A Novel AI Approach for Assessing Stress Levels in Patients with Type 2 Diabetes Mellitus Based on the Acquisition of Physiological Parameters Acquired during Daily Life.

Stress is the inherent sensation of being unable to handle demands and occurrences. If not properly managed, stress can develop into a chronic condition, leading to the onset of additional chronic health issues, such as cardiovascular illnesses and diabetes. Various stress meters have been suggested in the past, along with diverse approaches for its estimation. However, in the case of more serious health issues, such as hypertension and diabetes, the results can be significantly improved. This study presents the design and implementation of a distributed wearable-sensor computing platform with multiple channels. The platform aims to estimate the stress levels in diabetes patients by utilizing a fuzzy logic algorithm that is based on the assessment of several physiological indicators. Additionally, a mobile application was created to monitor the users' stress levels and integrate data on their blood pressure and blood glucose levels. To obtain better performance metrics, validation experiments were carried out using a medical database containing data from 128 patients with chronic diabetes, and the initial results are presented in this study.

The effect of multiple nursing interventions on physical activity and health promotion in the elderly: A randomized controlled trial.

Health promotion and physical activity practices for the elderly are important but still not sufficient. This study aimed to determine if the effects of education through home visit, mobile application (Google Fit), group walking, and phone reminder interventions on health promotion and physical activity in the elderly. The study has a randomized controlled design with pretest-posttest interventions and a control group. The study sample consisted of 66 elderly individuals, 33 of whom were assigned to the intervention group and 33 to the control group by randomization. Multiple nursing interventions, including education through home visit, mobile application (Google Fit) use, group walking, and phone reminder messages, were implemented by the researcher in line with Pender's Health Promotion Model. The first month score of the intervention group participants on the healthy lifestyle habits subscale was higher than that of the control group participants (all p-values < 0.05). The effect size was 0.577 (high effect size) and the confidence interval was 0.085-1.07. It can be recommended that interventions with reminders and repetitions regarding healthy lifestyle behaviors to health promotion in the elderly be planned.

Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process.

INTRODUCTION: Increasing numbers of ambulance calls, vacant positions and growing workloads in Emergency Medicine (EM) are increasing the pressure to find adequate solutions. With telemedicine providing health-care services by bridging large distances, connecting remote providers and even patients while using modern communication technologies, such a technology seems beneficial. As the process of developing an optimal solution is challenging, a need to quantify involved processes could improve implementation. Existing models are based on qualitative studies although standardised questionnaires for factors such as Usability, Acceptability and Effectiveness exist. METHODS: A survey was provided to participants within a German county. It was based on telemedical surveys, the System Usabilty Scale (SUS) and earlier works describing Usability, Acceptability and Effectiveness. Meanwhile a telemedical system was introduced in the investigated county. A comparison between user-groups aswell as an exploratory factor analysis (EFA) was performed. RESULTS: Of n = 91 included participants n = 73 (80,2%) were qualified as emergency medical staff (including paramedics n = 36 (39,56%), EMTs n = 28 (30,77%), call handlers n = 9 (9,89%)) and n = 18 (19,8%) as emergency physicians. Most participants approved that telemedicine positively impacts EM and improved treatment options with an overall Usabilty Score of 68,68. EFA provided a 3-factor solution involving Usability, Acceptability and Effectiveness. DISCUSSION: With our results being comparable to earlier studies but telemedicine only having being sparsely introduced, a positive attitude could still be attested. While our model describes 51,28% of the underlying factors, more research is needed to identify further influences. We showed that Usability is correlated with Acceptability (strong effect), Usability and Effectiveness with a medium effect, likewise Acceptability and Effectiveness. Therefore available systems need to improve. Our approach can be a guide for decision makers and developers, that a focus during implementation must be on improving usability and on a valid data driven implementation process.

Using Smartphone Technology to Track Real-Time Changes in Anxiety/Depression Symptomatology Among Florida Cannabis Users.

