Brain Fag Syndrome and Stimulant Use Among Undergraduate

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BRAIN FAG SYNDROME AND STIMULANT USE AMONG UNDERGRADUATE

STUDENTS AT THE UNIVERSITY OF BENIN

A DISSERTATION SUBMITTED TO THE

NATIONAL POSTGRADUATE MEDICAL COLLEGE OF NIGERIA

IN PART FULFILLMENT OF THE REQUIREMENTS FOR THE FELLOWSHIP OF

THE COLLEGE IN THE FACULTY OF PSYCHIATRY

FMC PSYCH. (NIG).

Dr. Ehigiator Okokhue Adayonfo

M.B.B.S (UNIVERSITY OF BENIN) 2000.

DEPARTMENT OF MENTAL HEALTH

UNIVERSITY OF BENIN TEACHING HOSPITAL

BENIN CITY, EDO STATE

NIGERIA.

NOVEMBER 2012

DEDICATION

This study is dedicated to the Almighty God.

iii

ACKNOWLEDGEMENT

I express profound gratitude to Prof. O. Morakinyo, Dr. K. O. Akhigbe (My Supervisor and 2nd Supervisor respectively), Dr. E. Uwadiae (My Head of Department, Department of

Mental Health, University of Benin Teaching Hospital, Benin City), Dr. S.O. Osasona

(Postgraduate Training Co-ordinator, Department of Mental Health, University of Benin

Teaching Hospital, Benin City) and Mr. O. Onofigho.

My thanks also go to Dr. V. Asemota and Dr. I. Aina, all resident doctors and indeed all staff of the Department of Mental Health, University of Benin Teaching Hospital, and all authors whose work were cited in this study.

I am also grateful to Dr. B.O. James, Mr. G.N. Okungbowa and Mr. I. Enang; the authorities of the University of Benin and the undergraduate students used for this study cooperated immensely, for which I am grateful.

I am also very grateful to my wife, children, parents and siblings for their support and understanding.

Finally, to God be the glory!

SUMMARY

Brain Fag Syndrome (BFS) which was first described by Raymond Prince in Nigeria in 1960, has continued to be studied. It is a culture bound syndrome found in Africans who are engaged in intellectual activities. It constitutes an impediment to the goal of studentship as it may lead to student wastage and or school dropout. Some theories have been put forward to explain the aetiology of BFS. Prince put forward the Forbidden Knowledge and the Ego

Energy theories while Morakinyo Olufemi propounded the Psychophysiological or Circular

Theory which links BFS to stimulant use.

Most appealing is the Psychophysiological Theory, which could be subjected to empirical study. However, there is a dearth of study to link BFS to stimulant use. The aims of this cross-sectional study were; to determine the prevalence of BFS and stimulant use among undergraduate students at the University of Benin, determine any association between the two, to know the socio-demographic factors associated with BFS and to identify factors that may contribute to BFS among students who use stimulants.

Multistage sampling technique was used to select five hundred, 300-level students from 7 of the 13 Faculties in the University, but 482 questionnaires were analysed due to attrition.

Prevalence of BFS and past 30 days general stimulant use among the respondents were high (42.9% and 39.4% respectively). There was a statistically significant association between BFS and use of stimulants by the respondents. The study supported the

Psychophysiological theory because BFS was common among the respondents that used stimulants.

There was no significant difference between the socio-demographic characteristics of students who had BFS and those who did not. The study showed a significant positive

v correlation between general psychiatric morbidity and BFS, in that BFS was significantly common among the respondents who were GHQ positive.

Gender and general psychiatric morbidity were significantly associated with the respondents who used stimulants and came down with BFS. BFS was commoner among females than males who used stimulants, and among the students who used stimulants that were positive on the GHQ.

Consequent upon the earlier mentioned findings, Nigerian undergraduate students may mind the use of stimulants during studies to forestall their coming down with BFS.

Undergraduate students in Nigeria may learn the right study habits that would not need the use of stimulants to stay awake. In addition, mental health service provision as a part of the

University health services rendered to the University community, for early detection and treatment of such problems as BFS among the undergraduate students. This could minimize

BFS and the rate of dropout among the students, for the good of the Nigerian society.

CONTENTS

Declaration ------i

Certification------ii

Dedication------iii

Acknowledgement------iv

Summary------v

Table of Contents------vii

Introduction and Relevance of the study------1

Literature Review------5

Aims, Objectives and Hypothesis------21

Methodology------23

Results------34

Discussion------65

Conclusion------75

Limitations of the study------76

Recommendations------77

References------78

Appendices------89

vii

Chapter One

INTRODUCTION

Prince classified Brain Fag Syndrome (BFS) as a culture-bound syndrome (Prince,

1985; DSM-IV, 1994; Aina and Morakinyo, 2011). It was first described by him in Nigeria in

1960 (Prince, 1960), and it occurs commonly among African people involved in intellectual activities, such as students.

Prince (1962) described the features of the syndrome as: (1) Intellectual impairment manifesting as inability to grasp the meaning of materials read, poor retention and recall, and difficulty with concentrating while reading. (2) Unpleasant sensations like heat or burning , pains, aches, and peppery feeling around the head and neck that are associated with study; either coming on when a student attempts academic activity or may be continuously present but becoming exacerbated when studying. Other sensory disturbances include blurring of vision or just seeing blank. (3) Fatigue and sleepiness in spite of adequate rest. (4) Affective disturbances may or may not be present, or volunteered by the student but may take the form of fear, anxiety and/or depression if present.

Prince called the syndrome, “Brain fag” (BFS) since this was the phrase used by the students to describe the illness, which they believed was the result of brain fatigue.

BFS was observed among students in other parts of Africa or in students of African origin studying abroad. On the contrary, the syndrome is rare among Caucasians (German,

Assael, Muhangi, 1970; Wintrob, 1971; Lehmann, 1972; Thebaud and Rigamer, 1976; Minde,

1974).

There are contentions about BFS been a separate nosological entity. Various researchers classified it as a depressive disorder, somatisation disorder, and an anxiety disorder or an anxiety depressive equivalent. Neki and Marinho (1968), and Guinness (1992b) classified

BFS as either a depressive disorder or an anxiety state; Jegede (1983), and Anumonye (1983);

Peltzer, Cherian and Cherian (1988) opined that it was an anxiety-depression equivalent; while

Mbanefo (1966), Ayorinde (1977), Ebigbo and Ihezue (1981), Nwezie (1982) and Ezeilo

(1982) classified BFS as a somatisation disorder. Fatoye and Morakinyo (2003), regard BFS as a distinct syndrome which incorporates features of somatisation, obsession and depressive disorders. Ola, Morakinyo and Adewuya claimed that BFS was real and not a myth (Ola,

Morakinyo and Adewuya, 2009). “The confusion about the nosological status of BFS seems to result from speculative opinions, failure to define the syndrome properly by authors, lack of biological markers to complement the clinical phenotype of the condition and the fact that most studies did not use the brain fag syndrome scale which is based on the definition of the syndrome” (Ola, Morakinyo and Adewuya, 2009).

Nevertheless, the components of the syndrome draw a line of demarcation between it and other related ones, hence the reason for BFS as a distinct diagnostic entity. In addition, this could be one of the reasons the International Classification of Diseases (ICD-10) grouped it under “Neurotic, Stress Related and Somatoform Disorder, F48.8 (WHO, 1992), while the

Diagnostic and Statistical Manual (DSM-IV) regards it as a Culture-Bound Syndrome

(“Appendix I; Outline for Cultural Formulation and Glossary of Culture-Bound Syndromes”)

(DSM-IV, 1994)).

A few reports may indicate that Brain fag syndrome is common. Prince reported an average prevalence of 54 % among secondary school students in Ibadan, Nigeria (Prince,

1962). Peltzer, Cherian and Cherian reported a prevalence of 25% among secondary school students in South Africa (Peltzer, Cherian and Cherian, 1998), Fatoye reported 38.9% in Ilesha

(Fatoye, 2005), and Eeguranti reported 24.2% amongst secondary school students in Oshogbo

(Eeguranti, 2006). Recently, Uchendu in a study of BFS among students of the University of

Abuja reported a prevalence of 36 % (Uchendu, 2009).

What are some of the factors that contribute to the genesis of BFS? Theories of causation have included the Forbidden Knowledge Theory and the Ego Energy Theory, both proposed by Prince in 1979 (Prince, 1979). The Psychophysiological Theory was put forward by Morakinyo in 1980 (Morakinyo, 1980). Among the three theories, the most appealing is the

Psychophysiological Theory which links the genesis of BFS with sleep deprivation due to stimulant use.

Prince’s Forbidden Knowledge Theory posits that the ancestors forbade books and western education at the inception of western colonisation in Africa; that the African manifests symptoms of BFS as an unconscious way of refusing to accept books and western education in conformity with the ancestors’ proscription of books. The Ego Energy Theory states that the

African lacks the requisite ego energy to cope with western type of education.

Morakinyo’s Psychophysiological Theory, also called Circular Theory (Finnemore,

2000) argues that learning in a second language and assimilating western designed education pose challenges and stress. Individuals involved in academic activity may then use stimulants to keep awake to study. This leads to sleep deprivation. Persons with susceptible personality traits such as high neuroticism may then develop symptoms of BFS.

Despite the report by the proponent of the circular theory, few researches have linked

BFS to the use of stimulants by students. Sometimes, undergraduate students of the University of Benin, complain of symptoms suggestive of BFS. Are these actually cases of BFS? And if this is so, is there an association between the use of stimulants by students and having brain fag syndrome among them? This study intended to explore the relationship between the use of stimulants and meeting the criteria for brain fag syndrome among undergraduate students at the

University of Benin.

Relevance of the Study.

Students represent an important group of a population of any community; they represent the future leaders of society; and should be in a good state of mental and physical health while undertaking academic activities.

The investigation of BFS among a population that is involved in academic activity is important since BFS is a disorder associated with studies. Optimum academic performance may be affected in students who suffer BFS; this may lead to school dropout and wastage of a prospective future leader.

Part of what this study would determine are some of the possible risk factors associated with BFS. This would help in the prevention and treatment of BFS, thereby improving the

Undergraduate Students’ mental health as well as reducing students’ wastage and dropout.

Chapter Two

LITERATURE REVIEW

2.1 Brief historical perspective of students’ mental health services.

Before 1914, health was viewed from the angle of physical illness/physical fitness only.

Thus, medical efforts at that time were to identify physical illness and to promote physical fitness by encouraging physical exercises (Lucas and Crown, 1974). Introduction of psychiatry to student health started in the 1950’s (Parnell, 1951). From this time, health was viewed from mental perspective. But, about 40 years later, Morakinyo stated that “very little is known and practiced about student mental health in West Africa, and it is not a subject that has been much researched in the sub-region” (Morakinyo, 1990).

However, a major advance in the concept of student mental health was made in 1956 with the convening of the first international conference on student mental health at Princeton,

United States of America. This conference was attended by eminent mental health experts from all over the world (Furkenstein, 1956).

Since this conference, there has increased worldwide interest to find the size of mental health problems among students to providing preventive and therapeutic strategies.

2.2 Historical development of the construct of the Brain Fag Syndrome.

“Brain fag” was a term in the United States as far back as 1852 for an over worked brain. In

1877 it described mental exhaustion in professionals, similar to neurasthenia. Later in 1919 it described mental fatigue in the elderly (Wikipedia, 2011). The modern usage of the term is traceable to the work of Raymond Prince. Prince adopted the phrase from his patients and used it to describe a syndrome he encountered among undergraduate students of the University of

Ibadan. The phrase was used by the students to describe their symptoms (Prince, 1960; Peltzer,

Cherian and Cherian, 1998).

BFS has been reported from other parts of Africa and in students from Africa who are studying abroad (Prince, 1979, Peltzer, Cherian and Cherian, 1998). Furthermore, Prince also quoted several personal communications reporting the presence of similar syndromes in

Southern and Western Africa, amongst African students in London and amongst students in

Brazil and Argentina (Chakrabouty and Malicke, 1966; Neki and Marinho, 1968 and Swift and

Asuni, 1975). The syndrome has also been reported in Liberia (Wintrob, 1971; Thebaud and

Rigamer, 1976) and Ivory Coast (Lehmann, 1972).

The syndrome is rather rare among Caucasians; thus DSM IV included Brain Fag

Syndrome as a Culture-Bound Syndrome. And also, Prince, having defined culture bound syndrome as “a collection of signs and symptoms (excluding the notion of cause) which is restricted to a limited number of cultures primarily by reason of certain of their psychosocial features”, argued that it be regarded as a culture bound syndrome in view of its lopsided distribution between African and European cultures. He likened BFS to Anorexia nervosa, a condition which seems to have almost exclusive occurrence among Caucasians only (Prince,

1985).

2.3 Clinical features of Brain Fag Syndrome.

In 1962, Prince described the cluster of symptoms which define the syndrome (Prince,

1962). The clinical features include:

“(1) Intellectual impairment, inability to grasp the meaning of materials read, poor retention and recall and difficulty with concentrating while reading,

(2) Unpleasant sensations like heat or burning sensations, pain, aches, peppery sensations around the head and neck, associated with study either coming on when the student attempts intellectual activity or may be continuously present but becoming exacerbated when study is attempted; other sensory disturbances include blurring of vision or just seeing blank;

(3) Fatigue and sleepiness in spite of adequate rest;

(4) Affective disturbances which may or may not be present or volunteered by the student, but which may take the form of fear, anxiety and or depression if present”.

The symptoms are similar to that of studiation madness seen in the Caribbean

(rjg42.tripod.com, 2012).

