Addiction Counseling Licensure Issues for Licensed Professional Counselors

Keith Morgen, Geri Miller, LoriAnn S. Stretch

This article addresses the obstacles of effectively integrating addiction counseling into a nationwide definition of professional counseling scope of practice. The article covers an overview of issues, specific licensure and credentialing frameworks (LPC, CADC, LCADC) in two U.S. states, and recommendations to effectively bridge the gap between professional and addiction counseling. Historical origins and an overview of addiction counseling are presented.

Keywords: addiction, licensure, credentialing, LPC, CADC, LCADC

The question of professional identity within the counseling profession, first considered during the founding of the American Personnel and Guidance Association (Sweeney, 1995), still exists today (Calley & Hawley, 2008; Cashwell, Kleist, & Schofield, 2009; Mellin, Hunt, & Nichols, 2011; Myers, Sweeney, & White, 2002; Nassar-McMillan & Niles, 2011; Remley & Herlihy, 2009). One possible reason for the continual debate around professional identity may lie in the multitude of specialty fields (e.g., addiction, career, and school) within counseling (Gale & Austin, 2003; Myers, 1995; O’Brien, 2010). Remley (1995) underscores that unlike psychology, psychiatry and social work, counseling is the only mental health profession that licenses specialty areas. Specialty areas such as career and school counseling only denote a practice area or population; whereas addiction counseling actually entails a DSM-IV-TR Axis I disorder (i.e., Substance Use Disorders; American Psychiatric Association, 2000). No other Axis I or Axis II disorder receives such attention.

Addiction is considered a part of professional counseling as implied by the latest CACREP standards (2009). However, a separate licensure track exists for the profession of addiction counseling. If the practice of addiction counseling really is a part of counseling (as implied by the latest 2009 CACREP standards), then the time has come to recalibrate the rest of the counseling profession to better fit an inclusive and unifying professional counseling identity that includes addiction counseling. Thus, the purpose of this paper is to start the dialogue regarding the mixed messages on the issue of counselor identity and specialization for addiction counseling (Morgen, Miller, Culbreth, & Juhnke, 2011; Tabor, Camisa, Yu, & Doncheski, 2011). The article is divided into an overview of issues, specific licensure and credentialing frameworks in two sample states (New Jersey and North Carolina), and recommendations in response to the concerns discussed.

Overview of Issues

Henriksen, Nelson, and Watts (2010) criticize the counseling specialty system by arguing that counseling specialties do not define counseling but merely denote a practice area, and that counseling specialty licensure/credentialing implies that only a small proportion of the counseling profession is qualified to work with this population. The addiction area is one such area of specialization that comes with a separate licensure/credentialing process. The authors believe that in regard to addiction counseling, the additional supervisory and training hours required for addiction licensure/credentialing (in addition to the supervisory and training hours required for licensure as a professional counselor) implies that addiction content falls outside the professional counseling scope of practice.

For instance, if the graduate counseling program does not possess an addiction track, a cursory review of curriculum at CACREP and non-CACREP programs found the typical option of one addiction course as an elective. However, curricular reviews of numerous programs find few to no electives on other DSM-IV-TR disorders (e.g., mood, anxiety). Thus, the authors argue this produces a confusing mixed message in that licensure as a professional counselor covers practice areas that typically receive minimal exclusive attention (e.g., one-week discussion on anxiety disorders in a maladaptive behavior course), yet an area where one (or more) electives are typically offered for in-depth study of a disorder (such as addiction) comes with an entirely unique and separate licensure process.

The presence of a separate licensure/credentialing process for addiction counseling seems antiquated considering the extensive training required for a graduate counseling degree. Furthermore, most states consider addiction work within the professional counselor scope of practice (Tabor et al., 2011). Thus, the pioneering issue this paper addresses is whether it is time to thoughtfully reconsider how addiction is conceptualized in professional counseling (beyond the inclusion in the most recent CACREP standards) and recalibrate the education and licensure processes accordingly. In order to begin this dialogue a brief review of the history of the licensure/credentialing process of addiction counselors needs to be provided.

Historical Origins of the Issue

Historically across most states, the advent of addiction counseling licensure/credentialing standards occurred parallel with the professionalization of the counseling field (i.e., the master’s-level state licensure laws). States mandated that graduate school-level professionals conduct counseling, leaving many long-time and effective addiction counselors (many of whom possessed only a high school diploma or GED) out of the counseling mainstream. Consequently, addiction licensure/credentialing boards were established to achieve two goals. The first goal was to professionalize the addiction counseling field in a manner similar to professional counseling via mandated supervised practice hours and education across a subscribed addiction curriculum. The second goal was to provide a mechanism to grandfather into the profession those addiction counselors who had long worked in the field and provided outstanding services. Without the grandfather clause, many of these addiction counselors would have lost their profession or would have needed to put their career on pause as they obtained the required education and/or training.

The professionalization of addiction counseling, including licensure and credentialing, strengthened the field and provided a higher quality of care to those struggling with addiction. Unfortunately, a system also was established that over 30 years reinforced the notion that addiction falls outside the scope of practice for professional counseling (i.e., the presence of a separate licensure and certification processes focused on addiction counseling). While the addiction counseling field did need professionalization, perhaps the original high standards (e.g. upwards of 3,000 hours of clinical practice with supervision) now require recalibration that takes into account a new era where counselor training for those engaged in addiction work extends far beyond a high school diploma or GED.

Professionalization or Deterrent?

The authors’ perspective in this paper is that imbedded in the current licensure and credentialing process for addiction counseling is the message that LPCs cannot or should not do addiction work. The message comes from a confusing mixed array of information. Using the graduate trainee (the next generation of counseling professional) as an example, it becomes clear as to how future LPCs may shy away from addiction work. For instance, in the classroom graduate students read about how counseling includes working in the addiction area (as per the latest CACREP standards). Graduate students are trained in a graduate counseling curriculum that offers advanced addiction course electives and the possibility of doing practicums or internships at an addiction facility. Many of these graduate students may even attend school in a state where addiction work is covered in the professional counseling scope of practice. But, these students also see professional counselors with separate addiction licenses (e.g., LPC and LCADC) and employment announcements requesting/requiring an addiction license. Even the National Board of Certified Counselors (NBCC) Master Addiction Counselor Credential (MAC) focused on this one DSM-IV-TR disorder class (with no other NBCC credential so narrowly focused on one DSM-IV-TR disorder). Because the student does not see an NBCC credential for mood disorders or sees a licensure for anxiety disorders, the imbedded message is strengthened.

The mixed messages coupled with the burdensome task of meeting the mandates for two professional bodies (professional counseling and addiction) may drive some new counselors from the addiction field. For example, at the end of a panel discussion on this topic at the 2011 American Counseling Association Conference (Morgen et al., 2011), a new graduate of a professional counseling master’s program said she would like to start accruing practice hours in a substance use disorders clinic as she had completed some internship hours there and took a course on substance use disorders. However, the facility where she wanted to work required her to obtain an addiction license in addition to her professional counseling license. She subsequently indicated that she did not have the time, money, or the energy to do both and was thus looking outside the substance use disorders field for employment. This anecdote clearly demonstrates how newly graduated counseling professionals (especially those working in the provisional licensure period) may be inhibited from entering the addiction counseling field.

How many qualified, talented and motivated students are we turning away from the addiction counseling field due to these extra training requirements unique to working with the specific DSM-IV-TR Axis I Substance Use Disorder diagnosis at a time when there is an ever-growing need for services (e.g., addiction in returning veterans or the chronically unemployed)? Effective training of LPCs who work with addiction requires coordination between educational training institutions and actual practice that reflects reasonable experienced-based requirements for working in the area of addiction as well as respect for the graduate-level degree (e.g., master’s or doctorate) and training the counselor has already received. Such coordination varies from state to state and without a guarantee of such coordination the danger is that well-intentioned, well-trained counselors will enter the field technically qualified to counsel individuals, but philosophically lacking the integration of theory and practice necessary for treating addiction. This could mean, for example, that the counselor is more vulnerable to enabling the active addictive process and thereby not providing counseling in the best interest of the client.

In an effort to initiate the dialogue on how to perhaps recalibrate the system, it first seems warranted to review the professional and addiction counseling licensure laws and policies within two states. The authors intend to (over the next few years) review the state laws and policies for all 50 states. However, for the purposes of this initial paper, New Jersey and North Carolina will be discussed below.

Specific State Issues

New Jersey
New Jersey operates a professional counseling license (LPC) with a minimum education of a graduate counseling degree, a certified alcohol and drug abuse counselor credential (CADC) requiring a minimum education of bachelor’s degree, associate degree, high school diploma or GED, and a licensed clinical and alcohol and drug abuse counselor (LCADC) with a minimum education of a graduate counseling degree and qualification for the CADC. The LPC is governed by the Professional Counselor Examiners Committee (imbedded within the Marriage and Family Therapy Board), whereas the CADC/LCADC is governed by the Alcohol and Drug Counselor Committee.

According to the regulations for professional counseling, New Jersey defines counseling in part as “using currently accepted diagnostic classifications including, but not limited to the DSM-IV” (NJ Board of Marriage and Family Therapy Examiners, 2009, 13:34-10.2, p. 34-22). Substance use disorders fall within Axis I of the DSM-IV-TR, thus work with substance use disorders seems in line with the professional regulations of the LPC. Further evidence of this fact exists within the LCADC regulations (NJ Alcohol and Drug Counselor Committee, 13:34C-2.6, p. 34C-10) that states the following individuals are exempt from the LCADC licensure requirement:

A person doing work of an alcohol or drug counseling nature, or advertising those
services, when acting within the scope of the person’s profession or occupation and
doing work consistent with the person’s training, including physicians, clinical social
workers, professional counselors, marriage and family therapists, psychologists, nurses
or any other profession or occupation licensed by the State, or students within accredited
programs of these professions, if the person does not hold oneself out to the public as
possessing a license or certification issued pursuant to the Act or this chapter.

As long as an LPC does not advertise oneself as an addiction or substance abuse counselor, they are completely free to practice counseling with individuals presenting with addiction.

However, new counselors and LPCs who wish to accrue hours toward addiction licensure/credentialing face obstacles within the hiring process for addiction-focused positions. For example, despite the clear language in the LPC and CADC/LCADC regulations, advertised positions in the addiction counseling field in New Jersey typically include language stating “actively pursuing CADC/LCADC” or “must hold a New Jersey CADC/LCADC.” These requirements (which again, contradict the language of the New Jersey LPC and LCADC regulations) are typically in place due to a mandate of the program funding source (e.g., state or federal). Private practice counselors (who do not operate any funded programs with the above-mentioned requirements) are free to practice addiction work if qualified. However, most (if not all) of the addiction counseling positions where a new professional counseling graduate can accrue hours are housed in some type of treatment facility that very likely must adhere to the LCADC mandate, thereby limiting access to positions for those seeking to accrue LPC hours within the addiction counseling field.

In New Jersey, the typical master’s student who wants to accrue hours for licensure as an LPC must produce approximately 4,500 supervised counseling hours. This process comes immediately after the challenging two to three years of graduate study and passing the National Counselor Exam (NCE). However, to obtain the LCADC these students must complete an additional and separate 3,000 supervised addiction counseling hours, 270 clock hours of education focused on counseling and addiction, and 300 hours of supervised practical training in core counseling areas such as screening, intake, assessment, etc. The primary and most time-consuming problem lies in the need to accrue the supervised addiction counseling hours. Since the supervised counseling hours cannot be combined (e.g., there is no language in either the LPC or LCADC regulations permitting or denying the “double-dipping” of an hour for inclusion in both the LPC and LCADC hours accrual for licensure; this alone is confusing and indicates a need for clarification), the trainee working towards licensure who wishes to work in an addiction facility must accrue thousands of extra hours or opt to only work towards the LCADC. No other DSM-IV-TR disorder class comes with this burdensome extra mandated training requirement.

Recent efforts to integrate the mental health and addiction licensure processes in New Jersey are in motion, but still in an early phase. Much of this work is coming from a project sponsored by the New Jersey Division of Mental Health and Addiction Services designed to train the next generation of dual-licensed and trained (mental health and addiction) practitioners. However, this need to streamline the process is only present because of the dual licenses already in place. Furthermore, the premise of the program (though an excellent contribution) still propels the notion that addiction falls outside the scope of LPC practice and there needs to be a process to merge the two together. Despite the benefits of this new initiative, the end result is still the same: two different licenses. Again, this is the only DSM-IV-TR disorder that receives this treatment.

North Carolina
North Carolina has a well-coordinated system for addiction counselors. All professionals who want to be licensed to work in the addiction counseling field need to go through the same board, the NC Substance Abuse Professional Practice Board (the Board), which is “recognized as the registering, certifying, and licensing authority for substance abuse professionals” (Practice Act, 2005, Senate Bill 705, North Carolina General Assembly, § 90 113.32). One board eliminates competition between boards and the related issues that arise. In fact, the Licensed Professional Counselors Act (LPC law) specifically exempts substance abuse counselors from the counseling law by declaring that nothing in the LPC law “shall prevent a person from performing substance abuse counseling or substance abuse prevention consulting” (NC Board of Licensed Professional Counselors, 2009, § 90-332.1.d). Having one board brings together individuals from various professions in a concerted effort to address the issues related to addiction counseling and to advocate for the field at a state level. This framework has the strength of cooperation between different professional groups and the absence of competition within a state.

This cooperation is enhanced by a tiered system (licensure and credentialing). Individuals may apply for licensure as a Licensed Clinical Addictions Specialist. With regard to entry at the licensure level, there are four main routes or criteria (Criteria A, Criteria B, Criteria C, and Criteria D). Although initially the system may be confusing to determine the criteria under which one fits, the advantage is that there is greater flexibility for the individual applying for licensure. This flexibility is the result of minimum requirement variation in the areas of education, training, experience, and supervision (Criteria A, B, & C), as well as professional discipline (e.g., psychology, social work, counseling—Criteria D). For specific guidelines and clarification of this summary, the reader is referred to:

In terms of similarities for the individual applying for licensure, there are two aspects that remain the same under Criteria A, B, and C: the submission of three letters of reference (there is some variation allowed for the individuals who can write these letters) and a passing score on a master’s level written examination administered by the Board. The variations under these criteria are as follows. In the area of education, Criteria A and B require a minimum of a master’s degree with a clinical application in a human services field from a regionally accredited college or university. In addition, in terms of training, Criteria A requires 180 hours of substance abuse specific training from either a regionally accredited college or university, which may include unlimited independent study or from training events of which no more than fifty percent (50%) shall be in independent study. Criteria C combines the education and training requirement in the minimum requirement of a master’s degree in a human services field with both a clinical application and a substance abuse specialty from a regionally accredited college or university that includes 180 hours of substance abuse specific education and training. In the area of experience, Criteria A requires two years postgraduate supervised substance abuse counseling experience, while Criteria B requires the applicant to be certified as a substance abuse counselor. Finally, regarding supervision, Criteria A requires documentation of a minimum of 300 hours of supervised practical training and provision of a board-approved supervision contract between the applicant and an applicant supervisor, while Criteria C requires one year of postgraduate supervised substance abuse counseling experience. Criteria D simply requires that the applicant has a substance abuse certification from a professional discipline that has been granted deemed status by the Board (i.e., possession of a certification to practice addictions work under another discipline, such as social work, and that certification is recognized by the counseling board).

Note that the Board also offers numerous credentials through certification for non-master’s-level professionals. These include the Certified Substance Abuse Counselor (CSAC), Certified Substance Abuse Prevention Consultant (CSAPC), Certified Criminal Justice Addictions Professional (CCJP) and the Substance Abuse Residential Facility Director (CSARFD) credentials. In terms of the CSAC and the CSAPC, the applicant needs to be of good moral character, not be (or have been) engaged in any practice or conduct that would be grounds for disciplinary action, have a minimum of a high school diploma or a high school equivalency certificate, sign a form attesting to the intention to adhere fully to the Board’s ethical standards, and submit a complete criminal history record check.

Additionally, a CSAC who completes a clinical master’s degree program in a human services field can seek the LCAS via Criteria B as outlined above. This criterion recognizes the fact that the CSAC has already completed a 300-hour supervised clinical practicum and has substance abuse specific work experience. In addition to submitting proof of one’s master’s degree, all one has to do to obtain the LCAS via this criteria is to submit three letters of reference from LCAS’s and/or master’s level CSAC’s and pass the LCAS examination.

This tiered system allows the counselor to enter the field with or without a masters’ degree and allows the master’s=level counselor to have an accelerated process if they acquire clinical application experience enhancing the possibility they are both technically and philosophically prepared to work in the addiction counseling field. The requirement of the clinical application experience may be a barrier for some counselors, but the intent is to serve the best interests of the public.

