Mar 9, 2020 | Volume 10 - Issue 1
Michael T. Kalkbrenner
College counselors work collaboratively with professionals in a variety of disciplines in higher education to coordinate gatekeeper training to prepare university community members to recognize and refer students in mental distress to support services. This article describes the cross-validation of scores on the Mental Distress Response Scale (MDRS), a questionnaire for appraising university community members’ responses to encountering a student in mental distress, with a sample of faculty members. A confirmatory factor analysis revealed the dimensions of the MDRS were estimated adequately. Results also revealed demographic differences in faculty members’ responses to encountering a student in mental distress. The MDRS has implications for augmenting the outreach efforts of college counselors. For example, the MDRS has potential utility for enhancing campus-wide mental health screening efforts. The MDRS also has implications for supporting psychoeducation efforts, including gatekeeper training workshops, for professional counselors practicing in college settings.
Keywords: Mental Distress Response Scale, mental health, college counselors, gatekeeper, outreach
College counselors play crucial roles in supporting students’ personal, social, and academic growth, as well as students’ success (Golightly et al., 2017). Outreach and prevention programming, including campus violence prevention and supporting college student mental health, are two key elements in the practice of college counselors (Brunner et al., 2014; Golightly et al., 2017). Addressing these two key areas has become increasingly challenging in recent years because of the prevalence of campus violence incidents, including mass shootings in the most severe cases, and the frequency of mental health distress among college students, which has increased substantially since the new millennium (Auerbach et al., 2016; Barrett, 2014; Vieselmeyer et al., 2017). In fact, supporting college student mental health has become one of the greatest challenges that institutions of higher education are facing (Reynolds, 2013).
Most college students suffering from mental health issues do not seek treatment (Downs & Eisenberg, 2012). In response, college counselors, student affairs professionals, and higher education administrators are working collaboratively to develop and implement mental health awareness initiatives and gatekeeper training workshops, which include training university community members (e.g., students, faculty, and staff) as referral agents to recognize and refer students who are showing warning signs for suicide or other mental health issues to support services (Albright & Schwartz, 2017; Hodges et al., 2017). Faculty members are particularly valuable referral agents, as they tend to interact with large groups of students on frequent occasions, and they generally report positive attitudes about supporting college student mental health (Albright & Schwartz, 2017; Kalkbrenner, 2016).
Despite the utility of faculty members as gatekeepers for recognizing and referring students to the university counseling center and to other resources, the results of a recent national survey indicated that a significant proportion of faculty members (63%) do not refer a student in mental distress to support services (Albright & Schwartz, 2017). The literature is lacking research on how faculty members are likely to respond to encountering a student in mental distress, including but not limited to making a faculty-to-student referral to mental health support services. The primary aim of this investigation was to confirm the psychometric properties of the Mental Distress Response Scale (MDRS), a screening tool for measuring university community members’ responses to encountering a student in mental distress. Past investigators validated the MDRS for use with 4-year university students (Kalkbrenner & Flinn, 2020) and community college students (Kalkbrenner, 2019). If found valid for use with faculty members, college counselors could find the MDRS useful for screening and promoting faculty-to-student mental health support. A review of the extant literature is provided in the following section.
Mental Health and the State of Higher Education
Active shooter incidents on college campuses are some of the most tragic events in American history (Kalkbrenner, 2016). The 2015 massacre that occurred on a college campus in Oregon received attention at the highest level of government; former President Barack Obama urged the nation to decide when voting “whether this cause of continuing death for innocent people should be a relevant factor.” (Vanderhart et al., 2015, section A, p. 1). Seung-Hui Cho was a perpetrator of another one of these tragedies at Virginia Polytechnic Institute in 2007. According to Cho’s mother, he had a history of social isolation and unresolved mental health issues (Klienfield, 2007). Without treatment, the effects of mental health disorders can be debilitating and widespread for students, including impairments in academic functioning, attrition, self-harm, social isolation, and suicide or homicide in the most serious cases (Kalkbrenner, 2016; Shuchman, 2007). The early detection and treatment of students who are at risk for mental health disorders is a harm-prevention strategy for reducing campus violence incidents and promoting college student mental health (Futo, 2011; Kalkbrenner, 2016). Consequently, the practice of college counselors involves deploying outreach and systems-level mental health support interventions (Albright & Schwartz, 2017; Brunner et al., 2014; Golightly et al., 2017).
The Role of College Counselors in Providing Systems-Level Interventions
Providing individual counseling is a key role of college counselors (Golightly et al., 2017). In recent years, however, the practice of college counselors has been extended to providing systems-level and preventative mental health interventions to meet the growing mental health needs of college student populations (Brunner et al., 2014; Golightly et al., 2017). In particular, college counselors and their constituents engage in both campus-wide and targeted prevention and outreach programs (Golightly et al., 2017; Lynch & Glass, 2019), including gatekeeper training workshops to prepare university community members as referral agents or train them to recognize and refer students at risk for suicide and other mental health issues to the university counseling center (Albright & Schwartz, 2017; Brunner et al., 2014). These collaborative, educative, and preventative efforts are particularly crucial given the increase in both the severity and complexity of mental health disorders among college students (Gallagher, 2015; Reetz et al., 2016). The findings of past investigators suggest that faculty members are particularly viable referral agents for recognizing and referring students in mental distress to the counseling center (Kalkbrenner, 2016; Margrove et al., 2014).
Faculty Members as Referral Agents
Faculty members have a propensity to serve as referral agents (i.e., recognize and refer students in mental distress to resources) because of their frequent contact with students and their generally positive attitudes and willingness to support their students’ mental and physical wellness (Albright & Schwartz, 2017). Albright and Schwartz (2017) found that approximately 95% of faculty members and staff considered connecting students in mental distress to resources as one of their roles and responsibilities. Similarly, Margrove et al. (2014) found that 64% of untrained university staff members expressed a desire to receive training to recognize warning signs of mental health disorders in students.
Past investigators extended the line of research on the utility of faculty members as gatekeepers by identifying demographic differences by gender and help-seeking history (previous attendance in counseling) in faculty members’ tendency to support college student mental health (Kalkbrenner & Carlisle, 2019; Kalkbrenner & Sink, 2018). In particular, Kalkbrenner and Sink (2018) identified gender as a significant predictor of faculty-to-student counseling referrals, with faculty who identified as female more likely to make faculty-to-student referrals to the counseling center compared to their male counterparts. Similarly, Kalkbrenner and Carlisle (2019) found that faculty members’ awareness of warning signs for mental distress in students was a significant positive predictor of faculty-to-student referrals to the counseling center. In addition, faculty members with a help-seeking history (previous attendance in counseling) were significantly more aware of warning signs for mental distress in their students compared to faculty without a help-seeking history (Kalkbrenner & Carlisle, 2019).
Faculty Members’ Responses to Encountering a Student in Mental Distress
Despite the growing body of literature on institutional agents’ participation in gatekeeper training (i.e., recognize and refer), research on the measurement and appraisal of how faculty members are likely to respond when encountering a student in mental distress is in its infancy. The results of a recent national survey of college students (N = 51,294) and faculty members (N = 14,548) were troubling, as 63% of faculty members did not refer a student in psychological distress to mental health support services (Albright & Schwartz, 2017). Making a referral to the university counseling center is one possible response of students and faculty members to encountering a peer or student in mental distress (Kalkbrenner & Sink, 2018). However, the findings of Albright and Schwartz (2017) highlight a gap in the literature regarding how university community members are likely to respond when encountering a student in mental distress, including but not limited to making a faculty-to-student referral to the college counseling center.
To begin filling this gap in the literature, Kalkbrenner and Flinn (2020) developed, validated, and cross-validated scores on the MDRS to assess 4-year university students’ responses to encountering a student in mental distress, including but not limited to making a referral to mental health support services. In a series of two major phases of psychometric analyses, Kalkbrenner and Flinn identified and confirmed two dimensions or subscales of the MDRS, including Diminish/Avoid and Approach/Encourage, with two large samples of undergraduate students. The Diminish/Avoid subscale measures adverse or inactive responses of university community members to encountering a student in mental distress (e.g., stay away from the person or warn the person that mental issues are perceived as a weakness). The Approach/Encourage subscale appraises facilitative or helpful responses of university community members when encountering a student in mental distress that are likely to help connect the person to resources (e.g., talking to a college counselor or suggesting that the person go to the campus counseling or health center). However, the psychometric properties of the MDRS have not been tested with faculty members. If found valid for such purposes, the MDRS could be a useful tool that college counselors and their constituents can use to screen and promote faculty-to-student referrals to mental health support services. In particular, the following research questions were posed: (1) Does the two-dimensional hypothesized MDRS model fit with a sample of faculty members? and (2) To what extent are there demographic differences in faculty members’ responses to encountering a student in mental distress?
Participants and Procedures
Data were collected electronically from faculty members using Qualtrics, a secure e-survey platform. A nonprobability sampling procedure was used by sending a recruitment email message with an electronic link to the survey to 1,000 faculty members who were teaching at least one course at a research-intensive, mid-Atlantic public university at the time of data collection. A total of 221 faculty members clicked on the electronic link to the survey and 11 responses were omitted from the data set because of 100% missing data, resulting in a useable sample size of 210, yielding a response rate of 21%. This response rate is consistent with the response rates of other investigators (e.g., Brockelman & Scheyett, 2015; Kalkbrenner & Carlisle, 2019) who conducted survey research with faculty members. For gender, 58% (n = 122) identified as female, 41% (n = 86) as male, and 0.5% (n = 1) as non-binary or third gender, and 0.5% (n = 1) did not specify their gender. For ethnicity, 79.0% (n = 166) identified as Caucasian, 6.2% (n = 11) as African American, 3.8% (n = 8) as Hispanic or Latinx, 2.9% (n = 6) as Asian, 2.9% (n = 6) as multiethnic, 0.5% (n = 1) as Hindu, and 0.5% (n = 1) as Irish, and 5.2% (n = 11) did not specify their ethnic identity. Participants ranged in age from 31 to 78 (M = 50; SD = 11). Participants represented all of the academic colleges in the university, including 28.6% (n = 60) Arts and Letters, 22.9% (n = 48) Education, 18.1% (n = 38) Sciences, 12.9% (n = 27) Health Sciences, 9% (n = 19) Engineering and Technology, and 7.6% (n = 16) Business, while 1% (n = 2) of participants did not specify their college.
Following informed consent, participants were asked to indicate that they met the inclusion criteria for participation, including (1) employment as a faculty member, and (2) teaching at least one course at the time of data collection. Participants then responded to a succession of demographic items about their gender, ethnicity, age, academic college, and highest level of education completed. Lastly, respondents indicated their rank and help-seeking history (previous attendance in counseling or no previous attendance in counseling) and if they had referred at least one student to mental health support services.
Mental Distress Response Scale (MDRS)
The MDRS is a screening tool comprised of two subscales (Approach/Encourage and Diminish/Avoid) for measuring university community members’ responses to encountering a student in mental distress (Kalkbrenner & Flinn, 2020). The items that mark the Approach/Encourage subscale appraise responses to mental distress that are consistent with providing support and encouragement to a student in mental distress (e.g., “suggest that they go to the health center on campus”). The Diminish/Avoid subscale measures adverse or inactive responses to encountering a student in mental distress (e.g., “try to ignore your concern”). Kalkbrenner and Flinn (2020) found adequate reliability evidence for an attitudinal measure (α > 0.70) and initial validity evidence for the MDRS in two major phases of analyses (exploratory and confirmatory factor analysis [CFA]) with two samples of college students. Kalkbrenner (2019) extended the line of research on the utility of the MDRS for use with community college students and found adequate reliability (α > 0.80) and validity evidence (single and multiple-group confirmatory analysis).
A CFA based on structural equation modeling was computed using IBM SPSS Amos version 25 to cross-validate scores on the MDRS with a sample of faculty members (research question #1). Using a maximum likelihood estimation method, the following goodness-of-fit indices and thresholds for defining model fit were investigated based on the recommendations of Byrne (2016) and Hooper et al. (2008): Chi square absolute fit index (CMIN, non-significant p-value with an x2/df ratio < 3), comparative fit index (CFI > 0.95), incremental fit index (IFI > 0.95), Tucker-Lewis index (TLI > 0.95), goodness-of-fit index (GFI > 0.95), root mean square error of approximation (RMSEA < 0.07), and standardized root mean square residual (SRMR < 0.08). Based on the findings of past investigators (e.g., Kalkbrenner & Sink, 2018) regarding demographic differences in faculty members’ propensity to support college student mental health, a 2 X 2 (gender X help-seeking history) MANOVA was computed to investigate demographic differences in faculty members’ responses to encountering a student in mental distress (research question #2). The independent variables included gender (male or female) and help-seeking history (previous attendance in counseling or no previous attendance in counseling). Discriminant analysis was used as the post hoc procedure for significant findings in the MANOVA (Warne, 2014). The researcher examined both main effects and interaction effects and applied Bonferroni adjustments to control for the familywise error rate.
The researcher ensured that the data set met the necessary assumptions for CFA (Byrne, 2016; Field, 2018). A missing values analysis revealed that less than 5% of data was missing for all MDRS items. Little’s Missing Completely at Random (MCAR) test revealed that the data was missing at random: χ2 (387) = 407.98, p = 0.22. Expectation maximization was used to impute missing values. Outliers were winsorized (Field, 2018) and skewness and kurtosis values for the MDRS items (see Table 1) were largely consistent with a normal distribution (+ 1; Mvududu & Sink, 2013). Inter-item correlations between the 10 items were favorable for CFA, and Mahalanobis d2 indices revealed no extreme multivariate outliers. The researcher ensured that the sample size was sufficient for CFA by following the guidelines provided by Mvududu and Sink (2013), including at least 10 participants per estimated parameter with a sample > 200.
Descriptive Statistics for MDRS Items
|1. I would stay away from this person
|2. Suggest that they go to the health center on campus
|3. Try to ignore your concern
|4. Take them to a party
|5. Tell them to “tough it out” because they will feel better over time
|6. Suggest that they see a medical doctor on campus
|7. Avoid this person
|8. Suggest that they see a medical doctor in the community
|9. Warn the person that others are likely to see their mental health issues as a weakness
|10. Talk to a counselor about your concern
SEKurtosis = 0.15, SESkewness = 0.17.
