Embed Size (px)
Citation preview
ii
USE OF PATIENT HEALTH QUESTIONNAIRE 2 (PHQ 2) AS A SCREENING TOOL
FOR DEPRESSION AMONG ADULTS ATTENDING THE GENERAL OUT PATIENT
CLINIC OF BHUTH, JOS
BY
DR BULNDI ISAAC GODWIN
A DISSERTATION SUBMITTED TO THE NATIONAL POSTGRADUATE MEDICAL
COLLEGE OF NIGERIA (NPMCN) IN PARTIAL FULFILMENT OF THE
REQUIREMENT FOR THE AWARD OF FELLOWSHIP EXAMINATION OF THE
COLLEGE IN FAMILY MEDICINE. (FMCFM)
NOVEMBER, 2017
iii
DECLARATION
I hereby declare that this work is original. This dissertation has neither been presented to any
College for Fellowship award nor has it been submitted elsewhere for publication.
DR BULNDI, ISAAC GODWIN
DATE
iv
CERTIFICATION
We certify that this project was carried out by Dr Bulndi Isaac Godwin under our supervision
in the Department of Family Medicine, Bingham University Teaching Hospital, Jos, Plateau
State, Nigeria.
DR MUSA DANKYAU (BM.BCh., FWACP)
Consultant, and Trainer.
Department of Family, Bingham University Teaching Hospital, Jos.
DR SHUAIBU ARJ (M.B.B.S., FMCFM, FWACP)
Consultant, and Trainer.
Department of Family, Bingham University Teaching Hospital, Jos.
______________________________________________________________________
DR GEORGE CHIMA (M.B.B.S., FMCFM)
Consultant, Trainer and Head of Department.
Bingham University Teaching Hospital, Jos.
v
DEDICATION
This research work is dedicated to God who made all things possible.
vi
ACKNOWLEDGEMENT
I acknowledge the tireless work and labour of my trainers to make this research a success. Dr
Dankyau and Dr Shuaibu, your painstaking supervision and contribution to this work is beyond
what words could express. I can only say may Almighty God reward your efforts.
My Head of Department and Mentor, Dr George Chima. Your encouragement has been so
helpful. May God Almighty reward you abundantly.
To all the Evangel Family and to my immediate family, I am ever grateful. May God bless you
all.
vii
TABLE OF CONTENTS
TITLE - -- -- -- - - - - - - - - - - - - - i
DECLARATION --- - - - - - - - - - - - - - ii
CERTIFICATION - - - - - - - - - - - - - iii
DEDICATION - - - - - - - - - - - - - - - - - iv
ACKNOWLEDGEMENT - - - - - - - - - - - - - - v
TABLE OF CONTENTS - - - - - - - - - - - - - - vi
LIST OF TABLES - - - - - - - - - - - - - - - - xi
LIST OF FIGURES - - - - - - - - - - - - - - - - - xii
LIST OF ABBREVIATIONS - - - - - - - - - - - - - - - xiii
SUMMARY - - - - - - - - - - - - - - - - - xvi
CHAPTER ONE/INTRODUCTION - - - - - - - - - - - - - - 1
1.1 Background - - - - - - - - - - - - - - - - - - 1
1.2 Statement of problem - - - - - - - - - - - - - - - - 5
1.3 Research question- - - - - - - - - - - - - - - 6
1.4 Hypothesis - - - - - - - - - - - - - - - - - - - - - 6
1.5 Justification - - - - - - - - - - - - - - - - 6
1.6 Aim of the study - - - - - - - - - - - - - - - - 7
1.7 Objectives of the study - - - - - - - - - - - - - - - 7
CHAPTER TWO: LITERATURE REVIEW- - - - - - - - - - 8
viii
2.1 Overview of occurrence of depression - - - - - - - - - - - - 8
2.2 Overview of the burden and impact of depression - - - - - - - 16
2.2 .1 Burden of depression on individuals - - - - - - - - - - - - 16
2.2.2 Burden of depression on families - - - - - - - - - - - - 17
2.2.3 Burden of depression on work, functioning and productivity - - - - - - 18
2.2.4 Burden of depression on the society - - - - - - - - - - - 19
2.3 Factors associated with depression - - - - - - - - - - - 20
2.3.1 Depression and socio-economic status - - - - - - - - - - - 20
2.3.2 Depression and chronic illnesses - - - - - - - - - - - - 21
2.3.3 Depression and marital status - - - - - - - - - - - - - 22
