Hrev_master [page 62] [Emergency Care Journal 2025; 21:13783] Emergency Care Journal 2025 volume 21:13783 Abstract The aim of the present study was to investigate the relationship between self-reported motorcycling behavior and the severity of physical injuries from 2018 to 2021. This is a retrospective descriptive study. Preliminary injury data were obtained from the trauma registration system. The Short Motorcycle Behavior Questionnaire (SMRBQ) asked about the injured person’s behav- ior during a telephone call. Data were analyzed with SPSS version 21. The Poisson regression estimation revealed a statistically sig- nificant relationship between the overall behavior of the motorcy- clist and having a motorcycle license and a collision history. The incidence of serious injuries is correlated with motorcyclist behav- ior, age, driving purpose, driving rate during the week, motorcycle riding experience, and motorcycle driving license. Hospital out- comes had a statistically significant relationship with motorcyclist behavior, age, motor driving experience, motorcycle driving license, and collision history. By fostering a culture, educating individuals, and motivating motorcyclists in the community to obtain a permit, as well as strengthening the driving education sys- tem, traffic rules, and driver safety while riding a motorcycle, we can reduce the number of people without a license, consequently decreasing the incidence of serious injuries and improving hospital outcomes. Introduction Injuries resulting from Motor Vehicle Accidents (MVAs) are a growing global public health concern.1,2 Each year, many individ- uals suffer serious injuries or die due to motorcycle accidents in urban areas.3 Reports indicate that approximately 38% of motorcy- clists are involved in MVAs, and more than half sustain injuries.4 Furthermore, about 50% of fatal traffic accidents involve motorcy- clists.5 Traffic accidents make up 30% of all accidents in Iran. According to statistics from the World Health Organization, Iran ranks first globally in terms of MVAs. Among road users, pedestri- ans, motorcyclists, and cyclists are the most frequently injured. Notably, 70% of injuries caused by traffic accidents affect youth.6 In northern Iran, the prevalence of traffic injuries is 31 per 10,000 people, with most incidents involving motorcycle-car col- lisions.7 Motorcyclists face a higher risk of crashes than drivers of other motor vehicles. Studies also show that age, gender, and driv- ing behavior significantly influence the likelihood of a collision.8 In Iran, many motorcyclists live under moderate to poor eco- nomic conditions and often use motorcycles for transportation.10 As a result, they may avoid wearing helmets or opt for low-quality ones.11 Additionally, lawlessness, family conflicts, interpersonal disputes, and juggling multiple responsibilities characterize many Iranian motorcyclists. These factors contribute to hostile reactions to others’ negative behavior.9 Evaluating motorcyclists’ risky driving behaviors is critical for designing road safety interventions. To understand these behav- iors, it is essential to recognize that motorcyclists form a distinct group of road users with various motives for riding, such as recre- ation, sports, delivery, passenger transport, and even illegal activi- Correspondence: Naema Khodadadi-Hassankiadeh, Guilan Road Trauma Research Center, Trauma Institute, Guilan University of Medical Sciences, Namjoo St, Rasht, Iran. Tel.: +989113378344. E-mail: n_khodadady@yahoo.com Key words: behaviors, injury, motorcyclist, trauma. Conflict of interest: the authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Contributions: SY, manuscript concept and review; LK, definition of intellectual content, literature search; MS, data acquisition; EH, sta- tistical analysis; NK, manuscript design, preparation and review; MH, manuscript translation and editing, Ethical approval: the study was performed by the Declaration of Helsinki and approved by the Institutional Review Board of Deputy of research and Health Technology, Guilan