Nodal Low-Grade B-Cell Lymphoma Co-Expressing CD5 and CD10 but Not CD23, IRTA1, or Cyclin D1: The Diagnostic Challenge of a Splenic Marginal Zone Lymphoma.

The diagnosis of lymphoma is based on histopathological and immunophenotypical features. CD5 and CD10 are traditionally considered a T-cell antigen and a germinal center B-cell antigen, respectively. It is very unusual for a low-grade B-cell lymphoma (BCL) to co-express CD5 and CD10. Although the biologic basis or clinical significance of such co-expression is unclear, this rare event may pose a significant diagnostic challenge. Here, we report a case of a 63-year-old male presenting with bilateral cervical lymphadenopathy and lymphocytosis. Histologically, the nodal tumor was largely diffuse with neoplastic small atypical lymphocytes co-expressing CD5, CD10, and CD20, but not CD23 or cyclin D1. The leukemic cells in the peripheral blood exhibited hairy projections. Taking together the marked splenomegaly, involvement of lymph nodes, bone marrow, and peripheral blood, a final diagnosis of splenic marginal zone lymphoma (SMZL) was reached. The patient was alive with partial response for 10 months after immunochemotherapy. The dual expression of CD5 and CD10 is extremely unusual for low-grade BCL and may lead to an erroneous diagnosis. Integrating the findings into peripheral blood smear tests, flow cytometry, histopathology, imaging, and clinical features is mandatory to exclude other lymphoma types and to reach a correct diagnosis, particularly for a case with nodal presentation.

Investigating mobile persuasive design for mental wellness: A cross-domain analysis.

BACKGROUND: Global mental health issues have increased the demand for digital mental health support. Mobile apps with persuasive technology play a vital role in enhancing mental well-being. OBJECTIVE: Analysing and Comparing persuasive intervention design across various app categories, this study aims to inspire innovative design approaches for improving the persuasiveness of mental wellness apps during their development. METHODS: We retrieved a total of 100 mobile apps from five distinct categories (20 for each): Mental wellness, Social media, Entertainment, Fitness & Physical health and News & Information from Apple Store and Google Play. Two researchers examined and coded the apps to identify the persuasive features employed within each category using the Persuasive Systems Design (PSD) Framework, while a third researcher participated in discussions to resolve discrepancies. Kendall's Rank Correlation Coefficient was performed to determine the relationship between persuasive features and effectiveness. RESULTS: Trustworthiness (n = 81), Liking (n = 78), Surface credibility (n = 71), Reminders (n = 63), and Reduction (n = 57) were the most widely implemented persuasive features. Dialogue support and system credibility support features were heavily used across different app types, while social support features were less commonly employed, particularly in mental health apps. A positive correlation was found between Surface credibility, Trustworthiness, Liking, Reminders, Self-monitoring, Expertise features and apps' effectiveness. CONCLUSION: Through a cross-domain analysis using the PSD framework to investigate persuasive feature implementations, the findings from this study offer design suggestions to create innovative and effective mobile apps promoting mental well-being.

Medication Adherence Support Applications for Chronic Arthritis Patients: Healthcare Providers' Perspective in Saudi Arabia.

Mobile health applications provide chronic disease patients with different capabilities and resources to support medication adherence. The study aims to understand the health care providers' (HCP) perceptions and recommendations about the design features and content of medication adherence support apps for individuals with chronic arthritis conditions in Saudi Arabia. Individual interviews were conducted with ten participants, such as rheumatologists, health educators, pharmacists, informaticians, and representatives from the Saudi Arthritis Association. The thematic analysis is utilised to code data and develop themes that help researchers in the design process. Four themes are identified: informational content, utilitarian, motivational, and socialisation features. The app content should improve arthritis patient awareness about medication management and adherence. Provide features that enable patients to set medication management and self-monitoring goals. The application design should be trustworthy, usable, enjoyable, and accessible for a diverse group of patients and respect patient privacy.

Empirical Evidence of Internal and External Factors Influencing Users' Motivation Toward Teleconsultation Use.

