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Introduction Influenza is a major global health concern, with its rapid spread and mutation rate posing significant challenges in public health education and communication. Effective patient education materials (PEMs) are crucial for informed decision-making and improved health outcomes. This study evaluates the efficacy of online influenza PEMs using traditional readability tools and introduces the Contextual Health Education Readability Score (CHERS) to address the limitations of existing methods that do not capture the diverse array of visual and thematic means displayed. Materials and methods A comprehensive search was conducted to select relevant online influenza PEMs. This involved looking through Google's first two pages of results sorted by relevance, for a total of 20 results. These materials were evaluated using established readability tools (e.g., Flesch Reading Ease, Flesch-Kincaid Grade Level) and the Patient Education Materials Assessment Tool (PEMAT) for understandability and actionability. The study also involved the creation of CHERS, integrating factors such as semantic complexity, cultural relevance, and visual aid effectiveness. The development of CHERS included weighting each component based on its impact on readability and comprehension. Results The traditional readability tools demonstrated significant variability in the readability of the selected materials. The PEMAT analysis revealed general trends toward clarity in purpose and use of everyday language but indicated a need for improvement in summaries and visual aids. The CHERS formula was calculated as follows: CHERS = (0.4 × Average Sentence Length) + (0.3 × Average Syllables per Word) + (0.15 × Semantic Complexity Score) + (0.1 × Cultural Relevance Score) + (0.05 × Visual Aid Effectiveness Score), integrating multiple dimensions beyond traditional readability metrics. Discussion The study highlighted the limitations of traditional readability tools in assessing the complexity and cultural relevance of health information. The introduction of CHERS addressed these gaps by incorporating additional dimensions crucial for understanding in a healthcare context. The recommendations provided for creating effective influenza PEMs focused on language simplicity, cultural sensitivity, and actionability. This may enable further research into evaluating current PEMs and clarifying means of creating more effective content in the future. Conclusions The study underscores the need for comprehensive readability assessments in PEMs. The creation of CHERS marks a significant advancement in this field, providing a more holistic approach to evaluating health literacy materials. Its application could lead to the development of more inclusive and effective educational content, thereby improving public health outcomes and reducing the global burden of influenza. Future research should focus on further validating CHERS and exploring its applicability to other health conditions.

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For cancer patients undergoing treatment who may be at higher risk of COVID-19, access to high-quality online health information (OHI) may be of particular importance amidst a plethora of harmful medical misinformation online. Therefore, we assessed the readability and quality of OHI available for various cancer types and treatment modalities. Search phrases included "cancer radiation COVID," "cancer surgery COVID," "cancer chemotherapy COVID," and "cancer type COVID," for the fourteen most common cancer types (e.g., "prostate cancer COVID" and "breast cancer COVID"), yielding a total of 17 search phrases. The first 20 sources were recorded and analyzed for each keyword, yielding a total of 340 unique sources. For each of these sources, the approximate grade level required to comprehend the text was calculated as a mean of five validated readability scores; subsequently, for the first ten results of each search, the DISCERN tool was manually used to assess quality. Search terms were translated into Spanish and French, and a quality assessment using the Health on the Net Code (HONcode) accreditation was conducted. The median grade level readability for all sources was 13 (IQR 11-14). Median DISCERN scores for the 170 sources assessed were 55 out of 75, suggesting good quality. OHI with quality scores below the median DISCERN score had a median readability of 12.5 (IQR 11-14) grade reading level vs 14 (IQR 12-17) for those above the median DISCERN score (T-test P < 0.0001). Percentages of HONcode-accredited websites were 34.9%, 39.9%, and 38.6% for English, Spanish, and French OHI, respectively. We conclude that efforts are needed to make high-quality OHI available at the appropriate reading level for patients with cancer; such efforts may contribute to the alleviation of disparities in access to healthcare information.

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BACKGROUND: Preventing sports injuries is at the forefront of sports medicine. Although effective preventive strategies in scientific literature exist, their implementation is lagging behind. The Internet could support the translation of knowledge from the literature to end-users, but the quality of the online resources would have to be assured. This online-based systematic review is to assess availability, readability, quality, and content of the websites presenting exercise-based sports injury risk reduction (prevention) programmes. Moreover, the quality of reporting and contents of the exercise programmes were assessed. METHODS: Google, Yahoo, and Bing were searched on 2 September 2018. We used 'sports injury prevention program*' and 'sports injury prevention warm-up' as search phrases. The owners/authors of the included websites were asked for further recommendations on online resources. Search updates were run in DuckDuckGo on 15 May 2020 and 22 August 2021. Eligible websites were active, in English, and contained instructions for the exercise/s aiming at sports injury prevention. Two reviewers independently screened the links and previews and performed an in-depth appraisal of included websites. The website quality was assessed using JAMA framework criteria and Health on the Net Foundation Code of Conduct (HONcode) certification. The readability of websites was assessed using the Flesch-Kincaid Reading Ease score. The reporting appraisal of exercise programmes was done using the modified Consensus on Exercise Reporting Template (CERT). RESULTS: Among 480 websites screened, 16 were eligible with an additional four recommended and nine found in search updates (29 in total). None of the websites was certified by HONcode. The overall quality of websites was low 2.1 ± 1.0/4, but overall readability was high 67 ± 17/100. The average quality of reporting of exercise programmes was low 5.79 ± 3.1/12. Websites with community input had the lowest readability, but the highest quality, and vice versa websites run by businesses had the highest readability, but the lowest quality. Eight websites presented programmes tested for effectiveness. CONCLUSIONS: Overall, the quality of the websites was low, but their readability was high. Improvements required are relatively easy to implement (i.e. including the date when the website was updated, applying for HONcode certification) and extremely important (e.g. providing resources on which the website's content is based). There are some sports injury risk reduction programmes reported with high quality and effectiveness-tested available online for team sports, but none for individual sports. Trial Registration This review has been registered in the PROSPERO (CRD42019107104).

