App Interaction Research Articles

Retraction Note: App interaction design in the pop music singing teaching system based on differential evolution algorithm

Retraction Note: App interaction design in the pop music singing teaching system based on differential evolution algorithm

A web experience exploring spatio–linguistic data: the case of place-making signs in Northern Sweden

ABSTRACT Previous research has highlighted the limitations encountered in representing the dynamism of language use and contacts. Here, linguistic landscapes from five towns in Northern Sweden are the point of departure for investigating novel perspectives through the geovisualization of multilingualism, with the ultimate aim of understanding how languages in our surroundings help construct public spaces. As an outcome, a web GIS application, based on 6865 thematically analyzed photographs, was developed as an interactive resource for visualizing and sharing the data and enabling new modes of analysis and new research questions. The article describes the data collection and curation processes, app development using GIS software and software-as-a-service, the eventual app design and interaction, and the update and maintenance plans, as well as discussing challenges and considerations related to temporalities, spatialities, and technicalities. The web GIS has potential applications in spatial analysis, research communication, and education.

Personalized AI-Driven Real-Time Models to Predict Stress-Induced Blood Pressure Spikes Using Wearable Devices: Proposal for a Prospective Cohort Study.

Referred to as the "silent killer," elevated blood pressure (BP) often goes unnoticed due to the absence of apparent symptoms, resulting in cumulative harm over time. Chronic stress has been consistently linked to increased BP. Prior studies have found that elevated BP often arises due to a stressful lifestyle, although the effect of exact stressors varies drastically between individuals. The heterogeneous nature of both the stress and BP response to a multitude of lifestyle decisions can make it difficult if not impossible to pinpoint the most deleterious behaviors using the traditional mechanism of clinical interviews. The aim of this study is to leverage machine learning (ML) algorithms for real-time predictions of stress-induced BP spikes using consumer wearable devices such as Fitbit, providing actionable insights to both patients and clinicians to improve diagnostics and enable proactive health monitoring. This study also seeks to address the significant challenges in identifying specific deleterious behaviors associated with stress-induced hypertension through the development of personalized artificial intelligence models for individual patients, departing from the conventional approach of using generalized models. The study proposes the development of ML algorithms to analyze biosignals obtained from these wearable devices, aiming to make real-time predictions about BP spikes. Given the longitudinal nature of the data set comprising time-series data from wearables (eg, Fitbit) and corresponding time-stamped labels representing stress levels from Ecological Momentary Assessment reports, the adoption of self-supervised learning for pretraining the network and using transformer models for fine-tuning the model on a personalized prediction task is proposed. Transformer models, with their self-attention mechanisms, dynamically weigh the importance of different time steps, enabling the model to focus on relevant temporal features and dependencies, facilitating accurate prediction. Supported as a pilot project from the Robert C Perry Fund of the Hawaii Community Foundation, the study team has developed the core study app, CardioMate. CardioMate not only reminds participants to initiate BP readings using an Omron HeartGuide wearable monitor but also prompts them multiple times a day to report stress levels. Additionally, it collects other useful information including medications, environmental conditions, and daily interactions. Through the app's messaging system, efficient contact and interaction between users and study admins ensure smooth progress. Personalized ML when applied to biosignals offers the potential for real-time digital health interventions for chronic stress and its symptoms. The project's clinical use for Hawaiians with stress-induced high BP combined with its methodological innovation of personalized artificial intelligence models highlights its significance in advancing health care interventions. Through iterative refinement and optimization, the aim is to develop a personalized deep-learning framework capable of accurately predicting stress-induced BP spikes, thereby promoting individual well-being and health outcomes. DERR1-10.2196/55615.