Finally, there is collaboration between the Board and specific university degree programs regarding the type and quality of the courses, thus increasing the chance that counselors are effectively trained to work in the addiction counseling field. While there is not “board approval” on the content areas, programs are approved for addiction counseling. Students who graduate from these master’s degree programs may seek the LCAS license via Criteria C (outlined above). The Board maintains a current list of school programs approved for application under Criteria C on its website:

While North Carolina’s tiered system of licensure and credentialing allows for greater flexibility for the individual applying to work in the addiction counseling field, the system can be overwhelming and does contribute to the perception that addiction counseling is a separate profession with separate education, training, supervision and practice. Kaplan and Gladding (2011), King (2011), and Gladding, Kaplan, Linde, Mascari, and Tarvydas (2011) have advocated along with others about the importance of a unified counseling identity with common skills, training and practice (particularly among counseling specialties).


Overall, there appears to be a need for a recalibration of the experienced-based training required for LPCs at a national level that will enhance their entrance into the field of addiction counseling. Currently, states that do not allow for multiple entries into the field have a tiered system of entry, or an approval mandate of the type or quality of the addiction training program, that may inhibit LPCs from practicing in the addiction counseling field. In states where there are significant barriers, professional counselors (fully licensed or in-training) entering the addiction counseling profession with a graduate degree may be required to complete additional training requirements that were created during a time when the addiction counseling professional possibly possessed no more than a high school diploma or GED, and such credentialing requirements (e.g., thousands of supervised hours) were imposed as a mechanism to professionalize the field. Considering the graduate counseling degree (and associated supervised counseling hours) held by a LPC or counselor-in-training accruing licensure hours, these mandates currently seem excessive and possibly even redundant. Presently, the North Carolina system may be one of the few in the United States that provides the fewest barriers for LPCs entering the addiction counseling field.

In the following section, two remedies for the licensure/credentialing problems are presented. Although myriad issues complicate the process (e.g., counselors are called different titles in different states and different state requirements are present for licensure/credentialing as an addiction counselor), the following suggestions in some conceptualization may spur more tangible action. Any formal action should likely come from a national committee set up through the American Counseling Association (ACA) and in conjunction with the ACA addiction division, The International Association of Addictions and Offender Counselors (IAAOC), as well as CACREP, and national bodies such as the National Association of Alcoholism and Drug Abuse Counselors (NAADAC) and the International Certification and Reciprocity Consortium (IC&RC). Committee representatives from these parties could examine the coordination of experience and training. Such a committee could develop guidelines for balancing these concerns for states to use in their individual recalibration of requirements.

Possible Solution #1: Nationally Recognized Tiered System of Addiction Counselor Credentialing
One of the difficulties in terms of the current state of addiction credentialing in the U.S. is the absence of uniform national curriculum training standards in the addiction field. Also, there are two main national credentialing groups: NAADAC and the IC&RC. Issues arise because affiliation with one of the two main credentialing groups and credentialing variations between these organizations can result in issues in terms of competition and the nature of the boards and exams required for credentialing. Miller, Scarborough, Clark, Leonard, and Keziah (2010) recommend the following with regard to addiction counseling: (a) portability of credentials, (b) competition reduction between credentialing groups and state boards, (c) national standards for addiction education and training, and (d) a standardized national licensure/credentialing process. Unfortunately, these recommendations have not yet been fully implemented.

One possible solution is to develop a tiered system of addiction counseling credentials at a national level that takes into account professional experience as well as educational training. There needs to be a balance between the idea that anyone with a general counseling degree can do addiction counseling and the idea that only a few select counselors can do the work. Furthermore, this balance should be firmly based upon the ACA Ethical Code that indicates that counselors only practice within their area(s) of competence (2005).

For example, graduates of professional counseling programs (e.g., those working towards LPC status) who have taken a nationally-approved addiction counseling curriculum and have completed practicum/internship experiences could be designated as having addiction credentials in addition to the LPC (i.e., a nationally approved addiction concentration). Therefore, graduate counseling coursework that includes addiction counseling education and practical experiences would enable new graduates to move seamlessly into the addiction counseling profession without the need for additional supervision hours or educational components (i.e., beyond the required supervised counseling hours and educational components required for the LPC). The system would eliminate the need for a professional counselor to acquire an additional and separate addiction license/certification. In addition, the national standards could promote portability of credentials. This compromise works to maintain the licensed/certified addiction counseling credentials in each state while also providing the LPC with the documented expertise required for many addiction facility positions. This tiered system also could facilitate enhanced training during the process of accruing hours for licensure by better focusing the training hours upon the interface between addiction and other mental health issues as opposed to the current parallel and disparate relationship between addiction and other mental health issues.

Possible Solution #2: Nationally Recognized Addiction Counseling Concentration Curriculum
There are issues regarding standardization of training that need to be addressed within the context of academia. In essence, what are the theoretical and practical skills required of an addiction counselor nationwide? There are numerous initial places to look into the process of establishing a nationally recognized addiction counseling concentration, such as the 2009 CACREP standards for addiction counseling and the Center for Substance Abuse Treatment’s (2006) Addiction Counseling Competencies: The Knowledge, Skills, and Attitudes of Professional Practice. By using these (and other) standards, all counseling programs (regardless of CACREP accreditation) can follow a standard recommended education experience for students who desire the addiction credential discussed in the first possible solution. Curricular issues would likely include standalone addiction courses, infusion of addiction content into other courses, faculty expertise in the addiction area and practicum and internship hours focused on addiction counseling practice.

In addition, the NCE and National Clinical Mental Health Counselor Examination (NCMHCE) would require some recalibration to take into account the curricular changes to a professional counseling education that includes the addiction counseling concentration. One caution is that any discussion of these and other training issues may produce opposing forces within academia, the counseling profession, the addiction counseling profession, state licensing/credentialing boards (both professional counseling and addiction) and individual counselor education professors and college/university departments. Again, that is why a national committee comprised of all involved parties is necessary to navigate this challenging process.

Concluding Comments

Two students graduate with a master’s degree in counseling. Both took elective courses in their area of interest; one in mood disorders, the other in addiction, and both did an internship in a counseling setting focused on their interest area. Upon graduation, the student with an interest in mood disorders can easily be brought onto the clinical roster of a mood disorders clinic and immediately start accruing hours towards licensure. Their provisional license is all that is required during the training period. Unfortunately, the graduate with an interest in addiction may face competing licensure and/or credentialing requirements between professional and addiction counseling, mandated extra training coupled with thousands of extra supervised hours, and/or the possibility of a denial of employment without the appropriate addiction credential.

The purpose of this article is to start the dialogue on how to effectively incorporate addiction counseling into the scope of practice and accepted role of the professional counselor. We firmly believe that effective counseling focused on addiction issues requires specific and rigorous counselor training. However, we also believe the current national practice of training and credentialing for addiction counseling must change. State-by-state, burdensome (and in some instances outdated) rules and regulations are keeping countless qualified, capable, and motivated counselors from entering the addiction field. The time has come to recalibrate the rest of the counseling profession to better fit an inclusive and unifying professional counseling identity that includes addiction counseling.


American Counseling Association. (2005). Code of ethics. Alexandria, VA: Author.
American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders: DSM-IV-TR (4th ed.). Washington, DC: Author.
Council for Accreditation of Counseling Related Educational Programs (2009). CACREP standards. Alexandria, VA: Author.
Calley, N., & Hawley, L. (2008). The professional identity of counselor educators. The Clinical Supervisor, 27(1), 3–16. doi:10.1080/07325220802221454
Cashwell, C., Kleist, D., & Schofield, T. (2009, August). A call for professional unity. Counseling Today, 52(2), 60–61.
Center for Substance Abuse Treatment. (2006). Addiction counseling competencies: The knowledge, skills, and attitudes of professional practice. Technical Assistance Publication (TAP) Series 21. DHHS Publication No. (SMA) 06-4171. Rockville, MD: Substance Abuse and Mental Health Services Administration.
Gale, A., & Austin, B. (2003). Professionalism’s challenges to professional counselors’ collective identity. Journal of Counseling & Development, 81(1), 3–10.
Gladding, S. T., Kaplan, D., Linde, L., Mascari, J. B., & Tarvydas, V. (2011, March). 20/20: A vision for the future of counseling – The new consensus definition of counseling. Educational session presented as the ACA 2011 Conference, New Orleans, LA.
Henriksen, R. C., Nelson, J., & Watts, R. E. (2010). Specialty training in counselor education programs: An exploratory study. Journal of Professional Counseling: Practice, Theory, and Research, 38(1), 39–51.
Kaplan, D. M., & Gladding, S. T. (2011). A vision for the future of counseling: The 20/20 principles for unifying and strengthening the profession. Journal of Counseling & Development, 89(3), 367–372.
King, J. H. (2011). The role of ethics in defining a counseling professional identity. Unpublished Ph.D. dissertation proposal, Capella University, United States: Minnesota.
Mellin, E. A., Hunt, B., & Nichols, L. M. (2011). Counselor professional identity: Findings and implications for counseling and interprofessional collaboration. Journal of Counseling & Development, 89(2), 140–147.
Miller, G. (2010). Learning the language of addiction counseling (3rd ed.). Hoboken, NJ: Wiley.
Miller, G., Scarborough, J., Clark, C., Leonard, J. C., & Keziah, T. B. (2010). The need for national credentialing standards for addiction counselors. Journal of Addictions & Offender Counseling, 30, 50–57.
Morgen, K., Miller, G., Culbreth, J., & Juhnke, G. (2011, March). Analysis of professional and addiction counseling licensure requirements, scope of practice, and training: National findings. Educational session presented at the American Counseling Association Conference & Exposition, New Orleans, LA.
Myers, J. (1995). Specialties in counseling: Rich heritage or force for fragmentation? Journal of Counseling & Development, 74(2), 115–116.
Myers, J., Sweeney, T., & White, V. (2002). Advocacy for counseling and counselors: A professional imperative. Journal of Counseling & Development, 80(4), 394.
Nassar-McMillan, S. C., & Niles, S. G. (2011). Developing your identity as a professional counselor. Belmont, CA: Brooks/Cole.
New Jersey Alcohol and Drug Counselor Committee. NJSA 45:2D-1 through 45:2D-18, 13:34C-1.1 through 13:34C-6.4.
New Jersey Board of Marriage and Family Therapy Examiners, NJSA 45:8B-13 and 34, Professional Counselor Regulations 13:34-9.1 through 13:34–19.6.
North Carolina Board of Licensed Professional Counselors, Licensed Professional Counselors Act § 90-332.1 (2009).
North Carolina Substance Abuse Professional Practice Board, North Carolina Substance Abuse Professional Practice Act § 90 113.32 (2005).
Remley Jr., T. (1995). A proposed alternative to the licensing of specialties in counseling. Journal of Counseling & Development, 74(2), 126–129.
Remley, T., & Herlihy, B. (2009). Ethical, legal, and professional issues in counseling (3rd ed.). Upper Saddle River, NJ: Merrill.
Sweeney, T. (1995). Accreditation, credentialing, professionalization: The role of specialties. Journal of Counseling & Development, 74(2), 117–125.
Tabor, J., Camisa, K., Yu, F., & Doncheski, M. (2011, March). Addressing nationwide Inconsistencies in the scope of practice for licensed professional counselors regarding substance abuse counseling. Poster presented at the American Counseling Association Conference and Exposition, New Orleans, LA.

Keith Morgen, NCC, teaches at Centenary College, Geri Miller teaches at Appalachian State University and LoriAnn S. Stretch teaches at Walden University. The authors thank Anna Misenheimer, Executive Director of the North Carolina Substance Abuse Professional Practice Board, for serving as a reader of the early drafts of this paper. Her feedback was critical in our sharpening the preliminary focus of the paper. Correspondence can be addressed to Keith Morgen, Centenary College, 400 Jefferson Street, Box 403, Hackettstown, New Jersey, 07840,

College-Student Personal-Growth and Attributions of Cause

W. P. Anderson Jr., Sandra I. Lopez-Baez

Little is known about levels of personal growth attributed by students to typical college life experiences. This paper documents two studies of student self-reported and posttraumatic growth and compares growth levels across populations. Both studies measure student attributions of cause to academic and non-academic experiences, respectively. It is suggested that future research on the outcome of college life experiences can use a similar approach with a variety of variables.

Keywords: college life, personal growth, posttraumatic growth, life experiences, attributions of cause, outcome of college

The results of a rapidly growing number of studies document high levels of adversarial growth attributed by survivors in retrospect to coping with negative life experiences (Linley & Joseph, 2004) including war, bereavement, or loss of a child. The Posttraumatic Growth Inventory (PTGI) by Tedeschi & Calhoun (1996) has been the most popular measure of adversarial growth to date (Joseph, Linley, & Harris, 2005; Linley & Joseph, 2004; Tedeschi & Calhoun, 2004). In this context, adversarial refers to the negative nature of an experience of interest to researchers. Growth refers to personal growth defined as the positive psychological changes described by assessment-instrument items, changes such as the building of interpersonal relationships, a greater appreciation of the value of life, and a realization of new possibilities in life (examples after Tedeschi & Calhoun, 1996). Thus, adversarial growth is personal growth attributed by participants to a naturalistic negative event of particular interest to researchers. We stumbled on the PTGI and the relationship between adversarial and personal growth while searching for an instrument for measuring personal growth attributed in retrospect to the sum of naturalistic experiences (both positive and negative) occurring during a time period of interest to researchers.

The growth of immediate interest to us is not adversarial, but rather the total personal growth of college students because our long-term goal is to determine how educators can best facilitate growth, whether adversarial or otherwise. Developmental theorists (Chickering, 1969; Chickering & Reiser, 1973; Pascarella & Terenzine, 1991; Perry, 1970) have suggested that students grow in response to the combination of typical experiences of college life. Although researchers have used a variety of instruments to measure both academic and personal growth (for recent examples see Hassan, 2008; Higgins, Lauzon, Yew, Brasweth, & Morley, 2009), little is known about how college-student growth compares to adversarial growth because comparisons require measures obtained with the same instrument. Therefore, we want to measure college-student growth with an instrument that has been used to measure adversarial growth. Tedeschi and Calhoun (2004) implied that the PTGI might be suitable for our purposes by characterizing its items as capturing the core of personal growth (without distinguishing between adversarial and personal growth). We decided to use the PTGI after noting that the developers themselves conducted the first study of non-adversarial growth based on the PTGI by using it to measure levels of personal growth described by college students in a small (n = 32) non-trauma comparison group (see study 3 in Tedeschi & Calhoun, 1996).

We conducted the second and third studies of interest (N = 347, N = 117) by using the PTGI to measure levels of college student personal growth, whether adversarial or otherwise attributed to a single semester of college life (Anderson & Lopez-Baez, 2008, 2011). All three previous studies documented mean levels of student personal growth near the midpoint of the range reported for posttraumatic studies (range 46.00–83.47 for 14 studies summarized by Linley & Joseph, 2004). In our second study, we elicited brief explanations from students to learn how they accounted for their growth (see Anderson & Lopez-Baez, 2011). Explanations were in the form of percentage attributions of total personal growth to student-identified naturalistic experiences and to a researcher-identified 3-hour course designed to facilitate growth (student explanations like: college internship accounted for 30% of my total personal growth, finding a job for 40%, 3-hour course of interest to researchers for 15%, miscellaneous other experiences for the remaining 15%). We refer to these explanations as attributions of cause. Student attributions of cause to academic experiences supported the appealing idea (to counselors and educators) that personal growth as defined and measured by the PTGI can be intentionally facilitated by activities designed to do so.

The two studies described in the current paper are the fourth and fifth based on the PTGI to measure college-student personal growth that was not strictly adversarial. Both samples are generally similar to those of our previous studies (Anderson & Lopez-Baez, 2008, 2011). The current studies extend the results of our previous ones by (1) measuring the growth attributed by sample members to substantially longer periods of college life and (2) eliciting separate attributions of cause for academic and non-academic experiences, respectively. The primary purpose of Study 1 was to examine the internal validity of student data collected with the PTGI by comparing the descriptive statistics among the results of Study 1 with those of the three previous studies described above (Anderson & Lopez-Baez, 2008, 2011; Tedeschi & Calhoun, 1996). The primary purpose of Study 2 was to measure graduating college-senior attributions of annual personal growth, in retrospect to their freshman, sophomore, junior, and senior years, respectively. Study 2 was descriptive.

