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There has been a universal growing concern over the mental health of students attending university. Studies have shown that students in higher education are among the most frequent population diagnosed with severe mental health problems such as substance misuse, severe depression, eating disorder suicidal and non-suicidal self-harm (Pedrelli, Nyer, Yeung, Zulauf, & Wilens, 2015). This shows how important mental health is in student’s academic performance and understanding this relationship could be useful in developing a lot of approaches that higher education settings can apply to support students. Longitudinal research presented significant empirical evidence that interventions that reinforce social, emotional and decision-making abilities effectively influenced students’ academic performance (Fleming, Haggerty, Catalano, Harrachi, Mazza & Gruman, 2005). However, there’s a gap on mental health research and academic disparity among ethnicities, which this study aims to cover. For example, in United Kindgom (UK) and the United States of America (USA), black ethnic minority students have reported being marginalized and susceptible to racism (National Union of Students, 2012; Harper, 2013). This is most likely to have an adverse effect on students’ mental health and academic performance and numerous studies have reported that ethnic minority students tend to attain lower university accomplishments than their white colleagues (Equality Challenge Unit, 2012).
Academic performance and mental health were discussed since these play a major role in every university student’s life. Academic performance is perceived as a primary stressor for students (Monk, 2004), and a significant relationship between academic performance and mental health has been found in previous literature (Greenberg, Weissberg, O Brien, Zins, Fredericks et al., 2003; Zins, 2004). For instance, the National Union of Students (2013) reported that twenty percent of students claim to have psychological problems. Farrer et al. (2015) argues that this has largely been associated with academic stressors. Research on this discourse support this and claims that there is a critical mental health situation in higher education. For example, the American Psychiatric Association introduced consultants to College Mental Health in 2005 to give advice and develop studies and treatment strategies (Kadison and Digeronimo, 2004; Macaskill 2012). Mental health remains at the forefront as National Epidemiological Research carried out in USA reported that nearly half of the students evaluated met the criteria for mental disorder, however, only twenty-five percent of those evaluated looked or wanted medical care. Furthermore, they reported that there was no significant difference in the ratio for college students and non-students (Blanco, Okuda, Wright, Hasin, Grant et al., 2008). In addition, research carried out in the United Kingdom by the UK Psychiatric Morbidity Survey showed a compelling increase in anxiety and depression in young people between the age of 16-24, although it did not establish that it was students in this researched population (Singleton and Lewis, 2001). There is a considerable gap in research findings on confirmed measure of mental disorder in the UK university student population (Royal College of Psychiatrists, 2011) stated this in their report review. Additionally, the UK Royal College of Psychiatrists, (2003; 2011) made a prediction that the severity of psychiatric disorders would increase due to the British government prompting a large number of students from extensive sectors of society to go to university and also increasing financial demands on students because of the government cutting off students’ funds (Macaskill, 2012). The UK Royal College of Psychiatrists (2011) argued that in the past, in the UK most people who attended university came from economically privileged backgrounds and they were academic elites. In their research, ensured family support was a big factor and reduced students’ exposure to develop mental health issues at university. Stanley, Mallon, Bell, Hilton, & Manthrope (2015) support this as he argues that this growing level of serious mental health problems among university students is caused by inadequate economic and human resources accessible within the higher education environment. Furthermore, Renaud et al., (2014) suggests that necessities for higher education students’ mental health are constantly not met, thus causing adverse effects of intensified levels of suicide and mental health illness. Additionally, University Counselling Services have reported a growing number of students with severe mental disorders in their referrals (Association for University and College Counselling, 2011). The present study aims to investigate the relationship between mental health and academic performance amongst black ethnic minority and white students.
Mental health is interpreted in numerous way which are signified by contrast of cultures, appraisal, area of subjective and professional theory. For example, Parameshvara (2010) describes mental health generally as a perfect state of mind made up of not only the absence of illness but also the existence of elements like life satisfaction, self acceptance and one’s social contributions which is basically anything an individual does in an attempt to better the community. However, the World Health Organisation (WHO) provide a definition on young adults’ mental health claiming mental health as, “A state of well-being in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community” (WHO, 2007). It is evident that both definitions employ the notion of an individual being able to accomplish a task efficiently (assigned university work) thus, a noted association between mental health and academic performance. Furthermore, Ghani (2013) defines mental health as a thriving state in which a person is conscious of their competency; are able to work under pressure, and are capable of contributing to society. All in all, although mental health interpretations vary they all have a correspondence between them. For instance, many definitions do acknowledge that mental health is made up of elements of emotion, rational reasoning and the capacity to accomplish things efficiently. This literature review on mental health aims to emphasis the significance of mental health as well as present the risks of its inadequacy and review common constructs of mental health. The deficit of mental health effect several risks and, thus, the likelihood of mental disorder developing, (Stead, 2010; Chan, 2009). Contradictory to the popular concept that mental health disorder is the inadequacy of mental health, studies show that there is a relationship between theories but however they differentiate from one another (WHO, 2012; Keyes, 2005).
