The Role of E-Health and Nutrition Literacy in Health-Related Decision-Making: A Cross-Sectional Study of University Students in Ghana

The Role of E-Health and Nutrition Literacy in Health-Related Decision-Making: A Cross-Sectional Study of University Students in Ghana | 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 The Role of E-Health and Nutrition Literacy in Health-Related Decision-Making: A Cross-Sectional Study of University Students in Ghana Martin Gameli Akakpo, Sheriffa Mahama, Glorian Goodluck Nnko, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6364493/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background . This study investigated the role of e-health literacy and nutrition literacy in health-related decision-making. The scope of health decision-making in this study included the use of social media to learn about diet and exercise, attitudes toward exercise and healthy eating self-efficacy. Methods. Data were collected from 592 university students in Ghana via a cross-sectional survey. A questionnaire collected data about e-health literacy, nutrition literacy, use of social media to learn about diet and exercise, attitudes toward exercise, healthy eating self-efficacy and demographics. Multiple linear regressions were used to test the hypothesis that e-health literacy and Nutrition literacy are related to health decision-making. Results. As hypothesized, e-health literacy (R 2 = .16, p = .00) and nutrition literacy (R 2 = .19, p = .00) were related to health decision-making. The findings show that e-health literacy and nutrition literacy are related to health-related decision-making. The implications for patients, public health educators and researchers are discussed. Conclusion. This study uniquely contributes to knowledge by demonstrating how e-health and nutrition literacy influence a patient’s use of social media for learning about diet and exercise. Moreover, these factors are related to attitudes toward physical activity and enhance self-efficacy in maintaining healthy eating habits. e-health literacy nutrition literacy exercise diet healthy eating health decision-making 1.0. Background In the modern information-driven world, individuals have unlimited access to health and nutritional information [ 1 , 2 ]. From advice about what to eat to the causes of health crises, the internet is a source of unlimited and ever-expanding information [ 3 ]. Amidst this abundant information, there is a risk of incorrect content. Motivated by profit, content creators can post information that directs people to patronize certain products or services, which might not be helpful to buyers. To protect individuals against this risk, a large body of research has identified health literacy and nutrition literacy as adaptable skills that allow people to make context-specific and timely decisions about their health [ 1 , 4 , 5 ]. E-Health literacy is the ability to rate online health information and use it to make timely health decisions [ 6 , 7 ]. It is a safety barrier against health-related misinformation and a promoter of responsible health decision-making [ 1 , 8 ]. E-Health literacy can be viewed as health literacy in the online context [ 9 ]. Since 2006, this term has been used by numerous studies, and its use has increased as online health information has increased [ 2 ]. Nutrition literacy is a potent defense against unhealthy cooking and eating [ 1 , 10 , 11 ]. Adults have the autonomy to make important decisions about their health, diet, and exercise. Knowledge of nutrients, metabolism, and the ability to make responsible dietary decisions is an important contributor to quality of health and quality of life [ 2 ]. In the present study, nutrition literacy is defined as the ability to acquire nutrition-related information about food and apply that knowledge to meet nutritional needs. Individuals need the ability to understand food labels or other information to understand which foods or combinations of foods will help them meet their nutritional needs [ 10 , 12 ]. Health content on social media is an important part of health promotion information. Information about exercise routines and healthy recipes is abundant on social media sites such as TikTok and YouTube [ 3 , 13 , 14 ]. It is common for dieticians and other healthcare workers to recommend these videos to their patients. 1.1. Aim and Objectives In the current study, the aim was to investigate how e-health literacy and nutrition literacy can be used as tools to navigate the abundant health information available through responsible health-related decision-making. Responsible health-related decision-making is conceptualized as learning about exercise and diet, positive attitudes toward exercise and healthy eating self-efficacy. The study pursued the following objectives: Understanding how e-health literacy is related to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy. Understand how nutrition literacy relates to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy. 1.2. Literature Review The ability to obtain, understand, and use health information and services to make appropriate health decisions plays a crucial role in individual and public health outcomes [ 5 , 7 , 15 ]. With the growing complexity of health information, the importance of literacy in this domain has become more evident, including implications for health policy and lifestyle practices such as diet and exercise. Two core activities promoted by clinicians and health educators are exercise and diet or healthy eating [ 16 ]. Many clinicians who detect a high risk of high blood pressure or diabetes in patients first recommend a combination of diet and exercise as a preventive or delay mechanism against these conditions [ 17 ]. To contextualize the review of relevant literature, the paper scoped e-health literacy and nutrition literacy before presenting relevant past findings about health-related decision-making. 1.2.1. Health literacy to e-health literacy: Definition and scope The WHO defines health literacy as "the cognitive and social skills which determine the motivation and ability of individuals to gain access to, understand and use information in ways which promote and maintain good health" [ 18 ]. Health literacy incorporates a range of skills necessary for individuals to function effectively in the healthcare environment. These include reading and understanding medical instructions, navigating healthcare systems, and communicating with healthcare providers [ 7 ]. E-Health literacy is the ability to access and use health information in the electronic context [ 6 ]. Today, which covers social media, generative artificial intelligence search engines such as Google are referred to by some researchers as ‘Dr. Google, patient portals, and other internet-driven sources of health information. In this study, e-health literacy is conceptualized as health literacy in the online context, as supported by many works, such as Britt et al. [ 9 ] and Lee et al. [ 7 ]. 1.2.2. Nutrition literacy: Concept and importance Nutrition literacy involves knowledge about nutrients, the ability to interpret nutrition labels, and the ability to make informed dietary choices. According to a study performed by Gibbs and Chapman-Novakofski [ 19 ], nutrition literacy is crucial for maintaining a healthy diet and preventing diet-related problems such as obesity, diabetes, and cardiovascular diseases. A growing body of research supports the important role of nutrition literacy in quality healthcare, especially through the prevention of noncommunicable diseases [ 20 ]. As food labeling has become a standard across health systems such as Ghana’s and nutrition systems, which are more widely discussed beyond classrooms and clinics, knowing what to do with nutritional information is crucial [ 12 ]. Koca and Arkan [ 20 ] reported that individuals with higher levels of nutrition literacy are more likely to adhere to dietary guidelines and engage in healthier eating behaviors. Conversely, low nutritional literacy was associated with poor dietary habits and an increased risk of dietary-related diseases. The current study conceptualizes nutrition literacy as the behavior of obtaining and understanding health information and using that information to acquire needed nutrients through eating. 1.2.3. Health-related decision-making In the literature, health-related decision-making ranges from the choice of caregiver visits to preventive action such as exercise and dieting to medication adherence, a concept sometimes described as shared decision-making [ 21 ]. In recent years, patients have been exposed to enormous volumes of online information, which advises them to take actions such as regular exercise [ 14 ] and dieting [ 22 ]. Moreover, some internet sources, motivated by commercial and political interests, discourage proven preventive measures such as vaccination and provide contradictory information regarding dieting and exercising. Individuals must be skilled in making independent decisions on the basis of their needs. These skills should be measurable and trainable. Individuals with higher health and nutrition literacy are better equipped to interpret health information, weigh the risks and benefits of different prevention or treatment options, and make informed decisions [ 5 , 11 ]. Koca and Arkan [ 20 ] highlighted that individuals with better nutrition literacy exhibit improved healthy behaviors. In their cross-sectional research, nutrition literacy improved eating habits aimed at preventing adverse health conditions. 1.2.4. Learning about diet and exercise on social media Social media is currently a regular source of health information for many adults [ 22 ]. Individuals rely on social media for video, text and audio information about a wide range of conditions [ 2 ]. This is done through expert content, influencers and the opinions of nonexperts. This means that while there is abundant information from experts, there is also commercially or politically driven information that may not suit the needs of all individuals [ 23 ]. In a study by Goodyear et al. [ 3 ], to test health-related quality of life and social media use, social media was supported as a promoter of health-related quality of life. The study in the United Kingdom, which used expert stakeholder focus group discussions to recruit 780 survey participants, yielded support for the use of social media for self-management of physical activity and diet. 1.2.5. Health Eating Self-Efficacy After discussing all the literacies and responsible decision-making, it is useful to consider an action that has been recommended as a key enabler of effective dieting [ 24 ]. In this study, healthy eating self-efficacy is positioned as a measurable behavior that describes an individual’s confidence in their ability to regulate their eating. This description is supported by Lombardo et al. [ 25 ], who acknowledged the ability of individuals with high healthy eating self-efficacy to adjust their eating habits to meet ideal body mass indices and other health-related goals. After individuals acquire e-health literacy and nutrition literacy, they are expected to engage in behaviors that promote good health without daily expert guidance. Healthy-eating self-efficacy is a skill that ensures that individuals can independently and confidently choose and eat meals that will allow them to live healthy lives [ 24 ]. Self-efficacy in general enables self-regulated and responsible action across fields of human endeavor. Concerning eating, this skill is targeted by experts who expect the public to make independent eating choices to promote responsible health-related decision-making. This is in line with suggestions in the literature to empower the public and promote behaviors that prevent lifestyle-related diseases [ 10 , 21 , 26 ]. 