Physical Activity in People With Dementia Living in Long-Term Care Facilities and the Connection With Environmental Factors and Behavior

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Suzanne Portegijs Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands

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Sandra van Beek Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands

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Lilian H.D. van Tuyl Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands

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Cordula Wagner Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands
Department of Public and Occupational Health, Amsterdam Public Health Research Institute (APH), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

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This study is conducted in order to gain a better understanding of the relationship between physical activity and agitated behavior among older people with dementia, and physical activity and characteristics of long-term care wards. Data were collected among people with dementia living in long-term care facilities (N = 76) by conducting observations at the wards and distributing questionnaires among professional caregivers. The results show that participants are largely inactive (82.8%) and a significant relation was found between the degree of physical activity and characteristics of the ward such as “taking sufficient time,” which relates to the time caregivers take when interacting with residents. This study supports the existing knowledge about the degree of physical activity among people with dementia in long-term care and adds information about the potential influence of organizational factors that could be valuable for daily practice.

Physical activity can positively affect numerous health outcomes of people with dementia, including cognitive functioning, independency in activities of daily living (ADL), and physical performance (Blankevoort et al., 2010; Groot et al., 2016). Research specifically focused on people with dementia in long-term care facilities shows additional valuable effects such as increased mobility and functional ability and lower risk of depression and agitation (Brett et al., 2016). Despite the benefits of physical activity, nursing home residents and especially people with dementia are mostly inactive (den Ouden et al., 2015; Marmeleira et al., 2017; Moyle et al., 2017; Parry et al., 2019; van Alphen, Volkers, et al., 2016). Furthermore, the relatively low number of activities undertaken are mostly of low intensity and limited to ADL, such as mobility, eating, and drinking (den Ouden et al., 2015; Marmeleira et al., 2017; Moyle et al., 2017; Parry et al., 2019; van Alphen, Volkers, et al., 2016).

As physical activity decreases agitated behavior, it could potentially contribute to enhancing residents’ psychological well-being and quality of life (Beerens et al., 2013; Brett et al., 2016; Jing et al., 2016; Scherder et al., 2010; Staedtler & Nunez, 2015). Yet, agitated behavior in people with dementia is complex and is also associated with less beneficial forms of physical activity such as compulsive walking (Robinson et al., 2007). Compulsive walking in itself enhances the degree of physical activity, but is also connected to multiple negative health outcomes including malnutrition, sleep disturbance, and injuries from fall incidents (Cipriani et al., 2014).

In addition to several personal features described above, various other factors influence the degree of physical activity of residents with dementia in long-term care facilities. For instance, the environment’s compatibility with the abilities of a resident including the accessibility, security, comfort, and aesthetics (Douma et al., 2017). In addition, external factors are also vital, mostly related to caregivers and include staffing levels, available time, the amount and type of care being provided, and difficulties with guiding and organizing physical activity (Douma et al., 2017; van Alphen, Hortobagyi, et al., 2016).

As the environment is an important factor regarding the degree of physical activity, the organization of institutionalized care is important. In the Netherlands various forms of long-term living for people with dementia exist, which can roughly be categorized as large-scale and small-scale facilities. Research shows that the physical environment of small-scale living facilities are generally more beneficial for people with dementia, especially with regard to independency in ADL activities and general well-being, in comparison with traditional large-scale nursing homes (de Boer et al., 2018; Marquardt et al., 2014). In addition, providing a “home-like environment” has a positive effect on numerous outcomes, especially on behavior (Marquardt et al., 2014). Despite the already established positive effects of small-scale facilities, the influence of different types of facilities on the degree of physical activity remains unclear.

In summary, a relatively large number of studies has been conducted on the degree of physical activity of people with dementia (den Ouden et al., 2015; Marmeleira et al., 2017; Moyle et al., 2017; Parry et al., 2019; van Alphen, Volkers, et al., 2016). However, research on the connection between various environmental factors and agitated behavior on physical activity is lacking and is needed to further understand the complexity of physical activity within long-term dementia care. Therefore, the aim of this study is to gain insight into the relations between the degree of physical activity, agitated behavior, and living environment among people with dementia living in long-term care facilities. In addition, this study includes qualitative descriptions of the included wards to provide more information and context on the participating wards.

Methods

Study Design

This study is conducted in light of a larger research project in collaboration with a care organization in the Netherlands that wants to improve the living conditions of people with dementia by providing more freedom and autonomy and enabling social interaction with the surrounding neighborhood. A part of this research project is this mixed-methods study, using observations for both physical activity and ambiance on the wards conducted by researchers, and questionnaires completed by nursing staff. The study was conducted between June 2018 and September 2019 within five long-term care facilities in two different regions in the Netherlands.

Participants

The participants included within this study were recruited from the care organization involved in the larger research project and the residents of two other long-term care facilities. The managers of both facilities were contacted by the researchers and invited to participate. The study was conducted solely at the wards specifically for people with dementia. Information letters and informed consent forms for participation within this study were sent by mail to the first legal representatives of all residents of the included wards by the care organizations. If the first legal representative agreed on participation, the informed consent forms were signed and sent back to the researchers. All nursing home residents with dementia of whom the informal caregivers gave consent for participation were eligible for inclusion.