Research shows that mental health is vital for maintaining a healthful living and that human being who experience mental health disorders are encourage to seek help (Satcher, 2000). Findings reported by WHO (2012) suggests that the absence of mental wellness, which is cited with the terminology “mental illness “, can also have critical adverse effect on an individual. In most western countries, 20 percent of illnesses are mostly accounted for by mental illnesses, and amongst the leading countries with high suicide rate, 9 countries are within European domain. Discourse supports this data with regards to the student population as well. For example, in 2011, a study carried out in the US by the American College Association showed that 1.1 percent of the student participants disclosed that they had attempted suicide in the past year (American College Health Association, 2012), this meets the criterion of mental health symptoms described in the diagnostic manual of mental health disorder (DSM-5) (APA, 2014). Suicide is usually caused by depression, a mental illness and the dominant motivator for young people’s disabilities (WHO, 2012; Izadinia, Amiri, Jahromi, & Hamidi, 2010), therefore it can be understood to be an adverse effect on mental health. Furthermore, WHO also argues that poor mental health well-being is associated with poor academic performance, eating disorders, temperament disorders substance misuse etc. (WHO, 2012; Buckelew et al. 2008). Their findings showed that 10 to 20 percent of young adults’ experience mental health issues at some time in their lives (WHO, 2012). There are multiple genetic, biomedical and social elements that determine whether a person develops mental issues.
Ingram and Luxon (2005) diathesis stress model summaries mechanisms that genetic, biological, mental and societal susceptibilities relate with stressors to develop the possibility of mental health happening. Though, protective factors may change how people handle stressors they experience and these defensive characteristics help to inhibit the development of mental illness even with the existence of diathesis (Rutter, 2001; 2007). Individual characteristics such as high confidence, academic performance, intelligence and personality, together with good support system like family, friends etc. are examples of protective factors (Macaskill, 2012). With regards to mental health constructs, literature review shows that, Watson (1991) establishing a mental health model that demonstrated that depression, anxiety and stress are the primary factors of mental health and these factors have been found to overlay among each other (Clack, 1989). Other models have also been formulated to assess mental health and preliminary data that indicated that depression, anxiety and stress carry acceptable convergent and divergent validity (Crawford, 2003). The establishment of mental health models has assisted researchers confirm and enhance the comprehension of mental health issues development, because without comprehension of this issue, it would have been harder to understand the fluctuation of mental health across university settings. Existing studies have common findings that acknowledge stress to be the leading problem, impacting approximately a third of the student population (33.9%), followed by depression and anxiety, or short-term affective illness affecting 16.1% of students, substance misuse was also claimed to affect 7.8% of students (Crawford, Burns, Chin, Hunt, Tilley et al., 2015). Stress is described as an individual’s reaction to conditions or events that endanger the ability to adapt to those circumstances (Madzhie, 2015). The two most frequent causes of stress that has been reviewed in existing literature are, temporary academic stress which is usually experienced by students before or during exam season, or near the deadline of assigned work, the second cause of stress is the long-term stress is the one which associates with the students’ transition into becoming independent (Loudlaw, McLellan and Ozakina, 2015), though Mazo (2015) object that stress is a standard part of life that cannot be fully prevented. This might be true to a greater extent but still its adverse impact on academic performance cannot be dismissed because of its normality but rather be researched more so that measures can be put in place to support students and reduce effects of stress as it has been indicated to lead to depression if it persists (Richard, Ratner, Sawatzky, Washburn, Sudmant et al., 2012).Depression is recognised as a complex problem that causes deterioration in interpersonal, social, and occupational performance (Sadock and Sadock, 2007). Anxiety is defined as an intuitive consciousness of mental stress, fear, distress and apprehensiveness related with stimulation of the nervous system ( Sevincer, Ezgi , Taymur and Konuk , 2016).According to research, the primary stressors amongst the student population was mainly of university or school concerns of assigned work (77%), or grades (74%), subsequently, financial pressures (64%) (Associate Press, 2009). Perhaps this explains why students’ mental health issues in the UK have been growing, with the government cutting higher education funds which means that students’ experience is limited in a way that makes mental issues amongst the university student population, because by doing so the government eliminates one of the protective factors (Macaskill, 2012). In addition, being anxious of academic underachievement is perceived as one of the factors that effect stress and depression in students (Kolko, 1980). Research also supports this notion that stress frequently move among students particularly in the academic prospects, assigned work, and financial issues (Shamsuddin, Fadzil, Ismail, et al 2013). This shows that stress, anxiety and depression are the dominant causal factors of students’ mental health and should be fixed to improve their academic performance and well-being. A study carried out by the Associate Press (2009) indicated the risks of stress as 85% of the student population expressed that they encounter stress in their everyday lives. Furthermore, the extensive consequences of stress are confirmed with the following findings, 69% of students stated that they had insufficient energy and felt tired; 55% had sleeping problems; 45% noticed a change in their eating tendencies; 42% felt low, depressed and hopeless, and 13% revealed that they had been diagnosed with a mental disorder (Associate Press, 2009). However, depression has also been found to a major component associated with academic performance (ACHA, 2012).
