Age, Mobility & Risk
Version 2.2 Tanya Fosdick September 2012
CONTENTS EXECUTIVE SUMMARY ............................................................................................................................ 3 INTRODUCTION ....................................................................................................................................... 5 RISK PROFILE ........................................................................................................................................... 6 CRASH PROFILES ................................................................................................................................. 6 WHAT? ............................................................................................................................................ 6 WHEN? .......................................................................................................................................... 10 WHERE?......................................................................................................................................... 11 HOW? ............................................................................................................................................ 12 OLDER CAR DRIVER PROFILES ........................................................................................................... 14 MOSAIC ANALYSIS ............................................................................................................................. 19 INDEX OF MULTIPLE DEPRIVATION (IMD) ........................................................................................ 21 ENGAGEMENT PLAN ......................................................................................................................... 27 Self Assessment ............................................................................................................................ 27 Manual for Older Drivers .............................................................................................................. 27 Flourish Course ............................................................................................................................. 27 Driving Assessments ..................................................................................................................... 27 Website & Apps ............................................................................................................................ 27 Messages ....................................................................................................................................... 28 EVALUATION ..................................................................................................................................... 29 CURRENT LOCAL SCHEMES ............................................................................................................... 30 SUMMARY OF OTHER EVIDENCE AND SUCCESSFUL SCHEMES ........................................................ 30 EXISTING SCHEMES ....................................................................................................................... 31
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EXECUTIVE SUMMARY Analysis of collisions involving people over the age of 60 years, either resident of or injured within Berkshire, has been undertaken to determine the extent of the issue. The following is a summary of this report’s findings:
21% of Berkshire’s fatalities between 2006 and 2010 were aged over 60 years. 60% of Berkshire’s over 60 year old casualties were drivers. These drivers are most likely to be aged between 60 and 69 years old. 84% of over 60 year old casualties injured in Berkshire were involved in a collision with a driver aged 60 years or over (suggesting that passenger and pedestrian casualty rates could be positively affected by reductions in driver risk). Passengers of older drivers tend to be of similar age to the driver and so are likely to be peers or partners. Children (perhaps grandchildren) appear as passengers for some of the younger age group of 60 to 64 year olds. Over 60 year old car drivers from Berkshire tend to crash on weekdays and during the day. This is consistent with national findings where some older drivers self‐regulate to avoid difficult situations. Most of their collisions occur in daylight and fine weather. 69% were involved in collisions on 30mph or 40mph roads. 39% were not at a junction whereas 30% were at a T‐junction and 12% were at a roundabout. 47% of the drivers were going straight ahead; 11% were moving off or stopping; and 14% were turning right. Two‐thirds of the drivers were involved in collisions with one other vehicle. 56% of Berkshire’s older car drivers were considered to be at fault in their collision. This is consistent with national research that found that 85 to 89 year olds were four times more likely to have caused the crash than to have been innocently involved. The most common contributory factors assigned to Berkshire’s older drivers are: ‘failed to look properly’; ‘failed to judge other person’s path or speed’; and ‘poor turn or manoeuvre’. ‘Illness or disability, mental or physical’ and ‘Uncorrected, defective eyesight’ are more likely to be attributed to older drivers than all drivers. The highest percentages of collision‐involved older drivers come from West Berkshire; Windsor and Maidenhead; and Wokingham. These areas have also seen the largest percentage increases in the older population since 1981 and also have the highest percentages of crash‐involved older drivers from the 25% least deprived IMD deciles. 65% of older drivers involved in collisions in Berkshire came from Berkshire. Super output areas within Wokingham, Bracknell Forest and Windsor and Maidenhead have been highlighted as areas of high risk based on average annual rates of collision involvement. One area of Wokingham has an average annual rate of one‐in‐332 older people involved in injury collisions as drivers. Three Mosaic Groups were highlighted as over‐represented amongst Berkshire’s older drivers – these are Groups C, D and L. Groups C and D share some characteristics – both types of people are successful, comfortably off and enjoy the arts and classical music. They are well educated and are likely to have grown up children. They also have high internet usage. This Group is over‐ represented in the younger age group but does not represent as many drivers in the collision statistics. However, the analysis did identify that there were some less affluent older drivers that need to be accounted for. Their communication preferences are face‐to‐face engagement, local newspapers and post.
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Three personas have been created to allow us to visualise the target audience and shape the intervention to fit their needs. Other research has found that a combination of on‐road training and in‐class education, tailored to specific needs, can be a positive intervention with older car drivers. It has also been recommended that ceasing driving should be made as painless as possible and that an information pack, providing details of alternative transport and forms of support, should be provided. There have been a variety of schemes based on these lines that have been provided across the country The intervention culminating from the research is called Flourish and is about assessment and self‐regulation being key to safer mobility in later life. The intervention is comprised of multiple components, including self‐assessment; a manual of advice; an educational course; driving assessments; and website and apps. All components are based on the research contained within this Insight Study. Process and outcome evaluations will be undertaken by measuring the number of self‐ assessments undertaken and how many subsequent Flourish courses and driving assessments booked.
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INTRODUCTION It is a known fact that there is an ageing population – a combination of lower birth rates and reductions in mortality have led to a situation where there is a greater proportion of older people in the population than younger people. “Currently in the UK around one in six of the population is aged 65 or over, and it is predicted that by 2050 one in five will be.”i With increases in the older population, measures should be put in place to ensure their independence, mobility and safety when using the roads. This report sets out analysis undertaken using MAST, an online analysis tool which combines casualty and collision data from the Department for Transport with socio‐demographic insights created by Experian through Mosaic Public Sector. The postcodes of drivers and casualties involved in collisions are used to determine which Mosaic Groups and Types these individuals are likely to belong to and this can be used by road safety professionals to understand who needs to be targeted in road safety interventions. The report looks at older people involved in collisions in Berkshire and also, more importantly, focuses on older people who live in Berkshire who have been involved in injury collisions. The intention of this report is to provide the road safety practitioner in Berkshire with a full understanding of the types of collision involving older people and to equip them with the tools to target the issue. The report works through the analysis by first determining the extent to which older people are involved in collisions in Berkshire and in what context they are involved. The analysis shows that, overwhelmingly, older people are most likely to be injured in Berkshire as car drivers. As such, the remainder of the analysis focuses most intensively on car drivers who are aged over 60 years old, who are from Berkshire and who were involved in an injury collision between 2006 and 2010. Environmental factors, such as when, where and how the older car drivers were involved in collisions are explored and provide information on the topics and issues that could be focused upon within an intervention. A large part of the analysis focuses on profiling the older car driver, with the aim of producing ‘personas’ that can be used to visualise the target audience. These personas are created using a variety of socio‐demographic data, including looking at Indices of Multiple Deprivation, rurality and Mosaic Groups. Profiling in this way allows the practitioner to understand how the older drivers will respond to a road safety intervention and in what way it should be delivered. All of this culminates in an ‘Engagement Plan’, where experts from Safer Roads have used all the available information from the analysis, external research, and learning outcomes from other older driver schemes, to create an intervention design. The report also contains a plan for evaluating the intervention, both in terms of assessing the processes involved in delivery and the overall effectiveness of the scheme. Principles and tools developed and promoted by RoSPA are used for creating the evaluation design.ii
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RISK PROFILE This profile covers two distinct areas: information about the crash and information about the person involved. Both are relevant to the analysis and are considered separately.