Study 1: Cumulative Growth

Research questions 1 and 2 are designed to collect descriptive data. Research question 3 is designed to collect information about the internal validity of our data by testing hypotheses on the basis of comparisons of the results of Study 1 with the results of previous studies (Anderson & Lopez-Baez, 2008, 2011).
Research question 1. What levels of cumulative personal growth do participants describe for their college undergraduate years (descriptive statistics for PTGI scores)?
Research question 2. What cumulative percentage attributions of cause do participants describe for academic experiences (college credit) and non-academic (all other) experiences, respectively, during their college undergraduate years (descriptive statistics for attributions of cause)?
Research question 3. To what extent do the results of comparable studies reflect internal validity (comparisons of statistical results across studies)?


We recruited participants from among the 147 students in a 3-hour elective course, Problems of Personal Adjustment, taught by the first author at a southeastern university. The course covered topics of psychological adjustment and included activities to facilitate student personal growth. Data was collected at the end of the fall semester of 2007. Most students were third- and fourth-year undergraduates in the College of Arts and Sciences or the School of Commerce. A total of 137 students elected to participate (response rate 93.20%). After 15 questionnaires with missing data were eliminated, sample size was 122 (67 men, 55 women). Most participants were Caucasian (4 African Americans, 4 Hispanics, Asians, and Asian Americans) with a mean age of 21.05 (.79) years and a mean college career of 6.54 (1.34) completed semesters. Students were given extra credit for electing to participate.


Posttraumatic Growth Inventory. Each of the 21 PTGI items (Cronbach alpha = .90, test-retest r = .71) describes a single positive psychological change (Tedeschi & Calhoun, 1996). Examples (with corresponding subscale and number of subscale items) include: “A sense of closeness with others” (Relating to Others, 7 items), “I developed new interests” (New Possibilities, 5 items), “A feeling of self-reliance” (Personal Strength, 4 items), “A better understanding of spiritual matters” (Spiritual Change, 2 items), and “My priorities about what is important in life” (Appreciation of Life, 3 items). Participants of trauma studies are instructed to describe the degree of each change resulting from their trauma. Responses are positions on a 6-point Likert-type scale anchored by 0 (no change) and 5 (great change). Total score range is 0 to 105 (per-item basis 0 to 5.00). Tedeschi and Calhoun (1996) reported evidence for concurrent and discriminant validity (their second study 1996) and construct validity (their third study). We have previously reported mean levels of college-student growth of 59.07 (SD = 15.77, N = 347; Anderson & Lopez-Baez, 2008) and 60.42 (SD = 16.61, N = 117; Anderson & Lopez-Baez, 2011).

Blank table. We use a blank, 2-column table to elicit attributions of cause (see Appendix A). In column 1, participants list life experiences thought to have contributed most to their growth during their college years. Participants list estimates of corresponding percentage contributions to total growth in column 2. For purposes of this study, we tailored the table to provide subtotals of attributions of cause to academic experiences (lines 1–5) and non-academic experiences (lines 6–10). We pre-labeled Lines 4, 5, and 10. Line 4 refers to the course taught by the principal author from which participants were recruited.


Like subjects in our two previous studies, participants were instructed to complete a preliminary exercise to stimulate thinking about personal growth by answering questions that distinguished between level and salience of growth. We do not report the results because the research questions of the current study do not involve salience.

After completing the preliminary exercise, participants were given the following instructions for completing the PTGI (after study 3, Tedeschi & Calhoun, 1996):
Consider the degree to which each change listed below [21 items] has occurred in your life during your years as an undergraduate, whether or not the change was directly related to university class work. For each change, select the best response from the following scale [6 Likert-type options of Tedeschi & Calhoun, 1996] and write the number in the space provided.

Participants provided attributions of cause by completing the form in Appendix A. Participants were instructed to complete lines 1–10 of column 1 (brief descriptions of experiences thought to have contributed most to total growth) and column 2 (corresponding percentage contributions). Participants also provided 1-line qualitative explanations of how each experience on lines 1–10 of column 1 contributed to their growth (entries not analyzed because not required by research questions).


Cronbach alphas for each subscale calculated from the data of Study 1 are: .87 (all), .82 (Relating to Others), .65 (New Possibilities), .56 (Personal Strength), .82 (Spiritual Change), and .54 (Appreciation of Life). The mean female PTGI score of 71.71 (11.72) is greater than the mean male score of 66.94 (10.98), t (120) = 2.32, p = .022 < α = .05 (2-tail), d = .42. Male and female scores were combined because no significant gender differences were found by t-tests of corresponding subscale means (Bonferroni-corrected α = .01).

Research Question 1

Table 1 contains descriptive statistics for participant PTGI scores on a total and per-item basis. Magnitudes of Cronbach alphas reported above can be seen to reflect the variations in magnitude among the standard deviations reported for per-item subscale scores in Table 1 (larger Cronbach alphas are associated with larger standard deviations). This observation suggests that restricted ranges among our data for Personal Strength and Appreciation of Life account for the low values of alpha for each subscale.

The mean total of 69.09 (SD = 11.52) is greater than the midpoint of 52.50 for the maximum range of 0–105 and greater than the midpoint of 64.74 for the range of 46.00–83.47 reported for trauma studies (Linley & Joseph, 2004). The per-item mean of 3.29 (SD = .55) exceeds 3 or “moderate growth” on the 0 to 5 response scale (scale midpoint = 2.50). The per-item means for four of the five subscales are between 3.30 (SD = .77) and 3.65 (SD = .62), inclusive. The per-item mean for Spiritual Change is lower, 1.68 (SD = 1.17).

Research Question 2

Table 2 contains descriptive statistics for participant percentage attributions of cause to academic and non-academic experiences, respectively (from column 2 of Appendix A). Both subtotals are large although the non-academic subtotal is larger by a ratio of approximately 3:2. The three academic experiences thought by each participant to have contributed most to his or her growth account for 30.76% (14.79 + 8.03 + 7.94%) of the mean subtotal of 39.63% (SD = 11.94) of total personal growth. Illustrative examples include internships, terms abroad, and three-credit semester courses. Participants attribute the third largest contribution (7.94%) to a course designed to facilitate growth. Three non-academic experiences account for 50.31% (25.96 + 15.18 + 9.17%) of the mean subtotal 60.36% (SD = 11.94). Examples include illnesses, extracurricular activities, deaths of family members, and positive and negative changes in significant relationships.

Research Question 3

Numerical PTGI scores and percentage attributions of cause are subjective assessments by participants, as are most self-reports. Our research purposes require data with a degree of internal validity (veridicality or truthfulness; that is, correspondence between self-reports and actual subjective impressions). Internal validity can be assessed by comparing results of analyses across samples of multiple studies. For purposes of the following comparisons, we will use words to number our previous studies and a numeral to designate Study 1 of the current paper. Thus, our sample one (Anderson & Lopez-Baez, 2008) was a group of 347 students who described total growth in 2005 and 2006 for their preceding semester, M = 59.07 (SD = 15.77). Our sample two (Anderson & Lopez-Baez, 2011) was a group of 117 students who described total growth and attributions of cause in May of 2007 for their preceding semester, M= 60.42 (SD = 16.61). Our sample 1 is that of the current study. Samples are characterized by similar demographic characteristics.

Comparison one. Members of samples one and two described total growth for a single semester. Therefore, we expected samples one and two to have similar mean PTGI scores (null 1: unequal mean PTGI scores). A visual inspection finds similar means. Null 1 is rejected on the basis of that visual inspection, Cohen’s d of .08 (minimal effect size), and 95% C. I. of – 4.71 to 2.01 that includes 0.00 (SE difference = 1.71). As expected, mean total scores of samples one and two are similar.

Comparison two. Members of sample 1 described total growth over more semesters than did members of samples one or two. Therefore, we expected our sample 1 mean PTGI score to be higher than the mean of either sample one or sample two (nulls 2 and 3: sample 1 mean less than or equal to means of samples one and two, respectively). Nulls 2 and 3 are rejected on the basis of a 1-way ANOVA F (2, 593) = 20.02, p = .000, η2 = .064 with an independent variable of 3 groups and dependent variable of student PTGI scores; and Bonferroni post-hoc t-tests of student PTGI scores: sample one and sample 1, t (467) = 6.44, p = 0.000 < α = .0167 (2-tail), d = .73; sample two and sample 1, t (237) = 4.70, p = 0.000 < α = .0167 (2-tail), d = .61; sample one and sample two, t (462) = .79, p = .430 > α = .0167 (2-tail), d = .08. As expected, the sample 1 mean of 69.09 is greater than the means of both sample one and sample two.

Comparison three. Visual inspection of the subscale per-item mean scores of sample one (Anderson & Lopez-Baez, 2008) and sample two (Anderson & Lopez-Baez, 2011) found that four of the per-item means in each sample are approximately equal and that all four are greater than the corresponding mean Spiritual Change score by 1.50 to 2.00 scale divisions. Therefore, we expected the subscale scores of our sample 1 to exhibit the same pattern. Visual inspection (Table 1) finds that they do. Thus, as expected, the five subscale per-item mean scores of each of our three samples are characterized by four comparatively high and approximately equal subscale mean scores and a comparatively low mean Spiritual Change score.

Comparison four. Members of all three samples completed the same 3-credit course (during different semesters) designed to facilitate personal growth. Members of sample two and sample 1 were asked for attributions of cause for the course (Anderson & Lopez-Baez, 2011). The resulting attributions of cause to a course designed to facilitate growth are themselves evidence of internal validity. We expected members of sample two to attribute a larger percentage of total growth for one semester to the class than members of sample 1 attributed for the longer period of several semesters (directional null 4: sample two mean attributions of cause to course less than or equal to corresponding mean of sample 1). Null 4 is rejected on the basis of an independent t (237) = 12.18, p = .000 < α = .05 (1-tail), d = 1.56. As expected, the sample two mean attribution of cause to the course of 25.28 (14.28)% is greater than the corresponding sample 1 mean attribution of 7.94 (6.46)%.

Comparison five. Concurrent validity is the extent to which different measures of the same construct agree. We formulated Comparison five only after we saw an opportunity to investigate concurrent validity among the data of sample 1 by measuring the correspondence between high and low Spiritual Change scores in sample 1 and the presence or absence of corresponding written attributions of cause, respectively (null 5: no agreement). We defined high participant Spiritual Change scores as per-item mean scores of at least 3.50 scale divisions (at least 1 division above scale midpoint 2.50). Sample 1 contains 11 high scorers (2 students scored 5.00, 1 scored 4.50, 3 scored 4.00, 5 scored 3.50). We defined low Spiritual Change scores as per-item mean scores no larger than 1.50 scale divisions. Sample 1 contains 64 low scorers (14 students scored .00, 17 scored .50, 20 scored 1.00, and 13 scored 1.50). We added 19 questionnaires selected at random from those of the 64 low scorers to provide a sample of 30 questionnaires for analysis.

We examined each sample member’s written attributions of cause for evidence of spiritual growth. We defined evidence of spiritual growth narrowly by the wording of the Spiritual Change items (PTGI items 5 and 18). Thus, we defined evidence of spiritual growth as student descriptions of one or more attributions of cause with at least one explicit reference to religion or spirituality including references to worship, God (or other deity or deities), prayer, or religious writings; but not references to ethics, morality, or meaning of life in the absence of the required explicit references. (Example attributions interpreted as evidence include: my faith deepened, came to accept God’s will, learned more about Bible; but not: grew in commitment to boyfriend, learned importance of moral behavior, decided on career choice, or obtained new understanding of life). We easily reached consensus on all identifications because of the simple and specific definition of evidence adopted beforehand. Attributions by 6 of the 11 high scorers and 2 of the 19 low scores contained at least one reference to spiritual growth. Half of the 8 attributions with references to spiritual growth referred to religious studies classes.

High and low Spiritual Change scores corresponded to the presence or absence, respectively, of attributions of cause for 24 of 30 sample 1 members, percentage agreement = 80.00%. Spearman r is a measure of agreement between two series of nominal data that does not take into account the probability of chance matches. The probability of chance matches is high among data of interest because the sample is characterized by many low scores and many non-positive attributions of cause. Cohen’s κ (1960) is a measure of agreement between two series of nominal data that accounts for the probabilities of chance matches. Cohen’s κ was originally developed to assess inter-rater agreement and is widely used for that purpose. We used it instead to measure agreement after accounting for chance between two series of nominal data rated jointly by consensus. Kappa values have a range 0 to 1 and are interpreted like positive correlation coefficients. Null 5 is rejected on the basis of a Spearman r = .51, p = .005 (1-tail) and κ = .44, approximate SE = .19, approximate p = .013.


This study is based on a mixed-methods design with two measures for data collection. The first is the PTGI, a self-report instrument developed from standard psychometric techniques. Posttraumatic researchers use the PTGI to measure personal growth attributed to a trauma of interest to researchers. We use the PTGI as described by the instrument developers (Tedeschi & Calhoun, 1996) to measure total personal growth attributed to the sum of experiences during a time period of interest. Our second measure is an open table for obtaining participant attributions of cause for total personal growth. Participants complete the table with written descriptions of personal experiences and estimates of corresponding percentage contributions. The table design is adapted from one introduced in a previous study (Anderson & Lopez-Baez, 2011).

The purposes of the current study require a degree of veridicality (truthfulness), a form of internal validity. Researchers have reported little evidence of any kind for the validity of subscale scores beyond the results of exploratory factor analysis (see review in Anderson & Lopez-Baez, 2008). This is perhaps the reason why researchers have drawn few conclusions about growth from subscale scores in their results. Our comparisons one to three in the current study demonstrate the existence of predicted relationships among total PTGI scores of three samples and therefore a degree of internal validity for the collection of individual items and total PTGI scores. Comparison four demonstrates the existence of a predicted relationship between the attributions of cause from two studies and therefore a degree of internal validity for data obtained with the table-based approach. Comparison five demonstrates a degree of concurrent validity for both the subscale of Spiritual Change and the table-based approach.

Posttraumatic Growth Inventory as a Measure of Personal Growth
The PTGI was developed as a measure of posttraumatic growth. Tedeschi and Calhoun (2004) described their instrument as reflecting the core of personal growth. The results of the current study offer strong support for Tedeschi and Calhoun’s description because the results report high levels of personal growth for students without regard to prior experiences of trauma. We believe that if the PTGI can be used to measure the personal growth of samples of populations as dissimilar as college students and trauma survivors, then the PTGI can probably be used as a measure of personal growth under other circumstances in future studies.

College-Student Growth and Posttraumatic Growth
Magnitude. Theorists have identified the college-student undergraduate years as a time of personal growth in response to both academic and non-academic experiences (Chickering, 1969; Chickering & Reisser, 1993; Perry, 1970) in terms that suggest the definition of personal growth embodied in the items of the PTGI. Researchers have generally confirmed theorist predictions of student growth (c.f., Hassan, 2008; Higgins et al., 2009), but not with measures that allow for comparison of personal growth in response to trauma. Therefore, we are not surprised that the results of the current study reflect student growth. We are surprised, however, by the magnitude of that growth, m = 69.09 (SD = 11.52) because it is so near the maximum of the range reported in previous studies of posttraumatic growth (Linley & Joseph, 2004). We believe that this comparison helps readers appreciate the magnitude of growth described by each population.

Factor structure and subscales. The developers of the PTGI reported a 5-factor structure for the items of their instrument on the basis of an exploratory factor analysis (Tedeschi & Calhoun, 1996) and developed five corresponding subscales of unequal length. Subsequent posttraumatic studies have reported 2- and 3-factor structures (see review in Anderson & Lopez-Baez, 2008). Taken together, we interpret these EFA results as evidence that the factor structure of posttraumatic growth is not highly differentiated or stable across different samples. The results of several EFA described in our first study (Anderson & Lopez-Baez, 2008) demonstrated that the factor structure of a sample of student scores also lacked differentiation and stability, and therefore resembled that of posttraumatic growth.

Posttraumatic researchers have typically reported descriptive statistics for the total PTGI score and for the original five subscales. We report our results this way in Table 1, but also include recalculations on a per-item average basis (total score and subscale scores divided by number of corresponding items). The per-item format allows for comparisons of scores for subscales of unequal length. The reader can verify by inspection of Table 1 that all of our subscale scores round to 3.50 (to nearest .5 scale units) except the score for Spiritual Change, which rounds to 1.50. We have observed a similar pattern among the results of our previous studies (Anderson & Lopez-Baez, 2008, 2011).

