Physical Activity Measurement in Older Adults with Dementia in Long-term Care Facilities: A Scoping Review

doi:10.21203/rs.3.rs-3104872/v1

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Physical Activity Measurement in Older Adults with Dementia in Long-term Care Facilities: A Scoping Review

https://doi.org/10.21203/rs.3.rs-3104872/v1

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Purpose

This scoping review systematically identifies methods of measuring physical activity in dementia patients, proposing strategies tailored to individual physical and cognitive statuses.

Methods

The methodological framework of Arksey and O’Malley was adopted, with studies identified via RISS, KISS, ScienceON, PubMed, PsychINFO, and CINAHL. Study with physical activity measurements used for dementia residents in long-term care facilities were selected. Each study was analyzed for publication features, participant characteristics, and measurement techniques.

Results

Out of the 30 studies reviewed, the majority were descriptive research in gerontology. Subjects, predominantly over 65, had their cognition and physical abilities assessed via the MMSE and Barthel Index, respectively. Physical activities were primarily measured using accelerometers, supplemented by caregiver observations. The choice of physical activity measurement correlated with cognitive function and levels of daily life dependency.

Conclusion

Although limited by the lack of literature, accelerometers proved effective in measuring physical activity in dementia patients with moderate to severe dependency, while surveys were utilized for those with total dependency. Future research should strive to offer more specific guidelines, ensuring measurement methods are effectively tailored to patients' cognitive and physical capacities.

Aged

Nursing homes

Exercise

Cognition

Activities of Daily Living

Due to the increase in life expectancy in South Korea, the number of people aged 65 and older is expected to account for 17.5% of the total population in 2022 (Statistics Korea, 2022). In addition, the rapid aging of the population has increased the social demand for care. The long-term care insurance system for the elderly was introduced in response to this trend (Sun, Woo-deok, et al., 2016), and the number of long-term care recipients has steadily increased, with the proportion of those aged 65 and older exceeding 8.4%. Of these, 51.5% are institutionalized dementia patients (Statistics Korea, 2022; Long-term Care Survey, 2022). Dementia is a disease characterized by cognitive decline, impaired ability to perform activities of daily living, and behavioral and psychological symptoms that progressively worsen over a long period of time, leading to a decrease in quality of life (Shin, 2006). In addition, after entering a facility, older adults with dementia lead an immobile lifestyle due to environmental limitations in a confined space (Chen & Li, 2014), and experience daily dependence due to reduced physical activity. This dependence has been shown to predict physical decline, cognitive decline, and depression (Taekema, Gussekloo, Maier, Wstendrop, & de Craen, 2010) and affect quality of life (Nam, Hye-Ri, & Heo-Song, 2020), making physical activity important for older adults with dementia.

The World Health Organization recommends physical activity for all older adults, including healthy and older adults with limited mobility. It emphasizes the importance of physical activity for older adults by recommending that even those unable to engage in some level of physical activity for health reasons should do so as much as their abilities and functional status allow (WHO, 2010). Furthermore, decreased physical activity is associated with decreased physical functioning, leading to adverse outcomes such as falls (Sherrington et al., 2017), and contributing to increased total healthcare costs (Centers for Disease Control and Prevention, 2023). Despite the importance of physical activity, 25% of older adults with dementia living in long-term care facilities have never participated in physical activity, and 75% do not engage in outdoor activities (Jeon, Seung-Yeon, & Kim, 2018). The decline in physical activity among institutionalized older adults is also seen internationally. More than 30% of institutionalized older adults report a decrease in physical activity after institutionalization (Ruuskanen & Parkatti, 1994), and even independently mobile older adults spend most of their time sitting or lying down (Kolanowski, Buettner, Litaker, & Yu, 2006; MacRae, Schnelle, Simmons, & Ouslander, 1996; Schmid, Weiss, & Heseker, 2003). Institutionalized older adults have been reported to spend less time in physical activity and less in physical activity for older adults with cognitive decline (Resnick & Galik, 2013).

Intervention studies have been conducted to increase physical activity among older adults with institutionalized dementia, and a variety of physical activity measures have been used to determine the effectiveness of interventions (Viviano, Balik, & Resnick, 2017; Arrieta, et al, 2018; Auerswald, 2018). Physical activity measures can be categorized as self-reported using questionnaires, indirectly measured by direct care providers, or directly measured using devices. The International Physical Activity Questionnaire (IPAQ) and the Modified Baecke Questionnaire for the Elderly are commonly used to measure physical activity in older adults with dementia (Öhlin, 2022; Farina, 2019), but the appropriateness of using self-reported questionnaires is controversial depending on the degree of cognitive impairment (Farina, 2019). Indirect measures have been proposed, such as caregivers observing and recording the amount of time spent in physical activity by older adults with dementia, recording the amount of time spent by older adults with dementia in 66 physical activities over a 24-hour period (Viviano, Balik, & Resnick, 2017), or recording the number of days spent outdoors (Jeon, Seungyeon, & Kim, Hongsoo, 2018). More recently, direct measurement methods using various devices such as accelerometers, pedometers, and wearable devices have been utilized to measure activity speed, steps, and calorie expenditure (Arrieta, et al, 2018; Auerswald, 2018; Jung, et al, 2019).

Studies have been conducted using various methods to measure physical activity in people with dementia living in long-term care facilities. However, the effectiveness of these methods may be affected by the level of cognitive and physical abilities of older adults with dementia. In other words, there are no guidelines on measuring physical activity according to the characteristics of older adults with dementia, and there is a lack of discussion on the physical and cognitive validity of the methods for older adults with dementia. Therefore, this study aimed to identify the methods used to measure physical activity in long-term care facility residents with dementia through a thematic review of studies published in domestic and international journals related to measuring physical activity in long-term care facility residents with dementia.

