Dementia Knowledge Assessment Scale

Abstract

The Dementia Knowledge Assessment Scale (DKAS) is a contemporary, multidimensional psychometric instrument developed to address critical measurement deficits in the evaluation of dementia literacy among healthcare professionals, paraprofessionals, students, and informal caregivers. Created by an interdisciplinary team of researchers led by Michael J. Annear at the Wicking Dementia Research and Education Centre (University of Tasmania) in collaboration with Curtin University, the DKAS represents a substantive departure from earlier legacy measures such as the Alzheimer’s Disease Knowledge Scale (ADKS). Legacy instruments frequently suffered from severe ceiling effects among educated cohorts, focused disproportionately on Alzheimer’s pathology while ignoring other dementias, and relied on dichotomous true/false formats that failed to capture nuance or distinguish genuine knowledge from lucky guessing.

The DKAS comprises 27 meticulously curated items designed to assess dementia understanding across distinct yet interrelated domains. Structurally, the instrument was calibrated through a rigorous multi-phase developmental architecture that combined an international Delphi expert consensus panel with comprehensive empirical field trials involving 1,767 participants across 96 countries. Principal Components Analysis (PCA) with oblimin rotation confirmed a four-component multidimensional structure accounting for 44.2% of the total variance, capturing fundamental sub-domains such as Causes and Characteristics, Communication and Engagement, Care Considerations, and Disease Trajectory/Symptom Presentation.

Items are administered using an authentic 4-point Likert scale (ranging from strongly disagree to strongly agree) accompanied by an auxiliary ‘I don’t know’ option to discourage unguided conjecture and permit accurate differentiation between misinformation and unformed knowledge. Ten negatively phrased items require reverse-scoring, and performance is graded against an objective correctness key. The scale exhibits exceptional psychometric stability, characterized by robust internal consistency, demonstrated test-retest reliability across a three-week interval among practicing healthcare personnel, and confirmed concurrent validity with established dementia benchmarks. Crucially, the scale has established strong construct and evaluative validity, functioning as a highly sensitive metric for measuring pre- and post-intervention learning gains following targeted dementia educational curricula, such as massive open online courses (MOOCs) and specialized clinical training.

Keywords

Dementia Knowledge Assessment Scale, DKAS, dementia literacy, psychometric evaluation, scale development, geriatric care, person-centered care, health education, Alzheimer’s disease, healthcare workforce training, neurocognitive disorders, curriculum evaluation

Authors

The Dementia Knowledge Assessment Scale was conceptualized, developed, and empirically validated by an interdisciplinary consortium of gerontologists, psychometricians, nurse educators, and behavioral scientists across Australia:

• Michael J. Annear, PhD ([email protected]) — Primary Investigator and Lead Psychometrician; Wicking Dementia Research and Education Centre, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
• Christine M. Toye, PhD, RN — Co-Investigator; Faculty of Health Sciences, School of Nursing and Midwifery, Curtin University, Perth, Western Australia, Australia; and Older People’s Health, Sir Charles Gairdner Hospital, Nedlands, Western Australia.
• Claire E. Eccleston, PhD — Co-Investigator; Wicking Dementia Research and Education Centre, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
• Frances J. McInerney, PhD, RN — Co-Investigator; Wicking Dementia Research and Education Centre, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
• Kate-Ellen J. Elliott, PhD — Co-Investigator; Wicking Dementia Research and Education Centre, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
• Bruce K. Tranter, PhD — Statistical and Quantitative Methodologist; School of Social Sciences, College of Arts, Law and Education, University of Tasmania, Hobart, Tasmania, Australia.
• T. F. Hartley, MSc — Co-Investigator; Faculty of Health, School of Health Sciences, University of Tasmania, Launceston, Tasmania, Australia.
• Andrew L. Robinson, PhD, RN — Senior Research Director; Wicking Dementia Research and Education Centre, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.

Purpose

As the global population ages, the prevalence of neurocognitive disorders is expanding exponentially, placing an unprecedented burden on healthcare infrastructures, community aged care systems, and informal family networks (Ferri et al., 2005). Effective clinical management, timely diagnostic assessment, ethical care planning, and compassionate symptom alleviation depend fundamentally on the knowledge base of those providing support. Historically, however, the tools employed by researchers and medical educators to measure dementia understanding suffered from profound conceptual, methodological, and psychometric vulnerabilities.

