| The research |
The NHMRC Partnerships in Injury - Prevention of Older People's Injuries (POPI) program involves 8 different research projects, related to falls (Projects F1-F6) and Transport injuries (Projects T1-T2). The details of these projects are outlined below.
Shortcut to:
Project F4. Preventing falls and injury in high-risk groups of older people
Project T2. Prospective cohort study of risk factors for motor vehicle crashes
Project F1. Human
balance (Leaders: Dr Richard
Fitzpatrick, A/Prof Paul Hodges)
Identifying
risk factors for falls has relied on understanding the mechanisms and
conditions affecting balance
[1-3]
. To date our studies of
human balance
[4-6]
and the tests included in
our falls-risk assessment consider only balance during standing. However,
most falls occur during walking and performing transfers
[7]
, and mechanisms to prevent
falls require stepping reactions. The studies outlined in this section
investigate the sensorimotor control of human walking, stepping reactions
and the causes of trips and slips. Apart from an understanding of the
physiology and biomechanics of these behaviours, a goal is to find simple
measures to be used in other areas of the falls-injury program.
Study A. Stepping
Background
Human
standing is normally stabilized by reflex contractions of the leg muscles
that apply appropriate forces to the ground to balance the body and
correct small postural disturbances. Previous work has identified the
sensory mechanisms responsible for the control of standing balance
[4, 5, 8]
. With bigger disturbances,
this is insufficient and a step is taken to maintain stability. Recent
studies indicate that inappropriate step responses are a significant cause
of falls and related injury
[9, 10]
. The sensory basis of this
stepping reflex is not known, but the feet, leg muscles, eyes and
vestibular organs are likely candidates. The size and speed of a
disturbance will determine whether a subject steps or remains standing.
When either, or both, reach a threshold level, a step needs to be taken to
stop falling.
Aims
To
determine the sensory basis of the stepping reflex and identify protective
stepping patterns in young subjects. To investigate abnormal responses in
older subjects. To quantify thresholds for stepping in both groups of
people.
Subjects
Approximately
30 subjects aged 20-45 years and 50 subjects aged 60-90 years (40 with a
known high risk of falling) will be recruited.
Study
Design
This
will be a cross-sectional study with each subject undergoing one
assessment at the Prince of Wales Medical Research Institute.
Procedures/measurement
tools
Subjects
will stand and be pulled forward by a servo-controlled linear motor while
body movement and the centre of foot pressure are recorded. The size and
speed of the pulls will be adjusted to determine the threshold region at
which subjects step. Different sensory conditions will be tested. Visual
input will be modified by blindfold, darkening the room or wearing
translucent lenses. Sensory input from the feet will be modified by
anesthesia, vibration or cutaneous stimulation. Vestibular input will be
modified by simultaneous electrical vestibular stimulation or tilting the
head. In addition to the threshold for stepping under different sensory
conditions, outcome measures will include the electromyographic, kinetic
and kinematic responses determined through motion analysis and force-plate
recordings.
Study B. Trips and
Slips
Background
Trips
and slips occur during locomotion and account for approximately 60% of all
falls in older people. A trip occurs when the advancing leg is stopped so
that the body weight cannot be transferred to that leg. It is commonly
encountered when a person does not see an obstacle. A slip occurs because
the frictional resistance of the walking surface is either too low or less
than expected. As with the stepping reflex, triggered recovery strategies
are required to prevent falling. Probably more so than for stepping, the
recovery strategy itself can be a cause of injury because of the much
greater forces involved. We will investigate these behaviours by inducing
trips and slips.
Aims
To
determine sensory triggers for recovery from trips and slips in younger
subjects. To identify appropriate responses in older subjects.
Subjects
Approximately
30 subjects aged 20-45 years and 50 subjects aged 60-90 years (40 with a
known high risk of falling) will be recruited.
Study
Design
This
will be a cross-sectional study with each subject undergoing one
assessment at the Prince of Wales Medical Research Institute.
Procedures/measurement
tools
Trips
will be produced with a specifically designed shoe that has an apparatus
that can be triggered to catch the floor at different times in the gait
cycle and thereby impede that leg from advancing to stance phase. Slips
will be induced by an apparatus built into the walkway that can be
triggered so that it moves in the direction of gait at heel strike and in
stance phase. The size and speed of the slip will be controlled. Subjects
will be medically assessed and those too frail or with known osteoporosis
or a history of fracture will be excluded. Participants will be protected
by a body harness that will prevent falling. Visual, vestibular and
peripheral sensory input will be modified in the manner described for the
stepping study (above). Outcome measures will include electromyographic,
kinetic and kinematic responses determined by motion analysis and
force-plate recordings.
Study C.
Accelerometry
Background
Our
assessment of stability and falls risk relies largely on determining body
sway when standing [1, 2]. Although falls occur more frequently when
walking, there is no simple measure of stability for walking. In the same
way that minimizing sway is considered “optimal” during standing when
considering falls-risk, a forward velocity that is constant could be
considered “optimal” for walking. Thus deviations from this trajectory
could provide a measure of instability. Using 3-D accelerometers at the
pelvis and head, pilot studies have shown a near-linear relationship
between walking speed and deviation from constant velocity.
Aims
To
develop a simple measure of stability while walking. To determine the
range of normal behaviour and the effects of modifying visual, vestibular
and sensory input from the feet in younger subjects. To determine the
effects of aging and specific sensorimotor deficits on stability while
walking. To correlate results with tests of physiological function already
known to predict balance problems and falls.
Subjects
Approximately
40 subjects aged 20-45 years, 100 subjects aged 60-90 years, and
approximately 20 subjects with different clinical conditions (such as
peripheral neuropathy, age-related maculopathy, vestibular disorders and
Parkinson’s Disease) will be recruited.
Study
Design
This
will be a cross-sectional study with each subject undergoing one
assessment at the Prince of Wales Medical Research Institute or the
Queensland University of Technology.
Procedures/measurement
tools
Data
will be obtained while walking on the floor and on an irregular,
rough-terrain surface. Subjects will wear a portable data collection
device. If necessary, an investigator with walk behind the subject to
ensure safety.
Study D.
Background
Aims
Subjects
Study
Design
Procedures/measurement
tools
For the whole F1
Project (studies A-D)
Outcomes
·
Understanding
the sensorimotor determinants of stepping responses for falls avoidance
and how it is affected in older people, especially groups at risk of
falling.
·
Understanding
recovery strategies from trips and slips in older people, especially those
at risk of falling.
·
Understanding
the sensory and motor basis for age-related changes in gait stability, and
gait factors associated with falls in older people.