1. Studty design

This research is a scoping review study aimed at identifying the trends in research related to the concept of physical activity in institutionalized dementia patients and its measurement methods. Scoping reviews are exploratory research methods that systematically map available literature on a topic to identify key concepts, theories, sources of evidence, and types. They should be planned and promoted according to a predefined protocol (Kim & Kang, 2022).

Thus, this study was conducted using the five stages proposed by Arksey and O'Malley: (1) generating the research question, (2) identifying relevant studies, (3) selecting suitable studies, (4) systematically charting the data, and (5) synthesizing and reporting the information (Arksey & O'Malley, 2005). Additionally, this study utilized the PRISMA-ScR (The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist for reporting (Tricco, et al, 2018).

2. Data collection

1) Step 1: Formulating the research question

This study used the Population-Concept-Context model to organize the key content regarding the physical activity measurement method of dementia patients living in long-term care facilities (Peters et al, 2015). The Population of this study is elderly dementia patients, the Concept is the physical activity measurement method, and the Context is long-term care facilities. The specific research question was 'How is the physical activity of dementia patients in long-term care facilities measured?' The study aimed to identify the concept of physical activity used in the research and the methods of measuring physical activity, and the characteristics of physical activity measurement methods used depending on the physical and cognitive function of institutionalized dementia patients.

2) Step 2: Identifying relevant studies

(1) Search strategy

The literature search was conducted without any restrictions on the publication year of the literature and targeted academic papers published in English and Korean domestically and internationally. The literature search was conducted from May 20 to June 1, 2023, and four researchers independently conducted the search after formulating the search strategy through literature review and meetings, followed by a mutual review process. The domestic databases to be used for the literature search are the Research Information Sharing Service (RISS), Korean studies Information Service System (KISS), and ScienceON, and the overseas databases are PubMed, PsycINFO via ProQuest, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) via EBSCO. The search terms for domestic academic journals were set as 'dementia', 'Alzheimer's', 'cognitive decline', 'exercise', 'activity', 'physical activity', 'long-term care facilities', 'nursing home', 'institutional facilities', and for overseas academic journals, search keywords were set by combining 'dementia', 'Alzheimer's disease', 'cognitive dysfunction', 'exercise', 'activity', 'physical activity', 'physical exercise', 'long term care', 'nursing homes' (Appendix 1).

(2) Selection and exclusion criteria for literature

The selection criteria for the literature included in the data analysis are research papers published in domestic and international academic journals, with no restrictions on the publication year of the literature. The selection criteria for the literature are as follows: (1) Include research targeting dementia patients aged 60 and above. (2) Include research that describes the measurement method of physical activity in dementia patients. (3) Include research conducted in long-term care facilities. And the exclusion criteria for the literature are as follows: (1) Exclude research that used measurement methods that did not utilize validated tools. (2) Exclude research conducted in community-based facilities.

(3) Step 3: Selecting appropriate studies

The results of the search in domestic and international databases showed a total of 36 articles from RISS, 36 articles from KISS, 7 articles from ScienceON, 646 articles from PubMed, 4,519 articles from CINAHL, and 841 articles from PsychINFO, totaling 6,085 articles. The searched literature was managed using the bibliographic management tool EndNote. After removing 721 duplicated articles, four researchers with experience in literature research independently reviewed them using the literature review program Covidence. A total of 5,364 articles were reviewed by title and abstract, and 88 articles were selected in the first round, excluding 5,276 articles that did not meet the selection criteria regarding research purpose, subjects, content, etc. After the first selection, the researchers individually reviewed the 76 articles, excluding 12 articles that could not secure the full text, and selected 27 pieces of literature through a consensus process that checked whether they met the selection criteria and exclusion criteria through a research meeting. An additional three articles were finally selected by manually searching for the literature cited in the selected articles. A total of 30 articles were finally selected as the target papers, and the process of data collection, selection, and extraction is as shown in Fig. 1.

3. Data analysis

(1) Analysis Framework

An analysis framework was used for the systematic analysis of research on physical activity measurement methods for older adults in long-term care facilities. The analysis framework was divided into publication characteristics, research participant characteristics, and tool characteristics for analyzing the features of the study. Publication characteristics included the publication date and type of academic field, and participant characteristics included the age of the research subjects, cognitive function, physical function, and type of facility. Tool characteristics included measurement methods, measurement periods, and measuring entities.

(2) Step 4: Systematic data analysis

The systematic analysis stage of the data was composed of publication characteristics, research participant characteristics, and physical activity measurement tool characteristics using the analysis framework, and recorded using the Microsoft Excel 2020 program.

1. Characteristics of the literature publication

A total of 30 papers were used for the final analysis, and the results are shown in Table 1. The publication years of the 30 analyzed papers were 1 (3.3%) from 19902000, 3 (10.0%) from 20012010, 22 (73.3%) from 20112020, and 4 (13.3%) from 20212023, with the most papers being published after 2011. The fields of the academic journals in which the papers were published were Gerontology 12 (40.0%), physiotherapy 5 (26.7%), nursing 4 (13.3%), biology 2 (6.7%), occupational therapy 1 (3.3%), psychology 1 (3.3%), and gynecology 1 (3.3%), with most published in gerontology journals. The research designs were descriptive studies 21 (70.0%), randomized experimental studies 5 (20.0%), and quasi-experimental studies 3 (10.0%), with the most being descriptive studies measuring the physical activity of the research subjects (Table 1).

