Timely receipt of health/mental healthcare can determine an individual’s health outcome [1,2] however, many students in tertiary institutions in Ghana do not utilise available health/mental healthcare services. A greater proportion of these students continue to experience some barriers in receiving health/mental healthcare. Barriers to health/ mental healthcare are issues that hinder a person from accessing health/mental healthcare services. These factors could be physical, psychological or geographical in nature [3]. They could also be linked to resources, culture or language. Persons may face more than one barrier to accessing services. Barriers to care have been identified at the provider, the patient level as well as the system level [4]. Studies into barriers to the utilisation of health/mental health care services have revealed that there could be real or perceived barriers to care. The most basic barrier to receiving health/mental healthcare services is the denial that a problem exists. Several factors may account for the inconsistency between the need for therapy and the actual utilisation of health/mental health services.

Known barriers to care from literature include the fear of negative consequences of treatment, privacy issues the shame/humiliation associated with seeking treatment [5], the mistrust of the health/mental healthcare system [6], the characteristics of the therapist [7], the issue of self-reliance being unaware of available services or how to access them [8], financial constraints lack of perceived need/scepticism about effectiveness of the health/mental healthcare system [9] and the issue of stigma [10-12].

There has also been some research into the possibility of demographic factors to act as barriers to health/mental healthcare. These factors which have been studied include, gender, marital status, religious affiliation, age, among others [13].

An extensive body of literature has revealed gender differences in perceived barriers to health/mental healthcare [14]. It is evident from literature that the main health related problem males face is their reluctance in receiving health/mental health treatment [15]. Studies into barriers to care have specified that males often report more barriers to receiving health/mental healthcare than their female counterparts [16]. Research has indicated that male socialisation could have an adverse effect on men’s health in that it affects their perceived barriers to care and mostly discourages them from seeking health/mental health care [17,18]. Furthermore, unlike females, males have been identified as non-regular attendees even for preventive health/mental healthcare (NHS, Executive, 1998). Other studies, on the contrary, have suggested no significant gender differences in perceived barriers to health/mental healthcare and have explained male’s reluctance to receiving health/ mental healthcare services as merely due to factors related to their career and lifestyle [19].

Findings from research have suggested age differences in perceived barriers to health/mental healthcare services [20]. It is evident from literature that the elderly often report more barriers to health/mental healthcare than the young [21]. In a research, older participants specified that it was more damaging to visit a psychiatrist for a condition like depression than to consult other practitioners [22].

Conversely, some findings have emerged from research which points to the fact that older adults have more positive mindset towards seeking health/mental healthcare than younger adults [23,24]. The explanation given for young people’s reluctance to utilising health/ mental healthcare services was that predominantly they are resilient and react positively to stressful life circumstances that older people react to negatively [25]. Hence, some young people cope well all by themselves in times of trouble to the extent that they never seem to have a problem.

Research which has been conducted to investigate the influence of demographic factors on the utilisation of health/mental healthcare services has revealed that married people have the tendency of reporting more barriers to psychological treatment than their single counterparts [26,27]. Nonetheless, other studies have specified that single people report more barriers to receiving health/mental healthcare services than the married [28].

Other studies on the other hand, have indicated that one’s marital status is not linked in any way to one’s perceived barriers to health/ mental healthcare.

Religion has often been viewed as a barrier to professional health/ mental healthcare services. To the Ghanaian/African, life is perceived as religion, and religion perceived as life. In other words religion and life are inseparable. Religion influences several aspects of one’s life including access to health/mental healthcare services. It affects the perception and the explanations for health and illness as well as the behavioural options to promote health or relieve suffering. The choice of treatment by the patient therefore is related to the patient’s concept of the aetiology of the illness, which is usually based on one’s spiritual beliefs.

Studies have indicated that most Ghanaians attribute the cause of illness to the supernatural. There is therefore the belief that an illness can only be cured by applying the appropriate magic/religious method. As a result of this, some Ghanaians visit their religious leaders with both physical and psychological conditions and resort to formal health/ mental healthcare services when the condition deteriorates and there is no sign of it improving [8]. Hence religion could be a barrier to the utilisation of health/mental healthcare services.

Barriers to health/mental healthcare have been identified at various levels [4]. These include barriers at the patient level, barriers at the provider level and barriers at the system level. Identified barriers at the patient level include the predisposing characteristics of a patient, an individual’s personal enabling resources and some community enabling resources. Predisposing characteristics like a person’s demographic factors, economic status and living conditions could act as barriers to care at the patient’s level. An individual’s personal enabling resources(for example, one’s income, the possession of health insurance, knowledge of available health services and how to use them and time constraints) have also been identified as capable of acting as barriers to care at the patient level. Community enabling resources (for instance, transportation issues and time involved in travelling to the source of help) have been identified as barriers to care at the patient level.

