Abstract
The role of personality in specialty choices of speech-language pathology (SLP) students was examined. Specialty choices were obtained using a demographic questionnaire, and personality was measured with the Multidimensional Personality Questionnaire (MPQ) in an electronic survey. The personalities of SLP students were compared to students in nine educational majors using Hotelling’s T 2-test analyses. Multivariate analyses of variance were conducted to evaluate the effects of the 11 primary personality traits on age and setting choice. SLP students were found to significantly differ from the nine examined majors in the MPQ primary traits—social potency, alienation, aggression, harm avoidance, and control. Students were found to be organized, trusting of peers, nonaggressive, and harm avoidant when compared to other student groups. Personality traits did not significantly contribute to age or facility choice, and the degree of variance in the responses may indicate that a variety of personality types can thrive within the field.
Changes in the field of speech-language pathology (SLP) have expanded vocational choices for students. SLPs may choose a vocational setting based on age of the patient population or communication deficits treated within a facility. Students must navigate these choices, which can often be overwhelming. Higher education professionals are often tasked with counseling students toward an environment in which they would thrive. Presently, little attention has been given to how to counsel SLP students on specific career decisions. Because the relationship between personality and career interests has been frequently investigated within vocational psychology, we chose to examine the relationship between personality and student indicated specialty choices. Given the limited evidence surrounding the relationship between personality and specialty choices specific to the field of SLP, evaluating whether certain personality traits may distinguish choices within the field appears warranted.
The present investigation was initiated to further examine and describe the personality of SLP students using the Multidimensional Personality Questionnaire (MPQ). The SLP student profile was further compared to students choosing other vocations. Finally, the personality measure was also used to evaluate whether personality contributes to specialty choice.
Personality and The MPQ
The MPQ, an established assessment of personality with a strong theoretical basis, was chosen to investigate SLP student personality. The MPQ is a standardized, self-report personality assessment that is composed of 18 total scales and 276 binary, primarily true/false questions, with remaining questions requiring a choice between two conditions. Of the 18 scales, 3 scales assess the validity of the participant’s self-report, 11 primary scales measure specific personality traits or dimensions, and 3 scales measure broad personality traits (Tellegan & Waller, 2008). The three validity scales are unlikely virtues, true response inconsistency, and variable response inconsistency, which indicate the reliability of the examinee’s test results by accounting for response bias, social desirability, and inconsistent responses (Tellegan, 2003). The MPQ also measures four broad traits, namely, positive emotionality, negative emotionality, constraint, and absorption. The 11 primary scales are comprehensive and are listed in Table 1. Table 1 also provides trait descriptors of high scorers for each of the 11 primary scales (Tellegan & Waller, 2008).
Descriptions of the 11 MPQ Primary Scales (Tellegan & Waller, 2008).
The MPQ assessment structure has been linked to the five-factor model (FFM; Church, 1994). The FFM is one of the most prominent theories stating that five broad, all-encompassing factors are needed to adequately describe human personality. The five traits are labeled: extroversion, openness, neuroticism, conscientiousness, and agreeableness (John & Srivastava, 1999). The FFM provides a unified structure through which to describe personality. Its development has allowed for the accumulation of research using a standard language (John & Srivastava, 1999). When examining the FFM and the MPQ, four of the five factors correlated with at least 1 of the 11 MPQ primary scales with a correlation coefficient of .50 or greater (Tellegan & Waller, 2008). Extroversion correlated with social closeness (0.61) and social potency (0.42). Agreeability negatively correlated with aggression (−0.5). Neuroticism correlated strongly with stress reaction (0.73) and had a weak negative correlation with wellbeing (−0.39). Conscientiousness correlated with control (0.52) and achievement (0.42). Lastly, openness correlated with the MPQ scale Absorption (0.40). Based on these analyses, each of the traits in the FFM is represented in Tellegan’s 11 primary traits. The findings of Tellegan and Waller (2008) also suggest that the MPQ provides a more specific description of personality than what the FFM provides alone. More specific, narrow measures of personality may be more effective and provide greater insight into discrete personality differences (Armstrong & Anthoney, 2009; Larson et al., 2010).
