深沉的心跳,深沉的思想? 从自然的音乐倾听行为预测一般认知能力
Larissa Sust1, Maximilian Bergmann2, Markus Bühner1
1Department of Psychology, Ludwig-Maximilians-Universität München, 80802 Munich, Germany.
Journal of Intelligence
|February 26, 2026
概括
每天听音乐的习惯,特别是歌词的偏好,与一般认知能力 (GCA) 微妙相关. 这项研究使用智能手机数据将音乐行为与认知见解联系起来,揭示了适度的预测性能.
科学领域:
- 认知心理学 认知心理学
- 计算社会科学 计算社会科学
- 数字化表型化是指数字化表型化.
背景情况:
- 听音乐是一种复杂的行为,涉及认知系统.
- 听音乐模式的个体差异可能反映出一般认知能力 (GCA).
- 数字行为数据为认知评估提供了新的途径.
研究的目的:
- 调查日常的音乐听力模式是否能预测一般认知能力 (GCA).
- 探索基于智能手机的行为数据对认知见解的有用性.
- 确定音乐听力行为的哪些方面最能预测GCA.
主要方法:
- 收集了来自185名参与者的五个月的智能手机音乐听力记录.
- 量化听力习惯 (持续时间) 和音乐偏好 (音频/歌词特征).
- 采用线性LASSO回归和随机森林模型,从行为特征预测GCA得分.
主要成果:
- 随机森林模型显示了音乐倾听行为和GCA之间的适度,可靠的关联.
- 基于歌词的偏好是最有预测力的特征组,其次是听力习惯.
- 音乐的音频特征对预测GCA的贡献很小.
结论:
- 认知能力可能微妙地反映在日常生活的微型模式中,与非成就相关的音乐听行为.
- 数字行为数据可以补充传统的认知评估,尽管仍然存在挑战.
- 未来的研究应该改进使用数字足迹来理解认知的方法.
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