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Article

COVID-19 and Its Influence on Prevalence of Dementia and Agitation in Australian Residential Aged Care: A Comparative Study

by
Yunshu Zhu
1,
Ping Yu
1,*,
Wanqing Li
1,
Ting Song
1,
Zhenyu Zhang
1,
Mengyang Yin
1,2,
Hui Chen (Rita) Chang
3,
Lixin (Lee) Song
4 and
Chao Deng
5
1
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
2
Clinical System Analyst, Opal HealthCare, Sydney, NSW 2000, Australia
3
School of Nursing and Midwifery, Western Sydney University, NSW 2148, Australia
4
School of Nursing, Center for Smart and Connected Health Technologies, UT Health San Antonio, San Antonio, TX 78229, USA
5
School of Medical, Indigenous and Health Sciences, University of Wollongong, Wollongong, NSW 2522, Australia
*
Author to whom correspondence should be addressed.
Psychiatry Int. 2024, 5(4), 642-659; https://doi.org/10.3390/psychiatryint5040046
Submission received: 17 July 2024 / Revised: 19 September 2024 / Accepted: 27 September 2024 / Published: 30 September 2024
Review Reports Versions Notes

Abstract

:
Agitation is one of the most common and persistent behavioral and psychological symptoms among persons with dementia (PWD) in residential aged care facilities (RACFs). While most studies have explored the general impact of COVID-19 on the mental health and well-being of aged care residents, there has been limited research on the pandemic’s impact on agitation in dementia within RACFs. This knowledge is crucial to ensuring that RACFs are better equipped to handle future public health emergencies. Therefore, this retrospective cohort study investigates the impact of the pandemic on agitation incidents within 40 Australian RACFs. Using Python, we extracted agitation symptoms from nursing notes and compared the frequency and percentage of symptom occurrence pre-pandemic versus during-pandemic. Chi-square tests examined any significant change in the prevalence of dementia and agitation in dementia between the comparative groups and periods. Dementia prevalence dropped significantly during the second year of the pandemic, with a concurrent increase in early-onset dementia cases. Overall, agitation symptoms decreased by 20.1%, but six symptoms significantly increased: resisting (28.98%), wandering (11.78%), restlessness (3.19%), complaining (10.1%), arguing (2.36%), and outbursts (1.74%). Conversely, pacing decreased by 15.88% and speaking loudly decreased by 10.9%. Over half of the care recipients with dementia experienced agitation symptoms 2–5 times each year, increasing from 50.56% in 2019 to 58.28% in 2021. Despite the co-occurrence of symptoms such as falls, confusion, and weakness, there was no evidence to suggest that these comorbidities were specific to COVID-19; rather, they appeared to be prevalent even before the pandemic. Persons with agitation in dementia had a significantly higher death rate during the COVID-19 pandemic than otherwise.

1. Introduction

The COVID-19 pandemic has had a profound impact on our society, with 775 million cases worldwide as of 21 January 2024 [1]. From February 2020 to December 2021, Australia experienced three waves of the COVID-19 pandemic, each increasing in severity [2]. The first wave occurred in March–April 2020, the second in July–September 2020, and the third commenced in August 2021 and continued into December and beyond [3]. The correlation between COVID-19 mortality and advanced age is well-established [4], and this risk is further compounded by concurrent comorbidities [5]. For example, in Canada, the COVID-19-related mortality rate within residential aged care facilities (RACFs) constitutes almost 80% of the national mortality rate [6]. Similarly, in Switzerland, RACFs account for 50% of COVID-19-related deaths [7,8]. In Australia, 75% of COVID-19-related deaths occurred within RACFs from January 2020 to March 2021 [9].
Dementia, characterized by cognitive decline and memory impairment [10], presents significant challenges for RACFs. A study across 185 countries found a significant correlation between dementia and COVID-19 mortality [11]. In Australia, 30% of COVID-19 deaths in the first 10 months of 2020 were among PWD, often residing in RACFs [12]. In addition, 54% of RACF care recipients were diagnosed with dementia during COVID-19 in 2021–2022 [13], with 84% requiring high levels of care due to cognitive impairment, wandering tendencies, verbal and physical behaviors, and depression [14]. These individuals accounted for 75% of all COVID-19-related deaths in RACFs [15].
Agitation, observed in 70%–80% of PWD living in RACFs, encompasses manifestations of disturbed perception, thought, mood, or behavior [16]. Agitated behaviors include, but are not limited to, restlessness, pacing, yelling, attempts to access inappropriate places, resistance to care, physical aggression, verbal disruption, and inappropriate sexual behavior [17]. It is triggered by factors like pain, discomfort, anxiety, disruption in routine, unfamiliar environment, and sensory overload. Agitation limits PWD’s ability to communicate their needs, comprehend their surroundings, adjust their behaviors and seek help [18]. These symptoms have increased with the progression of dementia, specifically during the COVID-19 pandemic [19,20]. Strategies to manage agitation include redirection, repositioning, psychotropic medication, reassurance, routine care practices, and offering of beverages [21,22]. These methods require care staff to have a close personal interaction with care recipients, incorporating input from physicians, allied health clinicians, behavioral therapists, and substitute decision-makers [7,22].
The COVID-19 pandemic and its associated restrictions have significantly impacted RACFs, their care recipients, and care staff [22,23]. In May 2020, Australian RACFs implemented visitation restrictions to reduce infection rates [24], which, while effective, led to a breakdown of social interaction between care recipients and their families. In total, 43% of nurses felt unprepared for the outbreak [25]. Staff faced numerous challenges, including compliance with infection control measures like physical and social distancing [26,27,28], confusion from unclear or rapidly changing guidelines, and shortages of personal protective equipment [29,30]. These challenges were exacerbated by shared communal spaces and close contact living environments in RACFs, leading to emotional strain, physical exhaustion, and contamination concerns among care staff [31,32].
Persons with dementia experienced a multidimensional impact from COVID-19 restrictions, manifesting in heightened levels of agitation, depression, anxiety, and other neuropsychiatric symptoms [33]. Prolonged confinement and delays in addressing other health conditions [34] adversely affected physical and mental health [35], leading to feelings of isolation, loneliness, and boredom [12,22]. Given this context, it is crucial to understand how the COVID-19 pandemic has influenced the prevalence of agitation in dementia within RACFs in Australia. Despite the acknowledged impact [36], there is a lack of empirical evidence demonstrating the extent and nature of this impact on agitation symptoms among PWD living in Australian RACFs. There is a knowledge gap on the impact of the isolation and lack of social services brought by quarantine/lockdowns on people living with dementia and their caregivers.
This study aims to fill this gap. Our primary objective is to gain valuable insights into the impact of the COVID-19 pandemic on the prevalence of dementia and agitation in dementia within RACFs in Australia. Our findings would reflect the impact of the pandemic on PWD and their caregivers [37], which may inform interventions that reduce the overall risk of cognitive decline for COVID-19 survivors [38]. Additionally, the findings can inform policy development, guiding the creation of effective health and safety protocols, and efficient resource allocation [39]. Furthermore, understanding these impacts can support families by improving communication and facilitating safer family visits, ensuring comprehensive care for residents during challenging times.

