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Abstract

Objective:

Since most health care programs have competitive entry and selective admission procedures, it is essential for colleges to select proper admissions tools to ensure student success in the health care programs. The purpose of the study was to determine what relationship exists between emotional intelligence (EI) and clinical success for diagnostic medical sonography (DMS) or radiography (RT) students. The main goal of this work was to explore if an EI model such as the Trait Emotional Intelligence Questionnaire (TEIQue) can be potentially used as one of the criteria in the admission selection process for DMS and RT programs in the future.

Materials and Methods:

The participants of this study were 26 imaging students. The convenient sample included 10 DMS and 16 RT students, enrolled in an Associate Degree in Applied Sciences program, within a community college. The study was conducted by administering the TEIQue questionnaire that collected EI data and demographic data of the participants in both programs. These data were gathered at the beginning of each respective program and 1 calendar year later. The clinical student success was examined over a period of 2 clinical semesters.

Results:

The analysis of the findings determined that a significant relationship existed between all EI variables such a global EI, 4 factors and 3 subscales of trait EI for both groups of students. The findings of this study did not show a significant relationship between clinical success and global EI as well as 3 subscales of trait EI for DMS or RT students. Nevertheless, a statistically significant increase was observed among 1 of the 4 EI factors, well-being, among RT students. Interestingly, DMS students did not show the same outcome.

Conclusion:

The results of this study provide limited empirical evidence that a strong relationship may exist between 1 of the 4 trait EI factors, well-being, among RT students and clinical success in this RT student cohort. This is an important finding that may support the use of the TEIQue questionnaire, as part of the admissions process for other RT programs. The DMS students did not exhibit the same results. However, the findings with the RT students demonstrate the need for further research.

Keywords

emotional intelligence noncognitive variables student success clinical success GPA diagnostic medical sonography radiography

Goleman¹ defined emotional intelligence (EI) as “the capacity for recognizing our own feelings and those of others, for motivating ourselves, and for managing emotions well in ourselves and in our relationships.” Even though there is a significant body of evidence regarding the cognitive selection tools being successful, there is a lack of evidence of noncognitive selection tools. According to Garcia,² cognitive skills are the skills that involve a conscious intellectual effort such as thinking, reasoning, or remembering. There is plenty of evidence in literature indicating that cognitive tools are reliable predictors of academic success, for students enrolled in health care and non–health care programs.^3–6 Yet, Mackay et al⁷ emphasized that clinical education is likely to be a contributing factor in EI skills development in radiography (RT) students and radiographers. Noncognitive or soft skills are defined as the critical thinking skills, problem solving skills, social skills, persistence, creativity, and self-control. Such skills enable individuals to contribute meaningfully to society and to succeed in their public lives, workplaces, homes, and other social settings. According to Kyllonen,⁵ behavioral science research in psychology and economics suggests that noncognitive soft skills such as motivation, work ethic, teamwork, organization, cultural awareness, and effective communication play a more important role in determining success in school and in the workplace than cognitive abilities.

According to Petrides,⁸ the concept of EI can be traced all the way to the 1920s. John Mayer et al⁹ are the developers of the first ability-based EI model in 1990. Later, Daniel Goleman, a psychologist and science writer, claimed that “EI may be the best predictor of success in life.” As a result, more in-depth research on EI and various EI models have been developed such as mental ability, trait, and mixed models.⁷ O’Connor et al¹⁰ emphasized that trait EI tests offer a good prediction of actual behaviors in a range of situations because they measure typical behavior rather than best performance. Some researchers in the literature such as Collins¹¹ proposed that in addition to cognitive “hard data” such as grade point average (GPA) as an admission criterion, there should be a way to measure a candidate’s level of “sensitivity to feelings and needs” of the people around them. Collins¹¹ suggested that perhaps in the future, an EI tool can be potentially utilized as an additional instrument in the admission process.