INFORMATION WANTS AND INFORMATION SEEKING ACTIONS FROM PORTUGUESE NEUROLOGIST

Background: Medical professionals nowadays must be well-versed in the most recent, scientifically confirmed facts on illness diagnosis, treatment, and patient care. Despite the fact that there are an increasing number and variety of information sources available to physicians, many questions remain concerning the authenticity, quality, and usefulness of medical information. With the goal of improving current medical information delivery, new methodologies are needed to assess doctors’ real-life demands. Objective: The goal of this study was to explore the information requirements and seeking behaviour of Portuguese’s neurologists treating patients with multiple sclerosis (MS) and migraine. Methods: An exploratory mixed methods (quantitative and qualitative) investigation of 15 consecutive days was conducted. It was necessary to recruit a total of 50 neurologists (25 MS experts and 25 migraine specialists). An instant messaging programme built for this study was used to gather data. Personal interviews were conducted by computer at each information-seeking session, which included semi structured interviews and closed-ended questions. Content analysis was used to identify emergent themes from the mobile app interactions and physician enquiries. Results: A total of 36/20, or 71 percent, of the questions posed by neurologists were linked to treatment management and pharmacological information, followed by diagnostic techniques and procedures. Online resources were preferred by doctors (48/50, 96 percent) over offline alternatives (24/50, 47 percent) in a quantitative study. In 33% of information-seeking activities, a multi-channel strategy was used, which included using both online and offline resources to address the same demand. Neurologists were more likely to use internet resources than offline ones (F=1.7; P=.01) to get information. Compared to migraine neurologists, MS specialists were 53% more likely to participate in a single information-seeking event (risk ratio 1.54; 95% CI 1.12 to 2.05). More than two-thirds of MS specialists (28 percent [7/25] vs. 10 percent [2/25], P=.06) were interested in patient-related material, whereas migraine physicians (85% [21/25] vs. 60% [15/25], P=.05) were more inclined to seek information on treatment management. Both online and offline information searching was more difficult for migraine experts (F=12.5, P=.01) and offline channels were utilised less often (30 percent [8/25] versus 60 percent of information-seeking events, P=.02). To get information from various sources, both migraine and MS experts reported lower satisfaction rates (single source vs multiple sources P=.003). Conclusion: Portuguese MS and migraine neurologists are described in great depth in this research, including their real-life search activity as well as educational requirements and information sources they use. Neurologist information demands and information-seeking behaviour are influenced by their professional field. Identifying the temporal and context-specific demands of physicians is essential for designing a successful medical information strategy, according to these results.

Innovation research of Application interaction design based on regional characteristics

With the development of mobile Internet in China and the popularity of mobile phones and various mobile devices, the demand for APP interaction design is becoming more and more common. China’s APP interface design industry started late, and a large number of international and standardized design styles have occupied the APP application market. Chinese traditional culture is extensive and profound, with rich cultural connotation and historical deposits. How to apply traditional cultural elements to APP interactive interface design and how to display traditional culture through APP interaction are the topics we want to study. We should give traditional Chinese culture vitality in the new era, and integrate it into the interactive interface of modern apps, so that traditional Chinese culture can be more widely inherited and carried forward.

Distribution of APP in endo‐lysosomal system induced by Aβ is modulated by Gβγ signaling

AbstractBackgroundAlzheimer´s disease is characterized by the deposition of aggregated species of amyloid beta (Aβ) in the brain, which leads to progressive cognitive deficits and dementia. We recently found that Aβ assemblies, oligomers and fibrils, increase APP and BACE1 interaction in recycling endosomes and accumulation of intracellular Aβ42 in human neurons derived from iPSCs by a mechanism dependent of APP/Go/Gβγ signaling (Antonino et al 2022, https://doi.org/10.3389/fcell.2022.852738). Now, we are interested on deepen in the APP trafficking in the endo‐lysosomal pathway in order to understand the mechanism underlying such effect.MethodN2a and human neurons derived from iPSc cultures were transfected with fluorescently tagged proteins (APP‐YFP, BACE‐CH, Rab11‐RFP, LAMP1‐CH, Rab7‐CH, APP‐VN, BACE‐VC). Cultures were treated with vehicle or the Gβγ inhibitor gallein and 30 minutes later with vehicle or 1 µM of Aβ oligomeric or fibrillar. After 24 h of treatment quantitative colocalization analysis and bimolecular fluorescence complementation assays were performed.ResultWe found that Aβ induced an enrichment of APP in recycling endosomes at the expense of a decrement of its levels in lysosomes. This change in APP intracellular distribution is drive by Gβγ signaling. Moreover, we found that the changes on APP distribution correlate with an increase in its interaction with BACE1 and with an increase in the number of recycling endosomes, both events modulated by Gβγ signaling (Figure 1,2).ConclusionTogether, these results suggest that Aβ pathological assemblies induce a re‐direction of APP from its physiological route to lysosomes, to recycling endosomes which favors its encounter with BACE1 and its amyloidogenic processing. These finding elucidate the intracellular process which sustain the feed‐forward mechanisms implicated in the amyloidogenesis induced by pathological assemblies of Aβ.