During preparation of this manuscript, we conducted an informal visual comparison (not based on comparative statistics) of intra-sample per-item subscale scores listed in the results of posttraumatic studies cited by Linley and Joseph (2004) and observed that most subscale scores in each sample were of almost equal magnitude. Most of the few exceptions were low subscale scores (greater than 1.00 per-item average scale value) for Spiritual Change. We do not interpret our observation of this pattern as empirical evidence of anything; however, the observation makes us wonder about the empirical relationship between Spiritual Change and the other four subscales and highlights the importance of assessing the internal validity of Spiritual Change to lay the groundwork for any future studies of the internal structure of growth.

Spiritual Change and spiritual growth. Tedeschi and Calhoun (2004) described the PTGI subscales as measures of five domains of personal growth. The results of our comparison three (see results section) reflect a pattern among mean subscale scores in which the per-item mean score for the Spiritual Change subscale is relatively low. This pattern is empirical evidence that growth does not occur uniformly across all domains at the same time, at least for spiritual growth as measured by Spiritual Change. The occurrence of the similar pattern we observed in the samples of many studies invites the following attempt to explain the pattern. An explanation might be especially important to educators and administrators of religious colleges and universities who actively seek to promote spiritual growth of students.

Developmental factors are probably at least partly responsible for the larger Spiritual Change scores in posttraumatic studies. Trauma study participants have generally been older than participants in samples of college students. Perhaps older people like those in many of the trauma-study samples are more likely than college undergraduates to describe spiritual growth. Perhaps spiritual growth is more characteristic of growth in response to trauma than of growth in response to college life. However, these two possibilities do not completely account for the pattern of interest (similar per-item subscale scores for four subscales and lower subscale score for Spiritual Change) because the pattern is not as pronounced among the five per-item subscale means reported by Tedeschi and Calhoun (1996) for their non-trauma comparison group of college undergraduates. The results of our comparison five (see results section) suggest another developmental factor. Comparison five is based on the narrow definition of spiritual growth embodied in the 2-item Spiritual Change scale. Participant interpretations of item content necessarily influence patterns among subscale scores. In particular, differences in religious background could contribute to different interpretations of Spiritual Change items. We recruited our sample members 12 years after Tedeschi and Calhoun recruited theirs, and we recruited ours from a different university in a different part of the United States. Perhaps our sample members have different religious backgrounds than the members of Tedeschi and Calhoun’s sample.

Intentional facilitation of growth. Personal growth can occur in response to very different kinds of experiences, from coping with horrible trauma to caring deeply for friends and significant others. Most of these experiences, certainly most of the traumatic ones, seem to arise spontaneously. This conclusion is important to philosophers and developmental theorists because it suggests that personal growth is central to the human condition. Developmental theorists have suggested that personal growth also can occur in response to planned academic activities. This prediction is important to educators and others concerned with how to facilitate growth.

Students in the current study sample attributed 40% of their personal growth to academic activities (see Table 1). We interpret these results as strong support for the prediction of personal growth in response to academic activities. Students in the current study and in the sample of our second study (Anderson & Lopez-Baez, 2011) also attributed substantial growth to a single 3-hour course designed to facilitate personal growth. We interpret these results as support for the prediction that substantial levels of personal growth can be facilitated by specific academic activities designed to do so.

Current study results include attributions of cause for a single academic course designed in part to facilitate growth. The course is generally similar to that described by Hassan (2008) in a study of growth attributed to a health education course. The percentage attributions of cause to the course described in the current study (Table 2) are consistent with percentages reported in our previous study (Anderson & Lopez-Baez, 2011). The results of that preceding study and the study of Hassan (2008) strongly suggest that personal growth can be intentionally facilitated if not taught explicitly. The results of the current study suggest that substantial growth is attributed by students to coursework in general.

Current study results include subtotals of attributions of cause for academic and non-academic experiences, respectively. Sample members report attributions of almost 40% of total personal growth to academic coursework and provide further evidence that personal growth can be intentionally facilitated.

Study 2: Annual Growth

Taken as a whole, the results of Study 1 and three previous studies (Tedeschi & Calhoun, 1996; Anderson & Lopez-Baez, 2008, 2011) suggest that college students like those in the samples attribute substantial personal growth to both academic and non-academic experiences of their college years. These conclusions lead us to wonder just how much growth graduating seniors attribute to each college year. We believe the answer is of interest to college educators and administrators charged with fostering student growth. Answering this question requires a descriptive study of a representative sample drawn from a population of interest. Study 2 uses a simple descriptive design to answer the question for the population of students similar to those in the sample of Study 1.

Research Question

What levels of personal growth do members of a sample of college seniors attribute to each year of their 4-year college careers and what percentages do they attribute to academic and non-academic experiences, respectively?


Participants were recruited from graduating college seniors enrolled during the spring semesters of 2009 and 2010 in the course described in Study 1. Students earned extra course credit for participating. A total of 117 participants were recruited (70 of the 84 graduating seniors among the 142 students enrolled in the spring of 2009 and 47 of the 67 graduating seniors among the 144 students enrolled in the spring of 2010). A total of 108 participants (59 women and 49 men) remained after eliminating 9 questionnaires with missing data. Most participants were Caucasian (5 African American, 9 Hispanics, Asians, Asian Americans and other). Mean age was 21.64 (SD = .48) years. Academic concentrations (and number of students) were: college of arts and sciences (77), commerce school (18), college of engineering (12) and school of architecture (1). Participants completed the survey at the end of the last class meeting, approximately three weeks before graduation.

We used the PTGI to measure total personal growth. We used the table in Appendix B to elicit attributions of cause. Participants completed the table with annual estimates (in percent) of their personal growth, growth from academic experiences, and growth from non-academic experiences. We also asked participants to identify on a separate page (not shown in Appendix B) the experiences that they thought contributed most to their growth each year and to identify these experiences as either academic or non-academic.


The first two pages of the Study 1 and Study 2 questionnaires (warm-up exercise and PTGI) were identical. Study 2 participants followed the instructions in Appendix B to provide attributions of cause.


Subscale Cronbach alphas for our data are .85 (Relating to Others), .57 (New Possibilities), .59 (Personal Strength), .88 (Spiritual Change), and .77 (Appreciation of Life). The male mean PTGI score of 65.71 (SD = 12.27) is less than the female mean of 70.02 (SD = 11.50), but not significantly less, t (106) = 1.93, p = .056, α = .05 (2-tail). A single significant gender difference was found among subscale scores between the male mean RTO score, M = 21.27 (SD = 6.05) and the corresponding female mean, M = 24.46 (SD = 5.51), t (106) = 2.87, p = .005, α = .01 (Bonferroni-corrected 2-tail). Subsequent analyses of PTGI scores in the sample of the current study are based on the combined scores shown in Table 3.

No gender differences were suggested by the results of independent t-tests of corresponding male and female percentages of total, academic, or non-academic growth, respectively, for any college year, α = .0125 (Bonferroni-corrected 2-tail for each set of 4 analyses). Therefore, subsequent analyses of percentages of growth are based on the combined scores in Table 4.

Table 3 contains the descriptive statistics for the sample of Study 2. A visual comparison of the contents of Table 3 with those of Table 1 shows that all corresponding entries are approximately equal. Table 4 documents mean attributions of substantial levels of personal growth to both academic and non-academic experiences for each of four years. The mean attribution to non-academic experiences exceeds the mean attribution to academic experiences for every year. The greatest mean growth is attributed to the senior year; the least is attributed to the sophomore year.

Participants were asked to identify the year of occurrence of the single experience (as defined by participants) to which they attributed the most personal growth (question not shown in Appendix B). Year and corresponding frequencies of selection by participants are: freshman (22), sophomore (9), junior (35), and senior (42). Participants also were asked to identify whether the experience that contributed most to growth was academic or non-academic. Type of experience and frequencies of selection are: academic (27) and non-academic (81). Finally, participants were asked to describe (in words) the experience that contributed most to their growth. Illustrative descriptions include: “getting a job,” “finding a new girlfriend,” “death of a friend,” “learning to live with fraternity brothers,” and “finishing my undergraduate thesis.”


The current study is the fourth we have conducted based on the PTGI for measuring student personal growth and the third based on a table for collecting attributions of cause in the form of quantitative percentages and qualitative descriptions. We believe the results of the four studies support the utility of both measures for measuring growth and the flexibility of both for measuring growth under different circumstances.

College-Student Personal Growth
The mean PTGI score and standard deviation described by the 108 college seniors with a college career of exactly 8 semesters in the sample of Study 2, M = 68.01 (SD = 12.01) are almost identical to the corresponding statistics described by the 122 college students with a mean college career of 6.54 (SD = 1.34) semesters in the sample of Study 1, M = 69.09 (SD = 11.52). We had expected the mean PTGI score of Sample 2 to exceed that of Sample 1 because the results of our previous studies reflected higher mean scores for more college semesters (Anderson & Lopez-Baez, 2008, 2011; Study 1 of this paper). The simplest way to explain the similarity between the total scores of Study 1 and Study 2 is to remind ourselves that we are comparing data from a cohort as opposed to longitudinal studies, and remind ourselves that college student growth varies widely among students in each sample as illustrated by the large standard deviations for total PTGI scores in each of our studies. The results reflected in Table 4 suggest that the college seniors in our sample attributed substantial growth to both academic and non-academic experiences during all four college years. We believe this pattern is evidence that college faculty and staff can influence the personal growth of many students during every year of a student cohort’s progression toward graduation.
General Discussion

We believe Study 1 provides substantial information about the validity of total PTGI scores and also of subscale scores for Spiritual Change. For this reason, we believe the results of Study 1 are of interest to researchers using the PTGI to measure adversarial or personal growth. The high levels of personal growth attributed by students to the sum of their college years and attributions of cause to academic activities will probably interest college administrators and educators.

The same results led us to wonder how student growth and attributions of cause might be distributed over each college year. For this reason, Study 2 seemed a natural extension of Study 1. The descriptive results of Study 2 are among the first to reflect levels of growth attributed by graduating seniors in retrospect to each year of their undergraduate careers. We believe these results will also interest college personnel concerned with facilitating student growth.

We developed the table-based approach used in Studies 1 and 2 to measure attributions of cause. Researchers can adapt the approach for use in future studies of personal growth. We believe that researchers with other research interests can use a similar approach to study a wide variety of other variables.


The two studies described in the current paper are based on self-reports. Thus, the results of both are subject to the many potential validity threats associated with self-reports including additional threats to the historical validity of retrospective self-reports. Our research purposes require data with sufficient internal validity. Comparisons of the results of our three studies reflect a degree of internal validity as described in Study 1. However, PTGI scores might be associated with ceiling effects if higher levels of growth are attributed to longer time periods at diminishing rates, and percentage attributions might be associated with recency effects if more vivid recall of recent experiences leads to larger attributions of growth. Finally, because our samples are representative of populations of similar students, but not university students in general, our conclusions do not necessarily apply beyond the population represented by our samples.

Future Research

We plan more studies of college student growth with the long-term goal of learning how best to facilitate growth. We hope that readers can adapt our approach to measuring attributions of cause for use in future studies of personal growth and other variables.


Anderson, W. P., & Lopez-Baez, S. I. (2008). Measuring growth with the Posttraumatic Growth Inventory. Measurement and Evaluation in Counseling, 40, 215–227.
Anderson, W. P., & Lopez-Baez, S. I. (2011) Measuring personal growth attributed to a semester of college life using the Posttraumatic Growth Inventory. Journal of Counseling and Values, 56, 73–81.
Chickering, A. W. (1969). Education and identity. San Francisco, CA: Josey-Bass.
Chickering, A. W., & Reisser, L. (1993). Education and identity. San Francisco, CA: Josey-Bass.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37–46.
Hassan, K. L. (2008). Identifying indicators of student development in college. College Student Journal, 42, 517–530.
Higgins, J. W., Lauzon, L. L., Yew, A., Bratseth, C., & Worley, V. (2009). University students’ wellness—What difference can a course make? College Student Journal, 43, 766–777.
Joseph, S., Linley, P. A., & Harris, G. J. (2005). Understanding positive change following trauma and adversity: A structural clarification. Journal of Loss and Trauma, 10, 83–96.
Linley, P. A., & Joseph, S. (2004). Positive change following trauma and adversity: A review. Journal of Traumatic Stress, 17, 11–21.
Pascarella, E. T., & Terenzine, P. T. (1991). How college affects students: A third decade of research. San Francisco, CA: Jossey-Bass.
Perry, W. G. (1970). Forms of intellectual and ethical development in the college years: A scheme. New York, NY: Holt, Rinehart and Winston.
Tedeschi, R. G., & Calhoun, L. G. (1996). The Posttraumatic Growth Inventory: Measuring the positive legacy of trauma. Journal of Traumatic Stress, 9, 455–472.
Tedeschi, R. G., & Calhoun, L. (2004). Posttraumatic growth: Conceptual foundations and empirical evidence Psychological Inquiry, 15, 1–18.

W. P. Anderson, Jr., is an Adjunct Professor in the Counselor Education Department and Sandra I. Lopez-Baez, NCC, is an Associate Professor and Chair of Counselor Education Programs, both at the University of Virginia. Correspondence can be addressed to W. P. Anderson, Jr., University of Virginia, Counselor Education Department, Box 400270, Charlottesville, VA 22904,

Appendix A

Specific Experiences that Contributed to your Personal Growth

Consider the experiences (both academic and personal) that contributed most to your Personal Growth during your undergraduate years, whether or not the experiences were directly related to work for which you earned academic credit. Name and briefly describe the 3 academic experiences (besides PPA) that contributed most to your Personal Growth on lines 1–3 of Column 1 in Table 1 below. For purposes of this study, academic experiences are defined as those for which you earned academic credit. Note that PPA (including your project) is listed on line 4 for comparison purposes. Next, on lines 6–10, name and briefly describe the 4 non-experiences that contributed most to your Personal Growth.

Column 1 Column 2
Specific experiences Contribution (%)

Academic credit experiences that contributed most to your Personal Growth during your undergraduate years (i.e., classes, internships, practicums, etc.)

1. ________________________________________________ ______ %
2. ________________________________________________ ______ %
3. ________________________________________________ ______ %
4. PPA (including project) %
5. Misc. other academic experiences %

Subtotal: Personal Growth from academic experiences ______ %

Non-academic experiences (if any) that contributed most to Personal Growth during your undergraduate years (i.e., friends, relationships, gains, losses, etc.)

6. ________________________________________________ ______ %
7. ________________________________________________ ______ %
8. ________________________________________________ ______ %
9. ________________________________________________ ______ %
10. Misc. other non-academic experiences %

Subtotal: Personal Growth from academic experiences _____ %


Appendix B

History of Personal Growth during your College Undergraduate Years

Step I. Recall the beginning and ending dates of each of your undergraduate years including the current one. Fill in
dates in the blanks of the line below to describe each year.

Freshman year Sophomore Year Junior Year Senior Year

Dates __/__ – __/__ __/__ – __/__ __/__ – __/__ __/__ – __/__
Mo Yr Mo Yr Mo Yr Mo Yr Mo Yr Mo Yr Mo Yr Mo Yr

Step II. Consider the total Personal Growth you have experienced during your undergraduate years. Estimate the
percent of that total experienced during each year including the current year and place your estimate in the
corresponding blank of the following line. Make sure that the total of your entries on the following line =

% of total ______ % + ______ % + ______ % + _____ % = 100 %
1a 2a 3a 4a

Step III. For each year above consider what percent of your Personal Growth that year resulted from academic
experiences (experiences for which you earned academic credit) and how much from non-academic (all other)
experiences. Fill in the corresponding percentages in the two lines below. Make sure that your academic and
non-academic growth for each year (column entries) equal the entry for the corresponding year in Step II
(above). That is, make sure: 1b + 1c = 1a, 2b + 2c = 2a, . . . .

Growth in response to academic experiences

______% ______% ______% ______%
1b 2b 3b 4b

Growth in response to non-academic experiences

______% ______% ______% ______%
1c 2c 3c 4c

Class Meeting Schedules in Relation to Students’ Grades and Evaluations of Teaching

Robert C. Reardon, Stephen J. Leierer, Donghyuck Lee

A six-year retrospective study of a university career course evaluated the effect of four different class schedule formats on students’ earned grades, expected grades and evaluations of teaching. Some formats exhibited significant differences in earned and expected grades, but significant differences were not observed in student evaluations of instruction. Career services providers, including curriculum designers, administrators and instructors, will find the results of this study helpful in the delivery of services, especially with high-risk freshman students.