Many scholars and researchers attempted to determine if EI can be used as a valid and reliable predictor of academic, non-academic or skill-based success measuring understanding and managing emotions in the health care field.^12–16 Nonetheless, there is some contradictory information in the literature that has been gathered to determine whether an additional type of tool such as an EI questionnaire can be used prior to the start of the students’ chosen health care programs to predict their non-academic or clinical success. Most of the EI research studies in the United States examined mostly nursing programs.^14,17 For instance, Sharon and Grinberg found a positive correlation between the level of EI and the degree of success in nursing studies. As a result, it was recommended to include EI as a criterion for admission of students to an undergraduate study program in nursing.¹⁸ Extremely limited literature exists on the topic of EI and its relationship on clinical success among diagnostic medical sonography (DMS) and RT students in the United States. Augusto de Galvão et al¹⁹ did not see significant changes in EI during the nonexplicit EI content curricula within their longitudinal study among RT and radiotherapy students in Hong Kong, the United Kingdom, Ireland, and Australia.

Students in health care programs must possess a certain set of skills that are required for taking care of sick patients and serving them with love, dignity, and respect. Rankin¹⁴ determined that there is a significant predictive relationship between EI and practice performance, academic performance, and retention in the nursing programs. He recommended considering EI as part of recruitment and selection procedures as an additional entrance criterion for nursing students. Furthermore, Chew et al¹⁶ reported that medical students with higher EI scores perform better “in both the continuous assessments and the professional examination.” In addition to academic abilities, it is beneficial for health care students to possess nonacademic abilities necessary to be successful employees in the medical field. Vandewaa et al²⁰ stated that nurses’ abilities such as empathy, problem-solving, interpersonal relationships, and emotional self-awareness were correlated with professionalism, performance level, and intuition. These abilities are some of the EI components and are beneficial to have for nurses in the workplace. For instance, the results of Vandewaa et al²⁰ found that emotionally intelligent nurses demonstrate increased levels of conscientiousness in performing nursing duties, participation in hospital activities as well as altruistic affairs and voluntary organizing efforts at the workplace.

According to Omid et al,²¹ clinical instructors in mentoring and role modeling, communicate with students in a different way than classroom instructors. Clinical instructors utilize role modeling for imitation by students and facilitation of learning of necessary clinical skills. During clinical supervision, students experience professional and personal growth under the supervision of experts in the field. Most clinical education happens in one-to-one communications between a clinical instructor and the student. Clinical instructors’ social and emotional competence or EI influences the outcomes of clinical teaching through 3 factors such as relationship with themselves, with others (patients, students, and patient care professionals), and with context. Socially and emotionally competent clinical instructors have self-awareness and self-management that lead to personal development and well-being.²¹

This study was undertaken to determine if a relationship exists between noncognitive variables such as global trait EI, 4 EI factors, and 3 EI subscales and clinical student success for the students who were enrolled in the DMS and RT programs. This research examined whether there is a relationship between EI and clinical success as the students progressed through the program. The main goal of this work was to explore if an EI model such the TEIQue can be potentially used as one of the criteria in the admission selection process for DMS and RT programs in the future. The outcomes of this study aimed to close the gap in knowledge and help various health care programs with strengthening their selective admission process.

Materials and Methods

This proposed study received institutional review board (IRB) approval to conduct educational research in May 2020. The participants were students who actively attended a DMS or RT program that culminated in an associate degree in applied sciences. The research followed a longitudinal quantitative correlational research design. This study allowed the researcher to evaluate the clinical success of the same cohort of students over 1 calendar year. The data collection took place over the semesters that comprised the school year of 2020–2021. All data gathered remained anonymized throughout the study.

The Participants’ Geographic Area

This study was conducted at a community college located in the state of Illinois. The college’s district spans 7 counties and covers 1,442 square miles, as well as serving students from 44 zip codes. In 2019, the district had a population of 734,761 residents with 370,626 females and 364,315 males. Within the college district, out of 24 public feeder high schools, 3 showed significantly lower income than others. The college enrollment consisted of 56.6% female students and 43.4% male students.²²

The Study’s Participants

The participants of this study were enrolled in a DMS or RT associate degree in applied sciences program, in a community college. The sample included 10 DMS and 16 RT students. A total of 26 students participated in this study.

