Evaluation of ChatGPT's responses to information needs and information seeking of dementia patients.

Many people in the advanced stages of dementia require full-time caregivers, most of whom are family members who provide informal (non-specialized) care. It is important to provide these caregivers with high-quality information to help them understand and manage the symptoms and behaviors of dementia patients. This study aims to evaluate ChatGPT, a chatbot built using the Generative Pre-trained Transformer (GPT) large language model, in responding to information needs and information seeking of such informal caregivers. We identified the information needs of dementia patients based on the relevant literature (22 articles were selected from 2442 retrieved articles). From this analysis, we created a list of 31 items that describe these information needs, and used them to formulate 118 relevant questions. We then asked these questions to ChatGPT and investigated its responses. In the next phase, we asked 15 informal and 15 formal dementia-patient caregivers to analyze and evaluate these ChatGPT responses, using both quantitative (questionnaire) and qualitative (interview) approaches. In the interviews conducted, informal caregivers were more positive towards the use of ChatGPT to obtain non-specialized information about dementia compared to formal caregivers. However, ChatGPT struggled to provide satisfactory responses to more specialized (clinical) inquiries. In the questionnaire study, informal caregivers gave higher ratings to ChatGPT's responsiveness on the 31 items describing information needs, giving an overall mean score of 3.77 (SD 0.98) out of 5; the mean score among formal caregivers was 3.13 (SD 0.65), indicating that formal caregivers showed less trust in ChatGPT's responses compared to informal caregivers. ChatGPT's responses to non-clinical information needs related to dementia patients were generally satisfactory at this stage. As this tool is still under heavy development, it holds promise for providing even higher-quality information in response to information needs, particularly when developed in collaboration with healthcare professionals. Thus, large language models such as ChatGPT can serve as valuable sources of information for informal caregivers, although they may not fully meet the needs of formal caregivers who seek specialized (clinical) answers. Nevertheless, even in its current state, ChatGPT was able to provide responses to some of the clinical questions related to dementia that were asked.

Smart city healthcare delivery innovations: a systematic review of essential technologies and indicators for developing nations.

BACKGROUND: In recent times, the concept of smart cities has gained remarkable traction globally, driven by the increasing interest in employing technology to address various urban challenges, particularly in the healthcare domain. Smart cities are proving to be transformative, utilizing an extensive array of technological tools and processes to improve healthcare accessibility, optimize patient outcomes, reduce costs, and enhance overall efficiency. METHODS: This article delves into the profound impact of smart cities on the healthcare landscape and discusses its potential implications for the future of healthcare delivery. Moreover, the study explores the necessary infrastructure required for developing countries to establish smart cities capable of providing intelligent health and care services. To ensure a comprehensive analysis, we employed a well-structured search strategy across esteemed databases, including PubMed, OVID, EMBASE, Web of Science, and Scopus. The search scope encompassed articles published up to November 2022, resulting in a meticulous review of 22 relevant articles. RESULTS: Our findings provide compelling evidence of the pivotal role that smart city technology plays in elevating healthcare delivery, forging a path towards improved accessibility, efficiency, and quality of care for communities worldwide. By harnessing the power of data analytics, Internet of Things (IoT) sensors, and mobile applications, smart cities are driving real-time health monitoring, early disease detection, and personalized treatment approaches. CONCLUSION: Smart cities possess the transformative potential to reshape healthcare practices, providing developing nations with invaluable opportunities to establish intelligent and adaptable healthcare systems customized to their distinct requirements and limitations. Moreover, the implementation of smart healthcare systems in developing nations can lead to enhanced healthcare accessibility and affordability, as the integration of technology can optimize resource allocation and improve the overall efficiency of healthcare services. It also may help alleviate the burden on overburdened healthcare facilities by streamlining patient care processes and reducing wait times, ensuring that medical attention reaches those in need more swiftly.

Design, development, implementation, and evaluation of a severe drug-drug interaction alert system in the ICU: An analysis of acceptance and override rates.

BACKGROUND AND OBJECTIVE: The override rate of Drug-Drug Interaction Alerts (DDIA) in Intensive Care Units (ICUs) is very high. Therefore, this study aimed to design, develop, implement, and evaluate a severe Drug-Drug Alert System (DDIAS) in a system of ICUs and measure the override rate of this system. METHODS: This is a cross-sectional study that details the design, development, implementation, and evaluation of a DDIAS for severe interactions into a Computerized Provider Order Entry (CPOE) system in the ICUs of Nemazee general teaching hospitals in 2021. The patients exposed to the volume of DDIAS, acceptance and overridden of DDIAS, and usability of DDIAS have been collected. The study was approved by the local Institutional Review Board (IRB) and; the ethics committee of Shiraz University of Medical Science on date: 2019-11-23 (Approval ID: IR.SUMS.REC.1398.1046). RESULTS: The knowledge base of the DDIAS contains 9,809 severe potential drug-drug interactions (pDDIs). A total of 2672 medications were prescribed in the population study. The volume and acceptance rate for the DDIAS were 81 % and 97.5 %, respectively. The override rate was 2.5 %. The mean System Usability Scale (SUS) score of the DDIAS was 75. CONCLUSION: This study demonstrates that implementing high-risk DDIAS at the point of prescribing in ICUs improves adherence to alerts. In addition, the usability of the DDIAS was reasonable. Further studies are needed to investigate the establishment of severe DDIAS and measure the prescribers' response to DDIAS on a larger scale.

