Co-Occurrence of Study Difficulty

CO-OCCURRENCE OF STUDY DIFFICULTY,

PSYCHOACTIVE SUBSTANCE USE/ABUSE AND

PSYCHIATRIC MORBIDITY (“THE TRIAD”) AMONG

SENIOR STUDENTS OF UNIVERSITY OF ABUJA

A DISSERTATION

SUBMITTED TO

THE NATIONAL POSTGRADUATE MEDICAL COLLEGE OF NIGERIA

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

FELLOWSHIP OF THE COLLEGE IN THE FACULTY OF PSYCHIATRY

DR. IFEDILICHUKWU UZOEGHE UCHENDU

M.B.B.S (ILORIN) 1995

MAY 2009

DECLARATION

This dissertation is submitted in partial fulfilment for the award of

Fellowship of the National Postgraduate Medical College of Nigeria in the Faculty

of Psychiatry. The study reported here has not been published or presented for

award of a degree by any other institution.

Signed by:

______

DR I. U. UCHENDU. Date

CERTIFICATION

The study reported in this Dissertation was conducted by Dr. I.U. Uchendu of

Psychiatric Hospital, Uselu Benin City, Edo State, under my supervision. I also supervised the writing of the dissertation.

______

PROF OLUFEMI MORAKINYO (FMCPsych.) DATE Consultant Psychiatrist Dept. of Mental Health University of Benin Teaching Hospital (UBTH) Benin City, Edo state, Nigeria.

TABLE OF CONTENT

Declaration ii

Certification iii

Table of Contents iv

List of Tables x

List of Figures xii

Abbreviations xiii

Dedication xiv

Acknowledgement xv

Summary xvi

CHAPTER ONE

INTRODUCTION 1

Relevance of the study 4

CHAPTER TWO

LITERATURE REVIEW 5

Students’ Mental Health 5

Study Difficulty 6

Classification of study difficulty 7

Factors associated with study difficulty 10

Psychoactive substance use/abuse 12

Socio-demographic correlates of psychoactive substance use 13

Psychiatric Morbidity 15

General psychiatric morbidity 15

Relationship between psychiatric morbidity & psychoactive substance use/abuse 15

Consequences of psychiatric morbidity in relation to study 17

Neurobiological basis for co-morbidity of psychiatric morbidity & psychoactive substance use /abuse 18

Specific psychiatric morbidity (Brain Fag Syndrome) 19

The Triad 20

CHAPTER THREE

AIMS AND OBJECTIVES 22

Theoretical Framework 22

General Aims 23

Specific Objectives 24

Hypotheses 25

CHAPTER FOUR

METHODOLOGY 26

Study Location &Settings 26

Inclusion Criteria 27

Exclusion Criteria 27

Ethical Considerations 27

Subjects Recruitment 27

Sample Size Determinations 29

Procedure 30

Sampling Procedure 30

Study Instrument 33

Part 1: Socio-demographic Questionnaire 33

Part 2: General Health Questionnaire 33

Part 3: The University College London Study Difficulty Questionnaire 34

Part 4: The World Health Organisation Questionnaire for Students Drug Use Survey 35

Part 5: The Brain Fag Syndrome Scale 36

Data Analysis 36

CHAPTER FIVE

RESULTS 39

Socio-demographic characteristics of the respondents 39

Gender distribution 39

Age distribution 39

Religion 39

Respondents’ geopolitical zones of origin 39

Socio-demographic characteristics of the respondents parents 41

Educational levels 41

Occupational status 41

Study Difficulty 44

Measure of central tendencies and dispersions of the UCLSQ subscales 44

Psychoactive Substance Use/Abuse 47

Psychiatric Morbidity 49

General psychiatric morbidity 49

Specific psychiatric morbidity 49

Identification of co-morbidities and estimation of their magnitudes 49

Co-morbidity of study difficulty & psychoactive substance use/abuse 49

Co-morbidity of psychoactive substance use & psychiatric morbidity 50

Co-morbidity of study difficulty & psychiatric morbidity 50

Co-occurrence of study difficulty, psychoactive substance use & psychiatric morbidity 50

Relationships of the Brain Fag Syndrome with the co-morbidities 52

Socio-demographic characteristics of subgroup H (‘TheTriad’) 55

Specific psychoactive substances associated with study difficulty 64

Specific psychoactive substances associated with psychiatric morbidity 64

Specific aspects of study difficulty associated with psychoactive substance use 66

Specific aspects of study difficulty associated with psychiatric morbidity 66

Prevalence of psychoactive substance use, study difficulty & psychiatric morbidity among students with BFS 68

Psychoactive substances commonly used by students with BFS 69

Association between the psychoactive substances (life-time) use & BFS 71

Relationship between the subscales of UCLSQ & ‘The Triad’ 73

Types of study difficulty commonly associated with BFS 74

Correlation coefficient of the quantitative variables 75

CHAPTER SIX

DISCUSSIONS 79

Response to self reported questionnaire 79

Socio-demographic characteristics of the respondents 80

Prevalence rates of study difficulty 81

Prevalence of psychoactive substance use 82

Prevalence of psychiatric morbidity 83

Prevalence rates of ‘The Triad’ 83

Socio-demographic characteristics of students with ‘The Triad’ 84

Specific psychoactive substances associated with study difficulty 87

Specific psychoactive substances associated with psychiatric morbidity 88

Specific aspects of study difficulty associated with psychoactive

substances & psychiatric morbidity 89

The magnitude of Brain Fag Syndrome among students with ‘The Triad’ 91

Prevalence rates of Brain Fag Syndrome among subgroups of the cohort 92

Psychoactive substances commonly abused by students with BFS 93

Types of study difficulty commonly associated with BFS 94

CHAPTER SEVEN

CONCLUSION 95

Implications of these finings 96

Recommendations 96

Limitations of the study 97

REFERENCES 98

APPENDICES 106

Appendix I: Socio-Demographic Variables 106

Appendix II: General Health Questionnaire (GHQ-30) 109

Appendix III: The WHO Questionnaire for Students Drug Use Survey 112

Appendix IV: University College London Study Difficulty Questionnaire 122

Appendix V: Brain Fag Syndrome Scale 127

Appendix VI: International Standard Classification of Occupations 128

Appendix VII: Respondents Consent Form 136

LIST OF TABLES

Table 1: Morakinyo’s Classification of Study Difficulty 9

Table 2: Full-time undergraduate students population according to their faculties 28

Table 3: Respondents Faculties, Departments & Levels by Gender 32

Table 4: Gender & Age distributions of the respondent 39

Table 5: Religion of the respondents 39

Table 6: Geopolitical zones of the respondents 40

Table 7: Socio-demographic characteristics of respondents parents 41

Table 8: Occupations of respondents’ parents 42

Table 9: Mean scores, Standard deviations & Median scores of subscales of UCLSQ 46

Table 10: Prevalence rates of psychoactive substance use among Respondents 48

Table 11: Prevalence rates of BFS among the subgroups of the cohort 54

Table 12: Associations between gender & ‘The Triad’ 55

Table 13: Relationships between age group & ‘The Triad’ 56

Table 14: Associations between respondents departments & ‘The Triad’ 58

Table 15: Associations between family status & ‘The Triad’ 60

Table 16: Associations between father’s level of education & ‘The Triad’ 61

Table 17: Associations between parental relationships & ‘The Triad’ 63

Table 18: Associations between specific psychoactive substances with

study difficulty & psychiatric morbidity 65

Table 19: Specific aspects of study difficulty associated with psychoactive

substance use & psychiatric morbidity 67

Table 20: Prevalence of BFS among students with study difficulty, psychoactive substance

use and psychiatric morbidity 68

Table 21: Psychoactive substance most commonly associated with BFS 70

Table 22: Relationship between the psychoactive substances (lifetime) use and the BFS 72

Table 23: Relationship between subscales of UCLQ and ‘The Triad’ 73

Table 24: The types of study difficulty most commonly associated with BFS 74

Table 25: Correlation coefficient of the quantitative variable 78

LIST OF FIGURES

Figure 1 Theoretical Framework depicting constituents of the total cohort 22

Figure 2 Prevalence rates of the various sub-groups of the study sample 51

Figure 3 Prevalence rates of BFS among subgroups of the cohort. 53

Figure 4 Respondents levels of education & ‘The Triad’ 57

Figure 5 Associations between family status & ‘The Triad’ 59

Figure 6 Associations between Parental relationship & ‘The Triad’ 62

ABBREVIATIONS

ANX: Anxiety

BFS: Brain Fag Syndrome

BFSS: Brain Fag Syndrome Scale

CSD: Consolidated Study Difficulty

DEP: Depression

DIS: Disorganised/Distractible

GHQ-30: General Health Questionnaire Version 30

ISCO : International Standard Classification of Occupations

L-MOT: Low motivation

OR: Odds Ratio

RR: Relative Risk

SOM: Somatic

SPSS: Statistical Package for Social Science Version 16

SYL: Sylbism

UATH: University of Abuja Teaching Hospital

UBTH: University of Benin Teaching Hospital

UCLSQ: University College London Study difficulty questionnaire

DEDICATION

This work is dedicated to God Almighty, my Saviour and Lord, Jesus Christ and to all those who found themselves within the intricate web of this syndrome ‘The Triad’.

ACKNOWLEDGEMENT

First of all my profound gratitude and appreciation goes to my supervisor Prof.

Olufemi Morakinyo, for his understanding, encouragements and guidance,; whom despite his busy schedules ensured that this work became a reality. I thank Dr.R.O. Osahon, the immediate past Medical Director of Psychiatric Hospital Uselu, Benin city, for giving me the opportunity to be trained in this institution. My thanks go to the current Medical Director (Dr

(Mrs.) F O Ihenyen), The Head of Clinical Services (Dr. G.O. Eze), Dr. Ikeji O C, Dr. A.O.

Lawani, and Dr (Mrs.) E Okogbeni, . for their support, and encouragements throughout the period of my training. I appreciate all the members of the Association of Resident Doctors

(ARD) Psychiatric Hospital, Uselu, especially Dr. Aweh Benjamin and Dr. Israel Adaigho for all their encouragements and assistance towards this work. The immense contributions of Dr.

Bakare of Neuro-Psychiatric Hospital, Enugu and Dr. U.E. Chikezie of Psychiatric Hospital

Uselu Benin City, towards the success of this work are highly appreciated.

I also wish to express my gratitude to Dr. Nandul Durfa and Dr. Titus Ameh (former

Chief Medical Directors of University of Abuja Teaching Hospital (UATH)) for their support, understanding and encouragements. I also appreciate the assistance of the following: the current CMD of UATH, (Dr. Peter Alabi), and The Chairman Medical Advisory

Committee of UATH: (Dr. Onofawokan O), and Dr S O Ajayi, Dr. Manven M.H, both of

Dept of Medicine UATH. I will not forget various contributions of Mr. Ishameal D. O, Mr.

Hosea Apeh and Mr. Bafeto A. A. of University of Abuja towards the success of this work. I remain grateful to my parents, siblings, wife and children for all their prayers and encouragements. Finally, my utmost gratitude goes to God Almighty for his mercies and gifts

15 of life, strength, protection and provisions without which this work could not have been possible.

SUMMARY

It has been documented in several reports in the literatures, that study difficulty is associated with psychiatric morbidity. Most studies have also investigated the co-morbidity of either study difficulty and psychiatric morbidity or psychoactive substance use/abuse and psychiatric morbidity.

This study aimed to determine the prevalence of a syndrome which consists of co- occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity

among undergraduate senior students of University of Abuja. It also aimed to identify socio- demographic characteristics of students who suffer from this syndrome.

In the study, six hundred and twenty four (624) students in 3rd and 4th year were sampled. The University College London Study Difficulty Questionnaire, World Health

Organisation Questionnaire for Students Drug Use Survey and General Health Questionnaire

(Version-30) were used to assess the prevalence of study difficulty, psychoactive substance use and psychiatric morbidity respectively. Prevalence rate of Brain Fag Syndrome was also determined using the Brain Fag Syndrome Scale.

The findings from this study show that prevalence of the syndrome of co-occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity (termed ‘The

Triad’) among senior students of University of Abuja was 16.7%, and this was associated with several socio-demographic factors. The study also revealed a highly significant positive association between ‘The Triad’ and Brain Fag Syndrome. The study showed that the components of this syndrome were major health problems for these students, and that the components interact very closely to the detriment of the mental health of the students.

These findings indicate the urgent need to incorporate mental health services in the

Health Services of our educational institutions, especially in tertiary institutions and for a co- ordinated approach by all the stakeholders to stem this vicious emerging trend (‘The Triad’).

CHAPTER ONE

INTRODUCTION

Reports have shown in literatures that passing examinations is an important means to a better and improved living standard in Nigeria. Much of one’s success in examinations depends on the ability to learn and reproduce what was learnt. This level of functioning is dependent on a good mental health, which is a prerequisite for effective studying at all levels of education, much especially in higher institutions of learning.

“The term, co-morbidity (also called dual diagnoses) applies, when criteria for two or more diagnoses are met. It covers two different circumstances: (a) disorders that are currently considered distinct but are probably causally related and (b) disorders that are casually unrelated, (Maj, 2005). This term has limited relevance in relation to developmental problems.( Kaplan et al 2006). However, the co-occurrence or co-occurring disorder is the more recent term for also two or more disorders or diagnoses existing together in an individual. This seems to be a more encompassing terminology, denoting the presence of psychoactive substance use/abuse, mental disorder and/ or medical disorders including developmental problems. Taking into cognisance that study difficulty has been associated with both mental, environmental and medical (including developmental) aetiological factors (Table 1: Morakinyo’s classification of study difficulty), this informed the choice of the term ‘co-occurrence’ in this study in preference to co- morbidity.

Studies of co-morbidity of psychoactive substance use and psychiatric disorders have shown that in some cases psychoactive substance abuse is primary and other psychiatric disorders are secondary and vice versa. These are exemplified by studies that include: Major Depression with Cocaine Dependence, Alcohol Dependence with Panic

Disorder, Alcoholism and Poly Drug Dependence with Schizophrenia, and Borderline

Personality with Episodic Poly Drug Abuse (Perfas 2006). The combinations of psychoactive substance abuse and psychiatric morbidity often vary along important dimensions of severity, chronicity, disability and degree of impairment in functioning,

(Perfas 2006). In general people with mental health disorders are at higher risks for psychoactive substance abuse disorders and also people with psychoactive substance abuse problems have increased risk for mental disorders.”(Perfas 2006)

Studies of psychiatric morbidity (disorders) associated with study difficulty have also been carried out. Earlier reports had indicated that the diagnosis of the psychiatric disorders found among student populations did not differ from the established nosological practice, any differences were only in pattern (e.g. prevalence of illness) (Morakinyo, 1990). Handforth

(1978) reported from Canada that one third of students with study difficulty seen in Queen’s

University Health Services complained of symptoms of both anxiety and depression. “This positive relationship between study difficulty and mental ill health has been corroborated by several studies. Also study difficulty has been observed to be secondary to many psychiatric morbidities and psychoactive substance (drug) abuse” (Morakinyo, 1990).

Okasha et al, (1985) in a study “Academic difficulty among male undergraduate students in an Egyptian university”, reported a high positive correlation between prevalence of mental ill health and rate of drop out from school among students. Also Morakinyo (1990) identified dropping out of school or difficulty with academic progress as two adverse consequences of mental ill health among students. 19

It is pertinent to state that previous studies among undergraduates were on co- morbidities of either the pairs of psychoactive substance use and psychiatric morbidity, or study difficulty/ academic difficulty and psychiatric morbidity (mental illness). However, this study is focusing on the co-occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity (‘The Triad’) among undergraduate students of University of

Abuja in Nigeria. :

Relevance of the study

The state of mental health of any student is vital in pursuance of excellent academic career. The co-occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity termed (‘The Triad’) in students definitely would have detrimental effects on their mental health. The three pronged negative impact of’ “The Triad” on mental health of the university students had led to school dropouts, and extra years of studying in the university, with the attendant economic burden and social consequences on their families and the society at large.

The dearth of studies on the co-occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity (“The Triad”) among undergraduate university students both internationally and locally justifies the need for this study.

It attempts to:

1. Provide information on the extent of the co-occurrence of study difficulty,

psychoactive substance use and psychiatric morbidity among students in our

universities.

2. Provide insight that may be useful in enhancing (a) students’ academic performance,

(b) reduction of psychoactive substance use/abuse among students and (c) the

development of mental health hygiene conducive to academic work among students.

CHAPTER TWO

LITERATURE REVIEW

Students Mental Health

Students need optimal mental health (successful performance of mental functions in terms of thought, mood and behaviour) to achieve academic success. The psychosocial and academic stresses and problems which students encounter, negatively affect their mental health. A report from the Summit on the Initiative for Mental Health, (1998) stated that

“studies indicate that approximately 1 in every 5 undergraduate students in North American schools has significant mental health problems that need attention. These problems cause pain and emotional distress, and they compromise their chances for fully using learning opportunities and for succeeding. These problems not only present challenging behaviours such as aggression and disruption, but also can cause internal turmoil through feelings such as anxiety and depression”. Also in a study conducted among medical students of Nepal, the workers found that a large proportion of students in both basic and clinical sciences had potential psychological problems. The stresses experienced by the students were mainly related to academic and psychosocial concerns resulting in higher level of psychological morbidities. It was also noted by these authors, that there was an increased rate of psychological morbidities among third, fourth and final year students, 15%, 18.9% and 24% respectively. (Chandrasekhar et al, 2007). Also in a related study “psychoactive substance use among medical students in a Nigerian university”, it was reported that the clinical (4th, 5th and

6th year) students were more likely to use psychoactive substances than students in pre clinical, (Daramola 2007).

Several other studies had suggested reasons for the increased psychiatric morbidities among university students. Handforth in 1978 noted that “students as groups of people have 22 to make both external and internal adjustments of a kind, which are not required to the same extent in other sections of the society.” Morakinyo (1990) stated that “they have to cope with success at studying, ability in functioning autonomously as well as positive relationships with others. Adjustments to these processes are expected to be smooth, but in some cases these adjustments are not well made, leading to the development of certain symptoms in which study difficulty is one of the most frequently encountered.” Handforth (1978) also cited the work of Blain and McArthur (1971), in which they reported 50% of study problems among students attending Student Health Services at Harvard University.

It is important at this juncture to state that “study is the main preoccupation of students.” It is the essence for being in school, hence problems in relation to studying would expectedly have adverse consequences on both the mental health and outcome of academic aspirations of affected students.( Morakinyo 1990).

Student mental health services should be an integral part of Student Health Services in our tertiary educational institutions. These services ought to be provided by mental health professionals, through the Consultation-Liaison Psychiatry. The extent to which this has been implemented is yet to be ascertained. . However, in the western world studies have shown that mental health services are integral part of students’ health services, (Parnel 1951, Mair

1967, Lucas and Crown 1974).

Study Difficulty

“Study difficulty can be defined as the impairment of the capacity to study effectively or inability to obtain maximal result from the effort put in the studying” (Morakinyo, 1990).

The following have been identified as causes of study difficulty: Diminished motivation, impaired ability to concentrate, retain or recall, improper presentation of materials, faulty study pattern, poor budgeting of available time, difficulty in social

23 adjustments to a new school environment, secondary effect of psychoactive substance use, personality related problems, neurotic conditions and psychotic disorders.

