The Scientific Method as a Point of Departure in Aging Research

  • Rubén FossionEmail author
  • Leonardo Zapata-Fonseca


What makes knowledge scientific is not its content per se but rather the form, in which it is obtained. Following the scientific method is a necessary condition to carry out a sound and methodologically valid research. However, for empirical researchers, it is not common practice to reflect upon the method itself. It has been argued that the scientific method is not so different from the common sense that we use in daily life to reach solutions, but with its successive steps better articulated so that scientific knowledge can approach more robust conclusions over time. Since the last quarter of the previous century, there are indications that reductionist strategy of the scientific method has reached its limits, and that therefore a complementary approach is needed to investigate new complex research problems. Consequently, emergentism and systemic thinking are becoming a new explanatory framework that is currently permeating virtually any field of knowledge and all spatiotemporal scales. In the present chapter, we focus on a very specific system under a rather specific yet common and relevant condition: the aging human being. Particularly, we introduce some notions on how the sciences of complexity can help, not only clinicians but also medical research in general –and in particular aging research– to reach a more complete understanding and assessment of the older adult both at an individual and population levels.


Philosophy of science Reductionism Complexity Effective theory 


  1. 1.
    Chalmers AF (1999) What is this thing called science? 3rd edn. Hackett Pub, IndianapolisGoogle Scholar
  2. 2.
    Kosso P (2011) A summary of scientific method. CrossRefGoogle Scholar
  3. 3.
    Hanson NR (1965) Patterns of discovery: an inquiry into the conceptual foundations of science. CUP Archive, CambridgeGoogle Scholar
  4. 4.
    Popper KR (1935) Logik der Forschung: zur Erkenntnistheorie der moderner NaturwissenschaftGoogle Scholar
  5. 5.
    Lakatos I (1969) The problem of inductive logic, proceedings of the international colloquium in the philosophy of science, London, 1965, vol II. North-Holland, AmsterdamGoogle Scholar
  6. 6.
    Jarrard RD (2001) Scientific methods, an online book. University of Utah, Salt Lake City Google ScholarGoogle Scholar
  7. 7.
    Kuhn TS (1970) The structure of scientific revolutions. University of Chicago Press, Chicago, pp 84–85Google Scholar
  8. 8.
    Box GE, Hunter JS, Hunter WG (2005) Statistics for experimenters: design, innovation, and discovery. Wiley Interscience, New YorkGoogle Scholar
  9. 9.
    Gauch HG (2003) Scientific method in practice. Cambridge University Press, CambridgeGoogle Scholar
  10. 10.
    McComas WF (2006) The nature of science in science education: rationales and strategies. Springer Science & Business Media, BerlinGoogle Scholar
  11. 11.
    Heisenberg W (1962) Physics and philosophy: the revolution in modern science [1958]; rpt. Harper & Row, New YorkGoogle Scholar
  12. 12.
    Carroll SM (2016) The big picture: on the origins of life, meaning, and the universe itself. Dutton est. 1852, an imprint of Penguin Random House LLC, New YorkGoogle Scholar
  13. 13.
    Anderson PW (1972) More is different. Science 177:393–396. CrossRefPubMedGoogle Scholar
  14. 14.
    Anderson PW (2011) More and different: notes from a thoughtful Curmudgeon. World Scientific, HackensackCrossRefGoogle Scholar
  15. 15.
    Zolli A, Healy AM (2013) Resilience: why things bounce back. Simon and Schuster, New YorkGoogle Scholar
  16. 16.
    Carpenter SR, Cole JJ, Pace ML, Batt R, Brock WA, Cline T, Coloso J, Hodgson JR, Kitchell JF, Seekell DA, Smith L, Weidel B (2011) Early warnings of regime shifts: a whole-ecosystem experiment. Science 332:1079–1082. CrossRefPubMedGoogle Scholar
  17. 17.
    Scheffer M, Carpenter S, Foley JA, Folke C, Walker B (2001) Catastrophic shifts in ecosystems. Nature 413:591–596. CrossRefPubMedGoogle Scholar
  18. 18.
    Scheffer M, Bascompte J, Brock WA, Brovkin V, Carpenter SR, Dakos V, Held H, van Nes EH, Rietkerk M, Sugihara G (2009) Early-warning signals for critical transitions. Nature 461:53–59. CrossRefPubMedGoogle Scholar
  19. 19.
    Scheffer M, Carpenter SR, Lenton TM, Bascompte J, Brock W, Dakos V, van de Koppel J, van de Leemput IA, Levin SA, van Nes EH, Pascual M, Vandermeer J (2012) Anticipating critical transitions. Science 338:344–348. CrossRefPubMedGoogle Scholar
  20. 20.
    Scheffer M (2009) Critical transitions in nature and society. Princeton University Press, PrincetonGoogle Scholar
  21. 21.
    Gershenson C (2008) Complexity: 5 questionsGoogle Scholar
  22. 22.
    Wiener N (1961) Cybernetics or control and communication in the animal and the machine. MIT press, CambridgeGoogle Scholar
  23. 23.
    Ashby WR (1957) An introduction to cybernetics. 2nd edn. Chapman & Hall Ltd, LondonGoogle Scholar
  24. 24.
    Bertalanffy LV (1968) General system theory, Foundations, Development, Applications. George Braziller, New YorkGoogle Scholar
  25. 25.
    Thom R (1975) Structural stability and morphogenesis: an outline of a general theory of models (trans. Fowler DH). Benjamin, ReadingGoogle Scholar
  26. 26.