·
Provide
normative data for a large group of older adults.
·
Provide
a simple, portable and reliable measure of stability during walking that
could be applied in many settings.
Researchers
Leo Carney (QUT), Richard Fitzpatrick (POWMRI), Graham Kerr (QUT),
Andrew Hills (QUT), Stephen Lord (POWMRI), Michael Halmagyi (U Syd), Paul
Hodges (POWMRI), Hylton Menz (UWS), Ian McCloskey (POWMRI), Anthony Parker
(QUT), Julie Steele (UoW), Janet Taylor (POWMRI), Charles Worringham (QUT).
Project F2. Risk
factors for falls (Leaders: Dr Graham
Kerr, A/Prof Stephen Lord)
The
Partnership investigators have made significant advances in identifying
risk factors for falls and injury in older people. In F2 we will build
upon and extend this research. Three controlled studies will be conducted
to enhance our understanding of vestibular disorders (Study A), vision and
gait (Study B) and choice stepping reaction time (Study C). Three
prospective studies will be conducted, one focusing on visual risk factors
for falling among community dwellers (Study D), one among of people with
Parkinson's Disease (Study E) and one among a large group of
community-dwelling older people, testing vision, vestibular function, and
neuropsychological function (Study F). This work will enable better
prediction of people at risk of injury and the implementation of targeted
interventions, and will provide simple tests that will be incorporated
into screening programs of falls-risk (see F6). Studies A, C and D will be
conducted in Sydney, Studies B and E will be conducted in Brisbane and
Study F will be conducted in both Sydney and Brisbane.
Study A. Developing
tests of vestibular function
Background
Caloric
ENG testing, the standard clinical test of vestibular function, is
unpleasant and technically difficult to administer
[16]
. It is a test of the
vestibulo-ocular reflex (VOR) and is only a general indicator of
vestibular balance problems where deficits may not be related to the
semicircular canals. The available screening tests of vestibular function,
Fukuda’s vertical X-writing and stepping tests, and a test of
vestibulo-ocular stability do not predict instability or falls in older
people
[1]
.
Aims
To
develop and validate feasible and safe tests of vestibulo-ocular stability
and vestibulo-postural function to identify vestibular dysfunction in
those with balance disorders.
Subjects
40-80
subjects will be recruited if they have complaints of unsteadiness,
vertigo, visual disruption, or inappropriate motion sense for 6 months or
more that has been accurately identified as a peripheral vestibular
disorder at the Hearing and Balance Unit, Royal Prince Alfred Hospital,
Sydney. Patients with position-provoked dizziness, non-surgical Menière’s
Disease, and those taking medications for dizziness will not be included.
Other subjects with no history of vestibular disorders will comprise a
control group.
Study
design
Study
A will be a cross-sectional study. Subjects will undergo one assessment at
the Prince of Wales Medical Research Institute.
Procedures/measurement
tools
A
test of vestibulo-ocular stability will measure visual acuity during
imposed head movement. Subjects will view high and low contrast letter E
stimuli with head movements at 0.5,1, 2 and 4 Hz to give indicators of
vestibular performance over a broad range of the VOR
[16]
. A test of
vestibulo-postural function will measure subjects’ ability to perceive
the gravitational vertical. Subjects will be supported upright,
blindfolded, on a motorized platform that will lean the body away from the
true upright in any direction. The subjects, or the experimenter, will use
a hand-held control to return the body to vertical, and any error will
provide a measure of vestibulo-postural acuity.
Study B.
Understanding visual impairment and gait
Background
Age-related
maculopathy (ARM) is the most prevalent cause of irreversible visual loss
in older people.
Aims
To
investigate the mechanisms of the effects of visual loss on balance and
gait in this clinical population.
Subjects
80
subjects with advanced age-related maculopathy (ARM) and 80 matched
control subjects with no ocular disease will be tested.
Study
design
Study
B will be a cross-sectional study. Subjects will undergo one assessment at
the Queensland University of Technology.
Procedures/measurement
tools
In
addition to the falls risk assessment tests
[1]
, these subjects will also
be assessed for stability during standing and several movement tasks
typical of conditions in which people with ARM could be expected to fall
(walking, turning, negotiating obstacles, stairs, slopes and slippery
surfaces). Standing will be assessed on a force plate with standard
stabilometric parameters and stabilogram-diffusion parameters
[19]
. During the movement
tasks, body kinematics will be recorded using video motion analysis, and
force reactions will be recorded with force plates. Head orientation,
joint angles, foot clearance and standard gait parameters will provide
insight into the mechanisms of visual loss on balance and gait in this
clinical population.
Study C.
Understanding choice stepping reaction time
Background
Avoiding
a fall requires perception of a postural threat, selection of an
appropriate corrective response and proper response execution. We have
devised a test of choice reaction time that requires body weight and
balance transfers that mimic the step response required to avoid a fall.
This test has been validated as a risk factor for falls (retrospective
reporting) in a retirement village.
Aims
To
enhance our understanding of stepping choice reaction time.
Subjects
Approximately
20 subjects aged 20-45 years and 40 subjects aged 60-90 years (20 with a
known high risk of falling) will be recruited.
Study
design
Study
C will be a cross-sectional study. Subjects will undergo one assessment at
the Prince of Wales Medical Research Institute.
Procedures/measurement
tools
Subjects
stand on a non-slip black platform that contains 4 rectangular panels (32
x 13cm), one in front of each foot and one to the side of each foot. The
panels are illuminated in a random order, and subjects are instructed to
step on to the illuminated panel as quickly as possible but using the left
foot only for the two left panels (front and side) and the right foot only
for the two right panels. Measures of reaction time and execution time
will be obtained by recording surface EMG of the leg muscles and the time
to turn off the switch. These measurements will be also taken while the
subject steps forwards on level ground, steps up onto and down off a
block, and using the platform for two-choice stepping up (in response to
illumination as described above). To further understand mechanisms of
falling and to validate this test, performances in a subset of subjects
will be compared with their responses to induced slips and trips (see F1).
Study D. Visual risk
factors for falls in community dwellers
Background
Standard
visual-acuity and visual-field tests are not consistently associated with
falls
[11, 12]
. However, contrast
sensitivity and depth perception are strongly associated with falls and
fractures
[11, 12]
. This indicates that tests
of specific visual functions used for balance and detecting hazards are
needed.
Aims
To
examine the relative predictive power of eight screening tests of vision,
alone and in combination with other physiological risk factors for
predicting falls in community-dwelling older people.
Subjects
A
sample of 150 people aged 65 and over will be recruited from the
community.