2.4 African Culture and symptoms of Brain Fag Syndrome.

Expressions of physical symptoms are the sole indicators of illness in an African society. This probably explains the manifestation of such culture related syndromes as BFS with physical symptoms (Prince, 1985). Africans with psychiatric morbidity frequently manifest physical complaints (Binitie, 1975; Makanjuola, 1987). Makanjuola presented 30 patients diagnosed by traditional healers of having a psychological illness known as “ode ori”

(a culture-bound disorder). Even though the most common DSM III diagnoses for these patients were depression and anxiety disorders, their chief complaints were physical symptoms.

Similarly, Binitie in his study of depression across cultures reported that Africans somatise.

2.5 Aetiology of Brain Fag Syndrome.

Theories of causation include the Forbidden Knowledge Theory, Ego Energy Theory

(Prince, 1979) and the Psychophysiological Theory (Morakinyo, 1980). Unfortunately, it is difficult to investigate the Ego Energy and the Forbidden Knowledge Theories empirically since they are psychoanalytically based.

The Psychophysiological Theory of the BFS was put forward by Morakinyo after he studied 20 undergraduate students of Obafemi Awolowo University, Ile-Ife, who had BFS

(Morakinyo, 1980). He observed that individuals who developed BFS had a high drive to achieve academically; and at the same time they were anxious over what the outcome of their academic activity and pursuit would be. Combination of this drive and anxiety made them to want to keep awake to study. They then resorted to the use of stimulants to keep awake to study. The resulting sleep deprivation caused cognitive dysfunction. The cognitive dysfunction became a threat to their academic ambition. The threat further increased their anxiety, thus forming a vicious circle; hence also called Circular Theory (Finnemore, 2000). The person may then develop decreased cognitive functioning, mental and somatic symptoms. Combination of decreased cognitive functioning, mental functions and somatic symptoms formation lead to

Brain Fag Syndrome. Morakinyo observed the following characteristics of people who developed BFS: (1) Above average students with a nervous predisposition (2) highly achievement-oriented and from poor backgrounds (3) Anxiety about academic performance as an outcome (4) Symptoms are more during periods of intense academic pressure (5) Staying late at nights and stimulant use (sleep deprivation) (6) Cognitive inhibition (Morakinyo, 1980,

Ola and Morakinyo, 2010). However, it is important to note that students who do not use stimulants may also develop BFS since BFS has multifactorial aetiology (Morakinyo,

1980).Omoluabi investigated this Psychophysiological Theory (Omoluabi, 1986) and proposed that studying is a stressor, and studying caused hyper-arousal in people who had BFS. Hyper-

8 arousal mediated by the cortex carries out cognitive appraisal of the stressor (studying). This cognitive appraisal is transmitted to the hypothalamus which then activates the hypothalamo- pituitary-adrenal axis and the sympathetic nervous system. The activation of this axis and the sympathetic nervous system causes symptoms such as headache, increase muscle tension, increase heart rate, insomnia, poor concentration and memory impairment.

Clash of cultures between African and Western societies has also been suggested as an aetiological factor (Durst, Minuchin-Itzigsohn and Jabotinsky-Rubia, 1993). The culture of

Africa is collective and cooperative while that of the west is individualistic and competitive.

The acquisition of western education seems to require that the African shifts from his culture to western culture which characterises western education. This results in a clash of African and western cultures. The clash makes psychological demands on the African who is acquiring western education and this may lead to BFS. In addition, proficiency in English language and learning in foreign language may be risk factors (Morakinyo and Peltzer, 2002).

2.6 Brain Fag Syndrome and Study Habits.

The study habits of students may predispose them to BFS. Ola and Morakinyo reported that “home work and assignments, examinations and written work were significant study habit variables associated with BFS” (Ola and Morakinyo, 2010)

2.7 Association between Brain Fag Syndrome, Personality Traits and Psychosocial Factors.

There seems to be a direct relationship between neuroticism and psychoticism personality traits and the BFS (Fatoye, 2004). Those who score high on these traits are more at risk of BFS compared to those who score low. Also, financial difficulties and individuals who report poor physical health are more at risk of BFS (Fatoye, 2004). It is also reported to be commoner in rural than in urban setting (Guinness, 1992).

2.8 Epidemiology of Brain Fag Syndrome.

Different researchers have reported different prevalence rate for BFS in different population. At the outset, about the time BFS was first described in Nigeria, Prince (1962) reported prevalence of 54% among secondary school students in Ibadan, Nigeria. While

Peltzer, Cherian and Cherian (1998) reported a rate of 25% among secondary school students in South Africa. More recently, Fatoye (2005) and Eeguranti (2006) obtained a rate of 38.9% and 24.2% respectively among secondary school students in Ilesha and Osogbo respectively.

Uchendu (2009) who carried out his study on University of Abuja students reported prevalence of 36%. One reason that may explain these differences in prevalence is the varying degrees of westernisation in the different populations of students studied (Peltzer, Cherian and Cherian,

1998). BFS is a disorder of Africans who engage in intellectual activities especially students, whether in their native countries or abroad. It has also been reported in westerners with African origin; for example in the Afro-Americans, but rare in Caucasians (German, Assael, Muhangi,

1970; Paniagua, 2000). Further study has shown that intellectual activity per se is not what is critical to development of BFS. What is critical is the western method of imparting knowledge which involves didactic education and book-reading. Morakinyo and Peltzer (2002) investigated the prevalence of BFS among apprentice who were learning western skills, for example automobile-mechanic. Learning in a school and learning in an automobile workshop are both western. But they differ in that learning in an automobile workshop does not involve didactic lectures and book reading. They found that cases of BFS were about 4 times more common among secondary school students than among the apprentice and the average score on the BFS scale by secondary school students was thrice that of the apprentice. Another finding of the study was that learning in a foreign language is also a risk factor for developing BFS while ‘books’ is not relevant to the pathogenesis.

In the past, BFS was commoner among men (Prince, 1960 and 1962; Morakinyo,

1980). But later studies have tended to show that gender does not significantly differentiate between BFS cases and non-cases (Peltzer, Cherian and Cherian, 1998; Fatoye, 2004).

2.9 Effects of Brain Fag Syndrome.

BFS has been found to be associated with study difficulty (Prince, 1960; Morakinyo,

1980; Fatoye, 1998; Fatoye and Morakinyo, 2003; Uchendu, 2009). The component of study difficulty are diminished motivation, impaired ability to concentrate, retain or recall, improper presentation of materials, faulty study pattern, poor budgeting of available time, difficulty in social adjustment to a new school environment, secondary effect of substance use, personality related problems as well as neurotic and psychotic conditions (Fatoye, 1998).

Osasona, Morakinyo and Akhigbe (2011) reported a statistically significant association between psychiatric morbidity and all aspects of study difficulty and a negative and significant correlation between grade point average and depression, disorganized/distractibility, low motivation and somatic subscales of the University College London Study Difficulty

Questionnaire (UCLSQ). And they further observed that “study difficulty has significant negative impact on academic performance of the students” and that even minor mental health impairment could lead to poor academic outcome for students. In addition, it has also been observed that some cases of BFS may progress to transient reactive psychosis (Guinness, 1992)

2.10 Treatment of Brain Fag Syndrome.

The treatment is by counseling and psychotherapy, use of antidepressants and anxiolytics; for example lorazepam (Minde, 1974; Anumonye, 1975; Culliton, 2008). The use of antidepressants, anxiolytics and psychological methods in the treatment of BFS may have been part of the reasons why BFS had been thought to be a depressive-anxiety equivalent.

2.11 Stimulants.

Stimulants are a group of psychoactive substances which are used across all cultures. They include substances like (1) caffeine, found in coffee, kola nuts, Proplus, etc. (2) theobromine (3) amphetamine and related compounds such as dexamphetamine, pep pills, ephedrine (4) theophylin (5) khat amongst others. Caffeine is the most widely used, worldwide (Barone and Roberts, 1996).

2.12 Classification of Stimulants Table 2.1: Classification of Stimulants

A. Stimulants under international control (Status 1996) 1. with no currently accepted medical use Amphetamine-type substances (1971, schedule 1) Others such as - Cathinone - Cocaine: occurring naturally in coca - Methcathinone (ephedrine) leaves (1961, Schedule I) - 4-Methylaminorex - Coca leaf (1961, Schedule I) - Tenamfetamine (MDA) - N-ethyl-tenamfetamine (MDE) - MDMA and - Other ring-substitute amphetamine derivatives 2. with currently accepted medical use Amphetamine-type substances (1971, Schedule II) Others (1988, Table I) - Amfetamine and its optical isomers: - Ephedrine - Dexamfetamine - Pseudoephedrine - Levamfetamine (both used in the clandestine manufacture of - Metamfetamine racemate + opt. isomers: methamphetamine and methcathinone) - Metamfetamine - Levomethamphetamine - Fenetylline - Methylphenidate - Phenmetrazine - Schedule III - Cathine - Schedule IV - Aminorex - Mazindol - Amfepramone - Mefenorex - (Diethylproprion) - Mesocarb - Benzfetamine - Pemoline - Etilamfetamine - Phendimetrazine - Fencamfamin - Phentermine - Fenproporex - Pipradrol - Pyrovalerone

B. Stimulants not subject to international control (Status 1996) Amphetaminee – type substances such as Others (pure substances, herbal products) - Amphetamine psycho stimulant such as - Clobenzorex anorectic - Caffeine (present in coffee, tea, - Dexfenfluramine anorectic cocoa, cola nuts, mate tea, guarana - Fencamine psycho stimulant paste, and in many products like - Fenfluramine anorectic chocolate, soft & energy drinks) - Furfenorex anorectic - Nicotine (present in tobacco) - Metamfepramone psycho stimulant, anorectic - Herbal stimulants, such as - Propylhexedrine nasal decongestant, anorectic - Betel nuts - Selegiline antidepressant, antiparkinsonian - Ephedra plant (ephedrine and pseudoephedrine, the main active ingredients, are controlled as precursors) - Khat plant (cathinone and cathine as the primary and secondary active ingredients are controlled)

(United Nations International Drug Control Programme, 1996)

Table 2.1: above shows the classification of stimulants according to the United Nations

International Drug Control Programme, Vienna (1996). The year in brackets indicates schedule of each substance under the three United Nations Conventions (Status 1996) (1961): Single

Convention on Narcotic Drugs, (1971): Convention on Psychotropic Substances, (1988):

Convention against Illicit Traffic in Narcotic Drugs and Psychotropic Substances.

The table shows the classification of stimulants into ‘A’ and ‘B’. ‘A’ includes stimulant under international control while ‘B’ are stimulants not subject to international control. There are 2 groups under ‘A’; stimulants that have medical uses and those that do not have.

2.13 Stimulant Use in Nigeria.

Nigeria has its own fair share of use of stimulants, especially among undergraduates

(Oshodi, 1973; Oviasu, 1976; Adelekan, 1989). Several studies have shown stimulant use is highest among the four leading groups of psychoactive substances which includes tobacco, alcohol, hypnosedatives and stimulants (Akindele and Odejide, 1978; Adelekan 1989;

Abiodun, Adelekan, Ogunremi, Oni, Obayan, 1994).

Nevadomsky in 1985 reported use of Reactivan, Proplus and Ephedrine among

University of Benin students. Reactivan has fencamfamin. Fencamfamin (2- Ethylamino-3- phenylnorcamphane hydrochloride) is a central nervous system stimulant. The addition of vitamins is supportive (Nevadomsky, 1981and Malahyde Information Systems, 2001).

Reactivan use by students to keep awake to study is no more common due to its relative unavailability (Eeguranti, 2006). The Table below shows the composition of Reactivan.

Table 2.2 Showing the Constituents of Reactivan.

Ingredients Reactivan tablets (each Reactivan syrup (each 5 ml tablet contains) contains) Fencamfamin HCL 10mg 10mg

Vitamin B1 10mg _

Vitamin B6 20 mg 10 mg

Vitamin B12 10 micrograms 5 micrograms

Vitamin C 100 mg –

Methyl Paraben _ 0,065% as preservative

Propyl Paraben _ 0,035% as preservative

Proplus contains caffeine. A tablet of proplus contains 50mg of caffeine (Nevadomsky,

1981; Bayer, 2011).

Stimulants are also used as prescription medicine despite its’ illicit use (Riddle,

Fleckenstein and Hanson, 2005).

Kola nut.

Kola tree belongs to the cocoa family known as sterculiaceae. There are two main species, Cola acuminate and Cola nitida (Encyclopaedia Britannica, 2012). The kola nut is the seed of these trees. The seeds are about 4cm by 3cm and it is light or dark red in colour and has the odour of roses. It has various local names like goro, guru, ombene, nangue, makatso, gonja etc (“Excitantia”).

Kola nut, which originated in tropical Africa, is also found in Europe and America

(Answers, 2012). Lagos State and Benue State have kola nut forests (“Excitantia”).

The main chemical component of kola nut is caffeine (caffeine makes up 2 – 3.5% of kola nut). Other components are theobromine, tannins and kolatin. Caffeine accounts for the effects of kola nuts (Njini, 2012; Encyclopaedia Britannica, 2012; Wikipedia, 2012).

Kola nut is chewed, dried and processed into powder and consumed as a beverage or kola biscuits (Njini, 2012). Ingestion of kola nut causes a feeling of stimulation and increased physical activity. It prevents sleep, reduces feeling of hunger and increases energy. It also acts as an aphrodiasic (Monterey bay, 2012; Answers, 2012). Due to the fact that it prevents sleep, students use it to keep awake to study (Adelekan, 1989; Eeguranti, 2006; Igwe et al, 2009;

Oshodi, Aina and Onajole, 2010). Excessive ingestion of kola nut causes intoxication and the features are a general state of weakness, prostration, tremors and insomnia.