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BACKGROUND: There is an increasing body of research on the development of machine learning algorithms in the evaluation of online health educational resources for specific readerships. Machine learning algorithms are known for their lack of interpretability compared with statistics. Given their high predictive precision, improving the interpretability of these algorithms can help increase their applicability and replicability in health educational research and applied linguistics, as well as in the development and review of new health education resources for effective and accessible health education. OBJECTIVE: Our study aimed to develop a linguistically enriched machine learning model to predict binary outcomes of online English health educational resources in terms of their easiness and complexity for international tertiary students. METHODS: Logistic regression emerged as the best performing algorithm compared with support vector machine (SVM) (linear), SVM (radial basis function), random forest, and extreme gradient boosting on the transformed data set using L2 normalization. We applied recursive feature elimination with SVM to perform automatic feature selection. The automatically selected features (n=67) were then further streamlined through expert review. The finalized feature set of 22 semantic features achieved a similar area under the curve, sensitivity, specificity, and accuracy compared with the initial (n=115) and automatically selected feature sets (n=67). Logistic regression with the linguistically enhanced feature set (n=22) exhibited important stability and robustness on the training data of different sizes (20%, 40%, 60%, and 80%), and showed consistently high performance when compared with the other 4 algorithms (SVM [linear], SVM [radial basis function], random forest, and extreme gradient boosting). RESULTS: We identified semantic features (with positive regression coefficients) contributing to the prediction of easy-to-understand online health texts and semantic features (with negative regression coefficients) contributing to the prediction of hard-to-understand health materials for readers with nonnative English backgrounds. Language complexity was explained by lexical difficulty (rarity and medical terminology), verbs typical of medical discourse, and syntactic complexity. Language easiness of online health materials was associated with features such as common speech act verbs, personal pronouns, and familiar reasoning verbs. Successive permutation of features illustrated the interaction between these features and their impact on key performance indicators of the machine learning algorithms. CONCLUSIONS: The new logistic regression model developed exhibited consistency, scalability, and, more importantly, interpretability based on existing health and linguistic research. It was found that low and high linguistic accessibilities of online health materials were explained by 2 sets of distinct semantic features. This revealed the inherent complexity of effective health communication beyond current readability analyses, which were limited to syntactic complexity and lexical difficulty.

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Increasingly, people turn to online sources for health information, creating human-non-human relationalities. Health websites are considered accessible in scope and convenience but can have limited capacity to accommodate complexities. There are concerns about who gets to 'assemble' with these resources, and who is excluded. Guided by Ahmed's socio-political theories of emotions, we questioned our feelings as we intra-acted with a consumer information website about back pain (MyBackPain). This encouraged us to approach resource evaluation in a way that alters conventional rational/cognitive judgement processes. Our inquiry was 'supra-disciplinary' involving public health, sociology, allied health and consumer collaborators. Specifically, we considered relationality - the feelings circulating between bodies/objects and implicated in MyBackPain's affective practices; impressions - the marks, images or beliefs MyBackPain makes on bodies/objects; and directionality - how these intra-actions pushed in some directions and away from others. Although Ahmed would likely not consider herself 'post-humanist', we argue that her socio-political theories of how objects and emotions entangle are of great interest to furthering critical post-human understandings of health. Rather than threatening decision-making, we suggest that feelings (and their affects) are central to it. The article demonstrates the productive potential of critical post-human inquiry in identifying/countering 'othering' possibilities, and catalysing a 'nomadic shift' towards new human-non-human formations.

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OBJECTIVE: Patients are increasingly using online materials to learn about gynecologic cancer. Providers can refer patients to online educational materials produced by a number of different major medical organizations and pharmacology companies. The National Institutes of Health (NIH) and the American Medical Association (AMA) recommend that patient educational materials (PEMs) are written between a sixth and eighth grade reading level. In this study, we assess the readability of online PEMs published by major medical organizations and industry partners. METHODS: Websites from twelve websites providing educational materials for gynecologic oncology patients were surveyed. Online PEMs were identified and analyzed using seven validated readability indices. One-way ANOVA and Tukey's Honestly Significant Difference (HSD) post-hoc analysis were performed to detect differences in readability between publishers. RESULTS: Two-hundred and sixty PEMs were included in this analysis. Overall, PEMs were written at a mean 11th±0.6 grade reading level. Only 6.5% of articles were written at the AMA/NIH recommended reading grade level of 6th to 8th grade or below. ANOVA demonstrated a significant difference in readability between publishing associations (p<0.01). PEMs from the Centers for Disease Control had a mean 9th±1.2 grade reading level and were significantly lower than all other organizations. PEMs from The Foundation for Women's Cancer had a mean 13th±1.8 grade reading level and were significantly higher than most other organizations. PEMs from pharmaceutical companies (mean readability=10.1±1.1, N=30) required the lowest reading grade level and were significantly more readable than those from governmental organizations (11.1±1.7, p<0.05) and nonprofit medical associations (12.4±1.7, p<0.01) in ANOVA and Tukey-Kramer post hoc analysis. CONCLUSIONS: Gynecologic oncology PEMs available from twelve major organization websites are written well above the recommended sixth to eighth grade reading difficulty level.

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