1.2.6. Attitude toward Exercise In studies focused on empowering individuals to make responsible health-related decisions, exercise is an important component [ 24 ]. The decision to engage in exercise must be independent and sustained through safe pain, unfriendly environmental pressure and seemingly difficulty in a continuous exercise routine. In the study of responsible health-related decision-making, it is useful to consider individuals’ perceptions of exercise. This perception or attitude can determine the actual conduct of regular safe exercise [ 27 ]. An effective exercise routine requires a high level of individual motivation and a positive attitude to commence and sustain it [ 28 ]. This positive attitude begins with an understanding of the benefits of exercise which is enabled by health literacy [ 29 ]. In addition to exercise, a combination of healthy eating is typically recommended. This requires health and nutritional literacy. Skilled with such literacies, individuals can evaluate health information and formulate their attitudes toward exercise. This formulation allows them to award the preferred priority to exercise in their quest to reach and maintain a healthy life. In this study, attitudes toward exercise are included to cover the perceptions of individuals about the role of exercise in health. A positive attitude denotes the belief that exercise is an important component of any lifestyle aimed at achieving optimal health followed by an effective exercise routine. 1.2.7. Hypotheses Based on the evidence reviewed in this paper and the objectives of the study, the following hypotheses were tested. E-Health literacy is related to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy. Nutrition literacy is related to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy. 2.0. Methods 2.1. Study design A cross-sectional survey design was used to explore the role of e-health, nutrition literacy and health-related decision-making among university students in Ghana. The design was suitable for assessing the prevalence of the variables and the relationships between them within a specific population at a single point in time. The participants were approached during lectures with the permission of their professors. On average, it took the participants 10–15 minutes to complete the questionnaire after agreeing to the informed consent statement. 2.2. Setting The study was conducted across multiple universities in Ghana, representing both public and private institutions. The universities included were selected to ensure diversity in geographical location, institutional type, and student demographics. The universities included the University of Ghana, the University of Cape Coast, Cape Coast Technical University and Regent University College. All the participants were approached physically during lectures, with all the questions in paper-pen format. 2.3. Participants The study targeted undergraduate and postgraduate students. A total of 592 students were selected via stratified sampling to ensure representation across different academic levels, fields of study, and genders. To be included in the study, one had to be an enrolled student aged 18 years or older. Exclusion criteria included students with sensory impairments, e.g., blindness or deafness, that could not be accommodated with the available survey tools. 2.4. Instrument and variables The study used a questionnaire with six sections to measure e-health literacy, nutrition literacy, social media used to learn about diet and exercise, attitudes toward exercise, healthy eating self-efficacy and demographics. E-health literacy was measured with an 8-item e-health scale developed by Norman and Skinner (2006), administered on a 5-point Likert scale ranging from Strongly disagree to Strongly agree . Nutrition literacy was measured with a 9-item interactive nutrition literacy scale developed by Al Tell et al. [ 30 ] and administered on a 5-point Likert scale ranging from No way to Definitely . Social media use for learning about diet and exercise was measured with an adapted version of a scale developed by Chintalapati et al. [ 31 ], which was administered on a 5-point Likert scale ranging from Strongly disagree to Strongly agree . Their original 22-item scale focused on YouTube. However, for our current study, we used 14 of the items and replaced YouTube with social media. Attitudes toward exercise were measured with 7 items from a scale developed by Simonton et al. [ 32 ], which was administered on a 5-point Likert scale ranging from Strongly disagree to Strongly agree . Healthy eating self-efficacy was measured with 15 items from a scale developed by Sheeskad, Woolcott and Mackinnon [ 33 ], and administered on a 5-point Likert scale ranging from Strongly disagree to Strongly agree . The internal consistency of the responses, as scored by the Cronbach’s alpha reliability coefficients, was between .73 and .88 ( see Table 1 ). The demographics section of the questionnaire asked about age, sex, level of study, field of study and socioeconomic background. 2.5. Bias To minimize selection bias, a stratified sampling method was employed, ensuring the representation of diverse student groups. Social desirability bias was addressed by ensuring participant anonymity and emphasizing the importance of honest responses. Recall bias was mitigated by limiting the timeframe of questions related to behaviors. 2.6. Study size The sample size of 592 was determined on the basis of Cochran's formula [ 34 ] for determining sample sizes for research. Statistical power calculations to detect significant relationships among the primary variables used a confidence level of 95% and a margin of error of 5%. 2.7. Quantitative variables and statistical methods The quantitative variables included scores for e-health literacy, nutrition literacy, social media use, attitudes toward exercise, and healthy eating self-efficacy. Statistical analysis was performed via IBM SPSS version 27.0. Descriptive statistical analyses were used to measure central tendencies as the first step; in the second step, a correlation analysis of all the hypothesized variables was computed. Finally, two multiple regression analysis models were tested, with e-health and nutrition literacy as outcomes. Assumptions checks for normality and autocorrelation were checked prior to conducting the regressions. 2.8. Ethical considerations Ethical approval for the study was obtained from the Ethics Review Committee (ERC) of Cape Coast Teaching Hospital, with the approval number CCTHERC/EC/2024/116. To improve scientific transparency, the project was preregistered on OSF with a project link osf.io/dxejw . The ethical principles of informed consent, anonymity and confidentiality were observed. The participants were provided with detailed information about the study and signed informed consent forms before participating. To guarantee anonymity, personal identifying information such as names, emails, initials and phone numbers was not collected. All data from the study were stored on a secure cloud accessible only to the researchers, and hard-copy questionnaire responses were stored in a secure vault accessible only to the principal investigator. 3.0. Results 3.1. Descriptive Descriptive statistical analysis was conducted to measure central tendencies, the range of scores on the scales and Cronbach’s alpha reliabilities ( see Table 1 ). To measure the correlation between variables, Pearson product moment reliability coefficients were computed. Table 1 Descriptive statistics and correlations of all variables. N L/H M SD 1 2 3 4 5 1. eHEALS 589 8/40 28.90 5.43 (.83) a 2.NL 581 9/45 29.57 5.01 .40** (.73) a 3.SM 555 21/70 53.72 29.86 .39** .38** (.85) a 4. Attitudes 587 11/35 29.86 4.11 .07 .25** .31** (.88) a 5.HE 571 24/75 53.41 9.77 .17** .27** .28** .29** (.86) Note: N = Sample Size, L/H = Lowest Score/Highest Score, M = Mean, SD = Standard Deviation, ** = Significant correlation at p < .01, () = Cronbach alpha reliability coefficient. NL = Nutrition Literacy, SM = use of social media to learn about diet and exercise, Attitudes = Attitudes toward exercise, HE = Healthy Eating self-efficacy 3.2. Main results - multivariate analysis In this study, two models were tested via multiple regression analysis. Before the two regression analyses were conducted, the assumptions were checked [ 35 ]. There was a normal distribution of the data and errors in the scatter plot and histogram, and there was no autocorrelation (Durbin Watson = 1.783 & 1.817, respectively). The correlation analysis ( see Table 1 ) revealed that there were no concerning high correlations between the predictor variables. 3.2.1. e-health literacy is related to attitudes toward exercise, healthy eating self-efficacy and social media use for learning about diet and exercise . In this regression test, a significant model emerged, as shown by the model summary F (3, 581) = 14,634, p = .000, R = .403, R 2 = .162, adjusted R 2 = .158. Table 2 Multiple regression analysis with e-health as the outcome b SE t p value SM .512 .053 9.590 .000 Attitude − .097 .047 -2.058 .040 HE .090 .043 2.115 .035 Note: b = Unstandardized B, SE = Standard error, p value = Significance. SM = use of social media to learn about diet and exercise, Attitudes = Attitudes toward exercise, HE = Healthy Eating self-efficacy In the first model e-health literacy was used as the outcome with social media use for learning about diet and exercise, attitude towards exercise and healthy eating self-efficacy used as predictors. 