Given that high stress levels and negative consequences associated with stress are experienced by physical therapist (PT) students,1-7 it is important to explore methods to reduce these stressors. College students have been shown to benefit from programs to learn strategies to manage stress and enhance resilience.8,9 Providing PT students with tools to improve psychological resilience is an important consideration in managing the stress inherent in physical therapy education programs.
The purpose of this exploratory randomized controlled trial was to assess changes in stress levels, resilience, protective factors, and illness after an 8-hour resilience curriculum presented to Doctor of Physical Therapy (DPT) students during a period of academic stress compared to a wait-list control group. Hypotheses: an evidence-based resilience curriculum will 1) increase resilience and protective factors against stress and 2) decrease stress, negative affect, and symptoms of illness, among DPT students who receive the intervention compared to those in a wait-list control group. A secondary aim was to explore student characteristics that were associated with baseline resilience.
REVIEW OF LITERATURE
Stress is defined as the physiological and psychological response to a perceived inability to meet the demands placed upon oneself.10 College students have higher stress levels than the general population,1,2,11,12 perhaps owing to the unique circumstances in this life stage of emerging adulthood.13 Similar to other health professional students,11,14-29 PT students experience stress and anxiety at greater levels than college students or adults in the same age range.1,2,7
Several studies of college students have reported differences in stress levels between the sexes. In a national study of college students, far more female than male students reported feeling “overwhelmed” (90.2% vs 75.1%) and “tremendous” stress (12.6% vs 8.7%)12 in the previous year.12(p16) Among students in 3 PT education programs in the United States, there were significantly greater levels of stress and anxiety in the female compared to male students.2 As the literature on this topic in the United States is limited, it may also be helpful to consider PT education programs abroad. Female gender was associated with greater levels of perceived stress in undergraduate PT education programs in Australia and Sweden, but there were no differences in a program in Israel.4 Among PT students in 2 undergraduate programs and a Masters level program in the United Kingdom and Australia; only the undergraduate programs demonstrated increased stress in female compared to male students.6 In these studies of PT students, male students were older than female students, pointing to increased age as a possible confounder of the relationship between gender and stress level. Thus, there appears to be a lack of consensus on the differences in stress levels between the sexes.
There are also mixed results with regards to differences in stress by year of study in PT education programs. Stress levels were greater in later years of study in undergraduate PT students in Sweden, and Masters level PT students in Australia reported more stress than Bachelors students,4,6 while another study found that stress levels were lowest in the final year of study for Israeli undergraduate students.5 Other studies have found no differences in stress by year of study in PT students.1,2,4,7 In a study in the United States by Frank and Cassady,2 there was no difference in levels of perceived stress by year of study; however, second-year DPT students reported more anxiety than did first-year DPT students. Further studies are needed to determine if there is a real association between the year of study in PT programs and the level of stress, or if the difference is due to variation in curricula or cultural differences among the countries studied.
A certain amount of stress may be perceived as positive, enhancing an individual's ability to focus or increase the motivation to learn, but for college students much of the stress causes illness and psychological distress, including for health professional students.7,17,22,30-33 Rawson et al30 found a significant association between stress and illness in undergraduate students, while O'Meara et al7 and Frazer et al3 also identified this association in Masters level physical therapy students.
For student PTs, similar to other health care students,28 academic stress is a greater source of stress than personal or financial issues.1,3-7 Even the academic environment can be a source of stress—classrooms that were crowded, too hot, or too cold were named as significant sources of stress.3 One might expect that PT students who were employed in addition to attending classes would experience greater levels of stress due to time constraints; however, Walsh et al1 found low levels of stress in undergraduate PT students who worked part-time (10.8 hours on average), and studies of Bachelor and Masters PT students4,6 found no association between employment and levels of stress.