Objective: Recent scientific attention has focused on the therapeutic effectiveness of cannabis use on a variety of physical and mental ailments. The present study uses smartphone technology to assess self-reported experiences of Florida cannabis users to understand how cannabis may impact anxiety and depression symptomatology. Method: Several hundred Releaf App™ users from the state of Florida provided anonymous, real-time reports of their symptoms of anxiety and/or depression immediately before and after cannabis use sessions. Linear mixed-effects modeling was used to analyze the data at the symptom and user level. Results: Results showed that for the majority of users, cannabis use was associated with a significant decrease in depression and anxiety symptomatology. While symptom type, doses per session, consumption method, and CBD levels were significant predictors of relief change, their effect sizes were small and should be interpreted with caution. At the user level, those who had positive relief outcomes in anxiety reported more doses and sessions, and those in the depression group reported more sessions. Conclusions: Our results generally support the therapeutic effectiveness of cannabis against depression/anxiety symptomatology. Future work should include standardized statistics and effect size estimates for a better understanding of each variable's practical contribution to this area of study.

Comparison of Dental Caries Risk Assessment Using CaRisk- A Simple Mobile Based Application and WHO deft, DMFT Scores: A Cross Sectional Study.

Statement of the Problem: It is essential to address caries risk at an early stage for the prevention of dental caries. Mobile application CaRisk is designed in a particular way to self-assess the dental caries risk by the individual's themselves. Purpose: The current study aimed to assess the dental caries risk among age groups 5-6 and 35-44 using self-assessment caries risk mobile application CaRisk and compare it with the deft and DMFT values. Materials and Method: This cross-sectional study was conducted in Chennai, India; to evaluate the risk of dental caries in children aged 5 to 6 and adults aged 35 to 44. The scores of the mobile application CaRisk and the decayed- extracted- filled teeth (deft)/ decayed-missing-filled-teeth (DMFT) caries risk assessment were evaluated. Descriptive statistics were performed. The risk category was determined by frequency. Chi-square analysis was done to determine whether the DMFT scores and the CaRisk mobile app were associated. The correlation was performed between the CaRisk mobile application and DMFT scores. Results: Association was found between the caries risk assessment score of the mobile application CaRisk and the DMFT and deft scores of the adults and children for both the age groups 5-6 and 35-44 years respectively and it indicates that it was found to be statistically significant. Pearson's correlation was performed to assess the strength of association and R-values obtained for the age group 5-6 and 35-44 years respectively, which was statistically significant (0.892 and 0.840). Conclusion: This CaRisk mobile application scores correlate with the deft and DMFT scores and it is an effective self-diagnosis tool for assessing dental caries risk assessment. Further, it is suggested that the mobile application CaRisk should be tested among a huge population.

Knowledge sharing in virtual communities of practice of family caregivers of people with Alzheimer's.

INTRODUCTION: Knowledge sharing can only happen in the context of a trusting and supportive environment, such as evolves in communities of practice and their virtual equivalent, virtual communities of practice. The main objective of this study was to understand knowledge sharing between participants in a virtual community of practice of caregivers of people with Alzheimer's. METHODS: The authors designed their own mobile application, and two virtual communities of practice were created independently and differentiated by how they were moderated: one by an expert caregiver and the other by three health professionals. 38 caregivers and four moderators were involved in the study, which ran between July 2017 and April 2018. A total of 1925 messages were exchanged within the two communities and used as data in the study. Message data was analysed using LINKS (Leveraging Internet Networks for knowledge sharing). RESULTS: Participants were more motivated to acquire knowledge related to caring for the person with Alzheimer's rather than caring for themselves. The purpose of the messages was to inform others about the sender and not to seek answers. It seems that the interaction was more to socialise and to feel heard, than to gain information. Face to face meetings appear to have accelerated community development. On nearly every parameter, behaviour was significantly different in the two communities, reflecting the importance of the character of the moderator. Caring for oneself was a much stronger theme in the community that included health professionals. Experiential knowledge sharing was particularly strong in the group led by a caregiver. DISCUSSION: Caregivers adapted the virtual community of practice to their own needs and mainly shared social knowledge. This focus on social support, which seems to be more valued by the caregivers than information about the disease, was not an expected pattern. Virtual communities of practice where peers count on each other, function more as a support group, whereas those moderated by health professionals function more as a place to go to acquire information. The level of interactivity points to such communities being important for knowledge sharing not mere knowledge transfer.

FireSync EMS: A Novel Mobile Application for Burn Surface Area Calculation.

