J Educ Eval Health Prof.  2018;15:19. 10.3352/jeehp.2018.15.19.

A novel tool for evaluating non-cognitive traits of doctor of physical therapy learners in the United States

• Roll M
• Canham L
• Salamh P
• Covington
• Simon C
• Cook C

• KMID: 2439275
• DOI: http://doi.org/10.3352/jeehp.2018.15.19

Abstract

PURPOSE
The primary aim of this study was to develop a survey addressing an individual's non-cognitive traits, such as emotional intelligence, interpersonal skills, social intelligence, psychological flexibility, and grit. Such a tool would provide beneficial information for the continued development of admissions standards and would help better capture the full breadth of experience and capabilities of applicants applying to doctor of physical therapy (DPT) programs.
METHODS
This was a cross-sectional survey study involving learners in DPT programs at 3 academic institutions in the United States. A survey was developed based on established non-proprietary, non-cognitive measures affiliated with success and resilience. The survey was assessed for face validity, and exploratory factor analysis (EFA) was used to identify subgroups of factors based on responses to the items.
RESULTS
A total of 298 participants (90.3%) completed all elements of the survey. EFA yielded 39 items for dimensional assessment with regression coefficients <0.4. Within the 39 items, 3 latent constructs were identified: adaptability (16 items), intuitiveness (12 items), and engagement (11 items).
CONCLUSION
This preliminary non-cognitive assessment survey will be able to play a valuable role in DPT admissions decisions following further examination and refinement.

Keyword

School admission criteria; Physical therapists; Statistical factor analysis; United States

MeSH Terms

Cross-Sectional Studies
Emotional Intelligence
Factor Analysis, Statistical
Humans
Physical Therapists
Pliability
Reproducibility of Results
School Admission Criteria
Social Skills
United States*

Reference

References

1. Cook C. 20th Pauline Cerasoli lecture: the Sunk Cost Fallacy. J Phys Ther Educ. 2017; 31:10–14. https://doi.org/10.1097/00001416-201731030-00005.

2. Megginson L. Noncognitive constructs in graduate admissions: an integrative review of available instruments. Nurse Educ. 2009; 34:254–261. https://doi.org/10.1097/NNE.0b013e3181bc7465.

3. Sharon D, Grinberg K. Does the level of emotional intelligence affect the degree of success in nursing studies? Nurse Educ Today. 2018; 64:21–26. https://doi.org/10.1016/j.nedt.2018.01.030.

4. Cook CJ, Cook CE, Hilton TN. Does emotional intelligence influence success during medical school admissions and program matriculation?: a systematic review. J Educ Eval Health Prof. 2016; 13:40. https://doi.org/10.3352/jeehp.2016.13.40.

5. Koenig TW, Parrish SK, Terregino CA, Williams JP, Dunleavy DM, Volsch JM. Core personal competencies important to entering students’ success in medical school: what are they and how could they be assessed early in the admission process? Acad Med. 2013; 88:603–613. https://doi.org/10.1097/ACM.0b013e31828b3389.

6. Guffey JS, Farris JW, Aldridge R, Thomas T. An evaluation of the usefulness of noncognitive variables as predictors of scores on the national physical therapy licensing examination. J Allied Health. 2002; 31:78–86.

7. Schutte NS, Malouff JM, Hall LE, Haggerty DJ, Cooper JT, Golden CJ, Dornheim L. Development and validation of a measure of emotional intelligence. Pers Individ Dif. 1998; 25:167–177. https://doi.org/10.1016/S0191-8869(98)00001-4.

8. Davis MH. A multidimensional approach to individual differences in empathy. JSAS Cat Sel Doc Psychol. 1980; 10:85.

9. Buhr K, Dugas MJ. The Intolerance of Uncertainty Scale: psychometric properties of the English version. Behav Res Ther. 2002; 40:931–945. https://doi.org/10.1016/S0005-7967(01)00092-4.

10. Frankovsky M, Birknerova Z. Measuring social intelligence-the MESI methodology. Asian Soc Sci. 2014; 10:90–97. https://doi.org/10.5539/ass.v10n6p90.

11. Ben-Itzhak S, Bluvstein I, Maor M. The psychological flexibility questionnaire (PFQ): development, reliability and validity. Webmed Cent Psychol. 2014; 5:WMC004606. https://doi.org/10.9754/journal.wmc.2014.004606.

12. Duckworth AL, Quinn PD. Development and validation of the short grit scale (grit-s). J Pers Assess. 2009; 91:166–174. https://doi.org/10.1080/00223890802634290.

13. Salovey P, Mayer JD. Emotional intelligence. Imagin Cogn Pers. 1990; 9:185–211. https://doi.org/10.2190/dugg-p24e-52wk-6cdg.

14. Enns A, Eldridge GD, Montgomery C, Gonzalez VM. Perceived stress, coping strategies, and emotional intelligence: a cross-sectional study of university students in helping disciplines. Nurse Educ Today. 2018; 68:226–231. https://doi.org/10.1016/j.nedt.2018.06.012.

15. Hojat M, Mangione S, Kane GC, Gonnella JS. Relationships between scores of the Jefferson Scale of Physician Empathy (JSPE) and the Interpersonal Reactivity Index (IRI). Med Teach. 2005; 27:625–628. https://doi.org/10.1080/01421590500069744.

16. Yu J, Kirk M. Evaluation of empathy measurement tools in nursing: systematic review. J Adv Nurs. 2009; 65:1790–1806. https://doi.org/10.1111/j.1365-2648.2009.05071.x.

