Annals of International Occupational Therapy

Original Research 

Association Between Performance on the Mini-Mental State Examination and the Montreal Cognitive Assessment Among Patients in a Subacute Inpatient Setting

Sze Tim Sonia Yu, BOT(Hons); Mong-Lin Yu, PhD, MOccTh, BSc(OT), GCHPE; Ted Brown, PhD, MSc, MPA, BScOT(Hons), GCHPE, OT(C), OTR, MRCOT, FOTARA; Hanna Andrews, BOT

Abstract

Background:

Occupational therapists often assess clients' cognitive skills. It is important for therapists to make informed decisions and choose the most appropriate and robust cognitive assessment.

Aim:

To explore the association between performance on the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) among patients in a subacute inpatient setting.

Methods:

A total of 20 participants (11 men, 9 women; mean age, 82 years; SD = 6.93) were recruited from a geriatric evaluation and management ward in an Australian hospital. Cognitive ability was assessed with the MMSE and MoCA. Spearman's rho correlation analysis with bootstrapping was completed.

Results:

Statistically significant associations were found between MMSE and MoCA total scores (rs = .63, p < .01), orientation subscale scores (rs = .65, p < .01), and attention subscale scores (rs = .76, p < .01). Other statistically significant correlations were found between MMSE and MoCA subscale scores.

Conclusion:

The MoCA appears to be a valid measure that can be used to evaluate cognitive status in a subacute geriatric evaluation and management setting. A small sample size and the use of convenience sampling were the main limitations of the study. Further studies with a larger sample are recommended to confirm these findings. [Annals of International Occupational Therapy. 2018;1(1):15–23.]

Abstract

Background:

Occupational therapists often assess clients' cognitive skills. It is important for therapists to make informed decisions and choose the most appropriate and robust cognitive assessment.

Aim:

To explore the association between performance on the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) among patients in a subacute inpatient setting.

Methods:

A total of 20 participants (11 men, 9 women; mean age, 82 years; SD = 6.93) were recruited from a geriatric evaluation and management ward in an Australian hospital. Cognitive ability was assessed with the MMSE and MoCA. Spearman's rho correlation analysis with bootstrapping was completed.

Results:

Statistically significant associations were found between MMSE and MoCA total scores (rs = .63, p < .01), orientation subscale scores (rs = .65, p < .01), and attention subscale scores (rs = .76, p < .01). Other statistically significant correlations were found between MMSE and MoCA subscale scores.

Conclusion:

The MoCA appears to be a valid measure that can be used to evaluate cognitive status in a subacute geriatric evaluation and management setting. A small sample size and the use of convenience sampling were the main limitations of the study. Further studies with a larger sample are recommended to confirm these findings. [Annals of International Occupational Therapy. 2018;1(1):15–23.]

Cognition refers to the integrated mental processes, including the acquisition and use of knowledge, that bring about thoughts and goal-directed actions (Levy, 2005; Radomski & Morrison, 2014). These processes can be classified into basic cognitive skills that include orientation, attention, memory, concentration, visual perception, visuospatial processing, language, and simple problem solving as well as higher level cognitive skills that include self-awareness and executive functions (Glogoski, Milligan, & Wheatley, 2006). These skills are directly related to the ability to engage in activities of daily living and participate in purposeful, proactive interactions and complex decision making (Radomski & Morrison, 2014).

Many older adults experience noticeable changes or a decline in cognition. When this decline starts to interfere with everyday functioning and occupational performance, it can be labeled as cognitive impairment (Radomski & Morrison, 2014). However, impaired cognition is not always a natural part of the aging process. Cognitive impairment can result from a number of clinical conditions, including dementia, delirium as a result of acute illness, depression, traumatic brain injury, stroke, medication side effects, developmental disabilities, and other neurological conditions (Glogoski et al., 2006; Woodford & George, 2007).

