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      Tackling Societal Challenges Related to Ageing and Transport Transition: An Introduction to Philosophical Principles of Causation Adapted to the Biopsychosocial Model

      review-article
      1 , 2 , * , 2 , 3
      Geriatrics
      MDPI
      traffic medicine, behavioural science, causality, transversal research

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          Abstract

          In geriatrics, driving cessation is addressed within the biopsychosocial model. This has broadened the scope of practitioners, not only in terms of assessing fitness to drive, but also by helping to maintain social engagements and provide support for transport transition. Causes can be addressed at different levels by adapting medication, improving physical health, modifying behaviour, adapting lifestyle, or bringing changes to the environment. This transdisciplinary approach requires an understanding of how different disciplines are linked to each other. This article reviews the philosophical principles of causality between fields and provides a framework for understanding causality within the biopsychosocial model. Understanding interlevel constraints should help practitioners overcome their differences, and favor transversal approaches to driving cessation.

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          Most cited references44

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          Stochasticity in gene expression: from theories to phenotypes.

          Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.
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            Thinking about Mechanisms

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              Causation and causal inference in epidemiology.

              Concepts of cause and causal inference are largely self-taught from early learning experiences. A model of causation that describes causes in terms of sufficient causes and their component causes illuminates important principles such as multi-causality, the dependence of the strength of component causes on the prevalence of complementary component causes, and interaction between component causes. Philosophers agree that causal propositions cannot be proved, and find flaws or practical limitations in all philosophies of causal inference. Hence, the role of logic, belief, and observation in evaluating causal propositions is not settled. Causal inference in epidemiology is better viewed as an exercise in measurement of an effect rather than as a criterion-guided process for deciding whether an effect is present or not.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Geriatrics (Basel)
                Geriatrics (Basel)
                geriatrics
                Geriatrics
                MDPI
                2308-3417
                23 December 2015
                March 2016
                : 1
                : 1
                : 3
                Affiliations
                [1 ]School of Health Sciences Fribourg, University of Applied Sciences and Arts Western Switzerland, Route des Cliniques 15, Fribourg 1700, Switzerland
                [2 ]Unit of Traffic Medicine and Psychology, University Centre of Legal Medicine, University Hospital of Lausanne (CHUV), Rue Saint-Martin 26, Lausanne 1005, Switzerland
                [3 ]Department of Ambulatory Care and Community Medicine, University of Lausanne, Rue du Bugnon 44, Lausanne 1011, Switzerland; bernard.favrat@ 123456hospvd.ch
                Author notes
                [* ]Correspondence: paul.vaucher@ 123456hefr.ch ; Tel.: +41-26-429-6041; Fax: +41-26-429-6010
                Article
                geriatrics-01-00003
                10.3390/geriatrics1010003
                6371111
                25186955
                9e43ec6d-bb76-4230-b922-6fcc54569a41
                © 2015 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 11 August 2015
                : 17 December 2015
                Categories
                Review

                traffic medicine,behavioural science,causality,transversal research

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