2 Evidence-Based Health Interventions and Health Literacy in Higher Education Worksite Wellness Programs The Patient Protection and Affordable Care Act of 2010 has highlighted the role of health education specialists in achieving preventive health goals. They can provide intervention programming in settings throughout the community, including universities and worksites (American Public Health Association, 2015). Health education specialists must select evidence-based health interventions and materials most appropriate for the target population (Speller et al., 2005). Most interventions include materials written at a third to sixth-grade reading level to match the health literacy level of the general population (Weiss, 2003). This literacy level is inappropriate for most higher education employees participating in a worksite wellness program. For that reason, health literacy recommendations must be revisited and analyzed for this special population to ensure that higher education worksite wellness program participants are adequately engaged (Rudd, 2015). By not speaking or teaching at this population's level, the health educator promotes an environment that ignores the elevated critical thinking skills that can enlighten and encourage individual behavior change, leading to improved health. When students participate in academic classes that do not present sufficient challenge, the resulting boredom can create a motivational barrier. This prevents the student from engaging in conversation or critical thinking about the topic at hand and may instead lead them to feel their mind wandering (Acee et al., 2010). Boredom can be described as a negative, deactivating emotion that can stifle the learning experience if the materials are not found to be challenging enough. This negative emotion blocks the impact of creative learning strategies such as 3 elaboration and critical evaluation, and instead leads to simple regurgitation of information and superficial responses (Pekrun et al., 2002). When applying this information to higher education worksite wellness participants, and understanding that a large portion of those participants have at least some college education, providing health information written at a lower reading level could prove disengaging. Kreuter (2000) found that tailoring health education materials to specific populations was two-thirds more effective than using generic materials. Evidence-based health interventions should be tailored to the target population to reduce boredom and increase effectiveness. The health literacy level of these materials should be adapted to challenge participants to interpret complex data and compare and contrast health documents, rather than simply reading short, bulleted statements. More research is needed to determine how much one can alter the language used in evidence-based health interventions to meet the needs of higher education employees without losing efficacy. Before these interventions can be tailored, it is necessary to identify the average health literacy level of higher education worksite wellness participants and then evaluate how current evidence-based health interventions compare with the anticipated skill set of this population. The hypothesis of this study is that participants in a higher education wellness program with the highest level of education and years of program participation will have the highest levels of health literacy. This level of health literacy will exceed the health literacy level of current evidence-based health intervention materials. RQ1: What is the average health literacy level of higher education worksite wellness participants? RQ2: Does this health literacy level match most evidence-based health intervention materials? 4 Literature Review Worksite Wellness Beginning in the 1970s as a perk for executive-level employees, worksite wellness has morphed into a health promotion strategy that targets all employees to lower healthcare costs for participating organizations (Sparling, 2010). The worksite environment was uniquely situated to provide ongoing health education as employees spend most of their waking hours at their place of employment (van de Put, 2020). Worksite wellness programs began offering financial incentives shortly after the Patient Protection and Affordable Care Act of 2010, which provided strict guidelines for structuring effective programs. During this period, health education specialists increased guidance on programming and promoted evidence-based interventions for this specific community environment. These interventions are focused on reducing the rates of non-communicable diseases (American Public Health Association, 2015). Evidence-Based Interventions The Centers for Disease Control and Prevention provides a clearinghouse of peerreviewed evidence-based interventions proven to improve the health of varying community settings (Sparling, 2010). However, Kemm (2006) determined that standardizedevidence-based interventions work best within the medical field and do not translate well to public health promotion. Researchers prefer randomized controlled trials when developing evidence-based interventions, as they yield reliable results. While these types of studies are best for determining medication outcomes, the method does not account for community health improvement applications. It can prove challenging to find enough controls within a community to produce a valid randomized study. It has also been noted that communities vary greatly, and evidencebased interventions cannot be expected to meet the complexities of each environment. 