Study
design
Study
D is a prospective cohort study. Subjects will be assessed on possible
visual measures of falls risk and followed for 12 months to determine falls outcome. The study will be based at
the Prince of Wales Medical Research Institute.
Procedures/measurement
tools
Vision
High-
and low-contrast visual acuity will be measured with log MAR charts.
Contrast sensitivity will be measured with the Melbourne Edge Test
[11]
. Depth perception will be
measured with a Howard-Dohlman apparatus and the Frisby stereotest.
Monocular and binocular visual field loss will be assessed for high and
low contrast stimuli
[13]
. Certain tests will be
administered at distances of two step lengths - the critical distance at
which people detect hazards when walking
[15]
.
Other
physiological risk factors for falling
In
addition, tests which have previously been found to be predictive of falls
[1]
will be administered.
These are: lower limb muscle strength (with a spring balance), peripheral
sensation (lower limb proprioception), reaction time (using movement of
the finger as the response) and body sway (with a sway meter while the
subject stands on a foam mat).
Study E (part 1). Falls risk
and Parkinson's Disease
Background
People
with Parkinson’s Disease (PD) have impaired balance control and high
rates of falls and injury
[20, 21]
. There is yet to be a
validated falls risk assessment tool for this group.
Aims
To
provide a validated falls-risk assessment specific to Parkinson’s
Disease (PD).
Subjects
80
people with Parkinson's disease will be recruited.
This study will be based at the Queensland University of
Technology.
Study
design
Study
E will be a prospective cohort study. Subjects will be assessed on
possible measures of falls risk and followed for 12 months to determine falls outcome.
Procedures/measurement
tools
Tests
which have previously been found to be predictive of falls
[1]
will be administered (ie
tests of lower limb muscle strength, peripheral sensation, reaction time,
body sway and vision).
In
addition the Unified Parkinson's Disease Rating Scale, and a set of
mobility tests including gait accelerometry, choice stepping reaction
time, biomechanical indices of shuffling and freezing, stair climbing,
turning, and obstacle clearance during gait will be administered.
Study E (part 2). Falls risk factors in Parkinson’s patients (Dr Mark Latt)
Background
Aims
Subjects
Study Design
Procedures/measurement tools
Study F. Falls risk
factors in community dwellers
Background
Previous
work
[1]
has led to the
establishment of a battery of tests which are strong predictors of falls
among community dwelling people. This study will investigate possible
additional risk factors with a focus on vestibular functioning,
neuropsychological functioning and choice reaction time.
Older
people with cognitive impairment are at increased risk of falls
[3]
. Asking older people to
perform attention tasks such as backward counting or answering a question
can impair balance and gait
[17, 18]
. Thus, even standing,
which is considered to be a “reflex” activity, requires cognitive
input in people with balance disorders. This study will include
psychometric tests to measure attention deficits and dual-tasking
abilities.
Aims
To
enable better prediction of people at risk of falls and to provide simple
tests that will be incorporated into screening programs of falls-risk.
To
establish the role of validated tests of vestibular function as risk
factors for falls in older people.
To
establish the role of attention deficits and dual-tasking abilities as
risk factors for falls in older people using psychometric tests.
To
measure the extent to which reduced function in particular sensorimotor
systems and the presence of health and lifestyle conditions are associated
with poor performance in a test of choice reaction time, and whether older
people with slow choice stepping reaction times are at increased risk of
falls.
Subjects
Two
samples of community-dwelling people will be recruited by random selection
from the Sydney and Brisbane electoral rolls: (i) 250 men and women aged
70 years and over from Sydney and (ii) 250 men and women aged 75 years and
over from Brisbane (these subjects will also take part in study T1 to
enable us to examine shared risk factors for falls and transport-related
injury). Based on our previous studies
[1]
and power analyses with
alpha levels of 0.05 (2-tail design) and power of 0.8, samples of this
size will be sufficient to detect any clinically significant differences
in the posited risk factors between faller and non-faller groups.
Study
design
Study
F will be prospective a cohort study. Subjects will be assessed on
measures of falls risk and followed for
12 months with monthly falls calendars to determine frequency of falls and
related injuries. This study will be based at the Prince of Wales Medical
Research Institute and the Queensland University of Technology.
Procedures/measurement
tools
Vestibular
Functioning
Tests
to be included following validation in Study A.
Neuropsychological
Functioning
Tests
will include a cued-attention switching task requiring subjects to change
balance stances in response to auditory cues, a working memory and divided
attention task in which participants are required to name objects
appearing on the screen while undertaking balance tasks, backward
counting, and Brook’s spatial and non-spatial memory tasks.
Choice
stepping reaction time
Subjects
stand on a non-slip black platform that contains 4 rectangular panels (32
x 13cm), one in front of each foot and one to the side of each foot. The
panels are illuminated in a random order, and subjects are instructed to
step on to the illuminated panel as quickly as possible but using the left
foot only for the two left panels (front and side) and the right foot only
for the two right panels.
Other
measures of falls risk
Tests
which have previously been found to be predictive of falls
[1]
will be administered (ie
tests of lower limb muscle strength, peripheral sensation, reaction time,
body sway and vision). The visual assessment tool(s) will be chosen based
on the results of study D.
T1
tests
Subjects
in this study who are current drivers will also undergo additional tests
of cognition, motor performance, vision and health as outlined in the
section describing study T1.
Study G. Sleep disturbances and falls in the elderly (Elizabeth Latimer-Hill)
Background
Aims
Subjects
Study
Design
Procedures/measurement
tools
Study H Cardiovascular and aerobic risk factors for falls in older people (Rebecca Roodveldt)
Background
Aims
Subjects
Study
Design
Procedures/measurement
tools
For the whole F2
Project (studies A-H)
Outcomes
·
Understanding the role of
impaired vision in predisposing older people to fall.
·
Understanding the role of
impaired vestibular function in predisposing older people to fall.
·
Understanding the role of
impaired neuropsychological function in predisposing older people to fall.
·
Understanding the role of
impaired choice stepping reaction time in predisposing older people to
fall.
·
Understanding the causes
of additional falls-risk in populations with conditions that affect
sensorimotor and balance performance: persons with advanced ARM, those
with vestibular disorders, and persons with Parkinson’s disease.
·
Validation of tests of
falls risk in these previously poorly-investigated aspects of physical and
psychological function.
·
Selection of tests for
use in screening tools.
