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Objective: The Sydney Health Literacy Lab (SHeLL) Editor is an online text-editing tool that provides real-time assessment and feedback on written health information (assesses grade reading score, complex language, passive voice). This study aimed to explore how the design could be further enhanced to help health information providers interpret and act on automated feedback., Methods: The prototype was iteratively refined across four rounds of user-testing with health services staff ( N  = 20). Participants took part in online interviews and a brief follow-up survey using validated usability scales (System Usability Scale, Technology Acceptance Model). After each round, Yardley's (2021) optimisation criteria guided which changes would be implemented., Results: Participants rated the Editor as having adequate usability (M = 82.8 out of 100, SD = 13.5). Most modifications sought to reduce information overload (e.g. simplifying instructions for new users) or make feedback motivating and actionable (e.g. using frequent incremental feedback to highlight changes to the text altered assessment scores)., Conclusion: terative user-testing was critical to balancing academic values and the practical needs of the Editor's target users. The final version emphasises actionable real-time feedback and not just assessment., Innovation: The Editor is a new tool that will help health information providers apply health literacy principles to written text., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: This study was primarily funded via the Lifespan Research Network seed funding. Development of the Editor was supported by a Lifespan Research Network seed funding grant at the 10.13039/501100001774University of Sydney. This user testing study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Dana Mouwad reports administrative support was provided by Western Sydney Local Health district, Health Literacy Hub. Administrative support was provided by Western Sydney Local Health Distrcit, Health Literacy Hub. Academic authors were supported by National Health and Medical Research Council, Heart Foundation, and Western Sydney Local Health District. Members of the research team (JA, DMM, CB, KM) are directors of a health literacy consultancy (Health Literacy Solutions Ltd., Pty)., (© 2023 The Author(s).)

Background: Online health misinformation about statins potentially affects health decision-making on statin use and adherence. We developed an information diary platform (IDP) to measure topic-specific health information exposure where participants record what information they encounter. We evaluated the utility and usability of the smartphone diary from the participants' perspective., Methods: We used a mixed-method design to evaluate how participants used the smartphone diary tool and their perspectives on usability. Participants were high cardiovascular-risk patients recruited from a primary care clinic and used the tool for a week. We measured usability with the System Usability Scale (SUS) questionnaire and interviewed participants to explore utility and usability issues., Results: The information diary was available in three languages and tested with 24 participants. The mean SUS score was 69.8 ± 12.9. Five themes related to utility were: IDP functions as a health information diary; supporting discussion of health information with doctors; wanting a feedback function about credible information; increasing awareness of the need to appraise information; and wanting to compare levels of trust with other participants or experts. Four themes related to usability were: ease of learning and use; confusion about selecting the category of information source; capturing offline information by uploading photos; and recording their level of trust., Conclusion: We found that the smartphone diary can be used as a research instrument to record relevant examples of information exposure. It potentially modifies how people seek and appraise topic-specific health information., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lim, Ng, Abdullah, Dalmazzo, Lim, Lee and Dunn.)

Producing health information that people can easily understand is challenging and time-consuming. Existing guidance is often subjective and lacks specificity. With advances in software that reads and analyzes text, there is an opportunity to develop tools that provide objective, specific, and automated guidance on the complexity of health information. This paper outlines the development of the SHeLL (Sydney Health Literacy Lab) Health Literacy Editor, an automated tool to facilitate the implementation of health literacy guidelines for the production of easy-to-read written health information. Target users were any person or organization that develops consumer-facing education materials, with or without prior experience with health literacy concepts. Anticipated users included health professionals, staff, and government and nongovernment agencies. To develop this tool, existing health literacy and relevant writing guidelines were collated. Items amenable to programmable automated assessment were incorporated into the Editor. A set of natural language processing methods were also adapted for use in the SHeLL Editor, though the approach was primarily procedural (rule-based). As a result of this process, the Editor comprises 6 assessments: readability (school grade reading score calculated using the Simple Measure of Gobbledygook (SMOG)), complex language (percentage of the text that contains public health thesaurus entries, words that are uncommon in English, or acronyms), passive voice, text structure (eg, use of long paragraphs), lexical density and diversity, and person-centered language. These are presented as global scores, with additional, more specific feedback flagged in the text itself. Feedback is provided in real-time so that users can iteratively revise and improve the text. The design also includes a "text preparation" mode, which allows users to quickly make adjustments to ensure accurate calculation of readability. A hierarchy of assessments also helps users prioritize the most important feedback. Lastly, the Editor has a function that exports the analysis and revised text. The SHeLL Health Literacy Editor is a new tool that can help improve the quality and safety of written health information. It provides objective, immediate feedback on a range of factors, complementing readability with other less widely used but important objective assessments such as complex and person-centered language. It can be used as a scalable intervention to support the uptake of health literacy guidelines by health services and providers of health information. This early prototype can be further refined by expanding the thesaurus and leveraging new machine learning methods for assessing the complexity of the written text. User-testing with health professionals is needed before evaluating the Editor's ability to improve the health literacy of written health information and evaluating its implementation into existing Australian health services., (©Julie Ayre, Carissa Bonner, Danielle M Muscat, Adam G Dunn, Eliza Harrison, Jason Dalmazzo, Dana Mouwad, Parisa Aslani, Heather L Shepherd, Kirsten J McCaffery. Originally published in JMIR Formative Research (https://formative.jmir.org), 14.02.2023.)

Objectives. To examine the role that bots play in spreading vaccine information on Twitter by measuring exposure and engagement among active users from the United States. Methods. We sampled 53 188 US Twitter users and examined who they follow and retweet across 21 million vaccine-related tweets (January 12, 2017-December 3, 2019). Our analyses compared bots to human-operated accounts and vaccine-critical tweets to other vaccine-related tweets. Results. The median number of potential exposures to vaccine-related tweets per user was 757 (interquartile range [IQR] = 168-4435), of which 27 (IQR = 6-169) were vaccine critical, and 0 (IQR = 0-12) originated from bots. We found that 36.7% of users retweeted vaccine-related content, 4.5% retweeted vaccine-critical content, and 2.1% retweeted vaccine content from bots. Compared with other users, the 5.8% for whom vaccine-critical tweets made up most exposures more often retweeted vaccine content (62.9%; odds ratio [OR] = 2.9; 95% confidence interval [CI] = 2.7, 3.1), vaccine-critical content (35.0%; OR = 19.0; 95% CI = 17.3, 20.9), and bots (8.8%; OR = 5.4; 95% CI = 4.7, 6.3). Conclusions. A small proportion of vaccine-critical information that reaches active US Twitter users comes from bots.