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In recent years, increasing attention has been paid to identifying new approaches to improve workplace well-being and manage stress with the help of m-health solutions. The primary purpose of this review is to provide an overview of the current use of smartphone applications integrated with wearable technologies in stress management and the promotion of well-being in the workplace. A key terms literature search was performed using multiple electronic databases. The review process followed the international PRISMA statement guidelines. A quality assessment was conducted using the Mixed Methods Appraisal Tool. A total of 25 eligible papers published between 2016 and 2023 were included. Interventions proposed were heterogeneous and primarily based on smartphone applications (72%). 84% of the interventions had background theories, with a high preference for Mindfulness. Interventions were reported as generally significant, and the combined use of smartphone applications and wearable technologies increased awareness at the individual and collective levels. In conclusion, the review demonstrates how the interventions developed through the synergy of technologies can effectively promote well-being and reduce stress in the workplace context, decreasing the stigma still related to mental health and increasing peer support strategies. This work opens the doors to several possibilities for future research. It could be interesting to indagate more in-depth the value of integration between technologies and, eventually, the integration with more traditional type of interventions, e.g., face-to-face activities, evaluating if this synergy can amplify and strengthen the results. Protocol registration: The review protocol was registered with PROSPERO: CRD42023423126 (May 2nd, 2023). [ABSTRACT FROM AUTHOR]

Purpose of Review: To review randomized controlled trials (RCTs) published from 2021–2023 that reported the effects of peer support interventions on outcomes in patients with type 2 diabetes (T2DM). Recent Findings: Literature searches yielded 137 articles and nine RCTs were ultimately reviewed. The reviewed trials involved in-person support groups, peer coach/mentor support, cultural peer support by community health workers, peer support during shared medical appointments (SMAs) including virtual reality-based SMAs, telehealth-facilitated programs, and telephone peer support. Most interventions combined two or more peer support strategies. Peer support was associated with significant decreases in HbA1c in 6 of the 9 reviewed studies. The largest statistically significant improvements in HbA1c were reported in a study of community health workers in Asia (-2.7% at 12 months) and a Canadian study in which trained volunteer peer coaches with T2DM met with participants once and subsequently made weekly or biweekly phone calls to them (-1.35% at 12 months). Systolic blood pressure was significantly improved in 3 of 9 studies. Summary: The findings suggest that peer support can be beneficial to glycemic control and blood pressure in T2DM patients. Studies of peer support embedded within SMAs resulted in significant reductions in HbA1c and suggest that linkages between healthcare systems, providers, and peer support programs may enhance T2DM outcomes. [ABSTRACT FROM AUTHOR]

Many people are unaware of the severity of melanoma disease even though such a disease can be fatal if not treated early. This research aims to facilitate the diagnosis of melanoma disease in people using a mobile health application because some people do not prefer to visit a dermatologist due to several concerns such as feeling uncomfortable by exposing their bodies. As such, a skincare application was developed so that a user can easily analyze a mole at any part of the body and get the diagnosis results quickly. In the first phase, the corresponding image is extracted and sent to a web service. Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. The final phase displays the confidence rates on the mobile application. The proposed model utilizes the Convolutional Neural Network and provides 84% accuracy and 72% precision. The results demonstrate that the proposed model and the corresponding mobile application provide remarkable results for addressing the specified health problem. [ABSTRACT FROM AUTHOR]

This study examined the effectiveness of a theory-based mHealth intervention on the quality of life (QOL) of people living with HIV. A randomized controlled trial was performed at two outpatient clinics in Hanoi, Vietnam. There were 428 patients with HIV/AIDs in selected clinics and were divided into the intervention arm (receiving HIV-assisted smartphone application and usual care) and the control arm (receiving only usual care). The WHOQOLHIV-BREF instrument was utilized to measure QOL. An intention-to-treat approach using Generalized Linear Mixed Model analysis was performed. The trial showed significant improvements in Physical health, Psychological health, and Level of Dependence among patients in the intervention arm compared to the control arm. However, the Environment and Spirituality/Personal beliefs improvements would require additional interventions, both individual, organizational, or governmental. This study explored the utility of a smartphone mobile application for individuals with HIV, and how the resultant application could improve the overall QOL. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management. Methods: Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA1c between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire – Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately. Results: A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group (n=111), HbA1c decreased from 60.6±14.7 mmol/mol (7.7±1.3%) to 56.7±12.1 mmol/mol (7.3±1.1%) (means ± SD, p<0.001), compared with no change in the usual care group (n=115) (baseline: 61.7±13.7 mmol/mol, 7.8±1.3%; end of study: 61.0±12.4 mmol/mol, 7.7±1.1%; p=0.19) (between-group difference 0.24%, p=0.008). In the sub-analyses in the POWER2DM group, HbA1c in participants with type 2 diabetes decreased from 62.3±17.3 mmol/mol (7.9±1.6%) to 54.3±11.1 mmol/mol (7.1±1.0%) (p<0.001) compared with no change in HbA1c in participants with type 1 diabetes (baseline: 58.8±11.2 mmol/mol [7.5±1.0%]; end of study: 59.2±12.7 mmol/mol [7.6±1.2%]; p=0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7±3.8; end of study: 16.3±3.5; p=0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3±1.2 to 7.7±1.2; p=0.002) and those with type 2 diabetes (from 6.5±1.3 to 6.7±1.3; p=0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed. Conclusions/interpretation: POWER2DM improves HbA1c levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life. Trial registration: ClinicalTrials.gov NCT03588104. Funding: This study was funded by the European Union's Horizon 2020 Research and Innovation Programme (grant agreement number 689444). [ABSTRACT FROM AUTHOR]

