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1.
Stud Health Technol Inform ; 315: 145-149, 2024 Jul 24.
Article in English | MEDLINE | ID: mdl-39049242

ABSTRACT

High-quality cardiopulmonary resuscitation (CPR) is important for successful revival. This test aimed to accurately and effectively assess parameters in CPR operations, particularly focusing on the non-quantified arm posture, to assist instructors in guiding students to enhance the quality of their performance. We used motion capture system (Mars series, Nokov, China) to collect compression data from four trained students about five rounds of CPR, recording dynamic data of each marker in three-dimensional space following time. Using the processed data, we calculated compression depth, frequency, and arm angles. Their performance still needed improvement, and there were variations in data within individuals. This suggests that when instructors conduct assessments, they should focus on not only the overall performance but also each compression. This experiment provides a new perspective for quantifying compression parameters, and future efforts should continue to optimize and incorporate new parameters for assessment.


Subject(s)
Cardiopulmonary Resuscitation , Cardiopulmonary Resuscitation/education , Humans , Motion Capture
2.
Stud Health Technol Inform ; 315: 316-321, 2024 Jul 24.
Article in English | MEDLINE | ID: mdl-39049275

ABSTRACT

This study investigates the acceptance of large language models (LLMs) among older adults using the Technology Acceptance Model (TAM). The research, conducted through a cross-sectional survey, explores the influence of perceived ease of use and perceived usefulness on intension to use among older adults. The results show that the subjective norm, image, job relevance, output quality, result demonstrability, perceived ease of use have a significant positive and direct impact on perceived usefulness (ß=0.138, 0.240, 0.213, 0.280, 0.181, 0.176, P<0.05). Perceived ease of use and perceived usefulness have a significant positive and direct impact on Intension to use (ß=0.335, 0.307, P<0.05). The study's practical implications highlight the need for tailored chatbots, offering valuable insights for developers and policymakers aiming to enhance the integration of innovative technologies among older populations.


Subject(s)
Attitude to Computers , Humans , Aged , Cross-Sectional Studies , Female , Male , Aged, 80 and over , Surveys and Questionnaires
3.
Stud Health Technol Inform ; 315: 386-391, 2024 Jul 24.
Article in English | MEDLINE | ID: mdl-39049288

ABSTRACT

The meta-analysis aimed to explore the effects of mobile phone applications on weight-related, behavior, and metabolic outcomes among adults with overweight and obesity. Six databases were searched for relevant randomized controlled trials (RCTs) published between January 1, 2010 and November 7, 2023 in English. Two independent authors conducted study selection, data extraction, quality assessment. The effect size of interventions was calculated using mean difference. A random-effects model was applied for data analysis. A total of 27 studies were included. The results indicated that mobile phone application intervention reduced weight (MD=-1.38 kg, P<0.001, 95% CI -1.97 to -0.80), BMI (MD=-0.44 kg/m2, P<0.001, 95% CI -0.57 to -0.30), WC (MD=-2.13 cm, P=0.004, 95% CI -3.57 to -0.69), fat mass, and DBP (MD=-2.04 mmHg, P=0.01, 95% CI -3.65 to 0.44) with statistical significance. Future studies could consider how to optimize app interventions through behavior change strategies to enhance their overall effectiveness.


Subject(s)
Mobile Applications , Obesity , Overweight , Humans , Obesity/therapy , Overweight/therapy , Adult , Randomized Controlled Trials as Topic
4.
Stud Health Technol Inform ; 315: 581-582, 2024 Jul 24.
Article in English | MEDLINE | ID: mdl-39049332

ABSTRACT

Prehypertension, an early stage in the development of hypertension, impacts a substantial segment of the adult population worldwide. Addressing this issue, our study introduces HabitBot, an AI-driven chatbot tailored to encourage physical activity (PA) habits among individuals with prehypertension. HabitBot combines natural language processing with multidisciplinary approaches, drawing from both theoretical frameworks and empirical studies. The chatbot development followed a systematic, five-phase process: comprehensive needs assessment, literature review on behavior change theories, analysis for selecting effective behavior change techniques (BCTs), prototype design through intervention mapping, and refining the intervention based on user feedback. The outcome includes a prototype that integrates the Health Action Process Approach and Habit Formation Theory, utilizing twelve identified BCTs effective in fostering PA habits. User feedback further refined the chatbot across multiple dimensions such as user interface, content accessibility, and privacy. HabitBot exemplifies an innovative integration of behavior change strategies with advanced language model technology, paving the way for digital health interventions in chronic disease prevention. Future studies should assess its long-term efficacy in habit formation and explore its applicability to various demographic groups.