Table 1

Publication Characteristics and Research Design of included Studies (N = 30)
Variables	Categories	n(%)
Year of publication	1990 ~ 2000	1(3.3)
	2001 ~ 2010	3(10.0)
	2011 ~ 2020	22(73.3)
	2021 ~ 2023	4(13.3)
Publication field	Geriatrics	12(40.0)
	Physical therapy	8(26.7)
	Nursing	4(13.3)
	Biology·Biomedical	2(6.7)
	Occupational therapy	1(3.3)
	Psychology	1(3.3)
	Gynecology	1(3.3)
Research design	Descriptive	21(70.0)
	Randomized controlled trial	6(20.0)
	Quasi-experiental	3(10.0)

2. Characteristics of research participants

Of the finally selected literature, the most common studies were those involving older adults over 65, with 12 such studies. 8 studies did not provide a specific age and simply targeted older adults, and 6 studies targeted older adults over 55. Regarding cognitive function status, 12 studies used the Mini-Mental State Examination for measurement, making this the most common method and 7 studies targeted dementia patients without providing diagnostic criteria. In addition, 3 studies used the Cognitive Performance Scale, and 2 used the Mini-Cog. Physical function status was largely measured based on the dependency on performing daily living activities and physical performance abilities. The dependency in performing daily living activities was mainly measured using the Barthel index, and other scales used included the Katz ADL (Katz Activities of Daily Living), ADL-H (Activities of Daily Living Hoarding), and FIM (Functional Independence Measure). For physical performance abilities, the most common studies were those differentiated by walking ability. There were measurements of balance abilities using the Timed-up and Go test, measurements of muscle strength using grip strength, and measurements of walking speed. In studies using the Barthel index, the research participants had a moderate to severe dependency on performing daily living activities (Table 2).

Table 2

Participants Characteristics of included Studies (N = 30)
Variables	Cateories	n(%)
Age criteria	Older adults without age limitation	8(26.7)
	Aged over 55 years	6(20.0)
	Aged over 60 years	2(6.7)
	Aged over 64 years	1(3.3)
	Aged over 65 years	12(40.0)
	Aged over 70 years	1(3.3)
Cognitive function (n = 30)
Measurement	Mini-Mental State Examination	12(40.0)
	Cognitive Performance Scale	3(6.7)
	Mini-Cog	2(6.7)
	Montreal Cognitive Assessment	1(3.3)
	Six-item Cognitive Impairment Test	1(3.3)
	Clinical Dementia Rating	1(3.3)
	Psychogeriatric Assessment Scale	1(3.3)
	Rowland Universal Dementia Assessment Scale	1(3.3)
	Saint Louis University Mental Status Examination	1(3.3)
	Diagnosed with dementia	7(21.1)
Physical function (multiple response n = 42)
ADL dependency	The Barthel index	9(21.4)
	Katz Activities of Daily Living	2(4.8)
	Activities of Daily Living Hierarchy	2(4.8)
	Functional Independence Measure	1(2.4)
Physical ability	Timed Up and Go	2(4.8)
	Sit to Stand test	2(4.8)
	Tinetti test	1(2.4)
	Berg’s Balance Scale	1(2.4)
	Handgrip strength	2(4.8)
	A Timed Chair Stand Test	1(2.4)
	The Physical Capability Scale	1(2.4)
	Gait speed	3(7.1)
	Mobility status	6(14.3)
	Short Physical Performance Battery	3(7.1)
	Not mentioned	6(14.3)

3. Characteristics of physical activity measurement tools

In the final selected literature, physical activity was measured directly or indirectly. Direct measurement is a method of directly measuring physical activity by attaching an accelerometer to the body of a dementia patient in a long-term care facility, and indirect measurement is a method where the degree of physical activity is observed and measured by a caregiver or measured through a questionnaire. There were 17 papers (56.7%) that performed direct measurements, which was the most common, 10 papers (33.3%) that performed indirect measurements, and 3 papers (10%) that simultaneously performed direct measurements with accelerometers and indirect measurements with observation tools. Direct measurement methods often measured the calories and time spent on physical activity, with 10 cases each, and a method that divided the intensity of physical activity based on the calories consumed and measured the frequency was also used. Among the indirect measurement methods, 6 papers observed and measured the time and degree of physical activity by the caregiver. The observation tools used were the PAS-LTC (Physical Activity Survey for Long Term Care), and MEDLO-tool (the Maastricht Electronic Daily Life Observation tool), and 2 studies measured the time spent on physical activities without using validated observation tools. There were 2 studies, each measured through questionnaires targeting caregivers and dementia patients in long-term care. The questionnaire for caregivers used the IPAQ-E (The International Physical Activity Questionnaire modified for the elderly) and Activity Pursuit Patterns, and the questionnaire for the residents used the Nursing Home Life Space Diameter and Assessment of Physical Activity. Direct measurement devices were measured for an average of 5.3 ± 2.4 days, and in the case of observation measurements, it was measured for an average of 40.3 ± 46.7 hours (Table 3).

Table 3

Physical Activity Measurement Characteristcs of included Studies
Variables	Categories	n (%) or M ± SD
Measurement Type (n = 30)
Direct measurement		17 (56,7)
Indirect measurement	Caregiver-reported survey
	IPAQ-E	1 (3.3)
	APP	1 (3.3)
	Self-reported survey
	The Nursing Home Life Space Diameter	1 (3.3)
	APA	1 (3.3)
	InterRAI	1 (3.3)
	Observation
	MEDLO-tool	1 (3.3)
	PAS-LTC	3 (10.0)
	Time of physical activities	1 (3.3)
Both measurement		3 (10.0)
Measured variables of direct measurement (multiple response n = 36)
Movements of arm		1 (2.8)
Calories of energy expended		10 (27.8)
Total time in activity		10 (27.8)
Count of sedentary behavior		4 (11.1)
Count of activity		8 (22.2)
Step count		3 (8.3)
Measurement duration
Direct measurement		5.3 ± 2.4 days
Observation measurement		40.3 ± 46.7 hr
PAS-LTC: Physical Activity Survey for Long Term Care; MEDLO-tool: the Maastricht Electronic Daily Life Observation tool; PAL: The Pool Activity Level Checklist; APA: Assessment of Physical Activity; IPAQ-E: The International Physical Activity Questionnaire modified for the elderly

4. Physical activity measurement methods according to cognitive function and physical function of research participants

Among the finally selected literature, papers that presented the average cognitive function scores and used tools that used daily living performance ability for physical function and presented the average scores were selected, and physical activity measurement methods used according to cognitive function status and physical function status were classified. If it was moderate dementia and completely dependent on daily life, the number of times the accelerometer value was measured through direct measurement was checked. In cases of severe dementia and moderate dependency in daily life, the time spent according to the activity level was measured through direct measurement. In cases of severe dementia and severe dependency, direct and indirect measurements were used in combination. In cases of severe dementia and complete dependency in daily life, physical activity was measured using a questionnaire filled out by the caregiver (Table 4).