The Association Between Mobile App Use and Change in Functional Capacity Among Cardiac Rehabilitation Participants: Cohort Study.

Cardiac rehabilitation (CR) is underused in the United States and globally, with participation disparities across gender, socioeconomic status, race, and ethnicities. The pandemic led to greater adoption of telehealth CR and mobile app use. Our primary objective was to estimate the association between CR mobile app use and change in functional capacity from enrollment to completion in patients participating in a CR program that offered in-person, hybrid, and telehealth CR. Our secondary objectives were to study the association between mobile app use and changes in blood pressure (BP) or program completion. We conducted a retrospective cohort study of participants enrolled in CR at an urban CR program in the United States. Participants were English speaking, at least 18 years of age, participated in the program between May 22, 2020, and May 21, 2022, and downloaded the CR mobile app. Mobile app use was quantified by number of exercise logs, vitals logs, and education material views. The primary outcome was change in functional capacity, measured by change in 6-minute walk distance (6MWD) from enrollment to completion. The secondary outcome was change in BP from enrollment to completion. We estimated associations using multivariable linear or logistic regression models adjusted for age, sex, race, ethnicity, socioeconomic status by ZIP code, insurance, and primary diagnosis for CR referral. A total of 107 participants (mean age 62.9, SD 13.02 years; 90/107, 84.1% male; and 57/105, 53.3% self-declared as White Caucasian) used the mobile app and completed the CR program. Participants had a mean 64.0 (SD 54.1) meter increase in 6MWD between enrollment and completion (P<.001). From enrollment to completion, participants with an elevated BP at baseline (≥130/80 mmHg) experienced a significant decrease in BP (systolic BP -11.5 mmHg; P=.002 and diastolic BP -7.7 mmHg; P=.003). We found no significant association between total app interactions and change in 6MWD (coefficient -0.03, 95% CI -0.1 to 0.07; P=.59) or change in BP (systolic coefficient 0.002, 95% CI -0.03 to 0.03; P=.87 and diastolic coefficient -0.005, 95% CI -0.03 to 0.02; P=.65). There was no significant association between total exercise logs and change in 6MWD (coefficient 0.1, 95% CI -0.3 to 0.4; P=.57) or total BP logs and change in BP (systolic coefficient -0.02, 95% CI -0.1 to 0.06; P=.63 and diastolic coefficient -0.02, 95% CI -0.09 to 0.04; P=.50). There was no significant association between total app interactions and completion of CR (adjusted odds ratio 1.00, 95% CI 0.99-1.01; P=.44). CR mobile app use as part of an in-person, hybrid, or telehealth CR program was not associated with greater improvement in functional capacity or BP or with program completion.

Caring the Sharing Apps – Exploration of the Factors Affecting User Satisfaction with Sharing Economy Apps

Sharing economy-based services are more prevalent in contemporary society, especially after the covid-19 pandemic. However, from the user’s perspective, it is still unclear what factors define the success of sharing economy-based apps. To address this issue, we conducted a study using an integrated theoretical framework that incorporated cognitive load theory, social network theory, and theory of planned behavior. 448 samples were collected from three tourist destinations in India to test the model. The results showed that mobile app user interface, interaction, and social networking would positively impact user satisfaction with sharing economy-based apps. User satisfaction also leads to recommendation and continuance intention. The study findings have several implications and recommendations for future studies on sharing economy apps.