Aim: Sedentary behavior poses a serious health risk. Students in particular are highly affected by prolonged, uninterrupted periods of sitting due to routines in everyday university life, such as attending lectures, self-study periods in the library, etc. Whereas university students are mostly young and therefore appear to be healthy, evidence-based consequences of prolonged sitting may come to pass in prospective times. Therefore, primary prevention must be initiated to shield university students from the occurrence of non-communicable diseases (NCDs). Consequently, the study aims to evaluate a messenger-based intervention designed to reduce sedentary time among university students. Subjects and Methods: The effectiveness of the intervention was assessed in a randomized controlled trial with a convenience sample of thirty-four German university students. ActivPal devices (Pal Technologies Ltd., Glasgow) were applied to measure sedentary behavior objectively before and after a 3-week intervention of messages to interrupt sedentary time. An additional evaluation of the messages was carried out. Results: Sedentary behavior decreased by about one hour in the intervention group. Explorative analysis shows a statistically significant, negative correlation between sedentary time at baseline and the change of sedentary behavior over time in the intervention group (r = −.81) indicating effectiveness of the intervention for the participants with the highest sedentary times at baseline. Additionally, the messages were considered appropriate by the participants. Conclusion: A reduction of sedentary time of one hour per day in the intervention group is practically significant. The current investigation had similar findings with prior studies where promising results for the reduction of sedentary behavior were observed through mobile-based interventions. The detected effects of the intervention in this pilot study demonstrate an opportunity for further research in this field. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to gather insights from colorectal cancer (CRC) survivors on how to improve care for CRC survivors and how e-health technology could be utilized to improve CRC care delivery. Methods: Three semi-structured focus groups were held with sixteen CRC survivors. To initiate the discussion, an online registration form and two vignettes were used. The data was analyzed using the framework method. Results: Based on survivors’ experiences, five themes were identified as opportunities for improving CRC care delivery. These themes include better recognition of complaints and faster referrals, more information as part of the care delivery, more guidance and monitoring of health outcomes, more collaboration between practitioners, and more attention for partners and relatives. In addition, survivors expressed opportunities for using e-health to facilitate information provision, improve communication, and monitor survivors’ health conditions. Conclusion: Several suggestions for improvement of CRC care delivery were identified. These often translated into possibilities for e-health to support or improve CRC care delivery. The ideas of survivors align with the vast array of existing e-health resources that can be utilized to enhance CRC care delivery. Therefore, the next step involves addressing the implementation gap between the needs of stakeholders, such as CRC survivors and healthcare providers, and the e-health tools currently available in clinical practice. [ABSTRACT FROM AUTHOR]

Purpose: Smartphone is an impending solution to influence long-term behavior change, including physical activity; however, the evidence regarding personalized prescription remains mixed in obese. We aimed to explore the influence of smartphone-based physical activity promotion on weight loss and cognitive functions in obese young adults. Methods: In our pilot randomised controlled trial, 24 obese adults were randomized to two conditions: (1) EXI group receiving a smartphone-application based personalized physical activity prescription; (2) CONT group continuing their routine work for eight weeks. Executive functions and cardiometabolic risk variables [body and fat mass, waist circumference (WC), blood pressure (BP)] and executive functions were measured before and after eight weeks. Results: Our study findings revealed a significant improvement in reaction times with overall (H = 7.71, p = 0.005), congruent stimuli (H = 4.43, p = 0.03) and incongruent stimuli (H = 5.35, p = 0.02) between groups. Though EXI participants reduced their fat mass by 5.07 kg more than CONT group users after eight weeks, the findings were statistically insignificant. Similarly, our study did not find significant differences in body mass, WC, BP or accuracy between EXI and CONT groups. There was a decreased user engagement (H = 5.80, p = 0.564) after the 3rd week of the study period. Conclusion: Short-term smartphone-based physical activity programs may offer favourable cognitive benefits to young adults; however, the weight loss benefits remain unconvincing. Trial Registration: The study was registered prospectively with the Clinical Trials Registry of India (CTRI/2022/02/040202). [ABSTRACT FROM AUTHOR]

Purpose: Patient-reported outcomes (PROs) are essential to evaluate inguinal hernia surgery. There is a need for digital and disease-specific PRO measurement. Current measuring instruments (PROMs) have several disadvantages, for example, fixed measuring moments with a chance of recall bias. The Q1.6 Inguinal Hernia application has been developed to overcome these challenges. This pilot study reports the first clinical feasibility results. Methods: All surgically treated inguinal hernia patients were eligible for inclusion. The application uses "twitch crowdsourcing"; after unlocking a smartphone or tablet, a single short question is asked. This can easily be repeated multiple times a day/week/month. Questions from validated questionnaires were implemented. The adaptive question engine generates an individualised set of questions. Alerts are generated when a complication is suspected. Results: A total of 229 patients were given over 50.000 questions of which 92% were answered. Pre- and postoperative patient characteristics and their reported clinical outcomes confirmed a standard inguinal hernia population. Compliance with the application was 91.7% after 14 days, 69.0% after 3 months and 28.8% after one year. After months 3, 6 and 11, respectively, 3.0%, 4.4% and 4.5% of patients reported inguinal pain or discomfort (NRS ≥ 4). Patients were highly satisfied (92.8% preferred the app over standard care). Conclusions: This smartphone application shows promising results for clinical practice. It might allow for continuous digital patient-reported outcome measurement using non-intrusive, concise questions. Remote monitoring may become standard postoperative care after (inguinal hernia) surgery. The current application will be further improved and evaluated for cost-effectiveness, safety and validity. [ABSTRACT FROM AUTHOR]

