Willingness to use eHealth and associated factors Among Disabled Students in Higher Education Institutions in Debre Markos city 2025

Willingness to use eHealth and associated factors Among Disabled Students in Higher Education Institutions in Debre Markos city 2025 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Willingness to use eHealth and associated factors Among Disabled Students in Higher Education Institutions in Debre Markos city 2025 Gizaw Hailiye Teferi, Zegeye Regasa Hordofa, Andualem Fentahun Senishaw, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7768341/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Background eHealth technologies offer a way to improve healthcare access for students with impairments at higher academic institutes particularly in low-income areas like Ethiopia. However the willingness of students in these to use eHealth and the factors that influence willingness of students to use the platforms has not yet been thoroughly investigated. Objective The aim of this study is examine the willingness of disabled students at higher academic institutes in Debre Markos city to use eHealth and the factors influencing their willingness. Method Institution based cross-sectional study was conducted from November 2024 to January 2025 among disabled students at higher academic institutes in Debre Markos city. Multi-stage stratified sampled technique was used. Data were collected using structured interviewers administered questionnaire and analyzed using SPSS version 26. Descriptive statistics were computed to represent the characteristics of study participants and binary and multivariable logistic regression analysis was conducted to identify factors associated with willingness of students to use eHealth. Result Among the total study participants approached (168), 61.9% were willing to use eHealth service and mentioned mobile health and telemedicine as preferred platforms. Factors including but not limited to smartphone ownership (AOR = 3.1, 95% CI: 1.3–7.5, p = 0.01), previous knowledge about eHealth (AOR = 1.6, 95% CI: 1-3.6, p = 0.001), Favorable attitude (AOR = 2.6, 95% CI: 1.1–6.5, p = 0.002), Availability of internet (AOR = 2.5, 95% CI: 1.2–5.2, p = 0.015), and perceived ease of use (AOR = 4.2, 95% CI: 2.24–7.81, p < 0.001) were significantly associated with willingness. Conclusion Despite most of the study participants were aware of eHealth; the willingness level was moderate.. Prior knowledge about eHealth, attitude, internet accessibility and perceived ease of use were the factors associated with willingness to use eHealth services. Academic institutions may improve willingness level by offering training courses that could boost awareness and knowledge about eHealth potentials in improving health service access, integrating eHealth with assistive technology, and designing disability friendly platforms. eHealth disability higher education willingness use Ethiopia Figures Figure 1 Figure 2 Background The world is home to an estimated 1.3 billion people with some form of disability, which represents 16% of the global population. Eighty percent of those with disabilities reside in low- and middle-income nations( 1 ). The estimates of the proportion of disabled persons in Africa range from 10% of the continent's total population to 20% in the poorer regions, or 60–80 million individuals. However, this number may be greater in areas with extreme poverty. Ethiopia one of the second most populated country in Africa is a home for 15 million people with disability ( 2 , 3 ). The rapid integration of technology into healthcare has paved the way for eHealth, which encompasses electronic health services, tools, and applications designed to enhance the delivery and management of healthcare( 4 ). Telemedicine services, mobile health apps, and health information systems are valuable tools for overcoming major healthcare access challenges faced by people with disabilities. These technologies can greatly improve the way individuals with disabilities receive care. In colleges and universities, eHealth platforms are particularly beneficial for students with disabilities( 5 ). These platforms can provide essential support that helps disabled students manage chronic health conditions, access mental health resources, and maintain their general well-being. By using these platforms, students can better handle their health needs while focusing on their studies ( 6 ). The Role of eHealth in Supporting Disabled Students It is more difficult for students with disabilities access conventional health care service often encounter significant challenges in accessing traditional healthcare services( 7 ). The ability of these individuals to seek prompt medical assistance may be hampered by physical restrictions, transportation issues, and time restraints related to academic commitments( 8 ). These challenges may also be made worse by stigmatization and misunderstandings of their particular needs for healthcare. In order to solve the healthcare issues that impaired students in higher education institutions experience, eHealth technologies have become revolutionary tools( 9 ). By utilizing digital platforms, eHealth solutions offer remote access to medical services, allowing students with chronic illnesses or mobility impairments or other forms disability to receive prompt care without physically visiting a medical institution( 10 ). The potential of eHealth to enable tele-consultations, which let students communicate with medical professionals via video chats, is one of its many noteworthy advantages ( 11 , 12 ). Factors influencing willingness to use eHealth The willingness of disabled students to use eHealth services is influenced by several factors, including technological accessibility, digital literacy, perceived usefulness, and privacy concerns( 13 ). Ownership of a smartphone or digital device is a key technology determinant for access to eHealth platforms. Familiarity with different smartphone platforms like social media and more recent devices make it easier for students to use services( 14 ), and students with access to up-to-date devices are more likely to engage with them, because of compatibility and user experience issues that also depend on the connection overall( 15 ). When students perceive these platforms as useful for their health management and easy to use, their intention to use eHealth tools grows( 16 ). Experiences with similar technological systems and robust digital literacy skills greatly boost individuals' capacity to navigate, comprehend, and utilize digital health platforms effectively. The development of expertise in digital tools builds user confidence for eHealth service utilization while simultaneously shortening the technological use learning curve. The integration of technical skill enhancement with critical assessment capabilities enables users to independently resolve digital issues while fully exploiting the advantages provided by advanced healthcare systems( 17 ). Even though digital health technology has become increasingly ubiquitous in Higher academic institutions, students with disabilities may face unique challenges in navigating digital tools due to sensory, cognitive, or physical impairments( 18 ). Moreover, the perceived reliability of eHealth platforms, along with concerns about data security and confidentiality, plays a pivotal role in shaping their attitudes toward eHealth use( 19 ). eHealth utilization in higher educational institutes The universities are trying to grant disabled students accessibility to eHealth through support structures such as accessible eHealth platforms and training geared toward helping them improve their digital literacy skills. Assistive Technology provides services such as supplying various specialized resources and advanced technologies to allow students with disabilities to gain increased independence concerning the self-management of their health and well-being. They may include screen readers, voice recognition software, and adaptable input devices-all of which highly improve the accessibility of digital health services. Apart from improving such technological methods, structured training programs would enable such students to attain key digital skills, which in turn make them feel confident and even competent in navigating eHealth systems ( 20 ). Higher education institutions usually play the function of setting up innovative methods and at the same time linkers of healthcare providers and students( 21 ). Thus, the significance of these programs mostly lies in the ability to comprehend the exact requirements, choices, and readiness of the disabled students to make use of eHealth technologies( 22 ). Research gap and importance Despite the fact that eHealth is becoming more and more popular, the willingness of the disabled students in the higher education sector to use these technologies and the factors affecting their willingness are not yet fully exploited( 23 ). The most part of the previous work concentrates on general groups or healthcare surroundings, which in turn creates a space of awareness for the unique situations of disabled students at academic institutions ( 24 ). On the one hand, the recognition of whether the students find eHealth technology effective and the influence of their attitudes toward it in their own academic performance can be achieved only if the students are the ones responsible for recognizing the problem and solving it( 25 ). Hence the aim of this research is assess the willingness of disabled students in higher education institutions to use eHealth service, and factors associated with willingness. Method and material Study period and setting. A cross-sectional study was conducted among disabled students at higher academic institution students at Debre Markos city from November 05, 2024 to January 25, 2025. Debre Markos city is situated in the Amhara Regional State in northwestern Ethiopia. Serving as the capital of the East Gojjam Zone, the city was established around 1852. It is located approximately 300 kilometers from Addis Ababa, the capital of Ethiopia, and 265 kilometers from Bahir Dar, the regional capital. The city spans a geographic area of 6,160 square meters and encompasses 17,000 hectares divided into four sub-cities and 20 kebeles. Sampling procedure A multi-stage sampling technique was used. Initially, the institutions were divided into four different strata—private colleges, a university, a polytechnic college, and a preparatory school—using a stratified sampling technique. From 9 private