Personality and Vocational Choice
Holland (1985) was an early examiner of personality and vocational choices across many fields. According to Holland’s theory of vocational personalities in work environments (1985), the choice of occupation or college major is a direct expression of personality. Holland’s model posits that people are interested in and choose a vocation with an environment that allows their personality traits to thrive (De Fruyt & Mervielde, 1997). According to his model, there are six basic areas of vocational interests—realistic, investigative, artistic, social, enterprising, and conventional types (RIASEC). The raw RAISEC scores for an individual are used to create a letter code, based on raw scores, with highest scores representing the first letter with the following letters descending in value (i.e., SIA, REC). Holland’s RAISEC typology codes can be accessed for each profession. The dictionary of Holland occupational codes and the O*NET database classify SLPs as having an SIA type (Gottfredson & Holland, 1996; National Center for O*NET Development, 2017). Although Holland’s codes have been published, there is often disagreement between sources (Eggerth, Bowles, Tunick, & Andrew, 2005). Based on Holland’s descriptions of each type and the codes for SLPs as described by the aforementioned sources, SLPs are helpers which correspond best with the social type. Holland (1985) describes the social type in the following manner: The special heredity and experiences of the Social person lead to a preference for activities that entail the manipulation of others to inform, train, develop, cure, or enlighten; and an aversion to explicit, ordered, systematic activities involving materials, tools, or machines. (p. 21)
Holland (1985) further indicated that individuals in the social type would prefer social occupations and avoid realistic occupations, with a tendency to rely on social skills to solve problems. They also report the enjoyment of helping and caring for others and a self-awareness in strength of teaching and weakness in mechanical and scientific skills. Holland also describes the value placed on social and ethical issues. He suggests that individuals who fit within the social type exhibit the following personality trait descriptors: cooperative, patient, friendly, generous, helpful, empathetic, kind, persuasive, responsible, sociable, tactful, understanding, and warm (Holland, 1985). Based on Holland’s descriptions, SLPs may score highly on the MPQ primary scales Social Closeness and Traditionalism. In contrast, Holland’s report of aversions to ordered activity would correspond to low scores on the Control Scale.
A breadth of research has been dedicated to relating personality and the FFM to both broad and specific vocational choices. Specifically, the relationship between Holland’s RAISEC types and the FFM has been evaluated, and congruence has been found between the two. The FFM trait, extroversion, has been linked to social and enterprising types (Armstrong & Anthoney, 2009; De Fruyt & Mervielde, 1997; Gottfredson, Jones, & Holland, 1993). Openness has also been linked to artistic and investigative interests (Armstrong & Anthoney, 2009; Hogan & Blake, 1999; Tokar, Fischer, & Subich, 1998). Additionally, openness was found to be negatively correlated with conventional interests (De Fruyt & Mervielde, 1997). However, low correlations between the FFM and realistic interests have been described (De Fruyt & Mervielde, 1997; Gottfredson et al., 1993).
Personality factors have also been used to examine broad vocational choice, medical specialty, and choice in academic major. Existing research investigating personality and career choice in the medical field has uncovered personality traits that are associated with multiple specialties including pediatrics. In their review of the literature on medical specialty and personality, Borges and Savickas (2002) found two sources regarding personality traits that separate pediatricians from other specialties, which described higher neuroticism, extroversion, and agreeableness (Borges & Savickas, 2002). Based on this description, SLPs choosing to specialize with children would have low scores in aggression, as agreeability is the negative correlate of aggression. Because neuroticism correlates strongly with stress reaction, pediatric specialists may have higher scores on the Stress Reaction Scale. Eley, Eley, Bartello, and Rogers-Clark (2012) studied the relationship between personality and the reasons for entering a career in nursing. They, through use of an interview and the Temperament and Character Inventory, found that the need and enjoyment of caring for others was the principle reason for entering the profession, and this trait could be found in the participants included in the study. This enjoyment of caring is also described by Holland (1985) in his description of the social type.
Larson and colleagues (2010) examined the relationship between a student’s selected college major and their personality using the MPQ. Nine different majors were examined: engineering, sport and exercise physiology, physical and biological sciences, architecture, humanities, social science, elementary education, business, and computer science. They found personality traits distinctly related to each of the examined majors. Many of these majors shared some qualities with or could be considered similar to the field of SLP, such as elementary education, sport and exercise physiology, and humanities. They found that the primary scale Social Closeness, which correlates strongly with the FFM trait extroversion, was able to separate elementary education majors from the other majors examined.