Table 4

Physical Activity Measurements according to Participants Cognitive and Physical Functioning.
Article	Cognitive function	Physical function	Physical activity measurement
Barber et al (2015)	Moderate dementia (MMSE 19.3 ± 7.4)	Total dependency (Barthel Index 14 ± 5.4)	ActiGraph 1) Total daily accelerometer counts
Resnick et al (2018)	Severe dementia (Mini-Cog〈3)	moderate dependency (Barthel Index 63.06 ± 20.20)	MotionWatch 8. 1) Counts of activity 2) Time in moderate activity, time in sedentary activity
Resnick et al (2019)	Severe dementia (Mini-Cog 2.53 ± .69)	Moderate dependency Barthel index 64.15 ± 19.15	MotionWatch 8, 1) The number of minutes ofand vigorous physical activity.
Resnick et al (2022)	Severe dmentia (Mini-Cog〈3)	Moderate dependency (Barthel Index 64.92 ± 16.32)	MotionWatch 8. 1) Counts of activity 2) Time spent in sedentary, moderate and vigorous levels of activity
Viviano et al (2021)	severe dementia (MMSE 7.8 ± 5.0)	severe dependency (Barthel Index 44.7 ± 27.5)	PAS-LTC ActiGraph 1) Activity counts 2) Calories of energy expended
Galik et al (2018)	severe dementia (MMSE 7.7 ± 5.1)	severe dependency (Barthel index 46.0 ± 27.6)	PAS-LTC
Resnick et al (2015)	severe dementia (MMSE 5.8 ± 4.9)	severe dependency (Barthel index 40.74 ± 29.54)	ActiGraph 1) Counts of physical activity 2) Time spent in light, moderate and heavy activity, 3) Calories of energy expended
Resnick et al (2007)	Severe dementia (MMSE 6.0 ± 6.9)	severe dependency (Barthel index 48.1 ± 23.9)	PAS-LTC ActiGraph 1) Activity counts 2) Calories of energy expended
Smit et al (2016)	Severe dementia (CPS 3.99 ± 1.5)	total dependency (Katz ADL 5.4 ± 1.7)	Activity Pursuit Patterns
Mirre den Ouden et al (2015)	Severe dementia (CPS 2.6 ± 1.9)	total dependency (Barthel Index 7.6 ± 5.8)	MELOD-Tool
MMSE: Mini-Mental State Examination; CPS: Cognitive Performance Scale; PAS-LTC: Physical Activities Scale for Long-Term Care

This study was conducted to identify the physical activity measurement methods used in domestic and international academic papers targeting dementia patients in long-term care facilities and to propose suitable physical activity measurement methods according to the status of the subjects. A total of 5,364 papers were reviewed through six domestic and international databases, and a literature review on the subject was conducted by analyzing the final 30 papers.

Studies on measuring physical activity targeting dementia patients in long-term care facilities both domestically and internationally showed an increasing trend after 2011, with 4 studies conducted until 2010, 22 between 2011 and 2020, and 4 from 2021 to 2023. This can be seen as a result of the advancement of information and smart technology, such as mobile devices after 2010, enabling an environment that can be closely linked to the body. It became possible to continuously identify biometric information such as physical activity and sleep using devices (Brickwood et al., 2019; BUTTE et al., 2012; Natarajan et al., 2020; Yang & Hsu, 2010), and interest in medical data analysis using this has increased (Cajita et al., 2020; Kim & Han, 2020).

Of the 30 selected articles, 12 were published in gerontology journals, while only 4 were in the nursing field, accounting for 13.3% of all selected articles. In particular, there were no relevant articles in Korean nursing journals. In Korea, a number of intervention studies have shown that increased physical activity has a positive impact on improving quality of life, including preventing cognitive decline and overcoming depression, anxiety, and fear of falling (Son, Bo-Young, Bang, Yosoon, Hwang, Min-Ji, Oh, Eun-Joo, & Bang, Ju-Hee, 2016; Choi, Yeon-Hee, & Lee, Chun-Ji, 2012). However, there is a lack of nursing research that objectively measures the degree of physical activity, explains how much physical activity is actually increased by the intervention, and how this increase leads to positive health outcomes. Therefore, research should be conducted to quantitatively measure physical activity through the validation of various physical activity measures and to demonstrate the effectiveness of nursing interventions in institutionalized older adults with dementia.

Regarding the research design, descriptive research (70.0%) was mainly used to identify the physical activity characteristics of older adults with dementia. Descriptive research is an effective research method for securing sufficient data on a phenomenon and understanding the phenomenon through it (Kim et al, 2017). In this study, we identified the characteristics of physical and cognitive functions of older adults with dementia and the physical activity measures collected for this purpose. However, another point of discussion regarding physical activity measures is whether the measures can sensitively identify small changes in physical activity according to the characteristics of older adults with dementia. Therefore, it can be said that descriptive studies have limitations to propose effective methods for measuring changes in physical activity according to functional status, rather than simply proposing methods for measuring physical activity according to functional status. Experimental studies should be conducted to determine whether changes in physical activity are effectively measured according to the characteristics of the research subjects. Therefore, it is necessary to conduct various experimental studies that present changes in physical activity according to the functional status of dementia patients in facilities before and after the intervention to propose a measurement method that effectively presents changes in physical activity.

