Developing a Mood Scale Suitable
for Use with Aphasic Stroke Patients
Paul Barrows
Stroke
Incidence & Prevalence
• In England and Wales it is estimated that 130,000
people have a stroke every year (Office for National
Statistics, 2001).
• There are over 1.1 million people living with stroke in
the UK, but by 2020 it is expected to double, mainly
due to the increasing proportion of older people
(Scarborough et al., 2009).
Stroke
Mortality
• After heart disease and cancer, stroke is the third
most common cause of death in the UK and
worldwide (Warlow et al., 2003)
• Stroke is responsible for over 60,000 deaths annually
in the UK. (The Stroke Association, 2006)
• Over the last decade, stroke has accounted for an
average of around 7.5% of deaths in men and 10% of
deaths in women (Office for National Statistics,
2010).
Stroke
Outcome
• Of those people who have a stroke, about third are
likely to die within the first ten days, about third can
be expected to make a recovery within one month
and about a third will likely be left severely disabled
(Bosanquet & Franks, 1998).
Depression after Stroke
Approximately one third of stroke survivors suffer from
poststroke depression (PSD) (Hackett et al., 2005).
This can lead to:
• Increased morbidity and mortality
• Poorer outcomes in recovery of physical and
cognitive function
• Impeded recovery and longer hospital stays
• Increased caregiver stress.
Depression after Stroke
Clinical guidelines recommend screening of stroke
patients, and assessment of those identified as at
risk of depression (The Royal College of Physicians,
2012).
Measuring Mood in Stroke Patients
Though many measures of depression and low mood
exist, stroke offers challenges to assessing patients for
co-morbid mental health problems.
Assessment of mood in this group is problematic
because:
• Mood states are often masked or mimicked by
neurological consequences of stroke, such as
dysprosodia and dyspraxia
• Impaired language and cognition – commonly in the
form of aphasia – makes assessment by self-report
measures problematic.
Exclusion of Aphasic Stroke Patients in Studies
• A study of adaptations to measuring depression in
stroke patients with aphasia revealed that 63% of
studies examining PSD excluded patients whose
aphasia was too severe for them to be amenable to
standard measures (E. Townend et al., 2007)
• Hackett and Anderson (2005) report that only 3 of 20
studies they reviewed in which predictors of PSD were
examined included aphasia as a potential risk factor.
This underlines an overwhelming tendency for
patients with communication impairments to
simply be omitted from such studies.
Stroke, Depression & Aphasia
Aphasia affects around 20–38% of stroke patients
(E.Townend et al., 2007).
• One of the two most important predictors of immediate
major depression is aphasia (p<0.001) (Astrom et al.,
1993)
• “Communication impairment was the greatest predictor
of depression severity and prognosis” (Thomas &
Lincoln, 2006)
• Two-thirds of patients with aphasia met the DSM-III-R
criteria for depression in the first year following stroke, a
figure that was significantly higher than in those without
aphasia (Kauhanen et al., 2000).
Measuring Mood in Stroke Patients
Observer-Rated
• Poststroke Depression
Rating Scale (PSDS)
(Gainotti et al., 1997)
• Stroke Aphasic Depression
Rating Scale (SADQ H10/21)
(Sutcliffe & Lincoln, 1998)
• Aphasic Depression Rating
Scale (ADRS) (Benaim et al.,
2004).
Self-Report
• Visual Analogue Mood
Scales (VAMS) (Stern et al.,
1997)
• Visual Analogue Self Esteem
Scales (VASES) (Brumfitt &
Sheeran, 1999)
• Depression Intensity Scale
Circles (DISCS) (TurnerStokes et al., 2005).
Need for Screening Measures
There is evidence to suggest that observer-rated
scales like the SADQ-H10 and the ADRS are of clinical
use (Bennett et al. 2006; Hacker et al., 2010; Benaim
et al. 2010). However self-report measures have
proven more problematic.
There is therefore a need for self report screening
tools that can more accurately assess patients in
the stroke population, particularly those with
communication difficulties.
