Assessment of Scientific Communication Self-efficacy,Interest,and Outcome Expectations for Career Development in Academic Medicine

Abstract

Competency in forms of scientific communication, both written and spoken, is essential for success in academic science. This study examined the psychometric properties of three new measures, based on social cognitive career theory, that are relevant to assessment of skill and perseverance in scientific communication. Pre- and postdoctoral trainees in biomedical science (N = 411) completed online questionnaires assessing self-efficacy in scientific communication, career outcome expectations, and interest in performing tasks in scientific writing, oral presentation, and impromptu scientific discourse. Structural equation modeling was used to evaluate factor structures and model relations. Confirmatory factor analysis supported a 22-item, 3-factor measure of self-efficacy; an 11-item, 2-factor measure of outcome expectations; and a 12-item, 3-factor measure of interest in scientific communication activities. Construct validity was further demonstrated by theory-consistent inter-factor relations and relations with typical communications performance behaviors (e.g., writing manuscripts, abstracts, and presenting at national meetings).

Keywords

scientific communication social cognitive theory SCCT career development academic medicine scale development measurement LISREL

Get full access to this article

View all access options for this article.

References

Bandalos

D. L.

(2002). The effects of item parceling on goodness-of-fit and parameter estimate bias in structural equation modeling. Structural Equation Modeling, 9, 78–102. doi:10.1207/S15328007SEMO901__5

Bandura

(1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215. doi:10.1037/0033-295x.84.2.191

Bandura

(1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.

Bandura

(1997). Self-efficacy: The exercise of control. New York, NY: W.H. Freeman.

Bentler

P. M.

(1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. doi:10.1037/0033-2909.88.3.588

Bentler

P. M.

Bonnett

D. G.

(1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606. doi:10.1037/0033-2909.88.3.588

Bentler

P. M.

Chou

(1987). Practical issues in structural modeling. Sociological Methods and Research, 16, 78–117. doi:10.1177/0049124187016001004

Browne

M. W.

Cudeck

(1993). Alternative ways of assessing model fit. In Bollen

K. A.

Long

J. S.

(Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.

Bryant

F. B.

(2013). EXCEL macro file for conducting Bryant-Satorra chi-square difference test via LISREL 8. Retrieved from http://www.econ.upf.edu/~satorra/

10.

Bryant

F. B.

Satorra

(2012). Principles and practice of scaled difference chi-square testing. Structural Equation Modeling, 19, 372–398. doi:10.1080/10705511.2012.687671

11.

Byars-Winston

Estrada

Howard

Davis

Zalapa

(2010). Influence of social cognitive and ethnic variables on academic goals of underrepresented students in science and engineering: A multiple groups analysis. Journal of Counseling Psychology, 57, 205–218. doi:10.1037/a0018608

12.

Cameron

Collie

C. L.

Baldwin

C. D.

Bartholomew

L. K.

Palmer

J. L.

Greer

Chang

(2013). The development of scientific communication skills: A qualitative study of the perceptions of trainees and their mentors. Academic Medicine, 88, 1499–1506. doi:10.1097/ACM.0b013e3182a34f36

13.

Cameron

Lee

H. Y.

Anderson

C. B.

Byars-Winston

Baldwin

C. D.

Chang

(2015). The role of scientific communication skills in trainees’ intention to pursue academic careers in biomedical research: A social cognitive analysis. CBE-Life Sciences Education, 14, 1–12. doi:10.1187/cbe.14-09-0152.

14.

Dores

G. M.

Chang

Berger

V. W.

Perkins

S. N.

Hursting

S. D.

Weed

D. L.

(2006). Evaluating research training outcomes: Experience from the Cancer Prevention Fellowship Program at the National Cancer Institute. Academic Medicine, 81, 535–541. doi:10.1097/01.ACM.0000225216.07584.60

15.

Fouad

N. A.

Guillen

(2006). Outcome expectations: Looking to the past and potential future. Journal of Career Assessment, 14, 130–142. doi:10.1177/1069072705281370

16.

Hackett

Betz

N. E.

Casas

J. M.

Rocha-Singh

I. A.

(1992). Gender, ethnicity, and social cognitive factors predicting the academic achievement of students in engineering. Journal of Counseling Psychology, 39, 527–538. doi:10.1037/0022-0167.39.4.527

17.

Bentler

P. M.

(1995). Evaluating model fit. In Hoyle

R. H.

(Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 76–99). Thousand Oaks, CA: Sage.

18.

Bentler

P. M.

(1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. doi:10.1080/10705519909540118

19.

Jöreskog

K. G.

Sörbom

(2006). LISREL 8.80. Chicago, IL: Scientific Software International, Inc.

20.

Kline

R. B.

(2005). Principles and practice of structural equation modeling. 2nd ed. New York, NY: Guildford Press.