Researchers
Kaarin Anstey (POWMRI), Richard Fitzpatrick (POWMRI), Graham Kerr (QUT),
Andrew Hills (QUT), Paul Hodges (POWMRI), David Le Couteur (CERA), Stephen
Lord (POWMRI), Hylton Menz (UWS), Vasi Naganathan (CERA), Michael Halmagyi
(U Syd) Beth Newman (QUT), Julie Steele (U Woll), Joanne Wood (QUT),
Charles Worringham (QUT).
Project F3.
Preventing falls and injury in hospitals (Leaders:
Prof Bob
Cumming, Prof Tony Broe)
Background
Falls
in acute hospitals increase morbidity, prolong hospital stays, and strain
the resources of the health care system, family and community
[23]
. In Australian hospitals,
38% of all reported patient incidents involve a fall
[24]
. In the geriatric ward of
an acute hospital, a 27% falls rate has been reported
[25]
and in general hospitals
reported rates were 1.6% and 1.7%
[26, 27]
. Two previous trials of
interventions to prevent falls in hospitals were too small to show an
effect but these, and an uncontrolled trial of a patient alarm, showed
some promise
[28]
.
Aims
To
investigate strategies to reduce the incidence of falls and related injury
in hospitals.
Subjects
Ten
hospitals in Sydney and Brisbane will participate in this trial (actual
hospitals to be confirmed). Patients aged over
75 years (n=3000) admitted to acute hospitals for at least one night, for
other than brief procedures, will be included. Four wards in each of the
ten sites, and 75 patients in each ward, will be included.
Study design
A
cluster-randomized design will be used. Patients will be randomized by
ward and stratified by ward type. The program will be applied for two
months in each ward. This sample size is estimated by a power analysis
with a reduction in the falls rate from 4% (estimated, see above) to 2% in
the intervention wards, a significance level of 0.05, a power of 0.8, and
an intra-class correlation of 0.01 to allow for cluster randomization
effects.
Procedures/measurement
tools
Patients
will be assessed to identify strength, balance, mobility and cognitive
problems that would increase their risk of falling. A researcher with
physiotherapy or nursing background will implement the following measures
designed to reduce falls. The patient, family and staff will be educated
about the person's increased risk of falling. The patient will be trained
to use an appropriate walking aid and will practice daily. Equipment to
assist in safe toileting (e.g. bottle, pan or bed-side commode) will be
provided if the person is unable to walk to the toilet unassisted. In
addition, steps will be taken to identify hazards and maximize the safety
of the ward environment. Following the clinical assessment, those patients
who are considered unsafe to mobilize without assistance, yet are
considered likely to attempt this, will wear a movement-sensing alarm that
will alert nursing staff if the person attempts to rise from a bed or
chair. This is designed to prevent falls from a standing height, which are
the most injurious. Alarms that emit a high frequency noise detectable by
nursing staff are being developed. The alarms will not distress the
patient, be comfortable to wear and be able to be cleaned using standard
hospital protocols.
Falls
will be recorded using hospital incident forms, which will be modified as
required. In addition, patients who fall will be interviewed regarding
location, causes, and circumstances. Morbidity data about stay in hospital
and treatment required will be recorded. A cost-benefit analysis will
establish whether the reduction in the incidence of falls and injury
justifies the expense of additional physiotherapy and nursing staff to
implement the intervention. To enable this, the researcher will record
time spent implementing the intervention. Nursing staff/patient ratios
will be used as covariate in outcome analysis. Measures of strength,
balance, mobility, cognition, reaction time and drug use will be used in a
multivariate analysis to identify objective risk factors for falls in
hospitals.
Outcomes
·
Development of
inexpensive alarms to alert hospital staff when patients at risk of
falling attempt to rise from a bed or chair unaided.
·
Identification
of effective strategies for preventing falls in acute hospitals.
Researchers
Adrian Bauman (UNSW), Guy Bashford (UoW), Mary Courtney (QUT), Helen
Edwards (QUT), Suzanne Kuys (PAH), David Le Couteur (CERA), Stephen Lord
(POWMRI), Lyn March (RNSH), Vasi Naganathan (CERA), Beth Newman (QUT),
Solomon Ni (USyd), Brian Oldenburg (QUT), Sue Ogle (RNSH), Cathie
Sherrington (POWMRI), Raja Salgado (Calvary Hosp), Paul Varghese (PAH),
Charles Worringham (QUT).
Project F4.
Preventing falls and injury in high-risk groups of older people (Leaders:
A/Prof Ian Cameron, Dr Cathie Sherrington)
Background
Specific
groups of older people have an increased risk of falls and injury, and so
provide an opportunity to test targeted interventions. Targeting
interventions of physical activity to patients with specific needs is
effective and sustainable. Falls risk factors such as strength and balance
deficits are common among older people, and promoting physical activity to
remedy them is likely to benefit a large segment of the older population.
In the six studies described in this section, we will develop, implement
and assess targeted interventions for the different populations of older
people known to be at increased risk of falls and injury. In addition, a
systematic literature review will update the evidence-based guidelines for
treatment and rehabilitation of hip fracture in acute-care and
rehabilitation settings.
Study A. Targeted
interventions
Aims
To
determine whether targeted interventions designed to compensate for
impairments in strength, balance, vision, peripheral sensation and visual
field dependence can reduce the rate of falling in community-dwelling
people.
Subjects
Subjects
aged 75 years and over (n=600) will be recruited from the community.
Study
design
Potential
subjects will undergo a physiological assessment of their risk of falling
using a physiological profile using normative data from large population
studies
[1, 29]
. Subjects who display a
significant risk will be randomised into one of three intervention groups
(n=200 for each). These groups will receive minimal intervention,
extensive intervention or no intervention. This study will be based at the
Prince of Wales Medical Research Institute. Assessments will occur at
Royal North Shore Hospital in Sydney.
Procedures/measurement
tools
In
the minimal intervention, subjects will receive a report about their falls
risks and recommendations about how to reduce them. The extensive
intervention will build on the minimal intervention by offering specific
strategies depending on the individual’s needs. These will include: 1)
tailored exercise programs to improve strength, balance and coordination,
2) a visual intervention to improve vision, 3) counselling on how to
compensate for reduced peripheral sensation and 4) counselling on how to
compensate for visual dependence. Subjects will be reassessed for the
physiological measures at six months, and followed up for 12 months to
determine falls and falls injury incidence. A full cost and
cost-effectiveness analysis will be undertaken. This project has the
potential for immediate application, and we anticipate that the model will
be incorporated into health care services.
Study B. Strength and
balance impairments
Aims
To
determine the effectiveness of a prescription of physical activity by GPs
for older patients with falls risk factors, and to provide a model of
physical activity promotion for older people with scope for wide
dissemination in Australia and the tools to enable the practical
application of the intervention.