Visual Analogue Self-Esteem Scale (VASES)
Brumfitt & Sheeran (1999) created a 10 item, self-esteem
scale for use with aphasic patients. It is made up of 10 pairs
of bipolar pictures of concepts related to self-esteem, which
are judged on a 5-point Likert scale below them. Often used
as an indirect indicator of depression.
Brumfitt & Sheeran (1999)
The Depression Intensity Scale Circles
(DISCs)
Essentially a Likert Scale, but
using black disks of increasing
size to enable cognitively
impaired patients to quantify
their mood state more easily.
Turner-Stokes et al. (2005)
Visual Analogue Mood Scales (VAMS)
Stern et al. (1997) developed a set of 8
VAS-based mood scales in pictographic
form.
Happy, Sad, Energetic, Tired, Angry,
Afraid, Tense, Confused.
Each is comprised of two cartoon faces
at either end of a 100mm line. The user
indicates their mood by making a mark
along the length of the line.
VAMS ‘Sad’ Item
Visual Analogue Mood Scales (VAMS)
VAMS validated in several populations, including stroke
and dementia patients (Stern et al. 1997; Arruda et al.
1999; Temple 2004). However:
• Researchers report patients being ‘bewildered’ by the
VAMS (Townend et al., 2007).
• Though VAMS offers a broad measure of severity of
depression, it is of little use as a screening instrument
(Bennett et al., 2006)
• “The use of Visual Analogue Mood Scales amongst
patients with aphasia {...} cannot be recommended.”
(Berg et al., 2009).
Visual Analogue Mood Scales (VAMS)
• Typically, studies use only a single VAMS scale – the
‘sad’ item – to assess mood
• VAMS are separate, single-item scales, so a combined
total score is not possible
• VAMS not underpinned by any theory of mood
• Evidence suggests that stroke patients with cognitive
impairments cannot use VASs effectively (Price et al.,
1999).
Addressing Limitations of VAMS
Cartoon faces
used to
denote affect
Poor realism
Use photos
of human
faces
1a. Using Photos Of Human Faces
Why use Human Faces?
VAMS ‘Sad’ Item
Study Participant
• Facial expression is arguably the most
powerful, universal communicator of
mood states (Ekman, 1971, 1993)
• Photographs of actual emotional
expressions offer a more nuanced,
detailed and accurate portrayal of
mood states
• “...use of realistic looking pictures {...}
may usefully support communication
about mood with people with
aphasia”– Townend et al (2007)
1b. Using Photos Of Human Faces
Why use Human Faces?
• Aphasia can impact upon a person’s ability to decode
symbols, such as those in written language, and this
may also affect their ability to recognise such graphics
• Evidence suggests that recognition of emotion in
facial expressions occurs primarily in the right
hemisphere (Adolphs et al., 1996; Philippi et al. 2009).
Most aphasic patients have left hemisphere lesions,
therefore affect recognition in faces is unlikely to be
affected.
Addressing Limitations of VAMS
Cartoon faces
used to
denote affect
Poor realism
Use photos
of human
faces
Scales
separate and
unconnected
No
underlying
theory
Adopt explicit
structural
theory
2a. Explicit Structural Theory
The Valence-Activation Model of Affect
Larsen & Diener (1992)
2b. Explicit Structural Theory
Using Scales Across 2-factor Affect Space
Larsen & Diener (1992)
2b. Explicit Structural Theory
Using Scales Across 2-factor Affect Space
2b. Explicit Structural Theory
Using Scales Across 2-factor Affect Space
2b. Explicit Structural Theory
Using Scales Across 2-factor Affect Space
2b. Explicit Structural Theory
Using Scales Across 2-factor Affect Space
Addressing Limitations of VAMS
Cartoon faces
used to
denote affect
Poor realism
Use photos
of human
faces
Scales
separate and
unconnected
No
underlying
theory
Adopt explicit
structural
theory
VAS requires
cognitive
interpolation
Cognitively
impaired can
not use VASs
Adopt explicit
graphical
interpolation
Cognitive Interpolation
Reference
State
?
