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Psychometric Evaluation of the Electronic Pain Assessment Tool: An Innovative Instrument for Individuals with Moderate-to-Severe Dementia

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Abstract

Background/aims: Pain is common in aged care residents with dementia; yet it often goes undetected. A novel tool, the electronic Pain Assessment Tool (ePAT), was developed to address this challenging problem. We investigated the psychometric properties of the ePAT. Methods: In a 10-week prospective observational study, the ePAT was evaluated by comparison against the Abbey Pain Scale (APS). Pain assessments were blindly co-performed by the ePAT rater against the nursing staff of two residential aged care facilities. The residents were assessed twice by each rater: at rest and following movement. Results: The study involved 34 residents aged 85.5 ± 6.3 years, predominantly with severe dementia (Psychogeriatric Assessment Scale - Cognitive Impairment score = 19.7 ± 2.5). Four hundred paired assessments (n = 204 during rest; n = 196 following movement) were performed. Concurrent validity (r = 0.911) and all reliability measures (κw = 0.857; intraclass correlation coefficient = 0.904; α = 0.950) were excellent, while discriminant validity and predictive validity were good. Conclusion: The ePAT is a suitable tool for the assessment of pain in this vulnerable population.
© 2018 S. Karg er AG, Basel
Original Research Article
Dement Geriatr Cogn Disord
Psychometric Evaluation of the Electronic
Pain Assessment Tool: An Innovative Instrument
for Individuals with Moderate-to-Severe
Dementia
Mustafa Atee a Kreshnik Hoti a, b Jeffery D. Hughes a
a School of Pharmacy, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia;
b Division of Pharmacy, Faculty of Medicine, University of Pristina, Pristina, Kosovo
Keywords
Psychometric properties · Validity · Reliability · Electronic Pain Assessment Tool · Pain ·
Dementia · Automated facial recognition · Facial action units · Automated facial analysis ·
Observational pain scales · Application
Abstract
Background/Aims: Pain is common in aged care residents with dementia; yet it often goes
undetected. A novel tool, the electronic Pain Assessment Tool (ePAT), was developed to ad-
dress this challenging problem. We investigated the psychometric properties of the ePAT.
Methods: In a 10-week prospective observational study, the ePAT was evaluated by compar-
ison against the Abbey Pain Scale (APS). Pain assessments were blindly co-performed by the
ePAT rater against the nursing staff of two residential aged care facilities. The residents were
assessed twice by each rater: at rest and following movement. Results: The study involved 34
residents aged 85.5 ± 6.3 years, predominantly with severe dementia (Psychogeriatric Assess-
ment Scale – Cognitive Impairment score = 19.7 ± 2.5). Four hundred paired assessments
(n = 204 during rest; n = 196 following movement) were performed. Concurrent validity (r =
0.911) and all reliability measures (κw = 0.857; intraclass correlation coefficient = 0.904; α =
0.950) were excellent, while discriminant validity and predictive validity were good. Conclu-
sion: The ePAT is a suitable tool for the assessment of pain in this vulnerable population.
© 2018 S. Karg er AG, Basel
Accepted: November 15, 2017
Published online: ■■■
Mustafa Atee
School of Pharmac y, Curtin University
PO Box U1987
Perth, WA 6845 (Australia)
E-Mail Mustafa.Atee @ curtin.edu.au
www.karger.com/dem
DOI: 10.1159/000485377
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Dement Geriatr Cogn Disord
Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, Basel
DOI: 10.1159/000485377
Introduction
A reduced self-reporting capacity in individuals with dementia is common due to disease-
related progressive cognitive impairment [1]. In the absence of a valid and reliable self-report
rating (i.e., gold standard), observational pain assessment tools are an appropriate
replacement to evaluate pain for nonverbal populations such as those with advanced dementia
[2, 3]. A study by Lukas et al. [4] concluded that the use of these tools improved pain recog-
nition (by up to 25.4%) and rating (by up to 42.5%) in older adults with cognitive impairment.
Because ageing predisposes individuals to a number of comorbidities, pain is very
common. In aged care facilities, up to 80% of residents experience pain at some stage during
their stay [5, 6]. In this setting, dementia affects more than 50% of aged care residents in
Australia and Germany [7, 8], and 69% in the UK [9, 10]. In the USA, over 61% of aged care
residents have moderate-to-severe cognitive impairment [11]. Nursing staff have reported
difficulty in detecting pain in these residents, and even with experience they remain poor at
interpreting facial expressions indicative of pain [12, 13]. Moreover, there is evidence that
even interdisciplinary evaluation of pain fails to assess pain correctly [14].
The importance of identifying pain in this population is critical to optimal pain
management. Failure to do so may result in a denial of appropriate medication or therapeutic
intervention, prescription of analgesics at inadequate dosages, or use of inappropriate medi-
cation (e.g., antipsychotics) [15–20]. These may lead to poor quality of life and premature
death in these individuals [21–25]. Assessing pain requires a tool with sound psychometric
properties and innovative characteristics so that timely access to appropriate pain
management is assured.
Currently, there are more than 35 observational-behavioral pain assessment tools
targeted at people with dementia [26]. Many of these tools have been criticized in a number
of reviews for being inadequate due to the paucity of systematic evaluation of their psycho-
metric properties [27–29]. Despite the abundance of tools for this population, they still suffer
from lack of innovation [27]. Since the face is the richest source of behavioral expressions, a
prudent approach is to integrate objective facial measures such as Ekman’s Facial Action
Coding System (FACS) into these tools [29, 30]. The FACS is an annotated catalogue of facial
micro-expressions which describes each facial muscle action with a unique code called an
action unit (AU) [31]. For instance, AU4 is brow lowering, while AU6 is a cheek raiser.
Current research supports this approach, which is why we have developed the electronic
Pain Assessment Tool (ePAT), a novel instrument of great potential to transform the process
of pain assessment in dementia [29, 32, 33]. The ePAT is a point-of-care tool that uses a hybrid
model: automated facial recognition and analysis, digitization, and clinical observations [33].
The tool is built as a software application that is compatible with Android and iOS smart
devices (see online suppl. File 1; see www.karger.com/doi/10.1159/000485377 for all online
suppl. material, ). Figure 1 illustrates the steps involved in pain assessment using the ePAT.
Previous psychometric evaluation of the prototype version of the app (Android V3.0) demon-
strated that ePAT had excellent concurrent validity and internal consistency when compared
to the Abbey Pain Scale (APS), while possessing good discriminant validity and interrater reli-
ability [33]. These data were evaluated using a mix of raters including nurses, health science
students, and care workers [33].
In this study the Android V4.0 app was evaluated in the setting of aged care in comparison
with APS assessments undertaken by nursing staff. The aim of the study was to evaluate the
psychometric properties (concurrent validity, discriminant validity, predictive validity,
internal consistency, and interrater reliability) of the ePAT (Android V4.0) in residents with
moderate-to-severe dementia, and to compare these findings to those reported in our
previous study.
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, BaselDOI: 10.1159/000485377
Methods
Study Design and Setting
This prospective observational study involved residents recruited from two accredited residential aged
care facilities (RACFs), located in the Perth metropolitan area, Western Australia. Table 1 provides a summary
of the characteristics of each RACF.
Procedure
The study was approved by the Human Research Ethics Committee of Curtin University, Western
Australia (HREC: HR10/2014) and by Mercy Health Care (R15/50AC). This study also had Clinical Trial Noti-
fication (CTN) approval (CT-2016-CTN-04886-1 v1) from Therapeutic Goods Administration (TGA). Written
invitations and information sheets were sent to authorized representatives to provide consent on behalf of
residents as they were deemed incompetent of providing their own informed written consent. All assess-
ments were completed in accord with the Declaration of Helsinki, as well as policy statements of the
Alzheimer’s Association and the World Health Organization on assistive technologies for people with
dementia. All data were de-identified and protected to maintain confidentiality.
In this study, the ePAT (Android V4.0, Samsung Note 3-N9005) was evaluated in comparison with the
APS in two RACFs. The study lasted for a period of 10 weeks, which was commenced in January and completed
in April 2017. Weekly pain ratings of residents were made concurrently by two independent raters, one using
the ePAT and the other using the APS. The ePAT rater was the primary investigator (M.A.), who is experienced
with the use of the tool, while the APS was administered by a member of the nursing staff of the two RACFs.