2. Materials and Methods

2.1. Study Design

This is a retrospective study on secondary analysis of electronic health records (EHRs) from a large, aged care organization running 40 RACFs in New South Wales and Queensland, Australia. The care recipients living in these RACFs were assessed for dementia and agitation in dementia before (2019) and during the pandemic (2020 and 2021) during the same data collection period each year: January to October.

2.2. Ethics Approval

This study was approved by the Human Research Ethics Committee of the University of Wollongong (Registration number 2019/159).

2.3. Datasets

Three de-identified datasets were collected from the participating RACFs: medical diagnosis, demographic data, and nursing progress notes.
The medical diagnosis dataset comprised 79,500 structured diagnostic notes recorded by medical doctors, specialists, allied health or other healthcare professionals who perform diagnostic procedures or interpret diagnostic test results. Since medical diagnoses are typically recorded only once a year, they do not capture the subtle and ongoing health changes in PWD, nor do they record behavioral and psychological symptoms.
The demographic dataset comprises details such as gender and age. A masked unique resident identifier, known as the client ID, was used consistently across all three datasets, allowing data linkage at individual levels.
The nursing progress notes comprised 2.23 million unstructured, free-text entries diligently recorded by registered nurses or enrolled nurses between January 2019 and December 2021. These notes were regularly documented in real-time, recording the care services provided, observations of their health, and activities of daily living. Nursing progress notes focus on symptom management, making them the primary source of information on exceptional conditions and daily health fluctuations. They offer a comprehensive view of a person’s condition, capturing nuances that medical diagnoses might miss. Therefore, nursing notes were the only data source for studying agitation prevalence and presentation in this study.
The 2020 dataset only contained data collected from January to October; further data retrieval was impeded due to the departure of key technical personnel from the aged care organization. During the COVID-19 pandemic, documentation and reporting of COVID-19 cases reverted to paper format following public health orders. These paper records were not accessible to the research team. Consequently, we included only the data collected from January to October each year to ensure a comparable timeframe, and the COVID-19 incidence was not captured.

2.4. Data Processing

2.4.1. Identification of Care Recipients with Dementia

Medical diagnosis was used to identify care recipients with dementia. Healthcare professionals employed four specific diagnostic codes to accurately identify and classify care recipients with dementia: Code 500 for dementia and Alzheimer’s disease (including various subtypes such as early onset, late onset, atypical, mixed type, or unspecified), 510 for vascular dementia, 520 for dementia in other diseases, and 530 for other dementias.

2.4.2. Identification of Agitation in Dementia

As agitation in dementia was documented solely in the free-text nursing progress notes, we applied a rule-based NLP algorithm that we developed [18] and further refined for data extraction. The algorithm refinement involved training the algorithm with 1000 nursing notes that were manually coded by aged care domain experts [40]. Within this dataset, 680 nursing notes documented instances of agitation in dementia (positive rules); the remaining 320 notes did not contain agitation instances. The algorithm achieved a sensitivity of 92.7%, a specificity of 87.3%, and an F-score of 96.3%.
We employed Python (version 3.9), the open-source data analysis library Pandas (version 1.5.3) [41], and our published method [18]. First, we conducted data preprocessing to eliminate (1) irrelevant or duplicate notes, (2) non-alphanumeric characters and punctuations, and (3) stop words, such as “a”, “the”, is”, and “are” using the Python Natural Language Toolkit tokenizer. Second, we conducted rule-based NLP to extract any agitation symptoms for care recipients with dementia. The rules captured the diverse language patterns used to describe all types of agitation symptoms. Additional packages included spaCy [42] and scispaCy (version 0.4.0) libraries [43]. Note that scispaCy has been specifically designed for processing clinical text. The models utilized in scispaCy are pre-trained on gold standard datasets we developed, as described above.

2.4.3. Identification of COVID-19-Related Comorbidities Either Trigger or Result from Agitation in Dementia

Hashan et al. identified 29 COVID-19-related symptoms (see Table 1) across 49 studies, encompassing 8502 RACFs and 25,567 confirmed COVID-19 cases [44]. We applied the rule-based extraction methods described above to extract these 29 COVID-19-related symptoms within 14 days of the identified top eight agitation symptoms’ occurrence.

2.5. Statistical Analysis

The Chi-square test was employed to evaluate the statistical significance of the presence of documented care recipients over three years. Descriptive statistics were employed to examine dementia and agitation prevalence before and during the pandemic. To identify significant differences in prevalence between years within sub-population groups, a Chi-square test was employed. Additionally, within the dementia care recipients, we further investigated the changes in agitation symptoms through the Chi-square test. A paired t-test, executed with IBM SPSS Statistics (version 28) [45], was employed to assess variations in record-taking patterns before and during the pandemic. Furthermore, a content analysis approach was employed to investigate the factors contributing to care recipients’ absence during the years 2020 and 2021. Specifically, the last ten nursing notes for each client were thoroughly examined to identify explicit reasons articulated by care recipients or healthcare providers for their departure. The Chi-square test was subsequently employed to ascertain whether there were statistically significant changes in client numbers between these two years.

3. Results

Significant changes in gender distribution were observed in 2021. Males exhibited a significant increase of 2.52% compared to both 2019 and 2020 (p < 0.05), whereas females experienced a significant decrease during the same period (Table 2). Breaking down sex composition by age group and year, different trends emerged among age groups (Table 3). The youngest (40–65) and oldest (95+) groups maintained consistent sex composition. However, the male composition decreased in the 66–85 age group and significantly increased in the 86–95 age group during the second year of the pandemic. No consistent changes were observed regarding the care recipients’ age distribution over the three years.

3.1. Changes in the Prevalence of Specific Agitation Symptoms during the COVID-19 Pandemic

In 2019, 59 agitation symptoms were observed. This number decreased to 39 in 2020, representing a 33.9% reduction, and declined to 34 in 2021, a 12.82% decrease (see Table 4). Most symptoms that disappeared during the COVID-19 pandemic were likely those triggered by social interactions or occurring in communal settings. Notably, this study consistently documented 31 agitation symptoms across all three years.
A total of eight (25.81%) out of the 31 agitation symptoms exhibited consistent changes, either increase or decrease, over the three years (Table 5). Among these, six symptoms consistently experienced a significant increase from 2019 to 2021: resisting (increased by 28.98%), wandering (increased by 11.78%), restlessness (increased by 3.19%), complaining (increased by 10.1%), arguing (increased by 2.36%), and outbursts (increased by 1.74%) (p < 0.05). Conversely, two symptoms showed a consistently significant decrease from 2019 to 2021, pacing (decreased by 15.88%) and speaking in an excessively loud voice (decreased by 10.9%) (p < 0.05).