Explicit Interpolation
Dynamic Visual Analogue Scale (DVAS)
Reference
State
A slider control dynamically
animates a picture to
explicitly anchor points of the
scale to transitional images
Explicit Interpolation
Dynamic Visual Analogue Scale (DVAS)
Reference
State
A slider control dynamically
animates a picture to
explicitly anchor points of the
scale to transitional images
Explicit Interpolation
Dynamic Visual Analogue Scale (DVAS)
Reference
State
A slider control dynamically
animates a picture to
explicitly anchor points of the
scale to transitional images
Explicit Interpolation
Dynamic Visual Analogue Scale (DVAS)
Reference
State
A slider control dynamically
animates a picture to
explicitly anchor points of the
scale to transitional images
Explicit Interpolation
Dynamic Visual Analogue Scale (DVAS)
Reference
State
A slider control dynamically
animates a picture to
explicitly anchor points of the
scale to transitional images
Addressing Limitations of VAMS
Cartoon faces
used to
denote affect
Poor realism
Use photos
of human
faces
Scales
separate and
unconnected
No
underlying
theory
Adopt explicit
structural
theory
VAS requires
cognitive
interpolation
Cognitively
impaired can
not use VASs
Adopt explicit
graphical
interpolation
Study 1
Part 1 – Producing aObjectives
Suitable Set of Photographs
1. To select and test a pool of mood words for their
ability to evoke recognisable facial expressions,
based on which a smaller pool of candidate
descriptors will be selected for further study
2. To confirm that judgments of facial expression are
consistent with a two-factor, circumplex model of
affect, and to establish a coordinate system for
mood words and corresponding expressions
3. To identify ‘actors’ who are good at producing
recognisable facial expressions, and whose photos
may be candidates for the final scales.
Study 1
Part 1 – Producing
of Photographs
Studya 1Suitable
- Three Set
Parts
1. Producing a suitable set of photographs
representing a range of candidate mood words
2. Judging the photographs
3. Eliminating weaker items, and identifying candidate
mood words/faces for the final scales
Study 1
Part
Part 11 –– Producing
Producing aa Suitable
Suitable Set
Set of
of Photographs
Photographs
Participants
Gender: 10 male, 10 female (n=20)
Age: mean 20.6 years; S.D. = 1.7 years
English: 12 (60%) spoke English as a first language, 8
(40%) spoke English fluently as a second language.
Ethnicity: 12 (60%) were ethnically European, 6 (30%)
were Asian or East Asian and 2 (10%) were of African
descent.
Study 1
Part
Part 11 –– Producing
Producing aa Suitable
Suitable Set
Set of
of Photographs
Photographs
Methods
Recruitment: Advertisements posted about University
of Nottingham and Community Centres
Selection criteria: >18 years; fluent in English; have no
facial hair, tattoos; capable of posing facial
expressions
Incentive: £10 for session up to approx 1 hour
Task: Participants photographed posing expressions
based on 26 mood words.
Study 1
Part
Part 11 –– Producing
Producing aa Suitable
Suitable Set
Set of
of Photographs
Photographs
Methods
Stimulus words
26 mood words from
previous research in
the area which:
1) span circumplex
well, 2) represent
persistent mood
states, and 3) include
items used in VAMS.
Study 1
Part
Part 11 –– Producing
Producing aa Suitable
Suitable Set
Set of
of Photographs
Photographs
Results
Photographs: Total of 1,560 photographs taken of 20
‘actors’ posing 26 mood states (3 photos each).
Pre-screening: ‘Best of three’ task independently
completed by experimenter and 2 staff. 520 (20 x 26)
photographs selected for final pool.
