Trustworthy Information Research Articles

Blockchain Applications in the Food Industry: A Systematic Literature Review

This paper presents the findings from a systematic literature review that explores the applications of blockchain technology within the food industry. The review is based on an analysis of 83 selected publications which have been sourced from ScienceDirect and Web of Science databases. The findings show promising and multifaceted ways of blockchain technology in the supply chain. By enabling secure and traceable data management, blockchain contributes to more safety and reliability of information hereby contributing to auditing functions as well as enabling sustainability-oriented business and reporting practices. The impact of blockchain technology is affecting various stakeholders in the supply chain. For example, consumers benefit from improved access to trustworthy food-related information, which in turn can shape purchasing decisions. Businesses, on the other hand, face the imperative of assessing the potential implications of blockchain technology on their existing strategies. Despite the evident progress and the promise of numerous advantages, it is apparent that blockchain technology in the food industry remains at an early stage of development with much work ahead with respect to academic contributions and practical implications. It is essential to tailor the implementation of blockchain technology to the specific conditions of individual supply chains, particularly regarding different types of food products. This applies equally to the bakery industry, where academic research is still missing so far. Therefore, insights from other sectors within the food industry are informative as to their applicability in the bakery industry as well if they are indirectly applied.

Examining regional variations in effective posts on X (Twitter) during the COVID-19 pandemic

Social media platforms play a significant role in disseminating information. The effectiveness of posts published on such platforms is often measured by the extent to which those posts are reshared — something that can be shaped by the regional social and cultural context. This study examines regional variations in effective posts (formerly tweets) published on X (formerly known as Twitter) during the initial phase of the COVID-19 pandemic, focusing on California’s two largest cities: Los Angeles and San Diego. By analysing a large dataset comprising the top 5,000 most reposted (formerly retweeted) posts from users in both cities, gathered between 17th March and 11th April, 2020, the research aims to identify key posters and content characteristics associated with higher repost rates. Employing techniques such as topic modelling and sentiment analysis, this study transforms unstructured text data into quantitative metrics in order to explore the relationship between content metrics and the number of reposts. The findings highlight the significant influence of local figures in shaping user engagement with shared posts spanning diverse topics and sentiments. These insights have significant implications for marketers, emphasising the importance of understanding local influencers, post topics and sentiment in geo-tagged posts. In regions with diverse populations, businesses can develop strategies to collaborate with local influencers and actively involve community leaders from various cultural backgrounds. By doing so, they facilitate the dissemination of trustworthy information and enhance engagement with culturally diverse audiences. Ultimately, this approach enables marketers to transform regional disparities into strategic advantages, fostering more effective communication and engagement on social media.

The Impact of Fast-Food Video Advertisements Through The Eyes of Young Creative Industry Practitioners

Video advertising has become a crucial marketing strategy for fast-food restaurants. While previous studies have identified factors influencing video advertisement effectiveness, these factors have yet to be investigated in light of current market preferences. In bridging this gap, it is crucial to consider the perspectives of young industry creative practitioners, who, with their dual roles as professionals and members of the target market, offer fresh insights into the factors influencing video advertisement effectiveness in alignment. Therefore, this study was conducted to investigate the fast-food video advertisements effectiveness in today’s market, specifically through the eyes of young creative industry practitioners. This study examines the effectiveness of fast-food video advertisements, focusing on content engagement, emotional arousal, information trustworthiness, and visual characteristics. Informant interview was utilized in the study, with data saturation achieved after collected insights from six interviewees who fulfilled the sampling criteria. The collected data underwent analysis using NVivo, involving coding and thematic analysis. The findings have substantiated strong relationships between visual attractiveness, content engagement, and the fast-food video advertisements effectiveness. However, it was determined that emotional arousal and information trustworthiness do not have a significant relationship with the fast-food advertisements effectiveness. Overall, this study contributes valuable insights for advertising agencies and offers a theoretical enhancement to existing models. Keywords: Fast-food restaurants, video advertisement, young creative industry practitioners, advertising effectiveness, advertisement content.