The raters were required to complete a questionnaire to ascertain their familiarity (i.e., prior experience
or exposure) with the APS. Before commencing the study, a test case was run and discussed between the
ePAT rater and the APS raters to cement understanding of the protocol. Paired ratings were undertaken
indoors during standard care in the afternoon hours of 1–4 p.m. The automated facial assessments with the
ePAT were done under ambient lighting conditions and within 1 m of the resident’s face. Each rater was
blinded to the other rater’s assessment/scoring and also to the drug and non-drug pain therapies received
by the residents under assessment during that day. At each encounter, the residents were assessed twice by
Step 1: The Face (Domain 1) Step 2: The Voice (Domain 2) Step 3: The Movement (Domain 3) Step 4: The Behavior (Domain 4)
Step 5: The Activity (Domain 5) Step 6: The Body (Domain 6) Step 7: Computation of Pain Scores
Fig. 1. Pain assessment process using the electronic Pain Assessment Tool (ePAT). Facial analysis is auto-
mated (step 1) in domain 1 (The Face), the app user then completes the checklists for the other 5 domains
(steps 2–6), and the app then calculates a total pain score and pain severity score (step 7).
Color version available online
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, Basel
DOI: 10.1159/000485377
each rater: at rest to replicate comfort conditions, followed by movement to instigate nociceptive experi-
ences. The residents were clinically stable during these assessments, which were carried out under similar
testing conditions (e.g., lighting). A similar methodology was used by the authors in a previous study [33].
Pain Assessments
The APS (see online suppl. File 2) was used as a point of reference in this study because it is widely used
in Australia for patients with dementia who cannot verbalize, has been translated into various languages, and
has sound psychometric properties [3, 27, 34–36]. The APS consists of 6 observational domains: vocalization,
facial expressions, change in body language, behavioral change, physiological change, and physical change
[37]. Scoring of the tool involves ordinal ratings that range from 0 to 3 to indicate the intensity in each
domain, where 0 = not present, 1 = mild, 2 = moderate, and 3 = severe. Total pain intensity is calculated after
adding all domain scores, which is then categorized based on the following cutoff points: 0–2 = no pain,
3–7 = mild pain, 8–13 = moderate pain, and 14 = severe pain [37].
The ePAT is the measure of interest in this study. Its psychometric data were investigated in comparison
with those from the APS. The ePAT is a point-of-care app that utilizes automated facial recognition and
analysis to detect pain-related facial AUs, which are then used in combination with other clinical indicators
to calculate a pain intensity score [33]. The tool has a total of 42 descriptors, which were selected based on
their association with pain according to the literature. Each descriptor is scored on a binary scale of yes = 1
and no = 0. These descriptors are contained within 6 domains: The Face, The Voice, The Movement, The
Behavior, The Activity, and The Body (Fig. 1). A summation of the domain scores results in a total numerical
score, which conforms to the following pain categories: no pain (0–6), mild pain (7–11), moderate pain
(12–15), and severe pain (16) [33]. A full description of the tool’s contents, scoring, and conceptual foun-
dation has been published elsewhere [33].
Cognitive Assessments
Cognition of the residents was measured using the Psychogeriatric Assessment Scale – Cognitive
Impairment Scale (PAS-Cog). The PAS-Cog is an informant-administered cognition scale which has been vali-
dated for various populations [38–40]. The scale is also endorsed by the Australian Government as a tool for
cognitive assessment for the purposes of aged care funding [41]. The cognitive scores of the residents were
extracted from their electronic profile data. Scores indicative of the stage of severity of cognitive impairment
are as follows: 0–3 = minimal, 4–9 = mild, 10–15 = moderate, and 16–21 = severe [38].
Resident s
Residents were selected for participation if they were older than 65 years; had been living in the facility
for at least 3 months; had been diagnosed with dementia by a geriatrician; had been classified as having
moderate-to-severe dementia based on a PAS-Cog score of >10; and had a medical history or presenting
complaint(s) that involved painful conditions.
Residents were excluded from the study if they were deemed medically unfit to participate (as deter-
mined by the treating physician); had a facial deformity; or were unable to display facial expressions.
Table 1. Characteristics of the RACFs involved in the study
RACF 1 RACF 2
Location of facility Metropolitan Metropolitan
State Western Australia Western Australia
Type of facility Residential Residential
Ownership of facility Non-for-profit Non-for-profit
Bed capacity 67 83
Clinical staff 4 registered nurses
1 enrolled nurse
1 clinical nurse
3 registered nurses
1 enrolled nurse
Re-accreditation due date July 2018 July 2018
RACF, residential aged care facility.
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, BaselDOI: 10.1159/000485377
APS Raters
APS raters were staff employed by the facility who were recruited into the study if they had been working
in the facility for at least 3 months to ensure familiarity with the residents; were familiar with or cognizant of
the use of the APS; were able to converse in English; were trained or registered nurses; were involved in
providing direct care to residents; and were willing to participate (conferred by providing a written consent).
Staff were excluded from participation if their duties did not include pain assessment and management
or if they were likely to be absent during the course of the study.
Statistical Analyses
Descriptive statistics were used in this study to provide a summary of variables for the residents, raters,
and assessments. Psychometric measures of validity and reliability were calculated using appropriate statis-
tical tests.
Concurrent validity was evaluated using Pearson’s (r) correlation coefficient between the two instru-
ments (ePAT vs. APS) for each of the following instances: at rest, with movement, and overall (i.e., at rest or
with movement). The strength of correlation is denoted by the following increment values: none to weak,
0.00–0.25; weak to moderate, 0.26–0.50; moderate to strong, 0.51–0.75; and strong to extremely strong,
0.76–0.99 [42].
Discriminant validity was examined through conducting a comparative analysis between ePAT scores
and APS scores for all residents under conditions of rest as opposed to movement. Regression analysis was
selected to show the difference in pain scores using a mixed model. The dependent variable was the difference
in pain scores, while the independent variable was timing (rest or with movement). The p value associated
with the timing of an activity – e.g., sitting (representative of rest) versus exercise (representative of
movement) – demonstrated whether the correlation of a difference in scores was activity dependent.
Predictive validity was assessed using t statistics of the mean pain scores. Other central tendency
measures (median and mode) for pain scores at rest compared to those following movement activities were
also reported.
Reliability measures explored in this study included internal consistency, interrater reliability, and the
intraclass correlation coefficient (ICC). Internal consistency determined whether the two instruments were
measuring the same construct, i.e., pain. Cronbach’s α was used to assess the internal consistency, with values
of 0.7 considered illustrative of good agreement between the two tools [43]. Interrater reliability was
assessed by measuring agreement using Cohen’s κ on the categorical pain scores: no pain, mild pain, moderate
pain, and severe pain. Weighted κ (κw) was used to determine the overall agreement on ordinal scores. Inter-
pretation of the κ values ranged from poor (0.0) to perfect (1.0), with moderate agreement in the range of
0.41–0.60 [44]. ICC values were calculated for continuous pain scores. Interpretation of the ICC values
followed the same guidelines as the correlation coefficients above [42].
Statistical significance was expressed as p values (<0.05) or 95% confidence intervals (CI). All analyses
were performed using the Statistical Package for the Social Sciences (SPSS) version 22 (SPSS, Inc., Apache
Software Foundation, Chicago, IL, USA).
Results
Resident Sample
Thirty-seven residents with differing dementias, pain conditions, and genders were
consented (through their proxies) to participate in the study. Three residents dropped out
before the study commenced; of these, 1 resident died and the other 2 were discharged to
other facilities/home, leaving a final sample of 34 residents. All the residents were over 68
years of age, with the majority being female (58.8%). A total of 27 residents (79.4%) were
classified as having severe dementia according to PAS-Cog scores (mean: 19.7 ± 2.5; median:
21; range: 11–21). Table 2 provides the clinical and demographic data on the residents.