3.2.2. Nutrition literacy is related to attitudes toward exercise, healthy eating, self-efficacy and social media use for diet and exercise. A significant model emerged, as indicated by the model summary. The multiple regression to predict nutritional literacy was significant, F(3, 581) = 40,876, p = .000, R = .417, R 2 = .174. Adjusted R 2 = .170 Table 3 Multiple regression with nutrition literacy as the outcome b SE t p value SM .355 .046 7.687 .000 Attitude .109 .041 2.662 .008 HE .112 .038 3.028 .003 Note: b = Unstandardized B, SE = Standard error, p value = Significance. SM = use of social media to learn about diet and exercise, Attitudes = Attitudes toward exercise, HE = Healthy Eating self-efficacy In the second model, nutrition literacy was used as the outcome with social media use for learning about diet and exercise, attitude towards exercise and healthy eating self-efficacy used as predictors. 3.3. Summary of results The results confirm the hypotheses that e-health literacy and nutrition literacy are related to social media use for diet and exercise, attitudes toward exercise and healthy eating, and self-efficacy. However, the relationship between e-health literacy and attitudes towards exercise was negative. 4.0. Discussion and conclusion There were two main findings from this study. First, e-health literacy is related to social media use for learning about diet and exercise, attitudes toward exercise and healthy eating, and self-efficacy. Second, nutrition literacy is related to social media use for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy. In discussing the first finding, it is useful to note that the outcome is like previous findings by Muscat et al. [ 21 ]. E-health literacy has been identified as a key influencer of responsible health-related decision-making. It is thus understandable that this is related to the use of social media for learning about diet and exercise. Social media has become a useful source of vital diet- and exercise-related information. Hospitals, clinicians, advocates and patients all disseminate findings and opinions intending to reach a large audience. Today, it is common for clinicians, dieticians and public health professionals to refer patients to social media videos whenever they want to recommend specific exercise routines, recipes and dietary plans. This finding indicates that individuals who have high e-health literacy are likely to utilize these sources of information. These individuals are responsible decision makers and are highly aware of the useful resources offered by the internet. The relationship between e-health literacy and attitudes toward exercise was unexpectedly negative. The paper did not speculate about this negative relationship because it was unexpected. Finally, the relationship between e-health literacy and healthy eating self-efficacy is plausible due to the nature of both variables. While e-health literacy drives responsible behavior, healthy eating self-efficacy refers to confidence in the ability to eat healthy meals safely. Individuals who score high on e-health literacy are likely to know the benefits of healthy eating and believe that they can determine a healthy eating regimen. This confidence can be driven by their understanding of the health benefits of healthy eating and their ability to use information to meet their nutritional needs. Nutrition literacy is the focus of the second finding. Nutrition literacy’s relationship with social media use for learning about diet and exercise, attitudes toward exercise and healthy eating, and self-efficacy is supported by studies such as those of Koca & Arkan [ 20 ] and Karadag et al. [ 11 ]. The relationship between nutrition literacy and the use of social media for learning about diet and exercise is plausible and has been well supported by data from this study. Nutrition literacy enables individuals to make safe decisions about their nutritional needs and their sources. Social media currently hosts an overwhelming volume of information on exercise and diet in multiple formats. These findings indicate that individuals with high nutritional literacy are more likely to use social media information effectively to help them meet their nutritional needs. They can do this by deriving information from videos about diet and exercise. Afterward, they find meals or products that contain the nutrients needed. Furthermore, they will know how to cook or serve food to preserve nutrients to help them meet their nutritional needs. Their nutritional literacy will help them evaluate their nutritional content and subsequently make decisions that will help them decide the best diet regimens and perform exercises with the best compatibility with their nutritional profiles. Nutrition literacy and attitudes toward exercise are related, according to the findings of this study. The results show that higher nutrition literacy corresponds to a more positive attitude toward exercise. One can explain this through the complementary nature of the desire for nutritional effectiveness and exercise goals. Individuals who score high on nutrition literacy are more likely to have a positive attitude toward exercise because they understand that the combination of a quality nutritional profile and an active exercise profile contributes to positive health outcomes. Finally, nutritional literacy and healthy eating self-efficacy are related. This finding suggests that individuals who score high on nutrition literacy are more likely to be confident in their ability to eat healthily. These individuals understand their nutritional profile, including their current status and needs. They also understand which choice of food can help them meet their nutritional needs. This understanding is important for avoiding food that creates or exacerbates adverse health conditions, such as diabetes, thus leading to healthy decision-making. According to the findings discussed in this paper, training in e-health literacy and nutrition literacy is important. These two literacies enable individuals to use social media to learn more effectively about diet and exercise. Nutrition literacy can help them formulate more realistic and healthy attitudes toward exercise. Finally, these literacies can drive more confidence in healthy eating, which is increasingly recognized by clinicians and advocates to prevent and manage a diverse range of health conditions. These findings have implications for patients, public health educators and researchers. These are discussed in the next subsection. 4.1. Practical implications The findings from this work provide relevant evidence that is valuable for improving patient decision-making, optimizing public health education programs and setting research directions. First, for patients, the findings imply the need for e-health literacy and nutrition literacy. These literacies can contribute to more responsible use of social media, a realistic attitude toward exercise and better healthy eating self-efficacy. These three attitudes are central to helping patients reap the much touted and scientifically supported benefits of exercise and healthy eating. Optimal e-health literacy and nutrition literacy can empower individuals to safely navigate social media and learn about safe ways to diet and exercise. These two behaviors of dieting and exercising are now widely accepted as efficient defenses against sedentary life-linked conditions such as obesity, diabetes and high blood pressure, which are currently burdening health systems in many countries, including Ghana. Second, public health educators can include e-health literacy and nutrition literacy in their campaigns tailored toward disease prevention and preparedness. An e-health literate and nutrition literate population is in a better position to adhere to advise on active lifestyles and healthy eating to prevent ongoing sedentary and poor lifestyle-related diseases and conditions. This is a more cost-effective approach for any health system, as it can effectively help patients adhere to medical advice. Lessons can be taken from relatively successful health education campaigns in Ghana against HIV/AIDS and ante-natal care in the early 2000s and against COVID-19 in 2020–2021. Educational campaigns can target e-health and nutrition literacies to drive useful behaviors such as diet and exercise. This creates a more resilient healthcare system where patients are skilled in finding and using information to improve their health and prevent the burdening of existing but limited health facilities. Finally, these findings imply the need for more investigations into how e-health literacy and nutrition literacy can be effective in disease prevention and adherence to healthy lifestyles. The study recommends research directions along two streams: 1) the role of these literacies and 2) how individuals can be effectively trained in them. Such research, when carried out within specific health systems and health programs, can generate data to effectively train these literacies in contextually relevant settings. These studies should be tailored to specific health conditions, demographics or health systems to allow context-specific data and discussions. Despite the data-driven discussions in this paper and the actionable implications, there were some limitations of the study, which will be discussed in the next paragraph. 4.2. Limitations The limitations of this study are the use of adult samples from universities and a survey method. First, the sample used was likely to be literate and exposed to online information, which would have made them more e-health and nutrition literate. It is recommended that future studies check the source of their e-health and nutrition literacy knowledge or include participants from the general population and not only university students. Second, the method used, although robust, does not provide enough information to shape the training of e-health and nutrition literacy. It is recommended that future studies use experimental methods to investigate how to train these literacies in public health education settings. 4.3. Conclusion This work identified e-health literacy and nutrition literacy as useful drivers of responsible health-related decision making. Today, these are essential components of preventive health and effective adherence. This study uniquely contributes to knowledge by identifying e-health literacy and nutrition literacy as skills related to a patient's health-related decision making. The study recommends that these literacies be trained through public health education methods to help build more health system resilience through more e-health- and nutrition-literate patients. Declarations Ethics approval and consent to participate The study adhered to the Helsinki Declaration on the use of human subjects. Ethics approval was secured by the Ethics Review Committee of the Cape Coast Teaching Hospital (Ghana) with the approval number CCTHERC/EC/2024/116. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing Interests None to declare Funding No external funding was received for this project. Author contributions Conceptualization: MGA, SM, MBA, GGN, HK Methodology: MGA, SM, MBA Validation: MGA, SM, MBA, GGN, HK Formal analysis: MGA, SM Investigation: MGA, SM Data curation: MGA, SM Writing-Original draft: MGA, MBA, GGN, HK Writing-Review & Editing: GGN Supervision: MGA, MBA Project administration: MGA, MBA Acknowledgments We are grateful to Maressa Neuerer of the Heidelberg Institute of Global Health, who helped us conceptualize this study. We thank Mr. Isaac Nyalaba, Ms. Fafali Faith Ganu, Ms. Francisca Gordor and Ms. Dorothy Owusuaah Ahardy for helping us with data collection. References Denniss E, Lindberg R, McNaughton SA. Quality and accuracy of online nutrition-related information: a systematic review of content analysis studies. Public Health Nutrition. 2023;26(7):1345-57. Wang Z, Xu X, Gao S, Wu C, Song Q, Shi Z, Su J, Zang J. Effects of internet-based nutrition and exercise interventions on the prevention and treatment of sarcopenia in elderly individuals. 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Public Health Nutrition. 2021;24(4):717-28. https://doi.org/10.1017/S1368980020001494 Muscat DM, Shepherd HL, Nutbeam D, Trevena L, McCaffery KJ. Health literacy and shared decision-making: exploring the relationship to enable meaningful patient engagement in healthcare. Journal of general internal medicine. 2021 Feb;36:521-4. https://doi.org/10.1007/s11606-020-05912-0 Folkvord F, Roes E, Bevelander K. Promoting healthy foods in the new digital era on Instagram: an experimental study on the effect of a popular real versus fictitious fit influencer on brand attitude and purchase intentions. BMC public health. 2020;20:1-8. https://doi.org/10.1186/s12889-020-09779-y Luo X, Pu H, Wang S, Zhong D, Liu F, Li Z. Influence of internet use on Chinese residents’ health: the mediating role of health knowledge. Technology in Society. 2024;76:102413. https://doi.org/10.1016/j.techsoc.2023.102413 Bales DW, Cotwright CJ, Lee JS, Celestin N, Parrott K, Akin J. Promoting Healthy Eating and Physical Activity in the Early Care and Education Setting as a Strategy to Improve Teacher Knowledge and Self-Efficacy. Early Childhood Education Journal. 2025. 1-3. https://doi.org/10.1007/s10643-025-01851-9 Lombardo C, Cerolini S, Alivernini F, Ballesio A, Violani C, Fernandes M, Lucidi F. Eating self-efficacy: validation of a new brief scale. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity. 2021;26:295-303. Alhazmi A, Ali M, Dawria A, Narapureddy BR, Hawash MM. Assessment of health behaviors of primary school teachers based on their nutritional knowledge and physical activity: A cross-sectional study in the Asir Region. PloS one. 2025 ;20(1):e0318146. https://doi.org/10.1371/journal.pone.0318146 Sokolova K, Perez C. You follow fitness influencers on YouTube. However, do you actually exercise? How parasocial relationships, and watching fitness influencers, relate to intentions to exercise. Journal of retailing and consumer services. 2021;58:102276. https://doi.org/10.1016/j.jretconser.2020.102276 Echieh CP, Dele-Ojo BF, Ahmad Oseni TI, Blankson PK, Duodu F, Tayo BO, Alabi BS, Sarpong DF, Amoakoh-Coleman M, Boima V, Ogedegbe G. The use of telehealth technology for lifestyle modification among patients with hypertension in Nigeria and Ghana. Digital Health. 2024;10:20552076241297035. https://doi.org/10.1177/2055207624129703 Durau J, Diehl S, Terlutter R. Motivate me to exercise with you: The effects of social media fitness influencers on users’ intentions to engage in physical activity and the role of user gender. Digital Health. 2022;8:20552076221102769. https://doi.org/10.1177/20552076221102769 Al Tell M, Natour N, Alshawish E, Badrasawi M. The relationship between nutrition literacy and nutrition information seeking attitudes and healthy eating patterns among a group of palestinians. BMC Public Health. 2023;23(1):165. https://doi.org/10.1186/s12889-023-15121-z Chintalapati N, Daruri VS. Examining the use of YouTube as a Learning Resource in higher education: Scale development and validation of TAM model. Telematics and Informatics. 2017;34(6):853-60. https://doi.org/10.1016/j.tele.2016.08.008 Simonton K, Mercier K, Centeio E, Barcelona J, Phillips S, Garn AC. Development of Youth Physical Activity Attitude Scale (YPAAS) for elementary and middle school students. Measurement in Physical Education and Exercise Science. 2021;25(2):110-26. https://doi.org/10.1080/1091367X.2020.1847113 Sheeshka JD, Woolcott DM, MacKinnon NJ. Social cognitive theory as a framework to explain intentions to practice healthy eating behaviors 1. Journal of applied social psychology. 1993; 23(19):1547-73. https://doi.org/10.1111/j.1559-1816.1993.tb01047.x Cochran WG. Sampling techniques. john wiley & sons; 1977. Field, A. Discovering Statistics Using IBM SPSS Statistics. 5th Ed, Sage, Newbury Park. 2018 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviewers agreed at journal 24 Apr, 2026 Reviews received at journal 29 May, 2025 Reviewers agreed at journal 20 May, 2025 Reviewers agreed at journal 06 May, 2025 Reviewers invited by journal 06 May, 2025 Editor assigned by journal 29 Apr, 2025 Editor invited by journal 09 Apr, 2025 Submission checks completed at journal 07 Apr, 2025 First submitted to journal 07 Apr, 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. 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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-6364493","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452522617,"identity":"40a89b6e-05e5-45b0-ba56-119e40a16d9c","order_by":0,"name":"Martin Gameli Akakpo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYFACNgbGBgYGOQYJMI8ZiHmI02JMupbEBqK16LYfS/w4c4dN+obbzY8/MFRYJzbwrz2AV4vZmbTDkhvPpOVuuHPMTILhTDrQuncJ+LUcSG+QfNh2OHfDjQQzBsa2w0AtZwzwazn/vPknUEu6wY30zx8Y/xGj5UbaMcmNbYcTDG7kGEgwNgC18PcQ0vIszXLmmTTDmTdyyiQSjqUbt0nwEHJYmvHN3h028nw30jd/+FBjLdvPT8BhYACKGDBIAGI2iQTCOhBawID/ABFaRsEoGAWjYCQBAMThUIllxVSkAAAAAElFTkSuQmCC","orcid":"","institution":"University of Health and Allied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Martin","middleName":"Gameli","lastName":"Akakpo","suffix":""},{"id":452522618,"identity":"f6e0b0b7-916d-4bfb-8c7d-7cd58591be80","order_by":1,"name":"Sheriffa Mahama","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Sheriffa","middleName":"","lastName":"Mahama","suffix":""},{"id":452522619,"identity":"b28f98bb-f2db-419b-9974-0a275bcd3bd3","order_by":2,"name":"Glorian Goodluck Nnko","email":"","orcid":"","institution":"University of Dodoma","correspondingAuthor":false,"prefix":"","firstName":"Glorian","middleName":"Goodluck","lastName":"Nnko","suffix":""},{"id":452522620,"identity":"c5579938-d33d-4171-8afa-1c0e3d64dc44","order_by":3,"name":"Mervin Boakye Agyeman","email":"","orcid":"","institution":"Cape Coast Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mervin","middleName":"Boakye","lastName":"Agyeman","suffix":""},{"id":452522621,"identity":"a63c8346-bf70-4e91-abe8-6e6efaf83635","order_by":4,"name":"Henrike Kleuser","email":"","orcid":"","institution":"University Hospital Würzburg","correspondingAuthor":false,"prefix":"","firstName":"Henrike","middleName":"","lastName":"Kleuser","suffix":""}],"badges":[],"createdAt":"2025-04-02 23:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6364493/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6364493/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82352504,"identity":"ce0ba25c-9686-43b6-bd22-38bef8d0afe2","added_by":"auto","created_at":"2025-05-09 11:01:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":838824,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6364493/v1/a8e0874b-a97b-4276-90e3-2e9ea80fff78.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Role of E-Health and Nutrition Literacy in Health-Related Decision-Making: A Cross-Sectional Study of University Students in Ghana\u003c/p\u003e","fulltext":[{"header":"1.0. Background","content":"\u003cp\u003eIn the modern information-driven world, individuals have unlimited access to health and nutritional information [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. From advice about what to eat to the causes of health crises, the internet is a source of unlimited and ever-expanding information [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Amidst this abundant information, there is a risk of incorrect content. Motivated by profit, content creators can post information that directs people to patronize certain products or services, which might not be helpful to buyers. To protect individuals against this risk, a large body of research has identified health literacy and nutrition literacy as adaptable skills that allow people to make context-specific and timely decisions about their health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eE-Health literacy is the ability to rate online health information and use it to make timely health decisions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. It is a safety barrier against health-related misinformation and a promoter of responsible health decision-making [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. E-Health literacy can be viewed as health literacy in the online context [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Since 2006, this term has been used by numerous studies, and its use has increased as online health information has increased [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNutrition literacy is a potent defense against unhealthy cooking and eating [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Adults have the autonomy to make important decisions about their health, diet, and exercise. Knowledge of nutrients, metabolism, and the ability to make responsible dietary decisions is an important contributor to quality of health and quality of life [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, nutrition literacy is defined as the ability to acquire nutrition-related information about food and apply that knowledge to meet nutritional needs. Individuals need the ability to understand food labels or other information to understand which foods or combinations of foods will help them meet their nutritional needs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHealth content on social media is an important part of health promotion information. Information about exercise routines and healthy recipes is abundant on social media sites such as TikTok and YouTube [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. It is common for dieticians and other healthcare workers to recommend these videos to their patients.