App interaction design in the pop music singing teaching system based on differential evolution algorithm

App interaction design in the pop music singing teaching system based on differential evolution algorithm

Neuronal deletion of nSMase2 reduces the production of Aβ and directly protects neurons

Extracellular vesicles (EVs) have been proposed to regulate the deposition of Aβ. Multiple publications have shown that APP, amyloid processing enzymes and Aβ peptides are associated with EVs. However, very little Aβ is associated with EVs compared with the total amount Aβ present in human plasma, CSF, or supernatants from cultured neurons. The involvement of EVs has largely been inferred by pharmacological inhibition or whole body deletion of the sphingomyelin hydrolase neutral sphingomyelinase-2 (nSMase2) that is a key regulator for the biogenesis of at-least one population of EVs. Here we used a Cre-Lox system to selectively delete nSMase2 from pyramidal neurons in APP/PS1 mice (APP/PS1-SMPD3-Nex1) and found a ∼ 70% reduction in Aβ deposition at 6 months of age and ∼ 35% reduction at 12 months of age in both cortex and hippocampus. Brain ceramides were increased in APP/PS1 compared with Wt mice, but were similar to Wt in APP/PS1-SMPD3-Nex1 mice suggesting that elevated brain ceramides in this model involves neuronally expressed nSMase2. Reduced levels of PSD95 and deficits of long-term potentiation in APP/PS1 mice were normalized in APP/PS1-SMPD3-Nex1 mice. In contrast, elevated levels of IL-1β, IL-8 and TNFα in APP/PS1 mice were not normalized in APP/PS1-SMPD3-Nex1 mice compared with APP/PS1 mice. Mechanistic studies showed that the size of liquid ordered membrane microdomains was increased in APP/PS1 mice, as were the amounts of APP and BACE1 localized to these microdomains. Pharmacological inhibition of nSMase2 activity with PDDC reduced the size of the liquid ordered membrane microdomains, reduced the localization of APP with BACE1 and reduced the production of Aβ1–40 and Aβ1–42. Although inhibition of nSMase2 reduced the release and increased the size of EVs, very little Aβ was associated with EVs in all conditions tested. We also found that nSMase2 directly protected neurons from the toxic effects of oligomerized Aβ and preserved neural network connectivity despite considerable Aβ deposition. These data demonstrate that nSMase2 plays a role in the production of Aβ by stabilizing the interaction of APP with BACE1 in liquid ordered membrane microdomains, and directly protects neurons from the toxic effects of Aβ. The effects of inhibiting nSMase2 on EV biogenesis may be independent from effects on Aβ production and neuronal protection.

Research on Architecture Strategy and Estimation Model of Digitized and Business-oriented Smart Community System

The level of intelligence in the community has become an important indicator to reflect the level of urban development. This article starts with the architecture strategy of the system and builds a dynamic digital business smart community system. The goals of software product management for the three-dimensional digital community are clarified, which improves the effectiveness and reliability of system development. Based on the function points, data management system estimation model, geographic information system estimation model, APP system estimation model, and content management system estimation model are created separately. The interaction interfaces of the information management system, information publishing system, activity publishing system with the geographic information system, APP interaction interface, and content management system are unified into the data management system estimation model. By analyzing the technical and economic theory, the bottleneck problem of promoting the application of digital communities is solved, and the development cost of digital community software systems can be predicted clearly. This also facilitates the calculation of the direct economic and social benefits brought by the promotion and application of results.

Comparison of Google Lens recognition performance with other plant recognition systems

In the context of the STEM approach to education, motivating pupils through tailored research and leveraging IT in the classroom is relevant. The justification of these approaches hasn't received much examination, though. The purpose of the study is to support the decision to use an AR-plant recognition application to give tailored instruction throughout both extracurricular activities and the school day. Every phase of an app's interaction with a user was examined and used to categorize every app. Also described were the social settings of the applications and how they were used for extracurricular activities. There has been discussion on the didactics of using AR recognition apps in biology classes. A survey of experts in digital education regarding the ease of installation, the friendliness of the interface, and the accuracy of image processing was conducted to give usability analysis. Applications were examined for their ability to accurately identify plants on the "Dneprovskiy district of Kiev" list in order to assess the rationale of usage. It has been established that Google Lens is the best option. As an alternative to Seek or Flora Incognita, according to the analysis's findings, these apps were less accurate.

