Pathways to usage intention of mobile health apps among hypertensive patients: A fuzzy-set qualitative comparative analysis.

The efficacy of mHealth apps in managing hypertension has been proven; however, low usage intention remains a significant challenge, warranting an in-depth exploration of the influencing factors. This study aimed to examine the factors influencing hypertensive new users' intention to use mobile health applications through a cross-sectional survey. Fuzzy-set qualitative comparative analysis (fsQCA) was employed to investigate the combinations of various determinants, including technology acceptance, adoption factors, compliance behavior initiation factors, and time motivation factors for decision making.

Influencing Factors and Implementation Pathways of Adherence Behavior in Intelligent Personalized Exercise Prescription: Qualitative Study.

Background: Personalized intelligent exercise prescriptions have demonstrated significant benefits in increasing physical activity and improving individual health. However, the health benefits of these prescriptions depend on long-term adherence. Therefore, it is essential to analyze the factors influencing adherence to personalized intelligent exercise prescriptions and explore the intrinsic relationship between individual behavioral motivation and adherence.

Influencing factors of delay in seeking medical attention of patients with obstructive sleep apnea based on the Model of Pathways to Treatment in China: a qualitative analysis.

Background: There is the highest estimated number of patients with obstructive sleep apnea (OSA) in China. Early treatment could lead to fewer complications associated with OSA. This study aimed to analyze the factors influencing help-seeking from the first symptom discovery to treatment in OSA.

Development of a Health Behavioral Digital Intervention for Patients With Hypertension Based on an Intelligent Health Promotion System and WeChat: Randomized Controlled Trial.

Background: The effectiveness of timely medication, physical activity (PA), a healthy diet, and blood pressure (BP) monitoring for promoting health outcomes and behavioral changes among patients with hypertension is supported by a substantial amount of literature, with "adherence" playing a pivotal role. Nevertheless, there is a lack of consistent evidence regarding whether digital interventions can improve adherence to healthy behaviors among individuals with hypertension.

Objective: The aim was to develop a health behavioral digital intervention for hypertensive patients (HBDIHP) based on an intelligent health promotion system and WeChat following the behavior change wheel (BCW) theory and digital micro-intervention care (DMIC) model and assess its efficacy in controlling BP and improving healthy behavior adherence.

Ankle reflex and neurological symptom score: a primary level screening method for diabetic peripheral neuropathy.

Herein, we aimed to develop an easily available and efficient screening method for diabetic peripheral neuropathy (DPN) suitable for primary care settings, emphasizing simplicity, speed, and accuracy. Nerve conduction studies were conducted on 214 patients with diabetes, encompassing the outcomes of five distinct assessments: diabetic neuropathy symptom (DNS), vibration perception threshold (VPT), and nerve screening. The diagnostic accuracy of the VPT and nerve screening was evaluated by comparing them with that of the nerve conduction study.

A Service-Learning Project Based on a Community-Oriented Intelligent Health Promotion System for Postgraduate Nursing Students: Mixed Methods Study.

Background: Service learning (SL) is a pedagogical approach that combines community service with cognitive learning for professionals. Its efficacy in promoting community health has gained broad recognition in nursing education. The application of postgraduate nursing SL programs in community-based intelligent health remains underexplored.

Evaluating a WeChat-Based Health Behavioral Digital Intervention for Patients With Hypertension: Protocol for a Randomized Controlled Trial.

Background: Hypertension is the most prevalent chronic condition and a significant risk factor for cardiovascular and kidney diseases. The efficacy of health behavioral interventions in blood pressure (BP) control has been demonstrated by a large and expanding body of literature, with "adherence" playing a crucial role. WeChat is the most common social communication mobile app in China, and it has been shown to be an acceptable delivery platform for delivering health interventions.

Machine learning models for diabetic neuropathy diagnosis using microcirculatory parameters in type 2 diabetes patients.

Background: Diabetic peripheral neuropathy (DPN) is a primary cause of diabetic foot, early detection of DPN is essential. This study aimed to construct a machine learning model for DPN diagnosis based on microcirculatory parameters, and identify the most predictive parameters for DPN.

Methods: Our study involved 261 subjects, including 102 diabetics with neuropathy (DMN), 73 diabetics without neuropathy (DM), and 86 healthy controls (HC).

Modeling of the Rating of Perceived Exertion Based on Heart Rate Using Machine Learning Methods.

Rating of perceived exertion (RPE) can serve as a more convenient and economical alternative to heart rate (HR) for exercise intensity control. This study aims to explore the influence of factors, such as indicators of demographic, anthropometric, body composition, cardiovascular function and basic exercise ability on the relationship between HR and RPE, and to develop the model predicting RPE from HR. 48 healthy participants were recruited to perform an incrementally 6-stage pedaling test.

An XGBoost-based model for assessment of aortic stiffness from wrist photoplethysmogram.

Background And Objective: Carotid-femoral pulse wave velocity (cf-PWV) is the gold standard for non-invasive assessment of aortic stiffness. Photoplethysmography used in wearable devices provides an indirect measurement method for cf-PWV. This study aimed to construct a cf-PWV prediction method based on the XGBoost algorithm and wrist photoplethysmogram (wPPG) for the early screening of arteriosclerosis in primary healthcare.

A Randomized Controlled Trial Evaluating the Effect of Tai Chi on the Drug Craving in Women.

This study was conducted in the purpose of investigating the effect of Tai Chi on drug craving for women with drug disorders. One hundred and twelve women were recruited from a drug rehabilitation center in China, and 47 and 48 were finally analyzed in the control group and exercise group, respectively. The exercise group underwent a 3-month Tai Chi training, whereas the control group experienced no exercise intervention during the same time period.