Prior to the introduction of the DKAS, the assessment of dementia knowledge was dominated by instruments such as the Alzheimer’s Disease Knowledge Scale (ADKS; Carpenter et al., 2009), the Knowledge about Memory Loss and Care (KAML-C; Kuhn et al., 2005), and earlier dementia quizzes (Gilleard & Groom, 1994). As documented in systematic reviews of the literature (Spector et al., 2012), these legacy instruments exhibited several major shortcomings:

• Narrow Disease Orientation: Earlier tools centered almost exclusively on Alzheimer’s disease, largely ignoring vascular dementia, Lewy body dementia, frontotemporal lobar degeneration, and mixed pathologies.
• Excessive Biomedical Focus: They emphasized esoteric neurobiology and laboratory diagnostic markers while omitting critical dimensions of communication, behavioral interpretation, and psychosocial support principles fundamental to person-centered dementia care.
• Ceiling Effects: Due to basic or outdated item pools, scores among registered nurses, allied health clinicians, and physicians routinely clustered near the maximum ceiling, severely limiting the instrument’s capacity to discriminate fine gradations of clinical expertise or measure advanced learning.
• Forced-Choice Response Distortions: Binary True/False scales introduced substantial measurement error by allowing respondents a 50% probability of guessing correctly, while failing to distinguish genuine misconceptions from self-acknowledged deficits in knowledge.

The primary purpose of the Dementia Knowledge Assessment Scale was to resolve these operational deficits by establishing a contemporary, psychometrically rigorous, and multidimensional standard. The DKAS was specifically engineered to serve multiple complementary purposes across clinical, research, and educational spheres:

1. Diagnostic Baseline Profiling: To benchmark the baseline knowledge profiles of varied demographic groups—spanning direct-care aged care staff, hospital-based clinicians, medical students, family caregivers, and the lay public—identifying pervasive myths and specific deficits in care competencies.
2. Targeted Educational Curriculum Engineering: By providing subscale-specific diagnostic data, the scale enables educators and clinical nurse specialists to design tailored instructional modules addressing documented gaps rather than wasting instructional resources on already mastered concepts.
3. Intervention Sensitivity and Program Evaluation: The scale was designed to exhibit high longitudinal sensitivity to change, enabling educators and institutional leaders to rigorously evaluate the efficacy of educational programs, continuing professional development (CPD) courses, and large-scale public health drives such as Massive Open Online Courses (MOOCs).
4. Cross-Sector Comparative Research: The scale allows international health policy researchers to systematically compare knowledge levels across professional sectors, geographical boundaries, and sociocultural environments, directly responding to the World Health Organization’s (WHO) mandate for evidence-based dementia workforce education.

Psychological Construct

Dementia knowledge, as operationalized within the framework of the DKAS, is conceptualized as an integrated, multidimensional cognitive and behavioral literacy construct. Rather than viewing dementia literacy simply as the passive recall of medical definitions, the construct synthesizes evidence-based biomedical understanding with empathetic, actionable principles of person-centered care. Mastery of this construct reflects a person’s capability to understand what neurodegenerative disorders represent, how they manifest dynamically across biological and psychological systems, and how best to support an individual whose cognitive, functional, and social capacities are progressively changing.

The 27 items of the DKAS tap into a four-component structural architecture derived from factor-analytic empirical investigation:

1. Causes and Characteristics

This dimension encompasses an understanding of the biological, pathological, and epidemiological foundations of major neurodegenerative syndromes. Rather than viewing dementia as an inevitable consequence of normal chronological aging, this subscale measures whether an individual recognizes dementia as an umbrella term representing distinct progressive, irreversible biological diseases affecting the cerebral cortex and subcortical structures. It evaluates knowledge regarding:

• The distinction between normal age-related cognitive changes and neurodegenerative pathology.
• The progressive, incurable, and eventually terminal trajectory of neurodegenerative conditions such as Alzheimer’s disease, vascular dementia, and Lewy body disorders.
• The cellular and vascular mechanisms leading to localized cerebral damage and associated functional declines.

