Participant Characteristics

Figure 7-11shows all 19 participants in the study performing the blender task. Table 7-6 gives the educational, occupational and medical background of each participant.

Figure 7-11 Study participants 1 to 19 using the blender

149

Table 7-6 Educational, occupational and medical background of the 19 study participants

# Age Sex Education Occupation Medical conditions and aids

1 62 F Secondary

School

Hester Adrian Thyroid medication, glasses

2 64 M Degree Retired School Teacher Early Parkinsons, glasses 3 50 M Training school Hester Adrian and

Tesco Epillepsy

4 82 M Degree Retired Engineer Glasses 5 65 F Hester Adrian Tinnitus, balance problems 6 71 F Diploma Retired bookseller Back problems (age related),

high blood pressure

7 44 M GCSE Hester Adrian Spinal Bifida, glasses 8 47 F Degree Local government

officer High blood pressure, macular

degeneration, guide dog, cane

9 54 F School for

learning

disabilities

Hester Adrian Glasses

10 61 F Degree Social Research

Interviewer (NATCEN) RSI in right hand, short

sightedness, dupitrons in hands,

glasses 11 63 M Degree Retired technology

consultant -

12 62 F Degree Retired Secretary Osteoporosis, glasses 13 66 M A'Levels Retired Army Officer Glasses

14 72 F Teacher's

Diploma Retired primary school

teacher Genetic condition, tinnitus,

lumps on hands, glasses

15 74 F O'Levels Self employed Genetic macular degeneration, magnifying glass, CCTV, text to

speech

16 61 F Postgraduate

certificate of

education

Retired teacher -

17 65 M Degree Retired Architect and

town planner Diabetes, thyroid deficiency,

retinitis pigmentosa, magnifying

glass, text to speech

18 64 F Degree, Diploma

in social work Retired Probation

Officer Chronic Fatigue Syndrome,

minor stroke, arthritis in spine and wrists, glasses

19 64 F GCSE Retired medical

secretary Arthritis in hands, structural

deformities in feet, glasses

Figure 7-12 shows the age and sex distribution for the study sample (Mean Age=62.68, SD=9.20) ranging from 44 years to 82 years. Of the 19 participants that participated in the study, 12 were female and 7 were male.

150

Figure 7-12 Age and sex distribution of participants

Figure 7-13 shows the educational background of the study sample. 3 participants attended special schools for disability training, 5 participants had a secondary school education, 2 participants studied to the diploma level, 8 participants had a university degree and one participant had a postgraduate qualification. 5 of the 19 participants worked at the Papworth Trust’s Hester Adrian centre which provides job opportunities for people with disabilities and illnesses. 11 participants were retired from their jobs which included teaching, engineering, business, government services, military services, and computer technology. 3 participants were still employed in local government, social research interviewing, and self-owned business. Thus participants presented with a wide range of backgrounds which was desirable in the study.

Figure 7-13 Educational background of study participants

151

When asked about current medical conditions, participants reported a range of conditions (including some associated with ageing): tinnitus, macular degeneration, retinitis pigmentosa, parkinson’s, epilepsy, arthritis, osteoporosis, structural deformities, spinal bifida, high blood pressure, RSI, diabetes, thyroid deficiency, chronic fatigue syndrome and minor stroke.

Participants were also asked to report if they had any problems with their general vision, hearing, memory, hand use and walking. 6 of 19 participants (31.6%) reported problems with their vision, 5 (26.3%) participants reported problems with their hearing, 6 (31.6%)

participants reported problems with their memory, 6 (31.6%) participants reported problems with using their hands, and 6 (31.6%) participants reported difficulties with walking. In addition, participants used various aids to assist with daily functions. One participant used a hearing aid, 11 participants used glasses, two participants used magnifying glasses and text- to-speech systems, and one participant used a guide dog with a cane. For movement, one participant used walking sticks and another used a wheelchair/walker.