University of Medical Sciences with the number (IR.GUMS.REC.1399.586 (. Informed consent: informed consent was obtained from the partici- pants. Acknowledgements: we would like to thank all the motorcyclists for their kind cooperation. Received: 1 March 2025. Accepted: 17 June 2025. Early view: 21 July 2025. This work is licensed under a Creative Commons Attribution 4.0 License (by-nc 4.0). ©Copyright: the Author(s), 2025 Licensee PAGEPress, Italy Emergency Care Journal 2025; 21:13783 doi:10.4081/ecj.2025.13783 Publisher's note: all claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. Risky behaviors and injury severity score of the injured motorcyclist Shahrokh Yousefzade-Chabok,1 Marjan Hosseinnia,2 Mohammad Sheikhi,3 Enayatollah Homaie Rad,4 Leila Kouchakinejad-Eramsadati,5 Naema Khodadadi-Hassankiadeh5 1Neuroscience Research Center, Trauma Institute, Guilan University of Medical Sciences, Rasht, Iran; 2School of Pharmacy, Department of Clinical and Administrative Sciences, Notre Dame of Maryland University, Baltimore, Maryland, USA; 3School of Medicine, Guilan University of Medical Sciences, Rasht, Iran; 4Social Determinants of Health Research Center, Trauma Institute, Guilan University of Medical Sciences, Rasht, Iran; 5Guilan Road Trauma Research Center, Trauma Institute, Guilan University of Medical Sciences, Rasht, Iran ties.12 Although many countries have developed detailed behav- ioral studies and specific questionnaires for motorcyclists, Iran lacks such research despite a higher rate of fatalities and unique cultural factors. Understanding how motorcyclist behavior corre- lates with Injury Severity Score (ISS) is essential. Materials and Methods Study design This retrospective descriptive study examined the relationship between the Injury Severity Score (ISS) and the behavior of motor- cyclists injured in traffic accidents. The study was conducted at Poursina Medical Center in Rasht, the capital of Guilan Province, from 2018 to 2020 (Ethics Code: IR.GUMS.REC.1399.586). Inclusion and exclusion criteria Inclusion criteria included: i) involvement in a traffic accident; ii) availability of a valid phone number in the hospital system; iii) the injured person was the motorcycle rider; iv) residency in Guilan province; v) age over 15 years; vi) ability to communicate fluently in Persian. Exclusion criteria included: i) individuals who could not be contacted due to unregistered phone numbers, disconnected or unavailable mobile phones, incorrect contact information, or fail- ure to answer calls; ii) patients recorded as deceased in the data system were excluded: in some cases, individuals passed away after discharge, which was discovered during follow-up calls; a total of 31 such individuals were excluded. An additional 46 injured individuals were excluded after they declined to participate during the interview. Sample size In the present study, random sampling was used due to the specificity, availability of the statistical population, and their con- tact information. According to the sample size formula, consider- ing a d = 0.1 and a = 0.88, the sample size was calculated as 298 people according to the following formula. Article Table 1. Questionnaire. Short Motorcycle Riding Behavior Questionnaire(SMRBQ) Items in English Item description Item Main factor: Unfit erroneous riding, intrusive and exhibitive behaviors Have you ever ridden so close to the vehicle in front that you had trouble stopping in an emergency? Tailgating the vehicles in front 1 Have you ever had to drive around corners, taking up the entire width of the road? Wide ride going round the corners 2 Have you ever lost control of your motorcycle while turning a corner due to high speed? Speeding (when reaching corners) 3 Have you ever entered a curve so fast that you got scared? Scaring speeding (when reaching corners) 4 Have you ever had a wheelie while riding a motorcycle or have you ever intended to? Wheelie attempts 5 Have you ever started going so fast that the front wheel of your motorcycle went off the road? Off road due to very quick pull away 