2.3.4 Depression and Ethnicity - - - - - - - - - - - - - 23
2.3.5 Depression and Age - - - - - - - - - - - - - - - 23
2.4 Diagnosis of depression in primary care - - - - - - - - - - - 24
2.4.1 Recognition of depression in primary care- - - - - - - - - - 29
2.4.2 Screening for depression in primary care - - - - - - - - - - - 31
2.4.3 Patient Health Questionnaire 2 (PHQ 2) - - - - - - - - - - 32
2.4.4 Patient Health Questionnaire 9 (PHQ 9) - - - - - - - - - 34
2.4.5 Suitability, usability and historical development of PHQ 2 and PHQ 9 - - - - 36
2.5 Management strategies for depression in primary care - - - - - - - - 37
2.5.1 System based management approach - - - - - - - - - - - 38
ix
2.5.2 Collaborative Care - - - - - - - - - - - - - - - 39
2.5.3 Patient centred care - - - - - - - - - - - - - - -40
2.5.4 Pharmacological management - - - - - - - - - - - - 40
2.5.4.1 Duration of use of antidepressants- - - - - - - - - - - 43
2.5.4.2 Resistant depression - - - - - - - - - - - - - - 44
2.5.5 Electroconvulsive therapy - - - - - - - - - - - - 45
2.6 Depression management outcome in primary care- - - - - - - - - 46
2.7 Prevention of depression in primary care - - - - - - - - - - - 47
2.7.1 Preventive measures categories - - - - - - - - - - - - 47
2.7.2 Universal prevention of depression - - - - - - - - - - - - 48
2.7.3 Selective or targeted preventive of depression - - - - - - - - - 48
2.7.4 Opportunistic screening - - - - - - - - - - - - - - 49
2.8 Lifestyle and nutritional interventions - - - - - - - - - - - - 50
2.8.1 Psychotherapy - - - - - - - - - - - - - - - 50
2.8.2 Minimal contact low intensity psychotherapy- - - - - - - - - 51
CHAPTER THREE: STUDY METHODOLOGY- - - - - - - - - 52
3.1 Study location - - - - - - - - - - - - - 52
3.2 Study area - - - - - - - - - - - - - - - - - - 53
3.3 Study population - - - - - - - - - - - - - - - 53
3.4 Study design - - - - - - - - - - - - - - - - - 54
x
3.5 Sampling size - - - - - - - - - - - - - - - - - 54
3.6 Sampling method - - - - - - - - - - - - - - - -55
3.7 Inclusion criteria - - - - - - - - - - - - - - - - 56
3.8 Exclusion criteria- - - - - - - - - - - - - - - 56
3.9 Study protocol - - - - - - - - - - - - - - - - 56
3.9.1 Pilot study- - - - - - - - - - 56
3.9.2 Study flow - - - - - - - - - 57
3.10 Tools for collection of data - - - - - - - - - - - - 62
3.10.1 PHQ 2 - - - - - - - - - - - - - - - - 63
3.10.2 PHQ 9 - - - - - - - - - - - - - - - - - 63
3.11 Method of data analysis - - - - - - - - - - - - - - 64
3.12 Cost and funding of the research- - - - - - - - - 66
CHAPTER FOUR: RESULTS - - - - - - - - - - - - - 67
4.1 Socio-demographic characteristics of respondents - - - - - - - - 69
4.2 Distribution of depression risk factors among respondents- - - - - - - 71
4.3 Diagnostic outcomes using the PHQ 2 - - - - - - - - - - 72
4.4 Diagnostic outcomes using the PHQ 9 - - - - - - - - - - 73
4.5 Correlates of PHQ 2 characteristics with PHQ 9 - - - - - - - - 74
4.6 Diagnostic characteristics of PHQ 2- - - - - - - - - - - - 75
CHAPTER FIVE: DISCUSSION - - - - - - - - - - - - 79
xi
5.1 Demographic characteristics of respondents- - - - - - - - - 79
5.1.1 Sex distribution of respondents - - - - - - - - - - - 79
5.1.2 Age distribution of respondents- - - - - - - - - - - - 80
5.1.3 Marital status of respondents - - - - - - - - - - - - 80
5.1.4 Educational status of respondents - - - - - - - - - - - 81
5.1.5 Occupational status of respondents- - - - - - - - 82
5.1.6 Income distribution of respondents - - - - - - - - - - - 82
5.1.7 Morbidity distribution of respondents - - - - - - - - - - 83