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Fun For Wellness (FFW) is a self-efficacy theory-based online behavioral intervention that aims to promote growth in physical activity and well-being. The FFW conceptual model for the promotion of subjective well-being posits that FFW exerts both a positive direct effect, and a positive indirect effect through well-being self-efficacy, on subjective well-being. Subjective well-being is defined in FFW as an individual's satisfaction with their status in seven key domains of their life. Well-being self-efficacy is defined in FFW as the degree to which an individual perceives that they have the capability to attain a positive status in seven key domains of their life. The objective of this study was to use baseline target moderation to assess variation in the impact of FFW on subjective well-being dimensions in adults with obesity. Data (N = 667) from the Well-Being and Physical Activity Study (ClinicalTrials.gov, identifier: NCT03194854) were reanalyzed. There was evidence that well-being self-efficacy at baseline moderated the direct effect of FFW on well-being self-efficacy at 30 days post-baseline for the occupational and psychological dimensions. Both of these findings suggest a "compensatory" effect. Similarly, there was evidence that well-being self-efficacy at baseline moderated the indirect effect of FFW on subjective well-being at 60 days post-baseline through well-being self-efficacy at 30 days post-baseline for the occupational and psychological dimensions. Both of these findings suggest a "compensatory" effect. Finally, there was evidence that well-being self-efficacy at baseline moderated the direct effect of FFW on subjective well-being at 60 days post-baseline for the community, occupational, and physical dimensions. Each of these three findings suggests some version of a "rich-get-richer" effect. In summary, results provide both supportive and unsupportive (i.e., interpersonal, economic, and overall dimensions) evidence regarding variation in the impact of the FFW intervention and should impact the design of future FFW trials. [ABSTRACT FROM AUTHOR]

While an increasing number of Informal CareGivers (ICGs) are assisting their dependent loved ones with the daily living tasks and medical care, they are rarely considered in the medical devices design process. The objective of this study is to identify the characteristics of ICGs impacting the use of the iHealth® Sense BP7 medical device, namely a connected wrist blood pressure monitor. For this purpose, user tests were conducted with 29 potential or actual ICGs. First, the participants filled out a socio-demographic questionnaire and then handled the blood pressure monitor. Finally, they completed the System Usability Scale questionnaire. The results revealed an impact of technophilia and age on usability dimensions. To conclude, the consideration of the ICG population in the design process of connected medical devices is discussed, particularly the age and level of technophilia. [ABSTRACT FROM AUTHOR]

Studies show positive affect buffers against stress for people living with HIV, however, limited research has examined its potential health benefits for sexual minority men living with HIV (SMM-LHIV). In our proof-of-concept pilot, we adapted a Positive Affect intervention for mobile app delivery. The Positively Healthy app was designed as an ecological momentary intervention using a just-in-time adaptive intervention (JITAI) delivery format. Participants were 22 SMM-LHIV (Mage = 37.82; SD = 10.52), who completed a 90-day ecological momentary assessment (EMA). JITAI activities were triggered based on reported stress in the EMA survey. Participants completed a post-intervention assessment assessing usability, feasibility, and acceptability. On average, participants reported stress in 58.21% of the EMAs and responded to 82.1% of the intervention activities. Qualitative interview data indicated that app-based delivery was acceptable and feasible. Participant feedback also revealed our intervention would benefit from further adaptation to enhance system usability and tailored content to optimize acceptability for SMM-LWH. [ABSTRACT FROM AUTHOR]

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Mobile health (m-health) has shown positive effects on disease prevention; however, several factors might influence its effectiveness, particularly in low- and middle-income countries. Randomized trials provide data with high internal validity but no major information on population impact. We conducted a pilot population-based study to assess the feasibility of cancer prevention through m-health in a Latin American population. A sample of affiliates to a health insurance company in Colombia was randomly selected and assigned to receive a short message service (SMS) or voice messages (VMS) during 4 weeks; weekly frequencies 2 and 7. Baseline and post-intervention surveys were conducted. Overall, 797 affiliates were contacted (SMS 393, VMS 404) but only 15.3% and 24.8% enrolled, respectively. Over 80% acceptability was observed among participants for all items evaluated (usefulness, understandability, timing, and frequency); however, 2-VMS per week was the only frequency consistent with the declared number of messages received and listened. Other frequencies resulted in high reception recall but low willingness to read/listen the messages. The willingness to be part of future programs was 20.0%. The gap between declared acceptability and practice, low participation rates, and low willingness to read/listen messages indicate m-health should be part of multicomponent interventions and should not be conceived as the sole intervention. [ABSTRACT FROM AUTHOR]

Aged macular degeneration (AMD) leads to a progressive decline in visual acuity until reaching blindness. It is considered as an irreversible pathology where an early diagnosis remains crucial. However, the lack of ophthalmologists, the permanent increase in elderly people, and their limited mobility involves a delay in AMD diagnosis. In this paper, we propose an automated method for AMD screening. The proposed processing pipeline consists in applying the well-known Radon transform to the macula region in order to model the AMD lesions even with a moderate quality of smartphone-captured fundus images. Thereby, the relevant features are carefully selected, related to the main proprieties of drusens, and then provided to an SVM classifier. The implementation of the method into a smartphone associated to a fundus image capturing device leads to a mobile CAD system that performs higher performance AMD screening. Within this framework and to achieve a real-time implementation, an optimization approach is suggested in order to reduce the processing workload. The evaluation of our method is carried out through the three public STARE, REFUGE, and RFMiD databases. A 4-fold cross-validation approach is used to evaluate the method performance where accuracies of 100%, 95.2%, and 94.3% are respectively obtained with STARE, REFUGE, and RFMiD databases. Comparisons with the state-of-the-art methods in the literature are done. Thereafter, the robustness of the proposed method was evaluated and proved. We note that 100% accuracy was preserved despite the use of degraded quality fundus images as noisy and blurred. Moreover, the propounded method was implemented in S7-Edge and S9 Smartphone devices, where the execution times of 19 and 15 milliseconds were respectively achieved, which proves the AMD real-time detection. Taking advantage of its mobility, cost-effective, detection performance, and reduced execution time, our proposed method seems a good solution for real-time AMD screening on mobile devices. [ABSTRACT FROM AUTHOR]