Development of a Mobile App for Self-Care Against COVID-19 Using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) Model: Methodological Study.

BACKGROUND: Mobile apps have been shown to play an important role in the management, care, and prevention of infectious diseases. Thus, skills for self-care-one of the most effective ways to prevent illness-can be improved through mobile health apps. OBJECTIVE: This study aimed to design, develop, and evaluate an educational mobile-based self-care app in order to help the self-prevention of COVID-19 in underdeveloped countries. We intended the app to be easy to use, quick, and inexpensive. METHODS: In 2020 and 2021, we conducted a methodological study. Using the ADDIE (analysis, design, development, implementation, and evaluation) educational model, we developed a self-care management mobile app. According to the ADDIE model, an effective training and performance support tool is built through the 5 phases that comprise its name. There were 27 participants who conducted 2 evaluations of the mobile app's usability and impact using the mobile health app usability and self-care inventory scales. The study design included pre- and posttesting. RESULTS: An Android app called MyShield was developed. The results of pre- and posttests showed that on a scale from 0 to 5, MyShield scored a performance average of 4.17 in the physical health dimension and an average of 3.88 in the mental well-being dimension, thereby showing positive effects on self-care skills. MyShield scored highly on the "interface and satisfaction," "ease of use," and "usefulness" components. CONCLUSIONS: MyShield facilitates learning self-care skills at home, even during quarantine, increasing acquisition of information. Given its low development cost and the ADDIE educational design on which it is based, the app can be helpful in underdeveloped countries. Thus, low-income countries-often lacking other tools-can use the app as an effective tool for fighting COVID-19, if it becomes a standard mobile app recommended by the government.

The effect of information technology intervention on using appropriate VTE prophylaxis in non-surgical patients: A systematic review and meta-analysis.

Introduction: Clinical decision support systems (CDSSs) play an important role in summarizing the best clinical practices, thereby promoting high standards of care in specific medical fields. These systems can serve as tools for gaining knowledge and mediating between clinical guidelines and physicians thereby providing the right information to the right person at the right time. Objective: This review aims to evaluate the effect of CDSSs on adherence to guidelines for venous thromboembolism (VTE) prophylaxis and VTE events compared to routine care without CDSSs in non-surgical patients. Methods: In order to conduct a systematic literature review, the published studies were identified through screening EMBASE, the international clinical trials registry, OVID, Cochrane database, PubMed, ISI Web of Science, and Scopus databases, from 1982 to March 2021. The included studies were reviewed by two independent reviewers; the proportion of patients that correctly received VTE prophylaxis has been next extracted for further analysis. Additionally, patients were divided into two groups: CDSS-recommended VTE prophylaxis and routine care without using a CDSS. Results: Twelve articles (three randomized controlled trials, seven prospective cohort trials, and two retrospective cohort trials) were in fine analyzed. The use of CDSSs is found to be associated with a significant increase in the rate of using the appropriate prophylaxis for VTE (p < 0.05) and a significant decrease in the incidence of VTE (p < 0.05). Conclusion: Implementation of CDSSs can help improving the appropriate use of VTE prophylaxis in non-surgical patients. Further, evidence-based and interventional studies on the development of CDSSs can provide more in-depth knowledge on both this tool design and efficiency.

Predicting and classifying hearing loss in sailors working on speed vessels using neural networks: a field study.

BACKGROUND:  Noise-induced hearing loss (NIHL) is one of the main risk factors affecting people's health and wellbeing in the workplace. Analysing NIHL and consequently controlling the causing factors can significantly affect the improvement of working environments. Methods: One hundred and twelve male sailors participated in this study. They were classified into three groups depending on occupational noise exposure: (A) none, i.e., sound pressure level (SPL) lower than 70dBA, (B) exposed to SPL in the range of 70-85dBA, and (C) exposed to SPL exceeding 80dBA. In a first phase, hearing loss shaping risk factors were identified and analysed, including hearing loss in different frequencies, age, work experience, sound pressure level (SPL), marital status, and systolic and diastolic blood pressure. Then, neural networks were trained to predict the hearing loss changes of personnel and used to determine the weight of hearing loss factors. Finally, the accuracy of predicting models was calculated relying on Bayesian statistics. Results and conclusion: In the present study using neural networks, five models were developed. Their accuracy ranged from 92% to 100%. The frequencies of 4000Hz and 2000Hz showed the strongest association with the hearing loss of the sailors. Also, including systolic and diastolic blood pressure did not have any impact on predicted hearing loss, indicating that SPL was poorly correlated with extra-auditory effects.

Effect of the level of manual performance disability caused by exposure to vibration among sailors working on sailing speed vessels.