5 Sparling (2010) addressed other concerns about applying randomized controlled trials within worksite wellness programs. To continuously adapt to the complexities of employee health, researchers should be receptive to a range of evaluative approaches to maintain rigor and standards. Research suggests a higher success rate when evidence-based interventions are tailored to the population being served. Golden et al. (2016) reviewed various forms of diabetes prevention programs and noted that those tailored to the population's needs produced better outcomes. This included adapting the provided materials to align with the population's culture and health literacy. However, it has not been defined how much of an evidence-based intervention can change while still maintaining fidelity. Aside from noting when a program changes, there are no set markers indicating when the program is no longer considered evidence-based (Youth.gov, n.d.). Identifying how much an evidence-based intervention can change needs further investigation. Health Literacy One stated common change to evidence-based interventions reviewed by Golden et al. (2016) was updating health literacy to meet the needs of the population. The national health objectives for 2020, known as Healthy People, defined health literacy as “the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions” (Cutilli & Bennett, 2009, p. 2). The National Assessment of Adult Literacy was implemented in 2003 to best understand the health literacy of the United States. This assessment reviewed 28 skills related to how well adults could read health documentation and make decisions, understand and complete health forms, and use math skills for tasks, such as proper medication dosage. Demographics such as 6 education level, income, race, native language, and civic engagement were also evaluated. For this assessment, 19,000 adults from the United States were surveyed. When the assessment was complete, four literacy levels were identified: below basic, basic, intermediate, and proficient. It was determined that 53% of the sample population fell into the intermediate range, with an additional 12% listed as proficient. With this literacy level, over half of the sample population could accurately determine a BMI score from a chart, identify when a child should receive certain vaccinations, use math to calculate when medication can be taken next, and assess if certain ingredients on a medication label could lead to a side effect. Those who identified as having some college meet the needs of the intermediate level, with each succeeding degree level increasing the individual's health literacy score (Cutilli & Bennett, 2009; Kutner et al., 2006). Guidelines have been developed to facilitate conversations and deliver written health information, as one-third of adults in the United States are categorized as having basic or below basic health literacy (Kutner et al., 2006). These guidelines come from various government entities, including the Centers for Disease Control and Prevention, the U.S. Department of Health and Human Services, and the U.S. National Library of Medicine. Most of these guidelines are targeted at physician-patient interaction (Office of Communications & Public Liaison, 2021). Large words and complex sentences should be avoided, and the final document should fall within the fifth to sixth-grade reading level. Documents should be drafted at a fourth- to fifthgrade reading level when working with adults with below-basic health literacy. When speaking, physicians should choose simpler words to ensure comprehension. Examples include using the words “get bigger” instead of “enlarge”, “heart isn’t pumping enough” instead of “heart failure”, and “going to die” instead of “terminal” (Weiss, 2003, p. 27). Oversimplifying to this degree is inappropriate when working with individuals in higher education. 7 Health Promotion in Higher Education Worksite wellness programs and evidence-based interventions need to be tailored to the educational levels of employees in higher education. Various studies have found that those with higher levels of education and higher health literacy scores tend to participate most in worksite wellness programs, and that these programs should be tailored to this group (Haynes et al., 1999; Van der Put et al., 2019; Zollner et al., 2016). Rickard et al. (2016) revisited the National Assessment of Adult Literacy, taking a more in-depth look at how civic engagement impacts health literacy. Civic engagement activities include voting, volunteering in the community, and visiting the public library. While educational status is correlated with health literacy, higher levels of civic engagement are associated with greater health literacy. When individuals vote, volunteer, and use resources such as public libraries, they become aware of how others are affected by poor health. They are more likely to get involved in improving the health of those around them while also improving their own. Civic engagement is an area where more universities are encouraging student participation. Students who volunteer in the community experience greater success in their university experience (Chittum et al., 2022). One could conclude that faculty and staff at higher education institutions who encourage and organize civic engagement events for students are most likely participating themselves, which may translate into a higher level of health literacy. In 1998, the World Health Organization (WHO) provided a second definition of health literacy that offers a more robust view of how it impacts individual lives. It has been suggested that health literacy is more than simply reading and comprehending a certain level of health information. It also includes individual knowledge from learned experiences, personal skills, and the confidence required to make changes to improve health (Nutbeam, 1998). This perspective 8 on health literacy should encourage health education specialists to engage adult learners in a broader range of educational mediums that will foster self-efficacy to make life-long health changes. Unfortunately, most evidence-based health interventions provide simplistic definitions and rudimentary problem-solving skills without questioning