An empirical study of factors influencing e-health services adoption among public in Saudi Arabia

Understanding Factors Influencing Diabetic Patients' Intention to Use Digital Health Services in Saudi Arabia Using the Technology Acceptance Model

This study employs the Technology Acceptance Model to investigate the factors influencing Saudi Arabian diabetic patients' intention to use digital health services. There is an urgent need to investigate the possibilities of digital health services in managing diabetes given the startlingly rapidly increasing prevalence rate of diabetes in KSA. The study examines the variables affecting patients' acceptance and desire to use digital health tools to manage their diabetes. The study employs the Technology Acceptance Model to ascertain the crucial factors that impact patients' opinions regarding the usefulness and ease of use of digital healthcare technologies. The proposed model extends the traditional Technology Acceptance Model by adding two new constructs, perceived privacy and trust. These constructs were examined by analyzing the intentions of 600 respondents through online surveys. The study's conclusions showed that attitudes toward using digital health services for KSA diabetic patients are greatly influenced by every component of the extended Technology Acceptance Model. The study's conclusions add to the body of knowledge already in existence and offer insightful information to decision-makers hoping to improve digital health services.

Development and Validation of the Saudi Telehealth Acceptance Scale Based on the Unified Theory of Acceptance and Use of Technology

Background

Telehealth is in early stages in the Kingdom of Saudi Arabia (KSA). Identifying barriers to using telehealth is an essential step prior to its implementation; however, no theoretically based scales exist for the same purpose.

Objective

To design a theory-based scale capable of measuring telehealth users' perceptions of benefits, barriers, and social influence in the KSA.

Methods

The Saudi Telehealth Acceptance Scale (STAS) was constructed based on the Unified Theory of Acceptance and Use of Technology and its content validity was determined by eight experts using the modified Delphi process. Only items with a content validity index score of ≥0.83 were chosen. Finally, the face validity of the questionnaire for healthcare professionals, which was in English, was determined by eight healthcare professionals, and for the patient version, which was in Arabic, by six patients.

Results

Initially, 37 items were identified; however, after Round 1, 29 items remained and after Round 2, 24 items were included in the STAS for both healthcare professionals and patients. In the healthcare professionals scale, there were 7 performance expectancy (PE) items, 6 effort expectancy (EE) items, 3 social influence (SI) items, 4 facilitating conditions (FC) items, and 4 behavioral intention (BI) items, while in the scale for patients, there were 9 PE items, 4 EE items, 3 SI items, 4 FC items, and 4 BI items.

Conclusions

The two new scales showed evidence of content and face validity. The significance of the two scales is that they were both designed in the context of the healthcare system in the KSA and could provide standardized data collection tools to measure the acceptance of telehealth among HCPs and patients.

Overcoming Electronic Medical Records Adoption Challenges in Saudi Arabia

In the digital era, the seamless integration of electronic medical records (EMR) stands as a pivotal milestone in transforming healthcare delivery, with Saudi Arabia at the forefront of this revolution in the Middle East. This literature review comprehensively explores the challenges and opportunities associated with adopting EMR in the Kingdom of Saudi Arabia (KSA) in alignment with the nation's Vision 2030 healthcare objectives. The review synthesizes research from various scholarly sources, utilizing databases such as PubMed, Scopus, Google Scholar, and regional databases, and focuses on literature published between 2010 and 2023. Our methodology included a strategic combination of keywords and a stringent selection criterion to ensure a focus on relevant EMR adoption studies within KSA. The review addresses key aspects of EMR adoption, including technical challenges, financial constraints, human factors, cultural and organizational barriers, privacy and security concerns, and policy and regulatory challenges. It also explores the integration of EMR with other digital health initiatives like telehealth, personal health records, and community pharmacy services. The findings reveal a complex interplay of factors influencing EMR adoption, highlighting the need for comprehensive strategies that address technical, financial, cultural, and policy-related barriers. The review concludes that while significant challenges exist, strategic approaches and solutions tailored to the specific context of Saudi Arabia can effectively facilitate EMR integration, thereby enhancing healthcare quality and efficiency in line with the nation's Vision 2030 goals.

Predictors of the Use of a Mental Health-Focused eHealth System in Patients With Breast and Prostate Cancer: Bayesian Structural Equation Modeling Analysis of a Prospective Study

BACKGROUND

eHealth systems have been increasingly used to manage depressive symptoms in patients with somatic illnesses. However, understanding the factors that drive their use, particularly among patients with breast and prostate cancer, remains a critical area of research.