3.2. Changes in the Prevalence of Comorbidities of Agitation in Dementia during the COVID-19 Pandemic

Table 5 lists the top 10 co-morbidities related to COVID-19 infection that were observed 14 days before or after the onset of the agitation to understand agitation triggers or consequences. Fall was the top trigger or consequence for all agitation symptoms. The second top one was confusion, and the third was weakness. These three co-morbidities had a decreased trend of occurrence in the second year of the pandemic. In descending order, the other co-morbidities were rash, cough, delirium, vomiting, nausea, dizziness, and headache. The occurrence rate of these comorbidities varied over the years, lacking a consistent pattern.
A total of 10 (32.26%) out of the 31 agitation symptoms remained relatively stable over the three years, while 13 (41.94%) exhibited significant but erratic changes, lacking a discernible pattern (as indicated in Appendix A).

3.3. Comparative Analysis of the Top Five Prevailing Agitation Symptoms

The five most prevailing agitation symptoms were resisting, pacing, wandering, speaking in an excessively loud voice, and restlessness (Table 5). Table 6 compares the average occurrence of these symptoms per recipient per year.
Two symptoms, resisting and pacing, consistently exhibited significant changes over three years, with no significant gender difference in occurrence frequency. The average occurrence of resisting declined significantly from 2.28 times per care recipient in 2019 to 2.03 times in 2021 (p < 0.05), while pacing substantially increased from 1.89 times in 2019 to 4.08 times per resident with the symptom in 2021 (p < 0.05). The rest of the three agitation symptoms, wandering, speaking in an excessively loud voice, and restlessness, exhibited significant gender differences in frequency of occurrence. The occurrence of wandering symptoms in males significantly decreased in three years, dropping from 1.98 times per care recipient in 2019 to 1.69 times in 2021 (p < 0.05). Conversely, the occurrence of restlessness in females significantly increased from 1.8 times in both 2019 and 2020 to 2.24 times in 2021 (p < 0.05). The rest of the symptoms did not exhibit a consistent change pattern.

3.4. Comparative Analysis of the Incidence Rate of Agitation in Dementia

More than half of the care recipients experienced agitation symptoms two to five times each year (Table 7). The portion of this cohort of dementia care recipients significantly increased from 50.56% in 2019 to 58.28% in 2021 (p < 0.05). In 2019, 27.44% of dementia care recipients, totaling 337, experienced agitation symptoms once. By 2021, this proportion had significantly decreased by 6.02%, dropping to 21.42% (p < 0.05). Additionally, agitation exceeding 20 occurrences significantly declined from 2019 to 2021. Due to incomplete records, we could not decide the destination of these care recipients (as indicated in Appendix B).

3.5. Changes in the Number of Nursing Notes per Client between Years

To assess whether the care staff consistently recorded the care recipient’s health condition and care delivered, we compared the number of nursing notes per care recipient over the three-year observation period for 1882 care recipients who stayed in the same RACF. In 2020, there was a significant increase of 20 notes per client compared to the year 2019 (2019: mean: 226, 95% confidence interval (CI): 219.45, 231.68; 2020: mean: 246, 95% CI: 243.55, 248.95) (p < 0.05). However, in 2021, there was a significant decrease of 111 notes per client compared to the year 2020 (2021: mean: 135, 95% CI: 134.98 to 135.42) (p < 0.05). Therefore, the frequency of nursing documentation was not consistent.

3.6. Trends in Care Recipients’ Discharge from RACFs over Three Years

In 2019, the death rate was the highest for PWD without agitation, followed by those without dementia, and the lowest for PWD with agitation (Table 8). In 2020, the highest death rate was observed in PWD with agitation, followed by those without agitation, and the lowest for care recipients without dementia. During the second year of the pandemic, the death rate for PWD with agitation significantly dropped but remained higher than the PWD without agitation. Over the three years, the death rate for PWD without agitation consistently decreased, from the highest in 2019 to the lowest in the three groups in 2021.
The group with PWD but no agitation appeared to have a consistently higher chance of returning home than the other two groups. The opposite trend is observed for PWD with agitation. PWD without agitation also had a higher rate of hospitalization in 2019; although this rank was taken by the group with agitation in 2020. In 2021, the hospitalization rate dropped across the three groups, likely explained by the government policy of treating COVID-19 infection at local residency instead of hospitalization. Yet, the hospitalization rate was higher in the two PWD groups than in those without dementia.
PWD with agitation had the lowest likelihood of transfer between RACFs, which was a rare occurrence. They also had a significantly higher rate of discharge without a clear destination over three years.

4. Discussion

This study aimed to investigate the impact of the COVID-19 pandemic on the prevalence of dementia, and agitation in dementia for care recipients living in Australian RACFs. Knowledge about these impacts can lead to tailored care model design, enhanced staff training, and better resident care. Insight from this research can inform policy development and help RACFs prepare for future crises, supporting both residents and their families through improved communication and care strategies. We have the following significant findings.

4.1. The Possible Reason for the Significant Increase in Male Care Recipients in the Age Group of 86 to 95 in the Second Year of the COVID-19 Pandemic

Notably, there was a significant increase in the proportion of male care recipients in the studied RACFs, particularly in the age group of 86 to 95. This increase could be attributed to the increased life expectancy of the male population over the decades due to social, economic, and public health advancements (e.g., anti-smoking champions) in Australia, which may have led to increased life expectancy for males. The COVID-19 pandemic may have altered family dynamics, placing additional strain on formal community services and informal caregivers, such as family members. Consequently, some families may have been unable to continue providing care at home, leading to increased admission of older men to RACFs. However, without specific admission data, these reasons remain speculative.

4.2. Dementia Prevalence between Sub-Groups during the COVID-19 Pandemic

There was a similar proportion of dementia care recipients before and in the first year of COVID-19, which was consistent with the Australia Institute of Health and Welfare report about dementia rate being around 54–55% between the pre-COVID-19 period (2017–18) and during the COVID-19 period (2021–22) [11]. However, there was a significant decline in dementia care recipients aged 76–95+ in the second year of COVID-19, 2021. This decline may be explained by the increased risk of COVID-19-related mortality with PWD aged over 80, as observed by Tahira et al. [46]
A contrasting trend emerged among the younger-onset dementia group, with a marginal rise in 2020 and a significant surge of 6.06% in 2021. These findings agreed with those of the Australian Institute of Health and Welfare, which documented a progressive escalation in the number of care recipients with younger-onset dementia residing in RACFs over the preceding years [47].
Several factors may have contributed to this increase: (1) direct impact of COVID-19 virus, which can cause neurological damage, such as brain fog, memory loss, and mental fatigue, accelerating dementia progression in at-risk individuals [48]; (2) heightened stress and isolation during the pandemic, which may exacerbate the cognitive decline in those already experiencing early dementia symptoms [49]; (3) disruptions in health services caused by delayed diagnosis and treatment may result in faster dementia progression; and (4) deterioration of pre-existing health conditions, such as cardiovascular problems and damage to organs like the lungs, kidneys and liver, can contribute to long-term cognitive deficits [50].
However, without additional data to confirm these impacts on specific individuals with younger-onset dementia, the exact cause of the observed phenomenon remains inconclusive. This observed significant increase calls for further healthcare planning, resource allocation, and strategy formulation to address the unique needs of younger-onset dementia in the context of pandemic-induced challenges.