In recent years, deep learning in healthcare applications has attracted considerable attention from research community. They are deployed on powerful cloud infrastructures to process big health data. However, privacy issue arises when sensitive data are offloaded to the remote cloud. In this paper, we focus on pervasive health monitoring applications that allow anywhere and anytime monitoring of patients, such as heart diseases diagnosis, sleep apnea detection, and more recently, early detection of Covid-19. As pervasive health monitoring applications generally operate on constrained client-side environment, it is important to take into consideration these constraints when designing privacy-preserving solutions. This paper aims therefore to review the adequacy of existing privacy-preserving solutions for deep learning in pervasive health monitoring environment. To this end, we identify the privacy-preserving learning scenarios and their corresponding tasks and requirements. Furthermore, we define the evaluation criteria of the reviewed solutions, we discuss them, and highlight open issues for future research. [ABSTRACT FROM AUTHOR]

Background: The number of e-health interventions developed for breast cancer survivors continues to increase. However, issues with engagement and retention are common. This study aimed to explore e-health literacy rates and access to smartphones and tablets in a large sample of breast cancer survivors. Methods: In study 1, women were recruited from outpatient breast clinics across England and Wales. Eligible women were asked to complete a questionnaire pack to assess their access to devices and their e-health literacy. Multiple regression analyses were run to assess the relationship between technology access and e-health literacy with sociodemographic variables such as age, social deprivation, and education. Study 2 presents a smaller sample recruited through social media who answered a questionnaire relating to use of mobile devices and e-health, and apps. Results: Two thousand nine women participated in the study. Seventy-one percent had access to a smartphone, 54% had access to a tablet, and 20% did not have access to either device. Multiple logistic regressions showed that women who were younger, had higher levels of education, and who were from less deprived areas were more likely to have access to either device. Poorer e-health literacy was associated with being older, having less education, and not having access to a mobile device. Conclusions: Whilst the results show relatively widespread access to mobile devices, there is evidence of a digital divide across some groups. Online interventions should be developed with consideration of individuals who are less e-health-literate and less technologically adept in order to increase the likelihood of engagement. [ABSTRACT FROM AUTHOR]

Introduction: Numerous digital tools to self-assess visual acuity have been introduced. The recent COVID-19 pandemic underlined the need for high-quality remote care. This review gives a current overview of digital tools for remotely assessing visual function and reports on their accuracy. Methods: We searched the databases of Embase and Pubmed, and systematically reviewed the literature, conforming to PRISMA guidelines. Two preliminary papers were added from medRxiv.org. The main outcome was the agreement of the digital tools with conventional clinical charts, as expressed by mean differences and 95% limits of agreement (95% LoA). Results: Seventeen publications included studies reported on 13 different digital tools. Most of the tools focus on distance visual acuity. The mean differences of the digital tools ranged from − 0.08 to 0.10 logMAR, when compared to traditional clinical assessments. The 95% LoA differed considerably between studies: from ± 0.08 logMAR to ± 0.47 logMAR, though the variability was less pronounced for higher visual acuities. Conclusion: The low mean differences between digital visual acuity assessments and reference charts suggest clinical equivalence, though the wide 95% LoA identify a lower precision of digital self-assessments. This effect diminishes in individuals with better visual acuities, which is a common feature of visual acuity assessments. There is great potential for the digital tools to increase access to eye care and we expect the accuracy of the current tools to improve with every iteration in technology development. [ABSTRACT FROM AUTHOR]

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The main objective of this paper is to review and analysis of the state of the art regarding triage applications (apps) for health emergencies. This research is based on a systematic review of the literature in scientific databases from 2010 to early 2021, following a prism methodology. In addition, a Google Play Store search of the triage apps found in the literature was performed for further evaluation. A total of 26 relevant papers were obtained for this study, of which 13 apps were identified. After searching for each of these apps in the Google Play Store platform, only 2 of them were obtained, and these were subsequently evaluated together with another app obtained from the link provided in the corresponding paper. In the analysis carried out, it was detected that from 2019 onwards there has been an increase in research interest in this area, since the papers obtained from this year onwards represent 38.5% of the relevant papers. This increase may be caused by the need for early selection of the most serious patients in such difficult times for the health service. According to the review carried out, an increase in mobile app research focused on Emergency Triage and a decrease in app studies for triage catastrophe have been identified. In this study it was also observed that despite the existence of many researches in this sense, only 3 apps contained in them are accessible. "TRIAGIST" does not allow the entry of an unidentified user, "Major Trauma Triage Tool" presents negative comments from users who have used it and "ESITriage" lacks updates to improve its performance. [ABSTRACT FROM AUTHOR]

Copyright of Herzschrittmachertherapie und Elektrophysiologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fun For Wellness is a self-efficacy theory-based online behavioral intervention developed to promote growth in well-being and physical activity by providing capability-enhancing opportunities to participants. Evidence has been provided for the efficacy of Fun For Wellness to promote subjective well-being in adults in a relatively controlled setting. The objective of this study was to evaluate the effectiveness of Fun For Wellness to increase subjective well-being in adults with obesity in the United States of America in a relatively uncontrolled setting. The data described in this manuscript were collected within a more broadly focused trial: the Well-Being and Physical Activity Study (ClinicalTrials.gov, identifier: NCT03194854, https://clinicaltrials.gov/ct2/show/NCT03194854). The study design was a large-scale, prospective, double-blind, parallel group randomized controlled trial. Participants were recruited through an online panel recruitment company. Data collection occurred at three time points: baseline, 30 days and 60 days after baseline. Participants (N = 667) who were assigned to the Fun For Wellness group (nFFW = 331) were provided with 30 days of 24 h access to the online intervention (i.e., from baseline to 30 days after baseline). Participants assigned to the usual care group (nusual care = 336) were asked to conduct their lives as usual. There was evidence for a positive indirect effect of Fun For Wellness on both occupational and psychological subjective well-being at 60 days after baseline through occupational and psychological well-being self-efficacy at 30 days after baseline, respectively. There was evidence for a positive direct effect of Fun For Wellness on both community (d = 0.33) and physical (d = 0.26) subjective well-being at 60 days after baseline. Results from this study provided some initial evidence for both the effectiveness (e.g., promoting community, occupational, physical, and psychological subjective well-being), and the ineffectiveness (e.g., failing to promote interpersonal, economic, and overall subjective well-being), of the Fun For Wellness intervention for increasing subjective well-being in adults with obesity in the United States of America. [ABSTRACT FROM AUTHOR]

