Herz & Gesundheit

Forget the Ideology of Mass Production in Medical Research! Quality, not Quantity is Decisive

Schluss mit der „Tonnenideologie“ in der medizinischen Forschung! Qualität, nicht Quantität ist wichtig

Every researcher wants to be important. If not manifestly, then at least frequently quoted by peers. This is an important basis for an academic career.

But how is the importance of a scientist really recognized? In the case of Albert Einstein and his theory of relativity or Alexander Fleming and penicillin, it’s easy. But what about the many others who always advance in small steps? If they are often cited by colleagues, that may be one sign. So how does one get there? It is necessary to publish as many articles as possible in journals which are widely read and cited. Various factors have been invented to quantify this. The Impact Factor and recently often the Hirsch-Index (h-Index) have been used as a measure of the frequency of citation. This is, however, being criticized more and more, and with good reason.

In 2013, I already wrote a critical editorial for this journal (2) about the Impact-Factor. Last year, three scientific academies in Europe (Académie des Sciences, Leopoldina and Royal Society) published a joint statement on the evaluation of scientists and their achievements (1). Similar ideas have been in the Support Guidelines of the German Research Foundation for some time, as the President, Peter Strohschneider, made clear in a speech in 2017 (7). In Forschung und Lehre, the journal of the Hochschullehrerverband (Association of University Lecturers), a sort of Professors‘ Union, there have also been many critical commentaries (for example (8)).

Essential Statement of the Academies

„Evaluation requires peer review by acknowledged experts working to the highest ethical standards and focusing on intellectual merits and scientific achievements. Bibliometric data cannot be used as a proxy for expert assessment. Well-founded judgment is essential. Overemphasis on such metrics may seriously damage scientific creativity and originality. Expert peer review should be treated as a valuable resource“ (1).

What are Bibliometric Data?

These are, among other things, the quantities mentioned above: They measure how often articles of one journal or a certain researcher are cited. They have been used for years, very often still today, without reservation to “calculate” the importance of scientists.

The Impact Factor

The best-known quantity is the Impact Factor. It describes how often an article from the preceding two years in a journal was cited on average in the report year; less often, the citations for articles in the last five years were assessed. It is, thus, actually a measure of the importance of a journal. If I manage to publish in Nature, Science, The Lancet or The New England Journal of Medicine, I am assigned a very high Impact Factor (40.1; 37.2; 47.8 and 72.4 in 2017), even if I, personally, was not quoted. The presumed importance of a researcher is deduced from the sum of the Impact Factors for his articles.

Why is the Impact Factor so high for the journals named above? They only accept articles, or even brief notices, which appear to be particularly important; correspondingly, they are often cited. In Nature and Science, the articles are mostly from natural sciences. Clinical medicine appears much more rarely. Since 1869, in a total of 389 000 articles in Nature, 1 878 dealt with Internal Medicine, 377 with Sports Medicine. And what do the editors consider important in Sports Medicine? Primarily doping and genetics. In the interdisciplinary medical journal The Lancet (founded in 1820), there is also very little about Sports Medicine: The word “doping” appeared 27 times in the title of an article, “physical training” 26 times, and “sports injury” seven times , when all volumes are evaluated.

Moreover, the Impact Factor depends in great measure on the size of the field. Most journals in small special fields like Sports Medicine, in which overall less is published than, say, in Internal Medicine, have difficulty reaching the rating 2. Language also plays a great role; these days, one must write in English to achieve international recognition.

Which Articles are Cited especially often (though not Necessarily Quickly)?

1. Important Knowledge or Theories
These articles often take time to become recognized. Occasionally a presumably important bit of news turns out after a few years to be a flop, like supposed autism after a measles vaccination in a Lancet article.

2. Methodical Advances
Here, too, the advances often take a long time before they are applied in other laboratories and can then be cited.

3. Reviews
These are often cited; but they are only important when new relationships are recognized (often, but not only by means of meta-analyses).

All of this reduces the usability of the Impact Factor, primarily for 2 years.

One particular problem is the skewed distribution of the citations (6). Few articles are usually cited very frequently, most rarely or not at all. With an article in Nature or The Lancet, I will still get a rating of 40 or 48 for my Impact sum, even for an article which is never cited at all.

Can the Impact Factor be enlarged in a not-quite honest manner? In an institute with various working teams, researchers who were not actually involved are often included mutually as authors. And the boss is almost always in the list: correctly, if he suggests and checks, incorrectly if he does nothing. A particularly bad way are the so-called quotation cartels, when various research groups agree to quote each other.

In past years, the greater the sum of Impact Factors, the greater the probability of obtaining a professorship or funding. Sociologists have coined the term “Tonnenideologie“ (~ Ideology of Tons) for the fondness for scientific mass production (8).