Research has shown that depression has been a prevalent issue among university students (Lyubomirsky, Kasri and Zehm, 2003; Walkiewicz, Tartas, Majkowicz and Budzinski, 2012). Studies also show that depression in students has remained persistent over the past years, for example, research done by Sherina, Rampal and Kason (2003) revealed that 41,9% of students who attended a public school were experiencing depression. Similarly, data presented by Goebert, Thompson, Bryson, Kent, Tate et al., (2009) and Vazquez, Torres, Blanco, Diaz, Otero et al., (2009) showed extensive differences in the ratio of students diagnosed with depression from comparatively low rates of about 10% as well as, significant levels of between 40% and 84% (Bayati et al., 2009). Zaid et al., (2007) argues that students who suffer from depression are at risks of attaining poor academic performance, for example, Hysenbegasi et al., (2005) conducted a study on depressed patients to investigate the association between decreased academic achievement. He applied both objective and subjective assessment, together with the grading system and perceptions about academic performance. His findings showed that subjective measures had a positive correlation with decreased academic achievement than objective scales, despite both of them being significant. Existing literature review also suggests that students are mostly depressed because of the workload and the struggle to meet deadlines, it is stated that the common depression symptoms in university students include attention deficit, lack of enthusiasm and low participation in lectures (Owens, Stevenson and Norgate, 2012). Lastly, have studies show that anxiety levels in students has been growing, this could be a result of students struggling with assigned work, new environment settings, identity crisis and social problems (Ibrahim et al, 2012).
Persistent anxiety symptoms have adverse effect on academic performance with studies investigating the relationship between anxiety and academic performances showing that students who have serious levels of anxiety attained low academic grades (Luigi et al., 2007; McCarty, 2007). Intense levels of anxiety also inhibit attention and memory deficit which play a major role in academic performance, Martin (2015) claims that students experiencing anxiety also encounter mental deficits such as, misunderstanding of information or memory inhibition. Other researchers have also established that students with severe symptoms of anxiety show notably less motivation in lectures that are seen as very evaluative in contrast to students with less anxiety symptoms (Hancock, 2001). Existing literature highlights the need for further study on university student mental health as a criterion variable, (Leyhan et al., 2009) points out that even though evidence of a continuous development in the rate of students with severe mental disorder, students’ mental health has somewhat been paid small attention and the lack of epidemiological findings indicates this. Additionally, the UK Royal College of Psychiatrists (2011) revealed that access to mental health systems in the National Health Services (NHS) has been becoming limited to students’, with the NHS mainly prioritising people with acute mental problems meaning that students with moderate mental health disorders do not match the criteria and for that reason do not obtain therapy or treatment. Conclusively, raised concerns regarding the effects of poor mental health amongst students is not uncommon, especially in the UK which has been revealed to have the highest cases of students with severe mental health than any other countries in Europe (Bridgette, Koutsopoulou, Mile, Barkham and Slaa et al., 2010). Approximately forty years ago, two researches in the UK disclosed distinctive levels of distress in UK university students (Kelvin, Lucas and Ojha, 1965). Their findings claimed that 40% of a participation group of students from University College, London had visited their general practitioner because of their mental health concerns, indicated by anxiety, stress and attention deficit. In comparison to the norm, the group altogether also had raised neuroticism records. However, their mental health issues did not relate to low attainment levels. 66% of the participants who achieved a first class degree had at one point had sought for mental health help (Andrews and Wilding, 2004). Contrastingly, Surtees, Wainwright and Pharaoh (2002)’s research revealed that anxiety or depressing circumstances experienced during the first year of university lessened the chance of attaining a first class degree, though this association dissolved when other factors were manipulated. More findings from Nottingham University student survey showed that distinguished scoring on the general health questionnaire at enrolment did not estimate first year poor academic performance, however they did predict voluntary withdraw from studies (Andrews and Wildings, 2010). Simultaneously, these findings present incoherent data about the relationship between mental health issues and academic achievement. This could be because distinct mental health disorders are yet to be identified in existing investigations of UK students in higher education. Considering the gap in the existing literature, the present study aims to investigate whether mental health and ethnicity are dominant predictors of academic performance and examine the disparity between black ethnic minority students’ academic attainment and mental health.
