利用数字技术量化心理健康的身体、社会和认知情感组成部分之间的相互关系。

Frank Iorfino, Mathew Varidel, William Capon, Matthew Richards, Jacob J. Crouse, Haley M. LaMonica, Shin Ho Park, Sarah Piper, Yun Ju Christine Song, Carla Gorban, Elizabeth M. Scott, Ian B. Hickie
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摘要

心理健康是一个超越简单关注主观情绪健康的概念,它更广泛地涵盖了我们的思维、感觉和行动能力,以实现我们在日常生活中的愿望。对多个领域(通常是相互影响的)进行测量和监测对于全面、完整地了解个人的心理健康至关重要。我们的目标是展示一款新型移动应用程序的能力,以描述澳大利亚普通人群的心理健康水平,并量化心理健康不同领域之间的相互关系。在2021年9月至2022年11月期间,我们从从事工作或教育的澳大利亚普通人群中收集了4901名成年人的横断面数据,他们都使用了一款移动应用程序(Innowell)。这些人填写了一份基线问卷,其中包括 26 个问题,涉及心理健康的七个领域(即体育锻炼、睡眠和昼夜节律、营养、药物使用、日常活动、社会联系、心理困扰)。网络分析同时应用于领域层面(例如,7 个节点代表每个项目群)和单个项目层面(即 26 个节点代表所有问卷项目)。只有 612 人(12%)在所有领域都表现良好。四分之一的人(n = 1204,25%)只有一个问题领域,而大多数人(n = 3085,63%)有多个问题领域。问题最多的两个领域是体育活动(n = 2631,54%)和社会联系(n = 2151,44%),紧随其后的是日常活动(n = 1914,39%)。在领域层面,心理困扰与日常活动之间的关联性最强(r = 0.301)。心理困扰是该网络中最核心的节点(根据强度和预期影响来衡量),紧随其后的是日常活动、睡眠和昼夜节律,然后是社会联系。项目级网络显示,网络中中心度最高的节点是:绝望、抑郁、功能障碍、努力程度、主观能量、无价值感和社会联系。由于社会联系、睡眠和昼夜节律以及日常活动在整个网络中的广泛关联,它们可能是干预的关键目标。虽然心理困扰并不属于最常见的问题,但它的中心地位可能表明其对于预防和早期干预的重要性。我们展示了一款新的移动应用程序监测心理健康和识别多个领域之间相互关系的能力,这可能有助于人们形成更加个性化的见解和方法。
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Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology
Mental fitness is a construct that goes beyond a simple focus on subjective emotional wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we want in our daily lives. The measurement and monitoring of multiple (often interacting) domains is crucial to gain a holistic and complete insight into an individual’s mental fitness. We aimed to demonstrate the capability of a new mobile app to characterise the mental fitness of a general population of Australians and to quantify the interrelationships among different domains of mental fitness. Cross-sectional data were collected from 4901 adults from the general population of Australians engaged in work or education who used a mobile app (Innowell) between September 2021 and November 2022. Individuals completed a baseline questionnaire comprised of 26 questions across seven domains of mental fitness (i.e., physical activity, sleep and circadian rhythms, nutrition, substance use, daily activities, social connection, psychological distress). Network analysis was applied at both a domain-level (e.g., 7 nodes representing each cluster of items) and an individual item-level (i.e., 26 nodes representing all questionnaire items). Only 612 people (12%) were functioning well across all domains. One quarter (n = 1204, 25%) had only one problem domain and most (n = 3085, 63%) had multiple problem domains. The two most problematic domains were physical activity (n = 2631, 54%) and social connection (n = 2151, 44%), followed closely by daily activity (n = 1914, 39%). At the domain-level, the strongest association emerged between psychological distress and daily activity (r = 0.301). Psychological distress was the most central node in the network (as measured by strength and expected influence), followed closely by daily activity, sleep and circadian rhythms and then social connection. The item-level network revealed that the nodes with the highest centrality in the network were: hopelessness, depression, functional impairment, effortfulness, subjective energy, worthlessness, and social connectedness. Social connection, sleep and circadian rhythms, and daily activities may be critical targets for intervention due to their widespread associations in the overall network. While psychological distress was not among the most common problems, its centrality may indicate its importance for indicated prevention and early intervention. We showcase the capability of a new mobile app to monitor mental fitness and identify the interrelationships among multiple domains, which may help people develop more personalised insights and approaches.
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