the participant’s inherent understanding and experience with the health topic. It is reasonable to conclude that higher education employees receiving evidence-based health interventions provided at a fourth to fifthgrade reading level are not deeply engaging with the materials, as they provide oversimplified information about health conditions and treatments. Along with the participant’s handouts and materials, most evidence-based health interventions provide facilitator guides that include a script for the program facilitator to recite. This script is also written at the fourth- to fifth-grade reading level to ensure the participant can comprehend the materials. Rudd (2015) states that greater emphasis should be placed on physicians' communication skills when relaying health information. Health literacy studies determine what is assumed about participants' understanding of written materials, but this could change if participants were given context. Comprehension can also improve through verbal communication, which was not considered during the National Assessment of Adult Literacy. There are 10 principles that every worksite wellness program should follow. The fifth principle states that health promotion materials should be tailored to fit the needs of the target population (Sparling, 2010). Health education specialists should use evidence-based health interventions. However, these interventions follow the guidelines for providing plain-language context, which may be too simplistic for those in higher education. Shapria et al. (2017) conducted a systematic review to determine the outcomes of tailoring health education materials and conversations to patients' health literacy levels. Only nine studies met their criteria, which 9 included providing health information in the population's primary language, using a health literacy screening tool, offering a tailored intervention for a target population, conducting preand post-test assessments, and demonstrating a measurable outcome. Of the nine studies, five demonstrated positive outcomes, with patients either showing increased knowledge or better management of their condition compared to the control group. However, only one of these studies tailored the health education materials to a higher reading level, whereas the other studies focused on tailoring materials to lower health literacy levels. Methods Study Site Introduction Located in Ogden, Utah, Weber State University employs 1650 full-time employees. The University offers over 100 undergraduate programs and 20 graduate degree programs across the College of Science, College of Engineering, College of Applied Science and Technology, College of Health Professions, College of Arts and Humanities, College of Business, and the College of Social Science and Education. The Employee Wellness program has been operational since 2000 and has approximately 1,035 registered employee participants. With the mission statement of “enhancing the health and well-being of employees, spouses, and retirees through comprehensive health assessment, education, and intervention strategies”, the Employee Wellness program provides biometric screenings, wellness coaching, personal training, and health education classes. Employees can earn financial incentives through both a healthcontingent program and a participatory program, as outlined by the ACA and the Health Insurance Portability and Accountability Act (HIPAA). Sampling and Recruitment 10 The survey tool was sent to 1,003 employees who met the following eligibility requirements: full-time employees, benefits-eligible, over the age of 18, and who accessed the wellness program software between January 1, 2023, and September 30, 2025. Of the potential population, 24% responded to the survey over a four-week timeframe. Along with the invitation to take the assessment, a reminder was sent on day 14. Research Design This study utilized a cross-sectional design to assess the health literacy levels of higher education worksite wellness participants. Health literacy was measured over a set time frame using a validated instrument, and demographic information was self-reported. The study helped to determine and characterize health literacy patterns within this population. Test Instrument As the NAAL survey is not publicly available, the Health Literacy Skills Instrument Short Form (HLSI-SF) was used in its place. This tool is publicly available, can be used to test both larger populations and individuals, and can be administered using a computer (McCormack, 2009). The Health Literacy Skills Instrument has proven to provide more data on the complexities of health literacy, including assessing reading ability and comprehension of print materials, numeracy, interpreting charts, maps, pictures, and videos, making inferences, and using Internet sources compared to other available health literacy assessments. McCormack et al. (2010) used the NAAL as a blueprint to engineer a more comprehensive and practical approach to establishing health literacy scores among the public. The resulting tool accurately shows that those with higher education levels have higher health literacy, correlates closely with the results of another proven health literacy test, the Test of Functional Health Literacy in Adults (TOFHLA), and yields similar scoring results to the NAAL. 11 Voigt-Barbarowicz and Brütt (2020) conducted a systematic review of studies that used the HLSI-SF to assess patient-reported health literacy. These scores were then compared to the assumed health literacy provided by the patient’s physician. The HLSI-SF indicated that 45% of those tested had lower health literacy. This is greater than the 34% that physicians identified. This could indicate that HLSI-SF assesses a larger range of health literacy skills than can be determined through a conversation with a physician. In a different study, the HLSI-SF was used to assess the health literacy