Setting

This study included five long-term care facilities from two different care organizations in different regions of the Netherlands. Detailed descriptions of the location are attached in Supplementary Material S2 (available online). Locations were visited one at a time for approximately 1 week or multiple days within a short period of time. Location 1 was visited during June and July 2018, Location 2 at the beginning of September 2018, Location 3 at the end of September 2018 and Locations 4 and 5 during the middle of September in 2019. During data collection, a maximum of three researchers were present on the locations each day.

Measures

Physical Activity

Observations as method for quantifying physical activity were chosen, as this is a reliable, unobtrusive method that has previously been used within long-term care research (de Boer et al., 2016; den Ouden et al., 2015), with little impact on the daily routine of residents (Lam et al., 2018), in particular when compared with sensor technology. Moreover, observations are not susceptible to social desirability, recall bias, or poor response rates associated with self-reported measures (Lim et al., 2018; Westerterp, 2009).

Observations of physical activity were conducted by researchers visiting the wards. Observations were carried out for a maximum of 30 min each and were conducted within three different timeframes: morning/breakfast (08:00–11:00), midday/lunch (11:00–14:30), and afternoon/dinner (14:30–19:00). Some observations took longer or shorter due to daily circumstances on the ward. Different specific time slots were chosen in order to gain a more accurate overview of the physical activity during different parts of the day. Furthermore, every time slot includes a meal that often stimulates physical activity and other aspects of long-term care such as care routine (morning/after lunch/evening) and leisure activities (late morning/early afternoon). Researchers aimed to observe all participating residents at least once during every time frame. Observations were carried out on different days within the same week, excluding weekends as daily care is organized differently during the weekends due to the larger presence of family members and less available professional caregivers, which would result in more heterogeneity during data collection. Observers scored the degree of physical activity per minute using four different categories: (a) lying, (b) sitting, (c) standing, and (d) walking. During the time that a resident moved out of sight either independently or assisted by professional caregivers the minutes were scored as “nonobservable.” As not all residents were sufficiently present in the shared rooms of the wards, a total of 57 residents were observed for physical activity. Furthermore, 27 observations were conducted simultaneously by two observers to establish the interobserver reliability. When checking for interobserver reliability few differences were found, with a match in activities over 91%. Small differences in interobserver reliability were found when a resident changed their form of (in)activity during the start of a new minute of observation. For example, when a resident changed from sitting to standing around the start of the sixth minute of observation, both observers registered this differently.

Questionnaire for Nursing Staff

Nursing staff were asked to complete a questionnaire about all participating residents with questions about age, gender, functioning in ADL, cognitive functioning, and psychological well-being (specifically agitated behavior). The questionnaires were placed in the nurses’ office with a return box. An email with information and instructions was sent by the manager to the nursing staff of the ward, all of whom were eligible for participation within this research. Under Dutch legislation (Medical Research Involving Human Subjects Act), ethical approval by a medical ethics committee was not required since the research subjects were not subjected to actions and no rules of behavior were imposed on them (https://english.ccmo.nl). Participant consent was assumed upon return of a completed questionnaire. The questionnaire data were stored and analyzed anonymously, in accordance with the General Data Protection Regulation. Nursing staff were asked to fill in the questionnaires in pairs to ensure an accurate reflection of daily reality.

ADL-H

ADL functioning was scored with the Activity of Daily Living Hierarchy (ADL-H) index of the Minimum Data Set (MDS) Short Form (Gerritsen et al., 2004; Morris et al., 1999). The interrater agreement of the ADL-H is 0.80 with an internal consistency of 0.84 (Gerritsen et al., 2004). The ADL-H consists of four items: mobility on ward, eating and drinking, toilet use, and personal hygiene, which can be scored from 0 (independent) to 4 (totally dependent) or 8 (activity did not occur during the last 7 days). The final score can be a final classification ranging from 0 (independent) to 6 (totally dependent on others) or a summation of the scores of the four items. Both outcomes were used within this study.

CPS

Cognitive functioning was assessed by using the Cognitive Performance Scale (CPS; Morris et al., 1994). The interrater agreement of the CPS is 0.85 (Morris et al., 1994), with an internal consistency of 0.74 (Gerritsen et al., 2004). The CPS consists of five items: comatose state (yes/no), long- and short-term memory (good and impaired), cognitive abilities for daily decision making, and making oneself understood (4-point Likert scale). The final classification ranges from 0 (intact) to 6 (very severe impairment).

CMAI-D

Agitated behavior was measured using the Cohen-Mansfield Agitation Inventory—Dutch version (CMAI-D; Cohen-Mansfield et al., 1989). The observation scale consists of 29 items with scores ranging from 1 (never) to 7 (several times an hour) and results in an overall score and subscores for aggressive behavior, physically nonaggressive behavior, and verbally agitated behavior. The interobserver reliability of the CMAI-D is 0.91 (Cohen-Mansfield et al., 1989). Within this study, only the scales for nonaggressive and aggressive behavior were used, since these types of behavior are most likely to influence the degree of activity. The Cronbach’s alpha in this study of nonaggressive behavior was .82 and for aggressive behavior was .79.

Walking Aid and Wheelchair Use

As the use of walking aids and wheelchairs gives an indication of a person’s physical functioning and influences the degree of physical activity, both aspects were inventoried within the questionnaire for nursing staff. The use of walking aids and wheelchairs was scored on a 5-point likert scale from never to always. Walking aids include walking sticks, crutches, and walkers. Wheelchairs include self-driven, manually pushed, and electric wheelchairs.

