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Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.
JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, and Science Citation Index Expanded (SCIE), and in June 2018 received an Impact Factor of 4.541, which ranks the journal #2 (behind JMIR) out of 25 journals in the medical informatics category indexed by the Science Citation Index Expanded (SCIE) by Thomson Reuters/Clarivate.
The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.
JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
JMIR mHealth and uHealth features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.
JMIR mHealth and uHealth adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.
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Background: The incidence and degree of cancer pain often progresses in discharged patients because of discontinued standard treatments and reductions in medication compliance. Motivated by the need f...
Background: The incidence and degree of cancer pain often progresses in discharged patients because of discontinued standard treatments and reductions in medication compliance. Motivated by the need for better pain management in discharged patients, our research team developed a mobile phone application (Pain Guard) for providing continuous treatment for discharged patients suffering from pain. Objective: We aimed to design, construct, and test the Pain Guard in patients managing cancer pain, and evaluate the total remission rate of pain and improvement in quality of life (QoL), in order to realize convergence management of patients within and outside the hospital. The system’s usability, feasibility, compliance, and satisfaction were also assessed. Methods: This randomized controlled double-arm study involved 58 patients with cancer pain symptoms. Participants were randomly assigned into the group receiving care through the Pain Guard and the control group receiving only traditional pharmaceutical care. In a pretest, participants were rated using a baseline cancer pain assessment and QoL evaluation. During treatment, the consumption levels of analgesic drugs were recorded every week. After a 4-week study period, another round of cancer pain assessment and QoL evaluation was conducted. Our primary outcome was remission rate of pain, and secondary outcomes were compliance with medication, improvements in QoL, frequency of breakthrough cancer pain (BTcP), incidence of adverse reactions, and satisfaction of patients. Results: All participants (58 patients) successfully completed the study. There were no significant differences in baseline pain score or baseline QoL scores between groups (P>0.1). At the end of the study, the rate of pain remission in the trial group was significantly higher than that in the control group (P<0.01). The frequency of BTcP in the trial group was considerably lower than that in the control group (P<0.01). The rate of medication compliance in the trial group was considerably higher than that in the control group (P<0.01). Improvements in QoL scores in the trial group were also significantly higher than those in the control group (P<0.01). The incidence of adverse reactions in the trial group (7/31) was much lower than that in the control group (12/27). The 31 participants in the trial group completed a satisfaction survey regarding Pain Guard: 23 (74%) indicated that they were satisfied with receiving pharmaceutical care by Pain Guard, 8 (26%) indicated that they were somewhat satisfied, 2 (6%) indicated neutral feelings, 1 (3%) indicated that they were somewhat dissatisfied, and no participants indicated that they were very dissatisfied. Conclusions: Pain Guard can effectively resolve the management dislocation of patients with cancer pain at home, control pain steadily, reduce the incidence of adverse reactions, improve patient compliance, and significantly improve patients’ quality of life. Additionally, Pain Guard operability is good and easily accepted by patients. Clinical Trial: identifier: ChiCTR1800016066
Background: Use of mobile health (mHealth) applications (apps) in dietetic practice could support delivery of nutrition care in medical nutrition therapy. However, apps are underutilized by dietitians...
Background: Use of mobile health (mHealth) applications (apps) in dietetic practice could support delivery of nutrition care in medical nutrition therapy. However, apps are underutilized by dietitians in patient care. Objective: This study aimed to determine the feasibility of an intervention, comprising of education, training and integration of apps, in improving dietitians’ perceived self-efficacy with using mHealth apps. Methods: Private practice Accredited Practising Dietitians who were not regular users or recommenders of mHealth apps were recruited into the intervention. The intervention consisted of two phases: 1) a workshop that incorporated an educational lecture and skill building activities to target self-efficacy, capability, opportunity and motivation factors; 2) 12-week intervention phase allowing for the integration of an app into dietetic practice via an app platform. During the 12-week intervention phase, dietitians prescribed an Australian commercial nutrition app to new (intervention) patients receiving nutrition care. Existing (control) patients were also recruited to provide a measure of patient satisfaction before the apps were introduced. New patients completed their patient satisfaction surveys at the end of the 12 weeks. Usability feedback about the app and app platform were gathered from intervention patients and dietitians. Results: Five dietitians participated in the study. The educational and skills training workshop component of the intervention produced immediate significant improvements in dietitians’ mHealth app self-efficacy compared to baseline (P=.02), particularly with regards to ‘familiarity with apps’ factor (P<.001). The self-efficacy factor ‘integration into dietetic work systems’ achieved significant improvements from baseline to 12 weeks (P=.03). Patient satisfaction with dietetic services did not differ significantly between intervention (n=17) and control patients (n=13). Overall, dietitians and their patients indicated they would continue using the app platform and app respectively, and would recommend it to others. To improve usability, enhancing patient-dietitian communication mediums in the app platform and reducing the burden of entering in meals cooked at home should be considered. Conclusions: Administering an educational and skills training workshop in conjunction with integrating an app platform into dietetic practice were feasible methods for improving the self-efficacy of dietitians towards using mHealth apps. Further translational research will be required to determine how the broader dietetic profession respond to this intervention.
