Knowledge of Dementia Among the Australian Health Workforce: A National Online Survey

Abstract

Dementia is a leading cause of death and disability in Australia. This research evaluated dementia knowledge and educational needs among the Australian health workforce. An online version of the validated Dementia Knowledge Assessment Scale (DKAS) was administered with a random sample of 234 health professionals across eight Australian states. Respondents provided additional self-report data concerning dementia experiences, educational needs, and demographic information. Dementia knowledge deficiencies were identified concerning risk factors, prevalent typologies of the condition, and cognitive symptoms. Prior university education and dementia-specific training were predictive of significantly higher knowledge scores. Self-reported dementia education needs included nonpharmaceutical interventions for the behavioral and psychological symptoms and best-evidence care provision. Knowledge deficiencies among health workers suggest patients with dementia may not be receiving consistent, best-evidence care in Australia. The research findings will support the development of a targeted online dementia education intervention that aims to improve health worker knowledge and patient care.

Keywords

Alzheimer’s disease education professional

Introduction

Dementia is a neurodegenerative syndrome that is increasing in global prevalence as populations age (Ferri et al., 2006; Kurrle, Brodaty, & Hogarth, 2012). Advancements in preventive and curative medicine have triumphed over many of the illnesses of the 20th century, yet a cure for the common forms of dementia, including Alzheimer’s disease, remains elusive (Kurrle et al., 2012; Mitchell et al., 2009). In Australia, dementia is officially recognized as the second leading cause of death behind coronary heart disease (Australian Institute of Health and Welfare, 2014), which attests to its growing significance as a public health concern. Consequently, it is necessary that health professionals understand best-evidence care and symptom management to provide patients with the highest quality of life possible as the condition progresses.

Due to the progressive nature of dementia, individuals with the condition require frequent contact with, and care from, a range of health professionals. In Australia, dementia contributes to annual health system costs exceeding 4.9 billion dollars (Australian Institute of Health and Welfare, 2012). Each year, dementia is the primary factor in over 83,000 hospital admissions, 112,000 permanent age care places, and 90,000 mental health service visits (Australian Institute of Health and Welfare, 2012). Beyond cost and service utilization, dementia creates challenges for those who provide care. Commonly experienced challenges include adverse drug effects and interactions (Janzen, Zecevic, Kloseck, & Orange, 2013), complex multimorbidity (Fick, Agostini, & Inouye, 2002; Thyrian et al., 2016), underdiagnosis or misdiagnosis (Perry et al., 2010), altered behaviors and psychological symptoms (Finkel, 2000), communication challenges (Savundranayagam, Hummert, & Montgomery, 2005), and palliative care needs (Hughes, Jolley, Jordan, & Sampson, 2007). The institutionalization and care needs of vulnerable older adults with dementia are a growing issue for health professionals in developed countries. Educational measures are required to ensure that health workers are well prepared for the increasing prevalence of dementia that is projected as populations continue to age.

Studies of health professional dementia knowledge are necessary to elucidate baseline understanding and support the development of evidence-informed educational interventions. In Australia, a small number of studies of health professional dementia knowledge have been undertaken in the last two decades. In a survey of 174 nurses and care workers from five aged care organizations across three Australian states, Robinson et al. identified a lack of understanding about the life-limiting nature of dementia and symptoms of disease progression (Robinson et al., 2014). Knowledge of dementia was also found to be positively associated with years of professional aged care experience in this study. A further survey of 107 aged care nurses undertaken in the state of Queensland revealed a lack of preparedness to deal with the mental health issues faced by older adults (Hsu, Moyle, Creedy, & Venturato, 2005). With regard to dementia, the study authors identified knowledge deficits relating to misunderstandings about psychological problems, choking and aspiration, and environmental influences on symptoms. A survey of Alzheimer’s disease knowledge conducted with 360 aged care professionals, also in Queensland, identified a moderate level of understanding across professional cohorts, but lower scores relating to risk factors and the clinical course of the disease (W. Smyth et al., 2013). W. Smyth and colleagues identified a positive and significant relationship between prior dementia education and higher knowledge about Alzheimer’s disease. Internationally, dementia knowledge deficiencies have also been identified in preliminary studies of health professionals with high levels of training. For example, in a 2004 study of general practitioners (GPs) in the United Kingdom, Turner and colleagues (2004) found a lack of understanding about the epidemiology of dementia, diagnosis strategies, and management of behavioral and psychological symptoms of dementia Behavioral and Psychological Symptoms of Dementia (BPSD). The studies identified above were limited by their regional focus, nonprobability sampling, and the use of measures that have inadequate psychometric properties. In addition, existing dementia knowledge measures have been relatively limited in their assessment of knowledge as they have frequently omitted assessment of understanding about care and communication issues (psychosocial challenges associated with the progression of dementia). Moreover, there have been limited efforts by researchers to categorize health professionals’ self-reported dementia education needs in consort with evaluations of knowledge.

