Mar 30, 2018 | Volume 8 - Issue 1
Trish J. Smith, Courtney M. Holmes
Intimate partner violence (IPV) is a public health concern that affects millions of people. Physical violence is one type of IPV and has myriad consequences for survivors, including traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD). It is estimated that as many as 23,000,000 women in the United States who have experienced IPV live with brain injury. This article overviews the intersection of TBI and PTSD as a result of IPV. Implications for counselors treating women impacted by IPV suggest counselors incorporate an initial screening for TBI and consider TBI- and PTSD-specific trauma-informed approaches within therapy to ensure best practices. A case study demonstrating the importance of the awareness of the potential for TBI in clients who experience IPV is included.
Keywords: intimate partner violence, traumatic brain injury, post-traumatic stress disorder, PTSD, public health
In 1981, the U.S. Congress declared October as Domestic Violence Awareness Month, marking a celebratory hallmark for advocates and survivors nationwide (National Resource Center on Domestic Violence, 2012). Since this time, similar social and legislative initiatives have increased overall awareness of gender inequality, thus influencing a decline in women’s risk for intimate partner violence (IPV; Powers & Kaukinen, 2012). Recent initiatives, such as a national briefing focused on brain injury and domestic violence hosted by the Congressional Brain Injury Task Force, continue to call increased attention to the various intersections and implications of this national public health epidemic (Brain Injury Association of America, 2017). Unfortunately, despite various social advocacy movements, IPV remains an underrepresented problem in the United States (Chapman & Monk, 2015). As a result, IPV and related mental and physical health consequences continue to exist at alarmingly high rates (Chapman & Monk, 2015).
IPV refers to any act of physical or sexual violence, stalking, or psychological aggression by a current or previous intimate partner. An intimate partner is an individual with whom someone has close relations with, in which relations are characterized by the identity as a couple and emotional connectedness (Breiding, Basile, Smith, Black, & Mahendra, 2015). An intimate partner may include but is not limited to a spouse, boyfriend, girlfriend, or ongoing sexual partner (Breiding et al., 2015). Physical violence is the intentional use of force that can result in death, disability, injury, or harm and can include the threat of using violence (Breiding et al., 2015). Sexual, emotional, and verbal abuse are often perpetrated in conjunction with physical violence in relationships (Krebs, Breiding, Browne, & Warner, 2011).
Heterosexual and same-sex couples experience IPV at similar rates (Association of Women’s Health, Obstetric and Neonatal Nurses, 2015). Researchers estimate that more than one in every three women and at least one in four men have experienced IPV (Sugg, 2015). These rates likely underestimate the true prevalence of IPV, given that populations with traditionally high incidences of abuse (e.g., poor, hospitalized, homeless, and incarcerated women) may not be included in survey samples (Scordato, 2013; Tramayne, 2012). Additionally, fear and shame often serve as a deterrent to reporting abuse (Scordato, 2013). Although both men and women are victims of IPV, women are abused at a disproportionate rate (Association of Women’s Health, Obstetric and Neonatal Nurses, 2015) and have a greater risk than men of acquiring injury as a result of physical violence (Scordato, 2013; Sillito, 2012). Data have shown that 2–12% of injuries among women brought into U.S. emergency departments are related to IPV (Goldin, Haag, & Trott, 2016), 35% of all homicides against women are IPV-related (Krebs et al., 2011), and approximately 22% of women have experienced physical IPV, averaging 7.1 incidences of violence across their lifespan (Sherrill, Bell, & Wyngarden, 2016). IPV is a pervasive relational problem that creates a myriad of complex mental and physical health issues for female survivors (Sugg, 2015). One health issue commonly experienced by female survivors of IPV is post-traumatic stress disorder (PTSD; Black et al., 2011).
PTSD and IPV
A Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) diagnosis of PTSD is based on the client’s exposure to a dangerous or life-threatening stressor and consists of the following symptomology: intrusion of thoughts or re-experiencing of the event, including flashbacks; avoidance of experiences or thoughts related to the stressor; negative alterations in cognition and mood; and changes in reactivity, including hypervigilance or hyperarousal. According to Bourne, Mackay, and Holmes (2013), flashbacks are the hallmark symptom of PTSD and involve a process in which the individual dissociates and feels as though they are re-experiencing the traumatic event through involuntary, vivid, and emotional memories. Although PTSD symptoms may occur immediately after a traumatic event, symptoms may have a delayed onset in which the full range of symptoms can manifest even 6 months after the event, showing only partial symptom criteria in the preceding months (Utzon-Frank et al., 2014).
Experiencing IPV increases risk for developing PTSD (National Center on Domestic Violence, Trauma, and Mental Health, 2014). In a national sample of 9,000 women, 62% who experienced some form of IPV reported at least one PTSD symptom (Black et al., 2011). Women who experience IPV are almost three times as likely to meet criteria for PTSD when compared with those who have not had such experiences (Fedovskiy, Higgins, & Paranjape, 2008). Although PTSD is a common manifestation of IPV, another condition, traumatic brain injury (TBI), also is prevalent in survivors (Sherrill et al., 2016). The symptomology of TBI mirrors that of PTSD, rendering the clinical tasks of appropriate diagnosis and treatment planning especially difficult (McFadgion, 2013).
TBI and IPV
TBI is defined as a change in brain function caused by an external force (e.g., strike to the head or strangulation; Murray, Lundgren, Olson, & Hunnicutt, 2016). Symptoms include headaches, dizziness, fatigue, difficulty concentrating, irritability, and perceptual difficulties with noise and light (Zollman, 2016). Other symptoms can include problems with attention, memory, processing speed, decision making, and mood (Jeter et al., 2013). Professionals can use computerized tomography (CT) scans to find contusions, hematomas, diffuse axonal injury, and secondary brain injuries, which aid in the medical diagnosis of TBI (Currie et al., 2016). Although CT is widely used in assisting with the identification of TBI, a final diagnosis is most often made in a clinical interview with the patient, treating physician, and if feasible, those who observed the violent incident or responded to it (Zollman, 2016). Violence that causes TBI may or may not leave internal or external physical evidence of trauma (e.g., bruising, scarring); thus it is crucial that assessment and screening attempts take place beyond neuroimaging technology and are included as a part of a comprehensive evaluation (Joshi, Thomas, & Sorenson, 2012).
Researchers indicate that over 60% of women, with estimates as high as 96%, who experience IPV sustain injury to the face or head areas, including attempted strangulation (McFadgion, 2013; Sherrill et al., 2016; St. Ivany & Schminkey, 2016). Acquired TBI through IPV can complicate the therapeutic treatment of women (Murray et al., 2016). Brain injury shares similar symptomology with PTSD, increasing likelihood for misdiagnosis, complications with care, and long-term brain damage (McFadgion, 2013). Additionally, TBI and PTSD are often comorbid diagnoses, and those who survive physical trauma and incur a TBI suffer negative mental health impacts such as depression, anxiety, and suicidal ideation (Smith, Mills, & Taliaferro, 2001).
PTSD and TBI have an extensive impact on brain functioning (Boals & Banks, 2012; Saar-Ashkenazy et al., 2016). Individuals with PTSD experience daily cognitive failures in memory, perception, and motor function (Boals & Banks, 2012; Saar-Ashkenazy et al., 2016). Other researchers have shown that PTSD negatively impacts brain functioning on multiple levels, including stimuli recognition, and overall cognitive functioning (Saar-Ashkenazy et al., 2016). Similarly, individuals with TBI may experience physical, sensory, cognitive, and social difficulties as a result of their brain injury (Brain Injury Association of Virginia , 2010). Given the overlapping symptoms of PTSD and TBI, and the overall impact on functioning, it is critical for counselors to consider these factors when diagnosing and treating women who have experienced IPV.
In sum, IPV is a widespread public health issue with a multitude of negative consequences related to human functioning. Incidences of TBI in women who have experienced IPV cannot be overlooked. A framework for mental health counselors that includes awareness of the overlapping symptoms between two likely outcomes of IPV and their manifestation is crucial for successful case conceptualization and treatment.
Counseling Implications
PTSD and TBI have extensive impact on human functioning, and it is critical that counselors examine appropriate responses and considerations for therapeutic treatment of female survivors of physical violence resulting from IPV. Clinical considerations should be incorporated into initial screening, therapeutic approaches, and communication with clients.