APS Raters
The APS raters were nursing staff employed in one or the other of the two facilities with
a mean age of 29.4 ± 6.8 years. Four of the 5 raters were female. The raters were nurses with
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, Basel
DOI: 10.1159/000485377
varying roles (1 clinical nurse and 4 registered nurses) and years of experience (2.8 ± 0.8).
All 4 registered nurses were employed in the same facility (RACF 1), while the clinical nurse
was working in the other facility (RACF 2). All nurses had received pain education in the past
and were familiar with the use of the APS. Table 3 describes the demographic characteristics
of the APS raters.
Clinical Pain Assessments
The residents had a total of 400 paired pain assessments conducted over the period of
the study. Of those, 204 assessments were performed during rest, whereas 196 assessments
were done following movement. All assessments were undertaken during activities of daily
living such as sitting, walking, and repositioning.
Table 2. Clinical and demographic characteristics of the resident sample at baseline (n = 34) from the two
aged care facilities
Mean age (SD), years 85.5 (6.3)
Median age (range), years 83.8 (68–93.2)
Gender, n (%)
Female 20 (58.8)
Male 14 (41.2)
Ethnicity, n (%)
Caucasian 33 (97.1)
Other 1 (2.9)
Country of birth, n (%)
Australia 24 (70.8)
UK 5 (14.7)
Italy 1 (2.9)
The Netherlands 1 (2.9)
Poland 1 (2.9)
South Africa 1 (2.9)
USA 1 (2.9)
Primary language, n (%)
English 33 (97.1)
Italian 1 (2.9)
Secondary language, n (%)
Afrikaans 1 (2.9)
Dutch 1 (2.9)
Polish 1 (2.9)
Ukrainian 1 (2.9)
None 30 (88.4)
Mobility, n (%)
Fully ambulant 1 (2.9)
Ambulant with assistance 19 (55.9)
Non-ambulant 14 (41.2)
Mean dementia severity (PAS-Cog) score (SD) 19.7 (2.5)
Median PAS-Cog score (range) 21 (11–21)
Diagnosis of dementia, n (%)
Alzheimer disease 12 (35.3)
Unspecified dementia 15 (44.1)
Frontotemporal dementia 1 (2.9)
Lewy body dementia 2 (5.9)
Parkinson dementia 2 (5.9)
Vascular dementia 2 (5.9)
PAS-Cog, Psychogeriatric Assessment Scale – Cognitive Impairment Scale
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, BaselDOI: 10.1159/000485377
Validity
Concurrent Validity
All correlation coefficients had high positive values, indicating excellent concurrent
validity of the ePAT when compared with the APS (Table 4). The association between ePAT
and APS total scores is also shown in Figure 2. The graph demonstrates the strong positive
correlation between the two instruments.
Discriminant Validity
The statistical difference (expressed by the p value) was computed to demonstrate
whether the timing of activity (rest vs. movement) had any effect on the correlation between
the ePAT and the APS. It was found that the correlation between the two instruments was not
situation dependent (p = 0.243).
Predictive Validity
Both tools showed increased pain scores as a consequence of movement. On the ePAT,
the pain scores were significantly higher (p < 0.0001) with movement (mean: 11.44 ± 3.54;
median: 11; mode: 13) than at rest (mean: 8.33 ± 3.34; median: 9; mode: 10). Similarly, the
APS had significantly higher pain scores (p < 0.0001) following movement (mean: 6.96 ± 3.85;
median: 7; mode: 8) than at rest (mean: 4.34 ± 3.14; median: 4; mode: 1).
Table 3. Demographic characteristics of the APS raters (n = 5)
n (%) Mean (SD) Median (range)
Age, years 29.4 (6.8) 28 (24–41)
Gender (female) 4 (80)
Ethnicity
Caucasian 1 (20)
Asian 4 (80)
Primary language (English) 5 (100)
Employment status, h 35.4 (3.2) 36 (30–38)
Part time (<38 h) 3 (60)
Full time (≥38 h) 2 (40)
Years of experience
Nursing 2.8 (0.8) 3 (2–4)
Aged care 2.4 (0.5) 2 (2–3)
Cognitive impairment/dementia care 2.4 (0.5) 2 (2–3)
Employment in facility 1.6 (0.9) 1 (1–3)
Role in facility
Clinical nurse 1 (20)
Registered nurse 4 (80)
Past pain education
Yes 5 (100)
No 0 (0)
Last received pain education
<3 months 2 (40)
<12 months 1 (20)
>12 months 2 (40)
Familiarity with the APS
Yes 5 (100)
No 0 (0)
APS, Abbey Pain Scale.
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, Basel
DOI: 10.1159/000485377
Reliability
Interrater Reliability (Interrater Agreement)
Overall agreement on the categorical pain scores was excellent w = 0.857; 95% CI:
0.819–0.895). Greater agreement among raters was found during rest (κ = 0.840; p = 0.000)
compared to movement (κ = 0.772; p = 0.000).
Intraclass Correlation Coefficient
As a single measure, the ICC value of the ePAT was excellent (0.904; 95% CI: 0.885–0.921).
During rest, the ICC value was 0.902 (95% CI: 0.872–0.925), while following movement the
ICC was 0.879 (95% CI: 0.843–0.908). Both of these values fall within the “excellent” range.
Internal Consistency
Overall internal consistency (Cronbach’s α) of the ePAT when compared to the APS was
0.950, which is classified as excellent. The α values were greater for movement (α = 0.797)
than for the rest condition (α = 0.766).
Discussion
The findings of this validation study provide further evidence of the psychometric prop-
erties of the ePAT which make it a suitable instrument for the assessment of pain in people
with moderate-to-severe dementia who cannot verbalize pain. The significance of the current
research was to demonstrate the robustness of a previous study and to ensure the repeat-
Number of paired pain
assessments, n (%)
Pearson’s
correlation, r
Rest 204 (51) 0.896
Movement 196 (49) 0.904
Overall 400 (100) 0.911
ePAT, electronic Pain Assessment Tool; APS, Abbey Pain Scale. All
correlation values are significant at the 0.01 level (2-tailed).
15
10
5
20
0
242220181614121086420
Total score (APS)
Total score (ePAT)
Timing
Move
Rest
Table 4. Correlation values
between the ePAT and the APS
under various conditions
Fig. 2. Association between elec-
tronic Pain Assessment Tool
(ePAT) and Abbey Pain Scale
(APS) total scores. Dark-colored
dots: rest; light-colored dots:
movement. One dot may repre-
sent more than one rating score.
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Atee et al.: Psychometric Evaluation of the Electronic Pain Assessment Tool: An
Innovative Instrument for Individuals with Moderate-to-Severe Dementia
www.karger.com/dem
© 2018 S. Karger AG, BaselDOI: 10.1159/000485377
ability of the initial psychometric findings. These are essential criteria for adopting a tool into
clinical practice.
Unsurprisingly, there was a strong positive correlation of the ePAT with standard
assessment of pain (i.e., by the APS) in the RACFs involved in the study. This is because both
scales have a similar construct and conceptual foundation and both measure similar aspects
of pain-related behaviors. Based on the current findings, it seems that the psychometric char-
acteristics of the ePAT have improved, as they have slightly higher correlation values when
compared to previous findings [33]. This is perhaps due to variation in the APS rater samples
between the two studies. In the current study, all APS raters were nurses (with a greater expe-
rience in pain assessment), whereas they were a mix of nurses, health science students, and
care workers in the previous study [33].
The “state-of-the-art” systematic review by Herr et al. [45] set correlation values of
0.4–0.6 as an adequate range for new pain assessment scales for nonverbal populations. The
ePAT had shown excellent concurrent validity under various testing conditions (rest: r =
0.896; movement: r = 0.904). These results are much higher than the recommended range
suggested by Herr et al. [45] and in line with our previous findings [33]. Other pain assessment
tools with good-to-excellent concurrent validity are the Rotterdam Elderly Pain Observation
Scale (REPOS) (0.61–0.75) when compared to the Pain Assessment in Advanced Dementia
(PAINAD) [46], and the Rating Pain in Dementia (RaPID) scale (0.8–0.86) when compared to
the McGill Pain Questionnaire [47]. In our study, the strength of correlation between the ePAT
and the APS was slightly better during movement than at rest. A number of studies on obser-
vational tools (the Checklist of Nonverbal Pain Indicators [CNPI], FACS, Mobilization-Obser-
vation-Behaviors-Intensity Dementia Pain Scale [MOBID], and Pain Behavior Measurement
[PBM]) have shown parallel findings in this regard [48–50].