needs of African American college students. This research challenged the reliability and validity of the tool, as the assessment results were lower-thanaverage health literacy. While the tool appears to more accurately predict health literacy among non-Hispanic white, married, and employed respondents, it might not resonate with the population in this study (Rosenbaum, Johnson, & Deane, 2018). The findings of this research should be considered when observing the population to be studied. Data Collection An assessment using the HLSI-SF tool's stimuli and questions was developed in Qualtrics. Demographic questions, including gender, age, employment classification (faculty or staff), level of education, and number of years participating in the worksite wellness program, were added to the assessment. The assessment was self-administered online. Based on the number of questions answered correctly, participants were placed into the following health literacy categories: proficient (score ≥ 82), basic (score 70-81), and below basic (score < 70). These result categories closely mirror those of the NAAL. Variables The dependent variable for this study is health literacy. This variable was assessed using the tool described above. The independent variables for this study are the self-reported 12 demographics, including gender, age, employment classification, level of education, and years of participation in the Employee Wellness program. Data Analysis This study analyzed the association between the health literacy level of higher education worksite wellness participants and their demographics. An ordinal logistic regression model was used to predict an individual's health literacy level based on employment classification, education level, and years of program participation. This model was chosen because the testing results are categorical: proficient, basic, and below basic. The study hypothesis was that participants with the highest level of education and the most years of participation in the worksite wellness program will have higher levels of health literacy. Ethical Considerations Before the study began, an application to use human study subjects was submitted to the Weber State University Institutional Review Board. Each participant completed an informed consent form before the assessment began. Participants were informed that they could end the study at any time without fear of retaliation. All eligible participants were over the age of 18 and of sound mind, therefore able to provide legal consent. The risks of the study are minimal, and the benefits could lead to an improved understanding of the individual's health literacy. Results Sample Demographics Table 1 provides an overview of the collected demographics and health literacy scores. At the close of the Health Literacy Assessment period, 237 participants engaged with the survey. 13 Three responses were removed from data analysis; two were incomplete, and one declined the informed consent. Approximately 69% of respondents were proficient in health literacy, 26% were at the basic literacy level, and 5% were at the below-basic literacy level. The sample population was primarily staff (85%) and female (74.8%). Mean health literacy scores were similar across employment classifications, with staff averaging 8.7 and faculty averaging 8.8 out of 10. The education levels and years of participation in the wellness program varied widely among respondents. Table 1 Participant Demographics and Health Literacy Characteristics (N = 234) Characteristic Health Literacy Level (HLSI-SF) Below Basic Basic Proficient Gender Male Female Age Group (years) 18–24 25–39 40–49 50–64 65+ Employment Classification Faculty Staff Education Level High school graduate Vocational/trade Some college n % 11 61 162 4.7 26.1 69.2 59 175 25.2 74.8 4 78 69 75 8 1.7 33.3 29.5 32.1 3.4 35 199 15.0 85.0 2 5 10 0.9 2.1 4.3 14 Characteristic n % Associate’s degree 15 6.4 Bachelor’s degree 76 32.5 Master’s degree 93 39.7 Doctorate degree 33 14.1 Wellness Program Participation (years) Less than 5 years 125 28.7 5-10 years 68 52.7 More than 10 years 44 18.6 Note. Percentages may not total 100 due to rounding. Health literacy was assessed using the Health Literacy Skills Instrument–Short Form (HLSI-SF). Tool Results Items from the HLSI-SF were reviewed and grouped by a primary health literacy task, and the number of correct answers were tallied. Tasks were categorized into reading and comprehension of health information, navigating and following instructions, and quantitative interpretation. Table 2 provides detailed results for these tasks. Overall accuracy was highest on items requiring reading and comprehension and navigating health information, but greater variability was observed with items requiring quantitative interpretation. Table 2 Item-Level Performance on the HLSI-SF by Primary Task Type (N = 234) Item Primary Task Type % Correct Stroke signs Reading & comprehension 98 Exercise video Reading & comprehension 98 Prostate cancer chart Reading & comprehension 95 Hospital map Navigation & instructions 96 Medical center phone menu Navigation & instructions 93 Medicine record Navigation & instructions 87 Portion size Quantitative interpretation 91 Calories burned Quantitative interpretation 90 Cholesterol levels Quantitative interpretation 82 15 Item Primary Task Type % Correct Nutrition label Quantitative interpretation 46 Note. Items are ordered by primary task type and percentage of correct responses. Percentages represent the proportion of respondents who answered each item correctly. Data Results Data was further analyzed using IBM SPSS Statistics software (version 29). Ordinal logistic regression examined employee demographics, including age, classification, education level, and years of program participation, across ordered levels of health literacy. Before the analysis was run, the proportional odds assumption was assessed using