CRASH PROFILES WHAT? In order to determine who to focus on for the analysis into older road users in Berkshire, some preparatory work was undertaken. Firstly, a needs analysis was undertaken to establish whether or not older road users represented a road risk in Berkshire. National research has found that: From the evidence available it is possible to deduce that older people are as safe behind the wheel as the rest of the population. Contrary to popular belief the majority of older drivers have good driving records. Up to age 80 most older drivers appear to perform as well as middle‐aged motorists and after this age only a small minority of active older drivers, often travelling less than approximately 2000 miles per year, are at an elevated risk per mile basis. The fatality rate per driving licence increases with age because as people get older they become increasingly frail, and so are more vulnerable to injury when involved in an accident. Older drivers are in fact involved in fewer slight accidents than younger travelers, but a disproportionate number of older travelers are killed in road accidents due to frailty. Drivers also tend to reduce the distance they travel as they get older, which increases the casualty rate per mile driven for the group. iii This study seeks to uncover what the casualty and collision issues are in Berkshire in relation to older residents; how these findings compare to the national picture and what interventions could be adopted to reduce Berkshire’s older citizens’ collision involvement. Looking at collision data from 2006 to 2010, there were 141 people over the age of 60 years old who were killed on Berkshire’s roads. This represents 21% of Berkshire’s fatalities. In terms of serious and slight casualties, over 60 year olds represented 12% and 9% of Berkshire’s casualties respectively. It would suggest that over 60 year olds are not over‐represented amongst Berkshire’s casualties generally but are more likely to be killed or seriously injured (KSI) than the average Berkshire casualty – 15% of over 60 years injured in Berkshire are KSI casualties compared to 10% for all casualties injured in Berkshire. To put this into context using population data, over 65 year olds represented 13% of Berkshire’s population in 2010 but, on average, 17% of fatal casualties in Berkshire. When indices are applied to the average annual rates of fatalities per head of population, over 65 year olds have an index of 123. This is in comparison to the index of 121 applied to 16 to 64 year olds in Berkshire, which is a much larger age range (unfortunately there are restrictions in the available population data available by age at local authority level). The over‐representation as fatal and serious casualties could be due to the type of collision older people are involved in; their vulnerability to injury and likelihood to suffer a collision due to frailty and existing conditions; or a combination of the two. The analysis would suggest that interventions aimed at older road users would be beneficial to reduce this severity ratio, especially when the ageing population is considered.
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350 300 250 200 150 100 50 0 60‐64
65‐69
70‐74 Driver
75‐79 Passenger
80‐84
85‐89
90+
Pedestrian
The next thing to consider is how these older road users became casualties. The chart above shows the casualty class of those over 60 year olds injured in Berkshire between 2006 and 2010. It provides several pieces of useful information. Firstly, it shows that older road users are most likely to be involved in collisions as drivers. In fact, 60% of the over 60 year olds injured in Berkshire were drivers. Secondly, it shows distinct reductions in collision involvement as drivers age. There is a sharp reduction in the number of driver casualties from the 60 to 64 age range to 65 to 69 age range and then a further steady reduction from 65 to 69 years down to 80 to 84 years. The downward trend continues to the 90+ age range where very few drivers are injured. There are less dramatic reductions in passengers and pedestrians as the ages of casualties increases. 200
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The last area to consider is to determine how the crash involvement of over 60 year olds has changed, if at all, in Berkshire over recent years. The previous chart shows the number of over 60 year old casualties, by casualty class, since 2004. It shows that the number of older driver casualties increased in 2005, remained steady until 2008 and has decreased in 2010 to just below the 2004 figure. The number of older pedestrians injured in Berkshire each year has remained fairly static and older passenger numbers have actually increased. It also shows the number of casualties of all ages injured in Berkshire (as the line). This line shows a similar trend to the older drivers pattern: an increase to 2006 in the number of casualties, followed by a plateau and then a reduction after 2007. To determine if there is an emerging trend in older casualties, all classes of older casualty have been compared over time with the total number of casualties of all ages in Berkshire and, to put it into context, for the UK. The following chart shows casualty rates compared to the 2004 to 2006 baseline. It shows that for the whole of the UK and for Berkshire, the numbers of 60 plus casualties are reducing at slower rates than for casualties of all ages (although for 2010, the gap in Berkshire was less pronounced).