Screening and Assessment
McLeod, Hays, and Chang (2010) suggested that counselors universally screen clients for a current or past history of IPV. Based on the literature, survivors of IPV face various challenges when seeking services and either reporting or disclosing abuse, including: self-blame for the abuse; fear of the perpetrator; internalized shame; lack of acknowledgement of the level of danger; perception that community services are not helpful; lack of housing, child care, and transportation; access to money; and lack of educational opportunities (Fúgate, Landis, Riordan, Naureckas, & Engel, 2005; Lutenbacher, Cohen, & Mitzel, 2003; McLeod et al., 2010; Scordato, 2013). Minority populations experience additional challenges, including fear of prejudice and systemic oppression (Scordato, 2013). Thus, counselors carry the responsibility to broach screening with all clients. With an intentional screening for IPV, counselors are able to further identify TBI as a result of physical violence in IPV to ascertain medical and related concerns. Given the statistical probability that a woman who experienced physical IPV sustained past injury to the head or neck, initial screening is critical (Murray et al., 2016). The Pennsylvania Coalition Against Domestic Violence (PCADV; 2011) provides a guide based on a classic TBI screening called HELPS. The guide asks questions in the context of IPV, including if the person has ever been: (a) hit on the head, mouth, or other places on the face; (b) pushed so hard the head strikes a hard or firm surface; (c) shaken violently; (d) injured to the head or neck, including strangulation, choking, or suffocating that restricted breathing; and (e) nearly drowned, electrocuted, or intentionally given something allergic. These questions serve as a guide in detecting if the survivor has acquired TBI; however, they should not be used in place of a medical assessment (PCADV, 2011).
The Brain Injury Association of America (2015) describes symptoms of TBI as including: headaches, dizziness, lack of awareness of surroundings, vomiting, lightheadedness, poor attention and concentration, fatigue, and ringing in the ears. Impairments involving functions related to memory, decision making, and processing speed may be indicators of brain injury (Jeter et al., 2013). Recognizing TBI allows for the appropriate response in treatment, including identifying necessary medical consultations and referrals.
Therapeutic Approaches to IPV
After the brain is injured, a recovery process involving three stages is prompted, including: cell repair, functional cell plasticity, and neuroplasticity (Villamar, Santos Portilla, Fregni, & Zafonte, 2012). Zasler, Katz, Zafonte, and Arciniegas (2007) described neuroplasticity as the process in which spared healthy brain regions compensate for the loss of functioning in damaged regions. Kimberley, Samargia, Moore, Shakya, and Lang (2010) suggested that repetition of activities is required to induce neuroplasticity, or recovery of the brain.
Researchers have shown that certain techniques in talk therapy can aid in the recovery of the brain, serving to benefit both the treatment of PTSD as well as the alleviation of symptoms in TBI (Chard, Schumm, McIlvain, Bailey, & Parkinson, 2011). For example, Chard et al. (2011) compared two therapies: (a) cognitive processing therapy (CPT), a form of cognitive behavioral therapy effective in treating PTSD; and (b) an alternate version of CPT, CPT-cognitive only (CPT-C), which omits the writing and reading of one’s trauma narrative and instead emphasizes cognitive challenging and rehearsal. Both approaches were applied to a sample of 42 male veterans who met criteria for PTSD, had history of TBI, and were compared across four groups based on severity and treatment approach (Chard et al., 2011). In addition to speech therapy two to three times a week and a psychoeducation group 23 hours a week, CPT-C individual sessions and group sessions were each held twice a week as a part of a residential treatment program (Chard et al., 2011). Chard et al. identified a significant main effect across PTSD and depression measures for both groups, indicating CPT-C as a plausible treatment for clients with TBI.
Another therapeutic approach includes CRATER therapy, which is an acronym that encompasses six targets for therapy: catastrophic reaction, regularization, alliance, triangulation, externalization, and resilience (Block & West, 2013). The first target, catastrophic reaction, is based on targeting the explosive reaction that is in response to overwhelming environmental stimuli; regularization is the therapist’s approach to establishing a regular daily routine for the client (e.g., sleep–wake cycle, meal times); alliance is the relationship between the professional and survivor; triangulate is the relationship expanded beyond the client to include a family member or friend; externalize negates self-blame; and resilience promotes the use of effective coping skills (Block & West, 2013). The individual’s family members and friends are specifically targeted in the approach to account for ecological validity and provide support. Block and West (2013) stated, “CRATER therapy targets the formation of a good working alliance, teaches the survivor to perform skills without cues from the provider and integrates both cognitive and therapy interventions” (p. 777). Overall, this theory infuses cognitive restructuring into individual psychotherapy and assists the client in developing effective coping strategies.
In addition to the implementation of specific therapeutic approaches in counseling, the counselor can incorporate management strategies to accommodate survivors’ brain injury symptoms in counseling sessions. For example, a client who takes longer to complete tasks and answer questions because of an impaired information processing speed can be accommodated by the counselor doing the following: (a) allowing extra time for responses, (b) presenting one thing at a time, and (c) not answering for them during the lapse in response time (BIAV, 2010). The PCADV (2011) also recommends speaking in a clear and literal sense as well as providing tasks in short increments. If memory is impaired, the counselor can make it a point to repeat information as necessary, encourage the use of external memory aids (e.g., journals, calendars), and give reminders and prompts to assist with recall (Block & West, 2013). In the case in which the client shows poor self-monitoring skills and lacks adherence to social rules or consistently dominates the dialogue in sessions, the counselor can provide feedback, encourage turn-taking, and gently provide redirection of behavior (BIAV, 2010). Implementing techniques that involve feedback and redirection also can decrease chances of oversharing that might re-traumatize the survivor (Clark, Classen, Fourt, & Shetty, 2014). Utilizing compensatory strategies such as these can ensure the accessibility and efficacy of counseling sessions to survivors with TBI.
Therapeutic Communication With IPV Clients
Aside from specific counseling approaches and management strategies, several considerations can be made by the counselor to ensure an informed response in communication and chosen interventions. Building a therapeutic relationship, including instilling hope for possible change, is especially useful with complex PTSD diagnoses (Marotta, 2000). Additionally, researchers suggest that receiving social support is a resiliency factor in trauma recovery (Shakespeare-Finch, Rees, & Armstrong, 2015; Zhou, Wu, Li, & Zhen, 2016). However, data suggest that women with brain injury, when compared with male counterparts, experience more negative alterations to social and play behavior, including more exclusion and rejection in social situations (Mychasiuk, Hehar, Farran, & Esser, 2014). Mychasiuk et al. (2014) indicated that group therapy or other social types of interventions related to social support building and safety planning may be contraindicated until these specific challenges can be addressed in individual counseling.
Counselors should be aware of the cyclical nature of abusive relationships that can result in multiple brain injuries over time (Murray et al., 2016). Additionally, counselors should understand complex PTSD, which is associated with prolonged exposure to severe trauma; alterations to affect and impulses, self-perception, interactions with others, and increased somatization; and medical problems (Pill, Day, & Mildred, 2017). Consideration of the potential impact that cumulative brain injuries and prolonged trauma have on health outcomes is critical for effective clinical intervention (Kwako et al., 2011), as myriad aspects of a woman’s ability to identify and understand her situation may be negatively impacted. A critical skill for women in violent relationships includes the need to account for, and effectively assess, one’s physical environment at the time of abuse. A client can take the following precautions to protect herself from future violence: (a) making herself a smaller target by curling up into a ball in a corner, (b) avoiding wearing scarves or necklaces that can be used in strangulation attempts, (c) guarding her head with her arms around each side of her head, and
(d) hiding guns or knives (PCADV, 2011). Furthermore, it is imperative that the counselor actively assist in the safety planning process given that head injury and trauma often impair cognitive processes such as a person’s ability to plan and organize (PCADV, 2011). Initiating the safety planning process as a psychoeducational component of treatment could serve to counter shame and self-blame for the survivor, ensuring that a trauma-informed approach and best practices are maintained (Clark et al., 2014).
Ethical Implications
Client cases that include current or past IPV are often fraught with numerous ethical considerations (McLaughlin, 2017). Perhaps the most pervasive ethical issue is the responsibility of mandated reporting. Counselors must be aware of the intricacies of such responsibility and understand the limits of reporting as it pertains to survivors of IPV (American Counseling Association, 2014). Clinicians should become skilled at assessing for violence in relationships so that reporting can occur if one of the following situations arise: abuse of children, older adults, or other vulnerable populations; duty to warn situations; or risk of suicide. The responsibility to report must be discussed with clients during the informed consent process and throughout treatment (American Counseling Association, 2014, B.1.d).