One of the ways in which dementia care professionals can prepare for growing numbers of patients with dementia is through education that aims to improve understanding about this complex syndrome. Best-evidence knowledge of dementia has the potential to positively influence care practices and patient outcomes in institutional settings. A systematic literature review following the Cochrane protocol revealed that knowledge attained through health professional education can significantly improve outcomes for older adults with chronic health conditions (Forsetlund et al., 2009). More specifically, intervention research from general practices in the United Kingdom has shown that dementia education for physicians significantly enhanced detection and diagnosis rates (Downs et al., 2006). Similarly, evidence from smaller scale Australian studies has shown that improvements in dementia knowledge following professional and workplace education enhanced self-reported attitudes and treatment practices among physicians and trainees (Annear, Lea, Lo, Tierney, & Robinson, 2016; Mason et al., 2016).

Although there is a small body of research identifying dementia knowledge deficits and showing that improvements in understanding can enhance clinical practice and patient outcomes, systematic and nationwide evaluations of health professionals’ understanding have not been undertaken in Australia. Such research is necessary to understand knowledge deficiencies and to inform the development of targeted dementia education interventions. The present research, therefore, explores dementia knowledge and educational needs among a national, random sample of Australian health professionals as a preliminary step to inform the development of targeted dementia educational interventions for the Australian dementia care workforce. Academics and government agencies have identified the need for gerontological research to make greater efforts to translate findings into practice that improves health or quality of life for people with dementia (Guest, Miller, Smith, & Hyleman, 2018). This research constitutes a needs analysis for the first phase of a multi-year study to inform educational intervention development and evaluate clinical outcomes. The research sits within the conceptual framework of educational evaluation in the field of translational health research (Hutchinson, 1999).

Method

Design and Method

An exploratory and cross-sectional design was employed in this study to investigate dementia knowledge among a national sample of health professionals from eight Australian states and territories. An online survey was administered during 2016 using Google Forms, which comprised sections on dementia knowledge, experiences of care, self-reported education needs, and demographic information. Dementia knowledge was measured by asking respondents to answer 27 items on the reliable and valid Dementia Knowledge Assessment Scale (DKAS) (described in detail below). Experiences of dementia care were measured by asking respondents to report their years of personal and professional dementia care. Education was assessed by asking respondents about their general and dementia-related educational record, and asking them to reflect candidly on their self-assessed areas of needed dementia knowledge improvement and preferred learning environments. Finally, demographic information was collected (including age, gender, occupation, and geographic location) to contextualize responses to the online survey and accurately describe the respondent cohort.

With the growing ubiquity of internet access, utilization of online surveys as a replacement for paper or telephone surveys is increasingly common in health research. Rationale for online survey administration in the present research included the accessibility of the approach for collaborative survey development and pilot testing as well as expectations for higher rates of data quality (with no need for additional data entry). The online survey reduced the time to send and receive responses among a national Australian sample and employed a forced choice algorithm (including an “I don’t know” option for most questions) that reduced the possibility of incomplete surveys or nonsensical responses (J. D. Smyth, Dillman, Christian, & Stern, 2006). The study was reviewed and approved by a university human research ethics committee prior to administration (Reference Number: H0015455).

Dependent and Independent Variables

The primary outcome measure (dependent variable) in this study was total score on the reliable and valid DKAS. The DKAS is a 27-item measure (α = .89) of understanding of dementia that is comprised of verifiably true and false statements about the syndrome presented on a 5-point Likert-type scale. The scale has been validated with large Australian and international samples (n > 3,500) of health professionals (nurses, aged care workers, physiotherapists, occupational therapists, health educators, and students) and lay respondents (Annear, Eccleston, et al., 2016; Annear, Toye, Eccleston et al., 2015; Annear et al., 2017). The scale contains four subscales that address different aspects of the condition and care provision: (a) Causes and Characteristics (n = nine items), (b) Communication and Engagement (n = seven items), (c) Care Needs (n = five items), and (d) Risks and Health Promotion (n = six items). The DKAS was developed to overcome common deficiencies among existing dementia knowledge measures, including ceiling effects, poor sensitivity, item ambiguity, and a limited focus on biomedical domains or particular typologies of the syndrome (Annear, Toye, Eccleston et al., 2015). The scale was subjected to both exploratory and confirmatory factor analyses (Annear, Toye, Eccleston et al., 2015; Annear et al., 2017) and compared directly with other commonly used measures, including the Alzheimer’s Disease Knowledge Scale (ADKS), to assess concurrent validity (Annear, Eccleston, et al., 2016). In relation to the existing gold standard measure of dementia knowledge (ADKS), the DKAS has shown higher levels of sensitivity (revealing a wider range of response possibilities), lower susceptibility to ceiling effects, a broader representation of dementia-related topics, and higher internal consistency (Annear, Eccleston, et al., 2016). Within the conceptual framework of educational evaluation research, independent variables were selected to permit the assessment of demographic, educational, and experiential factors that were hypothesized to be correlated with baseline dementia knowledge. These variables were previously selected by a team of dementia experts and clinical educators and validated as part of DKAS pilot-testing procedures, including the use of an international Delphi study (Annear, Toye, McInerney et al., 2015).