Kola nut use cuts across cultures. Used during social events like weddings, naming ceremonies, house-warming and entertainment of visitors. It is also used for religious purposes, like during worship of deities, and for divination (Nwachukwu, 2012; Answers, 2012;

Encyclopaedia Britannica, 2012).

Coffee.

Coffee is a beverage made from the roasted seeds (beans) of coffee plant. It is the most traded agricultural commodities in the world and is one of the most consumed beverages in the world (Wikipedia, 2012).

Its origin is traceable to Ethiopia in Africa, but its cultivation was first done in Arabia.

Drinking of coffee started in the middle of 15th century in shrines in Yemen. From the Muslim world, the cultivation and consumption of coffee spread to other parts of the world (Wikipedia,

2012).

The coffee plant belongs to the family of Rubiaceae and the two main species are

Coffee canephora and Coffee Arabica. They produce coffee berries where the coffee seeds or beans are found.

The commonest form of coffee for consumption is the instant coffee. This is coffee in a soluble powder or granules form, and Nescafe is the most popular product. Nescafe is dissolved in hot water and drunk. Other preparations of coffee are canned and bottled coffee.

The stimulant and energising effect of coffee is attributable to the caffeine content of coffee. One cup of coffee (207mls) contains between 80 and 135mg of caffeine (Wikipedia,

2012).

Atahye.

Yunusa et al (2009) reported the use of atahye as a stimulant in Sokoto, Northwestern

Nigeria. It is a tealeaf that is being introduced to Nigeria from Republic of Niger. The leaf is boiled over a long time and the resulting concentrated product is then drunk. A literature search did not show report of use of atahye by any other researcher and Yunusa et al did not report the content of this tealeaf. However, since it is a tealeaf, it is likely to contain caffeine (Wikipedia,

2012).

Energy drink

Energy drink is a beverage that boosts physical and mental energy and as such it is used as a stimulant. Their main constituent is caffeine. Examples are power horse, red bull, lipovitan, jolt cola e.t.c. A serving of the drink contains between 6 and 242 mg of caffeine and some containers contain more than one serving (Wikipedia, 2012; news.yahoo.com, 2012).

2.14 Reasons for Widespread Use of Stimulants.

Stimulants modify the physiological and biochemical functioning of the body (Fehr,

1981). Stimulants have the potential to arouse and lift the mood of the user. They also cause an improved sense of well-being and energy (Barone and Roberts, 1996; Kollins, MacDonald,

Rush, 2001). Misuse of stimulants has been observed particularly in the University settings

(Oviasu, 1976; Akindele and Odejide 1978; Adelekan, 1989; Abiodun et al 1994; McCabe et al, 2005; McCabe, Teter and Boyd, 2006). One reason why students use stimulants is study difficulty (Fatoye, 1998). Study difficulty has been defined as the impairment in the capacity to study effectively or obtain maximal effect from studying in students, either as a result of diminished motivation, impaired ability to concentrate, retain or recall, improper presentation of materials, faulty study pattern, poor budgeting of available time, difficulty in social adjustment to a new school environment or as secondary effect of substance use, as well as personality related problems and psychoneurotic conditions (Fatoye, 1998).

Stimulants are also known as “Study drugs”, “Cramming drugs” (Kollins and

MacDonald, 2001; Klein-Schwartz, 2002; Kapner, 2003). Some individuals use stimulants because of the increased energy and alertness derivable from the use; for example long distance drivers and farmers. Others use stimulants for recreational purposes and as a result of pervasive influence of media and peers (Isidore, 1999; Patel and Greydanus, 1999; Siqueira and Brook

2003; Lynskey et al 2003).

2.15 Prevalence of Stimulants Use among Students.

Adelekan et al in 1998 reported that 30% of secondary school students in Ilorin were current users of stimulants; Fatoye and Morakinyo (2002) reported a prevalence rate of current use of stimulants to be 20.9% while life time prevalence rate was 37.5% among rural and urban

18 secondary school students in Ilesa. Eeguranti reported a current prevalence rate for all stimulants as 20.3% among secondary school students in Osogbo (Eeguranti, 2006).

2.16 Association of Psychiatric Disturbance and Stimulants Use.

Amphetamine induces anxiety and mood disorder which can occur during intoxication or withdrawal (Castner and Goldman, 1999; Levin, 2005). It can also cause delusions, hallucinations and sleep disorder. Other disturbances associated with amphetamine include delirium, sexual dysfunction, psychosis, restlessness and irritability (Parran, Jr Jasinski, 1991;

Kaplan and Sadock, 1998; Meririnne, Kankaampaa, Seppala, 2001; Klein–Schwartz, 2002;

Coetzee, Kaminer, Morales, 2002; Braun et al, 2004).

How amphetamine causes the above disturbances is not exactly known. Chronic use may inhibit dopamine transporter in the corpus striatum and nucleus accumbens. In the long term, this leads to reduction in dopamine. In the short term, amphetamine causes increased dopamine in the synaptic cleft by causing release of dopamine. (Thirthalli, 2006).

Prescription amphetamine and illegally manufactured amphetamine can both cause psychiatric symptoms. For example, amphetamine prescribed for children can cause symptoms of psychosis or mania (Mosholder et al, 2009). Amphetamine is also reported to induce or worsen tics disorder (kumar and Lang, 1997).

Cocaine causes psychiatric disturbances similar to amphetamine (APA, 2000).

Caffeine use is associated with mood disorder and use of other psychoactive substances

(Lande and Labbate, 1998; Nehlig, 1999).

Stimulants raise blood pressure and may place users at risk of heart attacks and cerebrovascular accidents (White, Becker–Blease, Grace-Bishop, 2006; Alonso-Zaldivar,

2006). They can cause irregular heart beat and very high blood pressure (Schetchikova, 2002;

Kapner, 2003).

Furthermore, Morakinyo (1980), Okasha et al (1985), and Fatoye and Morakinyo

(2002) have associated academic difficulty with stimulant use.

It is worthy of note that the problems caused by stimulants like caffeine may be easily over looked because of its wide use and relative acceptability (Boulenger, Uhde, Wolff, Post,

1984). Nevertheless, as implied above, stimulants also have prescription or medical uses. For example, they are useful in the treatment of Narcolepsy, Attention Deficit Hyperactivity

Disorder, Obesity, Depression, Dysthymia, Chronic Fatigue Syndrome and Neurasthenia

(Kaplan and Sadock, 2003).

Chapter Three

AIM AND OBJECTIVES

General aim

The overall aim of the study was to determine the prevalence of Brain Fag Syndrome and stimulant use among undergraduate students at the University of Benin and to elucidate any association between Brain Fag Syndrome and stimulant use.

Specific objectives

These were to:

1. Determine the prevalence of Brain Fag Syndrome among University of Benin

undergraduate students.

2. Determine the prevalence of stimulant use among University of Benin undergraduate

students.

3. Elucidate the association, if any, between Brain Fag Syndrome and stimulant use.

4. Identify any significant socio-demographic and other factors that may be contributing

to the genesis of BFS among students who use stimulants.

Hypotheses

The following hypotheses were tested:

1. There is no significant difference in the prevalence of BFS in students who use

stimulants compared to those who do not use stimulants.

2. There is no significant difference between the socio-demographic characteristics of

students who have BFS and those who do not have.

3. There is no significant difference between the socio-demographic characteristics of

students who use stimulants and have BFS and those who use stimulants but do not

have BFS.

Chapter Four

METHODOLOGY

4.1 Study Location

The location of the study was the University of Benin, Ugbowo Campus, Benin City,

Edo State, Nigeria. The University, which was established in 1970, is one of the first generation Federal universities in Nigeria. The catchment area for admission into the university includes; the South-South geopolitical zone and part of the South-West zone. However the university also has students from other geopolitical zones as well as from other countries.

The undergraduate students’ population of the university was Forty Eight Thousand

Nine Hundred (48,900) as at 15th March, 2012; with a sex distribution of 28,498 males and

20,402 females. This gave a male: female ratio of approximately 1.5:1 (Students Affairs office,

University of Benin, 2012).

There are 13 academic Faculties with undergraduate students’ population distributions as shown in table 4.1 on the next page:

Table 4.1: Showing the undergraduate students’ population of the University of Benin.

S/N Faculty Male Female Total 1 Agriculture 1,521 963 2,484 2 Arts 2,872 4,178 7,050 3 Basic Medical Sciences 382 339 721 4 Dentistry 80 36 116 5 Education 1,533 1,840 3,373 6 Engineering 3,467 368 3,835 7 Law 474 398 872 8 Life Sciences 2,940 2,405 5,345 9 Management Sciences 5,271 4,485 9,756 10 Medicine 360 141 501 11 Pharmacy 551 405 956 12 Physical Sciences 4,327 1,175 5,502 13 Social Sciences 4,720 3,669 8,389 Grand Total 28,498 20,402 48,900

(Students Affairs office, University of Benin, 2012)

4.2 Sample size determination.

It would have been preferred to study the entire undergraduate students’ population, but this was not possible because of time and financial constraint and the physical exertion that would be involved. Thus a representative sample of the students’ population was studied after calculating the sample size.

Using the best estimate of prevalence of Brain Fag Syndrome [Current point prevalence rate of 36 % for Brain Fag Syndrome morbidity amongst University of Abuja Students

(Uchendu, 2009)], a sample size that will adequately represent the reference population was calculated using the Fisher’s formula (Vaughan and Morrow, 1989; Daniel, 1999):

N = Z2 Pq d2

Where

N = the desired sample size

Z = coefficient at 95 percent confident interval usually set at 1.96).

P= best estimate of prevalence of BFS (36 %) q = 1.0 – p d = degree of accuracy desired (usually set at 0.05)

Thus;

N = (1.96)2 x 0.36 x (1-0.36)

(0.05)2

3.84 x 0.36 x 0.64

0.0025

= 0.884736

0.0025

= 353.8944

Approximately 354.

Thus the minimum sample size would be 354; however, the sample size was increased to 500 to improve accuracy and also to accommodate inadequately completed questionnaires.

4.3 Sampling technique

The sampling method and procedure for distribution of questionnaire used by Osasona in a previous study in the same institution on student mental health was used in this study

(Osasona, 2009).

A multi-stage sampling technique (selection done in stages from Faculties through departments until the final sampling units were arrived at) was used.

Stage One – Selection of 7 Faculties out of the existing 13 Faculties was done by simple random technique (balloting).

Stage Two – Selection of 1 department from each of the selected 7 Faculties was also done by simple random technique. This applied to Faculties with multiple departments e.g. Social

Sciences, Education etc.

Stage Three – Across selected Faculty/departments, respondents were selected from 300-level students by systematic sampling. 300 level students were used for this study because most 300 level students would have spent at least 2 years in the university and, in most cases have completed half of their university educations. They are “midway” in the academic and socioeconomic experiences in the university system. Thus 300 level students were considered most representative of the university undergraduate students’ population compared to other levels. Previous works on university undergraduate students’ population also recruited participants from 300 level students (Osasona 2009; Uchendu, 2009). Yunusa et al, (2011) excluded 100 level students from their study on Psychostimulant Use among University

Students in Northwestern Nigeria. They also described “300 level as the make / break year for students, hence the motivation to use psychoactive substances”.

The number of students selected from each department/Faculty was determined by the population of such Faculty using equal sampling ratio (proportional allocation).

Thus X 1 = X2 . N X3

Where:

X1 = number of respondents to be selected from a Faculty

X2 = population of the Faculty

X3 = Reference population (total population of the 7 selected Faculties)

N = Sample Size (500)

For example, to select respondents from Faculty of Physical Sciences

X 1 = number of respondents to be selected

X 2 = 5,502 (total population of student of Faculty of Physical Sciences)

X3 = 34,042 (total population of Students of the selected 7 Faculties)

N = 500 (Sample Size)

Thus;

X 1= 5,502 X 500 34,042

= 81 respondents

4.4 Instruments

The instrument that was used for this study consisted of 4 sections:

Section A – This section contained questions about the socio-demographic characteristics (age, sex, etc), the socio-economic and family background of the respondent. Only this section was self-designed.

Section B – This section consisted of the 28–item version of the General Health Questionnaire

(GHQ), designed by Goldberg (Goldberg, 1972). The questionnaire was to screen for general psychiatric morbidity. It is a self-rated questionnaire. Each question has 4 possible responses; the respondents choose only 1 response which best fit how he or she felt recently. The first 2 responses earn a score of 0 while the last 2 are each scored 1. A score of 1 is considered positive on each item and a score of 0 negative. A score of 5 or more was sign of mental ill- health or caseness (Michael, 1983; Lobo, Perez-Echeverria and Artal, 1986; Akhigbe, 1996;

Makowska et al, 2002; Osasona, 2009). The General Health Questionnaire has been widely validated against criterion of clinical psychiatric interview and in different cultures, and found to have acceptable sensitivity and specificity (Radovanovic and Eric, 1983; Aderibigbe and

Gureje, 1992). For example, Aderibigbe and Gureje obtained sensitivity of 75% and a specificity of 83% for the GHQ-28 (Aderibigbe and Gureje, 1992).

Used in a number of psychiatric morbidity surveys in Nigeria and found useful as a screening instrument (Ohene, 1990; Abiodun and Ogunremi, 1990; Gureje, Obikoya and

Ikuesan, 1992; Abiodun, Adetoro and Ogunbode, 1993; Akhigbe, 1996; Fatoye, 2005;

Osasona, 2009).

