ArticlemHealth2025
The impact of an online personal health platform on lifestyle and anthropometric factors related to type 2 diabetes risk and management.
Article in mHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- ANGPTL4-dependent metabolic reprogramming fuels RhoA signalling and microvascular dysfunction in diabetes.Acta diabetologica · 2026Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Type 2 diabetes mellitus (T2DM) presents a significant global health challenge due to its complex aetiology and widespread impact on various bodily systems. Its prevalence and associated mortality rates have been steadily rising, imposing substantial economic burdens and deteriorating quality of life. With the advent of mobile and computer applications (apps), there has been growing interest in utilizing technology to promote healthier lifestyles among T2DM patients. The Shae platform, an online platform, takes a personalized approach to lifestyle recommendations. This study aims to evaluate the impact of engagement with Shae on T2DM risk using the Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK) tool and associated lifestyle and anthropometric values, highlighting the potential of targeted and personalized health apps in improving health outcomes and user adherence. Methods: Participants for this study were drawn from those engaging with the Shae online platform from May 2014 to March 2018, totalling 1,690 participants after accounting for exclusion criteria. Measures included anthropometric data, survey responses, and AUSDRISK risk score calculations. Statistical analysis involved paired sample Results: The data primarily comprises females, constituting 86.9% (1,468 individuals), with males making up 13.1% (222 individuals). Notably, both female and male participants showed reductions in average AUSDRISK scores from baseline to follow-up. Female participants saw a decrease from 8.95 to 7.87, while male participants experienced a decrease from 10.82 to 9.79. Additionally, improvements were observed in average anthropometric measures such as body mass index (BMI), body fat index (BFI), and waist-to-height ratio (WHt) across both genders. Conclusions: While improvements were noted in diabetes risk and anthropometric measures, challenges in reducing sedentary behavior were evident, emphasizing the need for targeted interventions. Reductions in BMI and WHt suggest positive shifts in body composition, crucial for mitigating metabolic risks. Integrating mobile health platforms into diabetes prevention strategies holds promise for enhancing outcomes and empowering individuals to manage their health effectively.
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