Note. Values were winsorized and reported as standardized t-scores (M = 50; SD = 10).
The 10 MDRS items (see Table 1) were entered in the CFA. A strong model fit emerged based on the GFI recommended by Byrne (2016) and Hooper et al. (2008). The CMIN absolute fit index demonstrated no significant differences between the hypothesized model and the data: χ2 (34) = 42.41, p = 0.15, CMIN/df = 1.25. In addition, the CFI = 0.98, GFI = 0.96, IFI = 0.98, TLI = 0.98, RMSEA = 0.03, 90% confidence interval [<.00, .06], and SRMR = 0.05 also demonstrated a strong model fit. Internal consistency reliability analyses (Cronbach’s coefficient alpha) revealed satisfactory reliability coefficients for an attitudinal measure, Diminish/Avoid (α = 0.73) and Approach/Encourage (α = 0.70). In addition, the path model coefficient (-0.04) between factors supported the structural validity of the scales (see Figure 1).
Confirmatory Factor Analysis Path Diagram for the Mental Distress Response Scale
Note. CFA = confirmatory factor analysis, MDRS = Mental Distress Response Scale.
A 2 X 2 (gender X help-seeking history) MANOVA was computed to investigate demographic differences in faculty members’ responses to encountering a student in mental distress (research question #2). G*Power was used to conduct an a priori power analysis (Faul et al., 2007) and revealed that a minimum sample size of 151 would provide a 95% power estimate, α = .05, with a moderate effect size, F2(v) = 0.063. A significant main effect emerged for gender: F(3, 196) = 8.27, p < 0.001, Wilks’ λ = 0.92, = 0.08. The MANOVA was followed up with a post hoc discriminant analysis based on the recommendations of Warne (2014). The discriminant function significantly discriminated between groups: Wilks’ λ = 0.91, X2 = 18.85, df = 2, p < 0.001. The correlations between the latent factors and discriminant function showed that Diminish/Avoid loaded more strongly on the function (r = 0.98) than Approach/Encourage (r = 0.29), suggesting that Diminish/Avoid contributed the most to group separation in gender. The mean discriminant score on the function was -0.27 for participants who identified as female and 0.37 for participants who identified as male.
The results of tests of internal consistency reliability (Cronbach’s coefficient alpha), CFA, and correlations between factors supported the psychometric properties of the MDRS with a sample of faculty members. The results of the CFA were promising as GFI demonstrated a strong model fit between the two-dimensional hypothesized MDRS model and a sample of faculty members (research question #1). In particular, based on one of the most conservative and rigorous absolute fit indices, the CMIN (Byrne, 2016; Credé & Harms, 2015), the researchers retained the null hypothesis—there were no significant differences between the hypothesized factor structure of the MDRS and a sample of faculty members. The strong model fit suggests that Approach/Encourage and Diminish/Avoid are two latent variables that comprise faculty members’ responses to encountering a student in mental distress. The findings of the CFA add to the extant literature about the utility of the MDRS for use with 4-year university students (Kalkbrenner & Flinn, 2020), community college students (Kalkbrenner, 2019), and now with faculty members.
An investigation of the path model coefficient between subscales (see Figure 1) revealed a small and negative association between factors, which supports the structural validity of the MDRS. In particular, the low and negative relationship between the Approach/Encourage and Diminish/Avoid subscales indicates that the dimensions of the MDRS are measuring discrete dimensions of a related construct. As expected, faculty members who scored higher on the Approach/Encourage subscale tended to score lower on the Diminish/Avoid subscale. However, the low strength of the association between factors suggests that faculty members’ responses to encountering a student in mental distress might not always be linear (e.g., a strong positive approach/encourage response might not always be associated with a strong negative diminish/avoid response). Haines et al. (2017) demonstrated that factors in the environment and temperament of a person showing signs of mental distress were significant predictors of mental health support staff’s perceptions of work safety. It is possible that under one set of circumstances faculty members might have an approach/encourage response to mental distress. However, under a difference set of circumstances, a faculty member might have a diminish/avoid response. For example, the extent to which a faculty member feels threatened or unsafe might mediate their propensity of having diminish/avoid or approach/encourage responses. Future research is needed to evaluate this possibility.
Consistent with the findings of previous researchers (Kalkbrenner & Carlisle, 2019; Kalkbrenner & Sink, 2018), the present investigators found that faculty members who identified as male were more likely to report a diminish/avoid response to encountering a student in mental distress compared to female faculty members. Similarly, Kalkbrenner and Sink (2018) found that male faculty members were less likely to make faculty-to-student referrals to the counseling center, and Kalkbrenner and Carlisle (2019) found that male faculty members were less likely to recognize warning signs of mental distress in college students. Similarly, the multivariate results of the present investigation revealed that male faculty members were more likely to report a diminish/avoid response to encountering a student in mental distress when compared to female faculty members. The synthesized findings of Kalkbrenner and Carlisle (2019), Kalkbrenner and Sink (2018), and the present investigation suggest that faculty members who identify as male might be less likely to recognize and refer a student in mental distress to mental health support services. The MDRS has valuable implications for enhancing the practice of professional counselors in college settings.
Implications for Counseling Practice
Outreach, consultation, and psychoeducation are essential components in the practice of college counselors (Brunner et al., 2014; Golightly et al., 2017). The findings of the present investigation have a number of practical implications for enhancing college counselors’ outreach and psychoeducation work—for example, gatekeeper workshops geared toward promoting faculty-to-student referrals to mental health support resources. The complex and multidimensional nature of college student mental health issues calls for interdisciplinary collaboration between college counselors and professionals in a variety of disciplinary orientations in higher education (Eells & Rockland-Miller, 2011; Hodges et al., 2017). College counselors can take leadership roles in coordinating these collaborative efforts to support college student mental health. In particular, college counselors can work with student affairs officials, higher education administrators, and their constituents, and attend new faculty orientations as well as department meetings to administer the MDRS, establish relationships with faculty, and discuss the benefits of gatekeeper training as well as supporting college student mental health. The results of the MDRS can be used to gain insight into the types of responses that faculty members are likely to have when encountering a student in mental distress. This information can be used to structure the content of gatekeeper training workshops aimed at promoting faculty-to-student referrals to mental health support services. Specifically, college counselors might consider the utility of integrating brief interventions and skills training components into gatekeeper training workshops. Motivational interviewing, for example, is an evidence-based, brief approach to counseling that includes both person-centered and directive underpinnings with utility for increasing clients’ intrinsic motivation to make positive changes in their lives (Iarussi, 2013; Resnicow & McMaster, 2012). Professional counselors who practice in higher education are already using motivational interviewing to promote college student development and mental health (Iarussi, 2013). Although future research is needed, integrating motivational interviewing principles (e.g., expressing empathy, rolling with resistance, developing discrepancies, and supporting self-efficacy; Iarussi, 2013) into gatekeeper training workshops might increase faculty members’ commitment to supporting college student mental health.
The MDRS has the potential to enhance college counselors’ outreach and mental health screening efforts (Golightly et al., 2017). College counselors can incorporate the MDRS into batteries of pretest/posttest measures (e.g., the MDRS with a referral self-efficacy measure) for evaluating the effectiveness of mental health awareness initiatives and gatekeeper training programs for faculty and other members of the campus community. If administered widely, the MDRS might have utility for assessing faculty members’ responses to students in mental distress across time and among various campus ecological systems, providing data to drive the prioritization and allocation of outreach efforts aimed at facilitating and maintaining referral networks for connecting students in mental distress to support services.
The results of the present study have policy implications related to campus violence prevention programming. The sharp increase in campus violence incidents has resulted in several universities implementing threat assessment teams as a harm-prevention measure (Eells & Rockland-Miller, 2011). Threat assessment teams involve an interdisciplinary collaboration of university faculty and staff for the purposes of recognizing and responding to students who are at risk of posing a threat to themselves or to others. College counselors can take leadership roles in establishing and supporting threat assessment teams at their universities. College counselors can administer the MDRS to faculty and staff and use the results as one way to identify potential threat assessment team members. University community members who score higher on the Approach/Encourage scale might be inclined to serve on threat assessment teams because of their propensity to support college student mental health. The brevity (10 questions) and versatility of administration (paper copy or electronically via laptop, smartphone, or tablet) of the MDRS adds to the practicality of the measure. Specifically, it might be practical for college counselors and their constituents to administer the MDRS during new faculty orientations, annual opening programs, or department meetings, or via email to faculty and staff. Results can potentially be used to recruit threat assessment team members.
Our findings indicate that when compared to their female counterparts, male faculty members might be more likely to have a diminish/avoid response when encountering a student in mental distress. College counselors might consider working collaboratively with student affairs professionals to implement gatekeeper training and mental health awareness workshops in academic departments that are comprised of high proportions of male faculty members. It is possible that male faculty members are unaware of how to identify warning signs of mental distress in their students (Kalkbrenner & Carlisle, 2019). College counselors might consider the utility of distributing psychoeducation resources for recognizing students in mental distress to faculty and staff. As just one example, the REDFLAGS model is an acronym of eight red flags or warning signs for identifying students who might be struggling with mental health issues (Kalkbrenner, 2016). Kalkbrenner and Carlisle (2019) demonstrated that the REDFLAGS model is a promising psychoeducational tool, as faculty members’ awareness of the red flags was a significant positive predictor of faculty-to-student referrals to the counseling center. The REDFLAGS model appears to be a practical resource for college counselors that can be distributed to faculty electronically or by paper copy, or posted as a flyer (Kalkbrenner, 2016; Kalkbrenner & Carlisle, 2019).
Limitations and Future Research
The findings of the present study should be considered within the context of the limitations. A number of methodological limitations (e.g., self-report bias and social desirability) can influence the validity of psychometric designs. In addition, the dichotomous nature of the faculty-to-student counseling referral variable (referred or not referred) did not provide data on the frequency of referrals. Future researchers should use a continuous variable (e.g., the number of student referrals to the counseling center in the past 2 years) to appraise faculty-to-student referrals. Future researchers can further test the psychometric properties of the MDRS through cross-validating scores on the measure with additional, unique populations of faculty members from a variety of different geographic and social locations. Invariance testing can be computed to examine the degree to which the MDRS and its dimensions maintain psychometric equivalence across different populations of faculty members. In addition, the criterion validity of the MDRS can be examined by testing the extent to which respondents’ MDRS scores are predictors of their frequency of student referrals to the counseling center and to other resources. Furthermore, future qualitative research is needed to investigate faculty members’ unique experiences around supporting college student mental health.
The low and negative association between the Approach/Encourage and Diminish/Avoid subscales suggests that faculty members might have an approach/encourage response to encountering a student in mental distress under one set of circumstances; however, they might have a diminish/avoid response under a difference set of circumstances. Future investigators might test the extent to which attitudinal variables mediate respondents’ MDRS scores—for example, the extent to which faculty members’ sense of safety predicts their MDRS scores. In addition, given the widespread public perception of individuals living with mental illness as violent and dangerous (Varshney et al., 2016), future researchers might identify demographic and background differences (particularly mental health stigma) among participants’ MDRS scores.
Summary and Conclusion
Mental health outreach and screening are essential components in the practice of college counselors, including training referral agents to recognize and refer students who might be struggling with mental health distress to support services (Golightly et al., 2017). Taken together, the results of the present study indicate that the MDRS and its dimensions were estimated sufficiently with a sample of faculty members. Our findings confirmed the two-dimensional hypothesized model for the types of responses that faculty might have when encountering a student showing signs of mental distress. In particular, the results of a CFA provided support for the MDRS and its dimensions, confirming a two-dimensional construct for the types of responses (approach/encourage and diminish/avoid) that faculty members might have when encountering a student in mental distress. Considering the utility of faculty members as gatekeepers and referral agents (Hodges et al., 2017; Kalkbrenner, 2016), researchers, practitioners, and policymakers may find the MDRS a useful screening tool for identifying the ways in which faculty members are likely to respond when encountering a student in mental distress. Results can be used to inform the content of mental health awareness initiatives and gatekeeper training programs aimed at promoting approach/encourage responses to connect students who need mental health support to the appropriate resources.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
Albright, G. & Schwartz, V. (2017). Are campuses ready to support students in distress?: A survey of 65,177 faculty, staff, and students in 100+ colleges and universities. https://www.jedfoundation.org/wp-content/uploads/2017/10/Kognito-JED-Are-Campuses-Ready-to-Support-Students-in-Distress.pdf
Auerbach, R. P., Alonso, J., Axinn, W. G., Cuijpers, P., Ebert, D. D., Green, J. G., Hwang, I., Kessler, R. C., Liu, H., Mortier, P., Nock, M. K., Pinder-Amaker, S., Sampson, N. A., Aguilar-Gaxiola, S., Al-Hamzawi, A., Andrade, L. H., Benjet, C., Caldas-de-Almeida, J. M., Demyttenaere, K., . . . Bruffaerts, R. (2016). Mental disorders among college students in the World Health Organization World Mental Health Surveys. Psychological Medicine, 46, 2955–2970. https://doi.org/10.1017/S0033291716001665
Barrett, D. (2014, September 24). Mass shootings on the rise, FBI says. The Wall Street Journal. http://online.wsj.com/articles/mass-shootings-on-the-rise-fbi-says-1411574475
Brockelman, K. F., & Scheyett, A. M. (2015). Faculty perceptions of accommodations, strategies, and psychiatric advance directives for university students with mental illnesses. Psychiatric Rehabilitation Journal, 38, 342–348. https://doi.org/10.1037/prj0000143
Brunner, J. L., Wallace, D. L., Reymann, L. S., Sellers, J.-J., & McCabe, A. G. (2014). College counseling today: Contemporary students and how counseling centers meet their needs. Journal of College Student Psychotherapy, 28, 257–324. https://doi.org/10.1080/87568225.2014.948770
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
Credé, M., & Harms, P. D. (2015). 25 years of higher-order confirmatory factor analysis in the organizational sciences: A critical review and development of reporting recommendations. Journal of Organizational Behavior, 36, 845–872. https://doi.org/10.1002/job.2008
Downs, M. F., & Eisenberg, D. (2012). Help seeking and treatment use among suicidal college students. Journal of American College Health, 60, 104–114. https://doi.org/10.1080/07448481.2011.619611
Eells, G. T., & Rockland-Miller, H. S. (2011). Assessing and responding to disturbed and disturbing students: Understanding the role of administrative teams in institutions of higher education. Journal of College Student Psychotherapy, 25, 8–23. https://doi.org/10.1080/87568225.2011.532470
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. https://doi.org/10.3758/BF03193146
Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). SAGE.
