higher score implying a greater level of prevention.

The last section assessed attitudes towards COVID-19 vaccination using self-developed instruments (five items) and vaccination intention. A four-point scale was used to assess attitudes towards COVID-19 vaccination (1, strongly agree; 2, agree; 3, disagree; 4, strongly disagree). Two items of the scale were reverse coded. The vaccination attitude score ranges from 5 to 20, with a higher score implying a higher level of positive attitude towards COVID-19 vaccination. The intention to accept a COVID-19 vaccine was measured using a one-item question (If a vaccine against COVID-19 was available on the market, would you take it?) on a four-point scale (definitely no to definitely yes).

2.1 Statistical analysis

The reliability of the scales used was evaluated by assessing the internal consistency of the items representing the scores. The STAI-6 items and preventive measures had a reliability (Cronbach's α) of 0.873 and 0.641, respectively. The reliability computed for the attitudes towards COVID-19 vaccination scale was 0.404.

Multivariable logistic regression analysis (MLRA), using a simultaneous forced-entry method, was used to determine the factors influencing practice towards measures in preventing SARS-CoV-2 infection and COVID-19 vaccination intention. Odds ratios (OR), 95% confidence intervals (95% CI) and p values were calculated for each independent variable. The model fit was assessed using the Hosmer−Lemeshow goodness-of-fit test (Hosmer et al., 2013). Small p values (<0.05) mean that the model is a poor fit. All statistical analyses were performed using the Statistical Package for the Social Sciences, version 20.0 (IBM Corp., Armonk, NY, USA). The level of significance was set at p < 0.05.

2.2 Ethical considerations

This research was approved by the University of Malaya Research Ethics Committee (UM.TNC2/UMREC – 994). Participants were informed that their participation was voluntary, and consent was implied by the completion of the questionnaire.

3 RESULTS

A total of 754 completed responses were received. Table 1 shows the overall distribution of baseline characteristics of the study participants. The mean age ±standard deviation (SD) of the study participants is 67.3 ± 6.0 years, age range 60–100 years old. The majority were aged between 60 and 70 years old (74.5%), with a highest education level of tertiary education (71.5%), were of Chinese descent (61.9%), and from the Central region (73.5%). The majority received information related to COVID-19 from mass media (55.2%) and social media (39.8%).

TABLE 1. Demographics of study participants and factors associated with total preventive measures scores (N = 754) N (%) Univariable analysis Multivariable analysis Total prevention measures score

