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Research Training in the Biomedical, Behavioral, and Clinical Research Sciences (2011)

Chapter: Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)

« Previous: Appendix D: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016
Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Appendix E
Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)

OVERVIEW

Appendix D provides demographic projections of the research workforce in the biomedical, clinical, and behavioral sciences for the years 2006-2016 using a traditional statistical (actuarial) approach. This appendix provides additional demographic projections for the same workforces using an alternative approach called system dynamics that is based on the “structure” of the system (i.e., the interconnections among the various entities or parts of the system). In this case, the system under study is the scientific research workforce.

For each of the biomedical, clinical, and behavioral sciences workforces, projections will be shown for the total population along with the populations in the following four (4) demographic categories:

  1. U.S.-trained males

  2. U.S.-trained females

  3. Foreign-trained males

  4. Foreign-trained females

In each projection, the beginning population values are the actual values for 2006, the latest published set of data points. For each of the three major workforces (i.e., biological, clinical, and behavioral sciences), three (3) scenarios will be considered.

  1. Scenario 1 (Moderate Risk): Use 50 percent of the value of the specified annual growth rate for each subgroup of the workforce. This is rated moderate risk because it is the most likely scenario and has the workforce projections that are most expected.

  2. Scenario 2 (High Risk): Use 75 percent of the value of the specified annual growth rate for each subgroup of the workforce. This is rated high risk because it produces very large workforces over the 10-year simulation.

  3. Scenario 3 (Low Risk): Use Ph.D. student growth rates in a “pipeline” model into the workforce. This is rated low risk because it is the most conservative set of projections for the workforces.

Figure E-1 shows the projections for the three major workforces for Scenario 1, the most likely scenario.

SUMMARY PROJECTIONS FOR ALL THREE SCENARIOS

Figures E-2 through E-4 show the projections for each of the three major workforces for each of the three scenarios in line-graph form. Tables E-1 through E-3 then show the projections for each of the three major workforces for each of the three scenarios in table form.

DEMOGRAPHIC DETAILS FOR SCENARIO 1 (MODERATE RISK)

Figure E-5 shows the projections for each of the four demographic groups for the biomedical sciences workforce for Scenario 1 in bar-graph form, and Table E-4 shows the same projections in table form.

Figure E-6 shows the projections for each of the four demographic groups for the behavioral sciences workforce for Scenario 1 in bar-graph form, and Table E-5 shows the same projections in table form.

Figure E-7 shows the projections for each of the four demographic groups for the clinical sciences workforce for Scenario 1 in bar-graph form, and Table E-6 shows the same projections in table form.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×
FIGURE E-1 Total biomedical, behavioral, and clinical sciences workforces, 2006-2016, scenario 1.

FIGURE E-1 Total biomedical, behavioral, and clinical sciences workforces, 2006-2016, scenario 1.

SOURCE: NRC analysis.

FIGURE E-2 Total biomedical sciences workforce, 2006-2016.

FIGURE E-2 Total biomedical sciences workforce, 2006-2016.

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×
FIGURE E-3 Total behavioral sciences workforce, 2006-2016.

FIGURE E-3 Total behavioral sciences workforce, 2006-2016.

SOURCE: NRC analysis.

FIGURE E-4 Total clinical sciences workforce, 2006-2016.

FIGURE E-4 Total clinical sciences workforce, 2006-2016.

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

TABLE E-1 Biomedical Sciences Workforce Projections for All Scenarios

 

BIOMEDICAL

 

Scenario 1

Scenario 2

Scenario 3

2006

159,853

159,853

159,853

2007

162,950

164,598

162,926

2008

166,423

170,244

166,296

2009

170,339

177,046

169,995

2010

174,782

185,354

174,063

2011

179,854

195,662

178,543

2012

185,684

208,677

183,489

2013

192,437

225,425

188,959

2014

200,321

247,417

195,024

2015

209,607

276,908

201,764

2016

220,642

317,302

209,274

SOURCE: NRC analysis.