Study 1
Part
Part 11 –– Producing
Producing aa Suitable
Suitable Set
Set of
of Photographs
Photographs
Results
26 Posed
Moods
Pleased
Happy
Excited
Energetic
Enthusiastic
Aroused
Afraid
Anxious
Tense
Angry
Nervous
Confused
Sad
Distressed
Miserable
Disappointed
Depressed
Bored
Tired
Sleepy
Relaxed
Content
Peaceful
Neutral
Calm
Satisfied
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Participants
Gender: 21 male, 23 female (n=44)
Age: mean 24.6 years; S.D. = 6.2 years
English: 25 (56%) spoke English as a first language, 20
(44%) spoke English fluently as a second language.
Ethnicity: 15 (33%) were ethnically European, 25 (56%)
were Asian or East Asian, 2 (4%) were of African
descent and 3 (7%) were mixed race.
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Methods
Recruitment: Advertisements posted about University
of Nottingham campus
Selection criteria: >18 years; fluent in English
Incentive: £4 per dataset
Task: Online judgement task. Each of 26 photographs
judged on 26, 7-point Likert scales corresponding to
the stimulus mood words.
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Methods
Data Collection
Project portal website and
database created to
manage data collection at
www.xvams.com.
100 (26x26) datasets
collected (n=44), Total of
67,600 judgements.
*XVAMS = Extended Visual
Analogue Mood Scales.
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Results
A principle component
analysis demonstrates
a clear, 2-factor
solution (Eigenvalue
cut-off 1.75–2.4).
Factor 1 identified as
valence (70%).
Factor 2 identified as
activation (20%).
Extraction Sums of Squared Loadings
Component
1
2
3
Total
18.279
4.963
1.278
% Variance Cumulative %
70.303
70.303
19.088
89.391
4.917
94.307
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Results
.60
Nervous
Tense
Confused
Distressed
Angry
Factor 2
Plot of factor loadings
yields clear evidence
of circumplexical
structure, with mood
words following
predicted pattern.
.80
1.50
Anxious
Afraid
Aroused
.40
Energetic
Excited
Enthusiastic
Happy
Pleased
Satisifed
Content
.20
Disappointed
Miserable1.00
.50
Depressed
Sad
.00
.00
-.50
-1.00
-.20
Peaceful
Relaxed
-.40
-.60
Bored
Tired
Sleepy
Neutral
-.80
-1.00
Factor 1
Calm
-1.50
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Results
Examination of correlation matrix and S.D. values identified
stronger items that could be retained for Part 3.
Energetic
Pleased
Excited
Happy
Enthusiastic
Sad
Afraid
Disappointed
Tense
Angry
Nervous
Distressed
Anxious
Aroused
Calm
Bored
Tired
Miserable
Depressed
Satisfied
Relaxed
Confused
Sleepy
Content
Peaceful
Neutral
Study 1
Part 1 – Part
Producing
a Suitable
Set of Photographs
2 – Judging
the Photographs
Results
Examination of correlation matrix and S.D. values identified
stronger items that could be retained for Part 3.
Satisfied
Happy
Excited
Afraid
Angry
Distressed
Sad
Miserable
Bored
Sleepy
Calm
Peaceful
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Repeat of Part 2, with 12 Item Subset
• After eliminating weaker items, results should be
more accurate
• Smaller datasets mean more images sets can be
completed (5 sets instead of just one); many more
datasets per actor required to allow comparison
• 44% of Part 2 participants spoke ESL. Higher
proportion of native English speakers desirable
• Most were students at Nottingham, need more
geographically diverse for external validity.
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Participants
Gender: 38 male, 26 female (n=64)
Age: mean 33 years (18–72 years); S.D. = 14.8 years
English: 53 (83%) spoke English as a first language, 11
(17%) spoke English fluently as a second language.
Ethnicity: 46 (72%) were ethnically European, 6 (9%)
were Asian or East Asian, 1 (2%) was of African
descent and 3 (5%) were mixed race.
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Participants – Locations
Canada & U.S.
U.K.
Europe (non-U.K.)
S.Afr/Austr/Asia
37
9
5
4
(67%)
(16%)
(9%)
(7%)
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Methods
Recruitment: Advertisements posted in U.S. and
Canada, and on online forums
Selection criteria: >18 years; fluent in English
Incentive: £4/$6/0.05BTC per experiment (5 datasets)
Task: Online judgement task. Each of 12 photographs
judged on 12, 7-point Likert scales corresponding to
the stimulus mood words.