colleges three colleges were chosen by simple random sampling among the private college stratum. For the remaining three institutions—Debre Markos University, Debre Markos Polytechnic College, and Debre Markos Preparatory School—purposive sampling was used. In order to ensure that all eligible participants were included in the study, a census method was finally used to include all students with impairments in the chosen institutions. The selection of this sampling technique was made in order to strike a balance between the requirements for inclusivity, pragmatism, and representativeness. The study included forty-four students from a preparatory school, sixteen from Debre Markos Polytechnic, twenty-two students from private colleges, and the remaining(93) students from Debre Markos University Source population and study population All students with disability in higher academic institutions in Debre Markos city Study population All students with disability from three private colleges, Debre Markos University, Debre Markos Polytechnic, and Debre Markos preparatory school were the study population for this study. Study variables and operational definitions Outcome variable The study's dependent variable was the participants' willingness to use eHealth (Yes/No) . Five Likert-scale questions were utilized to measure disabled students' willingness to use eHealth platforms, and the results were converted to a binary response (Yes/No). Independent variables The independent variables were socio-demographic factors (age, sex, department, year of study, smartphone type, and health app availability), system-related factors (perceived ease of use, perceived usefulness, innovativeness, optimism, discomfort), organizational factors (infrastructure), and behavioral factors (technical skill, trust). Operational definition Disability: Refers to a physical, sensory, mental, or intellectual condition that significantly restricts a person's ability to perform everyday activities or participate fully in society on an equal basis with others( 26 ). Willingness to use eHealth: Willingness of students with disability to use eHealth was measured using five willingness likert-scale questions( 27 ). The students with a score of 3 or higher were labeled as willing to use, while students who score less than a score of 3 labeled as not willing( 28 ). Data collection procedure and quality control The data were collected using a structured, interviewer-administered questionnaire adapted from a previous study and adjusted to fit to our context. The tool comprises 42 questions covering socio-demographic characteristics, prior knowledge, affordability, and willingness, perceived ease of use, perceived usefulness, and overall attitude. Sign language interpreters facilitated data collection from students with hearing impairments. Prior to the main data collection, a pilot study was conducted with 15 students from Injibara University. The tool's validity was assessed by panel of expert and factor analysis. Internal consistency were assessed using Cronbach’s alpha (0.78). Based on the pretest findings, adjustments were made to the questionnaire. Participants included students were from three private owned colleges (Gabist, Ghion, Brana), Debre Markos polytechnic college and Debre Markos University. They were invited to participate during their first morning class, with the process lasting 45 minutes. Data collectors received two days of training on the study’s objectives, participants’ rights, and data collection procedures. Supervisors closely monitored adherence to participants’ rights and ensured the quality of the data collected. This cross-sectional study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines( 29 ). The STROBE framework was utilized to ensure accurate reporting of the study design, methodology, and findings. Data management and analysis After the collection the data were exported from Kobo tool to excel and preprocessed to remove missing values and invalid entries and then analyzed with SPSS version 26. Descriptive analyses were performed to summarize the socio-demographic characteristics of disabled students and assess their willingness to use eHealth services presented using frequency and cross tabulation. Binary logistic regression was performed to examine the effect of each independent variable on willingness to use eHealth at a 95% confidence level. Variables with a p-value of 0.02 were considered for inclusion in the multivariable logistic regression. Multivariable analysis was then conducted to identify key factors influencing the willingness of disabled students to use eHealth. Adjusted odds ratios, along with 95% confidence intervals and p-values, were calculated to determine the strength and significance of associations between dependent and independent variables. Model fitness was tested using the Hosmer-Lemeshow goodness-of-fit test. Multi-collinearity among variables for the final model was assessed using variance inflation factors and no significant multicollinearity was detected among the variables included in the multivariable analysis. Result Socio-demographic characteristics of the respondents Out of 175 disabled students surveyed, 168 valid responses were received, yielding a response rate of 96%. The majority of participants 120(71.4%) were male, with 56% of the students were from Debre Markos University. Over half (62.5%) the study participants reported being a visual impaired, followed by physical disability (31%) and most of the students are enrolled in social science studies 120(76.2%). (Table 1 ). Table 1 Socio-demographic characteristics of disabled students at Debre Markos city (N = 168) Variable Category Frequency Percentage Gender Male 120 71.4% Female 48 28.6% Age Under 20 years 20 11.9% 20–25 years 88 52.4% Above 25 years 60 35.7% Institution Debre Markos University 94 56% Debre Markos Poly technic 16 9.5% Private colleges 35 20.8% Debre Markos preparatory school 23 13.7% Disability type Visual impairment 105 62.5% Hearing impairment 4 2.4% Mobility impairment 59 35.1% Marital status Single 120 71.4% Married 36 21.4% Divorced 12 7.1% Parental income > 5000 ETB 96 57.1% 5000–10000 ETB 60 35.7% 10000–15000 ETB 8 4.8% > 15000 ETB 4 2.4% Place residence Rural 96 57.1% Urban 72 42.9% Device ownership Feature phone 112 66.7% Smartphone 56 33.3% Access to technology and Awareness of eHealth among disable students Only 56(33.3%) of the respondents owned smartphones or devices enabling internet access and have internet access. Students were inquired about social media usage and 38.1% of the students use social media platform of which 33% used telegram followed by tiktok (31%) Fig. 1 . Among the study participants, 90% had heard of eHealth, with mobile health (50%) and Telemedicine (40.5%) being the most recognized services Fig. 2 . Beside the students were asked to select the types of communication media they prefer in relation to access information through eHealth platform and all of them preferred information in the form of Audio followed by video and picture. Willingness to Use eHealth and Preferences Among participants, 61.9% expressed willingness to use eHealth services if accessible. Preferred platforms included mobile apps (54.9%) and university-hosted portals (36.2%). Students were asked the preferred communication way of eHealth service most of the students preferred audio transmit service 128(76%) followed by video channels 13% while 11% of the students choose both video and picture. Determinants of eHealth Willingness The results of the bivariate analyses showed that age, place of residence, family monthly income, internet availability, ownership of a mobile device, attitude, perceived easiness, prior social media usage and perceived usefulness were associated with willingness to use eHealth services among students with disabilities at p < 0.2 Table 2 . All these factors were included in the multivariable logistic regression analysis model to control for potential confounders. Table 2 Bi-variable and multivariable logistic regression analysis result (N = 168) Variable Category Willingness OR(95% CI) AOR(95% CI) P value Yes No Age Under 20 years 12 8 1 1 20–25 years 64 24 1.78[1.5-6] 1.5[1.2–8.3] .003 Above 25 years 28 32 .58[.41-.74] .52[.2-2.01] .4 Place of residence Urban 44 20 1.32[.57 − 3.7] 1.22[.61 − 2.4] .56 Rural 60 36 1 1 Smartphone ownership Yes 46 10 4.35[2-9.6] 3.1[1.3–7.5] .01 No 57 54 1 1 Internet availability Yes 44 14 2.6[1.2–5.3] 2.5[1.2–5.2] .015 No 60 50 1 1 Knowledge Yes 88 45 2.3[1-4.9] 1.6[1-3.6] .001 No 16 19 Attitude Favorable 92 40 4.6[2.8–20] 2.6[1.1–6.5] .002 Unfavorable 12 24 1 1 Perceived easiness Yes 88 12 5.5[.21 − 14] 4.2[1.3–13.6] .014 No 16 12 1 Perceived usefulness Yes 96 44 5.4[2.2–13.3] 2.9[1.04–8.1] .012 No 8 20 1 1 Note: The stated p-values correspond to the adjusted odds ratio The study revealed several key factors influencing the willingness of disabled students to use eHealth services. Age of the of the students was of the factors that associate with willingness, students with age group 20 to 25 was 1.5 times more likely to express willingness to use eHealth platforms compared to under 20 age groups (AOR: 1.5, CI: 1.2–8.3, p = 0.003). Owning smartphone is strongly linked to willingness, with smartphone users being over three times more likely to be willing (AOR 3.1 95% CI: 1.3–7.5, p = 0.01). Likewise, having internet access increases the likelihood of willingness by 2.5 times, supported by confidence levels (95% CI: 1.2–5.2, p = 0.015). Previous knowledge about eHealth platform and favorable attitude were significant associated factors to willingness, Students who had prior knowledge were 1.6 times more likely willing to use eHealth platform compared to their counterpart’s. Furthermore, perceived easiness of the eHealth platform was a powerful determinant of willingness to use eHealth. Platforms with use friendly interface and easy to navigate were 4.2 times more likely to be used (AOR: 4.18, CI: 2.24–7.81, p < 0.001), underscoring the critical consideration in the designing user specific platforms. Meanwhile, where someone lives doesn't have a big impact on their willingness. These findings emphasize that having technology, prior knowledge, good attitudes, and seeing benefits are crucial in affecting whether someone is willing or not. Discussion Unintended barriers to healthcare access, such as physical inaccessibility, communication challenges, and stigma, could be mitigated through the use of eHealth technologies, which offer remote consultations, digital