All pain scores recorded by the ePAT following movement were higher than those under
rest conditions. Similarly, the APS had greater scores observed for each resident under the
same conditions. This is consistent with our previous work [33], which supports that the
ePAT has discriminative properties, i.e., discriminant validity. Out of 28 tools, Lichtner et al.
[27] listed only 8 (the Certified Nurse Assistant Pain Tool [CPAT], CNPI, Discomfort Scale –
Dementia of the Alzheimer’s Type [DS-DAT], Pain Assessment Checklist for Seniors with
Limited Ability to Communicate [PACSLAC], MOBID, APS, Assessment Discomfort in Dementia
[ADD] Protocol, and Behavior checklist) which showed evidence of discriminant validity.
There were also significant differences in mean ePAT and APS scores at rest (treated as
preintervention) and following movement (treated as postintervention), providing support
for the predictive validity. Abbey et al. [37] reported the predictive validity of the APS as a
significant change in mean pain scores before and after interventions.
The properties of reliability were excellent, as demonstrated by the overall values of α, κ,
and ICC. Except for internal consistency (α values), all reliability measurement values were
higher for rest than for movement. This is probably because when a resident is at rest, he/she
has fewer behaviors recorded by raters; hence the raters have a lower chance of disagreement.
Internal consistency is a reliability measure of the correlation of the subscales of an instrument
(i.e., the ePAT) to assess the construct of interest (i.e., pain behaviors). Raters may have
various interpretations as to whether certain behaviors are related to pain or part of neuro-
psychiatric symptoms of dementia. There is an overlap between pain and these symptoms,
and there is evidence to suggest that pain is linked to depressive symptoms in residents with
dementia [51, 52]. Other observational tools with excellent interrater reliability κ values
include the Pain Assessment in Noncommunicative Elderly Persons (PAINE) (0.711–0.999),
RaPID (0.97), DS-DAT (0.61–0.98), and PAINAD (0.72–0.97) [27].
Strengths of this study include the use of blinded rating and blinded knowledge of the
pain management given to reduce learning bias. Prior to the first (paired) rating, a test case
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DOI: 10.1159/000485377
was used to ensure the steps of the study protocol were followed correctly. The vast majority
of assessments were matched under various conditions indicative of rest and movement. The
study was conducted in a real-world clinical environment and without interrupting the work
flow. The statistical analyses of the psychometric data were comprehensive. Important impli-
cations of using this app include (1) automated facial analysis, which has the potential to
improve the process of pain assessment through objective measures, and (2) digital docu-
mentation, which provides a pragmatic approach for use in clinical settings.
This study has similar limitations to those documented in our previous study, such as
sampling bias and reporting bias [33]. Further, cognitive evaluations were based on informant
ratings, which have their own limitations regarding subjectivity. These evaluations were
conducted at various time points prior to commencement of the study. In our sample, the
majority (79.4%) of the residents had severe cognitive impairment, as indicated by their
PAS-Cog scores. Given the fact that the course of dementia has a progressive nature, it is likely
that the cognitive status of all residents (including the remaining 20.6%) may have worsened
since it was last assessed. In addition, the clinical pain assessments were limited to certain
time periods, i.e., the afternoon, and findings may be different if they are performed during
other times.
In conclusion, this study adds further to the body of evidence regarding the psychometric
merits of the ePAT as a valid and reliable tool for the assessment of pain in residents with
moderate-to-severe dementia. Further research on technology and refinements in using the
presence and intensity of facial expressions as a means of fully automating pain assessment
are warranted.
Acknowledgements
The authors want to thank the aged care staff, residents, and their families for their involvement in the
study. Sincere thanks also go to Jenny Lalor for assisting with the statistical analyses.
Disclosure Statement
All authors are shareholders in EPAT Technologies Ltd, which is marketing the ePAT instrument (also
known as PainChekTM). They also have a patent application titled “A pain assessment method and system”
(PCT/AU2015/000501), which is currently under national phase examination since February 2, 2017. M.A.
is a Research Scientist for EPAT Technologies Ltd while serving as a Research Fellow and PhD Candidate with
the School of Pharmacy, Curtin University. K.H. is employed as a consultant by EPAT Technologies Ltd while
serving as an Assistant Professor at University of Pristina, and an Adjunct Senior Lecturer at the School of
Pharmacy, Curtin University. J.D.H. is employed as Chief Scientific Officer of EPAT Technologies Ltd while
serving as a Professor at the School of Pharmacy, Curtin University.
Funding Sources
The original research that led to the development of the ePAT tool is part of a PhD project which was
supported by the Alzheimer’s Australia Dementia Research Foundation (AADRF) through grant funding and
a stipend scholarship. The content of the article is solely the responsibility of the authors and does not neces-
sarily represent the official views of AADRF. The project has been commercialized into a spin-off start-up
company (ePAT Pty Ltd), which has been publicly listed as EPAT Technologies Ltd in the Australian Share
Securities (ASX) since October 2016. This study was sponsored by EPAT Technologies Ltd as part of its appli-
cation to list the ePAT app as a Class 1 medical device with the TGA, and receive the CE mark in Europe. The
ePAT is commercially available as PainChekTM.
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Author Contributions
All authors conceived the idea and designed the study. M.A. conducted the literature search and drafted
the manuscript. All authors reviewed the manuscript. M.A. recruited the patients and collected the data. M.A.
and J.D.H. conducted some statistical analyses and interpreted all results. All authors contributed to and
approved the final version of the manuscript.
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... 12 Assessing pain usually begins with a person's verbal or non-verbal self-report using pain assessment tools but this can be challenging in older patients, consequently, technology-driven pain assessments have been developed to improve pain assessment in these patients. [13][14][15] One such application is PainChek Universal (www.painchek.com), which has sound psychometric validity and reliability and enables better assessment of pain at the point of care for patients whose ability to communicate fluctuates. ...
... PainChek uses automated facial recognition and analysis to identify pain-related facial microexpressions, together with a series of user completed checklists of pain behaviours to produce a pain score. [13][14][15] PainChek has been implemented and evaluated in aged care settings; however, no previous studies have evaluated its effectiveness in an AC setting. [13][14][15][16] Multicomponent interventions involving volunteers for hospitalised older adults improve clinical outcomes, with a reduction in fall rates, incidences of delirium, pain and reduced length of stay. ...
... [13][14][15] PainChek has been implemented and evaluated in aged care settings; however, no previous studies have evaluated its effectiveness in an AC setting. [13][14][15][16] Multicomponent interventions involving volunteers for hospitalised older adults improve clinical outcomes, with a reduction in fall rates, incidences of delirium, pain and reduced length of stay. 17 Volunteer programmes such as the Hospital Elder Life Program (HELP), which includes multicomponent physical, nutritional and cognitive strategies, have been implemented successfully around the world and have been shown to improve quality and effectiveness of care of hospitalised older adults; to maintain cognitive and physical functioning of high-risk older adults throughout hospitalisation; maximise independence at discharge; assist with the transition from hospital to home; and prevent unplanned hospital readmissions. ...
Article
Full-text available
Introduction Hospitalised older adults are prone to functional deterioration, which is more evident in frail older patients and can be further exacerbated by pain. Two interventions that have the potential to prevent progression of frailty and improve patient outcomes in hospitalised older adults but have yet to be subject to clinical trials are nurse-led volunteer support and technology-driven assessment of pain. Methods and analysis This single-centre, prospective, non-blinded, cluster randomised controlled trial will compare the efficacy of nurse-led volunteer support, technology-driven pain assessment and the combination of the two interventions to usual care for hospitalised older adults. Prior to commencing recruitment, the intervention and control conditions will be randomised across four wards. Recruitment will continue for 12 months. Data will be collected on admission, at discharge and at 30 days post discharge, with additional data collected during hospitalisation comprising records of pain assessment and volunteer support activity. The primary outcome of this study will be the change in frailty between both admission and discharge, and admission and 30 days, and secondary outcomes include length of stay, adverse events, discharge destination, quality of life, depression, cognitive function, functional independence, pain scores, pain management intervention (type and frequency) and unplanned 30-day readmissions. Stakeholder evaluation and an economic analysis of the interventions will also be conducted. Ethics and dissemination Ethical approval has been granted by Human Research Ethics Committees at Ramsay Health Care WA|SA (number: 2057) and Edith Cowan University (number: 2021-02210-SAUNDERS). The findings will be disseminated through conference presentations, peer-reviewed publications and social media. Trial registration number ACTRN12620001173987.
