Afrifa-Yamoah Ebenezer, Adua Eric, Anto Enoch Odame, Peprah-Yamoah Emmanuel, Opoku-Yamoah Victor, Aboagye Emmanuel, Hashmi Rashid
School of Science, Edith Cowan University, Joondalup, WA Australia.
Rural Clinical School, Medicine and Health, University of New South Wales, Kensington, NSW Australia.
EPMA J. 2023 Nov 8;14(4):585-599. doi: 10.1007/s13167-023-00344-2. eCollection 2023 Dec.
The Suboptimal Health Status Questionnaire-25 (SHSQ-25) is a distinctive medical psychometric diagnostic tool designed for the early detection of chronic diseases. However, the synaptic connections between the 25 symptomatic items and their relevance in supporting the monitoring of suboptimal health outcomes, which are precursors for chronic diseases, have not been thoroughly evaluated within the framework of predictive, preventive, and personalised medicine (PPPM/3PM). This baseline study explores the internal structure of the SHSQ-25 and demonstrates its discriminatory power to predict optimal and suboptimal health status (SHS) and develop photogenic representations of their distinct relationship patterns.
The cross-sectional study involved healthy Ghanaian participants ( = 217; aged 30-80 years; ~ 61% female), who responded to the SHSQ-25. The median SHS score was used to categorise the population into optimal and SHS. Graphical LASSO model and multi-dimensional scaling configuration methods were employed to describe the network structures for the two populations.
We observed differences in the structural, node placement and node distance of the synaptic networks for the optimal and suboptimal populations. A statistically significant variance in connectivity levels was noted between the optimal (58 non-zero edges) and suboptimal (43 non-zero edges) networks ( = 0.024). Fatigue emerged as a prominently central subclinical condition within the suboptimal population, whilst the cardiovascular system domain had the greatest relevance for the optimal population. The contrast in connectivity levels and the divergent prominence of specific subclinical conditions across domain networks shed light on potential health distinctions.
We have demonstrated the feasibility of creating dynamic visualizers of the evolutionary trends in the relationships between the domains of SHSQ-25 relative to health status outcomes. This will provide in-depth comprehension of the conceptual model to inform personalised strategies to circumvent SHS. Additionally, the findings have implications for both health care and disease prevention because at-risk individuals can be predicted and prioritised for monitoring, and targeted intervention can begin before their symptoms reach an irreversible stage.
The online version contains supplementary material available at 10.1007/s13167-023-00344-2.
亚健康状态问卷-25(SHSQ-25)是一种独特的医学心理测量诊断工具,旨在早期发现慢性病。然而,在预测、预防和个性化医学(PPPM/3PM)框架内,25个症状项目之间的突触连接及其在支持对亚健康结果(慢性病的先兆)监测方面的相关性尚未得到充分评估。这项基线研究探讨了SHSQ-25的内部结构,并展示了其预测最佳和亚健康状态(SHS)的鉴别能力,以及呈现它们不同关系模式的直观表示。
这项横断面研究纳入了健康的加纳参与者(n = 217;年龄30 - 80岁;约61%为女性),他们对SHSQ-25进行了回答。使用SHS得分中位数将人群分为最佳健康组和亚健康组。采用图形套索模型和多维缩放配置方法来描述两组人群的网络结构。
我们观察到最佳健康组和亚健康组的突触网络在结构、节点位置和节点距离上存在差异。最佳健康组(58条非零边)和亚健康组(43条非零边)网络之间的连接水平存在统计学显著差异(p = 0.024)。疲劳在亚健康人群中成为一个显著的核心亚临床状况,而心血管系统领域对最佳健康人群最为相关。跨领域网络连接水平的差异以及特定亚临床状况的不同突出程度揭示了潜在的健康差异。
我们已经证明了创建SHSQ-25各领域与健康状态结果之间关系演变趋势动态可视化工具的可行性。这将提供对概念模型的深入理解,以指导规避亚健康的个性化策略。此外,这些发现对医疗保健和疾病预防都有影响,因为可以预测有风险的个体并对其进行优先监测,并且在症状达到不可逆阶段之前就可以开始进行针对性干预。
在线版本包含可在10.1007/s13167-023-00344-2获取的补充材料。