1

Title: Discrepancy between subjective and objective assessments of wandering

behaviors in dementia as measured by the Algase Wandering Scale and the IC tag

monitoring system

So YAYAMA, RN, MS

Faculty of Nursing, Senri Kinran University, Osaka, Japan

Miyae YAMAKAWA, RN, Ph.D

Department of Clinical Nursing, Division of Health Sciences, Graduate School of

Medicine, Osaka University, Osaka, Japan

Shunji SUTO, Ph.D

Department of Medical and Welfare Management, Seibi University, Kyoto, Japan

Chieko GREINER, RN, Ph.D

The Japanese Red Cross College of Nursing, Tokyo, Japan

Kazue SHIGENOBU, MD, Ph.D

Department of Psychiatry, Asakayama General Hospital, Osaka, Japan

Kiyoko MAKIMOTO, RN, Ph.D

Department of Clinical Nursing, Division of Health Sciences, Graduate School of

Medicine, Osaka University, Osaka, Japan

Corresponding author

So YAYAMA, RN, MS

Faculty of Nursing, Senri Kinran University

5-25-1 Fujishirodai, Suita, Osaka 565-0873, Japan

Phone/Fax: +81-6-6872-7184

E-mail: s-yayama@cs.kinran.ac.jp

Short Running Title:

Bias in subjective wandering measurement

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Abstract

Background: Although wandering is one of the major focuses of the Behavioral

Psychological Symptoms of Dementia (BPSD) research, assessment of wandering has

mostly relied on caregiver-administered questionnaires. The purpose of this study was

to compare staff-administered Algase Wandering Scale outcomes with objective

temporal and spatial movement indicators obtained from the Integrated Circuit tag

monitoring system.

Methods: Patients with dementia were recruited from a dementia care unit in Osaka,

Japan in 2007. Primary nurses administered the Algase Wandering Scale, and the

temporal and spatial movements of the subjects were monitored by the Integrated

Circuit tag. Written informed consent was obtained from the subject’s proxies.

Results: Nurses’ assessments of wandering during dayshift hours were in agreement

with the Integrated Circuit tag outcomes but not during non-dayshift hours. Spatial

movements assessed by the staff did not reflect those measured by the Integrated

Circuit tag.

Conclusion: This objective measurement of wandering showed the limitations in the

assessment of spatial and temporal movement by the staff.

Keyword: Algase wandering scale, dementia, objective measurement, monitoring

system, wandering behavior

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INTRODUCTION

Wandering is one of the best known behavioral and psychological symptoms of

dementia (BPSD), and is probably one of the most researched BPSDs. However,

measurements of wandering still rely on caregiver-administered scales 1). The

Neuropsychiatric Inventory (NPI) 2) and the Cohen-Mansfield Agitation Inventory

(CMAI) 3) are scales commonly used to measure a wide array of BPSDs, one of which is

wandering. The Algase Wandering Scale (AWS) is the only one which specifically

assesses wandering 4).

A literature search identified two articles which validated a staff-administered

wandering scale by comparing objective measurements. One was the AWS and the

other was the Circadian Sleep Inventory for Normal and Pathological States

(CSINAPS). For the validation of the AWS, direct observation of the dementia residents

was used as one of the outcomes of interest, and cycle frequencies of spatial movement

(random, lapping, pacing, direct) were counted. Of these, only random movement was

correlated with more than one AWS subscale, namely, persistent walking, spatial

disorientation, and eloping behaviors 5).

In the other study, Actigraph® equipment was used to examine the association

between caregiver-assessed CSINAPS and actigraph sleep indicators. In the CSINAPS

study, the actigraph data were taken for two weeks from 78 elderly subjects, living in

group care facilities. Reports of sleep disturbances like wandering at night were

reflected in actigraph parameters. However, the questionnaire and actigraph variables

correlated only modestly 6).

Objective measurements of wandering have been attempted by videotaping or direct

observation. Martino-Saltzman et al. videotaped wandering behavior of 40

institutionalized elderly with dementia for 30 days in 1991 and identified four patterns

of spatial movement such as pacing and lapping 7). Coding of the movement seems to be

labor intensive, and this approach has not been replicated.