Futo, J. (2011). Dealing with mental health issues on campus starts with early recognition and intervention. Campus Law Enforcement Journal, 41, 22–23.
Gallagher, R. P. (2015). National survey of college counseling centers 2014. http://d-scholarship.pitt.edu/id/eprint/28178
Golightly, T., Thorne, K., Iglesias, A., Huebner, E., Michaelson-Chmelir, T., Yang, J., & Greco, K. (2017). Outreach as intervention: The evolution of outreach and preventive programming on college campuses. Psychological Services, 14, 451–460. https://doi.org/10.1037/ser0000198
Haines, A., Brown, A., McCabe, R., Rogerson, M., & Whittington, R. (2017). Factors impacting perceived safety among staff working on mental health wards. BJPsych Open, 3, 204–211.
Hodges, S. J., Shelton, K., & King Lyn, M. M. (2017). The college and university counseling manual: Integrating essential services across the campus. Springer.
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6, 53–60.
Iarussi, M. M. (2013). Examining how motivational interviewing may foster college student development. Journal of College Counseling, 16(2), 158–175. https://doi.org/10.1002/j.2161-1882.2013.00034.x
Kalkbrenner, M. T. (2016). Recognizing and supporting students with mental health disorders: The REDFLAGS Model. Journal of Education and Training, 3, 1–13. https://doi.org/10.5296/jet.v3i1.8141
Kalkbrenner, M. T. (2019). Peer-to-peer mental health support on community college campuses: Examining the factorial invariance of the Mental Distress Response Scale. Community College Journal of Research and Practice. https://doi.org/10.1080/10668926.2019.1645056
Kalkbrenner, M. T., & Carlisle, K. L. (2019). Faculty members and college counseling: Utility of The REDFLAGS Model. Journal of College Student Psychotherapy. https://doi.org/10.1080/87568225.2019.1621230
Kalkbrenner, M. T., & Flinn, R. F. (2020). Development, validation, and cross-validation of the Mental Distress Reaction Scale (MDRS). Journal of College Student Development.
Kalkbrenner, M. T., & Sink, C. A. (2018). Development and validation of the College Mental Health Perceived Competency Scale. The Professional Counselor, 8, 175–189. https://doi.org/10.15241/mtk.8.2.175
Kleinfield, N. R. (2007, April 22). Before deadly rage, a life consumed by a troubling silence. The New York Times. http://www.nytimes.com/2007/04/22/us/22vatech.html?pagewanted=all
Lynch, R. J., & Glass, C. R. (2019). The development of the Secondary Trauma in Student Affairs Professionals Scale (STSAP). Journal of Student Affairs Research and Practice, 56, 1–18.
Margrove, K. L., Gustowska, M., & Grove, L. S. (2014). Provision of support for psychological distress by university staff, and receptiveness to mental health training. Journal of Further and Higher Education, 38, 90–106. https://doi.org/10.1080/0309877X.2012.699518
Mvududu, N. H., & Sink, C. A. (2013). Factor analysis in counseling research and practice. Counseling Outcome Research and Evaluation, 4, 75–98. https://doi.org/10.1177/2150137813494766
Reetz, D. R., Bershad, C., LeViness, P., & Whitlock, M. (2016). The Association for University and College Counseling Center Directors annual survey. https://www.aucccd.org/assets/documents/aucccd%202016%
Resnicow, K., & McMaster, F. (2012). Motivational interviewing: Moving from why to how with autonomy support. International Journal of Behavioral Nutrition and Physical Activity, 9, 19.
Reynolds, A. L. (2013). College student concerns: Perceptions of student affairs practitioners. Journal of College Student Development, 54, 98–104. https://doi.org/ 10.1353/csd.2013.0001
Shuchman, M. (2007). Falling through the cracks—Virginia Tech and the restructuring of college mental health services. The New England Journal of Medicine, 357, 105–110. https://doi.org/10.1056/NEJMp078096
Vanderhart, D., Johnson, K., & Turkewitz, J. (2015, October 2). Oregon shooting at Umpqua College kills 10, sheriff says. The New York Times. https://www.nytimes.com/2015/10/02/us/oregon-shooting-umpqua-community-college.html?smid=pl-share
Varshney, M., Mahapatra, A., Krishnan, V., Gupta, R., & Deb, K. S. (2016). Violence and mental illness: What is the true story? Journal of Epidemiology & Community Health, 70, 223–225.
Vieselmeyer, J., Holguin, J., & Mezulis, A. (2017). The role of resilience and gratitude in posttraumatic stress and growth following a campus shooting. Psychological Trauma: Theory, Research, Practice, and Policy, 9, 62–69. https://doi.org/10.1037/tra0000149
Warne, R. T. (2014). A primer on multivariate analysis of variance (MANOVA) for behavioral scientists. Practical Assessment, Research & Evaluation, 19(17), 1–10.
Michael T. Kalkbrenner, PhD, NCC, is an assistant professor at New Mexico State University. Correspondence can be addressed to Michael Kalkbrenner, 1220 Stewart St., OH202B, NMSU, Las Cruces, NM 88001, firstname.lastname@example.org.
Jun 28, 2018 | Volume 8 - Issue 2
Michael T. Kalkbrenner, Christopher A. Sink
College counselors provide training to their campus constituents on various mental health issues, including the identification of warning signs and the referral of students to appropriate resources. Though extensive information on these topics is available in the counseling literature, college counselors lack a psychometrically sound screening instrument to support some of these educational efforts. To meet this need, the present researchers developed and validated the College Mental Health Perceived Competency Scale (CMHPCS). Based largely on self-determination theory, the measure appraises college student and faculty members’ perceived competence for supporting student mental health. Reliability and construct validity of the CMHPCS are demonstrated through exploratory and confirmatory factor analyses. Hierarchical logistic regression procedures yielded sufficient evidence of the CMHPCS’s predictive validity. Specific applications to assist college counselors with outreach and consultation are discussed.
Keywords: College Mental Health Perceived Competency Scale, college counselors, confirmatory factor analysis, hierarchical logistic regression, screening instrument
The prevalence and complexity of mental health disorders remain a serious concern for mental health professionals working in university and college settings in the United States and internationally (Lee, Ju, & Park, 2017). Another distressing trend is the incongruity between the relatively high frequency of students living with mental health disorders and the small number of students who receive needed treatment (Eisenberg, Hunt, Speer, & Zivin, 2011). Preliminary evidence shows that faculty members, staff, and college student peers might serve as helpful counseling referral agents for individuals at risk for mental health disorders (Kalkbrenner, 2016; White, Park, Israel, & Cordero, 2009). Identifying and training counseling referral agents (e.g., student peers and faculty members) to recognize and refer students to the counseling center is a key role of college counselors (Brunner, Wallace, Reymann, Sellers, & McCabe, 2014; Sharkin, 2012).
The purpose of the present study was to develop and validate a scale for appraising student and faculty members’ perceived competence for supporting college student mental health. Throughout the present study, “perceived competence for supporting college student mental health” refers to the extent to which university community members are confident in their ability to promote a campus climate that is supportive, accepting, and facilitative toward mental wellness. The College Mental Health Perceived Competency Scale (CMHPCS) has potential to aid college counselors with identifying and training university community members (e.g., student peers and faculty) to recognize issues and refer their peers and students to campus counseling services. In the following section, we provide an overview of the pertinent literature.
Undergraduates in Western countries are typically in late adolescence, a period when mental disorders are most likely to emerge, and college students report more frequent mental health concerns than other age groups (de Lijster et al., 2017; Eisenberg et al., 2011). Despite this reality, Eisenberg et al. (2011) indicated that only 20% of college students with mental health disorders were actively seeking treatment. Research suggests that there are common factors contributing to students’ underutilization of counseling services, including: stigma, gender, culture, experience and knowledge (mental health literacy), fear, and accessibility (Brunner et al., 2014; Marsh & Wilcoxon, 2015). For example, many undergraduates are simply unaware of the campus counseling services provided by their universities (Dobmeier, Kalkbrenner, Hill, & Hernández, 2013). Relatedly, college students’ general knowledge of mental health issues varies substantially. Kalkbrenner, James, and Pérez-Rojas (2018) found that students who attended at least one session of personal counseling reported a significantly higher awareness of warning signs for mental distress when compared to students who had not attended counseling. Other evidence suggests that the perceived stigma associated with obtaining mental health support can be a barrier to treatment (Rosenthal & Wilson, 2016) for college students.
Demographic differences exist in college students’ counselor-seeking behavior, with female students reporting a greater willingness to pursue counseling and to refer peers to resources for mental distress when compared to male students (Kalkbrenner & Hernández, 2017; Yorgason, Linville, & Zitzman, 2008). Students from ethnic minority groups also underutilize counseling centers’ mental health services (Han & Pong, 2015; Li, Marbley, Bradley, & Lan, 2016). In addition, Eisenberg, Goldrick-Rabe, Lipson, and Broton (2016) identified differences in college students’ utilization of resources for mental distress by age, with younger students (under 25) being particularly vulnerable to living with untreated mental issues. To enhance access and usage of counseling services by all college students, these variables must be seriously considered by campus policymakers and mental health practitioners.
Given this situation, college counselors must not only address the increased demand for counseling services, they may need to enhance prevention services as well. These latter activities include outreach, consultation, and education of university community members (e.g., student peers and faculty members). For instance, counselors educate students and faculty members on recognizing the warning signs of mental health distress in themselves and others (Brunner et al., 2014). Training also is commonly provided to campus members on the referral process. Participants learn the skills needed to guide others (e.g., students at risk for mental health disorders) to appropriate counseling and related services (Brunner et al., 2014; Sharkin, 2012). Preliminary investigations support these efforts, and faculty members, staff, and college student peers have been found to be helpful referral agents (Kalkbrenner, 2016; White et al., 2009).
Although research shows that students and faculty members are viable referral sources (Kalkbrenner, 2016; White et al., 2009), Albright and Schwartz’s (2017) national survey of these groups found that approximately half of their respondents felt unprepared to recognize the warning signs of mental distress in others. Based on these findings, as suggested above, college counselors may need to revise the content and delivery of their mental health–related training. Moreover, the literature appears to be lacking a psychometrically sound screening tool to assist with this effort. To help fill this instrumentation gap, the authors developed a brief questionnaire for college counselors to appraise student and faculty members’ perceived competence for supporting college student mental health.
Theoretical Foundation for Measurement Instrument
The first step in designing a measurement instrument involves the use of theory to guide the item development process (DeVellis, 2016). In recent years, self-determination theory (SDT), a psychological orientation to human motivation, is increasingly deployed by counseling researchers as an orienting conceptual framework (Adams, Little, & Ryan, 2017; Ryan & Deci, 2000; Ryan, Lynch, Vansteenkiste, & Deci, 2011). Aligned with this trend, SDT guided the item development for the CMHPCS. This perspective conceptualizes motivation in terms of the extent to which one’s behaviors are autonomous (self-motivated) contrasted with the extent to which behaviors are coerced or pressured (Patrick & Williams, 2012). Leading SDT proponents contend that the satisfaction of people’s needs is essential to foster their intrinsic motivation (i.e., a person’s autonomous or self-generated behaviors; Patrick & Williams, 2012; Ryan & Deci, 2000). Key elements of this approach include one’s perceptions of self-competence, autonomy, and relatedness to others (Ryan & Deci, 2000). Evidence suggests that increases in the extent to which individuals feel competent that they can perform an action or behavior are associated with increases in their motivation to participate in that action or behavior (Adams et al., 2017; Jeno & Diseth, 2014).
Elements of SDT are utilized in various helping professions, including psychiatry (Piltch, 2016), medicine (Mancini, 2008), and college counseling (A. E. Williams & Greene, 2016). Research suggests that SDT is a valuable framework for various mental health practices. For instance, Patrick and Williams (2012) demonstrated that perceived competence, a key dimension of SDT, was a significant predictor of clients’ medication adherence. Other investigators demonstrated the utility of SDT for promoting college student mental health (Emery, Heath, & Mills, 2016; A. E. Williams & Green, 2016). In one study, college students’ level of motivation and perceived competence were found to be important factors associated with their mental and physical well-being (Adams et al., 2017). Jeno and Diseth (2014) indicated that a college student’s sense of autonomy and perceived competence were significant predictors of improved academic performance. Another investigation found that group therapy based on SDT and motivational interviewing reduced college women’s susceptibility to high-risk alcohol use (A. E. Williams & Green, 2016). Moreover, university students’ sense of perceived competence and emotional regulation were associated with reductions in non-suicidal self-injury (Emery et al., 2016). Emery et al. (2016) concluded that SDT and college students’ need for perceived competence were salient notions for conceptualizing non-suicidal self-injury and supporting college student mental health.
Self-Determination Theory and Psychometric Instruments
SDT is a widely used theoretical framework to develop measurement instruments in the social sciences. Multiple educational scales have been founded on constructs aligned with SDT, including the Learning Climate Questionnaire (G. C. Williams & Deci, 1996), the Basic Psychological Need Scale (Ntoumanis, 2005), the Academic Self-Regulation Questionnaire (Ryan & Connell, 1989), and the Perceived Competence scale (G. C. Williams & Deci, 1996). Each instrument appraises latent variables related to students’ level of perceived competence and intrinsic motivation toward academic success (Jeno & Diseth, 2014). Given the promising implications of SDT for informing the development of clinical and educational interventions and appraisal instruments, college counselors might benefit from a scale that assesses student and faculty members’ perceived competence related to supporting college student mental health. Such a measure has potential to aid in the early identification of college students at risk for mental health issues and support general campus mental health services. Research indicates that effective screening generally leads to more college students seeking meaningful treatment and support (Hill, Yaroslavsky, & Pettit, 2015).