In the context of educational research, academic performance is defined as a student behaviour in certain circumstances that is observable and measurable (Yusuf, 2002). Academic performance has substantial significance in student’s future opportunities and occupational prospects, that is why students’ academic performance and graduation progression has been an area of concern for university systems (Shahzadi , Haider, Qureshi, and Piradaz 2011).Minnesota (2007) claims that “higher education achievement is determined by the academic performance of graduate students” this signifies the importance of academic performance in higher education settings and why this is a significant field to explore. Studies have also reviewed and researched to signify the importance of higher education performance (Richardson, 2012; Deary,Strand, Fernand and Smith, 2001; Fenollar, 2007). Moreover, Ruban and McCoach (2003) also suggest that the projection and exposition of academic performance and the study of elements associated with academic accomplishment and perseverance of students are the most relevance issues in higher education. Therefore, it can be concluded that academic performance is a relevant field of study because the comprehension of academic performance and engagement is useful in developing and facilitating students’ education experience, making it relevant in this paper. Naylor and Smith (2001) acknowledges that it is a generally believed concept that the degree classification attained by students’ is a vital causal factor of achievement in the graduate employment market. This means that one’s degree classification takes effect either as an indication of their competence, or as an assessment of gained skills, knowledge and experience, employers usually offer posts to applicants who achieved at least an upper second class degree.
This part of the dissertation aims to review the main elements that have been stated to determine or predict academic performance in university students, and also review how academic performance is assessed in higher education as this might help a further understanding of academic performance. There has been a lot of research done to investigate elements that affect the academic performance of students in higher education. For example, Hanson (2002) stated that students’ performance is influenced by various elements like studying competence, gender and race. Subsequent studies have established different types of individual differences that predict academic performance and proposed systematization of a broad variety of evaluation methods (Richardson and Abraham, and Bond, 2012). Interestingly they also point out how these variances in discourse have not explained what ways and to what degree independent predictors of academic performance associate (Richardson et al., 2012). Evident pieces of data show that prospectus of academic performance could be more factual if it was established on assessment of variation of personal differences, for example, McDougall et al., (2002) explains how higher education settings and student admissions process lessens disparity intelligence grades particularly at demanding universities. As a result, at this stage other aspects besides intelligence can be crucial to conclusive prediction of performance. For example, Garton, Ball and Dyer (2000) conducted a study on freshmen college students to assess the effectiveness of students’ studying approach, and other higher education selection variable as a prediction for academic achievement, as well as, high school GPA. Data reported that high school GPA was the most fitting predictor of academic performance. More generally, studies have distinguished different elements that correlate with higher education academic performance and review showed that the most traditional factors were, intelligence, high school GPA, A-Level results, and demographic determinants such as, age sex and socioeconomic standing. However, studies have investigated non-intellective elements that have been distinguished as conceivably practical correspondence of higher education performance (Richardson et al., 2012). Examples such as, motivational influences, personal individual learning approaches, and psychosocial background were some of the factors. Ackerman et al., (1997) produced a significant study of correlations between reasoning, individual traits and interests. Additionally, Poropat (2009) supported these findings by explaining that academic performance significantly correlated with the five-factor traits which are conscientiousness, extraversion, neuroticism, openness, and agreeableness (Costa et al., 1992). Conscientiousness was found to be the most significant predictor of academic performance, the scales used to assess conscientiousness evaluated the degree to which students were competent (e.g. well ordered), and determined to succeed in their course (e.g. goal- orientated). Students with high conscientiousness were found to be more motivated to successfully finish their studies (Mount et al., 1995), and to be more relentless when experiencing challenging assigned work. Other traits like emotional intelligence that are not clearly encompassed by the five-factor model have been established to predict academic performance (Mayer et al., 2002). Emotional intelligence was measured with regards to having the competence to understand emotions correctly, apprehending emotions, and application of emotion to further thinking (Mayer et al., 2002), thus, affecting academic performance, although scales of emotional intelligence have been found to be of small effect on academic performance (Parker et al., 2005) and mindfulness was also suggested to impact academic performance (Hupper and Johnson, 2010).