TABLE E-2 Behavioral Sciences Workforce Projections for All Scenarios

 

BEHAVIORAL

 

Scenario 1

Scenario 2

Scenario 3

2006

124,292

124,292

124,292

2007

127,049

128,501

125,660

2008

130,079

133,351

127,051

2009

133,414

138,958

128,465

2010

137,091

145,459

129,906

2011

141,149

153,018

131,373

2012

145,634

161,832

132,871

2013

150,599

172,137

134,399

2014

156,100

184,214

135,962

2015

162,203

198,404

137,561

2016

168,983

215,115

139,198

SOURCE: NRC analysis.

TABLE E-3 Clinical Sciences Workforce Projections for All Scenarios

 

CLINICAL

 

Scenario 1

Scenario 2

Scenario 3

2006

35,320

35,320

35,320

2007

36,327

36,859

36,291

2008

37,441

38,654

37,319

2009

38,680

40,763

38,408

2010

40,061

43,256

39,562

2011

41,605

46,221

40,785

2012

43,335

49,765

42,082

2013

45,279

54,024

43,456

2014

47,470

59,162

44,913

2015

49,943

65,388

46,458

2016

52,743

72,957

48,097

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×
FIGURE E-5 Breakout of biomedical sciences workforce, 2006-2016, scenario 1.

FIGURE E-5 Breakout of biomedical sciences workforce, 2006-2016, scenario 1.

SOURCE: NRC analysis.

TABLE E-4 Breakout of Biomedical Sciences Workforce, 2006-2016, Scenario 1

 

BIOMEDICAL - SCENARIO 1 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

80,268

45,828

23,636

10,121

2007

81,782

46,989

23,943

10,236

2008

83,502

48,218

24,337

10,366

2009

85,455

49,522

24,848

10,515

2010

87,675

50,906

25,517

10,684

2011

90,198

52,378

26,401

10,876

2012

93,066

53,946

27,577

11,095

2013

96,327

55,618

29,147

11,345

2014

100,034

57,403

31,254

11,629

2015

104,250

59,312

34,091

11,953

2016

109,044

61,356

37,919

12,322

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×
FIGURE E-6 Breakout of behavioral sciences workforce, 2006-2016, scenario 1.

FIGURE E-6 Breakout of behavioral sciences workforce, 2006-2016, scenario 1.

SOURCE: NRC analysis.

TABLE E-5 Breakout of Behavioral Sciences Workforce, 2006-2016, Scenario 1

 

BEHAVIORAL - SCENARIO 1 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

57,593

62,758

1,457

2,484

2007

58,495

64,335

1,464

2,755

2008

59,471

66,066

1,471

3,071

2009

60,525

67,971

1,478

3,440

2010

61,665

70,069

1,485

3,871

2011

62,897

72,384

1,492

4,375

2012

64,230

74,941

1,499

4,964

2013

65,671

77,770

1,507

5,652

2014

67,229

80,901

1,514

6,457

2015

68,914

84,371

1,521

7,398

2016

70,736

88,221

1,529

8,498

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×
FIGURE E-7 Breakout of clinical sciences workforce, 2006-2016, scenario 1.

FIGURE E-7 Breakout of clinical sciences workforce, 2006-2016, scenario 1.

SOURCE: NRC analysis.

TABLE E-6 Breakout of Clinical Sciences Workforce, 2006-2016, Scenario 1

 

CLINICAL - SCENARIO 1 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

9,457

14,706

6,359

4,798

2007

9,737

15,368

6,378

4,844

2008

10,055

16,096

6,398

4,893

2009

10,417

16,902

6,417

4,944

2010

10,829

17,797

6,436

4,998

2011

11,299

18,794

6,456

5,056

2012

11,835

19,909

6,475

5,116

2013

12,446

21,159

6,495

5,179

2014

13,143

22,566

6,515

5,246

2015

13,938

24,154

6,534

5,317

2016

14,846

25,952

6,554

5,391

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

DEMOGRAPHIC DETAILS FOR SCENARIO 2 (HIGH RISK)

Figure E-8 shows the projections for each of the four demographic groups for the biomedical sciences workforce for Scenario 2 in bar-graph form, and Table E-7 shows the same projections in table form.