5.1.8 Occurrence of stressful events in respondents - - - - - - - - - 84
5.2 Characteristics of depression diagnosis by PHQ 2 and PHQ 9 - - - - - - 85
5.2.1 Characteristic of depression diagnosis using PHQ 2- - - - - - - - 85
5.2.2 Characteristic of depression diagnosis using PHQ 9 - - - - - - - - 85
5.2.3 Comparative characteristics of PHQ 2 and PHQ 9- - - - - - - - 87
5.2.4 Performance characteristic outcome of PHQ 2- - - - - - - - - 87
5.3 Strength of the study- - - - - - - - - - - - - - 91
5.4 Conclusion - - - - - - - - - - - - 92
5.5 Limitations of study - - - - - - - - - - - - - - -93
5.6 Relevance of study to Family Medicine - - - - - - - - - -93
5.7 Recommendations - - - - - - - - - - - - - - 94
References - - - - - - - - - - - - - - - - - - - 95
xii
Appendices
Appendix I Ethical Approval
Appendix II Consent form
Appendix III Study Questionnaire
Appendix IV Patient Health Questionnaire 2
Appendix V Patient Health Questionnaire 9
LIST OF TABLES
Table 1: Performance characteristics of PHQ 2 - - - - - - - - - - - 68
Table 2: Socio-demographic characteristics of respondents - - - - - - - 70
Table 3: Depression risk factors among respondents - - - - - - - - - 72
Table 4: Diagnostic outcomes using the Patient Health Questionnaire 2 (PHQ 2) - - - 73
Table 5: Diagnostic outcomes using the Patient Health Questionnaire 9 (PHQ 9) - - - 74
Table 6: Correlation of PHQ 2 diagnostic characteristics to PHQ 9- - - - - - - 75
Table 7: Diagnostic characteristics of PHQ 2 - - - - - - - - - - - 76
xiii
LIST OF FIGURES
Figure 1: Area Under the Curve for PHQ 2 - - - - - - - - - - - - 77
xiv
LIST OF ABBREVIATIONS
ANC Antenatal Care Clinic
AIDS Acquired immune deficiency syndrome
AUC Area under the Curve
BCG Bacille Calmette-Guerin
BDI Becks Depression Index
BHUTH Bingham University Teaching Hospital
BMI Body mass index
BP Blood Pressure
CES-D Centre for Epidemiological Studies Depression Scale
CNS Central nervous system
OC Degree Celsius
CIDI Composite International Diagnostic Interview
DA Diagnostic Accuracy
DALY Disability Adjusted Life Years
DOR Diagnostic Odds Ratio
DPT Diphtheria, pertussis, tetanus
DSM-IV Diagnostic and Statistical Manual of Mental disorders, 4th Edition
ENT Ear, nose and throat
GBD Global Burden of Disease
GDS Geriatric Depression Scale
xv
GHQ- 12 General Health Questionnaire 12
Kg Kilogramme
HADS Hamilton Depression Scale
HIV Human immunodeficiency virus
HSCL-25 Hopkins Symptom Checklist -25
LR+ Positive Likelihood Ratio
LR- Negative Likelihood Ratio
M metres
MINI Mini International Neuropsychiatric Interview
ml Millilitre
mmHg Millimetres of mercury
mmol/L Millimole per litre
NPV Negative Predictive Value
PR Pulse Rate
PHQ 2 Patient Health Questionnaire 2
PHQ 9 Patient Health Questionnaire 9
PLWA People Living With HIV/AIDS
PPV Positive predictive Value
RR Respiratory Rate
SCAN Schedule for Clinical Assessment of Neuropsychiatry
xvi
SCID IV Structured Clinical Interview for DSM-IV Disorders
SRQ-20 Self Reporting Questionnaire 20
YI Youdens Index
YLD Years Lost to Disability
WHO World Health Organization
17
SUMMARY/ABSTRACT
Depression is a common primary care condition world-wide. It affects man’s
functioning physically, socially and economically. Depression incapacitates
productivity and human potentials, thereby compromising the quality of life and
psycho-social well-being of individuals, families and societies. Depression can be
diagnosed and appropriately managed in primary care settings. The Patient Health
Questionnaire 2 is a validated tool which can be used for screening for depression
in primary care.