Logistic regression

Score 14–15 vs. 0–13

Score 14–15

n = 428

Score 0–13

n = 326

p-value OR (95 CI%) Socio-demographic characteristics Gender Male 354 (46.9) 186 (52.5) 168 (47.5) 0.033 Reference Female 400 (53.1) 242 (60.5) 158 (39.5) 1.47 (1.07–2.03)* Age group (years old) 60–70 562 (74.5) 330 (58.7) 323 (41.3) 0.076 70–100 192 (25.5) 98 (51.0) 94 (49.0) Ethnicity Malay 208 (27.6) 111 (53.4) 97 (46.6) Chinese 467 (61.9) 272 (58.2) 195 (41.8) 0.539 Indian 53 (7.0) 32 (60.4) 21 (39.6) Others 26 (3.4) 13 (50.0) 13 (50.0) Highest educational level Secondary and below 215 (28.5) 106 (49.3) 109 (50.7) 0.009 Reference Tertiary education 539 (71.5) 322 (59.7) 217 (40.3) 1.41 (0.97–2.00) Main income source Financial support from children or family 104 (13.8) 50 (48.1) 54 (51.9) Pension/EPF/Community welfare assistance 391 (51.9) 232 (59.3) 159 (40.7) Currently still working 142 (18.8) 80 (56.3) 62 (43.7) 0.234 No financial assistance 117 (15.5) 66 (56.4) 51 (43.6) Living place Northern 96 (12.7) 60 (62.5) 36 (37.5) Central 554 (73.5) 310 (56.0) 244 (44.0) Southern 24 (3.2) 15 (62.5) 9 (37.5) 0.580 East coast 16 (2.1) 7 (43.8) 9 (56.2) East Malaysia 64 (8.5) 36 (56.2) 28 (43.8) Health status Diagnosed with any chronic diseases Yes 253 (33.6) 126 (49.8) 127 (50.2) 0.006 Reference No 501 (66.4) 302 (60.3) 199 (39.7) 1.28 (0.90–1.81) BMI status Underweight 53 (7.0) 26 (49.1) 27 (50.9) Reference Normal 526 (69.8) 315 (59.90) 211 (40.1) 0.032 1.04 (0.55–1.96) Overweight 175 (23.2) 87 (49.7) 88 (50.3) 0.73 (0.37–1.45) Smoking status Yes 56 (7.4) 27 (48.2) 29 (51.8) No 698 (92.6) 401 (57.4) 297 (42.6) 0.207 Independent in doing all daily activities Yes 729 (96.7) 417 (57.2) 312 (42.8) 0.220 No 25 (3.3) 11 (44.0) 14 (56.0) COVID-19 information Main source of information Mass media 418 (55.2) 236 (56.7) 180 (43.3) Social media 300 (39.8) 177 (59.0) 123 (41.0) 0.073 Family members, relatives, friends 38 (5.0) 15 (39.5) 23 (60.5) Attitudes towards COVID-19 Perceived susceptibility Based on my overall health, my chance of catching the Covid-19 coronavirus disease is high Agree/Strongly agree 429 (56.9) 225 (52.4) 204 (47.6) Reference Disagree/Strongly disagree 325 (43.1) 203 (62.5) 122 (37.5) 0.006 1.07 (0.74–1.54) Perceived severity Based on my overall health, if I caught the COVID-19 coronavirus disease, I believe I could be seriously affected Agree/Strongly agree 551 (73.1) 293 (53.2) 258 (46.8) 0.001 Reference Disagree/Strongly disagree 203 (26.9) 135 (66.5) 68 (33.5) 1.26 (0.84–1.91) Perceived benefit If I carry out recommended preventive measures (eg wear mask, social distancing)my chance/risk to catch the COVID-19 coronavirus disease will be low Agree/Strongly agree 747 (99.1) 424 (56.8) 323 (43.2) 1.000 Disagree/Strongly disagree 7 (0.9) 4 (57.1) 3 (42.9) If I carry out healthy eating habits and/or exercise regularly the chances of me getting COVID-19 is low Agree/Strongly agree 516 (68.4) 310 (60.1) 206 (39.9) 0.007 1.53 (1.09–2.14)* Disagree/Strongly disagree 238 (31.6) 118 (49.6) 120 (50.4) Reference Perceived barrier I always have difficulty (eg. forget, cannot get mask) to carry out preventive measures (eg wear mask, social distancing) Agree/Strongly agree 102 (13.5) 29 (28.4) 73 (71.6) Reference Disagree/Strongly disagree 652 (88.5) 399 (61.2) 253 (38.8) p < 0.001 3.01 (1.85–4.91)*** Perceived self-efficacy I can always carry out prevention practices Agree/Strongly agree 695 (92.2) 419 (60.3) 276 (39.7) p < 0.001 6.58 (3.10–13.96)*** Disagree/Strongly disagree 59 (7.8) 9 (15.3) 50 (84.7) Reference Cues to action Hearing someone I know (family/friend) infected by COVID-19 makes me more aware/likely to carry out prevention practices Agree/Strongly agree 709 (94.0) 402 (56.7) 307 (43.3) 1.000 Disagree/Strongly disagree 45 (6.0) 26 (57.8) 19 (42.2) Anxiety Anxiety level Low anxiety (20–43) 560 (74.3) 334 (59.6) 226 (40.4) 1.21 (0.84–1.73) High anxiety (44–80) 194 (25.7) 94 (48.5) 100 (51.5) 0.007 Reference a Hosmer–Lemeshow test, chi-square: 11.673, p-value: 0.166; Nagelkerke R2: 0.171. * p < 0.05. ** p < 0.01. *** p < 0.001. 3.1 Health Belief Model constructs measuring attitudes towards COVID-19

Over half (56.9%) of all the participants either strongly agreed or agreed that the chance of them becoming infected with SARS-CoV-2 is high (perceived susceptibility). Regarding perceived severity, 73.1% of all participants either strongly agreed or agreed that SARS-CoV-2 infection would be harmful to them. The majority (99.1%) perceived the benefit of carrying out preventive measures. Slightly over two-thirds (68.4%) perceived the benefit of practising healthy lifestyles in reducing the risk of infection. Under the perceived barriers construct, a minority (13.5%) reported having difficulties in carrying out preventive measures. The majority (92.2%) either strongly agree or agree that they can always carry out prevention practices. The majority also reported that (94.0%) hearing that someone in the family or a friend tests positive for COVID-19 is a cue to carry out prevention practices.

3.2 Anxiety level

Using a cut-off score of 44 for the STAI score, a total of 25.71% (95% CI 22.6–29.0) of the overall respondents reported moderate to severe anxiety. There were significant ethnic-related differences in the level of anxiety. Among the three main ethnic groups, the anxiety levels were highest among the Indian ethnicity (41.5%), followed by Malay (27.9%) (χ2 = 10.00, df =3, p = 0.019). A higher proportion of participants with existing chronic disease reported moderate to severe anxiety (31.2%) than those without chronic disease (23.0%) (χ2 = 6.018, df = 1, p = 0.017). A higher proportion of participants who depend on others in doing daily activities (48.0%) reported moderate to severe anxiety than those who are independent (25.0%) (χ2 = 6.711, df = 1, p = 0.010).

