A cross-sectional online survey was conducted to examine the self-tracking health practices of college students, both with and without disabilities, using the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) [24]. The web-based questionnaire was designed by the author using Qualtrics [25] and was reviewed for readability and clarity by 5 college students—2 college students without disabilities and 3 college students with disabilities—before being revised. The average time to complete the pilot survey was 15.4 minutes. Prospective participants representing college students with and without disabilities were invited to take part via email and social media platforms, including Twitter and Facebook. Upon clicking the URL in the email or social media post, participants were screened for eligibility and asked to provide informed consent. To be eligible for the survey, participants had to (1) be a US resident, (2) be aged between 18 years and 35 years, (3) be currently enrolled in college or university, (5) not have a cognitive impairment or psychiatric disorder, and (6) speak and write English. To assess disability status, the following additional screening question was asked: “Do you have a disability? If yes, please specify the type of disability you have (eg, visual impairment, hearing loss, mobility, learning).” No identifiable data, except for the email addresses of the participants for the compensation procedure, were collected. The online survey was open to respondents from February 20, 2023, to April 15, 2023. Participants who completed the survey were entered into a raffle for compensation in the form of Amazon eCodes. In 2 groups, 30 people each received US $20 worth of Amazon eCodes.

In this study, the self-tracking health practices refer to utilizing digital health technologies such as smartphone health apps, wearable sensors (eg, fitness trackers, smartwatches), and smart medical devices to regularly check one or more health-related data point as well as recording health data with manual tools (eg, pencil and notebook). The following questions were included in the survey to understand the self-tracking health practices and preferences of college students with and without disabilities: (1) “Do you currently track your health (eg, monitoring body weight, calculating calories intake, counting steps)?” (2) “What aspects of your health do you routinely track?” (3) “What types of tracking tools do you use to record your health data?” (4) “How frequently do you check your health data?” (5) “What are the reasons that you do not track your health?” (6) “What kinds of health data do you want to track in the future?” (7) “What smartphone apps have you used to manage your health?” (8) “What features do you prefer the health-related smartphone apps to contain?” (9) “What kinds of wearable devices have you used to manage your health?” (10) “Please describe any barriers or challenges you faced when tracking your personal health data.”

In this study, 2 self-reported questionnaires were used. First, the level of eHealth literacy was measured using the eHealth Literacy Scale (eHEALS) [26]. The eHEALS was developed to assess eHealth literacy for a wide range of populations [26]. It has 6 core skills such as traditional literacy, health literacy, information literacy, scientific literacy, media literacy, and computer literacy [27]. This self-report instrument includes 8 items and uses a 5-point Likert scale ranging from “Strongly disagree” to “Strongly agree.” Higher scores indicate higher levels of eHealth literacy. In the original study, which targeted a youth population aged between 13 years and 21 years, the internal reliability (Cronbach alpha) was .88, and the test-retest reliability (r) ranged from 0.40 to 0.68 [26]. In this study, the reliability (Cronbach alpha) was .88. Second, to quantitatively assess the perceived well-being of college students, the Flourishing Scale (FS) [28] was used. The FS is an 8-item, self-report scale and measures respondents’ perceived success in relationships, self-esteem, purpose, and optimism. It uses a 7-point Likert scale ranging from “Strongly disagree” to “Strongly agree.” Higher scores indicate higher functioning in social-psychological prosperity. The reported Cronbach alpha is .87, and the test-retest reliability is (r) 0.71. The reliability (Cronbach alpha) of this study was .91.

The minimum sample size of this study was 92 based on the number of predictors (n=5), targeted adjusted R² of 0.30 with type 1 error of <.05, medium effect size of 0.3, and power of 0.8. Descriptive statistics and multiple regression analysis were used to investigate the characteristics and relationships between variables using R software (RStudio). To identify any detectable differences between continuous variables, independent t tests, ANOVAs, and Wilcoxon-Mann-Whitney tests were conducted. In the cases of counts or frequencies of categorical variables, chi-square tests were performed. Multiple linear regression analysis was conducted to examine the relationships between the main variables (ie, disability status, self-tracking health practice, eHEALS, and FS). For this regression model, the categorical variables (ie, doing self-tracking health, living with disability) were coded into 2 categories (ie, 0=No, 1=Yes).

