Billot-Grasset Alice

Amoros Emmanuelle

Hours Martine

A Cyclist Accidents Typology: survey methodology using a medical registry

Keywords: cyclist, accident circumstances, injuries, survey method, medical registry BILLOT-GRASSET, Alice, AMOROS, Emmanuelle

Bicycle is promoted in many major cities as an healthy and eco-friendly transportation mode. However, cycling is risky and safety issues concern a few thousands of victims every year. In France we estimate an annual incidence rate of 70 road injuries per 100,000 inhabitants. Most of the existing studies focus on particular accident factors and are based on police registry. However, police data are biased and non-representative of cyclist crash circumstances. In this work, we propose to improve knowledge of accident circumstances by surveying 3337 cyclists injured in 2009-2011 and identified from a road trauma registry around Lyon in France. The main objective is to build a cycling accident configuration typology from detailed collisions or falls circumstances. To do so, we built up a questionnaire and tested it. The pilot survey response rate was 18%. Respondents were older, more often women, having more serious accidents, more often in urban areas. We observed that 1/3 accident occurred on a non-business trip, 1/3 on a commuting trip and 1/4 while practicing a cycling sport. A third party was involved in 45% of crashes whereas 37% declared that an obstacle, a loss of control (19%) or/and a mechanical failure (13%) was one of the crash factors. Learning from the pilot stage, the questionnaire design improvement is detailed, enabling a reduction of the selection bias. The final response rate reached 43%. Overall, the survey is successful and improves knowledge in comparison with existing studies.

INTRODUCTION

Bicycle is promoted as an urban transportation mode in many cities around the world because of health benefits at the microlevel addressing problems linked to obesity and diabetes diseases and at the macrolevel meaning air quality improvement. However, cycling is risky and in France we estimate about 70 road injuries per 100,000 inhabitants per year [START_REF] Amoros | Estimation de la morbidité routière, France, 1996-2004[END_REF]. Because of medical care costs, policy makers may have a major interest in preventing major and minor accidents [START_REF] Aertsensa | Commuting by bike in Belgium, the costs of minor accidents[END_REF]. Previous studies has shown that most of the existing studies are based on data that lack representativeness [START_REF] De Geus | A prospective cohort study on minor accidents involving commuter cyclists in Belgium[END_REF][START_REF] Heesch | Incidence, severity and correlates of bicycling injuries in a sample of cyclists in Queensland, Australia[END_REF][START_REF] Elvik | Incomplete Accident Reporting: Meta-Analysis of Studies Made in 13 Countries[END_REF][START_REF] Amoros | Under-reporting of road crash casualties in France[END_REF]. In this work, we propose a study of cyclist accidents from the "Rhône Road Trauma Registry". This medical database includes all outpatients and hospitalized patients, victims of road accident in the Rhône, a French department. It is located around Lyon, a major urbanized area. To collect detailed accident circumstances, questionnaires have been sent by mail to 3337 cyclists injured between 2009 and 2011. This survey is the first one of this magnitude in France and one of the few in the world using injury data from hospitals [START_REF] Laursen | Bicycle accidents. Differences between one-vehicle accidents and accidents involving two or more vehicles[END_REF][START_REF] Thulin | Tema Cycle -injured bicyclists: analysis based on hospital registered injury information from STRADA[END_REF][START_REF] Schoon | Frequency and causes of single-vehicle cyclist accidents: an accident analysis based on a survey of cyclist victims[END_REF][START_REF] Scheiman | Bicycle injury events among older adults in Northern Sweden: A 10-year population based study[END_REF][START_REF] Langley | Missing cyclists[END_REF].

In this paper, we describe population selection, questionnaire construction, pre-testing and pilot survey results that allow improving the final response rate as well as the relevance of this work. Finally, we identify key questionnaire improvements and we share methodological aspects on accident survey design.