Keywords: career, teaching, course, instruction, evaluation, grades

While individual counseling has been shown to be effective in helping students develop career decision-making skills (Brown & Ryan Krane, 2000; Reese & Miller, 2006; Whiston & Oliver, 2005; Whiston, Sexton, & Lasoff, 1998), undergraduate career courses also can be effective interventions (Folsom & Reardon, 2003; Reardon, Folsom, Lee, & Clark, 2011; Whiston et al., 1998).

Although college career courses have been shown to offer substantial benefits (Brown & Ryan Krane, 2000; Osborn, Howard, & Leierer, 2007; Reed, Reardon, Lenz, & Leierer, 2001; Reese & Miller, 2006; Whiston & Oliver, 2005; Whiston et al., 1998), the content and format of such courses vary greatly (Folsom & Reardon, 2003). The present study sought to focus on one aspect of such career course variability: alternative class schedule formats.

Effective career classes can be characterized by these features: (a) structured course approaches appear to be more effective than unstructured approaches (Smith, 1981); (b) individual career exploration should be a cornerstone of the course (Blustein, 1989); and (c) five components (written exercises, individualized interpretations and feedback, in-session occupational exploration, modeling, and building support for choices within one’s social network) (Brown & Ryan Krane, 2000; Brown et al., 2003).

What is the effect that class schedule might have on course effectiveness? Only one study (Vernick, Reardon, & Sampson, 2004) has examined this issue, and the results showed that such courses should be designed to meet more than once a week and avoid over-exposure to materials and activities so as not to overwhelm the student. Extending this concept, we hypothesized that certain course schedule formats (weekly meeting frequency and term length) could make a difference in student learning and evaluation of teaching.

Alternative Career Class Schedules

This study focused on a course based on cognitive information processing theory incorporated into the course textbook, Career Planning and Development: A Comprehensive Approach (Reardon, Lenz, Sampson, & Peterson, 2000). All sections of the course followed a prescribed curriculum comprising a mixture of lectures, panel presentations, small and large group instructional activities, personal research, and field work; however, the classes differed in terms of the class meeting schedule (class duration, number of weekly meetings, and number of weeks a class met during an academic term).

We examined 57 course sections that met over a six-year period and were team-taught by lead instructors and co-instructors with an instructor/student ratio of about 1:8. Lead instructors included both professional staff and faculty who supervised the co-instructors. During the time of this study, four class schedule formats were used. In the case of a 16-week semester, the class met once per week for 3 hours; twice per week for 1.5 hours; or three times weekly for 1 hour. A fourth schedule option was for a 6-week term with the class meeting four times weekly for about 8 hours per week. In the 16-week semester, the class met once per week for 3 hours on Wednesdays (W); twice per week for 1.5 hours on either Monday/Wednesday or Tuesday/Thursday (MW/TuTh); or three times weekly for 1 hour on Monday, Wednesday, and Friday (MWF). A fourth schedule option was for a 6-week term where the class met four times weekly for about 8 hours per week on Monday, Tuesday, Wednesday, and Thursday (MTuWTh). In summary, we sought to evaluate the influence of these four class schedule formats upon the educational experience of the students as measured by expected grades, earned grades, and student evaluations of teaching.

Course Measures

The following section gives details about the three measures of student learning and perceptions of teaching used in this study.

Earned Grade (EG)
Although a student’s grade point average has limitations as a measure of academic achievement, class grades are nevertheless a widely accepted method of quantifying students’ level of educational achievement and future success in graduate school or employment (Plant, Ericsson, Hill, & Asberg, 2005). Specific to career development, Reardon, Leierer, and Lee (2007) showed that grades might be useful measures of career course interventions, “especially if the treatment variables are carefully described and the grading procedures are fully explained and replicable by other researchers” (p. 495). For this study, we assumed that a student’s final EG would accurately reflect learning in the course.

Expected Grade (XG)
Grade expectations are a complex phenomenon that combines realistic data-driven grade expectations with unjustified optimism or wishful thinking (Svanum & Bigatti, 2006). The XG reflects the student’s assessment of course demands and optimism about successfully meeting those demands. This grade prediction may be informed or uninformed; however, after completing multiple assignments over the course of the semester, Svanum and Bigatti (2006) noted that students lower the value of their XG such that it will be only moderately inflated and will reliably predict their final EG. Because students in our course had the course grading scale in the syllabus, a signed performance contract, and predicted their grades during the last week of the semester when 85% of their grade had already been accounted for, we hypothesized that in aggregate their predictions would be only moderately inflated and thus a reliable predictor of their earned grades and success in the course. We felt this grade variable was important as a measure of students’ confidence in their mastery of the career development subject matter and the problem-solving skills taught in the course, and therefore a valid measure of the relative effectiveness of different class schedule formats.

In addition, comparing EG and XG informs us about students’ self-evaluation of learning and their actual performance in the course. When there is not a significant difference between the two scores, we might suppose that students have a fairly accurate understanding of their performance on completed assignments and those still to be graded. By contrast, a significant difference between XG and EG indicates a discrepancy between students’ self-evaluations of graded and as-yet-ungraded assignments and the official final grades. If XG is significantly higher than EG in a section, one may conclude that the academic work has been undervalued by the instructor or overvalued by the students. Conversely, if XG is significantly lower than EG, one might conclude that students’ estimates were conservative or instructors recognized a level of performance not seen by the students.

Student Evaluation of Teaching (SET)
Student evaluation of classes and teaching effectiveness is standard practice at most postsecondary institutions. There is substantial anecdotal and experimental evidence supporting the usefulness of SETs (Centra, 1993; Marsh & Dunkin, 1992; Marsh & Roche, 1997). Certain student ratings forms provide important feedback that can be used to improve teaching performance (Greenwald & Gillmore, 1997; Marsh & Roche, 1997; McKeachie, 1997), and when asked most faculty members support the use of SETs as a tool for teaching improvement (Baxter, 1991; Griffin, 1999; Schmelkin, Spencer, & Gellman, 1997). Although SET is not without its critics, it appears to be a pragmatic way to access and compare student perceptions of teachers’ effectiveness and therefore a potential measure of the relative efficacy of different class schedules.

In an effort to better evaluate students’ course experiences, the influence of EG (Goldman, 1985) and XG (Greenwald & Gillmore, 1997) on SET is receiving considerable attention in the literature. The present study provided an opportunity to examine the relationship of SET to both EG and XG relative to four different class schedule formats.

Research Questions
In seeking to discover if particular class schedules were more effective in a team-taught career course, we evaluated grades and participant feedback from undergraduate students. The goal was to determine if any of the four differing class schedules produced significant differences in the course evaluation measures EG, XG, and SET. Although we were examining these measures from the students’ perspective and such measures are typically scored at the individual student level, we chose to examine class section level scores because XG and SET data were only available to us in this way.

The first group of research questions examined differences between mean evaluative measures, aggregated by class format and averaged for classes that met one (W), two (MW/TuTh), or three times per week (MWF) for 16 weeks, or four times per week (MTuWTh) for 6 weeks.

Research Question 1: Were there any significant differences in the career course evaluation measures among the four class formats?
RQ 1.1: Are there differences in mean EG between formats?
RQ 1.2: Are there differences in mean XG between formats?
RQ 1.3: Are there differences in mean SET between formats?

The second group of research questions explored the differences between the evaluation measures (EG, XG, and SET) within the sections.

Research Question 2: Within any given format, are there significant differences between the mean of the aggregated class evaluation measures?
RQ 2.1: Is the mean XG significantly different than the mean EG?
RQ 2.2: Is the mean XG significantly different than the mean SET?
RQ 2.3: Is the mean EG significantly different than the mean SET?


Over a 6-year period, 1,479 students were enrolled in 57 sections of a career course to fulfill elective requirements for the baccalaureate degree. The class met in a standard classroom in academic buildings on the campus. Although the class was offered for variable credit, over 95% of the students took it for 3 credit hours. The number of students per section ranged from 19–34 with a mean of 26.5.

Ethnic diversity was generally proportional to the general student population of the university: Caucasian, 74%; African American, 12%; Hispanic American, 7%; Other, 4%; Asian, 3%; and American Indian, .4%. The course typically enrolled about 60% females and 40% males, including freshmen (15%), sophomores (45%), juniors (20%), and seniors (20%). Depending on the semester, between 15% and 25% of the course was composed of students with officially undeclared majors, and the large percentage of sophomores was the result of academic advisors referring these undeclared students to the class. While almost 40% of the members in a typical class reported satisfaction with their present career situation, about 60% were unsure, dissatisfied, or undecided.

Course Grading Procedures
Student grades were computed using scores earned on assignments contained in the performance contract. This contract was comprised of 28 different graded activities spread across the three units of the course. Given the use of the performance contract, students in this course should have had a very good idea of what their final grade would be when they filled out the SET and estimated their grade, because only two of the 28 activities accounting for 125 of 653 total points were still ungraded at that point.

Student Evaluation of Teaching Ratings
We used a standardized instrument for SETs, the Student Instructional Rating System (SIRS; Arreola, 1973), a student course on form developed at Michigan State University (Davis, 1969) and adapted for use at our university. SIRS provided an opportunity for instructors to obtain reactions to their instructional effectiveness and course organization and to compare these results to those of similar courses offered within the university.

The SIRS consisted of 32 items and 25 of these items enabled students to express their degree of satisfaction with the quality of instruction provided in the course by using a 5-point Likert scale. For example, the course was well organized could be marked strongly agree, agree, neutral, disagree, or strongly disagree. One item on the SIRS was of special interest in this study: What grade do you expect to receive in this course? A, B, C, D, or F.

We also employed a second instructional rating instrument, the State University System Student Assessment of Instruction (SUSSAI) which had been used at the university for five years prior to this study. This instrument consisted of eight items focused on class and instructor evaluation. One item was of special interest in this study: Overall assessment of instructor: Excellent=4, Very Good=3, Good=2, Fair=1, Poor=0.

Data Collection
After obtaining permission from the university institutional review board, we received the archived career course grade data for a six-year period. We aggregated the grades of these 1,479 students by class schedule and averaged the results to achieve a mean EG for each class schedule format.

The data relating to students’ perceptions of what they had achieved and the quality of instruction they had received was collected as follows: On the last week of class, while filling out their teacher evaluations, all students in a section were asked to indicate the grade they expected to receive and the results were tallied and averaged to determine a class mean XG. These class averages of 57 sections were forwarded to the researchers, and the results were tallied and averaged to find the mean XG for each class schedule format. In addition, we retrieved overall class ratings of instructors for an ad hoc sample of career classes over the 6-year period. These data enabled us to examine the relationships between mean EG and XG, EG and SET, and XG and SET.


In this team-taught course where all instructors were involved in making large- and small-group presentations, each co-instructor had primary responsibility for evaluating the progress of students in his or her small group and assigning a grade, while the lead instructor of the team had overall responsibility for course presentations and management. In completing the SIRS and SUSSAI items for the SET, students were asked to provide a composite rating of the instructional team for their section. SETs were completed anonymously during the final two class meetings while instructors were out of the room and then returned by a student proctor to the university’s office of evaluation services.

Data Analysis
We examined how different class formats influenced mean EG, XG, and SET. The independent variable of class schedule format had four levels. The first three levels met over the course of a 16-week fall or spring semester for either 3 hours once a week (W), 1.5 hours twice a week (MW/TuTh), or 1 hour three times a week (MWF). The final level met for 2 hours four times a week over the course of a 6-week semester (MTuWTh). Because the assumptions related to independence for the three evaluative measures could not be met (i.e., the evaluations for each class section were correlated), we analyzed the data using a split-plot design.


As is the case for other ANOVA and MANOVA tests, the dependent variables were assumed to be normally distributed. We tested the dependent variables to determine if they were normally distributed by computing skewness and kurtosis of each of the dependent variables to see if they fell between −1.0 and +1.0. Both the SET and EG scores did not violate the assumptions of normality as measured by skewness and kurtosis. However, while the skewness of XG did fall within the appropriate range, the kurtosis score was 1.04. Although this score is above 1.00, we believe this minor violation does not seriously affect the results and their interpretation.

Research Question 1
Using the split-plot MANOVA, we found a significant interaction of the three evaluative measures across the four class formats F (6, 106) = 4.47, p < .0005, η2 = .20. Specifically, there was a significant difference in EG between the four course formats, F (3, 53) = 19.15, p < .0005, partial η2 = .52. The EG for schedule MTuWTh (M = 3.50) was significantly higher (p < .005) than that of formats W, MW/TuTh, and MWF (M = 3.25, 3.32, and 3.31, respectively). Next, there was a significant difference in XG between the four course formats, F (3, 53) = 3.62, p = .019, η2 = .02. The means for XG for the W, MW/TuTh, MWF, and MTuWTh were 3.71, 3.57, 3.34, and 3.64, respectively. There was not a significant difference for XG between formats W, MW/TuTh, and MTuWTh. However, there was a significant difference between format MWF and format MTuWTh (p = .036), and format MWF was trending lower when compared with format W (p = .097) and format MW/TuTh (p = .051). Finally, there was not a significant difference on SET scores across the four formats, F(3, 53) = 1.36, p = ns. The mean SET scores for formats W, MW/TuTh, MWF, and MTuWTh were 2.88, 3.15, 3.31, and 3.11, respectively.

Research Question 2
When we compared evaluation measures within each format, we found significant differences with each one, F (2, 52) = 23.61, p < .0005, η2 = .47. We found XG significantly greater than EG within schedule format W (.46, p = .002) and format MW/TuTh (.35, p < .0005). By contrast, the difference between XG and EG was smaller and not statistically significant within format MWF (.13, p = ns) and format MTuWTh (.13, p = ns). This lack of a significant difference between EG and XG indicates that these students earned grades very similar to the grades they expected to receive. It is apparent that the students and instructors used similar evaluation and grading methods. Stated another way, this finding suggests that students in classes meeting more frequently per week have a slightly more accurate perception of how they are doing in the class.

We also found that mean XG was significantly greater than mean SET for format W (.83, p =.003), format MW/TuTh (.42, p < .0005), and format MTuWTh (.53, p < .0005). However, there was not a significant difference between XG and SET for format MWF (.13, p = ns). Finally, in comparing the difference between mean EG and mean SET within each of the four formats, we found a significantly higher EG only for format MTuWTh (.40, p < .0005). No significant differences were observed for formats W, MW/TuTh, and MWF, which had differences of .37, .07, and .13, respectively.

In summary, we found significant differences in the evaluation measures of XG, EG, and SET across the four different career course formats. Class sections which met four times a week for 6 weeks had a significantly higher EG than classes meeting one, two, or three times a week for a 16-week semester. Interestingly, formats W, MW/TuTh, and MTuWTh all had mean XG scores over 3.55, while format MWF’s XG was not only lower than the other formats, but significantly lower than that of format MTuWTh. Finally, mean SET scores were not significantly different from one another. Notably, they were all well above the rating of “good” (good = 2.0), with a mean of 3.15 on a 4-point scale. Means for the sections ranged between 2.88 and 3.31; thus we concluded that students found the instruction to be very good or excellent.


Career course interventions have been developed to help students improve their academic and career decision-making skills. Comprehensive career courses offered for academic credit represent a cost-effective intervention that could be described as a “mega-dose” of career services (Reardon et al., 2011). While the benefits of college career courses are clear, it is unclear what contributions specific class formats (differing by length of class period, number of classes per week, length of course in weeks) might make to their effectiveness. Thus, the purpose of our study was to analyze the influence of different schedule formats on earned and expected grades and students’ evaluation of their instructors.

Previous studies on career development classes have described various limitations (see Gold, Kivlighan, Kerr, & Kramer, 1993; Reese & Miller, 2010), and we attempted to address these in the following ways. First, although we did not directly address random selection and random assignment issues, we aggregated class section scores instead of individual student scores, thus reducing the effect of individual outliers. By using the aggregate mean for each career planning section, individual students’ evaluation of the teacher remained anonymous yet the evaluation of the course section remained intact. The second limitation described by other researchers is the small number of participants in the career class analyzed. Over a six-year period we were able to collect data from almost 1,500 students from 57 sections of the course. The third limitation we attempted to address was the lack of equal representation of different ethnic groups. While we did not have equal percentages of students from different ethnicities, the demographic composition of our sample closely matched the composition of our university.

Perhaps the greatest strength of this study’s design was the replication of the intervention. That is, because the course structure and specific assignments were very similar for all sections, in effect the replication of the career course occurred across all 57 of the course sections analyzed. In each section, the course content and procedures were clearly specified and grades were based on the successful execution of a performance contract by the student.

