Cross-Sectional Associations Between the Five Factor Personality Traits and Leisure-Time Sitting-Time: The Effect of General Self-Efficacy
Cross-Sectional Associations Between the Five Factor Personality Traits and Leisure-Time Sitting-Time: The Effect of General Self-Efficacy
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DOI：
10.1123/jpah.10.4.572
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发表时间：
2013-05-01
影响因子：
3.1
通讯作者：
Jorgensen, Torben
中科院分区：
文献类型：
--
作者：
Ebstrup, Jeanette Frost;Aadahl, Mette;Jorgensen, Torben
背景：休闲时间静坐时间（LTST）被视为身心健康的一个可能的独立危险因素，但对心理决定因素的研究很少。研究了坐姿时间与神经质、外向性、开放性、宜人性和责任心等人格维度之间的关联，以及一般自我效能感（GSE）的作用。方法：2006-08 年，丹麦预防与健康研究中心进行了一项基于人群的横断面研究。在哥本哈根郊区随机抽取 18 至 69 岁的男性和女性 (N = 3471)。使用 NEO 五因素量表、一般自我效能量表和身体活动量表 2。结果：LTST 与外向性、尽责性和开放性呈负相关，而神经质则呈正相关 (R-2 = .13)。当 GSE 被包括在内时，与宜人性的关联变得显着正相关。 5个关联均由GSE介导，介导比例在23%-60%之间；但效应大小适中。结论：这些横断面结果表明，人格特质和 GSE 可以被视为 LTST 的关联；但未来的纵向数据对于做出因果陈述并排除拟合数据的替代模型是必要的。
Background: Leisure-time sitting-time (LTST) is seen as a possible independent risk-factor for physical and mental health, but research on psychological determinants is sparse. Associations between sitting-time and the personality dimensions of neuroticism, extroversion, openness, agreeableness, and conscientiousness, and the role of general self-efficacy (GSE) were investigated. Methods: A population-based, cross-sectional study was conducted at the Research Centre for Prevention and Health, Denmark, in 2006-08. Men and women (N = 3471) aged 18 to 69, were randomly sampled in the suburbs of Copenhagen. The NEO Five-Factor Inventory, the General Self-Efficacy-Scale, and the Physical Activity Scale 2 were used. Results: Negative associations were found between LTST and extroversion, conscientiousness, and openness, while neuroticism showed a positive association (R-2 = .13). The associations with agreeableness became significantly positive, when GSE was included. All 5 associations were mediated by GSE, with mediation proportions between 23%-60%; but with modest effect sizes. Conclusions: These cross-sectional results indicate that personality traits and GSE could be considered as associates of LTST; but future longitudinal data are necessary to make causal statements and rule out alternative models fitting data.