In an extensive review of the measurement literature with no restrictions on participants or locations, Wei, McGrath, Hayden, and Kutcher (2015) identified 215 measurement instruments for appraising three major components of mental health literacy, including help-seeking, knowledge, and stigma. While these instruments have utility within the screening process, a measure designed to appraise one’s sense of perceived competence toward promoting mental health support on college campuses is absent. The characteristic of perceived competency has potential to act as a protective factor against mental distress (A. E. Williams & Green, 2016). Therefore, the authors incorporated the perceived self-competence dimension of SDT to formulate CMHPCS items.
To summarize, the purpose of the present study was to develop and validate a measurement instrument for appraising student and faculty members’ perceived competence for supporting college student mental health through recognizing and referring student peers to resources for mental wellness. The following research questions were posed: (1) What is the underlying factor structure of the CMHPCS using a large sample of college faculty and are the emergent scales reliable? (2) Is the emergent factor structure from the CMHPCS confirmed in a new sample of undergraduate students? and (3) To what extent do participants’ CMHPCS scores have predictive validity for whether or not they have made a student referral to the counseling center?
Participants and Procedures
Data were collected from students and faculty members at a large mid-Atlantic public university. G*Power was used to conduct a priori power analysis for the hierarchical logistic regression analyses described below (Faul, Erdfelder, Lang, & Buchner, 2007). A minimum sample size of 264 (132 in each sample) would provide a 95% power estimate, α = .05 (two tailed), with an odds ratio of 2.0. Based on the recommendations of Mvududu and Sink (2013), the researchers ensured that the ratio of respondents to each estimated parameter for the student sample (26:1) and for the faculty sample (11:1) was sufficient for factor analysis. The CMHPCS was administered to 513 university community members, including a sample of 201 faculty members and 312 undergraduate students. The sampling procedures and demographic profiles of the two samples are described in the following subsections.
Faculty. Potential faculty participants (N = 1,000) were solicited via an email list provided by the university’s Office of Institutional Research. The measure was administered to this sample using a well-known e-survey platform, Qualtrics (2017). Overall, the response rate was 21%, consistent with the response rates of previous survey research with faculty members (e.g., Brockelman & Scheyett, 2015). Of faculty respondents, 59% (n = 118) identified as female, 40% (n = 81) identified as male, 0.5% (n = 1) identified as “other gender,” and 0.5% (n = 1) did not specify their gender. The majority of participants, 81% (n = 162), identified as Caucasian or White, followed by African American, 4% (n = 8); Hispanic or Latinx, 4% (n = 8); Asian, 3% (n = 6); and multiethnic, 2% (n = 3); while 8% (n = 14) did not specify their ethnic background. Faculty members comprised a variety of different ranks, including adjunct instructor (29%, n = 59), lecturer (19%, n = 39), assistant professor (17%, n = 35), associate professor (18%, n = 37), and full professor (8%, n = 16), while 7.5% (n = 15) did not specify their rank.
Students. Data were collected from 312 undergraduate college students using a nonprobability sampling procedure. Over 34 days (four data collection sessions lasting 2.5 hours), the questionnaire was administered to students in the student union. These respondents ranged in ages from 18–51 (M = 21, SD = 5), with 95% of participants under the age of 29 at the time of data collection. Furthermore, 64% (n = 201) were females, 34% (n = 107) were males, 1% (n = 3) identified as “other gender,” and 0.3% (n = 1) did not specify their gender. The college generational status of these respondents was 37% (n = 116) first, 40% (n = 124) second, and 23% (n = 72) third and beyond. Ethnicities were distributed as follows: 48% (n = 150) African American, 30% (n = 95) Caucasian or White, 10% (n = 30) multiethnic, 6% (n = 19) Hispanic or Latinx, 4% (n = 12) Asian, 1% (n = 3) Native Hawaiian or Pacific Islander, and 0.3% (n = 1) American Indian or Alaska Native, while 0.6% (n = 2) did not report their ethnic identity.
Instrumentation and Procedures
The authors followed the instrument development guidelines discussed by experts in psychometrics and questionnaire design (DeVellis, 2016; Fowler, 2014). An initial set of 18 items was created on a Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree). As discussed above, the original theoretical framework of SDT (Ryan & Deci, 2000) and its contemporary extensions (Adams et al., 2017) guided the development of item content. Item content was also derived from major themes identified in the literature review (comfort, stigma, referrals, prevalence, and complexity), particularly those related to student and faculty members’ connection to college student mental health support (Bishop, 2016; Eisenberg et al., 2011; Lee et al., 2017). The following CMHPCS items, for example, reflect SDT (the positive association between one’s sense of competency and action) and the research findings that one’s sense of comfort with mental health disorders is associated with increased referrals to resources for mental health disorders: “I am comfortable talking to students about mental health”; “I am comfortable referring college students with mental health issues to the health center on campus”; “I am aware of the university resources for mental health”; and “Mental health issues are increasing among college students.” Negatively worded items were recoded so that higher scores would indicate higher perceived competence.
To obtain background information on the respondents, 11 demographic items were added to the questionnaire. These were developed in light of previous college counseling research that showed group differences (e.g., gender, ethnicity, previous attendance in counseling) on various mental health–related variables (Eisenberg et al., 2016; Kalkbrenner & Hernández, 2017). Sample items included the following: (1) Please select your gender; (2) Please specify your age (in years); and
(3) Indicate your ethnic identity.
The initial item pool was subjected to expert review and pilot testing to establish content validity. The items were sent to three expert reviewers with advanced training in clinical psychology, mental health counseling, and psychometrics. Their recommendations informed slight modifications to 15 items, improving their clarity and readability. A few additional items and formatting revisions were made based on pertinent feedback from pilot study participants (22 graduate students). For example, we clarified the meaning of “referred another student to counseling services” to “referred (recommended) that another student seek counseling services.”
A series of statistical analyses were computed to answer the research questions, including exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and hierarchical logistic regression (HLR). During phase 1 of the study using the faculty sample, a principal factor analysis (PFA) was conducted to determine the underlying latent factor structure of the CMHPCS (Mvududu & Sink, 2013). Given that the constructs related to SDT are generally correlated (Adams et al., 2017), the researchers used an oblique rotation (direct oblimin, ∆ = 0). The Kaiser criterion (eigenvalues [Λ] > 1), meaningful variance accounted for by each factor (≥ 5%), a review of the scree plot, and parallel analysis results guided the factor extraction process. Factor retention criteria were used based on the recommendations of Mvududu and Sink (2013): factor loadings > .40, commonalities (h2) > .30, and cross-loadings < .30. The content of items that loaded on each factor were reviewed for redundancy, as it is an accepted practice to remove an item that is highly correlated and conceptually similar to at least one other item (Byrne, 2016).
To cross-validate these initial factor analytic results, a CFA using a maximum likelihood estimation method was conducted to test the validity of the factor solution that emerged in the EFA with a sample of undergraduate students (research question 2). Using the recommendations of Byrne (2016), the following goodness-of-fit indices were reported: chi-square absolute fit index (CMIN), comparative fit index (CFI), root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), goodness-of-fit-index (GFI), and normed fit index (NFI).
Two HLR analyses were computed to examine the predictive validity of the CMHPCS for both faculty member and student participants (research question 3). Previous investigators found group demographic differences in college students’ willingness to utilize mental health services by age (Eisenberg et al., 2016) and their willingness to make peer-to-peer referrals to resources by gender (Kalkbrenner & Hernández, 2017). Based on these findings, gender and age were entered into the first regression model as predictor variables. Participants’ composite scores on the knowledge, fear, and engagement scales of the CMHPCS were entered into the second regression model as predictor variables. The criterion variable was participants’ referrals to the counseling center (1 = has not made a referral to the counseling center, or 2 = has made referrals to the counseling center).
After screening the data, descriptive statistics were computed on the faculty and student samples to examine unusual or problematic response patterns, missing data, and the parametric nature of the item distributions. Missing values analyses revealed that less than 2% of data was absent from faculty participants and less than 1% of data was absent from student participants. Both data sets were winsorized and missing values were replaced with the series mean (Field, 2018). Skewness and kurtosis values for items were largely within the acceptable range of a normal distribution (absolute value < 1) for the sample of faculty members and the sample of students (see Table 1). The findings are presented in three phases of analyses that correspond to the three research questions, respectively.
Phase 1: Exploratory Factor Analysis
A PFA was conducted using the sample of faculty members to establish the initial dimensionality of the CMHPCS (research question 1). The inter-item correlation matrix revealed low-to-moderate correlations among items (r = .17 to r = .69). The Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO = .81) and Bartlett’s Test of Sphericity (B  = 1375.91, p < 0.001) provided further evidence that the data set was factorable. The oblique rotated PFA (direct oblimin, ∆ = 0) revealed a 5-factor solution based on the Kaiser criterion (Λ > 1.00). Seventy percent of the total variance in the correlation matrix was explained by these five factors. The scree plot, parallel analysis, and meaningful variance explained (at least 5% for each factor) that a 3-factor solution was the most parsimonious with the least evidence of cross-loadings (see Table 2). Five items displayed commonalities < .30 and were consequently removed from the analysis. The first factor accounted for 31.6% of the variance (Λ = 4.74), the second factor comprised 12.5% of the variance (Λ = 1.89), and the third factor accounted for 11.8% of the variance (Λ = 1.78).
Redundant items that were highly correlated, and thus conceptually interrelated, were deleted. The inter-item correlation matrix was reproduced and indicated that item 8 (“I am aware of resources in the community for mental health”) and item 15 (“I am aware of the university resources for mental health”) were statistically and conceptually similar, suggesting that these items were measuring the same construct. Item 8 was subsequently removed, as the content of item 15 was more closely related to mental health services on campus. The PFA was recomputed and a final 3-factor solution (see Table 2) comprised of 12 items was retained. These 12 items were renumbered in chronological order.
Descriptive Statistics for Final Items
|| Faculty (N = 201)
|| Student (N = 312)
|Truncated Item Content
|1. Severity of mental health issues
|2. Complexity of mental health issues
|3. Comfortable making referrals to
|4. Fear of students with mental health issues
|5. Negative academic impact of mental distress
|6. Increasing prevalence of mental health issues
|7. Comfortable making student referrals to the health center
|8. Interacting with students living with mental distress
|9. Fear of students with mental disorders
|10. University resources for mental distress
|11. Negative impact of mental distress on well-being
|12. Comfortable making referrals to
Note. Windsorized values (z-scores) are reported; faculty: SEKurtosis = 0.34, SESkewness = 0.17; students: SEKurtosis = 0.13, SESkewness = 0.20. Spinets of item content are provided based on the guidelines from the Publication Manual of the American Psychological Association, 6th edition. To access the full version of the scale, please contact the corresponding author.
The three emergent factors were named engagement, fear, and knowledge, respectively (see Table 2). The first factor, engagement, was comprised of items 3, 7, 8, 10 and 12. It estimates the degree to which a faculty member is involved with interacting, supporting, and working with students who are struggling with mental health disorders (e.g., item 7 [“I am comfortable referring college students with mental health issues to the health center on campus”] and item 8 [“I am comfortable talking to students about mental health”]). The second factor, fear, was comprised of items 4 and 9 and appraises one’s anxiety or concern surrounding mental health issues on college campuses (e.g., item 4 [“Students with mental health issues are dangerous”]). The last factor, knowledge, was marked by items 1, 2, 5, 6, and 11. These items reflect the extent to which the respondent was familiar with mental health issues on college campuses (e.g., item 4 [“Mental health issues are becoming more complex among college students”] and item 10 [“Mental health issues are increasing among college students”]).
Principal Factor Analysis Results Using Oblique Rotation: Faculty Members (N = 201)
||Factor 1 (E)
||Factor 2 (F)
||Factor 3 (K)
|% of variance
Note. Factor loadings over 0.40 appear in bold and mark the particular factor. Blank cells indicate factor loadings ≤ 0.10.
E = Engagement; F = Fear; K = Knowledge.
Item and internal consistency reliability analyses were computed for the three derived factors to partially answer research question 1. Adequate reliability coefficients were found for the overall measure (α = .81) and for each dimension: engagement (α = .84), fear (α = .83), and knowledge (α = .75). The low correlations between factors (engagement and fear, r = 0.09; engagement and knowledge,
r = 0.37; and fear and knowledge, r = 0.11) supported the discriminant validity of the measure.
Phase 2: Confirmatory Factor Analysis
To cross-validate the CMHPCS with a sample of undergraduate students, a CFA was computed (research question 2). The assumptions necessary for conducting a CFA were met (Byrne, 2016). Multicollinearity was not present, as bivariate correlations did not exceed an absolute value of 0.36. In addition, Mahalanobis d2 indices revealed no extreme multivariate outliers. The standardized path model is depicted in Figure 1. It was not surprising that the CMIN absolute fit index was statistically significant due to the large sample size: χ2(51) = 1.97, p = .007. However, fit indices that are more appropriate for sample sizes larger than 200 revealed an adequate model fit. For example, the CFI = .96, RMSEA = .05, 90% CI [.04, .07], SRMR = .04, and GFI = .95. The path coefficients (see Figure 1) between the engagement and knowledge scales (.48) indicated a stronger relationship than the engagement and fear (.05) or fear and knowledge scales (.07). (These path coefficients are interpreted in the discussion section). Taken together, the CFA results produced a moderate-to-strong fit based on the guidelines from structural equation modeling researchers (Byrne, 2016). Reliability of the dimensions was re-examined with the student sample, yielding similar estimates to those found with faculty respondents. Internal consistency indices for the overall measure (α = .78) as well as for the three scales (engagement, α = .82; knowledge, α = .75; fear scale, α = .74) were adequate for an attitudinal questionnaire.
Phase 3: Hierarchical Logistic Regression Analyses
The guidelines for HLR assumption checking were followed (Field, 2018). Items were winsorized to remove extreme outliers. Skewness and kurtosis values (see Table 1) were largely within the acceptable range (± 1.00) for both samples. Pearson product correlations were computed between the independent variable scores, revealing no multicollinearity. Box and Tidwell’s (1962) procedure revealed that the assumption of linearity was met for both samples (i.e., the logit of the criterion variable was linearly related to all continuous predictor variables).