Participant Selection

The research sample was a convenient sample of students enrolled in the DMS and RT programs. Therefore, all students were asked to voluntarily participate in the study. The selection process did not include randomization. All members of this student cohort were included in the study. The sample consisted of the students who were accepted into the programs utilizing a point-ranking system via an anonymous selection process.

Research Design

The study followed a longitudinal quantitative correlational research design.²³ According to Creswell,²³ a longitudinal research design is a design in which the researcher collects data about trends with the same population and changes in a cohort, over time. A correlational research design can help to predict or explain relationships among variables.²³ Quantitative data were gained from the EI data and GPA of clinical education courses. All participants in this study completed 2 clinical rotations in the hospitals or outpatient centers. The TEIQue questionnaire was used to collect data that measured students EI. The student demographic survey was utilized to collect various demographic and situational variables including student’s age group, sex, race/ethnicity, employment status, level of education, relationship status, and number of children. The survey was administered online due to the COVID-19 pandemic. A SurveyMonkey link to the survey was emailed to the students, along with the consent form. The rate of survey return was 100% for the DMS students and 72.7% from the RT students. Students’ clinical GPA of the selected program courses were used to measure their clinical success throughout the program. Clinical success was measured by achieving a course score of 75% or higher in the clinical courses taken during the program. The researcher evaluated EI scores and clinical success of the same cohort of students over the course of 1 calendar year and explored correlations between these variables.

Data Analysis

The TEIQue is a self-reported questionnaire which provides a comprehensive assessment of the emotional aspects of human personality. It measures 15 trait EI subscales, 4 trait EI factors, and global trait EI. The TEIQue full-form questionnaire was administered at the beginning of the program and 1 calendar year later. The questionnaire comprised of 153 questions utilizing a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).²⁴ Thirteen out of 15 intelligence subscales were grouped into 4 factors: well-being, self-control, emotionality, and sociability. The well-being factor included: self-esteem, happiness, optimism; the self-control factor included: emotional regulation, impulsiveness, stress management; the emotionality factor included: relationships, emotional perception, empathy, emotional expression; and the sociability factor included: emotional management, assertiveness, and social awareness.²⁵ O’Connor et al¹⁰ emphasized that trait EI tests offer a good prediction of actual behaviors in a range of situations because they measure typical behavior rather than best performance. In addition, the TEIQue was chosen to assess trait EI considering both its cross-cultural stability and good psychometric properties, including superior incremental validity when compared with other trait EI measures.²⁶ For example, it has internal consistency or Cronbach’s alpha for the global trait EI score of 0.89.¹⁰ Another factor for choosing this test was that the TEIQue test is available free of charge for academic and clinical research.¹⁰ All data from the TEIQue surveys were entered by the researcher in an Excel spreadsheet template which was downloaded directly from the London Psychometric Laboratory website. Once the template was uploaded, the scoring engine produced a fully scored Excel file that included the Cronbach’s alphas, which is a measure of internal consistency for all TEIQue variables. The London Psychometric Laboratory analyzed the data automatically online by the scoring engine.

For the purposes of analysis, data were divided into 2 main groups: DMS and RT students. The global trait EI score was calculated by averaging all responses of the questionnaire. The global trait EI, 4 EI factors, 3 EI subscales and GPA of 2 clinical semesters were gathered to triangulate data analysis. The independent variable was the EI score. Clinical GPA was the dependent variable that served as an instrument to measure students’ clinical success. All variables provided nominal data. The Statistical Package for the Social Science (SPSS) Version²⁷ was used for data analysis. Statistical analysis required the use of the Shapiro-Wilk test, Pearson and Spearman’s rho correlations to describe characteristics of the student sample.