“Study (work) difficulty has always been observed to form part of the symptomatology or signs of the broad spectrum of mental health problems which students present with. It may either be reported by the student himself or may be the only complaint by the teacher, parents, guardian or other significant person in the student’s life. This is noteworthy, as the main pre-occupation of the student is studying. Apart from the fact that study difficulty is a common symptom or sign in students with mental health disorders, it is important also to note that it may lead to premature termination of the educational process and subsequent student wastage, in otherwise good and capable students” (Morakinyo, 1990).

Classification of study difficulty

Classifications of study difficulty have been reported by several scholars, notable among them are: Malleson (1957, 1965) , Ryle (1969), Crown et al, (1973), Handforth (1978), James (1980), and Morakinyo (1990). Malleson (1957,

1965) initially recognised three types of study difficulty: Anxiety related, apathetic / withdrawal type and somatic symptoms related. However, in his second report, he subdivided study difficulty into primary and secondary categories. The primary was sub-classified into: obsessionality, disorganized, retention and recall difficulties, and production difficulties.

While the secondary type was not sub classified, but was described, as due to personal problems.

Ryles (1965), subdivided study difficulty into: study difficulty associated with

psychiatric disturbances, and study difficulty not associated with psychiatric illness.

The type associated with psychiatric disturbances was further sub-classified into 2; disorganised and dynamic types, in which interpersonal relationships with significant others play important role.

Crown et al, (1973), and James, (1980), concluded that study difficulty could be classified into: Psychoneurotic difficulties, motivational difficulties and a mixture of both psychoneurotic and motivational difficulties.

Two major types of study difficulty, primary and secondary were identified by

Handforth in 1978. He noted that primary type, is associated with poor study habits, counterproductive obsessiveness or poor budgeting of time, and in this, psychiatric diagnosis is inappropriate, while the secondary type is associated with both rare and relatively common conditions like: dyslexia, drug induced amotivational syndrome, schizophrenia, anxiety states

, adjustment difficulties, depression , and developmental problems.

Morakinyo (1990) gave a comprehensive classification of study difficulty, which took into account many factors, which have been identified to be associated with study difficulty.

The details are shown in Table1.

Table 1: Morakinyo’s Classification of Study Difficulty

Type Possible Underlying Factors

Sub type A. Primary No 1. Educational/Psychological (a) Deficient intellectual capacity

25 association with (b) Impaired reading and comprehension ability psychiatric illness (c) Retention – recall difficulties (d) Aptitude vocational in-congruencies (e) Poor study habit (e.g. poor time budgeting etc.)

2. Motivational/Behavioural (a) Disorganisation (b) Syllabus bound/syllabus free work manner (c) Low motivation (d) Poor concentration/distractibility

3. Socio-Cultural (a) Learning is second language and understanding alien constructs (reading- comprehension difficulties). (b) Attitude to education. (c) Loneliness and social deprivation (d) Adjustment and interpersonal difficulties. (e) Structural and dynamic characteristic of the education system and institution. (f) Community expectations and indebtedness. (g) Family events

4. Psycho-Physiological (a) Sensory deprivation (e.g. poor lighting in reading room, classroom or at home). (b) Exertion-exhaustion stress (c) Sleep deprivation

5. Organic (a) Perceptual disabilities (e.g. poor sight, hearing). (b) Head injury, dementia and other brain diseases. (c) Arrest or retardation of development and growth.

B. Secondary Associated 1. Personality related i. Easy extinction of conditioning/learning with psychiatric (a) Hysterical personality ii. Drug induced amotivational syndrome disorders. 2. Substance (drug) abuse or i. Concentration and comprehension impairment dependence related under drug influence

3. Neurotic related i. Impairment of learning/performance due to hyperarousal (a) Somatic anxiety ii. Interest disorder (b) Anticipatory or reactive phobia iii Socio-cultural factors anxiety related to fear of failure and/or repeated failure (c) Neurasthenia iv Psycho-physical factors (d) Adjustment disorder with work or v. Social cultural factors as above academic inhibition DSM III, 309, 29 (e) Other neuroses in which study has vi. Constitutional factors special symbolic significance e.g. brain fag syndrome.

4. Psychotic related i. Abulia (a) Schizophrenia ii. Interest disorder Constitutional factors

Factors associated with study difficulty

Morakinyo’s comprehensive classification of study difficulty was an improvement on the preceding ones. In a lecture, that was delivered at the 15th Annual General Meeting of the

West African College of Physicians in Accra, Ghana, on the 13th November, 1990, he noted that the classifications of study difficulty proposed by Handforth and the London group were more operational than the others, but have not taken into account a number of factors that could be associated with study difficulty.

It is imperative to note that many of the factors highlighted in Morakinyo’s classification presented above (Table 1) obviously have direct aetiological complications.

However, when a complaint of study difficulty is associated with any of the psychiatric conditions listed in Table I, the cause-effect relationship becomes complex (Fatoye, 1998).

Handforth (1978), in a study among undergraduate students in Canada pointed out that “it has become necessary to determine whether this symptom is indeed secondary to some other problems or situational, developmental or associated with emotional distress or secondary to study difficulty derived from poor study habit”. Fatoye (1998), in a study among secondary school students, in Western Nigeria, noted that the nature of the contributions of study habits and attitudes, motivational and personality factors to study difficulty have received some attention. Miller (1970) reported the effect of effective study methods on academic achievement. He noted that high achievers tend to be more systematic in their study and effective study methods suggest higher motivation. Brown and Holzman

(1955) reported that attitude items differentiate high achievers from low achievers more than study test items.

Furneaux (1960) related academic success to moderate neuroticism and introversion, and Entwistle and Entwistle (1970) found the tendency for successful students to have below average scores on study methods and motivation. The tendency for motivated students to be

27 extroverted and those with good study habit to be introverted were reported by Entwistle et al, (1971).

In a survey of among undergraduate students at Ainshams University Cairo, in Egypt, during 1979-1980 academic years, about 6% of the students dropped out before graduating, while another 8% required substantial extra time to graduate. These figures were almost similar for both sexes. Also in a study of academic difficulty among male Egyptian undergraduate students using the Eysenck Personality Questionnaire (EPQ), the results suggested that university students especially those with academic difficulties are more neurotic and introverted than the general Egyptian population. (Okasha et al, 1985a) In a related study diagnoses of psychiatric disorders were made in 42% of male students with academic difficulties as against 9% among academically successful male students. The authors also noted that neurotic disorders accounts for nearly half of the cases and schizophrenia for a quarter. Serious psychiatry illness was found to about four times as frequent among 3rd year students as among 1st year students (Okasha et al,1985b).

Furthermore, Crown et al, (1977), studied the relationship of self-esteem and conscience with study difficulty. They found a significant positive relationship between conscience and psychoneurotic symptoms. Low motivation was also positively correlated to study difficulty. Conversely, self esteem showed significant negative correlation. Okasha et al., (1985) further noted that “significant positive association was found between study difficulty, low socio-economic status, overcrowded housing, paternal behavioural problems, strained relationship among parents, family history of psychiatric disorder and living away from home. “Academically less successful students had fewer friends especially women, and more limited recreational activities. They also scored significantly lower in verbal scale of

Wechsler Adult Intelligence Scale (WAIS) and Wechsler Intelligence Scale for Children

(WISC).” In a survey, of study difficulty among Nigerian students, psychological aspects and

28 psychosocial correlates. The results also show that self-reported academic problems, financial strain, polygamous family background, strained relationship between respondents’ parents, self-reported poor mental and physical health were significantly associated with study difficulty. These findings suggest interplay of personality and psychosocial factors in the development of study difficulty and may be useful in the planning of preventive and psychotherapeutic strategies, (Fatoye 2005).

Psychoactive substances

Psychoactive substances are chemical substances which when ingested, inhaled or injected into the body have the potential to alter mood, behaviour, perception or mental functioning of an individual. These substances could bring about changes in a person’s emotional state, body functioning or behaviour. These psychoactive substances also exert their effects by modifying chemical or physiological processes in the brain. (Okogbenin, 2008)

These substances are categorized as either illicit (illegal) for example cannabis, cocaine and heroin or licit (legal) substances like alcohol kola nuts, or coffee.

Studies have shown that these substances are misused or abused by undergraduate students

(Adelekan and Ndom 1996, Daramola 2004, and Onofa, 2005).

Over the years, the definition of psychoactive substance abuse has varied among researchers however operational definitions are now in place. The two internationally recognized definitions, which are similar in most aspects, are the Diagnostic and Statistical

Manual of Mental Disorders (DSM IV, APA, 1994) and the International Classification of

Diseases, tenth edition (ICD – 10 WHO, 1992).

DSM IV Criteria for substance abuse defines it as “a maladaptive pattern of substance used leading to clinically significant impairment or distress as manifested by one (or more) of the following:

1. Recurrent substance use resulting in a failure to fulfil major role obligations at work,

school or home.

2. Recurrent substance use in situations in which it is physically hazardous.

3. Recurrent substance related legal problems.

4. Continual substance use despite having persistent or recurrent social or interpersonal

problems caused or exacerbated by the effect of the substance”.

Socio-demographic correlates of psychoactive substance use/abuse

There is a general consensus that the abuse of psychoactive substances in Africa and other developing countries has been on the increase amongst youths (Pela 1988, Odejide

1980, Awaritefe and Ebie 1975, Asuni et al, 1994, Adelekan 1997, and Federal Ministry of

Health 1991). This had led to a corresponding increase in research in this area, but its detrimental effects on studying have not received corresponding attention. (Fatoye, 1998)

Pela in 1986 noted the increased involvement of females’ gender in drug use,

Aboidun et al, (1994), found that, in many cases of psychoactive substance abuse, about half of the students got initiated into it while in primary school, three quarters by early secondary school period. “Students many of whom are still in the formative years and in transition to adulthood phase are in period of experimental exploration and curiosity” (Pela 1986). They are particularly prone to the many destructive effects of psychoactive substances abuse, both physically and mentally, study difficulty inclusive. About 40-80% of Nigerian undergraduates were found to use alcohol (Ihezue 1988, Adelekan et al, 1993, Daramola,

2004).In a 30-country survey project in which Nigeria participated, Ibanga et al, (2005) noted

30 that 32.5% of 2,099 respondents were drinkers. Onofa (2005) reported that 69.2% life time use of all drugs among undergraduate students of three higher institutions in Abeokuta,

Western Nigeria.

It is likely that contemporary rural-urban drifts, shifts and breakdown in protective effect of the extended family system, socio-economic and psychosocial factors postulated by

Adamson and Sijuwola in 2001 may have worsened the pattern of psychoactive substance abuse of the youths in Nigeria.

The amphetamines are illegally imported into Africa (Ebie. 1982). Their use is a problem commonly found among adolescents, especially students (Oshodi 1973, Asuni and

Pela; 1980, Ebie, 1982). Students use stimulants to keep awake during intense studying

(Lambo 1965, Adelekan et al 1982). Labourers use them to fight fatigue, while farmers mostly in the Northern Nigeria use them both to fight fatigue and to suppress appetite during farming. Oshodi (1986) in his study of psychoactive substance abuse in Kaduna over a 3 year period noted that the abuse of amphetamine had assumed an epidemic proportion in the

Northern part of Nigeria especially among soldiers, farmers, labourers and students.

Psychiatric Morbidity

(a) General psychiatric morbidity

Relationship between psychiatric morbidity and psychoactive substance use/abuse

The abuse of psychoactive substances poses serious consequences to the abusers, leading to students’ wastage, dropout, financial loss and threat to societal well being, (Onofa,

2005). These are some of the notable consequences of psychoactive substance abuse.

However some authors have associated drug abuse with different forms of psychiatric morbidity.

Asuni in 1964 reported the development of schizophrenia-like psychosis in abusers of cannabis. Paton and Kandel, (1978) pointed out the association between drug use and depressive illness. Morakinyo; (1983) and Pela (1986) reported the contributory effects of cannabis abuse to the development of psychiatric morbidity.

Also, it has been reported that an increasing number of students in secondary schools and universities present to psychiatric clinics and hospitals with psychological problems following psychoactive substance use (Ogunremi and Okonofua, 1977). In Lesotho,

Mauritius, Mozambique, Namibia, the Seychelles and Swaziland, alcohol plays a significant role in treatment demand in both general and psychiatric hospitals. It was reported that 62%of the total admissions into psychiatric hospitals in Swaziland and 80% in Mauritius, were related to alcohol as primary psychoactive substance used (SACENDU, 2005). Also several studies have shown that alcohol is second only to cannabis as primary substance associated with admissions into Nigerian psychiatric hospitals (Ahmed1986, Obot and Olaniyi 1991;

Ohaeri and Odejide 1993). It was noted that many of these admissions are for co-morbid conditions, where alcohol use disorders are part of the mix, so it is not clear how much role alcohol (or cannabis for that matter) plays in the psychiatric morbidity resulting in hospitalisation.

The WHO Global Burden for Disease project noted that high burden of alcohol is partly due to a strong link with depression (Rehm et al, 2004). In the general population, the co-morbidity of mental illness and drug use was studied in the United States of America;

(Ragler et al, 1990) .The authors used interview technique to study 20,291 persons in the survey. Among those with alcohol abuse/dependence 37% had co-morbid mental disorder.

Among those with mental disorder a lifetime prevalence of having some addictive disorder was 29% including over lapping of 22% with an alcohol and 15% with another drug disorder.

A similar association was found in Connecticut, USA, in study by Merikangas and Gelernter,

(1990) between alcoholism and depression. Breslau, in 1995, reported that “co morbidities of psychiatric disorders and psychoactive substance use disorders are more pervasive than previously suspected.” The study further revealed that “males and females with nicotine dependence had increased odds for alcohol and illicit drug use, major depression and anxiety disorders compared with non dependent smokers and non smokers, increased odds for alcohol and illicit drug disorders were also observed in non dependent smokers compared to non smokers.

Abiodun et al, (1994) and Adelekan et al, (1993) in drug use surveys among secondary school students and university students in Ilorin Nigeria respectively showed significant correlations between mental ill health and the use of alcohol, cannabis and tobacco.

Ononye and Morakinyo, (1994) studied 50 inmates of a remand home in South

Western Nigeria for drug abuse, psychiatric morbidity and juvenile delinquency. A well matched comparison group of primary and secondary school students from the same geographical area was compared with the delinquent group. Both groups were subjected to the Carlson Psychological Survey (CPS) questionnaire. The questionnaire, which comprises

50 items, has basic content areas identified as follows; Chemical Abuse (CA) Thought

Disturbance (TD), Antisocial Tendency (AT) and Self Depreciation (SD).

For delinquency and comparison (non delinquent) group, a significant positive association was reported between chemical abuse and psychiatric morbidity (as measured by self depreciation and thought disturbance).

Generally, prevalence studies have reported substance abuse in patients with psychiatric morbidity as ranging from 20% to 75%, while 25% to 65% of alcoholics entering rehabilitation suffer from another major psychiatric disorder (el-Guebaly, 1990). No difference was found between sexes. Forty two percent of students with academic difficulty were diagnosed as having psychiatric problems compared with 9% among academically successful students. Neurosis accounted for half of the case, while schizophrenia accounted for nearly a quarter. More psychiatric problems were recorded among third year students than the first year.

Consequences of psychiatric morbidity in relation to study

In a study of co-occurrence study difficulty, drug use and psychopathology among secondary school students (Fatoye 1998), he stated that “A notable consequence of psychopathology is school absence, which invariably impedes performance of students and may lead to drop out.

Though the association between psychiatric morbidity and school absence with eventual dropping out of school may appear straight forward, the relationship of psychiatric morbidity and study difficulty may not be that simple” (Fatoye, 1998). Fatoye also noted that study difficulty may be a primary condition; however in many cases it is secondary to psychiatric morbidity of various types. (Table 1 Morakinyo’s Classification of study difficulty). Whether primary or secondary, the eventual outcome is undesirable to the students, their families and the society in general.

Neurobiological basis for co- morbidity of psychoactive use and psychiatric morbidity

In a 2004, in World Health Organization (WHO) publication, it was stated that “There is an increased risk of co-occurrence of substance use/ abuse in individuals who have mental illness, compared to individuals without any mental illness. It further stated that this might be due to either a shared neurobiological basis for both or an interaction of effects at some level”. Several hypotheses have been postulated to advance the reason why mental illness and psychoactive substance use/ abuse may co-occur.

(A). There may be a similar neurobiological basis for both.

(B). Psychoactive substance abuse may help to alleviate some of the symptoms of the

mental illness or the side effects of medications.

(C). Psychoactive substance abuse may precipitate mental illness or lead to biological

changes that have common elements with mental illness.

The evidence for all these hypotheses is compelling. However, it is interesting to note, that psychoactive substances can produce psychotic-like symptoms. Examples are amphetamines and cocaine that can induce psychotic-like symptoms. Hallucinogens can produce hallucinations, which are psychotic symptoms and are present in many psychotic disorders.

Psychoactive substances regularly alter mood states, producing either euphoria or happy feelings or inducing depressive symptoms. They also alter cognitive functioning. This impairs (memory) effective studying (study difficulty) which is also a core feature of many mental illnesses. The above factors are suggestive of common neurobiological basis to mental illness and psychoactive substance abuse and study difficulty.

Some studies done in United States, reported that more than 50% of people with mental illness also suffer from psychoactive substance dependence, compared to 6% of the 35 general population and odds of exhibiting substance dependence are 4.5 times higher for people with any mental disorder than for people without mental illness (Ragler et al, 1990).

(a) Specific psychiatric morbidity

Brain Fag Syndrome: A psychiatric syndrome which is related to study or intense academic (intellectual) work was reported by Raymond Prince in Nigeria in 1960. In that publication and in a subsequent one, he described the cluster of symptoms, which characterised the syndrome (Prince, 1962). He called, this syndrome, Brain Fag Syndrome due the belief by the affected students that their brains were fatigued. Morakinyo in 1990 stated that this syndrome is characterised by the following symptoms

(a) Intellectual impairments, inability to grasp the meanings of materials read poor retention and recall, and difficulty with concentrating when reading.

(b) 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 worsens when study is attempted and other sensory disturbances like blurring of vision or just seeing blank.

(d) Affective disturbance which may not be present or be volunteered by the student,

but which may take the form of fear, anxiety and/or depression.

The syndrome has since been reported in many parts of West Africa e.g. Liberia

(Wintrob, 1977), Sierra Leone (Thebaud and Rigamaer; 1976) and Cote d'Ivoire (Lehmann,

1977). It has also been reported from the other parts of Africa; South of Sahara and in students of African descent who were studying in the Western countries, but is rather rare among Caucasians. A debate as to why there should be this disparity in prevalence has ensued and some explanations have been offered. There have also been suggestions as to the

36 mechanism of its occurrence, and even whether it should be regarded as a distinct entity on its own, or as an anxiety equivalent or depression equivalent, (Fatoye, 2004).

Prince in 1980 has argued almost convincingly, that the condition could be regarded as a culture bound syndrome in view of its lop-sided distribution between African and

European cultures.

