1. Liz de Rome

2. Population 22.5m PTW709k (31 PTW per 1,000 population)

3. Road infrastructure Data collection & analysis Training & licensing Rider protection Road user education Risk taking Enforcement

4. National Road Safety Strategy – Safe Systems Reduce risk of crashes/reduce risk of injuries Research In-depth crash investigation studies in 3 States Emergency responses to motorcycle crashes Making roads motorcycle friendly (MRMF)

5. Guidelines ineffective if those who implement them do not understand motorcycle dynamics Products Guidelines/Seminar Multi-media presentation Target audience Road design, Construction & Maintenance staff

6. GLS (Graduated Licensing Schemes) Learner Provisional Full licence LAMS (learner approved motorcycles) PW 150 kilowatts per tonne/ 660cc Helmets mandatory for all riders Mandatory training (2 States) Research Novice rider survey, 2011 Evaluation of post-licence on-road coaching

7. Surveyed at compulsory training prior to licensing Response rate 81% (n=671) Average age 33 years 6 months as learner 6.4 hours riding per week 101 hours total riding Little or no experience riding in adverse conditions: At night – 36% In rain - 57% Heavy traffic– 22% High speed roads (51%) Should such experience be required before licensing or would that increase risk exposure before novices feel ready?

8. Small groups (3 riders + Coach) 4 hours including rural & urban riding Advice & feedback from coach Group discussion & feedback 2400 volunteers in randomised controlled trial Provisional licence Interviewed at recruitment then 3 & 12 months Randomly allocated to treatment or control group Treatment group do the coached ride Control group are not coached Compared on outcomes at 12 months Outcomes Self- reported crashes, near misses, violations Police records

9. Local and international market Many products not suitable for Australian climate Lack of independent information for consumers Pressure to buy most expensive Price and brand name unreliable indicators of quality

10. Aim: Investigate the effectiveness of motorcycle protective clothing in crashes Method: Injured & uninjured riders who crashed in the ACT* over 12 months (n=212) Recruited at hospitals & motorcycle crash repair services. In-depth interview + follow up survey at 2 & 6 months Exposure – what they were wearing Outcome – injury type & severity, general health, impairment, recovery progress & return to work Controlled for– age, gender, type of motorcycle, single/multi-vehicle crash, impact contact surface & estimated speed of impact. *ACT- Australian Capital Territory

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12. Those wearing motorcycle clothing were less likely to: be admitted to hospital have any cuts, lacerations & abrasions report severe pain at base line interview have disabilities at 2 months They were more likely to be back at work at 6 months Over 1 in 4 motorcycle jackets, pants & gloves failed in the crash. 12

13. Riders want: Certainty about product quality Independent information not just advertising Products suitable for Australian climate Industry needs: Incentive & assurance of market demand for reliable protective gear Consumer protection Ensure products are fit for the purpose for which they are sold

14. Use the EU Standards tests to evaluate locally available products Not pass/fail but test to destruction Rank performance on a scale – e.g. 5 star ratings Include weather protection & thermal qualities Make the information available to riders (e.g. swing tag at point of sale, website etc)

15. Acknowledgement of co-investigators Rebecca Ivers, Narelle Haworth, Michael Fitzharris, Stephane Heritier & Drew Richardson With thanks to The George Institute for Global Health Centre for Accident Research and Road Safety - Queensland (CARRS-Q) Monash University Accident Research Centre (MUARC) VicRoads and UK RiDE magazine, who have provided their readers with test results based on the EU standards for many years. 15

17. MC ClothingCuts/abrasionsSoft tissueAny injuries Jacket- 58%NS Jacket +BA- 63%- 33%- 23% Gloves- 70%- 40%NS Gloves + BA- 73%- 62%- 45% Pants- 37%NS Pants + BA- 91%- 47%- 39% MC BootsNS- 65%NS MC Boots + BA- 90%- 69%- 45% Non-MC boots- 76%- 61%- 53% NS Not statistically significant. BA Body Armour 17