Figure 1. Confirmatory Factor Analysis Path Model for Undergraduate Student Sample (N = 312)
Faculty members. HLR analyses were computed to investigate the predictive validity of the CMHPCS (research question 3). Specifically, researchers aimed to determine the extent to which respondents’ scores on the CMHPCS predicted if they had made a referral to the counseling center. Among the sample of faculty members, the correct classification rate of the null model was 56%. The first model of gender and age was significant (χ2 = 15.80, p < 0.001) and explained 11% (Nagelkerke R2) of the variance in participants’ referrals to the counseling center. There was a statistically significant increase in the odds (Exp(B) = 1.30) of female faculty members making a student referral to the counseling center. The second LR model revealed that adding the knowledge, fear, and engagement scales significantly improved the predictability of model (χ2 = 46.61, p < 0.001) and explained 30% (Nagelkerke R2) of the variance in participants’ referrals to the counseling center. The engagement scale was a significant predictor of referrals to the counseling center. The odds ratio, Exp(B), revealed that an increase in one unit on the engagement scale was associated with an increase in the odds of making a referral to the counseling center by a factor of 3.47. The correct classification rate of this model was 71.2%.
Undergraduate students. For the sample of undergraduate students, the correct classification rate of the null model was 58%. Gender and age were entered as predictor variables in the first regression block and revealed statistical significance (χ2(1) = 9.35, p = 0.01) and explained 4.2% (Nagelkerke R2) of the variance in participants’ referrals to the counseling center. A statistically significant increase in the odds emerged (Exp(B) = 1.78) for female students having made a peer-referral to the counseling center. In the second block, the knowledge, fear, and engagement subscales of the CMHPCS were added to the regression model. The addition of the CMHPCS scales as predictor variables significantly improved the model (χ2(1) = 29.82, p < 0.001) and explained 13% (Nagelkerke R2) of the variance in participants’ referrals to the counseling center. Similar to faculty members, the engagement scale was a significant predictor of students’ referrals to the counseling center. The odds ratio, Exp(B), revealed that an increase in one unit on the engagement scale was associated with an increase in the odds of having made a referral to the counseling center by a factor of 2.10.
The results of three major analyses provided evidence that the construct—perceived competence for promoting college student mental health—and its dimensions were estimated adequately by the CMHPCS. Feedback from expert reviewers and pilot study participants showed initial support for the content validity of the measure. The findings from the PFA and CFA provided evidence for the factorial validity of the measure. The low correlations between factors provided further support for the relative distinctiveness (discriminant validity) of each dimension. Tests of internal consistency revealed adequate support for the reliability of the measure with college students and with faculty members.
The results of the HLR models demonstrated a moderate level of predictive validity of the CMHPCS. Similar to previous investigations (e.g., Kalkbrenner & Hernández, 2017), female students in the present study were more likely to make peer-to-peer referrals to the counseling center when compared to male students. Extending previous findings, the addition of participants’ scores on the CMHPCS scale as predictor variables significantly improved the logistic regression model’s capacity to predict the odds of making a referral to the counseling center. The CMHPCS appears to be measuring a construct that is associated with greater odds of both students and faculty members supporting college student mental health (i.e., making a referral to the counseling center). In particular, higher scores on the engagement scale emerged as a significant predictor of an increase in the odds of having made a student referral to the counseling center among both faculty members and undergraduate students.
This study introduced a new theoretical dimension, perceived competence for promoting college student mental health, to the growing body of literature on the utility of SDT for supporting college student mental health. The emergent factor structure of the CMHPCS was largely consistent with key elements of SDT (Adams et al., 2017). According to the theory, individuals’ motivation for engaging in an action or behavior will be enhanced when they feel a sense of competence or self-efficacy for the activity (Adams et al., 2017; Ryan & Deci, 2000). Similarly, the emergent factor of knowledge on the CMHPCS (i.e., the extent to which one is familiar or knowledgeable with mental health issues on campus) is consistent with research on the personal competency component of SDT. Weber and Koehler (2017), for example, found a moderate, positive association between respondents’ knowledge and perceived competence. Similarly, in the present study, knowledge emerged as a factor of perceived competence (i.e., one who is more knowledgeable about college student mental health has a higher level of perceived competence for supporting college student mental health). Autonomy and relatedness also are central components of SDT, as individuals’ intrinsic motivation is enhanced when their behaviors are active and self-determined (Adams et al., 2017; Jeno & Diseth, 2014). Finally, the engagement scale on the CMHPCS reflects the extent to which one is actively involved with supporting college student mental health. One who is more engaged with supporting college student mental health has a higher level of perceived competence for supporting college student mental health.
The relationship between the path coefficients (see Figure 1) provided further support that the CMHPCS is largely consistent with SDT. The path coefficients were stronger between the engagement and knowledge scales (0.48) than they were with the fear scale—0.05 and 0.07, respectively. According to the theory, intrinsic motivation toward wellness generally increases when individuals are competent (knowledgeable) and related (engaged) to a person or activity (Patrick & Williams, 2012). Thus, it was not surprising that the strongest association between the three factors (knowledge, fear, and engagement) emerged between the knowledge and engagement subscales. There are complex associations between fear and one’s level of motivation (Halkjelsvik & Rise, 2015). Some researchers demonstrated that higher levels of respondent fear were associated with higher levels of motivation (e.g., motivation for smoking cessation; Farrelly et al., 2012). However, in other investigations, anxiety elicited the opposite response in participants, substantially decreasing their motivation (Halkjelsvik & Rise, 2015). Considering the complex connection between motivation and fear, it is possible in the present study that participants’ fear of mental health issues on college campuses was associated with ambivalence in their engagement. Fear may motivate students to support a peer experiencing mental distress. In other situations, fear might lead to students avoiding a peer in mental distress. While future research is needed to investigate these issues, there is sufficient statistical (EFA and CFA) and conceptual evidence to retain the fear scale.
To summarize, the theoretical construct underlying CMHPCS, which was designed to measure perceived competence toward promoting college student mental health, reflects aspects of SDT. Individuals with high levels of perceived competence for promoting college student mental health appear to be knowledgeable about, unfearful of, and engaged with supporting students who are living with mental health issues. At this stage of development, the CMHPCS has potential to enhance the practice of college counseling.
Implications for the Profession
Considering the rise in college counselors’ roles and responsibilities with outreach and consultation (Brunner et al., 2014; Sharkin, 2012), the CMHPCS can assist college counselors with these activities. Specifically, the CMHPCS can be used by college counselors to provide a baseline measure of perceived competence for promoting mental health on campus among students and faculty members. The questionnaire can be administered and scored as a holistic measure (total score), as an overall measure, or as three separate dimensions (subscales) of students and/or faculty members’ perceived competence for promoting mental health on campus. On a practical level, the CMHPCS has utility for college counselors when participating in new student and new faculty orientations due to the brevity (12 items) and versatility (use with faculty and student populations) of the measure. The results might provide college counselors with valuable baseline information on new students and faculty members’ perceived competence toward supporting college student mental health and aid in structuring the content of educational sessions for recognizing and referring students to the counseling center.
Brunner et al. (2014) identified supporting referral agents through consultation as another key aspect in the practice of college counseling. The findings presented above demonstrated that higher scores on the engagement scale predicted a greater likelihood in the odds of student referrals to the counseling center among both students and faculty members. This outcome can inform college counselors’ outreach and consultation efforts. Specifically, it is recommended that college counselors focus on increasing university community members’ knowledge and engagement with supporting college student mental health. Advocacy efforts can be directed toward implementing training sessions for faculty members and students for recognizing warning signs of mental health disorders in college students and connecting trainees to resources for mental health disorders. The CMHPCS can be used as a pretest/posttest measure to provide information about the extent to which trainings and mental health support resources are useful for promoting perceived competence for supporting college student mental health. For example, the REDFLAGS Model, an acronym of common warning signs of mental health disorders in college students (Kalkbrenner, 2016), and the National Suicide Prevention Lifeline’s wallet cards (National Suicide Prevention Lifeline, 2008) are resources for increasing university community members’ awareness of warning signs of mental health disorders in college students. The CMHPCS could be implemented to assess the value of these resources.
Limitations and Future Research
Although results of the current study were promising, the research caveats should be considered. First, self-report measures can sometimes generate response biases influenced by the respondent’s need for social desirability. Second, the 2-item fear scale is not ideal. Although dimensions composed of few items often generate lower reliability coefficients, there is no absolute threshold for the minimum number of items necessary to comprise a scale (Fowler, 2014). Given the CMHPCS’s stage of development, the researchers chose to retain the dimension. The strong reliability coefficient of the fear subscale (α = .83, student sample and α = .80, faculty sample) exceeded the threshold for acceptable internal consistency reliability. The overall scale is also stronger with the fear scale items included. Finally, it should be noted that other validated instruments in social sciences research have scales comprised of two items (Luecht, Madsen, Taugher, & Petterson, 1990), suggesting that the fear scale may be useful.
The demographic profile of faculty in our sample was consistent with the ethnic identities of the larger university and with a national sample of faculty members (Myers, 2016). However, the homogeneity of ethnicity among faculty participants still might have affected the generalizability of our findings. Most faculty participants (81%, n = 162) identified as Caucasian or White. It is recommended that future researchers confirm the factor structure of the CMHPCS with an ethnically diverse sample of faculty members. Subsequent investigation should examine the goodness-of-fit of the CMHPCS with different populations of college students and faculty members. Specifically, the following sub-groups of college students appear to be especially susceptible to mental health disorders: first-generation college students, community college students, students enrolled in Greek life organizations, international students, and male students (Dobmeier et al., 2013; Eisenberg et al., 2011).
The professional identity of college counselors has grown to include outreach and consultation with counseling referral agents as key components in the contemporary practice of college counseling (Brunner et al., 2014; Sharkin, 2012). The multidimensional aim of the present study was to establish the validity and reliability of the CMHPCS, a newly developed questionnaire designed to measure college student and faculty members’ perceived competence for promoting college student mental health. To do so, the measure was subjected to rigorous psychometric testing (EFA and CFA). A 3-factor model (knowledge, fear, and engagement) emerged from the data. Initial support for the reliability and factorial validity of the instrument was reported. A series of two HLR analyses reinforced, in part, the predictive validity of the measure. The brief nature of the CMHPCS coupled with its adequate reliability and coherent factor structure suggests the measure might have utility for supporting and enhancing the consultation and outreach activities of college counseling practitioners. For instance, the CMHPCS can be carefully utilized as a screening measure for students to enhance the practice (outreach, education, and consultation) of college counselors. The instrument also is perhaps useful as a pretest/posttest measure in outcome research aimed at assessing mental health support interventions among college students.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
Adams, N., Little T. D., & Ryan, R. M. (2017). Self-determination theory. In M. L. Wehmeyer, K. A. Shogren, T. D. Little, & S. J. Lopez (Eds.), Development of self-determination through the life-course (pp. 47–54). Dordrecht, Netherlands: Springer.
Albright, G., & Schwartz, V. (2017). Are campuses ready to support students in distress? Retrieved from https://www.jedfoundation.org/wp-content/uploads/2017/10/Kognito-JED-Are-Campuses-Ready-to-Support-Students-in-Distress.pdf
Bishop, K. K. (2016). The relationship between retention and college counseling for high-risk students. Journal of College Counseling, 19, 205–217. doi:10.1002/jocc.12044
Box, G. E. P., & Tidwell, P. W. (1962). Transformation of the independent variables. Technometrics, 4, 531–550. doi:10.2307/1266288
Brockelman, K. F., & Scheyett, A. M. (2015). Faculty perceptions of accommodations, strategies, and psychiatric advance directives for university students with mental illnesses. Psychiatric Rehabilitation Journal, 38, 342–348. doi:10.1037/prj0000143
Brunner, J. L., Wallace, D. L., Reymann, L. S., Sellers, J.-J., & McCabe, A. G. (2014). College counseling today: Contemporary students and how counseling centers meet their needs. Journal of College Student Psychotherapy, 28, 257–324. doi:10.1080/87568225.2014.948770
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). New York, NY: Routledge.
de Lijster, J. M., Dierckx, B., Utens, E. M. W. J., Verhulst, F. C., Zieldorff, C., Dieleman, G. C., & Legerstee,
J. S. (2017). The age of onset of anxiety disorders: A meta-analysis. The Canadian Journal of Psychiatry / La Revue Canadienne De Psychiatrie, 62, 237–246. doi:10.1177/0706743716640757
DeVellis, R. F. (2016). Scale development: Theory and applications (4th ed.). Thousand Oaks, CA: Sage.
Dobmeier, R. A., Kalkbrenner, M. T., Hill, T. T., & Hernández, T. J. (2013). Residential community college student awareness of mental health problems and resources. CSPA-NYS Journal, 13(2), 15–28. Retrieved from http://journals.canisius.edu/index.php/CSPANY/article/viewFile/331/500
Emery, A. A., Heath, N. L., & Mills, D. J. (2016). Basic psychological need satisfaction, emotion dysregulation, and non-suicidal self-injury engagement in young adults: An application of self-determination theory. Journal of Youth & Adolescence, 45, 612–623. doi:10.1007/s10964-015-0405
Eisenberg, D., Goldrick-Rabe, S., Lipson, S. K., & Broton, K. (2016). Too distressed to learn? Mental health among community college students. Retrieved from http://www.wihopelab.com/publications/Wisconsin_HOPE_Lab-Too_Distressed_To_Learn.pdf
Eisenberg, D., Hunt, J., Speer, N., & Zivin, K. (2011). Mental health service utilization among college students in the United States. Journal of Nervous and Mental Disease, 199, 301–308.
Farrelly, M. C., Duke, J. C., Davis, K. C., Nonnemaker, J. M., Kamyab, K., Willett, J. G., & Juster, H. R. (2012). Promotion of smoking cessation with emotional and/or graphic antismoking advertising. American Journal of Preventive Medicine, 43, 475–482. doi:10.1016/j.amepre.2012.07.023
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. doi:10.3758/BF03193146
Field, A. P. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). Thousand Oaks, CA: Sage.
Fowler, F. J. (2014). Survey research methods (5th ed.). Thousand Oaks, CA: Sage.
Halkjelsvik, T., & Rise, J. (2015). Disgust in fear appeal anti-smoking advertisements: The effects on attitudes and abstinence motivation. Drugs: Education, Prevention and Policy, 22, 362–369.