FIGURE E-8 Breakout of biomedical sciences workforce, 2006-2016, scenario 2.

FIGURE E-8 Breakout of biomedical sciences workforce, 2006-2016, scenario 2.

SOURCE: NRC analysis.

TABLE E-7 Breakout of Biomedical Sciences Workforce, 2006-2016, Scenario 2

 

BIOMEDICAL - SCENARIO 2 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

80,268

45,828

23,636

10,121

2007

82,594

47,588

24,119

10,297

2008

85,406

49,507

24,820

10,511

2009

88,808

51,605

25,863

10,770

2010

92,923

53,908

27,439

11,084

2011

97,903

56,441

29,852

11,466

2012

103,933

59,238

33,578

11,929

2013

111,235

62,333

39,367

12,490

2014

120,078

65,769

48,398

13,171

2015

130,791

69,591

62,528

13,998

2016

143,771

73,855

84,676

15,000

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

Figure E-9 shows the projections for each of the four demographic groups for the behavioral sciences workforce for Scenario 2 in bar-graph form, and Table E-8 shows the same projections in table form.

FIGURE E-9 Breakout of behavioral sciences workforce, 2006-2016, scenario 2.

FIGURE E-9 Breakout of behavioral sciences workforce, 2006-2016, scenario 2.

SOURCE: NRC analysis.

TABLE E-8 Breakout of Behavioral Sciences Workforce, 2006-2016, Scenario 2

 

BEHAVIORAL - SCENARIO 2 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

57,593

62,758

1,457

2,484

2007

58,966

65,165

1,467

2,902

2008

60,509

67,936

1,478

3,429

2009

62,242

71,135

1,489

4,092

2010

64,190

74,842

1,499

4,928

2011

66,378

79,148

1,510

5,982

2012

68,838

84,162

1,521

7,311

2013

71,602

90,014

1,532

8,988

2014

74,710

96,856

1,544

11,105

2015

78,204

104,868

1,555

13,778

2016

82,132

114,264

1,567

17,154

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

Figure E-10 shows the projections for each of the four demographic groups for the clinical sciences workforce for Scenario 2 in bar-graph form, and Table E-9 shows the same projections in table form.

FIGURE E-10 Breakout of clinical sciences workforce, 2006-2016, scenario 2.

FIGURE E-10 Breakout of clinical sciences workforce, 2006-2016, scenario 2.

SOURCE: NRC analysis.

TABLE E-9 Breakout of Clinical Sciences Workforce, 2006-2016, Scenario 2.

 

CLINICAL - SCENARIO 2 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

9,457

14,706

6,359

4,798

2007

9,887

15,716

6,388

4,868

2008

10,408

16,886

6,417

4,944

2009

11,040

18,252

6,446

5,026

2010

11,808

19,859

6,475

5,115

2011

12,741

21,765

6,505

5,211

2012

13,877

24,040

6,534

5,315

2013

15,259

26,773

6,564

5,427

2014

16,943

30,076

6,594

5,549

2015

18,995

34,088

6,624

5,682

2016

21,496

38,982

6,654

5,825

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

DEMOGRAPHIC DETAILS FOR SCENARIO 3 (LOW RISK)

Figure E-11 shows the projections for each of the four demographic groups for the biomedical sciences workforce for Scenario 3 in bar-graph form, and Table E-10 shows the same projections in table form.

FIGURE E-11 Breakout of biomedical sciences workforce, 2006-2016, scenario 3.

FIGURE E-11 Breakout of biomedical sciences workforce, 2006-2016, scenario 3.

SOURCE: NRC analysis.

TABLE E-10 Breakout of Biomedical Sciences Workforce, 2006-2016, Scenario 3

 

BIOMEDICAL - SCENARIO 3 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

80,268

45,828

23,636

10,121

2007

80,747

46,823

24,295

11,060

2008

81,255

47,858

25,008

12,175

2009

81,792

48,934

25,776

13,494

2010

82,358

50,051

26,602

15,052

2011

82,953

51,211

27,490

16,889

2012

83,577

52,416

28,444

19,052

2013

84,230

53,666

29,465

21,597

2014

84,913

54,963

30,559

24,588

2015

85,626

56,308

31,730

28,101

2016

86,369

57,702

32,981

32,223

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

Figure E-12 shows the projections for each of the four demographic groups for the behavioral sciences workforce for Scenario 3 in bar-graph form, and Table E-11 shows the same projections in table form.