Ward Observations

The observations on the wards were conducted using an observation list with 32 items which focused on safety of residents, physical activity, and ambiance on the ward (see Supplementary Material S1 [available online]). The observation list was derived from a list that was based on the aspects of quality of care defined by Rantz et al. (1998; Beek, 2013; Rantz et al., 1998). Eight items were used within this study: (2) “taking sufficient time,” (5) “calling residents by name,” (6) “visibly present,” (7) “active caring,” (16) “independent walking,” (17) “guided walking,” (30) “having a home-like environment,” and (31) “lively ward.” Other items of the observation list focused on, for example, the interaction between caregivers, personalization of residents’ rooms, and the presence of unpleasant smells. Each item was scored on a 5-point scale, with five representing the most positive score. The observations were conducted during three different time periods: morning, midday, and afternoon, spread out over different days in order to gain a more accurate overview of the ward at different points in time. The ward observations were performed separately from the physical activity observations. All the wards were observed by two researchers simultaneously. The participating wards and nursing staff were informed about the presence of the researchers, but received limited information about the focus and aim of the research. However, in order to recruit the wards some information provision was necessary. Therefore, the researchers shared that the study was part of a larger research project on quality of care, physical activity, and change management within long-term care. The researchers tried to minimize their interaction and interference with the residents and staff members, though this could not be totally avoided due to communication initiatives by residents and staff members and incidental safety concerns. Findings were discussed afterward. In total, nine researchers conducted the observations on the five units included within this study. Always accompanied by one of the two main researchers of the study. The nursing teams were not aware when the observations would take place. A score for each item was computed based on the average score of the two researchers over all three observation moments. In total, 42 observations were conducted simultaneously by two researchers. Interobserver reliability varied between 0.64 and 0.91 and was calculated using a linear mixed-effects model, with a mean of 0.77. Cronbach’s alpha for the combined items is .75.

Descriptions of the Included Wards

Of all the included locations, detailed descriptions were made by the researchers based on their experience and clinical expertise (see Supplementary Material S2 [available online]). In Table 1, the most important aspects of the locations are highlighted.

Table 1

Descriptions of the Locations Included

Location 1Location 2Location 3Location 4Location 5
SettingPsychogeriatric ward of a nursing homeSmall-scale department, part of residential care settingSmall-scale facilityLarge-scale department, part of large nursing homeSmall-scale facility
Number of residents2835284024
Sufficient room to moveVery spaciousModerate spaceModerate spaceVery spaciousLimited space
Outdoor areaTwo fenced gardensBalconySmall garden (patio)Unsafe balconySmall balcony
Type of environmentDated temporary building with home-like objectsHome-like environmentHome-like environmentClinical environmentHome-like environment

Data Analyses

All quantitative analyses were conducted using STATA (version 15). Descriptive analyses were performed for all five wards together as well as independently. Percentages were calculated for gender, CPS, ADL-H, and wheelchair and walking aid use. Mean scores were calculated for age and quantitative ward observations. Median scores were calculated for CMAI-D. The percentages of inactivity (lying and sitting) and activity (standing, walking, and other activities) were calculated using the total amount of minutes observed by the researchers and the minutes spent inactive, and active, by the residents. Percentages for the type of physical activity were calculated for the entire day, and the three time frames separately. Furthermore, overall inactivity and activity percentages were calculated for the five locations separately. Overall correlations were calculated for physical inactivity (as activity was rarely observed among residents), CMAI-D scores for aggressive and physically nonaggressive behavior, ADL short form scores, total score for ward observations, and CPS using Spearman’s rank order correlation coefficient when the variable showed no linear correlation or when categorical variables were analyzed, and Pearson’s correlation coefficient when the variable did show a linear correlation. Alpha for these analyses was set on .05. Specific correlations between settings could not be calculated due to the small sample size.

Ethical Considerations

The medical research ethics committee of UMC Utrecht approved the study protocol. The privacy of the residents within this study was respected by only observing while the resident stayed in one of the living rooms or the outside area. Residents were not followed into private areas such as their personal rooms and/or bathrooms.

Results

A total of 145 residents from five long-term care facilities were invited for participation within this study. Informed consent was received from the informal caregivers of 83 residents (57.2%). Of these residents, eight eventually did not participate in the study: five residents died before the start of the study and the observation lists of three residents were not received back from nursing staff resulting in incomplete data. However, one of these participants was included in the physical activity observations and the subsequent analyses. This resulted in a total of 76 residents being included in this study (52.4%), see Table 2 for the number of participating residents in each facility.

Table 2

Characteristics of the Research Population Per Included Ward

Location 1 (N = 14)Location 2 (N = 20)Location 3 (N = 14)Location 4 (N = 21)Location 5 (N = 6)
Age (mean, SD)84.7 (7.0)84.2 (5.0)83.9 (5.6)79 (20.3)79.8 (9.5)
Gender female (%)64.37071.45750
CPS (%)a
 (Borderline) intact2 (16.7)2 (10.5)0 (0)6 (33.3)1 (20)
 Mild–moderate severe impairment4 (33.3)9 (47.4)7 (53.9)4 (22.2)2 (40)
 (Very)severe impairment6 (50.0)8 (42.1)6 (46.2)8 (44.4)2 (40)
ADL short formb7.1 (5.2)7.4 (5.6)6.3 (3.7)7.5 (5.3)8.6 (5.9)
Walking aid use (%)c7 (53.9)9 (50.0)6 (46.2)7 (43.8)4 (66.7)
Wheelchair use (%)d8 (57.1)11 (55.6)7 (50)7 (53.3)0 (0)

Note. ADL = activities of daily living; CPS = Cognitive Performance Scale.

aCombining categories 0 and 1; 2, 3, and 4; and 5 and 6. bSummation of scores of all four items of the ADL short form, ranging from 0 to 16. cStick, scroller, or crutch defined as “sometimes,” “often,” and “always.” dSelf-driven, electric, or manually pushed defined as “sometimes,” “often,” and “always.”