More than half of people with known cognitive problems progress to dementia within 5 years of diagnosis, and dementia ranks as the fourth leading cause of death among people aged 65 years and older (Gauthier et al., 2006; Victorian Government Department of Health & Human Services, 2012). Therefore, it is vital for occupational therapists to assess patients' cognition to detect cognitive impairment, perform a differential diagnosis of the cause, determine the severity of impairment, and monitor the progression of disease, in addition to directing the need for further assessment and management (Ismail, Rajji, & Shulman, 2010; Woodford & George, 2007).

To assess a patient's cognitive status, screening assessment tools are typically used because they also assist occupational therapists in monitoring the patient's cognitive functioning (Aretouli & Brandt, 2010; Radomski & Morrison, 2014). A variety of cognitive screening instruments are available in current practice, each with its own strengths and weaknesses. These include, for example, the Mini-Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975); the Montreal Cognitive Assessment (MoCA) (Nasreddine et al., 2005); the Rowland Universal Dementia Assessment Scale (Storey, Rowland, Conforti, & Dickson, 2004); Addenbrooke's Cognitive Examination-III (Hsieh, Schubert, Hoon, Mioshi, & Hodges, 2013); the Neurobehavioral Cognitive Status Examination (Kiernan, Mueller, Langston, & Van Dyke, 1987); and the Neuropsychiatry Unit Cognitive Assessment Tool (Walterfang, Siu, & Velakoulis, 2006). Selection of an appropriate assessment tool is usually based on the psychometric properties of the tool, such as validity and reliability; clinical utility; time required for training; ease of scoring, administration, and interpretation; fit with the needs of the clinical setting; availability and accessibility; cost; and purpose and theoretical construction (which refers to the fit between the assessment and the clinician's theoretical approach to occupational therapy) (Bennett, Shand, & Liddle, 2011; Douglas, Liu, Warren, & Hopper, 2007; Law, Baum, & Dunn, 2005).

The MMSE is the most widely understood and used cognitive screening tool worldwide for other health and medical disciplines (Folstein et al., 1975; Radomski & Morrison, 2014). It is a quick assessment that takes approximately 5 to 10 minutes to administer. It is available in a variety of languages and has proven validity in many clinical populations (Damian et al., 2011). The MMSE was reported to have high internal consistency for older adults with cognitive impairment (Cronbach's alpha = 0.81) (Tombaugh, McDowell, Kristjansson, & Hubley, 1996) and for patients with cancer (Cronbach's alpha = 0.89) (Mystakidou, Tsilika, Parpa, Galanos, & Vlahos, 2007). High 24-hour test–retest reliability (Pearson r = .887, p < .05) and adequate to high interrater reliability also have been reported (Folstein et al., 1975), together with good concurrent and construct validity (Folstein et al., 1975; Razani et al., 2009). However, Tombaugh and McIntyre (1992) indicated that the MMSE has low sensitivity for mild cognitive impairment, and its score may be affected by the age, education, and cultural background of the respondents. The MMSE also has been shown to have a negative bias toward individuals from culturally and linguistically diverse backgrounds (Moraes, Pinto, Lopes, Litvoc, & Bottino, 2010; Naqvi, Haider, Tomlinson, & Alibhai, 2015).

New cognitive assessment tools have been developed to address the reported weaknesses of the MMSE (Damian et al., 2011). The MoCA stands out and is a relatively new screening tool that was developed to detect mild cognitive impairment (Nasreddine et al., 2005). It takes 10 to 15 minutes to administer and has exhibited good psychometric properties. For example, Nasreddine et al. (2005) and Gill, Freshman, Blender, and Ravina (2008) reported that the MoCA has excellent test–retest reliability, internal consistency, and interrater reliability. There is also evidence that the MoCA has excellent concurrent validity, discriminant validity, adequate predictive validity of functional status, and high sensitivity in identifying mild cognitive impairment (Damian et al., 2011; Gill et al., 2008; Nasreddine et al., 2005; Radomski & Morrison, 2014; Toglia, Fitzgerald, O'Dell, Mastrogiovanni, & Lin, 2011). In addition, the MoCA has been translated into 36 languages and has been used in many cross-cultural settings (Julayanont, Phillips, Chertkow, & Nasreddine, 2012; Nasreddine et al., 2005; Zheng et al., 2012). Yet, some studies have indicated that the MoCA may be overly sensitive in detecting mild cognitive impairment, and its previously reported high sensitivity is associated with low specificity (Godefroy et al., 2011; Radomski & Morrison, 2014).