Subjects
Participants
will be recruited through their GP after a simple falls risk assessment.
If they have balance, strength or reaction time deficits that could be
ameliorated by exercise intervention, they will be referred to the study
for a thorough assessment and measurement of baseline variables.
Study
design
Participants
will be randomly allocated (stratified by GP surgery) to the exercise
program (n=200) or continued routine care by their GP (n=200). This study
will be based at the South Western Sydney Area Health Service Health
Promotion Service.
Procedures/measurement
tools
Accredited
exercise instructors who have experience with older people will conduct
the exercise program. The program involves one group session per week and
instructional material for weekly home activities. Levels of physical
activity, falls-risk factors and quality of life will be measured at a
subsequent clinic assessment at 6 months, and physical activity will be
measured again by telephone interview at 12 months. The incidence of falls
will be monitored monthly for 12 months. The person making the assessments
will be blinded to group allocation.
Study C. Recent
hospitalisation
People
who have recently been hospitalized are at an increased risk of falling
[30]
. This is likely to be due
to deconditioning as a result of the immobility associated with illness
and hospitalization. Many studies of exercise in older people involve
relatively short-term programs (e.g. 10 weeks
[31]
). However, cessation of
this type of exercise may result in a loss of gains. If this is so, then
the findings from longer-term falls studies could erroneously indicate
that exercise does not prevent falls.
Aims
To
investigate the role of strength and balance training in the reversal of
post-hospitalisation deconditioning. To assess the effects of ceasing such
training.
Subjects
Participants
will be recruited from patients recently discharged from the Royal North
Shore Hospital, Sydney, Princess Alexandra Hospital, Brisbane, and the
Port Kembla Hospital, NSW.
Study
design
Participants
will be randomly allocated to either a strength-training exercise program
(n=200) or to a strength and balance training program (n=200) or a
non-exercising control group (n=200).
In the initial stages this study will be based at the Royal North
Shore Hospital, assessments will occur in participants’ homes.
Procedures/measurement
tools
The
interventions will be in the form of home exercise programs which will be
established and monitored by physiotherapists who will attend each
patient’s home once a week. The programs will involve 12 weeks of
exercise training, with follow-up for a further period of 12 weeks. Levels
of physical activity, falls-risk factors of balance and strength will be
measured at baseline and at weeks 12 and 24. The assessor will be blinded
to group allocation.
Study D. Frailty
Among
community-dwelling, relatively healthy older people, exercise programs
conducted in weight-bearing postures (e.g. standing and walking) reduce
the risk of falling
[32]
. In contrast, in frailer
or more disabled populations who have only had mild seated exercises,
little or no effect on falls risk factors has been demonstrated
[33]
. Thus, greater effects on
strength and balance may be found among frailer people if more challenging
exercise programs are undertaken.
Aims
To
evaluate a program of group exercise for people who have been discharged
from in-patient and outpatient rehabilitation services with ongoing
physical disability.
Subjects
A
total of 200 subjects will be recruited over 3 years. We will target those
whose level of disability precludes their attendance at general
community-based exercise classes.
Study
design
Subjects
will be randomly assigned to either a test program or a control (delayed
intervention) program. This study will be based at the Bankstown-Lidcombe
Hospital Physiotherapy Department.
Procedures/measurement
tools
The
exercise program, developed by physiotherapists at Bankstown-Lidcombe
Hospital in Sydney, involves 10 sessions over 5 weeks of exercise classes
attended by 6 to 8 people. The circuit-style classes are run by a
physiotherapist and focus on weight-bearing exercises designed to improve
strength, balance and endurance. Physiological assessments of strength and
balance that can provide a measure of risk of falling
[1]
will be made before and
after the first five-week period. The assessor will be blinded to the
group assignment.
Post hip fracture
(Studies E, F, G)
Hip
fracture is a major global public health issue. Following hip fracture,
patients have increased falls-risk factors and higher rates of further
injury. It has been recently shown that a program of weight-bearing
exercise at home after hip fracture improves strength and mobility
[34]
. This raises the question
of whether this program or the more commonly used bed exercise program is
more appropriate for rehabilitation after hip fracture. In the proposed
project, we will investigate the efficacies of these different exercise
strategies in two randomized trials for in-patient and community settings.
Study E. Hospital hip
fracture trial.
Aims
To
investigate the effects of different muscle strengthening strategies among
in-patients undergoing rehabilitation after hip fracture.
Subjects
80
subjects will be recruited from in-patients at the Bankstown-Lidcombe
Hospital.
Study
Design
Subjects
will be randomized to either a group (n=40) who will carry out traditional
bed exercises or to a group (n=40) who will exercise in weight-bearing
positions (using tasks such as standing, walking and stair-climbing). This
study will be based at Bankstown-Lidcombe Hospital Physiotherapy
Department and the Prince of Wales Medical Research Institute.
Procedures/measurement
tools
The
outcome measures of this study will be balance, strength, and functional
abilities (rising from a chair, walking, stair climbing). Subjects will be
re-assessed following two weeks of intervention.
Study F. Home hip
fracture trial.
Aims
To
investigate these two different approaches in home exercise programs among
people who have suffered a hip fracture.
Subjects
Subjects
for this study (n=120) will have been discharged from in-patient and
out-patient rehabilitation intervention at a number of acute and
rehabilitation hospitals in Sydney.
Study
Design
Subjects
will be randomized to either a group who will carry out bed exercises
(n=40), or to a group who will carry out weight-bearing exercises (n=40),
or to a control group who will not receive any intervention (n=40). This
study will be based at Bankstown-Lidcombe Hospital Physiotherapy
Department and the Prince of Wales Medical Research Institute
Procedures/measurement
tools
The
outcome measures of this study will be balance, strength, and functional
abilities. Subjects will be re-assessed following one and four months of
home exercise.
Study G. Hip fracture
literature review
A
systematic literature review will update the evidence-based guidelines for
treatment and rehabilitation of hip fracture in acute-care and
rehabilitation settings
[35]
. This review will be
conducted at the Royal North Shore Hospital and the University of Sydney.
Study H. Enhancing Mobility after Hip Fracture
Aims
To determine the effects of intensive weight-bearing exercise after hip fracture
Subjects
160 participants will be recruited from the physiotherapy and rehabilitation services of three large Sydney teaching hospitals. All patients who have surgical fixation, are admitted to the rehabilitation ward, do not have severe cognitive or other impairments and who plan to return home to the community or a hostel will be invited to participate.