health monitoring, and accessible health information. This study aimed to assess the willingness of disabled students at higher institutions in Debre Markos Town to use eHealth and identify factors influencing their willingness. In the current study, nearly all participants (90%) were aware of eHealth platforms. This, awareness level is higher compared to study in Gondar Ethiopia (73.7%)( 30 ). The disparity may reflect greater internet penetration, institutional promotion of digital tools, and targeted disability-inclusive initiatives in urban academic settings. Despite high awareness, only 61.9% of respondents expressed strong willingness to use eHealth. This gap may stem from inadequate digital literacy, concerns about privacy, or lack of tailored eHealth solutions for diverse disabilities. A study evaluating nursing students' confidence and willingness to use eHealth showed similar results, despite differences in the study population( 31 ).Among participants aware of eHealth, 50% identified m-Health as a primary service, while 16.7% recognized both telemedicine and mobile health apps. Key factors significantly associated with the willingness to use eHealth among disabled students included age, device ownership, knowledge, attitude and internet access among others. In this study middle age groups ( 20 – 25 ) were two times more likely to be willing to use eHealth compared to the age groups 15 to 20, while age groups above 25 were not associated with willingness of students to use eHealth. Ownership of electronic device (smartphone) which enables to use eHealth and accessibility of the internet where the students live were significant associated with willingness. Those who had internet access were 2.5 times more likely willing, while those with smartphone were more than three times more likely to be willing than those without. This result is comparable with previous researches indicating that access to digital device increase tendency to use eHealth ( 32 – 34 ). Additionally, participants tended to be willing to use eHealth when they had prior knowledge, demonstrating the importance of awareness in decision-making. This result aligns with Bandura's Social Cognitive Theory, which holds that learning affects behavior through the concepts of perceived control and self-efficacy ( 35 ). In particular, people who had a favorable attitude were more likely to be willing than those who had unfavorable attitude. This is in line with Theory of Planned Behavior, which holds that attitude plays a significant role in determining one's intention to carry out a particular behavior( 36 ). The perceived easiness of eHealth platform interfaces and perceived usefulness of the eHealth service were other factors strongly associated with willingness, which is in line with technology acceptance model assumptions ( 33 , 37 ). The perception of ease of use and usefulness is vital factor that influence behavioral intentions ( 38 , 39 ). These confirm that user-friendly design may boost student’s willingness to use. A study examining the digital divide between students with and without disabilities supports this finding. It revealed that students with disabilities had more difficulty using eHealth platforms compared to their non-disabled peers. This highlights the need for eHealth platform design to incorporate accessible features—such as voice recognition and Braille—to accommodate various types of disabilities( 40 ). However research was focused on Debre Markos Town, which may limit the generalizability of the findings to rural areas or non-academic populations. Furthermore, the study may have some bias in how visual impairment status and phone user status all varied among the participants. It is possible that the students with some visual impairment may have had difficulty interacting with the websites or digital platforms used in the study and the study process. Students' responses to the survey measures and ultimately, their experiences using eHealth tools may have been affected. Conclusion while awareness of eHealth is high among disabled students in Debre Markos, willingness to use these tools is moderate and influenced by age, smartphone ownership, and attitude and internet access. Intervention like improved internet access around disabled student dormitory, user interface tailored to disability type such as screen integration may enhance willingness of students to use eHealth. Future research should employ mixed methods to capture nuanced barriers and include populations outside academic institution to inform national disability-inclusive health policies. Declarations Ethics approval and consent to participate This study adhered to all ethical standards for conducting research. Ethical approval was obtained from the Debre Markos University Ethical Review Board, and permission to involve participants was secured from the respective college deans and admins. Furthermore, written informed consent was gained from all participants. Participation was entirely voluntary, and no incentives were offered to the participants. Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests Authors declare conflict of interest. Funding No funding received to conduct this study. Authors' contributions GHT conceptualized the research idea, conducted the statistical analyses, and prepared the original draft of the manuscript. MMT, AFS, TFD, ZRH and GTB were responsible for data entry and cleaning. ASG, LME, BLT, and TSM contributed to data analysis. All authors reviewed and approved the final version of the manuscript. Acknowledgements The researcher expresses sincere gratitude to Debre Markos University for its support and collaboration in conducting this study. Deep appreciation is extended to the data collectors for their commitment to data collection, and the research participants, the disabled students in higher educational institutions of Debre Markos City for their willingness to give their time. References Organization WH. Global report on health equity for persons with disabilities. World Health Organization; 2022. Swartz L. Representing disability and development in the global south. Med Humanit. 2018;44(4):281–4. Zeleke FT, Admas M, Alemnew Chekole F, Alem KG, Tenaw SG, Tefera DT, et al. Sexual and Reproductive Health Services Utilization and Associated Factors among Disabled Students in Selected Public Universities of Ethiopia. Sex Disabil. 2024;42(1):67–83. Hejazinia R. A framework for the requirements of e-health 2.0 in developing countries: a qualitative approach. Hum Inform Interact. 2023;10(3):77–95. Ha S, Ho SH, Bae Y-H, Lee M, Kim JH, Kim JH, et al. Digital Health Equity and Tailored Health Care Service for People With Disability: User-Centered Design and Usability Study. J Med Internet Res. 2023;25:e50029. Burns J, Birrell E. Enhancing early engagement with mental health services by young people. Psychology research and behavior management. 2014:303 – 12. Abodey E. Access to healthcare services among students with disabilities in Ghana. University of Cape coast; 2018. Ali A, Scior K, Ratti V, Strydom A, King M, Hassiotis A. Discrimination and other barriers to accessing health care: perspectives of patients with mild and moderate intellectual disability and their carers. PLoS ONE. 2013;8(8):e70855. Organization WH. Global diffusion of eHealth: making universal health coverage achievable: report of the third global survey on eHealth. World Health Organization; 2017. Al-Shorbaji N. Improving Healthcare Access through Digital Health: The Use of Information and Communication Technologies. 2021. Haleem A, Javaid M, Singh RP, Suman R. Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sens Int. 2021;2:100117. Tesfaye T, Woldesemayat EM, Chea N, Wachamo D. Accessing Healthcare Services for People with Physical Disabilities in Hawassa City Administration, Ethiopia: A Cross-Sectional Study. Risk Manage Healthc policy. 2021;14:3993–4002. Ali MA, Alam K, Taylor B, Ashraf M. Examining the determinants of eHealth usage among elderly people with disability: The moderating role of behavioural aspects. Int J Med Informatics. 2021;149:104411. Cho J, Quinlan MM, Park D, Noh G-Y. Determinants of adoption of smartphone health apps among college students. Am J Health Behav. 2014;38(6):860–70. Fisher M, Baird DE. Making mLearning work: Utilizing mobile technology for active exploration, collaboration, assessment, and reflection in higher education. J Educational Technol Syst. 2006;35(1):3–30. Shen H, van der Kleij R, van der Boog PJ, Wang W, Song X, Li Z, et al. Digital tools/eHealth to support CKD self-management: A qualitative study of perceptions, attitudes and needs of patients and health care professionals in China. Int J Med Informatics. 2022;165:104811. Ban S, Kim Y, Seomun G. Digital health literacy: A concept analysis. Digit Health. 2024;10:20552076241287894. Sharma S, Dureja S, Saini D, Jose R, Pant R, Singh A. Empowering impaired learners: Technological advancements in higher education. Technol Disabil. 2025:10554181251313711. Abdelwahed NAA, Al Doghan MA, Saraih UN, Soomro BA. Digital technology and intentions to adopt digital e-health practices among health-care professionals. Int J Hum Rights Healthc. 2025;18(1):36–57. Petretto DR, Carrogu GP, Gaviano L, Berti R, Pinna M, Petretto AD, et al. Telemedicine, e-Health, and Digital Health Equity: A Scoping Review. Clin Pract Epidemiol mental health: CP EMH. 2024;20:e17450179279732. van Niekerk L, Mathanga DP, Juban N, Castro-Arroyave DM, Balabanova D. Universities as catalysts of social innovation in health systems in low-and middle-income countries: a multi-country case study. Infect Dis Poverty. 2020;9(1):90. Fortune J, Manikandan M, Harrington S, Hensey O, Kerr C, Koppe S, et al. Understanding the use of digital technologies to provide disability services remotely during the COVID-19 pandemic; a multiple case study design. BMC Health Serv Res. 2024;24(1):323. Nickbakht M, Meyer C, Scarinci N, Beswick R. Exploring factors influencing the use of an eHealth intervention for families of children with hearing loss: An application of the COM-B model. Disabil health J. 2020;13(4):100921. Brewer G, Urwin E, Witham B. Disabled student experiences of Higher Education. Disabil Soc. 2025;40(1):108–27. van Velsen L, Ludden G, Grünloh C. The limitations of user-and human-centered design in an eHealth context and how to move beyond them. J Med Internet Res. 2022;24(10):e37341. Shakespeare T. Disability: the basics. Routledge; 2017. Berihun B, Atnafu DD, Sitotaw G. Willingness to use electronic medical record (EMR) system in healthcare facilities of Bahir Dar City, Northwest Ethiopia. Biomed Res Int. 2020;2020(1):3827328. Senishaw AF, Tilahun BC, Nigatu AM, Mengiste SA, Standal K. Willingness to use electronic medical record (EMR) system and its associated factors among health professionals working in Amhara region Private Hospitals 2021, Ethiopia. PLoS ONE. 2023;18(5):e0282044. Cuschieri S. The STROBE guidelines. Saudi J Anaesth. 