the Test of Parallel Lines. The test results were non-significant, showing that the proportional odds assumption was met. The relationship between predictors and health literacy was consistent across outcome thresholds. The proportional odds assumption for this model was met (χ² = 12.76, p = .466). The overall model was not statistically significant, χ²(13) = 11.72, p = .551. When the demographic variables were analyzed together, they did not significantly predict health literacy levels. Pseudo R² values were small (Nagelkerke R² = .063), suggesting limited explanatory power. Table 3 depicts these results. Table 2 Ordinal Logistic Regression Predicting Health Literacy Using Original Demographic Categories (N = 234) Predictor Age (ref = 65+) 18–24 25–39 40–49 50–64 Gender (ref = Female) Male B SE OR 95% CI for OR p 2.39 1.76 1.68 1.91 1.41 0.78 0.76 0.77 10.92 5.81 5.38 6.77 0.69, 173.49 1.25, 27.99 1.22, 23.68 1.49, 30.69 .090 .025 .026 .013 −0.36 0.34 0.70 0.36, 1.35 .289 16 Predictor B SE OR 95% CI for OR p Employment Classification (ref = Staff) Faculty 0.25 0.59 1.28 0.40, 4.08 .676 Education (ref = Doctorate) Bachelor’s −0.18 1.53 0.83 0.04, 16.69 .905 Master’s −0.31 1.08 0.74 0.09, 6.09 .775 Some college / Associate’s / Vocational / — — — — — High school† Note. χ²(13) = 11.72, p = .551; Nagelkerke R² = .063; OR = odds ratio; CI = confidence interval. The proportional odds assumption was met, χ²(13) = 12.76, p = .466. Reference categories are indicated in parentheses. †Small cell sizes in lower education categories resulted in unstable parameter estimates. Upon reviewing the model, it was noted that many variables had sparse cell counts. To improve model stability and reduce cell count issues, education levels were collapsed into three categories: Lower Education, Bachelor’s Degree, and Graduate Degree. Health literacy categories remained unchanged. This revised analysis returned a satisfactory proportional odds assumption (χ² = 3.84, p = .798). The revised model, described in Table 4, remained nonsignificant, χ²(7) = 9.31, p = .232. None of the demographic predictors was significantly associated with higher health literacy levels. Pseudo R² values remained low (Nagelkerke R² = .050) Table 4 Ordinal Logistic Regression Predicting Health Literacy With Collapsed Education Levels (N = 234) Predictor Age (ref = 65+) 18–24 25–39 40–49 50–64 Education (ref = Graduate Degree) Lower Education B SE OR 95% CI for OR p 2.27 1.80 1.66 1.98 1.38 0.74 0.73 0.73 9.69 6.04 5.27 7.24 0.65, 144.86 1.42, 25.76 1.27, 21.99 1.72, 30.44 .100 .015 .022 .007 −0.60 0.42 0.55 0.24, 1.25 .153 17 Predictor B SE OR 95% CI for OR p Bachelor’s Degree −0.47 0.32 0.63 0.34, 1.17 .145 Note: χ²(7) = 9.31, p = .232; Nagelkerke R² = .050; OR = odds ratio; CI = confidence interval. The proportional odds assumption was met, χ²(7) = 3.84, p = .798. Reference categories are indicated in parentheses. To account for additional sparse cell counts, health literacy was also collapsed into Inadequate and Adequate categories. Despite this adjustment, model fit remained nonsignificant, χ²(9) = 10.04, p = .347. Model diagnostics showed potential quasi-complete separation and instability of parameter estimates; therefore, the results in Table 5 should be interpreted with caution. Table 5 Ordinal Logistic Regression Predicting Collapsed Health Literacy (N = 234) Predictor B SE OR 95% CI for OR p Age (ref = 65+) 25–39 3.15 1.29 23.35 1.86, 294.27 .015 40–49 2.48 1.19 11.98 1.18, 122.61 .036 50–64 3.36 1.31 28.78 2.20, 372.20 .010 Gender (ref = Female) Male −0.31 0.71 0.73 0.18, 2.92 .658 Employment Classification (ref = Staff) Faculty 2.05 1.35 7.74 0.55, 109.41 .130 Education (ref = Graduate Degree) Lower Education 0.39 0.94 1.48 0.23, 9.30 .678 Bachelor’s Degree 0.97 0.85 2.64 0.50, 13.98 .253 Note. χ²(9) = 10.04, p = .347; Nagelkerke R² = .133; OR = odds ratio; CI = confidence interval. Health literacy was collapsed into Inadequate and Adequate categories. The model exhibited quasi-complete separation, and parameter estimates may be unstable. Reference categories are indicated in parentheses. Although the previous models did not reach statistical significance, age emerged as the sole demographic variable appearing to predict health literacy. Binary logistic regression examining age group as a predictor of adequate health literacy indicated this was not statistically 18 significant, χ²(4) = 5.32, p = .256, with low explanatory power (Nagelkerke R² = .071). Table 6 notes these results. Table 6 Binary Logistic Regression Predicting Adequate Health Literacy by Age Group (N = 234) Predictor B SE OR 95% CI for OR p Age (ref = 65+) 18–24 20.10 20096.49 — — .999 25–39 2.12 1.01 8.33 1.15, 60.20 .035 40–49 1.69 0.97 5.42 0.82, 35.76 .080 50–64 2.50 1.09 12.17 1.41, 105.18 .021 Note. χ²(4) = 5.32, p = .256; Nagelkerke R² = .071; OR = odds ratio; CI = confidence interval. Health literacy was dichotomized as adequate (95.3%) and inadequate (4.7%). Model estimation failed to fully converge due to severe imbalance in outcomes and quasi-complete separation. The odds ratio for the 18–24 age group could not be estimated. The findings of this study do not support the hypothesis that higher levels of education and longer participation in the worksite wellness program would predict higher levels of health literacy. Across all three models, neither education nor years of participation was a significant predictor of health literacy outcomes. Discussion The discussion that follows interprets these findings in relation to the study’s research questions, particularly whether commonly used evidence-based health interventions align with the assessed health literacy skills of higher education worksite wellness participants. Health literacy was measured using the Health Literacy Skills Instrument-Short Form (HLSI-SF), which assesses health literacy skills in the following areas: comprehension of health information, navigation