Sampling, Selection, and Recruitment

A cluster-randomized sample was generated, with additional snowballing, among a volunteer population. Clustering was performed by the eight states and territories in Australia to ensure that a diversity of perspectives was obtained to reflect the varied geography, demographic structure, and federal governance of health-funding systems in Australia. A diverse group of health professionals from hospitals, aged care facilities (nursing homes), respite centers (facilities that provide short-term care for people with dementia in the community), and clinical education programs were contacted. This cohort included nurses, doctors, allied health professionals (physical therapists, occupational therapists, speech pathologists, and other nontraditional dementia care support roles), care workers, care managers, clinical educators, and trainees. A list of potential participants who work with those who have dementia, as part of their professional role, was created from publicly accessible databases of Australian health and aged care service providers (these databases included staff lists, website information, and public registers of health professionals). The completed master list for sampling included 220 organizations and 1,677 health professionals. Within the group of dementia professionals, a systematic random selection of 50 professionals was selected for potential recruitment from each of Australia’s eight states and territories. A total of 400 invitations were sent to potential respondents. An introductory email provided information about the study, guarantees of confidentiality, and a link to the online survey. Respondents were informed that completion of the online survey counted as consent for the use of aggregated and anonymized data in analysis and reporting (consistent with national health and medical research ethics protocols in Australia). Respondents who completed the survey were also asked to forward the email invitation (containing the survey information and URL) to other colleagues within their organization or discipline who may be suitably qualified and interested in participation. This additional snowballing measure was undertaken to access potential respondents who were not identified during initial sampling.

Data Analysis

All analyses were conducted using SPSS (Version 23.0) for Windows (IBM Corp., 2011). Continuous data (summative DKAS scores) were initially assessed for normality and the potential effect of outliers. The DKAS provides a total score out of 54 where each of the 27 items is assigned a value ranging from 0 to 2. An item score of 0 indicates an incorrect response to a factually true or false statement or an acknowledgment that the respondent does know the veracity of the statement. A score of 1 indicates an individual’s assessment that an item is probably true or probably false with some remaining uncertainty. Finally, a score of 2 indicates an individual’s unequivocal alignment with the correct response. In addition to total and item scores, four subscale scores were also derived from DKAS responses. Validated subscales include causes and characteristics (nine items scored out of 18), communication and engagement (seven items scored out of 14), care needs (five items scored out of 10), and risks and health promotion (six items scored out of 12). Subscale scores are reported as both a raw value and a normalized value (presented as a fraction).

Descriptive statistics (frequencies, percentages, means, and standard deviations) elucidated the response and sample characteristics. Bivariate Spearman correlations (a Bonferroni-adjusted alpha level of .005 was used to account for multiple tests of significance) assessed potential relationships between demographic variables and DKAS score and identified appropriate variables for inclusion in a subsequent regression model. Correlation matrices are often used as a preliminary step before multiple linear regression to identify variables that are more likely to be predictive of a specified outcome variable (dementia knowledge scores in this case). Finally, a multiple linear regression analysis evaluated how much of the variance in total DKAS scores could be explained by the predictor variables identified in bivariate correlations.

Results

Demographic Characteristics and Response

In total, 234 respondents completed the dementia knowledge survey across Australia, representing a 59% response rate. There were no incomplete surveys received (response rate = completion rate) as the online data gathering system was designed to allow progression and final submission only once all answers had been lodged in each section (forced choice design). The only answers in the survey that were not compulsory were the inclusion of voluntary respondent contact details indicating a desire for potential involvement in future study phases. Average completion time for each survey was recorded at approximately 12 minutes. Among those who were contacted about survey participation and who chose not to respond or declined participation, general observations can be made. In the context of those selected for research participation (n = 400), nonrespondents were more likely to be from organizations in rural or remote locations and work in low-skilled dementia care professions (such as care or trainee workers). The primary reason for nonresponse was the inability to contact respondents due to inactive email addresses, institutional firewalls, or participants on leave. Higher response rates were achieved among participants from New South Wales, Tasmania, Queensland, and Western Australia, although responses were received from respondents across all eight states and territories. Females and nurses comprised a large portion of the sample. Respondents were generally well educated, with many reporting previous dementia training, university education, and significant experiences of professional care. DKAS scores were marginally nonnormal with a slight negative skew toward higher response values. There was close alignment between the true mean (44.92) and the 5% trimmed mean (45.55), indicating negligible outlier influence. Table 1 outlines the demographic characteristics of the national respondent sample.

Table 1.

Demographic Characteristics of the Respondent Cohort (N = 234).