Casualty Rates by Age 120% 100% 80% 60% 40% 20% 0% 2004
2005 UK All Ages
2006 UK 60+
2007
2008 Berks All Ages
2009
2010
Berks 60+
Looking at the relationships between casualty class and driver age, the analysis found that, on average, 84% of over 60 year olds injured in Berkshire were involved in collisions where the related drivers was over 60 years old. This means that either the over 60 year old driver was the casualty; the over 60 year old passenger was in a vehicle where the driver was over 60 years old; or the over 60 year old pedestrian was struck by a driver who was aged over 60 years old. The analysis also found that the percentage of over 60 year old passengers injured in an older driver’s vehicle increased with the driver’s age – 36% of the passengers injured in 60 to 64 year old drivers’ vehicles were aged over 60 years old compared to 91% for 85 to 89 year olds. The relationships between age of passenger and age of older driver are shown in the chart below. The analysis has been undertaken for the whole of the UK to increase the sample size; however, the Page | 8
pattern is very similar in Berkshire. It shows how the ages of passengers increase with driver age, implying that the passengers are partners and peers. For the younger older driver, there are younger passengers and this could reflect time spent caring for grandchildren in the early stages of retirement. These findings are consistent with an Australian study, which found that: older drivers have been shown not to pose a substantial threat to other road users. Once involved in a crash, older drivers are likely to be the ones either killed or injured. The next largest group consists of older drivers’ passengers, themselves likely to be elderly.iv
UK Age of Passenger verses Age of Driver 2500 2000 1500 1000 500 0
60‐64
65‐69
70‐74
75‐79
80‐84
85‐89
90+
Lastly, the vehicle type of older drivers involved in collisions in Berkshire was examined. It found that 86% of the over 60 year olds were driving a car. Based on the scoping analysis, it has been decided that the rest of the report will focus on over 60 year old car drivers as not only do they represent the largest casualty and driver group amongst older road users in Berkshire but there are potential casualty reduction benefits to be gained for older passengers and older pedestrians from reducing older driver crash involvement. Analysis of Berkshire’s pedestrians aged over 60 years old found that 15% were struck by a driver aged over 60 years old. Looking at the times of day for when older drivers, passengers and pedestrians are all injured shows that they all share the same time patterns as shown overleaf. This would suggest that older people tend to be out and about at the same times of day thus bringing older drivers and older pedestrians into conflict. There have sadly been cases across the country where older drivers have run over older friends and relatives (often on driveways and in car parks) by accidently pressing the accelerator instead of the brake and reversing instead of moving forward. It could be that restricted mobility of the older pedestrians prevents them from moving out of the way when these errors occur.v
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WHEN? The remainder of the analysis focuses on older drivers known to be from Berkshire rather than those who were involved in collisions in Berkshire but could live anywhere in the country. Analysis of the collisions involving over 60 year old car drivers from Berkshire produces the following chart. It clearly shows that Berkshire’s older drivers tend to be involved in collisions during the daytime (between 6am and 8pm) and are more likely to be involved in a collision on weekdays than weekends. In fact, Berkshire’s older drivers are 29% less likely to be involved in a collision on an average weekend than an average weekday. This compares to all Berkshire’s car drivers where they are only 17% less likely to be involved in a collision on an average weekend than an average weekday. There are not significant differences between individual weekdays, although 23% of the older drivers were involved in collisions on Tuesdays compared to 16% on Mondays. Some assumptions about journey purpose and potential self‐regulation could be made here – it might be the case that family days outs and visits which occur at weekends are when younger family members are more likely to drive their older relatives. Older drivers may have less choice about driving on weekdays because family support is unavailable and therefore in order to access shops, medical care and social situations, they must drive themselves. It could be that they practice self‐regulation, though, and opt to drive when they believe traffic is going to be lightest. 120 100 80 60 40 20
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Older car drivers from Berkshire were involved in collisions throughout the year, with slight increases in June and September and a slight decrease in February. Only 19% of Berkshire older drivers were involved in collisions in darkness and only 6% were in crashes which occurred at night or with no lit streetlights. For all Berkshire’s car drivers, 28% were involved in collisions in darkness, with 8% with no lighting at all. 84% of Berkshire older drivers were involved in collisions in fine weather (no wind or rain) compared to 82% for all Berkshire’s car drivers. These figures reflect national analysis where: around the age of 60 to 65 many older drivers adapt their lifestyle and change their driving patterns, thus avoiding driving in situations where they are uncomfortable: they avoid Page | 10
driving in the rain so they have fewer accidents when it is wet and more in dry weather, they avoid peak hour traffic periods but have more accidents between 10am and 4pm and they drive less at night so have fewer accidents in the dark but more in daylight.vi
WHERE? Analysis of the locations in which older car drivers from Berkshire were involved in collisions shows that 69% of the drivers crashed on 30mph or 40mph roads. Fifty‐four percent of the older drivers crashed on urban roads and they were most likely to be involved in a collision on A roads or unclassified roads (46% and 33% respectively). The following chart shows the details of the junctions at which Berkshire’s older car drivers were involved in collisions. It shows that 39% of the older drivers were not a junction when they were involved in a collision; a further 30% were at a T‐junction and 12% were at a roundabout. Slip Roads 1% Private Entrance 7%
Multiple Junction Other 1% Types 1%
Roundabou t 12% Mini Roundabout 2%
No Junction 39%
Crossroads 8%
T‐Junction 30%
The areas of Berkshire in which older casualties were involved in collisions between 2006 and 2010 were also looked at and were thematically mapped to show areas of concentration at the medium super output area level (MSOA). There were four MSOAs which had the highest number of over 60 year old casualties between 2006 and 2010 and these are shown in the darkest blue on the map. The areas were Reading 011 (covering the Civic Centre, King’s Meadow, Coley and HM Prison); Slough 014 (covering Colnbrook with Poyle Parish); West Berkshire 001 (covering Farnbrough, East Isley, Compton and Chaddleworth); and lastly Windsor and Maidenhead 002 (covering Cookham Rise, Waltham St Lawrence, Shurlock Row and Warren Row).
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HOW? Looking at the circumstances surrounding the collisions, analysis found that two‐thirds of the older car drivers from Berkshire were involved in a crash with one other vehicle. In terms of manoeuvres, 47% of the older drivers were going ahead in a straight line; 11% were moving off or stopping; and a further 14% were turning right. It is possible to analyse the contributory factors (CF) recorded by a police officer when completing the collision records. Individual CFs can be attributed to individual vehicles, which allows a basic analysis of the reasons for crashes. The following analysis only looks at collisions investigated at the scene by an officer and even then, it needs to be remembered that these factors reflect the officer’s opinion at the time of reporting and may not be the result of extensive investigation. Analysis shows that 56% of Berkshire’s older car drivers were considered to be at fault in their collisions. The next chart shows that contributory factors assigned to Berkshire drivers initially decreases from a peak with young drivers down to a plateau at 35 years old. Blameworthiness then increases with each age group from 70 years old onwards. As contributory factors are subjective and are the reporting Police Officer’s opinion at the time of the incident, there is the potential for prejudices within reporting which could potentially account for the higher percentages of blame attributed to younger and older drivers. It could also be the case that incidents involving younger and older drivers are more clear‐cut and therefore it is easier to attribute CFs or that because of higher casualty severities, there is better investigation.
