UNASSIGNED: Non-specific low back pain (NLBP) exerts a profound impact on global health and economics. In the era of Web 3.0, digital therapeutics offer the potential to improve NLBP management. The Rise-uP trial introduces a digitally anchored, general practitioner (GP)-focused back pain management approach with the Kaia back pain app as the key intervention. Here, we present the 12-months evaluation of the Rise-uP trial including clinical and economic outcomes, patient satisfaction and behavioral tracking analysis.
UNASSIGNED: The cluster-randomized controlled study (registration number: DRKS00015048) enrolled 1237 patients, with 930 receiving treatment according to the Rise-uP approach and 307 subjected to standard of care treatment. Assessments of pain, psychological state, functional capacity, and well-being (patient-reported outcome measures; PROMs) were collected at baseline, and at 3-, 6-, and 12-months follow-up intervals. Health insurance partners AOK, DAK, and BARMER provided individual healthcare cost data. An artificial intelligence (AI)-driven behavioral tracking analysis identified distinct app usage clusters that presented all with about the same clinical outcome. Patient satisfaction (patient-reported experience measures; PREMs) was captured at the end of the trial.
UNASSIGNED: Intention-to-treat (ITT) analysis demonstrated that the Rise-uP group experienced significantly greater pain reduction at 12 months compared to the control group (IG: -46% vs CG: -24%; p < 0.001) with only the Rise-uP group achieving a pain reduction that was clinically meaningful. Improvements in all other PROMs were notably superior in patients of the Rise-uP group. The AI analysis of app usage discerned four usage clusters. Short- to long-term usage, all produced about the same level of pain reduction. Cost-effectiveness analysis indicated a substantial economic benefit for Rise-uP.
UNASSIGNED: The Rise-uP approach with a medical multimodal back pain app as the central element of digital treatment demonstrates both, clinical and economic superiority compared to standard of care in the management of NLBP.

UNASSIGNED: Smartphone and mobile health (mHealth) applications (apps) have become an integral part of the day-to-day function of healthcare professionals, allowing quick, comprehensive, and up-to-date access to current clinical guidelines and other reference material.
UNASSIGNED: To evaluate the extent and nature of use of mHealth apps by paediatric department doctors in South Africa.
UNASSIGNED: E-mails requesting study participation were sent out to 285 paediatric department doctors employed at six hospitals affiliated to the University of the Witwatersrand. Willing participants were directed to complete the online study questionnaire.
UNASSIGNED: A total of 150 respondents completed the questionnaire. All respondents owned a mobile device and already had one or more mHealth apps, 95.3% were unaware of any regulatory body responsible for regulating the use of mHealth apps, 86.0% did not have access to free Wi-Fi at work and 87.3% used an mHealth app at least once daily. Drug dosing (81.3%), diagnostic (59.3%) and clinical decision-making (44.7%) apps were the most common app categories with Medscape® (62.0%) and EMGuidance® (41.3%) being the most frequently used apps. Peer recommendation (76.0%), app credibility (74.0%) and app functionality (66.0%) were the most common factors that were considered by respondents prior to downloading or using an mHealth app.
UNASSIGNED: Medical apps are frequently used among paediatric medical doctors of all ranks. Drug dosing, diagnostic and clinical decision-making apps are the most common app categories in use. Improved awareness of the regulations pertaining to the use of mHealth apps amongst doctors is required.