4.3. Decline in Overall Agitation Prevalence during the Pandemic Period

It is important to note a significant 20.1% decrease in the overall prevalence of agitation symptoms in dementia during the COVID-19 pandemic (2020–2021). This trend can be attributed to the following factors:
Firstly, the staff’s reduced frequency of nursing documentation in 2021 was likely caused by incomplete recording. In normal situations, nurses dedicate a considerable portion of their work time to EHR documentation, ranging from approximately one-quarter [51] to over one-third of their time [52]. However, their workload was significantly increased due to daily temperature measures and the manual reporting of COVID-19 cases. Staff shortage caused by the infected care staff refraining from returning to RACFs [53] further exacerbated the situation. These factors may lead to declining nursing progress in reporting and monitoring agitation symptoms.
Secondly, the confinement of care recipients to their bedrooms, with limited opportunities to interact with others in common areas, may have reduced instances of physical and verbal aggression. This isolation minimized interactions that could trigger agitation and limited the chances for busy care staff to observe and document such behaviors.
Additionally, the implementation of strict infection control measures, such as restricted visitation, enhanced hygiene practices, and isolation protocols [54], likely contributed to a calmer and less stimulating environment. This reduction in external stimuli may have decreased triggers for agitation among dementia care recipients, specifically for those agitation symptoms likely triggered by social interactions or occurring in communal settings.

4.4. Increased Occurrence of Specific Agitation Symptoms during the COVID-19 Pandemic

While overall agitation prevalence declined during the COVID-19 pandemic, it is essential to note that this apparent calmness was not entirely beneficial. The pandemic saw increased specific agitation symptoms, such as resisting care and wandering. This suggests that, while overall agitation may have declined, certain behaviors persisted or worsened. Our findings align with those of Leontjevas et al. [21] and Kuroda et al. [55], who also observed similar trends during the pandemic. Without additional data, the exact causes of these changes remain inconclusive, but the evidence points to a complex interplay of factors influenced by the pandemic.
Resisting behaviors in PWD often signal a breakdown in communication, stemming from a lack of understanding of care needs or misinterpretation of caregiver intentions [56]. In our study, COVID-19-related behavioral restrictions may have contributed to increased aggression, with significant rises in various physically aggressive behaviors, including fighting, hitting, and biting, observed during the pandemic compared to 2019 (Appendix A Table A2). This finding is consistent with recent research highlighting a surge in aggressive behaviors amid the pandemic [21,37,57].
Our study extends the understanding of aggression to include physical and verbal manifestations. Kuroda et al. reported a higher prevalence of verbal abuse between dementia care recipients and caregivers during the COVID-19 pandemic, with a 2.3% increase. We also found a significant increase in the use of shouting and abusive language, and a slight increase in the use of profane language in 2020 compared to 2019 (Appendix A Table A2). The elevated level of verbal aggression appears to be indicative of the significant stress experienced by PWD in response to changes in their living environment, a stressor that can manifest even in the early stages of cognitive decline [58]. The escalation of verbal abuse and violence places an additional burden on caregivers, emphasizing the complex dynamics involved in dementia care during the pandemic.
Previous research identifies an increased prevalence of emotional distress among PWD in RACFs during the COVID-19 pandemic. These include increased levels of anxiety [20,36], low mood [20], irritability [37], apathy [37], and depression [36]. Specifically, studies have found a surge in irritability within six to ten weeks following the initiation of quarantine measures associated with the COVID-19 pandemic [33]. Our research aligns with these observations, revealing an increase in anger (3.07%), irritability (2.72%), and outbursts (0.87%) in 2020 compared to the preceding year, 2019. The concordance between our findings and prior research underscores the pervasive impact of pandemic-related measures on the emotional well-being of PWD. Therefore, comprehensive dementia care strategies should encompass not only physical health but also the emotional and psychological well-being of PWD, particularly in the context of public health crises.

4.5. Agitation and Co-Morbidities

Research into the co-occurrence of the top eight agitation symptoms and comorbidities likely related to COVID-19 infection identified the top three COVID-19-like symptoms that co-occurred with agitation in dementia: falls, confusion, and weakness. Falls were the most frequently recorded comorbidities with agitation. More than half of resisting behavior observed before (in 2019) and during COVID-19 (in 2020) co-occurred with falls. However, this co-occurrence dropped by half in the second year of the pandemic.
Despite encountering many records mentioning COVID-19 testing, we could not find clear evidence of COVID-19 diagnosis, likely because this diagnosis was recorded in specific paper records by the public health order at that time. All the COVID-19-like symptoms happened at similar or even significantly higher rates in the pre-COVID period than in the COVID-19 period, except for confusion in 2020. Therefore, these findings did not provide clear evidence of the COVID-19 pandemic’s impact on the presentation of agitation systems in PWD. A manager mentioned that the RACFs producing the research data were managed well, with a very low COVID-19 infection rate. Therefore, the observed comorbidities with agitation in PWD were more likely to represent the comorbidities that either triggered or resulted from agitation onset in RACFs, rather than being specific to COVID-19 infection.

4.6. Comparison of Patterns of Departure from RACFs between and during the Pandemic

Our data provide a comprehensive overview of the departure patterns of documented care recipients without dementia, with dementia, and with agitation in dementia. The discharge destinations included death, home, hospital, and other RACFs. Our data show consistently higher rates of death, hospital transfer, and discharge to undecidable destinations for individuals with agitation in dementia than the other two groups but significantly less opportunity to be discharged to home or transferred to another RACF. Not alone, our finding that there was not a direct relationship between dementia rates and COVID-19 was seconded by the conclusion of a systematic review [59].
An interesting finding, which is not directly related to the study question under investigation, is that the overall number of male care recipients was significantly increased.