In France, bicycle safety literature has estimated the overall accident risk [START_REF] Amoros | Cyclistes Victimes d'Accidents (CVA). Partie 1 : Caractéristiques et bilan lésionnel[END_REF] and the risk exposure [START_REF] Blaizot | Accidentalité à Vélo et Exposition au risque (AVER), Risque de traumatismes routiers selon quatre types d'usagers[END_REF]. Both of them have been compared to other transport modes. Accident mechanisms for single bicycle crashes and collisions with a third party have mainly been studied from police records [START_REF] Bue | Analyse de l'insécurité des cyclistes dans la métropole lilloise[END_REF].

Nevertheless, police data are not appropriate to study cycling safety because of a well-known underreporting bias. This bias is mainly about road user type and whether another road user is involved or not in the accident [START_REF] Elvik | Incomplete Accident Reporting: Meta-Analysis of Studies Made in 13 Countries[END_REF]. For instance, the proportion of injuries related to collisions and bicycle-only crashes have been identified from the Rhône medical registry; respectively 30% and 70% [START_REF] Amoros | The injury epidemiology of cyclists based on a road trauma registry[END_REF]. Moreover, in some countries, the number of bicycle accidents reported in medical databases or through survey exceeds the police reported number by nearly two times [START_REF] Juhra | Bicycle accidents -Do we only see the tip of the iceberg?: A prospective multi-centre study in a large German city combining medical and police data[END_REF] and up to nine times in the department studied in this research [START_REF] Amoros | The injury epidemiology of cyclists based on a road trauma registry[END_REF]. Additionally to selection bias on road user type; police data is biased on injuries severity, road type [START_REF] Laumon | Analysis of biases in epidemiological knowledge of road accidents in France[END_REF]. As a result, most of the existing studies, as useful and informative they are, cannot replace a survey addressed to cyclists and aiming to identify accident mechanisms. Indeed, using a medical registry to identify victims is an asset. With respect to the Rhône road trauma registry, a coverage rate of 80% was estimated for all injured cyclists. [START_REF] Amoros | The injury epidemiology of cyclists based on a road trauma registry[END_REF]. These data limitations were underlined when some studies focused on single crash accident circumstances as they were missing from most of the sources. Besides, single bicycle accidents remain understudied in urban areas, in the literature they represent from 47% up to 81% of crashes depending on the country and its road accident definitions [START_REF] Laursen | Bicycle accidents. Differences between one-vehicle accidents and accidents involving two or more vehicles[END_REF][START_REF] Thulin | Tema Cycle -injured bicyclists: analysis based on hospital registered injury information from STRADA[END_REF][START_REF] Schoon | Frequency and causes of single-vehicle cyclist accidents: an accident analysis based on a survey of cyclist victims[END_REF]. The common definition of a one-vehicle accident is a loss of control. But it can be divided into three main cases: an obstacle avoidance, an avoidance of another road user and a simple loss of control [START_REF] De Geus | A prospective cohort study on minor accidents involving commuter cyclists in Belgium[END_REF][START_REF] Schepers | What do cyclists need to see to avoid single-bicycle crashes?[END_REF][START_REF] Munster | Role of road features in cycle-only crashes in New Zealand[END_REF]. That also explains why, from our point of view, single-crash and collisions circumstances have to be analyzed all together. In France, some recent work gives the accident distribution of 51 urban cyclist accident scenarios based on 650 police records from 2001 to 2007 [START_REF] Bue | Analyse de l'insécurité des cyclistes dans la métropole lilloise[END_REF]. However, only 9 scenarios have been especially created for cyclist crashes and all are mixing collisions and falls. Some more typologies are available in Europe [START_REF] Reed | Building the European Road Safety Observatory, deliverable5.5, Glossary of data Variables for Fatal and accident causation databases[END_REF] and in other countries around the world [START_REF] Cleven | A Compendium of NHTSA Pedestrian and Bicyclist Research Projects: 1969 -2007[END_REF] but their relevance is limited because they also focus on collision crashes. To summarize, there is an important need for data collection on cyclist's accidents circumstances looking at both collisions and single-crashes, linking it with injuries to address accident and injury prevention. So far, there is no data allowing us to analyze additionally: accident circumstances, type of accident and type of injury. The survey method explained in the following section will bridge the gap and enable the construction of a cyclist accident typology.