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Aim and Objectives\u003c/h2\u003e \u003cp\u003eIn the current study, the aim was to investigate how e-health literacy and nutrition literacy can be used as tools to navigate the abundant health information available through responsible health-related decision-making. Responsible health-related decision-making is conceptualized as learning about exercise and diet, positive attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e \u003cp\u003eThe study pursued the following objectives:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cul\u003e \u003cli\u003e \u003cp\u003eUnderstanding how e-health literacy is related to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUnderstand how nutrition literacy relates to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2. Literature Review\u003c/h2\u003e \u003cp\u003eThe ability to obtain, understand, and use health information and services to make appropriate health decisions plays a crucial role in individual and public health outcomes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. With the growing complexity of health information, the importance of literacy in this domain has become more evident, including implications for health policy and lifestyle practices such as diet and exercise. Two core activities promoted by clinicians and health educators are exercise and diet or healthy eating [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Many clinicians who detect a high risk of high blood pressure or diabetes in patients first recommend a combination of diet and exercise as a preventive or delay mechanism against these conditions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To contextualize the review of relevant literature, the paper scoped e-health literacy and nutrition literacy before presenting relevant past findings about health-related decision-making.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e1.2.1. Health literacy to e-health literacy: Definition and scope\u003c/h2\u003e \u003cp\u003eThe WHO defines health literacy as \"the cognitive and social skills which determine the motivation and ability of individuals to gain access to, understand and use information in ways which promote and maintain good health\" [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Health literacy incorporates a range of skills necessary for individuals to function effectively in the healthcare environment. These include reading and understanding medical instructions, navigating healthcare systems, and communicating with healthcare providers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. E-Health literacy is the ability to access and use health information in the electronic context [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Today, which covers social media, generative artificial intelligence search engines such as Google are referred to by some researchers as ‘Dr. Google, patient portals, and other internet-driven sources of health information. In this study, e-health literacy is conceptualized as health literacy in the online context, as supported by many works, such as Britt et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and Lee et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e1.2.2. Nutrition literacy: Concept and importance\u003c/h2\u003e \u003cp\u003eNutrition literacy involves knowledge about nutrients, the ability to interpret nutrition labels, and the ability to make informed dietary choices. According to a study performed by Gibbs and Chapman-Novakofski [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], nutrition literacy is crucial for maintaining a healthy diet and preventing diet-related problems such as obesity, diabetes, and cardiovascular diseases. A growing body of research supports the important role of nutrition literacy in quality healthcare, especially through the prevention of noncommunicable diseases [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. As food labeling has become a standard across health systems such as Ghana’s and nutrition systems, which are more widely discussed beyond classrooms and clinics, knowing what to do with nutritional information is crucial [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eKoca and Arkan [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] reported that individuals with higher levels of nutrition literacy are more likely to adhere to dietary guidelines and engage in healthier eating behaviors. Conversely, low nutritional literacy was associated with poor dietary habits and an increased risk of dietary-related diseases.\u003c/p\u003e \u003cp\u003eThe current study conceptualizes nutrition literacy as the behavior of obtaining and understanding health information and using that information to acquire needed nutrients through eating.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e1.2.3. Health-related decision-making\u003c/h2\u003e \u003cp\u003eIn the literature, health-related decision-making ranges from the choice of caregiver visits to preventive action such as exercise and dieting to medication adherence, a concept sometimes described as shared decision-making [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In recent years, patients have been exposed to enormous volumes of online information, which advises them to take actions such as regular exercise [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and dieting [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, some internet sources, motivated by commercial and political interests, discourage proven preventive measures such as vaccination and provide contradictory information regarding dieting and exercising. Individuals must be skilled in making independent decisions on the basis of their needs. These skills should be measurable and trainable.\u003c/p\u003e \u003cp\u003eIndividuals with higher health and nutrition literacy are better equipped to interpret health information, weigh the risks and benefits of different prevention or treatment options, and make informed decisions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Koca and Arkan [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] highlighted that individuals with better nutrition literacy exhibit improved healthy behaviors. In their cross-sectional research, nutrition literacy improved eating habits aimed at preventing adverse health conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e1.2.4. Learning about diet and exercise on social media\u003c/h2\u003e \u003cp\u003eSocial media is currently a regular source of health information for many adults [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Individuals rely on social media for video, text and audio information about a wide range of conditions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This is done through expert content, influencers and the opinions of nonexperts. This means that while there is abundant information from experts, there is also commercially or politically driven information that may not suit the needs of all individuals [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn a study by Goodyear et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], to test health-related quality of life and social media use, social media was supported as a promoter of health-related quality of life. The study in the United Kingdom, which used expert stakeholder focus group discussions to recruit 780 survey participants, yielded support for the use of social media for self-management of physical activity and diet.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e1.2.5. Health Eating Self-Efficacy\u003c/h2\u003e \u003cp\u003eAfter discussing all the literacies and responsible decision-making, it is useful to consider an action that has been recommended as a key enabler of effective dieting [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this study, healthy eating self-efficacy is positioned as a measurable behavior that describes an individual’s confidence in their ability to regulate their eating. This description is supported by Lombardo et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], who acknowledged the ability of individuals with high healthy eating self-efficacy to adjust their eating habits to meet ideal body mass indices and other health-related goals.\u003c/p\u003e \u003cp\u003eAfter individuals acquire e-health literacy and nutrition literacy, they are expected to engage in behaviors that promote good health without daily expert guidance. Healthy-eating self-efficacy is a skill that ensures that individuals can independently and confidently choose and eat meals that will allow them to live healthy lives [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Self-efficacy in general enables self-regulated and responsible action across fields of human endeavor. Concerning eating, this skill is targeted by experts who expect the public to make independent eating choices to promote responsible health-related decision-making. This is in line with suggestions in the literature to empower the public and promote behaviors that prevent lifestyle-related diseases [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e1.2.6. Attitude toward Exercise\u003c/h2\u003e \u003cp\u003eIn studies focused on empowering individuals to make responsible health-related decisions, exercise is an important component [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The decision to engage in exercise must be independent and sustained through safe pain, unfriendly environmental pressure and seemingly difficulty in a continuous exercise routine. In the study of responsible health-related decision-making, it is useful to consider individuals’ perceptions of exercise. This perception or attitude can determine the actual conduct of regular safe exercise [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn effective exercise routine requires a high level of individual motivation and a positive attitude to commence and sustain it [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This positive attitude begins with an understanding of the benefits of exercise which is enabled by health literacy [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In addition to exercise, a combination of healthy eating is typically recommended. This requires health and nutritional literacy. Skilled with such literacies, individuals can evaluate health information and formulate their attitudes toward exercise. This formulation allows them to award the preferred priority to exercise in their quest to reach and maintain a healthy life.\u003c/p\u003e \u003cp\u003eIn this study, attitudes toward exercise are included to cover the perceptions of individuals about the role of exercise in health. A positive attitude denotes the belief that exercise is an important component of any lifestyle aimed at achieving optimal health followed by an effective exercise routine.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e1.2.7. Hypotheses\u003c/h2\u003e \u003cp\u003eBased on the evidence reviewed in this paper and the objectives of the study, the following hypotheses were tested.