... The pain score is automatically calculated by summing the scores of each domain, and then assigned a pain category based on the following scores: 0-6 (no pain), 7-11 (mild pain), 12-15 (moderate pain), and 16-42 (severe pain) (18). These scores were blindly validated against the APS [a valid and reliable pain assessment tool for people with advanced dementia (20)] by a group of assessors (e.g., healthcare professionals) in previous studies (12,21). The association between pain intensity groups of the APS and PainChek R was evaluated using a contingency table. ...
... They were obtained by cross tabulating the raw PainChek R scores against the APS categories, and optimum cutoff scores were obtained in a manner similar to a discriminant analysis (12). The PainChek R pain scale has demonstrated strong psychometric (validity, reliability, internal consistency) and clinimetric (sensitivity, specificity, accuracy) properties in PLWD (12,21,22). ...
... To ascertain the self-reporting capacity of patients, PainChek R users/assessors were also instructed during training/coaching to ask these patients simple questions, such as "Do you have any pain, aching or soreness?" These questioning strategies were also used in previous validation studies of PainChek R prior to its use by assessors and regardless of patient's cognitive level (12,21). Staff training was relevant to their setting and consistent with their scope of practice. ...
Article
Full-text available
Pain is common in people living with dementia (PLWD), including those with limited verbal skills. Facial expressions are key behavioral indicators of the pain experience in this group. However, there is a lack of real-world studies to report the prevalence and associations of pain-relevant facial micro-expressions in PLWD. In this observational retrospective study, pain related facial features were studied in a sample of 3,144 PLWD [mean age 83.3 years (SD = 9.0); 59.0% female] using the Face domain of PainChek®, a point-of-care medical device application. Pain assessments were completed by 389 users from two national dementia-specific care programs and 34 Australian aged care homes. Our analysis focused on the frequency, distribution, and associations of facial action units [AU(s)] with respect to various pain intensity groups. A total of 22,194 pain assessments were completed. Of the AUs present, AU7 (eyelid tightening) was the most frequent facial expression (48.6%) detected, followed by AU43 (closing eyes; 42.9%) and AU6 (cheek raising; 42.1%) during severe pain. AU20 (horizontal mouth stretch) was the most predictive facial action of higher pain scores. Eye-related AUs (AU6, AU7, AU43) and brow-related AUs (AU4) were more common than mouth-related AUs (e.g., AU20, AU25) during higher pain intensities. No significant effect was found for age or gender. These findings offer further understanding of facial expressions during clinical pain in PLWD and confirm the usefulness of artificial intelligence (AI)-enabled real-time analysis of the face as part of the assessment of pain in aged care clinical practice.
... Secondly, the APS is commonly used in the UK and other English speaking countries. Lastly, previous studies in Australia demonstrated the validity and reliability of PainChek® when compared to the APS [19,20,22,30]. ...
... In addition, individuals with facial palsy, facial deformities or who were partially or fully unable to exhibit facial features were excluded. The inclusion and exclusion criteria were based on a previous study [30]. ...
... PainChek® is a Class 1 medical device with a regulatory clearance in Australia (Therapeutic Goods Administration), Europe (CE Mark) Canada (Health Canada) and Singapore (Health Sciences Authority) for the assessment of pain in individuals who are unable to verbalise their pain, such as those living with moderate to severe dementia. It is an observational pain assessment tool which consists of 42 items spread across six domains; namely The Face (n = 9), The Voice (n = 9), The Movement (n = 7), The Behaviour (n = 7), The Activity (n = 4) and The Body (n = 6) [30]. Items included in PainChek® cover all six pain domains recommended by the AGS [21] for accurate and reliable observational pain assessment in people with cognitive impairment (See Table 1). ...
Article
Full-text available
Background The aim of this study was to further validate PainChek®, an electronic pain assessment instrument, with a population living with dementia in a UK care home. Method This study utilised a correlational design to evaluate the psychometric properties of PainChek® when compared to the Abbey Pain Scale (APS). Blinded paired pain assessments were completed at rest and immediately post-movement by a researcher and a nurse. A total of 22 participants with a diagnosis of moderate-to-severe dementia and a painful condition were recruited using opportunity sampling. Results Overall, 302 paired assessments were collected for 22 participants. Out of these 179 were conducted during rest and 123 were immediately post-movement. The results demonstrated a positive significant correlation between overall PainChek® pain scores and overall APS pain scores ( r = 0.818, N = 302, p < .001, one-tailed), satisfactory internal consistency (α = 0.810), moderate single measure intraclass correlation (ICC = 0.680) and substantial inter-rater agreement (κ = 0.719). Conclusions PainChek® has demonstrated to be a valid and reliable instrument to assess the presence and severity of pain in people with moderate-to-severe dementia living in aged care.
... This finding is not surprising and aligns well with previous literature [4 -6]. Thus, the need to use validated facial cues in pain assessment tools [e.g., Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC-II), PainChek ® (formerly known as the electronic Pain Assessment Tool "ePAT")] for this population [7][8][9]. Further, the authors rightly point out the importance of using novel and automated methods in capturing facial expressions of pain in an attempt to improve pain assessment in this population [8,10]. These methods have proven to be effective in recognizing pain with strong psycho- metric and clinimetric properties in people living with dementia [8,[11][12][13]. ...
... Thus, the need to use validated facial cues in pain assessment tools [e.g., Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC-II), PainChek ® (formerly known as the electronic Pain Assessment Tool "ePAT")] for this population [7][8][9]. Further, the authors rightly point out the importance of using novel and automated methods in capturing facial expressions of pain in an attempt to improve pain assessment in this population [8,10]. These methods have proven to be effective in recognizing pain with strong psycho- metric and clinimetric properties in people living with dementia [8,[11][12][13]. ...
... Further, the authors rightly point out the importance of using novel and automated methods in capturing facial expressions of pain in an attempt to improve pain assessment in this population [8,10]. These methods have proven to be effective in recognizing pain with strong psycho- metric and clinimetric properties in people living with dementia [8,[11][12][13]. ...
... A strength of this study is that the DSA service used the PainChek device, a dementiaspecific multidomain pain assessment tool (with strong psychometrics) that combines various technologies such as AI and smart automation. 36,71,72 Although there is an overlap between pain behaviors and BPSD, the device is unique in that it has a pain scale that includes items with clear operational definitions circumventing any ambiguity associated with interpretation during assessments. 72 Despite that, we cannot rule out completely that some neuropsychiatric symptoms (e.g., agitation) were misinterpreted as pain behaviors. ...
... Unlike other observational pain scales, PainChek assigns pain intensity categories (no pain, mild pain, moderate pain, and severe pain) into a final score based on validated cutoff scores. 35,71 Given the subjective nature of pain, we acknowledge that the relationship between pain behaviors and intensity of pain is not fully understood. However, there is evidence that the number of pain behaviors observed is positively correlated with pain intensity. ...
... 82 Yet, this was possibly minimized in our study by the familiarity of consultants with residents' behaviors and the use of a robust, systemized, and structured pain assessment, which was validated in RACHs. 35,36,71,83 This assessment puts less emphasis on changes in physiological indicators (e.g., temperature) because these can be influenced by confounders (e.g., medications) and may be blunt and less useful in mild-moderate or chronic pain, particularly in those with AD. 36,84e87 Clinical Implications ...
