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1. chinaXiv:202004.00010 [pdf]

父母元情绪理念与青少年问题行为:迷走神经的调节作用

何晓丽; 袁小龙; 胡铭; 周丽晨
Subjects: Psychology >> Applied Psychology

探讨父母元情绪理念与青少年问题行为的关系以及青少年自身迷走神经功能对两者关系的影响。采用“心算任务范式”及问卷法,对224名青少年及其父母进行测量与调查。结果发现:(1)母亲情绪教导理念负向预测青少年内外化问题行为,母亲情绪失控理念正向预测青少年内外化问题行为,母亲情绪不干涉理念正向预测青少年外化问题行为;父亲情绪教导理念负向预测青少年内化问题行为,父亲情绪失控理念正向预测青少年外化问题行为。(2)当青少年迷走张力较低时,母亲情绪不干涉理念正向预测青少年外化问题行为;当青少年迷走抑制较低时,母亲情绪失控理念正向预测青少年内化、外化问题行为,父亲情绪失控理念正向预测青少年外化问题行为。综上,父母元情绪理念能够预测青少年问题行为,且父母元情绪理念对青少年问题行为影响存在差异。同时,迷走神经功能对父母元情绪理念与青少年问题行为的关系具有一定调节作用。

submitted time 2020-04-05 Hits50Downloads25 Comment 0

2. chinaXiv:202004.00009 [pdf]

CAN Algorithm: An Individual Level Approach to identify Consequences and Norms Sensitivities and Overall Action/inaction Preferences in Moral Decision-making

Chuanjun Liu; Jiangqun Liao
Subjects: Psychology >> Psychological Measurement

Gawronski et al. (2017) developed a CNI model to measure an agent’s norms sensitivity, consequences sensitivity, and generalized inaction/action preferences when making moral decisions. However, the CNI model presupposed that an agent considers consequences—norms—generalized inaction/action preferences sequentially, which is untenable based on recent evidence. Moreover, the CNI model generates parameters at the group level based on binary categoric data. Hence, the C/N/I parameters cannot be used for correlation analyses or other conventional research designs. To solve these limitations, we developed the CAN algorithm to compute norms and consequences sensitivities and overall action/inaction preferences algebraically in a parallel manner. We re-analyzed the raw data of Gawronski et al.(2017) to test the methodological predictions. Our results demonstrate that: (1) the C parameter is approximately equal between the CNI model and CAN algorithm; (2) the N parameter under the CNI model approximately equals N/(1 – C) under the CAN algorithm; (3) the I parameter and A parameter are reversed around 0.5 – the larger the I parameter, the more the generalized inaction versus action preference and the larger the A parameter, the more overall action versus inaction preference; (4) tests of differences in parameters between groups with the CNI model and CAN algorithm led to almost the same statistical conclusion; (5) Parameters from the CAN algorithm can be used for correlational analyses and multiple comparisons, and this is an advantage over the parameters from the CNI model. The theoretical and methodological implications of our study were also discussed.

submitted time 2020-04-03 Hits124Downloads48 Comment 0

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