The Triad

The term triad was first used by Fatoye in 1998 in a study of the co-occurrence of study difficulty, drug use and psychopathology among senior (SS2 and SS3) students from six secondary schools, in Ilesha, Western Nigeria. The University College London Study

Questionnaire, the WHO questionnaire for students drug use survey and the General Health

Questionnaire (12 items) were used to assess study difficulty, drug use and psychopathology respectively. In the study, a total of 562 respondents (296 males and 262 females) were analysed. In this dimensional survey, the result shows that the consolidated prevalence rates for all drug except antibiotics and analgesics were 39.8% 52.5%, and 60..0% for 30-day, 1- year and life-time rates respectively. It was also reported that, the prevalence rate of the psychopathology was 50.3% while prevalence rates of the subscales of UCLSQ ranged between 18. 1%-22.6 %. These rates were based on respondents’ scores above the 75 percentiles on Anxiety, Obsessionality, Depression, Disorganised / Distractible, Somatic,

Work Satisfaction and Sylbism subscales and scores below 25 percentiles for Low

Motivation subscale of UCLSQ. This study did not report the prevalence rate of the total scores of each respondent (consolidated study difficulty), hence the rates of the triads were calculated based on the rate of each subscale of UCLSQ and ranged between 4.6%- 6.2%. In this study, a survey of Brain Fag Syndrome among the respondents, using Brain Fag

Syndrome scale was also carried out and the prevalence rate of Brain Fag Syndrome was

22.9%.

CHAPTER THREE

AIMS AND OBJECTIVES

Theoretical Framework

The theoretical framework, on which this study is based, is depicted in the Venn diagram (Figure 1). This shows the constituents (areas) subgroups of the cohort and resultant possible interactions among study difficulty, psychoactive substance use/abuse and

38 psychiatric morbidity; giving rise to co-morbidities (Areas E, F & G) and co-occurrence

(“The Triad”) represented by Area H. .

Figure 1: The constituents’ sub-groups of the cohort

Psychoactive B -The Substance Cohort to be Use F studied D Study Difficulty H EE G

Psychiatric morbidity Morbidity

Key

Area A: No study difficulty, psychoactive substance use or psychiatric morbidity

Area B: Only Study difficulty.

Area C: Only psychiatric morbidity

Area D: Only psychoactive substance use/abuse

Area E: Co- morbidity of psychoactive substance use and study difficulty

Area F: Co- morbidity of study difficulty and psychiatric morbidity

Area G: Co-morbidity of psychiatric morbidity and psychoactive substance abuse

Area H: Co-occurrence of study difficulty, psychoactive substance abuse and psychiatric morbidity

The co- morbidity of psychoactive substance abuse and psychiatric morbidity

(psychological disorder or mental illness) has received much attention from researchers. 39

However, the co-occurrence of study difficulty, psychoactive substance use and psychiatric morbidity (“The Triad”) has not received corresponding attention, (Fatoye, 1998). He suggested that, “A shift in attention to studies involving the three conditions may provide more answers to the questions which have arisen from the observed co morbidity of any of the two conditions”. He further stated that, “An attempt should be made to know the extent of co-existence of the three conditions”. This formed the focal point of this study.

General Aims

This study aims at determining the prevalence of the co- occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity (‘The Triad’) among undergraduate students of the University of Abuja, and to identify the socio-demographic factors associated with “The Triad”.

Specific Objectives

The specific objectives are to:

1. Determine the prevalence of each of study difficulty, psychoactive substance abuse/

use and psychiatric morbidity among senior undergraduate students of University of

Abuja.

2. Determine prevalence of “The Triad”.

3. Identify the socio-demographic characteristics of students, who present with “The

Triad” of study difficulty, psychoactive substance abuse / use, and psychiatric

morbidity.

4. Identify the specific substances that are involved/ influenced in “The Triad” and are

associated with study difficulty and psychiatric morbidity.

5. Estimate the prevalence of Brain Fag Syndrome (BFS) among the students of

University of Abuja.

6. To identify the specific aspects of study difficulty that are associated with

combination of psychoactive substance use and psychiatric morbidity

7. Estimate the magnitude of Brain Fag Syndrome (BFS) among students with “The

Triad”.

8. Determine the prevalence of Brain Fag Syndrome among students with psychoactive

substance use and study difficulty.

9. Identify psychoactive substances commonly abused by students with the Brain Fag

Syndrome.

10. Identify types of study difficulty most commonly associated with Brain Fag

Syndrome.

Hypotheses

1. There would be no difference in prevalence of “The Triad” between male and female

students.

2. There would be no difference in degree of association of sedatives versus stimulants

in relation with “The Triad”.

3. There would be no difference in prevalence of Brain Fag Syndrome among students

with “The Triad” and the general study population.

4. There would be no difference in degree of association of low motivation for studying

with “TheTriad” compared with disorganisation in studying.

5 There would be no difference between degrees of association of stimulants and

sedatives with Brain Fag Syndrome.

CHAPTER FOUR

METHODOLOGY

Study location and settings

The study was conducted at the University of Abuja, Mini-Campus, Gwagwalada,

Abuja, in the Federal Capital Territory. The university still operates from the temporary site

(the Mini campus). The Main campus which is located along the road of the Nnamdi Azikwe

International Airport is yet to have adequate infrastructure for academic activities. The

University of Abuja was established on January 1st 1988, as a dual role university with mandate to run both conventional and distant learning programmes. It was the first university

42 in the country to assume such dual role. The university presently operates at the Mini-campus in Gwagwalada, about 55kilometers South-West axis of the Federal Capital Territory.

University of Abuja admits students from the Federal Capital Territory and the 36 states of Nigeria as well as the neighbouring countries. Admission policy takes cognisance of the Federal Character Policy.

It is pertinent to note at this juncture, that the university is fairly new in comparison with the first and second generation universities, hence only 6 Faculties (namely Social

Sciences, Management Sciences, Education, Law, Sciences and Arts) are fully developed.

The Faculties of Health Sciences, Agriculture, Veterinary Medicine and Engineering are still in an early stage of development, with the most senior students in second (2nd) academic year.

Inclusion criteria

1. Full time undergraduate students of the university.

2. Students in 3rd and 4th year of their course.

Exclusion criteria

1. Students who decided not to participate.

2. Students who were too ill to participate.

3 Students in 1st and 2nd year of their course.

4 5th year Law students

Ethical considerations

1. Permission was sought and received from the authorities of University of Abuja for

the purpose of this study.

2. Approval for the study protocol was obtained from the Research and Ethical

Committee of University of Abuja Teaching Hospital, Gwagwalada, prior to

commencement of the study.

3. Informed consent was also sought and received from the participating students. It

was emphasized that students had the right of refusal to participate in this study.

Subject’s recruitment

The subjects were full time undergraduates in 3rd and 4th year at the University of

Abuja. For the purpose of this study, the reference population of ten thousand, one hundred and thirty four (10,134) was based on the total population of full-time (Conventional,

Regular) students of the university. There were more females (5,200) than males (4,934). The distribution of the students according to their Faculties and gender is shown in Table 2 below.

The ratio of male to female in the total population of the students is 1:1.05.

Table 2: Full-time undergraduate students population according to . Their faculties FACULTIES MALE FEMALE TOTAL 1 Social Sciences 1,577 1,979 3,556 2 Management Sciences 1,522 1,205 2,727 3 Sciences 622 420 1,042 4 Arts 315 607 922 5 Education 424 479 903

6 Law 417 480 897 7 Agriculture 13 19 32 8 Health Sciences 15 8 23 9 Engineering 19 - 19 10 Veterinary medicine 10 3 13

Grand total 4,934 5200 10,134

Sample Size Determination

A sample size that gave a fair representation of the reference population was determined using this formula:

N= (Z) 2 pq d2

Where;

N= the desired sample size (when population is greater than 10,000).

Z=the standard normal deviation usually set at 1.96 (or more simply at 2.0), which corresponds to the 95% confidence level. p = the proportion in the target population with estimated prevalence rate of Co-occurrence of

“The Triad”. For this study, it was based on average of current prevalence of 4.6% to 6.2% among secondary school students in Ilesha, Osun state, Nigeria, (Fatoye 1998); The Mean

=4.6+6.2 /2=5.4 q=1.0- p.

45 d= degree of accuracy desired, usually set at 0.05.or tolerated {5%}.

Therefore, z2 = (2) 2, p = (5.4), q = (0.054), d= (0, 05)

N= 4x5.4 x0.054 0.0025

N = 466.6

The estimated sample size = 467 approximately.

The estimated minimum sample size was 467 respondents. To enhance the precision and increase the sensitivity of the study and to accommodate attrition, the sample size was increased to 624 respondents.

. In a multistage sampling, 26 respondents were chosen by random sampling from each of groups of students in 3rd & 4th year in each of the 12 departments of the 6 selected Faculties.

Procedure

The study was carried out after permissions were granted by the Research and Ethical

Committee of University of Abuja Teaching Hospital,, Gwagwalada, and the authorities of

University of Abuja. Research assistants were recruited and trained. The training was conducted by me, the lead investigator, having obtained adequate training from my supervisor. The training covered: i. Proper administration of the questionnaires. ii. Clear understanding of the contents of the questionnaires which enabled them to give

effective and proper guidance to the respondents.

The use of Research assistants enhanced the collection of data within a reasonable time.

Sampling procedure 46

1. A multistage sampling technique was used in this study. Only the 6 fully developed Faculties were chosen out of the existing 10 Faculties in the university. These are

Science, Social Sciences, Management Science, Arts, Education and Law. They had students in all levels while the remaining 4 had students only in 1st and 2nd year. The number of the students in the 6 selected Faculties was 10,047, 4877 were males and 5170 were females.

This gives male to female (M: F) ratio of 1:1.06.

2. A random sampling method was used to select two departments from each of the 6

Faculties, giving a total of 12 departments as shown in Table 3 below:

From the 12 departments, systematic random sampling was used to select 26 students each from 3rd & 4th year classes/students. This decision was based on the understanding that these groups of students (3rd &4th year) had spent at least 2 years and above in the university, hence were able to give adequate representation of the processes and study experiences in the university system. Since the M: F ratio in the study population was 1:1.05; which is approximately 1:1.

Since the instruments were administered when the students were assembled for their lectures, the researcher arranged for one assistant to administer instrument to female students only, while another administered to male students only.

As the students settled down in the class, the numbers of students were counted. A sampling interval was computed to enable 13 male and 13 female students to be recruited into the study (systematic random sampling). On some occasions, the required number of students of either gender could not be met. So the additional numbers from the other gender were recruited. However this situation did not occur more than four occasions, and the differences amounted to between 1 and 3. The breakdown of the sample test was eventually drawn and shown in Table 3.

Table 3: Respondents’ Faculties, Departments and Levels by Gender

N=624

Faculties Departments M F 3rd yr M F 4th yr Grand Total

Socials sciences Sociology 13 13 26 12 14 26 52 Economics 13 13 26 13 13 26 52

Management Business Administration 13 13 26 13 13 26 52 science Public Administration 13 13 26 13 13 26 52

Sciences Biology sciences 13 13 26 13 13 26 52 MSC 15 11 26 14 12 26 52

Arts English Lit. studies 13 13 26 13 13 26 52 History 13 13 26 13 13 26 52

Education FASSE 13 13 26 13 13 26 52 CSE 12 14 26 13 13 26 52

Law Public & International Law 13 13 26 13 13 26 52 Law 13 13 26 13 13 26 52

Six Faculties 12 Departments 13 13 312 13 13 312 624

Key

CSE: Counselling Science Education.

FASSE: Faculty of Arts and Social Science Education.

MSC: Mathematics, Statistics and Computer Science.

Study Instrument

The instrument consisted of five (5) major parts.

Part 1: Socio-demographic characteristics of the respondents

This part of the questionnaire was designed to capture the socio-demographic characteristics (age, sex etc), and family background of the students.

Part 2: General Health Questionnaire (GHQ-30)

This part of the instrument was designed by Goldberg in 1972. It is a screening

instrument that detects psychiatric disorders (psychological morbidity) generally, regardless

of diagnosis. The original form by Goldberg contains 60 items, each item having four

possible responses. It has been widely validated against the criteria of clinical psychiatric

interview and in different cultures and found to have acceptable sensitivity and specificity.

Goldberg & Blackwell (1970), Tamopolsky et al, (1979) Goldberg et al, (1979),

Radovanovic & Eric (1983) The GHQ has been used in a number of psychiatric morbidity

studies in Nigeria.

The 30-item version (GHQ-30) is the instrument of choice for this study. A score of 5

or more positive responses was taken as an indication for psychiatric morbidity. This was

based on sensitivity and specificity reported at this cut-off point, (Abiodun and Ogunremi,

1990).

Part 3: University College London Study Difficulty Questionnaire (UCLSQ)

This questionnaire was devised by Crown et al, (1973). It was produced after a careful clinical evaluation of complaints of students with study difficulty by the authors and other researchers, which include physicians and psychologists that are involved in students health work. They were specific only on affective and motivational factors contributing to study difficulty excluding socio-cultural and interaction factors.

The UCLSQ has been used to measure study difficulty in other centres including Nigeria. It was used in the cross-cultural study of education and health between Canada and Nigeria and in other projects, (Morakinyo, 1990). It was also used by Fatoye in 1998.

In its original form, UCLSQ consist of 7 subscales. Each scale consists of nine items with 3 possible responses. It was later modified by addition of another subscale bringing the total number to 8 subscales.

The three (3) possible responses are mainly True, Neither True nor False and only false, these are assigned scores of 2, 1 and 0 respectively. There are 9 questions for each subscale, hence the total score obtainable for each subscale, ranges from 0 to18.

The following names were given to the sub-scales.

1. Anxiety (ANX), the higher the score, the higher the level of anxiety.

2. Obsessionality (OBS), the higher the score the higher the level of Obsessionality.

3. Depression (DEP), the higher the score the higher the level of depression.

4. Disorganised-distractible (DIS), the higher the score the higher the level of

disorganisation/distractibility.

5. Low motivation (L-MOT), the higher the score the lower the level of motivation.

6. Somatic (SOM), the higher the score, the higher the level of somatization.

7. Work satisfaction (W-SAT), the higher the score the higher the level of satisfaction at

work (i.e. low score implies low satisfaction).

8. Sylbism (SYL), the higher the score the higher the level of sylbism or syllabus

boundness. This was the later addition (Lucas et al, 1976). With this addition, the

items were arranged so that Anxiety items are Numbers 1, 9, 17, 25 etc.

Obsessionality items are Nos 10, 18, 26 etc, with the other subscales following similar

sequence on the instrument. The authors reported satisfactory reliability and validity.

For this study the median scores of each of the eight subscales would be chosen as the cut off point. The respondents with the scores above the median score for each subscale will be classified as positive and those with scores below the median scores would be termed negative for the subscales respectively. To identify the respondents positive for study difficulty, the median score of the total scores of the respondents in all the subscale will chosen as the cut off point. The respondents with total scores (overall scores) above the median would be classified as positive for consolidated study difficulty, while those with total scores (overall scores) less than the median would be termed negative for consolidated study difficulty.

Part 4: WHO Questionnaire for Students Drug Use Survey

This instrument is a self administered interview schedule, which was developed by experts from many countries. It has three (3) sections, the first section consists of 6 questions items which deals with socio-demographic data of the respondent. The second section would consist of 14 groups of questions, on drug use, including 2 items for validity check. The third section contains a list of optional items and some ethical and moral questions relating to drug use.

The drug use items are concerned with the following drugs: Tobacco, Alcohol,

Cannabis, Cocaine, Amphetamines, Hallucinogens, Hypnosedatives, Barbiturates, Heroin,

Opium and Other Opiates.

Respondents were asked to indicate whether or not they have ever used any of these drugs and whether they had used them in the past one year or in the past 30 days. Age of first use and frequency of usage were also requested for. It was therefore possible to measure the

30-days, 1 year and lifetime prevalence rates while current and past use prevalence rates were determined. The two items for validity check were ‘honesty questions’ aimed at a rough assessment of the validity of the questionnaire.

The authors reported high reliability and validity of the questionnaire in different countries and cultures. In Nigeria Adelekan, {1989} reported high validity and a mean test- retest reliability of 86.7% for all items of the questionnaire.

Part 5: Brian Fag Syndrome Scale (BFSS)

The Brain Fag Syndrome scale was constructed in 1962 by Raymond Prince, specifically to elicit the symptoms of the Brain Fag Syndrome. However, in 1980 Prince and

Morakinyo developed this questionnaire into a 7 item scale. This was done in order to improve its validity for detecting the syndrome (Morakinyo, 1990).

For each item, there are three (3) responses, which are Often, Sometimes, and Never, relating to the presence or absence of symptoms. They assigned scores of 2, 1 and 0 respectively .The maximum score obtainable on the scale ranges from 0 to 14.The higher the score the higher the severity of the illness. The scale is designed to discriminate between

“caseness” and “non-caseness”. For caseness, two conditions must be satisfied. The respondent must have a minimum score of six (6) which must include a score one on each of items 4 and 5. These items deal with the presence of bodily symptoms such as crawling sensations or heat in the head and the interference of those bodily symptoms with studying.

Data Analysis

The data collected were appropriately coded and analysed using the Statistical

Package for Social Sciences (SPSS) version 16.0, and EPI Info. Frequencies of the variables were computed and independent sample t-test was used where appropriate. Fisher’s Exact

Chi-squared Test was used for cross tabulations of the variables. Fisher’s Exact Chi-squared

Test has the advantage of analysing cells with less than five counts; hence it gave more exact and appropriate results. The Odds Ratios otherwise termed OR were gotten using both SPSS

16.0 version and EPI Info. The Odds Ratio indicates the degree of association among the variables analysed. The minimum possible value for OR is zero and the maximum possible value is infinity. An Odds Ratio of 1 occurs when the Odds and hence the proportions are the same in the two groups and is equivalent to no association between the exposure and the disease. It follow that Odds Ratio of more than 1 indicates association between the two groups and the higher the Odds Ratio, the greater the degree of associations between the exposed and unexposed. Risk Ratio also called Relative Risk was also used to measure the strength of association between the exposed and the unexposed group. A risk ratio of greater than 1 occurs when the risk outcome is higher among those exposed to the factor than among

53 the unexposed, and when less than 1, it indicates that the risk is lower among those exposed, suggesting that factor may be protective.

Correlation Coefficient analysis of the quantitative (numerical) variables was carried out. This was done to determine degree of association (correlation) among the quantitative variables.

CHAPTER FIVE

RESULTS

A total of 624 questionnaires were administered to third (3rd ) and fourth (4th) year students. Sixteen questionnaires were rejected due to non-completion, and eight (8) due to inconsistent and conflicting data. Six hundred questionnaires were finally analysed giving a rate of 96.2%.

Socio-demographic characteristics of the respondents

Gender distribution: Two hundred and ninety five (49.2%) were males and 305 (50.8%) of the respondents were females. The male to female ratio (M: F) was 1: 1.03. This is comparable to that of the general population of the students with gender distribution ratio

1:1.05 of male to female.

Age distribution: The age range of the respondents was from 18 to 41 years. The mean age for females was 22.4yrs (±2.93) while that of the males was 23.9 yrs (±3.39) See Table 4.

There was a significant difference using independent sample t-test in the age distribution between the males and females respondents. (t = 5.52, df =7, P <0 .001). Religion: Most of the respondents (74.5%) professed Christian religion, while 23.5% were Muslims and only

2% practice other religions. See Table 5.

Respondents’ geopolitical zones of origin: The respondents were from 256 Local

Government Areas of 33 states in 6 geopolitical zones, and the Federal Capital Territory.