Han, M., & Pong, H. (2015). Mental health help-seeking behaviors among Asian American community college
students: The effect of stigma, cultural barriers, and acculturation. Journal of College Student
Development, 56, 1–14. doi:10.1353/csd.2015.0001
Hill, R. M., Yaroslavsky, I., & Pettit, J. W. (2015). Enhancing depression screening to identify college students at
risk for persistent depressive symptoms. Journal of Affective Disorders, 174, 1–6.
Jeno, L. M., & Diseth, Å. (2014). A self-determination theory perspective on autonomy support, autonomous self-regulation, and perceived school performance. Reflecting Education, 9, 1–20.
Kalkbrenner, M. T. (2016). Recognizing and supporting students with mental disorders: The REDFLAGS
Model. Journal of Education and Training, 3, 1–13. doi:10.5296/jet.v3i1.8141
Kalkbrenner, M. T., & Hernández, T. J. (2017). Community college students’ awareness of risk factors for
mental health problems and referrals to facilitative and debilitative resources. The Community College
Journal of Research and Practice, 41, 56–64. doi:10.1080/10668926.2016.1179603
Kalkbrenner, M. T., James, C., & Pérez-Rojas, A. E. (2018). College students’ awareness of mental disorders and counselor seeking behaviors: Comparison across academic disciplines. Journal of College Student Psychotherapy. Manuscript submitted for publication.
Lee, H. J., Ju, Y. J., & Park, E.-C. (2017). Utilization of professional mental health services according to recognition rate of mental health centers. Psychiatry Research, 250, 204–209.
Li, J., Marbley, A. F., Bradley, L. J., & Lan, W. (2016). Attitudes toward seeking professional counseling services among Chinese international students: Acculturation, ethnic identity, and English proficiency. Journal of Multicultural Counseling and Development, 44, 65–76. doi:10.1002/jmcd.12037
Luecht, R. M., Madsen, M. K., Taugher, M. P., & Petterson, B. J. (1990). Assessing professional perceptions: Design and validation of an interdisciplinary education perception scale. Journal of Allied Health, 19(2), 181–191.
Mancini, A. D. (2008). Self-determination theory: A framework for the recovery paradigm. Advances in Psychiatric Treatment, 14, 358–365. doi:10.1192/apt.bp.107.004036
Marsh, C. N., & Wilcoxon, S. A. (2015). Underutilization of mental health services among college students: An examination of system-related barriers. Journal of College Student Psychotherapy, 29, 227–243.
Myers, B. (2016). Where are the minority professors? The Chronical of Higher Education. Retrieved from https://www.chronicle.com/interactives/where-are-the-minority-professors
Mvududu, N. H., & Sink, C. A. (2013). Factor analysis in counseling research and practice. Counseling Outcome Research and Evaluation, 4(2), 75–98. doi:10.1177/2150137813494766
National Suicide Prevention Lifeline. (2008). Having trouble coping? With help comes hope. Retrieved from https://store.samhsa.gov/product/National-Suicide-Prevention-Lifeline-Wallet-Card-Having-Trouble-Coping-With-Help-Comes-Hope-/SVP13-0155R
Ntoumanis, N. (2005). A prospective study of participation in optional school physical education using a self-determination theory framework. Journal of Educational Psychology, 97, 444–453.
Patrick, H., & Williams, G. C. (2012). Self-determination theory: Its application to health behavior and complementarity with motivational interviewing. The International Journal of Behavioral Nutrition and Physical Activity, 9, 1–12. doi:10.1186/1479-5868-9-18
Piltch, C. A. (2016). The role of self-determination in mental health recovery. Psychiatric Rehabilitation Journal, 39, 77–80. doi:10.1037/prj0000176
Qualtrics [Online survey platform software]. (2017). Provo, UT, USA. Retrieved from https://www.qualtrics.com/
Rosenthal, B. S., & Wilson, W. C. (2016). Psychosocial dynamics of college students’ use of mental health services. Journal of College Counseling, 19, 194–204. doi:10.1002/jocc.12043
Ryan, R. M., & Connell, J. P. (1989). Perceived locus of causality and internalization: Examining reasons for acting in two domains. Journal of Personality and Social Psychology, 57, 749–761.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78. doi:10.1037/0003-066X.55.1.68
Ryan, R. M., Lynch, M. F., Vansteenkiste, M., & Deci, E. L. (2011). Motivation and autonomy in counseling, psychotherapy, and behavior change: A look at theory and practice. The Counseling Psychologist, 39(2), 193–260. doi: 10.1177/0011000009359313
Sharkin, B. S. (2012). Being a college counselor on today’s campus: Roles, contributions, and special challenges. New York, NY: Routledge Taylor & Francis Group.
Weber, M., & Koehler, C. (2017). Illusions of knowledge: Media exposure and citizens’ perceived political competence. International Journal of Communication, 11(2017), 2387–2410.
Wei, Y., McGrath, P. J., Hayden, J., & Kutcher, S. (2015). Mental health literacy measures evaluating knowledge, attitudes and help-seeking: A scoping review. BMC Psychiatry, 15, 1–20. doi:10.1186/s12888-015-0681-9
White, S., Park, Y. S., Israel, T., & Cordero, E. D. (2009). Longitudinal evaluation of peer health education on a college campus: Impact on health behaviors. Journal of American College Health, 57, 497–505.
Williams, A. E., & Greene, C. A. (2016). Creating change through connections: A group for college women experiencing alcohol-related consequences. Journal of Creativity in Mental Health, 11, 90–104.
Williams, G. C., & Deci, E. L. (1996). Internalization of biopsychosocial values by medical students: A test of self-determination theory. Journal of Personality and Social Psychology, 70, 767–779.
Yorgason, J. B., Linville, D., & Zitzman, B. (2008). Mental health among college students: Do those who need services know about and use them? Journal of American College Health, 57(2), 173–182.
Michael T. Kalkbrenner, NCC, is an assistant professor at New Mexico State University. Christopher A. Sink, NCC, is a professor and Batten Chair at Old Dominion University. Correspondence can be addressed to Michael Kalkbrenner, 1780 E. University Ave., Las Cruces, NM 88003, email@example.com.
Nov 30, 2017 | Volume 7 - Issue 4
Angelica M. Tello, Marlise R. Lonn
Latinx first-generation college students (FGCS) are a growing population faced with unique challenges for college retention and graduation. Because their parents did not attend postsecondary education, this group of college students has not inherited the social or cultural capital common to many traditional college freshmen. Both high school and college counselors are in positions to support the psychosocial and emotional needs of Latinx FGCS, which may increase successful college completion rates. This article provides high school and college counselors with (a) an overview of FGCS’ characteristics, (b) information specific to Latinx culture, (c) an understanding of the college experiences of Latinx FGCS, and (d) a discussion of counseling implications for addressing the psychosocial and emotional needs of this population.
Keywords: first-generation college students, school counselors, college counselors, Latinx, retention
Although higher education is now more accessible to students from disadvantaged backgrounds, universities are still struggling with retention and graduation rates of first-generation college students (FGCS; Slaughter, 2009). In higher education, FGCS refers to students whose parents did not attend college or any postsecondary institution (Wang & Castañeda-Sound, 2008). In 2008, 15 million FGCS were enrolled in higher education, and approximately 4.5 million were from low-income backgrounds (The Pell Institute, 2008). Additionally, only 11% of FGCS earn a bachelor’s degree in six years compared to 55% of non-FGCS (The Pell Institute, 2008). Moreover, FGCS are 71% more likely to leave college in their first year than non-FGCS (Pratt, Harwood, Cavazos, & Ditzfeld, 2017). Beyond the general challenges faced by many FGCS, including lack of transmission of cultural capital (e.g., familiarity with the dominant culture; Lundberg, Schreiner, Hovaguimian, & Miler, 2007; Saenz, Hurtado, Barrera, Wolf, & Yeung, 2007), Latinx FGCS experience additional barriers to college completion such as institutional invalidation and microaggressions (Saunders & Serna, 2004; Tello, 2015). Professional counselors working in high school and college settings are in unique positions to engage with FGCS to foster a supportive transition from high school to college to degree completion. The focus of this article is to provide high school and college counselors with (a) an overview of FGCS’ characteristics, (b) information specific to Latinx culture, (c) an understanding of the college experiences of Latinx FGCS, and (d) a discussion of counseling implications for addressing the psychosocial and emotional needs of this population. The term Latinx, a gender neutral term for Latina/o (Castro & Cortez, 2017; Vélez, 2016), is used throughout this article and is used interchangeably with the term Hispanic in the case of information cited from reports (e.g., by the U.S. Department of Education or the Pew Hispanic Center).
First-Generation College Students
Various studies (Lundberg et al., 2007; Prospero & Vohra-Gupta, 2007; Saenz et al., 2007) have highlighted how FGCS differ from the traditional non-FGCS college population. Demographically, FGCS tend to be female ethnic minorities from low socioeconomic families, and older than non-FGCS (Prospero & Vohra-Gupta, 2007). The struggles that FGCS face have been well documented. FGCS are often less academically prepared, often work while attending college, are not as likely to participate in campus extracurricular activities, and have family obligations (Bergerson, 2007; Tym, McMillion, Barone, & Webster, 2004). FGCS also tend to lack the cultural capital that non-FGCS receive from their parents (Lundberg et al., 2007; Saenz et al., 2007). In higher education, cultural capital relates to knowledge and understanding of what it means to be in college. Additionally, this is knowledge that is acquired over a long period of time (Ward, Siegel, & Davenport, 2012). For non-FGCS, parents are the most common source of cultural and social capital regarding ways to navigate academia and college life. The lack of cultural and social capital experienced by FGCS translates to a lack of knowledge about college degrees, persistence, and retention resources. Furthermore, FGCS tend to report not receiving familial support in navigating higher education (Lowery-Hart & Pacheco, 2011; Stieha, 2010). Studies (Orbe, 2004, 2008) have begun to highlight that many FGCS also struggle with negotiating multiple identities. Being an FGCS is not the only identity that these students experience. Other personal identities, such as race, ethnicity, and class, also tend to interplay with FGCS status.
In the research on FGCS, there is a lack of understanding of the intersection of identities experienced by specific FGCS populations. Latinxs are the fastest growing and largest racial group in the United States (Passel, Cohn, & Hugo Lopez, 2011). They also are the fastest growing population accessing higher education (Santiago, Calderón Galdeano, & Taylor, 2015). In 2010, the Pew Hispanic Center reported that Latinxs enrolled in college reached an “all-time high” (Fry, 2011, p. 3). From 2009 to 2010, there was a 24% growth in Latinx college enrollment (Fry, 2011). This represents an increase of 349,000 compared with an increase of 88,000 African Americans and 43,000 Asian Americans (Fry, 2011). Although the gap in college enrollment is beginning to narrow, Latinx continue to be the least educated racial group in regards to bachelor’s degree achievement. In 2010, only 13% of Latinxs completed a bachelor’s degree (Fry, 2011). In 2013–2014, White students earned 68% and Latinx students earned 11% of all bachelor’s degrees awarded (vs. 7% in 2003–2004). While this was a significant increase, Latinxs are still underrepresented in comparison to their percentage of the population (Snyder, de Brey, & Dillow, 2016). In order to provide Latinx FGCS support, high school and college counselors need to begin understanding their experiences, which can aid in increasing their college retention and graduation rates.
There are benefits of having professional school and college counselors working with Latinx FGCS. High school and college counselors can play vital roles in helping to increase the college enrollment and persistence of underrepresented groups in higher education, including low-income students, FGCS, and students of color (Bishop, 2010; McDonough, 2005; McKillip, Rawls, & Barry, 2012). The retention and graduation rates for Latinx FGCS are significantly lower than traditional students’ rates (Slaughter, 2009). Many universities have recognized that students of color are an at-risk group for dropping out prior to graduation (Atherton, 2014). As a result, these universities are trying to find ways to provide the best support for this population. Research on the academic performance and persistence of FGCS has increased, but there are only a few studies that focus on the psychological well-being of these students (Wang & Castañeda-Sound 2008). A deeper understanding of Latinx culture will assist counselors as they consider how to work effectively with this population.
Understanding Latinx culture can help high school and college counselors in providing culturally competent services to Latinx FGCS. In Latinx culture, there is an emphasis placed on upholding interpersonal relationships (Hernández, Ramírez Garcia, & Flynn, 2010; Kuhlberg, Peña, & Zayas, 2010). Therefore, many Latinx cultural values revolve around supporting interpersonal relationships. Although many Latinx groups share cultural commonalities, there are between-group and within-group differences (Sue & Sue, 2016). The Latinx cultural values described in this section may vary based on the individual’s generational status (e.g., first-generation in the United States versus third generation or beyond) and level of acculturation. According to Sue and Sue (2016), three-fourths of Latinx in the United States are third-generation Americans or higher. In order to gain an understanding of some of the significant Latinx cultural values, a discussion below is provided on familismo, personalismo, simpático, and fatalismo.
Familismo refers to family interdependence, cohesiveness, and loyalty, as well as placing family needs before personal needs (Baumann, Kuhlberg, & Zayas, 2010; Marín & Marín, 1991). For many Latinx, family also encompasses extended family (e.g., grandparents, aunts, uncles, and cousins), close friends, and godparents. The cultural value of familismo involves: “(a) perceived obligation to provide material and emotional support to members of the extended family, (b) reliance on relatives for help and support, and (c) the perception of relatives as behavioral and attitudinal referents” (Marín & Marín, 1991, pp. 13–14). Therefore, extended family and friends will be the first source of support for many Latinx. Seeking help from outside the family might only occur after no resources are provided by extended family and friends (Sue & Sue, 2016). Although familismo may be a source of support for many Latinx, it also can contribute to stress (Aguilera, Garza, & Muñoz, 2010). Family obligations and responsibilities may be placed above outside factors, such as school and work (Avila & Avila, 1995; Franklin & Soto, 2002). However, it is important for high school and college counselors to understand that placing family responsibilities above school does not mean education is not valued by Latinx students and their families. Counselors must tailor their approaches to take into account the client’s cultural expectations for assisting family in times of need.