17. Sherrill WW. Tolerance of ambiguity among MD/MBA students: implications for management potential. J Contin Educ Health Prof. 2001; 21:117–122. https://doi.org/10.1002/chp.1340210209.

18. Hillen MA, Gutheil CM, Strout TD, Smets EM, Han PK. Tolerance of uncertainty: conceptual analysis, integrative model, and implications for healthcare. Soc Sci Med. 2017; 180:62–75. https://doi.org/10.1016/j.socscimed.2017.03.024.

19. Allison JJ, Kiefe CI, Cook EF, Gerrity MS, Orav EJ, Centor R. The association of physician attitudes about uncertainty and risk taking with resource use in a Medicare HMO. Med Decis Making. 1998; 18:320–329. https://doi.org/10.1177/0272989x9801800310.

20. Wayne S, Dellmore D, Serna L, Jerabek R, Timm C, Kalishman S. The association between intolerance of ambiguity and decline in medical students’ attitudes toward the underserved. Acad Med. 2011; 86:877–882. https://doi.org/10.1097/ACM.0b013e31821dac01.

21. Bar-On R. The Bar-On model of emotional-social intelligence (ESI). Psicothema. 2006; 18 Suppl:13–25.

22. Marlow SL, Hughes AM, Sonesh SC, Gregory ME, Lacerenza CN, Benishek LE, Woods AL, Hernandez C, Salas E. A systematic review of team training in health care: ten questions. Jt Comm J Qual Patient Saf. 2017; 43:197–204. https://doi.org/10.1016/j.jcjq.2016.12.004.

23. Salas E, Zajac S, Marlow SL. Transforming health care one team at a time: ten observations and the trail ahead. Group Organ Manag. 2018; 43:357–381. https://doi.org/10.1177/1059601118756554.

24. Lloyd J, Bond FW, Flaxman PE. The value of psychological flexibility: examining psychological mechanisms underpinning a cognitive behavioural therapy intervention for burnout. Work Stress. 2013; 27:181–199. https://doi.org/10.1080/02678373.2013.782157.

25. Duckworth AL, Peterson C, Matthews MD, Kelly DR. Grit: perseverance and passion for long-term goals. J Pers Soc Psychol. 2007; 92:1087–1101. https://doi.org/10.1037/0022-3514.92.6.1087.

26. Stoffel JM, Cain J. Review of grit and resilience literature within health professions education. Am J Pharm Educ. 2018; 82:6150. https://doi.org/10.5688/ajpe6150.

27. MacCallum RC, Widaman KF, Zhang S, Hong S. Sample size in factor analysis. Psychol Methods. 1999; 4:84–99. https://doi.org/10.1037/1082-989X.4.1.84.

28. Field A. Discovering statistics: using SPSS for Windows. London: Sage Publications;2001.

29. Cattell RB. The scree test for the number of factors. Multivariate Behav Res. 1966; 1:245–276. https://doi.org/10.1207/s15327906mbr0102_10.

30. Stevens J. Applied multivariate statistics for the social sciences. Mahwah (NJ): Lawrence Erlbaum Associates;2002.

31. Garson GD. Factor analysis. Asheboro (NC): Statistical Associates Publishers;2013.

32. Richardson M, Abraham C, Bond R. Psychological correlates of university students’ academic performance: a systematic review and metaanalysis. Psychol Bull. 2012; 138:353–387. https://doi.org/10.1037/a0026838.

33. Connolly C, Gubbins C, Murphy E. Non-cognitive influences on trainee learning within the manufacturing industry. In : Proceedings of the 2010 IEEE Transforming Engineering Education: Creating Interdisciplinary Skills for Complex Global Environments; 2010 Apr 6-9; Dublin, Ireland. Piscataway (NJ). Institute of Electrical and Electronics Engineers. 2010. 1–6. https://doi.org/10.1109/TEE.2010.5508954.

34. Osadnik CR, Paynter SL, Maloney SR. Re: admission interview scores are associated with clinical performance in an undergraduate physiotherapy course: an observational study. Physiotherapy. 2016; 102:119–120. https://doi.org/10.1016/j.physio.2015.02.001.

35. Hayward LM, Blackmer B. A model for teaching and assessing core values development in doctor of physical therapy students. J Phys Ther Educ. 2010; 24:16–26. https://doi.org/10.1097/00001416-201007000-00003.

36. Wise D, Dominguez J, Kapasi Z, Williams-York B, Moerchen V, Brooks S, Ross LJ. Defining underrepresented minorities and promoting holistic review admission strategies in physical therapist education. J Phys Ther Educ. 2017; 31:8–13. https://doi.org/10.1097/jte.0000000000000009.

37. Glazer G, Clark A, Bankston K, Danek J, Fair M, Michaels J. Holistic admissions in nursing: we can do this. J Prof Nurs. 2016; 32:306–313. https://doi.org/10.1016/j.profnurs.2016.01.001.

38. Urban Universities for Health. Holistic admissions in the health professions: findings from a national survey [Internet]. Washington (DC): Urban Universities for Health;2014. [cited 2018 Feb 02]. Available from: http://urbanuniversitiesforhealth.org/media/documents/Holistic_Admissions_in_the_Health_Professions.pdf.

39. Kappe R, van der Flier H. Predicting academic success in higher education: what’s more important than being smart? Eur J Psychol Educ. 2012; 27:605–619. https://doi.org/10.1007/s10212-011-0099-9.

40. Niessen AS, Meijer RR, Tendeiro JN. Measuring non-cognitive predictors in high-stakes contexts: the effect of self-presentation on selfreport instruments used in admission to higher education. Pers Individ Dif. 2017; 106:183–189. https://doi.org/10.1016/j.paid.2016.11.014.