Algase et al. used direct observation to examine the stability of wandering in 25

nursing home residents with dementia for a 24-hour period.and stability of wandering

was checked by observing for two-hours in the following days8). Their later study used

videotaping, and the duration of observation was limited to 20 minutes per session9).

181 nursing home residents with dementia were monitored between 8:00 am and

8:00pm, and up to 12 sessions were videotaped. They developed a typology of wandering,

such as classic, moderate, and subclinical.

These previous studies could not measure the distance moved and wandering by time

of the day, and technology did not allow simultaneous observation of multiple samples.

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In recent years, technology such as the Integrated Circuit (IC) tag monitoring system

for measuring activity in dementia patients became available.

The IC tag monitoring system has been used to describe the variations in distance

moved and spatial movements 10), to examine the side effects of medication 11) and to

compare staff hourly observation records with the IC tag data during the night 12).

However, the IC tag monitoring system has not been used to validate any scales used to

measure wandering.

The aim of this study was to compare staff-administered AWS outcomes with objective

temporal and spatial movement indicators obtained from the IC tag monitoring system.

METHODS

Setting

This study was part of an IC tag monitoring project carried out at a 60-bed dementia

care unit in the Asakayama General Hospital in Osaka, Japan, between November 2006

and March 2007. The study unit was a closed system and consisted of 13 four-bed rooms

and 8 private rooms as displayed in Figure 1. The unit admission criteria selected

demented patients with various BPSD and/or care burden problems. When the patient

became stabilized, the patient was discharged to long-term care facilities or to home.

The unit has 2 common spaces used for dining and for occupational and recreational

therapies (hereafter called the activity rooms).

The IC Tag Monitoring System

The IC Tag monitoring system with Powertags was used to evaluate wandering

(Matrix Int, Osaka, Japan). Within the study unit, 15 antennae were placed over the

ceiling to receive signals from the IC tag (Figure 1). The IC tag was attached to a

patient’s shirt with adhesive tape so that it could be easily re-attached after changing

clothes. When the patient with the IC tag moved under an antenna, the tag sent

information regarding the time, place, and ID information, which was received by the

antenna 13-16).

Algase Wandering Scale Version 2 (AWS)

A Japanese version (J-AWS) consists of four subscales with 23 items, using a 4-point

Likert scale, with higher scores indicating more wandering activities. The five subscales

are persistent walking (PW), spatial disorientation (SD), eloping behavior (EB),

shadowing (SH), and routinized walking (RW) 4）. A J-AWS was developed by Greiner

and its reliability has been established (Greiner C, 2007, unpublished data). The

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patient’s primary nurse had evaluated each patient using a J-AWS in the previous two

week period.

Study subjects

Eligibility criteria for the study were as follows: 1) patients diagnosed with dementia,

2) patients who were able to walk independently, 3) patients could be monitored by the

IC tag monitoring system for more than 3 consecutive days before being evaluated by

J-AWS, 4) patients whom nurses evaluated wandering by J-AWS.

Ethical considerations

This research was approved by the Ethics Committee of Osaka University, Graduate

School of Medicine as well as the Ethics Committee of the Asakayama Hospital. The

study protocol and ethical considerations were explained to all the eligible patients and

patient proxies. The major components of the ethical considerations were: 1) study

participation was voluntary, 2) the patient could withdraw from the study at any time,

and 3) participation status would not affect treatment or care of the subject in any way.

Written informed consent was obtained from the patient's authorized proxies, and

monitoring was terminated when the patient tried to remove the IC tag.

Diagnosis Criteria

The diagnosis was made by the fifth author. For the differential diagnosis of

Alzheimer’s disease, vascular dementia, frontotemporal dementia, dementia with Lewy

bodies, and dementia related to alcoholism, the criteria of the Diagnostic and Statistical

Manual of Mental Disorders Fourth Revision [DSM-IV-R]17) were used.