Towards Reliable Healthcare LLM Agents: A Case Study for Pilgrims during Hajj

There is a pressing need for healthcare conversational agents with domain-specific expertise to ensure the provision of accurate and reliable information tailored to specific medical contexts. Moreover, there is a notable gap in research ensuring the credibility and trustworthiness of the information provided by these healthcare agents, particularly in critical scenarios such as medical emergencies. Pilgrims come from diverse cultural and linguistic backgrounds, often facing difficulties in accessing medical advice and information. Establishing an AI-powered multilingual chatbot can bridge this gap by providing readily available medical guidance and support, contributing to the well-being and safety of pilgrims. In this paper, we present a comprehensive methodology aimed at enhancing the reliability and efficacy of healthcare conversational agents, with a specific focus on addressing the needs of Hajj pilgrims. Our approach leverages domain-specific fine-tuning techniques on a large language model, alongside synthetic data augmentation strategies, to optimize performance in delivering contextually relevant healthcare information by introducing the HajjHealthQA dataset. Additionally, we employ a retrieval-augmented generation (RAG) module as a crucial component to validate uncertain generated responses, which improves model performance by 5%. Moreover, we train a secondary AI agent on a well-known health fact-checking dataset and use it to validate medical information in the generated responses. Our approach significantly elevates the chatbot’s accuracy, demonstrating its adaptability to a wide range of pilgrim queries. We evaluate the chatbot’s performance using quantitative and qualitative metrics, highlighting its proficiency in generating accurate responses and achieve competitive results compared to state-of-the-art models, in addition to mitigating the risk of misinformation and providing users with trustworthy health information.

Facilitated Collaborative Group Co-Design of Hypothetical Digital Tools to Understand University Students’ Well-being Support Needs and Requirements

The number of students in higher education encountering issues with their well-being is increasing every year, with many struggling to seek appropriate support due to reasons such as stigma or lack of access to services. Consequently, digital well-being support tools may be best placed to address their needs; however, few of these tools involve students in the design process, and thus, there is a lack of clarity as to whether these tools meet the needs of students. Therefore, the aim of the present research was to provide a series of design considerations that should be incorporated in the design and development of digital tools to support student well-being. Co-design methods were used to develop these design considerations by understanding the well-being domains in which students want support, their views on existing digital supports, and their desired features in a digital support tool. Undergraduate students enrolled in a well-being module at an Irish University completed a facilitated group assignment in which they were required to co-design a hypothetical digital tool to support other students’ well-being. Deductive thematic analysis of the 10-min presentations of their tools was carried out. The overall findings were that:Students recognize all well-being domains as interconnected and view social connectedness and time management as crucial for them to find good balance in their lives and to thrive;Current digital well-being tools do not appropriately meet their needs, being too expensive, unmotivating, not suited to the student lifestyle and perceived as untrustworthy;Students desire a digital well-being tool that can give them structured and streamlined support and that clearly relates to their specific university environment;Specific desired features include the ability to log and visualize data, personalization capabilities, a motivational rewards system, and trustworthy educational information, tips and advice.

Barriers and Concerns that Contribute to Vaccine Hesitancy in Black, Indigenous, and People of Colour (BIPOC) Individuals in Ontario, Canada.