Study Design
Subjects will be randomly allocated to intensive weight-bearing exercise or non-weight-bearing exercise groups.
Procedures/measurement tools
The primary outcomes are walking speed and isometric quadriceps strength. Subjects will be re-assessed following one and four months of exercise.
For the whole F4
Project (studies A-H)
Outcomes
·
Identification of
effective strategies to prevent falls in community-dwelling people with
visual, sensorimotor, coordination and balance problems.
·
Identification of
effective strategies to prevent falls in persons recently discharged from
hospital.
·
Identification of
effective strategies to prevent falls in frail older people.
·
Identification of
effective strategies to prevent falls in older people who have suffered a
hip fracture.
·
Production of systematic
literature review which will update the evidence-based guidelines for
treatment and rehabilitation of hip fracture in acute-care and
rehabilitation settings.
Researchers
Adrian Bauman (UNSW), Ian Cameron (USyd), Graham Kerr (QUT), Suzanne
Kuys (PAH), Lyn March (RNSH), Solomon Ni (USyd), Brian Oldenburg (QUT),
Sue Ogle (RNSH), Anthony Parker (QUT), Cathie Sherrington (POWMRI), Peter
Silburn (QUT), Paul Varghese (PAH), Mandy Williams (SWSAHS).
Project F5. Safe
Footwear and Walking Surfaces (Leaders:
A/Prof Julie
Steele, Dr Hylton Menz)
Footwear
contributes to approximately half of falls in older people
[36]
with most older people
choosing shoes for comfort rather than safety
[37]
As a large proportion of older adults wear poorly fitting slippers
indoors
[37, 38]
research pertaining to
factors associated with safe indoor footwear is urgently needed This
project will include two studies which will examine footwear factors
contributing to falls in older persons.
The studies will be undertaken at the Biomechanics Research
Laboratory, University of Wollongong, the Prince of Wales Medical Research
Institute and the School of Safety Science, University of NSW.
Study A. Shoe design
Background
The
main shoe features that affect postural stability are heel height, midsole
stiffness, heel-collar height, and midsole flaring
[39]
. Elevated heels impair
standing balance and increase the risk of falling in older people
[40]
. Shoes with compliant
midsoles impair foot position sense and make older subjects less stable
when walking on narrow beams compared with shoes that have stiff midsoles
[41]
, and high heel-collars may
benefit stability in some older people
[42]
. Lateral flaring of shoe
midsoles is used to increase lateral stability in sports shoes although no
studies have evaluated this potentially beneficial design in older people.
Aims
To
identify those features of shoes that are beneficial to stability in older
people, and those that are hazardous. To correlate anthropometrical data
and physiological factors known to be associated with falls (strength,
proprioception, reaction time, vision, standing balance) with response
patterns for different footwear.
Subjects
Subjects
over 65 years (n=60) and a younger group (n=30) will be recruited.
Study
design
This
will be a cross-sectional descriptive study with each subject undergoing
one assessment.
Procedures/measurement
tools
Subjects
will walk on level and uneven walkways in different footwear in which the
shoe features outlined above are controlled. The new technique being
developing to assess walking stability by measuring head and trunk
accelerations when walking on flat and uneven surfaces (F1) will be
applied to evaluate walking stability. Kinematic, ground reaction forces
and electromyographic recordings will be used to measure standard gait
parameters, foot clearance and their variability, and to identify trips,
slips and recovery. It is expected that the technique and understanding
obtained from the trips and slips project (F1) will be applied here to
determine shoe characteristics necessary to minimize and recover from
these events.
Study B. Slip
resistance
Background
About
one quarter of falls are attributed to slips that occur when there is
inadequate resistance at the heel contact phase of walking. Most research
on sole slip resistance has examined occupational footwear by testing this
footwear type on force plates. Consequently, maximizing slip resistance
has become an important goal in shoe design
[43, 44]
. However, this is not
necessarily the optimal condition for falls and injury prevention in older
people generally or for specific groups of older people. For example,
shuffling is common in some older clinical groups (e.g. Parkinson’s
Disease and hemiparesis) and can be viewed as an adaptive and protective
strategy
[45]
. Non-slip shoes prevent
shuffling, which may explain why Parkinson’s Disease patients often
dislike them.
Aims
This
study will develop patterns of heel shape, and sole tread and material
that will optimize slip resistance when walking.
Subjects
Subjects
over 65 years (n=60) and a younger group (n=30) will be recruited.
Study
design
This
will be a cross-sectional descriptive study with each subject undergoing
one assessment.
Procedures/measurement
tools
Modifying
the geometry of the heel region and sole material significantly alters
slip resistance in casual footwear
[46]
. This will be done in a
controlled manner and frictional resistances will be measured using a
dynamic friction-testing device. Analysis of gait in older and younger
subjects wearing shoes with different slip resistances while walking on
different indoor and outdoor surfaces will proceed as in Study A (“Shoe design”).
Study B. Biomechanics of slipping in people with rheumatoid arthritis (Bridget Munro)
Background
Aims
Subjects
Study
Design
Procedures/measurement
tools
For the whole F5
Project (studies A-B)
Outcomes
·
Design
recommendations for safe shoes for indoor and outdoor use.
Researchers
Anthony Parker (QUT), Guy Bashford (UoW), John Evans (QUT), Richard
Fitzpatrick (POWMRI), Stephen Lord (POWMRI), Bridget Munro (UoW), Hylton
Menz (UWS), Julie Steele (UoW).
Project F6.
Developing a Falls Assessment Screen (Leaders:
A/Prof Stephen
Lord, Dr Richard Fitzpatrick)
To
identify people at risk of falls injury, simple assessment screens need to
be used in a wide variety of clinical settings and populations. The
important “products” of the research outlined above will be validated
falls assessment screens that can be used in general practice clinics,
acute hospitals, nursing homes, physiotherapy departments and falls
clinics. These screens will range from simple pencil and paper checklists
to computer-generated assessment reports. Each assessment will be
evaluated for sensitivity and specificity for predicting falls, and
feasibility and usefulness in clinical settings. This project will be
based at the Prince of Wales Medical research Institute.
Aims
To
develop a very simple screen requiring minimal equipment which will be
applicable for general practice and community settings. To develop two
more precise versions of the assessment, a short screening version and a
longer comprehensive version.
Procedures
It
is anticipated that the screening version will take 10-15 minutes to
administer and will be suitable for acute hospitals and long-term care
institutions. The comprehensive version, that will take 45 minutes to
administer, will be suitable for rehabilitation, physiotherapy and
occupational therapy settings and for dedicated falls clinics. An Internet
program that generates a falls-risk report from prototype assessments can
be seen at http://www.powmri.unsw.edu.au/FBRG/FBRGhome.htm.