6 Have you intentionally caused your motorcycle's wheels to spin during takeoff? Wheel spin (on purpose) 7 Have you unintentionally caused your motorcycle's wheels to spin during takeoff? Wheel spin (unintentional) 8 Have you ever ridden a motorcycle in the dark with the lights off? Riding at night just with dipped light 9 Have you ever driven a defective motorcycle? Riding impaired motorbike 10 Have you ever used any medication or substances that affect you’re riding ability before riding a motorcycle? Riding while on drugs or medications affecting riding safety 11 Have you ever ridden a motorcycle the wrong way on the street? Riding against the legal traffic direction 12 Have you ever ridden a motorcycle on the sidewalk? Sidewalk riding 13 Have you ever used a cell phone (talking or texting) while riding a motorcycle? Mobile conversation or messaging while riding 14 Second factor: Time and money opportunistic behaviors Have you ever driven a motorcycle faster than the speed limit on highways? Speeding (motorways) 15 Have you ever driven a motorcycle faster than the speed limit in residential areas? Speeding(residential roads) 16 Have you ever driven at speed in the space between two lanes? Riding between fast lanes of traffic 17 Have you ever carried a large, bulky load on your motorcycle? Carrying heavy weight 18 Have you ever carried more than one passenger on your motorcycle? Ride with more than one pillion passenger 19 Have you ever noticed the door of a parked vehicle open too late and barely avoided a motorcycle accident? Likely of hitting opened car doors 20 Have you ever crossed an intersection when the traffic light was red? Passing the red lights 21 Third factor: Helmet use behaviors Have you ever ridden a motorcycle without a helmet? Not using helmets while riding 22 Have you ever had someone ride on your motorcycle without a helmet? Not using helmets by pillion passengers 23 [Emergency Care Journal 2025; 21:13783] [page 63] In the period 2019-2021, 9000 motorcyclists were registered in the trauma system. Using Rendering Software, 400 people were selected (Considering the possibility of falling), of which 77 peo- ple were excluded for the above-mentioned reasons, and finally 323 samples were included in the study. Data gathering The data were collected retrospectively and included system data and telephone interviews. The telephone interview with this research instrument took a maximum of 8 minutes; the interviewer was a medical student, and the student had previously been trained to conduct a telephone interview. The initial interviews were con- ducted in the presence of a tutor, answering questions about the motorbike’s behavior only by the driver, not a family member or passenger sitting with the motorcyclist on the same motorbike. The ISS was also calculated based on its formula. Data gathering tools Demographic characteristics examined in this study were: age, sex, marital status, and education. The social characteristics that were examined in this study were: type of motorcycle, driving experience, having a license, driving time during the day, driving time per week, previous acci- dent history, and driving purpose. The clinical features studied in this study were hospital out- come and ISS The Short Motorcycle Riding Behavior Scale (SMRBQ) was used in this study. The main MRB consisted of 43 items, and for each item, respondents were asked to rate the frequency of their riding behavior over the past year by choosing an option from a 6- point scale: 1 = never, 2 = hardly, three = sometimes, 4 = very often 5 = regularly and 6 = Almost full time. This scale provides relia- bility with Cronbach’s alpha coefficients for five factors from 0.70 to 0.84.13 In the present study, however, the abbreviated form of this tool will be used, which has 23 items. Hosseinpourfizi et al. (2018) found a high correlation between this form and the main form of the motorcycling behavior questionnaire (Kendall Tao = 0.82). ICC was the full version, with the short version (0.92). The internal consistency of this questionnaire with