Section C – Brain Fag Syndrome Scale (BFSS). This is a diagnostic instrument, which also measures severity of the illness. The instrument covers symptoms of the syndrome. Designed by Prince in 1960 (Prince, 1962). Modified by Morakinyo and Prince in 1980 (Morakinyo,

1980). It has 7 items and each item has 3 possible responses (often, sometimes and never) with assigned scores of 2, 1 and zero. Thus the largest score is 14 which imply severest degree of the illness, while the minimum score is 0, which signifies no illness. To name a case, 2

28 conditions are met. The respondent must score at least 6 totals, and must score at least 1 on each of items 4 and 5. Items 4 and 5 assess bodily symptoms such as crawling sensation or heat in the head and the interference these bodily symptoms have on study.

The instrument has been used in previous studies (Prince, 1962, 1990; Morakinyo,

1990; Fatoye and Morakinyo, 2003; Fatoye, 2005; Eeguranti, 2006; Uchendu, 2009). It is a valid and reliable instrument (Ola and Igbokwe, 2011). The instrument labeled "HEALTH

AND STUDY" For the purpose of this study. This was in a bid to avoid the use of the word syndrome which may make respondents defensive.

Section D- This consisted of the Stimulant Use Section of the World Health Organisation

Questionnaire for Student Drug Use Surveys. Designed by Smart, Anumonye, Navaratnam,

Hughes, Johnston, Varma, et al in 1980 (Smart, Anumonye, Navaratnam, Hughes, Johnston,

Varma, Khant, Mora, Poshyachinda and Wadud, 1980). It has 3 parts. The first part, made up of 6 questions, concerns social-demographic data of the respondent. The second part consists of 14 groups of questions containing information on drug use and 2 items for validity check.

The third part has a list of optional items, some ethical and moral issues relating to drug use.

The drug use items concerned tobacco, alcohol, cocaine, cannabis, amphetamine and other stimulants, hallucinogens, organic solvents and sniffing substances, tranquilisers, opium and opiates, sedatives and heroin. Respondents required indicating whether they have ever used each of the substances or not, and whether they have used them in the past 1 year, or in the past

30 days, age at first use and frequency of use are also inquired after. Thus, it is possible to determine 30-day (current), 1-year and life-time prevalence rates. The instrument was used in different cultures and countries, including Nigeria. This instrument validated in Nigeria by

Adelekan and Odejide has a high validity and a mean test-retest reliability of 86.7 percent for all items of the questionnaire (Adelekan and Odejide, 1989). This research used the stimulant section of the second part of this World Health Organisation Questionnaire for Student Drug

Use Surveys (the items on cannabis removed since it is not a stimulant); item number 7 added and the instrument labeled "SUBSTANCE USE".

4.5 Time of Administration of Instruments

The instrument would preferably been administered just before exams, but interview with

12 students (300 level class) selected systematically from 3 randomly selected

Faculties/department (four students each from Medicine, Law and Crop Science) showed that students may not agree to fill the questionnaire about the time of exams. All the 12 students said they would not fill instruments just before exams. Thus, administration of questionnaires started 3 weeks to the beginning of examinations, which was still close to exams, but tolerable to the students. Before commencement of administration of the instrument, I was adequately trained by my supervisors. The instrument was first administered on 5 students who did not form part of the participants for the main study. From this showed, that a respondent would need about 20 minutes to complete the instrument.

4.7 Procedure.

Data collection for the pilot and main study was by an earlier procedure used by

Osasona (Osasona, 2009). This pilot study served to assess the planned method.

4.7.1 Pilot Study.

Two Faculties which were not selected for the main study were randomly selected. The

Faculties were Arts and Medicine. The Faculty or School of Medicine is single degree awarding while the Faculty of Arts has 6 degree-awarding departments. The Department of

History selected by simple random technique from the Faculty of Arts. Thus, the

Faculty/department used for the pilot study were Medicine and History. The 300 level class captains and their assistants of these 2 Faculty/department approached, while class timetable was gotten from the class captains after due explanation of the study to them. After identifying a 2 hour lecture session from the class timetables, the lecturers who would take the lectures or courses were known from the class captains and contacted. The lecturers agreed to spare 20 minutes of their lecture time for instrument administration on some of the students present. On the day of the lectures, the entire class was given explanation about the study and informed that participation was voluntary. Refusal or inability to take part would not count against them in any way. There was counting of the students who were willing to take part by asking them to take numbers and systematic sampling used to recruit 20 students from the 2 classes. Done by dividing the total number of students by the number of students recruited to complete the questionnaires (that is 20). The quotient became the sampling interval. For example, in the 300 level class of School of Medicine, there were 66 students and all students were willing to take part. Sixty six divided by 20 to give 3.3. Thus the sampling interval was 3. Therefore, every

3rd student selected for the pilot study, to get a total of 20 participants. The first participant selected by simple random technique. Each selected student was given an informed consent form to read and sign if still willing to take part, before filling the instrument. All 40 students

(20 each from Faculty of Art and Medicine) returned their instruments; 2 students did not respond to all the items on the questionnaire and 3 were not specific with their father's occupation. This gave a success rate of 88 %. Many of the students asked the meaning of recently as used in item number 5 in appendix F, and informed this meant in the past 30 days.

4.7.2 Main Study

Having found the procedures used for the pilot study satisfactory, it was replicated in the main study. Seven Faculties were first selected from the 13 undergraduate students'

Faculties in the University of Benin by simple random technique. The Faculties were: Basic

Medical Sciences, Management Sciences, Life Sciences, Physical Sciences, Social Sciences,

Pharmacy and Education. Thereafter, a department selected also by simple random technique from the 6 multiple degrees awarding Faculties of Basic Medical Sciences, Management

Sciences, Life Sciences, Physical Sciences, Social Sciences and Education. Pharmacy is a single degree awarding Faculty, and remained selected as such. The selected departments were

Medical Laboratory Science, Banking and Finance, Optometry, Political Science and Public

Administration, Educational Psychology and Curriculum Studies. Participants were then recruited from the 300 level students of these 7 Faculties/departments by systematic sampling, as described in the pilot study. Emphasis was laid for respondents to answer all the items in the instrument in honesty and precisely; and told to ask questions on whatever was not clear to them. They were also told "recently" as used in item number 5 in appendix F meant past 30 days. This was in a bid to avoid the lapses observed in the pilot study, and a total of 500 instruments administered.

4.9 Ethical Issues

1. Approval was obtained from the authorities of the University of Benin to carry out the

study with their undergraduate student population as respondents.

2. Approval was also gotten from University of Benin Teaching Hospital Ethics and

Research Committee.

3. Written informed consent was obtained from the respondents.

Confidentiality and anonymity observed, and respondents did not have to write their

names on the questionnaire.

4.10 Inclusion Criterion

Any 300 level undergraduate student of the University who was selected by the sampling method and agreed to participate.

4.11 Exclusion Criteria

1. Any student that chose not to participate in the study.

2. Any student that was too ill to participate

4.12 Data management and analysis

Data collected and analysed using the Statistical Package for Social Sciences (SPSS) version 16.0 (SPSS, 2007).

The occupations of the parents of the respondents coded using the International Labour

Organisation's International Standard Classification of Occupation at the point of computation

(ISCO-08), (International Labour Organisation, 2008).

The statistics used included univariate analysis, chi-square test (asymptotic and exact significance methods), correlation coefficient and logistic regression, as appropriate. The results displayed in Tables and charts as appropriate, in the next chapter.

Chapter Five

RESULTS

A total of 500 instruments were administered but four hundred and ninety six questionnaires were returned. This yielded a response rate of 99.2%. But 14 of the returned questionnaires had many missing data or inconsistent responses or both and were therefore discarded. Thus, a total of 482 (96.4%) instruments were analysed.

5.1: Socio-demographic characteristics of the respondents

Table 5.1.1 shows the number of students selected from each Faculty. Majority of the respondents were from the Faculty of Management Sciences (28.8%) while Faculty of Basic

Medical Sciences contributed the least (2.3%). Chi Goodness of Fit Test showed that there was no statistically significant difference between the number of students selected from each

Faculty and population of students of each Faculty. Thus, there was a significant Goodness of fit between the sample used for this study and the total Undergraduate Students Population of the University of Benin, from where the sample came.

Table 5.1.1: Frequency distribution of respondents by Faculty.

Faculty Total Total χ2 Goodness of fit number of number of students in students Faculty selected Education 3373 45 χ2 = 0.001 (9.9%) (9.3%) df = 6 Pharmacy 956 14 p = 1.0 (2.8%) (2.9%) N.S Social Science 8389 117 (24.6%) (24.3%) Physical Science 5502 79 (16.2%) (16.4%) Basic Medical Science 721 11 (2.1%) (2.3%) Management Science 9756 139 (28.7%) (28.8%) Life Science 5345 77 (15.7%) (16.0%) Total 34,042 482 (100.0%) (100.0%)

N.S = Not Significant

Table 5.1.2 shows distribution of respondents by Faculties by sex. The total number of males was 277 while the total number of females was 205. This gave a male to female ratio of

1.35:1. There were more females in the Faculties of Pharmacy, Physical Sciences and

Management Sciences while there were more males in the Faculties of Education, Social

Sciences, Basic Medical Sciences and Life Sciences. These differences were statistically significant. There is an apparent contradiction between distribution of the gender of the respondents across the Faculties as shown on this table 5.1.2 and table 4.1. For example, while there are more females in the Faculty of Education as shown in table 4.1, table 5.1.2 showed that more males were selected from the Faculty of Education compared to females. This contradiction is because the systematic sampling technique that was used to recruit the participants from the respective 300 level classes did not divide the students into males and females. That is, it did not select males and females based on the ratio of males to females.

Table 5.1.2: Frequency distribution of respondents by Faculties by sex.

Sex Faculty Male Female Total Statistics Education 30 15 45 χ2 = 34.47 (10.8%) (7.3%) (9.3%) df = 6 Pharmacy 4 10 14 p = 0.001* (1.4%) (4.9%) (2.9%) Social Science 90 27 117 (32.5%) (13.2%) (24.3%) Physical Science 35 44 79 (12.6%) (21.5%) (16.4%) Basic Medical Science 7 4 11 (2.5%) (2.0%) (2.3%) Management Science 68 71 139 (24.5%) (34.6%) (28.8%) Life Science 43 34 77 (15.5%) (16.6%) (16.0%) Total 277 205 482 (100.0%) (100.0%) (100.0%)

*= significant at p < 0.05

The bar chart representation of the above distribution is included as Appendix G.

5.1.3 Age, Marital Statusand Religion

Table 5.1.3 shows the age, marital status and religion of the respondents by sex. The age range of the respondents was 17 to 40 years, while the mean age was 21.66 ± 2.63.

Majority of the respondents were in the age group 21-23 years (48.1%).

There were more males across all the age groups except for age group 30-32 years where the ratio of males to females was 1:1. These differences were not statistically significant.

Majority of the respondents were single (97.7%). Four fifth of the married respondents were females. However the difference was not statistically significant.

A higher proportion of the respondents were Christians (98.3%), with more females than males reporting so. But the difference was not statistically significant.

Table 5.1.3: Frequency distribution of respondents by age, marital status and religion by sex.

Sex Total Male Female Statistics n = 482 n = 277 n = 205 2 Age (yrs.) 15-17 1(.4%) 0 (.0%) 1 (.2%) χ = 7.44

18-20 90 (32.5%) 80 (39.0%) 170(35.3%) df = 7 p = .38 21-23 132 100 232(48.1%) NS (47.3%) (48.8%) 24-26 41 (14.8%) 20 (9.8%) 61 (12.7%) 27-29 8 (2.9%) 2 (1.0%) 10 (2.1%) 30-32 1 (0.4%) 1 (0.5%) 2 (0.4%) 33-35 3 (1.1%) 2 (1.0%) 5 (1.0%) 39-41 1 (0.4%) 0 (0.0%) 1 (0.2%)

Marital Single 2 274 197 χ = 6.58 status 471 (97.7%) (98.9%) (96.1%) df = 2

Married 2 (0.7%) 8 (3.9%) 10 (2.1%) p = .02*

Separated 1 (0.4%) 0 (0.0%) 1 (0.2%) Religion Christianity 272 202 2 474(98.3%) χ = 4.35 (98.2%) (98.5%) df = 2

Islam 5 (1.8%) 1 (0.5%) 6 (1.2%) p = .09

Others N.S 0 (.0%) 2 (1.0%) 2 (0.4%)

N.S = Not significant, * = Significant at p < 0.05

5.1.4 Years Spent in the University

Table 5.1.4 shows distribution of number of years spent in the university, reason for difference between number of years already spent in the university and the year of study and difficulties in paying school fees or buying school materials by respondents by sex.

Majority of the respondents have spent 1-2 years (83.4%). A higher proportion of those who have spent 1-2 years were males while a higher proportion of females have spent 3-4 years. The difference was not statistically significant.

Eighty two (17%) of the respondents had disparity in the number of years already spent and the year of study. More males reported strike as the reason for disparity while more females reported academic difficulty. The differences were not statistically significant.

One hundred and sixty of the respondents (33.2%) sometimes had difficulty paying school fees or buying school materials while 18 (3.7%) always had difficulty in paying school fees or buying school materials. More males than females always and sometimes, had difficulty. But the difference was not statistically significant.

Table 5.1.4: Frequency distribution of respondents by number of years already spent in the university, reason for discrepancy between the number of years in the university and course level (year of study).