The percent total body surface area burned is a critical determinant of the required level of care, initial management, and prognosis in burn patients. The current gold standard for estimating this measurement, the Lund-Browder chart, requires familiarity with its construction and may not be practical for use by first responders in the field. In this study, we present a novel burn surface area calculator mobile application developed for first responders and validate its accuracy. Infant, pediatric, and adult manikins were fabricated with eight simulated burns of varying sizes and distributions. 42 pre-clinical medical students and firefighters were tasked with estimating the total body surface area of each burn using both the FireSync-EMS app and Lund-Browder chart. Univariate analysis and mixed-effects linear regression modeling were performed to compare the accuracy of both methods in relation to user experience, manikin size, and burn size. FireSync-EMS significantly reduced overestimation bias (0.11%, SD 2.33 versus 0.91%, SD 4.12, p = 0.002), particularly for burns on child-size manikins (p < 0.001) and burns involving <10% (p = 0.005) and >20% (p = 0.030) total body surface area. Multivariable modeling revealed that the Lund-Browder chart was an independent determinant of the magnitude of estimation error, with a 1.19 times multiplicative effect relative to FireSyncEMS (p < 0.001). Participants overwhelmingly found FireSync-EMS easier, more intuitive, faster, and preferable (p < 0.001 for all). FireSync-EMS may be an easier, faster, and more accurate alternative to the Lund-Browder chart for estimation of the total body surface area burned.

Smartphone application for artificial intelligence-based evaluation of stool state during bowel preparation before colonoscopy.

OBJECTIVES: Colonoscopy (CS) is an important screening method for the early detection and removal of precancerous lesions. The stool state during bowel preparation (BP) should be properly evaluated to perform CS with sufficient quality. This study aimed to develop a smartphone application (app) with an artificial intelligence (AI) model for stool state evaluation during BP and to investigate whether the use of the app could maintain an adequate quality of CS. METHODS: First, stool images were collected in our hospital to develop the AI model and were categorized into grade 1 (solid or muddy stools), grade 2 (cloudy watery stools), and grade 3 (clear watery stools). The AI model for stool state evaluation (grades 1-3) was constructed and internally verified using the cross-validation method. Second, a prospective study was conducted on the quality of CS using the app in our hospital. The primary end-point was the proportion of patients who achieved Boston Bowel Preparation Scale (BBPS) ≥6 among those who successfully used the app. RESULTS: The AI model showed mean accuracy rates of 90.2%, 65.0%, and 89.3 for grades 1, 2, and 3, respectively. The prospective study enrolled 106 patients and revealed that 99.0% (95% confidence interval 95.3-99.9%) of patients achieved a BBPS ≥6. CONCLUSION: The proportion of patients with BBPS ≥6 during CS using the developed app exceeded the set expected value. This app could contribute to the performance of high-quality CS in clinical practice.

The effect of mobile application-based technology on post-stroke aphasia: a systematic review.

Background: Enhancing speech-language therapy remains the most effective strategy for improving post-stroke aphasia, However, conventional face-to-face interventions often lack the necessary therapeutic intensity. In recent years, mobile application-based speech-language therapy has emerged progressively, offering new opportunities for independent rehabilitation among aphasic patients. This review aims to evaluate the impact of mobile application-based interventions on post-stroke aphasic. Methods: By conducting a systematic search across five databases (PubMed, Web of Science, EMBASE, CINAHL, and Scopus), we identified and included studies that investigated the utilization of mobile application-based technologies (such as computers, iPads, etc.) for treating post-stroke aphasia. Results: This study included 15 research investigations, including 10 randomized controlled trials (RCTs), four self-controlled studies and one cross-over experimental design study. Among these, eight studies demonstrated the efficacy of mobile application-based therapy in enhancing overall language functionality for post-stroke aphasia patients, three studies highlighted its potential for improving communication skills, three studies observed its positive impact on spontaneous speech expression. Moreover, four studies indicated its effectiveness in enhancing naming abilities, two studies underscored the positive influence of mobile application-based interventions on the quality of life for individuals with aphasia. Six studies noted that speech improvement effects were maintained during the follow-up period. Conclusion: The results of this review demonstrate the potential of mobile application-based interventions for improving speech-language function in individuals with aphasia. However, further high-quality research is needed to establish their effects across different domains and to delve into the comparative advantages of various treatment approaches. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=405248.