Personality and Vocational Choice in SLP Students
Vocational choice in the field of SLP has been examined, with a focus on extrinsic factors influencing choice. Extrinsic factors commonly cited as reasons for entering the profession are positive interactions with professionals, job availability, and personal experiences (Byrne, 2007; Lass et al., 1995; Rockwood & Madison, 1992; Stone & Pellowski, 2016). Little research has focused on intrinsic factors that may describe SLP student choices, but the personalities of SLP students have been described (Baggs, 2013; Craig & Sleight, 1990).
The personalities of SLP students have been examined using personality assessments based on Jungian’s personality theory like the Myers–Briggs Type Indicator (MBTI). Using the MBTI, Craig and Sleight (1990) evaluated the personality of SLP supervisors in order to examine the relationship between supervisor personality and resulting relationships with their students. Significant difference between the generated MBTI personality types of supervisors and students was found. The personality types that occurred most frequently for supervisors included extroversion, intuition, thinking, judging (ENTJ); introversion, intuition, thinking, and judging (INTK); and extroversion, sensing, thinking, and judging (ESTJ). All but 1 of the 16 possible MBTI personality types were represented in the sample of SLP supervisors.
Baggs (2013) evaluated the personality of SLP students using a Jungian personality theory assessment, the Keirsey Temperament Sorter II. Three hundred and twenty graduate students participated in the personality assessment, and over 50% generated the personality types extroversion, sensing, feeling, and judging (ESFJ) or introversion, sensing, feeling, and judging (ISFJ). Therefore, a majority of the participants showed a sensing–judging (SJ) temperament. Individuals who generate this temperament are described as rational, practical, and traditional. They are perceptive to the needs of others and find enjoyment in helping others. Further, the majority of Baggs’s (2013) sample of SLP students were feeling (F) rather than thinking (T), in that they make decisions based on affective components rather than logical reasoning. Like Craig and Sleight (1990), all 16 personality types were represented within the sample.
When reviewing literature regarding SLP personality, research examining the personality of SLP students using the MPQ could not be found. Although the MBTI has been previously used to study the personalities of SLP students, personality researchers have criticized the assessment based on a lack of support for Jungian theory, the exclusion of the big five factor neuroticism, and a lack of construct validity (McCrae & Costa, 1989). The MPQ may provide a more specific description of the personality traits than what can be achieved through the MBTI.
The Present Study
Given that personality has been shown to differentiate vocational choices and contribute to vocational counseling, this study was undertaken to describe SLP student personality compared to other student groups and to determine the relationship between personality and specialty choice. The MPQ, a valid assessment of personality, was used to measure the personality traits of the participants. Two specific research aims were addressed. First, the personality profile for SLP students was compared to students pursuing other majors (Larson et al., 2010) using the MPQ. Comparing the profiles may reveal personality differences between SLPs and other students, further contributing to the literature describing the personality of SLP students. Based on the existing Holland’s code, SIA, and literature on SLP personality, and personalities of individuals within similar professions, we hypothesized that the MPQ scales Wellbeing, Social Closeness, Social Potency, Control, and Traditionalism would separate SLP students from other student groups (Baggs, 2013; Borges & Savickas, 2002; Holland, 1985; Larson et al., 2010). We also hypothesized that aggression, social closeness, and stress reaction would be able to separate SLPs choosing pediatric patients (Borges & Savickas, 2002; Larson et al., 2010). The second aim of the present investigation was to determine whether personality could differentiate specialty choice within the field of SLP. We hypothesized that personality traits would separate students choosing adults from those selecting children. If personality can separate students’ choices, personality may be used by higher education professionals tasked with advising students on specialty choices.
Method
Participants
Approval was received from a university institutional human research protection program committee. Participants provided consent to participate by indicating agreement to participate after reading an online information letter that preceded the survey. SLP students were recruited to participate using an initial recruitment survey distributed by e-mail to 174 department chairs from academic institutions across the country. The recruitment survey was also posted on the National Student Speech Language Hearing Association (NSSLHA) listserv. Although 508 students were initially interested in the study, 308 (58.2%) initiated the survey and 255 undergraduate and graduate students completed the survey, resulting in a response rate of 48.2%.