Cronbach’s alpha was calcu- lated to be 0.85. Therefore, the Persian version of the summary of motorcycling behavior was found to be a valid, reliable, and prac- tical tool for evaluating motorcycling behavior in the study popu- lation.12 This tool has three subscales. The first subscale includes unfit erroneous riding and intrusive and exhibitive behaviors; the second factor is inappropriate behaviors, errors, and demonstra- tions, with 14 questions. The second subscale includes Time and money opportunistic behaviors, with six questions. The third sub- scale includes Helmet use behaviors with two questions (Table 1). Data analysis Frequency, percentage, mean, and standard deviation statistics were used to examine demographic, social, clinical, and motorcy- clist behavior variables. The present study used a score of 0 to 100 for the 23-item SMRBQ. The Poisson regression model analyzed whether demographic, social, and clinical variables (such as hospi- tal outcome and ISS) significantly affected the motorcyclist’s Article [page 64] [Emergency Care Journal 2025; 21:13783] Table 2. Demographic characteristics of the participants (n=323). Variables Categories N (%) Marital status Single 166(51.39) Married 157(48.61) Education Illiterate/Under diploma 172(53.25) Diploma 112(34.67) University 39(12.07) The purpose of motorcycling Recreational 83(25.70) Work 240(74.30) Motorcycle license Yes 154(47.68) No 169(52.32) Car license Yes 156(48.30) No 167(51.70) Helmet use Yes 45(13.93) No 278(86.07) Collision history Last five year 198(61.30) Last ten year 36(11.15) Lifetime 89(27.55) Hospital outcome Recovery 316(97.83) Disability 7(2.17) Table 3. Relationship between motorcyclist self-report behaviors and demographic variable. Variable F Sig t df p Mean Std. E 95% CI Upper Lower Marital Sub scale1 4.55 .03 -1.66 321 .09 -2.96 1.77 .53 -6.46 Subscale 2 .98 .32 -.48 321 .62 -1.13 2.33 3.45 -5.72 Subscale 3 .08 .76 -.87 321 .38 -2.77 3.18 3.47 -9.03 Total .21 1.52 -1.14 321 .25 -2.29 1.99 1.64 -6.22 Helmet use Sub scale1 10.22 .002 1.75 321 .081 4.48 2.56 9.53 -.55 Subscale 2 7.26 .007 1.47 321 .142 4.93 3.35 11.54 -1.66 Subscale 3 6.76 .010 1.87 321 62 8.57 17.56 16.33 -.41 Total 6.78 .010 2.08 321 .009 6.00 2.87 11.65 .34 Motor license Sub scale1 15.58 .000 4.78 321 .000 8.26 1.72 11.66 4.86 Subscale 2 2.81 .094 5.14 321 .000 11.54 2.24 15.96 7.13 Subscale 3 1.78 .182 1.70 321 .089 5.41 3.17 11.65 -.82 Total 15.89 .000 4.31 321 .000 8.40 1.94 12.24 4.57 Car license Sub scale1 3.82 .052 2.71 321 .007 4.79 1.76 8.27 1.32 Subscale 2 1.14 .286 4.02 321 .000 9.16 2.27 13.64 4.68 Subscale 3 .61 .432 2.64 321 .009 8.33 3.15 14.53 2.14 Total 3.94 48 3.79 321 .000 7.43 1.96 11.29 3.57 behavior. After completing each questionnaire, the data were entered into SPSS software version 21 and statistically analyzed. Results Three hundred twenty-three eligible injured motorcyclists par- ticipated in the study, all male and had normal (non-electric) motorcycles. The mean driving rate of the samples was 2.49 hours per day and 5.48 days per week. The mean history of motorcycling was 10.48 years. The mean and standard deviation of the age of the injured were 30.84 ±11.80 years. The majority of motorcyclists, 166 (51.39%), were single, 112 (34.67%) had a diploma, and 240 (74.30%) had a work goal of motorcycling. 154 (47.68%) had motorcycle licenses. Only 45 (13.93%) wore helmets. Seven people (2.17%) have been dis- charged from the hospital with disabilities. Most of them, i.e., 198 people (61.30%), have a history of MVA in the last five years (Table 2). Statistical t-test showed a statistically significant relationship between helmet and overall motorcycle behavior, p = 0.03. There was also a statistically significant relationship between having a motorcycle license and the overall behavior of a motorcyclist, p ≤ 0.001. This relationship was significant in two subscales of unfit erroneous riding, intrusive and exhibitive behaviors p ≤ 0.001 and Time and money opportunistic behaviors subscale p ≤ 0.001. In addition, there was a statistically significant