Effectiveness of mobile health-based self-management application for posttransplant cares: A systematic review

BACKGROUND AND AIMS

Patients after transplantation need medical management for the rest of their lives, and self-management seems to lead to greater adherence to medical standards, improve early physical changes, and increase patient empowerment. The main objective of this article is to systematic review of the consideration to mobile health applications (m-Health apps) used in transplantation.

METHODS

A systematic search was conducted MEDLINE (through PubMed), Web of Science, Scopus, and Science Direct from inception to November 2020. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement was used in this study. Comprehensive research was carried out using a combination of keywords and MeSH terms associated with m-Health, empowerment, self-management, and transplantation. Two independent reviewers screened titles and abstracts, assessed full-text articles, and extracted data from articles that met inclusion criteria. Eligible studies were original research articles that included posttransplant care and mobile phone-based applications to support self-management and self-care. Also, thesis, book chapters, letters to editors, short briefs, reports, technical reports, book reviews, systematic reviews, or meta-analysis were excluded.

RESULTS

We divided all the reviewed articles into four categories, self-management (medication adherence, adherence to medical regimen, and remote monitoring), evaluation, interaction, and interface; 37.5% of the studies were focused on lung transplantation. In 56.25% of the studies, medication adherence was considered because one of the main reasons for the rejection and graft loss is stated medication nonadherence. Also, 62.5% of the studies demonstrated that the use of m-health improved medication adherence and self-management in transplantation.

CONCLUSIONS

The use of m-Health apps interventions to self-management after transplantation has shown promising feasibility and acceptability, and there is modest evidence to support the efficacy of these interventions. We found that m-Health solutions can help the patient in self-management in many ways after transplantation.

Evaluation of m‐Health‐rehabilitation for respiratory disorders: A systematic review

Background and Aims

Chronic respiratory diseases are prominent causes of morbidity worldwide that impose significant social and economic burdens on individuals and communities. Pulmonary rehabilitation is one of the main aspects of medical rehabilitation. Nowadays, mobile health apps deliver pulmonary rehabilitation support via smartphones. This article presents a systematic review of the literature on m‐Health apps used in respiration disorders rehabilitation.

Methods

A systematic search was performed on MEDLINE (through PubMed), Web of Science, and Scopus in May 2021 without any date limitation. This study was using a combination of keywords and MeSH terms associated with pulmonary rehabilitation. Relevant studies were selected by two independents and were categorized studies results. The inclusion criterion was m‐Health apps for pulmonary rehabilitation and exclusion criteria mobile‐based interventions, by voice call or short message service and cardiopulmonary articles.

Results

Searching scientific databases yielded 161 relevant articles. Then, 27 articles were included in the study with a complete evaluation of the articles. Sixty percent of them were related to patients with chronic obstructive pulmonary disease (COPD). Rehabilitation aiming to improve the quality of life, promote self‐management, encourage physical activity, and reduce the symptoms as the most common goals of pulmonary rehabilitation using m‐Health apps; 89% of these studies showed that m‐Health apps can be effective in improving pulmonary rehabilitation. In addition, 37% of studies reported high usability and acceptance. However, the results of some studies show that adherence to apps decreases in the long run.

Conclusion

Our study shows that m‐Health pulmonary rehabilitation apps are effective in improving the quality of life, self‐management, and physical activity. According to the results, it seems that using the m‐Health apps for pulmonary rehabilitation can be useful in the COVID‐19 pandemic and help reduce respiratory disorders in patients with COVID‐19 disease.

Technical aspects of virtual augmented reality-based rehabilitation systems for musculoskeletal disorders of the lower limbs: a systematic review

INTRODUCTION

Musculoskeletal disorders are one of the most common causes of physical disability. The rehabilitation process after musculoskeletal disorders is long and tedious, and patients are not motivated to follow rehabilitation protocols. Therefore, new systems must be used to increase patient motivation. Virtual reality (VR) and augmented reality (AR) technologies can be used in this regard. In developing such systems, various technologies and methods of movement recognition are used; therefore, this study aims to summarize the technical aspects of using VR/AR in rehabilitation and evaluate and discuss efficient methods of investigating studies using the Statement of Standards for Reporting Implementation Studies (StaRI).

