Measuring Flow: Refining Research Protocols That Integrate Physiological and Psychological Approaches

IF 4.3 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Martin Wonders, Dan Hodgson, Nicola Whitton
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Abstract

Measuring flow, an optimal mental state defined by intense focus and immersion, can provide valuable insights into research on human engagement. However, a review of 69 studies identified significant methodological issues that could be undermining progress in this area of research. We discovered the use of eight nonvalidated psychological flow verification instruments (used in 33 studies), ambiguity and a lack of transparency in the interpretation and reporting of the verification results (36 studies), and a lack of screening of participants with only two studies screening for a disposition to experience a flow state. Additionally, despite the balance of challenge and skill being an essential precondition for inducing a flow state, 33 studies did not appropriately match flow-inducing activities to participant’s skill levels. These issues with measuring flow through self-assessment make it impossible to accurately validate hypothesised flow states using physiological approaches. To address these limitations, we propose a set of research protocol guidelines for integrating physiological and psychological measures to triangulate flow indicators. This provides a robust research framework that will allow the identification of physiological measures of flow that can provide a real-time objective alternative to subjective self-assessment instruments.

Abstract Image

测量流量:完善整合生理和心理方法的研究方案
心流是一种由高度专注和沉浸所定义的最佳精神状态,测量心流可以为人类参与研究提供有价值的见解。然而,对69项研究的回顾发现了可能破坏这一研究领域进展的重大方法问题。我们发现使用了8种未经验证的心理流验证工具(在33项研究中使用),在验证结果的解释和报告中存在歧义和缺乏透明度(36项研究),并且缺乏对参与者的筛选,只有两项研究筛选了体验心流状态的倾向。此外,尽管挑战和技能的平衡是诱导心流状态的必要前提,但33项研究并未将诱导心流的活动与参与者的技能水平进行适当匹配。这些通过自我评估来测量流量的问题使得使用生理方法准确验证假设的流量状态成为不可能。为了解决这些限制,我们提出了一套研究方案指南,以整合生理和心理措施来三角测量流量指标。这提供了一个强大的研究框架,将允许识别流动的生理测量,可以提供一个实时的客观替代主观的自我评估工具。
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来源期刊
Human Behavior and Emerging Technologies
Human Behavior and Emerging Technologies Social Sciences-Social Sciences (all)
CiteScore
17.20
自引率
8.70%
发文量
73
期刊介绍: Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.
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