The coronavirus disease, or COVID-19, poses an unprecedented challenge to public health, specifically among the 962 million older adults worldwide (United Nations, Department of Economic and Social Affairs, Population Division, 2017). Emerging data show that persons age ≥60 years have a higher risk of mortality, and this risk increases exponentially for those with comorbidities such as frailty, dementia, and chronic medical conditions (e.g., cardiovascular disease, diabetes, lung disease) (Pan et al., 2020). It is alarming to hear that thousands of older adults and staff in nursing homes have lost their lives to COVID-19 (Werner et al., 2020). The COVID-19 infection rate in Malaysian nursing homes was <9%, with only five 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 influenza 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 significant (McMichael et al., 2020). The 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 mitigating COVID-19 risk among nursing home residents and staff. For example, individuals who perceive that wearing face masks is a good protective measure for vulnerable populations, such as nursing home residents, will likely adhere to the recommendation 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 societies (Officer & 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 stake-holders of gaps that exist for remediation and public health education or interventions.
Health education during the pandemic has relied heavily on digital and internet technology as delivery channels 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). However, 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 Center, 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 penetration 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 care-givers and nursing home staff).
To date, little is known about mobile technologies’ effects and use among informal caregivers of older adults in communities and nursing homes. The 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. The 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 Helsinki and in adherence to the Caldicott principles. Participants were advised to read the standardized study information sheet and click the button indicating consent.
Sampling and Procedure
Based on 80% power, alpha of 0.05, and modest effect 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). The 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 participate. By relying on professional and personal networks of researchers, the online survey was circulated on popular social media platforms among Malaysian 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 specific 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 Prevention [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. Three lay persons pretested the questionnaire and affirmed 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, preventive 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 accordingly 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 continuum 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’ sociodemographics, living arrangement with older parents, and access to internet communication technology (ICT).
Statistical Analysis
All data analyses were performed using IBM SPSS version 26. Descriptive analysis, exploratory factor analysis, and general linear model procedures were used. For all tests, the level of significance was set at 0.05.
Results
A total of 611 respondents participated. 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 excluded from analysis. A sizable 42.1% (n = 257) of participants disagreed and 17% (n = 104) were uncertain of the statement “The use of hand sanitizer on soiled hands is not effective to kill the virus.”
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Table A: Distribution of public’s responses to 16 items on perception towards mitigation of COVID-19 riskamong older people in nursinghomes and 9 items on knowledge of disease symptoms (N=611) |
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 Territory of Kuala Lumpur (19.5%). These two states had the highest number of COVID-19 cases and also a large proportion of nursing homes (Department of Social Welfare, 2018). Most participants had access to ICT; 86.9% owned a computer (e.g., desktop, 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%).
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Table B: Perception by demographic characteristics of participants (N=611) |
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. There 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%). The uncertainty on practices related to hand hygiene was 3.6% to 4% and face mask use was 6%. Assessment on knowledge shows that 15% to 53% of participants were unsure or did not know that fatigue, flu-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. The results are shown in Table B. Among the variables tested, only level of education and gender were significant (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. The highly supportive perception could have resulted from a heightened awareness among the Malaysian public from coordinated efforts undertaken by government agencies (i.e., Ministry of Health and the National Security Council). The initial COVID-19 misinformation leading to misperception among the public was aggressively tackled with multiple strategies since the nation’s lockdown began on March 18, 2020. The Malaysian government disseminated 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. Those observations imply that coordinated and timely efforts using appropriately designed material and suitable delivery modes are several factors to be considered in promoting and enhancing perception levels.
The current study found gender and educational level to be associated with perception. Females demonstrated higher supportive perception than males. This difference in perception between genders could be attributed to women being generally more pro-active and concerned about the impact 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, enabling them to acquire and comprehend the flood of information, and had better financial status to afford internet technology, which kept them well-informed. Two implications from these findings are as follows. First, additional qualitative research is recommended to explore gender perspectives on COVID-19 issues. Second, 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 beyond the scope of the current article to elaborate on the ever-growing literature describing the different learning behaviors and different 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. This finding 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 incorporated in the current educational campaign on COVID-19. The 6% non-supportive perception on wearing face masks for nursing home visitors is open to differing views. Interim guidelines on public use of face masks are subject to change according to the latest evidence or debate. One fact remains—the fluid-resistance property of surgical face masks forms a good physical barrier between wearer and the immediate environment; thus, face masks offer added protection for older adults and nursing home staff from asymptomatic infected visitors.
The misperception surrounding 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 official report on a cluster case from aged-care facilities in Selangor state (Ministry of Health Malaysia, 2020b), 18% of participants, albeit low, were uncertain that older adults in nursing homes also were at risk of contracting COVID-19. The 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 deficiency in knowledge among caregivers may lead to delayed recognition of COVID-19, as older adults may be incapable of verbalizing symptoms due to cognitive impairment 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 counter 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. The 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 authorities, 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 efforts for mitigation and strategies for interventions should be rolled out to benefit the 350 registered and >1,000 unregistered residential aged-care facilities operated by nongovernmental organizations and private entities (Hasmuk et al., 2020). Initiatives proposed should aim to draw participation from all operators of aged-care facilities, especially unregistered facilities, by offering 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 curriculum 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. The 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-bandwidth modalities, such as low-cost social media apps, can be used. Social 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 turnover.
Limitations
The 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 socioeconomic status, no internet access). On the other hand, this survey portrays the viewpoint of targeted respondents with older parents (age >65 years). Although items in the perception questionnaire are dependent on the interim guidelines, there is no major deviation of current policies that invalidates the findings. The inherent socially desirable response bias of self-reported questionnaires was minimized 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. Findings 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 offering a wide range of services and supports to caregivers of older adults in the community and nursing homes.
References
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Distribution of public’s responses to 16 items on perception towards mitigation of COVID-19 riskamong older people in nursinghomes and 9 items on knowledge of disease symptoms (N=611)
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | ||||
| 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 symptomcan 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) | ||||||||||||
| 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 score mean (SD) | 4.52 (0.48) | ||||||||||||
| 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 temperatureand 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 | |
| Cronbach alpha reliability (α) | α= .863 | ||||||||||||
| Domain score mean (SD) | 4.64 (0.46) | ||||||||||||
| 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 | |
| Cronbach alpha reliability (α) | α= .797 | ||||||||||||
| Domain score mean (SD) | 4.50 (0.46) | ||||||||||||
| n | (%) | n | (%) | |
|---|---|---|---|---|
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| 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%) |
| 90 | (14.7%) | |||
Perception by demographic characteristics of participants (N=611)
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean | (SE) | p | Mean | (SE) | p | Mean | (SE) | p | Mean | (SE) | p | |||
| <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) | ||||
| Male | 190 | (31.1) | 4.28 | (0.06) | 0.110 | 4.43 | (0.06) | 4.55 | (0.06) | 4.39 | (0.06) | |||
| Female | 421 | (68.9) | 4.35 | (0.05) | 4.55 | (0.05) | 4.65 | (0.05) | 4.52 | (0.05) | ||||
| 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) | ||||
| Tertiary | 530 | (86.7) | 4.44 | (0.05) | 4.55 | (0.05) | 4.66 | (0.05) | 4.55 | (0.05) | 0. |
|||
| Up to secondary | 81 | (13.3) | 4.18 | (0.07) | 4.43 | (0.07) | 4.55 | (0.07) | 4.37 | (0.07) | ||||
| 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) | ||||
| 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) | ||||
| 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) | ||||
| 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) | ||||
| 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) | ||||
| 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) | ||||
| 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) | ||||