relationship between having a vehicle license and overall motorcycle behavior of p ≤ 0.001 and all three subscales of Unfit erroneous riding, intrusive and exhibitive behaviors = p = 0.007, opportunistic monetary and temporal behavior of p ≤ 0.001 and helmet use behaviors p = 0.009 (Table 3). We are using ANOVA (analysis of variance) to assess the sta- tistically significant relationships between the overall scale of motorcycle behavior (p = 0.02) and two subscales: Unfit erroneous riding, intrusive and exhibitive behaviors (p = 0.02), and Time and money opportunistic behaviors (p = 0.03) in relation to a history of motorcyclist accidents (Table 4). Table 4 illustrates the relationship between the overall behav- ior of the motorcyclist and other variables. The Poisson regression estimation indicated that the overall behavior of the motorcyclist had a statistically significant relationship with possessing a motor- cycle license (p ≤ 0.001) and a history of accidents throughout the entire driving period (p = 0.01) (Table 5). The Poisson regression estimation indicated that ISS is corre- lated with motorcyclist behavior variables, with a p of ≤ 0.001, age (p = 0.003), driving purpose (p = 0.003), driving rate during the week (p = 0.003), motorcycle riding experience (p = 0.006), and it had a statistically significant relationship with motorcycle driving license (p ≤ 0.001) (Table 6). The Poisson regression estimation showed that a statistically significant relationship existed between hospital outcomes and the variables of motorcycle behavior (p ≤ 0.001), age (p = 0.001), motorcycle experience (p ≤ 0.001), motorcycle driving license (p ≤ 0.001), and accident history (p = 0.02) (Table 7). Discussion This study found that 52.32% of participants had no motorcy- cle license. A similar Iranian survey reported that only 29.4% of motorcyclists had licenses.14 Since this study focused on injured Article Table 4. The relationship between motorcyclist self-report behaviors and wearing a helmet. Variable N Mean Std. Std. E df F P 95% CI Lower Upper Education Sub scale1 323 71.82 16.01 .89 2 .28 .74 70.06 73.57 Sub scale2 323 69.14 20.92 1.16 2 .34 .71 66.85 71.44 Sub scale3 323 46.84 28.55 1.58 2 1.61 .20 43.71 49.96 Total 323 62.60 17.97 .99 2 .702 .49 60.63 64.57 Collision history Sub scale1 323 71.82 16.01 .89 2 3.59 .02 70.06 73.57 Sub scale2 323 69.14 21.75 1.16 2 3.41 .03 66.85 71.44 Sub scale3 323 46.84 28.556 28.55 2 1.73 .17 43.71 49.96 Total 323 62.60 17.97 17.97 2 3.68 .02 60.63 64.57 Table 5. Regression model of the correlation of total behavior scales with the motorcyclist's demographic variables. Variable Categories Coef Std. E t p 95% C I Upper Lower Marital Single 0.74 3.12 0.24- 0.81 5.40 6.90- Education Primary 1.19- 2.26 0.53- 0.59 3.25 5.64- Secondary 1.49 3.25 0.46 0.64 7.89 4.89- Age 0.22 0.25 0.90 0.36 0.72 0.27- Aim of driving Work 5.77 3.28 1.76- 0.07 0.67 12.23- Driving in week 0.76- 0.12 0.61- 0.54 0.16 0.32- Motor driving experience 0.07 0.31 0.23 0.81 0.68 0.53- License Motorcycles 10.23 2.27 4.50 0.000 14.71 5.76 Collision history Last 10 year 4.38- 3.47 1.17- 0.24 2.98 11.74- Lifetime 9.63- 3.84 2.50- 0.01 2.06- 17.19- [Emergency Care Journal 2025; 21:13783] [page 65] individuals, unlicensed riders are expected to be more prone to accidents and injuries. The need for compensation or insurance may also influence self-reports regarding licensure status. Only 14% of motorcyclists in this study reported helmet use. This rate is lower than those reported in Tehran (33%), southern Azerbaijan (18%), and Kerman (21.5%).15 The lower rate in Guilan may be attributed to the study’s focus on injured riders, where helmet use likely prevented hospitalization in other cases. Despite legal man- dates requiring helmet use for riders and passengers, the lack of public awareness and weak enforcement contribute to low compli- ance.5 Helmet usage is closely linked to motorcyclists’ overall behav- ior. Key factors influencing helmet-wearing behavior include per- ceived behavioral control, individual norms, behavioral goals, and perceived