IPV presents additional complications for treatment providers. Researchers suggest that more than 50% of couples in therapy report at least one incident of physical aggression against their partner (O’Leary, Tintle, & Bromet, 2014). Despite this implication, counselors fail to adequately assess for violence or intervene when violence is present. Once a thorough assessment has taken place, clinicians can evaluate the most appropriate and safe course of treatment for each individual and the couple together. Treatment options include continued couples work (when appropriate), separate individual therapy, or group work that may include anger management or other behavioral-change strategies (Lawson, 2003).
Counselors working with survivors of IPV should expect to regularly determine how to “maximize benefit and minimize harm” for each client (McLaughlin, 2017, p. 45). Counselors may find themselves working with clients who want or need to stay in the relationship or those who want or need to leave the relationship. Each situation is complicated with a variety of personal factors such as level of violent threat and access to financial and other types of resources. Individual assessment in collaboration with the client to determine the best therapeutic strategy is necessary (McLaughlin, 2017).
Finally, counselors may hold overt or covert personal biases toward IPV clients and violence against women. Counselors should evaluate personal feelings toward both victims and perpetrators of IPV prior to working with them and throughout the course of treatment. McLeod et al. (2010) developed a competency checklist for counselors to assist in necessary self-reflection and self-evaluation of their level of competency when working with this population. Finally, counselors should understand the critical nature of supervision and consultation and seek it out when necessary (McLaughlin, 2017).
Case Study
The following case study is a hypothetical case based loosely on the first author’s experience as a counselor in a domestic violence shelter. The case and treatment description are meant to provide a general overview of how counselors might implement an overarching lens of screening and treatment when working with survivors of IPV.
A 48-year-old Caucasian woman sat across from her counselor, elated as she described the sense of relief she felt to finally receive counseling support during what she explained to be the worst time of her life. In disclosing several accounts of physical, sexual, and emotional abuse, she described times in which her ex-partner had blackened her eye, broken bones, and strangled her. Knowing the various causes of TBI in IPV, the counselor started a conversation about the possibility of brain injury. The client denied going to the emergency room to be assessed for injuries, a process that would have likely detected contusions or swelling of brain tissue. The absence of medical treatment was not surprising to the counselor, given the numerous barriers that often leave survivors of IPV without medical attention, including fear of further harm. Knowing this, the counselor was careful in her communication so as to not suggest blame or judgement for the client’s decisions to not seek past medical assistance. The counselor proceeded to ask questions related to whether or not the client perceived any changes to physical or cognitive functioning in comparison to life before her abusive relationship, with focus on memory, attention, and learning experiences. The client found it very difficult to answer these questions in detail, indicating that her memory was potentially impaired because of either PTSD or brain injury. A neutral, yet warm and understanding, therapeutic stance was critical for the counselor to keep the client engaged in the therapeutic process.
Following the detection of probable TBI, the counselor provided psychoeducation to promote awareness on the nature of the injury as well as referrals to various local and state resources. The counselor and client then discussed the client’s experience of PTSD symptoms and how these symptoms could mirror the symptoms of brain injury. Education is a recommended strategy when working with clients with PTSD (Marotta, 2000). The counselor knew that helping the client to differentiate between the two would help her monitor and document symptoms for the journaling homework that would eventually be assigned to her. At this time, the counselor provided the client with a handout with a t-chart comparing PTSD and TBI symptoms, knowing that a concrete, visual representation might be a helpful accommodation. For her journaling homework, the counselor instructed the client to record the following: symptom type, duration, intensity, and any contextual details. This recording would benefit the client in multiple ways, including increasing personal awareness and attention to symptoms, indicating the necessity of additional referral sources, and providing a record for discussion with future medical professionals.
At the beginning of the next several sessions, the counselor followed up on the client’s journaling homework. During these check-ins, the client reported times of forgetfulness, difficulty with attention, and problems staying organized and making decisions. One particular incident allowed the counselor and client to actively probe through differences between PTSD and TBI when the client reported a time in which she “zoned out” while running errands. They explored the event, discussing duration and contextual details. It was in this conversation that the client mentioned a glass item having fallen nearby and shattering loudly just moments before she “zoned out.” From this detail, especially noting the infrequency of her zoning out day-to-day, the counselor discussed the likelihood of it being trauma-related, connecting it to the many nights of domestic disturbances with her abuser that ended in various household items being destroyed. On the other hand, the counselor associated her increased forgetfulness, headaches, and a distorted sense of smell with possible manifestations of brain injury. The counselor recommended that the client call the state’s brain injury association to learn about medical providers who had extensive experience treating TBI.
Noting shattering glass as one of her triggers, the counselor and client discussed what she could do after perceiving this stimulus to reorient to the present. Grounding techniques such as deep breathing were discussed. To address forgetfulness, the counselor implemented compensatory strategies that included shorter responses and questions, utilization of the present time frame, and repetition of responses provided by the counselor. To encourage further assessment and treatment, the counselor followed up on the client’s contact with experienced TBI medical professionals.
Clients may be involved in both individual and group counseling simultaneously. However, group counseling may be contraindicated for women who have experienced a TBI until social and relational challenges can be addressed in individual counseling (Mychasiuk et al., 2014). Therefore, before recommending entry into a counseling group, the counselor first assessed the client’s day-to-day interactions with individuals and how her social network changed before and after sustaining TBI. This assessment allowed the counselor an opportunity to both gauge the appropriateness of group therapy and identify possible barriers to group that might be assisted with accommodation. With careful consideration and assessment, counselors can maximize the use of group therapeutic factors such as interpersonal learning, socializing techniques, and imitative behavior.
Conclusion
PV is a prevalent public health issue that impacts the development of a wide range of mental and physical health diagnoses, in which PTSD and TBI are two pervasive complications that often affect survivors of IPV. Recent initiatives, such as the national briefing hosted by the Congressional Brain Injury Task Force, are indicative of the work still needed to properly address this underrepresented national issue (Brain Injury Association of America, 2017). Counselors should understand the intersectionality of PTSD and TBI and how such experiences can complicate treatment. This article has provided several suggestions for counselors to improve their clinical practice to better accommodate survivors of IPV, including screening and assessment techniques, therapeutic approaches, and communication suggestions. Counselors should be aware of the need to adopt specific therapeutic approaches and strategies in counseling that compensate for cognitive impairments so as to avoid gaps in the delivery of services and adhere to best treatment practices. Counselors also are required to abide by ethical codes and guidelines and are urged to continually seek supervision and consultation when working with this population to ensure that the various aspects of this complicated category of violence are thoroughly considered.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
References
American Counseling Association. (2014). 2014 ACA Code of ethics. Retrieved from https://www.counseling.org/resources/aca-code-of-ethics.pdf
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.
Association of Women’s Health, Obstetric and Neonatal Nurses. (2015). Intimate partner violence. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 44, 405–408. doi:10.1111/1552-6909.12567
Black, M. C., Basile, K. C., Breiding, M. J., Smith, S. G., Walters, M. L., Merrick, M. T., . . . Stevens, M. R. (2011). The National Intimate Partner and Sexual Violence Survey: 2010 Summary Report. Atlanta, GA: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention. Retrieved from https://www.cdc.gov/violenceprevention/pdf/nisvs_report2010-a.pdf
Block, C. K., & West, S. E. (2013). Psychotherapeutic treatment of survivors of traumatic brain injury: review of the literature and special considerations. Brain Injury, 27, 775–788. doi:10.3109/02699052.2013.775487
Boals, A., & Banks, J. B. (2012). Effects of traumatic stress and perceived stress on everyday cognitive functioning. Cognition and Emotion, 26, 1335–1343. doi:10.1080/02699931.2011.651100
Bourne, C., Mackay, C. E., & Holmes, E. A. (2013). The neural basis of flashback formation: The impact of viewing trauma. Psychological Medicine, 43, 1521–1532. doi:10.1017/S0033291712002358
Brain Injury Association of America. (2015). About brain injury: Concussion/Mild TBI. Retrieved from
http://www.biausa.org/mild-brain-injury.htm
Brain Injury Association of America. (2017, October 17). Briefing: The silent epidemic in America – brain injury and domestic violence. Retrieved from https://www.biausa.org/public-affairs/public-awareness/news/briefing-the-silent-epidemic-in-america-brain-injury-and-domestic-violence
Brain Injury Association of Virginia. (2010). Working with individuals with brain injury: A professional’s guide. Richmond, VA: Author.