Background: Patient Generated Health Data (PGHD) is any clinically relevant data collected by patients or their carers (consumers) that may contribute to better health care outcomes. Patient generated...
Background: Patient Generated Health Data (PGHD) is any clinically relevant data collected by patients or their carers (consumers) that may contribute to better health care outcomes. Patient generated health data, like patient reported outcome and patient experience measures, reflect the consumers perspective, promote patient centricity and can improve partnership with healthcare providers. Objective: The use of the data is also believed to encourage enhanced patient engagement and thus foster a therapeutic partnership with the healthcare provider. The aim of this study is to further identify how PGHD is used by consumers and how it influences their engagement. Methods: Study 1 used vignette-led interviews with patients, carers and doctors to test attitudes, perceptions and beliefs about the PGHD. Study 2 was a pilot trial with parents of children undergoing laparoscopic appendectomy. Parents were asked to generate post-operative surgical site photographs for 10 days and were then interviewed to deepen the understanding of parental engagement. Across both studies, interviews (n=60) were analysed to identify the themes and these were contrasted for notable differences. Results: When viewed holistically from the patient perspective PGHD can instigate an ecosystem of engagement providing clinicians with an extended view into the patient’s world. This paper proposes and validates an ‘ontological’ framework based on engagement literature which defines that categorises PGHD clarified by healthcare providers, patients and carers. A framework for understanding PGHD involves 11 themes organised into four domains; physiological, cognitive, emotional and behavioural. PGHD use is interconnected and complex but can engage and empower patients. PGHD increases reassurance, improves communication, aids sense making and can result in consumers taking on greater personal responsibility for their healthcare outcomes. Conclusions: This research demonstrates that in addition to the potential for enhanced clinical diagnosis and efficient use of healthcare resources, patient generated health data offers patients meaningful partnership with clinicians and a method of emotional empowerment, improving confidence and satisfaction in the service. Clinical Trial: ANZCTR: ACTRN12616000998448
Background: Tuberculosis (TB) management can be challenging in low- and middle- income countries (LMICs) not only due to its high burden, but also the prolonged treatment period involving multiple dru...
Background: Tuberculosis (TB) management can be challenging in low- and middle- income countries (LMICs) not only due to its high burden, but also the prolonged treatment period involving multiple drugs. With the rapid development in mobile technology, mHealth (Mobile Health) or using mobile device for TB has gained popularity. Despite the potential usefulness of mHealth for TB, few studies have quantitatively synthesized evidence on its effectiveness, presumably due to variability in outcome measures reported in the literature. Objective: The aim of this systematic review was to evaluate the outcome measures reported in TB mHealth literature in LMICs Methods: MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews were searched to identify mHealth intervention studies for TB (published up to May 2018) which reported any type of outcome measures. Extracted information included the study setting, types of mHealth technology used, target population, study design, and categories of outcome measures. Outcomes were classified into 13 categories including treatment outcome, adherence, process measure, perception, technical outcome, and so on. The qualitative synthesis of evidence focused on the categories of outcome measures reported by type of mHealth interventions. Results: A total of 27 studies were included for the qualitative synthesis of evidence. The study designs varied widely, ranging from randomized controlled trials (RCTs) to economic evaluations. Most studies adopted short message service (SMS), while others used SMS in combination with additional technologies or mobile applications. The study population was also diverse including TB patients, TB/HIV patients, healthcare workers and general patients attending a clinic. There was a wide range of variations in the definition of outcome measures across the studies. Amongst the diverse categories of outcome measures, treatment outcomes have been reported in most of the studies, but only a few studies measured the outcome according to the standard TB treatment definitions by the World Health Organization. Conclusions: This critical evaluation of outcomes reported in mHealth studies for TB management suggests that substantial variability exists in reporting the outcome measures. To overcome challenges in evidence synthesis for mHealth interventions, this study can provide insights into the development of a core sets of outcome measures by intervention type and study design.
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Background: All over the world the increasing prevalence of age-related disorders such as Alzheimer’s disease (AD) and frailty and its impact on functional decline is challenging the sustainability...