Stress can be managed if an individual possesses and uses appropriate resources to respond effectively. Individuals with greater resilience are better equipped to handle stress.34-36 “Resilience is a dynamic process wherein individuals display positive adaptation despite experiences of significant adversity or trauma.”37(p858) This description captures 2 basic components of resilience—adversity or hardship, and an affirmative, positive reaction to it. Not surprisingly, many believe that resilience cannot be demonstrated in the absence of adversity.36-39 Resilience resources, described as protective factors against stress, may mitigate the negative effects of stress. Examples of an individual's resilience resources include positive affect, dispositional optimism, perceived social support, and coping flexibility, among others.15,28,34,36,40-45
Fewer studies have demonstrated that college students have benefited from programs designed to increase levels of resilience. In a randomized controlled trial (RCT),8 undergraduate and graduate students participated in a 4-week resilience intervention during the final weeks of classes, a time of increased stress due to examinations. Participants demonstrated higher levels of resilience and protective factors against stress, and fewer psychological symptoms.8 In another RCT, graduate students who received an individualized resilience training program by computer demonstrated increased control over and recovery from stress compared to an attention-control student group who reviewed published information about stress.9 There are no published reports of resilience programs benefiting physical therapy students specifically, but it stands to reason that these types of curricula would also be an enhancement in physical therapy graduate education.
Student participants were recruited from 2 DPT educational programs in Indianapolis, IN—the University of Indianapolis and Indiana University. The author met with the DPT Program Director at each University to review the components and timeline of the intervention, and arranged for an email that described the study, to be delivered to all DPT students currently enrolled in any of the 3 years of the respective programs. There were no exclusion criteria. Personal visits were made to each of the 3 cohorts at each University to further explain the study and entertain questions from potential participants. Forty-three DPT student participants signed up for and completed the study and provided both baseline and follow-up survey data. No participants dropped out of the study.
Research Design and Procedures
This randomized, controlled trial was conducted at 2 universities to evaluate the effects of a resilience curriculum delivered to DPT students. Institutional Review Board approval was obtained by Rocky Mountain University of Health Professions, the University of Indianapolis, and Indiana University. Informed consent was obtained from all participants prior to data collection. The study process is demonstrated in Figure 1. This study was registered with ClinicalTrials.gov (ID D05500).
Participants who agreed to participate sent an email to a research assistant who assigned them a study code to use in place of their names for the duration of the study. The researcher was blinded to the identity of the participants for data collection. The random assignment function of Excel was used to randomly assign participants to the intervention group (n = 22) to receive the resilience curriculum or to a wait-list control group (n = 21). Participants were notified of this status by an email from the research assistant. Demographic and baseline assessment surveys were completed by both groups.
The resilience curriculum, “Stop Running on Empty!” was developed by the author using evidence of previously published resilience and stress management interventions and is described in detail elsewhere.46 The learning objectives of the curriculum are included in Table 1. The curriculum incorporated topics and techniques used in previous mental health prevention programs for college students.8,9,47-51 The face-to-face curriculum, presented by the researcher, involved education about components of resilience, skills building exercises, group and paired discussion, and homework exercises to practice the application of learned skills. Beginning in week 3 of the fall semester, the resilience curriculum was delivered in 4 consecutive 2-hour weekly sessions. Instead of delivering the curriculum in one 8-hour session, this schedule allowed participants time to reflect on each session's content and practice skills. This schedule also allowed the researcher the opportunity to review content from each of the previous sessions and address questions. Due to conflicting course schedules for different years of the program, the curriculum was presented to each cohort separately at the University of Indianapolis, and in the evening for all cohorts combined at Indiana University. The group sizes ranged from 4 to 7 students, and participants signed in using their code so attendance could be monitored for each session.
Data Collection Instruments
Online surveys were used to collect baseline demographic information, including sex, age, race, marital status, year of study, average number of hours worked outside of school (0–5 hours, 6–14 hours, or 15 hours or greater), institution, undergraduate major (exercise-related vs not exercise-related), history of psychological disorder, and Grade Point Average. The following survey tools were assessed for both groups at baseline, up to 2 weeks prior to the intervention, and again within 2 weeks after the intervention. All surveys were administered using Qualtrics Software Version 2016 (Qualtrics LLC, Provo, UT). Cronbach's alpha was measured for each instrument in this population. The total time to complete the surveys at baseline or postintervention was 25–45 minutes.