Data collection

Patient demographic data were obtained from medical records. The Mini-Mental State

Examination (MMSE) 18) was used for cognitive assessment and evaluated by a clinical

psychologist at the time of admission. The Clinical Dementia Rating score (CDR) 19) was

used to quantify severity of symptoms of dementia and evaluated by the fifth author

shortly after admission.

Comparing temporal movements measured by J-AWS data with those measured by the

IC tag monitoring system

Of 23 J-AWS items, 8 items could be compared with the temporal and spatial

movement measured by the monitoring system. Items which could not be evaluated by

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the IC tag included movements such as 'Resident gets lost' and 'Resident cannot locate

dining room without help', and these were not included in the analysis.

Of the 8 items, 5 belonged to temporal movements, and 3 belonged to spatial

movements. Temporal movements indicated the four time periods of: 1) between

awakening and breakfast, 2) between breakfast and lunch, 3) between lunch and dinner,

and 4) between dinner and bedtime. The corresponding times for the IC tag data were

as follows: 1) 5:00-8:00, 2) 8:30-11:30, 3) 12:00-17:30, and 4) 18:00-21:00. The fifth item

related to temporal movement was “During meals, resident tries to leave the table, or

walks away”, and the IC tag data of the following time periods were classified as meal

time: 1) 8:00-8:30, 2) 11:30-12:00, and 3) 17:30-18:00.

Three items pertained to spatial movements. “Resident paces up and down” was

interpreted as moving back and forth between any 2 antennae consecutively 7)., “Travels

same route over and over.” was defined as lapping, where the patient consecutively

moved around the 4 corners of the unit, in either a clockwise or a counterclockwise

direction 7). Consecutive movements were defined as a minimum number of the same

movement more than 3, which was based on our previous study 7). “Goes to same

location over and over.” was defined as frequency of detection by antennas of the

monitoring system, and the number of detections was determined as follows: if the

patient was detected at one place and remained in that same place, it was counted as

one.

In addition, one item was “Resident is a wanderer.” The differences in the distance

moved per day were tested among four responses ranging from ‘never’ to ‘yes, it is a

problem.’

Data analysis

Descriptive statistics were conducted for all the variables. The mean was used when

the distribution was normal, and the median was used when the distribution was

skewed. Spearman correlation coefficients were obtained in order to examine the

association 1) between a J-AWS subscales and the distance moved per day and 2)

between a J-AWS subscales and the MMSE. In order to test the differences in the

distances moved among the 4 responses to a J-AWS items, one-way analysis of variance

was used when the distribution was normal, and the Kruskal–Wallis test was used

when the distribution was skewed. SPSS version 15.0 for Windows was used for data

analysis. P-values less than 5% were considered statistically significant.

RESULTS

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Patients Characteristics

Thirty-six patients met eligibility criteria. Six patients were monitored less than 3

days prior to J-AWS administration and were excluded from analysis. The median

duration of monitoring was 7 days (range: 3–14 days; inter-quartile: 5 days), and the

median distance moved per day was 1,337m (range: 89m–13,542m; inter-quartile:

1,987m). The demographic data are displayed in Table1. The majority of the subjects

were elderly and men accounted for slightly less than 50%. Two-thirds of the subjects

had Alzheimer’s disease with a moderate to advanced stage of dementia (Table 1).

The means of 7 J-AWS items ranged from 1.9±1.1 for “During meals resident tries to

leave the table, or walks away” to 2.8±1.1. For the item 'Resident is a wanderer,' the

item mean was 2.5±1.1.

The median distance moved per day among the four wandering statuses differed

significantly (Kruskal–Wallis, p<0.05). Those who were rated as 'yes' had a longer

median distance moved per day than those who were rated 'no.' (Figure 2)

Distance moved per day was positively correlated with J-AWS total score, and MMSE

was negatively correlated with a J-AWS total score. ‘Persistent walking’ and ‘eloping

behavior’ were associated with both MMSE and the distance moved. Spatial

disorientation was associated with MMSE only, and ‘routinized walking’ was associated

with the distance moved per day only (Table 2).