The aim of this study was to determine the suitability of the Patient Health
Questionnaire 2 (PHQ 2) as a screening tool for depression among adults attending
the general outpatient department of Bingham University Teaching Hospital, Jos.
Through systematic random sampling, 132 respondents were selected from newly
registered outpatients between the months of August and September, 2015.
Consenting respondents were then given the PHQ 9 and PHQ 2 to complete. The
data obtained was entered into SPSS version 20 and analysed.
Most of the respondents were male (56.8%), within the age group of 26-47 years
and majority were married (56.8%). Most of the respondents had at least primary
or secondary education and were artisans or manual workers with average monthly
income of ₦30,000. The prevalence of depression in the subjects was 38.6%.
Factors associated with depression in the respondents include hypertension, and
being victims of natural disaster or sectarian violence. The sensitivity of PHQ 2
was 80.4% and the specificity was 81.5%. The Positive Predictive Value (PPV)
and the Negative Predictive Value (NPV) were 73.2% and 86.8% respectively. The
positive Likelihood Ratio (LR+) was 4.349, negative Likelihood Ratio (LR-)
18
0.2404, Diagnostic odds Ratio 18.04, Diagnostic Accuracy 81.1%, Youndens
Index 0.619, and the Area under the Receiver Operating Curve (AUC) was 0.832.
Depression was a common condition among patients attending GOPD of BHUTH,
with a prevalence of 38.6%. Co-morbid hypertension and being a victim of natural
disasters or sectarian violence were associated with depression. PHQ 2
demonstrated good diagnostic characteristics for the diagnosis of depression in the
GOPD of BHUTH, and could therefore be used in identifying persons with
depression in primary care settings.
19
CHAPTER 1: INTRODUCTION
1.1 BACKGROUND
Depression is a common mental disorder that presents with depressed mood, loss of interest or
pleasure, decreased energy, feelings of guilt or low self-worth, disturbed sleep or appetite, and
poor concentration.1 Depression often presents with recurrent symptoms of anxiety and could
lead to substantial impairment in an individual’s ability to take care of his or her everyday
responsibilities.2 Individuals with depression also suffer a threat to their emotional, social and
psychological wellbeing. In addition such individuals’ interpersonal interactions or
relationship with others often becomes poor.2 Poor interpersonal relationships could lead to
impaired psychosocial functioning.2,3 Consequently, people with depression become
incapacitated.2 At its worst, depression can lead to suicide.1 Worldwide, approximately one
million lives are lost yearly due to suicide, and this translates to 3,000 suicide deaths every day
as a result, while 80% of suicide victims suffer from major depression.1 Depression affects
over 350 million people worldwide.3 The World Health Organization’s (WHO) Global Burden
of Disease Survey estimates that by the year 2020, major depression would be only second to
ischaemic heart disease in terms of disability experienced by sufferers.3 Globally, the demand
to curb or manage the enormous burden of depression is on the rise with increasing unrest and
humanitarian emergencies.3 The needed resources, management or treatment will require
individuals, institutional and societal effort.3
Depression is the third leading cause of mental disorder, and a major contributor to the global
burden of disease.3 Globally, mental disorders affect all countries, societies, individuals of all
ages, women, men, rich and poor; both from urban and rural settings.3 Globally, approximately
20% of all patients seen by primary health care personnel have one or more mental health
disorders.3 One in four families is likely to have one member with behavioral or mental
20
disorder.3 These individuals usually require a structured and systematic multidisciplinary
approach to depression management.