Despite research demonstrating the effectiveness of COVID-19 vaccines, hesitancy is extremely common in minority communities. The purpose of this study was to identify key barriers and concerns that contribute to vaccine hesitancy in Black, Indigenous, and People of Colour (BIPOC) individuals and provide recommendations to address these barriers and concerns. The study was an online cross-sectional survey conducted among 1491 BIPOC and Caucasian adults, recruited using social media networks in August-September 2021. The questionnaire consisted of five sections that probed concerns and attitudes contributing to COVID-19 vaccine hesitancy. Respondents were mostly Caucasian males (75.7%) and the average age was 29.1 years. A higher proportion of BIPOC respondents received both doses (50.6%) than Caucasian respondents (36.4%). Out of the unvaccinated, a higher percentage of BIPOC respondents did not plan on getting vaccinated (17.1%) compared to Caucasian respondents (4.2%). BIPOC respondents preferred the Pfizer-BioNTech (34.1%) vaccine whereas Caucasian respondents preferred AstraZeneca (29.3%). The biggest concern BIPOC and Caucasian respondents had with COVID-19 vaccines were side effects (56.6% vs 54.4%, respectively). BIPOC respondents identified dependability as the next biggest concern after side effects. A higher percentage of BIPOC respondents were against getting vaccinated against COVID-19 (16% vs 1.2%) compared to Caucasian respondents. Among unvaccinated respondents, COVID-19 vaccine hesitancy was most evident in the BIPOC respondents compared to Caucasian respondents. Side effects, trustworthiness, and lack of information were identified as the three most common concerns surrounding vaccines in general. Increased accessibility to reliable and accurate vaccine information in various languages/dialects can raise awareness about COVID-19 vaccinations in BIPOC communities.

Playing an Augmented Reality Escape Game Promotes Learning About Fake News

AbstractThe spread of fake news poses a global challenge to society, as this deliberately false information reduce trust in democracy, manipulate opinions, and negatively affect people’s health. Educational research and practice must address this issue by developing and evaluating solutions to counter fake news. A promising approach in this regard is the use of game-based learning environments. In this study, we focus on Escape Fake, an augmented reality (AR) escape game developed for use in media literacy education. To date, there is limited research on the effectiveness of the game for learning about fake news. To overcome this gap, we conducted a field study using a pretest-posttest research design. A total of 28 students (14 girls, mean age = 14.71 years) participated. The results show that Escape Fake can address four learning objectives relevant in fake news detection with educationally desired effect sizes: Knowledge acquisition (d = 1.34), ability to discern information (d = 0.39), critical attitude toward trustworthiness of online information (d = 0.53), and confidence in recognizing fake news in the future (d = 0.41). Based on these results, the game can be recommended as an educational resource for media literacy education. Future research directions are also discussed.

Prioritizing family-centered developmental care: insights from parents of children with critical congenital heart disease: a qualitative study

As survivors of early cardiac surgery are at high risk of neurodevelopmental impairments, systematic health observations of children with critical congenital heart disease (CCHD) throughout childhood are recommended to enable early diagnosis and offer interventions to optimize neurodevelopment. A qualitative study using thematic analysis was performed to explore parents’ concerns, experiences, and needs regarding the development and received developmental care of their child (0–10 years) during hospital admission and beyond. Data were collected using semi-structured online interviews with 20 parents of children with CCHD. Four major themes were identified: (1) “impact of diagnosis and disease on the family-system,” (2) “parental concerns from diagnoses and beyond,” (3) “the need for information,” and (4) “the need for individualized and family-centered care.” The main themes can be divided into 13 sub-themes as impact, concerns, and needs are influenced by various impactful moments from diagnosis and afterwards. Conclusion: This study confirms the importance of early identification of neurodevelopmental problems by experienced healthcare professionals, especially in the early years when parental expectations and concerns about their child’s neurodevelopment are lower. A tailor-made family-centered follow-up program should be offered, which pays attention to both the neurodevelopment of patients with CCHD as well as the mental wellbeing of the entire family system. Furthermore, an online portal is recommended with a variety of reliable, controlled, understandable information from which parents can obtain the desired information to understand better the consequences of specific heart condition and to provide their child with the best possible guidance.What is Known:• Survivors of early cardiac surgery are at high risk of neurodevelopmental impairments; systematic health observations of children with CCHD throughout childhood are strongly recommended.What is New:• Parents need a tailor-made family-centered follow-up program, which pays attention to both the neurodevelopment of patients with CCHD as well as the mental wellbeing of the entire family system.• An online portal offering diverse, trustworthy information and sources would effectively meet parents’ needs by providing accessible insights into the potential consequences of specific heart conditions and guiding them in supporting their child optimally.