Results

The sample included 10 DMS and 16 RT students. The total cohort consisted of 38.5% of DMS students and 61.5% RT students. Nine (90%) of the DMS students were female and 1 (10%) was male. Twelve (75%) RT students were female and 4 (25%) were male. The gender bias was likely due to a female dominance of these imaging professions. The participants were of mixed racial backgrounds. Racial demographic data among the DMS students were 8 (80%) white, 1 (10%) Hispanic, and 1 (10%) Asian ethnicity. Racial demographics among the RT students were 10 (62.5%) white, 5 (31.25%) Hispanic, and 1 (6.25%) Asian student.

The number of clinical hours varied between the 2 educational programs. The RT students completed 256 clinical hours, in the first clinical semester and 256 hours in the second semester. The DMS students completed 375 clinical hours, in the first clinical semester and 300 hours in the second semester. Therefore, DMS students completed 163 clinical hours more than RT students throughout the 2 clinical semesters.

Diagnostic Medical Sonography Students

The Shapiro-Wilk test of normality was performed to determine if all non-cognitive variables such as global EI, 4 factors, 3 subscales, and the average clinical GPA for DMS students are normally distributed (see Table 1 for these results).

Table 1.

Tests of Normality of Average Clinical GPA, Global EI, 4 Factors, and 3 Subscales of Trait EI for Diagnostic Medical Sonography Students.

	Shapiro-Wilk
	Statistic	df	Sig.
Average Clinical GPA	.731	10	.002
Global EI DMS 2021	.795	10	.013
Well-being DMS 2021	.827	10	.031
SelfControl DMS 2021	.946	10	.625
Emotionality DMS 2021	.931	10	.462
Sociability DMS 2021	.925	10	.397
Optimism DMS 2021	.854	10	.065
Stress Management DMS 2021	.913	10	.301
Emotion Expression DMS 2021	.899	10	.216

Abbreviations: DMS, diagnostic medical sonography; EI, emotional intelligence; GPA, grade point average.

Table 1 showed that the Shapiro-Wilk statistics for most noncognitive variables such as global EI, 3 of factors (Self-Control DMS 2021 P = .625, Emotionality DMS 2021 P = .462, and Sociability DMS 2021 P = .397) and 3 subscales of trait EI (Optimism DMS 2021 P = .065, Stress Management DMS 2021 P = .301, and Emotion Expression DMS 2021 P = .216) had a P value ≥ .05. These findings indicate that these data are normally distributed. Therefore, the parametric Pearson correlation test was used to determine a relationship between them.

Since the 3 factors and 3 subscales of trait EI data are normally distributed, the parametric Pearson correlation test was used to determine if a relationship exists between these variables (See Table 2 for these results).

Table 2.

Pearson Correlation Test of Average Clinical GPA, Global EI, 3 Factors, and 3 Subscales of Trait EI for Diagnostic Medical Sonography Students.

		Aver Clin GPA	Gl EI DMS21	SelfContr DMS21	Emot DMS21	Sociab DMS21	Optim DMS21	Str Man DMS21	Em Expr DMS21
Aver Clin GPA	Pearson Correl	1	.034	.101	.112	.165	−.070	.411	.053
	Sig. (2-tailed)		.926	.781	.758	.648	.848	.238	.885
	N	10	10	10	10	10	10	10	10
Gl EI DMS21	Pearson Correl	.034	1	.894**	.900**	.952**	.921**	.705*	.914**
	Sig. (2-tailed)	.926		.000	.000	.000	.000	.023	.000
	N	10	10	10	10	10	10	10	10
SelfContr DMS21	Pearson Correl	.101	.894**	1	.821**	.754*	.716*	.790**	.756*
	Sig. (2-tailed)	.781	.000		.004	.012	.020	.007	.011
	N	10	10	10	10	10	10	10	10
Emot DMS21	Pearson Correl	.112	.900**	.821**	1	.817**	.743*	.576	.951**
	Sig. (2-tailed)	.758	.000	.004		.004	.014	.082	.000
	N	10	10	10	10	10	10	10	10
Sociab DMS21	Pearson Correl	.165	.952**	.754*	.817**	1	.922**	.653*	.888**
	Sig. (2-tailed)	.648	.000	.012	.004		.000	.040	.001
	N	10	10	10	10	10	10	10	10
Optim DMS21	Pearson Correl	−.070	.921**	.716*	.743*	.922**	1	.684*	.793**
	Sig. (2-tailed)	.848	.000	.020	.014	.000		.029	.006
	N	10	10	10	10	10	10	10	10
Str Man DMS21	Pearson Correl	.411	.705*	.790**	.576	.653*	.684*	1	.505
	Sig. (2-tailed)	.238	.023	.007	.082	.040	.029		.136
	N	10	10	10	10	10	10	10	10
Emot Exp DMS21	Pearson Correl	.053	.914**	.756*	.951**	.888**	.793**	.505	1
	Sig. (2-tailed)	.885	.000	.011	.000	.001	.006	.136
	N	10	10	10	10	10	10	10	10