risk.16 In some cases, external factors, such as police presence at intersections, significantly increase helmet usage.17 While external enforcement can support compliance, this study found that individual behaviors were responsible for helmet non- use. The study also showed a significant association between license status and overall riding behavior. Unlicensed riders dis- played riskier behaviors, aligning with previous research that asso- ciates the lack of a valid license with higher accident risks.19,20 Holding a license is a strong predictor of rule compliance, includ- ing helmet use.21,22 Further, a significant correlation was found between the ISS and various aspects of motorcycling behavior, such as erratic or aggressive riding and opportunistic behaviors related to time and money. These findings are consistent with other Iranian studies that link high-risk behaviors with traffic violations and previous accidents.23 Other research has highlighted behavioral and social traits among Iranian motorcyclists, including lawlessness, family stress, and multiple obligations, contributing to impulsive or retaliatory driving patterns.9 Since many high-risk drivers have a history of previous accidents, post-accident behavioral interventions and tar- geted training could help prevent recurrence. This study also revealed a statistically significant relationship between ISS and helmet use. Similar research in Iran found that wearing a standard helmet significantly reduced facial fractures.14 A study in Kenya showed that riders and passengers who wore hel- mets sustained less severe head injuries than those without hel- mets.24 Other studies suggest that helmets reduce head and facial injuries and may lower hospital costs by up to threefold.23 Additionally, ISS correlated significantly with age. Older motorcyclists, especially those over 55, experienced worse sur- vival outcomes and more severe injuries, consistent with findings in both Iranian and international studies.25-27 Severe injuries among elderly riders pose significant burdens not only on families but also on the healthcare system. Article [page 66] [Emergency Care Journal 2025; 21:13783] Table 7. Regression model of the relationship between hospital outcome and subscales of behavior and demographic variables of motor- cyclist. Variable Categories IRR Std. E t P 95% C I Upper Lower Behavior 0.97 0.001 -14.20 0.000 0.98 0.97 Marital Single 1.09 0.10 0.98 0.32 1.32 0.91 Education Primary 0.99 0.06 -0.14 0.89 1.12 0.87 Secondary 0.94 0.09 -0.53 0.59 1.15 0.78 Age 1.02 0.006 3.38 0.001 1.03 1.009 Aim of driving Work 0.99 0.09 -0.04 0.96 1.19 0.82 Driving in week 1.004 0.003 1.31 0.19 1.01 0.99 Motor driving experience 0.96 0.008 -4.31 0.000 0.97 0.94 License Motorcycles 0.78 0.05 -3.40 0.001 0.90 0.68 Collision history Last 10 Year 0.76 0.08 -2.31 0.02 0.96 0.61 Lifetime 1.04 0.11 0.37 0.71 1.29 0.83 Table 6. Regression model of the relationship between ISS and total subscale of behavior and demographic variables of motorcyclist. Variable Categories Coef Std. E t p 95% C I Upper Lower Behavior 0.26- 0.001 19.02- 0.000 0.024- 0.029- Marital Single 0.05 0.08 0.65 0.51 0.21 0.10- Education Primary 0.09- 0.05 1.60- 0.10 0.02 0.20- Secondary 0.02- 0.08 0.28- 0.78 0.14 0.18- Age 0.01- 0.00 3.01- 0.003 0.00 0.02- Aim Of Driving Work 0.20 0.08 2.46 0.01 0.36 0.04 Driving In Week 0.008 0.002 2.95 0.003 0.01 0.002 Motor Driving Experience 0.01 0.006 2.73 0.006 0.034 0.005 License Motorcycles 0.37 0.06 6.11- 0.000 0.25 0.49- Collision History Last 10 year 0.12 0.08 1.42- 0.15 0.29 0.04 Lifetime 0.05 0.08 0.56 0.57 0.22 0.12- The severity of ISS was also linked to driving frequency and job-related use. As shown in Roudsari’s 2004 study, fatigue from long hours of riding increases injury risk.28 In Iran, where many motorcyclists come from moderate or low-income backgrounds, financial pressure may lead to unsafe practices, including avoiding helmet use or opting for cheap, ineffective helmets.10,11 Driving experience also showed a strong correlation with ISS. Studies in China and Iran