Personalismo refers to a “personalized communication style that is characterized by interactions that are respectful, interdependent, and cooperative” (Sue & Sue, 2016, p. 534). In addition, a focus is placed on personal interactions in relationships instead of more formal approaches (Holloway, Waldrip, & Ickes, 2009). Counselors may consider attending to rapport building as an essential building block in the first session rather than the more formal interactions associated with completing paperwork and conducting initial assessments. Furthermore, relationships are not viewed as “means to another end” (Clauss-Ehlers, 2006, p. 412); instead, the focus is on privileging a sense of connectedness and warmth over individual achievements or material success. Maintaining positive relationships is central to the Latinx cultural value of personalismo (Clauss-Ehlers, 2006). As a result, high school and college counselors must work on being visible on their campuses and actively engaging with Latinx students.
In Latinx culture, simpático is a relational style that “emphasizes the promotion and maintenance of harmonious and smooth interactions” (Holloway et al., 2009, p. 1012). In relationships, a space is created that is personal, hospitable, and courteous (Holloway et al., 2009). Holloway et al. (2009) described simpático as a self-schema where “one attempts (a) to treat other people in a gracious and accepting manner, (b) to think about others as deserving such treatment, and (c) to think about oneself as the kind of person who treats others in that manner” (p. 1013). In a study conducted by Holloway et al., their findings indicated Latinx reported significantly higher simpáctico-related traits than White participants. As a result, Latinx students may not want to bring up problems that are occurring on their campuses. High school and college counselors must work on creating a safe space for Latinx clients to feel comfortable to voice their concerns.
Fatalismo, also known as fatalism, refers to the belief some Latinx hold related to fate. For Latinx who have traditional cultural values, they may “believe that life’s misfortunes are inevitable and feel resigned to their fate” (Sue & Sue, 2016, p. 532). Additionally, fatalismo is typically connected with religious and spiritual views (Hovey & Morales, 2006; Sue & Sue, 2016). Positive and negative life events can be viewed as controlled by “divine will” (Hovey & Morales, 2006, p. 410). When seeking counseling or mental health services, Latinx with fatalismo cultural values may seem to take a passive approach to problems or may not appear assertive in addressing the problem (Hovey & Morales, 2006; Sue & Sue, 2016). This does not mean the client does not want to address their presenting concern or problem. High school and college counselors will need to tailor their approaches for Latinx clients who hold this cultural belief.
In examining the psychosocial experiences of Latinx FGCS, an understanding of Latinx culture is necessary. Even though there are within-group differences, Latinx college students can sometimes share common cultural values and educational experiences. For many Latinx, supporting interpersonal relationships is an important cultural value (Hernández et al., 2010; Kuhlberg et al., 2010). However, the current literature on Latinx college students brings attention to the cultural incongruence this population experiences in higher education and the negative impact it has on their college persistence (Gloria & Rodriguez, 2000; Hurtado, 1994). In addition, many Latinx college students experience racial tensions on their campus, such as racism and microaggressions, which also negatively impact college retention (Yosso, Smith, Ceja, & Solórzano, 2009).
Factors That Impact the Retention of Latinx FGCS
Latinx college students often face similar challenges as the general FGCS population. They also face barriers in terms of cultural capital, socioeconomic status, and sociocultural experiences (Delgado Gaitan, 2013; Hurtado, Carter, & Spuler, 1996). The existing literature on Latinx college students identified the university environment, social support, and self-beliefs as factors that impacted the retention of Latinx college students (Cerezo & Chang, 2013; Gloria, Castellanos, Lopez, & Rosales, 2005; Hurtado et al., 1996).
Several researchers have discussed the impact a university’s environment can have on the persistence of Latinx college students (Gloria et al., 2005; Hurtado & Carter, 1997; Hurtado, Milem, Clayton-Pedersen, & Allen, 1998; Rendón, 1994). Many Latinx college students navigate higher education by balancing their cultural upbringing and the culture of college (Gloria & Rodriguez, 2000; Hurtado, 1994). However, some Latinx students experience a cultural incongruence (i.e., lack of cultural fit between the student and his or her university), and the difficulties that arise can lead to issues in college persistence (Gloria & Rodriguez, 2000; Hurtado, 1994). Recent studies have supported that the cultural congruency of Latinx college students is positively associated with academic achievement and persistence (Cerezo & Chang, 2013; Edman & Brazil, 2009). Latinx students who experience a cultural fit with their university perceive fewer barriers to their education (Gloria, Castellanos, Scull, & Villegas, 2009). According to Hurtado and Carter (1997), Latinx college students attending predominately White universities described that “feeling at ‘home’ in the campus community is associated with maintaining interactions both within and outside the college community” (p. 338). Furthermore, Latinx college students reported experiencing negative stereotypes, prejudices, marginalization, and microaggressions (Gonzales, Blanton, & Williams, 2002; Rodriguez, Guido-DiBrito, Torres, & Talbot, 2000; Valencia, 2002; Yosso et al., 2009).
Victims of racial and gender microaggressions have identified these as one of the most direct forms of verbal and/or physical assault (Pierce, 1995; Storlie, Moreno, & Portman, 2014). Moreover, microaggressions are more pervasive and occur at a more frequent rate than many realize. While these preconscious or unconscious slights, insults, and degradations may seem harmless or subtle, it is important to be aware that “the cumulative burden of a lifetime of microaggressions can theoretically contribute to diminished mortality, augmented morbidity, and flattened confidence” (Pierce, 1995, p. 281).
Yosso et al. (2009) interviewed 37 Latinx college students attending predominately White institutions that were classified as Carnegie Doctoral/Research Universities-Extensive to understand Latinx students’ experiences of microagressions. Focus groups were completed with three to six students at a time (Yosso et al., 2009). The researchers reported that the Latinx college students in the study experienced three types of microaggressions: (a) interpersonal microaggressions (i.e., verbal and nonverbal racial insults or slights that were directed to the students by faculty, staff, and students), (b) racial jokes, and (c) institutional microaggressions (i.e., a hostile campus climate created by racially marginalized actions through a university’s structure, discourses, and practices toward students of color; Yosso et al., 2009).
The interpersonal microaggressions experienced by the participants included White professors allowing for flexibility in rules with White students but not Latinx students, and Latinx students feeling their professors had low expectations for them or were uncomfortable talking to them (Yosso et al., 2009). For some of the students, racial jokes reduced their sense of belonging and decreased their participation in campus activities (Yosso et al., 2009). In terms of institutional microaggressions, some students felt they were only visible to administrators during culturally related programs on their campuses, but at other times they were neglected by administrators (Yosso et al., 2009). Moreover, the microagressions experienced by the students led them to doubt “their academic merits and capabilities, demean their ethnic identity, and dismiss their cultural knowledge” (Yosso et al., 2009, p. 667). As a result, the students felt rejected by their universities. Yosso et al. (2009) reported that the students engaged in community-building found “counterspaces” on their campuses (student-run spaces such as campus multicultural centers, community outreach programs, or cultural floors in residence halls) where they experienced their cultures as “valuable strengths” (Yosso et al., 2009, p. 677). These findings were similar to those identified in a content analysis of Latinx college student experiences conducted by Storlie et al. (2014).
The Strengths of Latinx FGCS
Researchers have examined the coping strategies and resiliency of Latinx college students (Cavazos, Johnson, Fielding, et al., 2010; Cavazos, Johnson, & Sparrow, 2010). Historically, the literature on Latinx college students focused on the challenges they experienced in higher education (Delgado Gaitan, 2013; Hurtado et al., 1996). However, researchers also can learn from the cultural assets, strengths, and resiliency of Latinx students (Borrero, 2011). Morales (2008) noted that a “deeper understanding of achievement processes can be attained” by examining the experiences of successful Latinx students (p. 25). Latinx FGCS have experienced success as students; they are the first in their families to attend college. Taking a strengths-based approach in evaluating the experiences of Latinx FGCS also aligns with the tenets of the counseling profession (American Counseling Association, 2014).
Cavazos, Johnson, and Sparrow (2010) conducted a qualitative study examining the coping responses of high-achieving Latinx college students. The researchers interviewed 11 Latinx college students attending a Hispanic-serving institution. Nine of the participants were low-income FGCS. When faced with barriers and stressors, the Latinxs interviewed in the study reported using the following coping strategies: (a) positive reframing (e.g., staying positive through optimism and self-confidence), (b) acceptance (e.g., challenges were unavoidable and a part of life), (c) positive self-talk, (d) long-term goal setting, (e) gaining motivation from low expectations, (f) self-reflection (e.g., learning from life experiences), (g) taking action, and (h) seeking support (e.g., reaching out to family members and falling back on religious views; Cavazos, Johnson, and Sparrow, 2010). Although Cavazos, Johnson, and Sparrow (2010) did not overtly discuss how Latinx cultural values integrated into the participants’ coping responses, it appears that many of the themes aligned with Latinx culture. For instance, the theme of acceptance had similar characteristics to fatalismo, and seeking support reflected the qualities of familismo.
Cavazos, Johnson, Fielding, et al. (2010) discussed the resiliency of Latinx college students. The researchers built upon the Cavazos, Johnson, and Sparrow (2010) study that examined the coping responses of Latinx students. Cavazos, Johnson, Fielding, et al. (2010) reported that Latinx participants experienced the following resiliency factors: (a) goal setting (e.g., they had clear and specific goals),
(b) interpersonal relationships (e.g., receiving high expectations and encouragement from family),
(c) intrinsic motivation (e.g., pursing majors that would allow them to help others), (d) internal locus of control, and (e) self-efficacy (Cavazos, Johnson, and Sparrow, 2010). Counselors working with Latinx FGCS on the high school or college levels need to be aware of these resiliency factors so they can provide culturally competent support.
Implications for High School and College Counselors
High school and college counselors can play important roles in the college transition and persistence of Latinx FGCS (Adelman, 1999; Avery, 2010; Bishop, 2010; McDonough, 2005; McKillip et al., 2012). Counselors can provide FGCS with college information and support, which is the cultural capital that most FGCS lack. Therefore, an implication for school counselors includes identifying college-bound Latinx FGCS and tailoring college information to these students. Counselors can design interventions at both the individual and school-wide levels to use the strengths inherent in Latinx cultural norms. Counselors may consider leveraging familismo and intentionally design outreach programs and psychoeducation related to college preparation, information, activities, and expectations to include students’ families and friends. Engaging in informal interactions and hosting events in the community (as opposed to within school buildings) may enhance participant comfort with attending events. Topics may include: (a) helping family members have realistic expectations of academia and campus life, (b) addressing the potential of students feeling isolated or stretched between campus and family life, and (c) fostering a college-going mentality by providing information on course rigor, careers, college admission, and the financial aid process.
A similar implication can be directed toward college counselors. It is important for college counselors to have a presence on their campus beyond the counseling center. In particular, they can develop and support initiatives on campus directed toward the psychosocial needs of Latinx FGCS. Thus, college counselors having an increased presence on their campus can help Latinx FGCS understand the support counseling can offer in assisting with college persistence. College counselors can time outreach, interventions, and services to target developmental windows when FGCS’ identity is most salient for students—typically when entering college and when approaching graduation (Orbe, 2004). Additionally, counselors are equipped to provide social and emotional support for negotiating and navigating new and multiple identities and addressing feelings of isolation, both on the college campus and with family. When conceptualizing clients, understanding and framing cultural expressions and values as strengths is critical. For example, fatalismo is reframed from the idea of accepting defeat to moving toward acceptance and using this as a strength that allows the client to move forward in new directions.
Many Latinx students also experience negative stereotypes, prejudices, marginalization, and microaggressions (Gonzales et al., 2002; Rodriguez et al., 2000; Valencia, 2002; Yosso et al., 2009) on their campuses. These experiences may lead many Latinx FGCS to question their sense of belonging on their campuses. High school and college counselors can develop and encourage initiatives supporting diversity on their campuses. Furthermore, high school and college counselors can help Latinx FGCS develop positive coping strategies for dealing with the lack of diversity on their campuses and the internal struggles that arise with their sense of belonging. Counselors should continue to maintain awareness of unconscious bias, engage in accessing diversity and advocacy continuing education, and act as allies. Adopting the habit of framing the unique cultural context of individual Latinx clients as strengths, fostering connections, and identifying culturally applicable adjunct supportive services (e.g., spiritual or religious supports) are within the purview of professional counselors.
The general consensus in college student development theory is that to successfully adjust to college, students need to break from their own culture in order to conform to higher education culture (Nora, 2001; Rendón, 1994). To address this, universities typically provide programming designed to help students adapt to and adopt the existing institutional culture (Rendón, 1994). Alternately, college counselors are in positions that can challenge the privileging of traditional assumptions and values of the academy and influence the recognition and valuing of multiple cultures and ways of being. Rather than requiring students to negotiate overt and covert norms that assume prior knowledge or familiarity with the culture of higher education, counselors can help students identify counterspaces within the institution. For Latinx FGCS, this might include connecting with diverse faculty who could serve as mentors, participating in programs from the multicultural affairs office, or participating in student organizations centered on Latinx culture and identities. Developing relationships with key members of the campus Latinx community and moving access to counseling services outside of the traditional, potentially restrictive environment of the university counseling center may enhance service access and delivery for this underrepresented student population.
Areas for Future Research
Researchers are beginning to examine the concept of cultural wealth (O’Shea, 2016; Yosso, 2005) as it applies to FGCS. Examining Latinx FGCS and the college experience from this lens fits with the strengths-based perspective inherent in counseling and provides an opportunity for professional counselors to reframe their interventions. Further research is warranted on the high school and college experiences of Latinx FGCS. All Latinx cultures tend to be lumped together. Researchers could investigate the experiences of FGCS from an ethnic-specific Latinx group (e.g., Mexicans, Puerto Ricans, or Cubans). Moreover, research could examine the counseling experiences of Latinx FGCS. Examining the counseling experiences of Latinx FGCS can help professional counselors gain a better understanding of their counseling needs. Another possible direction for future research includes examining the microaggressions experienced by Latinx FGCS; future studies need to fully investigate the impact of microaggressions on the college persistence of Latinx FGCS. The findings from these studies can help high school and college counselors understand how they can begin to address the concerns that negatively impact Latinx FGCS.