Barriers at the provider level include the characteristics of the service provider which discourages people from utilising healthcare/ mental healthcare services [8]. These factors include the service provider’s orientation, the provider’s skills, behaviour, communication style, bilingualism, translation cultural knowledge, family involvement, religion/spirituality and parallel sets of belief and practices.

Barriers to health/mental healthcare which have been reported in relation to issues at the system level have to do with the medical paradigm, consumer approach, working hours, waiting time, and treatment mode. The problem statement is that most students in Ghana find it difficult to utilise healthcare services especially when it has to do with mental health. Some delay the onset of treatment until the condition deteriorates and affect their education. Others end up as drop-outs as a result of this. There was the need to identify which groups of people report the most barriers to health/mental healthcare so that interventions could be instituted to encourage them receive such services with an open mind. The rational for the study is that researches into barriers to health/mental healthcare have mostly been conducted in the Western countries. Findings from these studies have failed to adequately explain barriers to care among Ghanaian university students in terms of gender, age, marital status and religious affiliation. This necessitated that a research be conducted to investigate the above phenomenon.

Research questions

• What are the barriers to the utilisation of health/mental healthcare services?

• Can socio-demographic characteristics influence the perception of what constitutes barriers to care?

Purpose of the study

This study intended to investigate the influence of demographic variables like age, gender, marital status and religious affiliation on the perception of some selected university students as to what constitutes barriers to the utilisation of health/mental healthcare system. The significance of the study lies in the fact that the outcome has unearthed barriers to care from which measures will be instituted in order to attract people to utilise various health/mental health services.

Objectives of the study

This study aimed to investigate the influence of demographic variables on perceived barriers to utilising health/mental healthcare. The ultimate goal was to identify which groups of people report the most barriers to care in order to target them when programmes and interventions are being designed to address barriers to care.

Several articles and papers on barriers to care were reviewed. The main search engines used were PubMed, Psychlit, PsychINFO, APAPsycNET, Medline and the Cochrane Library. Some of the keywords entered into these search engines included, “health care,” “mental health care” and “barriers to care.” Some write ups which have been presented at conferences, journals and books were also read.

Theoretical framework

The Health Belief Model (HBM) is a psychological model which was developed in the 1950’s by Rosenstock and others [29]. This model attempts to explain and predict health behaviours. This model explains the values that are assigned to maintaining wellness or seeking therapy when a person is ill and also describes a person’s beliefs about the effect of taking action to seek health [30]. HBM attempts to explain and predict health behaviours in terms of value-expectancy. The notion of valueexpectancy stems from cognitive theorists such as Kurt Lewin, who speculated that behavior can be understood when the value a person places on a particular outcome is known as well as the likelihood or the expectation that the behaviour would result in the desired outcome. The core assumptions of this model is that an individual will take a healthrelated action if he/she is of the opinion that a negative health condition could be avoided, or if that individual has a positive expectation that by adhering to the recommended action, he/she will avoid a negative health condition and also believes that he/she can successfully follow a recommended health action.

Initially, the HBM depicted four components which represented the perceived threats and the net benefits of a person’s readiness to act when ill. These components were: perceived susceptibility; perceived severity; perceived benefits and perceived barriers. Under perceived susceptibility, a person must perceive that he/she is at risk of the health problem and its negative consequences. The degree of perceived severity must be high enough to motivate a person to seek help [25]. For a person to seek help and adhere to the treatment regime, he/she must perceive that the outcome of the treatment will be positive and helpful. As part of the decision-making process, he/she also considers possible barriers to seeking healthcare and also considers the pros and cons of seeking health in a cost-benefit analysis.

Two other components were later added to this model, which are ‘cues to action” and “self-efficacy”. The HBM states that before the person decides to seek treatment or otherwise, he/she would take so many things to consideration which will be cues to actions. A person’s confidence in successfully executing an action even with the presence of barriers is self-efficacy.

Related literature

Linos studied the predictors of help seeking behaviour among women who had been exposed to physical and sexual violence in Nigeria and realised that barriers/facilitators to care included wealth, marital status, employment status, ethnicity, history of witnessing domestic violence and relationship to perpetrator. The researchers used self reports in collecting data. It is possible that the participants gave socially desirable answers. This could have confounded the outcome of their study.