Nerva, a mobile application of gut-directed hypnotherapy for irritable bowel syndrome: User characteristics, patterns of use, and predictors of persistence.

Background: Hypnotic intervention for irritable bowel syndrome (IBS), or gut-directed hypnotherapy (GDH), is an effective treatment for improving IBS symptoms with minimal burden and risk in delivery to patients. The Nerva app, developed by Mindset Health, shows promise for dissemination and implementation of evidence-based GDH intervention for IBS. Objectives: This study aimed to describe the demographic and clinical characteristics of Nerva app users, examine usage patterns, and explore potential factors associated with Nerva app usage. Methods: A retrospective analysis of data was conducted of 14,898 individuals who downloaded and used the Nerva app between January 2022 and September 2022. Descriptive statistics and Chi-square tests of independence were calculated to examine demographic/clinical characteristics, usage patterns, and their associations to program persistence. Simple linear regression models were used for correlations of GI symptoms severity scores to user persistence. Results: Users predominantly identified as female (77.2%; n = 11,503) and had a mean age of 38.59 years old (SD = 13.38). Thirty-one percent of users persisted with the program, and a small statistically significant association was found between Nerva app program persistence and age, χ2 (6, N = 6745) = 164.82, p < 0.001, V = .16. Conclusions: The present study found promising adherence rates for the Nerva app program within the first six weeks of use. Statistics in prevalence estimates of IBS agree with previous literature and significant associations were found between user/clinical characteristics and Nerva app program persistence.

Assessment of work-related stress utilizing the Find My Stress mobile application among university students and adult workers amidst the COVID-19 pandemic.

OBJECTIVES: This cross-sectional study aimed to evaluate work-related stress and the efficacy associated with the newly developed Find My Stress mobile application. The global impact of the COVID-19 pandemic has significantly influenced the quality of life, transcending geographical boundaries and inducing stress that has detrimentally affected health and work efficiency. METHODS: A total of 440 male and female participants, comprising university students and adult workers, were enrolled in the study. Participants completed an assessment in the application that consisted of three components: 1) perceived work stress, 2) environmental stress factors, and 3) application efficiency. RESULTS: University students exhibited higher perceived stress levels compared to adult workers (p = 0.031). The predominant physical factors contributing to musculoskeletal disorders in university students were identified as movement and posture factors, particularly related to vibration and organization. Conversely, environmental factors took precedence in adult workers, followed by posture and movement. The reliability of the perceived work stress questionnaire was evaluated by Cronbach's alpha coefficient and yielded a value of 0.96. The Find My Stress application demonstrated high efficiency. CONCLUSIONS: Elevated levels of work stress were observed in both university students and adult workers. Initial signs of musculoskeletal disorders in university students primarily manifested in the neck and upper back, arms, and hands, while adult workers predominantly reported complaints related to the arms and hands. The Find My Stress application emerges as a valuable tool for screening occupational stressors.

Cost-Outcome Descriptive Study for Mobile App (UPSCALER) in the Rehabilitation of Anterior Cruciate Ligament (ACL) Injuries After Reconstructive Surgery.

Anterior cruciate ligament (ACL) injuries are a significant concern in athletes, often leading to long-term complications and reduced quality of life. Despite advancements in surgical techniques, outcomes following ACL reconstruction remain suboptimal, largely due to poor adherence to postoperative rehabilitation. This study introduces a novel postoperative rehabilitation approach utilizing a smartphone application, UPSCALER, developed by the Universiti Putra Malaysia Sports Injury and Arthroscopic Surgery Center of Excellence. The application delivers a validated accelerated rehabilitation protocol through instructional videos tailored to each patient's recovery phase. Results from the study demonstrate promising outcomes, including improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) subscales post-rehabilitation, potentially attributed to increased adherence facilitated by the application's accessibility. Furthermore, the study explores the cost-effectiveness of this approach compared to conventional methods. In conclusion, smartphone application-guided rehabilitation shows promise in improving ACL reconstruction outcomes, warranting further research to validate its effectiveness and long-term impact on patient recovery and healthcare costs.