4.7. Study Limitations

We acknowledge several limitations of this study. Firstly, the research findings were primarily extracted from nursing progress notes in RACFs, which present several limitations: inconsistency in documentation, subjectivity and bias, lack of standardization, human errors, and limited scope [60,61]. For example, missing records on gender and age were excluded from the analysis, limiting the comprehensive understanding of the care recipient profile. Additionally, due to the lack of COVID-19 diagnosis data, we could not ascertain the direct impact of COVID-19 on agitation presentation.
Nonetheless, nursing progress notes are the primary communication tool among aged care staff and with external healthcare providers [61,62]. They are the only source of information about individual care recipients’ needs, preferences, symptoms, nursing interventions, and outcomes, recorded in near real-time. Therefore, they provide a detailed, regularly updated, rich data source for research and quality improvement initiatives. Our natural language processing technique effectively extracted key data to address the research aim.
Our comparative data analysis was confined to January to October over three years instead of the entire year. This period included 83% of the year and all four seasons, so we believe it provided a sufficiently representative sample. However, the generalizability of our findings is limited by the specific geosocial location, the status of COVID-19 infection in the studied RACFs, and the organization of aged care services during the study period. Therefore, caution should be exercised when extrapolating these results to other contexts or timeframes.
Moreover, this observational study in the natural setting did not account for potential confounding factors that could influence the observed outcomes. Although we observed many comorbidities with agitation, there is a lack of evidence to discern the causality between comorbidities and agitation onset, despite knowledge about the individual characteristics of dementia care recipients, such as the severity of cognitive impairment [55].
While this study examined the prevalence of agitation among dementia care recipients before and during the COVID-19 pandemic, it did not thoroughly investigate the underlying reasons for the observed changes in agitation. Factors such as staff training and education, time and resource allocation, individualized care, management strategies, and consistency of care could potentially contribute to fluctuations in agitation symptoms [16]. The lack of in-depth exploration of these factors limits our understanding of the specific mechanisms driving the changes in agitation observed during the pandemic.
Behavioral and psychological symptoms of dementia (BPSD) encompass a wide range of manifestations beyond agitation, including depression and psychosis. This study did not investigate the full spectrum of BPSD. Consequently, the findings regarding the impact of COVID-19 on individuals with dementia in RACFs are constrained. Readers should interpret the results with caution, acknowledging this limitation.
Despite limitations, this study provides valuable insights into the changes in agitation prevalence among dementia care recipients in RACFs before and during the COVID-19 pandemic. It generates evidence about the factors that may trigger or result from agitation in PWD, which can lead to more targeted interventions, management strategies, and departure patterns of different population groups. The insights can inform policy development at both the facility and governmental levels to support better management of agitation, including staff training, improved care protocols, and enhanced support for residents and their families [63].
Future studies can improve upon our research by extending the data collection period to include post-pandemic phases, offering a more comprehensive understanding of trends and potential recovery among PWD in RACFs post-COVID-19. This extension would allow exploring long-term effects and evolving patterns in agitation symptoms. Additionally, integrating data on triggers, interventions, and consequences, such as changes in care protocols or caregiver–care-recipient interactions, would enrich the analysis, contributing valuable insights and aiding the development of targeted interventions.

5. Conclusions

This research revealed a significant reduction in overall dementia prevalence during the second year of the COVID-19 pandemic, accompanied by an increasing trend in early-onset dementia cases. The prevalence of agitation also decreased by 20% during the pandemic. The diminished symptoms were predominantly those in human interactions or communal areas, likely reflecting the effects of COVID-19-induced isolation. The five most frequently observed agitation symptoms were resisting, pacing, wandering, speaking in an excessively loud voice, and restlessness. Despite the co-occurrence with symptoms such as falls, confusion, and weakness, which were common in both COVID-19 and dementia, there was no evidence to suggest that these comorbidities were specific to COVID-19. Instead, they appeared to be prevalent even before the pandemic. Care recipients with agitation in dementia experienced a higher impact of COVID-19 than their peers without agitation or dementia, as suggested by rates of discharge from RACFs over three years.
Future research should aim to extend data collection to include a broader range of data sets that allow research into causal analysis, providing a more comprehensive understanding of the observed trends and their driving factors. Continuous investigation into agitation and co-morbidities before and after the COVID-19 pandemic is essential to identify triggers, effective interventions, and consequences of agitation in dementia and the impact of COVID-19 and other comorbidities. Such research will be instrumental in designing person-centered care models, improving policies and practices for the care of individuals with dementia in residential aged care facilities, and ensuring that RACFs are better equipped to handle similar public health crises.

Author Contributions

Y.Z. contributed to study conception, methodology, formal analysis, and writing—original draft preparation. W.L., T.S., Z.Z., L.S., H.C.C. and C.D. contributed to the paper review. M.Y. contributed to data resources and paper reviewing. P.Y. contributed to study conception, guidance on methodology, paper reviewing, editing and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Human Research Ethics Committee of the University of Wollongong (Registration number 2019/159). Approval date: 15 January 2024.

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The data are not publicly available due to ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Agitation symptoms that had similar level of prevalence during the COVID-19 pandemic.
Table A1. Agitation symptoms that had similar level of prevalence during the COVID-19 pandemic.
Agitation SymptomsBefore COVID-19During COVID-19
201920202021
n = 1228 (100%)n = 1104 (100%)n = 719 (100%)
Frustration68 (5.54)42 (3.80)34 (4.73)
Using profane language56 (4.56)67 (6.07)34 (4.73)
Threat45 (3.66)40 (3.62)15 (2.09)
Grabbing36 (2.93)25 (2.26)14 (1.95)
Groaning15 (1.22)23 (2.08)11 (1.53)
Kicking11 (0.9)9 (0.82)5 (0.7)
Self-harm behavior8 (0.65)10 (0.91)11 (1.53)
Repetitive questioning4 (0.33)6 (0.54)1 (0.14)
Searching4 (0.33)3 (0.27)2 (0.28)
Mood swing2 (0.16)5 (0.45)1 (0.14)
Note: A Chi-square test was performed, and no statistically significant differences were found between the years (p < 0.05).
Table A2. Inconsistent agitation symptom changes during COVID-19.
Table A2. Inconsistent agitation symptom changes during COVID-19.
Agitation SymptomsBefore COVID-19During COVID-19
201920202021
n = 1228 (100%)n = 1104 (100%)n = 719 (100%)
Shouting88 (7.17) a121 (10.96) b57 (7.93) ab
Screaming56 (4.56) a127 (11.50) b54 (7.51) a
Gesture47 (3.83) ab60 (5.43) a22 (3.06) b
Using abusive language28 (2.28) a62 (5.62) b40 (5.56) b
Constant manipulation of object25 (2.04) a1 (0.09) b1 (0.14) b
Anger19 (1.55) a51 (4.62) b33 (4.59) b
Hitting14 (1.14) a119 (10.78) b77 (10.71) b
Fighting13 (1.06) a156 (14.13) b72 (10.01) b
Throwing object13 (1.06) a10 (0.91) b11 (1.53) ab
Irritability10 (0.81) a39 (3.53) b14 (1.95) b
Requests for reassurance6 (0.49) a24 (2.17) b10 (1.39) ab
Fidgeting2 (0.16) a34 (3.08) b19 (2.64) b
Biting2 (0.16) a10 (0.91) b10 (1.39) b
Note: The notations a, b and ab follow the same rules described in Table 2. Different superscript labels, a and b represent significant differences from Chi-square tests between the respective years: 2019, 2020, and 2021 (p < 0.05). Label ‘ab’ suggests similar results with both data with label ‘a’ and that with label ‘b’.