About half of the respondents have their permanent residence in suburb of cities, while the

55 remaining resides in villages, towns and inner cities. Most respondents (86.5%) had spent between 2 and 4 years in the university. (Table 6)

Table 4: Gender and Age distributions of the respondents (N=600)

Age Group N % N % N %

( years) M F Total

18 – 20 18 3 29 48 47 7.8

21 – 23 97 16.2 133 22.2 230 38.3

24 – 26 123 20.5 102 17 225 37.5

27 – 29 37 6.2 25 4.2 62 10.3

30 – 32 14 2.3 3 .5 17 2.8

33 – 35 7 1.2 2 .3 9 1.5

36 – 38 5 .8 3 .5 8 1.3

39 – 41 1 .2 1 .2 2 .3

Total 295 49.2 305 50.8 600 100

TABLE 5: RELIGION OF RESPONDENTS N = 600

RELIGION NUMBER PERCENT Christianity 447 74.5 Islam 141 23. 5 Traditional/ Others 12 2.0 Total 600 100

TABLE 6: GEOPOLITICAL ZONES OF RESPONDENTS N =600

ZONE FREQUENCY PERCENT North-East 16 2.7 FCT 29 4.8 North-East 39 6-5 South – West 88 14.7 South- South 117- 19.5 South– East 125 20.8 186 North – Central 31.0 Total 600 100

Socio-demographic characteristics of respondents parents

The demographic characteristics of the respondents’ parents showed that most of them

(94.3%) were from stable families (friendly parental relationships), and 71.8% were from monogamous family settings while 28.2% were from polygamous families.(Table 7)

Educational levels: A greater percentage (61.9%) of the respondents fathers had tertiary education compared with their mothers 56.8%. More of the mothers (10.4%) had no formal education in comparison with their fathers (8.2%). (Table 7).

Occupational status: Most of the respondents’ parents belonged to the first 5 groups of occupations namely Legislators, Senior Officials, Managers; Professionals, Technicians;

Clerical Officers and Sales Business and Services related workers. This implies that most of

57 them were from the middle and upper classes of the society. However, many of their mothers

(26.5%) fell into the sales, business and services group. (Table 8).

Table 7: Socio-demographic characteristics of respondents’ parents

Family Status %

Monogamy 431 71.8

Polygamy 169 38.2

Parental relationship

Divorced, one or both parent dead 22 3.7

Friendly 559 94.3

Not friendly 12 2.0

Educational level (fathers)

No formal Education 50 8.5

Primary Education/Koranic school 60 10.2

Secondary Education 93 15.8

Tertiary Education 364 61.9

Not sure 21 3.6

Educational levels (mothers))

No Formal Education 61 10.4

Primary Education/ Koranic school 73 12.5

Secondary Education 91 15.5

Tertiary Education 333 56.8

Not sure 26 4.8

Table 8: Occupational levels of respondents parents

Major Occupational Grouping of Father Mother their Parents n % n %

Legislators senior Officials & Managers 52 87 22 3.7

Professionals 205 34.2 86 14.3

Technical & related workers 64 10.7 106 17.7

Clerical officers & related workers 43 7.2 86 14.7

Sales, business & services related 77 12.8 160 28.2 workers

Farmers, lumbers, hunters related 34 5.7 22 3.7 workers

Miners, quarry & related workers 43 7.2 6 1.0

Workers in Transport industry 22 3.7 3 0.5

Workers in crafts, manual labourers 15 2.5 7 1.2

Other workers nec and / or not reported 31 5.2 90 15.0

Total 586 100 588 100

Study Difficulty

It was considered necessary to devise an index (measure) of the overall study difficulty. The simplest method that was chosen was to compute the students’ overall scores on the various subscales of UCLSQ, and this was called, “the consolidated study difficulty”

(CSD). A score above the median score for the CSD was regarded as indicating study difficulty in the respondent.

It was used in order to simplify classification of the students’ multiple scores, which would be cumbersome. Deriving and using these scores facilitated the categorical identification of respondents in the various sub-groups.

Prevalence rates of study difficulty among the respondents

Anxiety: The median scores of the respondents on Anxiety subscale was 8.00. . A total of

306 (51%) respondents fell into this group and were termed as positive for Anxiety subscale,

(Table 9).

Obsessionality: For this subscale the median score was 8 and 353 (58.8%) respondents were positive for Obsessionality subscale, (Table 9)

Depression: Respondents had median score of 7.00 on this subscale. A total of 298 (49.7 %) respondents were positive for Depression subscale of UCLSQ. (Table 9)

Disorganised / Distractible: Respondents had the median score of 6. A total of 351

(58.5%) respondents were positive for Disorganised subgroup of UCLSQ.

Low motivation: In this subscale respondents had median scores of 7.00 and 293 (48.8%) of these respondents were positive for this subscale.

Somatic: Respondents median score in this subscale was 7.00. A total of 342 (57%) respondents were positive for somatic subscale.

Work Satisfaction: The median score was 10.00. A total of 312 (54%) respondents were positive for this subscale.

Sylbism: Respondents had median score of 10.00. A total of 318(53.0%) of the respondents were positive for this subscale.

Among the UCLSQ subscales, respondents recorded the highest mean score of 10.08 on the Work Satisfaction subscale, while the lowest mean score of 6.30 was recorded by the respondents in the Disorganised/Distractible subscale. The highest median of 10.00 was also recorded by the respondents in the Work Satisfaction and Sylbism subscales and the lowest median of 6.00 were recorded by the respondents in the Disorganised/Distractible subscale.

(Table 9).

Consolidated study difficulty: The median score for the consolidated study difficulty was

63.00. A total of 323 (53.8%) respondents were positive for this group.

Table 9: Prevalence rates of study difficulty among the respondents (N=600) n % Median n %

Variables Positive Negative

Anxiety (ANX) 306 51 8.00 294 49

Obsessionality (OBS) 353 58.8 8.00 247 41.3

Depression (DEP) 298 49.7 7.00 302 50.3

Disorganised/ Distractible (DIS) 351 58.5 6.00 249 41.5

Low Motivation 293 48.8 7.00 307 51.2 (L-MOT)

Somatic (SOM) 342 57.0 7.00 258 43.0

Work satisfaction (W-SAT) 312 52.0 10.00 288 48.0

Sylbism(SYL) 318 53.0 10.00 282 47.0

Consolidated study difficulty ( CSD) 323 53.8 163.00 277 46.2

Psychoactive substance (drug) use/abuse

On honesty questions, 85.7% and 86.0% of the respondents stated, that they would have admitted if they had ever used cannabis or heroin/opium respectively, 13.3% and 12.7% reported they would not have admitted to ever use cannabis and heroin/opium, while 1.0% and 1.3% were not sure if they would have admitted to the use of cannabis and heron/opium respectively.

The prevalence rates of use of all categories of drugs by students are shown on Table 10.

Life time prevalence rate was highest for alcohol 57.3%, followed by stimulants (35.7%) and tobacco (24.0%). The least was opium/heroin with (1.7%). The previous year and 30 days prevalence rates followed similar pattern but the rates were lower than the life time use.

Consolidated life-time use (that is, the prevalence of all categories of psychoactive substances) was 67.7%, while that of current use was 46%.

Table 10: Prevalence rates of drug use among respondents (N=600)

Drug Lifetime Use Previous 12months use Previous 30days use

n % n % n %

Tobacco 144 24.0 102 17.0 84 14.0

Alcohol 344 57.3 274 45.7 206 34.3

Cannabis 87 14.5 73 12.2 54 9.0

Cocaine 29 4.8 25 4.2 16 2.7

Stimulants 214 35.7 202 33.7 179 29.8

Hallucinogens 22 2.7 13 2.2 9 1.5

Inhalants 67 11.2 43 7.2 30 5.0

Hypnosedatives 35 5.8 28 4.7 20 3.3

Barbiturates 10 1.7 6 1.0 6 1.0

Opium 10 1.7 7 1.2 5 0.6

Heroin 10 1.7 8 1.3 5 0.8

Other opiates 17 2.8 11 1.8 6 1.0

Total 600 100% 600 100% 600 100%

Psychiatric morbidity

(a)General psychiatric morbidity

This was measured using GHQ – 30. The respondents’ mean score was 4.09 (±3.31).

The scores ranged from 0 to 22, the respondents that scored ≥5 were classified to be positive for psychiatric morbidity. A total of, 213(35.5%) respondents were grouped as having psychiatric morbidity.

(b) Specific psychiatric morbidity

The Brain Fag Syndrome

The frequency distribution of the Brain Fag syndrome scale scores showed that the scores ranged from 0 to 13. The mean score was 5.19 (±0.08). Scores of 6 and above and minimum of one score in items 4 and 5 were used as criteria for caseness. A total of 216

(36.0%) respondents met the requirement for caseness and were categorised as positive for

BFS.

Identification of co-morbidities and estimation of their magnitudes

From the list of scores on the 3 main variables: study difficulty, psychoactive substance and psychiatric morbidity, the various subgroups were identified, and their magnitudes computed as follows:

1. Co-morbidity of study difficulty and psychoactive substance abuse

This subgroup comprised of respondents that scored above the median on the consolidated study difficulty and were positive for psychoactive substance abuse. They accounts for 9.2% of the total study sample and constitute the subgroup F in Figure 2.

2. Co-morbidity of psychoactive substance use and psychiatric morbidity

Respondents, who scored above the median of the consolidated psychoactive substance use as well as score positive on GHQ- 30, fell into this group. They constituted

6.5% of the total sample population and formed the subgroup E in Figure 2.

3. The co-morbidity of study difficulty and psychiatric morbidity

Respondents who scored above the median of 63 in the consolidated study difficulty and who were identified as having psychiatric morbidity by GHQ -30 constituted this group.

They accounted for 6.6% of the total study sample, and formed the subgroup G in Figure 2.

4. Co-occurrence of study difficulty psychoactive substance abuse and psychiatric morbidity (THE TRIAD):

This group was made up of respondents who were identified as having psychiatric morbidity by GHO 30 while scoring above the median scores of both the consolidated psychoactive substance use and consolidated study difficulty. This group of 100 respondents was deemed to be suffering from “The Triad”. They accounted for 16.7%, and formed the subgroup H in

Figure 2. It is interesting that of the 4 subgroups described so far, they had the highest percentage.

Figure 2: Prevalence rates of the various sub-groups of the study sample

A 66

Psychoactive B Substance Use F D 24.3%

9.2% 16.7% -The Cohort=600

16.7% 10.2% 6.6% E 6.5%

3.2%

Relationship between the Brain Fag Syndromes (BFS) with the co- morbidities

Having identified the various groups of co-morbidities as reported above, the respondents in each group were examined for their scores on the Brain Fag Syndrome Scale.

This was to determine the proportion in each group that could be described as suffering from

BFS. The results are shown in Figure 3 below. Table 11, also shows the proportions found positive for BFS in the various co-morbidities subgroups (D, E, F and G) as well single morbidities subgroups (A, B and C). Between 22 and 23 % (22.4%) of subgroup F (co- morbidity of study difficulty and psychoactive) substance use/abuse were found to have BFS.

About two-third (65%) of subgroup G (study difficulty and psychiatric morbidity) have BFS, while a much higher proportion (82.1%) of sub-group E had the syndrome. The highest proportion was among sub-group H (“The Triad”). Of the 100 respondents in subgroup H, 83

(83%) were positive for BFS. Thus it would seem that BFS was least associated with co- morbidity of study difficulty and psychoactive substance use while it was very highly associated with ‘The Triad’. There is a statistically significant difference between this and the

36% prevalence of BFS found among the study population generally. This disproves hypothesis three (3) which postulated that there would be no difference in prevalence of BFS among students with the ‘The Triad’ and the general study population”. There was high degree of association between Brain Fag Syndrome and ‘The Triad’ as shown by a high Odd

Ratio (OR) of those who had co-occurrence of ‘The Triad’ and Brain Fag Syndrome against those with ‘The Triad’ and had no Brain Fag Syndrome. OR=13.5.

Figure 3: Prevalence rates of BFS among the subgroups of the cohort

4.8% A

Psychoactive 22.4% B Substance 13% -The Use F Cohort=600 D Study 83% Difficulty 19.4% E H 65% 82.1% E G

Psychiatric morbidity. morbidity. morbidity. Morbidity57.9%

Table11: Prevalence rate of BFS among the subgroups of the cohort

Subgroups Prevalence Rate Prevalence Rate of BFS

N % N %

A No study difficulty, 146 24.3 7 4.8 psychoactive substance use or psychiatric morbidity B Study difficulty 100 16.7 13 13.0 only C Psychiatric 19 3.2 11 57.9 morbidity only D Psychoactive 61 6.5 12 19.4 substance use only E Psychoactive 39 6.5 32 82.1 substance use and psychiatric morbidity F Study difficulty 59 9.2 13 22.4 and psychoactive substance use

G Study difficulty & 40 6.7 26 65.0 psychiatric morbidity H The Triad 100 16.7 83 83.0

Socio-demographic characteristics of sub-group H (‘The Triad’)

(a) Gender: Of the 100 respondents with “”The Triad”, 67 (67.0%) were males while 33

(33.0%) were females (Table 12). There was a statistically significant association between the

70 male gender and “The Triad”, using Fishers Exact test. (P < 0.001).The Odds Ratio (OR) and

Relative Risks of male to female were 3.9 and 3. 1 respectively Thus hypothesis one (1), which postulated that, there would be no difference in prevalence of “The Triad” between the male and the female respondents was disproved.

Table 12: Association between gender and ‘The Triad’

N= 600

‘The Triad’

Gender No Yes %

Male 228 67 295

Female 272 33 305

Total 500 100 600

(b) Age: Table 13 shows that respondents who had ‘The Triad’ fell into the age groups 18-

35 years, while those in age groups 36-41 years had no Triad. Age group 27-29 years had the highest percentage (24.2%), while age group 18-20 had the least with 12.8%. However, there is no statistically significant association between age groups in general and ‘The Triad’ (P

>0.05, df =7).

Table 13: Association between Age group and ‘The Triad’

‘The Triad’

Age group No Yes % Total

18 – 20 41 6 12.8% 47

21 – 23 198 32 13.1% 230

24 – 26 183 42 18.7% 225

27 – 29 47 15 24.2% 62

30 – 32 14 3 17.6% 17

33 – 35 7 2 22.2% 9

36 – 38 8 0 0 8

39 – 41 2 0 0 2

Total 500 100 600

(c) Education: Forty four (14.7%) third ( 3rd) year students had ‘The Triad’ while fouth (4th ) year students were 56 (18.7%).Using Fisher’s Exact 2-sided, test p value was not statistically significant (P> 0.05) The Odds Ratio (OR) 0.75 95%CI ( 0.48-1.18) and Relative Risks

(RR)=0.79 95%CI ( 0.55-1.13), p value>0.05..

Figure 4: Showing the relationship between the educational level of the Respondents and “The Triad”

(d) Academic Discipline (Departments)

Department of Foundation of Arts and Social Sciences (FASSE) had greatest number of students (16%) with ‘The Triad’ followed by Departments of Biological sciences with

(13%), Counselling, & Sciences Education (CSE) (12%) Law (11%) and Department of

English Literature Studies had least number of students with ‘The Triad’ (2%). There is significant associations between the departments and ‘The Triad’ (P=0.05) See Table 14. 73

Table 14: Associations between respondents’ academic discipline and ‘The Triad’ (X² =26. 850 , df=11, p value= 0.05)

Faculties Departments No Triad Yes Total %

1. Arts English. Lit. 48 2 50 2 . History 42 8 50 8

2. Education FASSE 34 16 50 16 CSE 38 12 50 12

.3. Law Law 39 11 50 11 . Int & Pub. Law 44 6 50 6

4. Mgt.Sci. Bus. Admin 45 5 50 5 Pub.Admin. 47 3 50 3

5. Sciences. Bio. Sciences 37 13 50 13 . MSC 42 8 50 8

6. Social Sc. Sociology 42 8 50 8 Economics 42 8 50 8

Total 6 12 500 100 600 100

 FASSE: Foundation of Arts and Social Sciences  Pub. Admin: Public Administration  CSE; Counselling and Science Education  Pub. & Int. Law: Public & International Law  Bio. Sciences: Biological Sciences  English Lit: English Literature  MSC:; Mathematics, Statistics &Computer sciences

(e) Family status: Respondents from monogamous family settings account for 65% of students with ‘The Triad’ and the remaining 35% were from polygamous family setup. Using

Fisher’s Exact 2-sided test (P >0.05, df =1). However, Odds Ratio (OR) of monogamous family/polygamous family was 1.1.See Table 15.

Figure 5: Showing the association between family status and “The Triad”

Table 15: Associations between family status and ‘The Triad’

Triad

Family Status No Yes Total

Monogamy 366 65 431

Polygamy 134 35 169

Total 500 100 600

(f) Father’s level of education: The finding in, this study shows that there was no statistically significant association between paternal educational level and ‘The Triad’ (P

>0.05). See Table 16.

Table 16: Association between Fathers level of education & ‘The Triad’

N=588

Father level Triad

Of education No Yes Total. No Total %

No formal education. 38 12 50 12.1%

Primary 45 15 60 15.1%

Secondary 79 14 93 141%

Tertiary 309 55 364 55.6%

Don’t know 18 3 21 3.1%

Total 489 99 588 100

(g) Parental relationship: This study findings show that respondents whose parental relationship are unfriendly were highly associated with ‘The Triad’ ,followed by those whose parents live separately, while those respondents whose parents had healthy relationships were least associated with “The Triad”. There was a statistical significant association between parental relationship and “The Triad”, (P< 0.05).See Table 17.

Figure 6: Showing the association between parental relationship and “The Triad”

Table 17: Association between Parental relationship and ‘TheTriad’

N=593

Triad

Parental Relationship No Yes Total % age by group

1 17 5 22 23%

2. 470 89 559 15.9%

3. 7 5 12 41.6%

1. Parents don’t live together

2. Friendly .

3. Not friendly (they quarrel a lot

Specific psychoactive substances associated with study difficulty

The findings show that, all the psychoactive substances, namely Tobacco, Alcohol,

Cannabis, Cocaine, Stimulants, Hallucinogens, Volatile solvents, Tranquilizers, Sedatives,

Opium, Heroin and other Opiates were associated with Study difficulty in varied degrees.

Using Fisher’s Exact tests Tobacco, Alcohol, Cannabis, Cocaine and Stimulants had statistically significant (P <0.05) association with study difficulty. Measure of Agreements were statistically significant in association with Tobacco, Alcohol and Stimulants (P <0.05).

Odds Ratios of those that use these psychoactive substances and those that do not use them were measured. All except Hallucinogens, Tranquilizers and Other Opiates had high Odds

Ratio values. (Table18). .

Specific psychoactive substances associated with psychiatric morbidity

This study shows that all the psychoactive substances were associated with

psychiatric morbidity, also in varied degrees. Tobacco, Alcohol, Cannabis,

Stimulants, Heroin and Other Opiates had statistical significant association with

Psychiatric morbidity (P < 0.05). The Measure of Agreement was statistically

significant for Tobacco and Alcohol, (P<0.001) while that of Cocaine was not

significant. The other psychoactive substances had no Measure of Agreement. The

Odds Ratios were significant (P<0.05) for all psychoactive substances except that of

Heroin. (Table18).