However, recent revision also revealed that mindfulness association with academic performance is widely unrelated to intelligence and that when academic achievement at university level was manipulated, mindfulness correlated just as much to university academic performance as intelligence. Somewhat steady temperaments like motivation, self- regulatory studying system, and studying approaches have also been established to be significant predictors of academic performance (Chamorro- Premuzic & Arteche, 2008). The prediction of academic performance is determined by being able to assess it (Richardson et al., 2012). For example, university students performance is mostly indicated by the grade point average (GPA) which is the mean of grades from completed modules which are an important factor of the evaluation of the final degree classification (Strenze, 2007). The grade point average (GPA) practice as a criterion of academic performance is widely employed by a lot of higher education systems (Blue et al., 2000; Nguyen et al., 2005; Svanum et al., 2001). Strenze (2007) argues that GPA is the essential measure for postgraduate admission and graduate employment, he states that it is a prediction of career prospects. Essentially, other writers have similar theories that GPA results are an indication of performance directly correlated with education and employment opportunities (Asberg et al., 2005) meaning that it has importance to students and employers. Furthermore, GPA is withal an empirical scale with positive internal reliability and temporal stability (Bacon et al., 2006; Barbuti et al., 2008). GPA has very small limitations, however there has been some challenges about its reliability and validity occurring due to the rise of grades in higher education (Johnson, 2003), and variances in how higher education institutes asses their students (Didier e al., 2006). Regardless, Bloxham (2011) asserts that marking plays a significant role in determining students’ academic performance, and for that reason assessments in higher education include given credibility by procedures of quality guarantee. This quality security significance is contemporarily established in a pattern of responsibility and clarity based assessment (Quality Assurance Agency (QAA), 2006). This demand of accountability needs evaluations to be properly conducted, and is disclosed in the QAA Code of Practice which points out that higher education institutions should have explicit and equitable systems for marking (QAA, 2006), meaning that the GPA results reliability is strong to some extent. In spite of that there is no other scales to assess higher education academic performance that conflict with the assessment efficiency of GPA. For instance, behavioural scales like time spent learning seems to not relate or insignificantly correlated with degree classification, with coefficients ranging from -.02 to .12. In the case of assessment methods GPA is the profoundly researched criterion of academic performance in higher education.
Despite the term race and ethnicity being social constructs exercised to classify people, its effects are existent and can have deleterious student effects (Atwater, Lance, Woodard, and Johnson, 2013) which relates to this study. The term ethnicity is derived from a Greek term meaning people or tribe (Bhopal and Senior, 1994). They suggest that to some degree, the notion of ethnicity is not simple or precise, and that the application of ethnicity definition is determined by the type and piece of research being conducted. This has been an issue that has persisted and caused controversy in previous studies as they used race as a synonym of ethnicity. Disagreements about racial classification have been extensively reported (Cooper,1984; Webster and Fox, 1987), although these referrals are old they still apply today and are still relevant in the same sense. Bhopal et al., (1994)’s definition of ethnicity which in summary states that ethnicity signifies mutual social background, shared culture and practices that have been carried on from generations and effected the sense of identity, the warn that ethnicity must not be confused with nationality. Singh (2009) argues that just because students have the ethnicity does not automatically mean that they have shared cultures, beliefs and values, which is true to a greater extent. This study adopted what most higher education institutions use when conducting research to do with ethnic backgrounds of students . The Universities and Colleges Admissions Service (UCAS) and the Higher Education Statistics Agency (HESA) employs the same comprehensive categorisation for collecting data based on students’ ethnicity, they use the following classifications White; White – British; White – Irish; White – Scottish; Irish Traveller; Other White background. Black or Black British – Caribbean; Black or Black British – African; Other Black background (Singh, 2009; ECU, 2010). This is a valid and reliable classification because it creates a universal grouping that involves all types of ethnic background that are being investigated in this study. Woolf, Potts and McCanus (2011) argue that even though ethnicity cannot be easily measured but a number of methods have been accepted as reliable measures, for instance, skin colour which is understandably dependent on race, literature has distinguished participant’s colour.