Because the MMSE is no longer in the public domain and may be too costly to use in some countries because of copyright issues (Stewart, O'Riley, Edelstein, & Gould, 2012) and there have been mixed opinions regarding the psychometric properties and clinical utility of the MoCA, it is questionable whether the MoCA can completely replace the MMSE as a cognitive screening tool. A limited number of studies have compared the MMSE and the MoCA (Aggarwal & Kean, 2010; Lam et al., 2013; Markwick, Zamboni, & de Jager, 2012; Stewart et al., 2012; Sweet et al., 2011; Toglia et al., 2011; Trzepacz, Hochstetler, Wang, Walker, & Saykin, 2015). Therefore, this study was conducted to examine the association between performance on the MMSE and the MoCA among patients in a subacute inpatient setting. The findings will aid in the decision-making process of therapists in selecting an appropriate cognitive screening tool.

Methods

Research Questions and Hypotheses

Research question 1. What is the degree of association between MoCA and MMSE total scale scores?

Null hypothesis. There is no statistically significant association between MoCA and MMSE total scale scores.

Alternative hypothesis. There is a moderately strong level of statistically significant association between MoCA and MMSE total scale scores.

Research question 2. What is the level of correlation between MoCA and MMSE subscale scores?

Null hypothesis. There is no statistically significant association between MoCA and MMSE subscale scores.

Alternative hypothesis. There is a moderately strong level of statistically significant association between MoCA and MMSE subscale scores.

Participants

Participants were recruited from a geriatric evaluation and management hospital ward in Melbourne, Australia, using a convenience sampling method.

Inclusion criteria for the study participants included the following: (a) participants were inpatients on the sub-acute geriatric evaluation and management ward at Casey Hospital, Monash Health, Berwick, Australia; (b) participants were aged 65 years or older; (c) participants provided informed consent to participate in the study; (d) participants did not have a confirmed diagnosis of dementia or other forms of cognitive impairment and thus were able to provide informed consent to participate (for participants who were suspected of having cognitive impairment, the next of kin or a family member provided consent for participation); and (e) participants could read and write and had sufficient English competence to understand the questions on the MMSE and MoCA.

Exclusion criteria for participants included the following: (a) participants had a confirmed diagnosis of dementia or other forms of cognitive impairment or a secondary/pre-existing neurological medical condition (e.g., multiple sclerosis or Parkinson's disease) and thus were unable to provide informed consent to take part in the study; (b) participants were suspected of having cognitive impairment and their next of kin or family members did not provide consent for the participants to take part in the study; (c) participants were medically or psychiatrically unstable, were experiencing delirium, were profoundly deaf or blind, or had been admitted to the hospital for transient ischemic attack, cerebrovascular accident, traumatic brain injury, or urinary tract infection; (d) participants were unable to read and write or had insufficient English competence to understand the questions on the MMSE and MoCA; and (e) participants were unable to complete both the MMSE and MoCA.

Instrumentation

Mini-Mental State Examination. The MMSE is a widely used standardized cognitive screening scale that was designed to detect cognitive problems. It includes 11 questions that assess the cognitive domains of orientation to time and place, registration, attention/calculation, recall, language (including naming, repetition, comprehension, reading, and writing), and copying. The maximum score is 30, with a score of 24 or below suggesting cognitive impairment (Folstein et al., 1975; Radomski & Morrison, 2014).

