The PICOTS-ComTeC Framework for Defining Digital Health Interventions: An ISPOR Special Interest Group Report.

OBJECTIVES: Digital health definitions are abundant, but often lack clarity and precision. We aimed to develop a minimum information framework to define patient-facing digital health interventions (DHIs) for outcomes research. METHODS: Definitions of digital-health-related terms (DHTs) were systematically reviewed, followed by a content analysis using frameworks, including PICOTS (population, intervention, comparator, outcome, timing, and setting), Shannon-Weaver Model of Communication, Agency for Healthcare Research and Quality Measures, and the World Health Organization's Classification of Digital Health Interventions. Subsequently, we conducted an online Delphi study to establish a minimum information framework, which was pilot tested by 5 experts using hypothetical examples. RESULTS: After screening 2610 records and 545 full-text articles, we identified 101 unique definitions of 67 secondary DHTs in 76 articles, resulting in 95 different patterns of concepts among the definitions. World Health Organization system (84.5%), message (75.7%), intervention (58.3%), and technology (52.4%) were the most frequently covered concepts. For the Delphi survey, we invited 47 members of the ISPOR Digital Health Special Interest Group, 18 of whom became the Delphi panel. The first, second, and third survey rounds were completed by 18, 11, and 10 respondents, respectively. After consolidating results, the PICOTS-ComTeC acronym emerged, involving 9 domains (population, intervention, comparator, outcome, timing, setting, communication, technology, and context) and 32 optional subcategories. CONCLUSIONS: Patient-facing DHIs can be specified using PICOTS-ComTeC that facilitates identification of appropriate interventions and comparators for a given decision. PICOTS-ComTeC is a flexible and versatile tool, intended to assist authors in designing and reporting primary studies and evidence syntheses, yielding actionable results for clinicians and other decision makers.

Towards a better psychological satisfaction: developing a mixed multi-criteria evaluation system to urban 'Not in my back yard' facilities siting.

'Not in My Back Yard (NIMBY)' facilities are psychologically sensitive to urban and regional development. Multi-criteria evaluation (MCE) method has been widely used for the decision-making of optimum siting of urban NIMBY facilities which aim to improve residents' psychological satisfaction. However, the evaluation of qualitative criteria in siting analysis remains under researched, such as the insufficient focus on urban and regional spatial development, social public opinion, and psychological factors. Thus, the effective improvement of MCE method through an interdisciplinary view can optimise the decision process and advance the factor assessment system of siting, which helps to supplement qualitative criteria evaluation. The specific improvement steps are as follows. The first step is to introduce the mixed MCE method to improve the qualitative criteria evaluation method by pre-processing qualitative criteria with min-max standardisation and normalization. This process transfers all negative factors to positive ones and transforms the F function to linear functions. The second step is to optimise the existing two-phase siting decision-making including the feasibility evaluation phase and the MCE phase. The third step is to propose a modular criteria system composed of urban and regional spatial planning, social psychological factors and the corresponding improvement strategy of this system from three perspectives of composition, measure, and weight. We argue that the improved method could be broadly applied to optimum siting decision of urban NIMBY facilities and enhance the psychological satisfaction of residents.

The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19).

BACKGROUND AND AIMS: The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion. METHODS: We searched Baidu News using the keywords "Novel Coronavirus" and "COVID-19" from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data. RESULTS: We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event. CONCLUSIONS: The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability.

Enhanced Arabic disaster data classification using domain adaptation.

Natural disasters, like pandemics and earthquakes, are some of the main causes of distress and casualties. Governmental crisis management processes are crucial when dealing with these types of problems. Social media platforms are among the main sources of information regarding current events and public opinion. So, they have been used extensively to aid disaster detection and prevention efforts. Therefore, there is always a need for better automatic systems that can detect and classify disaster data of social media. In this work, we propose enhanced Arabic disaster data classification models. The suggested models utilize domain adaptation to provide state-of-the-art accuracy. We used a standard dataset of Arabic disaster data collected from Twitter for testing the proposed models. Experimental results show that the provided models significantly outperform the previous state-of-the-art results.

Public perception on active aging after COVID-19: an unsupervised machine learning analysis of 44,343 posts.