Unipolar depressive disorders place an enormous burden on society and are ranked as the third
leading cause of disease, accounting for 4.3% of the global burden of disease.2 Depression also
causes 4.4% of the total disability-adjusted life years (DALYs) and is the leading cause of years
lost due to disability (YLDs), accounting for 11.9% of the total YLDs.2
Worldwide, various risk factors predispose individuals to the development of depression. Some
people are also more likely to become depressed than others.3 Depression is two to three times
more common in women.3 Poverty, socially disadvantaged individuals and societies, low
educational status, and genetic makeup all predispose to depression.4 Having a family member
with depression makes an individual two to three times more likely to develop depression at
some point in his or her life.3,4 Exposure to violence, being separated or divorced and suffering
from disease conditions increase the risk for depression.3,4 The presence of chronic illnesses
such as hypertension, malignancies, HIV/AIDS, diabetes have been associated with
depression.3,4
Globally, mental health disorders are common in primary care settings, affecting 25% of all
people at some time during their lives.3 The prevalence of depression from studies conducted
in general populations was reported as 10- 15% globally.3 There are variations from 1.0%
(Czech Republic) to 16.9% (US), 8.3% (Canada) 9.0% (Chile) and 10% (South-Africa).4
In Nigeria, a depression prevalence of 50% was reported among patients attending Primary
Health Care facilities in Lagos Island using the General Health Questionnaire (GHQ 12).5 A
similar study using the Zungs Depression Scale conducted at a Family Practice clinic in Ilesha,
Nigeria, also reported depression in 52% of the subjects studied.6 In an assessment of
depression using the Mini International Neuropsychiatric Interview (MINI) amongst
21
University students, a prevalence of 8.3% was reported.7 Another community based study of
depression among the elderly using Geriatric Depression Scale (GDS) reported a prevalence
of 12.1%.8 In a study using the Structured Clinical Interview for DSM-IV Disorders (SCID) at
a general out-patient department of Jos University Teaching Hospital, 25.5% of the patients
were found to be depressed.9
These variations in depression prevalence were not as a result of the instruments used, as none
of the instruments was particularly superior to the other for diagnosis of depression.10 In
addition, all the instruments were validated tools.10 The heterogeneity of reported prevalence
showed a variance mainly due to the population studied. Higher rates of depression were
reported among health facility based studies,5,6,9 with relatively lower prevalence reported from
the community based studies.7,8 This was similar to studies that reported higher depression
prevalences among patients with co-morbidity compared to patients without co-morbidities.
With such rates of depression, the reported rate of recognition has been relatively low in
Nigeria.5-8 A study on detection of mental disorders with the Patient Health Questionnaire in a
primary care setting, reported that only 12% out of 63.1% of patients with mental illness were
recognized by Primary Care Physicians, and 29.1% of these patients with mental illness were
found to be depressed.11 Another researcher, using the Composite International Diagnostic
Interview (CIDI), reported that 98% of psychiatric disorders were not recognized by attending
physicians at the General Hospital Maiduguri.12 Approximately 61.5% of these patients were
depressed.12 Similarly in a study on recognition of mental health problems, doctors identified
only 6.8% of mental disorders using their clinical diagnostic skills, whereas screening with
PHQ 12 identified 46.6% of depressed cases in the same cohort of patients.13 This low case
detection of depressive disorders by primary care doctors has been similarly reported in other
studies and is attributed to poor knowledge of mental health illnesses and weak diagnostic
skills.14
22
The consequences of such misdiagnosis and mismanagement are numerous. For instance
depression negatively impacts growth and development of children, school performance, and
peer or family relationships.3 Depressive disorder is also a leading cause of suicidal behavior
and suicide.3 Depression is the leading cause of disability worldwide in terms of total years
lost due to disability.3 The Medical Outcomes Study, using a self- administered questionnaire,
assessed disability due to depression in domains of physical and social functioning. There was
a strong association between depression and daily function, performance at work and work lost
days (days patient is absent at work).3 This resulted in lost productivity and income with
various degrees of negative impact on the economy, the community, the family and the