Introduction: The use of teleconsultation systems has increased in recent years, which has improved patients' access to health care providers and enabled seamless interaction between them. The literature points out several factors that either facilitate or impede the use of teleconsultation. However, there is a lack of studies that provide empirical evidence of factors that influence consumers' motivation toward the use of teleconsultation systems. Aim and Objective: This study aimed to provide empirical evidence of the internal and external factors that influence consumers' motivation toward the use of teleconsultation systems. Methods: A cross-sectional survey was used to collect data from consumers who used a real-time teleconsultation system called the Sehha application in Saudi Arabia between March 13 and June 14, 2021. SPSS 27.0.1 was used for descriptive analysis. Results: Four hundred eighty-five participants completed the survey, 471 of whom were included in the analysis. The findings confirmed that internal and external factors exert an influence on consumers' motivation toward the use of teleconsultation systems. The findings indicated that the presence of factors such as saving time, saving cost, accessibility to health care, ease-of-use, reliable internet access, availability of devices, and appropriate places during the online connection would increase consumers' motivation toward teleconsultation systems use. Also, the findings indicated that users' familiarity with systems similar to teleconsultation systems, users' perception of teleconsultation convenience, the influence of others on users' decision to use teleconsultation, and user's skills and confidence in using teleconsultation easily, and their trust in the teleconsultation system would also increase their motivation to use it. Furthermore, the findings showed that demographic factors, including age, gender, level of education, and employment status, did not influence users' motivation toward the use of teleconsultation Conclusions: This study provided empirical evidence of a variety of internal and external factors that exert an influence on consumers' motivation toward the use of teleconsultation systems.

Smartphone application use patterns for mental health disorders: A systematic literature review and meta-analysis.

BACKGROUND: Mobile mental health applications play a significant role in mental health care to fill gaps in care for mental disorders. Despite the growth in mobile phone apps for mental health conditions, patients' mental health smartphone application use, perceived usefulness, and future interest in using apps for mental disorders have not been systematically examined. METHODS: The authors designed and conducted this systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. Articles reporting mobile/smartphone applications used for mental disorders describing ownership, application use, perceived helpfulness, future interest to use, use patterns, and attitudes were included. PubMed/MEDLINE, EMBASE, PsychINFO, Scopus, and Google Scholar were searched. Published articles from 2014 up to October 2022 were included. The methodological quality was assessed using the Joanna Briggs Institute critical appraisal tool. The heterogeneity test, publication bias, funnel plots and Egger's test were applied. The outcome was calculated by metaprop command using a random-effects model. RESULTS: Ten studies met the eligibility criteria. The pooled prevalence of smartphone ownership, application use for current mental health disorders, perceived usefulness, and future interest in using the app for their mental health problem was 88.63%, 23.29%, 72.80%, and 78.97%, respectively. Heterogeneity and publication bias were detected. CONCLUSIONS: The results of this study indicate that despite a considerable number of smartphone users, perceived usefulness, and future interest in using smartphone mental health applications among patients with mental disorders, only about one-fifth use an application for mental health disorders. The results show that there is a large potential to increase the use of apps for patients to support self-care in the growing era of digital mental health. Further research with consumers and mental health professionals is recommended to address barriers and improve mhealth app utilization. REGISTRATION: Prospero international prospective register of systematic reviews with ID: CRD42022359416.

Predicting lung cancer survival based on clinical data using machine learning: A review.

Machine learning has gained popularity in predicting survival time in the medical field. This review examines studies utilizing machine learning and data-mining techniques to predict lung cancer survival using clinical data. A systematic literature review searched MEDLINE, Scopus, and Google Scholar databases, following reporting guidelines and using the COVIDENCE system. Studies published from 2000 to 2023 employing machine learning for lung cancer survival prediction were included. Risk of bias assessment used the prediction model risk of bias assessment tool. Thirty studies were reviewed, with 13 (43.3%) using the surveillance, epidemiology, and end results database. Missing data handling was addressed in 12 (40%) studies, primarily through data transformation and conversion. Feature selection algorithms were used in 19 (63.3%) studies, with age, sex, and N stage being the most chosen features. Random forest was the predominant machine learning model, used in 17 (56.6%) studies. While the number of lung cancer survival prediction studies is limited, the use of machine learning models based on clinical data has grown since 2012. Consideration of diverse patient cohorts and data pre-processing are crucial. Notably, most studies did not account for missing data, normalization, scaling, or standardized data, potentially introducing bias. Therefore, a comprehensive study on lung cancer survival prediction using clinical data is needed, addressing these challenges.