Introduction: To analyze public perceptions of active aging in China on mainstream social media platforms to determine whether the "14th Five Year Plan for the Development of the Aging Career and Older Adult Care System" issued by the CPC in 2022 has fully addressed public needs. Methods: The original tweets posted on Weibo between January 1, 2020, and June 30, 2022, containing the words "aging" or "old age" were extracted. A bidirectional encoder representation from transformers (BERT)-based model was used to generate themes related to this perception. A qualitative thematic analysis and an independent review of the theme labels were conducted by the researchers. Results: The findings indicate that public perceptions revolved around four themes: (1) health prevention and protection, (2) convenient living environments, (3) cognitive health and social integration, and (4) protecting the rights and interests of the older adult. Discussion: Our study found that although the Plan aligns with most of these themes, it lacks clear planning for financial security and marital life.

Has the Supreme Court become just another political branch? Public perceptions of court approval and legitimacy in a post-Dobbs world.

Have perceptions of the U.S. Supreme Court polarized, much like the rest of American politics? Because of the Court's unique role, for many years, it remained one of the few institutions respected by both Democrats and Republicans alike. But the Court's dramatic shift to the right in recent years-highlighted by its Dobbs decision in 2022-potentially upends that logic. Using both eight waves of panel data and 18 nationally representative surveys spanning two decades, we show that while there was little evidence of partisan polarization in earlier years, in 2022 and 2023, such patterns are clear in favorability, trust, legitimacy, and support for reform. Factors that used to protect the Court-like knowledge about it and support for key democratic values-no longer do so. The Court has also become more important to voters, and will likely remain a political flashpoint, with disquieting implications for the Court's place in our polity.

Evaluating public opinions: informing public health policy adaptations in China amid the COVID-19 pandemic.

Public concern regarding safety policies serious consequences is anticipated to persist over an extended duration. A study examining a case of rapid public health policy adaptation in China during the COVID-19 epidemic was conducted by gathering public opinion data from major social media platforms. A systematic approach to comprehend public opinion was developed. Five fundamental elements and four dimensions were delineated. An indicator system was established utilizing the K-means text clustering model. Public prediction, expectation, and their evolution underlying public concern were elucidated employing TF-IDF text mining models. The HMM elucidated the way public opinion influences policy adjustments. The findings underscore that public concern regarding enduring events undergoes temporal shifts, mirroring the evolution of public opinion towards policy. Public opinion aroused by both the original event and derived events collaboratively influence policy adjustments. In China, public opinion serves as a mechanism for policy feedback and oversight; notably, negative public sentiment plays a pivotal role in expediting policy transitions. These findings aid in refining policies to mitigate emergencies through a feedback loop, thereby averting the emergence of safety risks such as social unrest prompted by public opinion.

Public perceptions of synthetic cooling agents in electronic cigarettes on Twitter.

Amid a potential menthol ban, electronic cigarette (e-cigarette) companies are incorporating synthetic cooling agents like WS-3 and WS-23 to replicate menthol/mint sensations. This study examines public views on synthetic cooling agents in e-cigarettes via Twitter data. From May 2021 to March 2023, we used Twitter Streaming Application Programming Interface (API), to collect tweets related to synthetic cooling agents with keywords such as 'WS-23,' 'ice,' and 'frozen.' The deep learning RoBERTa (Robustly Optimized BERT-Pretraining Approach) model that can be optimized for contextual language understanding was used to classify attitudes expressed in tweets about synthetic cooling agents and identify e-cigarette users. The BERTopic (a topic modeling technique that leverages Bidirectional Encoder Representations from Transformers) deep-learning model, specializing in extracting and clustering topics from large texts, identified major topics of positive and negative tweets. Two proportion Z-tests were used to compare the proportions of positive and negative attitudes between e-cigarette users (vapers) and non-e-cigarette-users (non-vapers). Of 6,940,065 e-cigarettes-related tweets, 5,788 were non-commercial tweets related to synthetic cooling agents. The longitudinal trend analysis showed a clear upward trend in discussions. Vapers posted most of the tweets (73.05%, 4,228/5,788). Nearly half (47.87%, 2,771/5,788) held a positive attitude toward synthetic cooling agents, which is significantly higher than those with a negative attitude (19.92%,1,153/5,788) with a P-value < 0.0001. The likelihood of vapers expressing positive attitudes (60.17%, 2,544/4,228) was significantly higher (P < 0.0001) than that of non-vapers (14.55%, 227/1,560). Conversely, negative attitudes from non-vapers (30%, 468/1,560) were significantly (P < 0.0001) higher than vapers (16.2%, 685/4,228). Prevalent topics from positive tweets included "enjoyment of specific vape flavors," "preference for lush ice vapes," and "liking of minty/icy feelings." Major topics from negative tweets included "disliking certain vape flavors" and "dislike of others vaping around them." On Twitter, vapers are more likely to have a positive attitude toward synthetic cooling agents than non-vapers. Our study provides important insights into how the public perceives synthetic cooling agents in e-cigarettes. These insights are crucial for shaping future U.S. Food and Drug Administration (FDA) regulations aimed at safeguarding public health.