Montreal Cognitive Assessment. The MoCA is a relatively new screening tool that was developed to detect mild cognitive impairment. It measures executive functions, visuospatial skills, language, attention and concentration, calculations, memory and delayed recall, conceptual thinking, and orientation. The maximum score is 30, with a score of 26 or below indicative of cognitive impairment (Nasreddine et al., 2005; Radomski & Morrison, 2014).

Data Entry, Management, and Analysis

The Statistical Package for the Social Sciences (SPSS), version 20, for Windows, was used for data entry, storage, and analysis. Descriptive statistics and Spearman's rho correlation analyses with bootstrapping were completed to investigate the association between the subscale and total scores of the MMSE and MoCA. For correlation analysis, sample size plays an important role because it affects the generalizability of the findings.

Therefore, a resampling technique referred to as “bootstrapping” was used (Chernick, 2007). Bootstrapping is a type of robust statistic that infers a population from sample data (Davison & Hinkley, 1997). It works by taking, with replacement, the values from the original sample to obtain thousands of bootstrapped samples to improve the accuracy of the confidence interval estimation for one or more statistics (Walters & Campbell, 2004). For bootstrapping, it is assumed that the original sample reasonably represents the population (LaFlair, Egbert, & Plonsky, 2015). The bootstrap results were based on 1,000 bootstrap samples. Bootstrap specifications were as follows: (a) sampling method, simple; (b) number of samples, 1,000; (c) confidence interval level, 95%; and (d) confidence interval type, bias-corrected and accelerated.

Procedures

Ethical approval was obtained through both the Monash Health and the Monash University Human Research Ethics committees. All ethical issues relevant to this study were considered. Participants who met the inclusion criteria were identified by their treating occupational therapists. Consent was obtained from all participants. For participants who were suspected of having cognitive impairment by their treating occupational therapists, consent was sought from the next of kin who had formal guardianship of the participants. This was deemed acceptable by the two ethics committees that approved this study in the jurisdiction where the study was completed.

Demographic data, including age, gender, country of birth, language spoken at home, reason(s) for admission, and estimated length of hospital stay, were collected via medical files. To ensure the reliability and accuracy of the data and minimize inconsistent scoring, the first author completed the two cognitive assessments (MMSE and MoCA) with all participants. The first author completed the two cognitive assessments during two individual sessions within 2 days of each other to minimize the effect of participant fatigue. All assessments were completed in accordance with the guidelines and protocols outlined in the MMSE and MoCA manuals. The order of completion of the MMSE and MoCA by participants was alternated. In other words, if one participant completed the MMSE first, followed by the MoCA, then the subsequent participant completed the MoCA initially and then the MoCA. This was done to minimize the potential influence of an order effect.

Results

Participants

A total of 20 participants (n = 20) took part in the study, including 11 men (55%) and 9 women (45%). Age ranged from 66 to 93 years, with mean age of 82.05 years (SD = 6.93). All participants spoke English, and most were born in Australia (n = 10, 50%) or the United Kingdom (n = 5, 25%). The most common reasons for admission to the hospital were orthopedic conditions secondary to a fall (n = 11, 55%), followed by general deconditioning (n = 2, 10%), cardiac conditions (n = 1, 5%), and other medical issues (n = 6, 30%). Length of stay ranged from 4 to 34 days, with a mean of 14.85 days (SD = 6.49).