The Hirsch-Index

Um verschiedene Nachteile des Impact-Faktors zu vermeiden, hat der amerikanische Physiker Jorge E. Hirsch einen Index vorgeschlagen (Hirsch-Index h), der personenbezogen ist (4). Man sortiert die Veröffentlichungen eines Autors nach der Zitierhäufigkeit. Die höchstzitierte Arbeit bekommt die Nummer 1, die anderen folgen nach absteigender Zitierhäufigkeit. Ein Wissenschaftler bekommt als Hirsch-Index den Wert, für den die Nummer mit der Zahl der Zitierungen übereinstimmt. Z. B. bedeutet h=10, dass die 10. Veröffentlichung zehnmal zitiert wurde. Der Index ähnelt daher nicht dem arithmetischen Mittel, sondern eher dem Medianwert.

Der Vorteil gegenüber dem Impact-Faktor ist, dass der Hirsch-Index nicht zeitschriften-, sondern autorbezogen ist. Damit endet aber schon fast die Brauchbarkeit. Der erste Nachteil ist, dass es 3 verschiedene Versionen gibt. Die niedrigsten Werte bekommt man mit SCOPUS, einer Abstract- und Zitationsdatenbank, die (mit Ausnahmen) nur bis 1996 zurückverfolgt. Man muss auch selbst darauf achten, dass verschiedene Namensversionen (in meinem Fall nicht nur Böning, sondern auch Boning, Boening, Bœning in englischen Artikeln) einbezogen werden. Am häufigsten wird das Web of Science benutzt, das meist etwas höhere Werte liefert; es berücksichtigt aber keine Bücher oder Buchkapitel. Die höchsten Werte bekommt man bei Google Scholar.

Weitere Eigenschaften machen den Hirsch-Index fast genauso ungeeignet wie den Impact-Faktor. Er beschreibt bevorzugt die Mittelmäßigkeit, nicht unbedingt die Exzellenz. Ob die wichtigste Veröffentlichung eines Autors 1000 Mal oder 50 Mal zitiert wurde, ist aus dem Hirsch-Index nicht ersichtlich. Und ob seine Thesen richtig oder falsch sind, erschließt sich ebenfalls nicht aus der Zitierhäufigkeit. Ich habe im Laufe der Jahre eine Reihe von typischen Fehlern in teils hochzitierten Veröffentlichungen gefunden (3). Und lässt sich ein behaupteter Effekt nicht reproduzieren, kann das auch öfters in der Literatur diskutiert werden.

Sicherlich haben viele bekannte Wissenschaftler, besonders in Physik oder Biowissenschaften, einen hohen Hirsch-Index um die 100 (z. B. Stephen Hawking). Aber selbst bei Nobelpreisträgern der Medizin gibt es auch bescheidene Werte von 20 noch nach der Preisverleihung (5). Und Peter Higgs, der das Higgs-Teilchen vorhergesagt hat (Nobelpreis für Physik 2013) hat den kläglichen Wert von 11!

Ich schlage daher vor, auch den Hirsch-Index zu vergessen – obwohl es mich persönlich trifft. Mein h-Wert ist nämlich höher als der einiger Nobelpreisträger.


  1. ACADÉMIE DES SCIENCES LARS. Statement by three nationalacademies (Académie des Sciences, Leopoldina and RoyalSociety) on good practice in the evaluation of researchers andresearch programmes. 2017, p. 1-4. [16th March 2013].
  2. BÖNING D. Publizieren in der DZSM lohnt sich! Dtsch Z Sportmed.2013; 64: 95.
  3. BÖNING D. Scientific progress or regress in Sports Physiology?Int J Sports Physiol Perform. 2016; 11: 1106-1110.
  4. HIRSCH JE. An index to quantify an individual‘s scientificresearch output. Proc Natl Acad Sci USA. 2005; 102: 16569-16572.
  5. KREINER G. The slavery of the h-index—measuring theunmeasurable. Front Hum Neurosci. 2016; 10: 556.
  6. OSTERLOH MF, BRUNO S. Absurde Mess-Manie. Der fragwürdigeImpact des Impact-Faktors. Forschung & Lehre. 2017; 24: 876-878.
  7. STROHSCHNEIDER P. Über Wissenschaft in Zeiten des Populismus.In: Jahrestagung der DFG. Halle/Saale: 2017.
  8. STRÜBING J. Problem, Lösung oder Symptom? Zur Forderungnach Replizierbarkeit von Forschungsergebnissen. Forschung &Lehre. 2018; 25: 102-105.
Univ. Prof. a. D. Dr. med. Dieter Böning
Institut für Physiologie
Charité-Universitätsmedizin Berlin
Charitéplatz 1
10117 Berlin