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CFs atrributed to Drivers by Age 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
A qualitative study of collisions involving over 60 year olds was undertaken to get a more in‐depth understanding of the circumstances of older driver collisions. The study involved taking 2,000 collision reports from 3 Midlands Police Forces and working through the full sequential nature of each collision and examining witness reports, without any time pressures or prejudices from the scene. vii The study found very similar results to the CFs attributed to Berkshire’s car drivers and are shown in the next chart. It found that 60‐64 year olds and 65‐69 year olds were no more likely to have caused a crash than they were to have been innocently involved in such a crash. However, by the second to last age‐band (85‐89 years), older drivers as a whole appeared to be over four times as likely to have caused a crash than they were to have been innocently involved.viii
Blameworthiness Ratios for Older Drivers 10 9 8 7 6 5 4 3 2 1 0 60‐64
65‐69
70‐74 All
75‐79 Male
80‐84
85‐89
90+
Female
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The most common CFs attributed to older drivers were ‘Failed to look properly’ – 27%, ‘Failed to judge other person’s path or speed’ – 12% and ‘Poor turn or manoeuvre’ – 7%. These percentages do not differ significantly when compared to all Berkshire car drivers (21%, 12% and 6% respectively) and therefore apart from ‘Failed to look properly’; older drivers are not behaving particularly differently to drivers of all ages. Two CFs which are commonly associated with older drivers are ‘Illness or disability, mental or physical’ and ‘Uncorrected, defective eyesight’. The illness CF was assigned to 4% of older drivers (compared to 1% of all ages of car drivers) and the eyesight CF was assigned to 1% of older drivers (compared to 0% of all car drivers). It could be due to better reporting that these CFs are attributed more to older drivers in that police officers are giving consideration to these factors for older drivers and undertaking more investigation.
OLDER CAR DRIVER PROFILES Moving away from the ‘when, where and how’ questions, we can now explore the ‘who’ question. It is essential to understand more about the people involved in the collisions, including information about their everyday lives, as well as demographics. 600
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Unsurprisingly, the largest age band of older Berkshire drivers is the 60 to 64 year old group. This group accounts for one‐third of all over 60 year old car drivers from Berkshire. The age range 60 to 74 years old accounts for 76% of all Berkshire’s over 60 year old car drivers. Two‐thirds of the over 60 year old car drivers from Berkshire are men and this increases to 72% for over 75 year olds. The percentages of men involved in collisions are perhaps to be expected given the ratios of licence holders: “More than 30 years ago, only one in three men and one in 20 women aged over 70 held a driving licence; today, three in four men and one in three women are licensed to drive.”ix Looking at the trips older car drivers make:
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“Men in their 60s drive for almost as many trips annually as men in their 40s and 50s; men in their 70s make more trips as drivers than do men in their late teens and 20s Older people rely heavily on their cars. Two thirds of trips made by men and one third by women in their 60s are as car drivers. In their 70s, more than half of trips by men and a fifth by women are as car drivers. Women make far fewer trips as car drivers than men as fewer of them have a driving licence, and men, tend to be the main car driver”x
Using the residency of Berkshire older car drivers can put the issue into context. It is a known fact that there is an ageing population – a combination of lower birth rates and reductions in mortality have led to a situation where there is a greater proportion of older people in the population than younger people. “Currently in the UK around one in six of the population is aged 65 or over, and it is predicted that by 2050 one in five will be.”xi It therefore makes sense to put collision involvement into context by comparing it to population rates. The following chart shows a variety of socio‐ demographic measures for each local authority within Berkshire. The chart tells us several things: firstly, it shows us the areas which have had the largest increases in older people since 1981; namely Bracknell Forest, West Berkshire, Windsor and Maidenhead and Wokingham. It shows that there has been little change in the percentage of older people who live in Reading and Slough since 1981. Secondly, unsurprisingly, it shows that a higher percentage of older drivers involved in collisions come from the areas with the largest increases in the older population. However, in West Berkshire, Windsor and Maidenhead and Wokingham, the percentage of collision‐ involved older residents is higher than the percentage of the population they represent. Lastly, it shows that the authorities with the highest percentages of older residents from the least 25% deprived areas who were involved in collisions are the same authorities with the highest percentages of older collision‐involved drivers. 100%
25%
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0% Reading
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Windsor & Wokingham Maidenhead
% Increase in Older Pop since 1981
% Least Deprived 25%
% Most Deprived 25%
% Older Collision Involved Residents
2010 % Pop 65+
0%
The issue of residency is explored in the next two tables. The first looks at the local authority in which the older drivers were involved in a collision and compares this to where the older drivers live. Page | 15
There is quite a range of how local the drivers are to the local authority in which the collision occurs – for Slough only 37% of the older drivers lived in Slough, compared to Wokingham where 60% were local residents. The benefits of joint working across Berkshire are shown in the highlighted row – sixty‐five percent of the older drivers who are involved in collisions across Berkshire come from Berkshire. There are other areas listed where older drivers who crash in Berkshire come from and there is perhaps scope for working in these areas or with their local authorities in order to help reduce their residents’ risk on Berkshire’s roads. Driver Home
Bracknell
Reading
Local to authority Local to Berkshire London South West Hampshire Surrey Buckinghamshire Oxfordshire
52% 72% 1% 3% 5% 4% 1% 1%
45% 69% 0% 3% 4% 1% 0% 5%
Crash Location 2006‐2010 West Slough RBWM Berkshire 37% 49% 52% 49% 57% 69% 11% 2% 4% 3% 9% 2% 2% 7% 1% 4% 1% 3% 11% 1% 6% 0% 5% 1%
Wokingham
Berkshire
60% 74% 0% 3% 4% 1% 2% 2%
‐ 65% 3% 3% 4% 2% 3% 2%
The second table looks at residency of older drivers compared to the location in which they were involved in a collision and therefore explores what Berkshire’s residents are involved in outside of the area. It shows that 72% of Berkshire’s residents are involved in collisions in Berkshire and that between 52% and 62% were from the local authority in which they crashed. There are a few authorities to which Berkshire’s residents travel to and are subsequently involved in collisions at but the two tables are implying that more older drivers travel to Berkshire and are involved in collisions than older drivers from Berkshire going elsewhere and crashing. Crash Location
Bracknell
Reading
In Local Authority Berkshire London South West Hampshire Surrey Buckinghamshire Oxfordshire
52% 67% 5% 1% 6% 14% 0% 0%
62% 77% 0% 6% 2% 1% 3% 8%
Residency 2006‐2010 West Slough RBWM Berkshire 53% 60% 50% 68% 75% 67% 8% 1% 2% 1% 6% 3% 0% 8% 1% 3% 2% 11% 15% 0% 10% 2% 4% 1%
Wokingham
Berkshire
55% 78% 2% 3% 4% 4% 2% 4%
‐ 72% 3% 4% 4% 6% 5% 3%
Thinking of how far older car drivers from Berkshire travel, the following chart shows the average distance from home at the time of the crash. It shows that older car drivers in England, the South East and Berkshire all share similar average distances from home (between 17.3 and 17.6km). Many of Berkshire’s older drivers have similar average distances from home, apart from Slough (where average distances are less at 9.3km) and West Berkshire and Bracknell Forest (where older drivers are slightly further away from home – 22.3km and 20.2km respectively). The chart also shows the Page | 16
average distance from for all car drivers. It shows how the average distance from home varies across the local authorities by age and that in Slough, Wokingham and Reading, older drivers tend to be closer to home than all drivers. In West Berkshire and Bracknell Forest, older drivers tend to be slightly further from home when involved in a collision. However, there should be some caution applied when interpreting these distances as the small number of drivers involved in the sample could affect the averages.
