Published on in Vol 22, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20619, first published .
The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

Journals

  1. Forbes M, Darney B, Ramanadhan S, Earp M, Waldner-James L, Han L. How do women interpret abortion information they find online?. Contraception 2021;103(4):276 View
  2. Chaiken S, Han L, Darney B, Han L. Factors Associated With Perceived Trust of False Abortion Websites: Cross-sectional Online Survey. Journal of Medical Internet Research 2021;23(4):e25323 View
  3. Khamisy-Farah R, Furstenau L, Kong J, Wu J, Bragazzi N. Gynecology Meets Big Data in the Disruptive Innovation Medical Era: State-of-Art and Future Prospects. International Journal of Environmental Research and Public Health 2021;18(10):5058 View
  4. Guendelman S, Pleasants E, Cheshire C, Kong A. Exploring Google Searches for Out-of-Clinic Medication Abortion in the United States During 2020: Infodemiology Approach Using Multiple Samples. JMIR Infodemiology 2022;2(1):e33184 View
  5. Jacobson L, Ramirez A, Bercu C, Katz A, Gerdts C, Baum S. Understanding the Abortion Experiences of Young People to Inform Quality Care in Argentina, Bangladesh, Ethiopia, and Nigeria. Youth & Society 2022;54(6):957 View
  6. Chaiken S, Darney B, Schenck M, Han L. Public perceptions of abortion complications. American Journal of Obstetrics and Gynecology 2023;229(4):421.e1 View
  7. John J, Martin Z. Abortion needs expressed on Reddit after the Dobbs v. Jackson Women's Health Organization decision in the United States. Perspectives on Sexual and Reproductive Health 2024;56(1):41 View

Books/Policy Documents

  1. Malki L, Patel D, Singh A. Human-Computer Interaction – INTERACT 2023. View