Design of a Patient Voice App Experience for Heart Failure Management: Usability Study.

The use of digital therapeutics (DTx) in the prevention and management of medical conditions has increased through the years, with an estimated 44 million people using one as part of their treatment plan in 2021, nearly double the number from the previous year. DTx are commonly accessed through smartphone apps, but offering these treatments through additional platforms can improve the accessibility of these interventions. Voice apps are an emerging technology in the digital health field; not only do they have the potential to improve DTx adherence, but they can also create a better user experience for some user groups. This research aimed to identify the acceptability and feasibility of offering a voice app for a chronic disease self-management program. The objective of this project was to design, develop, and evaluate a voice app of an already-existing smartphone-based heart failure self-management program, Medly, to be used as a case study. A voice app version of Medly was designed and developed through a user-centered design process. We conducted a usability study and semistructured interviews with patients with heart failure (N=8) at the Peter Munk Cardiac Clinic in Toronto General Hospital to better understand the user experience. A Medly voice app prototype was built using a software development kit in tandem with a cloud computing platform and was verified and validated before the usability study. Data collection and analysis were guided by a mixed methods triangulation convergence design. Common themes were identified in the results of the usability study, which involved 8 participants with heart failure. Almost all participants (7/8, 88%) were satisfied with the voice app and felt confident using it, although half of the participants (4/8, 50%) were unsure about using it in the future. Six main themes were identified: changes in physical behavior, preference between voice app and smartphone, importance of music during voice app interaction, lack of privacy concerns, desired reassurances during voice app interaction, and helpful aids during voice app interaction. These findings were triangulated with the quantitative data, and it concluded that the main area for improvement was related to the ease of use; design changes were then implemented to better improve the user experience. This work offered preliminary insight into the acceptability and feasibility of a Medly voice app. Given the recent emergence of voice apps in health care, we believe that this research offered invaluable insight into successfully deploying DTx for chronic disease self-management using this technology.

First-time Mothers' Understanding and Use of a Pregnancy and Parenting Mobile App (The Baby Buddy App): Qualitative Study Using Appreciative Inquiry.

Internationally, there is increasing emphasis on early support for pregnant women to optimize the health and development of mothers and newborns. To increase intervention reach, digital and app-based interventions have been advocated. There are growing numbers of pregnancy health care apps with great variation in style, function, and objectives, but evidence about impact on pregnancy well-being and behavior change following app interaction is lacking. This paper reports on the qualitative arm of the independent multicomponent study exploring the use and outcomes of first-time mothers using the Baby Buddy app, a pregnancy and parenting support app, available in the National Health Service App Library and developed by a UK child health and well-being charity, Best Beginnings. This study aims to understand when, why, and how first-time mothers use the Baby Buddy app and the perceived benefits and challenges. This paper reports on the qualitative arm of an independent, longitudinal, mixed methods study. An Appreciative Inquiry qualitative approach was used with semistructured interviews (17/60, 28%) conducted with new mothers, either by telephone or in a focus group setting. First-time mothers were recruited from 3 study sites from across the United Kingdom. Consistent with the Appreciative Inquiry approach, mothers were prompted to discuss what worked well and what could have been better regarding their interactions with the app during pregnancy. Thematic analysis was used, and findings are presented as themes with perceived benefits and challenges. The main benefit, or what worked well, for first-time mothers when using the app was being able to access new information, which they felt was reliable and easy to find. This led to a feeling of increased confidence in the information they accessed, thus supporting family and professional communication. The main challenge was the preference for face-to-face information with a health care professional, particularly around specific issues that they wished to discuss in depth. What could have been improved included that there were some topics that some mothers would have preferred in more detail, but in other areas, they felt well-informed and thus did not feel a need to seek additional information via an app. Although this study included a small sample, it elicited rich data and insights into first-time mothers' app interactions. The findings suggest that easily accessible pregnancy information, which is perceived as reliable, can support first-time mothers in communicating with health care professionals. Face-to-face contact with professionals was preferred, particularly to discuss specific and personalized needs. Further studies on maternal and professional digital support preferences after the COVID-19 global pandemic and how they facilitate antenatal education and informed decision-making are recommended, particularly because digital solutions remain as a key element in pregnancy and early parenting care. RR2-10.1017/S1463423618000294.