"Okay, I respect this publicity stunt." A snapshot of public perceptions of an online game-based blood donation campaign.

BACKGROUND: With a decrease in young and first-time donors, applying gaming elements to blood donation may provide a novel means of encouraging young donors. In August 2023, the online game DiabloIV launched the Blood Harvest in which players were encouraged to donate blood products in the United States to receive virtual in-game rewards. Given the novelty of this independent initiative, our aim was to capture Diablov IV players opinions of the Blood Harvest through thematically analyzing their online discourse related to this blood donation campaign. STUDY DESIGN AND METHODS: We captured publicly available Twitter/X posts (n = 78) and engagement (n = 390) relevant to the Blood Harvest posted during and immediately after the campaign (October 13, 2023-November 27, 2023). RESULTS: Using thematic analysis, we identified 5 themes relating to the Blood Harvest campaign: (1) Positive perceptions and community motivations to donate, (2) Negative perceptions of the initiative and online game, (3) Players' inability to donate and participate in the initiative, (4) Incentives and incentive comparisons, and (5) Benefiting from positive associations focusing on the reputational gain that may be accessed through promoting blood donation. DISCUSSION: Situating a donation campaign in an established video game provides a novel opportunity to engage young donors. Through capturing public data, we provide a unique snapshot of how an online gaming community perceives and reacts to an independently initiated game-integrated blood donation campaign. This highlights key strengths of the approach as well as identifying potential risks for blood collection agencies.

Understanding the consumer-citizen gap in Chinese public attitudes toward farm animal welfare.

Individuals of the general public can perform both consumer and citizen roles in farm animal welfare, and attitudes toward farm animal welfare may differ between these roles. However, scant research is available regarding this distinction, especially in developing countries such as China. The present study aimed to explore consumer-citizen gaps in Chinese public attitudes toward farm animal welfare across three dimensions and across demographic characteristics. A 36-item scale was designed, and completed by 5284 Chinese participants in a large-scale cross-sectional survey. Consumer-citizen gaps in attitudes toward farm animal welfare across three dimensions and demographic characteristics were analyzed using the Wilcoxon signed-rank test, and effects of demographic characteristics on attitudes were further explored by linear regression analysis. A significant consumer-citizen gap was found in overall attitudes, although the consumer role was only slightly more positive than the citizen role. The consumer-citizen gap is driven by differences in both cognitive attitudes and behavioral attitudes. The gap is most pronounced in cognitive attitudes, where the consumer role is significantly more positive, and smaller in behavioral attitudes, where the citizen role is significantly more positive. The consumer-citizen gap varies significantly among different demographic groups, including gender, age, education, monthly household income, area of residence, and occupation. Additionally, education, monthly household income, and area of residence have significant effects on attitudes in the dual role, whereas gender only affect consumer-role attitudes significantly. The findings provide evidence that consumer-citizen gaps in Chinese public attitudes toward farm animal welfare exist, and this distinction is mainly determined by demographic characteristics.

Climate change belief systems across political groups in the United States.

Beliefs and attitudes form the core of public opinion about climate change. Network analysis can reveal the structural configuration of these beliefs and attitudes. In this research, we utilize a belief system framework to identify key psychological elements, track change in the density of these belief systems over time and across political groups, and analyze the structural heterogeneity of belief systems within and between political groups in the United States. Drawing on fifteen waves of nationally representative survey data from 2010 to 2021 (N = 16,742), our findings indicate that worry about climate change is the most central psychological element. Interestingly, we find that among politically unaffiliated individuals, the connections between psychological elements have strengthened over time, implying an increase in the consistency of belief systems within this group. Despite the political polarization in beliefs about climate change between Republicans and Democrats, our findings reveal that the ways these two groups organize and structure climate change beliefs systems are not markedly different compared to those of other groups. These findings provide theoretical and practical insights for climate change experts and communicators.

Public Perception Toward the Malaysian National COVID-19 Immunisation Programme (PICK) in the State of Sabah, Malaysia: A Cross-Sectional Survey.

