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重金属音乐对青少年冒险行为影响的认知与神经机制研究
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摘要
许多研究都发现青少年阶段是冒险行为出现的高发期,并试图探究冒险行为背后的认知神经机制。近年来,Steinberg等人提出了青少年冒险行为的双系统模型,从发展认知神经科学的角度对这个问题进行了解释。音乐在青少年生活中占有重要的位置,许多青少年对于重金属音乐都表现出较为明显的偏好。本研究试图在双系统模型的基础上从社会认知神经科学的视角,对重金属音乐影响青少年冒险行为的认知与神经机制进行探讨,并进而在此基础上提出一种新的理论模型。
     研究一:考察重金属音乐偏好对青少年冒险行为的预测作用。首先采用探索性结构方程模型修订Arnett感觉寻求问卷并参考国外其他版本的结构对项目进行筛选,以中国初中生群体为样本(N=3,505),并对问卷信度、结构效度、效标关联效度分别进行考察。随后采用Rentfrow等人的音乐偏好测验通过Goldberg提出的层次结构策略对数据进行分析,考察中国青少年(N=445)的音乐偏好结构。最后考察重金属音乐所对应的强力性因素对Arnett感觉寻求问卷得分的预测作用。
     研究二:音乐的外部变量(重金属亚文化)对重金属音乐爱好者冒险行为影响。根据同伴音乐偏好的异同,创设不同社会情境(音乐偏好相同/不同的同伴在场),采用自主开发的交通灯任务,在重金属音乐爱好者(N=17)中考察对应情境下冒险行为的差异。
     研究三:音乐的内部变量(音乐速度)对冒险行为影响的行为与事件相关电位研究。首先通过改变背景中重金属音乐的音乐速度(快速/慢速),考察青少年(N=21)在完成BART任务时的冒险行为差异。随后通过事件相关电位技术,采用Go-Nogo范式考察背景中重金属音乐的音乐速度(快速/慢速)对青少年(N=17)认知控制能力的影响,及其电生理特征。
     在以上对于重金属音乐与冒险行为的实证研究基础上,本研究得到以下结论:
     1.修订的Arnett感觉寻求问卷具有良好的信度、效度,可有有效评估中国青少年的冒险行为。
     2.通过层次结构策略在中国青少年群体中进行音乐偏好结构验证,得到了由强力性、复杂性、甜美性、现代性、朴素性五个因素构成的MUSIC模型。
     3.与重金属音乐偏好有关的强力性因素,可以有效预测青少年的冒险行为水平。
     4.交通灯范式具有良好的适用性,可广泛用于冒险行为的相关研究。
     5.重金属音乐爱好者在不同社会情境下,冒险行为水平有显著差异,具体表现为音乐偏好相同的同伴在场时、音乐偏好不同的同伴在场时、被试独自完成任务时,三种背景下的冒险行为依次降低。
     6.背景中的重金属音乐速度对冒险行为有显著影响,个体在快速重金属音乐背景比慢速背景下产生更多的冒险行为。
     7.背景中的重金属音乐速度会通过占用认知控制资源,来影响个体的认知控制能力,音乐速度越快,占用的认知资源越多,认知控制能力会降低。
     8.背景中的重金属音乐速度通过影响个体抑制冲动的能力,来影响冒险行为。快速的重金属音乐背景,会降低个体抑制冲动的能力,导致冒险行为的增多。
     9.实证研究证实了重金属音乐对冒险行为影响的双系统模型的两条主要路径,重金属音乐的外部变量通过影响个体的社会情感奖赏系统影响冒险行为结果;重金属音乐的内部变量通过影响个体的认知控制系统影响冒险行为结果。
Heightened vulnerability to risk taking in adolescence has been found in many studies.Researchers tried to explore the neuro-cognitive mechanisms underlying risk-taking behavior.In recent years, Steinberg et al.(2008) proposed a dual system model, which tried to explainthis issue from a developmental cognitive neuroscience perspective. Music plays an importantrole in adolescents’ daily life. Moreover, adolescent shows significant preference for heavymetal music. This study attempts to propose a new theoretical model, using a social cognitiveneuroscience perspective, on the basis of the dual system model that could explain whatcognitive and neural mechanisms might underly the impact of heavy metal music onrisk-taking behavior.
     Study1: The predictive effect of heavy metal music preference on adolescent’srisk-taking behavior was examined. First, A Chinese version of the Arnett Inventory ofSensation Seeking (AISS) was refined among a young adolescent sample (N=3,505) usingexploratory structural equation modeling (ESEM).And the questionnaire’s reliability,construct validity, criterion-related validity were examined. Secondly, the musical excerpts,which were selected based on Rentfrow et al.(2011), were played to the Chinese adolescents(N=445). Adolescents were informed to indicate their degree of liking for each musicalexcerpt. The hierarchical structure of the one-through five-factor solution procedure whichwas proposed by Goldberg (2006) was conducted to confirm the musical preference structure.Finally, the predictive effect of the Intense factor which represented heavy metal music on theArnett Sensation Seeking Scale’s scores was calculated.
     Study2: The impact of external musical variables (heavy metal subculture) on a heavymetal music fan’s risk-taking behavior was examined. The heavy metal music fan (N=17)finished a traffic light task under different social contexts which were created by manipulatingpeer’s music preference similarities (same/different music preferences with participant). Thedifference of risk-taking behavior between the two social contexts was examined.
     Study3: A behavior and event related potentials (ERPs) study on the effect of externalmusical variables (music tempo) on risk-taking behavior. First, adolescents’(N=21)differences of risk-taking behavior under different speed (fast/slow) heavy metal musicbackgrounds were examined by the Balloon Analog Risk Task (BART). Secondly, by usingevent-related potentials technology, adolescents (N=17) were asked to finish Go-Nogoparadigms under different speed (fast/slow) heavy metal music backgrounds. Their cognitivecontrol abilities, and electrophysiological characteristics were examined.
     Based on the empirical research analyses results on the heavy metal music preferenceand risk-taking behavior, following conclusions were found in these studies:
     1. The results were quite supportive of the applicability of the AISS to Chinese youngadolescents
     2. A latent5-factor MUSIC structure underlying music preferences that is genre free andreflects primarily emotional/affective responses to music was confirmed to fit a Chineseadolescent sample.
     3. The Intense factor which represented heavy metal music predicted adolescents’risk-taking behavior.
     4. Traffic lights paradigm had a good applicability and could be widely used in studies ofrisk-taking behavior.
     5. Significant differences were found of heavy metal music fan’s risk-taking behaviorbetween different social contexts. Participants took more risks, when in same musicpreference conditions than different music preference conditions.
     6. The heavy metal music tempo in the background had a significant impact onrisk-taking behavior. Significantly greater risk-taking behaviors were demonstrated with fasttempo, heavy metal music backgrounds than slow tempo.
     7. Fast heavy metal music tempo in the background consumed more cognitive resources,that presumably can reduce cognitive control capacity.
     8. Fast heavy metal music tempo in the background induced more risk-taking behaviorby reducing cognitive control capacity.
     9. Two main paths were found in empirical studies. One path was external variables ofheavy metal music induced risk-taking behavior by affecting individuals' socio-emotionalreward systems. The other path was internal variables of heavy metal music inducedrisk-taking behavior by influencing individuals’cognitive control capacity.
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