Participant Instrument Scores

All participants completed the two cognitive assessments, the MMSE and the MoCA. Mean, median, SD, range, and interquartile ranges of the scores from the MMSE and MoCA are detailed in Table 1. Mean scores for the MMSE scales were as follows: orientation, 9.35 (SD = 0.75); registration, 3.00 (SD = 0.00); attention/calculation, 2.90 (SD = 1.89); delayed recall, 2.40 (SD = 0.68); language, 7.30 (SD = 0.86); copying, 0.90 (SD = 0.31); and total, 25.85 (SD = 2.68). For the MoCA, mean subscale scores were as follows: executive functions and visuospatial skills, 3.50 (SD = 1.10); naming, 2.60 (SD = 0.60); attention, 4.75 (SD = 1.37); language, 1.75 (SD = 0.72); abstraction, 1.10 (SD = 0.72); delayed recall, 1.15 (SD = 1.39); orientation, 5.65 (SD = 0.59); and total, 20.50 (SD = 3.19). Because the MMSE registration subscale score was a constant, no correlation coefficients were calculated with the MoCA subscales.

Participant Sample Mean, Median, Standard Deviation (SD), Range, and Interquartile Range Scores for the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) (n = 20)

Table 1:

Participant Sample Mean, Median, Standard Deviation (SD), Range, and Interquartile Range Scores for the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) (n = 20)

Correlation Results

Spearman's rho correlation analyses were performed with the MMSE total score and subscale scores (orientation, registration, attention/calculation, delayed recall, language, and copying) and the MoCA total score and sub-scale scores (executive functions and visuospatial skills, naming, attention, language, abstraction, delayed recall, and orientation) to identify statistically significant associations between these variables.

Spearman's rho correlation analyses between the total scores and subscale scores of the MMSE and MoCA (n = 20) identified significant correlation coefficients between the MMSE and MoCA, as shown in Table 2. A strong positive association was found between the MMSE total score and the MoCA total score (rs = .63, p < .01), with a high MMSE total score associated with a high MoCA total score.

Spearman's Rho Correlationsa Between the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) Total and Subscale Scores (n = 20)

Table 2:

Spearman's Rho Correlations Between the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) Total and Subscale Scores (n = 20)

Moreover, the MMSE orientation subscale score was significantly associated with the MoCA orientation sub-scale score (rs = .65, p < .01) and the MoCA total score (rs = .53, p < .05). A significant strong association also was found between the MMSE attention/calculation subscale score and the MoCA attention subscale score (rs = .76, p < .01), and a significant strong association was found between the MMSE delayed recall subscale score and the MoCA naming subscale score (rs = .61, p < .01).

Additionally, the MMSE language subscale score was significantly interrelated with the MoCA executive functions and visuospatial skills subscale scores (rs = .53, p < .05), moderately related to the MoCA attention subscale score (rs = .46, p < .05), and moderately associated with the MoCA total score (rs = .56, p < .01). The MMSE total score and the MoCA attention subscale score also were strongly associated (rs = .74, p < .01). Correlation coefficients for the MMSE registration subscale score could not be calculated with SPSS because the MMSE registration subscale score was a constant and therefore was excluded from the correlation analyses.

Discussion

This study was conducted to identify associations between performance on the MMSE and MoCA among patients in a subacute inpatient setting. Spearman's rho correlation analyses were performed. The findings showed several statistically significant associations between MMSE and MoCA total scores and MMSE and MoCA subscale scores.

These findings concur with several previously completed studies. A study by Sweet et al. (2011) that had a methodological design similar to that of the current study reported that the MoCA was significantly correlated with the MMSE, based on the scores obtained from 47 patients on admission to (correlation coefficient = .68, p < .005) and discharge from a geriatric rehabilitation program in Canada (correlation coefficient = .52, p < .005). Aggarwal and Kean (2010) also reported consistent findings in a comparison of the MMSE and MoCA as a cognitive screening tool in an inpatient rehabilitation setting. They reported that Pearson's correlation coefficient between total scores of the MMSE and MoCA, obtained from 50 patients admitted to a general subacute rehabilitation ward in an Australian hospital, was .70 (p < .003). Other studies of the MMSE and MoCA scores of patients with brain metastases (Olson et al., 2011), those with mild Alzheimer's disease or mild cognitive impairment (Freitas, Simões, Alves, & Santana, 2013; Lam et al., 2013; Markwick et al., 2012; Stewart et al., 2012; Trzepacz et al., 2015), those with mild subacute stroke (Toglia et al., 2011), and those admitted to an acute hospital (Saczynski et al., 2015) also reported significant relationships between the two cognitive screening tools.

