A model of trust in online COVID-19 information and advice: cross sectional questionnaire study (Preprint) DOI Creative Commons
Elizabeth Sillence, Dawn Branley-Bell, Mark Moss

и другие.

JMIR Infodemiology, Год журнала: 2024, Номер 5, С. e59317 - e59317

Опубликована: Ноя. 21, 2024

Background During the COVID-19 pandemic, many people sought information from websites and social media. Understanding extent to which these sources were trusted is important in relation health communication. Objective This study aims identify key factors influencing UK citizens’ trust intention act on advice about found via digital resources test whether an existing model of eHealth provided a good fit for COVID-19–related seeking online. We also wished any differences between evaluation general relating specifically vaccines. Methods In total, 525 completed online survey January 2022 encompassing web questionnaire, measures corroboration, coping perceptions, act. Data analyzed using principal component analysis structural equation modeling. The responses vaccine compared. Results revealed 5 factors: (1) credibility impartiality, (2) familiarity, (3) privacy, (4) usability, (5) personal experiences. final modeling model, had significant direct effect (β=.65; P<.001). Of factors, impartiality positive (β=.82; People searching vaccination felt less at risk, anxious, more optimistic after reading information. noted that most “official” sources. Finally, context COVID-19, “credibility impartiality” remain predictor resources, but comparison with previous models information, checking corroborating did not form part evaluations. Conclusions times uncertainty, when faced global emergent concern, place their familiar rely perceived those above other factors.

Язык: Английский

Exploring COVID-19 Vaccine Misinformation Exposure, Beliefs, Fear, and Information Avoidance via the Stimulus–Organism–Response Framework DOI
Xiaowen Xu, Carolyn A. Lin, Hongliang Chen

и другие.

Science Communication, Год журнала: 2023, Номер 45(6), С. 824 - 850

Опубликована: Ноя. 3, 2023

Empirical evidence generated from theory-driven research addressing the relationship between misinformation and vaccine information avoidance during a pandemic remains lacking. Using Stimulus-Organism-Response (S-O-R) framework, this study examined influence of exposure overload on cognitive affective responses as well behaviors. Findings showed that predicted health beliefs (perceived vaccination barriers benefits) negative emotions (fear) toward vaccines; in turn avoidance. Information moderated (a) (b) relation fear.

Язык: Английский

Процитировано

9

Leveraging digital technology to improve self-efficacy in response to public health crises DOI

Jiandong Lu,

Xiaolei Wang,

S.Z. Chen

и другие.

Information & Management, Год журнала: 2024, Номер 61(6), С. 103987 - 103987

Опубликована: Май 23, 2024

Язык: Английский

Процитировано

3

Impact of COVID-19 Confinement on Mental Health in Youth and Vulnerable Populations: An Extensive Narrative Review DOI Open Access
Manuel Reiriz, Macarena Donoso González,

Benjamín Rodríguez-Expósito

и другие.

Sustainability, Год журнала: 2023, Номер 15(4), С. 3087 - 3087

Опубликована: Фев. 8, 2023

The objective of this narrative review is to analyze the impact COVID-19 on mental health particularly vulnerable groups. This information will allow a better understanding determining factors that influence appearance and/or maintenance mood disorders. To achieve main study, critical was carried out in which primary sources such as scientific articles, secondary databases, and other appropriate reference indexes were considered. results indicated there an increase diagnosis disorders use medication associated with these disorders, mainly during period reclusion declared worldwide March 2020. In addition, risk loneliness, lack resilience, adequate coping strategies negatively impacted future consequences may be reflected over many years thereafter, it important all data obtained from point forward considered by professionals general population. can starting for looking directly at most populations considering both resources available them possible aftermath traumatic everyone’s lives.

Язык: Английский

Процитировано

8

Understanding the impact of government social media on citizens’ unverified information avoidance behavior during health crises: the health belief model DOI
Xueyan Dong, Zhenya Tang, Houcai Wang

и другие.

Online Information Review, Год журнала: 2024, Номер unknown

Опубликована: Сен. 4, 2024

Purpose Unverified information avoidance behavior refers to the conscious effort made by individuals avoid consuming that has not been verified credible sources. This is essential in preventing spread of misinformation can hinder effective public health responses. While previous studies have examined general, there a lack research specifically focusing on unverified during crises. study aims fill this gap exploring factors lead social media users’ crises, providing novel insights into determinants protective behavior. Design/methodology/approach We based our model belief and validated it using data collected from 424 who use media. The proposed was tested partial least squares structural equation modeling (PLS-SEM) approach. Findings Our results indicate individuals’ government participation (following accounts joining groups) affects their beliefs (perceived severity benefits avoidance), which turn trigger Originality/value contributes current literature crisis management implications these findings for policymakers, platforms theory are further discussed.

Язык: Английский

Процитировано

2

A deep learning and clustering‐based topic consistency modeling framework for matching health information supply and demand DOI Open Access
Dongxiao Gu, Liu Hu, Huimin Zhao

и другие.