Earned and Expected Grades
We examined how schedule influenced mean earned grade (EG) and expected grade (XG) scores. Like Vernick et al. (2004), we found that sections meeting only once per week over 16 weeks (format W) had the lowest EG, though not significantly lower than formats MW/TuTh and MWF. By contrast, schedule MTuWTh had a significantly higher EG than all the other formats, suggesting that a 6-week semester of 2-hour class meetings four times a week was more conducive to learning than a 16-week semester of classes meeting one, two, or three times per week for 3 hours, 1.5 hours, or 1 hour, respectively; that is, the “mega-dose” of career development interventions given in the course were intensified with MTuWTh.

Further analysis of the difference between mean section EG and XG scores enables us to compare the students’ view of their performance in the course with their actual performance. Ideally, we would prefer that there not be a significant difference between XG and EG in order to increase students’ confidence about the fairness of the grading and their sense of having mastered the material in the course. Expanding on these points, when the section mean XG was significantly higher than the mean EG, students could have left the course with a sense of failure and disappointment. Interestingly, in this study schedules W and MW/TuTh had significantly higher mean XG than mean EG, indicating an incongruity between the expected and earned grades. By contrast, for both schedules MWF and MTWF, the difference between mean XG and mean EG was not significant. One might conclude that fewer course meetings per week increased the difference between XG and EG scores.

Student Evaluation of Teaching
With regard to SET, there were no significant differences between the four class schedule formats, although we had suspected this might be the case. Perhaps a significant difference between section means for SET and XG would describe an incongruity between the students’ estimate of instruction quality and their evaluation of their own performance in the course. If XG were significantly higher than SET, this finding might indicate that students in these sections believed their performance was more related to their abilities and efforts rather than course instruction. By contrast, sections with significantly lower XG than SET scores may have rated instructors’ presentation of material higher than their own performance in the course. Interestingly, for schedules W, MW/TuTh, and MTuWTh, XG was significantly higher than SET, suggesting that students evaluated themselves more favorably than they did their instructors. We found it curious that for schedule MWF alone, XG was not significantly higher than SET.

Finally, EG is assigned to the student by the instructor, while SET is assigned to the instructor by the student. By comparing mean EG with SET, we can examine the relationship between an instructor’s evaluation of his or her students with students’ evaluation of the instructor. When EG is greater than SET, this means that instructors evaluated their students more favorably than they themselves were evaluated; conversely, when SET is greater than EG, students evaluated instructors more favorably than they themselves were evaluated. For schedules W, MW/TuTh, and MWF, there were no significant differences between mean EG and SET scores. However, for MTuWTh, in which students achieved a significantly higher mean EG than the other formats, the EG also was significantly higher than the SET, suggesting that this high-performing group had higher expectations for their instructors than they felt the instructors met.


Because this study is field research, there are a few limitations to discuss. First, participants were undergraduates taking a career planning course from one university. The advantage to using this approach was consistency of teaching content, training and quality control of teaching personnel, administration of tests, and assignments, thus reducing the possibility that course differences were responsible for random error variance. But, because these results come from only one university’s career course, caution should be exercised when generalizing them to other courses.

Second, participants were not randomly selected. In fact, random assignment was impossible given the students’ autonomy in selecting this course. Random selection is seldom an option in field research at an educational institution, but this fact does restrict the robustness and generalizability of results to other populations (Babbie, 2001).

Third, participants in the study may have been experiencing more career-related difficulties than other students who did not elect to take the course. It is to be expected that participants perceived a career course as more important to their progress than nonparticipants, which limits generalizability of these findings (Smith & Glass, 1987).

Fourth, because the data were collected over a six-year period, it is difficult to determine the effect of historical events on the behavior and attitudes of participants (Smith & Glass, 1987; Van Dalen, 1979). For example, students from the initial semester of the study took the class at the height of the tech bubble, while others took the class in the shadows of the 9-11 tragedy. Although we were not able to control for these events, we acknowledge that researchers and practitioners must be aware of the influence of external events upon any college course.


There are several implications regarding the findings of this study. The significant differences found between schedule formats in the outcomes of EG and XG serve to remind instructors, those who supervise them, and those managing career courses about the potential impact of this variable. For example, these findings indicate that classes meeting one time per week for three hours are not characterized by higher earned grades, and by implication this means student learning. Additional studies should isolate and evaluate format variables such as length of the entire course, number of classes per week, and length of individual classes so that those evaluating teachers might consider this in their evaluations. At the same time, the absence of any differences in student evaluations of teaching across the four schedule formats is reassuring for those teaching and supervising instructors, at least in a course that was as highly structured and standardized as the one in this study.

Career services providers, curriculum designers, administrators, and instructors may wish to consider these findings when making decisions about the design and delivery of career courses, especially for high-risk freshmen (Osborn et al., 2007). Students meeting for four classes a week over a 6-week semester earned and expected significantly higher grades overall than students meeting over a 16-week semester. Taking the 6-week intensive course during the summer term before beginning the freshman year could both increase students’ chances of academic success and their confidence in navigating the college experience.


Arreola, R. A. (1973). A cross-institutional factor structure replication of the Michigan State University SIRS faculty evaluation model. College Student Journal, 7, 38–42.
Babbie, E. (2001). The practice of social research. Belmont, CA: Wadsworth/Thomson Learning.
Baxter, E. P. (1991). The TEVAL experience, 1983–88: The impact of a student evaluation of teaching scheme on university teachers. Studies in Higher Education, 16, 151–179.
Blustein, D. L. (1989). The role of career exploration in the career decision making of college students. Journal of College Student Development, 30, 111–117.
Brown, S. D., & Ryan Krane, N. E. (2000). Four (or five) sessions and a cloud of dust: Old assumptions and new observations about career counseling. In S. D. Brown & R. W. Lent (Eds.), Handbook of counseling psychology (3rd ed., pp. 740–766). New York, NY: John Wiley & Sons.
Brown, S. D., Ryan Krane, N. E., Brecheisen, J., Castelino, P., Budisin, I., Miller, M., & Edens, L. (2003). Critical ingredients of career choice interventions: More analyses and new hypotheses. Journal of Vocational Behavior, 62, 411–428.
Centra, J. A. (1993). Reflective faculty evaluation: Enhancing teaching and determining faculty effectiveness. San Francisco, CA: Jossey-Bass.
Davis, R. H. (1969). Student Instructional Rating System (SIRS) Technical Bulletin. East Lansing, MI: Michigan State University, Office of Evaluation Services.
Folsom, B., & Reardon, R. (2003). College career courses: Design and accountability. Journal of Career Assessment, 11, 421–450.
Gold, P. B., Kivlighan, D. M. Jr., Kerr, A. E., & Kramer, L. A. (1993).The structure of students’ perceptions of impactful, helpful events in career exploration classes. Journal of Career Assessment, 1, 145–161.
Goldman, L. (1985). The betrayal of gatekeepers: Grade inflation. Journal of General Education, 37, 97–121.
Greenwald, A. G., & Gillmore, G. M. (1997). Grading leniency is a removable contaminant of student ratings. American Psychologist, 52, 1209–1217.
Griffin, B. W. (1999). Results of the faculty survey on student ratings of instruction: Preliminary report. Statesboro, GA: Georgia Southern University, Student Ratings Committee.
Marsh, H. W., & Dunkin, M. (1992). Students’ evaluations of university teaching: A multidimensional perspective. In J. C. Smart (Ed.), Higher education: Handbook on theory and research (Vol. 8, pp. 143–234). New York, NY: Agathon Press.
Marsh, H. W., & Roche, L. A. (1997). Making students’ evaluations of teaching effectiveness effective: The critical issues of validity, bias, and utility. American Psychologist, 52, 1187–1197.
McKeachie, W. J. (1997). Student ratings: The validity of use. American Psychologist, 52, 1218–1225.
Osborn, D. S., Howard, D. K., & Leierer, S. J. (2007).The effect of a career development course on the dysfunctional career thoughts of racially and ethnically diverse college freshmen. Career Development Quarterly, 55, 365–377.
Plant, E. A., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why study time does not predict grade point average across college students: Implications of deliberate practice for academic performance. Contemporary Educational Psychology 30, 96–116. doi:10.1016/j.cedpsych.2004.06.001
Reardon, R. C., Folsom, B., Lee, D., & Clark, J. (2011). The effects of college career courses on learner outputs & outcomes: Technical report No. 531. Tallahassee, FL: Center for the Study of Technology in Counseling and Career Development, Florida State University. Retrieved from
Reardon, R. C., Leierer, S. J., & Lee, D. (2007). Charting grades over 26 years to evaluate a career course. Journal of Career Assessment, 15, 483–498. doi:10.1177/1069072707305767.
Reardon, R. C., Lenz, J. G., Sampson, J. P., Jr., & Peterson, G. W. (2000). Career development and planning: A comprehensive approach. Pacific Grove, CA: Wadsworth-Brooks/Cole.
Reed, C., Reardon, R., Lenz, J., & Leierer, S. (2001). Reducing negative career thoughts with a career course. Career Development Quarterly, 50, 158–167.
Reese, R. J., & Miller, C. D. (2006). Effects of a university career development course on career decision-making self-efficacy. Journal of Career Assessment, 14, 252–26.
Reese, R. J., & Miller, C. D. (2010). Using outcome to improve a career development course: Closing the scientist-practitioner gap. Journal of Career Assessment, 18, 207–219.
Schmelkin, L. P., Spencer, K. J., & Gellman, E. S. (1997). Faculty perspectives on course and teacher evaluations. Research in Higher Education, 38, 575–592.
Smith, G. E. (1981). The effectiveness of a career guidance class: An organizational comparison. Journal of College Student Personnel, 22, 120–124.
Smith, M. L., & Glass, G. (1987). Research and evaluation in education and the social sciences. Englewood Cliffs, NJ: Prentice-Hall.
Svanum, S., & Bigatti, S. (2006). Grade expectations: Informed or uninformed optimism, or both? Teaching of Psychology, 33, 14–18.
Van Dalen, D. (1979). Understanding educational research: An introduction. New York, NY: McGraw-Hill.
Vernick, S. H., Reardon, R. C., & Sampson, J. P. Jr. (2004). Process evaluation of a career course: A replication and extension. Journal of Career Development, 30, 201–213.
Whiston, S. C., Sexton, T. L., & Lasoff, D. L. (1998). Career-intervention outcome: A replication and extension of Oliver and Spokane. Journal of Counseling Psychology, 45, 150–165.
Whiston, S. C., & Oliver, L. W. (2005). Career counseling process and outcome. In W. B. Walsh & M. Savickas (Eds.), Handbook of vocational psychology (3rd ed., pp. 155–194). Hillsdale, NJ: Erlbaum.

Robert C. Reardon, NCC, NCCC, is Professor Emeritus at the Career Center at Florida State University. Stephen J. Leierer is an Associate Professor at East Carolina University. Donghyuck Lee is an Assistant Professor at Konkuk University in Seoul, Korea. Correspondence can be addressed to Robert C. Reardon, Career Center, Florida State University, 100 S. Woodward St., Tallahassee, FL 32306-4162,

Wellness in Mental Health Agencies

Jonathan H. Ohrt, Laura K. Cunningham

Burnout and impairment among professional counselors are serious concerns. Additionally, counselors’ work environments may influence their levels of wellness, impairment and burnout. This phenomenological study included the perspectives of 10 professional counselors who responded to questions about how their work environments influence their sense of wellness. Five themes emerged: (a) agency resources, (b) time management, (c) occupational hazards, (d) agency culture, and (e) individual differences. Implications for professional counselors and future research are discussed.

Keywords: professional counselors, agencies, wellness, burnout, impairment

Wellness promotion focuses on individual strengths and emphasizes holistic growth and development. For example, Myers, Sweeney and Witmer (2000) defined wellness as:

A way of life oriented towards optimal health and well-being in which body, mind, and spirit are integrated by the individual to live life more fully within the human and natural community. Ideally, it is the optimum state of health and well-being that each individual is capable of achieving. (p. 252)

The authors’ definition of wellness alludes to one’s overall well-being. Counselors often advocate holism, exploration of self and self-actualization for their clients (Cain, 2001). Such aspirations may be achieved through a holistic wellness approach (i.e., attending to intellectual, emotional, physical, occupational and spiritual well-being; Witmer & Young, 1996). Therefore, counselors view wellness as an important aspect of overall human functioning. Although this fundamental view has historically been applied to clients, professional counselors themselves now recognize that they also may benefit from a wellness focus (Maslach, 2003).

Professional counseling organizations (e.g., American Counseling Association [ACA]; American Mental Health Counselors Association [AMHCA]; National Board for Certified Counselors [NBCC]) specifically emphasize the importance of counselor wellness and impairment prevention. For example, counselors are ethically required to recognize when they are impaired. The ACA (2005) ethical standards state that “Counselors are alert to the signs of impairment from their own physical, mental, or emotional problems and refrain from offering or providing professional services when such impairment is likely to harm a client or others” (Standard C.2.g). The AMHCA (2010) ethical standards further state that counselors:

recognize that their effectiveness is dependent on their own mental and physical health. Should their involvement in any activity, or any mental, emotional, or physical health problem, compromise sound professional judgment and competency, they seek capable professional assistance to determine whether to limit, suspend, or terminate services to their clients. (Standard C.1.h)

Furthermore, the NBCC (2005) ethical standards indicate that certified counselors discontinue providing services “if the mental or physical condition of the certified counselor renders it unlikely that a professional relationship will be maintained” (Standard A.15).

The Governing Council of the ACA states that “Therapeutic impairment occurs when there is a significant negative impact on a counselor’s professional functioning which compromises client care or poses the potential for harm to the client” (Lawson & Venart, 2005, p. 3). In 2003, this council became proactive in addressing the issue of counselor wellness by creating a task force on counselor wellness and impairment. The task force seeks to educate counselors about impairment prevention, promote resources for prevention and treatment of impaired counselors and to advocate within ACA and its division to address the broader issue of counselor impairment. As a result, they have distributed information on risk factors, assessment, resources and wellness strategies. Thus, a wellness focus is essential for professional counselors to prevent impairment and provide effective counseling services to clients (Witmer & Young, 1996).

Unfortunately, professional counselors encounter multiple factors that threaten their wellness (Lawson, 2007). For instance, counselors are at a particularly high risk for burnout due to the intense and psychologically close work they do with clients (Skovholt, 2001). Although there are many definitions of burnout, Pines and Maslach (1978) described it as “a condition of physical and emotional exhaustion, involving the development of a negative self-concept, negative job attitude, and loss of concern and feelings for clients” (p. 233). Additional consequences of burnout may include low energy and fatigue, cynicism towards clients, feelings of hopelessness and being late or absent from work (Lambie, 2006). When counselors fail to address burnout it can lead to impairment. Counselors also may experience occupational hazards such as compassion or empathy fatigue and vicarious traumatization (Figley, 2002; Lawson, 2007; Stebniki, 2007). Stebniki (2007) defined empathy fatigue as a state wherein counselors are exhausted by their duties because of their constant exposure to the suffering of others, which induces feelings of hopelessness and despair. Similarly, vicarious traumatization occurs when a counselor becomes emotionally impaired due to being exposed to an accumulation of traumatic stories from multiple therapy sessions (McCann & Perlman, 1990). Therefore, the actual nature of counselors’ work is a potential threat to their ability to be well.

In addition, environmental factors in counselors’ work settings also may be detrimental to their wellness (Ducharme, Knudsen, & Roman, 2008; Knudsen, Ducharme, & Roman, 2006; Vredenburgh, Carlozzi, & Stein, 1999). In a survey that included 501 professional counselors, Lawson (2007) found that those working in community agencies experienced higher levels of burnout and compassion fatigue and vicarious traumatization than those working in private practice. Agency variables that are associated with burnout include: work overload, low remuneration, lack of control over services, unsupportive or unhealthy work peers and ineffective or punitive supervisors (Lloyd, King, & Chenoweth, 2002). For example, low remuneration is a specific concern in many Southeastern states. Lambie and Young (2007) offered the following example of a work environment in a specific agency: “an employee assistance program in this area requires its counselors to conduct sessions for 35 clients a week…the counselor in such an organization faces stresses and work hours similar to a first year lawyer in a large firm, without the mitigating effects of financial compensation” (p.101). Additional stressors stem from nonprofit agencies’ dependence on government and state funding sources to operate. Agency compliance with government and state policies to maintain funding often require administrations to focus on the “bottom line,” sometimes to the detriment of client services and employee wellness (Rupert & Morgan, 2005). Counselors who experience such stressors are at serious risk for burnout. Nevertheless, counselors are ethically expected to avoid burnout because it ultimately reduces the quality of services provided to clients, compromises client care and creates potential for harm to the clients (Lawson & Venart, 2005).