Average Distance from Home (km) England South East Berks Wokingham Windsor & Maidenhead West Berks Slough Reading Bracknell Forest 0
5 All Drivers
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As with thematically mapping the locations of the older casualties injured in Berkshire, the home areas of older drivers from Berkshire have also been mapped. To put the information fully into context, annual rates have been calculated by taking the annual number of collision‐involved over 65 year old drivers and dividing it by the number of over 65 year olds living in each of the MSOAs. The analysis is limited to over 65 year olds as this is the age group for which population numbers at MSOA level are provided. This produces a risk rating for each area of Berkshire in the format of a one‐in‐figure; the lower the rate, the higher the risk.
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The areas with the highest risk are shown in the darkest green. The four areas with the lowest annual rates, and thus the highest risks, are Wokingham 018 (covering Carter’s Hill, Arborfield and Long Moor); Bracknell Forest 009 (covering Easthampstead Park area); Windsor and Maidenhead 001 (covering Pinkneys Green); and Wokingham 014 (covering Dowlesgreen and the south‐eastern area of Wokingham).
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MOSAIC ANALYSIS As well as demographic and spatial analysis of older car drivers, we can also undertake socio‐ demographic analysis using Mosaic. Mosaic is intended to provide an accurate and comprehensive view of citizens and their needs by describing them in terms of demographics, lifestyle, culture and behaviour. By matching postcodes we can segment the older driver community into one of 15 groups and analyse their relative representation in the statistics based on population figures. Mosaic analysis by age band is less accurate than looking at all ages because it uses the entire population of a postcode for the index value, rather than the population of the same age band within a postcode. Nevertheless it gives a good idea of relative under‐ and over‐representation. The first analysis looks at Mosaic Groups for all over 60 year old car drivers from Berkshire. The group with the highest representation, shown on the dark shaded area, is Group D with 281 drivers in five years. Other groups with high representations (over 100 drivers) are C, E and F. The index values, which demonstrate over‐ or under‐representation based on population figures, tell a slightly different story with Groups A, B, C, D, J and L being significantly over‐represented (index values over 120). When carrying out Mosaic analysis you initially look for levels of high representation and high index scores in individual groups and this is the case with Groups C and D. Groups E and F are highly represented in the driver numbers but are less at risk compared to the total populations.
Over 60 year old Car Drivers ‐ Mosaic Profile 300
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Index
In the demographic analysis earlier, it appeared that there were two distinct age groups amongst Berkshire’s older car drivers: those aged 60 to 74 years old (which account for 76% of crash‐involved older drivers) and those aged 75 years and older. Further Mosaic analysis was carried out on these two age bands.
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Unsurprisingly, the 60 to 74 year old Mosaic profile is very similar to that of all older drivers, because this is the largest age band. There were 132 60 to 74 year old drivers from Group C (with an index of 158) and 204 from Group D (with an index of 155).
60‐74 year old Car Drivers ‐ Mosaic Profile 250
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The over 75 year old Mosaic profile is shown in the chart below and reveals Group D is the most over‐represented (with an index of 174) where there were 77 drivers.
Over 75 year old Car Drivers ‐ Mosaic Profile 90
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INDEX OF MULTIPLE DEPRIVATION (IMD) As well as looking at the Mosaic socio‐demographic classifications, it also possible to look at relative wealth using the UK IMD values for each postcode. IMD uses a range of economic, social and housing data to create a single deprivation score for each small area of the country. The analysis uses deciles, which creates ten groups of equal frequency, ranging from the 10% most deprived areas to the 10% least deprived areas.
IMD Decile Distribution ‐ Berkshire 0% Most Deprived 10%
3% 4%
Most Deprived 20%
7%
Most Deprived 30% 35%
8%
Most Deprived 40% Most Deprived 50%
8%
Least Deprived 50% Least Deprived 40%
10% 15%
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Numbers of Berks 65+ Drivers per IMD ‐ Indexed by Pop 250
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65 plus Drivers
Index
The results shows that older car drivers in Berkshire tend to come from the least deprived areas. This is perhaps unsurprising given that 32% of Berkshire’s lower super output areas (LSOA) are classified as being in the 10% least deprived decile. The previous chart shows the number of Berkshire Page | 21
collision involved drivers who live in each IMD vigintile, indexed against the number of 65 plus residents of each vigintile. These indexes are the red bars and as with Mosaic, an index of 100 shows an over‐representation. There are more indexes of over 100 in the least deprived vigintiles than in the most deprived ones. A useful tool created by the Office of National Statistics is the Atlas of the Indices of Deprivation 2010 for England which maps to LSOA level the various indices of deprivation. Areas such as West Berkshire, Wokingham and Windsor and Maidenhead are mostly shown as light blue in the Index of Multiple Deprivation maps (as being least deprived) but when the Barriers to Services indicator is applied, these areas have LSOAs in the most deprived quintile. This indicator includes road distances to a GP surgery, post office, primary school and general store or supermarket and suggests a reason for the higher collision involvement of older drivers from these local authority areas; namely being forced to drive longer distances to access services. Screen shots of Wokingham are shown below to demonstrate the differences between overall IMD and the Barriers to Services indicator.