Demographic variable	Statistic
State of residence
Australian Capital Territory	12 (5.1%)
New South Wales	24 (10.3%)
Northern Territory	7 (3.0%)
Queensland	75 (32.1%)
South Australia	12 (5.1%)
Tasmania	48 (20.5%)
Victoria	18 (7.7%)
Western Australia	38 (16.2%)
Geographic location
Urban	164 (70.1%)
Rural	70 (29.9%)
Gender
Male	25 (10.7%)
Female	209 (89.3%)
Age
M age (SD)	53 years (10.61)
Occupation
Nurse	99 (42.3%)
Professional care worker	19 (8.1%)
Allied health professional	41 (17.5%)
Medical doctor or specialist	11 (4.7%)
Trainee or student	1 (0.4%)
Manager or administrator	48 (20.5%)
Researcher or academic	5 (2.1%)
Policy planner or advocate	3 (1.3%)
Other	7 (3.0%)
Organizational type represented
Hospital	68 (29.1%)
Aged care facility	103 (44.0%)
Respite service	29 (12.4%)
Clinical education program	34 (14.5%)
Highest educational achievement
Non-university educated (high school or vocational certificate)	86 (36.8%)
University education (undergraduate or postgraduate degree)	148 (63.2%)
Previous dementia education
Yes	199 (85%)
No	35 (15%)
Family members with dementia
Yes	106 (45.3%)
No	128 (54.7%)
Direct dementia care experience
Yes	218 (93.2%)
No	16 (6.8%)
Time spent providing dementia care or treatment professionally
M (SD)	12 years (9.67)

Dementia Knowledge

Mean score on the DKAS was 44.92 (83% of responses articulated as correct) out of 54, with a range of 38. Among the DKAS subscales, lowest scores were recorded on the Risks and Health Promotion Scale (deviation of ±10% from the normalized subscale mean). At the item level, four statements showed a comparatively low rate of correct response. Statements with lower scores (deviation of ±10% from the item mean) included those relating to the relative prevalence of vascular dementia (35% of respondents answered incorrectly), risks of high blood pressure (30% of respondents answered incorrectly), efficacy of a healthy lifestyle as a preventive measure (23% of respondents answered incorrectly), and differentiation of cognitive symptoms (31% of respondents answered incorrectly). The highest item score (deviation of ±10% from the item mean) related to respondents understanding about the terminal course of common forms of dementia (97% of respondents correctly identified that it was not possible to recover from common forms of dementia). Respondents rated their self-reported dementia knowledge and self-reported confidence with dementia care provision as moderate, indicating scope for improvements in understanding and self-efficacy. Within the sample, 58% of respondents reported that greater than half of all of their clients had dementia. Areas of greatest self-reported educational need included care provision for people with dementia and nonpharmacological interventions for BPSD. Table 2 presents information on the dementia knowledge characteristics of the respondent sample, whereas Table 3 provides a detailed overview of mean responses to the DKAS.

Table 2.

Dementia Knowledge Characteristics and Experiences.

Knowledge and experience parameters	Statistic
Self-reported current knowledge of dementia / 5
M (SD)	3.71 (0.62)
Self-reported confidence with dementia care / 5
M (SD)	3.79 (0.74)
Proportion of clients with dementia
Less than 25%	32 (13.7%)
Between 25% and 50%	66 (28.2%)
Between 50% and 75%	84 (35.9%)
Greater than 75%	52 (22.2%)
DKAS score / 54
M (SD)	44.92 (7.60)
Minimum	16
Maximum	54
DKAS subscale raw scores, M (SD)
Causes and characteristics / 18	15.20 (2.86)
Communication and engagement / 14	12.05 (2.34)
Care needs / 10	8.61 (1.93)
Risks and health promotion /12	9.06 (2.69)
DKAS subscale normalized scores / 1.00, M (SD)
Causes and characteristics	0.84 (0.16)
Communication and engagement	0.86 (0.17)
Care needs	0.86 (0.19)
Risks and health promotion	0.76 (0.22)
Self-reported dementia education needs
Care provision for people with dementia	44 (18.8%)
Dementia causes and risk factors	7 (3.0%)
Dementia pathology	31 (13.2%)
Dementia symptoms	6 (2.6%)
Nonpharmacological interventions for behavioral symptoms	101 (43.2%)
Pharmacological treatment options for people with dementia	27 (11.5%)
Prevention of dementia	10 (4.3%)
Other	8 (3.4%)

Note. DKAS = Dementia Knowledge Assessment Scale.

Table 3.

Mean Scores and Domains for DKAS Items.