Breiding, M. J., Basile, K. C., Smith, S. G., Black, M. C., & Mahendra, R. (2015). Intimate partner violence surveillance: Uniform definitions and recommended data elements. Retrieved from https://www.cdc.gov/violenceprevention/pdf/intimatepartnerviolence.pdf
Chapman, A., & Monk, C. (2015). Domestic violence awareness. American Journal of Psychiatry, 172, 944–945. doi:10.1176/appi.ajp.2015.15070853
Chard, K. M., Schumm, J. A., McIlvain, S. M., Bailey, G. W., & Parkinson, R. B. (2011). Exploring the efficacy of a residential treatment program incorporating cognitive processing therapy-cognitive for veterans with PTSD and traumatic brain injury. Journal of Traumatic Stress, 24, 347–351. doi:10.1002/jts.20644
Clark, C., Classen, C. C., Fourt, A., & Shetty, M. (2014). Treating the trauma survivor: An essential guide to trauma-informed care. New York, NY: Taylor and Francis.
Currie, S., Saleem, N., Straiton, J. A., Macmullen-Price, J., Warren, D. J., & Craven, I. J. (2016). Imaging assessment of traumatic brain injury. Postgraduate Medical Journal, 92, 41–50.
doi:10.1136/postgradmedj-2014-133211
Fedovskiy, K., Higgins, S., & Paranjape, A. (2008). Intimate partner violence: How does it impact major depressive disorder and post-traumatic stress disorder among immigrant Latinas? Journal of Immigrant and Minority Health, 10, 45–51. doi:10.1007/s10903-007-9049-7
Fúgate, M., Landis, L., Riordan, K., Naureckas, S., & Engel, B. (2005). Barriers to domestic violence help seeking: Implications for intervention. Violence Against Women, 11, 290–310.
Goldin, Y., Haag, H. L., & Trott, C. T. (2016). Screening for history of traumatic brain injury among women exposed to intimate partner violence. PM&R, 8(11), 1–7. doi:10.1016/j.pmrj.2016.05.006
Jeter, C. B., Hergenroeder, G. W., Hylin, M. J., Redell, J. B., Moore, A. N., & Dash, P. K. (2013). Biomarkers for the diagnosis and prognosis of mild traumatic brain injury/concussion. Journal of Neurotrauma, 30, 657–670. doi:10.1089/neu.2012.2439
Joshi, M., Thomas, K. A., & Sorenson, S. B. (2012). “I Didn’t Know I Could Turn Colors”: Health problems and health care experiences of women strangled by an intimate partner. Social Work in Health Care, 51, 798–814. doi:10.1080/00981389.2012.692352
Kimberley, T. J., Samargia, S., Moore, L. G., Shakya, J. K., & Lang, C. E. (2010). Comparison of amounts and types of practice during rehabilitation for traumatic brain injury and stroke. Journal of Rehabilitation Research & Development, 47, 851–861. doi:10.1682/JRRD.2010.02.0019
Krebs, C., Breiding, M. J., Browne, A., & Warner, T. (2011). The association between different types of intimate partner violence experienced by women. Journal of Family Violence, 26, 487–500.
doi:10.1007/s10896-011-9383-3
Kwako, L. E., Glass, N., Campbell, J., Melvin, K. C., Barr, T., & Gill, J. M. (2011). Traumatic brain injury in intimate partner violence: A critical review of outcomes and mechanisms. Trauma, Violence, & Abuse, 12(3), 115–126. doi:10.1177/1524838011404251
Lawson, D. M. (2003). Incidence, explanations, and treatment of partner violence. Journal of Counseling & Development, 81, 19–32. doi:10.1002/j.1556-6678.2003.tb00221.x
Lutenbacher, M., Cohen, A., & Mitzel, J. (2003). Do we really help? Perspectives of abused women. Public Health Nursing, 20, 56–64. doi:10.1046/j.1525-1446.2003.20108.x
Marotta, S. A. (2000). Best practices for counselors who treat posttraumatic stress disorder. Journal of Counseling & Development, 78, 492–495. doi:10.1002/j.1556-6676.2000.tb01933.x
McFadgion, A. (2013). Intimate partner violence and probable traumatic brain injury: Manifestations in the lives of abused women (Doctoral dissertation). Retrieved from ProQuest Dissertations Publishing. (Order No. 3613786)
McLaughlin, K. D. (2017). Ethical considerations for clinicians treating victims and perpetrators of intimate partner violence. Ethics & Behavior, 27, 43–52, doi:10.1080/10508422.2016.1185012
McLeod, A. L., Hays, D. G., & Chang, C. Y. (2010). Female intimate partner violence survivors’ experiences with accessing resources. Journal of Counseling & Development, 88, 303–310.
doi:10.1002/j.1556-6678.2010.tb00026.x
Murray, C. E., Lundgren, K., Olson, L. N., & Hunnicutt, G. (2016). Practice update: What professionals who are not brain injury specialists need to know about intimate partner violence-related traumatic brain injury. Trauma, Violence, & Abuse, 17, 298–305. doi:10.1177/1524838015584364
Mychasiuk, R., Hehar, H., Farran, A., & Esser, M. J. (2014). Mean girls: Sex differences in the effects of mild traumatic brain injury on the social dynamics of juvenile rat play behaviour. Behavioural Brain Research, 259, 284–291. doi:10.1016/j.bbr.2013.10.048
National Center on Domestic Violence, Trauma, & Mental Health. (2014). Current evidence: Intimate partner
violence, trauma-related mental health conditions & chronic illness. Retrieved from http://www.national
centerdvtraumamh.org/wp-content/uploads/2014/10/FactSheet_IPVTraumaMHChronicIllness_2014_Final.pdf
National Resource Center on Domestic Violence. (2012). DVAM history. Retrieved from http://www.nrcdv.org/dvam/DVAM-history
O’Leary, K. D., Tintle, N., & Bromet, E. (2014). Risk factors for physical violence against partners in the U.S. Psychology of Violence, 4, 65–77. doi:10.1037/a0034537
Pennsylvania Coalition Against Domestic Violence. (2011). Traumatic brain injury as a result of domestic violence: Information, screening and model practices. Harrisburg, PA: Fern Gilkerson.
Pill, N., Day, A., & Mildred, H. (2017). Trauma responses to intimate partner violence: A review of current knowledge. Aggression and Violent Behavior, 34, 178–184. doi:10.1016/j.avb.2017.01.014
Powers, R. A., & Kaukinen, C. E. (2012). Trends in intimate partner violence: 1980-2008. Journal of Interpersonal Violence, 27, 3072–3090. doi:10.1177/0886260512441077
Saar-Ashkenazy, R., Veksler, R., Guez, J., Jacob, Y., Shelef, I., Shalev, H., . . . Cohen, J. E. (2016). Breakdown of inter-hemispheric connectivity is associated with posttraumatic symptomatology and memory impairment. PLOS One, 11(2), 1–14. doi:10.1371/journal.pone.0144766
Scordato, M. M. (2013). Use of services by female survivors of intimate partner violence: In their own words (Doctoral dissertation). Retrieved from ProQuest Dissertations Publishing. (Order No. 3604177).
Shakespeare-Finch, J., Rees, A., & Armstrong, D. (2015). Social support, self-efficacy, trauma and well-being in emergency medical dispatchers. Social Indicators Research, 123, 549–565. doi:10.1007/s11205-014-0749-9
Sherrill, A. M., Bell, K. M., & Wyngarden, N. (2016). A qualitative examination of situational risk recognition among female victims of physical intimate partner violence. Violence Against Women, 22, 966–985. doi:10.1177/1077801215616706
Sillito, C. L. (2012). Physical health effects of intimate partner abuse. Journal of Family Issues, 33, 1520–1539. doi:10.1177/0192513X12448742
Smith, D. J., Mills, T., & Taliaferro, E. H. (2001). Frequency and relationship of reported symptomology in victims of intimate partner violence: The effect of multiple strangulation attacks. The Journal of Emergency Medicine, 21, 323–329. doi:10.1016/S0736-4679(01)00402-4
St. Ivany, A., & Schminkey, D. (2016). Intimate partner violence and traumatic brain injury. Family and Community Health, 39(2), 129–137. doi:10.1097/FCH.0000000000000094
Sugg, N. (2015). Intimate partner violence: Prevalence, health consequences, and intervention. Medical Clinics of North America, 99, 629–649. doi:10.1016/j.mcna.2015.01.012
Tramayne, S. R. (2012). Intimate partner violence as a risk factor for PTSD in female survivors of domestic violence: A meta-analysis (Doctoral dissertation). Retrieved from ProQuest Dissertations Publishing. (Order No. 3509648).