2. Communication and Engagement

This subscale evaluates actionable, relational knowledge regarding how to interact, communicate, and preserve interpersonal connection with individuals living with cognitive impairment. Rooted in the psychological tradition of personhood, this dimension assesses:

• Techniques for verbal and non-verbal pacing, clear phrasing, and reading non-verbal emotional cues.
• The awareness that behaviors that challenge caregivers—often mischaracterized as ‘aggressive’, ‘wandering’, or ‘uncooperative’—frequently represent unaddressed physical pain, sensory overload, emotional distress, or unmet psychological needs.
• Knowledge that people living with moderate-to-severe dementia retain emotional sensitivity, feelings, and the capacity for interpersonal connection long after semantic memory and expressive language have deteriorated.

3. Care Considerations and Environment

The third sub-dimension addresses the structural, clinical, and environmental realities of supporting a person with dementia throughout daily life and advanced progression. It reflects an operational understanding of how the physical and social milieu can either support functional autonomy or exacerbate cognitive disability. Key components include:

• Understanding the impact of environmental stressors (e.g., loud auditory environments, complex architectural layouts, disruptive transitions) on cognitive functioning and anxiety levels.
• Principles of palliative and end-of-life care in advanced dementia, including swallowing difficulties, systemic physical decline, and the management of comfort rather than invasive, futile interventions.
• The role of multidisciplinary support, caregiver respite, and the prevention of caregiver burnout.

4. Trajectory, Risk Factors, and Symptom Presentation

This domain captures the heterogeneous clinical manifestations, variable stages, and risk profiles that characterize the broader syndrome of dementia. It examines understanding of:

• The full spectrum of symptoms beyond episodic memory loss, including executive dysfunction, perceptual distortions, apraxia, agnosia, and emotional lability.
• Potentially modifiable versus non-modifiable cardiovascular, metabolic, and lifestyle risk factors associated with dementia onset.
• The variable rate of decline across individuals and the distinction between acute, reversible confusional states (e.g., delirium) and progressive, irreversible dementia.

Theoretical Framework

The architecture of the Dementia Knowledge Assessment Scale is grounded in two primary theoretical paradigms: Kitwood’s Social-Psychological Theory of Personhood and Bloom’s Revised Taxonomy of Educational Objectives, mediated through contemporary principles of health literacy theory.

Kitwood’s Dialectical Framework of Personhood in Dementia

Historically, medical models of dementia operated under a rigid organic-reductionist framework, where a person’s cognitive decline and behaviors were viewed entirely as direct, unmediated consequences of structural neurological lesions. In contrast, British social psychologist Tom Kitwood revolutionized dementia studies by proposing a dialectical model wherein a person’s manifested state ($B$) is a dynamic function of five interacting variables:

B = P + M + S + N + E

Where:

• P: Personality (the individual’s lifelong coping strategies, cognitive style, and emotional predispositions).
• M: Mental Health (underlying emotional vulnerabilities, depression, or subjective well-being).
• S: Social Psychology (the supportive or malignant interpersonal environment surrounding the individual).
• N: Neurological Impairment (the physical, biological damage within cerebral structures).
• E: Physical Environment (the sensory, social, and architectural context).

Kitwood emphasized that depersonalizing practices (labeled ‘malignant social psychology’)—such as infantilization, objectification, outpacing, and banishment—greatly accelerate disability beyond the direct damage of neuropathology. Conversely, skilled caregivers who maintain personhood through empathetic validation, tailored engagement, and communicative respect can optimize functional and emotional well-being. The DKAS reflects this paradigm by deliberately elevating relational, communicative, and supportive domains to equal standing with biological knowledge.

Bloom’s Revised Cognitive Taxonomy

From an educational measurement perspective, the DKAS is anchored in the revised Bloom’s Taxonomy (Anderson & Krathwohl, 2001). Traditional knowledge tests evaluated only lowest-tier cognitive functioning: rote memorization and immediate recall of definitions. The DKAS expands beyond superficial rote recall by designing items that test comprehension, conceptual categorization, and the evaluative synthesis of clinical scenarios.

By forcing respondents to differentiate between true neuropathological features and common myths (e.g., clarifying that sudden, acute fluctuating confusion is indicative of delirium rather than typical dementia progression), the DKAS measures the analytical depth of an individual’s cognitive schema. The inclusion of an explicit ‘I don’t know’ option directly addresses metacognitive awareness, testing not only what respondents know, but whether they accurately calibrate their own limits of knowledge.

Validity

The psychometric evaluation of the DKAS involved extensive empirical testing across diverse cohorts to establish strong content, construct, concurrent, and discriminant validity.