Connor-Davidson Resilience Scale
This 25-item tool52 measures characteristics of resilience, including hardiness, personal competence, social bonds, patience, and spiritual influences. Participants replied to items about psychological resilience in the past month, using a 5-point Likert scale. Scores for each item were summed, with the highest possible score of 100. Discriminant and convergent validity for this scale have been demonstrated; test–retest reliability has been reported at .87, and the reliability coefficient for the Connor-Davidson Resilience Scale (CD-RISC) ranges from .89 to .93.52,53 The CD-RISC has been studied in numerous populations including young adults and health professionals, in addition to college students.8,52-56
Perceived Stress Scale
The Perceived Stress Scale (PSS) was developed to assess “the degree to which situations in one's life are appraised as stressful,”57(p387) with higher scores indicating increased stress. Using a 5-point Likert scale, participants indicated the frequency, in the previous month, they experienced the feelings described. The scores of the 4 positively stated items were reverse coded and the scores for each of the 10 items were then summed, with the highest possible score equaling 40. The 10-item version of this tool was used as it had better psychometric properties than the other versions.58,59 In college students, internal reliability for this tool ranged from .74 to .91, and test–retest reliability was .77 when reflection involved the last 2 weeks.58,59 The PSS has been validated for ages 18–29 years and has been used extensively in studies of students.2,4,5,8,18,60,61
Coping Flexibility Scale
The Coping Flexibility Scale (CFS) is a 10-item tool used to measure the ability of an individual to effectively modify coping behavior.61 Kato61(p263) defines coping flexibility as “the ability to discontinue an ineffective coping strategy and produce and implement an alternative coping strategy.” Participants responded to the 10-item CFS scale using a 3-point Likert scale to reflect how a situation applied to them. Two items were reverse coded, and the scores for each of the 10 items of the CFS were then summed. The highest possible score was 30, with a higher score representing greater coping flexibility. The CFS contains 2 subscales: the Evaluation Coping subscale assesses the ability to consider the effectiveness of a coping strategy for a given situation, and the Adaptive Coping subscale measures the ability to change to a more effective strategy when needed. The CFS has demonstrated good to excellent overall reliability in college students (.73–.90); evaluation coping ranged from .71 to .91, while adaptive coping ranged from .83 to .90.61,62 In college students, the CFS had acceptable test–retest reliability (.71–.73), and both convergent and discriminant validity have been demonstrated.61
The Revised Life Orientation Test
The Revised Life Orientation Test (LOT-R) is a 10-item scale designed to measure dispositional optimism, with higher scores indicating higher optimism.63,64 Participants replied to items using a 5-point Likert scale. Four of 10 items in this survey were filler items and not scored, and 3 items were reverse coded, with the highest possible score of 30 for this tool. For a sample of undergraduate, masters, and doctoral students,8,65,66 internal reliability has been reported at .72.
Modified Differential Emotion Scale
The Modified Differential Emotion Scale (mDES) was used to measure positive and negative emotions of various states.66 Using a 5-point Likert scale and reflecting over the last 2 weeks, participants indicated the frequency they experienced the emotions described. For the average of the 9 items in the positive emotions subscale, a higher mean represented more positive moods, and for the average of the 8 items in the negative emotions subscale, a higher mean represented more negative moods. In a sample of college students and recent graduates, the internal reliability for this measure was .79 for the subscale of positive emotions and .69 for the negative emotions subscale, with discriminant validity demonstrated between the positive and negative scales.66,67
Social Provisions Scale
The Social Provisions Scale (SPS) is a 24-item assessment of perceived support from relationships with family, friends, and others.68,69 This scale assesses areas of social relationships with 6 subscales of 4 items each (Guidance Support, Reassurance of Worth, Social Integration, Attachment, Nurturance, and Reliable Alliance).68,69 Participants responded using a 4-point Likert scale, to items about perceived social support. After 12 of the items were reverse scored, the scores for each item were summed. For this scale, there was a possible high score of 96, with a higher score representing greater perceived social support. The SPS had excellent overall internal reliability of .92, with subscale reliability ranging from .65 to .76.68 This tool has been validated in a variety of populations, including college students.68
Symptoms of Illness Checklist
The Symptoms of Illness Checklist (SIC) is a 33-item tool designed to measure the number, frequency, and severity of physical symptoms in the previous 2 months, but has also been demonstrated to show sensitivity to discern changes within a 2-week period.70 Participants used a 4-point Likert scale to report symptom frequency, and a 5-point Likert scale to report symptom impact, of 32 separate symptoms during the previous 2 weeks. The item about blood pressure was not scored due to the lack of reliability that has been found for this item.70 The frequency score (1–4) was multiplied by the impact score (1–5) of each symptom, and these values were summed to compute the total SIC score. Each symptom could have contributed up to 20 points to the total score. Internal reliability of this instrument ranged from .75 to .86 for a sample of undergraduate students and a mixed group of community members and graduate students. There was also a high correlation between the SIC and an objective measure of physician interviews (.94).70
Follow-up assessments were collected anonymously from all participants using their assigned codes. These assessments were completed within 2 weeks after the intervention during the period of midterm examinations, a presumably stressful time for the students. The wait-list control group was offered a 2-hour condensed version of the curriculum 2 weeks after postintervention assessments.
