社会心理因素与交通环境对行人分心的联合影响

宁佩珊; 胡国清

doi:10.16462/j.cnki.zhjbkz.2023.02.016

社会心理因素与交通环境对行人分心的联合影响

doi: 10.16462/j.cnki.zhjbkz.2023.02.016

宁佩珊,
胡国清^,

410078 长沙，中南大学湘雅公共卫生学院流行病与卫生统计学系

基金项目:

国家自然科学基金 82103950

国家自然科学基金 82073672

国家自然科学基金 82273743

湖南省自然科学基金 2021JJ40808

详细信息

通讯作者:
胡国清，E-mail: huguoqing009@gmail.com

中图分类号: R195
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-25
- 修回日期: 2022-08-02
- 网络出版日期: 2023-02-20
- 刊出日期: 2023-02-10

Combined effects of psychosocial factors and traffic environment on pedestrians' distraction

NING Pei-shan,
HU Guo-qing^,

Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China

Funds:

National Natural Science Foundation of China 82103950

National Natural Science Foundation of China 82073672

National Natural Science Foundation of China 82273743

Natural Science Foundation of Hunan Province 2021JJ40808

More Information

Corresponding author: HU Guo-qing, E-mail: huguoqing009@gmail.com

摘要

摘要: 目的基于联合行为模型检验社会心理因素和交通环境对使用手机、与同行人员交谈、吃喝东西/吸烟3类行人分心的联合影响。方法采用多阶段随机抽样法抽取长沙市20个十字交叉路口作为研究现场，综合使用视频拍摄和现场问卷调查收集行人分心、社会心理因素和交通环境等数据。参照联合行为模型，从行人对不同分心的态度、主观规范、个人能动性和分心习惯等社会心理因素角度设计调查问卷。采用结构方程模型检验社会心理因素和交通环境对行人分心的联合影响。结果研究者共邀请到1 974名行人参与问卷调查，其中有效问卷1 741份(手机使用问卷600份、与同行人员交谈问卷660份、吃喝东西/吸烟问卷481份)。个人态度、主观规范、个人能动性、意图、分心习惯和交通环境因素共同解释行人手机使用、与同行人员交谈和吃喝/吸烟分心变异的22%、18%和23%。个人能动性、主观规范、个人态度是手机使用分心的主要解释因子，其间接效应分别为0.126、0.110和0.102(均有P＜0.05)；分心习惯是与同行人员交谈、吃喝东西/吸烟分心的主要解释因子，其总效应分别为0.158和0.250(均有P＜0.05)。交通环境对3类行人分心的影响均无统计学意义。结论社会心理因素和交通环境共同影响手机使用、与同行人员交谈和吃喝东西/吸烟3类行人分心的发生，不同分心的主要解释因子存在差异。未来应针对不同行人分心的主要解释因子，综合采用教育、立法和工程干预以减少行人分心。
- 行人 /
- 过街分心 /
- 社会心理因素 /
- 交通环境 /
- 联合行为模型
Abstract: Objective The combined influences of psychosocial factors and traffic environment on three types of pedestrian's distraction (including mobile phone use, chatting with other pedestrians, and eating/drinking/smoking) were examined based on the integrated behavioral model. Methods Multi-stage random sampling was used to select 20 road intersections in Changsha City as research sites. Video-taping and questionnaire surveys were used to collect data on distraction, psychosocial factors, and traffic environment. Based on the integrated behavioral model, we developed the questionnaire from the perspective of psychosocial factors including pedestrian's attitudes, subjective norms, personal agency, and distraction habits towards different types of distraction. A structural equation model was used to test the combined effect of psychosocial factors and traffic environment on pedestrians' distraction. Results A total of 1 974 pedestrians participated in the questionnaire survey, collecting 1 741 valid questionnaires (600 for mobile phone use, 660 for chatting with other pedestrians, and 481 for eating/drinking/smoking). The individual attitudes, subjective norms, personal agency, intention, distraction habits, and traffic environment accounted for 22%, 18%, and 23% of the variation of pedestrian's distraction in mobile phone use, chatting with other pedestrians, and eating/drinking/smoking, respectively. Personal agency, subjective norms, and attitudes were the main explanatory factors of mobile phone use, with indirect effects of 0.126, 0.110 and 0.102 (P < 0.05), respectively. Distraction habits was the major explanatory factor for chatting with other pedestrians and eating/drinking/smoking, with total effects of 0.158 and 0.250 (P < 0.05), respectively. The influence of traffic environment on the three types of distraction among pedestrians was not statistically significant. Conclusions Psychosocial factors and traffic environment jointly affected the incidence of three types of pedestrian's distraction, but the major explanatory factors differed across types of distraction. In the future, education, legislation, and engineering interventions should be integrated to address the major explanatory factors of distraction.
- Pedestrian /
- Street-crossing distraction /
- Psychosocial factor /
- Traffic environment /
- Integrated behavioral model

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图 1 手机使用影响因素的结构方程模型标准化路径图

注：^a P＜0.05。e1-e16表示各观察变量的残差。模型的绝对适配度统计量残差均方和平方根(root mean square residual, RMR)为0.037，渐进残差均方和平方根(root mean square error of approximation, RMSEA)为0.023，良适性适配指数(goodness-of-fit index, GFI)、调整后良适性适配指数(adjusted goodness-of-fit index, AGFI)、规准适配指数(normed fit index, NFI)、相对适配指数(relative fit index, RFI)均大于0.90，增值适配度统计量增值适配指数(incremental fit index, IFI)、非规准适配指数(Tacker-Lweis index, TLI)、比较适配指数(comparative fit index, CFI)均大于0.9，简约适配指数(parsimony goodness-of-fit index, PGFI)、简约调整后规准适配指数(parsimony-adjusted normed fit index, PNFI)、简约调整后比较适配指数(parsimony-adjusted comparative fit index, PCFI)均大于0.5，简约适配度统计量χ²/df＜2且理论模型的赤池信息准则(Akaike information criteria, AIC)和调整赤池信息准则(consistent Akaike information criteria, CAIC)均小于独立模型和饱和模型，提示该结构方程模型拟合良好^[8]。