Appendix B

Table A3. Frequency distribution of care recipients who had agitation episodes over 20 times, and their destination.
Table A3. Frequency distribution of care recipients who had agitation episodes over 20 times, and their destination.
Frequency of Agitation EpisodesThe Path of the Care Recipients201920202021
No. Care Recipients (%)No. Care Recipients (%)No. Care Recipients (%)
Total 13 (100%)8 (100%)1 (100%)
21–25Continue stay in RACFs 4 (30.77)7 (87.5)0 (0)
Deceased1 (7.69)0 (0)0 (0)
Transfer to hospital2 (15.38)0 (0)0 (0)
Not decidable6 (46.15) a1 (12.5) b1 (100) c
Total 10 (100%)2 (100%)0 (100%)
26–30Continue stay in RACFs 1 (10)2 (100) 0 (100)
Deceased000 (100)
Transfer to hospital000 (100)
Not decidable9 (90)00 (100)
Total 14 (100%)1 (100%)0 (100%)
31 and aboveDeceased2 (14.29)0 (0)0 (100)
Not decidable12 (85.71)1(100)0 (0)
Note: The notations a, b, and c follow the same rules described in Table 2. Different superscript labels, a, b, and c, represent significant differences in data between the respective years: 2019, 2020, and 2021 (p < 0.05).