Abbreviations: DMS, diagnostic medical sonography; EI, emotional intelligence; GPA, grade point average.

Correlation is significant at the .05 level (2-tailed). **Correlation is significant at the .01 level (2-tailed).

Table 2 showed that the Pearson correlation of more than 0.5 exists between global EI, 3 factors, and 3 trait EI subscales of trait EI for DMS students (SelfControl DMS 2021 P = .894, Emotionality DMS 2021 P = .900, Sociability DMS 2021 P = .952), and 3 subscales (Optimism DMS 2021 P = .921, Stress Management DMS 2021 P = .705, Emotion Expression DMS 2021 P = .914). These findings indicate that a strong relationship exists between global EI, 3 factors, and 3 trait EI subscales of trait EI variables for DMS students.

Since Table 1 demonstrated that the P value < .05 for the average clinical GPA (P = .002), global EI (P = .013) and 1 of the 4 subscales of trait EI well-being (P = .031) for DMS students, the nonparametric Spearman’s rho correlation test was used for these 3 variables (See Table 3 for these results).

Table 3.

Spearman’s Rho Correlation of Clinical GPA, Global EI, and 3 Factors of Trait EI Data for Diagnostic Medical Sonography Students.

			Average Clinical GPA	Global EIDMS 2021	Well-Being DMS 2021
Spearman’s rho	Average clinical GPA	Correlation coefficient	1.000	.354	−.097
		Sig. (2-tailed)		.316	.790
		N	10	10	10
	Global EI DMS 2021	Correlation coefficient	.354	1.000	.733*
		Sig. (2-tailed)	.316		.016
		N	10	10	10
	Well-being DMS 2021	Correlation coefficient	−.097	.733*	1.000
		Sig. (2-tailed)	.790	.016
		N	10	10	10

Abbreviations: DMS, diagnostic medical sonography; EI, emotional intelligence; GPA, grade point average.

Correlation is significant at the .05 level (2-tailed).

Table 3 showed that the Spearman’s rho between global EI and 1 of the 4 factors of trait EI well-being was .773 at a significance level of .016 for DMS students. This finding demonstrates a strong relationship between these 2 variables. Nevertheless, these data showed no significant relationship between the average clinical GPA, global EI, and the well-being factor of trait EI for DMS students.

Radiography Students

The Shapiro-Wilk test of normality was performed to determine if all noncognitive variables such as global EI, 4 factors, 3 subscales, and average clinical GPA for RT students are normally distributed (See Table 4 for these results).

Table 4.

Tests of Normality of Average Clinical GPA, Global EI, 4 Factors, and 4 Subscales of Trait EI for Radiography Students.

	Shapiro-Wilk
	Statistic	df	Sig.
Average clinical GPA	.496	16	.000
Global EI RT 2021	.919	16	.161
Well-being RT 2021	.881	16	.041
Self-control RT 2021	.950	16	.494
Emotionality RT 2021	.968	16	.808
Sociability RT 2021	.982	16	.980
Optimism RT 2021	.896	16	.069
Stress management RT 2021	.966	16	.776
Emotion expression RT 2021	.977	16	.939

Abbreviations: EI, emotional intelligence; GPA, grade point average; RT, radiography.