In a study conducted by [31] into perceived barriers to psychological treatment and their relationship to depression, it was found out that in general, there were no gender differences on perceived barriers to psychological treatment though women indicated greater barriers regarding the cost of treatment. Also, participants who were single reported greater perceived barriers to psychological treatment than their married counterparts in terms of stigma, lack of motivation, negative evaluation of therapy, participant restriction and cost of treatment. The age of the participants was related to reports on barriers to psychological treatment with regard to stigma, emotional concerns, negative evaluation of therapy and time constraints.

Statement of hypotheses

• Hypothesis 1: Males will report more barriers to the utilisation of health/mental healthcare than females.

Hypothesis 2: Older participants will report greater barriers to care than their younger Counterparts.

• Hypothesis 3: Participants’ marital status will affect their perceived barriers to health/mental healthcare.

• Hypothesis 4: Respondents’ religious affiliation will influence their perceived barriers to the utilisation of health/mental healthcare.

Sample/population

The population for this study were students who had been enrolled into various universities in the Republic of Ghana. The study utilised a non-probability, convenience sampling method to recruit participants. Participants were selected based on their convenient accessibility. The country (Ghana) was divided into two clusters; southern and northern clusters. The northern sector included universities in the Northern Region, the Brong Ahafo Region and the Ashanti Region. The southern sector constituted universities in the Central Region, the Greater Accra Region, the Western Region and the Volta Region. The study sample was selected from both the northern and the southern sectors of Ghana. These include the University of Cape Coast, the University of Ghana, Legon, and the Catholic University College of Ghana. One hundred and ninety eight (198) out of the 250 questionnaires distributed were returned, giving this survey a return rate was 79.2%. However, 192 questionnaires were complete. A summary of the demographic characteristics of the participants is presented in Table 1.

Table 1: Summary of the Demographic Characteristics of the Study’s Participants.

From Table 1, as many as 137 (71.4%) of the respondents were 25 years or below while 55 (28.6%) were above 25 years. The age range was between 18 years and 36 years with a mean age of 21 years. With regard to respondents’ marital status (Table 1), 20 (10.4%) were married, 159 (82.2%) were single. The group of respondents who were cohabiting was 6.8% (13). As many as 170 (88.5%) were Christians while 22 (11.5%) were either Muslims or affiliated to other religion. As shown in Table 1, the percentage of respondents pursing a diploma course was 2.1% (4). Respondents reading undergraduate courses at the first degree level constituted 96.9% (186) of the total sample whereas the percentage of those reading a second degree was 1% (2).

Research design

This study is a survey into barriers to health/mental health care services as reported by students who have enrolled into universities in Ghana. Questionnaires were sent out to be filled by respondents.

Measures

A validated instrument was used to gather data for this study. Barriers to health/mental healthcare were measured with the thirtynine item Barriers to Care Questionnaire (39-Item [1]). In addition to this instrument, a demographic information sheet was used to assess basic demographic information of the participants. This information included, gender, age, course being pursued at the university, marital status, and religion. The 39-item BCQ yields scores from zero (0) to (100). Each item is scored with 100 for “No Problem” or 75 for “Small Problem” or 50 for “Problem” or 25 for “Big Problem” and 0 for “Very Big Problem.” Hence, for BCQ, higher scores indicate fewer barriers. The 39-item BCQ also has subscales which ask questions about issues regarding pragmatics, skills, marginalisation, expectations about care, and health knowledge and beliefs.

Pilot testing of research instruments

The 39-item BCQ was developed and used in a culture/setting other than the Ghanaian setting. This warranted that this instrument be pilot tested using students from two tertiary institutions in Ghana in order to yield its psychometric properties. Eighty questionnaires were administered out of which sixty three (63) were retrieved. The reliability coefficient for the 39-item BCQ was also calculated as a single scale and for its subscales as well. A summary of the reliabilities are presented in Table 2.

Table 2: A Summary of the Psychometric Properties of the 39-item BCQ.

From Table 2, the Cronbach alpha value of the 39-item BCQ as a single scale was .925. The obtained Cronbach alpha values for the subscales ranged from .693 to .890 depicting a satisfactory level of reliability.

Study area

This study was conducted in three selected tertiary institutions in the Republic of Ghana. These institutions included two universities and one university college. Two of the institutions were situated within the southern sector of Ghana while the other one was within the northern sector.