These assessments contain tests of vision, peripheral sensation, lower
limb strength, reaction time and balance during standing. Performances in
these tests, when included in discriminant analyses, can correctly
classify fallers and non-fallers with an accuracy of 75%
[1]
.
By
using the research findings from the studies outlined above, we expect to
greatly enhance these assessment screens, by including better tests and
broadening the scope of the assessment to include psychosocial, medical
and neuropsychological domains, and to streamline the assessment
procedures to tailor them to different clinical settings.
These
tools will be evaluated by questionnaire for users in different settings
after a one-month trial period.
Outcomes
·
Development
of a range of validated screens that will accurately identify older people
at risk of falling. These tests will be able to be used by GPs, nurses,
physiotherapists, occupational therapists and exercise scientists.
Researchers
Richard Fitzpatrick (POWMRI), Stephen Lord (POWMRI),
Project T1. Test
development and validation (Leaders:
A/Prof Joanne
Wood, Dr Kaarin Anstey)
Background
In
this study we will develop and test a model that integrates a wide range
of sensorimotor and cognitive factors involved in driving performance. A
similar approach has been applied successfully to develop the falls injury
program.
Aims
To
develop and test a model to predict driving performance.
Subjects
Of
the random sample of 500 adults aged 70 and older recruited from the
electoral role for the injuries risk program (ie those subjects in the
large prospective study described in F2), it is expected that 60% will be
drivers. This group of approximately 300 subjects will participate in this
older drivers component (T1). This allows at least 10 subjects per
predictor variable for the 2 types of outcome measure (driving tests &
crash statistics), a number adequate for multiple regression analysis
[51]
. Analyses based on
previous studies
[48]
indicate that this is
sufficient to detect significant multiple associations between driver
performance and predictor variables from the 3 key domains (cognitive,
sensory & motor).
Study
design
This
study will be cross-sectional. It will compare results on driving tests
and predictor variables. This study will be conducted at both the Prince
of Wales Medical Research Institute and the Queensland University of
Technology.
Procedures/measurement
tools
Participants
will be tested in 2 sessions, the first comprising sensorimotor and
cognitive performance measures and questionnaires, and the second will be
an on-road driving test. The measures used in the study are classified as
either predictor variables or outcome
measures of driving performance.
Predictor variables
Cognition:
Cognitive tests will be administered that include measures of
cognitive domains implicated in driving
[48, 52]
. Where possible, tests
will have formats relevant to driving, many involving stimuli and
responses in more than one sensory modality or motor domain (e.g. vision +
hearing, feet + hands). Some tests in wide use have been validated whereas
others will be specifically designed and evaluated for assessing skills
required for driving.
Individual
cognitive tests are briefly described here. Processing
speed will be measured using a computerized digit substitution test in
which subjects identify whether a number corresponds with a symbol in a
code table
[53]
. Choice
reaction time will be measured with a 3-choice test with stimuli in
the format of a traffic light, with red, green and orange requiring
different responses in hands and feet. Selective
attention and response inhibition will be measured with a modified
Stroop task
[54]
, also in traffic light
format, where subjects first name the colour, then press colour-compatible
keys, and then incompatible keys. Visual
search and attention will be assessed with a digit-vigilance task
[55]
in which subjects identify
target digits in large arrays of numbers. Task
switching ability will be measured with the Trailmaking Test
[56]
where subjects connect
consecutive numbers then numbers and letters. Aurally
cued attention switching is tested with a dichotic listening paradigm
in which subjects must respond to signals relevant to driving presented in
either ear
[57]
. Divided
attention and working memory will be assessed in a task in which cars
appearing on screen are counted while subjects listen for target stimuli
such as car horns, car engines and brakes, occurring in a background
noise. The traditional short-term
memory test of word recall, a 3-item road
knowledge test with a question about roundabouts, when to give way and
right hand turns, and an apraxia
test (copying a 3-D figure) will be administered. Asking subjects
prior to the assessment tests to note the level of a petrol meter after
the completion of the assessment will test prospective
memory. Reasoning will be assessed using 12 items from Raven’s
Progressive Matrices
[58]
. The Mini-Mental State Examination (MMSE) will be used to evaluate the
driving relevance of this widely used dementia screen. A new Driving
Vigilance and Attention Test, will integrate the cognitive processes
of driving (attention, vigilance, divided attention and complex reaction
time) in a shorter format than if each is measured separately. This
computerized test involves responding with the foot to one of 2 stimuli
(cars) on the screen with either a “stop” or “go” response. After
20 trials, subjects must begin searching for visual cues from the left or
right. Correct responses to the unpredictable stimuli require visual
search, vigilance, attention switching and visual attention, and adequate
performance requires comprehension of the instructions and short-term
memory for the instructions.
Motor
performance.
Motor tasks include a measure of coordination, grip strength,
endurance and spinal rotation. A computerized visual tracking test will
require subjects to use a steering wheel to maintain a cursor position
(car) within target boundaries (road) that are displayed as a continuously
changing waveform. Changing road width and speed alters task difficulty.
Performance measures are RMS tracking error, velocity, movement amplitudes
and velocities, and response frequency
[59, 60]
.
Vision. Unlike the standard
high-contrast letter charts currently used in licensing centres, we have
developed a prototype visual assessment screen with tests relevant to
driving (motion perception, visual field size and contrast sensitivity).
Standard tests in wide use and new specifically designed tests relevant to
driving will be administered. Individual visual tests are briefly
described here. Visual acuity,
both high and low contrast, will be measured with The Australian Vision
Chart 5 (standard logMAR chart). Dot
Motion Sensitivity: Subjects identify
the direction of movement of a small central panel of dots against a field
of randomly moving bright dots, all of which are presented against a black
background. Thresholds are determined using a forced-choice staircase
procedure and calculated using probit analysis
[61]
. Useful
Field of View (UFOV):
This is a measure of the functional visual field for peripheral search and
localization, where targets are presented centrally and peripherally for
90ms. Subjects are required to detect the central targets and at the same
time determine the location of the peripheral targets presented against a
distracter array. Static
Visual Fields: Static
visual fields are measured using the Humphrey Field Analyser for the full
field 81 point test using a threshold-related quantity defects strategy. Pelli-Robson
Letter Contrast Sensitivity: Letter
contrast sensitivity is measured using the Pelli-Robson chart, which uses
relatively large letters at varying levels of contrast.