Mobile-UI-Repair: a deep learning based UI smell detection technique for mobile user interface.

The graphical user interface (GUI) in mobile applications plays a crucial role in connecting users with mobile applications. GUIs often receive many UI design smells, bugs, or feature enhancement requests. The design smells include text overlap, component occlusion, blur screens, null values, and missing images. It also provides for the behavior of mobile applications during their usage. Manual testing of mobile applications (app as short in the rest of the document) is essential to ensuring app quality, especially for identifying usability and accessibility that may be missed during automated testing. However, it is time-consuming and inefficient due to the need for testers to perform actions repeatedly and the possibility of missing some functionalities. Although several approaches have been proposed, they require significant performance improvement. In addition, the key challenges of these approaches are incorporating the design guidelines and rules necessary to follow during app development and combine the syntactical and semantic information available on the development forums. In this study, we proposed a UI bug identification and localization approach called Mobile-UI-Repair (M-UI-R). M-UI-R is capable of recognizing graphical user interfaces (GUIs) display issues and accurately identifying the specific location of the bug within the GUI. M-UI-R is trained and tested on the history data and also validated on real-time data. The evaluation shows that the average precision is 87.7% and the average recall is 86.5% achieved in the detection of UI display issues. M-UI-R also achieved an average precision of 71.5% and an average recall of 70.7% in the localization of UI design smell. Moreover, a survey involving eight developers demonstrates that the proposed approach provides valuable support for enhancing the user interface of mobile applications. This aids developers in their efforts to fix bugs.

Mobile App for Enhanced Anterior Cruciate Ligament (ACL) Assessment in Conscious Subjects: "Pivot-Shift Meter".

Anterior cruciate ligament (ACL) instability poses a considerable challenge in traumatology and orthopedic medicine, demanding precise diagnostics for optimal treatment. The pivot-shift test, a pivotal assessment tool, relies on subjective interpretation, emphasizing the need for supplementary imaging. This study addresses this limitation by introducing a machine learning classification algorithm integrated into a mobile application, leveraging smartphones' built-in inertial sensors for dynamic rotational stability assessment during knee examinations. Orthopedic specialists conducted knee evaluations on a cohort of 52 subjects, yielding valuable insights. Quantitative analyses, employing the Intraclass Correlation Coefficient (ICC), demonstrated robust agreement in both intraobserver and interobserver assessments. Specifically, ICC values of 0.94 reflected strong concordance in the timing between maneuvers, while signal amplitude exhibited consistency, with the ICC ranging from 0.71 to 0.66. The introduced machine learning algorithms proved effective, accurately classifying 90% of cases exhibiting joint hypermobility. These quantifiable results underscore the algorithm's reliability in assessing knee stability. This study emphasizes the practicality and effectiveness of implementing machine learning algorithms within a mobile application, showcasing its potential as a valuable tool for categorizing signals captured by smartphone inertial sensors during the pivot-shift test.

SnowMotion: A Wearable Sensor-Based Mobile Platform for Alpine Skiing Technique Assistance.

Skiing technique and performance improvements are crucial for athletes and enthusiasts alike. This study presents SnowMotion, a digital human motion training assistance platform that addresses the key challenges of reliability, real-time analysis, usability, and cost in current motion monitoring techniques for skiing. SnowMotion utilizes wearable sensors fixed at five key positions on the skier's body to achieve high-precision kinematic data monitoring. The monitored data are processed and analyzed in real time through the SnowMotion app, generating a panoramic digital human image and reproducing the skiing motion. Validation tests demonstrated high motion capture accuracy (cc > 0.95) and reliability compared to the Vicon system, with a mean error of 5.033 and a root-mean-square error of less than 12.50 for typical skiing movements. SnowMotion provides new ideas for technical advancement and training innovation in alpine skiing, enabling coaches and athletes to analyze movement details, identify deficiencies, and develop targeted training plans. The system is expected to contribute to popularization, training, and competition in alpine skiing, injecting new vitality into this challenging sport.

The Feasibility and Efficacy of Remote App-Guided Home Exercises for Frozen Shoulder: A Pilot Study.