Subject(s)
Exercise , Prehypertension , Humans , Artificial Intelligence , Natural Language Processing , Mobile Applications , Health Promotion/methods , Needs Assessment
5.
Sensors (Basel) ; 24(7)2024 Mar 27.
Article in English | MEDLINE | ID: mdl-38610365

ABSTRACT

High-quality cardiopulmonary resuscitation (CPR) and training are important for successful revival during out-of-hospital cardiac arrest (OHCA). However, existing training faces challenges in quantifying each aspect. This study aimed to explore the possibility of using a three-dimensional motion capture system to accurately and effectively assess CPR operations, particularly about the non-quantified arm postures, and analyze the relationship among them to guide students to improve their performance. We used a motion capture system (Mars series, Nokov, China) to collect compression data about five cycles, recording dynamic data of each marker point in three-dimensional space following time and calculating depth and arm angles. Most unstably deviated to some extent from the standard, especially for the untrained students. Five data sets for each parameter per individual all revealed statistically significant differences (p < 0.05). The correlation between Angle 1' and Angle 2' for trained (rs = 0.203, p < 0.05) and untrained students (rs = -0.581, p < 0.01) showed a difference. Their performance still needed improvement. When conducting assessments, we should focus on not only the overall performance but also each compression. This study provides a new perspective for quantifying compression parameters, and future efforts should continue to incorporate new parameters and analyze the relationship among them.


Subject(s)
Cardiopulmonary Resuscitation , Data Compression , Humans , Feasibility Studies , Motion Capture , China
6.
Int J Behav Nutr Phys Act ; 20(1): 109, 2023 09 12.
Article in English | MEDLINE | ID: mdl-37700303

ABSTRACT

BACKGROUND: Interventions aimed at promoting physical activity (PA) behavior through habit formation pathways are gaining popularity, as they differ from conventional interventions that rely on intention pathways. Past research has established a positive correlation between PA habits and behavior. However, the efficacy of current interventions designed to form PA habits and improve PA automaticity is not yet fully ascertained. Additionally, the intervention components that significantly impact the effectiveness of these interventions are yet to be determined. METHODS: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We conducted a search of three databases (PubMed, Embase, and Cochrane Library) from January 2000 to December 2022, with a focus on interventions for developing PA habits. Two independent authors conducted paper selection, quality assessment, data extraction, and coding of behavior change techniques (BCTs). The effect size of interventions was calculated using standardized mean difference. Subgroup analyses were carried out based on follow-up duration, delivery method, sample characteristics, and theory. Furthermore, we employed meta-regression to investigate the association between BCTs and PA habits. RESULTS: Ten eligible studies with relatively high quality were included in the final data set. Characteristics of studies varied in intervention sample and delivery way. The habit formation interventions significantly increased PA habit (SMD = 0.31, 95% CI 0.14-0.48, P < .001) compared to the control groups. Subgroup analysis demonstrated that the duration of follow-up ≤ 12 weeks have a higher effect size on PA habit than the duration > 12 weeks. Meta-regression revealed that problem solving has a significant positive association with effectiveness improvement (ß = 0.36, 95% CI 0.17-0.55), while social reward is linked with a reduction in effectiveness (ß = -0.40, 95% CI -0.74-0.06). CONCLUSIONS: Our findings reveal that habit formation interventions are effective in fostering PA habit. Future studies could leverage the insights form this study to optimize the intervention design and achieve better effectiveness.


Subject(s)
Exercise , Habits , Humans , Behavior Therapy , Databases, Factual , Intention
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