MATERIAL AND METHOD

Data selection

This study aims to better understand how people get injured because of bicycle accidents after a collision or a fall. Our dual objective is to improve primary prevention meaning accident avoidance and secondary prevention which is injury minimization. To be efficient, we must set up a typology of cyclist accidents as representative as possible. In an ideal world, we could survey a broader random sample of the national population. However bicycle modal share represents only 3% of French usage [START_REF] Papon | Les modes actifs : marche et vélo de retour en ville[END_REF]. Then, for an optimistic sample size of cyclist, we would have to contact a very large number of people, without knowing whether they have been injured in the previous years.. So we would have to include people injured many years ago and accept an important memory bias. Therefore, it is more realistic to use existing data. In France, we have 3 main sources and methodology to study cyclist accidents as follows.

Detailed accident study & prototypal scenarios

Since 1992, one research unit at the French Institute of Science and Technology for Transport, development and networks (IFSTTAR) is in charge of detailed accident study. The data has a thousand of vehicle crashes and aims to improve knowledge of accident mechanisms. To generate new research hypothesis, they collect accident reconstitution, description and detailed analysis. Some researchers construct accident prototypal scenarios from this data [START_REF] Fleury | Accident prototypical scenarios, a tool for road safety research and diagnostic studies[END_REF]. This method is of interest for our topic as it determined sufficient and necessary elements in the incident chain leading up to a crash. In addition, the chronology is decomposed to understand how a driving situation is interrupted by an accident situation, leading to an emergency situation that precedes a collision and its consequences. This method is a combination of a system approach (pilot-vehicle-infrastructure) and systems modeling (sequential-kinematic-operator). However, they collected only around 30 cyclist accidents in 20 years and almost only collisions. Obviously, even if representativeness is not necessary to understand intrinsic crashes mechanism, it is required for epidemiology studies addressing prevention.

Police data & bulletin of road traffic injuries accidents.

Since the 1950's, French police services have to complete a form for each accident with at least one injured person, named: "analysis bulletin of road traffic injury accidents". This data remains the main source for most of the accident studies and much research has been conducted thanks to it even if there is under-reporting and significant bias compared to medical sources [START_REF] Laumon | Analysis of biases in epidemiological knowledge of road accidents in France[END_REF]. Indeed, in the Rhône department, the police data registered around 150 bicycle accidents per year when, at the same time and on the same territory, the medical data registered around 1300 people injured while cycling. The differences between the two databases have been explained [START_REF] Amoros | Under-reporting of road crash casualties in France[END_REF]. To be more specific, under-reporting is mainly related to injury severity, meaning slightly injured road user are 0,35 times less registered than severely injured.

Rhône Road Trauma Registry

The Epidemiological Research and Surveillance Unit in Transport, Occupation and Environment (UMRESTTE) is one research unit of IFSTTAR in charge since 1995 of "The road trauma registry". This registry combines inpatients and outpatients from 260's medical services (public or private) in the Rhône area. This data contains several victims' characteristics such as age, gender, date of birth, postal address and type and severity of the lesions. In addition, there are a few accident indications such as date, place, type of road user, type of antagonist and some hints of crash circumstances. Using this registry, there are two small limitations biases: the injuries severity and the distance between the accident location and the hospital. Nevertheless, to extrapolate result to the French territory some statistical techniques tacking into account biases have already been developed and are operational [START_REF] Amoros | Registre des victimes d'accidents de la circulation routière : extrapolation au niveau national[END_REF].

Target population & survey method justification

From the Rhône Road Trauma Registry, we selected people over 10 years old on the accident day. This choice has been made for two main reasons. Firstly, to avoid young cyclist crashes corresponding to learners falls and traditionally related to 0-14 years old age group that have already been studied [START_REF] Rijk | The road safety of children : a crash analysis and literature study[END_REF]. Secondly, to include high school students from 11 years old because some of them commute to school. We excluded deceased people and passengers to collect pilot point of view. Using the most recent years, we aimed to reduce invalid address and memory bias. Overall, we had 3337 subjects. To contact them, we had two options: send them letters or search for phone numbers.