Leaders in the counseling profession strongly encourage counselors to be proactive in maintaining their own wellness and self-care. Counselors need to “fill the well” of their own sense of well-being continually, so they can “pour it out” for their clients (Shapiro, Brown, & Biegel, 2007). For example, Lawson (2007) reported that counselors who endorsed 15 highly valued career sustaining behaviors scored higher on compassion satisfaction and lower on burnout. However, despite individuals’ efforts to maintain a wellness lifestyle, the work environment may have a significant role in impeding or supporting wellness efforts. If the work environment does not allow for rejuvenation, or if wellness is not valued, employees (counselors) may become distressed and impaired (Maslach, Leiter, & Schaufeli, 2008). Witmer and Young (1996) suggested that counselor education programs promote and model wellness for their students so they can prepare themselves to make lasting changes in their life to reduce the risk of impairment. Further, if counselors create an individual sense of wellness, they can advocate for their personal well-being in the agency and redirect energies towards organization wellness (Lambie & Young, 2007).

Previous authors suggested that the agencies in which counselors work can help to create wellness environments that contribute to counselors’ overall functioning. For example, Witmer and Young (1996) posited that counselor education programs, employing organizations and regulatory boards should develop systemic preventative wellness protocols to prevent counselor impairment. Their recommendations to agencies included equally distributing the most difficult cases, providing employee assistance programs that include family counseling, adequate peer support, and supervision and team building exercises. Stokes, Henley, and Herget (2006) offered some concrete suggestions to increase wellness including healthy food options, on-site exercise facilities, smoke-free environments, break stations away from the work areas, wellness challenges, support groups, social activities, health risk assessments, self-care information, employee counseling, financial incentives for long term employees and conflict resolution training for supervisors. Further, Lambie and Young (2007) recommended that mental health agencies reduce stress and promote wellness among their employees (counselors) by reducing paperwork and cutting “red tape,” adopting a collaborative management style, improving interpersonal relationships and teamwork, developing ways to reduce role stress, helping counselors grow on the job (e.g., professional development) and improving environmental conditions.

Although the potential hazards related to counselor’s work have received some attention (Gaal, 2009), there is limited research about how counselors conceptualize their wellness in relation to the influence of their work environment. Thus, the purpose of this exploratory study was to gain a greater understanding of how counselors experience wellness and how their work environment influences their sense of wellness. A qualitative phenomenological approach was the most appropriate method to implement because we were seeking to understand the participants’ lived experience of the phenomena (Creswell, 2007). Following the phenomenological tradition, we sought to uncover the central underlying meaning of their experience by reducing data, analyzing specific statements, searching for all possible meanings and creating meaning units (Creswell, 2009). Thus, we developed two research questions. The first question was, “How do you relate to the concept of wellness as a professional counselor?” and the second question was, “How do you perceive your agency influences your sense of wellness?” The first open-ended question was designed to gain information on each of the counselors’ thoughts about wellness and how they interpret the concept. The second question was designed to obtain information about how they believe their work environment affects their sense of wellness.


Research Team
The research team consisted of two counselor educators who at the time of the study were doctoral students at a university in the southeastern U.S. The first author is a Caucasian male and the second author is a Caucasian female. The first author has previous work experience in a residential treatment setting and in a secondary school setting where he experienced a high level of turnover and burnout among the staff. The second author has previous work experience in a variety of agency settings and experienced different levels of emphasis on wellness in each agency. She became interested in researching in this area to assist counselors in the field. Both authors believe a wellness focus is important for professionals in the helping professions. Furthermore, the authors believe that one’s work environment affects each counselor’s ability to be well.

Prior to facilitating the interviews and focus groups, we obtained approval from the Institutional Review Board (IRB) to conduct the study. Next, we recruited the 10 participants through a mixture of criterion-based and snowball-sampling strategies (Teddlie & Yu, 2007). The criterion included contacting counselors or agency directors who were currently or very recently employed at mental health agencies in a southeastern state. The snowball strategy included contacting individuals from the first and second authors’ previous employers, e-mailing invites on group servers for counselors who are alumni from a university that educates counselors and through following up recommendations from other counselors. After we secured participants for the study, we obtained informed consent and confirmed dates for the interviews and focus group.

The sample included seven female and three male professional counselors whose ages ranged from 25 to 53. Seven of the counselors were Caucasian, one counselor was of Indian descent, one was Latino, and one was of Middle Eastern descent. Two participants were employed by an agency that provides palliative care by way of in-home visits. One participant was a clinical director of an adolescent residential unit. One was previously a clinical director of a domestic violence shelter and a community counseling clinic. One participant worked in a behavioral hospital while another participant worked in an inpatient facility and previously in a residential setting. Three of the participants worked in a university-based clinic. Three counselors were present in the focus group interview and seven counselors were interviewed individually on separate occasions. See Appendix for pseudonyms and demographics.

Data Collection
Demographic questionnaire. Participants completed a demographic questionnaire consisting of questions about their age, race/ethnicity, socioeconomic status, gender, years in the field and work setting prior to participating in the interviews.

Individual interviews. The second author facilitated individual, semi-structured interviews with seven of the participants. Each interview lasted between 60 and 90 minutes. The interview started with the interviewer explaining the purpose of the study and then posing the first question: “How do you relate to the concept of wellness as a professional counselor?” Once this area was completely explored between the researcher and the interviewee, the researcher posed the second question: “How do you perceive your agency impacts your sense of wellness?” The researchers used follow-up, open-ended questions to elicit significant depth for each of the questions.

Focus group. The focus group included three counselors at a university-based counseling clinic and was facilitated by the second author. Prior to the group, the researcher reminded the interviewees about confidentiality and its limitations. The group lasted approximately 90 minutes and followed the same protocol as the individual interviews.

Data Analysis
After completing the interviews, we transcribed the audio-recorded sessions. All identifying information of the participants and location of employment were altered to maintain confidentiality. Next, the first and second authors read through transcripts to find initial categories. We employed inductive coding to devise categories that represented the overall essential message that was being conveyed in each interview and the focus group. The coding categories that emerged were recorded as well as thoughts about possible relationships between the categories (Glesne, 2006). Next, using the qualitative research software ATLAS.ti (Muhr, 2004), we loaded the documents and reduced the data using a chunking method, which requires the researcher to highlight sections of the transcription and assign codes or categories. Finally, we numbered the code list and noted connections among the interviewees’ coded chunks. This procedure consists of the researcher reviewing the codes to determine if a pattern, theme or relationship occurs (Glesne, 2006).

Verification Procedures
We implemented multiple verification procedures in order to ensure the trustworthiness of the study (Creswell, 2008). First, we performed member checks with participants to verify that the themes developed captured the essence of their experience. We addressed the threat of subjectivity through revealing our positionality and attempting to view information as objectively as possible. Additionally, we employed a peer-debriefer who continuously asked the primary author questions about the study, reviewed the relationship between the data and the research questions and reviewed the accuracy of the data analysis in comparison to the transcriptions.


In this study, we conducted seven individual interviews and a focus group to explore wellness for professional counselors in various mental health agencies. From the two research questions, “How do you relate to the concept of wellness as a professional counselor?” and, “How do you perceive your agency influences your sense of wellness?” five themes emerged: (a) resources, (b) time management, (c) occupational hazards, (d) agency culture, and (e) individual differences. We discuss each theme with thick, rich descriptions.

Agency Resources
Resources within the agency appeared to be a common theme that influenced participants’ sense of wellness. Participants consistently discussed areas such as salary, staff coverage and workloads as barriers to wellness. For example, participants discussed how financial compensation affected their feelings of being valued as well as their means to do things to maintain wellness. One participant, Anne, explained, “I am a 37-year-old woman who has to live with a roommate… I’m paid half of what nurses [at the same facility] are paid for the same amount of time.” When asked how she handled being paid less than other helping professionals, Anne responded, “I commiserate with other people in the field about being underpaid and undervalued. I can’t beat my head against a wall.” Another participant, Brian, discussed how his salary often impeded his ability to engage in wellness activities:
One of the struggles I had at the beginning was pay. Because it didn’t afford me, literally, the chance to do things to take care of myself, that I wanted to do to take care of myself. So if I had a weekend I couldn’t take a trip to the beach for the weekend. It had to be a quick jaunt and back because I couldn’t afford a hotel.

Resources also included counselor workloads, specifically in terms of how many clients each counselor had to see a day to maintain reimbursement policies. Brian discussed the lack of funding and explained that agencies must work “bare bones…skeleton crew basically.” One participant, Helen, commented on her caseload:

Money can drive a lot of things. Like the choices that you could make [before reimbursement] were more about the clients and what was needed, or what you wanted to try, and then you know Medicaid or other external forces enter, and then decisions have to be made on a different basis. The number of people you would even take would change. [before Medicaid]… There was a lot of flexibility, there was no external pressure to take a certain amount of clients and then there were great conversations and the ability to envision what you should do, and there was the time do it, and there was opportunity to review what you have done, and build the relationships and get feedback on your work, and whereas now, you have put in the time and you have to make the numbers and you lose the time to create relationships or talk about what you are doing.

Similarly, Brian discussed how large caseloads and working with clients back-to-back affected his performance when stating:
Basically, it took away from the services I was able to offer. But most of all it took away from me. You know my energy level, and just across the board I wasn’t able to do all of the things you would like to do as a quality counselor like planning…often it was sort of on the cusp.

Participants described the various resources within their agencies that influenced their sense of wellness. They identified the lack of resources as a barrier to their wellness, which also affected the quality of client care and enthusiasm for their work.

Time Management
Participants discussed time constraints as barriers to their wellness and their ability to maintain optimal performance with clients. They mentioned heavy caseloads as well as administrative duties and paperwork requirements as obstacles to their wellness that also reduced the quality of client services. Additionally, they believed that there was not adequate time for other important aspects of their development, such as supervision. One participant, David, discussed his frustration with not being able to sufficiently prepare for sessions, stating, “there was kind of this disconnect with how long it took to prepare for a session to do it right, or how long it would take to do a group, and to do it right.” He further proposed that the problem may be lessened even without reducing the caseload; “maybe it’s not about the number of clients as much as, maybe it’s just about a scheduling thing too, if you could just spread these clients out, thin enough.”

Participants also discussed administrative duties such as paperwork as wellness barriers that take away from the true meaning of their work. For instance, David stated that, “what was most stressful wasn’t working one-on-one with clients, it was just the amount of paperwork and catch up. You literally feel like you’re running a marathon when you walk in the room.” Brian described the draining effects of paperwork by stating, “I found myself very disenchanted because the work that I wanted to do was with people and often I found I was just doing documentation.”

Finally, participants discussed the importance of making time for appropriate supervision and consultation in maintaining their wellness. For example, when comparing an agency where she felt greater wellness to her previous agency, Fatin stated that the difference is:
The support and the peer consultation, and the time to do that. The level of respect is much higher. There is respect for the administrator; you can approach her with feedback. [There are] high ethical standards and consulting, and the open-door policy. Just makes it so you never feel worried that you will make a mistake, because a lot of people are holding you up.

When talking about the need to differentiate client staffing from clinical supervision, Brian explained that supervisors often, “don’t do supervision with their employees…or supervision is staffing. It’s the same.” He further explained, “Ideally, you have a sit-down with a person and do supervision. So they have a chance to talk about how they’re feeling, the problems they are having, in a safe place to do that.” He conceded that time constraints often hinder this process because, “there’s a lot of crisis and things come up at any given moment. So, you have a schedule, but something trumps it very quickly.” David discussed the benefits of having a positive supervisor who made time for clinical supervision with him, stating:
It was a really important part of me so when I was getting close to burnout or when I was stressed out or in a funk or whatever, I could talk to him and that kind of supervision process which was more than just once a week for an hour. It was more of an as needed kind of a thing and was very, very helpful. It was more than just clients, so it was very helpful for personal growth and so I was totally happy to have that.

Participants described time constraints as significant barriers to their wellness and consequently their ability to provide the best care to clients. However, they also discussed how access to human resources (e.g., supervisors) can positively influence their sense of wellness and development.

Occupational Hazards
A second theme that emerged was occupational hazards. This theme involved the psychologically intense characteristics of the work itself that threaten wellness and included concepts such as empathy fatigue, vicarious traumatization, depersonalization, lack of meaning and wounded healing. Participants discussed the challenges of helping difficult clients while attempting to maintain their own wellness.

One participant, Peter, discussed his struggle to not personally take on too much of the clients’ concerns. He stated that:
I think the biggest challenge that I’ve faced, and I can’t say this challenge is gone to this day, is that I took on a lot of my clients’ stuff. You know, you hear as a counselor you develop empathy for your clients with their challenges and their stories and experiences can be very traumatic and you know can be very impactful. So I think the biggest thing that I had that was impactful is I feel I would take on a lot and I would feel a lot more of what others struggled to face, as opposed to be there in the moment and then walk away from it… That was something, if you think about wellness as this bubble around me and that bubble keeps me from taking on too much of people’s stuff and keeps me mentally and personally safe, then my wellness was gone, the bubble was gone.

Another participant, Anne, discussed the burden that builds when occupational hazards are ignored by the agency and/or supervisors:
A lot of vicarious trauma, grief trauma left unprocessed. When a patient dies it is like—okay next. My administrator actually said that we assume you are coming in with the clinical skills and you will take care of yourself with that. There is no facilitative process or it is not acknowledged in our agency—that it could be happening to us as counselors. We are not given a moment to have that time. [The administrators say] be sure your taking care of yourselves out there—it is sort of you take care of yourself out there.

Yet another participant, David, discussed how the quick client turnaround in the inpatient facility led him to question the value and meaning in his work when he stated:
It was a lot of treat and street, so in other words they come in, you’re basically working on discharge paperwork from the first day you meet them, so you are already thinking about where they need to go…I mean they had lost everyone else in their lives and they felt isolated and alone, so the relationship was incredibly crucial and I think most people would agree that the relationship is the most important part of the counseling process, and you can’t build a relationship if basically when they are coming in you are looking at the chart trying to get the form filled out and trying to get them out the door because either insurance won’t pay or it’s a bed that needs to be emptied out so it can be filled with someone who can maybe last longer.

David went on to discuss his resulting emotions:
There is almost like this shame/guilt you are kind of feeling or struggling with where you feel like you can’t seem to get anywhere, or I am not doing anything, or what am I doing…Am I helping?…Does this matter? And I think that once you have lost that meaning in your work, that passion for what you are doing then it just kind of all, it’s a sinking ship at that point and wellness is just kind of out the window, you just get frustrated.

Participants also discussed the potential setbacks that can occur when professional counselors over-identify with their clients (e.g., wounded healer). Helen comments on how unfinished business unfolds in an agency:
It isn’t quite a straight line. In other words, it is whatever the underlying energy of the agency that draws people in. If people come and then they go, they may not relate to it, but those people who stay for a while, for [more than] three years, that is an issue. You have to constantly reflect back ‘why am I here?’ What is it about this job that has pulled me here and what is it that I need to learn. I think you could stay in the field and never reflect or heal from anything.

One participant, Romie, who also does clinical supervision, discussed the importance of processing empathy fatigue and often spends her time processing the “heaviness of the work.” She responded that “managing the occupational hazards is a matter of keeping the counselors happy…if they are happy and they feel good, and if they feel rewarded in their work they are going to produce and stay.”

Participants discussed that intense and emotionally close work they do with clients is a potential barrier to their wellness. They alluded to the need to set personal boundaries while still finding meaning in their work. Additionally, participants discussed needing time to process the emotions that may arise.

Agency Culture
The next theme that emerged was agency culture. The participants expressed that the messages the administration convey as well as the morale of the agency often influence their sense of wellness. Participants discussed wanting to feel valued and respected by their agency. Sarita stated that she felt valued by her agency. When she was asked how that message was conveyed to her, she replied:
I have been made to feel okay about my developmental level, just…you know…. normalizing my learning level. Everyone can speak up about what their opinion is, even if they are new, you feel part of the team. You know you have been selected for a reason to work here. They have confidence in you and they remind you of that.

Romie paralleled Sarita’s statement:
I happen to believe that wellness comes from the agency itself through feeling valued as an employee, [when] someone hears you in the company and that you have a voice. Having a sense that you say things and that they are respected. Feeling like that if there is anything that the company could do to help, they would. People feel happier, more rewarded and better. What that is in an agency I think is different for each one. It is more of a relationship and personal style.

Brian discussed the value when agencies respect the employees’ need to take care of their family:
Most of the programs that I’ve been in—they are more than willing to let you take care of your family as long as you are doing your job. That’s been the biggest piece I think from a wellness standpoint is the understanding of that from the top.