    Omran AR (2005) The epidemiologic transition: a theory of the epidemiology of population change. 1971. Milbank Q 83:731–757. CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Ahn AC, Tewari M, Poon C-S, Phillips RS (2006) The limits of reductionism in medicine: could systems biology offer an alternative? PLoS Med 3:e208. CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Ahn AC, Tewari M, Poon C-S, Phillips RS (2006) The clinical applications of a systems approach. PLoS Med 3:e209. CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Hayflick L (1994) How and why we age. Ballantine Books, New YorkGoogle Scholar
  30. 30.
    Bulterijs S, Hull RS, Björk VC, Roy AG (2015) It is time to classify biological aging as a disease. Front Genet 6:205CrossRefGoogle Scholar
  31. 31.
    Hayflick L (2007) Biological aging is no longer an unsolved problem. Ann N Y Acad Sci 1100:1–13. CrossRefPubMedGoogle Scholar
  32. 32.
    Medawar PB (1957) Uniqueness of the individual. Methuen, LondonCrossRefGoogle Scholar
  33. 33.
    Kirkwood TBL (2005) Understanding the odd science of aging. Cell 120:437–447. CrossRefPubMedGoogle Scholar
  34. 34.
    Mossman KL (2014) The complexity paradox: the more answers we find, the more questions we have. Oxford University Press, New YorkGoogle Scholar
  35. 35.
    Cohen AA (2016) Complex systems dynamics in aging: new evidence, continuing questions. Biogerontology 17:205–220. CrossRefPubMedGoogle Scholar
  36. 36.
    Mitnitski AB, Rutenberg AD, Farrell S, Rockwood K (2017) Aging, frailty and complex networks. Biogerontology 18:433–446. CrossRefPubMedGoogle Scholar
  37. 37.
    Rutenberg AD, Mitnitski AB, Farrell SG, Rockwood K (2017) Unifying aging and frailty through complex dynamical networks. Exp Gerontol. CrossRefGoogle Scholar
  38. 38.
    Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, MA MB, Cardiovascular Health Study Collaborative Research Group (2001) Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 56:M146–M156. CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, Mitnitski A (2005) A global clinical measure of fitness and frailty in elderly people. CMAJ 173:489–495. CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Fried LP, Walston JD, Ferrucci L (2009) Hazzard’s geriatric medicine and gerontology. Halter, JB, pp 631–646Google Scholar
  41. 41.
    Parvaneh S, Howe CL, Toosizadeh N, Honarvar B, Slepian MJ, Fain M, Mohler J, Najafi B (2015) Regulation of cardiac autonomic nervous system control across frailty statuses: a systematic review. Gerontology 62:3–15. CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Romero-Ortuno R, Cogan L, O’shea D, Lawlor BA, Kenny RA (2011) Orthostatic haemodynamics may be impaired in frailty. Age Ageing 40:576–583CrossRefGoogle Scholar
  43. 43.
    Kim DH, Kim JA, Choi YS, Kim SH, Lee JY, Kim YE (2010) Heart rate variability and length of survival in hospice cancer patients. J Korean Med Sci 25:1140–1145. CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Brandan ME, Ávila MA, Fossion R, Zapata-Fonseca L (2018) Una mirada a la investigación futura en Física Médica en México. In: Torres Labansat M (ed) Hacia dónde va la Física en México? Fondo Cultural Económico (in print)Google Scholar
  45. 45.
    Lipsitz LA (1992) Loss of “complexity” and aging. JAMA 267:1806. CrossRefPubMedGoogle Scholar
  46. 46.
    Goldberger AL (1996) Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside. Lancet 347:1312–1314CrossRefGoogle Scholar
  47. 47.
    Goldberger AL, Amaral LAN, Hausdorff JM, Ivanov PC, Peng CK, Stanley HE (2002) Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci U S A 99(Suppl 1):2466–2472. CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Goldberger AL (2006) Giles F. filley lecture. complex systems. Proc Am Thorac Soc 3:467–471. CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Parati G, Ochoa JE, Lombardi C, Bilo G (2013) Assessment and management of blood-pressure variability. Nat Rev Cardiol 10:143–155. CrossRefPubMedGoogle Scholar
  50. 50.
    Modell H, Cliff W, Michael J, McFarland J, Wenderoth MP, Wright A (2015) A physiologist’s view of homeostasis. Adv Physiol Educ 39:259–266. CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Fossion R, Fossion JPJ, Rivera AL, Lecona OA, Toledo-Roy JC, García-Pelagio KP, García-Iglesias L, Estañol B (2018a) Homeostasis from a time-series perspective: an intuitive interpretation of the variability of physiological variables. In: Olivares-Quiroz L, Resendis-Antonio O (eds) Quantitative models for microscopic to macroscopic biological macromolecules and tissues. Springer International Publishing, Cham, pp 87–109CrossRefGoogle Scholar
  52. 52.
    Fossion R, Sáenz-Burrola A, Zapata-Fonseca L (2018b) On the stability and adaptability of human physiology: Gaussians meet heavy-tailed distributions. INTERdisciplina (CEIICH-UNAM), IN PRESSGoogle Scholar
  53. 53.
    Fossion R, Rivera AL, Estañol B (2018c) Homeostasis from a physicist point of view: what time series of continuous monitoring tell us about physiological regulation, Physiol. Meas., SUBMITTEDGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Nuclear Sciences Institute and Centre for Complexity Science (C3)National Autonomous University of MexicoMexico CityMexico
  2. 2.Faculty of MedicineNational Autonomous University of MexicoMexico CityMexico

Personalised recommendations