With the advent of cryptocurrencies and blockchain, the growth and adaptation of cryptographic features and capabilities were quickly extended to new and underexplored areas, such as healthcare. Currently, blockchain is being implemented mainly as a mechanism to secure Electronic Health Records (EHRs). However, new studies have shown that this technology can be a powerful tool in empowering patients to control their own health data, as well for enabling a fool-proof health data history and establishing medical responsibility. Additionally, with the proliferation of mobile health (m-Health) sustained on service-oriented architectures, the adaptation of blockchain mechanisms into m-Health applications creates the possibility for a more decentralized and available healthcare service. Hence, this paper presents a review of the current security best practices for m-Health and the most used and widely known implementations of the blockchain protocol, including blockchain technologies in m-Health. The main goal of this comprehensive review is to further discuss and elaborate on identified open-issues and potential use cases regarding the uses of blockchain in this area. Finally, the paper presents the major findings, challenges and advantages on future blockchain implementations for m-Health services and applications. [ABSTRACT FROM AUTHOR]

Internet-delivered intervention may be an acceptable alternative for the more than 90% of problem gamblers who are reluctant to seek face-to-face support. Thus, we aimed to (1) develop a low-dropout unguided intervention named GAMBOT integrated with a messaging app; and (2) investigate its effect. The present study was a randomised, quadruple-blind, controlled trial. We set pre-to-post change in the Problem Gambling Severity Index (PGSI) as the primary outcome and pre-to-post change in the Gambling Symptom Assessment Scale (G-SAS) as a secondary outcome. Daily monitoring, personalised feedback, and private messages based on cognitive behavioural theory were offered to participants in the intervention group through a messaging app for 28 days (GAMBOT). Participants in the control group received biweekly messages only for assessments for 28 days (assessments only). A total of 197 problem gamblers were included in the primary analysis. We failed to demonstrate a significant between-group difference in the primary outcome (PGSI − 1.14, 95% CI − 2.75 to 0.47, p = 0.162) but in the secondary outcome (G-SAS − 3.14, 95% CI − 0.24 to − 6.04, p = 0.03). Only 6.7% of the participants dropped out during follow-up and 77% of the GAMBOT group participants (74/96) continued to participate in the intervention throughout the 28-day period. Integrating intervention into a chatbot feature on a frequently used messaging app shows promise in helping to overcome the high dropout rate of unguided internet-delivered interventions. More effective and sophisticated contents delivered by a chatbot should be sought to engage over 90% of problem gamblers who are reluctant to seek face-to-face support. [ABSTRACT FROM AUTHOR]

Purpose of Review: This review discusses how wearable devices—sensors externally applied to the body to measure a physiological signal—can be used in heart failure (HF) care. Recent Findings: Most wearables are marketed to consumers and can measure movement, heart rate, and blood pressure; detect and monitor arrhythmia; and support exercise training and rehabilitation. Wearable devices targeted at healthcare professionals include ECG patch recorders and vests, patches, and textiles with in-built sensors for improved prognostication and the early detection of acute decompensation. Integrating data from wearables into clinical decision-making has been slow due to clinical inertia and concerns regarding data security and validity, lack of evidence of meaningful impact, interoperability, regulatory and reimbursement issues, and legal liability. Summary: Although few studies have assessed how best to integrate wearable technologies into clinical practice, their use is rapidly expanding and may support improved decision-making by patients and healthcare professionals along the whole patient pathway. [ABSTRACT FROM AUTHOR]

Recent advances in wearable sensor technology and smartphones enable simple and affordable collection of personal analytics. This paper reflects on the lessons learned in the SWELL project that addressed the design of user-centered ICT applications for self-management of vitality in the domain of knowledge workers. These workers often have a sedentary lifestyle and are susceptible to mental health effects due to a high workload. We present the sense–reason–act framework that is the basis of the SWELL approach and we provide an overview of the individual studies carried out in SWELL. In this paper, we revisit our work on reasoning: interpreting raw heterogeneous sensor data, and acting: providing personalized feedback to support behavioural change. We conclude that simple affordable sensors can be used to classify user behaviour and heath status in a physically non-intrusive way. The interpreted data can be used to inform personalized feedback strategies. Further longitudinal studies can now be initiated to assess the effectiveness of m-Health interventions using the SWELL methods. [ABSTRACT FROM AUTHOR]

Background: This study evaluates the accuracy of an automated classification tool of single attacks of the two major primary headache disorders migraine and tension-type headache used in an electronic headache diary. Methods: One hundred two randomly selected reported headache attacks from an electronic headache-diary of patients using the medical app M-sense were classified by both a neurologist with specialisation in headache medicine and an algorithm, constructed based on the ICHD-3 criteria for migraine and tension-type headache. The level of agreement between the headache specialist and the algorithm was compared by using a kappa statistic. Cases of disagreement were analysed in a disagreement validity assessment. Result: The neurologist and the algorithm classified migraines with aura (MA), migraines without aura (MO), tension-type headaches (TTH) and non-migraine or non-TTH events. Of the 102 headache reports, 86 cases were fully agreed on, and 16 cases not, making the level of agreement unweighted kappa 0.74 and representing a substantial level of agreement. Most cases of disagreement (12 out of 16) were due to inadvertent mistakes of the neurologist identified in the disagreement validity assessment. The second most common reason (3 out of 16) was insufficient information for classification by the neurologist. Conclusions: The substantial level of agreement indicates that the classification tool is a valuable instrument for automated evaluation of electronic headache diaries, which can thereby support the diagnostic and therapeutic clinical processes. Based on this study's results, additional diagnostic functionalities of primary headache management apps can be implemented. Finally, future research can use this classification algorithm for large scale database analysis for epidemiological studies. [ABSTRACT FROM AUTHOR]