Utzon-Frank, N., Breinegaard, N., Bertelsen, M., Borritz, M., Eller, N. H., Nordentoft, M., . . . Bonde, J. P. (2014). Occurrence of delayed-onset post-traumatic stress disorder: A systematic review and meta-analysis of prospective studies. Scandinavian Journal of Work, Environment & Health, 40, 215–229. doi:10.5271/sjweh.3420
Villamar, M. F., Santos Portilla, A., Fregni, F., & Zafonte, R. (2012). Noninvasive brain stimulation to modulate neuroplasticity in traumatic brain injury. Neuromodulation: Technology at the Neural Interface, 15, 326–338. doi:10.1111/j.1525-1403.2012.00474.x
Zasler, N. D., Katz, D. I., & Zafonte, R. D. (2007). Brain injury medicine: Principles and practice. New York, NY: Demos Medical.
Zhou, X., Wu, X., Li, X., & Zhen, R. (2016). The role of posttraumatic fear and social support in the relationship between trauma severity and posttraumatic growth among adolescent survivors of the Yaan earthquake. International Journal of Psychology. doi:10.1002/ijop.12281
Zollman, F. S. (2016). Manual of traumatic brain injury: Assessment and management (2nd ed.). New York, NY: Demos Medical.
Trish J. Smith is a resident in counseling and a senior client services advocate at Safe Harbor Shelter in Richmond, Virginia. Courtney M. Holmes, NCC, is an assistant professor at Virginia Commonwealth University. Correspondence can be addressed to Trish Smith, Safe Harbor Shelter, P.O. Box 17996, Richmond, VA 23226, trish@safeharborshelter.com
Mar 30, 2018 | Volume 8 - Issue 1
Danielle Pester, A. Stephen Lenz, Joshua C. Watson, Julia Dell’Aquila, Anthony Nkyi
As the counseling profession continues its globalization onto Ghanaian college campuses, there is an increased need for psychometric assessments that support programming and interventions that promote degree matriculation and general student well-being. A sample of 696 young adult Ghanaian college students completed the Inventory of New College Student Adjustment (INCA) and related measures to estimate evidence of internal structure and relationships with conceptually related constructs. Confirmatory factor analyses were completed and inspection of fit indices revealed strong evidence for internal structure, and bivariate correlations indicated statistically significant positive associations with related medium effect sizes between the INCA subscales (Supportive Network and Belief in Self) and related measures. Implications for use of the INCA to support the professional activities of Ghanaian counselors working on college campuses are provided.
Keywords: Ghanaian counselors, college student adjustment, globalization, psychometric inventory, assessment
Higher education in Ghana has experienced tremendous growth over the past two decades, increasing access to institutions of higher education and student enrollment. In 2012, there were 138 accredited higher education institutions throughout Ghana, including public and private institutions, polytechnics, and training colleges (Atuahene, 2013; National Council for Tertiary Education [NCTE], 2014). This is an exponential degree of growth when compared to the existence of only three public universities in Ghana at the close of the 1990s (Atuahene, 2013). Although access and participation in university education has grown rapidly, the proportion of enrolled students versus those eligible to be enrolled remains low. According to the United Nations Educational, Scientific and Cultural Organization (2017), the percentage of enrolled students compared to those eligible to be enrolled in higher education in Ghana for 2015 was only 16.23%, indicating inadequate pre-college academic preparation, lack of affordability, low retention rates, and inadequate supports once enrolled (Atuahene, 2012). With its higher education system facing such challenges, resources and tools that can assist Ghanaian higher education institutions meet student needs as they enter university life, adjust to the unique set of demands, and access existing supports are imperative.
Because the demand for higher education in Ghana has traditionally been greater than its supply, most of the available resources have been focused on the expansion of facilities rather than the improvement of student experiences that may promote university persistence and degree matriculation. Only in recent years has the NCTE begun to rate institutions on the quality and relevance of their academic programs. Atuahene (2012) identified several distinctive factors associated with Ghanaian student dropout, including: (a) inadequate financial support for low income students, (b) student socioeconomic and geographic background, (c) student pre-college academic preparation, (d) unfavorable institutional policies and practices, and (e) a lack of academic advising. With these barriers in mind, there is currently an opportunity in Ghanaian higher education to develop resources that can support student adjustment and academic persistence.
Researchers (e.g., Carter, Locks, & Winkle-Wagner, 2013; Gray, Vitak, Easton, & Ellison, 2013; Pascarella & Terenzini, 2005; Robbins, Oh, Le, & Button, 2009) have found first-year adjustment to an academic setting to be a crucial component in student retention. Furthermore, they have found that positive adjustment within the first year of college can significantly impact a student’s academic persistence to degree completion. Andoh-Arthur, Asante, and Osafo (2015) studied the help-seeking behaviors of Ghanaian university students and found that the first-year student population was least likely to engage in help-seeking behaviors. They attributed this to the students’ unfamiliarity with their new identity as university students. Knowing this, Ghanaian students’ first year of university experience is a crucial time for university support personnel to proactively engage students regarding college adjustment issues. The capacity to identify new university students who are struggling to adjust to college life and who also may be at a higher risk for attrition is essential for Ghanaian university personnel as they seek to improve university retention rates.
Globalization of Counseling and Its Role in University Settings
The welcome statement of NBCC International proposes an organizational intention to increase the “availability of competent, reliable services to any part of the world that indicates an interest in acquiring them . . . with the utmost care and respect for the social, cultural, political, and economic realities of the various areas where we are invited” (Clawson, 2011, para. 2). Lorelle, Byrd, and Crockett (2012) identified the globalization of counseling as an inevitability, wherein professional counseling activities are progressively transitioning from a Western-based practice to one that gives international communities the opportunity for transformation as well. Lorelle et al. suggested that as the counseling profession is introduced on a local level, opportunities emerge for adaptation to local cultures and new contexts that yield new ways of understanding culturally defined standards of care. Among the many international settings adopting the values and activities synonymous with the counseling profession, Ghana appears poised to increase the capacity and scope of counseling activities through meaningful placement of services on university campuses.
Quarshie, Annor, Tagoe, Osei-Poku, and Andoh-Arthur (2016) identified a growing population of mental health professionals within the country of Ghana. This expansion of service provider capacity has been positively correlated with growth in the Ghanaian economy and represents a commitment to developing public mental health infrastructure using existing resources and expanding capacity over time (Ghana Health Professions Regulatory Bodies Act 857, 2013). Quarshie et al.’s (2016) analyses also detected that the majority of Ghanaian mental health professionals are housed on college, polytechnic, and university campuses. Situating these providers within these settings not only provides them support for their professional preparation programs, but also provides proximal contact with students who may be experiencing mental health symptoms while attempting to adjust to new demands within university settings. This action has important consequences for both the globalization of the counseling profession and the promotion of optimal development, degree matriculation, and access to a more equitable life for Ghanaian students. However, evidence-supported interventions require evidence-supported assessments that are population-specific, and currently there is a paucity of such assessments that can be utilized by mental health professionals to understand the adjustment experiences of students at Ghanaian universities.
Rationale and Purpose of the Study
Given that one aspect of counselor identity is the use of evidence-supported assessment practices, and another is evidence-supported intervention and programming (American Counseling Association, 2014; Lorelle et al., 2012), there is a call to complete activities to support the actions of Ghanaian mental health professionals charged with promoting adjustment among local university students. The Inventory of New College Student Adjustment (INCA; Watson & Lenz, 2017) is one viable instrument for assessing college student adjustment that is free to use and has yielded promising psychometric properties among ethnically diverse samples within the United States. It has been identified as a resource to help determine the appropriate support services needed for university students, as well as a resource to assess the overall effectiveness of campus initiatives focused on student adjustment. Although the INCA could be a valuable tool to address the current needs and trends in Ghanaian higher education, the degree of validity of INCA scores for a Ghanaian university student population is currently unknown. Therefore, the purpose of this study was to evaluate the transferability of validity evidence for scores on the INCA to a sample of Ghanaian students. Specifically, we intended to identify the degree of evidence related to internal structure of the INCA scores and their relationships with conceptually related variables.