3.3 Prevention practices

Figure 2 shows the proportion of all the time responses for all the practice towards measures in preventing SARS-CoV-2 infection. The highest proportion reported all the time wearing a mask (84.2%; 95% CI 81.4–86.7) and practising hand hygiene (82.5%; 95% CI 79.6–85.1). The lowest proportion (56.5%; 95% CI 52.9–60.1) reported all the time avoiding going to crowded places. The mean overall total preventive practices score was 13.4 ± 1.73 out of the possible range 0–15. The median was 14.0 (IQR = 13.0–15.0). The prevention measure scores were categorised as a score of 14–15 or 0–13 based on the median split: thus, 428 (56.8%; 95% CI = 53.1–60.3) were categorised as having a score of 14–15 and 326 (43.2%; 95% CI = 39.7–46.9) with a score of 0–13. By demographic, females reported significantly higher total practices score than males. Participants with highest education level tertiary education reported higher prevention practices than those of secondary level and below (Table 1). Most of the HBM constructs were significantly associated with prevention practice scores. In the MLRA, perceived self-efficacy to carry out prevention practices was the strongest predictor of high prevention practices (OR = 6.58; 95% CI 3.10–13.96) followed by low difficulties in perceived barriers in prevention (OR = 3.01; 95% CI 1.85–4.91) and perceived benefits (OR = 1.53; 95% CI 1.09–2.41). Being female remains a significant correlate of higher prevention practices (OR = 1.47; 95% CI 1.07–2.03). Although there is a significant association between anxiety levels and prevention practices in the univariable analysis, the association is not significant in the MLRA.

Proportion of all the time responses for practises against COVID-19 (N = 754)

3.4 Vaccination attitudes and intention

Figure 3 shows the responses to vaccination attitudes. The majority (91.6%; 95% CI 89.4–93.5) strongly agreed or agreed that they will take the COVID-19 vaccine if recommended by a healthcare provider. Concerns of side effects of a new COVID-19 vaccine were reported by 71.4% (95% CI 68–74.6) of the participants. Slightly over half (58.4%; 95% CI 54.7–61.9) reported cost may be a barrier tor COVID-19 vaccine uptake. Only a small proportion (19.2%; 95% CI 16.2–22.2) felt that a COVID-19 vaccine is not needed for people of old age. The mean overall total vaccination attitude score was 13.4 ± 2.4 out of the possible range of 5–20. The median was 13.0 (IQR = 12.0–15.0). The vaccination attitude scores were categorised as a score of 13–20 or 5–12, based on the median split: thus, 509 (67.5%; 95% CI = 64.0–70.8) were categorised as having a score of 13–20 and 245 (32.5%; 95% CI = 29.2–36.0) with a score of 5–12.

Proportion of strongly agree or agree responses for attitudes towards COVID-19 vaccination (N = 754)

Findings on the intention to receive a COVID-19 vaccine revealed that a total of 657 (87.1%; 95% CI 84.5–89.4) participants responded yes to COVID-19 vaccine intent, while only 97 (12.9%; 95% CI 10.6–15.5) responded no. By a more specific breakdown, the majority responded definitely yes (55.0%; 95% CI 51.4–58.6) followed by probably yes (32.1%; 95% CI 28.8–35.6%). Only 2.1% (95% CI 1.2–3.4) responded definitely no and 10.7% (95% CI 8.6–13.2) reported probably no.

Table 2 shows the responses of definitely/probably yes against the definitely no/probably no) in vaccination intention by demographics, attitudes towards COVID-19 vaccination, anxiety level, prevention practices and vaccination attitudes. MLRA revealed that having a higher vaccination attitude score was 16 times more likely to accept the COVID-19 vaccination (OR = 16.10; 95% CI 8.97–28.91). Of all the HBM constructs, only cues to action emerged as a significant correlate of vaccination intent (OR = 4.25; 95% CI 1.80–10.03). Participants of normal weight (OR = 3.19; 95% CI 1.42–7.16) and overweight (OR = 2.02; 95% CI 0.83–4.91) were reported more likely to express intention to receive the COVID-19 vaccination. Lastly, participants below the age of 70 expressed a higher intention to receive the COVID-19 vaccination (OR = 2.07; 95% CI 1.19–3.58).

TABLE 2. Factors associated with intention to be vaccinated against COVID-19 (N = 754) N (%) Univariable analysis Mulrivariable analysis Intention to be vaccinated

Logistic binary regression

Intention to b