Sex Male Female Total Statistics Number of 1 – 2 236 (85.2%) 166 (81.0%) 402 (83.4%) χ2 = 3.641a years already 3 – 4 34 (12.3%) 35 (17.1%) 69 (14.3%) df = 3 spent in the p = 0.32 5 – 6 5 (1.8%) 4 (2.0%) 9 (1.9%) university N.S 7 – 8 2 (0.7%) 0 (.0%) 2 (0.4%) Total 277 (100.0%) 205 (100.0%) 482 (100.0%) Reason for Strike 18 (42.9%) 16 (40.0%) 34 (41.5%) χ2 = 4.54 difference Academic df = 2 between number 5 (11.9%) 12 (30.0%) 17 (20.7%) p = 0.10 difficulty of years already N.S spent in the Others 19 (45.2%) 12 (30.0%) 31 (37.8%) university and year of study Total 42 (100.0%) 40 (100.0%) 82 (100.0%) Difficulties in Yes, I χ2 = 2.36 paying school sometimes 98 (35.4%) 62 (30.2%) 160 (33.2%) df = 2 fees or buying do p = 0.31 school materials N.S Yes, I 12 (4.3%) 6 (2.9%) 18 (3.7%) always do

No, I don't 167 (60.3%) 137 (66.8%) 304 (63.1%) Total 277 (100.0%) 205 (100.0%) 482 (100.0%)

N.S = Not significant

5.2 General and Specific (BFS) Psychiatric Morbidity

Table 5.2.1 shows the GHQ scores, BFSS scores, GHQ status, BFS status, mean, standard deviation and median scores of the respondents on GHQ and BFSS. About two third

(63.1%) of the respondents scored 0-4 on GHQ-28 (GHQ negative). GHQ morbidity defined as a score of 5 and above. One hundred and seventy eight (36.9%) were GHQ positive. Thus, prevalence of general psychiatric morbidity was 36.9%. Distribution of respondents by BFS status measured by the Brain Fag Syndrome Scale (BFSS), while cases defined as a minimum total score of 6 and a score of at least 1 on each of items 4 and 5 on the BFSS. Two hundred and seven of the respondents, representing 42.9%, identified as cases while 275 (57.1%) were non-cases. Thus, prevalence of Brain Fag Syndrome was 42.9%. See appendix I for confidence interval determination (Easycalculation.com, 2012).

There was a positive, though weak correlation between BFSS scores and GHQ scores.

The correlation coefficient r, was 0.20 and p was 0.001.

Table 5.2.1: Frequency distribution of respondents by GHQ-28 and BFSS scores.

GHQ score Frequency Percent Cumulative Percent 0 – 4 304 63.1 63.1 5 – 9 127 26.3 89.4 10 - 14 47 9.8 99.2 > 16 4 0.8 100.0 Total 482 100.0 BFSS score 0 – 2 25 5.2 5.2 3 – 5 206 42.7 47.9 6 – 8 217 45.0 92.9 9 – 11 30 6.2 99.1 12 – 14 4 0.8 100.0 Total 482 100.0 GHQ positive 178 36.9 36.9 GHQ negative 304 63.1 100.0 Total 482 100.0 BFS Non-caseness 275 57.1 57.1 BFS Caseness 207 42.9 100.0 Total 482 100.0

GHQ BFSS Mean : 4.16 5.61 SD: ± 3.98 2.07 Median: 3.00 6.00

Table 5.2.2 shows the association between GHQ status/score and BFS. Fifty seven point three percent of those who were GHQ positive had BFS whereas only 34.5% of GHQ negative students had BFS. Meanwhile, 42.7% of students who were GHQ positive were BFS non-caseness as against 65.3% of GHQ negative students that were BFS non-caseness. These differences were statistically significant. Similarly, GHQ scores significantly varied between

BFS caseness and BFS non-caseness students. The differences were also statistically significant.

Table 5.2.2: Association between General Psychiatric Morbidity and BFS

BFS BFS non- Total Statistics caseness caseness GHQ status Positive 2 102 178 χ = 23.74 76 (42.7%) (57.3%) (100.0%) df = 1 n = 482 p = 0.001* Negative 105 199 304 (34.5%0 (65.5%) (100.0%) GHQ score 0-4 103 200 303 χ2 = 28.62 (34.0%) (66.0%) (100.0%) df = 3 n = 482 5-9 75 129 p = 0.001* 54 (41.9%) (58.1%) (100.0%) 10-14 28 18 46 (60.9%) (39.1%) (100.0%)

1 3 4 15 and above (25.0%) (75.0%) (100.0%)

* = Significant at p < 0.05

5.3 Stimulant Use

5.3.1 General Stimulant Use

Table 5.3.1 shows the lifetime, past year and past month use of stimulants in general, age at first use of stimulant, particular stimulant used most recently (previous 30 days prior to this study), and reason for using stimulant by the respondents. Two hundred and thirty five respondents, representing 48.8% had used stimulants without a doctor or health worker telling them to do so. Thus, the lifetime prevalence of stimulant use was 48.8% One hundred and ninety nine respondents; representing 41.3% had used stimulants in the 12 months prior to this study without a doctor or health worker's recommendation. Thus, the past year prevalence of stimulant use was 41.3%. Thirty nine-point four percent, representing 190 of the respondents had used stimulants in the past 30 days prior to this study. Therefore, the past month prevalence of stimulants use was 39.4%. A very high proportion of respondents, 174 (74.04%), first took stimulants when they were less than or 12 years, while 11 respondents (4.68%) were above 16 years when they first took stimulants. Of the respondents who recently used stimulants, the highest proportion, 112 (58.95%) had taken coffee recently, while 53 (27.89%),

24 (12.63%) and 1(0.53%) respondent had taken kola nut, coffee and kola nut in combination and ephedrine. Ninety point two one percent of those who have ever used stimulant, used stimulant to keep awake to study.

Table 5.3.1: Frequency distribution of respondents by lifetime, past year and past month use of general stimulants, age at first use, particular stimulant used most recently and reason for using stimulant.

Variable Response Frequency Percent Life time use 235 48.8 n = 482 Yes Past year use n = 482 Yes 199 41.3 Past month use No 292 60.60 n = 482 Yes 190 39.4 Age at first use 12 years old or less 174 74.04 n = 235 13 - 16 years old 50 21.28 17 years old or more 11 4.68 Most recently used Coffee 112 58.95 stimulant (past 30 days) Kola nut 53 27.89 n = 190 Coffee and Kola nut 24 12.63 Ephedrine 1 0.53 Reason for using 212 90.21 stimulant To keep awake to study n = 235 For relaxation 15 6.38

To keep awake to study and 2 0.85 I enjoy taking it I take it because others do 2 0.85 To keep awake to study and 1 0.43 for relaxation Others 3 1.28

5.3.2 Specific Stimulants Use

Table 5.3.2 shows distribution of respondents by lifetime, past year, past month and age at first use of cocaine, and past month use of coffee, kola nut, and combination of coffee and kola nut.

Only 2 (0.4%) of the respondents had ever taken cocaine. Thus, lifetime prevalence of cocaine use was 0.4%. Only one respondent had taken cocaine in the previous 12 months. This represented a past year prevalence of cocaine of 0.2%. None of the respondents had taken cocaine in the previous 30 days before the study. Thus, past month prevalence rate for cocaine was 0%. The two respondents who had ever taken cocaine did so for the first time between 15 and 18 years.

Meanwhile, past month use prevalence of coffee, kola nut, and combination of the two were 28.22%, 15.98% and 4.98% respectively.

Table 5.3.2: Showing the distribution of respondents by life time, past year, past month and age at first use of cocaine; past month use of coffee, kola nut, and combination of coffee and kola nut.

Frequency Percent

Cocaine Lifetime use Yes 2 0.4 n = 482 Past year use Yes 1 0.2 n = 482 Past month use Yes 0 0.0 n = 482 Age at first use 15-16 years old 1 0.2 n = 482 17-18 years old 1 0.2 Past month use Yes Coffee n = 482 136 28.22 Past month use Yes Kola nut n = 482 77 15.98 Coffee and Kola Past month use Yes nut n = 482 24 4.98

Table 5.3.3 shows the comparison of the sex, age, Faculty and number of years already spent in the university between students who had used coffee in the previous 30 days prior to the study and those who had not. The differences in these variables between users and non-users were not statistically significant.

Table 5.3.3: Socio-demographic characteristics of specific stimulant users (Coffee).

Coffee users Non-coffee users Total Statistics χ2 = 0.20 Sex Male 76 (27.4%) 201 (72.6%) 277 (100.0%0 df = 1 Female 60 (29.3%) 145 (70.7%) 205 (100.0%) p = 0.66 Total 136 (28.2%) 346 (71.8%) 482 (100.0%) N.S χ2 = 0.24 Age 15-26 130 (28.0%) 334 (72.0%) 464 (100.0%) df = 1 27-35 6 (33.3%) 12 (66.7%) 18 (100.0%) p = 0.6 Total 136 (28.2%) 346 (71.8%) 482 (100.0%) N.S χ2 = 5.11 Faculty Education 19 (42.2%) 26 (57.8%) 45 (100.0%) df = 3 Social and p = 0.16 Management 68 (26.6%) 188 (73.4%) 256 (100.0%) N.S Sciences Applied Sciences (Pharmacy, Basic Medical 26 (25.5%) 76 (74.5%) 102 (100.0%) Sciences, Life Sciences) pure sciences (physical 23 (29.1%) 56 (70.9%) 79 (100.0%) sciences) Total 136 (28.2%) 346 (71.8%) 482 (100.0%) Number of 1 – 2 109 (27.1%) 293 (72.9%) 402 (100.0%) χ2 = 1.45 years already 3-8 27 (33.8%) 53 (66.2%) 80 (100.0%) df = 1 spent in the p = 0.23 136 (28.2%) 346 (71.8%) 482 (100.0%) university Total N.S

N.S = Not significant

5.4 The Association between Mental Health Status and Stimulant Use.

Table 5.4.1: shows the association between general psychiatric morbidity and stimulant use. Whereas 45.8% of the respondents who had used stimulants in the previous 30 days were GHQ positive, only 31.2% of those who did not use stimulants in the same period were GHQ positive. On the other hand, 54.2% of the respondents who had used stimulant, in the previous 30 days were GHQ negative, 68.8% of those who did not use stimulant in the previous 30 days were GHQ negative. These differences were statistically significant.

It also shows that there was no statistically significant association between past month coffee use and general psychiatric morbidity, but shows the association between general psychiatric morbidity and past month kola nut use statistically significant, in that whereas

55.8% of the respondents who had used kola nut in the previous 30 days were GHQ positive, only 33.3% of those who did not use kola nut in the previous 30 days were GHQ positive. On the other hand, 44.2% of the respondents who had used kola nut in the previous 30 days were

GHQ negative, 66.7% of those who did not use kola nut in the previous 30 days were GHQ negative. These differences were statistically significant.

Table 5.4.1: Association between general psychiatric morbidity and past 30 days general stimulant use.

GHQ positive GHQ negative Total Statistics General stimulant 87 (45.8%) 103 (54.2%) 190 (100.0%) χ2 = 10.57 users df = 1 Non- p = 0.001* stimulant 91 (31.2%) 201 (68.8%) 292 (100.0%) users Total 178 (36.9%) 304 (63.1%) 482 (100.0%)

Coffee users 59 (43.4%) 77 (56.6%) 136 (100.0%) χ2 = 3.39 Non-coffee df = 1 119 (34.4%) 227 (65.6%) 346 (100.0%) users p = 0.07 N.S 178 (36.9%) 304 (63.1%) 482 (100.0%) Total kola nut 2 43 (55.8%) 34 (44.2%) 77 (100.0%) χ = 14.08 users df = 1 Non-kola nut p = 0.001* 135 (33.3%) 270 (66.7%) 405 (100.0%) users

Total 178 (36.9%) 304 (63.1%) 482 (100.0%)

* = Significant at p < 0.05, N.S = Not significant

Table 5.4.2 shows the association between BFS-caseness and general stimulant use in the previous 30 days, 12 months and lifetime. There was a statistically significant association between past month, past year and lifetime general stimulant use and BFS-caseness. For example, over 3 out of every 4 past month general stimulant users (78.4%) were BFS-positive while only 21.6% (one in 5) of general stimulant users were BFS non-caseness. Only 19.9%

(roughly 1 in 5) of non-users of general stimulants in the past month were BFS-caseness while

80.1% of non-general stimulant users were BFS-negative. These differences were statistically significant.

It also shows the association between BFS-caseness and coffee use in the previous 30 days. 77.2% of coffee users were BFS-positive while only 22.8% of coffee users were BFS non-caseness. Only 29.5% of non-users of coffee were BFS-caseness while 70.5% of non-users of coffee were BFS non-caseness. These differences were statistically significant.

Further more, it shows the association between BFS-caseness and kola nut use in the previous 30 days; 79.2% of kola nut users were BFS-caseness while only 20.8% of kola nut users were BFS non-caseness. Only 36.0% of non-users of kola nut were BFS-caseness while

64.0% of non-users of kola nut were BFS non-caseness. These differences were statistically significant.

Table 5.4.2: Association of BFS caseness and general stimulant use.