BACKGROUND: hand-arm vibration is one of the typical annoying physical factors. Hand-arm vibration syndrome (HAVS) is a disorder caused by vibrating working tools which vibrate hands beyond the threshold. Long-term HAVS may result in damage to blood vessels, chronic numbness in the fingers, bone injury, and muscular weakness. People are exposed to high-rate noise vibration in a variety of situations, including vessel employment and operating in tiny boats. Moreover, the extant study was conducted to examine manual function disability levels caused by Sailing Speed Vessels (SSV) vibration. METHODS: The extant study was quasi-experimental research in which, 52 male sailors in SSVs were chosen as the experimental group, and 27 office personnel were selected as the control group. The demographic factors questionnaire, DASH questionnaire, grip and pinch strength tests, the neurosensory exam, and the skill-dexterity test were all employed in this study. SPSS23 software was used to analyze the data. RESULTS: The findings suggested that the experimental group experienced greater vibration disorder symptoms than the control group. Because the experimental group had a higher score, the individuals experienced poorer circumstances in terms of arm, shoulder, and hand impairment as compared to the control group. The mean grip strength of hands and fingers in two hands of the experimental group was lower than the control group (P < 0.05). There was a statistically significant relationship among grip strengths of both experimental and control groups (P < 0.05). There was a reduction in skill and dexterity of both dominant and non-dominant hands of members in the experimental group. According to the statistical tests, there was no significant association between dominant (P = 0.001) skills and non-dominant (P = 0.010) hands in experimental and control groups. There was not also any significant relationship between skill and dexterity of both hands (P = 0.001) and the dominant hand tweezer test (P = 0.001) in two experimental and control groups. There was a statistically significant association between experimental and control groups in terms of assembly skill and dexterity (P = 0.482). CONCLUSION: Individuals who are at risk of vibration experience less physical and sensory function. DASH score, grip strength, skill, and dexterity could predict the reduction in physical function disability.

Mobile-Based Self-Care Application for COVID-19: Development Process Using the ADDIE Model.

During the COVID-19 era, technology-enhanced protection of this disease has saved lives in developed countries in which citizens have the privilege of accessing and using such technologies to fight Coronavirus. In the undeveloped countries, on the other hand, citizens have had no accession or ability to use digital technologies to prevent COVID-19. Having this in front, in the MyShield research project, we aim to address how to teach self-care skills in undeveloped countries in the era of COVID-19 using a mobile low-cost application effectively based on a standard educational model (ADDIE). This paper reports a framework that arises from the results of semi-structured interviews and online workshops conducted in the ADDIE design process for the self-care mobile application. The specialists contributed to indicte the appropriate content for teaching self-care skills while informants contributed to optimize the user experience flow.

Smartphone-Based Healthcare Apps for Older Adults in the COVID-19 Era: Heuristic Evaluation.

Many national governments have attempted to prevent and combat COVID-19 using mobile health (mHealth) technologies during the epidemic. During this time, governments began developing smartphone-based apps for prevention, call tracking, and monitoring people with COVID-19. An important question is, does everyone benefit from these technologies equally and fairly? To answer this question, we evaluated the user interface of smartphone-based apps developed during the COVID-19 era by considering their design for older adults, in order to determine whether social justice has been considered in the development of these apps.

MDA Framework for FAIR Principles.

This paper shows that the MDA framework can be helpful for designing and implementing FAIR principles. We reached this conclusion based on a focus group interview with six experts, during which we focused on the three MDA components: mechanics, dynamics and aesthetics.

Evaluation of Mobile Phone Healthcare Applications During the Covid-19 Pandemic.

Our aim in the present study was to evaluate the HealthBuddy+ smartphone app, designed and implemented by the World Health Organization for the European region. For this purpose, we have used Heuristic evaluation method. The tools utilized in this study included 10 heuristics and measure System Usability Scale (SUS), as well as Nielsen's five-point Severity Ranking Scale.

Need for recovery scale in the firefighting context: Examination of the Persian culture-adapted version.

BACKGROUND: Work-related fatigue can cause disruption in mental and physical activities of the workers. Considering the importance of recovery from fatigue in emergency services, as seen in firefighting duties, the preparation and validation of the Need For Recovery Scale (NFRS) questionnaire can be useful and effective. OBJECTIVE: This study assessed the reliability and validity of the Persian version of Need For Recovery Scale among industrial firefighters. METHODS: Need for recovery scale contains 11 questions. First, a questionnaire was translated using backward-forward method. Then, for measuring validity of the questionnaire, the opinions of 10 experts in related fields were obtained. Content Validity Index (CVI) and Content Validity Ratio (CVR) were calculated. The reliability was determined through 107 questionnaires completed by the industrial firefighters. RESULTS: The average age of the firefighters in this study was 37.5 years and they had an average of 10 years of work experience. The mean Need For Recovery Index from fatigue was 33.03 for the study population. Of the first 11 questions, 9 questions in the original NFRS showed a satisfactory level of CVR. The Content Validity Index and Cronbach's α were 0.89 and 0.77 respectively. CONCLUSION: Based on the results, the Need For Recovery Scale is a reliable tool for assessing fatigue and revealed an acceptable level of validity and reliability that makes it usable for fatigue assessment in the industrial firefighters.