DKAS items / 2.00	M	SD	Subscale
1. Dementia is a normal part of the aging process [FALSE].	1.86	0.43	Causes and Characteristics
2. Alzheimer’s disease is the most common form of dementia [TRUE].	1.65	0.68	Causes and Characteristics
3. People can recover from the most common forms of dementia [FALSE].	1.88	0.42	Causes and Characteristics
4. Dementia does not result from physical changes in the brain [FALSE].	1.84	0.50	Causes and Characteristics
5. Most forms of dementia reduce the length of a person’s life [TRUE].	1.62	0.69	Causes and Characteristics
6. Planning for end of life care is generally not necessary following a diagnosis of dementia [FALSE].	1.82	0.54	Causes and Characteristics
7. Blood vessel disease (vascular dementia) is the most common form of dementia [FALSE].	1.23	0.93	Causes and Characteristics
8. Most forms of dementia do not generally shorten a person’s life [FALSE].	1.52	0.79	Causes and Characteristics
9. Having high blood pressure increases a person’s risk of developing dementia [TRUE].	1.20	0.87	Risks and Health Promotion
10. Maintaining a healthy lifestyle does not reduce the risk of developing the most common forms of dementia [FALSE].	1.39	0.84	Risks and Health Promotion
11. Symptoms of depression can be mistaken for symptoms of dementia [TRUE].	1.65	0.65	Risks and Health Promotion
12. Exercise is generally beneficial for people experiencing dementia [TRUE].	1.87	0.41	Risks and Health Promotion
13. Early diagnosis of dementia does not generally improve quality of life for people experiencing the condition [FALSE].	1.67	0.65	Risks and Health Promotion
14. The sudden onset of cognitive problems is characteristic of common forms of dementia [FALSE].	1.28	0.91	Risks and Health Promotion
15. It is impossible to communicate with a person who has advanced dementia [FALSE].	1.73	0.64	Communication and Engagement
16. A person experiencing advanced dementia will not generally respond to changes in their physical environment [FALSE].	1.72	0.64	Communication and Engagement
17. It is important to correct a person with dementia when they are confused [FALSE].	1.74	0.64	Communication and Engagement
18. People experiencing advanced dementia often communicate through body language [TRUE].	1.78	0.52	Communication and Engagement
19. Uncharacteristic behaviors in a person experiencing dementia are generally a response to unmet needs [TRUE].	1.62	0.68	Communication and Engagement
20. People with dementia are unlikely to experience depression [FALSE].	1.71	0.66	Communication and Engagement
21. Medications are the most effective way of treating behavioral symptoms of dementia [FALSE].	1.75	0.57	Communication and Engagement
22. People experiencing dementia do not generally have problems making decisions [FALSE].	1.79	0.55	Causes and Characteristics
23. Movement is generally affected in the later stages of dementia [TRUE].	1.71	0.62	Care Needs
24. People with advanced dementia may have difficulty speaking [TRUE].	1.86	0.42	Care Needs
25. People experiencing dementia often have difficulty learning new skills [TRUE].	1.56	0.75	Care Needs
26. Difficulty eating and drinking generally occurs in the later stages of dementia [TRUE].	1.76	0.58	Care Needs
27. Daily care for a person with advanced dementia is effective when it focuses on providing comfort [TRUE].	1.73	0.59	Care Needs

Note. DKAS = Dementia Knowledge Assessment Scale.

Correlation Matrix for Potential Predictors of Dementia Knowledge

A Spearman correlation matrix was undertaken to explore potentially significant bivariate relationships between the primary outcome measure (DKAS total score) and continuous and categorical variables. A Bonferroni-adjusted alpha level of .005 was used to account for multiple tests of significance (n = 10). Significant correlations were identified between DKAS score and self-reported dementia knowledge, confidence in dementia care, prior dementia education, qualification level, time providing professional dementia care, and geographic location. DKAS total score showed no significant relationship with sentiments about professional education, experiences of family members with dementia, sex, or age. As the overwhelming majority of respondents reported experiences of professional dementia care, it was not possible to test correlations with knowledge scores among those without such experiences due to low numbers (n = 16). Table 4 outlines the relationships between potential predictor variables and DKAS score.

Table 4.

Correlation Matrix for Potential Predictors of Dementia Knowledge (N = 234).

Potential predictor variables	DKAS
Age in years
r	.068
p	.336
Sex (male or female)
r	.043
p	.233
Geographic location (urban or rural)
r	.230**
p	.000
Highest qualification (university or nonuniversity)
r	.242**
p	.000
How would you rate your current knowledge of dementia?
r	.295**
p	.000
How would you rate your level of confidence about providing care for a person with dementia?
r	.232**
p	.000
How important is continuing/professional education for your development as a health professional?
r	.123
p	.061
Have you ever undertaken a training course or workshop about dementia?
r	.354**
p	.000
Have any members of your immediate family ever been diagnosed with dementia?
r	−.053
p	.415
How much time have you spent providing care or treatment for people with dementia as part of your professional role?
r	.218**
p	.001

Note. DKAS = Dementia Knowledge Assessment Scale.

Significant at the .01 level.

Linear Multiple Regression

A linear multiple regression was undertaken using the six independent variables that showed a significant bivariate correlation with the total DKAS score to examine the potential predictive power of the model. Initial examination of the model revealed no multicollinearity and negligible influence from outliers. Although DKAS total score was nominally nonnormal (slight negative skew), assumptions required for the regression analysis were not violated following examination of the Normal Probability Plot of the Regression Standardized Residual. Evaluation of the R² summary statistic showed that the model explained 35.50% of the variance in DKAS scores, F(6, 217) = 19.40, p = .000. The two variables that provided the greatest explanation of DKAS score were prior university education and formal dementia education. Lesser contributions to DKAS score were made by time spent providing professional dementia care, self-reported knowledge of dementia, and geographic location. The contribution of the self-reported confidence in the provision of dementia care and treatment was not significant in the model. Results of the linear multiple regression analysis are presented in Table 5.

Table 5.

Linear Multiple Regression Analysis for Six Items Correlated With DKAS Score.

Variable	β	p
Completion of university education to at least bachelor level (dichotomous)	.315	.000**
Previous formal dementia education experiences (dichotomous)	.314	.000**
Self-reported knowledge of dementia	.187	.016*
Time (in years) spent providing professional dementia care or treatment	.170	.003**
Geographic location (urban or rural residence)	.155	.007**
Level of confidence in providing care for a person with dementia	.030	.626

Significant at the .05 level. **Significant at the .01 level.