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eE-Health literacy is related to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNutrition literacy is related to the use of social media for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e "},{"header":"2.0. Methods","content":"\u003ch2\u003e2.1. Study design\u003c/h2\u003e\u003cp\u003eA cross-sectional survey design was used to explore the role of e-health, nutrition literacy and health-related decision-making among university students in Ghana. The design was suitable for assessing the prevalence of the variables and the relationships between them within a specific population at a single point in time. The participants were approached during lectures with the permission of their professors. On average, it took the participants 10–15 minutes to complete the questionnaire after agreeing to the informed consent statement.\u003c/p\u003e\u003ch2\u003e2.2. Setting\u003c/h2\u003e\u003cp\u003eThe study was conducted across multiple universities in Ghana, representing both public and private institutions. The universities included were selected to ensure diversity in geographical location, institutional type, and student demographics. The universities included the University of Ghana, the University of Cape Coast, Cape Coast Technical University and Regent University College. All the participants were approached physically during lectures, with all the questions in paper-pen format.\u003c/p\u003e\u003ch2\u003e2.3. Participants\u003c/h2\u003e\u003cp\u003eThe study targeted undergraduate and postgraduate students. A total of 592 students were selected via stratified sampling to ensure representation across different academic levels, fields of study, and genders. To be included in the study, one had to be an enrolled student aged 18 years or older. Exclusion criteria included students with sensory impairments, e.g., blindness or deafness, that could not be accommodated with the available survey tools.\u003c/p\u003e\u003ch2\u003e2.4. Instrument and variables\u003c/h2\u003e\u003cp\u003eThe study used a questionnaire with six sections to measure e-health literacy, nutrition literacy, social media used to learn about diet and exercise, attitudes toward exercise, healthy eating self-efficacy and demographics.\u003c/p\u003e\u003cp\u003eE-health literacy was measured with an 8-item e-health scale developed by Norman and Skinner (2006), administered on a 5-point Likert scale ranging from \u003cem\u003eStrongly disagree\u003c/em\u003e to \u003cem\u003eStrongly agree\u003c/em\u003e. Nutrition literacy was measured with a 9-item interactive nutrition literacy scale developed by Al Tell et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and administered on a 5-point Likert scale ranging from \u003cem\u003eNo way\u003c/em\u003e to \u003cem\u003eDefinitely\u003c/em\u003e. Social media use for learning about diet and exercise was measured with an adapted version of a scale developed by Chintalapati et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], which was administered on a 5-point Likert scale ranging from \u003cem\u003eStrongly disagree\u003c/em\u003e to \u003cem\u003eStrongly agree\u003c/em\u003e. Their original 22-item scale focused on YouTube. However, for our current study, we used 14 of the items and replaced YouTube with social media. Attitudes toward exercise were measured with 7 items from a scale developed by Simonton et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], which was administered on a 5-point Likert scale ranging from \u003cem\u003eStrongly disagree\u003c/em\u003e to \u003cem\u003eStrongly agree\u003c/em\u003e. Healthy eating self-efficacy was measured with 15 items from a scale developed by Sheeskad, Woolcott and Mackinnon [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and administered on a 5-point Likert scale ranging from \u003cem\u003eStrongly disagree\u003c/em\u003e to \u003cem\u003eStrongly agree\u003c/em\u003e. The internal consistency of the responses, as scored by the Cronbach’s alpha reliability coefficients, was between .73 and .88 (\u003cem\u003esee\u003c/em\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The demographics section of the questionnaire asked about age, sex, level of study, field of study and socioeconomic background.\u003c/p\u003e\u003ch2\u003e2.5. Bias\u003c/h2\u003e\u003cp\u003eTo minimize selection bias, a stratified sampling method was employed, ensuring the representation of diverse student groups. Social desirability bias was addressed by ensuring participant anonymity and emphasizing the importance of honest responses. Recall bias was mitigated by limiting the timeframe of questions related to behaviors.\u003c/p\u003e\u003ch2\u003e2.6. Study size\u003c/h2\u003e\u003cp\u003eThe sample size of 592 was determined on the basis of Cochran's formula [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] for determining sample sizes for research. Statistical power calculations to detect significant relationships among the primary variables used a confidence level of 95% and a margin of error of 5%.\u003c/p\u003e\u003ch2\u003e2.7. Quantitative variables and statistical methods\u003c/h2\u003e\u003cp\u003eThe quantitative variables included scores for e-health literacy, nutrition literacy, social media use, attitudes toward exercise, and healthy eating self-efficacy. Statistical analysis was performed via IBM SPSS version 27.0. Descriptive statistical analyses were used to measure central tendencies as the first step; in the second step, a correlation analysis of all the hypothesized variables was computed. Finally, two multiple regression analysis models were tested, with e-health and nutrition literacy as outcomes. Assumptions checks for normality and autocorrelation were checked prior to conducting the regressions.\u003c/p\u003e\u003ch2\u003e2.8. Ethical considerations\u003c/h2\u003e\u003cp\u003eEthical approval for the study was obtained from the Ethics Review Committee (ERC) of Cape Coast Teaching Hospital, with the approval number CCTHERC/EC/2024/116. To improve scientific transparency, the project was preregistered on OSF with a project link \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eosf.io/dxejw\u003c/span\u003e. The ethical principles of informed consent, anonymity and confidentiality were observed. The participants were provided with detailed information about the study and signed informed consent forms before participating. To guarantee anonymity, personal identifying information such as names, emails, initials and phone numbers was not collected. All data from the study were stored on a secure cloud accessible only to the researchers, and hard-copy questionnaire responses were stored in a secure vault accessible only to the principal investigator.\u003c/p\u003e"},{"header":"3.0. Results","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Descriptive\u003c/h2\u003e \u003cp\u003eDescriptive statistical analysis was conducted to measure central tendencies, the range of scores on the scales and Cronbach\u0026rsquo;s alpha reliabilities (\u003cem\u003esee\u003c/em\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To measure the correlation between variables, Pearson product moment reliability coefficients were computed.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDescriptive statistics and correlations of all variables.\u003c/em\u003e\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 \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL/H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\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 \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. eHEALS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(.83) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.NL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.40**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(.73) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.SM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21/70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.39**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.38**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(.85) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Attitudes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11/35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.25**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(.88) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.HE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24/75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.27**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.28**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNote: N\u0026thinsp;=\u0026thinsp;Sample Size, L/H\u0026thinsp;=\u0026thinsp;Lowest Score/Highest Score, M\u0026thinsp;=\u0026thinsp;Mean, SD\u0026thinsp;=\u0026thinsp;Standard Deviation, ** = Significant correlation at p\u0026thinsp;\u0026lt;\u0026thinsp;.01, ()\u0026thinsp;=\u0026thinsp;Cronbach alpha reliability coefficient. NL\u0026thinsp;=\u0026thinsp;Nutrition Literacy, SM\u0026thinsp;=\u0026thinsp;use of social media to learn about diet and exercise, Attitudes\u0026thinsp;=\u0026thinsp;Attitudes toward exercise, HE\u0026thinsp;=\u0026thinsp;Healthy Eating self-efficacy\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Main results - multivariate analysis\u003c/h2\u003e \u003cp\u003eIn this study, two models were tested via multiple regression analysis. Before the two regression analyses were conducted, the assumptions were checked [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. There was a normal distribution of the data and errors in the scatter plot and histogram, and there was no autocorrelation (Durbin Watson\u0026thinsp;=\u0026thinsp;1.783 \u0026amp; 1.817, respectively). The correlation analysis (\u003cem\u003esee\u003c/em\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed that there were no concerning high correlations between the predictor variables.\u003c/p\u003e \u003cp\u003e3.2.1. \u003cem\u003ee-health literacy is related to attitudes toward exercise, healthy eating self-efficacy and social media use for learning about diet and exercise\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn this regression test, a significant model emerged, as shown by the model summary \u003cem\u003eF\u003c/em\u003e(3, 581)\u0026thinsp;=\u0026thinsp;14,634, p\u0026thinsp;=\u0026thinsp;.000, R\u0026thinsp;=\u0026thinsp;.403, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.162, adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.158.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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\u003eMultiple regression analysis with e-health as the outcome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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 \u003cp\u003eSM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttitude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: \u003cem\u003eb\u0026thinsp;=\u0026thinsp;Unstandardized B, SE\u0026thinsp;=\u0026thinsp;Standard error, p value\u0026thinsp;=\u0026thinsp;Significance. SM\u0026thinsp;=\u0026thinsp;use of social media to learn about diet and exercise, Attitudes\u0026thinsp;=\u0026thinsp;Attitudes toward exercise, HE\u0026thinsp;=\u0026thinsp;Healthy Eating self-efficacy\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the first model e-health literacy was used as the outcome with social media use for learning about diet and exercise, attitude towards exercise and healthy eating self-efficacy used as predictors.