Internet street view image fusion method using convolutional neural network

The use of image fusion technology in the area of information processing is continuing to advance in depth thanks to ongoing hardware advancements and related research. An enhanced convolutional neural network approach is developed to fuse visible and infrared images, and image pre-processing is carried out utilising an image alignment method with edge detection in order to gain more accurate and trustworthy image information. The performance of the fast wavelet decomposition, convolutional neural network, and modified convolutional neural network techniques is compared and examined using four objective assessment criteria. The experimental findings demonstrated that the picture alignment was successful with an offset error of fewer than 3 pixels in the horizontal direction and an angle error of less than 0.3∘ in both directions. The revised convolutional neural network method increased the information entropy, mean gradient, standard deviation, and edge detection information by an average of 46.13%, 39.40%, 19.91%, and 3.72%. The runtime of the modified approach was lowered by 19.42% when compared to the convolutional neural network method, which enhanced the algorithm’s performance and boosted the effectiveness of picture fusion. The image fusion accuracy reached 98.61%, indicating that the method has better fusion performance and is of practical value for improving image fusion quality.

Multi-source heterogeneous blockchain data quality assessment model for enterprise business activities.

Blockchain-based applications are becoming more and more widespread in business operations. In view of the shortcomings of existing enterprise blockchain evaluation methods, this paper proposes a multi-source heterogeneous blockchain data quality evaluation model for enterprise business activities, so as to achieve efficient evaluation of business activity information consistency, credibility and value. This paper proposes a multi-source heterogeneous blockchain data quality assessment method for enterprise business activities, aiming at the problems that most of the data in enterprise business activities come from different data sources, information representation is inconsistent, information ambiguity between the same block chain is serious, and it is difficult to evaluate the consistency, credibility and value of information. The method firstly proposes an entity information representation method based on the Representation learning for fusing entity category information (CEKGRL) model, which introduces the triad structure of related entities in blockchain, then associates them with enterprise business activity categories, and carries out similarity calculation through contextual information to achieve blockchain information consistency assessment. After that, a trustworthiness characterization method is proposed based on information sources, information comments, and information contents, to obtain the trustworthiness assessment of the business. Finally, based on the information trustworthiness characterization, a value assessment method is introduced to assess the total value of business activity information in the blockchain, and a blockchain quality assessment model is constructed. The experimental results show that the proposed model has great advantages over existing methods in assessing inter-block consistency, intra-block activity information trustworthiness and the value of blockchain.

Participatory design of bodysymptoms.org: An interactive web resource to explain multisystem functional somatic symptoms

ObjectiveThere is a lack of trustworthy information about Functional Somatic Symptoms (FSS) on the internet. This means integrative bio-psycho-social explanations of FSS and related health advice are not readily available to the public. To explore and address this problem, we carried out the bodysymptoms project, with the aim to build a website which presents current widely accepted explanations for FSS and shows how different explanations are inter-connected. MethodsBodysymptoms was set up as a research-in-action project with a diverse range of international stakeholder-participants, combining approaches from patient and public involvement in healthcare with participatory design. 7 participants with lived experience of multi-system functional symptoms took part in the project and measures of meaningful engagement throughout the project were rated highly. This manuscript describes the methodology by which the website was developed. ResultsThrough iterative cycles we determined the requirements for an interactive explanatory model and co-created a novel online health interactive resource with integrated actionable health advice. The target end user are young adults with persistent physical symptoms, maintained by functional mechanisms. The overall aim is to empower people at risk of developing functional disorders to seek better health outcomes. The website is intended to be used prior to or alongside engagement with healthcare. ConclusionBringing lived experience and multi-disciplinary perspectives into dialogue through participatory design can harness the power of research to create immediate shared value. This project has resulted in a usable open access website, bodysymptoms.org, which provides education about FSS for patients, healthcare professionals and members of the public looking to understand FSS.

Are Virtual Assistants Trustworthy for Medicare Information: An Examination of Accuracy and Reliability.