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Purpose of Review: Out-of-office blood pressure (BP) monitoring techniques, including home and ambulatory BP monitoring, are currently recommended by hypertension guidelines worldwide to confirm the diagnosis of hypertension and to monitor the appropriateness of treatment. However, such techniques are not always effectively implemented or timely available in the routine clinical practice. In recent years, the widespread availability of e-health solutions has stimulated the development of blood pressure telemonitoring (BPT) systems, which allow remote BP tracking and tighter and more efficient monitoring of patients' health status. Recent Findings: There is currently strong evidence that BPT may be of benefit for hypertension screening and diagnosis and for improving hypertension management. The advantage is more significant when BPT is coupled with multimodal interventions involving a physician, a nurse or pharmacist, and including education on lifestyle and risk factors and drug management. Several randomized controlled studies documented enhanced hypertension management and improved BP control of hypertensive patients through BPT. Potential additional effects of BPT are represented by improved compliance to treatment, intensification, and optimization of drug use, improved quality of life, reduction in risk of developing cardiovascular complications, and cost-saving. Applications based on m-health and making use of wearables or smartwatches integrated with machine learning models are particularly promising for the future development of efficient BPT solutions, and they will provide remarkable support decision tools for doctors. Summary: BPT and telehealth will soon disrupt hypertension management. However, which approach will be the most effective and whether it will be sustainable in the long-term still need to be elucidated. [ABSTRACT FROM AUTHOR]

Purpose Of Review: To summarize the latest evidence about mobile phone applications for the management of depression.Recent Findings: Depression apps are very heterogeneous, given the absence of standards for their development, description, and evaluation. Randomized clinical trials show the effectiveness of some of these applications in reducing depressive symptoms. Attrition is an important issue whose evaluation is limited by the frequent use of incentives in the studies. The number of mobile applications for depression far exceeds the number of studies evaluating their efficacy and feasibility. Despite the limitations of the digital market, there are a small number of apps that have demonstrated sufficient effectiveness and tolerability to think of short-term clinical use. However, there are still barriers at different levels that may delay the implementation of these interventions in daily clinical practice. [ABSTRACT FROM AUTHOR]

This study examines the accessibility and mobile readiness of 25 of the top health information website homepages using mobile-readiness heuristics and an accessibility analysis based on a combination of automated and manual inspection of the website code. The paper also explores whether there might be a relationship between an organization meeting accessibility guidelines and an organization making its site mobile-ready and whether there is a difference between government and non-government website digital inclusiveness. The findings revealed that the overwhelming majority of the sites were at least partially mobile-ready, reformatting for a mobile screen, but that many of the sites violated critical accessibility guidelines. While non-government sites tended to be somewhat more mobile -ready, government sites were more likely to perform well when it came to accessibility testing. The results question whether health information providers are putting a higher priority on mobile-readiness than on accessibility to users with disabilities [ABSTRACT FROM AUTHOR]

Introduction: Patient Reported Outcomes have become standard in the evaluation of inguinal hernia repair. However, the chosen outcomes remain heterogeneous and the measurements time-consuming or inadequate. Perioperative measurement of pain and recovery could benefit from the contemporary possibilities that mobile health applications offer.Methods: An application for smartphones and tablets was developed using the twitch crowdsourcing concept, classical questionnaires, experiences from randomised clinical trials, and patients' input.Results: Dichotomous questions and numeric rating scales, both pre- and post-operative, were implemented in the freely available Q1.6 application. Content, timing and frequencies were adapted to the inguinal hernia patient's daily life and assumed recovery. Certain combinations of answers were set as alert notifications to detect adverse events. Data are displayed on a web-based dashboard enabling real-time monitoring. Legal aspects were examined and taken into account.Discussion: The Q1.6 inguinal hernia app is an innovative tool for perioperative monitoring of pain and recovery of inguinal hernia patients. Previous limitations of classical measurements such as a large heterogeneity, retrospective data recording and different forms of bias can be eliminated. The `big data´ generated in this manner might be used for large-scale research to improve inguinal hernia surgery. The Q1.6 platform is not only hernia specific; it is also an innovative tool to measure PROs in any other domain. [ABSTRACT FROM AUTHOR]

