Evaluation of training and career development is one aspect of a longstanding program of financial incentives in support of good management practices at NIH. The original “One Percent Set-aside” was established to provide extra resources to managers and administrators to conduct independent assessments of how well their programs work. For many programs, this is a challenge. For training programs it is somewhat straightforward. The goals are clearer than for research centers and programs: Training programs are expected to produce scientists who can compete, and compete successfully, for research support and who develop and publish new knowledge and discover and test new treatments for human disorders.
There is an additional strong incentive to evaluate our training programs within the context of the labor market: Congress tells the NIH to do this. Since 1974 the NIH has been required to ask the National Academies to establish the level of need for training of biomedical and behavioral researchers to keep this enterprise going. In the past 30 years, the National Academy of Sciences (NAS) has delivered 11 such reports, and the twelfth is being birthed right now. In addition to recommendations and justifications for the number of trainees NIH should be supporting, the academy has conducted or encouraged separate studies of the outcomes of these programs. The academy has also experimented with various mathematical models to build its understanding of the dynamics of the workforce.
But NIH has supported many more studies, reviews, and task forces over the years to see how it is doing and what should be done differently. NIH typically does not focus on the achievements of individual scholars but on aggregate statistics describing the training experiences or settings and subsequent careers of groups of new scientists.
This paper describes some of the data resources NIH has developed and a few examples of how they are used to evaluate the influence or productivity of the training programs, both longitudinally and retrospectively, and examines some characteristics of NIH’s training and workforce. Some data shortcomings and emerging difficulties will be mentioned, as well as the need for additional data resources.
Here are some important data, provided by the Office of Extramural Research, that show the size of NIH’s known research training enterprise:
First, the numbers of trainees and fellows annually since 1976 are seen in Figure 1. There has been a gradual and persistent increase in the number of trainees during the past 25 years. In addition, the ratio of predoctoral to postdoctoral awards has increased slightly, from roughly 50 percent predoctoral awards in 1980 to 57 percent predoctoral awards in 2004.