7.3.2.1 Sensory Characteristics

Figure 7-14 shows the distribution of VAR scores in the study sample. The graph on the left of the figure shows that the distance acuity (M=88.7, SD=17.3, N=18) of most participants ranged between 80 and 100. Two participants had significantly lower acuity scores, and one participant could not read the chart at all. The graph on the right of the figure shows the distribution of “comfort acuity” scores (M=78.5, SD=19.2, N=17). This was measured by asking participants to pick a line on the logMAR chart that they felt comfortable reading without strain. The graph shows lower VAR scores for comfort acuity, which translates to larger letters. Most of the participants had good to fair visual acuity scores given the age group and vision correction devices used (mostly glasses). However, two participants had particularly poor vision with VAR scores of 55 and 35, and one participant’s vision was so low that she could not perform any of the vision tests.

Figure 7-14 Histograms of distance visual acuity on the left and a comfort acuity on the right

152

Figure 7-15 shows the results of contrast sensitivity testing at different sizes of letters. The graph plots mean minimum contrast levels in the sample at 6 different letter sizes (error bars show standard error of the mean). As expected, at larger text sizes, participants could recognise letters of low contrast, e.g. 5.2% at 1.8 logMAR on average. At smaller text sizes, the average contrast threshold is raised e.g. 20.2% at 0.4 logMAR. The variability in the minimum contrast threshold also increases as the letter size decreases.

Figure 7-15 Mean minimum contrast levels (%) at different sizes of text (logMAR) for the study sample.

7.3.2.2 Cognitive Characteristics

Figure 7-16 shows the distribution of the 4 cognitive capability measures. The distribution of digit span scores (M=5.95, SD=1.58, N=19) shows that a score of 7 had the highest

frequency, while a score of 4 had the second highest frequency. 5 participants had fairly low digit span scores of 4 or less. Two participants could not successfully perform the MOT test (and thus the three subsequent cognitive tests) because they could not see the objects on the screen. Spatial span scores (M=4.8, SD=1.29, N=17) show that scores of 5 and 6 were the most frequent, followed by relatively low scores of 3. The histogram of five choice reaction time (M=412.2, SD=122.31, N=17) shows times between 400 – 450 milliseconds to be the most frequent in the sample. One participant had a particularly long reaction time above 800 milliseconds. This participant had poor vision which possibly accounted for this high score.

The histogram for the graded naming task (M=62.5, SD=32.39, N=17) shows a large

distribution of scores across the 100% range. Scores between 80-90% were the most frequent.

153

The cognitive capability scores indicate a reasonable spread over their respective ranges. This is in keeping with the aims of the study to investigate performance of users across a range of capability profiles.

Figure 7-16 Histograms of cognitive variables measured: digit span, spatial span, five choice reaction time and graded naming task (GNT)

7.3.2.3 Motor Characteristics

Table 7-7 lists the descriptive statistics for the 37 motor capability variables recorded for each participant. All forces were measured in Newtons, rotational forces in Newton-metres and times in seconds. In addition to the forces listed, pinch strength between index finger and thumb for each hand was listed for measurement. However, the pinch gauge sourced for the study malfunctioned after the first session, and a replacement could not be sourced in time for the remainder of the study. Thus this capability measure was not captured. Since force measures were captured for each hand in different positions and grasps, it was possible to relate the motor actions captured on video, e.g. pushing, lifting etc., to the exact hand that was used. This led to accurate plots of relationships between motor capability and motor demand forces for each participant.

154

Table 7-7 Descriptive statistics for motor capability variables

Figure 7-17 shows some illustrative motor capability graphs for grip strength, clockwise rotation, index finger push and pushing while grasping for each hand.

155

Figure 7-17 Motor capability histograms for grip strength, clockwise rotation, index finger push and push

156

The graphs show that the participants represented a good range of capabilities for each measure which was required in the study. In addition, there were observable differences in the distribution of each measure between the right hand and the left hand. This justified

characterising each hand independently, especially given the unpredictable and asymmetrical effects of disease and trauma on hand/limb function.