This study focused on studies of older adults with dementia aged 60 and older. The final selected literature also included a number of studies with older adults with dementia aged 65 and older, but the average age of participants was mainly in the 80s, and many of the studies were conducted in older ages. Therefore, they did not include subjects with a wide range of physical and cognitive functions and focused on highly dependent subjects. However, this may reflect the situation in long-term care facilities, where residents with dementia are generally older and more dependent on physical and cognitive functions than community residents (Kim, 2011).

In this study, physical function was measured based on the ability to perform daily activities or expressed as equilibrium and muscle strength. In the case of cognitive function, specific scores were provided using assessment tools, but in some cases, specific cognitive status could not be identified because the medical records were categorized as having or not having a dementia diagnosis without assessment criteria (Jeon, Seungyeon, et al., 2018a). In particular, there are difficulties in determining the physical functioning of older adults with dementia in institutional settings because there are no criteria for interpreting the results, such as muscle strength and equilibrium ability. On the other hand, there are studies on scoring criteria for community-dwelling older adults (Ramírez-Vélez R et al., 2020; Welch, Ward, Beauchamp, Leveille, Travison, Bean, 2021), so it can be said that research on cut-off point criteria for long-term care facilities is needed.

The selected papers utilized direct measures of physical activity, such as accelerometers attached to participants' bodies, and indirect measures, such as caregiver observation or questionnaires. Accelerometers have been used in many studies, and 20 papers reported using accelerometers to measure physical activity. This can be attributed to previous research showing that accelerometer-based physical activity measurement can be effectively applied to people with dementia (Van alphen et al., 2016). The type of accelerometer used in the selected papers was Actigraph in 11 papers and MotionWatch 8 in 3 papers. The difference is that the actigraph is mainly worn around the waist, while the motion watch 8 is worn on the wrist to collect data. The MotionWatch 8 has the advantage of being easy to wear during daily activities and sleep, which can increase adherence (Landry et al., 2015; Littner et al., 2003), but wrist-worn devices are easier to remove (Olsen et al., 2016), and in one study, more than half of the participants did not meet the criteria for adequate wear time (Moyle et al., 2017). There are also issues with measuring physical activity based on wrist movements, which can overestimate physical activity intensity and underestimate physical activity associated with walking if the wrist is the primary source of physical activity (Kuzmik, A., et al., 2021, Viviano, N. A., et al., 2021). Actigraphs are mostly worn around the waist, which limits their ability to capture physical activity in wheelchair users and above the waist (Douma, et al., 2015, Viviano, N. A., et al., 2021, Leenders NYJM, et al., 2000). Using accelerometers to measure physical activity allows for detailed quantitative and semi-quantitative data analysis (Jansen et al, 2014), but can be inaccurate depending on the form of physical activity. In addition, the cut points on which measured activity is based have been developed primarily for younger adults (Strath, S. J., et al., 2012). Cut points for moderate and vigorous activity in older adults are unclear. Future research is therefore needed to define appropriate activity cut points for older adults with dementia.

Among indirect measurement methods, observational methods such as PAS-LTC and MEDLO-tool may not be sensitive to small changes because they cover the entire activity area (Galik et al., 2021), the nature of observation makes it impossible to observe when the subject is out of the observer's field of vision, such as when the bedroom or bathroom door is closed (De Boer et al., 2016), and they may include subjective views because a third party is involved as an evaluator (Galik et al., 2021). For questionnaires, we used the IPAQ-E and activity-seeking patterns for care providers and the Nursing Home Living Space Diameter and Physical Activity Assessment, InterRAI for residents. Questionnaires are subjective and rely on memory to answer questions, which can lead to issues such as recall bias or the desire to appear socially desirable (Resnick, B., et al., 2010), which can affect reliability. Before considering direct and indirect methods, it is necessary to determine the severity of dementia to determine whether self-response is possible, and it is necessary to select the appropriate method by considering the characteristics of the subject and the advantages and disadvantages of each method, such as identifying the type of activity in advance when selecting the type of accelerometer. It is also necessary to use a combination of different methods to compensate for the shortcomings of the measurement method.

The study found that physical activity measurement methods differed based on cognitive and physical function (ability to perform activities of daily living). For people with severe dementia and moderate dependence on activities of daily living, physical function was measured using accelerometers (Resnick et al, 2019). Similarly, for people with moderate dementia and high dependence on activities of daily living, direct measurement using accelerometers was used (Barber et al, 2015). However, studies of full dependence collected accelerometer readings. In general, studies utilizing accelerometers are based on readings taken while the subject is in motion, which differs from the measurement of physical activity time, which is considered physical activity if it is above a certain threshold (Resnick et al, 2022; Jansen et al, 2014). This difference stems from the fact that the subject is in complete dependence, unable to move independently. Given the lack of movement in institutionalized dementia patients, it is more appropriate to observe the number of times accelerometer readings are triggered by movement than to measure time spent in physical activity. On the other hand, for severe dementia and complete dependence, indirect measures using questionnaires completed by caregivers were used (Smit et al, 2016; Den Ouden et al, 2015). This suggests that when physical functioning is the same as complete dependence, the methodology varies depending on the degree of cognitive functioning. For moderate dementia, it is measured directly using an accelerometer, and for severe dementia, it is measured indirectly using a questionnaire. The questionnaire is called Activity Pursuit Pattern and asks participants to write down the approximate amount of time they have been awake in the last seven days or how much of the day (1/3, 2/3, etc.) they engage in activities of daily living. The questionnaire is also unstructured and asks participants to indicate whether they engage in activities of daily living for more than one minute per day. The difference between direct and indirect measures is that cognitive function is also influenced by physical activity levels (Rockwood & Middleton, 2007), so we might expect that people with severe dementia with the same "total dependence" level would have had a worse physical function. Indeed, subjects with moderate dementia and full dependence on physical activity had a Barthel index of 14 ± 5.4, and those with severe dementia and full dependence on physical activity had a Barthel index of 7.6 ± 5.8, indicating greater dependence on activities of daily living. Therefore, when measuring physical activity in institutionalized dementia, it is necessary to select a measurement method that considers both functions together rather than simply considering only one aspect of cognitive function or physical function. Therefore, in future studies on physical activity in institutionalized dementia, it is necessary to identify the most appropriate physical activity measurement method through a preliminary study on the effectiveness of the physical activity measurement method before conducting the study.