Ethical approval for the survey was obtained from the University of Illinois Urbana-Champaign (Protocol ID: 23316), and the study was monitored by the Institutional Review Board of the University of Illinois Urbana-Champaign. Participants gave their informed consent prior to participating in the survey. The study data were anonymized and stored securely at the university. Through a raffle, 30 participants were randomly selected and compensated with a US $20 Amazon e-gift card.

This exploratory study utilized an online survey method to examine the self-tracking health practices among college students with and without disabilities. A comparison was conducted with college students without disabilities to identify different patterns. Additionally, the study investigated the correlations between disability status, self-tracking health practices, eHealth literacy, and subjective well-being. The main findings of the study were as follows: (1) irrespective of disability, a majority of college students voluntarily engaged in self-tracking health; (2) college students with disabilities demonstrated significantly lower levels of eHealth literacy and subjective well-being compared with their peers without disabilities; (3) college students with disabilities reported significantly lower satisfaction and perceived efficacy when using smartphone health apps and wearable devices; (4) a significant portion of college students experienced frequent lapses in self-tracking health activities, along with difficulties in using self-tracking methods and interpreting personal health data; and (5) subjective well-being in college students was found to be significantly correlated with disability status, self-tracking health practices, and eHealth literacy.

Many college students reported engaging in digital self-tracking, stating that they check their personal health data on a daily or weekly basis. On the other hand, college students who indicated not engaging in self-tracking health mentioned difficulties in understanding how to track and interpret their health data as reasons for not self-tracking health. The perception of mobile or digital technology being challenging to use was identified as a significant barrier to adopting or maintaining its use. In other words, the complexity of self-tracking digital health technology was identified as one of the main reasons why college students found it challenging to incorporate them into their daily lives, contradicting previous research that suggests the younger population has higher technology familiarity [29]. This finding challenges the assumption that college students, as younger users, are inherently familiar with recent technologies, can easily learn to use them, and may not recognize any hidden usability issues.

Some college students displayed a reluctance to know or address their health status, reflecting a similar trend observed in older adults who avoid self-tracking health due to a heightened awareness of their illnesses and medical symptoms [30]. This means that, when individuals become aware of their existing health problems, collecting health data solely for the purpose of maintaining chronic conditions rather than promoting overall health can create self-avoidance or excessive burden. Sometimes, excessive self-tracking routines can result in adverse effects by making individuals too sensitive to minor fluctuations in health indicators or encouraging them to overinterpret the changed health data. It can also frequently evoke negative feelings for individuals who are diagnosed with chronic health problems. Therefore, it is advisable to avoid unnecessary data visiting for specific health issues. Rather than relying on generalized feedback, it would be more appropriate to offer personalized data-driven feedback that informs self-trackers when a health problem is expected or when immediate health behavior changes are necessary.

It is important to consider incorporating educational features in health-related apps that help college students learn how to monitor and interpret personal health data from a health literate approach [31]. This can include the use of charts, graphics, and illustrations to enhance comprehension [32]. In the cases with visual impairments, a detailed audio description should be added to the visualized health information [33]. Furthermore, as forgetting to engage in self-tracking health practices was identified as one of the primary reasons why college students find it challenging, incorporating time cueing features in the app that align with their daily routines would be beneficial [34]. To assist college students, reminders can be customized to their campus activities or sent at suitable times to notify them when health data collection is incomplete. The most convenient solution for individuals who forget to capture personal health data would be to automatically collect health data through digital devices that they can wear or carry. However, there is an argument that fully automated tracking requires additional feedback to encourage engagement and manage the high volume of data [35]. Therefore, finding a balanced point between manual and automated tracking is necessary.