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PERSONAS Following the analysis of risk, it is necessary to combine the elements of casualty and collision profiling to create a person or personas which capture the key characteristics of those communities or groups most at risk. Although a persona will not typify all, or perhaps even a majority of those involved in collisions, it should represent a significant proportion of those who are most vulnerable. The analysis of the socio‐demographic data as well as the collision information has allowed a picture to be built up about the kinds of older car drivers from Berkshire who are involved in collisions. We know that they mostly live in urban areas and are potentially self‐regulating their driving by avoiding bad weather, darkness and higher speed limits. They may be experiencing deprivation in the form of barriers to services. The data show that they are predominantly male. Older car drivers are often carrying older passengers with them and therefore by targeting the drivers, there could potentially be benefits to be gained in passenger casualty rates. The Mosaic data has shown that there are three Groups which are over‐represented in the collision statistics, with Group D, ‘Successful professionals living in suburban or semi‐rural homes’, representing the largest number of drivers and a high index. It also covers both age groups of 60 to 74 years old and 75 years and older. Group C, ‘Wealthy people living in the most sought after neighborhoods’ is over‐represented and has a high index.
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Least Deprived Group C Successful Rewarding careers Substantial wealth Influential Luxury Items Professional Well‐educated Specialist advice
Group D Suburban/semi‐rural Executive & managers Small businesses Senior positions Significant equity Married with children Comfortable Good education Theatre/arts Car ownership Exclusively pensioners (over‐ represented – 10.13% of Group)
Exclusively pensioners (over‐represented – 9.19% of Group) Receptive to: Internet Telephone Post Unreceptive to: Face‐to‐face
Receptive to: Telephone Internet Post Magazines Unreceptive to: Face‐to‐face Local newspapers National newspapers
More Deprived Group L Retired Bought a smaller property Bungalow Pensions Holidays, cruises Specialist shops Pay off credit card in full Grandchildren Heritage sites Exclusively pensioners (over‐ represented – 12.09% of Group) Single pensioner (over‐ represented – 23.92% of Group)
Receptive to: Face‐to‐face Local newspapers Post Unreceptive to: Internet Telephone Mobile telephone
Local newspapers 60‐74 years old
60‐74 years old
75+ years old
60‐74 years old
Groups C and D share some characteristics – both types of people are successful, comfortably off and enjoy the arts and classical music. They are well educated and are likely to have grown up children. Car ownership is high and they are likely to have multiple cars in the household. Group C’s annual mileage is 6,813 compared to Group D’s 8,287. In order to engage with these groups, it is necessary to identify what media they access. Group C has the second highest internet usage of any group in the country (57% use it every day) and Group D has the 3rd highest (50% every day). The types of internet sites Group D most commonly visit are related to stocks and shares; house and garden; travel; property; and insurance. Group C also visits sites associated with stocks and shares and property and in addition view news and media; food and beverage; and educational sites. The other key communication channels for these two groups are telephone and post. Both are unreceptive to face‐to‐face and local newspapers.
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Both Groups have similar shopping patterns and both tend to shop at Sainsbury’s and Marks and Spencer. Group L, ‘Active elderly people living in pleasant retirement locations’, is also shown in the table. This Group is over‐represented in the younger age group but does not represent as many drivers in the collision statistics. However, the analysis did identify that there were some less affluent older drivers that need to be accounted for. This group tends to be aged 60 to 74 years old and they are less well educated or comfortably off than Groups C and D. This Group is only likely to have one car and has an annual mileage of 5,527. They enjoy classical music and reading books. This Group has the second lowest internet usage, with 24% using the internet every day. Their communication preferences are face‐to‐face engagement, local newspapers and post. They are unreceptive to the internet, telephone and mobile telephones and so have opposite communication preferences to the other Groups. In essence, there are 3 personas (shown in order of number of drivers they represent): 1. ‘David’ – is in his mid to late sixties and is a recently retired professional. He was successful in his career and is wealthy. He has grown up children and the first change to his lifestyle after retirement is spending more time caring for his grandchildren. He has multiple cars and drives high mileage, perhaps due to habit but also to access services. He enjoys the arts and classical music and tends to shop at Sainsbury’s and Marks and Spencer. An important engagement tool for him is the internet and his website interests could allow the use of the language of ‘investment and return’. There are initial post‐retirement changes to his lifestyle and driving patterns and he will start to self‐regulate the times he drives as he gets older. He is no more likely to have caused the collision in which he was involved than been an innocent participant. As an educated individual, he may well be receptive to an intervention that improves his driving awareness and his practical skills. However, as a successful person, he will not be receptive to be lectured and as he is not more likely to have caused a crash than people of other ages, he may question ‘what’s in it for him?’ Driver cessation is unlikely to be a topic with him. (Between 2006 and 2010, there were 336 drivers from Berkshire involved in collisions that fit this persona). 2. ‘Peter’ – is aged in his late seventies and is an older version of David. He specifically belongs to Mosaic Group D. He has similar interests to David but spends less time caring for his grandchildren as he gets older. The self‐regulation of his driving has continued but skills errors are creeping in, possibly due to medical conditions. As his age increases, so does his blameworthiness. He will still retain the characteristics of a successful professional and may find the idea of ceasing driving difficult to cope with. It may be necessary to engage the assistance of his spouse, children or doctor to persuade his to evaluate his driving skills. (Between 2006 and 2010, there were 77 drivers from Berkshire involved in collisions that fit this persona). 3. ‘John’ – is in his mid to late sixties and he has recently retired and bought a smaller property, possibly a bungalow. He is likely to spend quite some time looking after his grandchildren. He is less wealthy than David and drives fewer miles. It may be that he would be receptive to information on alternative forms of transport (buses and cycling) for the financial benefits. As David, he is not more likely to have been caused a collision than been innocently involved Page | 25
and so would need to see the benefits of an intervention. He, too, will have changed his driving patterns after retirement but may also be subject to ‘barriers to services’ deprivation and be forced to drive. He is not receptive to the internet and instead prefers face‐to‐face interaction: there could be a place for road safety officers to directly engage with him. (Between 2006 and 2010, there were 42 drivers from Berkshire involved in collisions that fit this persona).
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ENGAGEMENT PLAN
It is important that the intervention design is regarded as offering positive support for the older driving community and that it chimes with the lifestyle choices of the more mature driving population. ‘Flourish’ seeks to convey a positive unfurling of the future with imagery that will chime with an audience who have invested time and energy into home and garden.
SELF ASSESSMENT Research shows that Self‐Assessment in older drivers encourages the process of self‐regulationxii, a key element of the engagement plan will therefore be the development of a self‐assessment tool for older drivers. Drawing on the work of the Royal Automobile Association of Queensland and the AAA Foundation for Traffic Safety, the questionnaire will be delivered online and provide instant structured feedback on areas of risk prevention and mitigation.