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Copyright of Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Depression is common in attention-deficit/hyperactivity disorder (ADHD), but preventive behavioural interventions are lacking. This randomised controlled, pilot phase-IIa trial aimed to study a physical exercise intervention (EI) and bright light therapy (BLT)—both implemented and monitored in an individual, naturalistic setting via a mobile health (m-health) system—for feasibility of trial design and interventions, and to estimate their effects on depressive symptoms in young people with ADHD. Two hundred seven participants aged 14–45 years were randomised to 10-week add-on intervention of either BLT (10,000 lx; daily 30-min sessions) (n = 70), EI (aerobic and muscle-strengthening activities 3 days/ week) (n = 69), or treatment-as-usual (TAU) (n = 68), of whom 165 (80%) were retained (BLT: n = 54; EI: n = 52; TAU: n = 59). Intervention adherence (i.e. ≥ 80% completed sessions) was very low for both BLT (n = 13, 22%) and EI (n = 4, 7%). Usability of the m-health system to conduct interventions was limited as indicated by objective and subjective data. Safety was high and comparable between groups. Changes in depressive symptoms (assessed via observer-blind ratings, Inventory of Depressive Symptomatology) between baseline and end of intervention were small (BLT: −0.124 [95% CI: −2.219, 1.971], EI: −2.646 [95% CI: −4.777, −0.515], TAU: −1.428 [95% CI: −3.381, 0.526]) with no group differences [F(2,153) = 1.45, p = 0.2384]. These findings suggest that the m-health approach did not achieve feasibility of EI and BLT in young people with ADHD. Prior to designing efficacy studies, strategies how to achieve high intervention adherence should be specifically investigated in this patient group.ClinicalTrials.gov, NCT03371810, 13 December 2017.Trial registration: Depression is common in attention-deficit/hyperactivity disorder (ADHD), but preventive behavioural interventions are lacking. This randomised controlled, pilot phase-IIa trial aimed to study a physical exercise intervention (EI) and bright light therapy (BLT)—both implemented and monitored in an individual, naturalistic setting via a mobile health (m-health) system—for feasibility of trial design and interventions, and to estimate their effects on depressive symptoms in young people with ADHD. Two hundred seven participants aged 14–45 years were randomised to 10-week add-on intervention of either BLT (10,000 lx; daily 30-min sessions) (n = 70), EI (aerobic and muscle-strengthening activities 3 days/ week) (n = 69), or treatment-as-usual (TAU) (n = 68), of whom 165 (80%) were retained (BLT: n = 54; EI: n = 52; TAU: n = 59). Intervention adherence (i.e. ≥ 80% completed sessions) was very low for both BLT (n = 13, 22%) and EI (n = 4, 7%). Usability of the m-health system to conduct interventions was limited as indicated by objective and subjective data. Safety was high and comparable between groups. Changes in depressive symptoms (assessed via observer-blind ratings, Inventory of Depressive Symptomatology) between baseline and end of intervention were small (BLT: −0.124 [95% CI: −2.219, 1.971], EI: −2.646 [95% CI: −4.777, −0.515], TAU: −1.428 [95% CI: −3.381, 0.526]) with no group differences [F(2,153) = 1.45, p = 0.2384]. These findings suggest that the m-health approach did not achieve feasibility of EI and BLT in young people with ADHD. Prior to designing efficacy studies, strategies how to achieve high intervention adherence should be specifically investigated in this patient group.ClinicalTrials.gov, NCT03371810, 13 December 2017. [ABSTRACT FROM AUTHOR]

In recent years, the UK's emergency call and response has shown elements of great strain as of today. The strain on emergency call systems estimated by a 9 million calls (including both landline and mobile) made in 2014 alone. Coupled with an increasing population and cuts in government funding, this has resulted in lower percentages of emergency response vehicles at hand and longer response times. In this paper, we highlight the main challenges of emergency services and overview of previous solutions. In addition, we propose a new system call Smart Hospital Emergency System (SHES). The main aim of SHES is to save lives through improving communications between patient and emergency services. Utilising the latest of technologies and algorithms within SHES is aiming to increase emergency communication throughput, while reducing emergency call systems issues and making the process of emergency response more efficient. Utilising health data held within a personal smartphone, and internal tracked data (GPU, Accelerometer, Gyroscope etc.), SHES aims to process the mentioned data efficiently, and securely, through automatic communications with emergency services, ultimately reducing communication bottlenecks. Live video-streaming through real-time video communication protocols is also a focus of SHES to improve initial communications between emergency services and patients. A prototype of this system has been developed. The system has been evaluated by a preliminary usability, reliability, and communication performance study. [ABSTRACT FROM AUTHOR]

Key Summary Points: Aim: This paper describes and evaluates an m-health application that allows cognitive functions to be tested. Findings: Using speech-processing techniques an Android application of a slightly modified Mini Mental state Examination (MMSE) test was developed. A small-scale pilot study was conducted in a nursing home showing comparable scores between the MMSE app and the (paper) MMSE test. Message: A mobile digital version of the slightly modified MMSE test has the potential to be used as an attractive alternative for the conventional paper version of the test. Purpose: This paper describes an implementation of an Android application that allows cognitive functions to be tested. Methods: The application consists of a slightly modified Mini Mental state Examination (MMSE) test that provides examiner assistance in diagnosing cognitive impairments. The application deploys speech recognition techniques to allow easy and automated scoring of the test. The test results and test-related information are stored in a database providing easy access to data for follow-up and analysis, resulting in overall benefits to the examiner workflow. A small-scale pilot study of 5 months duration was conducted in a nursing home where 15 residents were tested with the MMSE app test and with the (paper) MMSE test with the aim of determining the agreement between the two test methods. Results: The final MMSE test scores, with a maximum score of 30, agree; the differences have a mean of 0.1, a standard deviation of 2.1 and fall in a [− 4, + 4] range as is illustrated in a Bland–Altman analysis. From examiner reflections, the motoric skills of the participant are indicated to contribute strongly to the time benefit of the assessment itself. Conclusions: The findings of this study suggest that the mobile digital version of the slightly modified MMSE test has the potential to be used as an attractive alternative for the conventional paper version of the test. [ABSTRACT FROM AUTHOR]