BFS Caseness BFS non- Total Statistics caseness  Past 30 days χ2 = 1.61 general 149 (78.4%) 41 (21.6%) 190 (100.0%) df = 1 stimulant p = 0.001* users Non- stimulant 58 (19.9%) 234 (80.1%) 292 (100.0%) users Total 207 (42.9%) 275 (57.1%) 482 (100.0%) Past 12 χ2 = 1.46 months df = 1 general 150 (75.4%) 49 (24.6%) 199 (100.0%) p = 0.001* stimulant users Non- stimulant 57 (20.1%) 226 (79.9%) 283 (100.0%) users Total 207 (42.9%) 275 (57.1%) 482 (100.0%) Life time χ2 = 1.71 general 172 (73.2%) 63 (26.8%) 235 (100.0%) df = 1 stimulant p = 0.001* users Non- stimulant 35 (14.2%) 212 (85.8%) 247 (100.0%) users Total 207 (42.9%) 275 (57.1%) 482 (100.0%) Coffee users 105 (77.2%) 31 (22.8%) 136 (100.0%) χ2 = 90.76 Non-coffee df = 1 102 (29.5%) 244 (70.5%) 346 (100.0%) users p = 0.001* Total 207 (42.9%) 275 (57.1%) 482 (100.0%) Kola nut 2 61 (79.2%) 16 (20.8%) 77 (100.0%) χ = 49.21 users df = 1 Non-kola nut 146 (36.0%) 259 (64.0%) 405 (100.0%) p = 0.001* users Total 207 (42.9%) 275 (57.1%) 482 (100.0%)

* = Significant

5.5. Socio-demographic Characteristics and Psychiatric Morbidity (General and

Specific)

Table 5.5.1 shows the comparison of gender, age and marital status between BFS cases and non-cases; and their comparison between GHQ positive and negative. Although a higher proportion of females were BFS cases compared to males, the difference was not statistically significant. One may conclude that males and females were equally affected. The highest proportion of BFS caseness was found among those in the age group 27-32 years, and a lower proportion of students who were single were BFS cases, the differences were not statistically significant.

It also shows that the sex, age and marital status did not significantly differentiate between GHQ positive and negative respondents.

There was a very low positive correlation between GHQ score and age. The correlation coefficient r, was + 0.03; and p was 0.54.

Table 5.5.1: Comparison of socio-demographic variables of BFS caseness and non-caseness on one hand and GHQ positive and negative on the other hand.

Specific Psychiatric Morbidity General Psychiatric Morbidity BFS GHQ +VE -VE Total Statistics +VE -VE Total Statistics Total 207 275 482 178 304 482 2 2 Sex Male 115 162 276 χ = 0.54 108 169 277 χ = 1.19 (41.7%) (58.5%) (100.0%) df = 1 (39.0%) (61.0%) (100.0%) df = 1 Female 92 113 205 p = 0.46 70 135 205 p = 0.28 N.S N.S (44.9%) (55.1%) (100.0%) (34.1%) (65.9%) (100.0%) 2 2 Age 15-20 70 101 171 χ = 5.54 57 114 171 χ = 1.59 (40.9%) (59.1%) (100.0%) df = 3 (33.3%) (66.7%) (100.0%) df = 3 21-26 126 167 293 p = 0.14 114 179 293 p = 0.66 N.S N.S (43.0%) (57.0%) (100.0%) (38.9%) (61.1%) (100.0%) 27-32 9 3 12 5 7 12 (75.0%) (25.0%) (100.0%) (41.7%) (58.3%) (100.0%) 33-41 2 4 6 2 4 6 (33.3%) (66.7%) (100.0%) (33.3%) (66.7%) (100.0%0 Single 2 2 Marital 202 269 471 χ = 0.04 173 298 471 χ = 1.33 status (42.9%) (57.1%) (100.0%) df = 1 (36.7%) (63.3%) (100.0%) df = 1 Married/ P = 0.62 P = 0.52 5 6 11 5 6 11 Separated N.S N.S (45.5%) (54.5%) (100.0%) (45.5%) (54.5%) (100.0%)

N.S = Not significant

Table 5.5.2 shows the comparison of Faculty, number of years already spent in the university, residence and difficulties in paying school fees or buying school materials between

BFS cases and non-cases; and the comparison of these variable between GHQ positive and

GHQ negative students.

None of these variables significantly differentiated BFS cases from non-cases. But

Faculty and difficulties in paying school fees or buying school material significantly differentiated between GHQ positive and GHQ negative respondents while number of years already spent in the university and residence did not. The highest proportion of GHQ positive students was found in the Faculty of Education while the least proportion was found in the

Faculty of Physical Sciences. And the highest proportion of GHQ positive students was found among students who always had difficulties in paying school fees or buying school materials.

Table 5.5.2: Comparison of socio-demographic variables of BFS cases and non-cases; and comparison between GHQ positive and negative respondents.

Specific Psychiatric Morbidity General Psychiatric Morbidity BFS GHQ +VE -VE Total Statistics +VE -VE Total Statistics Total 207 275 482 178 304 482 2 2 Faculty Education 26 19 45 χ = 5.16 26 19 45 χ =19.00 df = 3 (57.8%) (42.2%) (100.0%) df = 3 (57.8%) (42.2%) (100.0%) p = 0.16 Social and p = 103 153 256 103 153 256 Management N.S 0.001* (40.2%) (59.8%) (100.0%) Sciences (40.2%) (59.8%) (100.0%) Applied Sciences (Pharmacy, 42 60 102 32 70 102 Basic (31.4%) (68.6%) (100.0%) Medical (41.2%) (58.8%) (100.0%) Sciences, Life Sciences) Pure Sciences 36 43 79 17 62 79 (Physical (21.5%) (78.5%) (100.0%) Sciences) (45.6%) (54.4%) (100.0%) 2 2 Number of 1-2 167 235 402 χ = 1.95 148 254 402 χ = 0.01 df = 1 (36.8%) (63.2%) (100.0%) df = 1 years (41.5%) (58.5%) (100.0%) p = 0.16 p = 0.91 already 3-8 N.S 50 40 40 80 30 80 N.S spent in the (62.5% (50.0%) (50.0%) (100.0%) (37.5%) (100.0%) university ) 2 2 Residence Home χ = 1.03 22 χ = 2.91 13 23 36 df = 2 14 36 df = 2 (61.1% (36.1%) (63.9%) (100.0%) p = 0.60 (38.9%) (100.0%) p = 0.23 N.S ) N.S University 171 109 148 257 86 257 hostel (66.5% (42.4%) (57.6%) (100.0%) (33.5%) (100.0%) ) Private/Non- 111 home 85 104 189 78 189 accommodati (58.7% (45.0%) (55.0%) (100.0%) (41.3%) (100.0%) on ) Yes, I 2 2 Difficulties χ = 1.24 89 χ =12.0 sometimes do 73 87 160 df = 2 71 160 6 in paying (55.6% (45.6%) (54.4%) (100.0%) p = 0.54 (44.4%) (100.0%) df = 2 school fees N.S ) p = Yes, I always or buying 6 12 18 11 7 18 0.002* do school (33.3%) (66.7%) (100.0%) (61.1%) (38.9%) (100.0%) No, I don't materials 128 176 304 96 208 304 (42.1%) (57.9%) (100.0%) (31.6%) (68.4%) (100.0%)

* = Significant at p < 0.05, N.S = Not significant

5.6 Comparison of the Socio-demographic characteristics of students who used

stimulants and had BFS and those who used stimulants but did not have BFS.

Table 5.6 shows the comparison of gender, age, Faculty, number of years already spent in the university, reasons for difference between number of years already spent in the university and year of study and difficulties in paying school fees or buying school materials between past month general stimulant users that had BFS and past month general stimulant users that did not have BFS.

A higher proportion of females (86.6%) compared to males (72.2%) where stimulant users that had BFS while a higher proportion of males (27.8%) compared to females (13.4%) were stimulant users that did not have BFS. These differences were statistically significant.

However, age, Faculty, number of years already spent in the university, reasons for difference between number of years already spent in the university and year of study and difficulties in paying school fees or buying school materials did not significantly differentiate between stimulant users that had BFS and stimulant users that did not have BFS.

Table 5.6: Showing comparison of the socio-demographic characteristics of respondents who used stimulants and were BFS cases and those who used stimulants but were non-cases

Stimulant Stimulant users Total Statistics users that had that did not have BFS BFS n = 149 n = 41 2 Sex Male 78 (72.2%) 30 (27.8%) 108 (100.0%) χ = 5.68 df= 1 n = 190 Female 71 (86.6%) 11 (13.4%) 82 (100.0%) P= 0.02*

Age 18-26 144 (79.6%) 37 (20.4%) 181 (100.0%) χ2 = 2.92 n = 190 df= 1 27-35 5 (55.6%) 4 (44.4%) 9 (100.0%) P= 0.10 N.S

2 Faculty Education 21 (87.5%) 3 (12.5%) 24 (100.0%) χ = 2.63 Social and df= 3 n = 190 P= 0.46 Management 66 (75.0%) 22 (25.0%) 88 (100.0%) Sciences N.S Applied Sciences (Pharmacy, Basic Medical 35 (83.3%) 7 (16.7%) 42 (100.0%) Sciences, Life Sciences) Pure Sciences (Physical 27 (75.0%) 9 (25.0%) 36 (100.0%) ciences) 2 Number of 1-2 117 (76.0%) 37 (24.0%) 154 (100.0%) χ = 2.88 df= 1 years already P= 0.12 spent in the N.S 3-8 32 (88.9%) 4 (11.1%) 36 (100.0%) university n = 190 2 Reasons for Strike 15 (93.8%) 1 (6.2%) 16 (100.0%) χ = 1.70 difference df= 2 between Academic P= 0.58 6 (85.7%) 1 (14.3%) 7 (100.0%) number of years difficulty N.S already spent in the university and year of Others 10 (76.9%) 3 (23.1%) 13 (100.0%) study n= 36 2 Difficulties in Yes, I χ = 2.11 53 (84.1%) 10 (15.9%) 63 (100.0%) df=2 paying school sometimes do P= 0.37 fees or buying Yes, I always N.S 4 (66.7%) 2 (33.3%) 6 (100.0%) school do materials No, I don't 92 (76.0%) 29 (24.0%) 121 (100.0%) n = 190

* = Significant, N.S = Not significant

5.7 Comparison of general psychiatric morbidity between respondents that used general stimulants and were BFS cases and those who used but were non-cases

Table 5.7 shows that GHQ morbidity was significantly associated with past 30 days stimulant users that had BFS; 87.4% of GHQ positive students were stimulant users that had

BFS while only 12.6% of GHQ positive students were stimulant users that did not have BFS.

Similarly, 70.9% of GHQ negative students were stimulant users that had BFS while 29.1% of

GHQ negative students were stimulant users that did not have BFS.

Table 5.7: Comparison of GHQ morbidity between general stimulant users that had BFS and users that did not have BFS

Stimulant Stimulant Total Statistics users that users that had BFS did not have BFS GHQ Positive 2 76 (87.4%) 11 (12.6%) 87 (100.0%) χ = 7.57 morbidity df=1 n = 190 P= 0.006* Negative 73 (70.9%) 30 (29.1%) 103 (100.0%)

* = Significant

5.8 Logistic regression

A logistic regression performed in order to elucidate the relationship between the various variables; with BFS as the dependent variable. The independent variables were past 30 days general stimulant use, past 30 days coffee use, past 30 days kola nut use, age, sex, number of years already spent in the university and GHQ status. Past 30 days general stimulants use and GHQ Score emerged as predictive of BFS. The GHQ is not surprising as it was measuring a state, part of which BFSS was also measuring.

Chapter Six

DISCUSSION

6.1 General

Self rated instruments are widely used to elicit responses for research purposes, probably as a result of the fact that it is easy to administer, and it allows for easy comparison among studies. The response rate gotten in this study (99.2%) is like that reported by Osasona

(2009) and Uchendu (2009), 99% and 96.2% respectively. One may safely conclude that using self report instruments to gather information is reliable.

The 482 instruments analysed had significant Goodness of fit with the general population of undergraduate students of the University of Benin, which imply that the sample is a good representation of the general undergraduate students’ population of the University.

Hence genealisations of findings from this study to the general undergraduate students' population of the university. In addition, appendix H shows that the study is properly powered.

6.2 Socio-demographic characteristics of the respondents.

6.2.1. Sex

More males than females were sampled in this study. Osasona (Osasona, 2009) similarly sampled more males than females in his study. The ratio of males to females in this study is similar to the ratio of males to females in the general population of the undergraduate students sampled, 1.35:1 and 1.5:1 respectively.

This higher proportion of males may reflect the traditional tendency to provide more education for male children. Traditionally, it is believed that male children will perpetuate the family lineage.

Yunusa, Obembe, Madawaki and Asogwa (2011) reported a male to female ratio of 7:3 in their study on Usmanu Danfodiyo University Students in Sokoto State. This much higher male to female ratio may reflect a lower female literacy level in the Northern Nigeria compared to the South.

6.2.2. Age

The age range of the respondents was 17 to 40 years while the mean age was 21.66 years ± 2.63. This is not very different from the mean age of 23.19 years ± 3.63 and age range of 15 – 59 reported by Osasona (Osasona, 2009) and the mean age of 23.2 ± 3.39 and age range of 18 to 41 years reported by Uchendu (Uchendu, 2009).

6.2.3 Marital status

Majority of the respondents were single 471 (97.7%) This is not surprising since the mean age was 21.66 ± 2.63 years and the respondents are students. Similarly, Osasona in 2009 reported that majority of his respondents were single (94.9%); but Yunusa et al (2011) reported that 85.1% of their respondents were single. This relatively lower rate of singlehood in their study may reflect the fact that people marry early in the Northern Nigeria, especially the females.

6.2.4 Religion

474 (98.3%) of the respondents were Christians. The predominant religion in the South-

South (main catchment area of the University) Nigeria is Christianity.