The 255 complete responses were then filtered based on the following inclusion criteria: (1) 19 years of age or older and (2) current enrollment status in undergraduate or graduate coursework at an accredited secondary/postsecondary institution, leaving 235 surveys. The 235 responses were further examined for decidedness as well as validity using the MPQ validity scales, resulting in the further exclusion of one participant. The data were also examined for missing data in the MPQ. Seventy-five responses contained random missing data, either due to computer error or due to the individual’s choice to skip the question. Three respondents were initially excluded because they skipped more than two questions from a single scale, negatively affecting the validity of their MPQ assessment. In order to increase the validity of the assessments containing missing data, data were imputed by the researcher based on the respondents’ own answers to similar or sometimes the same questions. The data were appropriate for imputation because the questions were missed at random and the respondents supplied answers to similar questions. In the final data set, 143 of the 63,756 total data points (0.22%) within the sample were imputed. After all methods of response filtering, 231 participants remained for analysis.
Participant demographics
The 231 participants were between 19 and 56 years of age, with the majority of participants between the ages of 19 and 30 (92.2%, n = 213). Most of the respondents described themselves as Caucasian (91.3%, n = 211), and the majority of the remaining participants were African American (2.6%, n = 6), Hispanic (1.7%, n = 4), and Asian (1.7%, n = 6). Regarding enrollment status, 35.1% (n = 81) were undergraduate students and 64.9% (n = 150) were graduate students. The respondents represented academic institutions from 31 different states, though the largest number of students reported completing coursework in Alabama (22.9%, n = 53), followed by Wisconsin (9.5%, n = 22), California (8.7%, n = 20), Ohio (7.4%, n = 17), Texas (4.8%, n = 11), and Pennsylvania (4.3%, n = 10). Most of these students had completed less than 50 hr of practicum (59.5%, n = 137).
Measures
Demographic and specialty choice questionnaire
A questionnaire was developed by the authors to obtain demographic and specialty choices using the online survey tool Qualtrics (2015). The questionnaire was also used to evaluate practice preference patterns of SLP students in another study (Leonard, Plexico, Plumb, & Sandage, 2016). Three areas were addressed: (1) background information, (2) preferred patient age specialty, and (3) preferred career setting. Demographic information and vocational choices were acquired before the MPQ assessment was administered. After indicating vocational choices, the decidedness scales were presented. Decidedness was measured to ensure that undecided students did not contribute invalid personality data. Using a Likert-type scale, the students were instructed to select a point on the three decidedness scales (1 = undecided, 2 = somewhat undecided, 3 = somewhat decided, and 4 = decided; Larson et al., 2010). The first decidedness scale was presented solely to undergraduates in order to ascertain their level of commitment to pursuing a career within the field of SLP. The remaining two decidedness scales were presented to all respondents in order to gauge their confidence in both age and facility specialty choices.
The effect of age and facility decidedness on the 11 primary personality traits was examined. MANOVA was used to evaluate whether students who were more undecided would differ across the primary personality traits. Significant differences were not found among the different degrees of age decidedness on the primary personality traits, Wilks’s Λ = 0.841, F(33, 640.026) = 1.173, p = .235. Similarly, significant differences were not observed among the different degrees of facility decidedness on the primary personality traits, Wilks’s Λ = 0.863, F(33, 640.026) = 0.991, p = .484. Because age and facility decidedness had no significant effects on the primary personality traits, no responses were removed from analysis based on degree of decidedness.
Following the demographic questions, the respondents were then asked to indicate the average age of the patients they wished to provide services to in future career opportunities. After selecting age specialty, the respondents identified a single facility or employment setting as their facility choice. Facility choices presented to respondents were dependent on indicated age specialty. Descriptions of both age and facility options were derived from a review of American Speech Language Hearing Association’s (ASHA, 2014, n.d.) information on career opportunities and were available to the respondents when indicating their specialty choices.
