Chances of Increasing Youth Health Awareness through Mobile Wellness Applications

Impact of dietary habit changes on college students physical health insights from a comprehensive study

College students' health and behavioral issues are gaining increasing global attention, with the optimization and choices of dietary structure becoming key factors affecting their physical and mental development. This study examines adolescents to explore the impact of dietary habit changes on their physical health. First, we investigated the factors influencing dietary habit changes after students entered college through questionnaires. Based on the theory of planned behavior, we constructed a structural equation model and found that perceived behavioral control had the greatest impact on college students' dietary choices. In addition, we investigated the patterns of dietary changes among adolescents and conducted an observational experiment on the impact of dietary changes on physical fitness. The results divided participants into three groups: those reducing high-calorie food intake, those increasing fiber intake, and those reducing high-fat and high-salt food intake. The findings showed that reducing high-calorie food intake had the most significant effect on students' physical health, resulting in a 7.5% improvement. Increasing fiber intake followed with a 5.68% improvement, while reducing high-fat and high-salt intake led to a 5.48% improvement in physical health. This study suggests that creating a supportive environment-within society, schools, and families-can encourage healthy eating habits among adolescents.

Infusing behavior science into large language models for activity coaching

Large language models (LLMs) have shown promise for task-oriented dialogue across a range of domains. The use of LLMs in health and fitness coaching is under-explored. Behavior science frameworks such as COM-B, which conceptualizes behavior change in terms of capability (C), Opportunity (O) and Motivation (M), can be used to architect coaching interventions in a way that promotes sustained change. Here we aim to incorporate behavior science principles into an LLM using two knowledge infusion techniques: coach message priming (where exemplar coach responses are provided as context to the LLM), and dialogue re-ranking (where the COM-B category of the LLM output is matched to the inferred user need). Simulated conversations were conducted between the primed or unprimed LLM and a member of the research team, and then evaluated by 8 human raters. Ratings for the primed conversations were significantly higher in terms of empathy and actionability. The same raters also compared a single response generated by the unprimed, primed and re-ranked models, finding a significant uplift in actionability and empathy from the re-ranking technique. This is a proof of concept of how behavior science frameworks can be infused into automated conversational agents for a more principled coaching experience.

Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health

Objectives

Recently, wearable device technology has gained more popularity in supporting a healthy lifestyle. Hence, researchers have begun to put significant efforts into studying the direct and indirect benefits of wearable devices for health and wellbeing. This paper summarizes recent studies on the use of consumer wearable devices to improve physical activity, mental health, and health consciousness.

Methods

A thorough literature search was performed from several reputable databases, such as PubMed, Scopus, ScienceDirect, arXiv, and bioRxiv mainly using “wearable device research” as a keyword, no earlier than 2018. As a result, 25 of the most recent and relevant papers included in this review cover several topics, such as previous literature reviews (9 papers), wearable device accuracy (3 papers), self-reported data collection tools (3 papers), and wearable device intervention (10 papers).

Results

All the chosen studies are discussed based on the wearable device used, complementary data, study design, and data processing method. All these previous studies indicate that wearable devices are used either to validate their benefits for general wellbeing or for more serious medical contexts, such as cardiovascular disorders and post-stroke treatment.

Conclusions

Despite their huge potential for adoption in clinical settings, wearable device accuracy and validity remain the key challenge to be met. Some lessons learned and future projections, such as combining traditional study design with statistical and machine learning methods, are highlighted in this paper to provide a useful overview for other researchers carrying out similar research.

Towards a low-cost mobile subcutaneous vein detection solution using near-infrared spectroscopy

Excessive venipunctures are both time- and resource-consuming events, which cause anxiety, pain, and distress in patients, or can lead to severe harmful injuries. We propose a low-cost mobile health solution for subcutaneous vein detection using near-infrared spectroscopy, along with an assessment of the current state of the art in this field. The first objective of this study was to get a deeper overview of the research topic, through the initial team discussions and a detailed literature review (using both academic and grey literature). The second objective, that is, identifying the commercial systems employing near-infrared spectroscopy, was conducted using the PubMed database. The goal of the third objective was to identify and evaluate (using the IEEE Xplore database) the research efforts in the field of low-cost near-infrared imaging in general, as a basis for the conceptual model of the upcoming prototype. Although the reviewed commercial devices have demonstrated usefulness and value for peripheral veins visualization, other evaluated clinical outcomes are less conclusive. Previous studies regarding low-cost near-infrared systems demonstrated the general feasibility of developing cost-effective vein detection systems; however, their limitations are restricting their applicability to clinical practice. Finally, based on the current findings, we outline the future research direction.