More specifically, the findings of the current study showed that the orientation (rs = .65, p< .01) and attention (rs = .76, p < .01) subscales of the MMSE and MoCA were significantly correlated. These findings also were reported by Toglia et al. (2011), who stated that the mean percent scores (calculated by dividing the mean score by the maximum score) of the orientation subscales of the MMSE and MoCA collected from 72 patients who had a stroke were 86% and 84%, respectively. The closer the mean percent scores, the stronger the relationship. Similarly, mean percent scores of the attention subscales of the MMSE and MoCA were 64% and 60%, respectively. Toglia et al. (2011) concluded that the orientation and attention subscales of the MoCA exhibited close relationships to the comparable subscales of the MMSE, consistent with the current findings.

Because the MMSE is considered a gold standard scale and it measures similar cognitive abilities to the MoCA (Brown, Elliott, & Fielding, 2014), the significant relationships between the MMSE and MoCA identified in the current study further confirm the concurrent and convergent validity of the MoCA. Concurrent validity is established when the results of a particular test are correlated with those of a previously well-established test, and convergent validity is the level of agreement between two tests that are being used to measure the same or parallel constructs or traits (Boyt Schell, Gillen, Scaffa, & Cohn, 2014). Therefore, the findings of the current study add to the growing evidence of the validity of the MoCA (Freitas et al., 2013; Lam et al., 2013; Sweet et al., 2011; Toglia et al., 2011).

However, notably, a number of nonsignificant correlations were found between MMSE and MoCA subscales that appeared to assess similar constructs. For example, the MMSE delayed recall subscale was not significantly correlated with the MoCA delayed recall subscale (rs = .15, p > .05) and the MMSE language subscale was not significantly correlated with the MoCA language subscale (rs =.38, p > .05) or the MoCA naming subscale (rs = −.15, p > .05). Further, the MMSE copying subscale was not significantly associated with the MoCA executive functions and visuospatial skills subscale (rs = −.02, p > .05). Others have reported similar results (Lam et al., 2013; Sweet et al., 2011; Toglia et al., 2011).

Implications for Practice

The findings of the current study support the use of the MoCA to screen for cognitive impairment among patients in a subacute geriatric evaluation and management setting. Both the MMSE and MoCA are currently used in Australian subacute geriatric evaluation and management settings, but the cognitive domains that they measure are slightly different. Therefore, when choosing an instrument, occupational therapists and other practitioners should consider carefully the reasons for assessing a patient's cognitive abilities because the MMSE and MoCA may not be interchangeable. Factors to consider when selecting one instrument over another as the primary cognitive screening tool may include the patient's educational level, medical diagnoses, and cultural and linguistic background as well as the ease and practicality of administering the cognitive scales.

Limitations

This study had several limitations that should be considered when interpreting the findings. The main limitations were the small sample size (n = 20) and the convenience sampling method used. Additionally, detailed demographic information about the participants, including educational level, living circumstances, and socioeconomic status, were not collected. Moreover, participants were recruited from a subacute geriatric evaluation and management ward located in a teaching hospital in the metropolitan region of Melbourne, Australia. Therefore, because only a small geographic region was sampled, the results may not be generalizable to the larger population. However, participants had a range of cultural backgrounds, reflecting the cultural and linguistic diversity of the general Australian population. Additionally, to ensure that the cognitive scales were completed consistently, the MMSE and MoCA were administered by the first author, minimizing the potential for bias.