Table 18: Association between specific psychoactive substances With study difficulty and psychiatric morbidity

Psychoactive substance Study Difficulty Psychiatric Morbidity

P-value P- value Odds ratio P-value P value Odds ratio

(Fisher’s Exact test) (MOA ) Ffisher’sEexact test) (MOA ) Tobacco 0.000** 0.000** 3.2 0.000** 0.000** 6.8

Alcohol 0.000** 1.9 0.000** 0.000** 2.8

Cannabis 0.000** 0.05** 2.3 0.000** 4.5

Cocaine 0.02** 0.02** 7.7 0.289* 0.219* 1.8

Stimulants 0.02** 0.02** 1.1 0.000** 3.6

Hallucinogens 0.334* 0.295* 0.5 0.727* 1.5

Volatile Solvent 0.351* 0.294* 1.5 0.46* 1.9

Hypnosedatives 0.655* 0.606* 0.8 0.08* 3.5

Sedatives 0.217* 0.108* 4.9 0.193* 3.7

Opium 1.000* 0.979* 0.9 0.131* 5.5

Heroine 1.000* 0.675* 1.5 0.005** 0.4

Other Opiates 0.656* 0.431* 2.0 0.023** 9.3

Key

**Statistically significant (P<0.05) Fisher’s Exact test

*Not statistically significant (P>0.05) Fisher’s Exact test

MOA Measure of Agreement

Specific aspects of study difficulty associated with psychoactive substance use

The findings show that all aspects of study difficulty had statistically significant association with psychoactive substance use, except Low motivation and Work satisfaction.

The following were found to have statistical significant associations with psychoactive substance use; Primary and Secondary types of study difficulty,(Table 1 Morakinyo’s

Classification of Study Difficulty) Anxiety, Obsession, Depression, Somatic, and Syllabism subscales of study difficulty, (P <0.05). Measure of Agreement was statistically significant in association with Anxiety, Obsession, Depression, Somatic, and Syllabism subscales. The

Odds Ratio (OR) was significant in all except also in Low motivation and Work satisfaction subscales. (Table 19)

Specific aspects of study difficulty associated with psychiatric morbidity

This study shows that all aspects of study difficulty except Low motivation and Work satisfaction had statistically significant association with psychiatric morbidity, using Fisher’s

Exact, test, Primary ,Secondary, Anxiety, Obsession, Depression and

Disorganised/Distractible had highly statistically significant association (p<0.001) with psychiatric morbidity. (Table19).

Table 19: Specific aspects of study difficulty associated with Psychoactive substance use and psychiatric morbidity

Study psychoactive substance Psychiatric morbidity Difficulty (current use) P value MOA OR P value MOA OR

Primary/Secondary 0.000** - - 0.000** - -

Anxiety 0.000** 0.000** 2.0 0.000** 0.000** 2.8

Obsession 0.000** 0.000** 0.8 0.000** 0.000** 3.0 Depression 0.000** 0.000** 2.1 0.000** 0.000** 2.4

Disorganised/ Distractible 0.115* 0.113* 1.3 0.000** 0.000** 2.4

Low motivation 0.257* 0.267* 0.8 0.174* 0.171* 0.8

Work satisfaction 0.512* 0.462* 0.9 0.459* 0.69* 0.7

Sylbism 0.011** 0.010** 1.5 0.000** 0.000** 2.1

Key * P .value not significant (P>0.05) Fisher’s Exact test ** P. value significant (P<0.05) Fisher’s Exact test MOA Measure of Agreement

OR Odds Ratio

Prevalence of psychoactive substance use, study difficulty and Psychiatric morbidity among students with Brain Fag Syndrome

A total of 216 students had B F S, of these, 145 (67.7%), 154 (71.3%) and 165 (77.5) students were positive for psychoactive substance use (lifetime use), study difficulty and psychiatric morbidity respectively. (See Table 20)

Table 20: Prevalence of Brain Fag Syndrome among students with Study difficulty, psychoactive substance use and psychiatric morbidity (N=216)

N %

Psychoactive substance 145 67.7%

Study difficulty 154 71.3%

Psychiatric morbidity 165 77.5%

Psychoactive substances commonly used by students with

Brain Fag Syndrome

The study shows that Stimulants, Tobacco, Alcohol, and Cannabis were psychoactive substances most commonly used by students with BFS. Using Fisher’s Exact test, they were statistical significant (P <. 001, df =11.). (Table21).

Table 21: Psychoactive substances most commonly associated with

Brain Fag Syndrome (BFS)

Psychoactive substance % P. value Life – time use

Tobacco 57.6% <.001***

Alcohol 45.0 <.001***

Cannabis 64.4 <.001***

Cocaine 58.6 <.045**

Stimulants 54.7% <.001***

Hallucinogens 54.5 >.05**

Volatile solvents 59.7% <.005**

Hypnosedatives 60.0 <.05**

Barbiturates 80.0 <.05**

Opium 60.0 >.05*

Heroin 80.0 >0.05 Other opiates 64.7 <.05**

* P. Value not significant (P>0.05) (Fisher’s Exact test ** P. Value moderately significant (P<0.05) Fisher’s Exact test *** P. Values highly significant (P<0.001) Fisher’s Exact test

Association between the psychoactive substances (lifetime) use and the BFS

This study has shown that most psychoactive substances had statistically significant association with BFS. Stimulants, Alcohol, Cannabis, Inhalants and Tobacco were highly statistically significant with p <0.001 using Fisher’s Exact test. (Table 22).

This has disproved hypothesis 5 (page 25) which postulated that “there would be no difference between degree of association of stimulants and sedatives with Brain Fag

Syndrome.

Table 22: Relationship between the psychoactive substances & BFS 87

Key

Psychoactive substance BFS N – 216 P value Odd Ratio (lifetime) use Fishers Exact No % Yes % Test (OR)

Tobacco (n = 144) 133 61.6 83 38.4 <0.001* 3.3

Alcohol (n = 344) 58 26.9 158 73.1 <0.001* 2.9

Cannabis (n = 87) 160 74.1 56 25.9 <0.001* 3.9

Cocaine (n = 29) 199 92.1 17 7.9 <0.05** 2.6

Stimulants (n = 214) 99 45.8 117 54.7 <0.001* 3.5

Hallucinogens (n = 22) 204 94.4 12 5.6 >0.05*** 2.2

Inhalants (n = 67) 176 81.5 40 18.5 <0.001* 3.0

Tranquillizers (n = 35) 195 90.3 21 9.7 <0.05** 2.8 (Hypo sedatives)

Barbiturates (n = 10) 208 96.3 8 3.7 <0.05** 7.3

Opium (n = 10) 210 97.2 6 1.0 >0.05*** 2.7

Heroin (n = 10) 208 96.3 8 3.7 >0.05*** 7.3

Other opiates (n = 17) 205 94.9 11 6.1 >0.05*** 3.3

* Highly significant (p<0.001) Fisher’s Exact test

* Moderately significant (p<0.05) Fisher’s Exact test

* Not significant (p>0.05) Fisher’s Exact test

Relationship between the subscales of UCLSQ and “The Triad”

The findings in this study show that the various subscales of the UCLSQ were associated with The Triad. However, the degree of association varied. They all have statistical significant association with ‘The Triad’ (p <0.001). Low motivation subscales, had the lowest Odd Ratios of 0.41, while Obsessionality had the highest (OR) 14.6, followed by

Anxiety (11.8), Depression (8.3), Somatic (4.9), Disorganised/Distractible (4.2), Sylbism

(4.1), and work satisfaction (0.61). Thus this has disproved hypothesis 4 (page 25) which postulated that “there would be no difference in degree of association of Low motivation with

“TheTriad” compared with disorganized.

Table 23: Relationship between subscales of UCLQ and ‘The Triad’

Study difficulty Triad Fishers Exact Odds ratio subscales No % Yes % P value

Anx 10 10 90 90 <0.001 11.8

Obs 6 6 94 94 p <0.001 14.6

Dep 14 6 86 86 p <0.001 8.3

Dis 17 17 83 83 p <0.001 4.2

Lmot 69 69 31 31 p <0.001 0.41

Som 16 16 84 84 p <0.001 4.9

Wsat 62 62 38 38 p <0.001 0.61

Sylbism 21 21 79 79 p <0.001 4.1

The types of Study difficulty most commonly associated with Brain Fag Syndrome (BFS)

The study shows that, the secondary (Type B) of study difficulty, which is associated with psychiatric disorders, was the most common type of study difficulty associated with

BFS. Of the 152 students with co morbidity of study difficulty and BFS, .118 (77.6%) had secondary types of study difficulty, while 34 (22.4%) student had type A (primary) study difficulty (.Morakinyo’s Classification of Study Difficulty).There is statistical significant difference between type 1( primary study difficulty) and type 2 (secondary study difficulty) in association with yhe Brain Fag Syndrome. ( X² =165.878, df = 2, p value < 0.001).

Table 24: The types of Study Difficulty most commonly associated With Brain Fag Syndrome (BFS)

Primary (Type A) Not associated 34 22.4% psychiatric illness

Secondary (Type B). Associated with 118 77.6% psychiatric illness

Total 152 100%

Chi-square t-test:

X² = 165.878, df = 2, p value < 0.001

Correlation Coefficient of the Quantitative variables

The correlation coefficient of quantitative variables at 95% confidence interval

(95%CI) show that

Age: Age was positively correlated to GHQ scores and BFS scores, but negatively correlated to consolidated study difficulty and all the 8 subscales of UCLSQ. However, none of the correlation was statistically significant (P>0.05).

Consolidated study difficulty scores: These scores were positively correlated with scores of all the 8 subscales of study difficulty, GHQ scores, BFSS scores, (P<0.001) which is indicative of high statistical significance. However, they were negatively correlated to age,

(P<< 0.05) which is moderately statistically significant.

General Health Questionnaire scores: G H Q scores had positive correlation with Age, all the 8 subscales of study difficulty, consolidated study difficulty and BFSS scores. The correlations were highly statistically significant (P<0.001) in all except Age and Work satisfaction (P >0.05).

Brain Fag Syndrome scales scores: Brain Fag Syndrome scale scores had statistical significant positive correlations with consolidated study difficulty, G HQ scores, and all the 8 subscales except work satisfaction subscale and Age.

Anxiety: Anxiety subscale scores were positively correlated with scores of other subscales, consolidated study difficulty, GHQ scores and BFSS scores. They were highly statistically significant, (P<0.001).

Obsessionality: Obsessionality subscale scores were found to have positive correlations with the scores of all other subscales, consolidated study difficulty, GHQ scores and BFSS scores. The correlations were highly statistically significant. (P< 0.001)

Depression: The scores of Depression subscale had high statistical significant positive correlations with consolidated study difficulty, GHQ scores, BFSS scores and all the other subscales of study difficulty except work satisfaction

Disorganised/distractible: The scores of disorganised /distractible subscale had statistical significance and positively correlated with consolidated study difficulty, GHQ scores, BFSS scores and all other subscales of study difficulty except work satisfaction subscale and age.

See Table 25.

Low Motivation: The scores of low motivation subscale also had high statistical significance positively correlated with the scores of consolidated study difficulty GHQ scores, BFSS scores and all other subscales of UCLSQ except work satisfaction subscale and age, in which they were negative correlation.

Somatic: Somatic subscale had statistical significance and positively correlated with consolidated study difficulty, GHQ scores and other subscales of UCLSQ but negatively correlated with age. (p > 0.05).

Work Satisfaction: The scores of Work Satisfaction subscale had positive and statistically significant correlations with Anxiety, Obsessionality, Sylbism and consolidated study

92 difficulty while it had negative and no statistical significant correlation with age. See Table

25.

Sylbism: Sylbism subscale had positive and statistical significant correlation with all other subscales, consolidated study difficulty, GHQ scores and BFSS scores, while negatively but not statistically significant correlated to age.

Table 25: Correlation Coefficient of Quantitative variables

AGE CSD GHQ BFSS ANX OBS DEP DIS LMT SOM WST SYL

AGE 1 -.081 .027 .032 -.036 -.079 -.080* -.019 -.078 -.043 .008 -.050

CSD -.081* 1 .295*** .348*** .798*** .692*** .781*** .746*** .740*** .638*** 348*** .618***

GHQ .027 295*** 1 .343*** .259*** .227*** .273*** 243*** .144*** .175*** .065 .269**8

BFSS .032 348*** 343*** 1 .353*** .273*** .391*** .319*** .294*** .239*** .069 .208***

ANX -.036 .798*** .259*** .353*** .1 .583*** 681*** .600*** .564*** .506*** 186*** .502***

OBS -.079 692*** .227*** .273*** .583*** 1 506*** .488*** .413*** .317*** .307*** 479***

DEP -.080* 781*** .273*** .391*** .681*** .506*** 1 .674*** 638*** 578*** .025 .393***

DIS -.019 .746*** .243*** .319*** 600*** .488*** .674*** 1 .671*** .567*** 026 .342***

LMT -.078 .740*** .144*** .294*** .564*** .413*** .638*** 671*** .1 .586**8 .079 .347***

SOM -.043 638*** .175*** .239*** .506*** .317*** 578*** .567*** 586*** 1 014 .238***

WST .-008 348*** .065*** .069 .186*** .307*** 025 .026 .079 .014 1 .447***

SYL -.050 .618*** .269*** .208*** .502*** .479*** .393*** .342*** .347*** .238*** .447*** 1

* Correlation significant at p value <0.05 ** Correlation significant at p value <0.01 *** Correlation significant at p value <0.001

AGE; Respondents’ age CSD; Consolidated Study Difficulty GHQ; General Health Questionnaire Scores BFS; Brain Fag Syndrome Scale Scores ANX; Anxiety OBS; Obsessionality DEP; Depression DIS; Disorganise/Distractible LMT; Low Motivation SOM; Somatic WST; Work Satisfaction SYL; Sylbism

CHAPTER SIX

DISCUSSION

Response to self-reported questionnaires

All over the world, use of self reported questionnaires in drug use surveys, and other surveys is quite popular. This may be due to the relative low cost, ease of administration, as well as ease of analysis and interpretation. It is believed that standardised questionnaires allow for easy comparison of results from different communities and in different populations.

This study recorded a high response rate of 96.2% which compared favourably with that reported by other authors, 85% by Akinhanmi, (1996), 87.8% Tawasu (2005), 94.3%

Daramola (2004), and 95.5% Okogbenin, (2008). These high response rates suggest that the use of self-reported questionnaires remains an acceptable method of obtaining data on drug use, and by extension on study difficulty and psychiatric morbidity. On the honesty questions of the World Health Organisation Students Drug Use Survey Questionnaire, 85.7% and

86.6% of the respondents stated that, they would admit in the instrument if they had ever used cannabis and heroin/opium respectively, while 1.0% and 1.3% were not sure if they would admit the use of cannabis and opium/heroin and about 13% affirmed, they would not admit if they had ever taken cannabis or opium/heroin. These figures are higher than the 68% reported by Smart et al, (1980), 57% Adelekan and Odejide (1989), but similar to that reported by

Tawasu (2005), Akinhanmi (1996) and Okogbeni (2008) which were 85%, 80% and 88% respectively. The rate of missing and inconsistent data in this study ranged from 0.8% to

2.7%. This is lower than the 5% reported by Akinhanmi (1996), Adelekan and Odejide

(1989), however similar to 1.5% - 2.2% reported by Okogbenin (2008). The low rates of missing data as well as the high rate of honesty answers were due to careful adherence to procedure that reassured the participants of anonymity and confidentiality of responses. The

95 respondents were requested to check for any missing data or mistakes before submitting their questionnaires.

Socio-demographic characteristics of the respondents

There were more females than males in the study population, male: female (M: F) ratio is 1:1.03. This is comparable to the general population of the students of University of

Abuja with male: female ratio (M: F) of 1:1.05. This differed from other studies where male dominance was reported in tertiary institutions, Daramola (2004) and Onofa (2006). The preponderance of female gender in this study could reflect the admission policy of the university and the sampling methodology which captured male and female based on equal chances.

The age of the respondents ranged between 18 and 41 years, this is similar to age range of (16 – 43) years reported by Daramola (2004) in a study of drug use among medical students in University of Ilorin. In this study the total mean age was 23.2 (SD± 3.39) years.,

This finding is similar to the mean age obtained in a sample of Ilorin undergraduate student

(23 ± 3.75SD years) by Adelekan (1992), a sample of South African University (22.6 ±

3.2SD) by Karl (1999) and also in a sample of undergraduate students in Ogun state

Western Nigeria. 23.95 SD± 3.0 years (Onofa 2006).The mean age for the males was 23.9

SD± 3.39 years; while that of the female gender was 22.4 SD±2.93 years. The males were much older than the females. This finding is also in tandem with reports from several authors

(Daramola 2004, Tawasu 2005, and Onofa 2006).

The majority of the respondents (74.5%) of the study population professed Christian religion, while 23.5% were Moslems and 2.0% practiced other religions. This differed from the expected pattern, Abuja though is the Federal Capital Territory, is situated in the Northern

96 part of Nigeria, with predominant Moslem population, hence the dominance of Islam was expected. The dominance of Christian religion could be explained by the over 55% of the respondents were from Southern part of Nigeria, where Christianity is a predominant religion.

Also a considerable percentage of students from North central zone are Christians.

More than 50% of the respondents’ parents had tertiary education, and belong to the first 5 groups of International Standard Classification of Occupations (ISCO-88). These findings were different from the one reported by Onofa (2005), where less than 48% of the fathers had tertiary education and about one-third (35%) of the mothers had tertiary education. Despite the down ward trend of economy, level of education still appears to be reliable measure of social class indicator in Nigeria (Okogbenin 2008). Educational level and occupational status of the respondents’ parents in this study seems to reflect the economic status of the respondents, hence it is not surprising that most of the respondents had parents in major 5 occupational groups; Legislators, Managers, Professionals, Technical, Business,

Sales & Services and related workers.

Prevalence rates of study difficulty, psychoactive substance use/abuse, psychiatric morbidity and ‘The Triad’

Prevalence rate of study difficulty: In this study, the prevalence rate of the study difficulty using the consolidated scores of the 8 subscales is 53.8%. The above finding is similar to the incidence rate of 50% among students attending the Student Health Services at

Harvard, Blain and McArthur, (1966).

To arrive at the prevalence rate of study difficulty of 53.8% in this study, 50 percentile was used as a reference point for the cumulative study difficulty scores by each

97 respondent in all the subscales of UCLSQ. The median score for the total (consolidated) score of 63 was chosen as cut off point. The respondents with consolidated scores above the median (63) were categorised as having study difficulty, hence were used as study difficulty component of “The Triad”. However the respondents’ scores on the individual subscales of the study difficulty instrument were comparable with that reported by Fatoye (1998), in a study carried out among senior secondary students in Western Nigeria, but higher than the ones reported among British subjects (Crown et al, 1976). In comparison with the findings reported by Fatoye (1998), the respondents in this study population scored marginally higher in all subscales. These degrees of difference could be due to difference in the level of pressure to achieve. The subjects used in the study, carried out by Fatoye (1998) were senior secondary school students who were day students, while this study focused on senior students in a tertiary institution, with higher level of education and away from home.