of health systems, and quantitative interpretation. In addition to health literacy, demographic characteristics were collected and analyzed, including gender, age, employment 19 classification, education level, and years of participation in the wellness program. These characteristics were reviewed to determine whether they were associated with levels of health literacy. Results from this study indicated that most survey respondents have proficient health literacy, with some respondents at basic and below-basic literacy levels. The survey data were analyzed using several approaches due to sparse cell counts and model instability. Approaches to improve analysis results included collapsing education and health literacy categories. However, none of the ordinal or binary regression models identified any demographic variables as significant predictors of health literacy. Across the four analytical models used, the explanatory power remained limited. These findings suggest that health literacy among higher education worksite wellness participants may be relatively consistent with this population and not easily differentiated by the collected demographic characteristics. The following discussion will interpret the study's findings in relation to existing evidence-based health interventions and how these may need to change for those in the higher education setting. Interpretation of Findings Given the limited explanatory power of the regression models, interpretation focuses on overall patterns and item-level performance rather than demographic prediction. The lack of predictive power is likely due to the limited variability of the dependent variable. The main finding of this study is that most participants in higher education worksite wellness programs demonstrate proficient health literacy. Nearly 70% of the survey respondents scored proficient, and only 5% scored below basic. When the health literacy scores were collapsed, 95% of the participants demonstrated adequate health literacy. Because most participants are clustered in this highest category, statistical models had limited ability to detect meaningful differences 20 between demographic groups. This imbalance led to quasi-complete separation in the logistic regression model, resulting in unstable parameter estimates. Despite these limitations, the distribution of scores implies that employees who participate in the worksite wellness program can interpret, navigate, and apply health-related information across multiple formats. Since the HLSI-SF assessed practical skills, the results indicate that this population has the health literacy competencies required to effectively engage with common health education materials. The 70% of higher education worksite wellness participants who scored proficiently, is significantly higher than the 12% reported in the NAAL. One explanation for this increase may lie in the environment and job requirements associated with higher education. Of the study participants, 86% have a bachelor’s degree or higher, 54% have graduate degrees. Higher levels of education have been associated with greater health literacy. Employees with advanced formal education engage with written, digital, and quantitative materials throughout their daily routines. These skills are similar to the tasks measured by the HLSI-SF, which include interpreting charts and detailed information and analyzing written content. Additionally, participants in a worksite wellness program typically choose to actively engage with health-related materials. This increased motivation to manage their health improves their health terminology and concepts, further advancing their health literacy. These three factors suggest that individual education, the broader higher-education environment, and participation in a worksite wellness program reinforce health literacy in this population. It is important to note that the lack of statistical significance within the demographic variables is a meaningful finding. Rather than indicating a lack of relationship, these results suggest consistent health literacy within this population, in which most individuals possess high levels of health literacy. 21 Age, gender, employment classification, education level, and years of participation in a wellness program did not appear to be significant in higher health literacy levels. This data demonstrated that there was no statistical difference in health literacy between faculty and staff, and those with a doctorate degree or vocational training. While age appeared statistically significant in a few models, the results were inconsistent. This demonstrates that these traditional variables provide minimal value when working with a highly educated population. The hypothesis for this study proposed that higher levels of education and more years of participation in the worksite wellness program would be associated with higher levels of health literacy. However, the findings did not support this assumption. Instead, the results do suggest that health literacy levels are consistently high across the study population, regardless of demographic differences. Higher education levels and participation in worksite wellness programs may contribute to elevated health literacy rather than being a determining factor. This shows that traditional predictors of health literacy may have limited predictive value in populations with uniformly high literacy levels. Due to a higher overall level of health literacy within the population, there was limited variability in the dependent variable. This led to reduced ability to identify predictors for health literacy. However, when examining test item responses to the HLSI-SF, specific health literacy skills were more dominant. This population excelled in reading comprehension, navigating health information, and following medical instructions, with correct response rates above 90%. There was a greater range