2019;13(Suppl 1):S31–4. Belachew EA, Getachew D, Netere AK, Gizachew E, Sendekie AK. Perception, willingness, and practices of telemedicine in patients with chronic diseases: implication of digital health in patients' perspective at a tertiary care hospital in Ethiopia. Front Public Health. 2023;11:1234436. Priya B, Ramya Kundayi R. Nursing Students’ Perceived Confidence in eHealth Concepts and Willingness to Learn: A Multi-site Cross-sectional Survey in India. New Emirates Med J. 2024;5:1–5. Bernhard T, Bygrave F, Witherspoon NO. Social media as a tool for breaking the cycle of children's environmental health disparities. Int Public Health J. 2018;10(4):527–34. Kassaw M, Amare G, Shitu K, Tilahun B, Assaye BT. Willingness to use remote patient monitoring among cardiovascular patients in a resource-limited setting: a cross-sectional study. Front Digit Health. 2024;6:1437134. Huisman M, van Dijk J. (2020). The digital divide. Cambridge/Medford: Polity. 208 pp. De Gruyter Mouton; 2021. Bandura A. Self-efficacy: The exercise of control. Macmillan; 1997. Ajzen I. The theory of planned behaviour. organizational behaviour and human decision processes. De Young. 1991;50(2):179–211. Masrom M. Technology acceptance model and e-learning. Technology. 2007;21(24):81. Wiprayoga P, Gede S, Suasana G. The role of attitude toward using mediates the influence of perceived usefulness and perceived ease of use on behavioral intention to use. Russian J Agricultural Socio-Economic Sci. 2023;140(8):53–68. Marhefka SL, Turner D, Lockhart E. Understanding Women's Willingness to Use e-Health for HIV-Related Services: A Novel Application of the Technology Readiness and Acceptance Model to a Highly Stigmatized Medical Condition. Telemedicine e-Health. 2019;25(6):511–8. Pettersson L, Johansson S, Demmelmaier I, Gustavsson C. Disability digital divide: survey of accessibility of eHealth services as perceived by people with and without impairment. BMC Public Health. 2023;23(1):181. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Feb, 2026 Reviews received at journal 16 Feb, 2026 Reviews received at journal 04 Dec, 2025 Reviewers agreed at journal 28 Nov, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviews received at journal 25 Nov, 2025 Reviewers agreed at journal 25 Nov, 2025 Reviews received at journal 24 Nov, 2025 Reviewers agreed at journal 23 Nov, 2025 Reviewers invited by journal 14 Nov, 2025 Editor assigned by journal 12 Nov, 2025 Editor invited by journal 17 Oct, 2025 Submission checks completed at journal 17 Oct, 2025 First submitted to journal 17 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7768341","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":550146652,"identity":"c098b0a7-33e3-436e-840a-b7a24c3df4de","order_by":0,"name":"Gizaw Hailiye Teferi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYDACZjB5gIGNnbGBgaECwpUgTgszSMsZhBb82kBawHoZ24jQIu/O/vAzD8MdeT5m5jaJj/Osow0OMB+8zcNgU4dLi+FhhmRpHoZnhm3MjG2SM7el5244wJZszcOQhtMWw2aGA9I5DIcZQVqkebcdBmrhMQMachiPFsbm30At9mAtf+eAtPB/A2r5j9svzMxsIFsSwVoYG8C2sAG1HMCpxYCZjc36D8PhZKCWZsueY+m5Mw+zGVvOMUiWbMBlS//xxzdnMBy2nd/e/vDGjxrr3L7jzQ9vvKmw48dpywEgwfgPzGaBuAUcNQa4NABtQbKe+QNudaNgFIyCUTCSAQD5Wk+o0Hzi6gAAAABJRU5ErkJggg==","orcid":"","institution":"Debre Markos University","correspondingAuthor":true,"prefix":"","firstName":"Gizaw","middleName":"Hailiye","lastName":"Teferi","suffix":""},{"id":550146654,"identity":"456377ad-021e-46e4-96e5-a1ba249629fc","order_by":1,"name":"Zegeye Regasa Hordofa","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Zegeye","middleName":"Regasa","lastName":"Hordofa","suffix":""},{"id":550146655,"identity":"d3194c67-9b1e-4336-befc-7c696991ccee","order_by":2,"name":"Andualem Fentahun Senishaw","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Andualem","middleName":"Fentahun","lastName":"Senishaw","suffix":""},{"id":550146656,"identity":"8aeb2ba3-7649-4f1a-99e8-3aa6d277d5aa","order_by":3,"name":"Getaye Tizazu Biwota","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Getaye","middleName":"Tizazu","lastName":"Biwota","suffix":""},{"id":550146661,"identity":"22fa74d3-f8ad-404b-9f01-9e7647cf2671","order_by":4,"name":"Temesgen Feyu Desalegn","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Temesgen","middleName":"Feyu","lastName":"Desalegn","suffix":""},{"id":550146662,"identity":"714c263b-b00a-45b6-90ac-ca3a7c82a381","order_by":5,"name":"Binyam Lakew Tilahun","email":"","orcid":"","institution":"Arsi University","correspondingAuthor":false,"prefix":"","firstName":"Binyam","middleName":"Lakew","lastName":"Tilahun","suffix":""},{"id":550146666,"identity":"f57cd727-aafd-403a-8244-c91efe67ab3e","order_by":6,"name":"Ayenew Sisay Gebeyehu","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Ayenew","middleName":"Sisay","lastName":"Gebeyehu","suffix":""},{"id":550146667,"identity":"478daa59-4aa8-46d3-9001-a16562daf32a","order_by":7,"name":"Tesfaye Shumet Mekonnen","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Tesfaye","middleName":"Shumet","lastName":"Mekonnen","suffix":""},{"id":550146669,"identity":"d87daa49-ca1b-4a26-8472-cbf8f26ec0f9","order_by":8,"name":"Lijalem Megibaru Eneyew","email":"","orcid":"","institution":"Debre Markos University Institute of technology","correspondingAuthor":false,"prefix":"","firstName":"Lijalem","middleName":"Megibaru","lastName":"Eneyew","suffix":""},{"id":550146670,"identity":"a3577e6f-9c2b-4cb2-9d92-fc940bafacd2","order_by":9,"name":"Maru Meseret Tadele","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Maru","middleName":"Meseret","lastName":"Tadele","suffix":""}],"badges":[],"createdAt":"2025-10-02 17:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7768341/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7768341/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96739021,"identity":"d07aaceb-0401-4e94-a6d5-dfb7d82000db","added_by":"auto","created_at":"2025-11-25 14:48:12","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92614,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscripteHealth.docx","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/7dc5f5d937984ac86da1c5b5.docx"},{"id":96914760,"identity":"16c9e450-aaf6-40e3-ac31-103a0b71028d","added_by":"auto","created_at":"2025-11-27 14:06:21","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9680,"visible":true,"origin":"","legend":"","description":"","filename":"c033c587e575480b89799941467b7541.json","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/f8d16dd23cfcb9ed70002b3b.json"},{"id":96739022,"identity":"0fb77345-07b2-4655-9e18-a3e6e6c76879","added_by":"auto","created_at":"2025-11-25 14:48:12","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":103527,"visible":true,"origin":"","legend":"","description":"","filename":"c033c587e575480b89799941467b75411enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/9c3f8b8eeca87934440dc8ac.xml"},{"id":96913310,"identity":"b7f5d12f-d04f-4b58-a248-3d2390020746","added_by":"auto","created_at":"2025-11-27 13:58:01","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100815,"visible":true,"origin":"","legend":"","description":"","filename":"c033c587e575480b89799941467b75411structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/06145031b269feb58137c64a.xml"},{"id":96739024,"identity":"6ff50a81-3c3b-45dd-8ec3-8347a8b4059d","added_by":"auto","created_at":"2025-11-25 14:48:12","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110520,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/708cc4687eb26ad1869b8bb8.html"},{"id":96739018,"identity":"50850850-9a86-4212-85ca-c527c93b4c8e","added_by":"auto","created_at":"2025-11-25 14:48:12","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78440,"visible":true,"origin":"","legend":"\u003cp\u003eSocial media usage pattern among disabled students at higher education institute in Debre Markos city.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/7667cde6ed8d0e99614b2b4d.jpg"},{"id":96739019,"identity":"cd5ae4e2-49ad-4a8d-abc9-2f616f30c880","added_by":"auto","created_at":"2025-11-25 14:48:12","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44324,"visible":true,"origin":"","legend":"\u003cp\u003eeHealth platform mentioned (Note: students can choose more than 1 option)\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/3af6521b3361d32fac7254e5.jpg"},{"id":96922221,"identity":"4da6c5ff-1c08-42e9-9c02-5f047cee0809","added_by":"auto","created_at":"2025-11-27 14:18:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1093488,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7768341/v1/b259a7c5-1e71-4de1-ba41-666d3085f9fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Willingness to use eHealth and associated factors Among Disabled Students in Higher Education Institutions in Debre Markos city 2025","fulltext":[{"header":"Background","content":"\u003cp\u003eThe world is home to an estimated 1.3\u0026nbsp;billion people with some form of disability, which represents 16% of the global population. Eighty percent of those with disabilities reside in low- and middle-income nations(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The estimates of the proportion of disabled persons in Africa range from 10% of the continent's total population to 20% in the poorer regions, or 60\u0026ndash;80\u0026nbsp;million individuals. However, this number may be greater in areas with extreme poverty. Ethiopia one of the second most populated country in Africa is a home for 15\u0026nbsp;million people with disability (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe rapid integration of technology into healthcare has paved the way for eHealth, which encompasses electronic health services, tools, and applications designed to enhance the delivery and management of healthcare(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTelemedicine services, mobile health apps, and health information systems are valuable tools for overcoming major healthcare access challenges faced by people with disabilities. These technologies can greatly improve the way individuals with disabilities receive care. In colleges and universities, eHealth platforms are particularly beneficial for students with