Method
Participant Characteristics
Six hundred ninety-six Ghanaian college students (435 male [63%], 237 female [34%], 24 did not report gender [3%]), the majority of whom were young adults (M age = 22.45 years; SD = 4.37) completing undergraduate coursework at one large university in Ghana, Africa, participated in this study.
Measurement of Constructs
Inventory of New College Student Adjustment. The INCA (Watson & Lenz, 2017) was developed to assess the adjustment difficulties experienced by first-year college students and was normed using an ethnically diverse sample of 474 freshmen students in the United States. The INCA is a 14-item instrument using a 4-point Likert scale to assess participant responses from 1 (strongly disagree) to 4 (strongly agree). Scores can range from 14 to 56, with higher scores indicating higher levels of college adjustment. The 6-item Supportive Network subscale includes items such as “My friends support me as I work toward my goals” and “My family’s support makes me feel stronger.” The 8-item Belief in Self subscale includes items such as “My study habits are effective” and “I know what I will do after graduation.” Initial psychometric testing demonstrates good alpha reliability coefficients for scores on INCA subscales ranging from .77 (Belief in Self) to .83 (Supportive Network), indicating good internal consistency. Moreover, our sample reported alpha reliability coefficients of .74 for both the Belief in Self subscale and the Supportive Network subscale.
The Multidimensional Scale of Perceived Social Support. The Multidimensional Scale of Perceived Social Support (MSPSS; Zimet, Dahlem, Zimet & Farley, 1988) was developed to assess an individual’s perception of social support from family, friends, and significant others. Each of these sources of social support is considered a distinct subgrouping and is assessed individually. The MSPSS was normed using a subject pool of 275 undergraduate students in the United States with a nearly equal sample of male and female students (Zimet, et al., 1988). After further psychometric testing, reliability has been established for diverse samples beyond the original norming group (Stanley, Beck, & Zebb, 1998). The MSPSS is a 12-item instrument using a 7-point Likert-scale to assess participant responses from 1 (very strongly disagree) to 7 (very strongly agree). Scores can range from 12 to 84, with higher scores representing higher levels of perceived social support. For the purposes of this study, we used the Family Relationships subscale and Relationships with Friends subscale. The 4-item Family Relationships subscale includes items such as “My family really tries to help me” and “I get the emotional help and support I need from my family.” The 4-item Relationships with Friends subscale includes items such as “My friends really try to help me” and “I can count on my friends when things go wrong.” Zimet et al. (1988) reported high Cronbach’s alpha coefficients for scores on MSPSS subscales ranging from .85–.91, indicating good internal consistency. The reliability of the total scale for the initial sample was .88. Additionally, our sample reported coefficients ranging from .81 for the Family Relationships subscale and .88 for the Relationships with Friends subscale.
College Self-Efficacy Inventory. The College Self-Efficacy Inventory (CSEI; Solberg, O’Brien, Villareal, Kennel, & Davis, 1993) was developed to assess a student’s confidence in their ability to successfully complete college-related tasks. Originally developed to measure college self-efficacy in Hispanic college students, CSEI data has established reliability beyond the initial norming population to also include ethnically diverse college students (Gore Jr., Leuwerke, & Turley, 2005). The CSEI is a 20-item instrument using a 10-point scale to assess a participant’s confidence in their ability to successfully complete a task from 1 (not at all confident) to 10 (extremely confident). Scores can range from 20 to 200, with higher scores indicating higher levels of confidence in one’s ability to successfully complete college-related tasks. The 20-item scale includes items such as “Make new friends at college,” “Talk to university staff,” and “Take good class notes” (Barry & Finney, 2009). Gore et al. (2006) reported Cronbach’s alpha coefficients for scores on the CSEI subscales ranging from .62–.89. The reliability of the CSEI for the initial sample was .93 (Solberg et al., 1993). Additionally, we observed a Cronbach’s alpha coefficient of .88 for our sample.
Procedure
After ethical review board approval, students registered in classes at one large university in Ghana were asked to participate in this study. A survey administrator, who was not the course instructor, shared the opportunity to participate in this study with students and disseminated an information sheet explaining the purpose, processes, and voluntary nature of the study. After having time to review the information sheet, the students choosing to participate in the study were given a packet including a demographic questionnaire, the INCA, the MSPSS, and the CSEI. All measures except for the demographic questionnaire were counter-balanced in an effort to control for random responding, order effect, and fatigue. Participants filled out hard copy surveys in class and turned them in to the survey administrator, who supplied them to the authors. Participant answers to the survey packet were entered into an SPSS spreadsheet. After all data was documented, the original hard copy surveys were securely destroyed.
Data Analysis
Statistical power analysis. We conducted a power analysis to determine the suitability of our sample size for identifying model fit using the criteria outlined by Stevens (2009): n/p ≥ 30. Using this standard, our largest scale (Belief in Self), consisting of eight items, would necessitate a sample size of at least 240. With a sample size of 696 (i.e., 87 participants per item), we considered our sample size sufficient for making statistical inferences about model fit. We also acknowledge that this model is over-powered for hypothesis testing and may lead to type I error. Therefore, when interpreting analyses, a greater emphasis was placed on model fit indices over p-values for χ2 tests.
Preliminary data analysis. The dataset was analyzed for missing values prior to performing statistical analyses. A small percentage of missing values (684 out of 71,100; .009%) was detected, but no identifiable pattern within these absent values was present. We used the series mean imputation function in IBM SPSS, Version 23, to replace all missing values.
Evidence regarding internal structure. We analyzed model fit for the INCA subscales using the SPSS Analysis of Moment Structures Software, Version 22. We conducted our analyses of the INCA subscale factor structures based on the initial factor structure emerging from the analyses completed by Watson and Lenz (2017). Initially, we interpreted the C-minimum/degrees of freedom (CMIN/DF), p-values, root mean residual (RMR), goodness of fit index (GFI), comparative fit index (CFI), Tucker-Lewis index (TLI), and root mean square error of approximation (RMSEA) metrics of model fit. Standards presented by Dimitrov (2012) were used to interpret these values with criteria for a strong model fit represented by CMIN/DF < 2, p > .05, RMR < .08, GFI > .90, CFI > .90, TLI > .90, and RMSEA < .10. When model fit proved inconsistent with these standards, modification indices were evaluated to determine items with potential covaried error. Covarying items provides a scenario within the factorial model wherein two items share their assumed variance. If such instances were identified, the model was computed again to re-inspect fit indices. If a factor model continued to have an inadequate fit, we inspected individual item correlation loadings and considered items for removal from the model. Items were removed if correlation coefficients were found to be less than .70.
Evidence regarding relationships with conceptually related constructs. Bivariate correlations were computed between scores on the INCA, MSPSS, and CSEI to depict degree of convergent validity between scores on the INCA subscales (Supportive Network and Belief in Self) with conceptually related constructs of perceived social support and academic self-concept, via the MSPSS and CSEI, respectively. Pearson’s correlation coefficients were interpreted as small (.10), medium (.30), or large (.50) based on the conventions reported by Swank and Mullen (2017) and evaluated at the .05 level of statistical significance.
Results
All alpha coefficients, descriptive statistics, and bivariate correlations for variables included within the analyses can be found in Table 1.