This study was conducted to analyze studies on the concepts and measurement methods of physical activity of older adults with dementia living in facilities using a scoping review to identify the characteristics of the studies and to suggest future research directions by analyzing physical activity measurement methods. Since 2010, with the development of smart devices, physical activity measurement methods using accelerometers have been rapidly increasing, and other studies have been conducted using indirect measurement methods using questionnaires and observation tools. As a result of identifying physical activity measurement methods according to physical function and cognitive function, we used accelerometers for moderate dementia and total daily dependence, severe dementia, and moderate physical dependence, and indirect measurement using questionnaires for severe dementia and total daily dependence. Due to the small number of studies included in this study, it is difficult to generalize the results. In future studies, it is necessary to provide accurate information on the physical and cognitive functions of the subjects to provide specific guidelines for measuring physical activity for each condition. In addition, in intervention studies that confirm the effectiveness of physical activity, it is necessary to objectively measure the degree of physical activity so that changes in physical functioning due to physical activity can be presented according to functional status. Therefore, it is necessary to present a measurement method that can effectively measure functional changes according to the functional status of research subjects so that the effectiveness of nursing interventions can be presented objectively.

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The authors of this manuscript have no conflicts of interest to disclose as described by BMC Geriatrics.

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Authors’ contributions

YL designed study methodology including the data extraction template. Full text review completed by YL, with assistance from CM, MK, YK. Data extraction was completed by YL, CM, MK, YK. Manuscript write up including data analysis and preparation of tables and figures was completed by YL with major contribution from CM, MK, YK. All authors collaborated closely, utilizing their respective expertise and knowledge throughout the research process, and reviewed the manuscript. All authors read and approved the final manuscript.

Acknowledgements

There are no personal acknowledgments to report.

