# In-Depth Evaluation of Association between Crash and Hand Arthritis via Naturalistic Driving Study
## 1 Introduction
Secondary task engagement, which has been defined as \"attention given to non-driving-related activity, typically to the detriment of driving performance\" (2019), has been shown to be a critical reason for crashes, causing about 1.2 million crashes and contributing to 16% of all fatal crashes in 2008 (2019). Secondary tasks such as cellphone use have a high prevalence among drivers and can significantly increase driving risk (2019; 2019). [PERSON] et al. (2019) examined secondary task engagement by age group and showed that, compared to middle-aged drivers (35-65 years old), senior drivers (\(\geq\)65 years old) were much less likely than others to be engaged in secondary tasks (40.49% vs. 51.68%) and cellphone use (0.87% vs. 5.30%). However, the relative risk associated with distraction was much higher, with OR = 1.71 versus 1.58 for overall distraction and OR = 5.72 versus 2.11 for cellphone use. Examining whether arthritis plays a role in the prevalence and relative risk of distraction can improve the general understanding of the risk for senior drivers. The majority of existing arthritis-related studies have relied on self-reported online surveys, or interviews or experiments with relatively small sample sizes. Large-scale NDSs enable researchers and policymakers to observe driver behavior and crash risk under real-life driving conditions (2019; 2020). The participants of an NDS will drive an instrumented vehicle with no specific instructions under real-life driving conditions for an extended period of time. The instrumented vehicles, typically the participants' own, are equipped with a nonintrusive data acquisition system (DAS). The DAS is capable of recording comprehensive driving data, including GPS, radar, acceleration, and multi-channel video, capturing both the environment and the vehicle interior. Large NDSs are typically accompanied by surveys to gather demographic information, health conditions, crash history, and other information. The combination of comprehensive driving data and survey data provides an opportunity to draw insight into crash causation, driver risk factors, and potential safety countermeasures. The inconsistency in the relationship between arthritic and crash risk, as well as the association between arthritis and other known risk factors, deserves in-depth research using novel data sources. In this study, we attempt to fill in the knowledge gap by utilizing the SHRP 2 NDS dataset to assess the impact of arthritis and crash risk, as well as the association of arthritis with other risk factors. The HPR 2 NDS is the largest NDS to date, with more than 3400 participants and 1 million hours of continuous driving data. The objectively collected naturalistic dataset provides accurate information about the moment the crashes happened and the driver's behavior under normal driving conditions. The NDS data provide complementary evidence to studies based on self-reported crashes ([PERSON] et al. [9] and [PERSON] et al. [20]). A comprehensive analysis was conducted to examine the association between arthritis and crash risk, secondary task engagement, driver personality, and fitness-drive information.