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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
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Consider an isolated system in which a hot object is placed in contact with a cold one. This is an irreversible process that eventually leads both objects to reach the same equilibrium temperature. It is crucial to note that the constituents of any substance exhibit increased disorder at higher temperatures. As a cold substance absorbs heat, its constituents become more disordered. The energy transfer from a hotter object to a cooler one increases the system's disorder or randomness. This...
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The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
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Related Experiment Video

Updated: Mar 16, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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[Information is more than just the number].

D R M Timmermans1

  • 1VUmc, afd. Sociale Geneeskunde, Amsterdam en RIVM, Bilthoven.

Nederlands Tijdschrift Voor Geneeskunde
|August 25, 2016
PubMed
Summary

Providing patients with transparent treatment information is crucial. The number unnecessarily treated (NUT) requires clear communication, as non-effective treatments can cause harm and numbers may be difficult for patients to understand.

Area of Science:

  • Medical Decision Making
  • Health Communication
  • Biostatistics

Background:

  • Informed patient choices depend on transparent information regarding treatment pros and cons.
  • Communicating treatment outcomes effectively is essential for shared decision-making.

Purpose of the Study:

  • To evaluate the optimal presentation of treatment outcome data for patient comprehension.
  • To assess the utility of the number unnecessarily treated (NUT) in patient information.

Main Methods:

  • Comparative analysis of information presentation formats for patient understanding.
  • Focus on natural frequency trees versus population diagrams for data visualization.

Main Results:

  • Patients may not understand that non-effective treatments can cause harm.

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  • Numerical data and probabilities present comprehension challenges for many patients.
  • Natural frequency trees are more effective than population diagrams for intuitive understanding.

    • Conclusions:

    • The presentation format significantly impacts patient comprehension of treatment information.
    • Effective patient communication prioritizes message clarity over raw numerical data.
    • Careful consideration of presentation is vital when using metrics like the number unnecessarily treated (NUT).