MANUAL FOR OLDER DRIVERS The flourish manual will provide a distillation of advice on the issues raised by the self‐assessment tool and that are pertinent to the older driving population in general. The manual will be available for distribution by local authorities with a digital version presented online.
FLOURISH COURSE Adopting a similar approach to the DriveStart model of unified branding for a portfolio of courses and events working alongside projects that are already underway elsewhere, Flourish branding and exhibition materials will be made available for local authority use. A proposed curriculum will also be developed that draws on the insights from this study and research into other courses available elsewhere.
DRIVING ASSESSMENTS Adopting a model similar to the ‘Be a Better Driver’ scheme in Buckinghamshire would allow driving assessments to be carried out by Advanced Driving Instructors who have received extra training to support older drivers. The cost for these courses would be borne by the individual, though there would need to be a process of training and vetting appropriate ADIs to undertake the training.
WEBSITE & APPS
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The elements above would be underpinned by website information and possibly a smartphone application which has been highlighted as a potential access point to informationxiii.
MESSAGES K EY T HEME Assessment and self‐regulation is the key to safer mobility in later life M EDIA M ESSAGES You have planned for and invested in your retirement – look after yourself to make sure it counts Older Drivers do a great job keeping themselves safe; we can help them even more by training and assessment Ill‐health & impairment increase risks; but these can be managed to keep you mobile and active F ACTS WHEN?
76% of all the drivers were involved in collisions between 8 am and 5pm 84% of the drivers were involved in collisions in daylight or with lighting present
WHERE?
61% were at junctions, crossroads or roundabouts 69% were on 30mph or 40mph roads
HOW?
56% of the older drivers were considered to be at fault The most common reason was ‘Failed to look properly’ ‘Poor turn or manoeuvre’ was another common contributory factor, as was ‘Failed to judge other person’s path or speed’
M EASURES Number of self‐assessment questionnaires completed Number of Flourish Manuals distributed Number of flourish courses attended
Numbers or driving assessments booked
Website traffic
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EVALUATION An evaluation framework has been created which builds upon the analysis in this Study. Evaluation work will see to measure outcomes that are reflective of changes in the knowledge, intentions, attitudes and behavior of the target audience of older drivers. The following logic model shows the aims and objectives of Flourish and how the intervention will be measured. Uptake of self‐assessments, courses and driving assessment will be the main measures of the evaluation. This will allow the Safer Roads team to undertake a process evaluation of the intervention (to ensure that the correct mechanisms are in place to engage with the right people and that the outputs lead to the desired outcomes). It will allow an outcome evaluation to be undertaken by measuring the overall results of the intervention and to assess whether the aims and objectives have been achieved.
Time Funding
# of mature drivers spoken to at events # of Flourish manuals distributed # of self‐ assessments completed # of courses booked # of driving assessments booked
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Mature drivers encouraged to visit the Flourish website and gain more information Mature drivers receive Flourish manual with information on safer mobility
Mature drivers undergo self‐ assessment Mature drivers attend Flourish course to discuss safer mobility
Long Term Outcomes
Research
Mature drivers spoken to at events and provided with information on safer mobility
Medium Term Outcomes
Partners
# of engagement events
Short Term Outcomes
Staff
Outputs
To encourage assessment and self‐regulation amongst mature drivers to provide safer mobility in later life OBJECTIVES: To encourage X number of mature drivers to undergo self‐assessment For X number of mature drivers to attend a Flourish course For X number of mature drivers to take a driving assessment ASSUMPTIONS: That information and self‐assessment will lead to self‐regulation and decision to assess skills EXTERNAL Barriers to services could limit ability to self‐regulate driving FACTORS: Perceived restrictions on independence and freedom could limit willingness to engage Economic factors could limit ability to pay for courses/driving assessments
Inputs
AIM:
Mature drivers reflect on their driving and make choices surrounding self‐ regulation and skills assessing Mature drivers undertake driving assessments
CURRENT LOCAL SCHEMES In Berkshire, only West Berkshire Council has a current programme of engagement with older drivers. The ‘O’ Drivers course has been promoted through a number of locations where the ‘retired but mobile’ populous are likely to congregate; places such as garden centres. Whilst the information has been well received and a number of bookings received attendance at the most recent course was quite poor.
SUMMARY OF OTHER EVIDENCE AND SUCCESSFUL SCHEMES Devon County Council’s Knowledge Transfer Partnership project with the University of Plymouth conducted a literature review of older driving training interventions. The research found that training interventions have focused on addressing the needs of older drivers, for example identifying particular impairments, changing driver behaviour and knowledge and promoting behavioural strategies to compensate for age decline. Increasing knowledge and behaviours that will lead to safe driving is assumed to lead to a reduction in collisions. Research has shown that the combination of on‐road training and in‐class education results in increased awareness, driver knowledge and skills specific to driving. Older drivers have been shown to be good candidates for in‐class education training due to their motivation to continue driving, time to attend class and ability to acquire information in an interactive environment.xiv The research also found that training interventions need to be tailored to specific needs as it was identified that women require information on driving skills and encouragement to continue driving. Men, on the other hand, often find the idea of stopping driving harder to accept and need information on health and age‐related limitations.xv Driving is often seen as the most obvious choice for maintaining mobility as it gives individuals the freedom to go where they please when they want and benefits those who can’t walk long distances or carry shopping. Interventions should be aimed at making driving as safe as possible for as long as possible. The car’s status and role in modern day life can make it particularly difficult to give up driving. This will be even harder for the younger old who are more likely to have driven all their lives. In addition, as a result of urban planning, it is more common for them to drive to the out of town supermarket than walk to the high street... However, although there are many advantages to owning a car, there are also disadvantages, and many people choose not to or simply cannot. Three quarters of single people over the age of 65 do not have a car.xvi As giving up driving has been linked to an increase in depression and lonelinessxvii and that mobility is important to life satisfaction and quality of life, any intervention which might lead to the cessation of driving should aim to make the process as easy and painless as possible. PACTS recommends the development of a national information pack to inform and raise awareness amongst older drivers, promote mobility, and encourage conversations and reflections which may not have otherwise happened. Producing this content nationally Page | 30