disabilities(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These platforms can provide essential support that helps disabled students manage chronic health conditions, access mental health resources, and maintain their general well-being. By using these platforms, students can better handle their health needs while focusing on their studies (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eThe Role of eHealth in Supporting Disabled Students\u003c/h3\u003e\n\u003cp\u003eIt is more difficult for students with disabilities access conventional health care service often encounter significant challenges in accessing traditional healthcare services(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The ability of these individuals to seek prompt medical assistance may be hampered by physical restrictions, transportation issues, and time restraints related to academic commitments(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These challenges may also be made worse by stigmatization and misunderstandings of their particular needs for healthcare. In order to solve the healthcare issues that impaired students in higher education institutions experience, eHealth technologies have become revolutionary tools(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). By utilizing digital platforms, eHealth solutions offer remote access to medical services, allowing students with chronic illnesses or mobility impairments or other forms disability to receive prompt care without physically visiting a medical institution(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The potential of eHealth to enable tele-consultations, which let students communicate with medical professionals via video chats, is one of its many noteworthy advantages (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eFactors influencing willingness to use eHealth\u003c/h2\u003e\u003cp\u003eThe willingness of disabled students to use eHealth services is influenced by several factors, including technological accessibility, digital literacy, perceived usefulness, and privacy concerns(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Ownership of a smartphone or digital device is\u0026ensp;a key technology determinant for access to eHealth platforms. Familiarity with different smartphone platforms like social media and more recent devices make it easier for students to use services(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e),\u0026ensp;and students with access to up-to-date devices are more likely to engage with them, because of compatibility and user experience issues that also depend on the connection overall(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). When students perceive these platforms\u0026ensp;as useful for their health management and easy to use, their intention to use eHealth tools grows(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Experiences with similar technological systems and robust digital literacy skills greatly boost individuals' capacity to navigate, comprehend, and utilize digital health platforms effectively. The development of expertise in digital tools builds user confidence for eHealth service utilization while simultaneously shortening the technological use learning curve. The integration of technical skill enhancement with critical assessment capabilities enables users to independently resolve digital issues while fully exploiting the advantages provided by advanced healthcare systems(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEven though digital health technology has become increasingly ubiquitous in Higher academic institutions, students with disabilities may face unique challenges in navigating digital tools due to sensory, cognitive, or physical impairments(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Moreover, the perceived reliability of eHealth platforms, along with concerns about data security and confidentiality, plays a pivotal role in shaping their attitudes toward eHealth use(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eeHealth utilization in higher educational institutes\u003c/h3\u003e\n\u003cp\u003eThe universities are trying to grant disabled students accessibility to eHealth through support structures such as accessible eHealth platforms and training geared toward helping them improve their digital literacy skills. Assistive Technology provides services such as supplying various specialized resources and advanced technologies to allow students with disabilities to gain increased independence concerning the self-management of their health and well-being. They may include screen readers, voice recognition software, and adaptable input devices-all of which highly improve the accessibility of digital health services. Apart from improving such technological methods, structured training programs would enable such students to attain key digital skills, which in turn make them feel confident and even competent in navigating eHealth systems (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Higher education institutions usually play the function of setting up innovative methods and at the same time linkers of healthcare providers and students(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Thus, the significance of these programs mostly lies in the ability to comprehend the exact requirements, choices, and readiness of the disabled students to make use of eHealth technologies(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eResearch gap and importance\u003c/h3\u003e\n\u003cp\u003eDespite the fact that eHealth is becoming more and more popular, the willingness of the disabled students in the higher education sector to use these technologies and the factors affecting their willingness are not yet fully exploited(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The most part of the previous work concentrates on general groups or healthcare surroundings, which in turn creates a space of awareness for the unique situations of disabled students at academic institutions (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). On the one hand, the recognition of whether the students find eHealth technology effective and the influence of their attitudes toward it in their own academic performance can be achieved only if the students are the ones responsible for recognizing the problem and solving it(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHence the aim of this research is assess the willingness of disabled students in higher education institutions to use eHealth service, and factors associated with willingness.\u003c/p\u003e"},{"header":"Method and material","content":"\u003cp\u003e\u003cb\u003eStudy period and setting.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA cross-sectional study was conducted among disabled students at higher academic institution students at Debre Markos city from November 05, 2024 to January 25, 2025. Debre Markos city is situated in the Amhara Regional State in northwestern Ethiopia. Serving as the capital of the East Gojjam Zone, the city was established around 1852. It is located approximately 300 kilometers from Addis Ababa, the capital of Ethiopia, and 265 kilometers from Bahir Dar, the regional capital. The city spans a geographic area of 6,160 square meters and encompasses 17,000 hectares divided into four sub-cities and 20 kebeles.\u003c/p\u003e\n\u003ch3\u003eSampling procedure\u003c/h3\u003e\n\u003cp\u003eA multi-stage sampling technique was used. Initially, the institutions were divided into four different strata—private colleges, a university, a polytechnic college, and a preparatory school—using a stratified sampling technique. From 9 private colleges three colleges were chosen by simple random sampling among the private college stratum. For the remaining three institutions—Debre Markos University, Debre Markos Polytechnic College, and Debre Markos Preparatory School—purposive sampling was used. In order to ensure that all eligible participants were included in the study, a census method was finally used to include all students with impairments in the chosen institutions. The selection of this sampling technique was made in order to strike a balance between the requirements for inclusivity, pragmatism, and representativeness. The study included forty-four students from a preparatory school, sixteen from Debre Markos Polytechnic, twenty-two students from private colleges, and the remaining(93) students from Debre Markos University\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSource population and study population\u003c/h2\u003e\u003cp\u003eAll students with disability in higher academic institutions in Debre Markos city\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eAll students with disability from three private colleges, Debre Markos University, Debre Markos Polytechnic, and Debre Markos preparatory school were the study population for this study.\u003c/p\u003e\n\u003ch3\u003eStudy variables and operational definitions\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eOutcome variable\u003c/h2\u003e\u003cp\u003eThe study's dependent variable was the participants' willingness to use eHealth \u003cb\u003e(Yes/No)\u003c/b\u003e. Five Likert-scale questions were utilized to measure disabled students' willingness to use eHealth platforms, and the results were converted to a binary response (Yes/No).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eIndependent variables\u003c/h2\u003e\u003cp\u003eThe independent variables were socio-demographic factors (age, sex, department, year of study, smartphone type, and health app availability), system-related factors (perceived ease of use, perceived usefulness, innovativeness, optimism, discomfort), organizational factors (infrastructure), and behavioral factors (technical skill, trust).