The MPQ
Personality traits were assessed using the MPQ (Tellegan and Waller, 2008). The 11 primary MPQ traits were evaluated through the participant’s self-report. The MPQ measurement has been shown to be a valid measure of personality, demonstrating strong psychometric properties including test–retest reliability, internal consistency, and construct validity (Tellegan & Waller, 2008). Regarding internal consistency and reliability, α coefficients were computed by Tellegan and Waller (2008) for four separate samples. Based on their report, none of the α coefficients in any of the samples fell below .75. Using step-down Spearman Brown correction, mean interitem correlations (r) were also estimated across each scale. The median r value was .18. Test–retest correlations were obtained over the course of 1 month, which yielded a median value of .89. The MPQ is typically administered in paper–pen format, but the assessment was presented electronically via Qualtrics (2015). DiLalla (1996) evaluated the validity of a computer administrated form of the MPQ. Analysis of the results indicated similar psychometric properties between the two versions such as scale reliability and internal consistency.
The MPQ responses were examined for validity. Three validity scales can be derived from the MPQ responses and include The Variable Response Inconsistency (VRIN), True Response Inconsistency (TRIN), and a scale that reflects the combination of VRIN and TRIN. The VRIN Scale reveals respondents who provide inconsistent answers to assessment content (Tellegen and Waller, 2008). The TRIN Scale identifies individual assessments where the respondent gave fixed response of true, regardless of question content. High and low TRIN scores reflect indiscriminate responding (Tellegen and Waller, 2008). Responses more than 3 standard deviations from the mean for either of the VRIN or TRIN Scales were excluded from analysis, and respondents with scores 2 standard deviations from the mean on both the VRIN and the TRIN Scales were also excluded (Miller, Greif, & Smith, 2003). As previously indicated, only one respondent met exclusion criteria based on VRIN and TRIN Scales and was excluded from analysis.
Results
Analysis
The results of the MPQ were scored using scoring syntax provided by Tellegan (2003). The personality profile of speech therapy students was determined by obtaining descriptive statistics for each of the 11 primary scales, as demonstrated in Table 2.
MPQ Means, Standard Deviations, and Significance Values for SLP Majors (N = 231) Compared to Nine Majors From Larson et al (2010)—Engineering, Sports and Exercise Physiology, Sciences, Architecture, Humanities, Sociology, Elementary Education, Business and Computer Science, as well as the Average Means for All Nine Examined Groups.
Note. M = Mean. SD = Standard Deviation. p = Significance Value. WB = Wellbeing. SP = Social Potency. AC = Achievement. SC = Social Closeness. SR = Stress Reaction. AG = Aggression. AL = Alienation. CO = Control. HA = Harmavoidance. TR = Traditionalism. AB = Absorption. SLP = Speech-Language Pathology. ENG = Engineering. SEP = Sports and Exercise Physiology. SCI: Physical and Biological Sciences. ARC = Architecture. HUM: Humanities. SOC = Social Science. ELE = Elementary Education. COM = Computer Science. BUS: Business. ALL 9: Combined mean scores of all 9 examined majors. * indicates significance when compared to SLP students.
*Indicates significance when compared to SLP students.
Hotelling’s T 2 tests were conducted to examine the difference between the personality profile of SLP students and the profiles of students from nine other educational departments (Larson et al., 2010). Multivariate analyses of variance (MANOVAs) were then conducted to determine the effect of the 11 primary traits described by the MPQ on the two dependent variables, age and setting specialty choice.
Personality of SLP students compared to students in nine educational majors
Larson et al. (2010) examined the relationship between a student’s selected college major and their personality for nine different majors—engineering, sport and exercise physiology, physical and biological sciences, architecture, humanities, social science, elementary education, business, and computer science. The professions’ profile, defined by the average of the 11 MPQ scales, was analyzed using Hotelling’s T 2 test for two independent groups (i.e., the multivariate extension of t test for two independent groups). The SLP student’s profile was compared against the profile of each of the other disciplines. Because the 11 scales covariance matrix for the Larson et al. (2010) data were not available, we used the matrix for the SLP students as an estimate of the pooled covariance matrix for the test. Effect sizes, Δ, defined as the distance between the two vectors of means when weighted by the variances and covariances of the scales, were calculated using G*Power (Faul, Erdfelder, Lang, & Buchner, 2007). A significant Hotelling’s T 2 test was followed by univariate t tests using a Bonferroni corrected α level of .0045 to control for experiment-wise Type 1 error.