Kim YM. (2011). A Comparative study on the Activities of Daily Living, Cognitive Function and Depression between the Elderly residing Institution and Home [Doctoral dissertation, Hanyang University].
Kim HY, Kang H. Research Trends in Intervention Studies for Frail Elderly Audlts in Korea: A Scoping Reivew. Korean J Adult Nurs. 2022;34(3):233–48. https://doi.org/10.7475/kjan.2022.34.3.233.
Nam HR, Heo HS. Effects of Subjective Memory Complaints, Depression and Activities of Daily Living on the Health-related Quality of Life in the Elder. Nurs Health Issues (NHI). 2020;25(1):10–8.
Ministry of Health and Welfare. (2022). 2019 Long-Term Care Survey Research Report. http://www.mohw.go.kr/react/jb/sjb030301vw.jsp?PAR_MENU_ID=03&MENU_ID=032901&CONT_SEQ=354919.
Sunwoo D, Kang EN, Hwang JH, Lee YK, Kim HS, Choi ID, Han EJ, Nam HJ, Seo DM, Lee SH. Performance Evaluation and Improvement on Long-Term Care Insurance. Korea Institute for Health and Social Affairs; 2016.
Son BY, Bang YS, Hwang MJ, Oh EJ, Bang JH. The Effects of Physical Functions and Depression on Quality of Life According to Fall Prevention Exercise - Applying Otago Exercise Program with Musi. J Korea Entertainment Industy Association. 2016;10(2):113–25.
Shin HY. A Preliminary Study on Korean Version of the Quality of Life-Alzheimer's Disease (QOL-AD) in Community-Dwelling Elderly with Dementia. J Prev Med Public Health. 2006;39(3):243–8.
Jeon SY, Kim HS. Current Status and Factors Related to Physical Activity of Older Nursing Home Residents with and without Dementia: Effects of Individual and Institutional Characteristics. Health Policy and Management. 2018a;28(4):392–401.
Jeon SY, Kim HS. (2018b). Current Status and Factors Related to Physical Activity of Older Nursing Home Residents with and without dementia: Implication for Smart and Person Centered Intervention. Korea Gerontological Society. 2018, 193–194.
Korea Disease Control Agency. (2023). National Injury Fact Book 2023. https://www.kdca.go.kr/contents.es?mid=a20601030600.
Choi EH, Lee CJ. ë ˆEffects of a Recreational Combination Gymnastics Program for Old-old Women. J Korean Acad Nurs. 2012;42(6):843–52.
Arksey H, O'Malley L. Scoping Studies: Towards a Methodological Framework. Int J Social Res Methodology: Theory Pract. 2005;8(1):19–32. https://doi.org/10.1080/1364557032000119616.
Arrieta H, Rezola-Pardo C, Echeverria I, Iturburu M, Gil SM, Yanguas JJ, Irazusta J, Rodriguez-Larrad A. Physical activity and fitness are associated with verbal memory, quality of life and depression among nursing home residents: preliminary data of a randomized controlled trial. BMC Geriatr. 2018;18(1):80. https://doi.org/10.1186/s12877-018-0770-y.
Auerswald T, Meyer J, von Holdt K, Voelcker-Rehage C. Application of Activity Trackers among Nursing Home Residents-A Pilot and Feasibility Study on Physical Activity Behavior, Usage Behavior, Acceptance, Usability and Motivational Impact. Int J Environ Res Public Health. 2020;17(18):6683. https://doi.org/10.3390/ijerph17186683.
Barber SE, Forster A, Birch KM. Levels and patterns of daily physical activity and sedentary behavior measured objectively in older care home residents in the United Kingdom. J Aging Phys Act. 2015;23(1):133–43. https://doi.org/10.1123/JAPA.2013-0091.
Brickwood K-J, Watson G, O'Brien J, Williams AD. Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis [Review]. JMIR Mhealth Uhealth. 2019;7(4):e11819. https://doi.org/10.2196/11819.
Cajita MI, Kline CE, Burke LE, Bigini EG, Imes CC. Feasible but Not Yet Efficacious: a Scoping Review of Wearable Activity Monitors in Interventions Targeting Physical Activity, Sedentary Behavior, and Sleep. Curr Epidemiol Rep. 2020;7(1):25–38. https://doi.org/10.1007/s40471-020-00229-2.
Chen YM, Li YP. (2014). Motivators for physical activity among ambulatory nursing home older residents. The Scientific World Journal, 2014. https://doi.org/10.1155/2014/329397.
De Boer B, Beerens HC, Zwakhalen SM, Tan FE, Hamers JP, Verbeek H. Daily lives of residents with dementia in nursing homes: development of the Maastricht electronic daily life observation tool. Int Psychogeriatr. 2016;28(8):1333–43. https://doi.org/10.1017/S1041610216000478.
Den Ouden M, Bleijlevens MH, Meijers JM, Zwakhalen SM, Braun SM, Tan FE, Hamers JP. Daily (in) activities of nursing home residents in their wards: an observation study. J Am Med Dir Assoc. 2015;16(11):963–8. https://doi.org/10.1016/j.jamda.2015.05.016.
Douma JG, Volkers KM, Vuijk JP, Sonneveld MH, Goossens RH, Scherder EJ. The effects of observation of walking in a living room environment, on physical, cognitive, and quality of life related outcomes in older adults with dementia: a study protocol of a randomized controlled trial. BMC Geriatr. 2015;15(1):1–12. https://doi.org/10.1186/s12877-015-0024-1.
Farina N, Hughes LJ, Watts A, Lowry RG. Use of Physical Activity Questionnaires in People With Dementia: A Scoping Review. J Aging Phys Act. 2019;27(3):413–21. https://doi.org/10.1123/japa.2018-0031.
Galik EM, Resnick B, Holmes SD, Vigne E, Lynch K, Ellis J, …, Barr E. A cluster randomized controlled trial testing the impact of function and behavior focused care for nursing home residents with dementia. J Am Med Dir Assoc. 2021;22(7):1421–8. https://doi.org/10.1016/j.jamda.2020.12.020.
Gill DL, Hammond CC, Reifsteck EJ, Jehu CM, Williams RA, Adams MM, Lange EH, Becofsky K, Rodriguez E, Shang YT. Physical activity and quality of life. J Prev Med Public Health. 2013;46(Suppl 1):28. https://doi.org/10.3961/jpmph.2013.46.S.S28.
Holmes SD, Galik E, Resnick B. Factors that influence physical activity among residents in assisted living. J Gerontol Soc Work. 2017;60(2):120–37. https://doi.org/10.1080/01634372.2016.1269035.
Jansen CP, Claßen K, Hauer K, Diegelmann M, Wahl HW. Assessing the effect of a physical activity intervention in a nursing home ecology: a natural lab approach. BMC Geriatr. 2014;14:1–12. https://doi.org/10.1186/1471-2318-14-117.
Jung HW, Roh HC, Kim SW, Kim S, Kim M, Won CW. Cross-comparisons of gait speeds by automatic sensors and a stopwatch to provide converting formula between measuring modalities. Annals of Geriatric Medicine and Research. 2019;23(2):71. https://doi.org/10.4235/agmr.19.0016.
Kim H, Sefcik JS, Bradway C. Characteristics of Qualitative Descriptive Studies: A Systematic Review. Res Nurs Health. 2017;40(1):23–42. https://doi.org/10.1002/nur.21768.
Kim K-B, Han K-H. A Study of the Digital Healthcare Industry in the Fourth Industrial Revolution. J Convergence Inform Technol. 2020;10(3):7–15. https://doi.org/10.22156/CS4SMB.2020.10.03.007.
