five

Model fit indices for six CFA specifications.

收藏
Figshare2025-12-05 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Model_fit_indices_for_six_CFA_specifications_/30806855
下载链接
链接失效反馈
官方服务:
资源简介:
Flow is an absorbing, effortless, and intrinsically rewarding state that unfolds over time. We adapted the nine-item Psychological Flow Scale (PFS) to Polish and evaluated it in a preregistered laboratory study designed to capture fine-grained changes in flow. After individual skill calibration, participants completed a 20-trial pursuit-tracking task following a chaotic Lorenz trajectory; data from 140 participants met inclusion criteria. Multilevel confirmatory factor analysis supported the theorized structure: Absorption, Effortless Control, and Intrinsic Reward formed correlated first-order factors nested under a second-order Flow factor at both the within-person and between-person levels (χ²(46) = 345.35, CFI = 0.98, RMSEA = 0.05). Reliability was excellent for aggregated scores (generalizability RkF = 1.00) and remained high for detecting trial-to-trial change (Rc = 0.88), indicating sensitivity to momentary fluctuations. Convergent validity was evidenced by moderate correlations with the Flow Short Scale administered concurrently (r = .28–.39), low-to-modest correlations with task performance score (r = .13–.32), and low-to-modest associations with the General Flow Proneness Scale (r = .13–.26). Complementary hierarchical exploratory graph analysis corroborated this three-facet-plus-general structure. Collectively, these findings establish the Polish PFS as a reliable, culturally appropriate instrument for tracking the temporal dynamics of optimal experience and illustrate how repeated measurement coupled with multilevel modelling can advance research on flow.
创建时间:
2025-12-05
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作