Group differences between SLP majors on the 11 MPQ Scales and all other majors were statistically significant: English, T2 = 174.70, F(11, 246) = 167.88, p < .0001, Δ = 2.17; sports and exercise physiology, T2 = 246.82, F(11, 246) = 237.18, p < .0001, Δ = 2.58; physical and biological sciences, T2 = 131.70, F(11, 246) = 126.56, p < .0001, Δ = 1.88; architecture, T2 = 184.36, F(11, 246) = 177.16, p < .0001, Δ = 2.23; humanities, T2 = 130.66, F(11, 246) = 125.55, p < .0001, Δ = 1.88; social sciences, T2 = 283.30, F(11, 246) = 272.23, p < .0001, Δ = 2.80; elementary education, T2 = 157.68, F(11, 246) = 151.52, p < .0001, Δ = 2.06; business, T2 = 311.40, F(11, 246) = 299.24, p < .0001, Δ = 2.90; and computer science, T2 = 304.78, F(11, 246) = 292.87, p < .0001, Δ = 2.86. As shown in Table 2, SLP majors significantly differ on their average scores for the MPQ primary traits social potency, alienation, aggression, harm avoidance, and control.
Descriptions of each of the primary scales used were derived from Tellegan and Waller’s (2008) study. On the Social Potency Scale, the mean score of the SLP students was lower than that of all nine other examined majors. Lower Social Potency scores may indicate that the SLP students avoid being overly persuasive or the center of attention when compared to peers within different majors. On the Aggression and Alienation Scales, the SLP students also scored significantly lower than all other examined groups, indicating an abhorrence for violence. Low alienation scores indicate that the student sample does not feel victimized by their peers. On the Control and Harm Avoidance Scales, the SLP students had a significantly higher mean score than all other examined groups. These high scores indicate that SLP students may have a tendency to be more cautious and detail oriented, and they may enjoy safe environments.
Personality and age specialty
A one-way MANOVA using a Bonferroni adjustment (p = .5/11) was conducted to determine the effect of age specialty on the 11 MPQ primary scales. The multivariate test for homogeneity of dispersion matrices, Box test, was not significant, F(66, 104.751) = 0.889, p = .727, indicating that the variance and covariance among the personality factors are homogenous. The mean differences were small and not significant across the two primary age divisions: child (birth to 18) and adult (19 and older), Wilks’s Λ = 0.939, F(11, 217.0) = 1.272, p = .242.
Personality and facility choice
MANOVAs using a Bonferroni adjustment (p = .5/11 = .005) were conducted for facility specialty on the 11 MPQ primary scales. The multivariate test for homogeneity of dispersion matrices, Box test, was significant, F(198, 39.444) = 1.305, p = .003, indicating variance or covariance among facility specialty. Covariance matrices were evaluated for large group differences. Large group differences were observed and are believed to be contributing to the covariance. The mean differences were not significant across the six facility divisions—school, acute care hospital, rehabilitation facility, home health, outpatient clinic, and skilled nursing facility; Wilks’s Λ = 0.773, F(55, 989.52) = 1.031, p = .415. Facilities were then combined into the two broad categories of health care and school settings to reduce the observed large group differences. The multivariate test for homogeneity of dispersion matrices, Box test, remained significant, F(66, 79.309) = 1.422, p = .014. The mean differences remained not significant across the two divisions, Wilks’s Λ = 0.946, F(11, 217) = 1.128, p = .340.
Discussion
Literature has been dedicated to relating personality and broad choice in the occupation SLP; however, little research exists describing the impact of personality on specialty choices (Baggs, 2013). SLP student personality was further examined through comparisons between SLP students and nine other student groups choosing a different major. Using the MPQ personality profile, the relationship between personality and specialty choices within the field of SLP was also examined.