Advances in artificial intelligence (AI)-based virtual assistants provide a potential opportunity for older adults to use this technology in the context of health information-seeking. Meta-analysis on trust in AI shows that users are influenced by the accuracy and reliability of the AI trustee. We evaluated these dimensions for responses to Medicare queries. During the summer of 2023, we assessed the accuracy and reliability of Alexa, Google Assistant, Bard, and ChatGPT-4 on Medicare terminology and general content from a large, standardized question set. We compared the accuracy of these AI systems to that of a large representative sample of Medicare beneficiaries who were queried twenty years prior. Alexa and Google Assistant were found to be highly inaccurate when compared to beneficiaries' mean accuracy of 68.4% on terminology queries and 53.0% on general Medicare content. Bard and ChatGPT-4 answered Medicare terminology queries perfectly and performed much better on general Medicare content queries (Bard = 96.3%, ChatGPT-4 = 92.6%) than the average Medicare beneficiary. About one month to a month-and-a-half later, we found that Bard and Alexa's accuracy stayed the same, whereas ChatGPT-4's performance nominally decreased, and Google Assistant's performance nominally increased. LLM-based assistants generate trustworthy information in response to carefully phrased queries about Medicare, in contrast to Alexa and Google Assistant. Further studies will be needed to determine what factors beyond accuracy and reliability influence the adoption and use of such technology for Medicare decision-making.

Tackling disinformation in the UE with “truthster”: technological design and DLT

Tackling disinformation is crucial for the development of the Information Society. To do this, it is necessary to empower journalists in the production of trustworthy information, and to nurture an economic ecosystem centred on the secure circulation of content. In this contribution we present an interdisciplinary approach that aims (1) to find a balance between freedom of expression and other fundamental rights (e.g., privacy and data protection), (2) to develop business models driven by the production of genuine content, and (3) to exploit the potential of distributed ledger systems to provide media certification.

Assessment of the Arabic patient-centered online information about orthodontic pain: A quality and readability assessment.

This study assesses the quality and readability of Arabic online information about orthodontic pain. With the increasing reliance on the internet for health information, especially among Arabic speakers, it's critical to ensure the accuracy and comprehensiveness of available content. Our methodology involved a systematic search using the Arabic term for (Orthodontic Pain) in Google, Bing, and Yahoo. This search yielded 193,856 results, from which 74 websites were selected based on predefined criteria, excluding duplicates, scientific papers, and non-Arabic content. For quality assessment, we used the DISCERN instrument, the Journal of the American Medical Association (JAMA) benchmarks, and the Health on the Net (HON) code. Readability was evaluated using the Simplified Measure of Gobbledygook (SMOG), Flesch Reading Ease Score (FRES), and Flesch-Kincaid Grade Level (FKGL) scores. Results indicated that none of the websites received the HONcode seal. The DISCERN assessment showed median total scores of 14.96 (± 5.65), with low overall quality ratings. In JAMA benchmarks, currency was the most achieved aspect, observed in 45 websites (60.81%), but none met all four criteria simultaneously. Readability scores suggested that the content was generally understandable, with a median FKGL score of 6.98 and a median SMOG score of 3.98, indicating middle school-level readability. This study reveals a significant gap in the quality of Arabic online resources on orthodontic pain, highlighting the need for improved standards and reliability. Most websites failed to meet established quality criteria, underscoring the necessity for more accurate and trustworthy health information for Arabic-speaking patients.

COVID-19 InfoVaccines: A WHO-supported educational project to promote COVID-19 vaccination information among professionals and the general population