Discussion

This research sought to elucidate dementia knowledge and educational needs among a national sample of 234 Australian health care professionals using an online survey methodology. Across the cohort, the largest number of responses was received from nurses, allied health professionals, care workers, and care managers. These respondents represent cohorts that provide high levels of instrumental support for activities of daily living among institutionalized older adults. Most respondents were women aged over 50 years, reflecting the gendered nature of dementia care and the aging of the health workforce (Alzheimer’s Disease International, 2015). The majority of respondents estimated that at least 50% of their clientele had dementia. This suggests a high level of workplace exposure to the condition, which aligns with reports of dementia prevalence in aged care institutions where 53% of permanent residents in Australia have been diagnosed with the condition (Australian Institute of Health and Welfare, 2012). True prevalence of dementia within the Australian health system, however, is likely to be higher than official statistics suggest due to frequent misdiagnosis and underdiagnosis of the condition (Perry et al., 2010).

Within the respondent cohort, there was evidence of knowledge deficits in several areas. Relatively low mean scores were observed for the risks and health promotion subscale and items addressing blood pressure, influence of lifestyle factors, prevalence of vascular dementia, and differentiation of cognitive symptoms. Risk factors for dementia were not well understood by many respondents. Maintaining stable blood pressure and a healthy lifestyle are known to reduce the risk of developing dementia in later life (Spence, 2004). Current evidence suggests that the onset of dementia can be prevented or delayed by the management of vascular factors through pharmaceutical and lifestyle intervention (Larson et al., 2006; Spence, 2004). Such understanding is critical as it indicates an area for health promotion, preventive measures, and personal responsibility in the management of risk factors for dementia among the adult population. Alzheimer’s disease is the most prevalent form of dementia (Reitz, Brayne, & Mayeux, 2011), yet many respondents (n = 81) considered vascular dementia to be more commonplace. This misunderstanding may reflect the challenges associated with accurately diagnosing dementia. It is often difficult for clinicians to conclusively diagnose dementia antemortem when there are myriad possible causative factors and symptoms that often mimic other conditions, including depression (Kurrle et al., 2012). Finally, some respondents had difficulty identifying cognitive symptoms of dementia. Many respondents (n = 73) falsely identified the sudden onset of cognitive problems as a common symptom of dementia. Although there may be acute exacerbations of BPSD during the course of dementia, progression tends to be slow with major functional changes occurring over years (Carlson et al., 2008). Sudden changes in cognitive function in later life are symptomatic of treatable conditions, such as delirium or infection, and greater clinical awareness is required as such conditions may be superimposed on patients with dementia (Morandi et al., 2014).

Knowledge parameters identified among a national sample of Australian health workers validate, challenge, and extend regional Australian findings. Previous studies have identified health worker knowledge deficits concerning symptomatology (Hsu et al., 2005; Hughes, Bagley, Reilly, Burns, & Challis, 2008; Robinson et al., 2014; W. Smyth et al., 2013), which reinforces findings from the present research concerning difficulties differentiating dementia symptoms from those of treatable conditions. The research also supports the findings of W. Smyth et al. who identified that risk factors for dementia may not be well understood by Australian health workers. In contradistinction to other Australian findings, the present research did not find evidence for a lack of understanding about the terminal course of dementia, problems arising with eating or drinking in later stages, or environmental influences on BPSD. Of particular note, the highest DKAS item score related to the terminal course of dementia (implied in terms of the possibility of recovery). In previous Australian studies among convenience samples of aged care workers, Robinson et al. and W. Smyth et al. both reported poor understanding of the terminal course of dementia (Robinson et al., 2014; W. Smyth et al., 2013). The present research challenges these results and suggests that there may have been a growth in awareness of the clinical course of dementia among the Australian Health Workforce over the last 5 years. The clinical course of common forms of dementia has been well established (Mitchell, Kiely, & Hamel, 2004; Mitchell et al., 2009), and the condition has been recognized as a leading cause of death by the Australian Government (Australian Institute of Health and Welfare, 2014). Growing awareness of the course of dementia is important as it opens the way for patients, family members, and clinicians to begin timely discussions about palliative and end-of-life care. Dementia palliative care remains a developing area of clinical practice and research as the condition has not traditionally been viewed as a life-threatening illness (Hughes et al., 2007).

Potential predictors of dementia knowledge were also identified in this study. Dementia knowledge was found to be moderately associated with prior education. Respondents with a university qualification or formal dementia training were found to have higher DKAS scores than respondents without such educational backgrounds. Weaker associations were also identified with number of years of professional experience (greater length of service associated with higher DKAS score), self-reported knowledge (higher self-reported knowledge associated with higher DKAS score), and geographic location (urban responders scored higher than rural responders). Although the link between educational attainment and higher DKAS scores may seem self-evident, it shows the primacy of education over professional experience, self-confidence (self-efficacy), familial care, and other potentially influential factors. Although our results could not show a causal link between previous education and dementia knowledge, they contribute to the validation of existing evidence. For example, in an earlier regional study, W. Smyth et al. (2013) observed that education appears to improve dementia knowledge among Australian health professionals independent of demographic factors and personal experience. The present research reinforces the finding of W. Smyth et al. and offers potential avenues for designing effective interventions. Future phases on this study will examine the extent to which evidence-informed dementia education can improve health professional knowledge and whether resultant knowledge change translates into improved care and patient outcomes. We hypothesize that knowledge may be a vector through which better dementia care can be achieved in a cost-effective and timely manner.