Home exercise programs are beneficial in managing frozen shoulder (FS), yet adherence remains challenging. This pilot study introduces the remote app, Defrozen, designed for home exercises and assesses its feasibility and clinical outcomes in FS patients undergoing intra-articular and sub-acromial corticosteroid treatment. Over a four-week period, patients used the Defrozen-app, engaging in guided exercises. The feasibility of the intervention was assessed through several measurement scales, including adherence, the Technology Acceptance Model 2 (TAM2), the System Usability Scale (SUS), and User Satisfaction and Engagement (USE). Clinical outcomes included pain scale, Oxford Shoulder Score (OSS), Quick Disability of the Arm, Shoulder, and Hand (QuickDASH) Score, and passive range of motion. The TAM2 results indicated high perceived usefulness (4.5/5), ease of use (4.8/5), and intention to use (4.4/5); the SUS score was high at 81.7/100, complemented by USE scores reflecting ease of learning (4.9/5) and satisfaction (4.3/5). Clinical outcomes showed significant pain reduction, improved shoulder function, reduced shoulder-related disability, and increased shoulder range of motion. These findings suggest the Defrozen-app as a promising solution for FS, significantly improving adherence and showing potential to enhance clinical outcomes. However, these clinical outcome results are preliminary and necessitate further validation through a large-scale randomized controlled trial to definitively confirm efficacy and assess long-term benefits.

Prevention, diagnosis and pharmacological treatment of infections in pregnancy: The mobile app GAIA! for healthcare providers and patients.

OBJECTIVE: To develop and assess the GAIA! app, designed to assist pregnant women and healthcare professionals in managing infectious diseases during pregnancy, and to bridge the information gap between health professionals and expectant mothers. STUDY DESIGN: This collaborative initiative in Italy involved partnerships with the University of Florence, Careggi University Hospital, and other institutions. The app, built on the Ionic framework, is available on both Apple and Google App Stores. It offers two distinct modes: "healthcare providers" and "patients." Content for the app was derived from extensive literature reviews and clinical guidelines. RESULTS: Since its August 2022 launch, the GAIA! app has garnered over 2,500 downloads, indicating its effectiveness and acceptance within the community. The app differentiates itself from others, such as the Sanford Guide, by focusing specifically on the needs of pregnant women. It ensures cross-platform compatibility, a user-friendly interface, and offline functionality. CONCLUSIONS: The GAIA! app has successfully addressed a niche in infectious disease management for pregnant women, gaining significant traction within the community. While it has seen substantial success, challenges like continuous updates and potential language expansion remain. Future endeavors will address these challenges and further evaluate the app's impact on maternal and child health.

The 1-min sit-to-stand test induces a significant and reliable level of neuromuscular fatigability: insights from a mobile app analysis.

PURPOSE: The performance metric associated with the execution of the 1-min sit-to-stand (1STS) typically relies on the number repetitions completed in 1 min. This parameter presents certain limitations (e.g., ceiling effect, motivational factors) which can impede its interpretation. Introducing additional parameters, such as neuromuscular fatigability level, could enhance the informative value of the 1STS and facilitate its interpretation. This study aimed to assess (i) whether the 1STS induces fatigability and (ii) the reliability of the fatigability level. METHODS: Forty young, healthy, and active participants underwent the 1STS twice during the same session. Isolated sit-to-stand maneuvers were performed before, immediately, and 1 min after completing the 1STS. A mobile app was utilized to obtain time (STST), velocity (STSV), and muscle power (STSP) from these sit-to-stand maneuvers. The pre-post change in these parameters served as the fatigability marker. Reliability was assessed using the intra-class correlation coefficient (ICC) and the coefficient of variation (CV). RESULTS: The mean number of repetitions during the 1STS was 63 ± 9. Significant decline in performance was observed for STST (13 ± 8%), STSV (-11.2 ± 6%), and STSP (-5.2 ± 3%), with more than 74% of participants exhibiting a decline beyond the minimal detectable change. Excellent between-session reliability (ICC ≥ 0.9; CV ≤ 5.3) was observed for the mobile app variables. CONCLUSION: The 1STS induces significant levels of fatigability. The fatigability indicators derived from the mobile app demonstrated remarkable reliability. Utilizing this user-friendly interface for computing fatigability may empower professionals to acquire insightful complementary indicators from the 1STS.