A test has been conducted to estimate the time required to find and contact all people for a phone survey. It takes only one minute to search a phone number per address. But, it takes 55 hours to search 3337 times. Also, we found that one address out of two was really associated with a number, then to find the 1668 and reach each household, 150 and 200 hours is required with an average number of 5 calls of one minute duration. Postulating an average response rate of 50%, we could obtain 800 respondents interviewed during 15 minutes on average, hence another 200 hours is required. The total time cost would be from 400 to 450 hours meaning 12 full weeks for one person.

The second option is to send a postal survey. It takes one day to print 3337 letters, questionnaires and pre-addressed envelopes. Then, it takes around one hour to prepare 250 envelopes. In one week the survey is sent. The response rate might be lower but, with a recall letter the response rate is improvable. In addition, we can identify differences between target population and sample in terms of age, gender, type of accident and injury severity. So far, there is no good reason to invest 10 times more in a phone survey. From another point of view, we can lose respondents because some people have difficulties reading and writing. To make sure that this may not happen often, we suggest in the first part of the questionnaire that people can participate through phone or using the internet.

Interviews to understand risk of accident definition

A very important step is questionnaire design, especially for a postal survey. To do so we first studied from the existing literature several questionnaires constructed to collect data on cycling accidents. However, none of them had our objective to construct a typology. We decided to conduct interviews with a mind of combining researchers' and stakeholders' viewpoints about cyclist safety. Exploratory talks aimed to identify a pattern in risky situations and the perception of a safe trip. We determined that cycling instructors were the relevant target group because they can inform us about their own practice assuming they are experienced and firmly convinced cyclist. Moreover they can inform us about the less skilled cyclists. The ultimate goal of this research is prevention and instructors will have to relay safety related findings; hence, it will be easier to convince them knowing their point of view.

There are 35 "cycling schools" in the French cycling community network and we interviewed 14 instructors working in different cities as volunteers or employees for between one month and 10 years.

The interview guide questioned them about accidents, risks and tips to avoid crashes or collisions. For instance, we asked them: 'what is an accident?'; 'which are the common ones?'; 'which are the serious ones?'; 'Does each type of cyclist have the same risk of accident? (meaning: child, adolescent, adult, men, women…)'; 'what good advice can be given to learners for their safety?'. To be more specific, we used interviews for questionnaire design but there is enough material to be analyzed and compared later on with statistical results.

Pilot Survey

Questionnaire creation: pre-test & target population

The first version of the questionnaire was distributed in February 2012 to cyclists from organizations, as well as colleagues, friends and family. Our objective was to test each question and to determine a response rate. Using comments, an improved version has been submitted to the French Data Protection Authority (CNIL), which requires it for legal purposes. This second version was addressed to cyclists injured in 2007. A total of 885 questionnaires were mail posted with an introductory letter and a preaddressed envelope to conduct a pilot survey. The questionnaire format was an A4 two-side printed and stapled with the letter to identify respondents.

Pilot survey, Response Rate and possible bias

The response rate was 18% (N=103); there were 325 invalid addresses and 457 non-responses.

Analyses were conducted on 95 people because 8 forms were non-retrievable. Most responses arrived one week later and some up to 3 months later. Results showed differences between respondents and non-respondents. Participants were older than non-respondents, 75% are over 35 years old versus 35.4%. They are more often women (37% vs. 23%) and mainly cycling on urban roads (78% vs. 60%).