Exercise Intervention Based on Behavioral Change Theory: Influence on Body Morphology and Body Composition.

Context: Increased sedentary time and insufficient physical activity have become independent risk factors for chronic diseases. An exercise intervention can focus on increasing an individual's amount of exercise to change his or her body shape and body composition. No studies have occurred to find out if any relationships exist between the amount of exercise and body shape and body composition.

Design and evaluation of an exergame system to assist knee disorders patients' rehabilitation based on gesture interaction.

Unlabelled: We designed a knee rehabilitation exercise game (Exergame) for home-based rehabilitation of patients with knee disorders. The system includes three functional components: knee exercise plan formulation, exergame, and exercise feedback. The 3D Human Pose Estimation based on images is used as the gesture interaction to capture the patient's primary joint motion data.

[Design and Verification of Lung Diffusion Function Detection System].

A lung diffusion function detection system is designed. Firstly, the controllable collection of air, test gas source and calibration gas source was based on single-breath method measurement principle. Secondly, pulmonary diffusing capacity for carbon monoxide () was calculated by gas concentration measured by the non-dispersive infrared sensor to measure, the gas flow measured by the differential pressure sensor, and the temperature, humidity and atmospheric pressure sensors to test and evaluate the quantitative detection and evaluation of lung diffusion function.

[Simulation Study on the Influence of Sampling Delay on the Accuracy of Energy Metabolism Measurement].

Indirect energy metabolism measurement is the gold standard for providing nutritional support for critical illness. The accuracy of the measurement data directly affects the outcome of the disease. In order to study the influence of sampling delay on the accuracy of energy metabolism measurement under mechanical ventilation, the Matlab/Simulink platform and respiratory electrical model were used for simulation and quantitative analysis.

Nutritional Status and Body Composition in Wilson Disease: A Cross-Sectional Study From China.

Abnormal nutritional status is frequently seen in patients with chronic diseases. To date, no study has investigated the detailed characteristics of abnormal nutritional status among Wilson's disease (WD) patients in the Chinese cohort. This study aimed to describe the nutritional status of WD patients, with a particular focus on the differences between patients with different phenotypes.

Effect of Eight-Month Exercise Intervention on Bone Outcomes of Young Opioid-Dependent Women.

Objective: To evaluate the bone response to an 8 month aerobic gymnastics training program in young opioid-addicted women.

Design: Randomized controlled trial (parallel design).

Setting: Women's Specific Drug Rehabilitation Center in China.

Metabolic low-frequency oscillation and abbreviated protocol for estimating REE by indirect calorimetry in healthy adults.

The aim of this study is to propose a new wave protocol to identify low-frequency oscillations for evaluating resting energy expenditure (REE) and compare its performance with the 5-min interval abbreviated protocol and standard protocol. Consecutive 20-min indirect calorimetry (IC) was used to collect metabolic data from 23 women and 37 men (between 23 and 43 yr old). Sliding window filter algorithms were used to eliminate noise.

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention that contributes to the early prevention and management of hypertension. The implementation of such intervention requires an effective and easy-to-implement hypertension risk prediction model.

Intelligent Personalized Exercise Prescription Based on an eHealth Promotion System to Improve Health Outcomes of Middle-Aged and Older Adult Community Dwellers: Pretest-Posttest Study.

Background: A scientific, personalized, and quantitative exercise prescription that has the potential to be an important therapeutic agent for all ages in the prevention of chronic disease is highly recommended. However, it is often poorly implemented, as clinicians lack the necessary knowledge and skills while participants have low adherence due to design defects (eg, prescriptions fail to take individual willingness, the appeal of exercise, and complex physical conditions into account). Intelligent personalized prescription is thus worth exploring.

Association of dietary pattern and physical activity with lipid-related indices among Chinese population: a cross-sectional study.

Background And Objectives: To explore the relationship between dietary patterns, physical activity and lipid-related indices in Chinese Population.

Methods And Study Design: This study included 21,472 (72.3% men) participants aged 16 to 78 years.

Dietary diversity and physical activity associations with lipid indices among Beijingese: A cross-sectional study.

Background And Objectives: To examine the association of dietary diversity and physical activity with lipidrelated indices in a Beijing population.

Methods And Study Design: This cross-sectional study included 21,472 participants (72.3% men) aged 16 to 78 years.

A cross-section study of main determinants of arterial stiffness in Hefei area, China.

Background: Arterial stiffness has emerged as an independent risk factor for adverse cardiovascular disease events and is the consequence of multiple risk factors. The aim of the present study is to explore the main determinants of arterial stiffness in a Chinese population and to study how the arterial stiffness levels affected by different number of risk factors.

Methods: This study included 358 subjects in Hefei area of China.

Increased foot-stretcher height improves rowing performance: evidence from biomechanical perspectives on water.

The aim of this study was to investigate whether changes on foot-stretcher height were associated with characteristics of better rowing performance. Ten male rowers performed a 200 m rowing trial at their racing rate at each of three foot-stretcher heights. A single scull was equipped with an accelerometer to collect boat acceleration, an impeller with embedded magnets to collect boat speed, specially designed gate sensors to collect gate force and angle, and a compact string potentiometer to collect leg drive length.

Indirect calorimetry using a ventilated hood may be easier than using a facemask to achieve steady state when measuring resting energy expenditure.

Previous studies have demonstrated differences in subjective comfort between different gas collecting methods during resting energy expenditure (REE) measurement. We hypothesized that gas collecting methods may have an influence on the time to achieve steady state and the optimum abbreviated period to estimate REE. Gas exchange variables were obtained using IIM-IC-100 (ventilated hood) and VO2000 (facemask) alternately among 32 healthy adults.