Table 4 showed that the Shapiro-Wilk statistic for global EI, 3 factors (Global EI RT 2021 P = .161, Self-Control RT 2021 P = .494, Emotionality RT 2021 P = .808, and Sociability RT 2021 P = .980), and 3 subscales of trait EI (Optimism RT 2021 P = .069, Stress Management RT 2021 P = .776, and Emotion Expression RT 2021 P = .939) had a P value ≥ .05. These findings indicate that these data are normally distributed for RT students. Therefore, the parametric Pearson correlation test was used. The average clinical GPA (P = .000) and one of the trait EI factors, well-being, (P = .041) demonstrated significance levels less than .05 which means that the data are not normally distributed. Therefore, the nonparametric Spearman’s rho correlation was used for this variable.

Since global EI, 3 factors and 3 subscales of trait EI are normally distributed, the Pearson correlation test was used to determine if a relationship exists between the average clinical GPA, global EI, 3 factors and 3 subscales of trait EI for RT students (See Table 5 for these results).

Table 5.

Pearson Correlation Test of Average Clinical GPA, Global EI, 4 Factors and 3 Subscales of Trait EI for Radiography Students.

		Aver Clin GPA	Gl EI RT21	Self-Contr RT21	Emot RT21	Sociab RT21	Optim RT21	Str Man RT21	Emot Expr RT21
Aver Clin GPA	Pearson Correl	1	.386	.319	.231	−.095	.422	.260	.354
	Sig. (2-tailed)		.140	.229	.390	.727	.104	.330	.178
	N	16	16	16	16	16	16	16	16
Gl EI RT21	Pearson Correl	.386	1	.895**	.773**	.564*	.752**	.723**	.817**
	Sig. (2-tailed)	.140		.000	.000	.023	.001	.002	.000
	N	16	16	16	16	16	16	16	16
Wellb RT21	Pearson Correl	.663**	.875**	.698**	.635**	.311	.825**	.590*	.719**
	Sig. (2-tailed)	.005	.000	.003	.008	.241	.000	.016	.002
	N	16	16	16	16	16	16	16	16
Self-Contr RT21	Pearson Correl	.319	.895**	1	.697**	.373	.590*	.801**	.625**
	Sig. (2-tailed)	.229	.000		.003	.155	.016	.000	.010
	N	16	16	16	16	16	16	16	16
Emot RT21	Pearson Correl	.231	.773**	.697**	1	.170	.636**	.393	.780**
	Sig. (2-tailed)	.390	.000	.003		.528	.008	.132	.000
	N	16	16	16	16	16	16	16	16
Sociab RT21	Pearson Correl	−.095	.564*	.373	.170	1	.222	.341	.452
	Sig. (2-tailed)	.727	.023	.155	.528		.409	.196	.079
	N	16	16	16	16	16	16	16	16
Optim RT21	Pearson Correl	.422	.752**	.590*	.636**	.222	1	.627**	.584*
	Sig. (2-tailed)	.104	.001	.016	.008	.409		.009	.017
	N	16	16	16	16	16	16	16	16
Str Man RT21	Pearson Correl	.260	.723**	.801**	.393	.341	.627**	1	.421
	Sig. (2-tailed)	.330	.002	.000	.132	.196	.009		.105
	N	16	16	16	16	16	16	16	16
Emot Exp RT21	Pearson Correl	.354	.817**	.625**	.780**	.452	.584*	.421	1
	Sig. (2-tailed)	.178	.000	.010	.000	.079	.017	.105
	N	16	16	16	16	16	16	16	16

Abbreviations: EI, emotional intelligence; GPA, grade point average; RT, radiography.