Content and Face Validity

Content validity was established through a structured multi-round Delphi consensus methodology involving an international panel of recognized academic, clinical, and education specialists in dementia. The expert panel conducted iterative reviews of candidate items, evaluating each statement for:

• Absolute alignment with current, uncontested international clinical guidelines and empirical research.
• Absence of cultural, geographic, or discipline-specific jargon.
• Linguistic clarity, readability, and freedom from misleading grammatical ambiguity.

Items marked by ambiguity, clinical controversy, or conflicting empirical evidence were removed, leaving an unambiguous 27-item core inventory.

Construct and Evaluative Validity (Sensitivity to Educational Change)

Construct validity was validated through a large-scale intervention study examining the scale’s capacity to measure meaningful changes following targeted educational training. The DKAS was administered to thousands of participants before and after completing an 11-week online dementia curriculum (the Understanding Dementia MOOC, hosted by the Wicking Dementia Research and Education Centre; King et al., 2014). The empirical findings revealed:

• Statistically significant and substantial increases in total DKAS scores from pre-test to post-test ($p < .001$, large effect size), confirming that the instrument sensitively registers educational acquisition.
• Differential gains across subscales, verifying that the subscales capture distinct facets of learning rather than an undifferentiated general factor.

Concurrent Validity

Concurrent criterion-related validity was confirmed by administering the DKAS alongside the widely utilized Alzheimer’s Disease Knowledge Scale (ADKS) among clinical healthcare workers. Correlation analyses demonstrated a robust, statistically significant positive correlation between overall DKAS scores and ADKS total scores ($p < .001$). However, while correlating strongly on overlapping biomedical markers, the DKAS demonstrated superior dynamic range and absence of ceiling effects among experienced registered nurses and medical practitioners, who scored at near-maximum levels on the ADKS but displayed variable, nuanced scores on the DKAS.

Discriminant and Known-Groups Validity

Known-groups validation demonstrated that the scale effectively separates cohorts with predictably disparate levels of clinical training:

• Final-year medical students ($N = 40$) and experienced healthcare clinicians ($N = 76$) achieved baseline DKAS scores significantly higher than lay community respondents ($p < .01$).
• The scale successfully distinguished between general healthcare workers without geriatric credentials and specialized aged care professionals, supporting its discriminant utility.

Reliability

The DKAS exhibits strong internal consistency, minimal measurement error, and temporal stability across repeated administrations.

Internal Consistency

In the primary empirical validation cohort comprising 1,767 international respondents across 96 countries, the overall scale demonstrated excellent internal consistency:

• Total Scale Cronbach’s Alpha ($lpha$): Consistently reported between $.84$ and $.89$ across diverse demographic subgroups, reflecting a cohesive, harmonized instrument.
• Item-Total Correlations: Corrected item-total correlation coefficients across the 27 items ranged from $.30$ to $.61$, meeting classical test theory thresholds for scale cohesion without excessive item redundancy.
• Subscale Consistency: Individual subscales demonstrated acceptable-to-good internal reliability (alphas ranging from $.68$ to $.82$), which is notable given the intentionally concise length of each subscale (typically 5 to 9 items each).

Test-Retest Reliability (Temporal Stability)

To confirm that the scale measures stable cognitive schemas rather than transient moods or testing artifacts, temporal stability was evaluated using a test-retest design across a three-week interval with a dedicated cohort of Australian health workforce professionals ($N = 76$):

• Respondents received no educational training or feedback during the three-week window.
• The test-retest correlation coefficient was high and statistically significant ($r = .80$ to $.84$, $p < .001$), confirming exceptional temporal stability over time.
• Paired samples $t$-tests revealed no statistically significant drift in total scores across testing intervals, verifying the scale’s resilience against practice effects in the absence of instruction.

Factor Analysis

The underlying factorial structure of the DKAS was identified through rigorous exploratory and confirmatory multivariate psychometric procedures.