of responses to questions involving quantitative literacy, particularly with interpreting a food guide label, which only 46% of the participants answered correctly. This finding highlights that proficient health literacy does not imply uniform knowledge across all 22 health literacy skills. Even highly educated individuals may benefit from adapting some health education materials for lower literacy levels. The findings from this study suggest that participants in higher education worksite wellness programs tend to have strong health literacy skills. This health knowledge is supported by both occupational environment and a general interest in wellbeing. While scores are predominantly proficient, skills are not uniform across all health literacy categories. Demographic variables provided limited explanation of who will have a higher health literacy score. However, the variables did help highlight that the population as a whole has higher health literacy regardless of the recorded demographics. These findings suggest that health literacy approaches designed primarily to support foundational health knowledge and behavior change may be insufficient for populations with high health literacy. Instead, the results provide the groundwork for examining whether current evidence-based health interventions align with the assessed capabilities of higher education employees. Based on these results, a “scaling-up” model, one that increases health intervention material complexity rather than simplifying content, may prove to be more useful for this population. Comparison to Existing Literature The NAAL results indicated that the percentage of U.S. adults who demonstrate health literacy proficiency is limited. Kutner et al. (2006) and Cutilli & Bennett (2009) determined that health literacy levels will increase linearly with education level. However, this study expands on these findings by demonstrating that, within a higher education context, health literacy proficiency may be weakly associated with traditional demographic indicators. This concept can be linked to additional research showing that individuals who participate in civic engagement tend to have higher health literacy levels. Rikard et al. (2016) found that adults who engaged in 23 activities such as voting, volunteering, and using the library tended to have higher health literacy scores, regardless of educational status. Higher education employees, while setting an example for those they serve, often participate in civic engagement activities. It could be assumed that those who volunteered for this study did so to demonstrate their commitment to civic engagement. The findings of this study support existing research that suggests health literacy is not solely determined by educational years but is shaped by continued exposure to an information-rich environment that encourages critical thinking and applied decision-making. Reviewing the results of the individual assessment items highlights the need to understand the unique skill sets of the population in question. While higher education employees excelled in reading comprehension and navigational tasks, numeracy-related skills, especially those related to reading a nutrition food guide, proved challenging. This suggests that health literacy materials should not be uniform in the information and skills they provide, but should instead offer layered mastery. This concept aligns with Baker (2006), who indicated that health literacy is a skill that can be developed and refined over time through systematically scaled educational experiences. Interpreting food guide labels, medication dosages, or potential medical risks requires quantitative literacy that is not typically addressed in common health education materials. Kreuter (2000) also found that tailored materials, while not necessary for all populations, can be effective when matched to the skill level and individual needs of the population. This study found that overly simplified or poorly individualized materials are ineffective. Nutbeam (2000) explains how health literacy can be divided into three subcategories: basic/functional health literacy, communicative/interactive health literacy, and critical health literacy. Much of the standard health education materials provided to all populations is focused on basic and functional comprehension. This is achieved by tailoring down materials and 24 providing generic scenarios. However, this does not align with the health literacy levels and needs of higher education employees. These individuals would benefit from opportunities to engage with the materials that promote reflection, evaluation, and informed decision-making. These types of health literacy materials would fall under the critical literacy category, which encourages them to draw on their lived experiences and apply critical thinking to concepts in their situation. Applying health education materials to personal and environmental relevance may better support sustained engagement and behavior change. The results of this study suggest that participants in higher education worksite wellness programs may benefit from adopting a more tailored approach to health education. This would include better opportunities for skill development, deeper critical thinking, and personalized application. Rather than assuming simplifying health education materials is the universal best practice, health education specialists should consider whether current evidence-based materials are appropriately aligned with the health literacy levels of the population they serve. By doing this, the health education specialist will honor the participant's innate expertise and prior knowledge, leading to greater program adherence. Since this study found that health literacy levels are fairly consistent across employee classifications and education levels, the tailored information could be used by most wellness program participants in higher education. Limitations Several limitations of this study should be considered when interpreting the findings. Although the sample size was sufficient to support statistical analysis of the target population, the distribution of responses resulted in limited variability across demographic categories. The lack of substantial data in these categories resulted in sparse cells in most regression models. Computer-based administration may have affected participation among some eligible employees. 