A Novel Mobile App for Personalized Dietary Advice Leveraging Persuasive Technology, Computer Vision, and Cloud Computing: Development and Usability Study.

BACKGROUND: The Australian Dietary Guidelines (ADG) translate the best available evidence in nutrition into food choice recommendations. However, adherence to the ADG is poor in Australia. Given that following a healthy diet can be a potentially cost-effective strategy for lowering the risk of chronic diseases, there is an urgent need to develop novel technologies for individuals to improve their adherence to the ADG. OBJECTIVE: This study describes the development process and design of a prototype mobile app for personalized dietary advice based on the ADG for adults in Australia, with the aim of exploring the usability of the prototype. The goal of the prototype was to provide personalized, evidence-based support for self-managing food choices in real time. METHODS: The guidelines of the design science paradigm were applied to guide the design, development, and evaluation of a progressive web app using Amazon Web Services Elastic Compute Cloud services via iterations. The food layer of the Nutrition Care Process, the strategies of cognitive behavioral theory, and the ADG were translated into prototype features guided by the Persuasive Systems Design model. A gain-framed approach was adopted to promote positive behavior changes. A cross-modal image-to-recipe retrieval model under an Apache 2.0 license was deployed for dietary assessment. A survey using the Mobile Application Rating Scale and semistructured in-depth interviews were conducted to explore the usability of the prototype through convenience sampling (N=15). RESULTS: The prominent features of the prototype included the use of image-based dietary assessment, food choice tracking with immediate feedback leveraging gamification principles, personal goal setting for food choices, and the provision of recipe ideas and information on the ADG. The overall prototype quality score was "acceptable," with a median of 3.46 (IQR 2.78-3.81) out of 5 points. The median score of the perceived impact of the prototype on healthy eating based on the ADG was 3.83 (IQR 2.75-4.08) out of 5 points. In-depth interviews identified the use of gamification for tracking food choices and innovation in the image-based dietary assessment as the main drivers of the positive user experience of using the prototype. CONCLUSIONS: A novel evidence-based prototype mobile app was successfully developed by leveraging a cross-disciplinary collaboration. A detailed description of the development process and design of the prototype enhances its transparency and provides detailed insights into its creation. This study provides a valuable example of the development of a novel, evidence-based app for personalized dietary advice on food choices using recent advancements in computer vision. A revised version of this prototype is currently under development.

Mobile apps used for people living with multiple sclerosis: A scoping review.

BACKGROUND: Multiple Sclerosis (MS) is a chronic neurodegenerative disorder. People living with MS (plwMS) require long-term, multidisciplinary care in both clinical and community settings. MS-specific mHealth interventions have advanced in the form of clinical treatments, rehabilitation, disease monitoring and self-management of disease. However, mHealth interventions for plwMS appear to have limited proof of clinical efficacy. As native mobile apps target specific mobile operating systems, they tend to have better interactive designs leveraging platform-specific guidelines. Thus, to improve such efficacy, it is pivotal to explore the design characteristics of native mobile apps used for plwMS. OBJECTIVES: This study aimed to explore the design characteristics of native mobile apps used for adults living with MS in academic settings. METHODS: A scoping review of studies was conducted. A literature search was performed through PubMed, CINAHL, MEDLINE and Cochrane Library. Per native mobile apps, characteristics, persuasive technology elements and evaluations were summarized. RESULTS: A total of 14 native mobile apps were identified and 43% of the identified apps were used for data collection (n=6). Approximately 70% of the included apps involved users (plwMS) whilst developing (n=10). A total of three apps utilized embedded sensors. Videos or photos were used for physical activity interventions (n=2) and gamification principles were applied for cognitive and/or motor rehabilitation interventions (n=3). Behavior change theories were integrated into the design of the apps for fatigue management and physical activity. Regarding persuasive technology, the design principles of primary support were applied across all identified apps. The elements of dialogue support and social support were the least applied. The methods for evaluating the identified apps were varied. CONCLUSION: The findings suggest that the identified apps were in the early stages of development and had a user-centered design. By applying the persuasive systems design model, interaction design qualities and features of the identified mobile apps in academic settings were systematically evaluated at a deeper level. Identifying the digital functionality and interface design of mobile apps for plwMS will help researchers to better understand interactive design and how to incorporate these concepts in mHealth interventions for improvement of clinical efficacy.