Respondents had been involved in collisions more often than others (30% vs. 22%) and had more serious injuries (55% minor injury vs. 67%). Age group differences are explainable by residential mobility since the accident in 2007: the youngest [START_REF] Scheiman | Bicycle injury events among older adults in Northern Sweden: A 10-year population based study[END_REF][START_REF] Langley | Missing cyclists[END_REF][START_REF] Amoros | Cyclistes Victimes d'Accidents (CVA). Partie 1 : Caractéristiques et bilan lésionnel[END_REF][START_REF] Blaizot | Accidentalité à Vélo et Exposition au risque (AVER), Risque de traumatismes routiers selon quatre types d'usagers[END_REF][START_REF] Bue | Analyse de l'insécurité des cyclistes dans la métropole lilloise[END_REF][START_REF] Amoros | The injury epidemiology of cyclists based on a road trauma registry[END_REF] have a larger probability to be still living with their parents while the oldest (over 35) often own their residence. Therefore addresses probably didn't change and then both groups have a higher response probability. At the same time, young adults move to individual places when they start to study or to work [START_REF] Reed | Building the European Road Safety Observatory, deliverable5.5, Glossary of data Variables for Fatal and accident causation databases[END_REF][START_REF] Cleven | A Compendium of NHTSA Pedestrian and Bicyclist Research Projects: 1969 -2007[END_REF][START_REF] Papon | Les modes actifs : marche et vélo de retour en ville[END_REF][START_REF] Fleury | Accident prototypical scenarios, a tool for road safety research and diagnostic studies[END_REF][START_REF] Amoros | Registre des victimes d'accidents de la circulation routière : extrapolation au niveau national[END_REF] while their elders have to move to find housing with more rooms to raise children [START_REF] Granie | Différences de sexe et rôle de l'internalisation des règles sur la propension des enfants à prendre des risques à vélo[END_REF][START_REF] Bechtel | True-Value Regression with Non-Response[END_REF][START_REF] Mckenzie | Part 2 -Assessing and minimising the impact of non-response on survey estimates, in Taskforce on "Improvement of Response Rates and Minimisation of Respondent Load[END_REF][START_REF] Macdonald | Addressing nonresponse bias in postal surveys[END_REF](34).

To sum up, the response rate must be improved and the final survey must reduce some bias even if analyses can be performed to adjust non-response bias, as in a previous work based on mail survey [START_REF] Tivesten | Nonresponse analysis and adjustment in a mail survey on car accidents[END_REF]. Typically, non-respondents are younger and more often men in many mail surveys. In addition, a classic bias is on the accident type because people involved in a collision are more likely to recall it and generally feel more concerned by road safety surveys. Therefore injury severity bias is consistent because collision generally involves more serious injuries. Moreover, the ridden surface and type of practice are both linked with injuries severity. For instance, utilitarian trips are on-road practice then cyclists have a higher probability to collide with motorized vehicle, thus to be seriously injured.

People practicing off-road sport have a higher probability to collide with objects or to lose control.

Data collection and data Entry.

For the pilot survey data entry we chose an online software named LimeSurvey. After creating the questionnaire, we used the input mask to fill out our data. During this step, some technical problems were identified and solved. After all, we realized that we can afford to promote internet participation for the final survey; this could raise the response rate. With online participation we were able to create a unique link for each person in the sample in order to link the survey data with the medical registry as we planned to do with the paper form. On average, both questionnaire formats could be completed in 20 minutes.

Pilot survey main results

Most of the accidents occurred in cities (57%), during daylight (87%) and away from intersections (67%), as we can observe on table 1. In one case out of two the main purpose for cycling was utilitarian; some were commuting (25%) and other people were visiting friends, going shopping, or to a leisure activity (32%). Another quarter (24%) were practicing sport such as road cycling or mountain biking while 18% were on a leisure ride. Less than half of the accidents involved a third party (45%).

Compared to obstacle (37%), slipping on the ridden surface (19%) and a mechanical failure (14%) are other common accidents factor. One person out of two did not have the time to do anything to avoid the accident (52%). Lastly, around half of the victims (49%) required medical assistance on site.

Police came in 13% of all cases which confirms under-reporting evaluated between medical and police data as stated above. Regarding secondary safety, almost half of our sample were wearing helmets (47%). This proportion reflects a socially acceptable response bias because it is much more than what we can observe in France; hence we must modify this question. Other conspicuity garments such as fluo or retro-reflective vests or legs bands had largely not been worn (respectively 97% and 96%) whereas two cyclists out of ten were wearing light or bright colored cloth.