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eOperational definition\u003c/h2\u003e\u003cp\u003eDisability: Refers to a physical, sensory, mental, or intellectual condition that significantly restricts a person's ability to perform everyday activities or participate fully in society on an equal basis with others(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWillingness to use eHealth: Willingness of students with disability to use eHealth was measured using five willingness likert-scale questions(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The students with a score of 3 or higher were labeled as willing to use, while students who score less than a score of 3 labeled as not willing(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eData collection procedure and quality control\u003c/h2\u003e\u003cp\u003eThe data were collected using a structured, interviewer-administered questionnaire adapted from a previous study and adjusted to fit to our context. The tool comprises 42 questions covering socio-demographic characteristics, prior knowledge, affordability, and willingness, perceived ease of use, perceived usefulness, and overall attitude. Sign language interpreters facilitated data collection from students with hearing impairments. Prior to the main data collection, a pilot study was conducted with 15 students from Injibara University. The tool's validity was assessed by panel of expert and factor analysis. Internal consistency were assessed using Cronbach’s alpha (0.78). Based on the pretest findings, adjustments were made to the questionnaire. Participants included students were from three private owned colleges (Gabist, Ghion, Brana), Debre Markos polytechnic college and Debre Markos University. They were invited to participate during their first morning class, with the process lasting 45 minutes. Data collectors received two days of training on the study’s objectives, participants’ rights, and data collection procedures. Supervisors closely monitored adherence to participants’ rights and ensured the quality of the data collected.\u003c/p\u003e\u003cp\u003eThis cross-sectional study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The STROBE framework was utilized to ensure accurate reporting of the study design, methodology, and findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eData management and analysis\u003c/h2\u003e\u003cp\u003eAfter the collection the data were exported from Kobo tool to excel and preprocessed to remove missing values and invalid entries and then analyzed with SPSS version 26. Descriptive analyses were performed to summarize the socio-demographic characteristics of disabled students and assess their willingness to use eHealth services presented using frequency and cross tabulation. Binary logistic regression was performed to examine the effect of each independent variable on willingness to use eHealth at a 95% confidence level. Variables with a p-value of 0.02 were considered for inclusion in the multivariable logistic regression. Multivariable analysis was then conducted to identify key factors influencing the willingness of disabled students to use eHealth. Adjusted odds ratios, along with 95% confidence intervals and p-values, were calculated to determine the strength and significance of associations between dependent and independent variables.\u003c/p\u003e\u003cp\u003eModel fitness was tested using the Hosmer-Lemeshow goodness-of-fit test. Multi-collinearity among variables for the final model was assessed using variance inflation factors and no significant multicollinearity was detected among the variables included in the multivariable analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"Result","content":"\u003ch2\u003eSocio-demographic characteristics of the respondents\u003c/h2\u003e\u003cp\u003eOut of 175 disabled students surveyed, 168 valid responses were received, yielding a response rate of 96%. The majority of participants 120(71.4%) were male, with 56% of the students were from Debre Markos University. Over half (62.5%) the study participants reported being a visual impaired, followed by physical disability (31%) and most of the students are enrolled in social science studies 120(76.2%). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristics of disabled students at Debre Markos city (N = 168)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder 20 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20–25 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbove 25 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eInstitution\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDebre Markos University\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDebre Markos Poly technic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrivate colleges\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDebre Markos preparatory school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eDisability type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVisual impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHearing impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMobility impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eParental income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt; 5000 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5000–10000 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10000–15000 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt; 15000 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePlace residence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDevice ownership\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFeature phone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmartphone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eAccess to technology and Awareness of eHealth among disable students\u003c/h2\u003e\u003cp\u003eOnly 56(33.3%) of the respondents owned smartphones or devices enabling internet access and have internet access. Students were inquired about social media usage and 38.1% of the students use social media platform of which 33% used telegram followed by tiktok (31%) Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eAmong the study participants, 90% had heard of eHealth, with mobile health (50%) and Telemedicine (40.5%) being the most recognized services Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Beside the students were asked to select the types of communication media they prefer in relation to access information through eHealth platform and all of them preferred information in the form of Audio followed by video and picture.\u003c/p\u003e\u003ch2\u003eWillingness to Use eHealth and Preferences\u003c/h2\u003e\u003cp\u003eAmong participants, 61.9% expressed willingness to use eHealth services if accessible. Preferred platforms included mobile apps (54.9%) and university-hosted portals (36.2%). Students were asked the preferred communication way of eHealth service most of the students preferred audio transmit service 128(76%) followed by video channels 13% while 11% of the students choose both video and picture.\u003c/p\u003e\u003ch2\u003eDeterminants of eHealth Willingness\u003c/h2\u003e\u003cp\u003eThe results of the bivariate analyses showed that age, place of residence, family monthly income, internet availability, ownership of a mobile device, attitude, perceived easiness, prior social media usage and perceived usefulness were associated with willingness to use eHealth services among students with disabilities at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.2 Table\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All these factors were included in the multivariable logistic regression analysis model to control for potential confounders.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBi-variable and multivariable logistic regression analysis result (N = 168)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eWillingness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOR(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAOR(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder 20 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20–25 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.78[1.5-6]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5[1.2–8.3]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbove 25 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.58[.41-.74]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.52[.2-2.01]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePlace of residence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.32[.57 − 3.7]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.22[.61 − 2.4]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSmartphone ownership\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.35[2-9.6]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.1[1.3–7.5]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eInternet availability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.6[1.2–5.3]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.5[1.2–5.2]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eKnowledge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.3[1-4.9]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.6[1-3.6]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAttitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFavorable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.6[2.8–20]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.6[1.1–6.5]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnfavorable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePerceived easiness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.5[.21 − 14]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.2[1.3–13.6]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePerceived usefulness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.4[2.2–13.3]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9[1.04–8.1]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: The stated p-values correspond to the adjusted odds ratio\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eThe study revealed several key factors influencing the willingness of disabled students to use eHealth services. Age of the of the students was of the factors that associate with willingness, students with age group 20 to 25 was 1.5 times more likely to express willingness to use eHealth platforms compared to under 20 age groups (AOR: 1.5, CI: 1.2–8.3, p = 0.003).\u003c/p\u003e\u003cp\u003eOwning smartphone is strongly linked to willingness, with smartphone users being over three times more likely to be willing (AOR 3.1 95% CI: 1.3–7.5, p = 0.01). Likewise, having internet access increases the likelihood of willingness by 2.5 times, supported by confidence levels (95% CI: 1.2–5.2, p = 0.015).\u003c/p\u003e\u003cp\u003ePrevious knowledge about eHealth platform and favorable attitude were significant associated factors to willingness, Students who had prior knowledge were 1.6 times more likely willing to use eHealth platform compared to their counterpart’s. Furthermore, perceived easiness of the eHealth platform was a powerful determinant of willingness to use eHealth. Platforms with use friendly interface and easy to navigate were 4.2 times more likely to be used (AOR: 4.18, CI: 2.24–7.81, p \u0026lt; 0.001), underscoring the critical consideration in the designing user specific platforms.