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Methods
Data Collection
Project portal website and
database created to
manage data collection at
www.xvams.com.
540 (12x12) datasets
collected (n=64), Total of
77,760 judgements.
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Results
As before, principle
component analysis
demonstrates a clear,
2-factor solution
(Eigenvalue cut-off
1.45).
Factor 1 identified as
valence (60.2%).
Factor 2 identified as
activation (24.7%).
Extraction Sums of Squared Loadings
Component
1
2
Total
7.228
2.964
% Variance Cumulative %
60.232
60.232
24.704
84.937
Study 1
Part
a Suitable
Set of Photographs
Part13––Producing
Judging the
12 Item Photograph
Subset
Results
-.80
Excited
-.60
Afraid
Happy
-.40
Angry
Distressed
Satisfied
-.20
Factor 2
As in Part 2, plot of
factor loadings yields
evidence of
circumplexical
structure, with mood
words following
predicted pattern.
-1.00
1.50
1.00
.50
.00
-.50
-1.00
.00
Miserable
.20
Sad
Peaceful
.40
.60
Bored
.80
Sleepy
1.00
Factor 1
Calm
-1.50
Study 2
Part 1 – Producing aObjectives
Suitable Set of Photographs
1. To construct a number of bipolar scales based on the
positions of the 12 mood words in plots of factor
loadings, and to fill in a gap corresponding to ‘alert’
2. To recall two of the top scoring actors to pose a series
of photos of facial expressions representing transitions
between candidate scale endpoints (key-frame images),
and to process the images, and to obtain a new ‘alert’
(valence-neutral, high activation) image.
3. To run two further judgement studies to establish
coordinate systems and scaling data specifically for
these actor images
Study 2
PartPart
1 – 1Producing
a Suitable
Set of Photographs
– Producing
Scale Key-frame
Images
7 Candidate Scales
-1.00
-.80
Pole 1
Pole 2
1
Miserable
Satisfied
2
Sad
Happy
3
Distressed
Peaceful
4
Bored
Excited
5
Afraid
Calm
6
Angry
Peaceful
7
Sleepy
[Alert]
5
-.60
Afraid
3
6
Distressed
Happy
-.40
Angry
Satisfied
-.20
Factor 2
Scale
Excited
1.50
1.00
.50
.00
-.50
-1.00
.00
Miserable
1
.20
Sad
Peaceful
2
.40
.60
.80
Bored
4
Sleepy
3
1.00
Factor 1
Calm
-1.50
Study 2
Part 1 – Producing Scale Key-frame Images
Recalling Actors for Second Sitting
Two highest scoring actors recalled to pose images of facial
expressions transitioning each of the scales
Actor #1
(A017)
Actor #2
(A014)
Study 2
Part 1 – Producing Scale Key-frame Images
Processing the Key-Frame Images (i)
Images re-mastered from digital negative (CR2) files and normalised for
brightness and exposure using darkroom software.
Study 2
Part 1 – Producing Scale Key-frame Images
Selecting and Processing the Key-Frame Images (ii)
Runs of images were selected for the scales, then cropped and centred
in preparation for judgment experiments and morphing process.
#1 Scale 5: Bored-Excited
#2 Scale 5: Bored-Excited
Study 2
Part 2 - Judgement Experiment (i)
Repeat of Word Rating
Judgement Experiment
As before, an online
judgement experiment
was undertaken to
produce a coordinate
system for the images.
This time, endpoint scale
images from actors #1
and #2 were used
(n=110).
Study 2
Part 3 - Judgement Experiment (ii)
Key-frame Image Scaling
Judgement Experiment
In order to produce an
interval level scale,
however, scaling
judgements of key-frame
images needed to be
collected to establish
their interval level, scale
positions. This was done
alongside the word
judgement study
(n=110).