Future Research

Several recommendations for future research are apparent. To increase the generalizability of the findings, replicating this study with a larger sample size drawn from a wider geographical area and using randomized sampling methods is suggested. Adding control groups is also recommended to allow comparisons between healthy older adults and older adults with mild cognitive impairment. Additionally, to allow comparisons between different cognitive assessments and further confirm the validity of the MoCA, different or more comprehensive cognitive measures, such as Addenbrooke's Cognitive Examination-III or the Neuropsychiatry Unit Cognitive Assessment Tool, should be used to evaluate patients' cognitive status.

Conclusion

This study showed statistically significant associations between the MMSE and MoCA total scores and some of the subscale scores, further confirming the validity of the MoCA. The MoCA appeared to be a valid measure that can be used to evaluate patients' cognitive status in a sub-acute geriatric evaluation and management setting. However, occupational therapists or other practitioners should use caution when selecting the most appropriate cognitive screening tool because the assessment tools measure slightly different cognitive domains.

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Participant Sample Mean, Median, Standard Deviation (SD), Range, and Interquartile Range Scores for the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) (n = 20)

Cognitive scale M Median SD Range Interquartile range (Q1, Q3)
MMSE subscales
  Orientation 9.35 9.00 0.75 7–10 9, 10
  Registration 3.00 3.00 0.00 3–3 3, 3
  Attention/calculation 2.90 2.50 1.89 0–5 1, 5
  Delayed recall 2.40 2.50 0.68 1–3 2, 3
  Language 7.30 8.00 0.86 6–8 6, 8
  Copying 0.90 1.00 0.31 0–1 1, 1
  Total 25.85 25.50 2.68 21–30 24, 28
MoCA subscales
  Executive functions and visuospatial skills 3.50 3.00 1.10 2–5 3, 5
  Naming 2.60 3.00 0.60 1–3 2, 3
  Attention 4.75 5.00 1.37 1–6 4, 6
  Language 1.75 2.00 0.72 1–3 1, 2
  Abstraction 1.10 1.00 0.72 0–2 1, 2
  Delayed recall 1.15 0.50 1.39 0–4 0, 3
  Orientation 5.65 6.00 0.59 4–6 5, 6
  Total 20.50 21.00 3.19 13–25 19, 23

Spearman's Rho Correlationsa Between the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) Total and Subscale Scores (n = 20)

MoCA subscales MMSE subscales
Orientation Registrationb Attention/calculation Delayed recall Language Copying Total
Executive functions and visuospatial skills .37 - −.09 −.18 .53* −.02 .23
Naming −.16 - .09 .61** −.15 −.24 .01
Attention .25 - .76** −.08 .46* .03 .74**
Language .11 - .06 .20 .38 −.16 .25
Abstraction .10 - .35 .04 .23 −.19 .41
Delayed recall .41 - .16 .15 .16 −.06 .17
Orientation .65** - .03 .24 −.01 −.22 .26
Total .53* - .39 .22 .56** −.22 .63**
Authors

Ms. Sze Tim Sonia Yu is Occupational Therapy Student, Dr. Mong-Lin Yu is Lecturer and Fieldwork Coordinator, and Dr. Brown is Associate Professor and Undergraduate Course Coordinator, Department of Occupational Therapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University–Peninsula Campus, Frankston, Victoria, Australia. Ms. Andrews is Occupational Therapist—Sub-Acute, Casey Hospital, Monash Health, Berwick, Victoria, Australia.

The authors have no relevant financial relationships to disclose.

The authors thank all participants and their families who volunteered to take part in this study.

Address correspondence to Ted Brown, PhD, MSc, MPA, BScOT(Hons), GCHPE, OT(C), OTR, MRCOT, FOTARA, Associate Professor and Undergraduate Course Coordinator, Department of Occupational Therapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University–Peninsula Campus, Building G, 4th Floor, McMahons Road, PO Box 527, Frankston, Victoria 3199, Australia; e-mail: ted.brown@monash.edu.

Received: July 15, 2017
Accepted: November 22, 2017

10.3928/24761222-20180212-02

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