6.2.5 Hardship encountered in school

Majority of the respondents (83.4%) had spent 1 to 2 years as expected, since the questionnaires administered on 3rd year undergraduate students in their first semester. Strike was the main contributor to disparity between number of years already spent in the university and the year of study. More than one-third of the respondents (36.9%) had difficulties in paying school fees or buying school materials. This reflects the economic circumstances of

Nigeria. Relatively higher proportion of males than females experience this difficulty. Parents, family members and friends may give financial support more to females. Osasona (2009) also reported more males than females to have financial difficulty.

6.3 General and Specific psychiatric morbidity

Prevalence of general psychiatric morbidity was 36.9%. This rate is worrisome in view of the positive association between psychiatric morbidity and study difficulty (Prince, 1960;

Fatoye, 1998 and Osasona, 2009).Students need be in a state of good mental health to attend to their academic activities, since they may experience study difficulty with psychiatric morbidity. Study difficulty may in turn lead to students' wastage and or drop out.

Consequently, the society will be at peril by endangering her future elites. The imperative to reduce prevalence of general psychiatric morbidity is obvious. The rate of general psychiatric morbidity (36.9%) reported by this study is similar to that reported by Osasona, (Osasona,

2009) who reported a rate of 33.5% and Uchendu’s report of 35.5% (Uchendu, 2009). But

Akhigbe reported 25.3% (Akhigbe, 1996). Akhigbe’s study was carried out among medical students only and he used a two stage diagnostic procedure.

Osasona (2009) found a strong association between study difficulty and psychiatric morbidity. He reported that "more GHQ positive respondents belonged to the study difficulty group". It is difficult to prove cause and effect relationship between study difficulty and

67 psychiatric morbidity, therefore, need for studies to look at this relationship. At the moment it seems likely that study difficulty and psychiatric morbidity “cause and effect” each other.

Again, this emphasises the need to reduce psychiatric morbidity among students which may also reduce study difficulty and thus better academic outcome for them. The prevalence rate of

BFS in this study was 42.9%. This rate is lower than the 54% reported by Prince (Prince,

1962). The fact that Prince's study is an older study may explain the difference in prevalence rate. However, the 42.9% is higher than the prevalence rate of BFS of 24.2%, 25% and 38.9% reported by Eeguranti (2006), Peltzer, Cherian and Cherian (1998) and Fatoye (2005) respectively. This rate may have been lower because the studies were among secondary school students who may have less academic challenges than what obtain in the university. The 36% prevalence rate of BFS reported by Uchendu (2009) may have been because of his sampling method which recruited participants from all 6 fully developed faculties of the University of

Abuja. This high prevalence of BFS underscores the need to quickly put machinery in place to enhance students' mental health especially as it concerns BFS which is associated with study difficulty (Fatoye and Morakinyo, 2003) and (Uchendu, 2009). There was a positive and significant correlation between GHQ score and BFS scale score. General psychiatric morbidity was significantly associated with BFS. A higher percentage of respondents who had general psychiatric morbidity had BFS. Fatoye (2004) and Uchendu (2009) also reported a positive correlation. The findings of this study support the finding by Uchendu in 2009. He found that

BFS was strongly associated with the ‘Triad'. The ‘Triad' consists of psychiatric morbidity, psychoactive substance use/abuse and study difficulty co-occurring in the same individual.

Uchendu reported stimulants the most commonly used psychoactive substance by his respondents; second only to alcohol. In a similar way, the findings of this study showed that

BFS was strongly associated with stimulant use and psychiatric morbidity. This study did not look at study difficulty among the respondents. Uchendu further found out that respondents

68 with BFS were eight times more at risk of having the “Triad”. Consequently, reducing the prevalence of BFS may help to check the prevalence of ‘The Triad’.

6.4 Socio-demographic Characteristics and Psychiatric Morbidity.

Gender, age, marital status, Faculty, number of years already spent in the university, residence, difficulties in paying school fees or buying school materials compared between

GHQ positive and GHQ negative students. Faculty and difficulties in paying school fees significantly differentiated them. The highest proportion of GHQ positive students was found in the Faculty of Education while the least was found in the Faculty of Physical Sciences.

General psychiatric morbidity was highest among respondents who had difficulties in paying school fees. Osasona found GHQ positive students highest in the Faculties of Agriculture and

Education (Osasona, 2009). Faculty of Agriculture was not incorporated into this study by the sampling technique. There was no statistically significant correlation between GHQ score and age. This was the same finding on University of Abuja undergraduate students (Uchendu,

2009). There was no significant difference between the socio-demographic characteristics (sex, age, marital status, Faculty, number of years already spent in the university, residence, difficulties in paying school fees or buying school materials) of the students who had BFS and those who did not have BFS, thus accepting hypothesis 2. Prince (1960), Morakinyo (1980),

Guinness (1992) Peltzer, Cherian and Cherian (1998) and Peltzer (2002) reported low socio- economic class and financial difficulty associated with BFS. Fatoye (2004) found an association between financial strain and BFS but reported that there was no difference in the gender, family set up, residence and parental relationship of BFS cases and Non-cases. Peltzer,

Cherian and Cherian (1998) also reported that there was no significant difference between prevalence of BFS in males and females. However, older studies reported that BFS was commoner in males than females. (Prince, 1960; Boroffka and Marinho, 1963; Neki and

Marinho, 1968; German, Assael and Muhangi, 1970). But these studies are old, and further explained by the fact that more females are now attending school. In the past, many parents preferentially educated male children. The number of parents who have this mindset seems to have reduced as more females are now in school. The numbers of females using stimulants may have also increased. This study as well as some other studies has shown that using stimulants to keep awake to study is strongly associated with developing BFS. Also, that the drive to achieve academically is now equal in both gender, hence both gender equally use stimulants to keep awake to study. In the past, society saw high academic pursuit as the prerogative of males. However, the matter of equal prevalence of BFS in males and females is a focus for future research.

6.5 Stimulant use

6.5.1 Pattern of stimulant use

The lifetime use, past year use and past month use prevalence rates of general stimulant were 48.8%, 41.3% and 39.4% respectively. Majority of stimulant users first used stimulant while they were 12-year-old or less (74.04%). This represents primary school age. Invariably efforts at curtailing the use of stimulant must start very early and incorporating such strategy into primary school curriculum will be worthwhile. The prevalence rate of stimulant use reported by Eeguranti (Eeguranti, 2006) decreased in a similar fashion as reported in this study; lifetime, prevalence rate for stimulant use was 88.6%, 1 year prevalence rate was 37.9% while past 30 days prevalence rate was 20.3%. His reported lifetime prevalence rate may have been higher than what is found in this study because of location of his study, which was the South-

Western Nigeria, especially since kola nut was the stimulant most used by his respondents. He also reported past month coffee and kola nut use prevalence of 6.2% and 11.2% respectively.

Uchendu (Uchendu, 2009) reported prevalence of 35.7%, 33.7% and 29.8% for life time use,

70 past year use and past month use respectively of stimulants. Adelekan (1989) and Yunusa et al

(2011) reported a lifetime prevalence of stimulant use of 47% and 52.6% respectively. This is similar to the 48.8% found in this study. However Fatoye (2003) reported 37.5%. The finding that most respondents in this study began to use stimulant in the primary school age is akin to the finding of Adelekan (1989). Adelekan (1989) Eeguranti (2006) and Igwe, Ojinnaka,

Ejiofor, Emechebe and Ibe, ( 2009), Oshodi, Aina and Onajole (2010) and Yunusa et al (2011) reported coffee and kola nut as the most commonly used stimulant like it was found in this study. Nevamdosky also reported coffee and kola nut to be among the most often used substances by University of Benin students (Nevamdosky, 1985). The current prevalence rate of 52.1% and 23.0% for coffee and kola nut respectively, reported by Yunusa et al (2011) is higher than the 28.22% and 15.96% respectively found in this study. Probably as a result of the

Islāmic religion which is popular in the Northern Nigeria and which forbade the use of commonly used substance like alcohol. And so people in this part of Nigeria are likely to make use of coffee and kola nut which are readily available and are not forbidden by Islam. It is worthy of note that Yunusa et al (2011) reported use of atahye while this study did not. Atahye appears new to Nigeria and like the authors documented, introduced from Republic of Niger which has a boundary with Sokoto, the study area. The study reported lifetime, past year and past month prevalence rates of cocaine use of 0.4%, 0.2% and 0.0% respectively. The very low prevalence rate of cocaine use reported in this study is not unique. Other studies have similarly reported a low prevalence rate. For example, Yunusa et al (2011) did not report use of cocaine in their study. Nevadomsky in 1981 reported that no clear evidence exists for use of cocaine among secondary school students in the then Bendel State of Nigeria (Nevadomsky, 1981).

Fatoye reported a current prevalence of cocaine use of 0.2% (Fatoye, 2003), Adelekan reported current prevalence of 0.3% (1989). But Oshodi, Aina and Onajole reported current use prevalence for cocaine to be 1.9% (2010) and Uchendu reported 2.7% (2009). These two last

71 studies were carried out in Lagos and Abuja respectively and the fact that these two cities occupy a higher socio-economic profile may explain the reason for the relatively higher prevalence of cocaine use in these cities. It is however worthy of note that respondents are likely to under report use of illicit substances like cocaine (Ononye and Morakinyo, 1994). The main reason why the students used stimulants was to keep awake to study; just like other researchers have found (Morakinyo, 1980; Adelekan, 1989; Eeguranti, 2006; Fatoye and

Morakinyo, 2008; Igwe et al, 2009; Oshodi, Aina and Onajole, 2010; Yunusa et al, 2011).

6.5.2 Socio-demographic characteristics of stimulant users.

The study compared sex, age, Faculty, number of years already spent in the university, between past month stimulant users and non-users; none of the variables significantly differentiated between them.

6.5.3 Association between stimulant use and general psychiatric morbidity

General psychiatric morbidity was found to be significantly associated with past month use of general stimulant and kola nut use. There was no significant association between general psychiatric morbidity and past month use of coffee.

6.5.4 Comparison of the socio-demographic characteristics and other factors of students

that used stimulant and had BFS and those that used stimulant but did not have

BFS.

Gender and GHQ morbidity were significantly different between the students who used stimulant and had BFS and those that used stimulant but did not have BFS. Stimulant users that had BFS were more among the female students thus, rejecting hypothesis 3. The study showed that there was a significant association between BFS and general stimulant use. There was also significant association between BFS and coffee and kola nut use. A higher proportion of

72 general stimulant users, coffee users and kola nut users had BFS. And majority of stimulant users did use stimulants to keep awake to study. This lent credence to the Psychophysiological

Theory of BFS proposed by Morakinyo. The Psychophysiological Theory states that due to anxiety over academic outcome, students may use stimulants to keep awake to study. The hyperarousal state (sleep deprivation) leads to development of cognitive symptoms. Studying is then hampered and anxiety over academic outcome is further heightened. Thus, a vicious cycle formed. Morakinyo (1980), Fatoye and Morakinyo (2003), Eeguranti (2006), Ola (2007) and

Uchendu (2009) reported significant association between BFS and stimulant use. Hypothesis 1 is thus rejected; prevalence of BFS in students who use stimulant was higher than that in students who did not use stimulant and the difference was statistically significant. Use of general stimulant and general psychiatric morbidity were predictors of BFS. As shown in table

5.8, a number of variables subjected to logistic regression with BFS as the dependent variable.

Some of the variables were independently statistically significantly associated with BFS (that is current coffee use, current kola nut use, current use of any stimulant and general psychiatric morbidity). The logistic regression statistics showed that development of BFS was not related to any particular stimulant, but stimulants in general. General psychiatric morbidity was also a predictor of BFS. However, BFS is a kind of psychiatric morbidity. Consequently, control of stimulants use and better mental well-being would curtail the prevalence rate of BFS. On the other hand, the Forbidden Knowledge Theory of BFS is not supported by the findings of this study. Western education has come to stay. The findings of the study does not show that the students are rejecting western education; if anything, they are in love with western education, hence majority of the students in a bid to achieve academically are using stimulants to stay awake and study western education more. However, the Forbidden Knowledge Theory of BFS may have been relevant at the outset of western education in Nigeria when it was viewed with suspicion at the time, due to colonisation. And such suspicion may have caused an unconscious

73 rejection of western education. However, the finding of this study may have some support for the Ego Energy Theory of BFS. The need to use stimulants to keep awake to study for longer hours may show low ego energy. Stimulants are energisers.

Chapter Seven

CONCLUSION

The prevalence rates of BFS and current stimulant use were found high, 42.9% and

39.4% respectively; and there was a significant association between BFS and stimulant use.

BFS was commonest among stimulant users compared to non-users. Consequently, this supports the Psychophysiological Theory of BFS. There was no significant difference between the socio-demographic characteristics of students who had BFS and those who did not have

BFS. Gender and general psychiatric morbidity were significantly associated with stimulant users that had BFS. BFS was commoner among females who used stimulant than males who used stimulant and there was a significant correlation between general psychiatric morbidity and BFS. To reduce prevalence of BFS needs ameliorating the use of stimulant. Students must learn proper study habits devoid of using stimulants to keep awake to study. And need for best mental health services for students to cut general psychiatric morbidity.

Chapter Eight

LIMITATION OF THE STUDY

The following were the limitations of this study:

1. Owing to the relative paucity of studies on BFS especially, on the socio-demographic

variables associated with BFS, the available data to compare with the findings of this

study were limited.

2. The general health questionnaire is a screening instrument. So it was not possible to

determine the specific psychiatric diagnosis associated with BFS.

3. If this study were a longitudinal study, one would have wanted to know the prognosis

of BFS especially if the students stopped use of stimulant.