Table 5 showed that the Pearson correlation was .663 at a significance level of .005 between the well-being EI factor and the average clinical GPA. This finding confirms that there is a strong relationship between the well-being EI factor and the average clinical GPA for RT students. All other variables did not show a significant relationship between all other EI variables and the average clinical GPA for RT students. In addition, Table 5 demonstrates that there is significant correlation between global EI, 4 factors (well-being RT 2021 P = .875, Self-Control RT 2021 P = .895, Emotionality RT 2021 P = .773, and Sociability RT 2021 P = .564) and 3 trait EI subscales of trait EI (Optimism RT 2021 P = .752, Stress Management RT 2021 P = .723, and Emotion Expression RT 2021 P = .817) for RT students at the P > .5 level. These findings demonstrate that there is a strong relationship among them.

Since the Shapiro-Wilk statistic in Table 4 demonstrates significance level less than .05 for the average clinical GPA and 1 factor of trait IE well-being for RT students, it indicates that these data are not normally distributed. Therefore, the nonparametric Spearman’s rho correlation was used for these 2 variables (See Table 6 for these results).

Table 6.

Spearman’s Rho Correlation Test of Average Clinical GPA and 4 Factors of Trait EI Data for Radiography Students.

			Average Clinical GPA	Well-Being RT 2021
Spearman’s rho	Average clinical GPA	Correlation coefficient	1.000	.516*
		Sig. (2-tailed)		.041
		N	16	16
	Well-being RT 2021	Correlation coefficient	.516*	1.000
		Sig. (2-tailed)	.041
		N	16	16

Abbreviations: EI, emotional intelligence; GPA, grade point average; RT, radiography.

Correlation is significant at the .05 level (2-tailed).

Table 6 showed that the Spearman’s rho between the average clinical GPA and 1 of the 4 factors of trait EI well-being was .516 at a significance level of .041. Therefore, this finding indicates that there is a strong relationship between the average clinical GPA and 1 of the 4 factors of trait EI well-being for RT students.

Discussion

The Pearson and Spearman’s rho correlation tests demonstrated a significant relationship between all EI variables such as global trait EI, 4 factors and 3 subscales of trait EI for both groups of students. These results were anticipated because the TEIQue questionnaire’s global EI consists of 4 factors and all the subscales of EI, and they are all interconnected. A statistically significant relationship (r = .516, P = .041) at the .05 level of significance was observed among 1 of the 4 EI factors, well-being, and clinical success for RT students. These findings substantiate the existing research found in the literature. Individuals who score high on this factor reflect a general sense of well-being, expanding from previous achievements to future expectations. Such individuals feel positive, happy, and fulfilled.²⁵ Kyllonen⁵ emphasized that behavioral science research in psychology and economics suggests that noncognitive soft skills such as motivation, work ethic, teamwork, organization, cultural awareness, and effective communication play a more important role in determining success in school and in the workplace than cognitive abilities. According to Halian et al,²⁸ empathy, emotional competence, and self-improvement are crucial factors needed for adaptation of future health care professionals to their professional setting. The literature review conducted by Dugué et al²⁹ concluded that a high level of EI is beneficial to students. They revealed that “emotionally intelligent students or health care professionals are more efficient, better manage stress and emotions, have better health, and have better relationships with patients, families and health care teams.” In addition, Zoromski¹⁷ asserted that employees with high EI skills may experience better general well-being and experience less-emotional exhaustion and burnout in service positions. Sliter et al³⁰ recommended that service industries investigate utilizing EI instruments for hiring selections to improve customer service performance and reduce health care expenses. O’Connor et al¹⁰ confirm that people who possess high trait EI tend to have “high levels of self-efficacy regarding emotion-related behaviors and are competent at managing and regulating emotions in themselves and others.” Moreover, the results of the study conducted by Gutiérrez-Cobo et al³¹ demonstrated that an improvement in the ability to manage emotions can improve the capacity for cognitive control in undergraduate students.