Prevalence and Predictors of Knowledge and Attitudes Toward Eye Donation Among the General Population: A Systematic Review.

PURPOSE: The purpose of this systematic review was to investigate knowledge and attitudes toward eye donation and sources of eye donation information among the general population. METHODS: A search was conducted using MEDLINE through Ovid and Scopus; CINAHL through EBSCOhost and ProQuest; and Embase through Ovid database entries from January 2010 to March 2021. Quantitative studies were selected if they included participants aged 16 years or older from the general population (nonhealthcare) and had a sample size of >200. Studies were included if they measured knowledge and attitudes toward eye donation and sources of eye donation information. Methodological quality was assessed using JBI criteria, and the data were analyzed using SUMARI software. RESULTS: A total of 25 studies were included in this review. Pooled data from 6 studies demonstrated that 30.8% of participants [95% confidence interval (CI) = 11.0-55.4] had some knowledge of eye donation. Seventeen studies reported that 40.6% (95% CI = 39.8-41.3) were willing to donate their eyes, and 5 of these studies found that 7.3% (95% CI = 6.5-8.3) had already pledged their eyes. Eleven studies reported on the source of eye donation information, indicating 50.9% of participants (95% CI = 49.8-52.1) received information from mass media. CONCLUSIONS: The results of this review indicate that understanding eye donation knowledge and attitudes is crucial for developing interventions or tools to increase eye donation rates. Further studies in different populations are required.

Orf Infection on the Scalp of a Taiwanese Woman: A Case Report and Literature Review.

BACKGROUND: Orf, or ecthyma contagiosum, is a zoonosis caused by Parapoxvirus that infects sheep and goats. Human transmission typically occurs in persons in contact with the infected animals or contaminated fomites and environment. In humans, it generally occurs as solitary or multiple skin lesions on the hands or fingers. Involvement of the head region has rarely been reported. CASE PRESENTATION: We report an unusual case with multiple orf lesions on the scalp of a middle-aged woman, along with a review of previously reported Orf cases on the head region. CONCLUSIONS: Although Orf infection rarely happens on the head region, it should be considered in the differential diagnosis of cases with relevant animal exposure.

Practical, epistemic and normative implications of algorithmic bias in healthcare artificial intelligence: a qualitative study of multidisciplinary expert perspectives.

BACKGROUND: There is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race). OBJECTIVES: Our objectives are to canvas the range of strategies stakeholders endorse in attempting to mitigate algorithmic bias, and to consider the ethical question of responsibility for algorithmic bias. METHODOLOGY: The study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers. RESULTS: Findings reveal considerable divergent views on three key issues. First, views on whether bias is a problem in healthcare AI varied, with most participants agreeing bias is a problem (which we call the bias-critical view), a small number believing the opposite (the bias-denial view), and some arguing that the benefits of AI outweigh any harms or wrongs arising from the bias problem (the bias-apologist view). Second, there was a disagreement on the strategies to mitigate bias, and who is responsible for such strategies. Finally, there were divergent views on whether to include or exclude sociocultural identifiers (eg, race, ethnicity or gender-diverse identities) in the development of AI as a way to mitigate bias. CONCLUSION/SIGNIFICANCE: Based on the views of participants, we set out responses that stakeholders might pursue, including greater interdisciplinary collaboration, tailored stakeholder engagement activities, empirical studies to understand algorithmic bias and strategies to modify dominant approaches in AI development such as the use of participatory methods, and increased diversity and inclusion in research teams and research participant recruitment and selection.

Persuasive features for patient engagement through mHealth applications in managing chronic conditions: A systematic literature review and meta-analysis.