Characteristics of Residents

Demographic characteristics of the nursing home residents are presented in Table 3. The mean age of the residents is 82.4 (SD = 12.0) years, 48 residents (64%) were women. Most residents have a higher CPS score; 30 residents (44.8%) are classified as “severely impaired” or “very severely impaired.” A fairly large group of 26 residents (38.8%) is classified as “mild impairment” to “moderate-severe impairment.” The smallest group classifies as having a “(borderline) intact” cognition. Hierarchy and general ADL-scores are calculated. Mean score is 7.2 (SD = 5.0). A third of the residents were classified as “Extensive 1” (36.6%), 32.4% as “Independent,” “Supervision,” or “Limited” and 31% as “Extensive 2,” “Dependent,” and “Total Dependence.” A large number of residents use a walking aid (43.4%) or a wheelchair (44%) in their daily life, at least sometimes, and at most always.

Table 3

Characteristics of the Research Population

Research population (N = 76)
Age (N = 75) (mean, SD)82.4 (12.0)
Gender female (N = 75) (%)48 (64)
CPS (N = 67) (%)a
 (Borderline) intact11 (16.4)
 Mild–moderate severe impairment26 (38.8)
 (Very)severe impairment30 (44.8)
ADL short form (N = 66) (mean, SD)b7.2 (5.0)
ADL self-performance hierarchy (N = 71) (%)c
 Independent5 (7.0)
 Supervision9 (12.7)
 Limited9 (12.7)
 Extensive 126 (36.6)
 Extensive 26 (8.5)
 Dependent12 (16.9)
 Total dependence4 (5.6)
Walking aid use (N = 70) (%)d33 (43.4)
Wheelchair use (N = 67) (%)e33 (44.0)

Note. ADL = activities of daily living; CPS = Cognitive Performance Scale.

aCombining categories 0 and 1; 2, 3, and 4; and 5 and 6. bSummation of scores of all four items of the ADL Short Form, ranging from 0 to 16. cIndex scores of the ADL Self-performance hierarchy index. dStick, scroller, or crutch defined as “sometimes,” “often,” and “always.” eSelf-driven, electric, or manually pushed defined as “sometimes,” “often,” and “always.”

When comparing the demographic characteristics of the nursing home residents independently, small differences appear (see Table 2). The mean age of the residents at Location 4 is lower (79 years) and there is a relatively larger variety regarding the ages of the residents (SD = 20.3). CPS scores somewhat vary across the different locations with a relatively larger group of residents with a “(borderline) intact” cognition at Location 4. However, when comparing the amount of residents with a “(very) severe impairment” hardly any differences occur. Small differences can be found within the ADL-scores of the location, with Location 5 having the highest score (8.6, SD = 5.9) and Location 3 the lowest (6.3, SD = 3.7).

Degree of Physical Activity

Table 4 presents the percentages of the observed activity of the residents included. In total, 57 of all residents were observed. The results are based on all observations conducted at the five different wards. Residents were observed to be mostly inactive during the day by either laying or sitting (82.8%). The degree of activity and inactivity hardly varied between the different time frames. The percentage of nonobservable minutes however is higher during midday.

Table 4

Observed Daily Activities on All Included Nursing Home Wards

(N = 57)OverallMorningMiddayAfternoon
Total observed minutes5,6291,5492,6841,396
Laying (%)3.82.03.46.6
Sitting (%)79.082.577.877.4
Standing (%)1.40.61.22.7
Walking (%)5.96.05.75.9
Other (%)0.40.80.50
NO (%)9.58.111.47.4

Note. NO = nonobservable minutes during the observations.

The different locations show some small differences with regard to the degree of physical activity (see Table 5). The percentage of residents observed walking at Location 3 (10.9) is relatively high compared with the other location, but remains low. Furthermore, Location 3 and Location 4 have a higher percentage of nonobservable minutes (18.9 and 12.5) in comparison with the other wards. During the investigation of potential correlations, no significant correlation is found between physical inactivity and cognition.

Table 5

Observed Overall Percentages of Daily Activities for Each Included Nursing Home Ward Separately

Location 1Location 2Location 3Location 4Location 5
Laying (%)0008.40.1
Sitting (%)898966.571.790.2
Standing (%)30.51.61.30.4
Walking (%)4.64.510.95.65.1
Other (%)002.10.50
NO (%)3.46.018.912.54.2

Note. NO = nonobservable minutes during the observations.

Agitated Behavior

Agitated behavior was assessed in 73 residents (see Table 6). The median total score of the CMAI-D for physically nonaggressive behavior is 10 (IQR = 7–17). For aggressive behavior the total mean score is 9 (IQR = 8–14).