Data collection/procedure

After a respondent’s consent had been sought and confidentiality had been assured, a set of questionnaires and a token (a pen or a packet of tissue) were given to him or her. The questionnaires were randomly presented to the participants.

Data analysis

The Version 17 of the Statistical Package for the Social Sciences (SPSS v 17.0) was used to analyse the data after which appropriate statistical tests were used to test each hypothesis. Hypothesis 1, 2 and 4 were subjected to the Mann-Whitney (U) test while Hypothesis 3 was tested with the Kruskal-Wallis One Way Analysis of Variance by Ranks (H test). Prior to the analysis, the questionnaires were checked to ensure that they had been completed.

Ethical consideration

Ethical issues relating to research were strictly adhered to. Using American Psychological Association’s (APA) ethical code as guideline, permission was sought from several institutions, people and individuals who were directly or indirectly involved in the study. An email was sent to the author of the 39-item BCQ to seek his permission to use it for this study before it was pilot tested and subsequently used for the study. In addition, permission was sought from the necessary authorities in various institutions before the questionnaires were administered to their students. Anonymity and confidentiality of respondents were ensured. No respondent was maltreated in any way. All literature sources that were consulted and used for the study have been duly acknowledged.

Results from the study indicated that in the past three months prior to the study, 35 (18.2%) respondents reported that the health/ mental healthcare system had never worked for them. Twenty six (13.5%), respondents also indicated that health/mental healthcare system had almost never worked for them. To seventy-two (37.5%) of the respondents the health/mental health care system had sometimes worked for them. Whilst 34 (17.7%) and 25 (13.1%) of the respondents reported that the health/mental health care system had often and almost always worked for them respectively. This is shown in Table 3.

Table 3: A Summary of responses on how often the health/mental healthcare system had worked well.

In terms of reports on barriers to care, 26 (13.5%) of the sample reported virtually no barriers to care, whilst 67 (34.9%) reported very few barriers. Few barriers to care were also reported by 81 (42.2%) of the sample and respondents reporting some barriers to care and many barriers to care were 16 (8.3%) and 2 (1.1%) respectively. These figures are depicted in Table 4.

Table 4: A Summary of Reports on Barriers to Care.

The BCQ has five subscales: Pragmatics, Health Beliefs, Expectation, Skills and Marginalisation subscales. The respondents reported more barriers to care on the Expectation subscale than on the other four subscales. In other words more respondents were of the opinion that the health/mental healthcare system did not meet up to their expectation in the past three months prior to the day the data was collected. Apart from the Skills subscale of the 39-item BCQ, male respondents reported more barriers to care than female respondents on the other subscales like the Pragmatics, Health Beliefs, Expectation and Marginalisation subscales. However for the single scale, the female respondents reported more barriers to care than their male counterparts.

Respondents who were above 25 years old reported more barriers to care than those who were 25 years or below for the single scale as well as for all the subscales. Married respondents reported more barriers to care than their other counterparts for the single scale and all the subscales. For religious affiliation, the Muslim/Other Religion respondents reported more barriers to care on the single scale as well as on all the subscales. Table 5 depicts the means and standard deviation of the response for the 39-item BCQ single scale and its subscales according to the demographic factors.

Table 5: Means and standard deviation according to the demographic breakdown for scores on the 39-item BCQ as a single scale and for the subscales.

Hypotheses testing: Hypothesis 1: Males will report more barriers to the utilisation of health/mental healthcare than females:

Hypothesis 1 sought to investigate the influence of gender on reports on barriers to the utilisation of health/mental health care. The data collected was analysed with the aid of the SPSS software. The means and standard deviations (from the SPSS output) are shown in Table 6. The data in Table 6 was further subjected to the Mann-Whitney (U) Test. The Mann-Whitney (U) Test was chosen as the statistical test for this hypothesis because it involved a single independent variable (gender) with two levels (males and females). These two levels of the independent variable had two groups of respondents. Respondents’ scores on the 39-item BCQ constituted the dependent variable for this data. A summary table of the Mann-Whitney (U) Test (derived from the SPSS output) is presented in Table 7. The SPSS output indicated that the observed differences between the group ranks for males and females in terms of their scores on the BCQ were not statistically significant (N = 192, U= -1.29, p = n.s.). In other words, though the male respondents reported more barriers to care than the female respondents the differences were not significant. This finding is consistent with the findings of [32] whose research into barriers to care indicated that generally there were no gender differences on perceived barriers to psychological treatment. This study’s finding is however dissonant with that of [33] which indicated that gender had an influence on perceived barriers to care.