FIGURE E-12 Breakout of behavioral sciences workforce, 2006-2016, scenario 3.

FIGURE E-12 Breakout of behavioral sciences workforce, 2006-2016, scenario 3.

SOURCE: NRC analysis.

TABLE E-11 Breakout of Behavioral Sciences Workforce, 2006-2016, Scenario 3

 

BEHAVIORAL - SCENARIO 3 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

57,593

62,758

1,457

2,484

2007

57,491

63,830

1,605

2,735

2008

57,391

64,907

1,750

3,003

2009

57,293

65,990

1,892

3,291

2010

57,197

67,078

2,031

3,600

2011

57,102

68,172

2,167

3,932

2012

57,010

69,273

2,301

4,287

2013

56,920

70,379

2,432

4,669

2014

56,831

71,493

2,560

5,078

2015

56,744

72,613

2,686

5,518

2016

56,659

73,739

2,809

5,991

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

Figure E-13 shows the projections for each of the four demographic groups for the clinical sciences workforce for Scenario 3 in bar-graph form, and Table E-12 shows the same projections in table form.

FIGURE E-13 Breakout of clinical sciences workforce, 2006-2016, scenario 3.

FIGURE E-13 Breakout of clinical sciences workforce, 2006-2016, scenario 3.

SOURCE: NRC analysis.

TABLE E-12 Breakout of Clinical Sciences Workforce, 2006-2016, Scenario 3

 

CLINICAL - SCENARIO 3 DETAILS

 

US Male

US Female

Foreign Male

Foreign Female

2006

9,457

14,706

6,359

4,798

2007

9,591

15,283

6,439

4,978

2008

9,728

15,890

6,520

5,181

2009

9,869

16,528

6,604

5,408

2010

10,013

17,199

6,689

5,661

2011

10,160

17,904

6,777

5,944

2012

10,311

18,645

6,866

6,259

2013

10,466

19,424

6,958

6,608

2014

10,624

20,242

7,052

6,995

2015

10,785

21,101

7,148

7,424

2016

10,950

22,004

7,246

7,897

SOURCE: NRC analysis.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

DESCRIPTION OF DATA USED FOR WORKFORCE PROJECTIONS

Table E-13 shows the data for U.S.-trained Ph.D.s. In Table E-13, the values in the rightmost columns are the average annual growth rates using the past 5 years of data (i.e., 2001 to 2006) and the past 7 years of data (i.e., 1999 to 2006). The numbers in these columns that are shaded gray are the annual growth rates used for those demographic groups in the workforce projections. To mitigate large changes, the smaller of the two annual growth rates is typically used, or the most reasonable value is used based on inspection.

TABLE E-13 Data for U.S.-Trained Ph.D.s

SOURCE: Data adapted from National Science Foundation Survey of Doctoral Recipients, 1995-2006.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

Table E-14 shows the data for foreign-trained Ph.D.s. It should be noted that information regarding foreign-trained Ph.D. students is not as well documented as the information for U.S.-trained Ph.D. students. In Table E-14, the values in the rightmost column are the average annual growth rates using the past 3 years of data (e.g., 2003 to 2006) because there are no data available for 2001. These are the annual growth rates used for the various foreign-trained Ph.D. groups in the workforce projections. Where there are “blanks” in the 2003 or 2006 data, values have been assumed to be the same as either the preceding data or the succeeding data. These cells are shaded gray and will show no growth between 2003 and 2006 because the same numbers are used for both years.