Data analysis was completed using SPSS Version 23 (IBM Corporation, Armonk, NY). Missing values were replaced by the median values for the measure instead of the mean, since the data were not normally distributed.71 Cronbach's alpha was used to assess the internal reliability of the survey instruments.
Demographic differences between the intervention and wait-list control groups were analyzed using t tests to compare differences in mean values in data that were normally distributed, and a Mann–Whitney U nonparametric test was used for data that were not normally distributed. Fisher's exact test was used to compare differences in nominal data with small frequencies. Chi-square tests were used to compare differences in other nominal data.
To test the effectiveness of the curriculum, a 2 by 2 (group by time) mixed model analysis of variance (ANOVA) was used to analyze the survey outcomes that were normally distributed. For the survey outcomes that were not normally distributed, nonparametric Mann–Whitney U tests, to compare outcomes preintervention and postintervention, and Wilcoxon signed ranks tests, to compare intervention and control groups, were used.
To identify baseline predictors of stress or resilience measures in the intervention and control groups combined, Pearson's correlations were used to find bivariate associations between normally distributed continuous variables and the PSS and CD-RISC scores. Spearman's correlation was used for continuous variables that were not normally distributed. The association of binary nominal variables to PSS and CD-RISC was tested with a t-statistic. For nominal variables with greater than 2 levels, ANOVA was used. Baseline variables that demonstrated a significant association with PSS or CD-RISC in bivariate analyses were entered into a multiple linear regression model predicting resilience. Variables that were not statistically significant in the regression were dropped from the model.
Forty-three DPT students completed baseline and follow-up surveys. Attendance at the curriculum sessions ranged from 86% to 100%, with 15 participants attending all 4 sessions. Ten students from the wait-list control group attended the 2-hour condensed curriculum that was offered 2 weeks postintervention. Table 2 describes the baseline demographic characteristics of the intervention and control groups. Both groups consisted of predominantly White, female, single students, in their mid-20s. Fewer participants did not allow for meaningful analysis of the results by year in the program, race, or marital status. There were no statistically significant differences between the control and intervention groups on demographic characteristics.
A total of 14 individual item values were missing among the survey measures and replaced with median values. One participant did not include values for items 6–33 in the SIC. That participant's score for that measure was not included in the analysis. Reliability of the survey instruments, as measured by Cronbach's alpha, is shown in Table 3. Total scales and most subscales showed good to excellent internal reliability.
Table 4 depicts the mean and standard deviation, or the median and interquartile range (for nonnormally distributed variables), for all survey variables, and shows the results of the ANOVA group by time effect for each. There was a significant group by time interaction for the CD-RISC (F = 4.893, df = 1, P = .03), meaning the curriculum significantly improved resilience over time. This occurred despite the fact that the groups did not differ significantly at baseline. The mean difference in CD-RISC scores from baseline to postintervention for the intervention group (14.5% increase) was statistically significant (F = 7.015, df = 1, P = .01), and the mean difference in CD-RISC score for the control group (6.5% increase) was also statistically significant (F = 7.015, df = 1, P = .01).
There was also a significant group by time interaction for the positive emotions of the mDES (F = 5.730, df = 1, P = .02) even though the groups did not differ significantly at baseline. The mean difference in positive emotion scores of the mDES from baseline to postintervention for the intervention group was statistically significant (F = 19.507, df = 1, P < .001), but the mean difference for the control group was not statistically significant. There were no significant group by time interactions for measures of perceived stress, coping flexibility, negative emotions, optimism, social support, or illness symptoms. However, there was a significant increase in social support in both the intervention group (Z = 4.109, P < .01) and the control group (Z = 4.016, P < .01), from baseline to postintervention.
There were no statistically significant associations between baseline PSS scores and participant characteristics. The only statistically significant association between baseline participant characteristics and baseline CD-RISC scores was in hours worked (F = 4.076, df = 2, P = .02). Because there was a statistically significant association between hours worked and baseline resilience, this variable was entered into the regression equation.