Chapter Nine

RECOMMENDATIONS

This study revealed high prevalence rates of BFS and stimulant use and the probable aetiological role of stimulant use in BFS. Based on the findings of this study, the following recommendations are made: 1. It observed that most respondents who use stimulant first did so when they were 12 years and below. Therefore efforts to prevent the use of stimulant should start very early and be incorporated into primary school education programme. 2. The two most commonly used stimulants were coffee and kola nuts; hence need for enlightening health education effort towards harmful use of these substances. This health education should start from primary school, through secondary school and the university. The media should also be activated to give publicity to the health hazards of use of coffee and kola nuts especially among students. 3. Majority of the students use stimulants to keep awake to study. Students may use effective ways of studying that does not rely on use of stimulants. 4. Incorporate mental health clinic in the University health centre for the early detection and treatment of BFS. Alert and responsive medical and health workers alert to the high prevalence rates of BFS and stimulant use. 5. Female gender was found associated with BFS cases that used stimulants. Therefore, more attention be given to women, in a bid to discourage them from using stimulants, since they are more at risk of developing BFS when they are stimulant users compared to men. 6.

General psychiatric morbidity was found positively correlated with BFS. Administration of

GHQ be part of assessment for medical fitness. This will help to identify individuals who have a general psychiatric morbidity. Thereafter the type of morbidity determined and adequately treated. It is strongly believed that taking the above measures will reduce prevalence of BFS.

Consequently, students' mental health will improve, students' wastage and drop out will reduce; for the betterment of individual students, families and society at large.

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Yunusa MA, Obembe A, Madawaki A, Asogwa F. A Survey of Psychostimulant Use among a University Students in Northwestern Nigeria. Nigerian Journal of Psychiatry, 2011: 9; 3: 40- 5.

APPENDIX A

INTERNATIONAL LABOUR ORGANIZATION (ILO) INTERNATINAL STANDARD CLASSIFICAITON OF OCCUPATIONS (ISCO)

Major Group 1. legislators,, senior officials and managers

11 legislators and senior officials

111 legislators

Major Group 2

Professionals

21 physical, mathematical and engineering science professionals

211 physicists, chemists and related professionals

Major Group 3

Technicians And Associate Professionals

31 physical and engineering science associate professionals

311 physical and engineering science technicians

Major Group 4

Clerks

41 office clerks

411 secretaries and keyboard-operating clerks

Major Group 5

Service Workers and Shop And Market Salas Workers

51 personal and protective services workers

511 travel attendant and related workers

Major Group 6

Skilled Agricultural and Fishery Workers

61 market-oriented skilled agricultural and fishery workers

611 market gardeners and crop growers

Major Group 7 Craft And Related Trades Workers

71 extraction and building trades workers

711 miners, shot firers, stone cutters and carvers

Major Group 8 Plant And Machine Operators And Assemblers

81 stationary-plant and related operators

811 mining-and mineral-processing-plant operators

Major Group 9 Elementary Occupations 91 sales and services elementary occupations 911 street vendors and related workers

Major Group 0 Armed Forces

APPENDIX B – INFORMED CONSENT FORM

I am Dr. Ehigiator O. Adayonfo of the Department of Mental Health, University of

Benin Teaching Hospital, Benin City.

This is a research on Brain Fag Syndrome and Stimulant Use among undergraduate students at the University of Benin. The outcome of this research will help in the prevention and treatment of Brain Fag Syndrome.

All the information you give will be treated as confidential. You are free to decide to participate or not at any stage of the study. Your non-participation will not count against you in any way.

Thank you for your anticipated cooperation.

I, ______have accepted to take part in this research voluntarily

Signature of participant.

APPENDIX C - SOCIO-DEMOGRAPHIC VARIABLES

Instruction: Fill in the appropriate answers or put an X in the box opposite the appropriate answer.

1. Sex ( ) Male

( ) Female

2. Age last birthday ______years

3. Marital Status (tick which one is applicable to you)

Never – married

Married

Separated

Divorced

Widowed

4. Nationality (tick which one is applicable to you)

Nigerian

Non- Nigerian

5. Ethnicity ______

6. Religion Christianity ( ) Islam ( ) Others (Please Specify) ______

7. No of years already spent in the University:______

8. Year of study, (that is your level) ______

9. If there is a difference between your responses to items number 7 and 8

above, please state reason for difference

Strikes ______

Academic difficulty ______

Others, please specify ______

10. Parents’ educational status:

(I) Father

a) No formal education

b) Some primary school education

c) Completed primary school education

d) Some secondary school education

e) Completed secondary school education

f) Tertiary school education

Completed______

Uncompleted ______

(ii) Mother (tick which one is applicable)

a) No formal education

b) Some primary school education

c) Completed primary school education

d) Some secondary school education

e) Completed secondary school education

f) Tertiary school education

Completed______

Uncompleted ______

11. Father’s occupation______

12. Mother’s occupation______

13. Family set up ( ) Monogamous

( ) Polygamous

14. Where do you reside?

Home

Student hostel

Private accommodation

Others (Please Specify)______

15. Why do you reside at the above location?

______

16. How will you describe the relationship between your parents at home?

( ) Not applicable (My parents don’t live together)

( ) Friendly

( ) Not friendly (they quarrel a lot)

17. How many (living) children altogether have your father? ____

18. How many (living) children have your mother?_____

19. What is your birth position among your father’s children? (e.g. 1st, 2nd etc.) ______

20. What is your birth position among your mother’s living children? ______

21. Do you have difficulties in paying your school fees or buying school materials?

( ) yes, I sometimes do

( ) yes, I always do

( ) No, I don’t

22. How religious are you?

( ) very religious (I pray regularly)

( ) Just religious (I pray occasionally)

( ) Not religious (I hardly pray)

APPENDIX D - GENERAL HEALTH QUESTIONNAIRE

PLEASE READ THIS CAREFULLY

We should like to know if you have had any medical complaint, and how your health has been

in general, over the past few weeks. Please answer ALL the questions on the following pages

simply by ticking the column which you think most nearly applies to you. Remember that we

want to know about present and recent complaint, not those that you had in the past. It is

important that you try to answer ALL the questions. Thank you very much for your

cooperation.

Have you recently:

Better Same Worse Much than as than worse usual usual usual than usual 1 Been feeling perfectly well and in good health?

2. Been feeling in need of a good tonic?

3 Been feeling down and out of sorts?

4 Felt that you are ill?

5 Been getting any pains in your head?

6 Been getting feeling of up-tightness or pressure in your head 7 Been having hot or cool spells?

8 Lost much sleep over worry?

9 Had difficulty in staying asleep once you are off?

10 Felt constantly under strain?

11 Been getting edgy and bad tempered?

Have you recently:

Better Same Worse Much than as than worse usual usual usual than usual 12 Been getting scared or panicky for no good reason?

13 Found everything getting on top of you?

14 Been feeling nervous and strung-up all the time?

15 Been managing to keep yourself busy and occupied

16 Been taking longer over the things you do?

17 Felt on the whole you are doing things well?

18 Been satisfied with the way you have carried out tasks?

19 Felt that you are playing a useful part in things?

20 Felt capable of making decisions about things?

21 Been able to enjoy normal day to day activities?

22 Been thinking of yourself as a worthless person?

23 Felt that life is entirely hopeless?

24 Felt that life isn’t worth living?

25 Thought of the possibility that you might make away with yourself? 26 Found yourself wishing you were dead and away from it all? 27 Found that the idea of taking your own life kept coming into your mind? 28 Found at times you could not do anything because your nerves were too bad.

APPENDIX E - HEALTH AND STUDY

THE FOLLOWING ARE SOME COMPLAINT THAT STUDENTS SOMETIMES HAVE

WHEN THEY STUDY. PLEASE TICK THE ANSWER THAT BEST APPLIES TO YOU.

1. I get periods of complete exhaustion and fatigue; 1.

1. Often ______

2. Sometimes ______

3. Never ______

2. When I read, I feel that the words don’t make sense:

1. Often______

2. Sometimes______

3. Never______

3. I find it difficult to concentrate when studying:

1. Often______

2. Sometimes______

3. Never______

4. I experience crawling, heat or cold or other unpleasant sensations in my head while

studying:

1. Often______

2. Sometimes______

3. Never______

IF THE ANSWER TO QUESTION NUMBER 4 ABOVE IS NEVER, GO TO QUESTION 6

5. These unpleasant sensations (burning, crawling, heat, cold) make it

difficult for me to study or assimilate what I read:

1. Often______

2. Sometimes______

3. Never______

6. I suffer unpleasant sensations in my body related to study:

1. Often______

2. Sometimes______

3. Never______

7. I am satisfied with my general efficiency in studying and with

retention (assimilation) of what I study:

1. Often______

2. Sometimes______

3. Never______

APPENDIX F – SUBSTANCE USE

INTRODUCTIONS

This is not a test, there is no right or wrong answers but please answer carefully.

For each question pick the answer that fits you the best and put an X in the box opposite that answer. Pick only one answer for each question.

Look at the example below:

Have you drunk any water during the last 30 days?

[ ] A No

[ ] B Yes, on -5days

[ ] C Yes, on 6-19 days

[X] D Yes, on 20 or more days.

The answer chosen was “D”, indicating that the person who answered the question had drunk water on 20 or more days during the previous 30 days.

If you do not know the answer to a question, or if you feel that you cannot answer honestly, leave the question blank. Complete as many questions as possible.

1. Have you ever taken any amphetamine or other stimulants (Upper, Dexa, Reactivan,

Ephedrine, Kola nut, Coffee) without a doctor or health worker telling you to do so?

[ ] A No

[ ] B Yes

2. Have you taken any amphetamines or other stimulants in the past 12 Months

without a doctor or health worker telling you to do so?

[ ] A No

[ ] B Yes

3. Have you taken any amphetamines or other stimulants in the past 30 days

without a doctor or health worker telling you to d so?

[ ] A Has never taken amphetamines

[ ] B Yes, on 1 – 5 days

[ ] C Yes, on 6-19 days

[ ] D Yes, on 20 or more days.

4. How old were you when you first took amphetamine or other stimulants without a

doctor or health worker telling you to take it?

[ ] A has never taken amphetamine

[ ] B 10 years old or less

[ ] C 11-12 years old

[ ] D 13-14 years old

[ ] E 15-16 years old

[ ] F 17-18 years old

[ ] G 19 years old or more

5. If you have ever taken amphetamines or other stimulants, write in the name of the one

you have taken most recently, e.g. coffee, Kola-nuts, Dexa,

Ephedrine______

6. (a) Have you ever taken any cocaine? [ ] A No

[ ] B Yes

(b) Have you taken any cocaine in the past 12 months [ ] A No

[ ] B Yes

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[ ] A No

[ ] B Yes, on 1 – 5 day(s)

[ ] C Yes, on 6 -19 days

[ ] D Yes, on 20 or more days

(d)How old were you when you first took cocaine?

[ ] A has never taken cocaine

[ ] B 10 years old or less

[ ] C 11 – 12 years old

[ ] D 13 – 14 years old

[ ] E 15 – 16 years old

[ ] F 17 – 18 years old

[ ] G 19 years old or more

7. If you have taken amphetamines or other stimulants, state your reason for taking the

substance.

[ ] To keep awake to study

[ ] For relaxation

[ ] I enjoy taking it

[ ] I take it because others do

[ ] Others. Please specify______

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APPENDIX G

Bar chart representation of the distribution of respondents by Faculty.

Bar chart showing the Faculty of the Respondents 160 140 120 100 80 60 40 Bar chart showing the faculty of 20 the respondents 0

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APPENDIX H

Power of the study

This is the probability that the study will reject the null hypothesis when the null hypothesis is false, that is not committing type II error (also known as sensitivity)

The formula is :

2 n = po qo (z1 – α/z + z1 - β √ p1q1 /poqo)

2 (p1 – po) n = sample size = 482

po = prevalence of BFS = 42.9% = 0.429

qo = 1 – po

p1 = estimate of prevalence of BFS used to calculate sample size = 36% = 0.36

q1 = 1 – p1

1 – β = power of the study z = z table value

z1 - β = ϰ

z1 – α/z = 1.96 = coefficient at 95% confidence interval

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Thus:

482 = 0.429 x 0.571 (1.96 + ϰ √0.36 x 0.64 / 0.429 x 0.571)2 (0.36 – 0.429)2

ϰ = 1.135

Thus:

z1 - β = 1.135

Read the value of 1.135 from z table (Wikipedia, 2012) to get 1 - β

1 - β = 0.8729

1 - β > 0.8

Therefore, the study is properly powered since 1 - β > 0.8 (Wikipedia, 2012)

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APPENDIX I

Pattern of psychiatric morbidities / confidence interval

Psychiatric morbidity on the GHQ-28 was defined as a score of five and above. One hundred and seventy eight (36.9%) of the students scored five and above. Thus, the prevalence of psychiatric morbidity was 36.9%. The 95% confidence interval was 0.30 - 0.41. Therefore prevalence at 95% confidence limit would be between 36.6 - 37.3.

Brain fag syndrome caseness was defined as a total score of 6 and above with a score of at least 1 on items 4 and 5. Two hundred and seven of the respondents were by this definition

BFS cases. Thus, the prevalence of brain fag syndrome was 42.9%. The 95% confidence interval was 0.39 - 0.47. Therefore, prevalence at 95% confidence limit would be between 42.5 and 43.4.

Similarly, one hundred and ninety of the respondents used general stimulant in the past

30 days (1 month) prior to the study. This represented 39.4%. Thus, the prevalence rate of current use (past month or past 30 days) of general stimulant was 39.4%. The 95% confidence interval was 0.35 - 0.44. Therefore, prevalence at 95% confidence limit would be between 39.1 and 39.8.

105