Background: Mobile applications and social media serve their users as convenient tools to improve and monitor diseases and conditions such as pregnancy. These tools exert a positive impact on Gestational diabetes mellitus (GDM) self-management. Introduction: Despite the expansion of mobile health apps for the management of GDM, no study has evaluated these apps using a valid tool. This study aimed to search and review the apps developed for this purpose providing overall and specific rating scores for each aspect of MARS. Method: Two cases of app stores (IOS and Google Play) were searched in January 2019 for apps related to GDM. Search keywords included “gestational diabetes”, “pregnant diabetes”, and “Health apps”. Eligibility criteria include: capable of running on Android or IOS operating systems, in the English language, especially for GDM, and available in Iran. After removal of duplicates, then, they were reviewed, rated, and evaluated independently by two reviewers with Mobile App Rating Scale (MARS) tools. Results: Initially, 102 apps were identified after the exclusion process, five selected apps were downloaded and analyzed. All apps were classified into four categories according to contents and their interactive capabilities. In most quadrants of MARS, the Pregnant with Diabetes app received the highest scores. Also, in general, the maximum app quality mean score belonged to Pregnant with Diabetes (3.10 / 5.00). Conclusion: Findings revealed that apps designed for GDM are small in number and poor in quality based on MARS tools. Therefore, considering pregnant women’s need for using the capabilities of these apps in pregnancy management and promoting community-based care, it seems essential to develop and design a series of high-quality apps in all four specified categories (only giving comments, obtaining data and giving comments, diagnosis of GDM, and diet calculator).

AIMTo design a fuzzy expert system to help detect and diagnose the severity of diabetic neuropathy.METHODSThe research was completed in 2014 and consisted of two main phases. In the first phase, the diagnostic parameters were determined based on the literature review and by investigating specialists’ perspectives (n = 8). In the second phase, 244 medical records related to the patients who were visited in an endocrinology and metabolism research centre during the first six months of 2014 and were primarily diagnosed with diabetic neuropathy, were used to test the sensitivity, specificity, and accuracy of the fuzzy expert system.RESULTSThe final diagnostic parameters included the duration of diabetes, the score of a symptom examination based on the Michigan questionnaire, the score of a sign examination based on the Michigan questionnaire, the glycolysis haemoglobin level, fasting blood sugar, blood creatinine, and albuminuria. The output variable was the severity of diabetic neuropathy which was shown as a number between zero and 10, had been divided into four categories: absence of the disease, (the degree of severity) mild, moderate, and severe. The interface of the system was designed by ASP.Net (Active Server Pages Network Enabled Technology) and the system function was tested in terms of sensitivity (true positive rate) (89%), specificity (true negative rate) (98%), and accuracy (a proportion of true results, both positive and negative) (93%).CONCLUSIONThe system designed in this study can help specialists and general practitioners to diagnose the disease more quickly to improve the quality of care for patients.

Attention is a basic and main mental task and can play an important role in the functioning of other brain abilities such as intelligence, memory, learning, and perception, and its deficit occurs in 80% of patients with traumatic brain injury. The use of game-based tools for rehabilitation is rapidly expanding. Cognitive rehabilitation via video games is an emerging hot topic in cognitive science. Serious games serve a specific purpose in addition to entertainment. They can be more engaging than exercises since they replace reward and motivation systems with real-world motivations as a complement for rehabilitation activities. This study was aimed at identifying and categorizing serious computer games used for attention rehabilitation and evaluating their effects. Six electronic databases (Scopus, PubMed, ISI, Embase, IEEE, and Cochrane) were searched in August 2021. The search strategy consisted of three main concepts of “serious game”, “cognitive deficits”, and “cognitive rehabilitation”. The inclusion criteria were (1) journal articles, (2) English language, (3) being published in the last 10 years, (4) human participants, and (5) game-based intervention. In the 30 included studies, 22 unique games were utilized for attention rehabilitation. Lumosity (20%), Brain Age (Dr. Kawashima’s Brain Training) (10%), and MoHRS (6.66%) were the most common games among the studies. There were (57%) casual, (23%) action, (10%) simulation, and (10%) multiple genres. Of the 47 tools used in the studies, 5 utilized cross-modal oddball attention tasks, 4 utilized game performance, 3 utilized the paced auditory serial additional test (PASAT), and the rest employed other tools. A total of 73 outcome measures were related to attention, 42 measures did not have significant results, 30 were significantly improved, 1 was significantly deteriorated, and 4 articles did not have any specific measures for attention evaluation. Thus, the results revealed the positive effect of serious games on attention. However, issues such as absence of scientific teams, the variety of the disorders that cause defects, the variety of criteria, differences in measurements, lack of long-term follow-up, insufficient RCT studies, and small sample sizes should be considered when designing, developing, and using game-based systems to prevent bias.

Background: Literature on the prevention of medication errors is growing, highlighting that knowledge, attitude and behavior with regard to medication errors are strategic to planning of educational activities and evaluating their impact on professional practice. In this context, the present pilot study aims to translate and validate nursing professionals’ knowledge, attitudes and behavior (KAB theory) concerning medication administration errors in ICU from English into Persian. Furthermore, two main objectives of the project were: performing a pilot study among Iranian nurses using the translated questionnaire and carrying out a cultural measurement of the KAB theory concerning medication administration errors in an ICU questionnaire across two groups of Italian and Iranian populations. Methods: A cross-cultural adaptation of an instrument, according to the Checklist for reporting of survey studies (CROSS), was performed. The convenience sample was made up of 529 Iranian and Italian registered nurses working in ICU. An exploratory factor analysis was performed and reliability was assessed. A multi-group confirmatory factor analysis was conducted to test the measurement invariance. Ethical approval was obtained. Results: There was an excellent internal consistency for the 19-item scale. Results regarding factorial invariance showed that the nursing population from Italy and Iran used the same cognitive framework to conceptualize the prevention of medication errors. Conclusions: Findings from this preliminary translation and cross-cultural validation confirm that the questionnaire is a reliable and valid instrument within Persian healthcare settings. Moreover, these findings suggest that Italian and Persian nurses used an identical cognitive framework or mental model when thinking about medication errors prevention. The paper not only provides, for the first time, a validated instrument to evaluate the KAB theory in Iran, but it should promote other researchers in extending this kind of research, supporting those countries where attention to medical error is still increasing.

Mobile health as one of the new technologies can be a proper solution to support care provision for the elderly and provide personalized care for them. This study is aimed at reviewing the benefits and challenges of personalized mobile health (PMH) for elderly home care. With a systematic review methodology, 1895 records were retrieved by searching four databases. After removing duplicates, 1703 articles remained. Following full-text examination, 21 articles that met the inclusion criteria were studied in detail, and the output was presented in different tables. The results indicated that 25% of the challenges were related to privacy, cybersecurity, and data ownership (10%), technology (7.5%), and implementation (7.5%). The most frequent benefits were related to cost-saving (17.5%), nurse engagement improvement (10%), and caregiver stress reduction (7.5%). In general, the number of benefits in this study was slightly higher than the challenges, but in order to use PMH technologies, the challenges presented in this study must be carefully considered and a suitable solution must be adopted. Benefits can also be helpful in persuading individuals and health-care providers. This study shed light on those points that need to be highlighted for further work in order to convert the challenges toward benefits.