Michael J. Telch (born March 28, 1953, in Boston, Massachusetts)[1] is an American psychologist who has taught at the University of Texas at Austin (UT-Austin) since 1986. At UT-Austin, he is a professor of clinical psychology, the founding director of the Laboratory for the Study of Anxiety Disorders (which he founded in 1988),[2] and the former Director of Clinical Training. He is a fellow of the Association for Psychological Science and the American Association of Applied and Preventive Psychology.[3] He is known for his research on posttraumatic stress disorder among American soldiers, and the extent to which it can be predicted before the soldiers serve in combat.[4][5][6][7]

Michael Telch
Born
Michael Joseph Telch

(1953-03-28) March 28, 1953 (age 71)
EducationUniversity of Massachusetts, Amherst (B.S., 1975); University of the Pacific (M.A., 1978); Stanford University (Ph.D., 1983)
AwardsUniversity of Texas Dean's Fellowship (2005), Revesz Professor at the University of Amsterdam (2010)
Scientific career
FieldsClinical psychology
InstitutionsUniversity of Texas at Austin
Thesis A comparison of behavioral and pharmacological approaches to the treatment of agoraphobia  (1983)
Academic advisorsWilliam Stewart Agras
Doctoral studentsJesse Cougle

References

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  1. ^ "Michael Telch CV". Retrieved 2 June 2017.
  2. ^ "Laboratory for the Study of Anxiety Disorders". Labs. University of Texas at Austin. Retrieved 2 June 2017.
  3. ^ "Michael J. Telch". University of Texas at Austin. Retrieved 2 June 2017.
  4. ^ Brandeis, Amanda (8 March 2017). "UT study finds PTSD risk can be predicted before deployment". KXAN. Retrieved 2 June 2017.
  5. ^ Munsey, C. (May 2008). "Which service members are most at risk for PTSD?". Monitor on Psychology. American Psychological Association. Retrieved 2 June 2017.
  6. ^ Chang, Alicia (20 November 2009). "Military Experiment Seeks to Predict PTSD". U.S. News & World Report. Retrieved 2 June 2017.
  7. ^ Miller, Greg (29 July 2011). "Predicting the Psychological Risks of War". Science. 333 (6042): 520–1. doi:10.1126/science.333.6042.520. PMID 21798911. Retrieved 2 June 2017.
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