Article
Full-text available
Context: Pain is linked to behaviours and psychological symptoms of dementia (BPSD); however, it often remains under-recognised in this population. Objectives: We aimed to investigate the prevalence and intensity of pain in people living in aged care homes with BPSD and by dementia subtypes, and the association between pain intensity and specific BPSD. Methods: A 1-year retrospective cross-sectional analysis was conducted on BPSD and the presence of pain in referrals to a national BPSD support service using the Neuropsychiatric Inventory (NPI) and PainChek®, respectively. Referrals were categorised into two groups: Pain group and No Pain group. Results: Of the 479 referrals (81.9 ± 8.3 years old) included in the analysis, two-thirds (65.6%) had pain identified with almost half (48.4%) of these categorised as experiencing moderate-severe pain. Pain was highly prevalent (range: 54.6-78.6%) in all subtypes of dementia, particularly in mixed dementia and DLB. Compared to the No Pain group, the Pain group had 25.3% more neuropsychiatric behaviours, 33.6% higher total severity of these behaviours, and 31.4% higher total distress caused to caregivers. For all results, effect sizes were small to medium (η²p = 0.04-0.06). Despite a high prevalence of aggressive or agitated behaviours across the entire group, the Pain group was 3.8 times more likely to experience these behaviours compared to referrals not in pain. Conclusion: There is a strong need to consider the possibility of pain as a contributor to behavioural changes in aged care residents living with dementia.
... Pain was assessed using PainChek ® , a valid and reliable regulatory cleared pain assessment medical device in the form of a point-of-care app for people living with cognitive impairment including those living with dementia (Atee et al., 2017a(Atee et al., , 2018. The app has a 42-item pain scale that are distributed over six domains: Face (9 items), Voice, (9 items), Movement (7 items), Behaviour (7 items), Activity (4 items) and Body (6 items). ...
... PainChek ® scores above 6 (i.e. ⩾7) indicate the presence of pain (Atee et al., 2017a(Atee et al., , 2017b(Atee et al., , 2018. ...
Article
Objective Younger-onset dementia accounts for about 5–10% of all dementias in Australia. Little data is available on neuropsychiatric symptoms in people with younger-onset dementia compared to those with older-onset dementia. This study aims to compare the types of neuropsychiatric symptoms and their clinico-demographic characteristics of people with younger-onset dementia and older-onset dementia who are referred to a specific dementia support service. Methods A 2-year retrospective observational cross-sectional analysis was undertaken on referrals with neuropsychiatric symptoms from Dementia Support Australia programmes. Neuropsychiatric symptoms were measured using the Neuropsychiatric Inventory total severity scores and distress scores. Contributing factors to neuropsychiatric symptoms for dementia groups were examined. Logistic regression was used to examine the relationship between individual neuropsychiatric symptoms and having older-onset dementia vs younger-onset dementia. Results Of the 15,952 referrals, about 5% ( n = 729, mean age: 60.7 years, standard deviation = 5.4) were individuals with younger-onset dementia. Referrals with older-onset dementia were more likely to be female (56%), whereas referrals with younger-onset dementia were more likely to be male (54%). There was a four times greater rate of frontotemporal dementia for those with younger-onset dementia (16.0%, n = 117) compared to those with older-onset dementia (2.8%, n = 427), χ ² (1) = 366.2, p < 0.001. Referrals with younger-onset dementia were more likely to be referred from community settings and those with older-onset dementia were more likely to be from residential aged care. Overall, there was no difference in the severity and distress of neuropsychiatric symptoms between the two groups. Contributing factors to neuropsychiatric symptoms were different between the groups, with pain being more frequently endorsed for individuals with older-onset dementia whereas communication difficulties were more commonly identified for those with younger-onset dementia. Conclusion Clinico-demographics of referrals with younger-onset dementia differ from those with older-onset dementia. There were some differences in the characteristics of neuropsychiatric symptoms between younger-onset dementia and older-onset dementia. Our findings have implications for service provision and support for people with dementia at different ages.
... 44 45 Based on a number of clinical studies (total participants n=74, 753 paired pain assessments) the PainChek application has demonstrated sound psychometric validity and reliability and clinical utility in people with moderate-to-severe dementia. [44][45][46][47] The prevalence of pain has not previously been assessed across an entire hospital using a technology driven assessment of pain. The use of such a device would allow data to be collected from all participants including those unable to provide a reliable self-report rating of their pain. ...
... Both the mod-REFS and PainChek were developed for use by non-health professionals. Evidence from previous studies found excellent inter-rater reliability, on the REFS when administered by two non-medically trained research scientists, 19 and PainChek when administered by nurses trained to administer the assessment, 46 which suggests a single assessment of each patient is sufficient. ...
Article
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Introduction Frailty and pain are associated with adverse patient clinical outcomes and healthcare system costs. Frailty and pain can interact, such that symptoms of frailty can make pain assessment difficult and pain can exacerbate the progression of frailty. The prevalence of frailty and pain and their concurrence in hospital settings are not well understood, and patients with cognitive impairment are often excluded from pain prevalence studies due to difficulties assessing their pain. The aim of this study is to determine the prevalence of frailty and pain in adult inpatients, including those with cognitive impairment, in an acute care private metropolitan hospital in Western Australia. Methods and analysis A prospective, observational, single-day point prevalence, cross-sectional study of frailty and pain intensity of all inpatients (excluding day surgery and critical care units) will be undertaken. Frailty will be assessed using the modified Reported Edmonton Frail Scale. Current pain intensity will be assessed using the PainChek smart-device application enabling pain assessment in people unable to report pain due to cognitive impairment. Participants will also provide a numerical rating of the intensity of current pain and the worst pain experienced in the previous 24 hours. Demographic and clinical information will be collected from patient files. The overall response rate of the survey will be reported, as well as the percentage prevalence of frailty and of pain in the sample (separately for PainChek scores and numerical ratings). Additional statistical modelling will be conducted comparing frailty scores with pain scores, adjusting for covariates including age, gender, ward type and reason for admission. Ethics and dissemination Ethical approval has been granted by Ramsay Health Care Human Research Ethics Committee WA/SA (reference: 2038) and Edith Cowan University Human Research Ethics Committee (reference: 2020–02008-SAUNDERS). Findings will be widely disseminated through conference presentations, peer-reviewed publications and social media. Trial registration number ACTRN12620000904976.
... Further efforts must be undertaken to promote their use in daily care practice as they guide attention to valid pain-related expressions and provide more objective assessments. The development of electronic assessment tools offers also promising perspectives for the improvement of pain management in people with dementia (Atee et al., 2017). ...
Article
Introduction Pain of nursing homes residents with Alzheimer’s disease remains under detected compared to their cognitively intact counterparts. Communication difficulties may partly explain this poor quality of care but the influence of stigmatization on pain assessment has never been explored. Research question The objective of this research was to analyze whether a diagnosis label of Alzheimer’s disease or the stage of the disease may bias pain assessment scores and empathic reactions of health care staff in nursing homes. Methods Two studies were conducted based on a similar experimental between-subjects design with a video showing an older adult woman experiencing undefined pain. Different labels and vignettes were manipulated to characterize the subject of the video. In the first study, 84 certified nursing assistants were asked to watch the video and then to assess the pain intensity and their empathic reaction. Participants were randomized in two conditions that varied the disease label (Alzheimer’s disease vs no diagnosis). In the second study, 67 certified nursing assistants were enrolled who did not participate in the first study. They watched the same video as in the first study and assessed the pain intensity and their empathic reaction. They were randomized in two conditions that varied the stage of the Alzheimer’s disease (mild stage vs severe stage). Results Alzheimer’s disease label had no influence on assessment scores. In contrast, the stage of the disease had a significant effect on the health care staff assessments with severe stage associated with lower pain intensity scores and empathic reactions. Conclusion These results confirm that the Alzheimer’s disease stigma is a real phenomenon that tends to be mainly elicited by the symptoms of the acute phase of the disease. These findings are crucial to better understand the stigma related to Alzheimer’s disease and to enhance the pain management of this frail population.
... In a study with 353 paired assessments across 40 residents of aged care homes in Perth using both PainChek and the Abbey Pain Scale (as ground truth), they found their system had a good concurrent validity with r=0.882. A follow up study with geriatric residents showed similar results [28]. Despite the good match between human raters and the system based on automatic FACS and human input, the study did not decompose the results to a level to know how well a fully automatic face-only approach would work. ...