\u003c/p\u003e\u003cp\u003eMeanwhile, where someone lives doesn't have a big impact on their willingness. These findings emphasize that having technology, prior knowledge, good attitudes, and seeing benefits are crucial in affecting whether someone is willing or not.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eUnintended barriers to healthcare access, such as physical inaccessibility, communication challenges, and stigma, could be mitigated through the use of eHealth technologies, which offer remote consultations, digital health monitoring, and accessible health information. This study aimed to assess the willingness of disabled students at higher institutions in Debre Markos Town to use eHealth and identify factors influencing their willingness.\u003c/p\u003e\u003cp\u003eIn the current study, nearly all participants (90%) were aware of eHealth platforms. This, awareness level is higher compared to study in Gondar Ethiopia (73.7%)(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The disparity may reflect greater internet penetration, institutional promotion of digital tools, and targeted disability-inclusive initiatives in urban academic settings. Despite high awareness, only 61.9% of respondents expressed strong willingness to use eHealth. This gap may stem from inadequate digital literacy, concerns about privacy, or lack of tailored eHealth solutions for diverse disabilities. A study evaluating nursing students' confidence and willingness to use eHealth showed similar results, despite differences in the study population(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).Among participants aware of eHealth, 50% identified m-Health as a primary service, while 16.7% recognized both telemedicine and mobile health apps.\u003c/p\u003e\u003cp\u003eKey factors significantly associated with the willingness to use eHealth among disabled students included age, device ownership, knowledge, attitude and internet access among others. In this study middle age groups (\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) were two times more likely to be willing to use eHealth compared to the age groups 15 to 20, while age groups above 25 were not associated with willingness of students to use eHealth. Ownership of electronic device (smartphone) which enables to use eHealth and accessibility of the internet where the students live were significant associated with willingness. Those who had internet access were 2.5 times more likely willing, while those with smartphone were more than three times more likely to be willing than those without. This result is comparable with previous researches indicating that access to digital device increase tendency to use eHealth (\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e Additionally, participants tended to be willing to use eHealth when they had prior knowledge, demonstrating the importance of awareness in decision-making. This result aligns with Bandura's Social Cognitive Theory, which holds that learning affects behavior through the concepts of perceived control and self-efficacy (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In particular, people who had a favorable attitude were more likely to be willing than those who had unfavorable attitude. This is in line with Theory of Planned Behavior, which holds that attitude plays a significant role in determining one's intention to carry out a particular behavior(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe perceived easiness of eHealth platform interfaces and perceived usefulness of the eHealth service were other factors strongly associated with willingness, which is in line with technology acceptance model assumptions (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The perception of ease of use and usefulness is vital factor that influence behavioral intentions (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). These confirm that user-friendly design may boost student\u0026rsquo;s willingness to use. A study examining the digital divide between students with and without disabilities supports this finding. It revealed that students with disabilities had more difficulty using eHealth platforms compared to their non-disabled peers. This highlights the need for eHealth platform design to incorporate accessible features\u0026mdash;such as voice recognition and Braille\u0026mdash;to accommodate various types of disabilities(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever research was focused on Debre Markos Town, which may limit the generalizability of the findings to rural areas or non-academic populations. Furthermore, the study may have some bias in how visual impairment status and phone user status all varied among the participants. It is possible that the students with some visual impairment may have had difficulty interacting with the websites or digital platforms used in the study and the study process. Students' responses to the survey measures and ultimately, their experiences using eHealth tools may have been affected.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ewhile awareness of eHealth is high among disabled students in Debre Markos, willingness to use these tools is moderate and influenced by age, smartphone ownership, and attitude and internet access. Intervention like improved internet access around disabled student dormitory, user interface tailored to disability type such as screen integration may enhance willingness of students to use eHealth. Future research should employ mixed methods to capture nuanced barriers and include populations outside academic institution to inform national disability-inclusive health policies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eThis study adhered to all ethical standards for conducting research. Ethical approval was obtained from the Debre Markos University Ethical Review Board, and permission to involve participants was secured from the respective college deans and admins. Furthermore,\u0026nbsp;written informed consent was gained from all participants.\u0026nbsp;Participation was entirely voluntary, and no incentives were offered to the participants.\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eAuthors declare conflict of interest.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eNo funding received to conduct this study.\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; contributions\u003c/h3\u003e\n\u003cp\u003eGHT conceptualized the research idea, conducted the statistical analyses, and prepared the original draft of the manuscript. MMT, AFS, TFD, ZRH and GTB were responsible for data entry and cleaning. ASG, LME, BLT, and TSM contributed to data analysis. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe researcher expresses sincere gratitude to Debre Markos University for its support and collaboration in conducting this study. Deep appreciation is extended to the data collectors for their commitment to data collection, and the research participants, the disabled students in higher educational institutions of Debre Markos City for their willingness to give their time.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrganization WH. Global report on health equity for persons with disabilities. World Health Organization; 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSwartz L. Representing disability and development in the global south. Med Humanit. 2018;44(4):281\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeleke FT, Admas M, Alemnew Chekole F, Alem KG, Tenaw SG, Tefera DT, et al. Sexual and Reproductive Health Services Utilization and Associated Factors among Disabled Students in Selected Public Universities of Ethiopia. Sex Disabil. 2024;42(1):67\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHejazinia R. A framework for the requirements of e-health 2.0 in developing countries: a qualitative approach. Hum Inform Interact. 2023;10(3):77\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHa S, Ho SH, Bae Y-H, Lee M, Kim JH, Kim JH, et al. Digital Health Equity and Tailored Health Care Service for People With Disability: User-Centered Design and Usability Study. J Med Internet Res. 2023;25:e50029.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBurns J, Birrell E. Enhancing early engagement with mental health services by young people. Psychology research and behavior management. 2014:303\u0026thinsp;\u0026ndash;\u0026thinsp;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbodey E. Access to healthcare services among students with disabilities in Ghana. University of Cape coast; 2018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli A, Scior K, Ratti V, Strydom A, King M, Hassiotis A. Discrimination and other barriers to accessing health care: perspectives of patients with mild and moderate intellectual disability and their carers. PLoS ONE. 2013;8(8):e70855.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganization WH. Global diffusion of eHealth: making universal health coverage achievable: report of the third global survey on eHealth. World Health Organization; 2017.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl-Shorbaji N. Improving Healthcare Access through Digital Health: The Use of Information and Communication Technologies. 2021.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaleem A, Javaid M, Singh RP, Suman R. Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sens Int. 2021;2:100117.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTesfaye T, Woldesemayat EM, Chea N, Wachamo D. Accessing Healthcare Services for People with Physical Disabilities in Hawassa City Administration, Ethiopia: A Cross-Sectional Study. Risk Manage Healthc policy. 2021;14:3993\u0026ndash;4002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli MA, Alam K, Taylor B, Ashraf M. Examining the determinants of eHealth usage among elderly people with disability: The moderating role of behavioural aspects. Int J Med Informatics. 2021;149:104411.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCho J, Quinlan MM, Park D, Noh G-Y. Determinants of adoption of smartphone health apps among college students. Am J Health Behav. 