Published on in Vol 21, No 3 (2019): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13058, first published .
Characterizing Media Content and Effects of Organ Donation on a Social Media Platform: Content Analysis

Characterizing Media Content and Effects of Organ Donation on a Social Media Platform: Content Analysis

Characterizing Media Content and Effects of Organ Donation on a Social Media Platform: Content Analysis

Journals

  1. Gao S, He L, Chen Y, Li D, Lai K. Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media. Journal of Medical Internet Research 2020;22(7):e16649 View
  2. Karmegam D, Mapillairaju B. What people share about the COVID-19 outbreak on Twitter? An exploratory analysis. BMJ Health & Care Informatics 2020;27(3):e100133 View
  3. ASIMAKOPOULOU E, STYLIANOU V, DIMITRAKOPOULOS I, ARGYRIADIS A, BELLOU–MYLONA P. Knowledge and Attitudes Regarding Organ Transplantation Among Cyprus Residents. Journal of Nursing Research 2021;29(1):e132 View
  4. Xiong X, Lai K, Jiang W, Sun X, Dong J, Yao Z, He L. Understanding public opinion regarding organ donation in China: A social media content analysis. Science Progress 2021;104(2) View
  5. Siste K, Hanafi E, Sen L, Murtani B, Christian H, Limawan A, Siswidiani L, Adrian . Implications of COVID-19 and Lockdown on Internet Addiction Among Adolescents: Data From a Developing Country. Frontiers in Psychiatry 2021;12 View
  6. Karmegam D, Mappillairaju B. Social media analytics and reachability evaluation - #Diabetes. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2022;16(1):102359 View
  7. Liu J, Shi M. What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?. International Journal of Environmental Research and Public Health 2022;19(10):6129 View
  8. Kraft S, Rohrig A, Williams A, Shah S. Better recognition for research participants: what society should learn from covid-19. BMJ 2023:e071178 View
  9. Asghari M, Nielsen J, Gentili M, Koizumi N, Elmaghraby A. Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study. JMIR Medical Informatics 2022;10(11):e37884 View
  10. Zhang Z, Jin J, Luo C, Chen A. Excavating the social representations and perceived barriers of organ donation in China over the past decade: A hybrid text analysis approach. Frontiers in Public Health 2022;10 View
  11. Martin S, Rocque B, Emamaullee J. Social Media in Transplantation: An Opportunity for Outreach, Research Promotion, and Enhancing Workforce Diversity. Transplantation 2022;106(11):2108 View
  12. Gong F, Jia Y, Zhang J, Cao M, Jia X, Sun X, Wu Y. Media use and organ donation willingness: A latent profile analysis from Chinese residents. Frontiers in Public Health 2022;10 View
  13. Olsacher A, Bade C, Ehlers J, Freitag B, Fehring L. Messaging strategies for communicating health-related information in social media—a content and effectiveness analysis of organ donation posts on Instagram in Germany. BMC Public Health 2023;23(1) View
  14. Walton P, Pérez-Blanco A, Beed S, Glazier A, Ferreira Salomao Pontes D, Kingdon J, Jordison K, Weiss M. Organ and Tissue Donation Consent Model and Intent to Donate Registries: Recommendations From an International Consensus Forum. Transplantation Direct 2023;9(5):e1416 View
  15. Olsacher A, Bade C, Ehlers J, Fehring L. How to effectively communicate health information on social media depending on the audience's personality traits: An experimental study in the context of organ donation in Germany. Social Science & Medicine 2023;335:116226 View
  16. Fu J, Li C, Zhou C, Li W, Lai J, Deng S, Zhang Y, Guo Z, Wu Y. Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review. Journal of Medical Internet Research 2023;25:e43349 View
  17. Alhasan K, Aljamaan F, Ajlan A, Aleid H, Al Ghoufi T, Alabbad S, AlDhaferi R, Almaiman W, Ali T, Hakami A, Hakami R, Alqarni B, Alrashed A, Alsharidi T, Almousa H, Altamimi I, Alhaboob A, Jamal A, Shalaby M, Kari J, Raina R, Broering D, Temsah M. Awareness, Attitudes, and Willingness: A Cross-Sectional Study of Organ Donation in Saudi Arabia. Healthcare 2023;11(24):3126 View
  18. Brassel S, Brunner M, Campbell A, Power E, Togher L. Exploring Discussions About Virtual Reality on Twitter to Inform Brain Injury Rehabilitation: Content and Network Analysis. Journal of Medical Internet Research 2024;26:e45168 View
  19. Hoang C. Promoting organ donation through philanthropic partnerships. Psychology & Marketing 2024;41(8):1703 View
  20. Hui E, Singh S, Lin P, Dillon D. Social Media Influence on Emerging Adults’ Prosocial Behavior: A Systematic Review. Basic and Applied Social Psychology 2024;46(4):239 View
  21. Zhang Y, Fu J, Lai J, Deng S, Guo Z, Zhong C, Tang J, Cao W, Wu Y. Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review. Journal of Medical Internet Research 2024;26:e51496 View
  22. Feldens T, Jacinto P. Does the media contribute to raising awareness of organ donation? Evidence from Brazil. International Journal of Social Economics 2024 View
  23. Dong S, Walker J, Nematollahi S, Nolan N, Ryder J. The ID Digital Institute: Building a digital education toolset and community. Transplant Infectious Disease 2024;26(4) View
  24. Jiang X, Su M, Hwang J, Lian R, Brauer M, Kim S, Shah D. Polarization Over Vaccination: Ideological Differences in Twitter Expression About COVID-19 Vaccine Favorability and Specific Hesitancy Concerns. Social Media + Society 2021;7(3) View
  25. Nielsen J, Chen X, Davis L, Waterman A, Gentili M. Classification of Living Kidney Donation Experiences on Reddit: Understanding the Sensitivity of ChatGPT to Prompt Engineering (Preprint). JMIR AI 2024 View
  26. Liu P, Li Q, Zhao X. Organ donation information scanning, seeking, and discussing: Impacts on knowledge, attitudes, and donation intentions. Social Science & Medicine 2025;365:117543 View
  27. AU A, CHENG S, WU W, SHUM D, NEZLEK J, HUI B. Understanding age-related differences in online prosocial behavior: A qualitative thematic analysis of interpersonal, ideological, and mixed patterns. Computers in Human Behavior Reports 2024:100557 View