Study 3
Part 1 – Producing aObjectives
Suitable Set of Photographs
1. To process the key-frame images, and to morph them
into continua of 101 images for each of the seven
scales. Then to assemble these into prototype, sliderbased scales animating transitions between facial
expressions
2. To validate the scales in a sample of stroke patients
against word-versions of the scales, and the Hospital
Anxiety and Depression Scales (HADS), and to assess
test-retest reliability.
Study 3
Part 1 – Creating the Scales
Mapping Key-frame Positions
First, key-frame positions were charted to map the morphs
required for the 0-100 images representing 1% interval levels of a
VAS. Means of scaling judgements (n=110) were used to locate
the % positions (blue) from which morphs would be generated.
#1 Scale 2: Sad-Happy
Study 3
Part 1 – Creating the Scales
Morphing of Key-frame Images
Scale key-frame images were then morphed to create the
required number of transitional images between key-frames.
Morphing scale
key-frames for
Bored-Excited
Scale
Study 3
Part 1 – Creating the Scales
Creating the VAS Interface
The scales images were then
incorporated into software.
The scales are selected from a
menu, and the images are
dynamically displayed via a
slider control.
The scales are cloud-based
and accessible via any web
browser at dvams.com (fully
tested in Firefox and Chrome).
Study 3
Part 1 – Creating the Scales
Accessibility & the User Interface
1.
2.
3.
4.
Desktop – Click & Drag: A point anywhere along the scale ‘ruler’ can be
clicked upon to set the slider position. The slider can also be dragged to
the desired position
Desktop – Mousewheel: The slider can also be operated by hovering the
pointer over the image and rotating the mousewheel, especially useful
when mouse has ‘freewheel’ setting
Tablet – Tap & Drag: As with mouse-click functionality, anywhere along
the scale ‘ruler’ can be clicked upon to set the slider position. The slider
can also be dragged to the desired position
Tablet – Swipe & Hold: The image can be swiped up or down to move
the slider, or swiped and held to control its rate of change.
Summary
D-VAMS Project Plan
Study 1 – Test of
Affect Model,
Selection of
Words, Actors
Photographic
sitting of 20
Actors, 26 Mood
Images
Mood Word
Judgement
Experiment 1 (26
item)
Mood Word
Judgement
Experiment 2 (12
item)
Study 2 –
Collection/Scaling
of Key-frame
Images
Photographic
sitting: Two
Actors pose Scale
Key-frame Images
Mood Word
Judgement
Experiment (12items)
Key-frame Image
Scaling
Judgement
Experiment
Study 3 – Creation
& Validation of
Scales
Construction of
Scales
Validation Study
Photographic Sittings
Online Judgement Studies
Pending
Study 3
Part 2 – Validating the Scales
It is proposed that a pilot study be performed on a small,
community-based sample of stroke survivors.
1. Construct Validity: This can be assessed by having
participants respond to ‘face’ and ‘word’ versions of
the scales in random order
2. Criterion Validity: It is proposed that the HADS
(Hospital Anxiety and Depression Scale) is used as a
criterion measure against which DVAMS scores can be
correlated
3. Reliability: The DVAMS can simply be repeated after
the administration of the HADS.
Study 3
Part 2 – Validating the Scales
1.
2.
3.
Implementation: Online task performed via the D-VAMS portal to
manage the data collection (approx. 15-20 mins)
Adaptation for Participants: Where participants do not have
internet, a home visit can be arranged with a 4G enabled tablet or
laptop
Use of Scales: Gender-matched, males are given male scales,
females are given female scales. Self-report based on last week.
1. Presentation of
randomised word/face
versions of the VAS scales
Proposed Tasks for Validation Study
2. Administration
of electronic
version of the
HADS
3. Repeat of 1.
References
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Astrom, M., Adolfsson, R., & Asplund, K. (1993). Major depression in stroke patients.
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Benaim, C., Cailly, B., Perennou, D., & Pelissier, J. (2004). Validation of the aphasic
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Journal of Clinical Psychology, 45(Pt 3), 367-376.
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