Kolanowski A, Buettner L, Litaker M, Yu F. Factors that relate to activity engagement in nursing home residents. Am J Alzheimer's Disease Other Dementias®. 2006;21(1):15–22. https://doi.org/10.1177/153331750602100109.
Kuzmik A, Resnick B, Cacchione P, Arendacs R, Boltz M. Physical activity in hospitalized persons with dementia: feasibility and validity of the MotionWatch 8. J Aging Phys Act. 2021;29(5):852–7. https://doi.org/10.1123/japa.2020-0275.
Landry GJ, Best JR, Liu-Ambrose T. Measuring sleep quality in older adults: a comparison using subjective and objective methods. Front Aging Neurosci. 2015;7:166. https://doi.org/10.3389/fnagi.2015.00166.
Leenders NY, Sherman WM, Nagaraja HN. Comparisons of four methods of estimating physical activity in adult women. Med Sci Sports Exerc. 2000;32(7):1320–6. https://doi.org/10.1097/00005768-200007000-00021.
Littner M, Kushida CA, Anderson WM, Bailey D, Berry RB, Davila DG, Hirschkowitz M, Kapen S, Kramer M, Loube D, Wise M, Johnson SF. Practice parameters for the role of actigraphy in the study of sleep and circadian rhythms: An update for 2002. Sleep: J Sleep Sleep Disorders Res. 2003;26(3):337–41. https://doi.org/10.1093/sleep/26.3.337.
MacRae PG, Schnelle JF, Simmons SF, Ouslander JG. Physical activity levels of ambulatory nursing home residents. J Aging Phys Act. 1996;4(3):264–78. https://doi.org/10.1123/japa.4.3.264.
Moyle W, Jones C, Murfield J, Draper B, Beattie E, Shum D, Thalib L, O’Dwyer S, Mervin CM. Levels of physical activity and sleep patterns among older people with dementia living in long-term care facilities: A 24-h snapshot. Maturitas. 2017;102:62–8. https://doi.org/10.1016/j.maturitas.2017.05.015.
Öhlin J, Toots A, Almevall AD, Littbrand H, Conradsson M, Hörnsten C, Werneke U, Niklasson J, Olofsson B, Gustafson Y. Concurrent validity of the International Physical Activity Questionnaire adapted for adults aged ≥ 80 years (IPAQ-E 80+)-tested with accelerometer data from the SilverMONICA study. Gait Posture. 2022;92:135–43. https://doi.org/10.1016/j.gaitpost.2021.11.019.
Olsen C, Pedersen I, Bergland A, Enders-Slegers MJ, Jøranson N, Calogiuri G, Ihlebæk C. Differences in quality of life in home-dwelling persons and nursing home residents with dementia–a cross-sectional study. BMC Geriatr. 2016;16(1):1–11. https://doi.org/10.1186/s12877-016-0312-4.
Peters M, Godfrey C, McInerney P, Soares CB, Khalil H, Parker D. (2015). Methodology for JBI scoping reviews. The Joanna Briggs Institute Reviewers manual 2015 (3–24). Joanna Briggs Institute.
Ramírez-Vélez R, Pérez-Sousa MA, Venegas-Sanabria LC, Cano-Gutierrez CA, Hernández-Quiñonez PA, Rincón-Pabón D, García-Hermoso A, Zambom-Ferraresi F, de Sáez ML, Izquierdo M. Normative Values for the Short Physical Performance Battery (SPPB) and Their Association With Anthropometric Variables in Older Colombian Adults. The SABE Study, 2015. Front Med. 2020;7:52. https://doi.org/10.3389/fmed.2020.00052.
Resnick B, Galik E. Using function-focused care to increase physical activity among older adults. Annu Rev Nurs Res. 2013;31(1):175–208. https://doi.org/10.1891/0739-6686.31.175.
Resnick B, Boltz M, Galik E, Zhu S. The Impact of Cognitive impairment on Clinical Symptoms, Physical Activity and Care Interactions among Residents in Assisted Living Settings. Clin Nurs Res. 2022;31(2):310–9. https://doi.org/10.1177/10547738211040628.
Resnick B, Galik E, Boltz M, Vigne E, Holmes S, Fix S, Zhu S. The impact of physical activity and function on falls in assisted living residents. J Aging Phys Act. 2019;27(6):816–22. https://doi.org/10.1123/japa.2018-0291.
Resnick B, Galik E, Gruber-Baldini AL, Zimmerman S. Satisfaction with assisted living: The unexplored role of physical activity. Geriatr Nurs. 2010;31(3):197–205. https://doi.org/10.1016/j.gerinurse.2010.04.010.
Ruuskanen JM, Parkatti T. Physical activity and related factors among nursing home residents. J Am Geriatr Soc. 1994;42(9):987–91. https://doi.org/10.1111/j.1532-5415.1994.tb06593.x.
Schmid A, Weiss M, Heseker H. Recording the nutrient intake of nursing home residents by food weighing method and measuring the physical activity. J Nutr Health Aging. 2003;7(5):294–5.
Sherrington C, Michaleff ZA, Fairhall N, Paul SS, Tiedemann A, Whitney J, Cumming RG, Herbert RD, Close JCT, Lord SR. Exercise to prevent falls in older adults: an updated systematic review and meta-analysis. Br J Sports Med. 2017;51(24):1750–8. https://doi.org/10.1136/bjsports-2016-096547.
Smit D, De Lange J, Willemse B, Twisk J, Pot AM. Activity involvement and quality of life of people at different stages of dementia in long term care facilities. Aging Ment Health. 2016;20(1):100–9. https://doi.org/10.1080/13607863.2015.1049116.
Strath SJ, Pfeiffer KA, Whitt-Glover MC. Accelerometer use with children, older adults, and adults with functional limitations. Med Sci Sports Exerc. 2012;44(1S):77–S85. https://doi.org/10.1249/MSS.0b013e3182399eb1.
Taekema DG, Gussekloo J, Maier AB, Westendorp RG, de Craen AJ. Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing. 2010;39(3):331–7. https://doi.org/10.1093/ageing/afq022.
Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, Hempel S, Aki EA, Chang C, McGowan J, Stewart L, Hartling L, Aldcroft A, Wilson MG, Garritty C, Lewin S, Godfrey CM, Macdonald MT, Langlois EV, …, Straus SE. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169(7):467–73. https://doi.org/10.7326/M18-0850.
Van Alphen HJ, Volkers KM, Blankevoort CG, Scherder EJ, Hortobágyi T, van Heuvelen MJ. Older adults with dementia are sedentary for most of the day. PLoS ONE. 2016;11(3):e0152457. https://doi.org/10.1371/journal.pone.0152457.
Viviano NA, Galik E, Resnick B. Racial differences in physical activity in nursing home residents with cognitive impairment. Appl Nurs Res. 2021;60:151445. https://doi.org/10.1016/j.apnr.2021.151445.
Welch SA, Ward RE, Beauchamp MK, Leveille SG, Travison T, Bean JF. The short physical performance battery (SPPB): a quick and useful tool for fall risk stratification among older primary care patients. J Am Med Dir Assoc. 2021;22(8):1646–51. https://doi.org/10.1016/j.jamda.2020.09.038.
World Health Organization, T. Global recommendations on physical activity for health. World Health Organization; 2010. http://www.who.int/iris/bitstream/10665/44399/1/9789241599979_eng.
World Health Organization, T. (2010). Global recommendations on physical activity for health. World Health Organization. http://www.who.int/iris/bitstream/10665/44399/1/9789241599979_eng

No competing interests reported.

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Physical Activity Measurement in Older Adults with Dementia in Long-term Care Facilities: A Scoping Review

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