How Feedback Biases Give Ineffective Medical Treatments a Good Reputation

Journals

1. Emmert M, Meszmer N, Schlesinger M. A cross-sectional study assessing the association between online ratings and clinical quality of care measures for US hospitals: results from an observational study. BMC Health Services Research 2018;18(1) View
2. Ioannidis J. Does evidence-based hearsay determine the use of medical treatments?. Social Science & Medicine 2017;177:256 View
3. Ibáñez R, Lupiañez-Villanueva F. Análisis de 51.996 opiniones online sobre profesionales sanitarios en una web comercial. Revista de Calidad Asistencial 2017;32(5):294 View
4. Hao H. The Development of Online Doctor Reviews in China: An Analysis of the Largest Online Doctor Review Website in China. Journal of Medical Internet Research 2015;17(6):e134 View
5. Witteman H, Fagerlin A, Exe N, Trottier M, Zikmund-Fisher B. One-Sided Social Media Comments Influenced Opinions And Intentions About Home Birth: An Experimental Study. Health Affairs 2016;35(4):726 View
6. Acerbi A. A Cultural Evolution Approach to Digital Media. Frontiers in Human Neuroscience 2016;10 View
7. de Barra M, Cownden D, Jansson F. Aversive medical treatments signal a need for support: a mathematical model. Evolutionary Human Sciences 2019;1 View
8. Miton H, Claidière N, Mercier H. Universal cognitive mechanisms explain the cultural success of bloodletting. Evolution and Human Behavior 2015;36(4):303 View
9. Ziebland S, Powell J, Briggs P, Jenkinson C, Wyke S, Sillence E, Harris P, Perera R, Mazanderani F, Martin A, Locock L, Kelly L, Booth M, Gann B, Newhouse N, Farmer A. Examining the role of patients’ experiences as a resource for choice and decision-making in health care: a creative, interdisciplinary mixed-method study in digital health. Programme Grants for Applied Research 2016;4(17):1 View
10. van Veggel N. “But it worked for my mother’s cat”. Some common misconceptions about anecdotal evidence. Veterinary Nursing Journal 2017;32(8):239 View
11. de Barra M. Reporting bias inflates the reputation of medical treatments: A comparison of outcomes in clinical trials and online product reviews. Social Science & Medicine 2017;177:248 View
12. Shah A, Naqvi R, Jeong O. The Impact of Signals Transmission on Patients’ Choice through E-Consultation Websites: An Econometric Analysis of Secondary Datasets. International Journal of Environmental Research and Public Health 2021;18(10):5192 View
13. Li X, Chou S, Deily M, Qian M. Comparing the Impact of Online Ratings and Report Cards on Patient Choice of Cardiac Surgeon: Large Observational Study. Journal of Medical Internet Research 2021;23(10):e28098 View
14. Smart S, Dimes H, Lumley C, Spooner S, Anderson S, Platt S, Davidson S. A Volunteer-Run, Face-to-Face, Early Intervention Service for Reducing Suicidality. Crisis 2023;44(4):349 View
15. Hong Z. Dream Interpretation from a Cognitive and Cultural Evolutionary Perspective: The Case of Oneiromancy in Traditional China. Cognitive Science 2022;46(1) View
16. Hong Z. The Cultural Evolution of Medical Technologies. Human Nature 2023;34(1):64 View
17. Brown R, de Barra M, Earp B. Broad Medical Uncertainty and the ethical obligation for openness. Synthese 2022;200(2) View
18. Hong Z. Ghosts, Divination, and Magic among the Nuosu: An Ethnographic Examination from Cognitive and Cultural Evolutionary Perspectives. Human Nature 2022;33(4):349 View
19. Hong Z, Zinin S. The psychology and social dynamics of fetal sex prognostication in China: Evidence from historical data. American Anthropologist 2023;125(3):519 View
20. Martynenko M, Martynenko A. Development of enterprise reputation management in the sphere of medical services. Development management 2022;20(4) View

Books/Policy Documents

1. Ru B, Yao L. Social Web and Health Research. View