Table 6

CMAI-D Subscores for Entire Research Population

CMAI-D subscore
Aggressive behavior (N = 71) (median, IQR)a9 (8–14)
Physically nonaggressive behavior (N = 73) (median, IQR)b10 (7–17)

Note. CMAI-D = Cohen-Mansfield Agitation Inventory—Dutch version; IQR = interquartile range.

aRange 8–56, percentile 95 > 24. bRange 7–49, percentile 95 > 28.

When comparing CMAI-D scores, Location 1 and Location 2 have slightly higher scores, for physically nonaggressive behavior (11.5, IQR = 7–17 and 13, IQR = 8–24; see Table 7). When calculating correlations, no significant result is found between physical inactivity and agitated behavior (both aggressive and physically nonaggressive behavior).

Table 7

CMAI-D Subscores for Included Wards Separately

Location 1Location 2Location 3Location 4Location 5
Aggressive behavior (median, IQR)a8 (8–9)10 (8–13)11 (8–15)8 (8–19)11 (8–13)
Physically nonaggressive behavior (median, IQR)b11.5 (7–17)13 (8–24)9.5 (8–25)8 (7–16)10 (7–12)

Note. CMAI-D = Cohen-Mansfield Agitation Inventory—Dutch version; IQR = interquartile range.

aRange 8–56, percentile 95 > 24. bRange 7–49, percentile 95 > 28.

Observations on the Wards

In total, 86 observations were conducted at the five wards included within this study (see Table 8). “Taking sufficient time” and “Calling residents by name” is lower at Location 4 and Location 5. Differences in “Visibly present” are small between the different locations, with Location 3 having the highest score (4.4, SD = 1.0). “Active caring” is the highest at Location 1 (4.5, SD = 0.4). All locations score low on “Independent walking,” but this score is the highest at Location 4 (2.5, SD = 0.7). “Guided walking” is scored low on every location and hardly differs. Location 4 scores much lower in comparison with the other locations on “Home-like environment” (2.3, SD = 0.2). “Lively ward” scores midrange on all locations, but is the highest at Location 2 (3.1, SD = 0.7). Moreover, a significant correlation is found between inactivity and the total score of the characteristics of the ward, rs(51) = −.28, p = .04, with a specific correlation between inactivity and “Taking sufficient time,” rs(51) = −.2, p = .01. Finally, there is no significant relation between CMAI-D scores for physically nonaggressive behavior and the total score of the ward observations.

Table 8

Mean Scores With SD of the Observations on the Wards of All Time Moments

Location 1 (N = 14)Location 2 (N = 26)Location 3 (N = 18)Location 4 (N = 12)Location 5 (N = 16)
Totala27.4 (3.0)26.3 (3.7)28.1 (2.8)23.3 (5.8)26.8 (8.3)
Taking sufficient time4.1 (0.5)3.7 (0.6)4.0 (0.5)2.9 (0.8)3.8 (1.2)
Calling residents by name4.6 (0.5)4.0 (0.5)4.1 (0.7)3.3 (1.2)3.6 (2.1)
Visibly present3.6 (1.1)3.8 (1.0)4.4 (1.0)4.0 (0.9)4.4 (2.0)
Active caring4.5 (0.4)3.7 (1.0)3.8 (0.7)3.6 (1.1)4.4 (1.6)
Independent walking1.9 (1.1)2.0 (0.8)2.4 (0.8)2.5 (0.7)2.2 (1.7)
Guided walking1.6 (0.8)1.8 (0.6)1.7 (0.7)1.8 (0.8)1.4 (0.4)
Home-like environment4.2 (0.3)4.0 (0.1)4.7 (0.4)2.3 (0.2)4.6 (1.3)
Lively ward2.9 (0.7)3.1 (0.7)3.0 (0.6)2.8 (1.7)2.4 (0.8)

Note. aAll items based on a 5-point Likert scale (1–5).

Discussion

People with dementia living in long-term care facilities are physically inactive with limited variations in activity during the day. Physical activity is positively connected with some aspects of the ambiance and physical environment of the wards. However, as the number of participants is relatively low in this study, results should be interpreted with caution.

In addition to the results described, an already expected strong correlation was found between the degree of physical activity and ADL. Calculating reliable correlations between physical activity and ADL is challenging as most measurements include aspects about physical capabilities. One of four items of the ADL-H is “Locomotion on unit” and has a strong overlap with physical activity. This correlation is, therefore, not included in the “Results” section.

Results found within this study with regard to the degree of physical activity in people with dementia in long-term care facilities do not differ from other studies conducted in long-term dementia care (den Ouden et al., 2015; Marmeleira et al., 2017; Moyle et al., 2017; Parry et al., 2019; van Alphen, Volkers, et al., 2016). Even though efforts are undertaken to facilitate physical exercise by organizing weekly group activities within Dutch Nursing homes, the day-to-day physical activity of people with dementia living on long-term care wards remains very low. The study of Den Ouden et al. (2015), which also reported on daily physical activity of nursing home residents by conducting manual observations, found similar percentages for active and passive activities (den Ouden et al., 2015). Therefore, this study supports the general finding that people with dementia in long-term care facilities are mostly inactive.

