Comparing the effects of mHealth application based on micro-learning method and face-to-face training on treatment adherence and perception in haemodialysis patients: a randomised clinical trial

The utilization of renal dialysis: a comprehensive study in Saudi Arabia

BACKGROUND

Understanding the trend of utilization of renal dialysis in Saudi Arabia (SA) is fundamental as it provides a general overview of renal care. The practice of renal dialysis assists in identifying challenges, opportunities, and potential areas for improvement in the provision of the services.

OBJECTIVES

This research investigated the utilization of renal dialysis services in SA by exploring the number of renal dialysis centers, hemodialysis machines (HD), and peritoneodialysis patients.

METHODS

The dataset for this study was derived from a collaboration between the General Authority of Statistics (GaStat) and the Ministry of Health (MoH), focusing on indicators for renal dialysis centers and patients across health sectors in 2021. Analysis was conducted using MS Excel 365 and IBM SPSS Version 29, incorporating multiple regression techniques. The health sector was treated as the dependent variable. At the same time, the number of hemodialysis (HD) machines and the counts of HD and peritoneal dialysis patients were considered independent variables.

RESULTS

Around 275 renal dialysis centers, over 8000 HD machines, 20,440 HD patients, and 1,861 peritoneal patients were tallied from two resources. The findings revealed a negative relationship between the health sector and several renal dialysis centers and peritoneodialysis patients, as demonstrated by p < 0.05 in multiple regression analysis.

CONCLUSION

The number of renal dialysis centers influences the availability of HD machines, affecting the number of HD and peritoneodialysis patients. Most national patients preferred MoH over other semi-governmental and private sectors, and vice versa for non-Saudis.

Mobile health management among end stage renal disease patients: a scoping review

Aims

The health management of end-stage renal disease patients is a complicated process, and mobile health management technology provides a new choice for the health management of end-stage renal disease patients. The scope of clinical studies on mobile health management for patients with end-stage renal disease was reviewed, and found that about mobile health management problems existing in the literature were identified to provide ideas for subsequent mobile health management research.

Methods

The databases Web of Science, PubMed, The Cochrane Library, Embase, CNKI, Wan Fang Data, BMJ, and VIP were systematically searched for studies on Mobile health management among end-stage renal disease in adult and adolescent patients or children undergoing kidney replacement therapy. The search covered the period from the inception of the databases to June 20, 2023. Two independent reviewers conducted the literature screening process. Following eligibility screening, a total of 38 papers were included for data extraction and descriptive analysis.

Results

A total of 38 studies from 14 countries were finally included. The majority of which were interventional trials. The platforms used in these studies included remote monitoring systems, apps, websites, mobile phones or tablets, and social platforms. These platforms provided patients with a wide range of services, including disease management, behavioral intervention, social support, and follow-up care. Most studies focused on patient clinical indicators, patient experience, quality of life, and healthcare costs.

Conclusion

Our findings that mobile health management has been widely used in disease management of end-stage renal disease patients, with rich management content and many evaluation indicators. Future studies should strengthen the evaluation of patients' mental health, quality of life, and healthcare costs. Additionally, developing a clinical decision support system would enable mobile health management to play a more effective role in end-stage renal disease patients.

Impact of Nutrition Education on Various Health-Related Components of Hemodialysis Patients: A Systematic Review

This study aimed to identify the impact of nutrition education on various health-related components of hemodialysis patients. A systematic review was conducted according to the PRISMA guidelines. Relevant literature published between 2013 and 2023 was identified across two databases (PubMed and Science Direct). The protocol was registered in PROSPERO (CRD42023460681). Two independent reviewers retrieved the data, and 41 studies were selected. Nine components related to the impact of nutrition education in hemodialysis patients were identified. Each component was clarified by mentioning each study and its results. This study enabled us to characterize the various components of the impact of nutritional education in hemodialysis patients, namely biological markers, quality of life, cost of care, adherence to dietary recommendations, knowledge, malnutrition inflammation, dietary intake, weight change, and behavior change. This systematic review enables healthcare providers to assess the impact of nutritional education on hemodialysis patients. Also, it gives professionals an exact idea of the impact of nutrition education on hemodialysis patients, with knowledge of new methods using behavior change theories and innovative technological tools.