Understanding the Paths and Patterns of App-Switching Experiences in Mobile Searches

Mobile searches have become the main channel for people to search for information, and mobile searches have received attention in the field of information-seeking behavior. Especially as users use various apps to search network information, the app-switching behaviors in mobile searches have also attracted scholars’ attention in recent years. Research on app-switching behaviors in mobile searches can help to further understand users’ search motivations, evaluate search results, and improve users’ mobile search experiences. This study recruited participants (n = 30) and conducted a 15-day user experiment. This study collected all participants’ mobile phone log data during the experiment and identified the app-switching behaviors in mobile searches through a log collection tool. This study aimed to discover the app-switching behavior paths and patterns in mobile searches. Firstly, the basic characteristics of app-switching behaviors in mobile searches were analyzed, as were the app-switching paths in mobile searches from the perspective of switching probability between apps. Then, the different behaviors in mobile search sessions were identified and app-switching behavior patterns were put forward. These behavior patterns summarize user behavior changes in mobile search sessions. This paper focused on analyzing app-switching behavior paths under different patterns and found apparent differences in app-switching behavior paths. This study examined mobile search behavior from the perspective of app-switching. The research of this paper can help to better understand the relationship between users’ mobile search behaviors and app interactions and is an excellent supplement to the analysis of mobile search behaviors.

A study on the effect of user experience of fitness APP on product trust and purchase intention

Purpose - The purpose of this study is to take fitness APP users as the research object from the perspective of user experience to explore the influence of fitness APP user experience factors on product trust and purchase intention. Design/methodology/approach - The study collected data on 275 customers who had experience buying and using fitness apps. To test the hypothesis, SPSS 27.0 and AMOS 26.0 statistical packages were used based on the collected data. Findings - The results showed that the user experience factors (usefulness, ease to use, enjoyment, interaction) of fitness APP and the relationship between product trust had a positive effect, and product trust had a positive effect on purchase intention. In addition, exercise experience, showed a moderating effect in the relationship between the usefulness, easy to use of user experience and product trust. Research implications or Originality - This study provided research model among user experience factors of fitness APP, product trust and purchase intention. This study can help sports and fitness companies with product optimization and marketing decisions.

APOE ε4 influences cognitive decline positively in APP and negatively in PSEN1 mutation carriers with autosomal-dominant Alzheimer's disease.

The aim was to investigate the effect of APOE ε4 allele on cognitive decline in adAD. Presence of the APOE ε4 allele reduces age of symptom onset, increases disease progression, and lowers cognitive performance in sporadic Alzheimer's disease (AD), while the impact of the APOE ε4 allele in autosomal-dominant AD (adAD) is incompletely known. Mutation carriers (MCs; n= 39) and non-carriers (NCs; n= 40) from six adAD families harbouring a mutation in the APP (28 MCs and 25 NCs) or the PSEN1 genes (11 MCs and 15 NCs) underwent repeated cognitive assessments. A timeline of disease course was defined as years to expected age of clinical onset (YECO) based on history of disease onset in each family. The MC and NC groups were comparable with regard to demographics and prevalence of the APOE ε4 allele. The relationship between cognitive decline and YECO, YECO2 , education, APOE, and APOE-by-YECO interaction was analysed using linear mixed-effects models. The trajectory of cognitive decline was significantly predicted by linear and quadratic YECO and education in MCs and was determined by age and education in NCs. Adding APOE ε4 allele (presence/absence) as a predictor did not change the results in the MC and NC groups. The outcome also remained the same for MCs and NCs after adding the APOE-by-YECO interaction as a predictor. Analyses of APP and PSEN1 MCs separately showed favourable APOE-by-YECO interaction in APP (less steep decline) and unfavourable interaction in PSEN1 (steeper decline), linked to the APOE ε4 allele. The APOE ε4 allele influences cognitive decline positively in APP and negatively in PSEN1 mutation carriers with adAD, indicating a possible antagonistic pleiotropy.