This section of the paper aims to explore literature on the relationship between ethnicity and academic performance, highlighting the gap in attainment experienced between white students and ethnic minority students in higher education. Currently, the attainment ratio of it draws on previous studies that have investigated elements of student experience to make sense of the gap in academic performance, with the critical matter summed up that ethnic minority students achieve students tend to achieve lower grades than white students (Cotton & Joyner, 2015; Richardson, 2009; Currant, 2013). Recently, a lot of attention has been fixed on academic achievement gap of students attending university, still higher education institutions have struggled to minimise the gap and comprehend the complication of this matter (Currant, 2013). This is evidently true to a greater extent because for the past 16 years, it has been widely recognised that ethnic minority students attain low grades than white students (ECU, 2012; Richardson, 2009). For example, Connor, La Valle, and Tackey and Perryman (1996) did a research on graduates from four United Kingdom universities, findings showed that 65% of white students had attained a first or upper second class degree, whereas only 39% of ethnic minority students had managed to attain at least a second upper class honours degree. Subsequently, this disposition was substantiated in archived data established from all United Kingdom graduates and universities and the findings still supported the view that white students are more probable of attaining better degree classification than ethnic minority students (Owen & Green, Pitcher, and Maguire, 2000). They suggest that students’ level of achievement may be associated with other determinants like socio-economic contexts, previous qualifications, educational, and pastoral support experienced at university should also be taken into account when addressing this gap, which is evidently true as previous reviewed in the mental health section of this paper. The justification for this rationally notable attainment gap is still to be extensively unravelled, even though the plausible participation of racism is a particular aspect that has been given developed importance recently (Back, 2004; Singh 2009). Back (2004) argues that the higher education field has been slowing behind other academic sectors in addressing the of racial discrimination because the university staff are not so much subject to prejudicial distinction. Black (2004) also goes on further to explain the self-concept that “white” universities consider themselves to be “unprejudiced minded logical intellectuals” spliced with the idea that racism is a result of illiberal, condescending hostile people, thus, downright way for placing the issue elsewhere. Furthermore, he suggests that there is a requirement for a change in thinking and accepting that our mental analysis is not in the least thorough and, “that racial discrimination has prejudicial cause, prejudicial education and subjective liberations and adverse to the idea of learning itself”. Meaning that even though higher education sectors aim to be of liberal and unprejudiced essence, there is still need of acknowledgement and that like other institutes, universities settings are not exempt from institutional discrimination. Some literature has suggested that ethnic minority students’ university experience is lowly compared to that of white students because they experience prejudiced teaching and assessment conducts are also vague confined behaviours and attitudes from staff and white students (Richardson, 2013). There is proof that white students are unwilling to team with black students or other ethnic minority students especially if the assigned work is graded (Harper, 2013), though Leslie (2006) argues that the majority of assessment marking in higher education these days is now being done through anonymous system, thus, the possibility for direct prejudice to happen. This is debatable as direct prejudice can still happen in university settings than affect students’ academic attainment. Additionally, the lack of diversity in university staff is a concern, with 87.7% of being white (ECU, 2012), and might not possess the needful empathy to form good relations with black or ethnic minority students. Also, unconscious discrimination in academic settings (Milkman, Akinola, and Chugh ,2014) and racial micro-aggression could mean that some teachers or student interaction is adverse to black students (Harper, 2013; NUS, 2012). For instance, Currant (2013) conducted a quantitative study exploring student experience to understand the gap attainment, his findings showed that ethnic minority students who took part in the study felt that their university settings were to an extent unfriendly to black students. Interestingly, this is not new data at all as both in the United Kingdom and United States ethnic minority students have expressed how they are treated as insignificant and more exposed to racial discrimination (Harper, 2013), which is most likely to affect their academic performance and mental health. More studies have been carried out and have found similar results that ethnic minority students were not satisfied with their university experience (Tyers, Modood, and Hillage, 2004; Singh 2011). Richardson (2013) argues that the differentiation in university experience between white and ethnic minority students is not enough to account for the outstanding disparities in their achievement, that is fair enough as this is a complex issues and cannot be determined by a singular factor. However, it is partly accountable to a greater extent because student engagement and sense of belonging which makes up student’s experience has been noted to have a significant impact in the academic gap attainment (Harper and Guayer, 2009; Tovar, 2010).