LEARNING FROM THE PILOT STAGE: QUESTIONNAIRE DESIGN IMPROVEMENT

Increasing response rate.

The main conclusion from the pilot survey was the necessity to improve the response rate. To do so we first chose to build up a shorter questionnaire by selecting the most meaningful questions and items. We removed sensitive questions, such as 'did you run the red lights or the stop sign?' disappeared from the last version because even if they did it, people answered 'no'. Most of the questions have been reorganized to reduce average time of completion. For instance, as shown in table 2, items to answer the question 'How was the weather at the time of the accident?' have been simplified. Another example of removed items is the 'business trip' for the question 'your accident took place while cycling to…' because it is an unlikely situation (1%). In the same vein, we added an item 'other, please specify' to each question to collect rare events. We want to underline here that the "I don't know" item is always offered to allow people to choose this answer for sensitive questions just as much for amnesia because of a brain trauma. Indeed, 2.6% of the studied population have moderate to severe injuries on the head using the MAIS scale (Maximum Abbreviated Injury Scale on a 6 level scale, from 1 "minor" to 6 "beyond treatment" [START_REF] Hirsch | Impairment scaling from the Abbreviated Injury Scale[END_REF]). Another way to ask sensitive questions is to underline behavior normality. For instance, the final version of the helmet question is therefore:

'Were you wearing one of the following NON COMPULSORY pieces of equipment?' Thirdly, we reorganized every section from the most common question to the least common one because some people cycling for sport felt that their experience was not related to our pilot survey while reading the first page therefore, they were mostly non-respondents. To do so, questions 2 shows that question ordering is not influencing only overall response rate but also the proportion of 'unknown' answers.

Between the pilot study and the final study this proportion has been divided by 3 when we asked 'Were you at an intersection?'. Following the same approach, items were classified from the most common answer to the least common one. For example, items for "how was the road surface?" were ordered according to occurrences in the pilot survey: dry, graveled, wet, others. Finally, phone calls and e-mails that we received demonstrated that the introductory letter provided efficient information about our research and the way to participate.

Questionnaire description

The questionnaire format is a double-sided, folded A3 sheet presented in figure 1. Previous studies and our team's professional experience demonstrated preferences for this standardized size. A personal introductory letter went together with the questionnaire to explain our research. The date of the accident was specified on it to make sure that people would complete the form about the accident registered in our medical database. In addition an ID number was attributed to each patient and allows us to link the questionnaire with the registry.

The questionnaire aims to understand accident's circumstances to construct a typology of cyclist collisions and falls. It is mainly about accident factors but also it collects cyclist characteristics and habits as well as trip characteristics. It has been split into seven categories: identification; context of the accident; meteorological conditions and road surface; falls and collisions; cyclist and bicycle equipment; accident's consequences and lastly accident story which that can also be used as a comment space.

The opening part has two objectives. First, identify people thanks to the date of birth and ID number in order to link each questionnaire with the registry. Second, ask internet and phone details to contact people and increase participation. The following category aims at locating the accident in terms of place and time. In this part we also ask the trip purpose and the type of traffic environment to get a frame of mind setting. In third part, we focus on meteorological accident factors such as weather, light, topology and trajectory. There are two main hypotheses to be tested here: accidents related to a lack of visibility for detecting any moving or stationary obstacle and those associated with poor road surface maintenance.

The next category aims at identifying the type of accident: fall or collision with or without the avoidance of an object or another road user. We ask in questions 16 to 18 for cyclist trajectory and in question 19 for the involvement of a third party or the involvement of an obstacle. The pilot survey demonstrated that cyclists do not make any distinction between an object and a person on their path.