College students with disabilities reported similar levels of daily use and interest in digital health technology as college students without disabilities. However, their eHealth literacy and subjective well-being levels were significantly lower than for their counterparts. This could be attributed to the direct impact of disabilities, but it could also be interpreted as the result of the benefits they are unable to enjoy due to their disabilities. For example, the college students with disabilities in this study reported significantly lower satisfaction and perceived efficacy with using smartphone health apps and wearable devices. These unsatisfying technology experiences can affect their motivation to engage in self-tracking health practices. This poor user experience for college students with disabilities represents a lack of inclusivity in the current distributed digital health technology, similar to how older adults may feel resistant toward new technology [36]. The fact that users with physical, sensory, and learning limitations cannot experience the same level of positive effectiveness and behavioral changes as common users can be understood as a paradoxical effect of technology that contributes to health inequality in the future [37].

Currently, there are very limited efforts to enhance the usability of mobile or digital health technologies for users with disabilities by addressing their unmet needs, challenges, and barriers. One of the important missing pieces in this study is the exploration of accessibility issues faced by college students with disabilities and their adaptive strategies to overcome these challenges. Recently, Lee and colleagues [38] reported on multiple unique accessibility challenges faced by visually impaired individuals in digital self-tracking systems. They also discussed design opportunities to reduce the gap between visually impaired and sighted users. This highlights the need for greater inclusivity in the design of digital health technologies to ensure that all individuals, regardless of ability, have equal access to the benefits of self-tracking health. Given the heterogeneous nature of disability impacts on technology adoption and users’ preferences and values in technology, diverse disability groups’ user experiences should be deeply understood and considered for future product designs. To prevent the digital divide and its impact on health disparities, a mindset of accessibility and inclusivity is necessary for all software developers and health informatics researchers.

Developing healthy lifestyle habits and the ability to sustain them in the long term is particularly important for college students with disabilities. They are more likely to face barriers and challenges in self-care compared with individuals without disabilities [39,40]. College students with disabilities should receive health education that is tailored to their specific needs and provides them with a proper understanding of health and how to model healthy behaviors. This education should also include information about health information accessibility and the use of necessary assistive technologies to ensure that students with disabilities can freely access and utilize health-related information. For instance, for visually impaired female students, it is important to provide health education on cervical cancer vaccination and breast self-examination in an accessible manner. This could include providing detailed audible descriptions or tangible education materials that they can feel and touch. Ensuring their participation in diverse virtual and in-person health education opportunities should be established.

This study identified positive correlations between disability status, self-tracking health practices, eHealth literacy, and subjective well-being among college students with and without disabilities. This highlights the potential benefits of using digital health technology on the well-being and quality of life of all college students. Based on these findings, higher education institutions can consider offering learning opportunities specifically for college students with disabilities, who face additional challenges in managing their health conditions. These opportunities should aim to teach them how to effectively and systematically use digital health technology to monitor their daily health conditions and manage their health behaviors. Experiencing rewarding outcomes from self-tracking their health using digital health technology could lead to improved quality of life and well-being in adulthood.

This cross-sectional, online survey study has certain limitations that warrant careful consideration when interpreting the findings. First, the sampling strategy used in the study was not a sophisticated design. Due to the small sample size of the target population and practical barriers in implementing random or quota sampling, the respondents may not adequately represent the broader population of college students with disabilities. Second, a substantial number of college students majoring in Health Science participated in the survey due to the relevance of the topic to their field of interest, potentially introducing bias to the results. Last, the study did not account for the detailed characteristics of disabilities, such as their type and severity, when interpreting the results. Conducting a subgroup analysis to address this issue would have been ideal; however, the small sample size made it infeasible. Therefore, further research is necessary to obtain study results that reflect the specific characteristics associated with each disability.

This study indicates that college students with disabilities are engaged in digital self-tracking health activities, much like their peers without disabilities. However, they experience poor satisfaction and efficacy from current digital health technology. Software developers and health informatics researchers should not assume that young adults, including those with disabilities, will readily adopt and effectively utilize technology for health management. Rather, it is crucial to closely examine their abilities and accessibility needs to ensure that digital self-tracking health tools are inclusive and promote long-term self-care. In addition, given their lack of eHealth literacy skills, it is important for health educators in campus settings to provide personalized health consultations for both college students with and without disabilities to enhance the effective utilization of self-tracking health. For college students with disabilities, accessible self-tracking tools can be helpful for establishing healthy behavioral patterns in young adulthood and preventing chronic illnesses, thereby optimizing their life satisfaction and self-control.