Furthermore, Naylor et al., (2004) researched respective probit analyses on the degree classification obtained by graduates from United Kingdom higher education institutions, participants were categorised as white, black Caribbean, Indian, Chinese or other, the data showed that the probability of attaining a first or second upper class degree was subordinate for ethnic minority students than that of white students. Interestingly, Leslie (2005) argued that ethnic minority students especially black students had low attainment because of their comparatively high participation levels, though, contrary to that, Connor et al., (2004) found that this high level of participation had no correlation with and was not disclosed in the academic performance of ethnic minority students, Owen et al., (2000) also found similar results, it fair to say higher participation levels do not essentially account for the gap in attainment levels being reviewed. This has been researched further by Richardson (2008) who explained that the probability of black ethnic minority students obtaining top classification improved by approximately 50% when the results of admission qualification were manipulated. His findings also showed that influences of age, gender, method and issue of research all related with ethnicity, making it difficult to distinguish causality relating to any particular element. Cotton, Joyner and George, (2015) argued that most of the studies on student attainment disparities between ethnicities was quantitative, lacking depth and very limited, conversely, researchers employing econometric methods have firmly established that the likelihood of white students attaining good degrees than students from other ethnic backgrounds is still high, even when the influences of other demographical and conventional variables had been considered (Broecke and Nicholls, 2007; Richardson, 2013). The fact that these results have been persistent for more than 10 years (ECU, 2012) show that there is need for research development to reduce the causal factors of this disparities. Moreover, Richardson (2012) reviewed that ethnicity in essence is transparently not the effectual variable determining students’ academic performance, but, it is a representative of other elements that confound with ethnicity and are yet to be established. Some have argued that systemic discrimination in the community decreases both the performance and ambitions of ethnic minority students, and as result they have a tendency of being inadequately represented in universities (Obu, 1978). Concerns like that however do not apply to the current circumstances in the United Kingdom as the participation of ethnic minority students is higher than of white students (Richardson, 2008). It was also pointed out that ethnic minority students’ low academic performance might be explained by their specialisation in courses that are harder to graduate with an upper second or first class degree (Cameron and Heckman, 2001). For example, just 4.5% of ethnic minority graduates who study language were able to achieve a good degree compared to the 68% of white students. On the other hand, only 21.7% of ethnic minority students who studied computer sciences managed to get a good degree compared to 52% of white students who attained a good degree. Leslie (2006) argues that several white advantages remain despite these influences put into consideration.
The present study aims to develop the existing literature on the relationship between mental, ethnicity and academic performance, by bringing together mental health and ethnicity within the same study. Linking these concepts provides a significant addition to the existing literature as many have explored the variables separately, even with the extensive in this field, there has been little to no study investigating the effects of mental health and ethnicity on degree outcomes. A considerable amount of existing literature has evidently showed that mental health is significantly correlated with mental health, but there are more incoherent findings in studies that have researched the relationship between ethnicity and academic performance. The review of existing literature highlights the need for research that explores both mental health and ethnicity collectively to further the comprehension of how they may affect students’ academic performance and reports also show that there is a pressing need for an increase in the availability of comprehensive assessment of student health, as well as its promotion which this study aims to contribute to. However, because of the complications in reality of this issue and the associations that go hand in hand with a research of this nature, other effects of student academic performance were taken into account. From this, it can be understandable that this study on its own cannot achieve a complete resolution of this issue as it is past the reach of a research this size. Regardless, this paper is important because it raises more awareness on students’ mental health and also raises awareness concerns over the gap in academic performance faced by students’ from ethnic minority backgrounds. Awareness is a key strategy to making changes, as lack of awareness leaves matters in question not addressable. The aim is that this and consecutive studies will effect a better understanding of the outlook of ethnic minority students in universities so that higher education institutions can take into consideration the changes that need to be in place to improve students’ university experience and perhaps decrease the attainment gap.
The main research question was whether there is a correlation between mental health, ethnicity and academic performance of university students. Established on the literature reviewed, this study will investigate the following hypotheses:
1: Both the predictor variable of academic performance will have a significant and positive relation with academic performance.
2: Ethnicity will be the highest predictor of academic performance amongst the researched population.
3: There will be significant disparities in levels of academic performance and mental health between black and white students.
This present study used repeated measure design to analyse the degree to which mental health and ethnicity can predict academic performance applying a multiple regression method. Measures used were, the General Health Questionnaire (GHQ-28) (Goldberg, 1978), to measure mental health. Students’ academic performance was measured by the participants’ current provisional grade or result which was then converted into a statistical figure. The demographic questionnaire was used to gather the participant’s ethnicity. The study investigated the relationship between academic performance and the two independent variables which are mental health and ethnicity, and academic performance being the dependent variable of the research.
N= 100(55 black students and 45 white students) participated in this study, they were recruited using opportunity sampling, the researcher aimed to recruit a larger sample size in order to get greater power to identify the differences between the two groups and also have significant accuracy. Participants were from all age groups but the majority were between the age of 18- 25 years which is relevant to this study as previous stated that young adults in this age group are the ones who are at risk of developing serious mental illnesses which have considerable effect of academic failure. All participants were students from the University of Northampton, this was essential for making sure that all grades put down by participants as part of the academic performance measurement could be changed into a statistical score using the same basis. The study categorised ethnicity as; White; White – British; White – Irish; White – Scottish; Irish Traveller; Other White background. Black or Black British – Caribbean; Black or Black British – African; Other Black background. This is because usually higher education institutions like UCAS and HESA apply the same comprehensive categorisation when collecting data on black ethnic students. This study adopted this method because it generally a true representation of the white and black ethnic background. Participants were also either in second or third year, first year students were not included because they had not yet attained their end of year results which the study requested, though 3 of the participants were postgraduate students.