Table 5 demonstrates the association between CD-RISC scores and the other survey measures. The 5 variables that were significantly associated with baseline resilience (baseline PSS, CFS, LOT-R, positive items of the mDES, and hours worked) were entered as predictor variables into a stepwise multiple linear regression model, predicting baseline resilience. Criterion to enter a variable into the model was P < .05, and the criterion to remove a variable was P < .10.71 Three predictor variables, i.e., PSS (t = −3.046, P = .004, B = −.370), CFS (t = 2.778, P = .008, B = .318), and positive items of the mDES (t = 2.387, P = .022, B = .296), remained significant and were retained in the model. The stepwise regression, ANOVA, F = 16.878, df = 3, P < .001, indicated a significant linear predictive model. The linear regression model accounted for 56.5% (R2 = .565) of the variation in the CD-RISC measure of resilience.
DISCUSSION AND CONCLUSION
This study demonstrated the effectiveness of a resilience intervention for students in 2 DPT educational programs. Doctor of Physical Therapy students who attended an 8-hour resilience curriculum had significantly greater increases in resilience, as measured by the CD-RISC, and positive emotions, as measured by the mDES, compared to students in the wait-list control group. Both groups experienced a significant increase over time in perceived social support. In addition, lower levels of perceived stress, higher positive emotions, and greater coping flexibility were found to be significant independent predictors of resilience at baseline. The literature describing associations of perceived stress level by gender, year of study, or hours of employment is mixed. The current study, likely due to the small sample size, found no significant associations with perceived stress in any of these areas.
Although it has been shown that resilience programs can improve levels of resilience in college students,8,9 this is the first, albeit small, RCT to demonstrate the effectiveness of a resilience program for DPT students in particular. Evidence of this curriculum's effectiveness is supported by the study design (RCT) where baseline differences in outcomes were controlled. Similar to the resilience curriculum studied by Steinhardt and Dolbier8 with undergraduates and graduate students, the current study also found significantly increased resilience and positive emotions and increased social support. However, unlike that study, the current study did not find decreased perceived stress, negative emotion, or symptoms of illness. Previous studies have reported a 4% increase in CD-RISC scores in a study of college freshman, an 11% increase in a sample of undergraduate and graduate students, and a 4% increase in a study of nursing students.72 The increase of 14.5% in CD-RISC scores by the intervention group in the current study compared to previous research was quite high, and even the wait-list control group's increase of 6.5% is greater than changes reported in previous literature.72
The finding that the wait-list control group also demonstrated increases in resilience and social support is interesting. Grouping DPT students in cohorts allows them to interact and become increasingly comfortable with each other, using one another for support. Since social support has been shown to decrease the stress response68,73-75 and is associated with resilience,52,54-56,74,76,77 instinctively relying on each other for instrumental and appraisal social support may serve to improve resilience of student PTs.
The current study found that lower stress levels, more positive emotions, and greater coping flexibility predicted greater resilience in DPT students. This is consistent with previous literature demonstrating the association of positive emotions and adaptive coping skills with resilience in other populations.28,36,54,78,79 Based on the findings of this study, the measures that appear to be most appropriate to predict resilience in the DPT student population are the PSS, CFS, and the mDES.
Previous literature cites the following norms for the PSS for samples of students: 4-year college (12.0 ± 5.6), graduate school (12.2 ± 5.4), and advanced degree (11.4 ± 5.2). The mean PSS scores for the current study (intervention pre [13.9 ± 5.0] and post [11.68 ± 5.1], control pre [13.9 ± 4.6] and post [13.60 ± 5.5]) demonstrate the sample of DPT students to be within the established norms for undergraduate and graduate students.