Table 1
Alpha Coefficients, Descriptive Statistics, and Bivariate Correlations for Variables Included Within Analyses.
| Scale-Construct |
α |
M |
SD |
1 |
2 |
3 |
| INCA – Belief in Self |
.74 |
23.31 |
3.32 |
44* |
|
.34* |
|
INCA – Supportive Network |
.74 |
17.44 |
2.65 |
.44* |
|
|
1. MSPSS – Family Relationships |
.88 |
20.02 |
6.49 |
|
|
|
2. MSPSS – Relationships with Friends |
.81 |
16.70 |
5.91 |
|
|
|
3. CSEI – College Self-Efficacy |
.88 |
36.77 |
14.69
|
|
|
| Note. * indicates statistical significance at .01 level |
Evidence Regarding Internal Structure
INCA – Belief in Self. The primary analysis of the Belief in Self subscale was significant for the hypothesized model, χ2(20) = 124.51, p < .01, and was suggestive of an unacceptable fit for the data: CMIN/DF = 6.22, RMR = .02, GFI = .95, CFI = .88, RMSEA = .08. After deleting item 6 and pairing the error terms for items 2 and 5 (“Past experiences help me cope with the demands of university life” and “Challenging courses make me a better student”) and 3 and 4 (“I believe I handle adversity well” and “My classmates value my opinions”), a good model fit emerged for scores on the Belief in Self subscale: χ2(12) = 28.58, p < .01. This finding was additionally supported by the fit indices: CMIN/DF = 2.38, RMR = .01, GFI = .98, CFI = .98, RMSEA = .04. Inspection of the alpha coefficient for scores for this sample (α = .74) was within the good range, indicating an acceptable degree of consistency and precision suitable for social sciences research activities.
INCA – Supportive Network. The primary analysis of the Supportive Network subscale was significant for the hypothesized model, χ2(9) = 102.28, p < .01, and was suggestive of an unacceptable fit for the data: CMIN/DF = 11.37, RMR = .03, GFI = .95, CFI = .80, RMSEA = .12. After pairing error terms for items 1 and 3 (“My friends support me as I work toward my goals” and “My friends help me to grow in important ways”) and items 4 and 6 (“My family’s support makes me feel stronger” and “I can be real with at least a few of my friends”), a good model fit emerged for scores on the Supportive Network subscale: χ2(7) = 14.03, p = .08. This finding was additionally supported by the fit indices: CMIN/DF = 3.41, RMR = .01, GFI = .98, CFI = .96, RMSEA = .05. Inspection of the alpha coefficient for scores for this sample (α = .74) was within the marginal range, indicating an acceptable degree of consistency and precision suitable for social sciences research activities.
Evaluation of Conceptually Related Measures
Family Relationships. The primary analysis of the Family Relationships subscale of the MSPSS was significant for the hypothesized model, χ2(2) = 45.47, p < .01, and was suggestive of an unacceptable fit for the data: CMIN/DF = 22.73, RMR = .10, GFI = .96, CFI = .97, RMSEA = .17. After pairing the error terms for items 3 and 4 (“I can talk about my problems with my family” and “My family is willing to help me make decisions”) a good model fit emerged for scores on the Family Relationships subscale: χ2(1) = 9.21, p <.01. This finding was additionally supported by the fit indices: CMIN/DF = 9.21, RMR = .04, GFI = .99, CFI = .99, RMSEA = .10. Inspection of the alpha coefficient for scores for this sample (α = .88) was within the good range, indicating an acceptable degree of consistency and precision suitable for social sciences research activities.
Relationships with Friends. The primary analysis of the Relationships with Friends subscale of the MSPSS was significant for the hypothesized model, χ2(2) = 49.52, p < .01, and was suggestive of an unacceptable fit for the data: CMIN/DF = 24.76, RMR = .15, GFI = .96, CFI = .95, RMSEA = .18. After pairing the error terms for items 1 and 2 (“My friends really try to help me” and “I can count on my friends when things go wrong”), a good model fit emerged for scores on the Relationships with Friends subscale: χ2(1) = 1.43, p = .23. This finding was additionally supported by the fit indices: CMIN/DF = 1.43, RMR = .02, GFI = .99, CFI = 1, RMSEA = .02. Inspection of the alpha coefficient for score for this sample (α = .81) was within the good range, indicating an acceptable degree of consistency and precision suitable for social sciences research activities.
College Self-Efficacy. The primary analysis of the College Self-Efficacy subscale of the CSEI was significant for the hypothesized model, χ2(9) = 66.70, p < .01, and was suggestive of an unacceptable fit for the data: CMIN/DF = 7.41, RMR = .34, GFI = .97, CFI = .98, RMSEA = .09. After pairing the error terms for items 1 and 2 (“Manage time effectively” and “Research a term paper”) and 3 and 5 (“Do well on your exams” and “Understand your textbooks”), a good model fit emerged for scores on the College Self-Efficacy subscale: χ2(7) = 22.45, p <.01. This finding was additionally supported by the fit indices: CMIN/DF = 3.20, RMR = .10, GFI = .98, CFI = .99, RMSEA = .05. Inspection of the alpha coefficient for scores for this sample (α = .88) was within the good range, indicating an acceptable degree of consistency and precision suitable for social sciences research activities.
Evidence Regarding Relationships With Conceptually Related Constructs
Bivariate correlation analysis of scores on the INCA Belief in Self subscale and CSEI resulted in a statistically significant positive relationship (r = .34, p < .01) indicative of a medium effect size. The correlation analysis of scores on the INCA Supportive Network subscale and MSPSS Family Relationships and Relationships with Friends subscales also resulted in statistically significant positive relationships (r = .448, p < .01, r = .448, p < .01, respectively) indicative of medium effect sizes. The strong positive relationships between scores on the two INCA subscales and conceptually related constructs are suggestive of support for convergent validity wherein the scores on the INCA tended to increase while scores on related measures increased too. Taken together, students who reported a greater belief in self also tended to report a greater sense of college self-efficacy. Similarly, participants who reported a greater belief in self during the first year of transition to college life also tended to report higher scores, indicating strong relationships with friends and family.
Discussion
The purpose of this study was to evaluate the validity evidence for the INCA using a Ghanaian college student population, with the hope that the instrument could be used by mental health professionals working in Ghanaian universities. Given the robust nature of our findings, we are heartened by the potential for the INCA and other emerging assessments to contribute to evidence-supported practices for optimal development and adjustment among students at Ghanaian universities. In light of our findings, several considerations warrant discussion.
Foremost, the INCA has potential uses that could address some of the most prominent issues facing higher education in Ghana today, particularly low matriculation rates. As the NCTE begins to rate institutions on the quality and relevance of their academic programs, the INCA can be used by university personnel to assess student adjustment so that necessary changes to student affairs programming can be made to improve the adjustment experiences of Ghanaian college students. Specifically, the INCA can be used by university personnel to gain a better understanding of the adjustment experiences of their first-year college students. This understanding can have important implications for program development at Ghanaian higher education institutions. As university personnel better understand the adjustment experiences of their first-year students, they can create programs that are more specialized to meet the needs of the Ghanaian student population, improve retention rates, and increase matriculation. Such activities have auspicious implications for not only promoting optimal development proximally, but encouraging access to a more equitable life, one characterized by fewer disparities than individuals within the emerging Ghanaian economy who do not have similar educational preparation and training.
Additionally, scores on the INCA can support early identification of first-year students who are struggling to adjust to university life. Because first-year students are least likely to engage in help-seeking behaviors (Andoh-Arthur et al., 2015), university personnel can develop proactive strategies to support struggling students and provide psychoeducation about the benefits of help-seeking behaviors. Such activities may include designing early detection protocols within orientation activities or integrating screening and referral within initial coursework activities.
In the cases of both program development and early identification, scores on the INCA have potential for evaluating outcomes in a manner that is culturally valid to a reasonable degree. Thus, the quantification of intervention outcomes by student affairs programmers and mental health professionals can provide an impetus for further understanding their students’ needs and the best strategies for meeting them. This is an important consideration in an era wherein Ghanaian mental health professionals are leveraging existing resources while extending their scope of influence within an emerging sociopolitical climate, which has expanded professional counseling activities through legislative action (Ghana Health Professions Regulatory Bodies Act 857, 2013). It is reasonable to conjecture that through the use of the INCA and other emerging assessments, the utilization and extension of personnel resources can not only be data-driven, but data-justified as well.
Finally, as the globalization of the counseling profession continues to be cultivated worldwide, it is important that counselors in international settings have valid psychometric tools that are population specific. Validation activities, such as the INCA project reported here, provide psychometrically robust assessments that Ghanaian mental health professionals can add to their growing corpus of resources. Although the use of assessment-based programming and outcome measurement do not define the whole of a counselor’s professional identity, it is a critical feature (American Counseling Association, 2014; Lorelle et al., 2012). Therefore, as the INCA and other assessments continue to be validated with Ghanaian student populations, the professionalization of Ghanaian mental health professionals grows lockstep.