Participants who agreed to take part in the study were requested to fill in a questionnaire and provide some general biographical details such as age, gender, race, degree program, year of study and academic grades. The scale used to measure the participants’ mental health was the GHQ-28 (Goldberg, 1987) refer to appendix. The questionnaire required participants to note the difference between their present mental health condition and their usual condition. The questionnaire is divided into four subscales which are, somatic symptoms (found in items 1-7); anxiety (items 8-14); social functional disorder (items 15-21), and severe depression (items 22-28). The items on the questionnaire consisted on questions like, “have you recently been feeling perfectly well and in good health?”, “have you recently been getting edgy and bad-tempered?”, “have you recently been satisfied with the way you’ve carried out your task?”, and “Found at times you couldn’t do anything because your nerves were too bad?”. Each item has four possible answers like, Not at all, No more than usual, Rather more than usual, and Much more than usual. Likert scoring method (1,2,3,4) was used in the study, with the total score ranging from 28-112. The high scores on the scale indicate poor mental health. This scale proved fit to assess mental health because it covered the common mental health issues reviewed in university students like anxiety, depression etc. Additionally, studies have been conducted to investigate the reliability and validity of the GHQ-28 in numerous populations (Sterling, 2011) and it also proved to have a high coefficient stability. Its test- retest reliability has been recorded to be very high, ranging from 0.78 to 0.09 (Sterling, 2011). This is how much the test results of the GHQ-28 have been undeviating over the years, meaning that this scale is reliable to accurately measure mental health. It is the most frequently used and validated scale examining mental in the general population. Falide and Ramos (2000) also indicated the GHQ-28 ‘s high internal consistency, they stated that its interrater and interrater reliability to have been both reliable (Cronbach’s a 0.9 to 0.95) indicating that the GHQ-28 is a reliable scale of mental health.
The ethnicity and academic performance was developed by the researcher. The questionnaire is made up of simple questions which require participants to select their ethnicity (Refer to appendix), which was the categorised using dummy variables (black variable being 0 and White variable being 1). Participants also give out their attained grades. To measure academic performance participants to identify their indicative classifications as shown by the University of Northampton online module information and results website, which are already in statistical scores. Provisional grades are a reliable and valid measures of academic performance which is subject to the grades a student has attained in their course studies.
The questionnaire was developed online using Google Forms. Data was collected through social media where participants were given a link which directed them to the information sheet which gave them in-depth details about the aims and purpose of the research, as well as informing them of what was required from their participation. The same procedure was applied with the data which was collected in person at University of Northampton park campus, were participants were approached and asked if they would like to take part in the study. Participants were informed of their right to withdraw their data from the study without having to justify themselves, provided they did so within 7 days of their participation. The information sheet also ensured participants that their data collected would be confidential and anonymous, they were assured that their data would only be used for this study purposes only and would be destroyed once the results were published in July 2017. After this, participants had to fill in a consent form to confirm that they were over 18years old and that they had given informed consent to take part in the study. Following this, participants were required to complete the GHQ-28 questionnaire (Goldberg, 1978), provide their demographic information and also provide their grades. There was no time restrictions to complete the study but the most of the participants took approximately 20 minutes to complete the study. Debrief was given after the participants had finished completing the questionnaire, it made clarified the aims of the study and reminded the participants of their right to withdraw from the study up until the end of the debrief. The debrief also provided participants with the appropriate student services contacts that offer support with academic performance as well as mental health.
Once all the data had been collected, it was put on the Statistical Package for the Social Sciences (SPSS) for analysis, though some of the participants did not provide their academic grades, a stand in variable of 1 was used so that despite this, the other data they had provided could still be used.
Ethical approval was sought prior to data collection from the University of Northampton ethics committee which was approved with minor corrections that were corrected before any data collection. Detailed information about the study was provided to all participants who agreed to take participate, their informed was also obtained (Appendix). To ensure guaranteed confidentiality and anonymity, each participant was given a number to allow easy identification in case they wanted to withdraw from the study. Participants were reminded of their right to withdraw throughout the study, they were given the researcher’s contact information is case they wished to withdraw. The only demographic information collected from participants was their age, gender and ethnicity which cannot be traced back to any specific individual. Due to the nature of the research, focusing on students’ academic grades and mental health, it was made sure that the participants confirmed that they were 18 years old or older. Furthermore, because participants’ academic grades were required, which some people may be worried about disclosing or embarrassed about, participants were ensured about the study’s confidentiality and anonymity. Participants’ were also provided with student services contact information in case of any raised concerns or if the participants felt any type of mental distress because of the study.
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