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Original article

Vol. 148 No. 1920 (2018)

A digitally facilitated citizen-science driven approach accelerates participant recruitment and increases study population diversity

  • Milo A. Puhan
  • Nina Steinemann
  • Christian P Kamm
  • Stefanie Müller
  • Jens Kuhle
  • Roland Kurmann
  • Pasquale Calabrese
  • Jürg Kesselring
  • Viktor von Wyl
  • on behalf of the Swiss Multiple Sclerosis Registry (SMSR)
DOI
https://doi.org/10.4414/smw.2018.14623
Cite this as:
Swiss Med Wkly. 2018;148:w14623
Published
16.05.2018

Summary

QUESTION UNDER STUDY

Our aim was to assess whether a novel approach of digitally facilitated, citizen-science research, as followed by the Swiss Multiple Sclerosis Registry (Swiss MS Registry), leads to accelerated participant recruitment and more diverse study populations compared with traditional research studies where participants are mostly recruited in study centres without the use of digital technology.

METHODS

The Swiss MS Registry is a prospective, longitudinal, observational study covering all Switzerland. Participants actively contribute to the Swiss MS Registry, from defining research questions to providing data (online or on a paper form) and co-authoring papers. We compared the recruitment dynamics over the first 18 months with the a priori defined recruitment goals and assessed whether a priori defined groups were enrolled who are likely to be missed by traditional research studies.

RESULTS

The goal to recruit 400 participants in the first year was reached after only 20 days, and by the end of 18 months 1700 participants had enrolled in the Swiss MS Registry, vastly exceeding expectations. Of the a priori defined groups with potential underrepresentation in other studies, 645 participants (46.5%) received care at a private neurology practice, 167 participants (12%) did not report any use of healthcare services in the past 12 months, 32 (2.3%) participants lived in rural mountainous areas, and 20 (2.0% of the 1041 for whom this information was available) lived in a long-term care facility. Having both online and paper options increased diversity of the study population in terms of geographic origin and type and severity of disease, as well as use of health care services. In particular, paper enrolees tended to be older, more frequently affected by progressive MS types and more likely to have accessed healthcare services in the past 12 months.

CONCLUSION

Academic and industry-driven medical research faces substantial challenges in terms of patient involvement, recruitment, relevance and generalisability. Digital studies and stakeholder engagement may have enormous potential for medical research. But many digital studies are based on limited participant information and/or informed consent and unclear data ownership, and are subject to selection bias, confounding and information bias. The Swiss MS Registry serves as an example of a digitally enhanced, citizen-science study that leverages the advantages of both traditional medical research, with its established research methods, and novel societal and technological developments, while mitigating their ethical and legal disadvantages and risks.

Trial registration number

ClinicalTrials.gov identifier NCT02980640.