Preprint
Managing post-surgical pain is critical for successful surgical outcomes. One of the challenges of pain management is accurately assessing the pain level of patients. Self-reported numeric pain ratings are limited because they are subjective, can be affected by mood, and can influence the patient's perception of pain when making comparisons. In this paper, we introduce an approach that analyzes 2D and 3D facial keypoints of post-surgical patients to estimate their pain intensity level. Our approach leverages the previously unexplored capabilities of a smartphone to capture a dense 3D representation of a person's face as input for pain intensity level estimation. Our contributions are adata collection study with post-surgical patients to collect ground-truth labeled sequences of 2D and 3D facial keypoints for developing a pain estimation algorithm, a pain estimation model that uses multiple instance learning to overcome inherent limitations in facial keypoint sequences, and the preliminary results of the pain estimation model using 2D and 3D features with comparisons of alternate approaches.
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Pain is common among people with moderate to severe dementia, but inability of patients to self-report means it often goes undetected and untreated. We developed the electronic Pain Assessment Tool (ePAT) to address this issue. A point-of-care App, it utilizes facial recognition technology to detect facial micro-expressions indicative of pain. ePAT also records the presence of pain-related behaviors under five additional domains (Voice, Movement, Behavior, Activity, and Body). In this observational study, we assessed the psychometric properties of ePAT compared to the Abbey Pain Scale (APS). Forty aged care residents (70% females) over the age of 60 years, with moderate to severe dementia and a history of pain-related condition(s) were recruited into the study. Three hundred and fifty-three paired pain assessments (either at rest or post-movement) were recorded and analyzed. The ePAT demonstrated excellent concurrent validity (r = 0.882, 95% CI: 0.857-0.903) and good discriminant validity. Inter-rater reliability score was good overall (weighted κ= 0.74, 95% CI: 0.68-0.80) while internal consistency was excellent. ePAT has psychometric properties which make it suitable for use in non-communicative patients with dementia. ePAT also has the advantage of automated facial expression assessment which provides objective and reproducible evidence of the presence of pain.
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Background: Pain is associated with depression in nursing home patients with dementia. It is, however, unclear whether pain increases depression. Therefore we evaluated the prospective associations between pain and depressive symptoms in nursing home patients at different stages of cognitive impairment. Methods: Two longitudinal studies were combined, including 931 patients (≥65 years) from 65 nursing homes. One study assessed patients at admission, with 6-month follow-up (2012-2014). The other study assessed residents with varying lengths of stay, with 4-month follow-up (2014-2015). Patients were assessed with the Mini-Mental State Examination, the Mobilisation-Observation-Behaviour-Intensity-Dementia-2 Pain Scale, and the Cornell Scale for Depression in Dementia. Results: At baseline, 343 patients (40% of 858 assessed) had moderate to severe pain, and 347 (38% of 924) had depression. Pain increased the risk of depression (OR 2.35, 95% CI 1.76-3.12). Using mixed model analyses, we found that a 1-point increase in pain was associated with a .48 increase in depression (p<.001). This association persisted in mild, moderate, and severe cognitive impairment. In those recently admitted, depressive symptoms decreased over time, and having less pain at follow-up was associated with a decrease in depressive symptoms (within-subject effect; p=.042). Limitations: The two cohorts had different inclusion criteria, which may reduce generalisability. The study design does not allow conclusions on causality. Conclusions: Pain and depressive symptoms are associated in patients with dementia. Because reduced pain is associated with less depressive symptoms, these patients should be assessed regularly for untreated pain. The benefit of analgesic treatment should be weighed carefully against the potential for adverse effects.
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Background/Aims Many variables influence the quality of life in older adults with dementia. We aim to quantify how the relationship between pain and quality of life in nursing home residents with severe dementia can be explained by neuropsychiatric symptoms, depressive symptoms, and activities of daily living. Methods This article presents cross-sectional baseline data from a cluster randomised controlled trial. Results The total and direct effects of pain on quality of life were statistically significant. Both neuropsychiatric and depressive symptoms partially mediated the relationship between pain and quality of life. Activities of daily living acted as a mediator only when modelled together with depressive symptoms. Conclusion Pain, neuropsychiatric symptoms, and depressive symptoms appear to be important factors that influence the quality of life for nursing home residents with severe dementia. Therefore, multidimensional interventions may be beneficial for maintaining or improving quality of life in this population.
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BACKGROUND: To determine which characteristics are associated with quality of life (QOL) in residents with moderate to very severe dementia in long-term care facilities (LTCFs). MATERIAL AND METHODS: This was a cross-sectional analysis of a cluster randomized controlled study in 12 Dutch LTCFs that enrolled 288 residents, with moderate to severe dementia assessed with the Reisberg Global Deterioration Scale (Reisberg GDS) and QOL with the QUALIDEM. Characteristics that were hypothesized to be associated with the six domains of QOL (applicable to very severe dementia) included demographic variables, activities of daily living (Katz ADL), cognitive performance (Cognitive Performance Scale; CPS), pain (Pain Assessment Checklist for Seniors with Limited Ability to Communicate; PACSLAC-D), neuropsychiatric symptoms (Neuropsychiatric Inventory-Nursing Home Version; NPI-NH) and comorbidities. RESULTS: Multivariate logistic regression modelling showed associations with age in the domain Social isolation [odds ratio, OR, 0.95 (95% confidence interval, CI, 0.91-0.99)], ADL level in the domain Positive affect [OR 0.89 (95% CI 0.83-0.95)] and the domain Social relations [OR 0.87 (95% CI 0.81-0.93)], severity of dementia in the domain Social relations [OR 0.28 (95% CI 0.12-0.62)] and in the domain Social isolation [OR 2.10 (95% CI 1.17-3.78)], psychiatric disorders in the domain Positive affect [OR 0.39 (95% CI 0.17-0.87)] and pulmonary diseases in the domain Negative affect [OR 0.14 (95% CI 0.03-0.61)] of the QUALIDEM. Neuropsychiatric symptoms were independently associated with all six domains of the QUALIDEM [OR 0.93 (95% CI 0.90-0.96) to OR 0.97 (95% CI 0.95-0.99)]. Pain was associated with the domains Care relationship [OR 0.92 (95% CI 0.84-1.00)] and Negative affect [OR 0.92 (95% CI 0.85-1.00)]. CONCLUSION: QOL in dementia is independently associated with age, ADL, dementia severity, pain, psychiatric disorders, pulmonary diseases and neuropsychiatric symptoms. It is possible to detect persons with dementia at risk for a lower QOL. This information is important for developing personalized interventions to improve QOL in persons with dementia in LTCFs.
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Background: Numerous studies have reported on pain in dementia. It has been hypothesized that pain perception differs between dementia subtypes, and therefore, the prevalence of pain differs between dementia subtypes. However, there remains a paucity of evidence on the differences in the prevalence of pain in different dementia subtypes. This review aimed to determine the prevalence of pain for the major dementia subtypes: Alzheimer's disease (AD), vascular dementia (VaD), frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB). Summary: We found 10 studies that met our inclusion criteria. Most of these studies reported on AD; studies reporting the prevalence of pain in people with DLB were scarce, and for FTD, we found no studies. The sample-weighted prevalence of pain could only be calculated for AD, VaD and mixed dementia: AD 45.8% (95% confidence interval, CI: 33.4-58.5%), VaD 56.2% (95% CI: 47.7-64.4%) and mixed dementia 53.9% (95% CI: 37.4-70.1%). Key messages: Studies investigating the prevalence of pain in dementia subtypes were scarce; however, we found a high prevalence of pain in dementia without significant differences between the dementia subtypes. More studies are required to draw firm conclusions on the differences in the prevalence of pain between dementia subtypes.