Patient engagement is currently considered the cornerstone of a revolution in healthcare for its positive impact on health outcomes, health behaviors and healthcare costs. Patient engagement is focused on personalized care to consumers through providing knowledge, skills and confidence. Mobile health (mHealth) applications are an innovative means to facilitate patient engagement. Nevertheless, the extent to which the current mHealth applications are designed to engage patients in managing their chronic diseases is unclear. This paper aims to identify the Persuasive System Design (PSD) features present in current mHealth applications that increased the engagement of patients with chronic diseases. This review also aims to identify patient engagement-related outcomes of these features. This paper conducted a systematic literature review and meta-analysis to find relevant studies published from all years up to 2020 through six databases: PubMed, Scopus, Web of Science, Cinahl plus with full text, MEDLINE with full text, and Cochrane Library (Central register of controlled trials). The database search returned 4939 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 13. A qualitative content analysis was performed to identify PSD model features and their patient engagement-related outcomes. The quality assessment has been done through the Cochrane Risk of Bias tool for RCTs. The systematic literature review and meta-analysis identified eleven PSD features that can increase patient engagement through using mHealth applications. The identified PSD features have been shown to have various patient engagement-related outcomes. Behavior Change Techniques (BCTs) were combined with the identified PSD features. This paper identified persuasive features of mHealth application design that influence the engagement of patients with chronic diseases toward changing their behavior. The impact of these features is also analyzed in this review. The results show that an mHealth technology-mediated patient engagement model is needed.

mHealth Apps Targeting Obesity and Overweight in Young People: App Review and Analysis.

BACKGROUND: Overweight and obesity have been linked to several serious health problems and medical conditions. With more than a quarter of the young population having weight problems, the impacts of overweight and obesity on this age group are particularly critical. Mobile health (mHealth) apps that support and encourage positive health behaviors have the potential to achieve better health outcomes. These apps represent a unique opportunity for young people (age range 10-24 years), for whom mobile phones are an indispensable part of their everyday living. However, despite the potential of mHealth apps for improved engagement in health interventions, user adherence to these health interventions in the long term is low. OBJECTIVE: The aims of this research were to (1) review and analyze mHealth apps targeting obesity and overweight and (2) propose guidelines for the inclusion of user interface design patterns (UIDPs) in the development of mHealth apps for obese young people that maximizes the impact and retention of behavior change techniques (BCTs). METHODS: A search for apps was conducted in Google Play Store using the following search string: ["best weight loss app for obese teens 2020"] OR ["obesity applications for teens"] OR ["popular weight loss applications"]. The most popular apps available in both Google Play and Apple App Store that fulfilled the requirements within the inclusion criteria were selected for further analysis. The designs of 17 mHealth apps were analyzed for the inclusion of BCTs supported by various UIDPs. Based on the results of the analysis, BCT-UI design guidelines were developed. The usability of the guidelines was presented using a prototype app. RESULTS: The results of our analysis showed that only half of the BCTs are implemented in the reviewed apps, with a subset of those BCTs being supported by UIDPs. Based on these findings, we propose design guidelines that associate the BCTs with UIDPs. The focus of our guidelines is the implementation of BCTs using design patterns that are impactful for the young people demographics. The UIDPs are classified into 6 categories, with each BCT having one or more design patterns appropriate for its implementation. The applicability of the proposed guidelines is presented by mock-ups of the mHealth app "Morphe," intended for young people (age range 10-24 years). The presented use cases showcase the 5 main functionalities of Morphe: learn, challenge, statistics, social interaction, and settings. CONCLUSIONS: The app analysis results showed that the implementation of BCTs using UIDPs is underutilized. The purposed guidelines will help developers in designing mHealth apps for young people that are easy to use and support behavior change. Future steps involve the development and deployment of the Morphe app and the validation of its usability and effectiveness.

Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills.

BACKGROUND: Alongside the promise of improving clinical work, advances in healthcare artificial intelligence (AI) raise concerns about the risk of deskilling clinicians. This purpose of this study is to examine the issue of deskilling from the perspective of diverse group of professional stakeholders with knowledge and/or experiences in the development, deployment and regulation of healthcare AI. METHODS: We conducted qualitative, semi-structured interviews with 72 professionals with AI expertise and/or professional or clinical expertise who were involved in development, deployment and/or regulation of healthcare AI. Data analysis using combined constructivist grounded theory and framework approach was performed concurrently with data collection. FINDINGS: Our analysis showed participants had diverse views on three contentious issues regarding AI and deskilling. The first involved competing views about the proper extent of AI-enabled automation in healthcare work, and which clinical tasks should or should not be automated. We identified a cluster of characteristics of tasks that were considered more suitable for automation. The second involved expectations about the impact of AI on clinical skills, and whether AI-enabled automation would lead to worse or better quality of healthcare. The third tension implicitly contrasted two models of healthcare work: a human-centric model and a technology-centric model. These models assumed different values and priorities for healthcare work and its relationship to AI-enabled automation. CONCLUSION: Our study shows that a diverse group of professional stakeholders involved in healthcare AI development, acquisition, deployment and regulation are attentive to the potential impact of healthcare AI on clinical skills, but have different views about the nature and valence (positive or negative) of this impact. Detailed engagement with different types of professional stakeholders allowed us to identify relevant concepts and values that could guide decisions about AI algorithm development and deployment.