Comparing temporal movement measured by J-AWS data with that by the IC tag

monitoring system

The median distance moved per time period among the 4 levels of wandering measured

by a J-AWS differed significantly for the morning and afternoon periods

(Kruskal–Wallis, p<0.05), and a higher rating of wandering was associated with a

longer distance moved per time period (Figure 3). In contrast, no dose-response

relationship was apparent for before breakfast, after dinner, and mealtime, and

statistical significance was not attained (Kruskal–Wallis, p>0.05) (Figure 3).

The proportion of the subjects who walked during the night (22:00–5:00) (which was

not covered by a J-AWS scale) was 56.7%, and the median distance moved during the

night was 5.2m (range: 0m–878m; inter-quartile: 33m).

The number of those who were rated as pacing ‘more than others’ was 4, and of these 2

had a median number of pacings more than 0. The number of those who were rated as

lapping ‘more than others’ was 7, and of those, only one had a median number of

lappings more than 0. As repetitive pacing and lapping were rare, non-repetitive spatial

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movements were used to compare IC tag data with corresponding AWS item scores.

When the median number of non-repetitive spatial movements was compared with a

J-AWS assessment, the median number of pacings differed significantly among the four

responses of a J-AWS pacing item (Kruskal–Wallis, p<0.05), and the median number of

lappings did not differ significantly among the four responses of a J-AWS lapping item

(Kruskal–Wallis, p>0.05). The number of non-repetitive pacings was strongly associated

with the distance moved per day (r=0.81, p<0.05), and it was the same for lapping

(r=0.80, p<0.05).

The item asking about habitual behavior related to spatial movement was examined

by plotting the median frequency of detections for each antenna according to the 4

responses of the item “Goes to same location over and over.” Of these four responses, the

median number of distributions for those rated as 'never' and 'on a daily basis’ were

displayed in Figure 4a and 4b, respectively. Of 6 patients rated as ‘never’, the highest

median number of detections was 60, and 2 out of 5 subjects had median distances

moved per day of less than 1km. Of those who were rated as wandering ‘on a daily basis',

only 2 exceeded 60 detections, and 2 out of 8 subjects had median distances moved per

day of less than 1km. Field notes taken by the research assistants showed that these

less mobile subjects tended to spend most of the day in the activity room.

DISCUSSION

The current study found that assessments of the temporal aspect of wandering by

nurses reflected the distance moved as measured by the IC tag monitoring system well

during the day shift hours but not during the non-day shift hours and at mealtimes.

The major strength of our research is the around-the-clock monitoring of ambulation

for more than 7 consecutive days. Another study to validate a J-AWS used direct

observations recorded by a bar code reader to code pattern and rhythm of ambulation 4).

This paper did not provide a duration of observation while their other study mentioned

a period of 24 hours for direct observation 20). The paper noted extensive error checking

and cleaning based on the field notes of data collectors, suggesting limitations in the

use of direct observation to monitor wandering 5). Our monitoring system is fully

automated for recording movements in the facility with high precision, eliminating

inter-rater reliability problems.

No other studies have compared professional caregiver assessment of wandering with

objective measurements. Only in a study of sleep-awake disturbances in dementia

patients, professional caregivers’ assessments were compared with actigraphic

measurements 6). The scale included an item on nighttime wandering which was not

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defined in the paper. The study subjects who were assessed as wandering at night had

lower Sleep Efficiency than those assessed as not wandering at night, with the former

having higher L5 (least active 5 hours out of 24 hours) values than the latter. Although

these findings support the validity of caregiver assessment to some extent, the

actigraph was not developed specifically to assess ambulation itself.

Poor agreement on temporal movements between a J-AWS evaluations and the IC tag

measurements during non-day shift hours suggests the difficulty in assessing patient

ambulation during the night shift, probably due to the minimum staff-to-patient ratio at

night. Of note, a J-AWS itself does not have any item to evaluate nighttime wandering.