25 The HLSI-SF was chosen because it is a validated instrument with results similar to those of the NAAL. However, it was designed to detect health literacy deficits among the larger population, potentially leading to an overestimation of this population's health literacy. As previously mentioned, the HLSI-SF may produce results that do not accurately predict health literacy scores for those who do not identify as non-Hispanic white and are not married. Ethnicity and marital status were not collected as part of the study demographics. The HLSI-SF is only one of many health literacy tools that could have been used and may not assess other important health literacy skills. This study was conducted at a single institution of higher education. Other institutions will most likely have different demographic ratios, and worksite wellness programs are not universal. Implications for Future Research This study lays the groundwork for future research on how best to adapt evidence-based health education materials to the health literacy levels of the study population. Much of the existing health literacy research and assessment tools are designed to identify literacy weaknesses and comprehension barriers. This approach may not be applicable when working with a population with defined proficient health literacy. The findings of this study highlight the need for tools to assess advanced health literacy skills, including the ability to critically evaluate, synthesize, and apply health information across multiple health-related topics. The development of this tool would provide a necessary foundation for subsequent research examining how health education materials can be intentionally “scaled up” to meet the skill sets of individuals with higher baseline literacy. Scaling-up approaches that draw on a critical literacy skillset have the potential to support greater engagement, informed decision-making, and individualized behavior change. This is done by challenging and building on participants' existing skills rather than relying solely on foundational concepts. Much of the existing guidance on developing health 26 promotion materials focuses on simplified language and health concepts. While this strategy works for a large portion of the general population, the results of this study suggest that this is insufficient for a population with proficient health literacy. Adopting a scaling-up approach that moves from basic/functional literacy to critical literacy should enable more complex scenarios, better data interpretation, and opportunities for critical thinking in health information. Additional research can be used to identify how health literacy differs between higher education worksite wellness program participants and non-participants. Comparing the results of this study with those of non-program participants would help clarify whether high health literacy levels result from program participation, the environment of a higher education institution, or both. This type of research would help health education specialists and worksite wellness program administrators determine whether the wellness program serves as an entry point to health education or primarily attracts a population with inherently higher health literacy. This data would provide a deeper understanding of health literacy levels across higher education, improving intervention strategies to expand program reach and inclusion. Conclusion This study examined whether the health literacy levels of higher education worksite wellness program participants align with currently available evidence-based health intervention materials. Using a validated skills assessment tool, the findings showed that the majority of the study participants exhibited proficient health literacy, with limited variability across demographic characteristics. These results suggest that higher education employees who engage in a worksite wellness program generally possess the skills required to interpret, navigate, and 27 apply health information across multiple formats. Traditional demographic characteristics used to predict health literacy scores provided limited explanatory power within this population. Although overall health literacy levels were high, item-level analysis revealed marked variation across skill areas, particularly in tasks requiring quantitative interpretation. This finding reinforces the idea that proficient health literacy does not necessarily lead to mastery across all areas and highlights the importance of examining health literacy scores beyond aggregate scores. Together, these results indicate that while higher education worksite wellness participants can engage with most health information, there are opportunities to provide education beyond foundational health concepts. Future research should focus on developing assessment tools capable of measuring advanced health literacy skills, including critical evaluation and application. These tools would provide researchers with a better understanding of how highly educated populations interact with health information. Aligning health education materials with participants' skill levels can enhance engagement and support informed decision-making. The findings of this study raise important questions about the continued reliance on evidence-based health information that is designed to provide rudimentary health information. 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