The Malaysian Government has initiated the National COVID-19 Immunisation Programme, known as PICK, to be a national strategy for addressing the spread of the coronavirus disease (COVID-19) pandemic across the country. Although the government intensified public awareness to increase program registration, the total number that registered in the state of Sabah, located in East Malaysia, was relatively low during August 2021, accounting for only 42.9% as compared to that of Peninsular Malaysia. Therefore, this paper examines the public perception toward the PICK program in Sabah based on 4 main components: safety, communication, psychology, and milieu. This study is based on the empirical findings drawn from 1024 respondents across Sabah using online Google Form surveys. This study adopts 5 methodologies for data analysis by using K-means clustering, mean score, Mann-Whitney U test, spatial analysis, and frequency analysis. It has been revealed that the percentage of respondents (categorized as Cluster 1) who have a negative perception toward the vaccination program is higher (55.9%) than those who have a positive perception (44.1%). This study further discovered that Cluster 1 has shown high skepticism regarding the vaccination program, which can be explained through the communication component (M = 3.33, SD = 0.588), especially Co2, Co3, Co1, and Co4. Following the communication factor, a chain of negative perceptions also affects other components such as safety, psychology, and milieu among Cluster 1, all of which contribute to poor participation in the PICK program. The study outcomes are extremely useful for informing local authorities to establish policies related to public interests, primarily in the areas of public health. Understanding the community's perspectives and their obstacles in participating in such programs may assist local authorities in developing or implementing public policies and campaigns that ensure such related public programs can be conducted more effectively in the future.

Impact of Faculty Mentorship in the Orthopedic Surgery Interest Group at a New Medical School: A Blueprint for Future Initiatives.

OBJECTIVES: Orthopedic surgery is a highly competitive field. The residency applicant pool is expected to grow with the increasing number of new medical schools in the United States, posing significant challenges for applicants. This study explored the impact of an engaged faculty mentor in an orthopedic surgery interest group (OSIG) at a new medical school and the impact it has on students. The study aimed to uncover the most valuable features of an OSIG at a new medical school to create a blueprint for other student-leaders and/or faculty in future initiatives. METHODS: An observational study was conducted via survey responses from active OSIG members at a new medical school in Texas. Questions were mostly in a "before and after" format asking about students' perspectives of the group before and after the addition of an engaged faculty advisor. Descriptive and inferential statistics were used to analyze the data. RESULTS: Twenty of 21 (95.2%) eligible OSIG members participated in the study. The survey results revealed that faculty engagement significantly enhanced the OSIG and its members' medical school experience. Following faculty involvement, average OSIG event attendance more than tripled, there was a statistically significant increase in medical student well-being, and confidence in their ability to be a competitive orthopedic surgery applicant nearly doubled. OSIG participation influenced their career interests significantly more after faculty engagement. A total of 93.3% of participants voted that they felt having an engaged faculty advisor is critical for the OSIG. CONCLUSIONS: Mentorship was identified as the most crucial activity for career development, followed by clinical exposure and research. The study provides valuable insights for new medical schools in establishing and optimizing OSIGs and potentially other interest groups, particularly in competitive specialties.

Precision nutrition in pediatric IBD: A position paper from the ESPGHAN special interest group for basic science and translational research, the IBD Porto group, and allied health professionals.

Stratified and precision nutrition refers to disease management or prevention of disease onset, based on dietary interventions tailored to a person's characteristics, biology, gut microbiome, and environmental exposures. Such treatment models may lead to more effective management of inflammatory bowel disease (IBD) and reduce risk of disease development. This societal position paper aimed to report advances made in stratified and precision nutritional therapy in IBD. Following a structured literature search, limited to human studies, we identified four relevant themes: (a) nutritional epidemiology for risk prediction of IBD development, (b) food-based dietary interventions in IBD, (c) exclusive enteral nutrition (EEN) for Crohn's disease (CD) management, and (d) pre- and probiotics for IBD management. There is scarce literature upon which we can make recommendations for precision or stratified dietary therapy for IBD, both for risk of disease development and disease management. Certain single-nucleotide polymorphisms related to polyunsaturated fatty acid (PUFA) metabolism may modify the effect dietary PUFA have in increasing the risk of IBD development. Non-colonic CD, mild-to-moderate CD, and high microbiota richness may predict success of EEN and may be used both for prediction of treatment continuation, but also for early cessation in nonresponders. There is currently insufficient evidence to make recommendations for precision or stratified dietary therapy for patients with established IBD. Despite the great interest in stratified and precision nutrition, we currently lack data to support conclusive recommendations. Replication of early findings by independent research groups and within structured clinical interventions is required.

Topic prediction for tobacco control based on COP9 tweets using machine learning techniques.

