2026-09-19T06:12:57Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/728922026-06-06T01:06:10Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Richard C. Larson.
Diaz, Mauricio Gomez
Massachusetts Institute of Technology. Technology and Policy Program.
Massachusetts Institute of Technology. Engineering Systems Division
Technology and Policy Program
2012-09-13T18:59:54Z
2012-09-13T18:59:54Z
2012
2012
http://hdl.handle.net/1721.1/72892
808420022
Thesis (S.M. in Technology and Policy)-- Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 63-66).
The U.S. government doubled NIH appropriations between 1998 and 2003, aiming to significantly foster research activities in biomedicine. However, several indicators demonstrate not only that the impact of the budget increase fell short of expectations; in many cases it resulted in unintended negative effects. Compared to pre-doubling conditions, researchers now spend significantly more time writing grant proposals, impacting their ability to carry out research. Paradoxically, the probability with which a grant proposal is accepted for funding deteriorated sharply after the doubling and continues to fall. The average age of first-time NIH grant recipients has increased by almost a decade since the early 70's, while the percentage of biomedical doctorates securing tenured or tenure-track positions relentlessly drops. These trends represent a threat to the quality, stability, and availability of the U.S. biomedical research workforce. This thesis takes a system dynamics approach to test the hypothesis that a sudden and temporary increase in research funds can result in unintended long-term effects hampering research discoveries and workforce development. A simulation model is therefore developed using the available literature and calibrated to replicate historical trends. The model is then used to perform experiments that test the effects of changes in certain parameters or policies. The outcomes of these experiments provide policy insights that can help improve the effectiveness of NIH funding and its impact on the workforce.
by Mauricio Gomez Diaz.
S.M. in Technology and Policy
66 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Engineering Systems Division.
Technology and Policy Program.
Unintended effects of changes in NIH appropriations : challenges for biomedical research workforce development
Unintended effects of changes in National Iinstitutes of Health appropriations
Challenges for biomedical research workforce development
Thesis
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Publication
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<Abstract>The U.S. government doubled NIH appropriations between 1998 and 2003, aiming to significantly foster research activities in biomedicine. However, several indicators demonstrate not only that the impact of the budget increase fell short of expectations; in many cases it resulted in unintended negative effects. Compared to pre-doubling conditions, researchers now spend significantly more time writing grant proposals, impacting their ability to carry out research. Paradoxically, the probability with which a grant proposal is accepted for funding deteriorated sharply after the doubling and continues to fall. The average age of first-time NIH grant recipients has increased by almost a decade since the early 70's, while the percentage of biomedical doctorates securing tenured or tenure-track positions relentlessly drops. These trends represent a threat to the quality, stability, and availability of the U.S. biomedical research workforce. This thesis takes a system dynamics approach to test the hypothesis that a sudden and temporary increase in research funds can result in unintended long-term effects hampering research discoveries and workforce development. A simulation model is therefore developed using the available literature and calibrated to replicate historical trends. The model is then used to perform experiments that test the effects of changes in certain parameters or policies. The outcomes of these experiments provide policy insights that can help improve the effectiveness of NIH funding and its impact on the workforce.</Abstract>
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