Making sense of personal health information: challenges for information visualization

This article presents a systematic review of the literature on information visualization for making sense of personal health information. Based on this review, five application themes were identified: treatment planning, examination of patients' medical records, representation of pedigrees and family history, communication and shared decision making, and life management and health monitoring. While there are recognized design challenges associated with each of these themes, such as how best to represent data visually and integrate qualitative and quantitative information, other challenges and opportunities have received little attention to date. In this article, we highlight, in particular, the opportunities for supporting people in better understanding their own illnesses and making sense of their health conditions in order to manage them more effectively.

Collaborative learning about e-health for mental health professionals and service users in a structured anonymous online short course: pilot study

BACKGROUND

Professionals are interested in using e-health but implementation of new methods is slow. Barriers to implementation include the need for training and limited awareness or experience. Research may not always convince mental health professionals (MHPs). Adding the 'voice' of mental health service users (MHSUs) in collaborative learning may help. Involving MHSUs in face-face education can be difficult. We had previously been unable to engage MHPs in online discussion with MHSUs. Here we assessed the feasibility of short online courses involving MHSUs and MHPs.

METHODS

We ran three e-health courses, comprising live interactive webcast, week's access to a discussion forum, and final live interactive webcast. We recruited MHPs via posters, newsletters, and telephone from a local NHS trust, and online via mailing lists and personal contacts from NHS trusts and higher education. We recruited MHSUs via a previous project and an independent user involvement service. Participants were presented with research evidence about e-health and asked to discuss topics using professional and lived experience. Feasibility was assessed through recruitment and attrition, participation, and researcher workloads. Outcomes of self-esteem and general self-efficacy (MHSUs), and Internet self-efficacy and confidence (MHPs) were piloted.

RESULTS

Online recruiting was effective. We lost 15/41 from registration to follow-up but only 5/31 that participated in the course failed to complete follow-up. Nineteen MHPs and 12 MHSUs took part and engaged with each other in online discussion. Feedback was positive; three-quarters of MHPs indicated future plans to use the Internet for practice, and 80% of MHSUs felt the course should be continued. Running three courses for 31 participants took between 200 to 250 hours. Before and after outcome measures were completed by 26/31 that participated. MHP Internet self-efficacy and general Internet confidence, MHSU self-esteem and general self-efficacy, all seemed reliable and seemed to show some increase.

CONCLUSIONS

Collaborative learning between MHSUs and MHPs in a structured online anonymous environment over a one-week course is feasible, may be more practical and less costly than face-face methods, and is worthy of further study.

Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC

Objectives

This study is part of the ongoing development of treatment methods for metabolic syndrome (MS) project, which involves monitoring daily physical activity. In this study, we have focused on detecting walking activity from subjects which includes many other physical activities such as standing, sitting, lying, walking, running, and falling. Specially, we implemented an integrated solution for various physical activities monitoring using a mobile phone and PC.

Methods

We put the iPod touch has built in a tri-axial accelerometer on the waist of the subjects, and measured change in acceleration signal according to change in ambulatory movement and physical activities. First, we developed of programs that are aware of step counts, velocity of walking, energy consumptions, and metabolic equivalents based on iPod. Second, we have developed the activity recognition program based on PC. iPod synchronization with PC to transmit measured data using iPhoneBrowser program. Using the implemented system, we analyzed change in acceleration signal according to the change of six activity patterns.

Results

We compared results of the step counting algorithm with different positions. The mean accuracy across these tests was 99.6 ± 0.61%, 99.1 ± 0.87% (right waist location, right pants pocket). Moreover, six activities recognition was performed using Fuzzy c means classification algorithm recognized over 98% accuracy. In addition we developed of programs that synchronization of data between PC and iPod for long-term physical activity monitoring.

Conclusions

This study will provide evidence on using mobile phone and PC for monitoring various activities in everyday life. The next step in our system will be addition of a standard value of various physical activities in everyday life such as household duties and a health guideline how to select and plan exercise considering one's physical characteristics and condition.