Figure 1. Standardized path diagram of structural equation model about the influence factors of pedestrians' mobile phone use

下载: 全尺寸图片幻灯片

图 2 与同行人员交谈影响因素的结构方程模型标准化路径图

注：^a P＜0.05。e1-e13表示各观察变量的残差。模型的绝对适配度统计量RMR=0.042，RMSEA=0.024，GFI、AGFI、NFI、RFI均大于0.9，增值适配度统计量IFI、TLI、CFI均大于0.9，PGFI、PNFI、PCFI均大于0.5，简约适配度统计量χ²/df＜2且理论模型的AIC和CAIC均小于独立模型和饱和模型，提示该结构方程模型较为合理、简练且模型适配度较好^[8]。

Figure 2. Standardized path diagram of structural equation model about the influence factors of chatting with other pedestrians

下载: 全尺寸图片幻灯片

图 3 吃喝东西/吸烟影响因素的结构方程模型标准化路径图

注：^a P＜0.05。e1-e13表示各观察变量的残差。模型的绝对适配度统计量RMR=0.035，RMSEA=0.035，GFI、AGFI、NFI、RFI均大于0.9，增值适配度统计量IFI、TLI、CFI均大于0.9，PGFI、PNFI、PCFI均大于0.5，简约适配度统计量χ²/df＜2且理论模型的AIC和CAIC均小于独立模型和饱和模型，提示该结构方程模型较为合理、简练且模型适配度较好^[8]。

Figure 3. Standardized path diagram of structural equation model about the influence factors of eating/drinking/smoking

下载: 全尺寸图片幻灯片

表 1 多因素logistic回归分析模型纳入因变量及自变量赋值表

Table 1. Assignment table of dependent and independent variables of multivariate logistic regression model

类型	变量名	赋值
因变量	手机使用	发生=1，未发生=0(参照)
	与同行人员交谈	发生=1，未发生=0(参照)
	吃喝东西/吸烟	发生=1，未发生=0(参照)
自变量	性别	男性=1，女性=0(参照)
	年龄组(岁)	20~＜40=1，40~＜60=2，≥60=3(参照)
	教育程度	小学及以下=1(参照)，初高中=2，大学及以上=3
	出行目的	休闲游玩=1(参照)，上下班/上下学=2，办事(含购物)=3
	出行时段	上午=1，下午=0(参照)
	工作日/周末出行	工作日=1，周末=0(参照)
	态度得分(分)	原始值
	主观规范得分(分)	原始值
	个人能动性得分(分)	原始值
	意图得分(分)	原始值
	分心习惯	有=1，无=0(参照)
	车道数(个)	原始值
	道路宽度(m)	＜22=1(参照)，22~＜32=2，≥32=3
	限速	是=1，否=0(参照)
	中央隔离带	是=1，否=0(参照)
	过街安全岛	是=1，否=0(参照)

下载: 导出CSV

表 2 被调查过街行人的一般特征[n(%)]

Table 2. Basic characteristics of the surveyed street-crossing pedestrians [n(%)]

变量	手机使用问卷		与同行人员交谈问卷		吃喝东西/吸烟问卷
变量	分心者	未分心者	分心者	未分心者	分心者	未分心者
性别
男性	102(42.7)	159(44.0)	163(36.3)	85(40.3)	69(68.3)	164(43.2)
女性	137(57.3)	202(56.0)	286(63.7)	126(59.7)	32(31.7)	216(56.8)
年龄(岁)
20~＜40	194(81.2)	210(58.2)	311(69.3)	131(62.1)	70(69.3)	235(61.8)
40~＜60	40(16.7)	120(33.2)	115(25.6)	62(29.4)	27(26.7)	110(29.0)
≥60	5(2.1)	31(8.6)	23(5.1)	18(8.5)	4(4.0)	35(9.2)
教育程度
小学及以下	6(2.5)	13(3.6)	13(2.9)	7(3.3)	3(3.0)	13(3.4)
初高中	62(25.9)	79(21.9)	111(24.7)	56(26.5)	21(20.8)	88(23.2)
大学及以上	171(71.6)	269(74.5)	325(72.4)	148(70.1)	77(76.2)	279(73.4)
出行目的
上下班/上下学	98(41.0)	119(33.0)	93(20.7)	28(13.3)	39(38.6)	120(31.6)
办事(含购物)	95(39.8)	154(42.6)	180(40.1)	99(46.9)	37(36.6)	162(42.6)
休闲游玩	46(19.2)	88(24.4)	176(39.2)	84(39.8)	25(24.8)	98(25.8)
出行时段
上午	102(42.7)	192(53.2)	165(36.7)	132(62.6)	54(53.5)	188(49.5)
下午	137(57.3)	169(46.8)	284(63.3)	79(37.4)	47(46.5)	192(50.5)
工作日/周末
工作日	122(51.1)	198(54.9)	211(47.0)	87(41.2)	50(49.5)	201(52.9)
周末	117(48.9)	163(45.1)	238(53.0)	124(58.8)	51(50.5)	179(47.1)
合计	239(100.0)	361(100.0)	449(100.0)	211(100.0)	101(100.0)	380(100.0)

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