Participants also discussed how the overall morale of the agency and coworker relationships influence their sense of wellness. For example, Helen commented on how one of her previous places of employment communicated messages of wellness through promoting coworker relationships:
A lot that has to do with the attitude with the people running the place, what they valued, that fact they were invested in relationships. They realized we have to have connection with each other in order to give support to do the work here.

Similarly, Peter discussed how he believed staff cohesion plays a role in wellness:
My experience is that when there is a sense of cohesion, a sense of togetherness and teamwork, I think that people get along better and there’s a natural well, not well, but a natural happiness that goes along with it. My experience, where I’ve had the most stable or happy wellness have been places that encourage staff meals or having staff getaways, or doing events that brought the staff together to enjoy one another…not to work, but just to be around one another and enjoy one another and support one another.

Participants also discussed how agency directors and supervisors directly advocate for self-care. Catherine commented about self-care and wellness:
There is an encouragement for self-care. It is double-binded, you have to get your stuff done, but you know it is like it is Friday, let’s go home. They encourage each other to work less and have fun. Other places (agencies) had more pressure to get it done. There is a consciousness of balance.

Peter also discussed positive feelings when his supervisor supported his self-care efforts, “There was one day there was an accumulation of things, a combination of feeling sick, but also in the middle of a stressful time…he said go home, have a great day. So he was in support of wellness.” Peter continued, “he understood the job is not always easy and can bring on a lot of stress and he was willing to let us take care of ourselves if we needed to.”

Overall, when the agency promoted the respect and value of professional counselors and encouraged counselors to have a voice and affect change, it promoted the counselors’ own sense of wellness. Furthermore, sensing an investment in work relationships and promoting a work-life balance influenced the wellness of these counselors.

Individual Differences
The final theme that emerged involved the different perspectives of the participants and how that influenced their feelings of wellness. Two participants from the same agency held very different feelings about how their agencies influenced their sense of wellness. Jill felt very positive about her agency and spoke of the many financial incentives and freedoms allotted and that the agency’s independent scheduling fit her. Anne also mentioned the same financial incentives, but believed that she received negative mixed messages and that her wellness was being negatively affected by the same agency. Conversely, Jill, who felt positive towards her agency, noted, “No one had to tell me to take care of myself.” David also expressed that wellness is often left up to the individual; when speaking about one of his agencies he stated, “it wasn’t really like it was a place of wellness. Wellness is something that happened, or self-care happened long after you left.” Romie responded about her intentionality with wellness:

Personally, what I do is many things. I exercise; I make sure I get plenty of sleep. I take time for myself when I need to. I will do yoga and meditate and do a lot of reading and I am highly spiritual. I have a wonderful home-life, a very supportive love-mate in my life. I am really in a good place.

Throughout the interviews, the participants discussed very different values in terms of their wellness. Some of the participants mentioned spiritual practice and journaling as being important in maintaining wellness. Others expressed time with family as being most important, whereas others discussed setting clear boundaries or finding meaning in their work.

Other participants discussed how wellness initiatives within their agencies often seemed inconvenient to them. When talking about a discounted gym membership that was offered, Brian viewed the offer as superficial, saying “in my experience, most of what they offer in terms of wellness is, in my experience, is somewhat superficial.” He further stated, “Very few people are able to utilize the gym membership because of the hours they work and where it’s located and the cost is still too high for the employees.” Peter discussed the positives and negatives of a wellness initiative:

The book was a 40 week-by-week event where you learned about wellness…physical, mental, spiritual; all these different components. The problem was they had these events that took place scattered all over the district and so for anyone to attend them, they would have to drive half an hour to 45 minutes to attend them and which if you’re trying to have a good basis for wellness, then having people drive 45 minutes after a long day of work is not a good place to start for that.

However, Peter acknowledged that this may be only his view, stating:

The planning of the events I felt could have been better. And of course, not to say other people didn’t go to them and find them successful, but it was just my experience of do I go home or drive 45 minutes then attend a 2-hour meeting on nutrition. I felt like going home was more beneficial for me at that time.

These statements reveal that professional counselors may value different things related to wellness. Other counselors in Brian or Peter’s agency may have appreciated the wellness initiatives.

The participants responded differently in terms of wellness values. One cannot overlook how different individuals will react to the stress of being a counselor. Knowing what type of atmosphere is the best fit for the counselor’s personality and interests can factor in overall well-being. Romie commented, “It is good to know what kind of atmosphere is the best fit for you, if you love it, then that is your wellness, if you don’t, then nothing you do will ever click.”


The findings in this study suggest that the environment in which the participants work may play an important role in their overall wellness. This finding is consistent with previous research that suggested agencies directly affect well-being and satisfaction of counselors (Knudsen, Ducharme, & Roman, 2006; Lloyd, King, & Chenowith, 2002; Maslach, 1982, 1986). Participants in this study discussed lack of resources as potential barriers to wellness including unsatisfactory salaries, large caseloads, heavy paperwork and lack of supervision. This finding is consistent with previous research that maintaining caseloads above 15 per week increases chances of occupational hazards (Trippany, Kress, & Wilcoxon, 2004). Additionally, counselors have reported increased salaries as directly relating to their wellness (Bell et al., 2003), and comprised a major setback for counselors in this study. Further, our findings support previous research that poor supervision, little to no peer-to-peer conversations, low salaries, heavy paperwork, lack of control over services and managed care influences are all correlated with decreased wellness and increased likelihood of burnout (Ackerly, Burnell, Holder, & Kurdek, 1998; Gaal, 2009). Clients deserve to receive the best care possible in agencies; therefore, funding sources should be aware of what counselors specifically need to function at their best. However, it is the responsibility of all counseling professionals to organize and advocate for gains such as salary increases, caseload limits, qualified supervisors, and funding for wellness activities. Advocating through joining local, state and national organizations is one way to work toward these goals, as organizations stay abreast of current legislative changes and locate opportunities to improve the counseling profession.

The finding in this study that occupational hazards influenced counselors’ wellness is consistent with previous literature (Skovholt, 2001; Stebnicki, 2007). Additionally, participants in this study discussed the importance of supervision and processing time in order to work through such hazards. This finding reinforces the importance of supportive environments where counselors can obtain peer support and adequate supervision. Consequently, counselors’ wellness may be increased when agencies have consistent treatment-team meetings and supervision sessions, where counselors have an opportunity to process their work with others and obtain consultation. Additionally, supervisors should have appropriate training in supervision to ensure that a quality supervision experience occurs.

Participants in this study expressed that the culture of the agency influenced their sense of wellness. Factors that positively influenced them included feeling valued by administrators, feeling that they had a voice, being respected and feeling cohesion with coworkers. Agencies may assist in counselor wellness by developing employee committees that provide a forum for counselors to express concerns and provide recommendations to the agency. This may help to foster a sense of value among the counselors when their perspectives are heard. Additionally, employee committees may serve to organize wellness activities and professional development opportunities for the staff, encourage peer support and cohesion, and organize advocacy efforts.

Implications for Professional Counselors

The findings in this study suggest that one’s wellness is very personal and is heavily influenced by personally salient values. In this study, the participants mentioned different wellness values. Individually, counselors can develop holistic wellness plans and gain self-knowledge concerning what aids them in performing at their best, while considering the realities of their work environment and resources that are available to them. Counselor educators can model wellness activities and highlight the resilience that stems from a comprehensive wellness plan so new professionals are prepared to attend to wellness when they enter the field. Counselor educators also should educate counselor trainees as to the realities of agency work (e.g., caseloads, paperwork, difficult clients) so they can prepare themselves mentally to enter the system. Counselors and clinical directors can vocalize ways to enhance the well-being of the atmosphere in the agencies by advocating for reasonable caseloads and encouraging wellness days for the staff (e.g., days where the entire staff rejuvenates together through team building or other enjoyable workshops or activities). Given that funding is often mentioned as a factor that influences wellness, agencies and individual counselors may benefit from learning how to secure various types of grants to assist with resources (e.g., additional staff, technology, wellness initiatives). Additionally, agencies may benefit from developing ad-hoc committees that will evaluate processes and procedures (e.g., paperwork, documentation) to potentially reduce workloads and ensure that counselors’ time is used efficiently. Finally, counselors should be proactive in seeking out further training in wellness, self-care and burnout prevention through conferences (e.g., ACA, AMHCA) or other professional development opportunities, and should advocate that their agencies provide these types of trainings.

Limitations and Future Research

Despite the depth and richness of information obtained in this exploratory study, there are multiple limitations. First, we did not spend prolonged time in the field in order to gather further data about wellness practices through observation or document analysis. Future researchers may benefit from direct observations of wellness practices in the natural setting. Additionally, we only utilized one source of data for interpretation (i.e., interview/focus group) which may have affected the depth of information obtained. Finally, although generalizability is not a major goal of qualitative research, readers should be mindful that the findings may not be representative of other counselors in different settings.

Future researchers could explore wellness experiences of more diverse racial/ethnic groups and those at various income levels. Additional studies may include more prolonged engagement in the field by the researcher in order to make observations about wellness practices as well as multiple data sources (e.g., observations, questionnaires, reflective journals). Other studies may include agencies that are currently implementing specific wellness practices in order to evaluate their effect on counselor wellness. Finally, future researchers may benefit from identifying particular agencies that maintain effective wellness practices and exploring them through in-depth analysis.


Counselor wellness is an important aspect of ensuring effective and ethical services to clients (ACA, 2010; NBCC, 2005). The findings in this study provide some initial information about the various aspects of wellness that may be influenced by professional counselors’ work environment. Although agencies may not be able to immediately change all aspects of the work environment (e.g., salary, caseloads, work hours), other aspects such as agency culture and adequate supervision are easier to address. Counselors and clinical directors may benefit from evaluating their current wellness practices through staff questionnaires, focus groups, or needs’ assessments. Attending to professional counselors’ wellness needs may help to improve the morale in the agency, help counselors avoid burnout, and ensure more quality care for clients.


Ackerly, G. D., Burnell, J., Holder, D. C., & Kurdek, L.A. (1988). Burnout among licensed psychologists. Professional Psychology: Research and Practice, 19, 624–631.
American Counseling Association. (2005). ACA code of ethics. Alexandria, VA: Author. American Mental Health Counselors Association. (2010). AMHCA code of ethics. Author.
Bell, H., Kulkarni, S., & Dalton, L. (2003). Organizational prevention of vicarious trauma. Families in Society: The Journal of Contemporary Services, 84, 463–470.
Cain, D. J. (2001). Defining characteristics, history, and evolution of humanistic psychotherapies. In D. J. Cain & J. Seeman (Eds.), Humanistic psychotherapies: Handbook of research and practice (pp. 3–54). Washington, DC: American Psychological Association.
Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five traditions (2nd ed.). Thousand Oaks, CA: Sage.
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage.
Ducharme, L. J., Knudsen, H. K., & Roman, P. M. (2008). Emotional exhaustion and turnover intention in human
service occupations: The protective role of coworker support. Sociological Spectrum, 28, 81–104. doi:10.1016/j.jsat.2006.04.003
Figley, C. R. (2002). Treating compassion fatigue. New York, NY: Routledge.
Gaal, N. (2009). Comparing burnout levels experienced by therapists working in a mental health organization versus therapists working in private practice. (Doctoral dissertation). Retrieved from ProQuest. (3360424)
Glesne, C. (2006). Becoming qualitative researchers (3rd ed.). Boston, MA: Pearson Education.
Knudsen, H. K., Ducharme, L. J., & Roman, P. M. (2006). Counselor emotional exhaustion and turnover intention in therapeutic communities. Journal of Substance Abuse Treatment, 31(2), 173–180. doi:10.1016/j.jsat.2006.04.003
Lambie, G., & Young, M. E. (2007). Wellness in school and mental health systems: Organizational influences. Journal of Humanistic Counseling, Education and Development, 46, 98–113.
Lawson, G. (2007). Counselor wellness and impairment: A national survey. Journal of Humanistic Counseling, Education and Development, 46, 21–34.
Lawson, G., & Venart, B. (2005). Preventing counselor impairment: Vulnerability, wellness, and resilience. In G. R. Walz & R. K. Yep (Eds.), VISTAS: Compelling perspectives on counseling 2005 (pp. 243–246). Alexandria, VA: American Counseling Association.
Lloyd, C., King, R., & Chenoweth, L. (2002). Social work, stress and burnout: A review. Journal of Mental Health, 11, 255–265. doi; 10.1080/09638230020023642
Maslach, C. (1982/2003). Burnout: The cost of caring. Cambridge, MA: Malor Books.
Maslach, C. (1986). Burnout research in the social services: A critique. Journal of Social Service Research, 10, 95–105.
Maslach, C., Leiter, M.P., & Schaufeli, W.B. (2008). Measuring burnout. In Cooper, C.L., Cartwright, S. (Eds), The Oxford handbook of organizational wellbeing (pp. 86–108). Oxford: Oxford University Press.
McCann, I. L., & Pearlman, L. A. (1990). Vicarious traumatization: A framework for understanding the psychological effects of working with victims. Journal of Traumatic Stress, 3, 131–149. doi: 10.1007/BF00975140
Muhr, T. (2004). ATLAS.ti 5.0 (Version 5:). Berlin, Germany: ATLAS.ti Scientific Software Development GmbH. Available from http://www.
Myers, J. E., Sweeney, T. J., & Witmer, J. M. (2000). The wheel of wellness counseling for wellness: A holistic model for treatment planning. Journal of Counseling & Development, 78, 251–266. Retrieved from
National Board for Certified Counselors (2005). NBCC code of ethics. Greensboro, NC: Author.
Pines, A., & Maslach, P. (1978) Characteristics of staff burnout in mental health settings. Hospital and Community Psychiatry, 29, 233–237.
Rupert, P., & Morgan, D. (2005). Work setting and burnout among professional psychologists. Professional Psychology: Research and Practice, 36, 544–550. doi: 10.1037/0735-7028.36.5.544
Shapiro, S., Brown, K., & Biegel, G. (2007). Teaching self-care to caregivers: Effects of mindfulness-based stress reduction on the mental health of therapists in training, Training and Education in Professional Psychology, 1, 105–115. doi: 10.1037/1931-3918.1.2.105
Skovholt, T. M. (2001). The resilient practitioner: Burnout prevention and self-care strategies for counselors, therapists, teachers, and health professionals. Boston, MA: Allyn & Bacon.
Stebnicki, M. (2007). Empathy fatigue: Healing the mind, body, and spirit of professional counselors. American Journal of Psychiatric Rehabilitation, 10, 317–338. doi:10.1080/15487760701680570
Stokes, G., Henley, N. & Herget, C. (2006), Creating a culture of wellness in workplaces. North Carolina Medical Journal, 67, 446–448.
Teddlie, C., & Fen, Yu (2007). Mixed methods sampling: A typology of examples. Journal of Mixed Methods Research, 1, 77–100. doi: 10.1177/2345678906292430
Trippany, R. Kress, V., & Wilcoxon, S. (2004). Preventing vicarious trauma: What counselors should know when working with trauma survivors. Journal of Counseling & Development, 82, 31–37.
Vredenburgh, L., Dale , C., Alfred, F., & Stein, L. B.(1999). Burnout in counseling psychologists: Type of practice setting and pertinent demographics. Counselling Psychology Quarterly, 12, 293–302. doi: 10.1080/09515079908254099
Witmer, M., & Young, M. E. (1996). Preventing counselor impairment: A wellness approach. Journal of Humanistic Counseling, Education, & Development, 34, 141–156.

Jonathan H. Ohrt is an Assistant Professor at the University of North Texas. Laura K. Cunningham, NCC, is an Assistant
Professor at Argosy University. Correspondence can be addressed to Jonathan H. Ohrt, University of North Texas, 1155 Union Circle #310829, Denton, TX 76203,

Participant Demographics

Name (pseudonyms were assigned) Type of Facility Gender Age Race Experience in Field Interview Method

Palliative Care Facility



11 Years

Palliative Care Facility Female 40 Caucasian 2 Years Individual

Clinical Director for Domestic Violence Shelter and Community Counseling Center Female 45 Caucasian 13 Years Individual


Clinical Director of an Adolescent Residential unit
Female 53 Caucasian 20 Years Individual
University Counselor
Female 27 Caucasian/Middle Eastern 1 Year Focus Group

University Counselor
Female 28 Caucasian 9 Months Focus Group
University Counselor
Female 33 East Indian 1 Year Focus Group
David Behavioral Hospital Male 29 Latino 3 Years Individual
Peter Inpatient & Residential Male 28 Caucasian 3 Years Individual
Brian Adolescent Residential Male 38 Caucasian 13 Years Individual