would ensure a research‐based approach and consistency across local authorities, and would benefit from economies in scale…. Following on from awareness‐raising and information providing, the next stage would be formal assessment and training. PACTS recommends the development of a national standard course for older drivers, in line with best practice and academic research. xviii Information which could be covered in the national information pack could be:
How to renew the driving licence and information on self‐declaration; The potential difficulties older drivers may face and possible self‐regulation; How vehicles can be made safer by adapting the vehicle or adding active safety devices; Awareness of the cost of owning and driving a car; Advice on vision and fitness to drive, particularly for those on medication or suffering from dementia; A self‐assessmentxix
In addition, local information could be added that includes:
Local information on transport provision/prices Cycle map and information on bike storage facilities A bus journey voucher – information on timetables and fares Information on taxis with prices of example trips
EXISTING SCHEMES The Driving Standards Agency (DSA) launched a scheme in 2002 entitled Arrive Alive Classic which provides presentations for people aged over 50 years on topics such as complex road systems, rising traffic volumes, effects of medication, eyesight and licensing requirements at 70 years old. The presentation is free of charge and is conducted by an experienced, current, DSA driving examiner. It last approximately an hour and includes a short DVD. http://webarchive.nationalarchives.gov.uk/+/www.direct.gov.uk/en/Motoring/DriverSafety/DG_402 2428 In 2008, Norfolk County Council launched a scheme in partnership with the Department for Transport for drivers who by age, ill health or mobility reasons would benefit from guidance and advice via a scheme called GOLD – Guidance for the Older Driver. The scheme coordinator visits the client in their own home and carries out an informal screening process centred on driving and health/medical questions and eyesight screening. The client is subsequently contacted to arrange a drive with a specialist appointed trainer, who will take the client out in the client’s own vehicle and on roads they are familiar with. Further drivers are arranged if necessary and advice on future mobility decisions provided if the client decides to cease driving or they have been advised to refrain from driving, following the assessment. Discussions on future mobility sometimes involve the client and family. http://www.think.norfolk.gov.uk/Older‐Driver/Training‐and‐Campaigns
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SAGE (Safer Driving with Age) is a program established by Gloucestershire County Council in 2000. In a similar format to Norfolk’s scheme, a medication and health review is undertaken but involves the client’s GP or practice nurse. The client must have had an eye examination in the last 12 months and a ‘field test’ should be undertaken by their GP if the client has a medical condition which has affected their field of view. A driving assessment is undertaken in the client’s own car, on roads they are familiar with, with an experienced driving assessor. A written report is produced at the end of the drive. The program is a three‐stage process and needs the buy‐in of the client’s GP or practice nurse to complete the medical assessment. The current fee is £30 for a one hour assessment. http://roadsafety‐gloucestershire.org.uk/wp‐content/uploads/2011/04/SAGE‐fact‐sheet.pdf Dorset County Council provides the Dorset Driver course, which involves two elements: the first part is a Driver Refresher Course us two hours long and is aimed at helping drivers update their knowledge and skills through group discussions about observation, distractions, safety margins, dual carriageways/motorways and roundabouts. The session costs £5. The optional Practical Refresher Course lasts 90 minutes and involves the client driving their own car with an experienced driving professional. The route usually includes town and country driving and costs £37.50. http://www.boroughofpoole.com/transport‐and‐streets/public‐transport/drive‐55‐plus‐road‐safety‐ information/ Buckinghamshire run a similar scheme to SAGE called Be a Better Driver. It includes a driving assessment for the cost of £35 and allows individuals to make referrals to the program, so concerned family, friends and professionals can recommend an older driver attend. http://www.buckscc.gov.uk/bcc/news/older_driver.page Devon Road Casualty Reduction Partnership launched its Driving Safer for Longer (DSFL) program in 2007. An information pack and website provides information on mobility, fitness, medication, driving tips and other travel options. The program also includes a two hour workshop and a practical driving skills assessment. More information on the success of the scheme can be found on page 25 of Poppy Husband’s report ‘A literature review of older driving interventions: implications for the delivery programmes by Devon County Council and Devon Road Casualty Reduction Partnership’. http://www.devon.gov.uk/drivingsaferforlonger Sussex Safer Roads Partnership has produced a brochure called Safer for Older Drivers which provides extensive but clear information on eyesight, hearing, mobility and medication. It also provides information on the law, provides suggestions for alternative modes of transport and how to calculate the yearly cost of motoring. The brochure provides information on their Experienced Driver Assessment, which involves the client undertaking a 45 minute driving assessment in their own car, in a similar format to other schemes. http://www.sussexsaferroads.gov.uk/safer‐for‐older‐drivers.html
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i
Baster, N., It’s my choice – Safer mobility for an ageing population, Parliamentary Advisory Council for Transport Safety, 2012, p.3 ii http://www.roadsafetyevaluation.com iii Box, Gandolfi and Mitchell, Maintaining safe mobility for the ageing population, RAC Foundation, April 2010, p. 15 iv Baster, N., , p.3 v Examples of older pedestrians (or disabled people) injured by older drivers are included below: http://www.thisishullandeastriding.co.uk/Beverley‐woman‐87‐dies‐hit‐elderly‐neighbour‐s‐car/story‐ 11955459‐detail/story.html http://www.telegraph.co.uk/news/uknews/crime/7951296/Elderly‐driver‐who‐killed‐disabled‐woman‐walks‐ free‐from‐court.html http://www.stornowaygazette.co.uk/news/elderly‐driver‐being‐questioned‐after‐suspected‐hit‐and‐run‐1‐ 2140959 http://www.dailyrecord.co.uk/news/scottish‐news/2012/03/25/driver‐who‐ran‐over‐and‐killed‐fisherman‐ hits‐pedestrian‐on‐skye‐s‐only‐zebra‐crossing‐86908‐23801187/ vi Hopkin, J., Older Drivers – Safe or unsafe?, IAM Motoring Trust, 2010, P.3 vii Clarke, D., Ward, P., Truman, W., and Bartle, C., Collisions Involving Older Drivers: An In‐depth Study, Department for Transport, September 2009, p. 11 viii ibid., p. 16 ix Hopkin, p. 4 x ibid., p. 5 xi Baster, N., p.3 xii Berry, ‘Can Older Drivers be Nudged?’ 2011, Pg 38 xiii ibid., p.39 xiv Husband, P., A literature review of older driving training interventions: implications for the delivery programmes by Devon County Council and Devon Road Casualty Reduction Partnership, 2010, p. 5 xv Baster, N., p.30 xvi ibid., p. 34 xvii ibid., p.35 xviii ibid., p.45 xix ibid., p.45
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