TY - JOUR
T1 - Going to extremes
T2 - The Goldilocks/Lagom principle and data distribution
AU - Leese, Henry J.
AU - Sathyapalan, Thozhukat
AU - Allgar, Victoria
AU - Brison, Daniel R.
AU - Sturmey, Roger
N1 - © Author(s) (or their employer(s)) 2019.
PY - 2019/11/27
Y1 - 2019/11/27
N2 - Numerical data in biology and medicine are commonly presented as mean or median with error or confidence limits, to the exclusion of individual values. Analysis of our own and others' data indicates that this practice risks excluding € Goldilocks' effects in which a biological variable falls within a range between € too much' and € too little' with a region between where its function is € just right'; a concept captured by the Swedish term € Lagom'. This was confirmed by a narrative search of the literature using the PubMed database, which revealed numerous relationships of biological and clinical phenomena of the Goldilocks/Lagom form including quantitative and qualitative examples from the health and social sciences. Some possible mechanisms underlying these phenomena are considered. We conclude that retrospective analysis of existing data will most likely reveal a vast number of such distributions to the benefit of medical understanding and clinical care and that a transparent approach of presenting each value within a dataset individually should be adopted to ensure a more complete evaluation of research studies in future.
AB - Numerical data in biology and medicine are commonly presented as mean or median with error or confidence limits, to the exclusion of individual values. Analysis of our own and others' data indicates that this practice risks excluding € Goldilocks' effects in which a biological variable falls within a range between € too much' and € too little' with a region between where its function is € just right'; a concept captured by the Swedish term € Lagom'. This was confirmed by a narrative search of the literature using the PubMed database, which revealed numerous relationships of biological and clinical phenomena of the Goldilocks/Lagom form including quantitative and qualitative examples from the health and social sciences. Some possible mechanisms underlying these phenomena are considered. We conclude that retrospective analysis of existing data will most likely reveal a vast number of such distributions to the benefit of medical understanding and clinical care and that a transparent approach of presenting each value within a dataset individually should be adopted to ensure a more complete evaluation of research studies in future.
KW - data analysis and interpretation
KW - data distributions
KW - statistics & research methods
UR - http://www.scopus.com/inward/record.url?scp=85075791085&partnerID=8YFLogxK
U2 - 10.1136/bmjopen-2018-027767
DO - 10.1136/bmjopen-2018-027767
M3 - Article
C2 - 31780584
AN - SCOPUS:85075791085
SN - 2044-6055
VL - 9
JO - BMJ Open
JF - BMJ Open
IS - 11
M1 - e027767
ER -