As a result, those two questions have been combined in the final questionnaire and respondents were asked to specify if they avoided or hit any object or road user in the list. In the case of a collision, we also asked them if they got hit by another road user. If the accident was related to another person, then we also ask for the trajectory of this person in relation with the cyclist. By adopting the cyclist's point of view we intend to detect accident factors in the pre-crash situation, in the crash situation and in the emergency manoeuvre if any. Assuming that equipment has a protective action in some cases and is contributing accident factor in some others; the fifth part is dedicated to bike gear and maintenance as well as cyclist use of conspicuity device or protective equipment. Part six asks about crash consequences to identify causes of injuries and severity by selecting in the list an object by which they got injured. In addition, respondents had to specify if any emergency services came on site. To evaluate the proportion of people giving up with cycling after a crash, we ask them if they are still cycling. We also want to test the hypothesis that a lack of experience contributes to certain accident type. For instance, occasional cyclist who are mainly quasi exclusive car drivers; may have a higher probability to fall on a dedicated infrastructure during a Sunday leisure ride than experimented cyclists able to anticipate with obstacles such as kerbsides, gravels, holes or bumps. At the opposite, too much confidence may contribute to increase risk taking for experimented cyclists and contribute to different type of accident such as a collision with a turning car while overtaking a line of vehicule. In the final part of the questionnaire the cyclist is asked to write in details about how the accident occurred.

Survey Response Rate

The final survey response rate is 43% (1 095 questionnaires). There were 794 invalid addresses and 1455 non-responses. Most of responses arrived during the 2 first weeks. We consider the survey as successful given its nature: a postal survey with only one remind letter and a questionnaire sent together. Results showed differences between respondents and non-respondents. As in the pilot study, participants were older (62.5% are over 35 years old vs. 33%), more often women (27% vs. 19%), more often cycling on urban roads (65% vs. 54%). Respondents have been more often than others involved in collisions (30% vs. 22%). Age, gender and type of road bias are reduced compared to the pilot survey. We observe that the proportion of collisions is the same as in the pilot survey.

DISCUSSION

Learning from the pilot survey, the final response rate reached 43%. Using a mail survey, we can say that it has been successful [28,[START_REF] Kwak | A Comparison Between Mail and Web Surveys: Response Pattern, Respondent Profile, and Data Quality[END_REF]. The final sample exceeds 1000 respondents and should improve knowledge because accident factor measurement can be considered as representative as possible of injured cyclist crashes. As we explained in the above, the Rhône road trauma registry is slightly biased on injury severity and distance to the hospital. Furthermore, ir contains inpatients and outpatients; hence, we may only miss very slightly injured people.

Thanks to the questionnaires design improvement and the use of the most recent years available in the road trauma registry we also obtained bias reduction between respondents and non-respondents. A critical remark would be about the biggest bias which is age related. Therefore, using classification methods we need to determine if age is a constructive or an explanatory variable in the typology.

Gender bias is also important but classic for this type of survey. Nevertheless we must pay specific attention to gender effect because an estimate gives that women have 2.43 times more chances to have an accident than men while cycling [START_REF] Blaizot | Accidentalité à Vélo et Exposition au risque (AVER), Risque de traumatismes routiers selon quatre types d'usagers[END_REF]. At this stage we can only suppose that men are cycling for sport more than women even if they take more risks and ride faster; they may have more experience in cycling situations. For instance, we can suppose that a person cycling off-road learns and capitalizes knowledge that might be transferable to urban practice while avoiding an obstacle. In addition, most of commuters in urban areas are man and therefore we can suppose that they also may have more knowledge as a group on risky situations and black spots for the majority of their daily trips. At the opposite, women are mainly cycling on utilitarian trips in the city but not only to commute from home to work. They also shop, pick up children at school or kinder garden, take care of administrative formalities. Moreover, they are rarely practicing bike as a sport since childhood. As a result, they may have, as a group, globally less knowledge and less experience coming from the diversity of ridded surfaces. Then they may have more probability to crash because of an obstacle or a loss of control.