The prediction of tweets associated with specific topics offers the potential to automatically focus on and understand online discussions surrounding these issues. This paper introduces a comprehensive approach that centers on the topic of "harm reduction" within the broader context of tobacco control. The study leveraged tweets from the period surrounding the ninth Conference of the Parties to review the Framework Convention on Tobacco Control (COP9) as a case study to pilot this approach. By using Latent Dirichlet Allocation (LDA)-based topic modeling, the study successfully categorized tweets related to harm reduction. Subsequently, various machine learning techniques were employed to predict these topics, achieving a prediction accuracy of 91.87% using the Random Forest algorithm. Additionally, the study explored correlations between retweets and sentiment scores. It also conducted a toxicity analysis to understand the extent to which online conversations lacked neutrality. Understanding the topics, sentiment, and toxicity of Twitter data is crucial for identifying public opinion and its formation. By specifically focusing on the topic of "harm reduction" in tweets related to COP9, the findings offer valuable insights into online discussions surrounding tobacco control. This understanding can aid policymakers in effectively informing the public and garnering public support, ultimately contributing to the successful implementation of tobacco control policies.

Understanding the barriers and facilitators to implementing and sustaining Mobile Overdose Response Services from the perspective of Canadian key interest groups: a qualitative study.

INTRODUCTION: Unregulated supply of fentanyl and adulterants continues to drive the overdose crisis. Mobile Overdose Response Services (MORS) are novel technologies that offer virtual supervised consumption to minimize the risk of fatal overdose for those who are unable to access other forms of harm reduction. However, as newly implemented services, they are also faced with numerous limitations. The aim of this study was to examine the facilitators and barriers to the adoption of MORS in Canada. METHODS: A total of 64 semi-structured interviews were conducted between November 2021 and April 2022. Participants consisted of people who use substances (PWUS), family members of PWUS, health care professionals, harm reduction workers, MORS operators, and members of the general public. Inductive thematic analysis was used to identify the major themes and subthemes. RESULTS: Respondents revealed that MORS facilitated a safe, anonymous, and nonjudgmental environment for PWUS to seek harm reduction and other necessary support. It also created a new sense of purpose for operators to positively contribute to the community. Further advertising and promotional efforts were deemed important to increase its awareness. However, barriers to MORS implementation included concerns regarding privacy/confidentiality, uncertainty of funding, and compassion fatigue among the operators. CONCLUSION: Although MORS were generally viewed as a useful addition to the currently existing harm reduction services, it's important to monitor and tackle these barriers by engaging the perspectives of key interest groups.

Perspectives on phenotypic screening-Screen Design and Assay Technology Special Interest Group.

Here we offer perspectives on phenotypic screening based on a wide-ranging discussion entitled "Phenotypic screening, target ID, and multi-omics: enabling more disease relevance in early discovery?" at the Screen Design and Assay Technology Special Interest Group Meeting at the 2023 SLAS Conference. During the session, the authors shared their own experience from within their respective organizations, followed by an open discussion with the audience. It was recognized that while substantial progress has been made towards translating disease-relevant phenotypic early discovery into clinical success, there remain significant operational and scientific challenges to implementing phenotypic screening efforts, and improving translation of screening hits comes with substantial resource demands and organizational commitment. This Perspective assesses progress, highlights pitfalls, and offers possible solutions to help unlock the therapeutic potential of phenotypic drug discovery. Areas explored comprise screening and hit validation strategy, choice of cellular model, moving beyond 2D cell culture into three dimensions, and leveraging high-dimensional data sets downstream of phenotypic screens.

Clinical performance of the infant nutrition early warning score in routine practice across four international clinical settings in Europe: A study by the ESPGHAN special interest group in clinical malnutrition.

There is a scarcity of nutritional screening tools for use in infants (<1 year). The infant Nutrition Early Warning Score (iNEWS) has been developed to identify infants who need further dietetic review. We introduced the iNEWS into clinical practice and evaluated its performance in Scotland, Belgium, Athens and Bulgaria. Of the 352 infants screened, 72 (20%) were placed in the high iNEWS category, and of these, 70 (97%) were reviewed by a hospital dietitian. iNEWS produced a true positive rate of 80% which increased to 96% after accounting for anticipated misclassified cases due to prematurity. In Belgium, false positive screens had a shorter length of stay (p = 0.014). Otherwise, misclassification was not related to a specific iNEWS component. This study corroborates previous research, underscoring the validity of iNEWS as a dietetic referral tool and demonstrating that it can be integrated into "real-world" clinical practice across international settings with diverse healthcare resources.