Health. Measures of self-rated
health, disease history, medications and a brief form of the Depression,
Anxiety and Stress Scale
[62]
will be administered.
Outcome measures
Driving
performance (these tests will only be conducted in the Brisbane arm of the
study).
Objective measurements of on-the-road driving skills in
closed-track and in-traffic conditions will be made using an instrumented
car. Closed-track assessment provides highly standardized conditions
whereas in-traffic assessment represents actual driving conditions, and
together will provide a complete assessment of driving performance. These
validated measures
[63, 64]
are more relevant than
performance in simulators because of the very different sensorimotor
conditions (e.g. acceleration forces, vestibular input, visual-vestibular
conflict). For both closed-track and in-traffic assessments an overall
driving rating as well as standardized scoring of specific driving tasks
will be recorded. Data collected on 150 subjects show that closed-track
performance significantly predicts in-traffic performance
[64]
, and show a high
association between the research raters. Closed
Road: Driving performance, in daylight conditions, will be assessed on
a closed road circuit
[63]
. This circuit has a
standard bitumen road surface, markings and signage. Measures of driving
performance include: total driving time, road sign recognition, road
hazard recognition, manoeuvering, and gap perception. The instrumented
vehicle also allows measures of driving reaction times, braking and
acceleration, steering angle and speed. A permanent video record of each
run will be obtained. There is a high between-session reliability of
driving scores (r=0.82; p<0.001). Open
Road Measures: Assessment of driving performance under in-traffic
conditions is undertaken using standardized validated techniques
[64]
. The 15 km driving route
consists of city and suburban streets, simple and complex intersections
and a range of traffic densities. Each assessment is undertaken at a
similar time of day (off-peak traffic) for each subject to minimize
variations in road conditions. A dual brake vehicle is used, with a
driving instructor experienced in driving assessment who gives an overall
rating of driver safety. A research rater, experienced in assessment of
driving and rehabilitation, scores subjects independently on all driving
tasks
[64]
. The driving tasks include
turns, merges, responses to traffic signs and signals, driving straight
and performing complex manoeuvers. Subjects are also required to find
their way to a particular destination. Five categories of behaviours are
recorded: scanning of the environment, lane position, following distance,
speed and use of turn signals.
Crash
statistics. Will
be obtained where participant consent is granted. The study would be
enhanced by state crash records which will be gathered if the participant
provides consent.
Self
reported crashes and driving habits.
A questionnaire of crashes and driving habits will be administered
to determine kilometers driven and where and why they drive. It is adapted
from an existing questionaire with extra questions on changes to driving
patterns
[65]
.
Statistical analysis
Multiple
regression analysis will determine which combination of visual, cognitive
and motor factors best predict the driving performance measure. Logistic
regression will be used to identify measures that predict road crashes. Of
particular interest will be the tests most easily administered in the
following prospective study (T2).
Outcomes
·
Development
of a validated screening assessment to accurately identify drivers who may
not be capable of safe driving due to visual, cognitive or sensorimotor
impairment.
Researchers
Kaarin
Anstey (POWMRI), Guy Bashford (UoW), Vida Bliokas (PKH), Ian Cameron (USyd),
Leo Carney (QUT), Stephen Lord (POWMRI), Paul Mitchell (U Syd), Joanne
Wood (QUT).
Project T2.
Prospective cohort study of risk factors for motor vehicle crashes
(Leaders: Dr Kaarin Anstey, A/Prof Stephen Lord, A/Prof Joanne Wood)
Background
A
large prospective cohort study is planned to determine which tests or
combination of tests best predict major and multiple minor motor vehicle
crashes and traffic infringements. We acknowledge that there could be
political and social sensitivities about this study, and other
implementation issues such as possible difficulties in recruiting older
volunteer subjects. We plan to work closely with older people's
organizations and government agencies to ensure acceptability and
feasibility. Negotiations have commenced with the Roads and Traffic
Authority, NSW (RTA) and they have agreed to in-principle support pending
ministerial approval. In years 4 & 5 of this program, i.e. after T1,
we will recruit subjects for a 5-year prospective cohort study of drivers
aged 80 and older. These drivers will be followed for 5 years after the
end of this program and we will seek funding as required. We anticipate
the final outcome of this research to be a brief screening battery that
takes less than 10 minutes to administer, and identifies a very high
proportion of “at risk” older drivers. This will provide an objective
tool that can be used by traffic authorities in licensing. Such a model
may be adapted for use in evaluating individuals' fitness to drive after
head injury or stroke. It may also be used to evaluate the effect of
psychotropic medication and alcohol on driving.
Aims
To
determine which tests or combination of tests best predict major and
multiple minor motor vehicle crashes and traffic infringements.
Subjects
Drivers
aged 80 and older (n=2500) will be recruited into the study. Subjects aged
80-84 will be referred by the RTA for the assessment at the time of their
license renewal. For those over 85 the assessment will coincide with their
first annual assessment within the study period. Testing will be conducted
at a mobile unit in convenient locations within the Sydney metropolitan
area. Power analyses based on RTA crash statistics per 10,000 licenses and
prevalence of poor cognitive and visual performance based on published
studies
[66, 67]
showed that approximately
2500 subjects are required to detect a relative risk of 3.0 over follow-up
period of 5 years, taking into account sample attrition due to death and
cessation of driving.
Study
design
A
5-year prospective cohort study which will be based at the Prince of Wales
Medical Research Institute.
Procedures/measurement
tools
A
short form of the battery devised in T1 will be administered. It will
include the significant independent predictors of driving performance and
crashes, but until T1 is concluded we cannot determine the exact tests. We
anticipate that it will include at least one or two vision tests, one
motor test and one or two cognitive tests.
Results
of the assessments will be linked to state government crash data and
followed for a period of 5 years. The relevant government authority will
do the linking and researchers will obtain statistical data that cannot be
associated with individuals. Data analysis will allow for identification
of the predictive utility and validity of the tests, and allow for further
refinement.
Outcomes
·
Development,
in conjunction with Road Traffic Authorities, of guidelines and tests for
definitive assessment of driving ability in older drivers.
Researchers
Adrian
Bauman (UNSW), Kaarin Anstey (POWMRI), Guy Bashford (UoW), Vida Bliokas (PKH),
Ian Cameron (USyd), Leo Carney (QUT), Stephen Lord (POWMRI), Paul Mitchell
(U Syd), Beth Newman (QUT), Joanne Wood (QUT).
Staffing
Three research assistants to undertake subject recruitment, conduct interviews, administer physical and psychological tests, undertake data coding and assist with data analysis.
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