TELEHEALTH AND VIRTUAL NURSING CARE MODELS

Background: Telehealth and virtual nursing care models have become revolutionary methods of healthcare delivery, offering access to care remotely and improving the interaction between patients, and decreasing the use of the hospital facility when unnecessary. Although they have become increasingly important, doubts still exist regarding their reliability, validity, and acceptability by the various demographic groups. This research was intended to assess psychometric characteristics of a telehealth questionnaire and examine demographic, perceptual, and technological factors that determine the uptake of virtual nursing care. Methods: A cross-sectional survey was used, and 266 participants, such as nurses, physicians, patients, and caregivers, were involved. The structured questionnaire was administered as a data-gathering tool comprised of demographic questions and Likert-scale items, including the perception and quality of care, usability of technology, challenges, and future views. Statistical tests were the Shapiro–Wilk test (normality) and Cronbach's Alpha (reliability), Kaiser-Meyer Olkin and Bartlett test (validity), independent samples t-test, one-way ANOVA, Kruskal-Wallis test, Chi-square test of independence, Pearson correlation analysis, and multiple linear regression. Findings: Normality tests were used to ascertain whether the data were normally distributed (p > 0.05). That instrument showed a good reliability (Cronbach's Alpha = 0.87) and reasonable validity (KMO = 0.72, Bartlett's 2 = 560.45, p = 0.001). There were notable male-female (t = 2.45, p = 0.016) and occupational (ANOVA, p = 0.003; Kruskal-Wallis, p = 0.021) differences. According to the chi-square test, there was a significant relationship between gender and previous telehealth utilization (X 2 = 15.78, p=0.001). The analysis of the correlation showed positive relationships between perception, quality, technology usability, and future acceptance (r = 0.25 -0.85). Regression analysis has verified that factors that significantly predicted future adoption of telehealth were perception ( = 0.32, p = 0.001), quality ( = 0.28, p = 0.001), and technology usability ( = 0.21, p = 0.001). Conclusion: The study shows that the questionnaire was reliable and valid in the determination of telehealth nursing models. Results indicate that demographic variables like gender and occupation have a great impact on telehealth perceptions, whereas perception and technology usability have a strong association with future acceptance. In order to integrate tele-nursing into healthcare systems in a sustainable way, it should be approached by strategies to improve usability, quality of care, and tackle demographic disparities in uptake and use.