Moreover, women respect road rules because of a different internalization of safety rules by comparison with men [START_REF] Granie | Différences de sexe et rôle de l'internalisation des règles sur la propension des enfants à prendre des risques à vélo[END_REF]. Basically, to feel in security while interacting with other people, they respect rules. But, doing so, they will more hesitate in an urgent situation.

FIGURE 1 Questionnaire for a cyclist accident typology set up

The fact that the respondent group was more often cycling on city roads may go together with women overrepresentation in the respondent sample. Indeed, men practicing sport out of town and having an increased risk of single vehicle crashes are mainly non-respondents. The bigger proportion of collisions in our respondent sample is explainable by a double bias. The first one is a memory bias meaning people remember more easily an accident with a third party involved in an avoidance or a collision than a cyclist-only fall. The second is a self-selection bias which is the tendency to better be disposed to talk about an experience when someone else is involved because the cyclist feels unfairly involved. To sum up about non-response bias, we can suppose that it will not be a big problem to build up the typology because all distinctive types of accidents should be present in the statistical analysis. However, the population distribution in each type of accident may not reflect the reality and must be weighted. There are many adjustment techniques available in statistical literature that can be used if required [START_REF] Tivesten | Nonresponse analysis and adjustment in a mail survey on car accidents[END_REF][START_REF] Bechtel | True-Value Regression with Non-Response[END_REF][START_REF] Mckenzie | Part 2 -Assessing and minimising the impact of non-response on survey estimates, in Taskforce on "Improvement of Response Rates and Minimisation of Respondent Load[END_REF][START_REF] Macdonald | Addressing nonresponse bias in postal surveys[END_REF]. To conclude on biases, differences between respondents and non-respondents suggest to test different models in which some variables (age, gender and type of practice) will be included as constructive and explanatory to build up a typology of cyclist accidents.

All findings will be based on compiled cyclists' points of view and on a declaratory basis. Obviously, we do not take into account any other perspective: neither the witness nor the third part of the accident, if any. Nevertheless, there exists no study to our knowledge that determines if the typology accuracy would be better using other people's testimonies. From detailed accident studies analysis it appears that in most of the cases, cyclist declarations and testimonies, are coinciding on major accident factors collected in our questionnaire. Indeed, some details differ between cyclist and third part views (speed, exact trajectory…). Moreover if those details are crucial to build up prototypical scenario or crashes simulations, they are not in our typology construction. Also, we can assume a better efficiency of a cyclist accidents typology built by cyclists' declarations for single-crash accident prevention addressed to them.

CONCLUSION

The Cyclist Accident Typology survey is unprecedented in its scope in terms of number of participants (more than one thousand) and representativeness, the medical registry covering 80% of injured cyclist. In France, injured cyclists have been surveyed taking into consideration the circumstances of their accident from the lowest to the highest injury severity and for the very first time. The questionnaire improvement is detailed and can be used as an example for other studies. The response rate of 43 % for this postal survey partly ensures the quality of the main analysis results detailed in a next article. Some of the variables that influence response propensity have been identified; hence the typology results could be weighed. Although statistical analyses have to be done, some of the results presented here are already a first step toward a better cycling safety knowledge.

TABLE 1 Main results from the pilot survey

 1 concerning each person in the target population have been moved such as the third question in the final form 'where did your accident happen?' is before 'where was the other person coming from in relation to you?'; this question clearly concern cyclist who collided. Table

	N=95 %

ACKNOWLEDGMENTS

The authors wish to thank the French Institute for public heath surveillance for funding this research project, all the persons who took part in data collection and data recording, both within the Rhône Road Trauma Registry association (ARVAC, president E Javouhey), and within the IFSTTAR-UMRESTTE research unit (B Laumon, scientific adviser and A Ndiaye medical coordinator), all members of our research unit for their kindness and good advices about questionnaire revisions and packing/sending off. Cyclists associations in the Rhône to have made their members aware of the pilot survey and of the interviews, the 1078 victims who took time to fill the form and return the questionnaire, especially the several ones who sent us long letters to thank us for our interest in this subject, the few family members who contacted us to report the death of loved ones.