Prevalence rate of psychoactive substances use: The prevalence rate of all drugs

(current use) was 46% and this was used as the psychoactive substance use component of

‘The Triad’. The prevalence rate of all drugs (life-time use) 67.7% was significantly higher than the current use. This is similar to 69.9%, reported by Onofa (2006), but lower than 88% and 85% reported by Akinhanmi (1996) respectively in his two phased study. However, the figure in this study was higher than that reported by Ihezue (1988) and Tawasu (2005), 56% and 23.7% among medical students of University of Nigeria, Nsukka and University of

Maiduguri respectively. These differences might be accounted for, by differences in methodology, and criteria used in assessing drug use and contributions of cultural and religious factors.

Prevalence rate of psychiatric morbidity: The prevalence rate of psychiatric morbidity in this study was 35.5%.This finding is similar to that reported by Fatoye (2004.)

In a study ‘Rate, Pattern and Psychosocial Correlates of Emotional Distress among

Undergraduates in a Nigerian University’, he noted that “the rates of anxiety and depression among the study population were 36.4% and 29.7% respectively. However, in another study among senior secondary school students in Western Nigeria, a higher prevalence rate of

50.3% was reported, Fatoye (1998). The differences could have been accounted for by the use of GHO-30 items version in this study and also that the university students have better understanding of the questions resulting from higher level of education.

‘The Triad’

`In the theoretical framework of this study (Figure 1), on page 22, it would be recalled that Area H represent a subgroup of students in whom the following could co-occur; study difficulty, psychoactive substance use/abuse and psychiatric morbidity. This was labelled as

‘The Triad’. And taken into cognisance that the term syndrome, could be defined as a group of symptoms that occur together and that are characteristic of a disease or a group of symptoms that collectively indicate or characterised a disease, a psychological disorder or other abnormal condition.(Medical Dictionary), then “ The Triad “ is in essence, a syndrome.

But since a befitting nomenclature is still to be given to this syndrome, the term “The Triad” will be retained and used.

This study showed that the prevalence rate of the co-occurrence of study difficulty, psychoactive substance use and psychiatric morbidity (‘The Triad’) is 16.7%, (Figure 2) on page 51. This figure is higher than that reported in a previous study by Fatoye in 1998, where the prevalence rates of respondents with The Triad ranged between 4.6%-6.2%. More so, this study focused on senior university students, who are assumed to have a higher exposure to

99 psychoactive substance use/abuse, more stressful academic work, social problems, emotional crises. And higher level of pressure to achieve.

Socio-demographic characteristics of students with ‘The Triad’

This study has shown, that students with ‘The Triad’ were affected by adverse socio- demographic factors, however in some cases, statistically significant differences were not found. This is similar with the study of secondary school student in Ilesha, Western, Nigeria

(Fatoye 1998).

Male gender accounted for 67% of respondents with ‘The Triad.’ This is quite significant taken into cognisance that female gender was only marginally higher in the study population. There is a statistically significant association between male gender and ‘The

Triad’ (P<0.001) The Odds Ratio (OR) =3.9, this implied that male gender had 4 times Odds of having ‘The Triad’ than the female gender. They were also, at a higher risk of developing

‘The Triad’ than the female gender, (Relative risk (RR)>3.1). This dominance of male gender was earlier reported by (Prince 1960) in the study of Brain Fag Syndrome, which had high significant positive correlation with ‘The Triad’ He observed that out of 10 cases seen at

Abeokuta, none was a female. He also noted in another study that none of the cases attending clinics at Abeokuta and Ibadan was a female, Prince (1962). The finding of this study, of less vulnerability by female gender to ‘The Triad’ in this study was also earlier replicated in a study among senior secondary school students in Ilesha, Western Nigeria, Fatoye (1998).

Morakinyo (1980) in a study of subjects with Brain Fag Syndrome observed that out of 20 consecutive referrals with established BFS at University Health Centre of Obafemi Awolowo

University, Ile-Ife, in Western Nigeria, only 1 was a female. The reason for this dominance could be adduced to combinations of several factors namely higher exposures to social, academic stress and psychoactive substance use. The reports of these studies had further lent

100 credence to the findings in this study; that male gender had statistically significant association, with high preponderance of vulnerability to ‘The Triad’ and Brain Fag

Syndrome.

On the relationship between age of respondents and ‘The Triad’, the respondents above the age of 35 years had no Triad. (Table13). This was contrary to the expectation that the more matured respondents were more likely to have ‘The Triad’.

The respondents in 4th year had greater number of students 56 (56%) with ‘The Triad’ than the 3rd year with 44 (44%) students. This finding is in agreement with a study carried out among medical students in Nepal, in which the study found, increasing level of psychological morbidities with increasing number of years in medical school (Chandrasekhar et al, 2007).

Also, in agreement of this finding, is the report from a survey of psychoactive substance use among medical students, in a Nigerian university, in which it was noted that the clinical students had higher prevalence rates of psychoactive substance use, than the preclinical students, (Daramola, 2004).

The association between respondents’ department and ’The Triad’ was

statistically significant (P<0.05). This study observed that department of Foundation

for Arts & Social Science Education, in Faculty of Education. (Table14) had highest

number of respondents (16%) with ‘The Triad’. However, in contrary to the finding

stated above, Onofa, (2006),noted, in related study on drug use in three higher

institutions (University, Polytechnic, and College of Education) in Ogun state, South

West Nigeria, the prevalence rate of drug use was lowest (33.6%) for College of

Education, while the University and the Polytechnic had prevalence rates of 62.6%

and 89.2% respectively. The finding in this study is indicative of a high magnitude of

poor mental health in the future teachers in our educational institutions. It is

imperative for more studies to be carried out among this group of students to ascertain

101

possible reasons for this disparity. However, the study among the three tertiary

institutions focussed only on drug use, while this study focussed on the Triad of study

difficulty psychoactive substance use and psychiatric morbidity.

The association between family status and ‘The Triad’ was statistically significant

(P<0.001). Respondents from polygamous family background accounted for greater number of students with ‘The Triad’ (65%). They had higher degree of association and relative risk of developing ‘TheTriad’ than students from monogamous family background. These findings were earlier corroborated in a study of senior secondary school students, where majority of students with ‘The Triad’ had polygamous family background (Fatoye, 1998). .

This study also observed that association between strained parental relationship and

‘The Triad’ were statistically significant (p< 0.001). This finding differed from previous report in the study of secondary school students (Fatoye 1998) in which no correlation was found between strained parental relationship and’” The Triad’. However, in another study,

“Rate, pattern and psychosocial correlates of emotional distress among undergraduate students in a Nigerian university” (Fatoye 2004), he noted that strained relationship between parents and study difficulty had significant association with anxiety (p< 0.05). He also found a significant association between strained parental relationship, study difficulty and financial difficulty with depression.

Surprisingly, religiosity and financial strains did not show any statistical significant association with ‘The Triad’ (p> 0.05). This was partly in agreement with the previous study by Fatoye (1998) He noted that, religiosity had no statistical significant association with ‘The

Triad’ but differed in the aspect of financial strain, in which he reported statistically significant correlation. Singh et al, (1991) and Adelekan, (1987) in their studies found a negative correlation between drug use and religiosity. The difference could have been due to the fact that they focused on only one component of ‘The Triad’, psychoactive substance use.

102

Specific Psychoactive substances associated with study difficulty and Psychiatric morbidity

Study difficulty

The findings in this study indicate that all psychoactive substances are associated with study difficulty in varied degrees. As was shown in Table 18 (page 65), cocaine had highest degree of association, which is statistically significant, (P<0,001) followed by tobacco, cannabis, alcohol and other stimulants (kola nuts, coffee and amphetamine). The findings in this study were similar to that reported by Fatoye (1998) concerning the positive association between stimulants (coffee and kola nuts) and study difficulty. Although in his study, the subscales of UCLSQ were compared with individual psychoactive substances separately, while in this study, the comparison was between psychoactive substances and the consolidated study difficulty. However, in contrast to his finding that stimulants use had the strongest association with study difficulty, as stated above, this finding was not replicated in this study. The reasons for the dissimilarities in both studies could have arisen, from different methods used in assessing study difficulty, or due to possible changes in the pattern of use of psychoactive substances over the years.

As previously stated the positive association of stimulants with study difficulty lent credence to the psychophysiological theory of Brain Fag Syndrome. This study also did not find any causal relationship, however, a direct relationship was proposed between sleep deprivations caused by stimulants use, which consequently results in study difficulty in subjects with the BFS (Morakinyo 1990).

Psychiatric morbidity

The findings in this study showed that the following psychoactive substances; tobacco, cannabis, stimulants and alcohol, had high degree of associations with psychiatric

103 morbidity (p<0.001). (See Table 18 for more details). These findings are not totally different from that reported by Fatoye (1998), in which he found stimulants use (coffee and kola nuts) with strongest association with psychopathology (psychiatric morbidity). This is not the case in this study; nevertheless Stimulants use had a very strong association with psychiatric morbidity (p<0.001. Previous studies had found a strong association between psychoactive substance use, specifically stimulants use and Brain Fag Syndrome which is a form of psychiatric morbidity.

The findings in this study that stimulants use has strong statistically significant associations with study difficulty and psychiatric morbidity (p<0.001), lent credence to

Morakinyo’s psycho-physiological theory. The theory states in essence that; difficulty in study drive students to stimulants use, so as to study for longer periods. This leads to sleep deprivation which causes Brain Fag Syndrome, which, in turn is associated with study difficulty; hence a vicious cycle is established. (Fatoye1998).

Specific aspects of study difficulty associated with psychoactive substance use and psychiatric morbidity

The following specific aspects of study difficulty were found to have statistically significant association (p<0.001) with both psychoactive substance use and psychiatric morbidity; Primary and Secondary types of study difficulty, Anxiety, Obsessionality,

Depression, Disorganised/Distractible, Somatic and Sylbism subscales of UCLSQ as shown in page 67 (Table 19). These findings differed from observations made in the study among secondary school students, in which no significant difference was found when comparisons were made between subscales of UCLSQ and Tobacco (current use). However, significant associations between Psychopathology and Anxiety, Obsessionality,

Disorganised/Distractible, Low motivation, Work satisfaction and Sylbism were reported.

104

The disparity in these studies could have arisen from different methods applied in assessments of relationships among the variables, difference in pressure of work, and that the previous study was among adolescents while this study is among university students.

Using correlation coefficient, this study found that the consolidated study difficulty is positively correlated to General Health Questionnaire scores, (Psychiatric morbidity) Brain

Fag Syndrome scores, and with all the eight (8) subscales of the UCLSQ. This had given credence to the use of consolidated study difficulty as a component of ‘The Triad’. General

Health Questionnaire (GHQ) scores and Brain Fag Syndrome scores also had high significant positive correlation with subscales of UCLSQ except for work satisfaction. Work satisfaction had statistically significant positive correlation with consolidated study difficulty, Anxiety,

Obsessionality and Sylbism but correlation with GHQ scores, BFS scores, Depression,

Disorganised/Distractible, Low motivation and Somatic subscales of UCLSQ, were not statistically significant (p>0.05). These findings differed from that reported by Fatoye (1998) that General Health Questionnaire scores correlated negatively with Work satistifaction,

Obsessionality and Sylbism subscales of UCLSQ, in contrast to the above report, in this study

Obsessionality and Sylbism had positive correlation with GHQ scores and BFS scores.

As noted above, there is a significant positive inter correlation between the UCLSQ subscales. These findings are not significantly different from those reported by Crown et al,

(1973) Lucas et al, (1976) and Fatoye (1998). Some of these studies also reported that Work satisfaction had a predominantly negative relationship with other subscales. In a study by

Crown et al., (1973) Work satisfaction was negatively correlated to Anxiety, Obsessionality,

Depression, Disorganised/Distractible, Low motivation and Somatic while Lucas et al, (1976) reported negative relationship between Work satisfaction and Anxiety,

Disorganised/Distractible, Low motivation, Somatic and Sylbism subscales. The findings in this study as noted above differed from the reports of studies by Crown et al (1973) and

105

Lucas (1976) but are in total agreement with that reported by Fatoye (1998). He noted that

Work satisfaction had no negative correlation with other subscales of UCLSQ, but showed consistent lowest positive correlations. He however, noted that it had positive correlations with Anxiety, Obsessionality, Depression and Sylbism.

The General Health Questionnaire scores had statistically significant positive correlations (p <0.001) with the Brain Fag Syndrome scores, consolidated study difficulty and all the scores of eight (8) subscales of UCLSQ. (See Table 25 for details).

General Health Questionnaire is a screening instrument for psychiatric morbidity

(psychopathology) and as stated above, the scores had high positive statistical significant associations with the Brain Fag Syndrome and study difficulty both of which are psychopathological states which were assessed using Brain Fag Syndrome Scale and

University College London Study Difficulty Questionnaire respectively.

The magnitude of Brain Fag Syndrome among students with ‘The Triad’

The findings in this study had shown that 83% of students with ‘The Triad’ were also found to have Brain Fag Syndrome. There is a very high statistical significant association between B FS and ‘The Triad’ (p<0.001). This is evident by very high Odds ratio (13.47) and Relative risk (8.08). The implications of these findings are that students with Brain Fag

Syndrome had 13.5 times Odds of co-morbidity with ‘The Triad’ and are also 8 times more at risk of having ‘The Triad’ than those who had no Brain Fag Syndrome. ’The Odds Ratio of 1 implies no association, and also that students with Brain Fag Syndrome are not at more risk of developing ‘The Triad’ than those without Brain Fag Syndrome. The prevalence rate of

Brain Fag Syndrome in this study is 36%, while that of ‘The Triad’ is 16.7%. In a dimensional study among adolescents in secondary school students, the findings show that a prevalence rate of 22.9% for Brain Fag Syndrome and that of the Triad ranging between

106

4.6% and 6.2% (Fatoye 1998). The difference in both studies could be due to higher level of academic workload, financial constraints, emotional distress, and greater exposure to psychoactive substances use occasioned by independent life styles in the university and higher pressure to achieve by the undergraduates. .

Fatoye in 1998 noted, that using psychoactive substances (lifetime) could definitely lead to higher rate of ‘The triad’. This observation is corroborated in this study. More so, in cases of Brain Fag Syndrome, it is reported that, those affected usually have stopped use of stimulants after the onset of symptoms of Brain Fag Syndrome (Fatoye 1998).

Furthermore, as noted above psychiatric morbidity (GHQ scores) had high positive statistically significant correlation with Brian Fag Syndrome (BFS scores). This positive relationship was further strengthened by not too different figures recorded by use of two psychopathological screening instruments, which gave prevalence rates of 35.5% (psychiatric morbidity) and 36% (Brain Fag Syndrome). These figures differed from the rate reported by

Fatoye (1998), in which about 50% prevalence rate was recorded for psychopathology and

22.9% for Brain Fag Syndrome among secondary school students, while this study was conducted among university students. The prevalence rate of 35.5% for psychiatric morbidity reported in this study is lower than 42% reported among students with study difficulty and higher than 9% among academically successful male students in Ain Shams University,

Egypt (Okasha et al, 1985). However, it is important to note, that the figure in this study was much closer to the findings in the Egyptian study, since both studies were on university students, but the settings may be quite different.

The prevalence rates of Brain Fag Syndrome (BFS) among subgroups of the cohort

107

With reference to Figure 3, (page 53) the following observations were made in relation to the prevalence rates of Brain Fag Syndrome among the constituents’ components of the total cohort shown.

Students who were negative for study difficulty, psychoactive substance use, and psychiatric morbidity had the least prevalence rate of 4.8% for BFS. While the prevalence rates of BFS among students who had only one of the 3 components of ‘The Triad’ namely study difficulty, psychoactive substance use, or psychiatric morbidity are 13% , :57.9% and

:19.4% respectively. The study also showed that students with dual or co-morbidity had the following prevalence rates for BFS; 82.2% (Co-morbidity of psychoactive substance use and psychiatric morbidity), 22.4% (Co-morbidity of study difficulty and psychoactive substance use), and: 65% (Co-morbidity of study difficulty and psychiatric morbidity).The highest prevalence rate of 83% was observed among students who had co-occurrence of study difficulty, psychoactive substance use and psychiatric morbidity. Another significant finding is the observation that groups of students with psychiatric morbidity (Areas; C, E, G & H) had significant high prevalence rates for BFS.

These findings have further confirmed the interrelationships of the three components of “The Triad”, and psychiatric morbidity with Brain Fag Syndrome. .

Psychoactive substances commonly abused by students with Brain Fag Syndrome (BFS)

The findings in this study showed that alcohol, tobacco, stimulants and cannabis were commonly used psychoactive substances, by students with BFS, (P<0 .001.). Fatoye (1998) reported that Stimulants were the most commonly abused psychoactive substances by students with Brain Fag Syndrome. He noted that, the finding further reinforced the psycho physiological theory of Brain Fag syndrome (BFS) (Morakinyo 1980). However, in this

108 study, stimulants is third among the four most commonly used psychoactive substances. (See

Table 19 on page 67 for details.

Types of study difficulty commonly associated with Brain Fag Syndrome

The positive inter-relationships among study difficulty, psychiatric morbidity and

Brain Fag Syndrome noted in this study is strengthened, as this study went further, to show that Brain Fag Syndrome is most commonly associated with secondary (type B) of study difficulty, which main characteristic is its’ association with psychiatric illness, using

Morakinyo’s classification of study difficulty, (Table 24). This aspect of study has not been carried out locally; hence comparison with other local findings is impossible.

109

CHAPTER SEVEN

CONCLUSION

The findings in this study have shown that use of psychoactive substances is quite common among the senior students of University of Abuja. The most commonly used psychoactive substance is Alcohol, followed by Stimulants, Tobacco, Cannabis and Inhalants, while

Hypnosedatives, Cocaine, Other opiates, Hallucinogens, Sedatives and Opium/Heroin were used in lesser degrees.

The prevalence rate of 16.7% was observed for the syndrome of co-occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity (“The Triad”). It also observed that prevalence rates of psychiatric morbidity and Brain Fag Syndrome were

35.5% and 36.0% respectively, while that of consolidated study difficulty was 53.8%.

The following socio-demographic variables were found to have statistically significant associations with “The triad”, namely: male gender, age group, respondents’ level of education, family status and strained parental relationships.

Brain Fag Syndrome had statistically significant correlation with consolidated study difficulty, psychiatric morbidity and all the 8 subscales of UCLSQ except Work Satisfaction.

This study also found that students with Brain Fag Syndrome most commonly use stimulants

(coffee and kola nuts), alcohol, tobacco and cannabis. The commonest type of study difficulty associated with Brain Fag Syndrome is the Secondary (Type B) associated with psychiatric disorders. (Morakinyo’s classifications of study difficulty)

110

Implications of these findings

This study shows that the prevalence of co-occurrence of study difficulty, psychoactive substance use, and psychiatric morbidity among university students is 16.7%.

This is indicative of the magnitude of mental health problems in our tertiary institutions. The adverse effects of "The Triad” on the mental health of these students will impact negatively on the society with it’s social and economic consequences.

Recommendations

1. More collaborative studies of higher magnitude than this study should be carried out

in the 6 geopolitical zones of this country. This would help to bring to forefront the

wide spread and magnitude of this syndrome “The Triad”.

2. Students Mental Health services which are non existence in most, if not all our

educational institutions should as a matter of urgency be established in all educational

institutions.

