根据年轻司机的感知风险和驾驶时发短信的频率,对年轻司机进行了分层集群分析
Yusuke Hayashi1, Jonathan E Friedel2, Anne M Foreman3
1Pennsylvania State University, Hazleton, United States.
Journal of safety research
|June 18, 2023
概括
这项研究使用了集群分析,以根据驾驶时发短信 (TWD) 风险感知和频率找到不同的驾驶员群体. 它确定了三组,男性认为风险,但经常发短信显示出更高的冲动性.
科学领域:
- 交通安全研究 交通安全研究
- 行为心理学 行为心理学
- 数据分析技术 数据分析技术
背景情况:
- 驾驶时发短信 (TWD) 仍然是一个重大的安全问题.
- 了解驱动子组对于有效干预至关重要.
- 以前的研究并没有根据风险感知和频率明确区分TWD行为.
研究的目的:
- 证明集群分析在识别不同的驱动子组中的实用性.
- 根据司机的感知风险和TWD的频率来区分司机.
- 探索这些子组内的冲动性性别差异.
主要方法:
- 使用分层集群分析将驱动器组合起来.
- 根据感知TWD风险和频率分析了司机.
- 分组根据性别对特征冲动性和决策进行了比较.
主要成果:
- 三个不同的驾驶员子组出现了: (a) 高风险/高频率的TWD, (b) 高风险/低频率的TWD,以及 (c) 低风险/高频率的TWD.
- 高风险/高频率组的男性司机表现出比其他组更高的特征冲动性.
- 在冲动性决策中没有发现任何显著的性别差异.
结论:
- 这项研究首次提供了基于风险感知的频繁TWD违法者中明显的子组的证据.
- 研究结果表明,对于那些将TWD视为风险但却经常参与其中的司机来说,需要量身定制的干预策略,可能是性别特定的.
相关概念视频
Schemas
11.7K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
11.7K
Hypothesis Test for Test of Independence
3.7K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
H0: The two variables (factors)...
3.7K
Determination of Expected Frequency
2.2K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.2K
Introduction to Test of Independence
2.3K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
2.3K
Relative Risk
238
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
238
Cross-Sectional Research
11.4K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
11.4K