Panfolliculoma: Report of the Youngest Case and Literature Review of Its Histopathologic Variants.

Background: Panfolliculoma (PF) is a relative rare, benign follicular tumor comprised of all elements of the hair follicle, with a limited number of cases reported in the literature. Articles on the demographic and pathological analysis of this tumor are also lacking. Case presentation: In this report, we presented an unusual case of cystic PF on the back of a 14-year-old male, and we performed a thorough literature review and analysis of all previously reported cases. Conclusions: PF is a rare benign follicular neoplasm with characteristic differentiation toward all components of the hair follicle. In our analysis, PF occurred most frequently on the head region and was usually diagnosed in middle- to old-aged persons, with cystic PF being the most common histologic subtype. Since this tumor is rare and easily misdiagnosed as other tumors both clinically and pathologically, a thorough understanding of the histopathological manifestations and differential diagnosis of this tumor is necessary for both dermatologists and pathologists.

Design and content validation of an instrument measuring user perception of the persuasive design principles in a breastfeeding mHealth app: A modified Delphi study.

BACKGROUND: Persuasive design principles are increasingly employed in mHealth apps for motivating users and promoting healthy behaviours among individuals. However, how the persuasive design principles are perceived by the mHealth app users remains unclear. AIM: To develop and validate the content validity of an instrument designed to measure the user's perceptions of the persuasive design principles assimilated in a breastfeeding mHealth app. METHODS: A critical review of the literature guided the development of the research instrument. The developed instrument was refined and validated through a two-round modified Delphi process. Ten experts drawn from academic and clinical settings evaluated the items through two content validity indicators, relevance, and clarity and provided narrative feedback. The content validity of the instrument was determined by calculating the Content Validity Index (CVI). Content validity indicators at the scale-level (S-CVI) and item-level (I-CVI) were calculated. RESULTS: The results demonstrated high content validity index of individual items in the instrument. All items in the instrument reached an excellent I-CVI ≥ 0.78 for both relevance and clarity except one item. The overall content validity index of the instrument using the average approach was moderate to high (S-CVI/Ave was 0.89 and 0.92 for relevance and clarity, respectively). The developed research instrument is composed of 5 constructs representing 24 items: (1) primary task support, (2) dialogue support, (3) system credibility support, (4) social support and (5) perceived persuasiveness. CONCLUSIONS: Using a modified Delphi approach, the development and validation of the research instrument demonstrated moderate to high content validity for measuring users' perceptions of the persuasive design principles assimilated in a breastfeeding mHealth app. The evidence from this study supports that the research instrument is valid, relevant, and clear.

An empirical study on factors influencing consumers' motivation towards teleconsultation system use. A preliminary report about the Sehha application from Saudi Arabia.

BACKGROUND: The use of the teleconsultation system has increased in recent years, which enabled healthcare providers and patients to share, communicate and transfer information in real-time via different types of telemedicine services and applications. However, there is a lack of studies that underpin factors that motivate patients to use teleconsultation systems. AIM AND OBJECTIVE: This study aimed to identify factors that influence consumers' motivation to use teleconsultation systems by developing a theoretical framework and empirically testing the developed framework with a real-world teleconsultation system. METHODS: A cross-sectional study was used for this research to empirically validate the proposed model. The online survey consisted of 51 items, which were developed by the researchers. Partial least squares structural equation modelling (PLS-SEM) was used to analyze the measurement model and structural model. RESULTS: 485 participants completed the online survey, 471 of which were included in the model analysis. The measurement analysis indicated that convergent validity was achieved as all items' outer lording were well above the threshold of 0.70, all indicators reliability and AVEs were well above the threshold of 0.50. Also, the measurement analysis indicated that discriminate validity was achieved as the Heterotrait-Monotrait ratio of correlations for all constructs were below the threshold of 0.90. In the structural model analysis, the inner constructs of the model, autonomy, competence and relatedness explained 60.1% of the variance in users' motivation toward the use of the teleconsultation system. The outer constructs of the model, subjective norm, external and internal facilitating conditions, explained 67.3% of the variance in users' autonomy, whereas attitude, performance expectancy, external and internal facilitating conditions explained 51.9% of the variance in the users' competence, and subjective norm explained 25.6% of the variance in the users' relatedness. CONCLUSIONS: The developed framework can explain why consumers are motivated to use teleconsultation systems for online medical consultations. The model indicated that a variety of internal and external factors can positively or negatively influence consumers' perceived autonomy, competence and relatedness, which can impact their motivation toward the use of teleconsultation systems.