Using the MPQ, a profile of SLP student personality was created. It is important to note that although descriptive statistics for each of the 11 primary scales were used to create the overall profile, there was variability in the scores. This may indicate that the field of SLP allows many personality types to succeed within it. The profile was compared to the profiles of students in other majors as measured by Larson et al. (2010) in order to further describe SLP personality. Descriptions of SLP personality were created by referencing Tellegan and Waller (2008) and their descriptions of high scorers for each of the MPQ primary scales. The SLP student profile was found to significantly differ from other student group profiles for five MPQ primary traits—social potency, alienation, aggression, harm avoidance, and control. Based on these differences, we gain a broader understanding of SLP personality. The SLPs indicated an aversion to holding leadership roles and receiving attention from others as indicated by lower scores in social potency. Lower scores for alienation and aggression indicate a general tendency for SLP students to feel that they are treated justly by their peers and are not victimized or targeted by those surrounding them. They are also nonviolent, usually choosing to refrain from confrontation and retaliation. Significant differences for both control and harm avoidance were also found, as the SLP students scored higher than the other groups. High scores for control indicate that the SLP students view themselves as rational, organized, and detail oriented. High harm avoidance scores indicate that the SLPs are more cautious in their experiences rather than taking risks in which outcomes are unknown. They would rather participate in activities and environments deemed safe. Although the other six primary traits did not significantly differ from the other groups, comparisons of the descriptive statistics can provide more insight into the personality of SLP students. On the Achievement Scale, the SLPs scored higher than eight of the nine other groups. As high scorers in achievement, SLP students may be driven, hardworking, and ambitious. SLP students scored higher on the Wellbeing Scale than seven other groups, possibly indicating a tendency toward cheerfulness and optimism. The SLPs also scored higher than seven academic groups on traditionalism, which may point to the students’ high priority on morality. Regarding the Absorption Scale, the SLPs scored lower than eight examined groups. Based on this comparison, the SLPs considered themselves less creative than students in other majors.
Based on previous descriptions of health care/helping professionals and SLP students (Baggs, 2013; Holland, 1985; Larson et al., 2010), it was hypothesized that the MPQ scales Wellbeing, Social Closeness, Social Potency, Control, and Traditionalism would separate SLP students from other students. Social closeness and wellbeing were not found to significantly differentiate SLP students from the other examined student groups. Although not significant, the mean scores for social closeness were high when considering the range of scores available for each trait. For social closeness, the mean score was 15 with a maximum value of 21. Based on our findings, SLP students are likely warm and sociable as described by Holland (1985), but not more so than other groups. Holland’s description of the social type indicated that the individuals within it have an aversion to ordered, systematic activities. Contradictory to Holland’s description of helping professionals, the SLP students obtained high control scores. High scorers on the Control Scale are rational, careful, and enjoy planning and attention to detail. The SLP students also scored lower than the other student groups for the MPQ primary trait social potency. This is contrary to Holland’s assertion that individuals within the social type have a preference for strong leadership, as low scorers on the Social Potency Scale are not forceful and do not enjoy strong manipulations of others (Holland 1985).
The current findings were also compared to the findings of Baggs (2013) who used the Keirsey Temperament Sorter II to evaluate personality. Baggs reported that the majority of SLP students are ESFJ and ISFJ. The students are, according to his findings, practical, rational, traditional, perceptive to the needs of others, and compassionate toward others. He also explained that SLP students are more likely to make decisions based on affective response rather than logical reasoning. Our findings also reflect the rational, sensible nature of SLP students as shown through significantly high scores on the MPQ primary scale Control. Significant differences were not found for the traits social closeness and traditionalism; the MPQ Scales that correspond with Baggs’s (2013) description of SLP students as compassionate, perceptive to others, and traditional. Although the SLP’s scores on the Traditionalism and Social Closeness Scales were not significant, the SLP students may be considered high scorers when examining the range of scores. The mean score on the Traditionalism Scale was 17.21 with 26-point maximum value, and the mean score on the Social Closeness Scale was 15 with a 21-point maximum value. When considering the range of scores, the students described themselves as compassionate to the needs of others with value placed on tradition. Baggs (2013) also reported a balance of introversion and extroversion(I and E) within the students. Although the social closeness scores did not significantly differentiate students from the nine student groups, the scores were high considering the range indicating a tendency toward extroversion, as social closeness correlates strongly with extroversion. In contrast, SLPs scored lower than expected on social potency, the other correlate for extroversion. Our findings, therefore, may also indicate a balance of I and E. This finding should be interpreted cautiously, given that comparisons are difficult due to the differences in scoring and traits examined. Personality has been shown to differentiate specialty choice within the medical field (Borges & Savickas, 2002). We hypothesized that personality could also be used to separate SLP specialty choices. Our findings indicate that personality was not able to separate students choosing different areas or populations that instead a wide variety of personality types may exist within age and facility choices.