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Table 1. Keywords for Identifying COVID-19-Related Symptoms (adapted from Hashan et al. (2021) [44]).
Table 1. Keywords for Identifying COVID-19-Related Symptoms (adapted from Hashan et al. (2021) [44]).
“Cough”, “Dyspnoea”, “Sore throat”, “Rhinorrhoea”, “Hypoxia”, “Polypnea”, “Fever”, “Hypothermia”, “Weakness”, “Malaise”, “Anorexia”, “Myalgia”, “Hypotension”, “Chill”, “Rash”, “Conjunctivitis”, “Diarrhoea”, “Nausea”, “Vomiting”, “Acute gastrointestinal symptoms”, “Ageusia”, “Anosmia”, “Headache”, “Confusion”, “Altered mental status”, “Delirium”, “Fall”, “Dizziness”, “Seizure”
Table 2. Comparison of prevalence of dementia and agitation in dementia during the COVID-19 pandemic: number and percentage, by gender and age.
Table 2. Comparison of prevalence of dementia and agitation in dementia during the COVID-19 pandemic: number and percentage, by gender and age.
DemographicsBefore COVID-19During COVID-19
201920202021
No. of care recipients (%)n = 3528 (100%)n = 3495 (100%)n = 2692 (100%)
Sex
Male
Female
1261 (35.74) a1249 (35.74) a1030 (38.26) b
2267 (64.26) a2246 (64.26) a1662 (61.74) b
Age group (yrs)
40–65
66–75
76–85
86–95
95+
108 (3.06) a108 (3.09) a79 (2.93) b
414 (11.73) a456 (13.05) b274 (10.18) c
1010 (28.63) a1049 (30.01) a712 (26.45) b
1645 (46.63) a1600 (45.78) a1285 (47.73) b
351 (9.95) a282 (8.07) b342 (12.70) c
No. of care recipients with dementia (%)n = 1556 (44.10) an = 1615 (46.21) an = 1134 (42.12) b
Sex
Male553 (43.85) a594 (47.56) a448 (43.50) b
Female1003 (44.24) a1021 (45.46) ab686 (41.28) b
Age group (yrs)
40–65
66–75
76–85
86–95
95+
29 (26.85) a30 (27.78) a26 (32.91) b
145 (35.02) a178 (39.04) b110 (40.15) c
476 (47.13) a536 (51.10) b315 (44.24) c
774 (47.05) a772 (48.25) a544 (42.33) b
132 (37.61) a99 (35.11) b142 (41.52) c
No. of care recipients with agitation in dementia (%)n = 1228 (78.92) an = 1104 (68.36) bn = 667 (58.82) c
Sex
Male440 (79.57) a417 (70.20) a260 (58.04) b
Female788 (78.56) a687 (67.29) b407 (59.33) c
Age group (yrs)
40–6521 (72.41) a14 (46.67) b10 (38.46) c
66–75118 (81.38) a129 (72.47) b65 (59.09) c
76–85390 (81.93) a385 (71.83) b180 (57.14) c
86–95604 (78.04) a513 (66.45) b326 (59.93) c
95+95 (71.97) a63 (63.64) b86 (60.56) c
Note: 1. % of care recipients with dementia is calculated by dividing the number of care recipients with dementia by the total number of care recipients in one year; for example, in 2019, 1556/3528 = 44.10%. 2. % of care recipients with agitation in dementia is calculated by dividing the number of care recipients with agitation in dementia by the total number of care recipients with dementia in one year; for example, in 2019, 1228/1556 = 78.92%. 3. The same superscript labels (e.g., 2019 and 2020, labeled ‘a’) indicate no statistically significant difference in data between those years. Different superscript labels (e.g., 2019 labeled ‘a’ and 2021 labeled ‘b’) indicate a significant difference in data between those years (p < 0.05). (Label ‘ab’ suggests similar results with both data with label ‘a’ and that with label ‘b’.) Data with three different letters (e.g., 2019 labeled ‘a’, 2020 labeled ‘b’, and 2021 labeled ‘c’) suggest significant differences in data among all three years. This notation applies to all subsequent tables.
Table 3. Change of sex composition in different age groups over three years.
Table 3. Change of sex composition in different age groups over three years.
Age GroupYearTotalMale n (%)Female n (%)
40–65201910852 (48.15)56 (51.85)
202010851 (47.22)57 (52.78)
20217934 (43.04)45 (56.96)
66–752019414295 (71.26) a119 (28.74) a
2020456235 (51.54) b221 (48.46) b
2021274167 (60.95) c107 (39.05) c
76–8520191010517 (51.19) a493 (48.81) a
20201049449 (42.8) b600 (57.2) b
2021712315 (44.24) b397 (55.76) b
86–9520191645480 (29.18) a1165 (70.82) a
20201600458 (28.63) a1142 (71.38) a
20211285466 (36.26) b819 (63.74) b
95+201935163 (17.95)288 (82.05)
202028256 (19.86)226 (80.14)
202134253 (15.5)289 (84.5)
Note. The notations a, b, and c follow the same rules described in Table 2. The same superscript labels (e.g., 2019 and 2020, both labeled ‘a’) indicate no statistically significant difference in male or female composition between those years. Different superscript labels (e.g., 2019 labeled ‘a’ and 2021 labeled ‘b’) indicate a significant difference in data between those years (p < 0.05). Data with three different letters (e.g., 2019 labeled ‘a’, 2020 labeled ‘b’, and 2021 labeled ‘c’) suggest significant differences in data among all three years.
Table 4. Agitation symptom presentation over three years.
Table 4. Agitation symptom presentation over three years.
No. SymptomsSymptoms201920202021
31Resisting, Wandering, Speaking in Excessively Loud Voice, Pacing, Restlessness, Pushing, Complaining, Frustration, Using Profane Language, Screaming, Gesture, Threat, Grabbing, Using Abusive Language, Constant Manipulation of Object, Arguing, Spitting, Anger, Groaning, Hitting, Fighting, Scratching, Throwing Object, Irritability, Constant requests for reassurance, Outburst, Repetitive Questioning, Searching, Mood Swing, Biting, Fidgeting√√√
6Self-Harm Behavior, Kicking, Inappropriate Sexual Behavior, Repetitive Physical, Constant Repetition of Word, Pointing Finger√√
3Absconding, Punching, Rummaging√ √
19Shouting, Hand Wringing, Tearing, Rocking, Destroying Property, Inappropriate Dressing and Undressing, Cursing, Making Noise, Using Hostile Language, Slamming, Constant Requests for Help, Rambling Speech, Negativism, Starring, Inappropriately Handling Object, Hiding, Urinating in the Courtyard, Grunting, Howling√
2Shoving, Self-Talk √
Table 5. Agitation symptoms and associated comorbidities within a 14-day period, both before and after the onset of agitation. Number of PWD with agitation over three years: 2019: n = 1228; 2020: n = 1104, 2021: n = 719.
Table 5. Agitation symptoms and associated comorbidities within a 14-day period, both before and after the onset of agitation. Number of PWD with agitation over three years: 2019: n = 1228; 2020: n = 1104, 2021: n = 719.
Agitation SymptomsYear N (%)FallConfusionWeaknessRashCoughDeliriumVomitingNauseaDizzinessHeadache
Resisting2019546 (44.46) a289 (52.93) a152 (27.84) a31 (5.68) a25 (4.58) 32 (5.86) ab18 (3.3) 13 (2.38) 16 (2.93) 10 (1.83) ab10 (1.83)
2020495 (44.84) a258 (52.12) a128 (25.86) b48 (9.7) b26 (5.25) 39 (7.88) a19 (3.84) 22 (4.44) 14 (2.83) 11 (2.22) a6 (1.21)
2021528 (73.44) b130 (24.62) b53 (10.04) c9 (1.7) c25 (4.73) 22 (4.17) b22 (4.17) 16 (3.03) 16 (3.03) 3 (0.57) b6 (1.14)
Wandering2019407 (33.14) a116 (28.5) a58 (14.25) a7 (1.72) ab13 (3.19) ab5 (1.23) 10 (2.46) 3 (0.74) 3 (0.74) 5 (1.23) 7 (1.72) a
2020399 (36.14) a201 (50.38) b93 (23.31) b13 (3.26) a21 (5.26) a11 (2.76) 13 (3.26) 4 (1) 2 (0.5) 5 (1.25) 3 (0.75) ab
2021323 (44.92) b83 (25.7) a28 (8.67) c2 (0.62) b3 (0.93) b4 (1.24) 15 (4.64) 1 (0.31) 2 (0.62) 2 (0.62) 0 (0) b
Restlessness2019123 (10.02) a67 (54.47) a34 (27.64) a12 (9.76) a11 (8.94) 6 (4.88) 9 (7.32) 1 (0.81) 3 (2.44) 5 (4.07) 1 (0.81)
2020132 (11.96) ab67 (50.76) ab35 (26.52) a7 (5.3) ab16 (12.12) 13 (9.85) 8 (6.06) 4 (3.03) 5 (3.79) 2 (1.52) 0 (0)
202195 (13.21) b36 (37.89) b11 (11.58) b2 (2.11) b6 (6.32) 3 (3.16) 8 (8.42) 1 (1.05) 2 (2.11) 1 (1.05) 0 (0)
Complaining201969 (5.62) a22 (31.88) 12 (17.39) 2 (2.9) 2 (2.9) 4 (5.8) 2 (2.9) 2 (2.9) 3 (4.35) 1 (1.45) 1 (1.45)
2020153 (13.86) b53 (34.64) 13 (8.5) 4 (2.61) 9 (5.88) 3 (1.96) 4 (2.61) 3 (1.96) 1 (0.65) 1 (0.65) 9 (5.88)
2021113 (15.72) b37 (32.74) 9 (7.96) 1 (0.88) 6 (5.31) 8 (7.08) 9 (7.96) 4 (3.54) 2 (1.77) 1 (0.88) 2 (1.77)
Arguing201924 (1.95) a12 (50) 4 (16.67) 0 (0) 1 (4.17) 1 (4.17) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
202034 (3.08) ab13 (38.24) 7 (20.59) 1 (2.94) 1 (2.94) 2 (5.88) 0 (0) 0 (0) 0 (0) 0 (0) 1 (2.94)
202131 (4.31) b7 (22.58) 5 (16.13) 0 (0) 1 (3.23) 0 (0) 3 (9.68) 0 (0) 0 (0) 0 (0) 0 (0)