TABLE E-14 Data for Foreign-Trained Ph.D.s

SOURCE: Dara adopted from National Science Foundation Survey of College Graduates, 1995-2006.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

DESCRIPTION OF SYSTEM DYNAMICS MODELS

System dynamics (SD) is the application of feedback control systems principles and techniques to managerial, organizational, and socioeconomic problems. As such, the methodology seeks to bring together multiple views or aspects of the same problem under study and integrate them into a conceptual and meaningful whole. In fact, most difficulties to fully understanding complex issues arise from looking independently at various elements of an issue instead of considering pertinent interrelations. Consequently, optimization is sought for each separate element in the system, which inadvertently leads to sub-optimization of total system performance. With SD, it is possible to take hypotheses about the separate parts of a system, to combine them in a computer simulation model, and to learn both the “local” and “global” consequences of decisions and actions, as well as the impact of these decisions and actions on short-term and long-term performance. Most of the time, the impact on short-term and long-term performance are opposite: an action that looks positive in the short-term is often very detrimental in the long-term. Conversely, an action that produces favorable long-term performance must usually suffer poor performance in the short-term.

SD extends modeling methods traditionally associated with engineering design and feedback control theory into the arena of policy evaluation and management decision making. The following characteristics distinguish SD models from traditional decision support methodologies:

  • Its building blocks are feedback loops;

  • It can accommodate non-linear relationships among variables;

  • It enforces causality;

  • It can include delays;

  • It can model “soft” variables;

  • It can model management policies; and

  • It presents a dynamic environment for decision analysis.

These characteristics are important because they allow SD models to capture the key structural relationships that define a social system. The structure, in turn, produces the dynamic behavior of interest. The resulting simulation mirrors reality because the underlying model structure includes the appropriate feedback loops, causality, delays, and other relationships. SD models include real-world causal logic, which allows someone to trace through the model to see why things happen the way they do.

The SD modeling and simulation approach is different from traditional statistical approaches in several ways. First, the models are more realistic because they capture cause-and-effect linkages, feedback loops, delays, non-linear relationships, and management policies. Second, the simulations are more accurate and reliable because they provide a sanity check on assumptions and are more rigorous than mental models or spreadsheets, allow for analysis of a wider range of issues, and identify the actions that are most effective (and least effective) for improving performance. Third, communication is more effective because the approach is graphical (the connections are easily seen and understood), logical (the results can be traced back to their root causes), and experiential (we learn best by doing and simulation is a good substitute for the real world).

In SD models, a “stock” and “flow” methodology is used in which stocks represent accumulations of “things” (e.g., people, inventory), and flows are the movement of these “things” into, out of, and between stocks (Figure E-14). For Scenario 1 (moderate risk) and Scenario 2 (high risk), a very basic SD model was used in which the stocks represent groups of people in the following categories (which were established based on available data):

  • In Science and Engineering (S&E)—The number of people employed in science and engineering positions (not considered postdoctorates).

  • Out of S&E—The number of people employed in areas other than science and engineering.

  • Unemp Seeking Work—The number of people currently unemployed but are seeking work.

  • Unemp Not Seeking Work—The number of people currently unemployed but not seeking work, but are not retired.

  • Retired—The number of people currently retired.

  • Postdoctorate—The number of people employed as postdoctorates.

The total number of people considered in the “workforce” is the sum of all people that are not retired. Thus, the workforce for any particular demographic group (e.g., U.S.-trained males in biomedical science) is the following:


Workforce = In S&E + Out of S&E + Unemp Seeking Work + Unemp Not Seeking Work + Postdoctorate


The flows in and out of the stocks (e.g., In 1, Out 1) are based on growth rates determined from the data for the specific demographic group and shown earlier in Tables E-13 and E-14. If the growth rate is greater than zero (i.e., positive), then people are added to the stock through the In flow. If the growth rate is less than zero (i.e., negative), then people are removed from the stock through the Out flow. The amount of people that are added or removed is based on the percentage growth rate multiplied by the current number of people in the stock. For example, if 100 people were in a stock and the growth rate is 5 percent, then 5 people would be added to the stock during that simulation step.

Figure E-14 below shows this stock-and-flow diagram for the U.S.-trained males in biomedical science. This exact same model structure is used for all other demographic

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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FIGURE E-14 Model for U.S.-trained males in biomedical science for scenarios 1 and 2.