Latinx FGCS are a growing demographic on college campuses. However, it is clear that these students are not receiving the support needed to assist in their transition from high school to college. The psychosocial and emotional needs of Latinx FGCS are often overlooked in the literature. Latinx students who feel culturally incongruent on their campuses struggle with their sense of belonging (Edman & Brazil, 2009; Hurtado & Carter, 1997). High school and college counselors have the skills to help address the psychosocial and emotional needs of Latinx FGCS. Furthermore, high school and college counselors can work together to share knowledge and bridge the gap between high school and college expectations, institutional culture, and provision of counseling services in ways that would benefit Latinx FGCS.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
Adelman, C. (1999). Answers in the tool box: Academic intensity, attendance patterns, and bachelor’s degree attainment. Washington, DC: U.S. Department of Education.
Aguilera, A., Garza, M. J., & Muñoz, R. F. (2010). Group cognitive-behavioral therapy for depression in Spanish: Culture-sensitive manualized treatment in practice. Journal of Clinical Psychology, 66, 857–867. doi:10.1002/jclp.20706
American Counseling Association. (2014). 2014 ACA code of ethics. Retrieved from http://www.counseling.org/docs/ethics/2014-aca-code-of-ethics.pdf?sfvrsn=4
Atherton, M. C. (2014). Academic preparedness of first-generation college students: Different perspectives. Journal of College Student Development, 55, 824–829. doi:10.1353/csd.2014.0081
Avery, C. (2010). The effects of college counseling on high-achieving, low-income students. Cambridge, MA: National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w16359.pdf
Avila, D. L., & Avila, A. L. (1995). Mexican-Americans. In N. A. Vacc, S. B. DeVaney, & J. Wittmer (Eds.), Experiencing and counseling multicultural and diverse populations (3rd ed., pp. 119–146). Bristol, PA: Accelerated Development.
Baumann, A. A., Kuhlberg, J. A., & Zayas, L. H. (2010). Familism, mother-daughter mutuality, and suicide attempts of adolescent Latinas. Journal of Family Psychology, 24, 616–624. doi:10.1037/a0020584
Bergerson, A. A. (2007). Exploring the impact of social class on adjustment to college: Anna’s story. International Journal of Qualitative Studies in Education, 20, 99–119. doi:10.1080/09518390600923610
Bishop, J. B. (2010). The counseling center: An undervalued resource in recruitment, retention, and risk management. Journal of College Student Psychotherapy, 24, 248–260. doi:10.1080/87568225.2010.509219
Borrero, N. (2011). Shared success: Voices of first-generation college-bound Latino/as. Multicultural Education, 18(4), 24–30.
Castro, E. L., & Cortez, E. (2017). Exploring the lived experiences and intersectionalities of Mexican community college transfer students: Qualitative insights toward expanding a transfer receptive culture. Community College Journal of Research and Practice, 41(2), 77–92. doi:10.1080/10668926.2016.1158672
Cavazos, J., Jr., Johnson, M. B., Fielding, C., Cavazos, A. G., Castro, V., & Vela, L. (2010). A qualitative study of resilient Latina/o college students. Journal of Latinos and Education, 9(3), 172–188. doi:10.1080/15348431003761166
Cavazos, J., Jr., Johnson, M. B., & Sparrow, G. S. (2010). Overcoming personal and academic challenges: Perspectives from Latina/o college students. Journal of Hispanic Higher Education, 9, 304–316.
Cerezo, A. C., & Chang, T. (2013). Latina/o achievement at predominantly white universities: The importance of culture and ethnic community. Journal of Hispanic Higher Education, 12, 72–85. doi:10.1177/1538192712465626
Clauss-Ehlers, C. S. (2006). Religious/spiritual beliefs: Personalismo. In Y. Jackson (Ed.), Encyclopedia of multicultural psychology (pp. 411–412). Thousand Oaks, CA: Sage.
Delgado Gaitan, C. (2013). Creating a college culture for Latino students: Successful programs, practices, and strategies. Thousand Oaks, CA: Corwin.
Edman, J. L., & Brazil, B. (2009). Perceptions of campus climate, academic efficacy and academic success among community college students: An ethnic comparison. Social Psychology of Education, 12, 371–383. doi:10.1007/s11218-008-9082-y
Franklin, C. G., & Soto, I. (2002). Keeping Hispanic youths in school. Children & Schools, 24, 139–143. doi:10.1093/cs/24.3.139
Fry, R. (2011). Hispanic college enrollment spikes, narrowing gaps with other groups. Washington, DC: Pew Hispanic Center.
Gloria, A. M., Castellanos, J., Lopez, A. G., & Rosales, R. (2005). An examination of academic nonpersistence decisions of Latino undergraduates. Hispanic Journal of Behavioral Sciences, 27, 202–223. doi:10.1177/0739986305275098
Gloria, A. M., Castellanos, J., Scull, N. C., & Villegas, F. J. (2009). Psychological coping and well-being of male Latino undergraduates: Sobreviviendo la universidad. Hispanic Journal of Behavioral Sciences, 31, 317–339.
Gloria, A. M., & Rodriguez, E. R. (2000). Counseling Latino university students: Psychosociocultural issues for consideration. Journal of Counseling & Development, 78, 145–154. doi:10.1002/j.1556-6676.2000.tb02572.x
Gonzales, P. M., Blanton, H., & Williams, K. J. (2002). The effects of stereotype threat and double-minority status on the test performance of Latino women. Personality and Social Psychology Bulletin, 28, 659–670. doi:10.1177/0146167202288010
Hernández, B., Ramírez Garcia, J. I., & Flynn, M. (2010). The role of familism in the relation between parent-child discord and psychological distress among emerging adults of Mexican descent. Journal of Family Psychology, 24(2), 105–114. doi:10.1037/a0019140
Holloway, R. A., Waldrip, A. M., & Ickes, W. (2009). Evidence that a simpático self-schema accounts for differences in the self-concepts and social behavior of Latinos versus Whites (and Blacks). Journal of Personality and Social Psychology, 96, 1012–1028. doi:10.1037/a0013883
Hovey, J. D., & Morales, L. R. (2006). Religious/spiritual beliefs: Fatalismo. In Y. Jackson (Ed.), Encyclopedia of multicultural psychology (pp. 409–410). Thousand Oaks, CA: Sage.
Hurtado, S. (1994). The institutional climate for talented Latino students. Research in Higher Education, 35, 21–41.
Hurtado, S., & Carter, D. F. (1997). Effects of college transition and perceptions of the campus racial climate on Latino college students’ sense of belonging. Sociology of Education, 70, 324–345.
Hurtado, S., Carter, D. F., & Spuler, A. (1996). Latino student transition to college: Assessing difficulties and factors in successful college adjustment. Research in Higher Education, 37, 135–157.
Hurtado, S., Milem, J. F., Clayton-Pederson, A. R., & Allen, W. R. (1998). Enhancing campus climates for racial/ ethnic diversity: Educational policy and practice. The Review of Higher Education, 21, 279–302. doi:10.1353/rhe.1998.0003
Kuhlberg, J. A., Peña, J. B., & Zayas, L. H. (2010). Familism, parent-adolescent conflict, self-esteem, internalizing behaviors, and suicide attempts among adolescent Latinas. Child Psychiatry & Human Development, 41, 425–440. doi:10.1007/s10578-010-0179-0
Lowery-Hart, R., & Pacheco, G., Jr. (2011). Understanding the first-generation student experience in higher education through a relational dialectic perspective. New Directions for Teaching & Learning, 2011(127), 55–68. doi:10.1002/tl.457
Lundberg, C. A., Schreiner, L. A., Hovaguimian, K., & Miller, S. S. (2007). First generation status and student race/ethnicity as distinct predictors of student involvement and learning. NASPA Journal, 44, 57–83.
Marín, G., & Marín, B. V. (1991). Research with Hispanic populations: Applied social science research methods series volume 23. Thousand Oaks, CA: Sage Publications.
McDonough, P. M. (2005). Counseling and college counseling in America’s high schools. Alexandria, VA: National Association for College Admission Counseling. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.543.5670&rep=rep1&type=pdf
McKillip, M. E. M., Rawls, A., & Barry, C. (2012). Improving college access: A review of research on the role of high school counselors. Professional School Counseling, 16, 49–58.
Morales, E. E. (2008). Academic resilience in retrospect: Following up a decade later. Journal of Hispanic Higher Education, 7, 228–248. doi:10.1177/1538192708317119
Nora, A. (2001). The depiction of significant others in Tinto’s ‘‘Rites of Passage’’: A reconceptualization of the influence of family and community in the persistence process. Journal of College Student Retention: Research, Theory & Practice, 3, 41–56. doi:10.2190/BYT5-9F05-7F6M-5YCM
Orbe, M. P. (2004). Negotiating multiple identities within multiple frames: An analysis of first-generation college students. Communication Education, 53, 131–149. doi:10.1080/03634520410001682401
Orbe, M. P. (2008). Theorizing multidimensional identity negotiation: Reflections on the lived experiences of first-generation college students. New Directions for Child and Adolescent Development, 2008(120), 81–95. doi:10.1002/cd.217
O’Shea, S. (2016). Avoiding the manufacture of ‘sameness’: First-in-family students, cultural capital and the higher education environment. Higher Education, 72, 59–78. doi:10.1007/s10734-015-9938-y
Passel, J. S., Cohn, D., & Hugo Lopez, M. (2011). Hispanics account for more than half of nation’s growth in past decade: Census 2010: 50 million Latinos. Washington, DC: Pew Hispanic Center.
The Pell Institute. (2008). Moving beyond access: College success for low-income first-generation students. Retrieved from https://files.eric.ed.gov/fulltext/ED504448.pdf
Pierce, C. M. (1995). Stress analogs of racism and sexism: Terrorism, torture, and disaster. In C. V. Willie, P. P. Rieker, B. M. Kramer, & B. S. Brown (Eds.), Mental health, racism, and sexism (pp. 277–293). Pittsburgh, PA: University of Pittsburgh Press.
Pratt, I. S., Harwood, H. B., Cavazos, J. T., & Ditzfeld, C. P. (2017). Should I stay or should I go? Retention of first-generation college students. Journal of College Student Retention: Research, Theory & Practice, 36, 1–14. doi:10.1177/1521025117690868
Prospero, M., & Vohra-Gupta, S. (2007). First generation college students: Motivation, integration, and academic achievement. Community College Journal of Research and Practice, 31, 963–975. doi:10.1080/10668920600902051
Rendón, L. I. (1994). Validating culturally diverse students: Toward a new model of learning and student development. Innovative Higher Education, 19, 33–51.
Rodriguez, A. L., Guido-DiBrito, F., Torres, V., & Talbot, D. (2000). Latina college students: Issues and challenges for the 21st century. NASPA Journal, 37, 511–527. doi:10.2202/1949-6605.1111
Saenz, V. B., Hurtado, S., Barrera, D., Wolf, D. S., & Yeung, F. P. (2007). First in my family: A profile of first-generation college students at four-year institutions since 1971: The Foundation for Independent Education. Retrieved from https://heri.ucla.edu/PDFs/resSummary051807-FirstGen.pdf
Santiago, D. A., Calderón Galdeano, E., & Taylor, M. (2015). Factbook 2015: The condition of Latinos in education. Retrieved from http://www.edexcelencia.org/research/2015-factbook
Saunders, M., & Serna, I. (2004). Making college happen: The college experiences of first-generation Latino students. Journal of Hispanic Higher Education, 3, 146–163. doi:10.1177/1538192703262515
Slaughter, J. B. (2009). It’s time to get angry about underserved students. Chronicle of Higher Education, 55(20), A68.
Snyder, T. D., de Brey, C., & Dillow, S. A. (2016). Digest of education statistics 2015 (NCES 2016-014). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC. Retrieved from https://nces.ed.gov/pubs2016/2016014.pdf
Stieha, V. (2010). Expectations and experiences: The voice of a first-generation first-year college student and the question of student persistence. International Journal of Qualitative Studies in Education, 23, 237–249. doi:10.1080/09518390903362342
Storlie, C. A., Moreno, L. S., & Portman, T. A. A. (2014). Voices of Hispanic college students: A content analysis of qualitative research within the Hispanic Journal of Behavioral Sciences. Hispanic Journal of Behavioral Sciences, 36, 64–78. doi:10.1177/0739986313510283
Sue, D. W., & Sue, D. (2016). Counseling the culturally diverse: Theory and practice (7th ed.). Hoboken, NJ: John Wiley & Sons, Inc.
Tello, A. M. (2015). The psychosocial experiences of Latina first-generation college graduates who received financial and cultural capital support: A constructivist grounded theory (Doctoral dissertation). Retrieved from ProQuest. (3702397)
Tym, C., McMillion, R., Barone, S., & Webster, J. (2004). First generation college students: A literature review. Austin, TX: Research and Analytical Services. Retrieved from https://www.tgslc.org/pdf/first_generation.pdf
Valencia, R. R. (2002). Mexicans don’t value education!: On the basis of the myth, mythmaking, and debunking. Journal of Latinos and Education, 1(2), 81–103. doi:10.1207/S1532771XJLE0102_2
Vélez, V. N. (2016). Organizing for change: Latinx im/migrant parents, school decision-making, and the racial politics of parent leadership in social reform. Association of Mexican American Educators Journal, 10(3), 108–125. Retrieved from https://eric.ed.gov/?id=EJ1124412
Wang, C.-C. D. C., & Castañeda-Sound, C. (2008). The role of generational status, self-esteem, academic self-efficacy, and perceived social support in college students’ psychological well-being. Journal of College Counseling, 11(2), 101–118.
Ward, L., Siegel, M. J., & Davenport, Z. (2012). First-generation college students: Understanding and improving the experience from recruitment to commencement. San Francisco, CA: Jossey-Bass.
Yosso, T. J. (2005). Whose culture has capital? A critical race theory discussion of community cultural wealth. Race Ethnicity and Education, 8, 69–91. doi:10.1080/1361332052000341006
Yosso, T. J., Smith, W. A., Ceja, M., & Solórzano, D. G. (2009). Critical race theory, racial microaggressions, and
campus racial climate for Latina/o undergraduates. Harvard Educational Review, 79, 659–690.
Angelica M. Tello, NCC, is an assistant professor at the University of Houston-Clear Lake. Marlise R. Lonn, NCC, is an assistant professor at Bowling Green State University. Correspondence can be addressed to Angelica Tello, 2700 Bay Area Blvd., Houston, TX 77058-1002, firstname.lastname@example.org.