Abstract P304: Persistent Use Of Aktiia 24/7 Blood Pressure Monitor Is Associated With Lower Blood Pressure In Hypertensive Patients

Introduction: Cuffless blood pressure (BP) monitors are a promising innovation for hypertension diagnosis and monitoring. Aktiia (Aktiia 24/7 BP Monitor, Aktiia, Switzerland) is a CE-marked, commercially available BP monitor that passively and continually collects BP waveforms via optical sensors at the wrist. After initial cuff calibration, the app displays BP estimates on a smartphone. No data exist on the impact of persistently showing a person their BP data with this device. Hypothesis: If people with hypertension persistently use Aktiia and are exposed to their BP data, there will be a change in behavior resulting in measurably lower BP. Methods: We analyzed the systolic BP (SBP) trends of 838 real-world users (Age 57±11, 14% female) who consistently used Aktiia for 6 months (375±287 app interactions, 3646±1417 cuffless readings per user, and 9±7 cuff readings per user). Users were grouped by the mean monthly SBP (&lt;140 and &gt;140 mmHg) calculated over 6 months. Then, cuff SBP averages were calculated monthly and compared to the SBP average of the first month. A t-test analysis was used to detect the difference in SBP between the first and successive months. Results: Hypertensive users (SBP &gt; 140 mmHg) saw a reduction in SBP of -3.2 mmHg (CI: -0.70, -5.59, p&lt;0.02), beginning at 3 months and sustained through 6 months. For users with SBP &lt; 140 mm Hg, the mean SBP remained unchanged (Fig. 1). Conclusion: Persistent BP monitoring with Aktiia’s cuffless device is associated with a significant, sustained reduction in SBP for hypertensive patients at 6 months. Possible explanations include the Hawthorne effect or intensified treatment.

Hansenapp: Development of a mobile application to assist primary healthcare providers to control leprosy.

To describe the development and validation of a mobile application to assist health professionals in the management of patients with leprosy and surveillance of contacts in primary healthcare. A methodological and developmental study was conducted in three phases: integrative literature review, mobile application development and application validation by health professionals. The construction of the application was supported by the literature review, Nielsen's heuristics and expert validation. Five experts individually analysed the prototype draft and performed two rounds of iterations to refine their recommendations. The validation step was performed by consulting health professionals working in primary healthcare, who evaluated the application for relevance, clarity and usability using a questionnaire based on task-technology fit theory. The mobile app's content, navigation methods and interaction were refined based on the discussions with experts. Their recommendations were applied, and the mobile app was revised until the final version was approved. Content validity indexes of 0.94 (p= 0.007), 0.99 (p> 0.0001) and 0.93 (p= 0.01) were obtained. The developed application is a technological tool that could assist primary healthcare providers in dealing with leprosy patients and their contacts in terms of management, planning, monitoring, evaluation, treatment and follow-up, in addition to leprosy control actions.

Curate: A news app for the millennial news consumers

Nowadays we access news on smartphones and tablets and this virtual news reading is increasing day by day, so there is an obvious need for reading news in personalised virtual app interactions. We collectively analysed a set of studies that addressed the concerns in the process involve in the development of versatile news app interfaces. The goal of this application is to deliver the news extracted from different platforms at a single place as fast as possible. On a priority basis, firstly we surveyed the users, secondly their preferences, and lastly conduct; this analysis of survey outcome into three primary types of readers. This evaluation illustrates the different advantages of the familiarization for various users of the news app and the viability of interactive interfaces for news apps. Then we implemented and developed an Interactive news app.