Evaluation of Pain Through a Novel Mobile Application: The Visual, Auditory, and Tactile Scale (VATAS).

Developing a validated, standardized, and easily accessible pain assessment tool is the first step toward improving pain management. Since pain measurement is often used as a primary or secondary endpoint in daily clinical practice and clinical trials, accurate and precise pain measurement is of great importance. Therefore, there is a need for a valid, reliable, safe, and low-cost method to measure and assess pain levels more objectively. Traditional measurement tools, still considered the gold standard in clinical pain research, have significant disadvantages, including low sensitivity and higher rates of false responses. Perhaps most importantly, the assumption that general pain is a one-dimensional experience that can be measured with a single-item scale is limiting. Recently, new technologies utilizing smart devices have emerged to improve existing traditional pain outcome measures. The Visual, Auditory, and Tactile Analog Scale (VATAS) was designed to address tactile, auditory, and visual senses. By including multiple senses, it is thought that errors arising from the objectification of pain solely through a single-dimensional scale, such as Visual Analog Scale (VAS), could be eliminated, providing a more standardized and repeatable pain assessment. VATAS has the potential to complement the deficiencies of standard pain measurement methods by appealing to multiple senses. It can provide a more standardized, patient-compliant, and repeatable pain assessment. Furthermore, it can be used for evaluating and recording pain in visually impaired patients and has the potential for data tracking, allowing patients' pain to be monitored even when they are at home.

Jalinan Kasih android mobile phone application improves knowledge, attitude, and practice regarding early marriage among high school students: Evidence from quasi-experimental study.

Child marriage has a significant health impact on young mothers and their offspring. This study aims to compare the effectiveness of the Jalinan Kasih Android-based application, the Marriage Age Maturity (PUP) module, and the lecture method in improving knowledge, attitude, and practice regarding early marriage among high school students. A quasi-experiment with control groups was conducted, involving 72 students selected from three high schools in Bengkulu City, Indonesia who met the inclusion criteria. The participants were divided into three groups: 24 individuals in the application intervention group, 24 individuals in the module intervention group, and 24 individuals in the control group. The Jalinan Kasih application group showed an increase in average scores before and after the intervention, in terms of knowledge (6.46), attitude (6.79) and practice (1.75), with a p-value of 0.000, 0.000 and 0.17, respectively, The Jalinan Kasih application had a greater influence on knowledge, attitude and practice compared to the PUP module and the lecture method with a p-value of 0.000. In other words, the Jalinan Kasih mobile application was effective in improving the knowledge, attitude, and practice of high school students regarding early marriage through the use of its contents and consultation feature. It is recommended that the Jalinan Kasih application be used as an educational medium to prevent early marriage and improves family planning.

Le mariage des enfants a un impact significatif sur la santé des jeunes mères et de leur progéniture. Cette étude vise à comparer l'efficacité de l'application basée sur Android Jalinan Kasih, du module Marriage Age Maturity (PUP) et de la méthode magistral pour améliorer les connaissances, l'attitude et la pratique concernant le mariage précoce chez les lycéens. Une quasi-expérience avec des groupes témoins a été menée, impliquant 72 étudiants sélectionnés dans trois lycées de la ville de Bengkulu, en Indonésie, qui répondaient aux critères d'inclusion. Les participants ont été divisés en trois groupes : 24 personnes dans le groupe d'intervention d'application, 24 personnes dans le groupe d'intervention du module et 24 personnes dans le groupe témoin. Le groupe d'application Jalinan Kasih a montré une augmentation des scores moyens avant et après l'intervention, en termes de connaissances (6,46), d'attitude (6,79) et de pratique (1,75), avec des valeurs p de 0,000, 0,000 et 0,17, respectivement. L'application Jalinan Kasih a eu une plus grande influence sur les connaissances, l'attitude et la pratique par rapport au module PUP et à la méthode magistral avec une valeur p de 0,000. En d'autres termes, l'application mobile Jalinan Kasih a été efficace pour améliorer les connaissances, l'attitude et la pratique des lycéens concernant le mariage précoce grâce à l'utilisation de son contenu et de sa fonction de consultation. Il est recommandé d'utiliser l'application Jalinan Kasih comme support pédagogique pour prévenir les mariages précoces et améliorer la planification familiale.