Table 6: Means and Standard Deviation of scores on the 39-Item BCQ in terms of gender.

Table 7: A Summary Table of the Mann-Whitney (U) Test Performed on the Data Contained in Table 6.

Hypothesis 2: Older participants will report greater barriers to care than their younger counterparts: The purpose of Hypothesis 2 was to observe if age will have an effect on perceived barriers to care. The means and standard deviations (extracted from the SPSS output) are presented in Table 8.

Table 8: Means and Standard Deviation of scores on the 39-Item BCQ in relation to age.

The Mann-Whitney (U) Test was adopted to test the data contained in Table 8. A summary table of the Mann-Whitney (U) Test (obtained from the SPSS output) is presented in Table 9.

Table 9: A Summary Table of the Mann-Whitney (U) Test Performed on the Data Presented in Table 8.

The observed Mann Whitney value from the SPSS output indicated that the differences between respondents who were above 25 years and those who were 25 years or below in terms of their scores on the 39- item BCQ were statistically significant (N = 192, U= -1.644, p = 0.05 (one tailed). Respondents who were above 25 years old reported more barriers to the utilisation of health/mental healthcare than those who were 25 years and below. This finding is in harmony with the findings of which specified that among other demographic factors, age could possibly have an impact on reports on barriers to care. This finding is also congruent with the outcome of a study on refugees conducted by which revealed that older participants were more likely to report more barriers to care than their younger participants. However, the finding from this study contradicts that from a study done on the influence of age on the utilisation of mental health services which revealed that older adults had more positive mindset towards the utilisation of health/mental healthcare services than younger adults [34].

There was the need to determine which of the subscales depicted significant age differences in perceived barriers to health/mental healthcare. Thus, an analysis was done on scores for the various subscales in relation to the age of the participants. The observed Mann Whitney (U) value from the SPSS output is shown in Table 10 below.

Table 10: A Summary Table of the Mann-Whitney (U) Test Performed on the various subscales in relation to age

Table 10 portrays that the observed differences between participants who were 25 years old and below and those who were above 25 years were significant for the pragmatic subscale (N = 192, U = -3.174, p = 0.001 for a one tailed test), the Health Beliefs subscale (N = 192, U = -1.884, p = 0.03 for a one tailed test), and the Marginalisation subscale. These results indicated that participants who were 25 years and below differed significantly from those who were above 25 years in their perceived barriers to care as far are issues of pragmatics, their beliefs about the health/mental health care system and marginalisation issues were concerned. In general, as people transition from childhood to adulthood they develop a belief system. Belief system is difficult to change for older people than for younger people. Possibly the respondents who were above 25 years reported more barriers to health/ mental health care because their opinions might have already developed for health/mental healthcare. This might have accounted for their high barriers with regards to pragmatics, health beliefs and marginalisation.

The observed U values were however not significant for the Skills subscale (N = 192, U = -1.147, p = n.s.) and for the Expectation subscale (N = 192, U = -2.784, p = n.s.). The scores of the participants who were 25 years and below and those who were above 25 years did not differ statistically.

Hypothesis 3: Participants’ marital status will affect their perceived barriers to mental healthcare: Hypothesis 3 was to examine the effect of marital status on reports on barriers to care. The means and standard deviations (extracted from the SPSS output) are shown in Table 11. The data in Table 11 was further subjected to the Kruskal-Wallis One Way Analysis of Variance by Ranks (H) Test). This was chosen to test this hypothesis, the reason being that the independent variable (marital status) had three levels (which were married respondents, single respondents and cohabiting respondents). The dependent variable comprised scores from the the 39-item BCQ. A summary table of the Kruskal-Wallis One Way Analysis of Variance by Ranks (H Test (drawn from the SPSS output) is presented in Table 12.

Table 11: Means and Standard Deviation of Scores on BCQ in relation to marital status.

Table 12: A Summary Table of the Kruskal-Wallis One Way Analysis of Variance by Ranks (H Test) Computed on the Data Presented in Table 11.

The Kruskal-Wallis One Way Analysis of Variance by Ranks (H) test indicated that the marital status of the participants did not affect their perceived barriers to health/mental healthcare (N= 192, H(2) = 3.707, p = n.s.). The differences in the mean ranks for the various marital groups were not statistically significant. This finding is in harmony with the findings of [28], whose study concluded that some demographic factors including the marital status of respondents were not significantly related to barriers to seeking health/mental healthcare. This finding is however contradictory to the findings of [26] and [35] which suggested that barriers/facilitators to care included the marital status of an individual.