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Background/aims: Prior studies have shown that patients with dementia are at risk of receiving insufficient treatment for pain after a hip fracture. We therefore hypothesized that elderly hip fracture patients with dementia received less postoperative pain treatment than those without dementia. Method: All patients (age ≥65 years) who had been operated on for a hip fracture in the Copenhagen University Hospital region in 2009 were included. Data about analgesic use for the first 72 h after surgery were acquired from the hospitals' electronic medication system and linked with information about dementia, comorbidity, and prior drug use. Results: A total of 1,507 patients were included, of which 296 (19.6%) suffered from dementia. Both groups were equally likely to receive paracetamol and opioids. Patients with dementia received lower doses of oral morphine equivalents during the first [dementia vs. no dementia: 29.0 (26.4-31.8) vs. 34.7 (33.1-36.4) mg, p = 0.001] and second [27.8 (25.4-30.5) vs. 31.2 (29.9-32.4) mg, p = 0.019] but not on the third postoperative day (p = 0.10). Conclusion: The lower doses of opioids may reflect uncertainty about how to treat pain patients with dementia. Further guidance is needed, as inadequate treatment of pain may have adverse consequences.
Article
Background: Many studies have investigated factors associated with quality of life (QoL) in nursing home residents with dementia. Both pain and neuropsychiatric symptoms (NPS) are clinically relevant and individually associated with a lower QoL; however, there are no studies that investigated pain and NPS together in relation to QoL. Purpose: In this study, we explored the relationship of pain and NPS with QoL in nursing home residents with dementia by investigating the association between pain concurrently with NPS, and QoL. Methods and patients: Secondary data analyses of cross-sectional data from 199 residents were collected by observations at dementia special care units of 10 nursing homes. QoL was measured with Qualidem, pain with the Mobilization Observation Behavior Intensity Dementia (MOBID-2) Pain Scale and NPS with the Neuropsychiatric Symptoms Inventory. The relation of pain and NPS to QoL was studied using multiple linear regression analyses. Analyses were adjusted for age, sex, activities of daily living, comorbidity, medication use, and dementia severity. Results: Regression models with pain and NPS, showed no independent relationship between pain and QoL subdomains, but NPS, in particular agitation and depressive symptoms, were significantly associated with lower QoL subdomain scores. Agitation was related to lower scores on the subdomains "relationship" [95% confidence interval (CI), -0.083 to -0.059], "positive affect" (95% CI, -0.037 to -0.013), "restless tense behavior" (95% CI, -0.003 to -0.004), and "social relations" (95% CI, -0.033 to -0.009), whereas depression was related to lower scores on the subdomains "positive affect" (95% CI, -0.054 to -0.014), "negative affect" (95% CI, -0.114 to -0.074), "restless tense behavior" (95% CI, -0.075 to -0.025), and "social relations" (95% CI, -0.046 to -0.002). Conclusions: Only NPS were significantly associated with QoL in nursing home residents with dementia. Further longitudinal research is needed to estimate the nature of the relationship between pain, NPS, and QoL.
Article
Aim: To validate a Danish version of the observational Abbey Pain Scale (APS) in a geriatric ward. Material and methods: The study population consisted of 50 old patients (70+ years), consecutively admitted to the geriatric wards of Aarhus University Hospital, Denmark, and fulfilling one of the following inclusion criteria: Mini Mental State Examination (MMSE) < 5, delirium, non-communicative aphasia, or unconsciousness. APS has six subscales and ranges from 0 (no pain) to 18 (worst pain). Criterion validity was assessed by using Verbal Rating Scale (VRS) as the gold standard. Cohen's kappa (k) was the measure of agreement. Inter-rater reliability was measured by two independent ratings of the same patient at the same time and assessed by Intraclass Correlation Coefficient (ICC). Internal consistency between the subscales was analysed by Cronbach's Alpha. Responsiveness was tested if the first APS score was positive for pain. 'Before' and 'after' sum scores were compared by paired t-test. Results: We found poor agreement between APS and VRS (k=0.42). The inter-rater reliability was good (ICC=0.84). Cronbach's Alpha was 0.52 (fair agreement). In 66% of the patients, pain was observed and re-tested when an expected effect of analgesics had occurred. Of these, 88% reached a reduction on the APS sum-score (p<0.001). Conclusion: Our assessment of the Danish version of APS shows that this pain assessment scale should be considered as qualified and usable in severely demented and non-communicative older patients admitted to a geriatric ward.
Article
Background: The key factor to improving pain management for cognitively impaired elderly patients is accurate pain assessment. Behavioural-observation methods are required for individuals who cannot communicate their pain verbally. A thorough understanding of the key components of behavioural pain assessment and the use of valid and reliable behavioural pain assessment tools would enhance the assessment of pain in this vulnerable population. Objectives: To identify the key components involved in behavioural pain assessment in cognitively impaired elderly people and to analyse the reported psychometric properties, feasibility and utility of behavioural pain assessment tools. Selection criteria: Studies using descriptive, correlation and comparative designs were included.Cognitively impaired elderly people older than 65 years in aged care, acute care or nursing home settings were included.Components measured in behavioural pain assessment; psychometric properties, feasibility and utility of behavioural pain assessment tools used to assess pain in cognitively impaired elderly people in acute or long-term care settings.Identification of behavioural criteria for assessment of pain and investigation of any aspect of the psychometric properties of behavioural pain assessment tools. Search strategy: An initial limited search of MEDLINE and CINAHL to find published studies between 1990 to 2010 in the English Language was undertaken, following an analysis of the text words contained in the title and abstract. A second search using all identified keywords and index terms was undertaken and extended to a further seven relevant databases. Thirdly, the reference lists of all identified reports and articles were searched for additional studies. Methodological quality: Studies selected for retrieval were assessed for inclusion by two independent reviewers for methodological validity using the Critical Appraisal Tool for Psychometric Studies adapted from Fallon, Westaway, and Moloney1. Data extraction: Quantitative data were extracted from included studies using the Data Extraction Tool for Psychometric Studies adapted from Fallon, Westaway, and Mahoney1. Data synthesis: As statistical pooling was not possible, evidence in relation to psychometric properties, was analysed and presented in narrative summary. Results: Twenty three studies were included in the review. No tool has been found suitable for use across both acute and long-term care settings. Nevertheless, three tools show the most promising outcomes and potential for use. Conclusions: Although behavioural measures may inform healthcare providers on the presence of pain in an individual, they do not provide information about the aetiology of pain. Hence, pain assessment should not depend solely on behavioural observation conducted using standardised behavioural pain assessment tools, but regarded as an essential component of a multifaceted approach to pain assessment. Clinicians may select tools which show promising qualities and pilot them in their respective clinical settings and populations. In particular, the MPS, the PACSLAC and the PAINAD are recommended for potential use in the cognitively impaired elderly in acute and long-term care settings.Several tools show promise for use in acute or long-term care settings. These tools require tool revisions to strengthen their psychometric properties. Instead of developing new tools, modification of existing tools and conducting further psychometric evaluations on them can provide more evidence of their psychometric properties.
Article
Background: Dementia-related societies worldwide have called for palliative end-of-life care for those suffering dementia; meanwhile, the Japanese dementia plan was revised on January 2015 to introduce into its objectives the support for end-of-life care via increased social and health care collaboration. Objective: The study focus was the use of medical procedures in the last month of life among dementia patients in different care locations in Japan. Methods: This study was conducted using a retrospective study design. Data from the Survey of Institutions and Establishments for Long-Term Care, which is a nationally representative cross-sectional survey of the public long-term care insurance services, were used. The 6,148 patients who received end-of-life care in their own home, nursing homes, or hospitals in September 2007, 2010, and 2013 were included for analysis. The primary disease of each patient was based on the ICD-10 code; a diagnosis of dementia included F00 (Alzheimer's), F01 (vascular), F02 (other), and F03 (unspecified). Results: Of 6,148 patients, 886 (14.4%) had dementia as a primary disease; most received care in the last month of life in nursing homes (48.0%) or hospitals (44.8%) rather than in their own home (7.2%). Patients were less likely to undergo pain management when their primary disease was dementia (adjusted odds ratio, 0.44; 95% confidence interval, 0.21-0.91). Conclusion: Education and policy efforts are required to provide palliative end-of-life care to people with dementia at home. The national dementia plan should also explore possible approaches regarding pain management for dying people who have dementia.