21.

Lent

R. W.

Brown

(2008). Social cognitive career theory and subjective well-being in the context of work. Journal of Career Assessment, 16, 6–21. doi:10.1177/1069072707305769

22.

Lent

R. W.

Brown

S. D.

(2006). On conceptualizing and assessing social cognitive constructs in career research: A measurement guide. Journal of Career Assessment, 14, 12–35. doi:10.1177/1069072705281364

23.

Lent

R. W.

Brown

S. D.

Brenner

Chopra

S. B.

Davis

Talleyrand

Suthakaran

(2001). The role of contextual supports and barriers in the choice of math/science educational options: A test of social cognitive hypotheses. Journal of Counseling Psychology, 48, 474–483. doi:10.1037/0022-0167.48.4.474

24.

Lent

R. W.

Brown

S. D.

Hackett

(1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45, 79–122. doi:10.1006/jvbe.1994.1027

25.

Lent

R. W.

Brown

S. D.

Hackett

(2000). Contextual supports and barriers to career choice: A social cognitive analysis. Journal of Counseling Psychology, 47, 36–49. doi:10.1037/0022-0167.47.1.36

26.

Lent

R. W.

Brown

S. D.

Larkin

K. C.

(1984). Relation of self-efficacy expectations to academic achievement and persistence. Journal of Counseling Psychology, 31, 356–362. doi:10.1037/0022-0167.31.3.356

27.

Lent

R. W.

Brown

S. D.

Larkin

K. C.

(1986). Self-efficacy in the prediction of academic performance and perceived career options. Journal of Counseling Psychology, 33, 265–269. doi:10.1037/0022-0167.33.3.265

28.

Lent

R. W.

Brown

S. D.

Schmidt

Brenner

Lyons

Treistman

(2003). Relation of contextual supports and barriers to choice behavior in engineering majors: Test of alternative social cognitive models. Journal of Counseling Psychology, 50, 458–465. doi:10.1037/0022-0167.50.4.458

29.

Lent

R. W.

Brown

S. D.

Sheu

Schmidt

Brenner

B. R.

Gloster

C. S.

Treistman

Dana.

(2005). Social cognitive predictors of academic interests and goals in engineering: Utility for women and students at historically Black universities. Journal of Counseling Psychology, 52, 84–92. doi:10.1037/0022-0167.52.1.84

30.

Lent

R. W.

Larkin

K. C.

Brown

S. D.

(1989). Relation of self-efficacy to inventoried vocational interests. Journal of Vocational Behavior, 34, 279–288. doi:10.1016/0001-8791(89)90020-1

31.

Lent

R. W.

Lopez

A. M.

Jr Lopez

F. G.

Sheu

H.-B.

(2008). Social cognitive career theory and the prediction of interests and choice goals in the computing disciplines. Journal of Vocational Behavior, 73, 52–62. doi:10.1016/j.jvb.2008.01.002

32.

Marsh

H. W.

Balla

J. R.

McDonald

R. P.

(1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103, 391–410. doi:10.1037/0033-2909.103.3.391

33.

Marsh

H. W.

Lüdtke

Nagengast

Morin

A. J. S.

von Davier

(2013). Why item parcels are (almost) never appropriate: Two wrongs do not make a right-camouflaging misspecification with item parcels in CFA models. Psycholgical Methods, 18, 257–284. doi:10.1037/a0032773

34.

Marsh

H. W.

O’Neill

(1984). Self-description questionnaire III: The construct validity of multidimensional self-concept ratings by late adolescents. Journal of Educational Measurement, 21, 153–174. doi:10.1111/j.1745-3984.tb00227.x

35.

Mills

B. A.

Caetano

Rhea

A. E.

(2014). Factor structure of the Clinical Research Appraisal Inventory (CRAI). Evaluation & the Health Professions, 37, 71–82. doi:10.1177/0163278713500303

36.

Mullikin

E. A.

Bakken

L. L.

Betz

N. E.

(2007). Assessing research self-efficacy in physician-scientists: The Clinical Research Appraisal Inventory. Journal of Career Assessment, 15, 367–387. doi:10.1177/1069072707301232

37.

National Institute of General Medical Sciences. (2013). Research to understand and inform interventions that promote the research careers of students in biomedical and behavioral sciences. NIH Guide. Retrieved from http://grants.nih.gov/grants/guide/rfa-files/RFA-GM-14-013.html

38.

Satorra

Bentler

P. M.

(1988). Scaling corrections for chi-square statistics in covariance structure analysis. American Statistical Association 1988 proceedings of the business & economics section (pp. 308–313) Alexandria, VA: American Statistical Association.

39.

Satorra

Bentler

P. M.

(2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66, 507–514. Retrieved from http://www.statmodel.com/chidiff.shtml