In addition to the objective measure of knowledge deficiencies and identification of potential predictive variables, survey respondents offered subjective assessments of their dementia education needs. Prevalent self-reported education needs included desires for greater understanding about nonpharmacological interventions for BPSD and care provision for people with dementia. Such requirements likely reflect the growing awareness of the terminal course of dementia, the dangers of medical management, and appreciation of the need to take a person-centered approach to care. Dementia is a progressive, neurodegenerative condition that causes significant cognitive changes and challenging BPSD (Kurrle et al., 2012), including emotional disturbances, delusions, aggression, hallucinations, wandering, and changes in sleep and appetites (Cerejeira, Lagarto, & Mukaetova-Ladinska, 2012). Pharmacological interventions for BPSD (particularly antipsychotic medications) carry significant risks and are associated with deleterious side effects, including stroke, delirium, and death (Guthrie, Clark, & McCowan, 2010). Nonpharmacological interventions for BPSD are considered comparatively safe and involve a range of activities, communication strategies, and counseling techniques that have proven efficacy in reducing the severity and frequency of BPSD (Douglas, James, & Ballard, 2004). Examples of nonpharmacological interventions include cognitive behavior therapy, reminiscence therapy, environmental modification, pet therapy, and multisensory therapy (Douglas et al., 2004; Janzen et al., 2013). Learning about less invasive and person-centered approaches to care can help health professionals to support clients with dementia without increasing the risks associated with medical management. Importantly, such approaches offer benefits for health workers in rural and regional locations where access to geriatricians and advanced health services may be limited.

Limitations

Although this research represents the first systematic, nationwide study of health professionals’ dementia knowledge undertaken in Australia, it was limited by a lack of statistical power. To provide comparative data between states and health professions, higher levels of recruitment are required. In particular, future research should elucidate potential state and territory differences in health professionals’ dementia knowledge. This is important as the Australian health system is funded at multiple levels with a significant state/territory and local component. This (multi-tiered). funding system may be associated with geographically based differences in dementia knowledge and patient outcomes, which should be investigated in greater detail. Due to power restrictions, the current findings remain preliminary and will primarily inform the development and pilot testing of a novel online dementia education intervention for a general cohort of Australian dementia care professionals. Attaining larger and representative samples from individual dementia care professions (nurses, care workers, GPs, and others) is potentially important in future studies as it will allow for enhanced targeting of online dementia education interventions. The present research, however, is intended to inform the development of a generalized program of online dementia education due to the widespread low baseline of dementia knowledge that has been reported across diverse health professions in Australia and elsewhere (Robinson et al., 2014; W. Smyth et al., 2013). Furthermore, as the research design was based on online communications, some difficulties were encountered when attempting to recruit health workers due to institutional firewalls or out-of-date email addresses. In practice, however, less than 2% of the sample could not be reached for technical reasons associated with the use of an online survey methodology. The health workforce in Australia is highly mobile and not typically confined to desk-based roles. In this regard, it is also possible that the online survey methodology may have encountered challenges obtaining responses from busy professionals. Time pressure is a common factor to consider when surveying health professionals, although we considered the use of an online survey to be more efficient than a traditional pen and paper method, which would have added additional time in terms of physically receiving and returning the survey. Moreover, the forced choice design of the online survey was found to be a strength of the research as it proved useful for limiting nonresponse and yielded no apparent nonsense answers. In this regard, 100% of all responses received provided viable data for analysis. The higher proportion of female respondents in this study may be considered a limitation. However, such response reflects the gendered nature of aged care. International reports have confirmed that dementia care is a heavily gendered issue: “across all regions and settings, females bear the brunt of the incidence of dementia and the responsibility for caring for people with dementia” (Alzheimer’s Disease International, 2015, p. 44). Internationally it has been estimated that women comprise over 75% of health professionals who work in the aged and dementia care sector (Alzheimer’s Disease International, 2015). In Australia, workforce surveys have revealed that over 88% of those working in dementia care are female (Senate Community Affairs Committee, 2017). Our sample, therefore, reflects higher female participation in the dementia care workforce. This research achieved an acceptable diversity of geographic locations, professional roles, and organization types, although there were notably lower rates of response among rural respondents and lower skilled care workers. The online and anonymous nature or responses created challenges for the elucidation of nonrespondent demographics and rationale for nonparticipation. Larger studies are indicated that can recruit - representative cohorts of dementia professionals using a cluster and systematic sampling informed by the design of the present study. Finally, although the DKAS has been shown to have high levels of validity and reliability in relation to existing measures of dementia knowledge (including the ADKS), it remains limited (like comparable measures) by testing on relatively small populations of GPs. Although large, population-based studies have been successfully completed with other groups in an aged care context (nurses, care workers, health students, and others), the number of GPs in pilot trials of the DKAS has been comparatively low (n < 50). Future studies that seek to elucidate the dementia knowledge and education needs of health professionals with the highest levels of dementia training in the aged care sector should also include a pilot phase to first confirm that validity and reliability of the DKAS measure with a nationally representative sample of GPs.