Nighttime ambulation was common in our study as well as in Yamakawa's study

conducted in 2008 and 2009 in the same study unit, and it was substantially

underreported in the staff ’s hourly observation sheet when compared with the IC tag

monitoring system data 12).

Discrepancies between the subjective and objective data were also seen for the spatial

movements of pacing and lapping. There is a problem in evaluating interventions to

reduce wandering because the NPI is one of the most commonly used scales to measure

wandering 21), and the NPI contains only one item on wandering. That is ‘pace or wheel

around the facility with no reason’ which belongs to 'Aberrant Motor Behavior’, a

subcategory measuring repetitive behavior. In the study by Nakaoka et al., repetitive

pacing and lapping spatial movements were only observed in frontotemporal dementia

patients 10), which suggests that pathological changes in the brain may account for

repetitive spatial movements. Objective measurements of spatial movement seem to be

worth pursuing.

Nurses' evaluations of wandering may reflect their overall patient assessments

including sleeping patterns and mental status. Yamakawa et al. reported that the

agreement rates between the staff ’s hourly observation records and the IC tag

monitoring data at night were higher when the patient had certain conditions such as

afternoon naps, or alterations in mental status 12). Their findings suggest that nurses

set priorities for observation based on patients’ conditions. In our sample, the least

mobile patient had a high rating for ‘go to the same place over and over.’ Some patients

with visible signs of BPSD are likely to get more attention from the staff than those

without, and these selective attentions may lead to overestimations of patients’

movements.

Implications for clinical practice

A J-AWS offers a rich description of wandering behaviors. However, it has not been

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used frequently to evaluate interventions to reduce wandering compared with the NPI.

A couple of reasons may explain the limited use. First, the clinical significance of the

AWS has not been well described and the scale does not measure care burden. Second,

wandering is only one of the BPSDs and in clinical settings, staff needs to evaluate a

wide array of BPSDs. Therefore, a scale to measure a set of BPSDs such as the NPI is

more pragmatic to use than the AWS.

Although there is no consensus on the definition of wandering, two aspects of

wandering need to be assessed and documented in clinical practice. One is care

burden-related behavior and the other is physical burden resulting from excessive

ambulation. Care burden-related behaviors include exit seeking, eloping, boundary

transgression, and nighttime wandering 1). Most of these behaviors are safety issues as

well, and multiple strategies are necessary to secure patient safety.

Physical burden occurs when patients have excessive wandering. In our sample,

median distance moved per day exceeded 10km in a few patients, and Miyoshi et al.

described weight loss problem in dementia patients with excessive wandering as

measured by the IC tag monitoring system 15). Patients who appear to walk incessantly

are in need of weight monitoring and nutritional assessment.

Limitations and future research needs

The major limitation of this study was that the median duration of IC tag monitoring

was less than two weeks. Nevertheless, primary nurse evaluations of wandering during

the daytime were in agreement with the distance moved as measured by the IC tag

monitoring system. The other limitation is a small sample size from only one institution

in Japan. In spite of these problems, our study finding of an association between a

J-AWS subscales and the MMSE were in agreement with the international study by

Algase et al. 4), and the association between AWS subscales and the distance moved per

day was in the expected direction.

The IC tag monitoring system is currently the only system capable of monitoring

patient temporal and spatial movement around the clock for an extended period and is

an excellent tool to monitor the effects of medication on patient patterns of movement 11）.

However, there are limitations for clinical application. The IC tag needs to be attached

to the patient's shirt, and it needs to be reattached whenever the shirt is changed. A

device like an actigraph worn around the wrist was not well accepted in our study

population. Development of a monitoring device which is acceptable for patients with

dementia is necessary to advance this research.

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CONCLUSIONS

This study compared staff-assessed wandering behaviors in dementia patients with

objective measurement outcomes using the IC tag monitoring system and found that

staff assessments of temporal movements was in agreement with the IC tag

measurement outcomes only during the dayshift hours but not during the early

morning or late evening. Our finding suggests that staff assessment alone is

insufficient for evaluating wandering behaviors.

