探索孩童幸福感之家庭因素：結合數位表現型與生態瞬時評估法

Abstract

幸福感是心理健康重要的指標，其中兒童幸福感更是影響個體一生，我們以生理、認知、心理、社交與經濟面向回顧了兒童幸福感，並探索家庭場域內各項指標的影響；然而，過往研究受限於無法動態探索家庭環境、仰賴事後回報與他人陳述以及缺乏綜合性研究，故可能造成缺乏環境效度或矛盾結果。因此，本研究以數位表現型結合生態瞬時評估，開發一款智慧型手機應用程式，並結合智慧手環，向家庭中父親、母親、孩子的生理、認知、心理與社交進行評估與資料蒐集，並持續進行了一周的時間，累計上萬條數位表現型事件與上千次的生態瞬時評估。我們檢驗了此方法取得的資料具有不錯的信效度，依此建立初步預測模型，發現了不同過往研究的結果，並提出可能的解釋與未來的研究方向。本研究提供了一項新的方法探索實際家庭場域的動態資料，並在兒童幸福感上取得初步發現，望未來能以此方法作為基礎，設計更加細緻的家庭研究。

Well-being is a crucial indicator of mental health, particularly for children, as it significantly influences a lifetime. In this study, we reviewed the multidimensional aspects of children’s well-being, including physiology, cognition, psychology, social interaction, and economy, with a focus on their impact within the family context. However, previous research has been limited by the inability to capture the dynamic changes in the family, often relying on retrospective memory or reports from others, and a lack of comprehensive studies, potentially resulting in mixed results or ecological validity issues. To address these limitations, we employed a novel approach integrating digital phenotyping with ecological momentary assessment. We developed a smartphone application and used smartphones and smart bands to collect data continuously for a week on the physiological, cognitive, psychological, and social indicators of father, mother, and child within families. Finally, we accumulated tens of thousands of digital phenotypic events and over a thousand ecological momentary assessments. We examined the data obtained through this method and found it to have good reliability and validity. Based on this, we established the preliminary predictive models, which revealed results differing from previous studies, and proposed possible explanations and future research directions. This study offers an innovative approach to exploring dynamic data within actual family contexts and provides valuable insights into children's well-being research. This method lays the groundwork for future dedicated family studies.