2014;38(6):860\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFisher M, Baird DE. Making mLearning work: Utilizing mobile technology for active exploration, collaboration, assessment, and reflection in higher education. J Educational Technol Syst. 2006;35(1):3\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShen H, van der Kleij R, van der Boog PJ, Wang W, Song X, Li Z, et al. Digital tools/eHealth to support CKD self-management: A qualitative study of perceptions, attitudes and needs of patients and health care professionals in China. Int J Med Informatics. 2022;165:104811.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBan S, Kim Y, Seomun G. Digital health literacy: A concept analysis. Digit Health. 2024;10:20552076241287894.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharma S, Dureja S, Saini D, Jose R, Pant R, Singh A. Empowering impaired learners: Technological advancements in higher education. Technol Disabil. 2025:10554181251313711.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbdelwahed NAA, Al Doghan MA, Saraih UN, Soomro BA. Digital technology and intentions to adopt digital e-health practices among health-care professionals. Int J Hum Rights Healthc. 2025;18(1):36\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePetretto DR, Carrogu GP, Gaviano L, Berti R, Pinna M, Petretto AD, et al. Telemedicine, e-Health, and Digital Health Equity: A Scoping Review. Clin Pract Epidemiol mental health: CP EMH. 2024;20:e17450179279732.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Niekerk L, Mathanga DP, Juban N, Castro-Arroyave DM, Balabanova D. Universities as catalysts of social innovation in health systems in low-and middle-income countries: a multi-country case study. Infect Dis Poverty. 2020;9(1):90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFortune J, Manikandan M, Harrington S, Hensey O, Kerr C, Koppe S, et al. Understanding the use of digital technologies to provide disability services remotely during the COVID-19 pandemic; a multiple case study design. BMC Health Serv Res. 2024;24(1):323.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNickbakht M, Meyer C, Scarinci N, Beswick R. Exploring factors influencing the use of an eHealth intervention for families of children with hearing loss: An application of the COM-B model. Disabil health J. 2020;13(4):100921.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrewer G, Urwin E, Witham B. Disabled student experiences of Higher Education. Disabil Soc. 2025;40(1):108\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Velsen L, Ludden G, Gr\u0026uuml;nloh C. The limitations of user-and human-centered design in an eHealth context and how to move beyond them. J Med Internet Res. 2022;24(10):e37341.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShakespeare T. Disability: the basics. Routledge; 2017.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerihun B, Atnafu DD, Sitotaw G. Willingness to use electronic medical record (EMR) system in healthcare facilities of Bahir Dar City, Northwest Ethiopia. Biomed Res Int. 2020;2020(1):3827328.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSenishaw AF, Tilahun BC, Nigatu AM, Mengiste SA, Standal K. Willingness to use electronic medical record (EMR) system and its associated factors among health professionals working in Amhara region Private Hospitals 2021, Ethiopia. PLoS ONE. 2023;18(5):e0282044.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCuschieri S. The STROBE guidelines. Saudi J Anaesth. 2019;13(Suppl 1):S31\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBelachew EA, Getachew D, Netere AK, Gizachew E, Sendekie AK. Perception, willingness, and practices of telemedicine in patients with chronic diseases: implication of digital health in patients' perspective at a tertiary care hospital in Ethiopia. Front Public Health. 2023;11:1234436.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePriya B, Ramya Kundayi R. Nursing Students\u0026rsquo; Perceived Confidence in eHealth Concepts and Willingness to Learn: A Multi-site Cross-sectional Survey in India. New Emirates Med J. 2024;5:1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBernhard T, Bygrave F, Witherspoon NO. Social media as a tool for breaking the cycle of children's environmental health disparities. Int Public Health J. 2018;10(4):527\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKassaw M, Amare G, Shitu K, Tilahun B, Assaye BT. Willingness to use remote patient monitoring among cardiovascular patients in a resource-limited setting: a cross-sectional study. Front Digit Health. 2024;6:1437134.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuisman M, van Dijk J. (2020). The digital divide. Cambridge/Medford: Polity. 208 pp. De Gruyter Mouton; 2021.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBandura A. Self-efficacy: The exercise of control. Macmillan; 1997.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAjzen I. The theory of planned behaviour. organizational behaviour and human decision processes. De Young. 1991;50(2):179\u0026ndash;211.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMasrom M. Technology acceptance model and e-learning. Technology. 2007;21(24):81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWiprayoga P, Gede S, Suasana G. The role of attitude toward using mediates the influence of perceived usefulness and perceived ease of use on behavioral intention to use. Russian J Agricultural Socio-Economic Sci. 2023;140(8):53\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarhefka SL, Turner D, Lockhart E. Understanding Women's Willingness to Use e-Health for HIV-Related Services: A Novel Application of the Technology Readiness and Acceptance Model to a Highly Stigmatized Medical Condition. Telemedicine e-Health. 2019;25(6):511\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePettersson L, Johansson S, Demmelmaier I, Gustavsson C. Disability digital divide: survey of accessibility of eHealth services as perceived by people with and without impairment. BMC Public Health. 2023;23(1):181.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"eHealth, disability, higher education, willingness, use, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-7768341/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7768341/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eeHealth technologies offer a way to improve healthcare access for students with impairments at higher academic institutes particularly in low-income areas like Ethiopia. However the willingness of students in these to use eHealth and the factors that influence willingness of students to use the platforms has not yet been thoroughly investigated.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThe aim of this study is examine the willingness of disabled students at higher academic institutes in Debre Markos city to use eHealth and the factors influencing their willingness.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e\u003cp\u003eInstitution based cross-sectional study was conducted from November 2024 to January 2025 among disabled students at higher academic institutes in Debre Markos city. Multi-stage stratified sampled technique was used. Data were collected using structured interviewers administered questionnaire and analyzed using SPSS version 26. Descriptive statistics were computed to represent the characteristics of study participants and binary and multivariable logistic regression analysis was conducted to identify factors associated with willingness of students to use eHealth.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eAmong the total study participants approached (168), 61.9% were willing to use eHealth service and mentioned mobile health and telemedicine as preferred platforms. Factors including but not limited to smartphone ownership (AOR\u0026thinsp;=\u0026thinsp;3.1, 95% CI: 1.3\u0026ndash;7.5, p\u0026thinsp;=\u0026thinsp;0.01), previous knowledge about eHealth (AOR\u0026thinsp;=\u0026thinsp;1.6, 95% CI: 1-3.6, p\u0026thinsp;=\u0026thinsp;0.001), Favorable attitude (AOR\u0026thinsp;=\u0026thinsp;2.6, 95% CI: 1.1\u0026ndash;6.5, p\u0026thinsp;=\u0026thinsp;0.002), Availability of internet (AOR\u0026thinsp;=\u0026thinsp;2.5, 95% CI: 1.2\u0026ndash;5.2, p\u0026thinsp;=\u0026thinsp;0.015), and perceived ease of use (AOR\u0026thinsp;=\u0026thinsp;4.2, 95% CI: 2.24\u0026ndash;7.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with willingness.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eDespite most of the study participants were aware of eHealth; the willingness level was moderate.. Prior knowledge about eHealth, attitude, internet accessibility and perceived ease of use were the factors associated with willingness to use eHealth services. Academic institutions may improve willingness level by offering training courses that could boost awareness and knowledge about eHealth potentials in improving health service access, integrating eHealth with assistive technology, and designing disability friendly platforms.\u003c/p\u003e","manuscriptTitle":"Willingness to use eHealth and associated factors Among Disabled Students in Higher Education Institutions in Debre Markos city 2025","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-25 14:48:07","doi":"10.21203/rs.3.rs-7768341/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-16T11:51:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-16T06:07:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-04T10:28:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275647254543241539831739080769345885013","date":"2025-11-28T21:21:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222851232483783634232852669728386323589","date":"2025-11-26T16:12:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-25T15:49:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199629948736632669684250276367924434502","date":"2025-11-25T15:33:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T19:16:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210966472494153749252408072364578517468","date":"2025-11-23T15:17:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-14T09:16:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-12T16:47:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-17T14:03:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-17T10:52:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-10-17T10:49:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b2c45579-f11c-4f8c-9e49-0bcbf052acf6","owner":[],"postedDate":"November 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T15:24:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-25 14:48:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7768341","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7768341","identity":"rs-7768341","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}