Development and validation of a new tool to identify factors that influence users' motivation toward the use of teleconsultation systems: A modified Delphi study.

BACKGROUND: Healthcare providers have improved consumer access to healthcare services by the adoption of information communication technology and the use of telemedicine. With the current COVID-19 pandemic, consumers are shifting to remote teleconsultation. There are several studies regarding consumers' acceptance and satisfaction with telemedicine among healthcare providers and a few among patients at healthcare facilities. However, studies about patients' motivation toward the use of teleconsultation systems are very few. AIM: The aim of this study was to validate an instrument of a newly developed framework to identify factors that motivate patients to use a teleconsultation system. METHOD: This study used a modified eDelphi method incorporating content validity index and content validity ratio procedures to validate the instrument among fifteen experts from different disciplines. The eDelphi consisted of three rounds to review each item's relevance, clarity, importance and the overall validity of the instrument. RESULT: The result showed a significant level of agreement among experts for individual items' relevance, clarity and importance. For relevance, all items had excellent I-CVI above 0.889, except one item with I-CVI = 0.78, which is still acceptable. For clarity, all items had an excellent I-CVI > 0.889, except one with I-CVI = 0.667. For importance, most items had CVR above the threshold value of 0.778, except 5 items. Also, the result showed moderate to high content validity of the overall instrument (S-CVI/UA = 0.694; S-CVI/Ave = 0.996). DISCUSSION: These findings support the validity and reliability of the developed instrument, which can be used to identify factors that motivated patients to use a teleconsultation system. Future testing of the instrument should be conducted with a larger population that uses a teleconsultation system. CONCLUSION: An instrument was developed to identify factors that motivated consumers to use teleconsultation, using a modified eDelphi method among experts. The eDelphi method consisted of three rounds and the results showed that the instrument is a valid and reliable tool.

Adaptation of the MAUQ and usability evaluation of a mobile phone-based system to promote eye donation.

INTRODUCTION: Mobile Applications (apps) are commonly used in the health care settings to improve the quality of care, however prior to the release of the app it is vital to evaluate its usability. Therefore, the aim of this study is to adapt the mobile Health App Usability Questionnaire (MAUQ) and measure the usability of the Eye donor Aust App using the modified instrument (m-MAUQ). METHODS: The study was undertaken using a convenience sample of 94 patients and their carers attending three eye clinics and one outpatient department in a large hospital in Sydney Australia. The study was conducted in two phases. Phase 1 involved the adaptation of the MAUQ, and validity testing of the modified version. Phase 2 included the usability evaluation of the Eye donor Aust App using the modified MAUQ (m-MAUQ). RESULTS: The m-MAUQ comprised of 15 items and the content validity of the instrument was considered satisfactory. Exploratory factor analysis supported a three-factor structure namely: ease of use and satisfaction (nine items), usefulness in obtaining information (three items), and system information arrangement (three items). The internal consistency for the subscales and the total scale was high with Cronbach's alpha values greater than 0.90. The usability score for the Eye donor Aust App was high (mean 5.99; SD 0.74). The construct validity was supported as there were no differences in usability scores among males and females. Older people found the app less useful for obtaining information about eye donation. CONCLUSIONS: The results support the use of the m-MAUQ as a valid instrument to measure the usability of the Eye Donor Aust App. This instrument requires further testing in other groups of people. Usability testing of the Eye Donor Aust app demonstrated that the participants were satisfied with the content and functionality of the app stating that it was well organised, visually appealing and user friendly. This result could translate into more people using the app and thereby increasing their knowledge and attitude towards eye donation as well as registering to become a donor.