ABSTRACT COVID-19 vaccine uptake varied across countries, in part due to vaccine hesitancy fueled by a lack of trustworthy information. To help health workers provide evidence-based answers to common questions about COVID-19 vaccines and vaccination, and thereby, assist individuals´ decisions on vaccine acceptance, COVID-19 InfoVaccines, a joint WHO-EU project, was launched in February 2021 to support COVID-19 vaccine rollout in 6 Eastern European countries. COVID-19 InfoVaccines was made available in seven languages and shared on social media networks. A total of 262,592 users accessed COVID-19 InfoVaccines.com between February 11, 2021, and January 31st, 2023. The users were most interested in: general questions; vaccine efficacy and duration of protection; vaccine safety; vaccine co-administration, and dose-interval and interchangeability; though the interest in a specific theme varied in function of the epidemiological situation. A total of 118,510 (45.1%) and 46,644 (17.7%) users scrolled up to 35% and 75% of the COVID-19 InfoVaccines webpage, respectively. The average engagement rate was 71.61%. The users accessed COVID-19 InfoVaccines from 231 countries and territories, but the majority were in Ukraine (N = 38,404; 14.6%), Spain (N = 23,327; 8.9%), and Argentina (N = 21,167; 8.1%). Older Facebook users were more interested in COVID-19 information than younger individuals (X 2 p-value < .0001). Two hundred twenty-eight videos were shared on YouTube. The average Click-Through-Rate on Facebook was 7.82%, and that on YouTube was 4.4%, with 60 videos having a Click-Through-Rate >5%, falling in the range of average YouTube video Click-Through-Rate (2% – 10%). As misinformation about vaccines and vaccination spreads easily and can negatively impact health-related decisions, initiatives like COVID-19 InfoVaccines are crucial to facilitate access to reliable information.

Enriching the Fake News Process of Classifying Model using Deep Learning and Machine Learning Algorithm

Fake news detection has become a pressing issue due to the rapid propagation of misinformation through various online platforms. In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world. An important goal in improving the trustworthiness of information in online social networks is to identify the fake news timely. This paper aims at investigating the principles, methodologies and algorithms for detecting fake news articles, creators and subjects from online social networks and evaluating the corresponding performance. Information carefulness on Internet, especially on social media, is an increasingly important concern, but web-scale data hampers, ability to identify, evaluate and correct such data, or so called "fake news," present in these platforms. In this paper, we propose a method for "fake news" detection and ways to apply it on Facebook, one of the most popular online social media platforms. This method uses Naive Bayes classification model to predict whether a post on Facebook will be labelled as real or fake.

Identifying primary care clinicians’ preferences for, barriers to, and facilitators of information-seeking in clinical practice in Singapore: a qualitative study

BackgroundThe growth of medical knowledge and patient care complexity calls for improved clinician access to evidence-based resources. This study aimed to explore the primary care clinicians’ preferences for, barriers to, and facilitators of information-seeking in clinical practice in Singapore.MethodsA convenience sample of ten doctors and ten nurses was recruited. We conducted semi-structured face-to-face in-depth interviews. The interviews were recorded, transcribed verbatim, and analysed using thematic content analysis.ResultsOf the 20 participants, eight doctors and ten nurses worked at government-funded polyclinics and two doctors worked in private practice. Most clinicians sought clinical information daily at the point-of-care. The most searched-for information by clinicians in practice was less common conditions. Clinicians preferred evidence-based resources such as clinical practice guidelines and UpToDate®. Clinical practice guidelines were mostly used when they were updated or based on memory. Clinicians also commonly sought answers from their peers. Furthermore, clinicians frequently use smartphones to access the Google search engine and UpToDate® app. The barriers to accessing clinical information included the lack of time, internet surfing separation of work computers, limited search functions in the organisation’s server, and limited access to medical literature databases. The facilitators of accessing clinical information included convenience, easy access, and trustworthiness of information sources.ConclusionMost primary care clinicians in our study sought clinical information at the point-of-care daily and reported increasing use of smartphones for information-seeking. Future research focusing on interventions to improve access to credible clinical information for primary care clinicians at the point-of-care is recommended.Trial registrationThis study has been reviewed by NHG Domain Specific Review Board (NHG DSRB) (the central ethics committee) for ethics approval. NHG DSRB Reference Number: 2018/01355 (31/07/2019).

Perceptions of yellow fever emergency mass vaccinations among vulnerable groups in Uganda: A qualitative study.

