Smartphones promise great potential for personality science to study people's everyday life behaviours. Even though personality psychologists have become increasingly interested in the study of personality states, associations between smartphone data and personality states have not yet been investigated. This study provides a first step towards understanding how smartphones may be used for behavioural assessment of personality states. We explored the relationships between Big Five personality states and data from smartphone sensors and usage logs. On the basis of the existing literature, we first compiled a set of behavioural and situational indicators, which are potentially related to personality states. We then applied them on an experience sampling data set containing 5748 personality state responses that are self‐assessments of 30 minutes timeframes and corresponding smartphone data. We used machine learning analyses to investigate the predictability of personality states from the set of indicators. The results showed that only for extraversion, smartphone data (specifically, ambient noise level) were informative beyond what could be predicted based on time and day of the week alone. The results point to continuing challenges in realizing the potential of smartphone data for psychological research. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

中文翻译：

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人格状态如何与智能手机数据相关联？

智能手机有望为人格科学研究人们的日常生活行为提供巨大潜力。即使人格心理学家对人格状态的研究越来越感兴趣，尚未研究智能手机数据和个性状态之间的关联。这项研究为了解如何将智能手机用于人格状态的行为评估提供了第一步。我们探索了五种人格状态与智能手机传感器和使用日志中的数据之间的关系。在现有文献的基础上，我们首先编制了一组行为和情境指标，这些指标可能与人格状态有关。然后，我们将它们应用于包含5748个个性状态响应的体验采样数据集，这些响应是30分钟时间范围的自我评估以及相应的智能手机数据。我们使用机器学习分析来从一组指标调查人格状态的可预测性。结果表明，仅对于外向性，智能手机数据（特别是环境噪声水平）具有比仅基于时间和星期几可以预测的信息更多的信息。结果表明，在实现智能手机数据在心理学研究中的潜力方面仍存在挑战。©2020作者。John Wiley＆Sons Ltd代表欧洲人格心理学协会出版的《欧洲人格杂志》