ACKNOWLEDGEMENTS:

This study was supported by a Grant-in-Aid for Scientific Research (Scientific

Research B, No. 17406032, 2005-07) from the Japan Ministry of Education, Culture,

Sports, Science, and Technology. The authors would like to express their appreciation

for the cooperation extended by the staff of Asakayama Hospital.

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167–172.

11) Liao X, Yamakawa M, Suto S et al. Changes in Activity Patterns after the Oral

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14) Makimoto K, Eun AL, Kang Y et al. Temporal patterns of movements in

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Changes in Bodyweight in dementia Patients. Psychogeriatrics 2008; 8: 170–174.

16) Segawa N, Yamakawa M, Shigenobu K et al. Attempts to differentiate the pattern of

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17) American Psychiatric Association. Diagnostic and statistical manual of mental

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Table1. Demographic and clinical characteristics of the subjects

n=30

Variable (%) Mean±SD

Age (year-old) 67.6±13.1

Sex male 46.7

female 53.3

Types of dementia Alzheimer’s Disease 63.3

Vascular Dementia 16.7

Frontotemporal dementia 10.0

Dementia related to

alcoholism 6.7

Dementia with Lewy Bodies 3.3

MMSE* score 10.4±8.4

Clinical Dementia

Rating score

3 (severe) 33.3

2 (moderate) 40.0

1 (mild) 26.7

*MMSE: Mini-Mental State Examination

Table 2 Spearman correlation coefficient between J-AWS subscale scores and the

distance moved per day and Mini Mental State Exam (MMSE)

AWS subscales Distance moved per day MMSE

Persistent walking 0.73* -0.52*

Spatial Disorientation 0.32 -0.63*

Eloping Behavior 0.40* -0.62*

Shadowing 0.34 -0.18

Routinized Walking 0.44* -0.26

Total score 0.60* -0.63*

*p<0.05

15

Figure 1．Layout of the unit

Figure 2: Box plot of the median distance moved per day according to the 4 responses

of the AWS item, “Resident is a wanderer”.

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

11000

1 (definitely

not)

2 (at times) 3 (yes, but it

is not a

problem)

4 (yes, and it

is a problem)

median

distance

moved

per day

n=8

n=6

n=9 n=7

16

Figure 3．Median distance moved according to J-AWS item score by time period.

＊p<0.05

†Responses for this item were as follows: 1) never, 2) on a few occasions, 3) regularly but

not daily, 4) on a daily basis).

207

9 43 24 10

123 63

211

464

158

302 418

948

775

18

308

1076

1921

646

306

0

200

400

600

800

1000

1200

1400

1600

1800

2000

5:00-8:00

(between

awakening and

breakfast)

8:30-11:30*

(between

breakfast and

lunch)

12:00-17:30*

(between lunch

and dinner.)

18:00-21:00

(between

dinner and

bedtime)

during meals†

(During meals,

resident tries

to leave the

table, or walks

away.)

1 (never)

2 (less than others of same age and ability)

3 (like others of the same age and ability)

4 (more than others of same age and ability)

Median distance moved per time period

ｍ

17

Figure 4a Median number of detections by 15 antennas for those who were assessed as

'never goes to same location over and over.’

Figure 4b. Median number of detections by 15 antennas for those who were assessed as

'goes to same location over and over on a daily basis'

*Antenna number locations are shown in Figure 1.

0

20

40

60

80

100

120

140

160

180

200

1 2 4 12 13 5 6 11 14 15 3 7 8 9 10

ID1 (2,493m)

ID2 (1,837m)

ID3 (1,414m)

ID4 (418m)

ID5 (89m)

corridor activity room room

antenna number*

Median

number of

detections

for

antenna

0

20

40

60

80

100

120

140

160

180

200

1 2 4 12 13 5 6 11 14 15 3 7 8 9 10

ID6 (11,605m)

ID7 (3,827m)

ID8 (2,363m)

ID9 (1,191m)

ID10 (843m)

ID11 (117m)

corridor activity room room

antenna number*

Median

number of

detections

for

antenna