3. In addition, a multi-institutional approach should be employed by Drug Law

Enforcement Agencies, Drug Use related Non Governmental Organisations,

Authorities of Educational Institutions, Mental Health Specialities and Mental Health

Institutions in fighting this three pronged menace (syndrome) “The Triad” using

preventive strategies. These should include counselling and educating students on

the need to:

1. Plan their academic work, so to avoid last minute rush, which predisposes them to use

of stimulants to meet up with lost time.

2. Imbibe good study habit in and out of school.

3. Know the consequences of using stimulants and other psychoactive substances.

111

4. Seek advice and help from mental health service providers

Limitations of the study

(a). This study is the first of its kind among University students, with a sample size of 624 respondents, using a larger, sample size would have yielded higher figures for better comparison. Use of a large sample size was not possible due to constrain of finance, time and human resources.

(B) The instruments used were many, hence some students, could have found the questions too many with high possibility of fatigue setting in; however, this was mitigated by light refreshments provided for respondents half-way into the exercise.

(c). Extensive analysis of each drugs and variables in drug instrument was not feasible due to time, material and financial constrains.

(D) The limited resources at the disposal of the author, led to the inability to assess mental disorders separately hence all were grouped under psychiatric morbidity (psychological disorders).

REFERENCES

112

Abiodun O.A, M.L. Adelekan, O.O Ogunremi, and G.A. Oni, (1994) Pattern of substance use amongst secondary school students in Ilorin, Northern Nigeria. West African Journal of Medicine Vol. 13, No2, 91-97.

Abiodun et al, (1994b) Psychosocial correlates of alcohol, tobacco and cannabis in Ilorin, Nigeria, West Africa Journal of Medicine 13(4); 213-217.

Adamson T.A (1991) Initial Data on Clinical and Social complications of Drug Abuse (Book on Substances). Venue: Paper presented at Aro National workshop on Drug Abuse.

Adamson T. A & Sijuwola O.A, (2001). Ilewo Onile, Nigeria. ‘Epidemiological study psychiatric morbidity in a rural community’ using the (GHQ 12) Nigerian Journal of Psychiatry. Vol. I No5, 313-321.

Adamson T. A, (2002), Alcohols and Drug Abuse. Text of Lecture: National Postgraduate Medical College of Nigeria.

Adelekan M.L (1989). Self- reported drug use among secondary school students in the Nigerian state of Ogun. Bulletin on Narcotics 41; 109-116.

7. Adelekan M.L, Abiodun O.A, Oni G. A, Ogunremi O.O. (1992): Prevalence and pattern of substance use among undergraduates students in a Nigerian University. Drug A/C dependence 29.255-261

8. Adelekan M. L, Abiodun O A, Obayan A I, Oni G A & Ogunremi O .O, (1993); Psychosocial correlates of alcohol, tobacco and cannabis use findings from a Nigerian University. Drug and Alcohol Dependence 33 (3) 247-256.

Adelekan M L and Ndom R.J.E, (1996) Trend in prevalence and pattern of substance use among secondary school students in Ilorin, Nigeria. West African Journal of Med. 16 157-164.

113

Araoye M.O, Research Methodology with Statistics for Health and Social Sciences 1st Edition 2003 pp. 115 – 126.

Awaritefe, A and Ebie, J.C (1975) on the strategy for prevention of drug abuse; African Journal of psychiatry 130-144.

Asuni T, (1964) Socio-psychiatric problems of cannabis in Nigeria, U.N Bulletin on Narcotics, 16, No. 2, 17.

Asuni T, and Pela O A, (1986) Drug Use in Africa Bulletin on Narcotics 38(1-2)55- 64.

Blaine G.B and McArthur C.C, (1966) The Delineation and Measurement of Study Difficulty in University Student: New York, Double Pay & Co. 83, 84 & 104.

Breslau N. (1995), Psychiatric co morbidity of Smoking and Nicotine dependence, Behaviour Genetics, Vol 25, No 2, pp 96-101.

Bridget M be wick, (2008) Changes in undergraduate students’ consumption of alcohol, as they go through university. B M C Public Health; Research Article pp 1-8.

. Brown W F and Hotzman WH, (1955); ‘Survey of Study Habits and Attitudes’. New York. The psychological corporation

Chandrasekhar T. et al, (2007) Psychological morbidities, sources of stress, and coping strategies among undergraduate medical students in Nepal; B M C Public Health Crown S. Lucas C.J and Supramanuim, S (1973), The Delineation and Measurement of study difficult in University students British. J. Psychiatry; 122: 381-393.

Daramola T.O, (2004) Dissertation: Psychoactive Substance Use among Medical Students of University of Ilorin. A Dissertation for the National Postgraduate Medical College of Nigeria, Faculty of Psychiatry (2004)

114

. Daramola T O, Makanjuola A B, and Obembe O O, (2007). ‘Psychoactive substance use among medical students in a Nigerian university’ Journal of WPA, v 6 (2);

Statistical Manual of Mental Disorders (DSM-IV, APA, 1994)

Ebie, J.C and Pela, O.A, (1982) Some Aspects of Drug Abuse Among Students in Benin-City. Drug and Alcohol Dependence 8:265.

Ebie, J.C (1988) Report of a research project on substance use in some urban and rural areas of Nigeria. International Council on Alcoholism and addictions. Lausanne, Switzerland Nigerian Medical Journal 80, pp 72-75.

El Guebaly N. (1990). Substance Abuse and Mental Disorders: The Dual Diagnosis concept “Canadian Journal of Psychiatry, 35(3) 261-267.

EPI-INFO (1991): Sample size estimation for population survey of descriptive study using random sampling, the statistical package for Epidemiological information version 5. 1b.

Entwistle J N and Entwistle D, (1970) “The relationship between personality, study methods and academic performance” Brit J. Educational psychol, 40:132-141

Fatoye F .O, (1998), Co-occurrence of study difficulty, drug use and psychopathology among secondary school students in Ilesha, Western Nigeria. Dissertation for the National Postgraduate Medical College of Nigeria

Fatoye F.O (2004) ‘Rate, Pattern and Psychosocial Correlates of Emotional Distress among Undergraduates in a Nigerian University’ Nigerian Journal of Health Sciences, 4(1-2(; 21-26. Federal Republic of Nigeria, (1989) Official Gazette, No. 47 Vol, 70 The Federal Government press. Lagos.

115

FMOH, WHO and APN, (2007); Mental Health Advocacy pamphlet: “Mental Health and You”.

Furneaux W.D (1962). “The psychologist and the University” Universities Quarterly 17:35-47

Goldberg. D.P (1972) “The Detection of Psychiatric illness by Questionnaire Maudslay Monograph, 21, Oxford University Press London

Handforth, J.R (1978) Study Difficulty Psychiatric and Psychological Aspects,” Can Psychiatric Association 1. 23(8): 549-556

Ibanga, A.K.J et al (2005). the contexts of alcohol consumption by men and women in Nigeria, In I.S. Obot and R Room (eds.) , Alcohol, gender & drinking problems, perspective from low and middle income countries. Pp 143-166. Geneva WHO

Ihezue U.H (1988), Drug abuse among medical students at a Nigerian University. Part I; Prevalence and Pattern of use The Journal of the National Medical. Association; 80, 81- 6

International Classification of Diseases tenth edition (ICD-10, WHO, 1992) International Standard Classifications of Occupations, International Labour Office Geneva (1988)

Lambo T.A. (1964) Economic and Social Aspects of Drug abuse in Africa confidential report submitted to United Nations.

Lambo T.A (1965): Medical and social problems of drug addictions in West Africa with special emphasis on psychiatric aspects. Bull. Narcotic 17, N0 13

Maj M (2005). Psychiatric morbidity: an artefact of current diagnostic systems? British Journal of Psychiatry, 186, 182- 84

116

Malleson, N.B (1965), A handbook on British Student Health Service, 91, 12 s 6 d, London. Pitman

. Malleson, N.B (1957) “Treatment of pre-examination stress” British Medical Journal, 2. 551-55

Merikangas K. R and Gelernter C.S, (1990). “Co- morbidity of alcoholism and depression in psychiatric clinics in North America” 13 (4), 613-632

Miller G W, (1970). “Success, failure, and wastage in higher education:” London, George Harrup; 111-123.

Morakinyo .O. (1980) Psychophysiological theory of a psychiatric illness (The “Brain Fag’ Syndrome) associated with study among Africans; Journal of Nervous and Mental Disease 168(2):84-89.

Morakinyo O, (1990) “Students mental Health in Africa. Present status and future prospects”, 15th Annual Lecture of the West African College of Physicians, Accra Ghana.

Morakinyo O. (2002). “A Handbook for Students on Mental Health Posting”: 1st Edition. pp 123 – 125.Media ware Ibadan.

Morakinyo O, (1990) “Students mental Health in Africa. Present status and future prospects”, 15th Annual Lecture of the West African College of physicians, Accra Ghana.

Ndom R.J.E and M.L Adelekan (1996) psychosocial correlate of substance use among undergraduates in Ilorin University Nigeria. East African Medical Journal Vol. 73, No 85 August 1996. 541-547

Obot, I.S (1993), Drinking behaviour and Attitudes in Nigeria; the middle belt study; Jos centre for development studies University of Jos Odejide A.O Problems of drug 117

abuse in Nigeria. “A review of the existing literature and suggestions on preventive measures” Nigerian. Medical Journal 1980, 10 5-11.

Odejide A.O, Olatawura M.O and Adetuyibi A. (1980) Preventive aspects of Drug Abuse in Nigeria. Preventive psychiatry: 1, 307-10.00.

Ogunremi O.O and Okonfua F.E “Abuse of drugs among Nigerian Youths” African Journal of Psychiatry, 1977, 107-112.

Okasha A, Kamel M, Lotair A.R, Khali A.H and Bishry Z (1985) “Academic difficulty among male students in Egyptian, University students; and its Association with demographic and psychosocial factors” Brint J. of psychiatry 146; 144-150

50. Ononye, F. and Morakinyo.O (1994) “Drug Abuse, Psychopathology and Juvenile Delinquency in South Western Nigeria” Journal of Forensic Psychiatry, 5(3) 527-537 In a Rural area of Benin City. Drug and Alcohol Dependences

Okogbenin E. (2008) Prevalence and Correlates of Alcohol use/abuse among adolescents secondary school students in Benin City. A Dissertation for West Africa College of Psychiatry, (2008)

Onofa, (2006) “Prevalence and pattern of drug abuse among students of three tertiary institutions in Abeokuta.” A Dissertation for West Africa College of Physicians (2006)

Oshodi O. O, (1986). Drug dependence and addiction: My studies in Kaduna: 1970- 1972, Cannabis and Amphetamines, Nigerian Journal of Psychiatry, 1, 194-203

. Paton S.M and Kandel DB (1978) “Psychological factors and Adolescent illicit Drug use. Ethnicity and Sex differences Adolescence 30 (50), 187-200.

Perfas F “Incidence of Co-occurring Disorders” A Day Top Workshop at Neuropsychiatric Hospital Aro Abeokuta 118

Prince R.H (1960), Brain Fag Syndrome in Nigeria” J. Mental Sci. 106:

Prince R.H (1962) Functional Symptoms associated with study in Nigerian Students” West African Medical Journal; 199-207

Ragler D.A Farmer M.E Rae, D.S, J Locke B Z-, Keith S.J Judd, LL and Goodwin, FK (1990) Co morbidity of Mental Disorder with Alcohol other drug abuse results from Epidemiological Attachment Area (ECA) study JAMH 264 (192517-2528.

Rehm J. Room, R. Monteiroro, M. et al, (2004) Alcohol use. In Ezzati, M Lopez, A. Rodger’s A. Murray. C.J.L, (Eds) comparative quantification of health risks Global and regional burden of Disease attributable to selected major risks factors. Pp 959- 1108; Geneva, WHO SADC Epidemiology Network on Drug use (SENDU), 2004 Research brief 8(1) 3

Ronald C Kessler, Incidence of Mental Illness in USA (Sadock and Sadock, 2007)

World Health Organization (2004a) Global Status Report: Alcohol Policy. Geneva WHO

119

APPENDICES

APPENDIX I

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. Local Government Area______

4. State of origin______

5. Nationality [ ] Nigerian

[ ] Others Specify ______

6. Ethnicity ______

7. Religion [ ] Christianity [ ] Islam [ ] others

120

8. Level ------

9. Department ------

10. Faculty ------

11. No. of years already spent on the university education:______

12. Parental education: a. Father [ ] No formal education [ ] Don’t Know [ ] Primary school education [ ] Secondary school education [ ] Post Secondary Education

b. Mother [ ] No formal education [ ] Don’t know [ ] Primary school education [ ] Secondary school education [ ] Post Secondary education

13. Father’s occupation:______

14. Mother’s occupation______

15. Family set up: [ ] Monogamous

[ ] Polygamous

16. Who do you stay with: [ ] Parent (s) [ ] Guardian [ ] Alone

17. How best can you describe your father?

[ ] Not applicable (my father is dead or not around) [ ] Loving [ ] Too strict [ ] Kind [ ] Wicked [ ] Too permissive

18. How best can you describe your mother?

121

[ ] Not applicable (my mother is dead or not around) [ ] Loving [ ] Too strict [ ] Wicked [ ] Too permissive

19. 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)

20. How many children altogether has your father (Living only)______

21. How many children have your mother (Living only)? ______

22. What is your birth position among your mother’s living children (e.g., 1st, 2nd, last born, etc)? ______

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

24. 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

25. How religious are you? [ ] Very religious (I pray regularly) [ ] Just religious (I pray occasionally) [ ] Not religious (I hardly pray).

122

APPENDIX II

THE GENERAL HEALTH QUESTIONNAIRE (GHQ -30)

PLEASE READ THIS CAREFULLY

We should like to know if you have had any medical complaints, and how your health has been in general, over the past few weeks. Please answer ALL the questions on the following pages simply by underlying the answer which you think most nearly applies to you. Remember that we want to know about present and recent complaints, 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 co-operation.

HAVE YOU RECENTLY:

1. -been able to Better than Same as usual Less than usual Much less concentrate on usual than usual whatever you’re doing? 2 -lost much sleep Not at all No more than Rather more Much more over worry usual than usual than usual 3 -been having restless Not all No more than Rather more Much more disturbed nights? usual than usual than usual 4 -been managing to More than Same as usual Rather less Much less keep yourself busy usual than usual than usual and occupied?

123

5 -been getting out of More than Same as usual Rather less Much less the house as much as usual than usual than usual usual? 6 -been managing as Better than About the same Less well than Much less well as most people usual usual well would in your shoes? 7 -felt on the whole Better than About the same Less well than Much less you were doing usual usual well things well? 8 -been satisfied with More satisfied About same as Less satisfied Much less the way you have usual than usual satisfied carried out your task? 9 -been able to feel Better satisfied About same as Less well than Much less warmth and usual usual well affection for those near to you? 10 -been finding it easy Better satisfied About same as Less well than Much less to get on with other usual usual well people? 11 -spent much time More time than About same as Less than usual Much less chatting with usual usual than usual people? 12 -felt that you are More so than Same as usual Less useful Much less playing useful part usual than usual useful in things? 13 -felt capable of More so than Same as usual Less so useful Much less making decisions usual than usual capable about things? 14 -felt constantly Not at all No more than Rather more Much more under strain usual than usual than usual 9tension)? 15 -felt you couldn’t Not at all No more than Rather more Much more overcome your usual than usual than usual difficulties? 16 -been finding life a Not at all No more than Rather more Much less struggle all the time? usual than usual than usual 17 -been able to enjoy More so than Same as usual Less so than Much less your normal day-to- usual usual than usual day activities? 18 -been taking things Not at all No more than Rather more Much more hard? usual than usual than usual

124

21 -found everything Not at all No more than Rather more Much more getting on top of usual than usual than usual you? 22. -been feeling Not at all No more than Rather more Much more

19 -been getting scared Not at all No more than Rather more Much more or panicky (afraid) usual than usual than usual for no good? 20 -been able to face up More so than Same as usual Less able than Much less to your problems? usual usual able

125

unhappy and usual than usual than usual depressed/ 23 -been losing Not at all No more than Rather more Much more confidence in usual than usual than usual yourself? 24 -been thinking of Not at all No more than Rather more Much more yourself as a usual than usual than usual worthless person? 25 -felt that life is Not at all No more than Rather more Much less entirely hopeless? usual than usual than usual 26 -been feeling More so than About same as Less so as Much less hopeful about your usual usual usual than usual own future? 27 -been feeling More so than About same as Less so as Much less reasonably happy, usual usual usual than usual all things considered? 28 -Been feeling Not at all No more than Rather more Much more nervous, strung-up usual than usual than usual all the time? 29 -felt that life isn’t Not at all No more than Rather more Much more worth living? usual than usual than usual 30 -found at times you Not at all Rather more than Much more couldn’t do anything usual than usual because your nerves were too bad (i.e. because you get excited or irritated)?

APPENDIX III

126

The WHO Questionnaire for Student Drug Use Surveys

INSTRUCTIONS

This is not a test, there are not 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? [ ] 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. Are you a male or a female? [ ] A Male [ ] B Female 2. What is your age? [ ] Years 3. How many years of school have you [ ] Years Completed? (Do not count kindergarten) 4. For most of the last 12 months, [ ] I was not a student during most of Were you a student, full-time or part-time last 12 months? [ ] I was a part-time student [ ] I was a full-time student

5. For most of the last 12 months [ ] I have not worked [ ] un paid jobs [ ] have not worked on a paid job 6. During most of the last 12 months

127

[ ] I have worked on a part-time paid job. [ ] I have worked on full-time paid job. 7. For most of the last 12 months, [ ] I have not worked on an unpaid job Have you worked on an unpaid during most of the last 12 months Jobs, full-time or part-time [ ] I have worked on a part-time unpaid job [ ] I have worked on a full-time unpaid job.

128

FOR EVERY QUESTION YOU MUST READ PARTS (a), (b), (c), and (d), AND ANSWER EACH PART 8. (a) Have you ever smoked, chewed, [ ] A No or sniffed any tobacco (such as [ ] B Yes Cigarettes, cigars, pipe tobacco, Chewing tobacco)?

(b) Have you smoked, chewed, or [ ] A No Sniffed a tobacco product in the [ ] B Yes Past 12 months?

(d) How old were you when you first [ ] A Have never smoked, Smoked, chewed, or sniffed a chewed, or sniffed Tobacco product? Tobacco product

[ ] 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

8. (a) Have you ever drunk any [ ] A No Alcoholic beverage (including [ ] B yes Beer, wine, and spirits, Oguro and Ogogoro)? (b) Have you drunk any alcoholic [ ] A No Beverage in the past 12 months? [ ] B Yes

(d) How old were you when you first [ ] A Have never drunk had drink of beer, wine, or alcoholic beverages spirits-more than just a sip? [ ] 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 (9) (a) Have you ever taken any [ ] A No 129

Cannabis (marijuana, pot, [ ] B yes Hashish, grass, bhang, Igbo, Ganja)?