Implications for Practice
Of use to higher education professionals are the results from the comparisons of SLPs and students from other majors. The five MPQ personality scales that were found to separate SLP students included Social Potency, Alienation, Aggression, Harm Avoidance, and Control. Our findings along with previous resources on SLP personality and RAISEC types can be used to gain an understanding of the students currently within the field. According to their self-report, the sample of SLP students included in this study are hardworking, driven, and ambitious. They have a tendency toward cheerfulness but avoid roles that draw attention to themselves. The students are nonviolent, choosing safer activities and environments rather than adventure and spontaneity. The SLPs view themselves as rational, organized, and detail oriented, but they do not consider themselves overly creative and artistic. The students have good interactions with their peers, feel less victimized by others, and they place emphasis on morality. Having a better understanding of the student can help educators tailor their education and advising to highlight the strengths and improve the weaknesses of students.
Although both personality and Holland types for SLPs have been described, little attention has been given to what is inherently different about SLP students who chose different specialties. When describing student decision to pursue a career in SLP, factors such as interactions with professionals, availability of jobs, and personal experiences are frequently discussed (Byrne, 2007; Lass et al., 1995; Rockwood & Madison, 1992; Stone & Pellowski, 2016). Little could be found on how to counsel students in these decisions. Because personality traits have been used to inform career decisions (Kennedy & Kennedy, 2004; McCauley & Martin, 1995), we initially examined personality and specialty choices with the goal that identified differences could assist in career counseling. The hypothesis that personality can differentiate between specialty choices was not demonstrated in the context of this investigation. Therefore, personality assessment may not be informative when advising student training and educational placements. Factors other than personality may be more useful in the early identification of specialty choices for SLP students. Eley et al. (2012) described the joy of helping as the primary reason for joining the nursing career. Holland (1985) also described the importance of helping to individuals within the social type. It may be that the SLP students choose the field with the primary goal of helping others, regardless of age and facility. Extrinsic factors such as experiences with professionals, internship experience, and benefits of the job have already been described as motivators for joining the field but could also be the primary motivators for facility and age preferences. Based on the lack of support for personality as a factor in specialty choice, these described extrinsic factors may be more helpful in guiding students in their specialty choices.
Limitations and Future Research
The sample size was sufficient for power, overall, but it was not possible to control for sample size across specialty choices. The MPQ results were not analyzed for sex differences. The sex of the SLP students was not obtained in the demographic questionnaire; however, previous studies did not separate for sex during vocational analysis, and no significance was found when gender interactions were examined (Baggs, 2013; Tellegan, 2003). Males currently make up 3.7% of employed SLPs, and separating for gender would likely generate significantly different group sizes and was therefore deemed unwarranted (ASHA, 2014). While the students’ level of decidedness was queried, career aspirations expressed by SLP students during their undergraduate/graduate careers may not reflect their careers as certified SLPs. An investigation of the personalities of current professionals may provide more insight into the personality traits that distinguish different age and facility choices. Another future research direction could be to examine the relationship between personality and specialty in an area of communication disorders and sciences such as dysphagia, language, or voice. Because a personality profile for SLP students has been reported, they can continue to be compared to the means and standard deviations of other profiles to determine the degree of convergence or divergence between SLPs and other professionals.
Conclusion
The development of an MPQ personality profile and the comparison of the profile to those of nine other majors revealed information regarding the difference between SLP students and students pursuing other fields. Current SLP students may avoid overt leadership roles and attention, have a trusting attitude toward others, avoid confrontation and dislike violence, evade risky and unknown situations, and may be rational, organized, and detail oriented compared to other student groups. The hypothesis that personality can differentiate between specialty choices in SLP students was not demonstrated by the present investigation. Neither age nor facility choices were differentiated by personality type. Counseling students on age and facility choices, based on our findings, should not be based on personality alone, and other factors should be considered. Factors to consider may include positive or negative experience during educational placement, interactions with professionals, and social desirability of given specialty.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.