Previous research shows a connection between physical activity and agitated behavior (Brett et al., 2016; Ishimaru et al., 2020; Thuné-Boyle et al., 2011), which differs from the findings within our study. This could be explained by various aspects. First of all, previous studies are not always conducted exclusively in nursing homes, but also include home dwelling or hospitalized older adults with dementia (Ishimaru et al., 2020; Thuné-Boyle et al., 2011). More agitation is expected within a hospital setting as people with dementia are less familiar with the environment and staff. Furthermore, studies focusing on physical activity and agitation in the nursing home mainly include intervention studies and provide structural exercise programs, which differ from normal day-to-day physical activity. Finally, most of the average CMAI-D scores of our study population are within or below the 50th percentile and only a fairly small amount of people within our study show severe agitated behavior which makes it more difficult to reveal a strong connection. However, our study shows a clinical and realistic view of day-to-day physical activity and agitation and the results are therefore valuable for daily care.

Evidence on the influence of the physical environment on the degree of physical activity is limited (Anderiesen et al., 2014). A systematic review of Anderiesen et al. (2014) focusing on the effect of the nursing home environment on physical activity in people with dementia found that a home-like environment seems to have a positive impact on the degree of physical activity and self-initiated activities. However, a sufficient number of studies to fully support this finding is lacking. Moreover, the influence of small-scale living facilities and the footprint of the building on physical activity remain unclear. These findings are supported by this study, as we found the lowest percentage of inactivity within both large-scale and small-scale facilities.

Our study also found no connection between the degree of agitated behavior and the layout of the ward. A finding that is partially supported by the existing literature which shows that the influence of the physical environment on the behavior of people with dementia in long-term care facilities is still conflicting (Marquardt et al., 2014). These conflicting results can partially be explained by the impact the physical environment may have on the well-being of professional caregivers and their attitude and behavior toward people with dementia (Woodbridge et al., 2018). Furthermore, the inconclusive findings could also be explained by the influence of the professional caregivers on the utilization of the physical environment (de Boer et al., 2018).

Of further importance is the different methods of data collection used during the study. Some data are collected by the researchers, namely the general observations on the ward and the physical activity observations of the residents. The observation methodology is reliable, unobtrusive, and less prone to social desirability, recall bias, or poor response rates associated with self-reported measures. Although it is not an objective measure of physical activity, several other studies in similar settings have adopted the same methodology (de Boer et al., 2016; den Ouden et al., 2015), as it is more reliable than self-reported measures and has a relatively low impact for residents compared with, for example, sensor technology (Lam et al., 2018; Lim et al., 2018). Large validation studies to provide more insight into the validity of observations compared with objective measures using sensor technology within this specific population are currently lacking. As we have studied a vulnerable population, we aimed to  minimize the impact for the residents and have therefore chosen observations as the preferred methodology.

The more personal data on the residents, however, was collected using questionnaires completed by professional caregivers and might facilitate more personal interpretation, errors, and subjectivity (Lam et al., 2018). In order to enhance the objectivity of the data, validated questionnaires were used and completed by two professional caregivers. Proxy data collection is common within long-term (dementia) care (Lam et al., 2018) and is of added value when gaining insight into physical activity and other health-related outcomes. Results found within this study are promising and emphasize the need for research on this subject.

This study has a mixed-methods approach and incorporates quantitative analyses and extensive qualitative descriptions of the wards, which provides broader insight into the setting in which the study has been performed and the influence of organizational factors. Also, this study was conducted within multiple care organizations in different regions in the Netherlands and included both large-scale and small-scale facilities, which provides a more holistic view of the Dutch long-term care for people with dementia. Even though the sample size might be too small to be representative of the entire long-term dementia care in the Netherlands, a common finding is that, despite setting, residents are very physically inactive. The degree of activity was measured with reliable manual observations during three different time frames by multiple researchers and was complemented with quantitative observations on the wards. Finally, the observations of the wards are conducted by multiple observers and have a high interrater reliability, which provided consistent data on safety, physical activity, and ambiance.

However, this study also has some weaknesses. First, the study cohort is quite small and limited the use of more robust analyses. Consequently, the results of this study should be interpreted with caution. Nonetheless, several interesting results were found which provide inside into the coherence of physical activity and organizational factors and shows the need for larger and higher impact studies about this topic. Second, the availability of residents differed due to their time schedules or preference to stay in their room, it was therefore not always possible to observe a resident during three different time frames. Moreover, the physical activity observations of the residents are conducted in shared areas of the wards only. Hence, possible physical activity during the night, morning care, or other ADL-activities were not taken into account. Furthermore, the percentage of nonobservable minutes is the highest during the afternoons and at the wards with the largest walking space and/or more confusing layout. It is likely that residents are partially walking on the ward during the nonobservable minutes or are engaged in other activities that take place out of sight of the researchers. Some residents could therefore be more physically active than shown by the current results. However, the overall conclusion of this study will not differ as the degree of physical activity is still low when the nonobservable and active minutes are combined, which was the main reason to include these minutes and the high possibility that a resident is performing an activity when out of sight of the researchers. Most residents were taken away during observations for daily care, toileting, physical therapy, or leisure activities. Third, as the amount of physical activity was low among the residents, all correlations were calculated using physical inactivity. However, all correlations were also calculated using the variable physical activity and the results hardly differed. In order to take a potential type 1 error into account, the Bonferroni method was applied to the results from the correlation analyses. However, as the sample size within this study is small, this method is less applicable and all results turned out not significant as expected. These findings were therefore not included in the “Results” section. Fourth, the presence of the researchers on the wards could potentially have influenced the degree of physical activity, both positively and negatively, as unfamiliar faces and additional people can cause more unrest among the residents. However, the researchers involved within this study have extensive experience within long-term dementia care and research, monitored the general atmosphere on the wards and left when needed. Fifth, despite the percentage of nonobservable minutes, the absence of observations during the night and morning care, and the potential influence of researchers’ presence, manual observations are a widely used method to determine the degree of physical activity (den Ouden et al., 2015; Harper Ice, 2002). Finally, participants were recruited for this study by asking their informal caregivers for consent, which might have influenced the study population. Informal caregivers are possibly more likely to participate when residents are more physically independent. However, the ADL-H index scores show a representation of participants with various levels of independence within our study and reflect the average nursing home population in the Netherlands.

