Mahasarakham University Social Network Survey: A Dataset for Motorcycle Helmet Use and Traffic Injury Prevention in Thailand
Year: 2024
Type: dissertation
Study design: Observational Study
Abstract: This article presents data from a social media-hosted (Facebook) survey conducted between May and September of 2018 of multiple motorcycle-related risk behaviors, including not using a helmet, cell phone use, riding a motorcycle with multiple driver/passengers, and speeding, conducted among undergraduate students from Mahasarakham University (MSU). MSU is located in the Northeastern region of Thailand, which exhibits the lowest rate of motorcycle helmet use, according to national risk behavior surveys. This survey data includes 168 motorcycle users, who answered 28 questions on their demographics, subjective social status (SSS), the multiple motorcycle-related risk behaviors, decision-making preference (derived from time discounting and risk preference scenarios), friendship network information at the university (the information on who are friended with whom), and network threshold questions (how many close friends or nearby students exhibiting a behavior would alter one’s behavior). The survey data allows scientists to examine social determinants of motorcycle-related risk behaviors and the role of decision-making preference in the at-risk population in Thailand to enhance the global health perspective of these topics. In addition, the friendship data can allow the generation of network graphs and analyze risk clustering over their social networks. The shared dataset includes participant anonymized IDs, raw survey responses, and ID numbers of nominated friends. The availability of this dataset will provide scientists with information and global health research opportunities on motorcycle-related risk behaviors in a particularly at-risk population for motorcycle accidents in a location where motorcycle use is widespread.
Author: Albers, Alexandra Na
Institution: Mahasarakham University
Language: English
Topic: Traffic and Road Safety
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7002043561