Background: All over the world the increasing prevalence of age-related disorders such as Alzheimer’s disease (AD) and frailty and its impact on functional decline is challenging the sustainability of health care systems. In the field of AD and related disorders, Information and Communication technologies (ICT) showed promising results in improving clinical assessment and implementing interventions to delay functional decline and decrease the burden of behavioral symptoms. Objective: The SafEE (Safe Easy Environment) project, is a collaborative French-Taiwanese project aiming to develop: 1/ an ICT-based behavior analysis platform able to automatically detect, recognize and assess daytime and nighttime behavioral patterns, and 2/ adapted tailored non pharmacological interventions. Partners of the projects include clinicians, research engineers and industrials. Methods: This study was designed as a randomized controlled trial. We recruited 3 patients with cognitive frailty syndrome [≥ 60 years, MMSE ≥ 26, CDR ≤ 0.5] randomized either to the intervention group (ICT-based therapeutic solutions, N=1) or to the control group (care as usual, N=2). The 6-month intervention included detection of daytime and nighttime behaviors based on 2D and 3D video cameras (for both groups), and tailored therapeutic solutions based on serious-games, aromatherapy and music therapy for the intervention group. The primary outcome is the acceptability of the solutions measured by the frequency of use and self-reports. The secondary outcome is the solution efficacy, measured by the results on neuropsychological tests. Results: This project made it possible to develop a communicating platform between the automatic recognition of activity and the non-pharmacological solutions developed. This platform is thus able to 1) provide healthcare professionals with continuous feedback on immediate and long-term risk events; 2) Automatically combine an online assessment with non-pharmacological interventions that can act on the detected disorders; 3) obtain relevant information in the context of an early diagnosis at home of frail people at risk of developing Alzheimer's disease. Conclusions: Building a global system aiming to detect and prevent loss of autonomy in frail people is a rather complicated task, involving numerous ICT solutions which are not always easy to use in everyday life. The innovation of the project lies in a new methodological approach to deal with care of elderly people, based on an innovative use of ICT based on the association of assessment and intervention for specific cognitive and behavioral patterns. The results of this trial may have important implications for future interventions, and provide relevant information for the general transferability of this platform as part of the AD prevention. Clinical Trial: ClinicalTrials.gov, NCT02288221. First received: August 19, 2014. Last updated: November 7, 2014. Last verified: June 2014.
Background: Nonadherence to self-management is common among patients with type 2 diabetes (T2D) and often leads to severe complications. Short messages service (SMS) technology provides a practical me...
Background: Nonadherence to self-management is common among patients with type 2 diabetes (T2D) and often leads to severe complications. Short messages service (SMS) technology provides a practical medium for delivering content to address patients’ barriers to adherence. Objective: The aim of this study was to design a series of SMS intervention templates, and to evaluate the feasibility of the SMS through a short message quality evaluation questionnaire and to explore the intervention effect. Methods: 1. The SMS evaluation was assessed through the 10-point scale SMS Quality Assessment Questionnaire. 2. A randomized controlled trial was conducted. The patients in SMS intervention were randomly divided into intervention group (IG) and control group (CG), which received evaluated messages education and regular education, respectively. The intervention was divided into four phases, a telephone interview was conducted to evaluate the effectiveness of the intervention after each phase. The main outcome were changes in blood glucose and blood pressure (BP) and their control rates, and secondary outcomes were changes in diet, physical activity, weight control and other health-related behaviors. Results: 1. SMS design: 42 SMS text messages were designed to promote healthy behaviors in different stages of behavior change, covering four key domains: healthy knowledge, diet, physical activity, living habits and weight control. 2. SMS evaluation: The average score for healthy knowledge, diet, physical activity, living habits, weight control were 8.0 (SD 0.7), 8.5 (SD 0.6), 7.9 (SD 1.0), 8.0 (SD 0.7), and 8.4 (SD 0.9), respectively. 3. SMS intervention: A total of 146 people completed the four-phase intervention, including 72 in the CG and 74 in the IG. At the end of the intervention period, in the IG, the decrease in fasting blood glucose (FBG, mean 1.5mg/l [SD 3.0] vs 0.4 mg/l [SD 2.8], P=0.011), postprandial blood glucose (PBG, mean 5.8mg/l [SD 5.1] vs 4.2 mg/l [SD 4.7], P=0.028), systolic blood pressure (SBP, mean 9.1mmHg [SD 15.8] vs 2.2mmHg [SD 13.3], P=0.025), FBG control rate (45.9% vs 31.0%, P=0.046) and PBG control rate (57.8% vs 33.7%, P=0.002) were better than the CG. In self-behavior management, the changes of the weight control, diet and physical activity in the IG were better than those in the CG, and the average score of the IG was greater than that of the CG (1.1 vs [-0.3] ), P0.001). Conclusions: The overall quality of SMS content is higher to meet the needs of patients; Diet, physical activity and weight control message need to be focused on push. SMS interventions contribute to the management of blood glucose and BP, and help to promote a series of healthy-related behaviors.