Conclusion

People with dementia living in long-term care facilities are generally inactive in daily life. The physical environment and ambiance of the ward seems to have an influence on the degree of physical activity. This study supports the existing knowledge about the degree of physical activity among people with dementia in long-term care and adds information about the influence of organizational factors that could be valuable for daily practice. However, more research is needed to further explore the connection between physical activity, agitated behavior, and organizational factors, and to incorporate the influence of professional caregivers.

Acknowledgments

The authors would like to thank the participating nursing homes and residents for their contribution to this study. The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Our research was funded by the Netherlands Organization for Health Research and Development (ZonMw). The funder had no role in conducting this research. Ethics approval and consent to participate: The medical research ethics committee of the UMC Utrecht approved the study protocol. Information letters and informed consent forms for participation within this study were sent by mail to the first legal representatives of all residents of the included wards by the care organizations. If the first legal representative agreed on participation, the informed consent forms were signed and sent back to the researchers. All research reported in this manuscript was conducted in accordance with the Declaration of Helsinki.

References

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    • Search Google Scholar
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    • Export Citation
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Portegijs (s.portegijs@nivel.nl) is corresponding author.

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  • Anderiesen, H., Scherder, E.J., Goossens, R.H., & Sonneveld, M.H. (2014). A systematic review–physical activity in dementia: The influence of the nursing home environment. Applied Ergonomics, 45(6), 16781686. https://doi.org/10.1016/j.apergo.2014.05.011

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Beek, S.v. (2013). Social networks of nursing staff and organizational performance: A study in long-term care facilities.

  • Beerens, H.C., Zwakhalen, S.M., Verbeek, H., Ruwaard, D., & Hamers, J.P. (2013). Factors associated with quality of life of people with dementia in long-term care facilities: A systematic review. International Journal of Nursing Studies, 50(9), 12591270. https://doi.org/10.1016/j.ijnurstu.2013.02.005

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Blankevoort, C.G., van Heuvelen, M.J., Boersma, F., Luning, H., de Jong, J., & Scherder, E.J. (2010). Review of effects of physical activity on strength, balance, mobility and ADL performance in elderly subjects with dementia. Dementia and Geriatric Cognitive Disorders, 30(5), 392402. https://doi.org/10.1159/000321357

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Brett, L., Traynor, V., & Stapley, P. (2016). Effects of physical exercise on health and well-being of individuals living with a dementia in nursing homes: A systematic review. Journal of the American Medical Directors Association, 17(2), 104116. https://doi.org/10.1016/j.jamda.2015.08.016

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Cipriani, G., Lucetti, C., Nuti, A., & Danti, S. (2014). Wandering and dementia. Psychogeriatrics, 14(2), 135142. https://doi.org/10.1111/psyg.12044

  • Cohen-Mansfield, J., Marx, M.S., & Rosenthal, A.S. (1989). A description of agitation in a nursing home. Journal of Gerontological, 44(3), M7784. https://doi.org/10.1093/geronj/44.3.m77

    • Search Google Scholar
    • Export Citation
  • de Boer, B., Beerens, H.C., Katterbach, M.A., Viduka, M., Willemse, B.M., & Verbeek, H. (2018). The physical environment of nursing homes for people with dementia: Traditional nursing homes, small-scale living facilities, and green care farms. Healthcare, 6(4), Article 137. https://doi.org/10.3390/healthcare6040137

    • PubMed
    • Search Google Scholar
    • Export Citation
  • de Boer, B., Beerens, H.C., Zwakhalen, S.M., Tan, F.E., Hamers, J.P., & Verbeek, H. (2016). Daily lives of residents with dementia in nursing homes: Development of the Maastricht electronic daily life observation tool. International Psychogeriatrics, 28(8), 13331343. https://doi.org/10.1017/s1041610216000478

    • PubMed
    • Search Google Scholar
    • Export Citation
  • den Ouden, M., Bleijlevens, M.H., Meijers, J.M., Zwakhalen, S.M., Braun, S.M., Tan, F.E., & Hamers, J.P. (2015). Daily (in)activities of nursing home residents in their wards: An observation study. Journal of the American Medical Directors Association, 16(11), 963968. https://doi.org/10.1016/j.jamda.2015.05.016

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Douma, J.G., Volkers, K.M., Engels, G., Sonneveld, M.H., Goossens, R.H.M., & Scherder, E.J.A. (2017). Setting-related influences on physical inactivity of older adults in residential care settings: A review. BMC Geriatrics, 17(1), 97. https://doi.org/10.1186/s12877-017-0487-3