Limitations and Recommendations for Future Research
Some important limitations and related recommendations for future research are indicated. First, although we sampled almost 700 Ghanaian students, the scope of our participant sample was limited to one campus. Therefore, we regard our findings as preliminary and most relevant to the student body from which they were affiliated. While it is reasonable that a substantial degree of validity generalization may be present, future studies completed at other Ghanaian universities are needed to estimate the transferability of INCA scores across regions. Second, internal consistency of INCA scores (α) were within the acceptable range (.70–.80), yet they did not reach a level that would warrant use for high stakes decision-making, such as program eligibility or dismissal. Further research evaluating content-oriented evidence (Lambie, Blount, & Mullen, 2017), cognitive processing, and response processes (Peterson, Peterson, & Powell, 2017) of INCA items and scores is needed to identify variables that may influence the reliability of items. It is possible that because INCA factors were developed from a Western theory of student adjustment, that consistency may be affected and indicative that some modification of item wording may be warranted (Lenz, Soler, Dell’Aquila, & Uribe, 2017). Thus, further evaluation related to cross-cultural adaptation and representation of constructs consisting within Ghanaian culture is warranted. Finally, this study only reported two sources of validity evidence. Although evidence across all sources of validity would not necessarily imply that INCA is inherently useful (Lenz & Wester, 2017), future research that elucidates INCA features associated with construct irrelevance and underrepresentation would further promote responsible testing and evaluation practice (Spurgeon, 2017).
Conclusion
In conclusion, this study evaluated the transferability of validity evidence for scores on the INCA to a sample of Ghanaian college students. The findings suggest the INCA is a valid psychometric assessment that has the potential to contribute to evidence-supported practices for optimal development and adjustment among students at Ghanaian universities. Specifically, the INCA can be used by Ghanaian university personnel to assess student adjustment, make any necessary changes to student affairs programming to improve the adjustment experiences of their college students, identify first-year students who are struggling to adjust to university life, and develop proactive strategies to support struggling students. Although initial results are promising, continued research is needed to validate the INCA at various universities across Ghana to continue to determine its degree of generalizability.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
References
American Counseling Association. (2014). 2014 ACA code of ethics. Retrieved from https://www.counseling.org/resources/aca-code-of-ethics.pdf
Andoh-Arthur, J., Asante, K. O., & Osafo, J. (2015). Determinants of psychological help-seeking intentions of university students in Ghana. International Journal for the Advancement of Counselling, 37, 330–345.
Atuahene, F. (2012). The impact of “tuition-paying” policy on retention and graduation rates at the University of Ghana. Journal of College Student Retention: Research, Theory & Practice, 14, 37–65.
Atuahene, F. (2013). Charting higher education development in Ghana: Growth, transformations, and challenges. In A. W. Wiseman & C. C. Wolhuter (Eds.), The development of higher education in Africa: Prospects and challenges (pp. 215–263). Bingley, UK: Emerald Group Publishing Limited.
Barry, C. L., & Finney, S. J. (2009). Can we feel confident in how we measure college confidence? A psychometric investigation of the College Self-Efficacy Inventory. Measurement and Evaluation in Counseling and Development, 42, 197–222. doi:10.1177.0748175609344095
Carter, D. F., Locks, A. M., & Winkle-Wagner, R. (2013). From when and where I enter: Theoretical and empirical considerations of minority students’ transition to college. In M. B. Paulson (Ed.), Higher education: Handbook of theory and research (Vol. 28; pp. 93–149). New York, NY: Agathon Press.
Clawson, T. W. (2011). Welcome to NBCC International. Retrieved from http://www.nbccinternational.org/Who_we_are/Welcome_Message
Dimitrov, D. M. (2012). Statistical methods for validation of assessment scale data in counseling and related fields. Alexandria, VA: American Counseling Association.
Ghana Health Professions Regulatory Bodies Act 857. (2013). Accra, Ghana: Ghana Publishing Company Limited, Assembly Press. Retrieved from http://www.pcghana.org/wp-content/uploads/2017/02/Health-
Professions-Regulatory-Bodies-Act.pdf
Gore Jr., P. A., Leuwerke, W. C., & Turley, S. E. (2005). A psychometric study of the College Self-Efficacy Inventory. Journal of College Student Retention: Research, Theory & Practice, 7, 227–244.
doi:10.2190/5CQF-F3P4-2QAC-GNVJ
Gray, R., Vitak, J., Easton, E. W., & Ellison, N. B. (2013). Examining social adjustment to college in the age of social media: Factors influencing successful transitions and persistence. Computers & Education, 67,
193–207. doi:10.1016/j.compedu.2013.02.021
Lambie, G. W., Blount, A. J., & Mullen, P. R. (2017). Establishing content-oriented evidence for psychological assessments. Measurement and Evaluation in Counseling and Development, 50, 210–216.
doi:10/1080/07481756.2017.1336930
Lenz, A. S., Soler, I. G., Dell’Aquila, J., & Uribe, P. M. (2017). Translation and cross-cultural adaptation of assessments for use in counseling research. Measurement and Evaluation in Counseling and Development, 50, 224–231. doi:10.1080/07481756.2017.1320947
Lenz, A. S., & Wester, K. L. (2017). Development and evaluation of assessments for counseling professionals. Measurement and Evaluation in Counseling and Development, 50, 201–209. doi:10.1080/07481756.2017.1361303
Lorelle, S., Byrd, R., & Crockett, S. (2012). Globalization and counseling: Professional issues for counselors. The Professional Counselor, 2, 115–123. doi:10.15241/sll.2.2.115
National Council for Tertiary Education. (2014). Annual report 2014. Retrieved from http://ncte.edu.gh/images/pdf/annual%20report%202014.pdf
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: Volume 2: A third decade of research. San Francisco, CA: Jossey-Bass.
Peterson, C. H., Peterson, N. A., & Powell, K. G. (2017). Cognitive interviewing for item development: Validity evidence based on content and response processes. Measurement and Evaluation in Counseling and Development, 50, 217–223. doi:10.1080/07481756.2017.1339564
Quarshie, E. N. B., Annor, F., Tagoe, T., Osei-Poku, E., & Andoh-Arthur, J. (2016). Psychologists in Ghana: Analysis of the standing register. New Voices in Psychology, 12, 55–69.
Robbins, S. B., Oh, I. S., Le, H., & Button, C. (2009). Intervention effects on college performance and retention as mediated by motivational, emotional, and social control factors: Integrated meta-analytic path analyses. Journal of Applied Psychology, 94, 1163–1184. doi:10.1037/a0015738
Solberg, V. S., O’Brien, K., Villareal, P., Kennel, R., & Davis, B. (1993). Self-efficacy and Hispanic college students: Validation of the College Self-Efficacy Instrument. Hispanic Journal of Behavioral Sciences, 15, 80–95. doi:10.1177/07399863930151004
Spurgeon, S. L. (2017). Evaluating the unintended consequences of assessment practices: Construct irrelevance and construct underrepresentation. Measurement and Evaluation in Counseling and Development, 50, 275–281. doi:10.1080/07481756.2017.1339563
Stanley, M. A., Beck, J. G., & Zebb, B. J. (1998). Psychometric properties of the MSPSS in older adults. Aging & Mental Health, 2, 186–193. doi:10.1080/13607869856669
Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). New York, NY: Routledge.
Swank, J. M., & Mullen, P. R. (2017). Evaluating evidence for conceptually related constructs using bivariate correlations. Measurement and Evaluation in Counseling and Development, 50, 270–274.
doi:10.1080/07481756.2017.1339562
United Nations Educational, Scientific and Cultural Organization. (2017). Ghana. Retrieved from http://uis.unesco.org/en/country/gh?theme=education-and-literacy
Watson, J. C., & Lenz, A. S. (2017). Development and evaluation of the Inventory for New College Student Adjustment. Manuscript submitted for publication.
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52, 30–41. doi:10.1207/s15327752jpa5201_2
Danielle Pester is a doctoral student at Texas A&M University-Corpus Christi. A. Stephen Lenz is an associate professor at Texas A&M University-Corpus Christi. Joshua C. Watson, NCC, is a professor at Texas A&M University-Corpus Christi. Julia Dell’Aquila is a doctoral student at Texas A&M University-Corpus Christi. Anthony Nkyi is a lecturer at the University of Cape Coast. Correspondence can be addressed to Danielle Pester, 6300 Ocean Drive, Corpus Christi, TX 78412, danielle.pester@tamucc.edu.