A variety of factors have been shown to influence resilience and stress management in student populations that are beyond the scope of this study. Mindfulness and other meditation techniques studied in health professional students and practitioners have been shown to be associated with lower levels of stress and increased resilience.50,51,78,80-82 Self-esteem and hardiness are characteristics that have been associated with higher levels of resilience in students.8,50,83-85 Many studies have also shown that physical activity may decrease stress, which may affect resilience.11,51,60,77,86-88 Since physical therapy students have been shown to exercise at higher levels than the average American,89,90 it is reasonable to assume that participants in both the intervention and the control groups engaged in physical activity in comparable amounts at baseline. However, since the resilience curriculum included information about the role of physical activity as part of a coping strategy, it is possible that the intervention group performed physical activity at higher levels compared to the wait-list control group. Additionally, psychological disorders such as depression and anxiety have been associated with higher levels of stress in students.21,29,30,52,91,92 In the current study, the psychological disorders of depression, anxiety, and eating disorder did not show statistically significant association with any outcomes, likely due to fewer participants. Even though the percentage of participants who reported a psychological condition (23%) appears excessive, it is in line with the presence of psychological distress and disorders in other studies of college students (up to 29%) in the United States and other countries.29,93-95 None of the other factors mentioned above were assessed for this study of resilience, and participants were not asked to alter any behaviors such as meditation or physical activity during the study period. These factors certainly could have affected the assessment of resilience and other outcome measures.
The time frame of the curriculum, based on that of a previous resilience program for college students,8 could be seen as a strength of the program. It allowed time for the researcher to review content at each subsequent session and also allowed time for participants to practice skills and complete the assigned homework in between sessions.
The main limitation of the study was the small sample size, limiting the extent to which true effects could be detected. Great efforts were taken to recruit more participants; all potential DPT students from the 2 programs were recruited by email and in person. Although several additional students inquired about the study, fewer than expected consented to participate. Even though the current program was shorter in duration than other stress management programs offered to college and health professional students,23,26,49,78,82 the 8-hour commitment may have appeared excessive for busy DPT students. Therefore, the study sample size was underpowered to detect some effects and predictors of stress and resilience.
Another limitation is the lack of outcomes to measure learning. Students offered anecdotal remarks during curriculum sessions, but no objective measures were used for assessment. At the beginning of each session when content from the previous session was reviewed, students presented examples of how they used the material during the previous week, suggesting that learning did occur. However, an objective assessment of learning should be included in future studies, along with a longitudinal component to demonstrate retention of information and application of resilience techniques.
An additional factor that may have affected the outcomes is that the resilience curriculum was not delivered to the entire intervention group at once, due to differing course schedules. This may have affected how components of the curriculum were perceived since not all participants heard the same discussion from peers. However, the smaller groups may have fostered more meaningful discussions.
Generalization of these findings to other entry-level PT education programs should be made with caution. The study sample was small and not diverse, consisting of mostly single, White, female students, in their mid-20s, from the Midwest. The age and gender differences in the study sample contrast those of recent student applicants according to American Physical Therapy Association data.96 The median age of recent applicants is younger (22–23 years of age) than the study participants, and the proportion of male participants (39.2%) to female participants (60.7%) is greater.96 Research with larger samples of diverse DPT students is needed to confirm these study results and to allow the data to be compared with other health disciplines.
Given the high risk for depression and anxiety in health profession students, Mazurek et al11 recommend early identification of mental health issues and the provision of support for mental health early in health professional graduate programs. Other researchers have recommended offering stress management programs to health professions students, including DPT students, to assist in managing high levels of stress.3,4,7,28,79,80,97-99 The current study supports addressing high levels of stress with a resilience program to increase positive emotions and improved resilience. Adding a resilience program to current DPT curricula may be an important way to manage the stress inherent in DPT education programs.
Physical therapists are called upon to address the physical and mental health needs of patients. This task may be better suited to health care providers who have experience with practicing effective resilience mechanisms themselves. This may allow practitioners to promote resilience to their patients and model it for their peers. Future research should focus on the outcomes of DPT students who have had resilience training compared to those who have not. Differences in resilience with respect to performance on written and practical examinations, clinical experiences, and performance on the National Physical Therapy Examination could be explored. In addition, the impact of resilience training on daily stress and burnout of PTs practicing in the clinical environment could be addressed.
The author would like to acknowledge the members of her Dissertation Committee who supported and advised her throughout the study process: Dr. Christyn Dolbier, Dr. Frederick May, and especially Dr. Janelle O'Connell, Dissertation Chair. The author would also like to thank the Directors of the Doctor of Physical Therapy Programs who supported this research, Dr. Peter Altenburger at Indiana University, and Dr. Stacie Fruth, formerly at the University of Indianapolis. Thanks also to Kathy deJong, research assistant at the University of Indianapolis. Finally, the author expresses appreciation for the students who participated in the study.
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