References

  1. Thornton S. Beyond rhetoric: we need a strategy for patient involvement in the health service. BMJ. 2014;348(jun23 18):g4072–4072. doi:.https://doi.org/10.1136/bmj.g4072
  2. Hernandez AF, Fleurence RL, Rothman RL. The ADAPTABLE Trial and PCORnet: Shining Light on a New Research Paradigm. Ann Intern Med. 2015;163(8):635–6. doi:.https://doi.org/10.7326/M15-1460
  3. Estellat C, Ravaud P. Lack of head-to-head trials and fair control arms: randomized controlled trials of biologic treatment for rheumatoid arthritis. Arch Intern Med. 2012;172(3):237–44. doi:.https://doi.org/10.1001/archinternmed.2011.1209
  4. Mills EJ, Ioannidis JPA, Thorlund K, Schünemann HJ, Puhan MA, Guyatt GH. How to use an article reporting a multiple treatment comparison meta-analysis. JAMA. 2012;308(12):1246–53. doi:.https://doi.org/10.1001/2012.jama.11228
  5. Van Spall HGC, Toren A, Kiss A, Fowler RA. Eligibility criteria of randomized controlled trials published in high-impact general medical journals: a systematic sampling review. JAMA. 2007;297(11):1233–40. doi:.https://doi.org/10.1001/jama.297.11.1233
  6. Boyd CM, Vollenweider D, Puhan MA. Informing evidence-based decision-making for patients with comorbidity: availability of necessary information in clinical trials for chronic diseases. PLoS One. 2012;7(8):e41601. doi:.https://doi.org/10.1371/journal.pone.0041601
  7. Frist WH. Connected health and the rise of the patient-consumer. Health Aff (Millwood). 2014;33(2):191–3. doi:.https://doi.org/10.1377/hlthaff.2013.1464
  8. Topolovec-Vranic J, Natarajan K. The Use of Social Media in Recruitment for Medical Research Studies: A Scoping Review. J Med Internet Res. 2016;18(11):e286. doi:.https://doi.org/10.2196/jmir.5698
  9. Khatri C, Chapman SJ, Glasbey J, Kelly M, Nepogodiev D, Bhangu A, et al.; STARSurg Committee. Social media and internet driven study recruitment: evaluating a new model for promoting collaborator engagement and participation. PLoS One. 2015;10(3):e0118899. doi:.https://doi.org/10.1371/journal.pone.0118899
  10. Vayena E, Salathé M, Madoff LC, Brownstein JS. Ethical challenges of big data in public health. PLOS Comput Biol. 2015;11(2):e1003904. doi:.https://doi.org/10.1371/journal.pcbi.1003904
  11. Rothman M, Gnanaskathy A, Wicks P, Papadopoulos EJ. Can we use social media to support content validity of patient-reported outcome instruments in medical product development? Value Health. 2015;18(1):1–4. doi:.https://doi.org/10.1016/j.jval.2014.10.001
  12. Horton DK, Mehta P, Antao VC. Quantifying a nonnotifiable disease in the United States: the National Amyotrophic Lateral Sclerosis Registry model. JAMA. 2014;312(11):1097–8. doi:.https://doi.org/10.1001/jama.2014.9799
  13. Disanto G, Benkert P, Lorscheider J, Mueller S, Vehoff J, Zecca C, et al.; SMSC Scientific Board. The Swiss Multiple Sclerosis Cohort-Study (SMSC): A Prospective Swiss Wide Investigation of Key Phases in Disease Evolution and New Treatment Options. PLoS One. 2016;11(3):e0152347. doi:.https://doi.org/10.1371/journal.pone.0152347
  14. Calabrese P, Kobelt G, Berg J, Capsa D, Eriksson J ; European Multiple Sclerosis Platform. New insights into the burden and costs of multiple sclerosis in Europe: Results for Switzerland. Mult Scler. 2017;23(2_suppl):192–203. doi:.https://doi.org/10.1177/1352458517708685
  15. Thiel S, Leypoldt F, Röpke L, Wandinger K, Kümpfel T, Aktas O, et al. Neuroimmunological Registries in Germany. Neurol Int Open. 2018;2(1):E25–39. doi:.https://doi.org/10.1055/s-0043-108830
  16. Hillert J, Stawiarz L. The Swedish MS registry – clinical support tool and scientific resource. Acta Neurol Scand. 2015;132(199):11–9. doi:.https://doi.org/10.1111/ane.12425
  17. Magyari M, Koch-Henriksen N, Sørensen PS. The Danish Multiple Sclerosis Treatment Register. Clin Epidemiol. 2016;8:549–52. doi:.https://doi.org/10.2147/CLEP.S99500
  18. UK MS Register. https://ukmsregister.org/Portal/Home
  19. North American Research Committee on Multiple Sclerosis (NARCOMS). https://www.narcoms.org/
  20. World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4. doi:.https://doi.org/10.1001/jama.2013.281053
  21. Beer S, Kesselring J. High prevalence of multiple sclerosis in Switzerland. Neuroepidemiology. 1994;13(1-2):14–8. doi:.https://doi.org/10.1159/000110353
  22. Blozik E, Rapold R, Eichler K, Reich O. Epidemiology and costs of multiple sclerosis in Switzerland: an analysis of health-care claims data, 2011-2015. Neuropsychiatr Dis Treat. 2017;13:2737–45. doi:.https://doi.org/10.2147/NDT.S143180

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