UNASSIGNED: To provide an overview of the digital mental health care landscape for individuals with spinal cord injury (SCI).
UNASSIGNED: PubMed, PsycInfo, and PSYNDEX were searched for articles meeting the following criteria: (1) article written in English or German; (2) digital psychosocial intervention; (3) SCI only; (4) treatment of individuals with SCI and not their relatives or caregivers. Records were screened by title and abstract and records meeting the inclusion criteria were obtained for full text screening. The references of identified articles were screened to find further relevant articles. The literature search was updated before submission. Risk of Bias was assessed by using the Cochrane risk-of-bias tool for randomized trials (RoB 2) and a narrative synthesis was conducted.
UNASSIGNED: Ten randomized-controlled trials (RCT) and ten non-randomized-controlled trials were identified and compared in this review, evaluating twelve internet- and mobile-based interventions, five smartphone apps, and three virtual reality applications. The interventions were primarily used as stand-alone aftercare programs. While some were not based on any theory, cognitive behavioral therapy mostly served as the theoretical basis for the online interventions. The extent of human support also varied greatly between the studies. The number of intervention modules ranged between 2 and 72. There were also major differences in outcome variables and effects. A meta-analytical evaluation of the data was not conducted due to heterogeneity of studies.
UNASSIGNED: Digital applications to promote the psychosocial health of individuals with SCI are an emerging field of research with many treatment approaches still to come. First high quality RCT studies report promising results. Unfortunately, not all studies are of high quality or the interventions have been insufficiently adapted to the needs of people with SCI. Therefore, more research is needed to further develop applications, and to generalize and test the effects found in the long term.

Background: Covert hepatic encephalopathy (CHE) is underdiagnosed and is difficult to detect. The EncephalApp Stroop test is validated for its screening. The aim of the study was to define Tunisian norms for the test based on healthy controls norms and to estimate the prevalence of CHE in cirrhotic Tunisian patients. Methods: A prospective, multicenter, cross-sectional study was conducted. Ambulatory or hospitalized cirrhotic patients aged 40 years and over were recruited at 11 centers. Healthy subjects aged 40 years and over were recruited at 8 centers. We used a translated Arabic version of the streamlined EncephalApp Stroop test. The task has two components: \"Off\" and \"On\" state depending on the discordance or concordance of the stimuli. Results: 142 patients were included. The mean age was 57.26 years [40-86]. 40 (28.17%) of cirrhotic patients who were included were diagnosed as having a minimal hepatic encephalopathy or CHE. Among the ineligible patients, 22 had overt hepatic encephalopathy. If we consider these patients, the overall prevalence rate of CHE was around 24.39% in cirrhotic patients. It was more frequent in women (34.21% vs 25.96%), and in patients whose level of school education is between 6 and 13 years. Its prevalence does not appear to be affected by gender, MELD score, etiology of cirrhosis and age group of patients, as these variables were independent with respective p according to the chi-square test 0.413; 0.736; 0.663 and 0.1. The stroop times (On / Off and On + Off) correlated significantly with each other, are associated significantly and positively with age (respective Pearson coefficients: 0.578; 0.567 and 0.6). The more the age increases, the more the stroop response times increases (p > 10 -3). Conclusions: EncephalApp Stroop test was an efficient screening tool for CHE in Tunisian cirrhotic patients.

UNASSIGNED: Artificial intelligence (AI) has been increasingly applied in various fields of science and technology. In line with the current research, medicine involves an increasing number of artificial intelligence technologies. The introduction of rapid AI can lead to positive and negative effects. This is a multilateral analytical literature review aimed at identifying the main branches and trends in the use of using artificial intelligence in medical technologies.
UNASSIGNED: The total number of literature sources reviewed is n = 89, and they are analyzed based on the literature reporting evidence-based guideline PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for a systematic review.
UNASSIGNED: As a result, from the initially selected 198 references, 155 references were obtained from the databases and the remaining 43 sources were found on open internet as direct links to publications. Finally, 89 literature sources were evaluated after exclusion of unsuitable references based on the duplicated and generalized information without focusing on the users.
UNASSIGNED: This article is identifying the current state of artificial intelligence in medicine and prospects for future use. The findings of this review will be useful for healthcare and AI professionals for improving the circulation and use of medical AI from design to implementation stage.