Hypothesis 4: Respondents’ religious affiliation will influence their perceived barriers to the utilisation of health/mental healthcare: The purpose of Hypothesis 4 was to uncover whether reports on barriers to health/mental health care would differ based on a participant’s religious affiliation. The means and standard deviations (obtained from the SPSS output) are shown in Table 13. The data in Table 13 was further analysed with the Kruskal-Wallis One Way Analysis of Variance by Ranks (H Test).

Table 13: Means and Standard Deviation of Scores on BCQ in relation with religious affiliation.

A summary table of the Mann-Whitney (U) Test (derived from the SPSS output) is presented in Table 14. The Mann-Whitney (U) test indicated that the religious affiliation of the participants did not affect their scores on perceived barriers to care (N= 192, U = -.326, p = n.s.). The differences in the mean ranks for the various religious groups were not statistically significant. This finding is however not consistent with that of [8,36,4] which depicted that religion could influence one’s perception of what constitutes barriers to health/mental healthcare. The sample size for the Muslim/other religious group was smaller than that for Christians. This probably, might have accounted for this discrepancy in findings. Also, the inconsistency in findings could have also arisen from the non probability sampling technique used in recruiting respondents for this study. Probably, a simple random sampling could have yielded results which would have been more consistent with previous findings. A diagram depicting the findings from the study is shown in Figure 1.

Table 14: A Summary Table of the Mann-Whitney (U) Test Performed on the Data Presented in Table 13.

Figure 1: A diagram depicting the major findings from the study.

Majority of the respondents reported that while the health/mental health care system had sometimes worked satisfactorily for them it had at other times failed them. In general, participants reported more barriers to care on the Expectation subscale than on the other four subscales. Using the Mann Whitney (U) test, the age of respondents influenced their reports on barriers to receiving health/mental healthcare services though it was not apparent from the Mann-Whitney (U) test that the gender and the religious affiliation of participants influenced perceived barriers to health/mental healthcare. Results from the Kruskal Wallis one way analysis of variance also indicated that the respondents’ marital status did not affect their reports on barriers to utilising health/mental healthcare.

This study used convenience sampling technique to select participants. To strengthen the methodology, the researcher recommends that the study is replicated using random sampling technique to select participants. In addition, the researcher recommends the use of a larger sample. In analysing such data, it is recommended that for future studies, the hypotheses should be tested with parametric tests since they are more powerful than the non-parametric tests used for this study.

This study is a significant contribution to previous knowledge and understanding of barriers to seeking health/mental healthcare. This study detected age differentials in perceived barriers to care which is a pertinent finding which could guide mental healthcare/healthcare workers to strategize in order to increase services utilisation. Also, emerging from the study, was the fact that there was no significant gender differences in perceived barriers to care, neither was there a significant difference in reports on perceived barriers to care among the different religious affiliation groups nor the different marital status groups. What this demonstrates is that one’s age rather than other predisposing factors could be a major determinant of the nature and types of psychological support one may need. If only heads of health institutions/policy makers could put this finding into consideration, they could promote the utilisation of health/mental health services.

The findings from the present study have enormous implications for clinical practice, counselling services, research, mental health policy, and educational institutions. For clinical practice and school counsellors this study provides significant information on perceived barriers to seeking health/mental health services as far as demographic variables are concerned. When addressing barriers to the utilization of psychological treatment, clinicians/counsellors should target the elderly and develop interventions accordingly. This study also has implications for research. Findings from this study have increased knowledge on the existing knowledge of perceived barriers to health/mental healthcare. Some of the findings would pave way for others to research into help seeking behaviour. This study also has implications for mental health policies. Findings from this study suggest that new policies on mental health should consider age differentials in order to make mental health services available, accessible, acceptable, affordable and friendly to the elderly.

This study used the non-probability sampling method to recruit its respondents instead of simple random sampling. This probably could have affected the outcome of the study.

The following areas are recommended to be studied for future research:

- Studies to investigate perceived barriers to health/mental healthcare among senior high secondary school students in Ghana, and

- Studies into religion as a barrier to psychological help seeking.

May God’s name be praised for the successful completion of this research. The authors gratefully acknowledge analytical inputs to this study made by Prof. J. Y. Opoku and Dr. B. Amponsah both of the Department of Psychology, University of Ghana, Legon. Alexander Ebo B. Okyere-Boateng, God bless you for your patience. Special appreciation goes to the participating institutions and the respondents. Thank you all for your help and support.

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