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.2.2. Nutrition literacy is related to attitudes toward exercise, healthy eating, self-efficacy and social media use for diet and exercise.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA significant model emerged, as indicated by the model summary. The multiple regression to predict nutritional literacy was significant, F(3, 581)\u0026thinsp;=\u0026thinsp;40,876, p\u0026thinsp;=\u0026thinsp;.000, R\u0026thinsp;=\u0026thinsp;.417, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.174. Adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.170\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple regression with nutrition literacy as the outcome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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 \u003cp\u003eSM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttitude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eNote: b\u0026thinsp;=\u0026thinsp;Unstandardized B, SE\u0026thinsp;=\u0026thinsp;Standard error, p value\u0026thinsp;=\u0026thinsp;Significance. SM\u0026thinsp;=\u0026thinsp;use of social media to learn about diet and exercise, Attitudes\u0026thinsp;=\u0026thinsp;Attitudes toward exercise, HE\u0026thinsp;=\u0026thinsp;Healthy Eating self-efficacy\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the second model, nutrition literacy was used as the outcome with social media use for learning about diet and exercise, attitude towards exercise and healthy eating self-efficacy used as predictors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Summary of results\u003c/h2\u003e \u003cp\u003eThe results confirm the hypotheses that e-health literacy and nutrition literacy are related to social media use for diet and exercise, attitudes toward exercise and healthy eating, and self-efficacy. However, the relationship between e-health literacy and attitudes towards exercise was negative.\u003c/p\u003e \u003c/div\u003e"},{"header":"4.0. Discussion and conclusion","content":"\u003cp\u003eThere were two main findings from this study. First, e-health literacy is related to social media use for learning about diet and exercise, attitudes toward exercise and healthy eating, and self-efficacy. Second, nutrition literacy is related to social media use for learning about diet and exercise, attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e \u003cp\u003eIn discussing the first finding, it is useful to note that the outcome is like previous findings by Muscat et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. E-health literacy has been identified as a key influencer of responsible health-related decision-making. It is thus understandable that this is related to the use of social media for learning about diet and exercise. Social media has become a useful source of vital diet- and exercise-related information. Hospitals, clinicians, advocates and patients all disseminate findings and opinions intending to reach a large audience. Today, it is common for clinicians, dieticians and public health professionals to refer patients to social media videos whenever they want to recommend specific exercise routines, recipes and dietary plans. This finding indicates that individuals who have high e-health literacy are likely to utilize these sources of information. These individuals are responsible decision makers and are highly aware of the useful resources offered by the internet.\u003c/p\u003e \u003cp\u003eThe relationship between e-health literacy and attitudes toward exercise was unexpectedly negative. The paper did not speculate about this negative relationship because it was unexpected.\u003c/p\u003e \u003cp\u003eFinally, the relationship between e-health literacy and healthy eating self-efficacy is plausible due to the nature of both variables. While e-health literacy drives responsible behavior, healthy eating self-efficacy refers to confidence in the ability to eat healthy meals safely. Individuals who score high on e-health literacy are likely to know the benefits of healthy eating and believe that they can determine a healthy eating regimen. This confidence can be driven by their understanding of the health benefits of healthy eating and their ability to use information to meet their nutritional needs.\u003c/p\u003e \u003cp\u003eNutrition literacy is the focus of the second finding. Nutrition literacy\u0026rsquo;s relationship with social media use for learning about diet and exercise, attitudes toward exercise and healthy eating, and self-efficacy is supported by studies such as those of Koca \u0026amp; Arkan [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and Karadag et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The relationship between nutrition literacy and the use of social media for learning about diet and exercise is plausible and has been well supported by data from this study. Nutrition literacy enables individuals to make safe decisions about their nutritional needs and their sources. Social media currently hosts an overwhelming volume of information on exercise and diet in multiple formats. These findings indicate that individuals with high nutritional literacy are more likely to use social media information effectively to help them meet their nutritional needs. They can do this by deriving information from videos about diet and exercise. Afterward, they find meals or products that contain the nutrients needed. Furthermore, they will know how to cook or serve food to preserve nutrients to help them meet their nutritional needs. Their nutritional literacy will help them evaluate their nutritional content and subsequently make decisions that will help them decide the best diet regimens and perform exercises with the best compatibility with their nutritional profiles. Nutrition literacy and attitudes toward exercise are related, according to the findings of this study. The results show that higher nutrition literacy corresponds to a more positive attitude toward exercise. One can explain this through the complementary nature of the desire for nutritional effectiveness and exercise goals. Individuals who score high on nutrition literacy are more likely to have a positive attitude toward exercise because they understand that the combination of a quality nutritional profile and an active exercise profile contributes to positive health outcomes. Finally, nutritional literacy and healthy eating self-efficacy are related. This finding suggests that individuals who score high on nutrition literacy are more likely to be confident in their ability to eat healthily. These individuals understand their nutritional profile, including their current status and needs. They also understand which choice of food can help them meet their nutritional needs. This understanding is important for avoiding food that creates or exacerbates adverse health conditions, such as diabetes, thus leading to healthy decision-making.\u003c/p\u003e \u003cp\u003eAccording to the findings discussed in this paper, training in e-health literacy and nutrition literacy is important. These two literacies enable individuals to use social media to learn more effectively about diet and exercise. Nutrition literacy can help them formulate more realistic and healthy attitudes toward exercise. Finally, these literacies can drive more confidence in healthy eating, which is increasingly recognized by clinicians and advocates to prevent and manage a diverse range of health conditions. These findings have implications for patients, public health educators and researchers. These are discussed in the next subsection.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Practical implications\u003c/h2\u003e \u003cp\u003eThe findings from this work provide relevant evidence that is valuable for improving patient decision-making, optimizing public health education programs and setting research directions. First, for patients, the findings imply the need for e-health literacy and nutrition literacy. These literacies can contribute to more responsible use of social media, a realistic attitude toward exercise and better healthy eating self-efficacy. These three attitudes are central to helping patients reap the much touted and scientifically supported benefits of exercise and healthy eating. Optimal e-health literacy and nutrition literacy can empower individuals to safely navigate social media and learn about safe ways to diet and exercise. These two behaviors of dieting and exercising are now widely accepted as efficient defenses against sedentary life-linked conditions such as obesity, diabetes and high blood pressure, which are currently burdening health systems in many countries, including Ghana.\u003c/p\u003e \u003cp\u003eSecond, public health educators can include e-health literacy and nutrition literacy in their campaigns tailored toward disease prevention and preparedness. An e-health literate and nutrition literate population is in a better position to adhere to advise on active lifestyles and healthy eating to prevent ongoing sedentary and poor lifestyle-related diseases and conditions. This is a more cost-effective approach for any health system, as it can effectively help patients adhere to medical advice. Lessons can be taken from relatively successful health education campaigns in Ghana against HIV/AIDS and ante-natal care in the early 2000s and against COVID-19 in 2020\u0026ndash;2021. Educational campaigns can target e-health and nutrition literacies to drive useful behaviors such as diet and exercise. This creates a more resilient healthcare system where patients are skilled in finding and using information to improve their health and prevent the burdening of existing but limited health facilities.\u003c/p\u003e \u003cp\u003eFinally, these findings imply the need for more investigations into how e-health literacy and nutrition literacy can be effective in disease prevention and adherence to healthy lifestyles. The study recommends research directions along two streams: 1) the role of these literacies and 2) how individuals can be effectively trained in them. Such research, when carried out within specific health systems and health programs, can generate data to effectively train these literacies in contextually relevant settings. These studies should be tailored to specific health conditions, demographics or health systems to allow context-specific data and discussions. Despite the data-driven discussions in this paper and the actionable implications, there were some limitations of the study, which will be discussed in the next paragraph.