(b) Have you taken any cannabis in [ ] A No the past 12 months? [ ] B Yes

(c) Have you taken any cannabis [ ] A No during the past 30 days? [ ] B Yes, on 1-5 days [ ] C Yes, on 6-19 days [ ] D Yes, on 20 or more days

10. (a) Have you ever taken [ ] A No any cocaine? [ ] B Yes

(b) Have you taken any [ ] A No Cocaine in the past 12 [ ] B Yes months? (c) Have you taken any [ ] A No Cocaine during [ ] B Yes, on 1-5 days (s) the past 30 days? [ ] C Yes, on 6-19 days [ ] D yes, on 20 or more days

(d) How old were you when [ ] A No You first took [ ] B 10 yes old or less. Cocaine? [ ] 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

11. (a) Have you ever taken [ ] A No any amphetamines or [ ] B yes other stimulants (Uppers, Dexa, Reactivan, Ephedrine, Kolanut, Coffee, pep pills, Diet pills) Without a doctor or health worker telling you to do so

(b) Have you taken any [ ] A No

130

Amphetamines or other [ ] B Yes stimulants in the past 12 months without a doctor or health worker telling you to do so?

(c) Have you taken any [ ] A Have never taken Amphetamines or other amphetamines Stimulants in the past 30 days [ ] B Yes, on 1-5 days without a doctor or health [ ] C Yes, on 6-19 days worker telling you to do so? [ ] D yes, on 20 or more days

(d) How old were you when you [ ] A Have never taken first took an amphetamine or amphetamines Other stimulants without a [ ] B 10 years old or less. Doctor or health worker telling [ ] 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

(e) if you have ever taken amphetamines or Other stimulants, write in the name of the one you have taken most recently. e.g., Coffee, Kolanut. Dexa, Ephedrine______

12. (a) Have you ever taken [ ] A No any hallucinogens [ ] B Yes (LSD, Mescaline Peyote, Psilocybin, PCP)? (b) Have you taken any [ ] A No hallucinogens in the past [ ] B Yes 12 months? (c) Have you taken any [ ] A No Hallucinogens in the past 30 [ ] B Yes, on 1-5 days (s) days? [ ] C Yes, on 6-19 days [ ] D Yes, on 20 or more days

(d) How old were you when you [ ] A No

131 first took a hallucinogen? Hallucinogens [ ] 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 (e) If you have ever taken Hallucinogens, write in the Name of the one you took most Recently ______

13 (a) Have you ever Sniffed or [ ] A No inhaled things (such as glue, [ ] B Yes Aerosol sprays, or other gases0 to get high (do not include smoke)? (b) Have you sniffed or inhaled [ ] A No things to get high during the [ ] B Yes past 12 months (c) Have you sniffed or inhaled [ ] A No things to get high during the [ ] B Yes, on 1-5 days (s) past 30 days/ [ ] C Yes, on 6-19 days [ ] D Yes, on 20 or more days

(d) How old were you when [ ] A Have never sniffed or first sniffed or inhaled inhaled anything to get something to get high high

[ ] 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

(e) If you have ever sniffed or Inhaled things, write in the Name of the thing you have Sniffed or inhaled most recently ______

132

14. (a) Have you ever taken any [ ] A No Hypnosedatives (Librium, Valium, [ ] B Yes Mogadon, Miltown) without a doctor or health worker telling you to do so, i.e. sleeping drugs?

(b) Have you taken any [ ] A No Hypnosedatives in the past 12 [ ] B Yes months without a doctor or health worker telling you to do so?

(c) Have you taken any [ ] A No Hypnosedatives in the past 30 [ ] B Yes, on 1-5 days (s) days without a doctor or health [ ] C Yes, on 6-19 days worker telling you to do so? [ ] D Yes, on 20 or more days

(d) How old were you when you [ ] A Have never taken first took a Hypnosedatives without hypnosedatives a doctor or health worker [ ] 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 (e) If you have ever taken Hypnosedatives write in the name Of the one you have taken most Recently ______

15. (a) Have you ever taken any [ ] A No (Barbiturates, [ ] B yes Phenobarbital, Downers, Goof- Balls, seconal) without a doctor Or health worker telling you to Do so? (b) Have you taken any barbiturates in [ ] A No the past 12 months without a [ ] B Yes doctor or health worker telling you to do so? (c) Have you taken any barbiturates in [ ] A No

133 the past 30 days without a [ ] B Yes, on 1-5 days(s) Doctor or health worker telling [ ] C Yes, on 6-19 days you to do so? [ ] D Yes, on 20 or more days

(d) How old were you when you [ ] A Have never taken barbiturates first took a barbiturates without a Doctor or health worker telling [ ] 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 (e) If you have ever Sedatives, write in the name of the one you have taken most recently ______

16 (a) Have you ever smoked or eaten [ ] A No any opium without a doctor or [ ] B Yes Health worker telling you to do so?

(b) Have you smoked or eaten any [ ] A Yes Opium in the past 12 months [ ] B Yes without a doctor or health

(c) Have you smoked or eaten any [ ] A No Opium in the past 30 days [ ] B Yes, on 1-5 day(s) without a doctor or health [ ] C Yes, on 6-19 days worker telling you to do so? [ ] D Yes, on 20 or more days

(d) How old were you when you [ ] A Have never smoked or first smoked or ate opium eaten opium. Without a doctor or health [ ] B 10 years old or less worker telling you to do so? [ ] 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

17 (a) Have you ever taken any heroin [ ] A No

134

(Horse, Smack, H) [ ] B Yes

(b) Have taken any heroin in [ ] A No the past 12 months? [ ] B Yes

(c) Have you any heroin in [ ] A No the past 30 days? [ ] 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 [ ] A Have never taken heroin first took heroin? [ ] 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

19. (a) Are there any other drugs not [ ] A No mentioned that you have taken [ ] B Yes in the past year without a Doctor or health worker telling you to do so?

(b) If yes, write in the name of the ……………………………………… drug or drugs here

20. (a) Do you know of any other drugs [ ] A No that people are now taking to [ ] B Yes make them feel good or intoxicated? (b) If yes, write in the name of the ______drug or drugs here ______21. If you had ever taken cannabis [ ] A No (Indian hemp): would you have [ ] B Not sure admitted it in this questionnaire? [ ] C Yes

22. If you had ever used alcohol, [ ] A No would you have admitted it in this [ ] B Not sure

135 questionnaire? [ ] C Yes

23. (a) Have you taken any pain killing [ ] A No drug like Panadol, Daga, Induced [ ] B Yes Phensic or Antibiotic, like Ampicillin, Tetracycline, etc Recently, without a doctor or Health worker telling you to do So? (b) If yes, write down the name of the drug ______

APPENDIX IV

136

The University College London Study Questionnaire (UCLSQ)

Below is a list of feelings or reactions which students sometimes experience in relation of study. Please indicate how you yourself stand in respect of each item placing a tick in the appropriate column. Work quickly and remember to answer each question.

Mainly Neither Mainly True no False False 1. I can’t stop thinking about work event when trying to relax ………. ……….. ……… 2 I go over work again and again even when I know it ………. ……….. ……… 3 When I start a piece of work I feel inadequate and incapable of doing it. ………. ……….. ……… 4 I keep losing the trend of things ………. ……….. ……… 5 I just can’t get down to working as much as I should do. ………. ……….. ……… 6 Thinking about work can make me feel physically ill. ………. ……….. ……… 7 I enjoy tackling a difficult topic or problem. ………. ……….. ……… 8 I prefer to concentrate on set work rather than following my own ideas. ………. ……….. ……… 9 I always feel I have to hurry through work tasks. ………. ……….. ……… 10 I can’t bear to hand in an untidy piece of work ………. ……….. ……… 11 My tutors over-estimate my abilities ………. ……….. ……… 12 I keep changing from one topic to another ………. ……….. ……… 13 I am quickly bored ………. ……….. ……… 14 I often get headaches when trying to study ………. ……….. ……… 15 Some aspects of my courses are really exciting. ………. ……….. ………

137

16 I cover assigned work equally well whether it interests me or not. ………. ……….. ……… 17 Sometimes when studying I get downright panicky. ………. ……….. ……… 18 I spend too much time on unimportant detail. ………. ……….. ……… 19 I often can’t be bothered to respond to questions even when I know the ………. ……….. ……… answer 20 I often can’t be bothered to respond to questions even when I know the ………. ……….. ……… answer. 21 I am always behind in my work. ………. ……….. ……… 22 I often can’t get to sleep for thinking about work ………. ……….. ……… 23 I often study purely for pleasure ………. ……….. ……… 24 I prefer to restrict myself to recommended reading. ………. ……….. ……… 25 I feel guilty unless I am working ………. ……….. ……… 26 I rarely complete any work to my satisfaction ………. ……….. ……… 27 If I get good marks I feel a fraud. (If I get good marks I feel as if I have ………. ……….. ……… cheated). 28 I get excited about a topic but soon lose interest ………. ……….. ……… 29 When working, I continually break off, to smoke, drink coffee, walk about or ………. ……….. ……… talk to someone. 30 My hand get stiff and clumsy so that I can’t write properly ………. ……….. ……… 31 I enjoy discussing work topics with others ………. ……….. ……… 32 I consider the best way of learning is my completing the set work and doing ………. ……….. ……… the required reading 33 I get anxious when I hear others talking about work. ………. ……….. ……… 34 I am always planning out work

138

schedules ………. ……….. ……… 35 I feel I ought not to be taking up a place in college. ………. ……….. ……… 36 I am always mislaying my notes or textbooks. ………. ……….. ……… 37 I don’t worry enough about work ………. ……….. ……… 38 I am frequently distracted by aches and pains. ………. ……….. ……… 39 I look forward to lectures or classes. ………. ……….. ……… 40 I find a systematic presentation of a topic more useful than discussion ………. ……….. ……… 41 As soon as I start one task, I feel I should be doing something else. ………. ……….. ……… 42 I like to do things thoroughly or not at all ………. ……….. ……… 43 My thinking about work matters seems very slow ………. ……….. ……… 44 My notes get into a muddle. (My notes get disorganised) ………. ……….. ……… 45 I keep wanting to sleep all the time ………. ……….. ……… 46 I am often handicapped by sheer physical tiredness ………. ……….. ……… 47 I like reading around my subject ………. ……….. ……… 48 I find it difficult to tackle something unless I know just what is expected. ………. ……….. ……… 49 When I try to revise my work, my mind goes blank. ………. ……….. ……… 50 I spend a lot of time on making preparation to work. ………. ……….. ……… 51 I am often too depressed to concentrate properly on my work ………. ……….. ……… 52 I forget to go to lectures or tutorials ………. ……….. ……… 53 I read automatically without taking thins ………. ……….. ……… 54 I get a feeling of nausea and sickness when there is a lot to do ………. ……….. ……… 55 I would like to continue post-

139

secondary ………. ……….. ……… 56 I don’t let myself get diverted onto something that is not strictly relevant ………. ……….. ……… to the course 57 I am afraid of panicking in exams ………. ……….. ……… 58 I find it difficult to decide which parts of my work are the most important ………. ……….. ……… 59 I often feel that others know more ………. ……….. ……… 60 I keep getting out books but never really read them. ………. ……….. ……… 61 I often think another subject would be more interesting. ………. ……….. ……… 62 I suffer from eye strain when working ………. ……….. ……… 63 I believe in knowledge for its own sake ………. ……….. ……… 64 It isn’t often I try to think of doing something different from the way ………. ……….. ……… described in lecture or book. 65 When I am asked a question about work, I ‘seize up’ (or become stuck or ………. ……….. ……… blank) 66 I force myself to work, even if I don’t feel like it ………. ……….. ……… 67 I fear exam will expose all my weakness. ………. ……….. ……… 68 I work in fits and starts. (I work irregularly, in short periods from time ………. ……….. ……… to time). 69 I seem to have no real drive to work ………. ……….. ……… 70 I never seem to be able to get comfortable when trying to study ………. ……….. ……… 71 My interest in my subject grows continuously ………. ……….. ……… 72 I like to feel everything important is contained in my notes. ………. ……….. ………

140

141

APPENDIX V

THE ‘BRAIN FAG’ SYNDROME SCALE (BFSS)

The following are some complaints that students sometimes have when they study. Please tick the answer that best applies to you

1. I get period of complete exhaustion and fatigue 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 ______

142

4. I experience brain burning, crawling heat or cold or other unpleasant sensations in my head while studying: 1. Often ______

2. Sometimes ______

3. Never ______

IF ANSWER IS NEVER, GO TO QUESTION 6

5. These Unpleasant sensations (burning, crawling, heat, could make it difficult for me to study or assimilate what I read; 1. Often ______

2. Sometimes ______

3. Never ______

6. I am satisfied with my general efficiency in studying and with retention (assimilation) of what I study: 1. Often ______

2. Sometimes ______

3. Never ______

7. I suffer unpleasant sensations in my body related to study: 1. Often ______

2. Sometimes ______

3. Never ______

143

APPENDIX VI

International Standard Classification of Occupations (ICSO-88)

Major, Sub major, Minor and Unit group title:

Major Group 1: Legislators, senior officials and Managers:

11. Legislators, senior officials and Managers.

111. Legislators.

112. Senior government officials.

113 Traditional Chiefs and Heads of Villages

114. Senior officials of Special-Interest Organisations

12. Corporate Managers.

121. Directors & Chief Executives.

122. Production and Operations Department Managers.

13. General Managers.

131. General

Major Group 2: Professionals:

21. Physical mathematical & engineering professionals

212. Mathematicians, statisticians and related professionals

213. Computing Professionals

144

214. Architect, Engineers and Related Professionals

22. Life Science and Health Professionals

221. Life Science Professionals

222. Health Professionals (except nursing)

223. Nursing & Midwifery Professionals

Major Group 3: Technicians and Associate Professionals

31. Physical and Engineer & Science Associate Professionals

311. Physical & Engineering& Science Technicians

312. Computer Associate Professionals

313. Optical & Electronic Equipment Operators

314. Ship & Aircraft Controller and Technicians

315. Safety & Quality inspectors.

32. Life Science & Health associate Professionals

321. Life Science and Health Associate Professionals

322. Modern Health and Associate Professionals except Nursing

323. Nursing & Midwifery Associate Professionals

324. Traditional Medicine Practioners & Faith Healers

33. Teaching associate Professionals

331. Primary Education Teaching Associate Professionals

332. Pre-Primary Education Associate Professionals

333. Special Education Teaching Associate Professionals

145

334. Other Teaching Associate Professionals

34. Other Associate Professionals

341. Finance and Sales Associate Professionals

342. Business, Service Agents and Trade Brokers

343. Administrative Associate Professionals

344. Customs, Tax and Related Government Associate Professionals

345. Police Inspectors and Detections

346. Social work, Associate Professionals

347. Artistic, Entertainment & sports Associate Professionals

Major group 4: Clerks:

41. Office Clerks

411. Secretaries and Keyboard-operating Clerks

412. Numerical Clerks

413. Material-recording and Transport Clerks

414. Library, Mail and Related Clerks

419. Other Office Clerks

42. Customer Service Clerks

421. Cashiers, Tellers and Related Clerks.

422. Client Information Clerks

Major Group 5: Service Worker & Shop & Market Sales Workers:

51. Period and Protective Service Workers

511. Travel Attendants and Related Workers

146

512. Housekeeping and Restaurant Service Workers

513. Personal Care and Related Workers

514. Other Personal Service Workers

515. Astrologist, Fortune Teller & Related Workers.

52. Models, Sales Persons & Demonstration

521. Fashion and other Models

522. Shop Sales persons and Demonstrations

523. Stall and Market Sales person.

Group 6: Skilled Agriculture & Fishery Workers:

61. Market-Oriented Skilled Agricultural and Fishery workers

611. Market-Gardener and Crop Growers.

612. Market-Oriented Crop & Animal Products & Related Workers

613. Market-Oriented Crop & Animal Producers

614. Forestry & Related Workers

615. Fishery Workers, Hunters and Trappers.

62. Substance Agricultures and Fishery Workers

621. Subsistence Agricultural & Fishery Workers

Major Group 7: Craft and Related Trades Workers:

71. Extracting and Building Trade workers.

711. Miners, Short fires, Store Cutters and Carvers.

712. Building frame and Related Trade Workers

713. Building Fisheries and Related Trade Workers

147

714. Printers, Building Structure Cleaners and Related Trades Workers

72. Metal, Machinery and Related Trades Workers

721. Metal Moulders, Welders, Sheet metal Workers, Structural preparer and Related

Trades Workers.

722. Blacksmiths, Toolmakers, & Related Trade Workers

723. Machinery mechanics and Filters

724. Electrical and Electronic Equipment Mechanics and Filters

73. Precision, Handcraft, Printing & Related Trades Works

731. Precision worker in metal and Related Materials

732. Potters, Glass workers and Related Trade Workers

733. Handicraft workers in Wood, Textile, Leather and Related Materials

734. Printing card related Trade workers

74. Other Craft and Related Trades Workers

741. Food processing and Related Trades Workers

742. Wood trader, Cabinetmakers and Related Traders Workers

743. Textile, Garment and Related Trades Workers

744. Pelt, leather and Shoe making trades workers

Major Group 8: Plant and Machine Operators and Assembles:

81. Stationery-plant and related operators

811. Mining and Mineral in processing plant operators

812. Metal-processing plant operators

148

813. Glass, Ceramics and related Plant operators

814. Wood-processing and Paper-making & Plant Operators.

815. Chemical-processing-plant operator

816. Power production and related plant operators.

817. Automated-assembly-line and Industrial robot operators

82. Machine operators and Assemblers

821. Metal and Mineral-product Machine operators

822. Chemical-Product Machine Operators

824. Wood-Products Machine Operators.

825. Printing, binding and Paper-products Machine Operators

826. Textile, fur, and Leather-Products machine operators

827. Assemblers

829. Other Machine operators and Assemblers

83. Drivers and Mobile-Plant operators

831. Locomotive-Engine drivers and related workers

832. Motor Vehicle Drivers

834. Ships, deck crews and related workers.

Major Group 9: Elementary Occupation

91. Sales and Service Elementary Occupations

911. Street Vendors and related Workers.

912. Shoe Cleaning and other street services elementary occupation

913. Domestic and related helpers, Cleaners and Launders.

914. Building, Caretakers, Window and Related cleaners

915. Messenger, Porters, Doorkeepers and related Workers

149

916. Garbage collectors and related labourers

92. Agricultural, Fishery and related labourers

921. Agricultural, fishery and related labourers.

93. Labourers in mining, construction, manufacturing and transport

931. Mining and Construction labourers.

932. Manufacturing, labourers

933. Transport labourers and freight handlers.

Major Group 10: Armed Forces

Armed Forces

ISCO-88 International Standard

Classification of Occupations

International Labour Office, Geneva.

150

APPENDIX VII

RESPONDENT’S INFORMED CONSENT FORM

Co-occurrence of Study Difficulty, Psychoactive substance use/abuse and Psychiatric morbidity among Undergraduate students of University of Abuja

(The following information/statements shall be made known to the subject before consent is signed). I am Dr. Uchendu I.U., a Resident Doctor in Training at Psychiatric Hospital Uselu, Benin City. I am conducting a research on the co-occurrence of study difficulty, psychoactive substance use/abuse and psychiatric morbidity among undergraduate students of the University of Abuja. Participation in this study is voluntary. The study is considered safe and has no known harmful effects. None of the information collected will be released except to the people involved in the study. If anything is written about the study, you will not be identified by name. If you choose to enroll in this study, you will be asked some questions about your personal life.

Consent: I agree to be included in this study. I have been offered a copy of this document.

______Name of Respondents Date Signature Initials only witness or Right thumbprint

151

152