The results of the Pearson correlation and Spearman’s rho statistical analysis did not show a significant relationship (r < .5 and P > .05) between the average clinical GPA, global EI, 4 factors and 3 subscales of trait EI for DMS students. This finding affirms that there was no relationship between EI and clinical success at the completion of 3 consecutive semesters of DMS students. These findings differ from the prior research found in the literature. A number of contradictory research articles exist in the literature regarding the relationship of EI and student college success. The majority of the EI research studies in the United States have been conducted among the nursing students.^14,17 Virtually no literature exists to ascertain whether EI can be a reliable tool that can forecast student clinical success in the imaging health care programs such as DMS and RT students.^15,16 The topic of EI should remain to be investigated further to gather more meaningful data.

It appears that there are inconsistent findings between the DMS and RT programs. This potentially can be due to various styles of teaching, grading techniques, and differences in clinical education courses between the 2 programs. It is important to note that the DMS and RT programs had a different number of clinical courses throughout their clinical rotations. Diagnostic medical sonography students completed 163 clinical hours more than RT students throughout the 2 clinical semesters. In addition, each program had different students’ daily clinical schedules throughout their clinical rotations. These differences may be contributing factors explaining the inconsistencies between the results of the 2 groups of students.

Limitations

This study has 4 internal validity threats that must be discussed such as the interactions with selection, maturation, mortality, and testing. The interactions with selection internal validity threat exists because even though the participants are an “imaging professionals” student cohort, they belong to 2 different professions, DMS and RT. The maturation internal validity threat is an issue because the participants’ maturation level may change throughout the length of the study. Some of the RT participants withdrew from the program due to COVID-19-related challenges which resulted in the mortality internal validity threat. Their results were excluded from the calculations and only complete data were utilized for data analysis. It is worth noting that the RT programs’ attrition rate was about 22.7% compared to the DMS programs’ average attrition rate of 0%.

This study has external validity threats such as the interaction of setting and treatment because it limits the generalization of the sample. This threat lies in the fact that students in this sample have different personalities and learning styles and may not necessarily represent the same sample, if replicated at another college. In addition, it is important to note that the DMS students were mostly female, and the RT students have a more even distribution of gender. Furthermore, this study was completed at a large community suburban college, and therefore, the findings of this study may not apply to a small suburban community college or a large 4-year institution elsewhere. Since the data were collected based on a convenient sample of respondents, small sample size is another important limitation.

Conclusion

The findings of this study provided limited evidence that there may be a strong relationship between 1 of the 4 trait EI factors, well-being, among RT students and clinical success in this RT student cohort. This may be a significant finding that supports the use of the TEIQue questionnaire, as part of the admissions process for other RT programs. Interestingly, this DMS student cohort did not result in the same outcome. Goleman³² emphasized that soft skills in the service field are significant, and therefore, it is important to determine whether student EI skills can be measured and improved throughout students’ studies in health care programs to better prepare them for the workforce. Therefore, further research should be conducted to investigate whether these findings are similar in other imaging programs. This research could lead to further studies exploring relationships between other noncognitive variables such as EI and student clinical success in various imaging and health care programs.

Supplemental Material

sj-doc-1-jdm-10.1177_87564793221138102 – Supplemental material for The Relationship Between Emotional Intelligence and Clinical Success at the Completion of One Year of Courses for Diagnostic Medical Sonography or Radiography Students

Supplemental material, sj-doc-1-jdm-10.1177_87564793221138102 for The Relationship Between Emotional Intelligence and Clinical Success at the Completion of One Year of Courses for Diagnostic Medical Sonography or Radiography Students by Elena Miller in Journal of Diagnostic Medical Sonography

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Ethical Approval

Ethical approval for this study was obtained from the Institutional Review Board of the University of St. Francis, Joliet, IL (approval id. IRB # 2019-20-081).

Informed Consent

Written consent was obtained from all participants after they were informed of the objective and design of the study, and they were free to leave the study at any time if they wished.

Animal Welfare

Guidelines for humane animal treatment did not apply to the present study because [REASON].

ORCID iD

Elena Miller

Supplemental Material

Supplemental material for this article is available online. Scan the QR code with your smart device to view the online supplemental videos available at

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Supplementary Material

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