Exploratory Factor Analysis (EFA) and Principal Components Analysis (PCA)

The initial pool of candidate items generated through the Delphi consensus phase was subjected to Principal Components Analysis (PCA) using an oblique (direct oblimin) rotation method:

• Rationale for Oblique Rotation: Because knowledge dimensions within health sciences are theoretically interrelated (e.g., knowledge of biological pathology naturally correlates with understanding care strategies), oblique rotation was selected to allow factors to correlate realistically rather than forcing artificial orthogonality.
• Sampling Adequacy: The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was well above $.85$, and Bartlett’s Test of Sphericity was highly significant ($p < .0001$), confirming the data’s suitability for factor analysis.
• Factor Retention Criteria: Multiple criteria were evaluated to determine factor retention, including Kaiser’s eigenvalue criterion ($lambda > 1.0$), inspection of the scree plot inflection point, and parallel analysis.
• Variance Explained: The PCA supported the retention of 27 items distributed across a clean 4-component solution that accounted for 44.2% of the total cumulative variance in the dataset.

Factor Loadings and Structural Matrix

Item selection and retention adhered to rigorous psychometric benchmarks:

• Items were retained if they achieved primary pattern matrix factor loadings of $ge .35$ on their designated component.
• Items displaying complex cross-loadings (loadings $ge .30$ across multiple factors without a dominant primary loading) or communalities ($h^2 < .20$) were removed.
• Moderate inter-factor correlations (ranging from $r = .25$ to $.45$) confirmed that while the four components represent distinct, discernible facets of dementia literacy, they function together within an overarching general construct.

Instrument / Measurement Tool

• Test Type: Standardized, objective cognitive knowledge assessment questionnaire (Self-report / Multiple-choice objective format).
• Format: 27 written declarative statements administered in either web-based digital or physical paper-and-pencil formats.
• Item Count: 27 items.
• Response Scale: 27 items, 4-point Likert scale (strongly disagree to strongly agree) with an auxiliary ‘I don’t know’ option.
• Response Options:
  • Strongly Disagree
  • Disagree
  • Agree
  • Strongly Agree
  • I Don’t Know (Auxiliary option designed to prevent blind guessing)
• Scoring Architecture:
  • Items are evaluated against an objective scientific correctness answer key.
  • Direction of Scoring: Statements are divided between positively phrased statements (where ‘Agree’ / ‘Strongly Agree’ represent correct clinical knowledge) and 10 negatively phrased statements (where ‘Disagree’ / ‘Strongly Disagree’ represent correct clinical knowledge).
  • Reverse Scoring: The scale includes 10 negatively phrased statements that must be reverse-scored prior to calculating the total knowledge score.
  • Correct responses are awarded points (typically 1 point per correct response in binary scoring systems, or graded weighting depending on the analytical protocol, with incorrect and ‘I don’t know’ responses receiving 0 points).
  • Total Scale Score: Summed across all 27 items (raw range: 0 to 27 points, with higher scores reflecting greater dementia literacy).
• Language: English (with official and cross-culturally validated translations published in multiple languages, including Chinese, Japanese, Spanish, and Norwegian).
• Target Population: Broadly applicable to adult populations, including registered nurses, physicians, allied health specialists, direct-care residential aged care staff, undergraduate medical and nursing students, informal family caregivers, and the general public.
• Administration Time: Approximately 10 to 15 minutes.

Permissions & Fee and Test Year

The Dementia Knowledge Assessment Scale was formally published in 2015 in the Journal of the American Geriatrics Society (Annear et al., 2015). The instrument was created by the academic research team at the Wicking Dementia Research and Education Centre, University of Tasmania, and Curtin University.

The DKAS is made accessible for academic, clinical, and non-commercial research investigations. Researchers, clinical educators, healthcare organizations, and educational institutions are generally permitted to use the scale free of charge for non-commercial research, institutional evaluation, and instructional quality improvement, provided that the original publication is fully and accurately cited. The scale is proprietary and copyrighted by the developers. Commercial applications, widespread reproduction in commercial educational software, or formal inclusion in fee-for-service training packages require prior formal written licensing approval from the primary author (Dr. Michael J. Annear) or the Wicking Dementia Research and Education Centre, University of Tasmania.

