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Philosophy&Psychiatry Study group: Jan-Willem Romeijn

22 June @ 19:00 - 20:30

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During this online session (starting at 19:00 sharp), prof. Jan-Willem Romeijn (RUG) will give a talk (see abstract below).   =================================== Data-driven psychiatry: Geertz meets Kraepelin Jan-Willem Romeijn (Faculty of Philosophy, University of Groningen) Joint work with Hanna van Loo (University Centre for Psychiatry, University of Groningen) Owing to new research methods and the availability of ever larger data sets, psychiatric research is becoming increasingly data-driven. A well-known concern about data-driven predictions is that the data are infused with theoretical suppositions…
During this online session (starting at 19:00 sharp), prof. Jan-Willem Romeijn (RUG) will give a talk (see abstract below).   =================================== Data-driven psychiatry: Geertz meets Kraepelin Jan-Willem Romeijn (Faculty of Philosophy, University of Groningen) Joint work with Hanna van Loo (University Centre for Psychiatry, University of Groningen) Owing to new research methods and the availability of ever larger data sets, psychiatric research is becoming increasingly data-driven. A well-known concern about data-driven predictions is that the data are infused with theoretical suppositions that do not get properly adjudicated. The opposite concern, namely that the data do not carry enough information to bring psychiatric illness into view, has received far less attention in the philosophy of science. Our paper directs attention precisely there. Our worry about the turn to data-driven research in psychiatry is that, while rich in implicit theory, the data are still too poor for adequate modeling and predicting. There are many aspects to the doctor-patient interaction that do not get represented in the predictive system, while they are vital to an adequate understanding of the patient’s situation and potential recovery. Our primary conclusion is that, if we want to rely on data-driven predictions in the clinic and in research psychiatry, we are in need of what Clifford Geertz would call “thick descriptions”, i.e., highly detailed data that includes intentions and meanings, over and above the direct observational facts. Some thickening of clinical descriptions may be relatively easily accommodated. But there are limits to this, e.g., variation in what the personal specifics mean to a patient is much harder to accommodate in database infrastructure. Our paper ends with some indications on how far we might get in converting thick descriptions into data sets, against the background of a much broader discussion on the nature of explanation and understanding in the human sciences.

Details

Date:
22 June
Time:
19:00 - 20:30
Event Categories:
,

During this online session (starting at 19:00 sharp), prof. Jan-Willem Romeijn (RUG) will give a talk (see abstract below).

 

===================================

Data-driven psychiatry: Geertz meets Kraepelin

Jan-Willem Romeijn (Faculty of Philosophy, University of Groningen)

Joint work with Hanna van Loo (University Centre for Psychiatry, University of Groningen)

Owing to new research methods and the availability of ever larger data sets, psychiatric research is becoming increasingly data-driven. A well-known concern about data-driven predictions is that the data are infused with theoretical suppositions that do not get properly adjudicated. The opposite concern, namely that the data do not carry enough information to bring psychiatric illness into view, has received far less attention in the philosophy of science. Our paper directs attention precisely there. Our worry about the turn to data-driven research in psychiatry is that, while rich in implicit theory, the data are still too poor for adequate modeling and predicting. There are many aspects to the doctor-patient interaction that do not get represented in the predictive system, while they are vital to an adequate understanding of the patient’s situation and potential recovery.

Our primary conclusion is that, if we want to rely on data-driven predictions in the clinic and in research psychiatry, we are in need of what Clifford Geertz would call “thick descriptions”, i.e., highly detailed data that includes intentions and meanings, over and above the direct observational facts. Some thickening of clinical descriptions may be relatively easily accommodated. But there are limits to this, e.g., variation in what the personal specifics mean to a patient is much harder to accommodate in database infrastructure. Our paper ends with some indications on how far we might get in converting thick descriptions into data sets, against the background of a much broader discussion on the nature of explanation and understanding in the human sciences.

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