在生态瞬间评估数据的动态网络分析中,双极与单极缩放
Arwin Nemani1, Bettina Hufschmidt1, Viktoria Kohl1
1Department of Clinical Psychology and Psychotherapy, Goethe University Frankfurt, Frankfurt am Main, Germany.
PloS one
|March 18, 2025
概括
在生态瞬间评估 (EMA) 中,双极缩放显著提高了动态网络分析的数据质量,通过减少零通货膨胀和增加响应可变性,从而导致更强大的模型.
科学领域:
- 心理学是一门科学.
- 网络分析 网络分析
- 数据科学是数据科学.
背景情况:
- 生态瞬间评估 (EMA) 越来越多地用于实时数据收集.
- 动态网络分析为复杂的心理过程提供了洞察力.
- 选择合适的测量尺度对于EMA的数据质量至关重要.
研究的目的:
- 为了比较双极和单极缩放在EMA数据中的双极和单极缩放的统计和临床益处.
- 评估扩展方法对动态网络分析的影响.
- 确定哪种缩放方法可以为网络建模提供更高质量的数据.
主要方法:
- 47名学生参加了为期五周的EMA研究.
- 参与者每天三次使用单极或双极尺度完成自我报告测量.
- 为每个参与者构建和分析了非图形网络模型.
主要成果:
- 双极缩放组表现出明显较低的零通货膨胀 (2.37%对10.31%) 和更大的响应变化.
- 网络分析显示,在双极组中,具有显著网络边缘的参与者比例较高 (69.57%对41.67%).
- 与单极缩放相比,双极缩放与零反应的几率较低有关 (p = .038).
结论:
- 双极缩放通过减少零通货膨胀和增加可变性来提高EMA数据质量.
- 这导致了更丰富,更具信息性的动态网络模型.
- 建议在临床人群中进一步验证.
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