confirmed that less experienced riders are more likely to suffer severe injuries in accidents.29,30 Moller (2020) found that holding additional certifications can reduce acci- dent risk by 2% per month.31 The study also found a statistically significant relationship between ISS and having a motorcycle license. Existing evidence supports the effectiveness of helmet laws and licensing require- ments in reducing injuries.32,33 Implementing automated systems such as camera-based helmet detection, license plate recognition, and vehicle tracking can enhance enforcement, particularly in urban areas.34 However, technologies like helmet-worn sensors remain eco- nomically unfeasible for widespread deployment. Law enforce- ment and automated detection systems can work together to reduce reliance on traffic police and increase rule compliance.34-36 In Vietnam, for example, the government distributed 50,000 helmets to low-income families to address the low rate of helmet use.37 This underscores the importance of combining legal enforcement with ethical responsibility and economic support for motorcyclists. This study also revealed a strong relationship between hospital outcomes and risky behaviors, especially speeding and opportunis- tic driving. An Iranian research study similarly identified high- speed motorcycle use as a key risk factor in fatal crashes.38 Research confirms that motorcyclist behavior strongly influences injury severity in accidents.39 Hospital outcomes were also significantly related to the rider’s age. Other studies show that older patients required longer hospital stays and more intensive post-discharge care.27,40-42 Given that physical injury severity increases with age, more extended hospi- talization is a logical outcome. Furthermore, having a valid license was significantly associat- ed with hospital outcomes. A study in Taiwan linked unlicensed riding to increased mortality and severe injuries in critical areas of the body.43 Similarly, Doan and Hobday reported that the lack of a driver’s license correlated with higher injury risks.44 Finally, the study found a strong relationship between hospital outcomes and prior accident history. Mekonnen et al. and Möller et al. both found that previous accidents significantly increased the likelihood of repeat incidents, reinforcing the need for preventive interventions for high-risk riders.31,45 Limitations This was a monocentric retrospective study that captured motorcycling behavior in a specific geographical area through a self-report questionnaire. Therefore, many negative and bad behaviors may not have been reported. However, the reported rate was also questionable and controversial. Observational studies can better examine motorcyclists’ behavior in the moment than retro- spective studies and portray the facts. Therefore, it is recommend- ed that future studies be observational and multicenter to overcome some of the limitations of the present study. Excluding deceased patients was a major limitation because those deceased motorcyclists may have engaged in unsafe riding behavior, were not wearing a helmet, exceeded the speed limit, or did not have a license at all. Conclusions This study demonstrates a clear association between high-risk motorcyclist behavior, Injury Severity Score (ISS), and hospital outcomes. Given the large number of motorcyclists and the high rate of motorcycle-related accidents in the community, addressing risky behavior is critical to reducing human and financial losses for both individuals and the healthcare system. The low rate of helmet use and its strong association with ISS highlight the urgent need for stricter enforcement of protective gear regulations. Public education campaigns, cultural initiatives promoting licensure, and improved training systems focused on traffic laws and safety could help reduce the number of unlicensed riders and decrease injury severity. Moreover, encouraging employers to require safety equipment for motorcycle-related activities could reduce physical injuries. 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