References

Below is the complete reference list in APA 7th edition format:

• Aarli, J. A. (2006). Neurological disorders: Public health challenges. World Health Organization.
• Annear, M. J., Toye, C. M., Eccleston, C. E., McInerney, F. J., Elliott, K. E. J., Tranter, B. K., Hartley, T. F., & Robinson, A. L. (2015). Dementia Knowledge Assessment Scale: Development and preliminary psychometric properties. Journal of the American Geriatrics Society, 63(11), 2375–2381. https://doi.org/10.1111/jgs.13707
• Arai, Y., Arai, A., & Zarit, S. H. (2008). What do we know about dementia? A survey on knowledge about dementia in the general public of Japan. International Journal of Geriatric Psychiatry, 23(4), 433–438. https://doi.org/10.1002/gps.1977
• Australian Bureau of Statistics. (2011). Census of population and housing: Socio-economic indexes for areas (SEIFA). Australian Bureau of Statistics.
• Carpenter, B. D., Balsis, S., Otilingam, P. G., Hanson, P. K., & Gatz, M. (2009). The Alzheimer’s Disease Knowledge Scale: Development and psychometric properties. The Gerontologist, 49(2), 236–247. https://doi.org/10.1093/geront/gnp023
• Ferri, C. P., Prince, M., Brayne, C., Brodaty, H., Fratiglioni, L., Ganguli, M., Hall, K., Hasegawa, K., Hendrie, H., Huang, Y., Jorm, A., Mathers, C., Menezes, P. R., Rimmer, E., & Scazufca, M. (2005). Global prevalence of dementia: A Delphi consensus study. The Lancet, 366(9503), 2112–2117. https://doi.org/10.1016/S0140-6736(05)67889-0
• Gandy, S. (2011). Perspective: Prevention is better than cure. Nature, 475(7355), S15–S15. https://doi.org/10.1038/475S15a
• Gilleard, C., & Groom, F. (1994). A study of two dementia quizzes. British Journal of Clinical Psychology, 33(4), 529–534. https://doi.org/10.1111/j.2044-8260.1994.tb01149.x
• Hughes, J., Bagley, H., Reilly, S., Burns, A., & Challis, D. (2008). Care staff working with people with dementia: Training, knowledge and confidence. Dementia, 7(2), 227–238. https://doi.org/10.1177/1471301208091159
• King, C. E., Robinson, A. L., & Vickers, J. C. (2014). Targeted MOOC captivates students. Nature, 505(7481), 26–26. https://doi.org/10.1038/505026a
• Kitwood, T. (1997). Dementia reconsidered: The person comes first. Open University Press.
• Kuhn, D., King, S., & Fulton, B. R. (2005). Development of the Knowledge about Memory Loss and Care (KAML-C) test. American Journal of Alzheimer’s Disease & Other Dementias, 20(1), 41–49. https://doi.org/10.1177/153331750502000108
• Mitchell, S. L., Kiely, D. K., & Hamel, M. B. (2004). Dying with advanced dementia in the nursing home. Archives of Internal Medicine, 164(3), 321–326. https://doi.org/10.1001/archinte.164.3.321
• O’Brien, J. T. (2014). The importance of longitudinal cohort studies in understanding risk and protective factors for dementia. International Psychogeriatrics, 26(4), 541–542. https://doi.org/10.1017/S104161021400009X
• Robinson, A., Eccleston, C., Annear, M., Elliott, K. E., Andrews, S., Stirling, C., Ashby, M., & Toye, C. (2014). Who knows, who cares? Dementia knowledge among nurses, care workers, and family members of people living with dementia. Journal of Palliative Care, 30(3), 158–165. https://doi.org/10.1177/082585971403000305
• Smyth, W., Fielding, E., Beattie, E., Gardner, A., Moyle, W., Franklin, S., MacAndrew, M., & Gray, M. (2013). A survey-based study of knowledge of Alzheimer’s disease among health care staff. BMC Geriatrics, 13(1), Article 2. https://doi.org/10.1186/1471-2318-13-2
• Spector, A., Orrell, M., Schepers, A., & Shanahan, N. (2012). A systematic review of ‘knowledge of dementia’ outcome measures. Ageing Research Reviews, 11(1), 67–77. https://doi.org/10.1016/j.arr.2011.09.002
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
• Toye, C., Lester, L., Popescu, A., McInerney, F., Andrews, S., & Robinson, A. (2014). Dementia Knowledge Assessment Tool Version Two: Development of a tool to inform preparation for care planning and delivery in families and care staff. Dementia, 13(2), 248–256. https://doi.org/10.1177/1471301212471960
• Turner, S., Iliffe, S., Downs, M., Wilcock, J., Bryans, M., Levin, E., Keady, J., & O’Carroll, R. (2004). General practitioners’ knowledge, confidence and attitudes in the diagnosis and management of dementia. Age and Ageing, 33(5), 461–467. https://doi.org/10.1093/ageing/afh140

Items of the Scale