Background: Arrhythmias and heart failure are common and invalidating sequelae in adult patients with congenital heart disease (CHD). Mobile health (m-Health) enables daily monitoring and a timely response that might prevent deterioration. We present an observational prospective registry to evaluate feasibility of an m‑Health telemonitoring program for managing arrhythmia, heart failure and blood pressure in symptomatic adults with CHD.Methods: Symptomatic adult patients with CHD are enrolled in an m‑Health telemonitoring program, which evaluates single-lead ECG, blood pressure and weight measurements. In case of symptoms extra measurements could be performed. Data are collected by mobile apps, matched with individualised thresholds. Patients are contacted if thresholds were exceeded or if arrhythmias were found, for treatment adjustments or reassurance. Data on emergency care utilisation, hospitalisation and patient-reported outcome measures are used to assess quality of life and self-management.Results: 129 symptomatic CHD patients were invited to participate, 55 participated. Reasons for refusing consent included too time consuming to participate in research (30) and to monitor vital signs (14). At baseline 22 patients were in New York Heart Association class ≥ II heart failure, 43 patients had palpitations or documented arrhythmias, and 8 had hypertension. Mean follow-up was 3.0 months, one patient dropped out, and adherence was 97%.Conclusion: The first results indicate that this program is feasible with high adherence. [ABSTRACT FROM AUTHOR]

Among the extensive and impressive collection of applications enabled by IoT, smart and interactive healthcare is a particularly important one. To gather rich information indicator of our mental and physical health, IoT based sensors are either worn on the body or embedded in the living environment. Moreover, by incorporating the mobile computing technology in IoT based healthcare systems, the reactive care system can be transformed to proactive and preventive healthcare systems. Relative to this context, a cloud-centric IoT based smart student m-healthcare monitoring framework is proposed. This framework computes the student diseases severity by predicting the potential disease with its level by temporally mining the health measurements collected from medical and other IoT devices. To effectively analyze the student healthcare data, an architectural model for smart student health care system has been designed. In our case study, health dataset of 182 suspected students are simulated to generate relevant waterborne diseses cases. This data is further analyzed to validate our model by using k-cross validation approach. Pattern based diagnosis scheme is applied using various classification algorithms and then results are computed based on accuracy, sensitivity, specificity and response time. Experimental results show that Decision tree (C4.5) and k-neighest neighbour algorithms perform better as compared to other classifiers in terms of above mentioned parameters. Moreover, the proposed methodology is effective in decision making by delivering time sensitive information to caretaker or doctor within specific time. Lastly, the temporal granule pattern based presentation reterives effective diagnosis results for the proposed system. [ABSTRACT FROM AUTHOR]

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Although several hundreds of apps are available that (cl)aim to promote mindfulness, only a few methodologically sound studies have evaluated the efficacy of these apps. This randomized waiting-list controlled trial therefore tested the hypothesis that one such app (the VGZ Mindfulness Coach) can achieve immediate and long-term improvements of mindfulness, quality of life, general psychiatric symptoms, and self-actualization. One hundred ninety-one experimental participants received the VGZ Mindfulness Coach, which offers 40 mindfulness exercises and background information about mindfulness without any form of therapeutic guidance. Compared to 186 control participants, they reported large (Cohen's d = 0.77) and statistically significant increases of mindfulness after 8 weeks and small-to-medium increases of the Observing, Describing, Acting with awareness, Nonjudging, and Nonreactivity mindfulness facets as measured with the Five Facet Mindfulness Questionnaire (Cohen's d = 0.66, 0.26, 0.49, 0.34, and 0.43, respectively). Also, there were large decreases of general psychiatric symptoms (GHQ-12; Cohen's d = −0.68) and moderate increases of psychological, social, and environmental quality of life (WHOQOL-BREF; Cohen's d = 0.38, 0.38, and 0.36, respectively). Except for social quality of life, these gains were maintained for at least 3 months. We conclude that it is possible to achieve durable positive effects on mindfulness, general psychiatric symptoms, and several aspects of quality of life at low costs with smartphone apps for mindfulness such as the VGZ Mindfulness Coach. [ABSTRACT FROM AUTHOR]

Even with the adoption of modern technology within the medical system, the spread of deadly pathogens remains a silent, yet deadly killer. Indeed, e-health, and in particular m-health is at the forefront of the computing portion of modern medical care. It follows the ubiquity of mobile computing devices that has become synonymous with modern life. Although the focus of m-health is patient based, this paper attempts to provide a focus on the healthcare service provider in an attempt to reduce the fatalities due to pathogen transmissions in care facilities. This paper proposes, and describes the creation and evaluation of an AI based context-aware mobile learning system designed to provide real-time training and support for medical cleaning staff. This learning system aims to bridge the gap between context-aware learning systems and m-health. As such, the system provides context information to the learner about the various threats and best ways to deal with possible pathogens in a long-term care scenario. The evaluation, field tested within the adult long-term care system demonstrates the benefit and validity of the system in both training and ongoing usage within the medical system. [ABSTRACT FROM AUTHOR]

Purpose: Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. Method: Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. Results: Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. Conclusion: We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed. [ABSTRACT FROM AUTHOR]

Electronic processes and communication technologies are more and more often employed to provide healthcare services to caregivers and their patients. Such solutions are currently referred as e-health, the most popular and widely distributed being those based on telemedicine and mobile health (m-health). A specific application of telemedicine for hypertension management is blood pressure telemonitoring (BPT), which allows remote data transmission of BP and additional information on patients' health status from their living site or from a community setting to the doctor's office or the hospital. Several randomized studies have documented a significant BP reduction with regular BPT compared to usual care, particularly in high risk hypertensive patients. Additional benefits are observed when BPT is offered under the supervision of a team of healthcare professionals, including a community pharmacist. BPT may also be provided in the context of m-health solutions, which commonly include wireless diagnostic and clinical decision support tools. M-health has the potential to promote patient's self-management, as a complement to the doctor's intervention, and encourage greater participation in medical decision making. Current statistics show that half of smartphone owners gather health information through their phone and 19 % use a health app. In case of hypertensive patients the most popular apps are those with tracking function, including BPT. Thus, e-health, and in particular BPT and m-health, are progressively gaining a key role in the management of hypertensive patients, having the potential to improve the quality of the delivered care and to more effectively prevent cardiovascular consequences of high BP. [ABSTRACT FROM AUTHOR]