Implications

The research findings have identified specific deficiencies in dementia knowledge and educational needs among a national sample of Australian health professionals. This cohort appeared to have a relatively low level of understanding about risk factors for dementia, prevalent typologies of the syndrome, and cognitive symptoms associated with disease progression. These deficiencies suggest that there are inroads yet to be made to improve health professional knowledge and resultant patient care. Prior education, both general and dementia-related, appears to be associated with higher scores on a validated dementia knowledge scale. Although evidence is still required to identify the most effective mode of dementia education for health professionals, an implication of this research is that even general health education at university may support higher levels of dementia knowledge. Tertiary institutions and health service employers have an important role to play in supporting an aging society by preparing the health workforce to manage an increasing number of individuals with dementia. In the coming years, tertiary institutions and health service employers should aim to steadily increase the number of students and staff who receive targeted and evidence-informed dementia education to prepare the workforce for the demographic and clinical realities of 21st-century health care. Beyond the objectively measured knowledge deficiencies in this study are subjective health professional needs for more training in the areas of nonpharmacological management of BPSD and best-practice dementia care provision. A focus on person-centered care and nonpharmacological approaches to behavior management offer pathways for improving quality of life for patients with dementia, while reducing the risks associated with medical management. As dementia grows in prevalence in both community and institutional settings, greater attention will need to be paid to the psychosocial elements of disease management that balance patient quality of life, family member burden, and stresses on care professionals.

The findings of this study will inform the development of targeted online dementia education for health professionals that aims to improve institutional care and treatment practices. The next step for this research is to evaluate the efficacy of evidence-informed educational programs to establish the degree of knowledge change possible among the health workforce and assess clinically significant patient outcomes. Following the implementation and evaluation of a generalized program of online dementia education that is based on evidence gathered in this study, it will be desirous to gain further information about finer grained dementia education needs by health professions to permit further targeting of the intervention. Although it is anticipated that there will be differences in dementia education knowledge between health professions, there is also emerging evidence to show that within the health sector there are broad deficiencies in understanding and a low knowledge baseline, including among highly trained professionals (such as GPs; Robinson et al., 2014; W. Smyth et al., 2013; Turner et al., 2004). For this reason, it is important to initially address the low dementia knowledge baseline in online education before moving to specifically target educational interventions by profession.

The development of an online dementia intervention for health care workers will focus on disseminating best-practice information about current techniques that are appropriate for the provision of person-centered dementia care that aims to maintain quality of life as dementia progresses. Much is already known about the best ways to provide quality of life and quality of care for people who live with dementia, and the utility of online education is that it allows for wider dissemination of current evidence to health professionals in diverse locations. For example, the harms of psychotropic medications (also known as antipsychotics) for controlling BPSD are well known and include stroke and premature death (Gill et al., 2007; Guthrie et al., 2010). Nonpharmacological approaches for safely modifying behaviors have been trialed and are known to be equally effective with much lower risks. These approaches include talking therapies, music therapy, physical therapy, art therapy, and others (Chen et al., 2014; Janzen et al., 2013; Svansdottir & Snaedal, 2006). The utility of nonpharmacological therapies for BPSD and the limitations of comparatively dangerous psychotropic medications are educational issues that affect most individuals involved in dementia care (from GPs who are responsible for drug prescriptions to nurses, care workers, and allied health professionals who administer nonpharmacological therapies). The challenge for an online mode of education will be to present evidence-informed alternatives to potentially harmful dementia treatments and show how nonpharmacological approaches, for example, can be implemented by different practitioners across a range of community and clinical settings. Video examples of common practitioner–patient scenarios and expert testimonies/lectures may be particularly effective for helping practitioners to relate to the challenges and benefits of implementing evidence-based practices in their dementia care. The creation of online communities of practice that are moderated by dementia experts may also be possible to facilitate sharing of clinical experiences and lessons learned in practice. There is emerging evidence that improved clinician education may significantly enhance patient outcomes across a range of chronic conditions (Forsetlund et al., 2009), although work is required to conceptualize potential effects in the area of dementia care. Translational research reported in the United States also suggests that intervening in the education of dementia carers and volunteers can manifestly improve advocacy and support for neglected people living with this debilitating condition in the community (Guest et al., 2018). If targeted and evidence-informed dementia education that is provided in an online context can be shown to improve patient care and outcomes, this would provide a cost-effective strategy for improving the quality and consistency of dementia care as prevalence increases.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a Dementia Research Development Fellowship from the National Health and Medical Research Council (NHMRC) and Australian Research Council (ARC) (Grant 1099245).

ORCID iD

Michael J. Annear

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