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Gerritsen, D., Ooms, M., Steverink, N., Frijters, D., Bezemer, D., & Ribbe, M. (2004). Drie nieuwe observatieschalen in het verpleeghuis: Schalen uit het resident assessment instrument voor activiteiten van het Dagelijks Leven, cognitie en depressive [Three new observational scales for use in Dutch nursing homes: Scales from the resident assessment instrument for activities of daily living, cognition and depression]. Tijdschrift voor Gerontologie en Geriatrie, 35(2), 5564.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Groot, C., Hooghiemstra, A.M., Raijmakers, P.G., van Berckel, B.N., Scheltens, P., Scherder, E.J., van der Flier, W.M., & Ossenkoppele, R. (2016). The effect of physical activity on cognitive function in patients with dementia: A meta-analysis of randomized control trials. Ageing Research Review, 25, 1323. https://doi.org/10.1016/j.arr.2015.11.005

    • Search Google Scholar
    • Export Citation
  • Harper Ice, G. (2002). Daily life in a nursing home: Has it changed in 25 years? Journal of Aging Studies, 16(4), 345359. https://doi.org/10.1016/S0890-4065(02)00069-5

    • Search Google Scholar
    • Export Citation
  • Ishimaru, D., Tanaka, H., Nagata, Y., Takabatake, S., & Nishikawa, T. (2020). Physical activity in severe dementia is associated with agitation rather than cognitive function. American Journal of Alzheimer's Disease & Other Dementias, 35, Article 1533317519871397. https://doi.org/10.1177/1533317519871397

    • Search Google Scholar
    • Export Citation
  • Jing, W., Willis, R., & Feng, Z. (2016). Factors influencing quality of life of elderly people with dementia and care implications: A systematic review. Archives of Gerontology and Geriatrics, 66, 2341. https://doi.org/10.1016/j.archger.2016.04.009

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Lam, H.R., Chow, S., Taylor, K., Chow, R., Lam, H., Bonin, K., Rowbottom, L., & Herrmann, N. (2018). Challenges of conducting research in long-term care facilities: A systematic review. BMC Geriatrics, 18(1), 242. https://doi.org/10.1186/s12877-018-0934-9

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Lim, S.E.R., Ibrahim, K., Sayer, A.A., & Roberts, H.C. (2018). Assessment of physical activity of hospitalised older adults: A systematic review. Journal of Nutrition, Health and Aging, 22(3), 377386. https://doi.org/10.1007/s12603-017-0931-2

    • Search Google Scholar
    • Export Citation
  • Marmeleira, J., Ferreira, S., & Raimundo, A. (2017). Physical activity and physical fitness of nursing home residents with cognitive impairment: A pilot study. Experimental Gerontology, 100, 6369. https://doi.org/10.1016/j.exger.2017.10.025

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Marquardt, G., Bueter, K., & Motzek, T. (2014). Impact of the design of the built environment on people with dementia: An evidence-based review. Herd, 8(1), 127157. https://doi.org/10.1177/193758671400800111

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Morris, J.N., Fries, B.E., Mehr, D.R., Hawes, C., Phillips, C., Mor, V., & Lipsitz, L.A. (1994). MDS cognitive performance scale. Journal of Gerontological, 49(4), M174182. https://doi.org/10.1093/geronj/49.4.m174

    • Search Google Scholar
    • Export Citation
  • Morris, J.N., Fries, B.E., & Morris, S.A. (1999). Scaling ADLs within the MDS. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 54(11), M546553. https://doi.org/10.1093/gerona/54.11.m546

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Moyle, W., Jones, C., Murfield, J., Draper, B., Beattie, E., Shum, D., Thalib, L., O’Dwyer, S., & Mervin, C.M. (2017). Levels of physical activity and sleep patterns among older people with dementia living in long-term care facilities: A 24-h snapshot. Maturitas, 102, 6268. https://doi.org/10.1016/j.maturitas.2017.05.015

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Parry, S., Chow, M., Batchelor, F., & Fary, R.E. (2019). Physical activity and sedentary behaviour in a residential aged care facility. Australasian Journal on Ageing, 38(1), E12E18. https://doi.org/10.1111/ajag.12589

    • Search Google Scholar
    • Export Citation
  • Rantz, M.J., Mehr, D.R., Popejoy, L., Zwygart-Stauffacher, M., Hicks, L.L., Grando, V., Conn, V.S., Porter, R., Scott, J., & Maas, M. (1998). Nursing home care quality: A multidimensional theoretical model. Journal of Nursing Care Quality, 12(3), 3046, quiz 69–70. https://doi.org/10.1097/00001786-199802000-00007

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Robinson, L., Hutchings, D., Corner, L., Finch, T., Hughes, J., Brittain, K., & Bond, J. (2007). Balancing rights and risks: Conflicting perspectives in the management of wandering in dementia. Health, Risk & Society, 9(4), 389406. https://doi.org/10.1080/13698570701612774

    • Search Google Scholar
    • Export Citation
  • Scherder, E.J., Bogen, T., Eggermont, L.H., Hamers, J.P., & Swaab, D.F. (2010). The more physical inactivity, the more agitation in dementia. International Psychogeriatrics, 22(8), 12031208. https://doi.org/10.1017/s1041610210001493

    • PubMed
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