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Limitations\u003c/h2\u003e \u003cp\u003eThe limitations of this study are the use of adult samples from universities and a survey method. First, the sample used was likely to be literate and exposed to online information, which would have made them more e-health and nutrition literate. It is recommended that future studies check the source of their e-health and nutrition literacy knowledge or include participants from the general population and not only university students. Second, the method used, although robust, does not provide enough information to shape the training of e-health and nutrition literacy. It is recommended that future studies use experimental methods to investigate how to train these literacies in public health education settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Conclusion\u003c/h2\u003e \u003cp\u003eThis work identified e-health literacy and nutrition literacy as useful drivers of responsible health-related decision making. Today, these are essential components of preventive health and effective adherence. This study uniquely contributes to knowledge by identifying e-health literacy and nutrition literacy as skills related to a patient's health-related decision making. The study recommends that these literacies be trained through public health education methods to help build more health system resilience through more e-health- and nutrition-literate patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study adhered to the Helsinki Declaration on the use of human subjects. Ethics approval was secured by the Ethics Review Committee of the Cape Coast Teaching Hospital (Ghana) with the approval number CCTHERC/EC/2024/116.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding was received for this project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: MGA, SM, MBA, GGN, HK\u003c/p\u003e\n\u003cp\u003eMethodology: MGA, SM, MBA\u003c/p\u003e\n\u003cp\u003eValidation: MGA, SM, MBA, GGN, HK\u003c/p\u003e\n\u003cp\u003eFormal analysis: MGA, SM\u003c/p\u003e\n\u003cp\u003eInvestigation: MGA, SM\u003c/p\u003e\n\u003cp\u003eData curation: MGA, SM\u003c/p\u003e\n\u003cp\u003eWriting-Original draft: MGA, MBA, GGN, HK\u003c/p\u003e\n\u003cp\u003eWriting-Review \u0026amp; Editing: GGN\u003c/p\u003e\n\u003cp\u003eSupervision: MGA, MBA\u003c/p\u003e\n\u003cp\u003eProject administration: MGA, MBA\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to Maressa Neuerer of the Heidelberg Institute of Global Health, who helped us conceptualize this study.\u003c/p\u003e\n\u003cp\u003eWe thank Mr. Isaac Nyalaba, Ms. Fafali Faith Ganu, Ms. Francisca Gordor and Ms. Dorothy Owusuaah Ahardy for helping us with data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDenniss E, Lindberg R, McNaughton SA. 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Food label literacy among urban dwelling households in Ghana. Food and Humanity. 2024;2:100312. https://doi.org/10.1016/j.foohum.2024.100312\u003c/li\u003e\n\u003cli\u003eClark L, Lopez EI, Woods L, Yockey A, Butler R, Barroso CS. Nutrition-related information shared by latine influencers: A YouTube content analysis. Health promotion practice. 2023;24(4):713-22. https://doi.org/10.1177/1524839922108330.\u003c/li\u003e\n\u003cli\u003eKim K, Shin S, Kim S, Lee E. The relation between eHealth literacy and health-related behaviors: systematic review and meta-analysis. Journal of Medical internet Research. 2023;25:e40778.\u003c/li\u003e\n\u003cli\u003eTeshale AB, Biney GK, Sarfo M, Ameyaw EK, Yaya S. What Do Mothers Know About Nutrition? Impacts on Childhood Nutrition Outcomes in Sub-Saharan Africa. Maternal and Child Health Journal. 2025:1-2.https://doi.org/10.1007/s10995-025-04052-3\u003c/li\u003e\n\u003cli\u003eAzagba-Nyako JM, Tortoe C, Akonor PT, Padi A, Boateng J, Otwey R. 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Technology in Society. 2024;76:102413. https://doi.org/10.1016/j.techsoc.2023.102413\u003c/li\u003e\n\u003cli\u003eBales DW, Cotwright CJ, Lee JS, Celestin N, Parrott K, Akin J. Promoting Healthy Eating and Physical Activity in the Early Care and Education Setting as a Strategy to Improve Teacher Knowledge and Self-Efficacy. Early Childhood Education Journal. 2025. 1-3. https://doi.org/10.1007/s10643-025-01851-9\u003c/li\u003e\n\u003cli\u003eLombardo C, Cerolini S, Alivernini F, Ballesio A, Violani C, Fernandes M, Lucidi F. Eating self-efficacy: validation of a new brief scale. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity. 2021;26:295-303.\u003c/li\u003e\n\u003cli\u003eAlhazmi A, Ali M, Dawria A, Narapureddy BR, Hawash MM. Assessment of health behaviors of primary school teachers based on their nutritional knowledge and physical activity: A cross-sectional study in the Asir Region. PloS one. 2025 ;20(1):e0318146. https://doi.org/10.1371/journal.pone.0318146\u003c/li\u003e\n\u003cli\u003eSokolova K, Perez C. You follow fitness influencers on YouTube. However, do you actually exercise? How parasocial relationships, and watching fitness influencers, relate to intentions to exercise. Journal of retailing and consumer services. 2021;58:102276. https://doi.org/10.1016/j.jretconser.2020.102276\u003c/li\u003e\n\u003cli\u003eEchieh CP, Dele-Ojo BF, Ahmad Oseni TI, Blankson PK, Duodu F, Tayo BO, Alabi BS, Sarpong DF, Amoakoh-Coleman M, Boima V, Ogedegbe G. The use of telehealth technology for lifestyle modification among patients with hypertension in Nigeria and Ghana. Digital Health. 2024;10:20552076241297035. https://doi.org/10.1177/2055207624129703\u003c/li\u003e\n\u003cli\u003eDurau J, Diehl S, Terlutter R. Motivate me to exercise with you: The effects of social media fitness influencers on users\u0026rsquo; intentions to engage in physical activity and the role of user gender. Digital Health. 2022;8:20552076221102769. https://doi.org/10.1177/20552076221102769\u003c/li\u003e\n\u003cli\u003eAl Tell M, Natour N, Alshawish E, Badrasawi M. The relationship between nutrition literacy and nutrition information seeking attitudes and healthy eating patterns among a group of palestinians. BMC Public Health. 2023;23(1):165. https://doi.org/10.1186/s12889-023-15121-z\u003c/li\u003e\n\u003cli\u003eChintalapati N, Daruri VS. Examining the use of YouTube as a Learning Resource in higher education: Scale development and validation of TAM model. Telematics and Informatics. 2017;34(6):853-60. https://doi.org/10.1016/j.tele.2016.08.008\u003c/li\u003e\n\u003cli\u003eSimonton K, Mercier K, Centeio E, Barcelona J, Phillips S, Garn AC. Development of Youth Physical Activity Attitude Scale (YPAAS) for elementary and middle school students. Measurement in Physical Education and Exercise Science. 2021;25(2):110-26. https://doi.org/10.1080/1091367X.2020.1847113\u003c/li\u003e\n\u003cli\u003eSheeshka JD, Woolcott DM, MacKinnon NJ. Social cognitive theory as a framework to explain intentions to practice healthy eating behaviors 1. Journal of applied social psychology. 1993; 23(19):1547-73. https://doi.org/10.1111/j.1559-1816.1993.tb01047.x\u003c/li\u003e\n\u003cli\u003eCochran WG. Sampling techniques. john wiley \u0026amp; sons; 1977.\u003c/li\u003e\n\u003cli\u003eField, A. Discovering Statistics Using IBM SPSS Statistics. 5th Ed, Sage, Newbury Park. 2018\u003c/li\u003e\n\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-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"e-health literacy, nutrition literacy, exercise, diet, healthy eating, health decision-making","lastPublishedDoi":"10.21203/rs.3.rs-6364493/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6364493/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e. This study investigated the role of e-health literacy and nutrition literacy in health-related decision-making. The scope of health decision-making in this study included the use of social media to learn about diet and exercise, attitudes toward exercise and healthy eating self-efficacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods. \u003c/strong\u003eData were collected from 592 university students in Ghana via a cross-sectional survey. A questionnaire collected data about e-health literacy, nutrition literacy, use of social media to learn about diet and exercise, attitudes toward exercise, healthy eating self-efficacy and demographics. Multiple linear regressions were used to test the hypothesis that e-health literacy and Nutrition literacy are related to health decision-making.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults.\u003c/strong\u003e As hypothesized, e-health literacy (R\u003csup\u003e2\u003c/sup\u003e = .16, p = .00) and nutrition literacy (R\u003csup\u003e2\u003c/sup\u003e = .19, p = .00) were related to health decision-making. The findings show that e-health literacy and nutrition literacy are related to health-related decision-making. The implications for patients, public health educators and researchers are discussed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion. \u003c/strong\u003eThis study uniquely contributes to knowledge by demonstrating how e-health and nutrition literacy influence a patient’s use of social media for learning about diet and exercise. Moreover, these factors are related to attitudes toward physical activity and enhance self-efficacy in maintaining healthy eating habits.\u003c/p\u003e","manuscriptTitle":"The Role of E-Health and Nutrition Literacy in Health-Related Decision-Making: A Cross-Sectional Study of University Students in Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 10:45:40","doi":"10.21203/rs.3.rs-6364493/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-18T06:41:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"56198447366578997584053122518974065269","date":"2026-04-24T14:14:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-29T15:10:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205834231298083518200790124034796626127","date":"2025-05-21T03:37:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"223065702240906454850433923336195167198","date":"2025-05-06T08:31:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-06T07:34:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-29T17:33:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-09T11:19:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-07T12:32:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-04-07T12:31:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"052943bb-e455-48ab-999f-18b27a99add6","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T06:41:30+00:00","index":99,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-05-09T10:45:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 10:45:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6364493","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6364493","identity":"rs-6364493","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}