Yellow fever (YF), a mosquito-borne viral hemorrhagic fever, is endemic in Uganda and causes frequent outbreaks. A total of 1.6 million people were vaccinated during emergency mass immunization campaigns in 2011 and 2016. This study explored local perceptions of YF emergency mass immunization among vulnerable groups to inform future vaccination campaigns. In this qualitative study, we conducted 43 semi-structured interviews, 4 focus group discussions, and 10 expert interviews with 76 participants. Data were collected in six affected districts with emergency mass vaccination. We included vulnerable groups (people ≥ 65 years and pregnant women) who are typically excluded from YF vaccination except during mass immunization. Data analysis was conducted using grounded theory. Inductive coding was utilized, progressing through open, axial, and selective coding. Participants relied on community sources for information about the YF mass vaccination. Information was disseminated door-to-door, in community spaces, during religious gatherings, and on the radio. However, most respondents had no knowledge of the vaccine, and it was unclear to them whether a booster dose was required. In addition, the simultaneous presidential election during the mass vaccination campaign led to suspicion and resistance to vaccination. The lack of reliable and trustworthy information and the politicization of vaccination campaigns reinforced mistrust of YF vaccines. People in remote areas affected by YF outbreaks rely on community sources of information. We therefore recommend improving health education, communication, and engagement through respected and trusted community members. Vaccination campaigns can never be seen as detached from political systems and power relations.

Exploring the role of digital tools in rare disease management: An interview-based study.

While digital tools, such as the Internet, smartphones, and social media, are an important part of modern society, little is known about the specific role they play in the healthcare management of individuals and caregivers affected by rare disease. Collectively, rare diseases directly affect up to 10% of the global population, suggesting that a significant number of individuals might benefit from the use of digital tools. The purpose of this qualitative interview-based study was to explore: (a) the ways in which digital tools help the rare disease community; (b) the healthcare gaps not addressed by current digital tools; and (c) recommended digital tool features. Individuals and caregivers affected by rare disease who were comfortable using a smartphone and at least 18 years old were eligible to participate. We recruited from rare disease organizations using purposive sampling in order to achieve a diverse and information rich sample. Interviews took place over Zoom and reflexive thematic analysis was utilized to conceptualize themes. Eight semistructured interviews took place with four individuals and four caregivers. Three themes were conceptualized which elucidated key aspects of how digital tools were utilized in disease management: (1) digital tools should lessen the burden of managing a rare disease condition; (2) digital tools should foster community building and promote trust; and (3) digital tools should provide trusted and personalized information to understand the condition and what the future may hold. These results suggest that digital tools play a central role in the lives of individuals with rare disease and their caregivers. Digital tools that centralize trustworthy information, and that bring the relevant community together to interact and promote trust are needed. Genetic counselors can consider these ideal attributes of digital tools when providing resources to individuals and caretakers of rare disease.

Are Internet Information Sources Helpful for Adult Crohn's Disease Patients Regarding Nutritional Advice?

Background: Adult patients suffering from Crohn's disease (CD) are often dissatisfied with the information they receive from their physicians about nutrition and its impact on CD inflammation activity. Only a few publications are available about patients' internet research on nutrition in CD. The study aim is to elucidate the internet information sources of adult CD patients regarding nutritional advice via a questionnaire. Methods: A questionnaire with 28 (general and specific) questions for outpatients at our tertiary center with CD was created and used for an analysis of their information sources about nutrition in CD. Four CD and/or nutritional medicine experts examined the 21 most relevant websites referring to nutritional advice for CD patients. Results: One hundred and fifty CD patients reported their Internet research behavior for nutritional advice and their dietary habits. Many CD patients prefer to consult the Internet instead of asking their general practitioner (GP) for nutritional recommendations. Most of the websites providing nutritional advice for CD patients are of very poor quality and cannot be recommended. We found significant correlations between (a) nutritional habits of CD patients, (b) their information sources and several demographic or CD-related factors. There is a lack of websites which provide high-quality, good nutritional advice to CD patients. Conclusions: The majority of the examined websites did not provide sufficient information according to the CD guidelines and nutritional medicine guidelines. A higher quality level of website content (e.g., on social media or on university/center websites) provided by experienced physicians is required to secure trustworthy and reliable nutritional information in CD.