FIGURE E-14 Model for U.S.-trained males in biomedical science for scenarios 1 and 2.

groups (e.g., U.S.-trained females in biomedical science, foreign-trained males in clinical science, etc.). However, different data are used to initialize the model based on which specific demographic group is being modeled.

For Scenario 3, a slightly different stock-and-flow structure is used that includes more of the “supply pipeline” (Figure E-15). For each demographic group, a stock of Ph.D. students is also included that precedes the stock for the entire workforce. (At this point, because the data for Ph.D. students is aggregate, the workforce is represented as aggregate to maintain consistency, as opposed to multiple portions of the workforce as in Scenarios 1 and 2 and in Figure E-14.) The inclusion of the supply pipeline in Scenario 3 is the reason that this scenario is considered low risk. Adding the Ph.D. student pool produces limits to the growth of the following workforce, which is more realistic than letting the workforce

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×
FIGURE E-15 Model for U.S.-trained females in biomedical science for scenario 3.

FIGURE E-15 Model for U.S.-trained females in biomedical science for scenario 3.

continue to grow (or shrink) at its current pace. Consequently, the workforce projection numbers are lower for all three major workforces (i.e., biomedical science, clinical science, and behavioral science).

In the pipeline model for each demographic group, the model starts with the number of Ph.D. students and uses the growth rate for Ph.D. students to determine how many Ph.D. students enter the Ph.D. pool. The Avg Grad Length then determines how quickly students move through the Ph.D. pool to enter the workforce. For the purposes of this analysis, the average graduation time is assumed to be 7 years. Thus, 1/7th of the Ph.D. pool enters the workforce each year. For the Workforce, the Avg Work Length determines how many people retire or move out of the workforce each year. For the purposes of this analysis, the average time that someone spends in the workforce is assumed to be 50 years. Thus, 1/50th of the people leave the workforce each year of the simulation.

Table E-15 shows the data used for the Ph.D. pipeline model. The values in the rightmost columns are the average annual growth rates using the past 5 years of data (i.e., 2001 to 2006), as highlighted by the gray shaded cells. The 5-year average annual growth rates are the ones used in the Scenario 3 model for the growth of the Ph.D. student population.

It should be noted that the pipeline model is not complete. Additional stocks could precede the Ph.D. pool (e.g., undergraduate students, K-12 students, etc.) to represent the full pipeline of students progressing up to employment in the workforce. In addition, based on detailed data for the Ph.D. pool, several pipeline models could be used to show the movement through the pipelines for the fields of science, engineering, etc. in addition to the separation of male/female and U.S./foreign.

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
×

TABLE E-15 Ph.D. Data Used in Scenario 3

Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Suggested Citation:"Appendix E: Demographic Projections of the Research Workforce in the Biomedical, Clinical, and Behavioral Sciences, 2006-2016 (Using the System Dynamics Simulation Methodology)." National Research Council. 2011. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. Washington, DC: The National Academies Press. doi: 10.17226/12983.
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Comprehensive research and a highly-trained workforce are essential for the improvement of health and health care both nationally and internationally. During the past 40 years the National Research Services Award (NRSA) Program has played a large role in training the workforce responsible for dramatic advances in the understanding of various diseases and new insights that have led to more effective and targeted therapies. In spite of this program, the difficulty obtaining jobs after the postdoc period has discouraged many domestic students from pursuing graduate postdoc training. In the United States, more than 50 percent of the postdoc workforce is made up of individuals who obtained their Ph.D.s from other countries. Indeed, one can make a strong argument that the influx of highly trained and creative foreigners has contributed greatly to U.S. science over the past 70 years.

Research Training in the Biomedical, Behavioral, and Clinical Research Sciences discusses a number of important issues, including: the job prospects for postdocs completing their training; questions about the continued supply of international postdocs in an increasingly competitive world; the need for equal, excellent training for all graduate students who receive NIH funding; and the need to increase the diversity of trainees. The book recommends improvements in minority recruiting, more rigorous and extensive training in the responsible conduct of research and ethics, increased emphasis on career development, more attention to outcomes, and the requirement for incorporating more quantitative thinking in the biomedical curriculum.

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