Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Comment
  • Published:

The evolving model of pediatric research

Pediatric Research volume 94, pages 412–415 (2023)Cite this article

This month’s article “Prenatal and perinatal factors associated with neonatal neurobehavioral profiles in the ECHO program”1 demonstrates how pediatric research has evolved over time from single institution, single disease studies to multi-site collaborations that employ “big data” to reach more impactful and far-ranging conclusions. The study also goes beyond cross-sectional associations to more powerful longitudinal analysis that recognizes and incorporates prenatal factors affecting child health in a life course perspective. New technologies, methods, and paradigms are transforming research and the opportunities to accelerate scientific discovery and translation to practice. As policies on research conduct and funding are changing, understanding the evolving research model is imperative to keep child health research strong.

The advancement in pediatric research involves all domains of the scientific process including the investigative team, the study’s focus and participants, the time frame examined, and new types of study sites and innovative technologies. A framework summarizing these changes details the Who, What, When, Where, and How of this evolving model of research (Table 1) compared to the old model.

Table 1 The evolving model of research.
Full size table

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Building a biomedical knowledge network.

References

  1. Camerota, M., McGowan, E.C., Aschner, J. et al. Prenatal and perinatal factors associated with neonatal neurobehavioral profiles in the ECHO Program. Pediatr Res (2023). https://doi.org/10.1038/s41390-023-02540-2.

  2. National Research Council. Convergence: facilitating transdisciplinary integration of life sciences, physical sciences, engineering, and beyond. (The National Academies Press, Washington, DC, 2014) https://doi.org/10.17226/18722.

  3. Collaco, J. M., St. Geme, J. W., Abman, S. H. & Furth, S. L. It takes a team to make team science a success: career development within multicenter networks. J. Pediatr. 252, 3–6 (2023).

    Article  PubMed  Google Scholar 

  4. Varnell, C. D. Jr, Margolis, P., Goebel, J. & Hooper, D. K. The learning health system for pediatric nephrology: building better systems to improve health. Pediatr. Nephrol. 38, 35–46 (2023).

    Article  PubMed  Google Scholar 

  5. Keck, C., Hartley, D. M., Havens, M., Margolis, P. A. & Seid, M. Getting what is needed, when it’s needed: sharing information, knowledge, and know-how in a Collaborative Learning Health System. Learn Health Syst. 5, e10268 (2021).

    PubMed  PubMed Central  Google Scholar 

  6. Cheng, T. L., Johnson, S. B. & Goodman, E. Breaking the intergenerational cycle of disadvantage: the three generation approach. Pediatrics 137, 1–12 (2016).

  7. Cheng, T. L., Cohn, R. D. & Dover, G. J. The genetics revolution and primary care pediatrics. JAMA 299, 451–453 (2008).

    Article  CAS  PubMed  Google Scholar 

  8. Permar, S., Creech, C. B., Edwards, K. M. & Walter, E. B. Proposals to accelerate novel vaccine development for children. Pediatrics e2021054593, https://doi.org/10.1542/peds.2021-054593 (2021).

  9. DuBois, S. G., Corson, L. B., Stegmaier, K. & Janeway, K. A. Ushering in the next generation of precision trials for pediatric cancer. Science 363, 1175–1181 (2019).

    Article  CAS  PubMed  Google Scholar 

  10. Mandl, K. D., Genomics Research and Innovation Network, et al. The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system. Genet Med. 22, 371–380 (2020).

  11. Haug, C. J. & Drazen, J. M. Artificial intelligence and machine learning in clinical medicine, 2023. N. Engl. J. Med. 388, 1201–1208 (2023).

    Article  CAS  PubMed  Google Scholar 

  12. Cheng, T. L., Bogue, C. & Dover, G. The next seven great achievements in pediatric research. Pediatrics 139, e20163803 (2017).

Download references

Acknowledgements

On behalf of the Pediatric Policy Council: S.S., MD, Chair, Pediatric Policy Council. M.P., MD, Academic Pediatric Association Representative. J.R., MD, MPH, Academic Pediatric Association Representative. D.K., MD, American Pediatric Society Representative. L.C., MD, MPH, American Pediatric Society Representative. T.C., MD, MPH, Association of Medical School Pediatric Department Chairs Representative. A.R., MD, Association of Medical School Pediatric Department Chairs Representative. J.J., MD, MPH, MS, Society for Pediatric Research Representative. L.L., MD, MPH, Society for Pediatric Research Representative.

Author information

Authors and Affiliations

  1. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

    Tina L. Cheng & Tracy A. Glauser

  2. Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA

    Tina L. Cheng & Tracy A. Glauser

  3. Department of Pediatrics, Duke University, Durham, NC, USA

    Ann Reed

  4. Chair, Pediatric Policy Council, Valhalla, NY, USA

    Shetal Shah

  5. Academic Pediatric Association Representative, McLean, VA, USA

    Mona Patel & Jean Raphael

  6. American Pediatric Society Representative, The Woodlands, TX, USA

    David Keller & Lisa Chamberlain

  7. Association of Medical School Pediatric Department Chairs Representative, McLean, VA, USA

    Tina Cheng & Ann Reed

  8. Society for Pediatric Research Representative, The Woodlands, TX, USA

    Joyce Javier & Lois Lee

Authors
  1. Tina L. Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tracy A. Glauser
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ann Reed
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

On behalf of the Pediatric Policy Council

  • Shetal Shah
  • , Mona Patel
  • , Jean Raphael
  • , David Keller
  • , Lisa Chamberlain
  • , Tina Cheng
  • , Ann Reed
  • , Joyce Javier
  •  & Lois Lee

Contributions

T.L.C.: She is consulting editor for Pediatric Clinics of North America. She conceptualized and wrote the manuscript, revised each draft, and approved the final manuscript. T.A.G.: He conceptualized and wrote the manuscript, revised each draft, and approved the final manuscript. A.R.: She wrote portions of the manuscript, revised each draft, and approved the final manuscript.

Corresponding author

Correspondence to Tina L. Cheng.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cheng, T.L., Glauser, T.A., Reed, A. et al. The evolving model of pediatric research. Pediatr Res 94, 412–415 (2023). https://doi.org/10.1038/s41390-023-02677-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41390-023-02677-0

Search

Advanced search

Quick links