This study aimed at assessing the extent to which the general Saudi population has embraced digital health medical applications to meet their health-related needs so that the Saudi Ministry of Health and government can appropriately be guided on scaling up digital health across the country. As such, this study was guided by the question of to what extent the Saudi people use digital health mobile-based applications. This was a cross-sectional study utilizing snowballing sampling approach. Frequencies, Chi-square, and Spearman rank correlation statistics were used to offer descriptive and inferential analysis of the variables. The majority of the participants were economically able to afford smart devices that have medical apps, had at least an app on such devices, and highly regarded the benefits of the apps. Unfortunately, their understanding of how to use such apps was limited, and this posed a barrier to embracing digital health alongside difficulty downloading apps and medical ethical concerns. Although there is a willingness, extra effort is needed from the Saudi Ministry of Health and the government to promote the uptake of digital health in Saudi Arabia.

暂无摘要。

BACKGROUND: Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), metabolic syndrome as well as cardiovascular diseases. Against this background, mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM. Therefore, we analyzed the clinical effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes in mother and child.
METHODS: A systematic literature search in Medline (PubMed), Cochrane Library, Embase, CINAHL and Web of Science Core Collection databases as well as Google Scholar was performed. We selected studies published 2008 to 2020 analyzing women diagnosed with GDM using specific mHealth-Apps. Controlled clinical trials (CCT) and randomized controlled trials (RCT) were included. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool.
RESULTS: In total, n = 6 publications (n = 5 RCTs, n = 1 CCT; and n = 4 moderate, n = 2 weak quality), analyzing n = 408 GDM patients in the intervention and n = 405 in the control groups, were included. Compared to control groups, fasting blood glucose, 2-h postprandial blood glucose, off target blood glucose measurements, delivery mode (more vaginal deliveries and fewer (emergency) caesarean sections) and patient compliance showed improving trends.
CONCLUSIONS: mHealth-Apps might improve health-related outcomes, particularly glycemic control, in the management of GDM. Further studies need to be done in more detail.

Smartphones and mobile applications have seen a surge in popularity in recent years, a pattern that has also been reflected in the health care system. Despite increased reliance among clinicians however, limited research has been conducted on the uptake and impact of smartphone usage in medical practice, especially outside the Western world.
This study aimed to identify the usage of smartphones and medical apps by doctors in the clinical setting in 2 culturally distinct countries: King Hamad University Hospital (KHUH), Bahrain and Queen Mary Hospital (QMH), Hong Kong.
A cross-sectional, comparative study was conducted where doctors in both hospitals were asked to take part in a 15-item online survey. The questions were categorized into the following groups: demographics of the study population, ownership and main use of smartphones, number and names of medical apps currently owned, rating usage of smartphones for medical purposes, time spent on a smartphone related to clinical use, clinical reliance on smartphones, and views on further integration of smartphones. The results were then tabulated and analyzed using SPSS Statistics 25 for Mac (IBM Corp Inc, Armonk, NY).
A total of 200 doctors were surveyed, with a total of 99.0% (99/100) of the doctors owning a smartphone in both KHUH and QMH; 58% (57/99) and 55% (54/99) of the doctors from KHUH and QMH, respectively, identified communication as their main use of smartphones in the clinical setting (P=.004). Doctors from KHUH were likely to spend more time on medical apps than doctors from QMH (P=.002). According to the overall results of both hospitals, 48% (32/67) of the junior doctors claimed high reliance on smartphones, whereas only 32.3% (41/127) of the senior doctors said the same (P=.03). Of doctors in KHUH and QMH, 78.0% (78/100) and 69.0% (69/100), respectively, either strongly agreed or agreed that smartphones need to be integrated into the clinical setting. In terms of preferences for future apps, 48% (48/100) and 56% (56/100) of the doctors in KHUH and QMH, respectively, agreed that more medical applications need to be created in order to support smartphone use in the clinical setting.
These results suggest a substantial acceptance of smartphones by doctors in the clinical setting. It also elicits the need to establish policies to officially integrate smartphone technology into health care in accordance with ethical guidelines. More emphasis should be placed on creating medical applications that aid health care professionals in attaining their information from accurate sources and also regulate a system to monitor the usage of mobile devices within hospitals to prevent a breach of patient privacy and confidentiality.

According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited.
The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM.
A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c).
In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of -0.54% (95% CI -0.8 to -0.28) for T2DM and -0.63% (95% CI -0.93 to -0.32) for T1DM.
DM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.