METHODS

Search in four scientific databases was done systematically based on PRISMA through online search engines from inception to June 2021. These databases include Medline (PubMed), Scopus, IEEE, and Web of Science. An updated search was also conducted on 17 December 2021. The research used keywords and MeSH terms associated with VR/AR, musculoskeletal disorder, and rehabilitation. Selected articles were evaluated qualitatively using the Standards for Reporting Implementation Studies (StaRI) statement.

RESULTS

A total of 2343 articles were found, and 20 studies were included. We found that 11 (55%) studies used Kinect technology as input tools, and 15 (75%) studies have described the techniques used to analyze human movements, such as dynamic time warping (DTW) and support vector machines (SVM). In 10 (50%) studies, the Unity game engine was used for visualization. In 8 studies (40%), usability was assessed, and high usability was reported. Similarly, the results of the review of studies according to the StaRI checklist showed poor reporting in the title and discussion of the studies.

CONCLUSIONS

We found that academic studies did not describe the technical aspects of rehabilitation systems. Therefore, a good description of the technical aspects of the system in such studies should be considered to provide repeatability and generalizability of these systems for investigations by other researchers.

Technical Requirement of Clinical Decision Support system for Diabetic Patients

Introduction: Diabetes is a public health problem which is originating an increment in the demand for health services. There is an obvious gap exists between actual clinical practice and optimal patient care, Clinical decision support systems (CDSSs) have been promoted as a promising approach that targets safe and effective diabetes management. The purpose of this article is reviewing diabetes decision support systems based on system design metrics, type and purpose of decision support systems. Materials and Methods: The literature search was performed in peer reviewed journals indexed in PubMed by keywords such as medical decision making, clinical decision support systems, Reminder systems, diabetes, interface, interaction, information to 2019. This article review the diabetes decision support systems based on system design metrics (interface, interaction, and information), type and purpose of decision support system. Results: 32 of the 35 articles were decision support systems that provided specific warnings, reminders, a set of physician guidelines, or other recommendations for direct action. The most important decisions of the systems were support for blood glucose control and insulin dose adjustment, as well as 13 warning and reminder articles. Of the 35 articles, there were 21 user interface items (such as simplicity, readability, font sizes and ect), 23 interaction items (such as Fit, use selection tools, facilitate ease of use and ect. ) and 31 item information items (such as Content guidance, diagnostic support and concise and ect ).Discussion: This study identified important aspects of designing decision support system, It can be applied not only to diabetic patients but also to other decision support systems.Conclusion: Most decision support systems take into account a number of design criteria; system designers can look at design aspects to improve the efficiency of these systems. Decision support system evaluation models can also be added to the factors under consideration.

A Comprehensive Tool for Usability Evaluation of Telehealth

INTRODUCTION

Telehealth has a high potential for delivering healthcare by overcoming the geographical distance, increased access to care, and efficiency. To obtain the potential benefits of telehealth, this system should be usable to the patients and healthcare providers. The aim of this study was to report a new comprehensive tool for assessing the usability of telehealth services and systems, covering different aspects of usability.

METHOD

We searched the keywords, such as telemedicine, telehealth, usability, satisfaction, questionnaires, and evaluation in Google, Scopus, PubMed, and Google Scholar from 1988 to 2019. All the studies that used the Telehealth services and computer& information technology evaluation tools were included.

RESULT

We identified 204 items and extracted 10 criteria that were classified into two categories. The first category is system usability, which includes Efficiency, Memorability, Learnability, Usefulness, and Satisfaction. Second category system reliability, included Interaction, Interface design, Saving, System capabilities, and Getting rid of Errors. This tool consider many aspects of telehealth service evaluation from the usability aspect.

CONCLUSION

Further studies are warranted to evaluate other aspects of Telehealth services and measuring reliability so that researchers can have access to a comprehensive tool for assessing interventions in the field of Telemedicine and Telehealth.