Outburst20196 (0.49) a5 (83.33) 4 (66.67) a2 (33.33) 0 (0) 3 (50) a0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
202015 (1.36) b7 (46.67) 3 (20) ab1 (6.67) 0 (0) 1 (6.67) ab1 (6.67) 1 (6.67) 1 (6.67) 0 (0) 0 (0)
202116 (2.23) b8 (50) 1 (6.25) b0 (0) 0 (0) 0 (0) b1 (6.25) 0 (0) 0 (0) 0 (0) 1 (6.25)
Pacing2019224 (18.24) a26 (11.61) a10 (4.46) a5 (2.23) 1 (0.45) 0 (0) 2 (0.89) a0 (0) 0 (0) 1 (0.45) a3 (1.34)
202029 (2.63) b10 (34.48) b10 (34.48) b3 (10.34) 0 (0) 0 (0) 0 (0) ab0 (0) 0 (0) 2 (6.9) b1 (3.45)
202117 (2.36) b4 (23.53) ab1 (5.88) ab0 (0) 1 (5.88) 0 (0) 2 (11.76) b0 (0) 0 (0) 1 (5.88) ab0 (0)
Speaking in excessively loud voice2019233 (18.97) a57 (24.46) a30 (12.88) 5 (2.15) 7 (3) a3 (1.29) 5 (2.15) a1 (0.43) 1 (0.43) 1 (0.43) 0 (0)
2020203 (18.39) a72 (35.47) b25 (12.32) 9 (4.43) 8 (3.94) ab6 (2.96) 1 (0.49) a2 (0.99) 1 (0.49) 0 (0) 1 (0.49)
202158 (8.07) b23 (39.66) b5 (8.62) 0 (0) 6 (10.34) b2 (3.45) 7 (12.07) b0 (0) 1 (1.72) 0 (0) 0 (0)
Note: The notations a, b, and c follow the same rules described in Table 2. These notations are used to compare data across three years for one variable. For example, for Restlessness, the label ab suggests that the 2020 data (11.96%) ab showed no significant difference from either the 2019 data (10.02) a or the 2021 data (13.21) b. However, there was a significant difference between the 2019 data (10.02) a and the 2021 data (13.21) b, as indicated by the superscript letters a and b. n: Number of PWD with agitation symptoms each year. The percentage is calculated by dividing the number of individuals with a specific symptom by the total number of individuals with all agitation symptoms each year. For example, in 2019, the percentage of individuals exhibiting the symptom ‘Resisting’ is calculated by 546/1228 = 44.46%.
Table 6. Comparison of the top five prevailing frequently occurring agitation symptoms over three years. Unit of analysis: the number of occurrences per person with the symptom in one year.
Table 6. Comparison of the top five prevailing frequently occurring agitation symptoms over three years. Unit of analysis: the number of occurrences per person with the symptom in one year.
Agitation SymptomsGenderBefore COVID-19During COVID-19
201920202021
n = 1228 (100%)n = 1104 (100%)n = 719 (100%)
ResistingAlla 2.28 (1.87–2.66), n = 546b 2.13 (1.88–2.38), n = 495c 2.03 (1.8–2.27), n = 528
PacingAlla 1.89 (1.45–2.32), n = 224b 2 (0.82–3.18), n = 29c 4.08 (3.4–4.75), n = 17
WanderingFemalea 1.99 (1.75–2.23), n = 274b 2.5 (2.21–2.79), n = 277c 1.74 (1.49–1.99), n = 192
Malea 1.98 (1.64–2.32), n = 133b 1.87 (1.54–2.2), n = 122c 1.69 (1.4–1.98), n = 131
Speaking in excessively loud voiceFemalea 1.71 (1.45–1.97), n = 162b 2.07 (1.74–2.4), n = 148c 1.9 (1.36–2.44), n = 48
Malea 1.7 (1.3–2.1), n = 71b 2.6 (1.91–3.29), n = 55c 1 (0.38–1.62), n = 10
RestlessnessFemalea 1.8 (1.41–2,19), n = 82a 1.8 (1.42–2.18), n = 86b 2.24 (1.71–2.77), n = 68
Malea 1.5 (1.04–1.96), n = 41b 3 (2.13–3.87), n = 46c 2.24 (1.71–2.77), n = 6
Note: The notations a, b, and c follow the same rules described in Table 2. Different superscript labels, a, b, and c, represent significant differences in data between the respective years: 2019, 2020, and 2021 (p < 0.05).
Table 7. Frequency of agitation symptoms in dementia care recipients over three years.
Table 7. Frequency of agitation symptoms in dementia care recipients over three years.
Frequency of Agitation EpisodesNo. Care Recipients (%)
Before COVID-19During COVID-19
201920202021
Total1228 (100%)1104 (100%)719 (100%)
1337 (27.44) a316 (28.62) a154 (21.42) b
2 to 5622 (50.56) a589 (53.35) a419 (58.28) b
6 to 10148 (12.05)117 (10.6)96 (13.35)
11 to 1552 (4.23)49 (4.44)35 (4.87)
16 to 2032 (2.61)22 (1.99)14 (1.95)
21 to 2513 (1.06) a8 (0.72) ab1 (0.14) b
25 to 3010 (0.81) a2 (0.18) ab0 (0) b
31 and above14 (1.14) a1 (0.09) b0 (0) b
Note: The notations a, b and ab follow the same rules described in Table 2. Different superscript labels, a and b represent significant differences from Chi-square tests between the respective years: 2019, 2020, and 2021 (p < 0.05). Label ‘ab’ suggests similar results with both data with label ‘a’ and that with label ‘b’.
Table 8. Comparison of discharge rates from RACFs in three years for three population groups: care recipient without dementia, with dementia but without/with agitation.
Table 8. Comparison of discharge rates from RACFs in three years for three population groups: care recipient without dementia, with dementia but without/with agitation.
Discharge Destination YearWithout DementiaDementia without AgitationDementia with Agitation
n (%)n (%)n (%)
Death 2019280 (14.2) a,188 (26.83) b,1125 (10.18) c,1
2020183 (9.73) a,258 (11.35) b,2172 (15.58) c,2
2021194 (12.45) a,340 (8.6) b,392 (13.79) c,3
Home201961 (3.09) a,125 (7.62) b,121 (1.71) c,1
202023 (1.22) a,210 (1.96) b,212 (1.09) a,2
202176 (4.88) a,317 (3.64) b,313 (1.95) c,1
Hospital201938 (1.93) a,111 (3.35) b,121 (1.71) a,1
202017 (0.9) a,213 (2.54) b,236 (3.26) c,2
202115 (0.96) a,27 (1.5) b,39 (1.35) b,3
Another RACF201915 (0.76) a,11 (0.3) b,16 (0.49) c,1
20203 (0.16) 20 (0) 20 (0) 2
20218 (0.51) a,314 (3) b,119 (2.85) b,3
Not decidable2019148 (7.51) a,18 (2.44) b,176 (6.19) c,1
202057 (3.04) a,231 (6.07) b,2102 (9.24) c,2
2021144 (9.24) a,319 (4.07) b,368 (10.19) c,3
Note: The annual rate is calculated by dividing the number of individuals who were discharged to a specific destination (e.g., death) by the total number of individuals with that health condition (without dementia, dementia without agitation, or dementia with agitation) in that year. For example, in 2019, there were 1972 individuals without dementia. Of these, 280 died, resulting in a percentage of 280/1927 = 14.20%. Different superscript labels (a,b, or c) indicate significant differences in data between the respective years: 2019, 2020, and 2021 (p < 0.05). For example, in the first row that presents the 2019 dataset, (14.2) a, (26.83) b, and (10.18) c indicate statistically significant differences among all three population groups in death rate. Different superscript numbers (1, 2, or 3) denote statistically significant differences between years for the same population. Identical numbers (e.g., 1, 1) indicate no statistically significant difference between those years. For example, for the group without dementia, the death rates for 2019, 2020, and 2021 were all different, as indicated by (14.2) 1, (9.73) 2, and (12.45) 3.
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Zhu, Y.; Yu, P.; Li, W.; Song, T.; Zhang, Z.; Yin, M.; Chang, H.C.; Song, L.; Deng, C. COVID-19 and Its Influence on Prevalence of Dementia and Agitation in Australian Residential Aged Care: A Comparative Study. Psychiatry Int. 2024, 5, 642-659. https://doi.org/10.3390/psychiatryint5040046

AMA Style

Zhu Y, Yu P, Li W, Song T, Zhang Z, Yin M, Chang HC, Song L, Deng C. COVID-19 and Its Influence on Prevalence of Dementia and Agitation in Australian Residential Aged Care: A Comparative Study. Psychiatry International. 2024; 5(4):642-659. https://doi.org/10.3390/psychiatryint5040046

Chicago/Turabian Style

Zhu, Yunshu, Ping Yu, Wanqing Li, Ting Song, Zhenyu Zhang, Mengyang Yin, Hui Chen (Rita) Chang, Lixin (Lee) Song, and Chao Deng. 2024. "COVID-19 and Its Influence on Prevalence of Dementia and Agitation in Australian Residential Aged Care: A Comparative Study" Psychiatry International 5, no. 4: 642-659. https://doi.org/10.3390/psychiatryint5040046

APA Style

Zhu, Y., Yu, P., Li, W., Song, T., Zhang, Z., Yin, M., Chang, H. C., Song, L., & Deng, C. (2024). COVID-19 and Its Influence on Prevalence of Dementia and Agitation in Australian Residential Aged Care: A Comparative Study. Psychiatry International, 5(4), 642-659. https://doi.org/10.3390/psychiatryint5040046

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