The effect of resilience training with mHealth application based on micro-learning method on the stress and anxiety of nurses working in intensive care units: a randomized controlled trial

INTRODUCTION

Nurses in intensive care units (ICUs) face high stress and anxiety, impacting their well-being and productivity. Addressing this, this study evaluated the impact of resilience training via a mHealth application based on micro-learning on ICU nurses' stress and anxiety levels.

MATERIALS AND METHODS

This study, a single-blind randomized controlled trial conducted in 2022-23, involved sixty ICU nurses from two Tehran hospitals. Nurses were chosen through purposive sampling and divided into intervention and control groups by simple randomization. The intervention group was taught resilience via an educational mHealth application based on micro-learning, with data collected using the anxiety and stress subscales of DASS-21.

RESULTS

Before the intervention, there were no significant differences in stress and anxiety scores between the intervention and control groups (P > 0.05). Upon utilizing the mHealth application, the intervention group exhibited significant reductions in stress, from 10.77 ± 3.33 to 9.00 ± 1.66 (P = 0.001), and in anxiety, from 9.43 ± 3.35 to 7.93 ± 0.98 (P < 0.001). In contrast, the control group experienced a slight increase in stress levels, from 10.10 ± 2.19 to 10.73 ± 2.15 (P = 0.002), and in anxiety levels, from 9.10 ± 1.63 to 10.23 ± 1.65 (P < 0.0001).

CONCLUSIONS

The micro-learning-based mHealth application for resilience training significantly reduced ICU nurses' stress and anxiety, recommending its adoption as an innovative educational method.

TRIAL REGISTRATION

The study has been registered in the Iranian Registry of Clinical Trials (No. IRCT20221225056916N1, Date: 04/29/2023).

Adapting power calculations to include a superiority margin: what are the implications?

This paper examines the application of super-superiority margins in study power calculations. Unlike traditional power calculations, which primarily aim to reject the null hypothesis by any margin, a super-superiority margin establishes a clinically significant threshold. Despite potential benefits, this approach, akin to a non-inferiority calculation but in an opposing direction, is rarely used. Implementing a super-superiority margin separates the notion of the likely difference between two groups (the effect size) from the minimum clinically significant difference, without which inconsistent positions could be held. However, these are often used interchangeably. In an audit of 30 recent randomized controlled trial power calculations, four studies utilized the minimal acceptable difference, and nine utilized the expected difference. In the other studies, this was unclarified. In the post hoc scenario, this approach can shed light on the value of undertaking further studies, which is not apparent from the standard power calculation. The acceptance and rejection of the alternate hypothesis for super-superiority, non-inferiority, equivalence, and standard superiority studies have been compared. When a fixed minimal acceptable difference is applied, a study result will be in one of seven logical positions with regards to the simultaneous application of these hypotheses. The trend for increased trial size and the mirror approach of non-inferiority studies implies that newer interventions may be becoming less effective. Powering for superiority could counter this and ensure that a pre-trial evaluation of clinical significance has taken place, which is necessary to confirm that interventions are beneficial.

Exploring the Potential of Chatbots in Critical Care Nephrology

The exponential growth of artificial intelligence (AI) has allowed for its integration into multiple sectors, including, notably, healthcare. Chatbots have emerged as a pivotal resource for improving patient outcomes and assisting healthcare practitioners through various AI-based technologies. In critical care, kidney-related conditions play a significant role in determining patient outcomes. This article examines the potential for integrating chatbots into the workflows of critical care nephrology to optimize patient care. We detail their specific applications in critical care nephrology, such as managing acute kidney injury, alert systems, and continuous renal replacement therapy (CRRT); facilitating discussions around palliative care; and bolstering collaboration within a multidisciplinary team. Chatbots have the potential to augment real-time data availability, evaluate renal health, identify potential risk factors, build predictive models, and monitor patient progress. Moreover, they provide a platform for enhancing communication and education for both patients and healthcare providers, paving the way for enriched knowledge and honed professional skills. However, it is vital to recognize the inherent challenges and limitations when using chatbots in this domain. Here, we provide an in-depth exploration of the concerns tied to chatbots' accuracy, dependability, data protection and security, transparency, potential algorithmic biases, and ethical implications in critical care nephrology. While human discernment and intervention are indispensable, especially in complex medical scenarios or intricate situations, the sustained advancements in AI signal that the integration of precision-engineered chatbot algorithms within critical care nephrology has considerable potential to elevate patient care and pivotal outcome metrics in the future.