OBJECTIVE

This study aimed to determine the factors influencing use of the NEVERMIND eHealth system among patients with breast and prostate cancer over 12 weeks, with a focus on the Technology Acceptance Model.

METHODS

Data from the NEVERMIND trial, which included 129 patients with breast and prostate cancer, were retrieved. At baseline, participants completed questionnaires detailing demographic data and measuring depressive and stress symptoms using the Beck Depression Inventory-II and the Depression, Anxiety, and Stress Scale-21, respectively. Over a 12-week period, patients engaged with the NEVERMIND system, with follow-up questionnaires administered at 4 weeks and after 12 weeks assessing the system's perceived ease of use and usefulness. Use log data were collected at the 2- and 12-week marks. The relationships among sex, education, baseline depressive and stress symptoms, perceived ease of use, perceived usefulness (PU), and system use at various stages were examined using Bayesian structural equation modeling in a path analysis, a technique that differs from traditional frequentist methods.

RESULTS

The path analysis was conducted among 100 patients with breast and prostate cancer, with 66% (n=66) being female and 81% (n=81) having a college education. Patients reported good mental health scores, with low levels of depression and stress at baseline. System use was approximately 6 days in the initial 2 weeks and 45 days over the 12-week study period. The results revealed that PU was the strongest predictor of system use at 12 weeks (βuse at 12 weeks is predicted by PU at 12 weeks=.384), whereas system use at 2 weeks moderately predicted system use at 12 weeks (βuse at 12 weeks is predicted by use at 2 weeks=.239). Notably, there were uncertain associations between baseline variables (education, sex, and mental health symptoms) and system use at 2 weeks, indicating a need for better predictors for early system use.

CONCLUSIONS

This study underscores the importance of PU and early engagement in patient engagement with eHealth systems such as NEVERMIND. This suggests that, in general eHealth implementations, caregivers should educate patients about the benefits and functionalities of such systems, thus enhancing their understanding of potential health impacts. Concentrating resources on promoting early engagement is also essential given its influence on sustained use. Further research is necessary to clarify the remaining uncertainties, enabling us to refine our strategies and maximize the benefits of eHealth systems in health care settings.

A fuzzy-set qualitative comparative analysis exploration of multiple paths to users' continuous use behavior of diabetes self-management apps

BACKGROUND

Despite the obvious potential benefits of diabetes self-management apps, users' continuous use of diabetes self-management apps is still not widespread. Influential factors coexisted in information ecologies are likely to have a synthetic effect on users' continuous use behavior. However, it is less clear how factors in information ecologies combine to influence users' continuous use behavior.

OBJECTIVE

The objectives of this study are to explore combinations of factors (perceived severity, information quality, service quality, system quality, and social influence) in information ecologies that lead to users' continuous use behavior of diabetes self-management apps and which combination is the most important.

METHODS

Purpose sampling was used to recruit diabetes self-management app users from July 1, 2021 to January 31, 2022. Fuzzy-set qualitative comparative analysis (fsQCA) was then employed by conducting necessity and sufficiency analysis.

RESULTS

In total 280 diabetes self-management app users participated. The necessity analysis indicated that no single factor was necessary to cause users' continuous use behavior, and the sufficiency analysis identified five different combinations of factors that lead to users' continuous use behavior. Of these five, the combination of high information quality, high service quality, and high social influence was found to be the most important path.

CONCLUSIONS

Users' continuous use behavior of diabetes self-management apps results from the synergistic effects of factors in information ecologies. The five paths that directly contribute to users' continuous use, as well as the four user types preliminarily identified in this study may provide a reference for healthcare providers and app developers.

Paving the way for increased e-health record use: elaborating intentions of Gen-Z

This paper presents the determinants of personal e-health records adoption by the Gen-Z population and reveals barriers to use. Gen-Z members are one of the most prominent users of digital health services that have an influence on older generations' technology adoption but have often been overlooked in scholarly research. A survey of 1,000 Gen-Z university students based on modified UTAUT was used to address this research gap. The analysis revealed the vital role of social influence in paving the way for higher adoption among Gen-Z. Moreover, significant influences of performance expectancy, facilitating conditions, and e-health literacy on behavioural intentions were detected. Effort expectancy was found to be insignificant in impacting Gen-Z's intentions to adopt electronic health record systems. Moreover, privacy concerns acted as a barrier to adoption, yet the offsetting effect of users' trust in health systems was shown to be instrumental in overcoming such privacy-related barriers.