Journal of the Association for Information Science and Technology, Год журнала: 2023, Номер 75(2), С. 152 - 166

Опубликована: Ноя. 1, 2023

Abstract Improving health literacy through information dissemination is one of the most economical and effective mechanisms for improving population health. This process needs to fully accommodate thematic suitability supply demand reduce impact overload supply–demand mismatch on enthusiasm acquisition. We propose a topic modeling analysis framework that integrates deep learning methods clustering techniques model supply‐side demand‐side topics quantify alignment demand. To validate effectiveness framework, we have conducted an empirical dataset with 90,418 pieces textual data from two prominent social networking platforms. The results show in general has not yet met demand, been considerable extent, especially disease‐related topics, there clear inconsistency between sides same topics. Public policy‐making departments content producers can adjust their selection strategies according distribution identified thereby public dissemination.

Язык: Английский

Процитировано

6

Infodemic: Challenges and solutions in topic discovery and data process DOI Creative Commons
Jinjin Zhang, Yang Pan, Han Lin

и другие.

Archives of Public Health, Год журнала: 2023, Номер 81(1)

Опубликована: Сен. 7, 2023

The Coronavirus Disease 2019 (COVID-19) pandemic was a huge shock to society, and the ensuing information problems had impact on society at same time. urgent need understand Infodemic, i.e., importance of spread false related epidemic, has been highlighted. However, while there is growing interest in this phenomenon, studies topic discovery, data collection, preparation phases analysis process have lacking. Since epidemic unprecedented not ended day, we aimed examine existing Infodemic-related literature from January December 2022. We systematically searched ScienceDirect IEEE Xplore databases with some search limitations. From selected titles, abstracts keywords, limitations sections. conducted an extensive structured by filtering sorting out available information. A total 47 papers up meeting requirements review. Researchers all these literatures encountered different challenges, most which were focused collection step, few challenges phase almost none discovery section. mainly divided into points how collect quickly, get required samples, filter data, what do if set too small, pick right classifier deal drift diversity. In addition, researchers proposed partial solutions also possible solutions. This review found that Infodemic rapidly research area attracts disciplines. number field increased significantly recent years, countries, including United States, India, China. are easy, each step faces challenges. While emerging field, still many be addressed. These findings highlight for more articles address issues fill gaps.

Язык: Английский

Процитировано

4

Understanding SNS use reduction from the perspective of the cognitive-affective model DOI
Pedro Nascimento, Tiago Oliveira, Joana Neves

и другие.

Internet Research, Год журнала: 2024, Номер unknown

Опубликована: Окт. 26, 2024

Purpose This investigation delves into the elements influencing social networking sites (SNS) use reduction behavior through lens of cognitive-affective (CA) model to understand driving forces behind decline in SNS use. Design/methodology/approach Following CA model, this research introduces a theoretical framework that integrates emotions regret and guilt along with principles cognitive dissonance theory. The proposed was subjected empirical validation, utilizing 453 responses gathered from Instagram users. Findings results suggest have favorable impact on users’ intention decrease their usage, exerting an indirect positive influence these emotions. Additionally, further examination unveils fear moderates connection between addiction components. Research limitations/implications Additional affective may intricate relation intention. Originality/value contributes existing body knowledge information system lifecycle by examining shifts user behavior, notably transition excessive adoption strategies. Furthermore, it sheds light role elucidating reduce perspective model. study advances our current understanding how negative consequences arising usage plays as moderating factor underlying internal factors related reducing usage.

Язык: Английский

Процитировано

1

Engaging with underserved communities during times of crises: A computational analysis of social media interactions with government information about COVID-19 economic relief programs DOI Creative Commons
Jihye Lee, Soojong Kim

Telematics and Informatics, Год журнала: 2024, Номер 95, С. 102209 - 102209

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

1

Desarrollo de competencias socioemocionales en estudiantes de educación básica regular DOI Open Access
Rosa Gonzales Rivera, Beatriz Valles Ríos, S. M. Pereyra

и другие.

Horizontes Revista de Investigación en Ciencias de la Educación, Год журнала: 2023, Номер 7(28), С. 652 - 659

Опубликована: Фев. 9, 2023

Tras la aparición del COVID-19 educación tuvo un cambio, al igual que el desarrollo de las Competencias Socioemocionales (CSE) en los estudiantes. El objetivo fue determinar si aplicación Programa Trabajando Juntos fortalece CSE enfoque cuantitativo, cuasi experimental, se dos grupos estudio, comprendidos como: control y usó técnica encuesta, tomándose instrumentos inicio final programa. Además, participantes fueron estudiantes segundo grado secundaria, siendo estos 64 repartidos grupos, tratamiento datos realizado a través Excel SPPS versión actual para 2023. Los resultados encontrados, determinaron que, programa propuesto desarrolla manera alta, significativa positiva; por tanto, concluye programas educativos viabilizan promueven aprendizaje significativo aulas básic

Процитировано

2

The effect of fear on health information searching behavior during the pandemic: The case of COVID-19 DOI
Mesut Teleş

International Journal of Medical Informatics, Год журнала: 2024, Номер 184, С. 105368 - 105368

Опубликована: Фев. 7, 2024

Язык: Английский

Процитировано

0