individual.3 The hardship and suffering due to depression disrupts the life of the people affected
and their families. It also makes management of chronic diseases such as diabetes and
hypertension difficult.3
The growing burden of depression, its social, economic and medical impact makes early
detection and treatment necessary. Depression is treatable and when diagnosed early, its impact
on quality of life, disability and work performance is effectively prevented.10
SCREENING DEPRESSION WITH TOOLS/INSTRUMENTS
Screening for depression in Primary Care is recommended by the World Health Organization
and the United States Preventive Services Task Force.4 Short, ultra short and lengthy screening
tools are all used and have proven effectiveness in screening for depression.15 The PHQ 2
which ask two simple questions about mood and anhedonia was discovered to be as effective
as the long screening instruments such as the Becks Inventory Questionnaire and the Zungs
Depression Scale.16 These tools are used initially for screening depression and the results
confirmed using a definitive diagnostic tool. This practice enhances the identification and
management of patients with depression in primary care.16
23
1.2 STATEMENT OF PROBLEM
People with depressive illnesses are commonly seen in primary care, but are mostly
misdiagnosed or improperly managed.11 Some may progress to severe depression and even
commit suicide.1 Considering the busy nature of the primary care clinics, short and easily
applied screening tools enhance early recognition and proper management of depression in
primary care.
In the average primary care practice, approximately six cases of depression go unrecognized
each week, globally.3 This worldwide estimate derives from studies that consistently reported
an average of 10% prevalence of depression in primary care patients.3 However the rate of
recognition of depressed patients by Primary Care Physicians is approximately 12% - 35 %.3,10
Mental Health is an integral aspect of Primary Health Care in Nigeria. It is not rare in the
Nigerian setting to find only one doctor in a Primary Care facility, with few other staff. In
addition, some Primary Care Physicians often have inadequate knowledge of mental health
necessitating the use of diagnostic tools such as the PHQ 2 to screen for depression.14
1.3 RESEARCH QUESTION
How suitable is Patient Health Questionnaire 2 for the screening of depression in a primary
care setting?
1.4 HYPOTHESIS
PHQ 2 is as suitable as other standardized diagnostic tools like the PHQ 9 in detection of
depression in primary care settings.16
1.5 JUSTIFICATION OF THE STUDY
In view of the burden of depression in primary care settings, patients with depressive illnesses
can easily be identified and treated using a short, valid and reliable tool that is quick to apply
24
will be indispensable in such settings. Moreover, prompt diagnosis and appropriate
management of depression at primary care level will prevent complications and promote the
quality of life of its sufferers. PHQ 2 has been validated in many different populations.14 Proof
of its effectiveness in the screening of depression in an African primary care practice, would
not only enhance early diagnosis of depression, but its prompt and appropriate management by
treating the depressed patients or referring such patients for appropriate care.
Competency and familiarity with short screening tools that are simple to apply, sensitive,
specific and well validated like the PHQ 2, is expected to increase the rate of recognition of
depression in Primary Care. This in turn will enhance the appropriate management of
depression and reduce its overall burden while promoting the quality of life (QOL) of the
individuals, their families and the society at large.
1.6 AIM OF THE STUDY
This study aimed to determine the suitability of Patient Health Questionnaire 2 (PHQ 2) as a
screening tool for depression among adults attending the general outpatient department of
Bingham University Teaching Hospital, Jos.
1.7 OBJECTIVES OF THE STUDY
i. To determine the proportion of patients diagnosed depressed with PHQ 2 Score
in the GOPD of BHUTH.
ii. To determine the proportion of patients diagnosed depressed with PHQ 9, as
gold standard diagnostic tool.
iii. To compare the results in (i) and (ii) above.
25
CHAPTER 2: LITERATURE REVIE
2.1 overview of occurrence of depression
Worldwide, depression is a common occurrence among outpatients, inpatients and the
community at large.3 According to the World Health Organization (WHO), depression is the
second most prevalent illness-induced disability worldwide.17 The disability caused by
depression affects men and women, adults and young, whites and blacks, poor and rich.18
The people affected by depression experience hopelessness in their life, and it most often
renders them incapable of coping with daily activities.17 The period of time during which
depression renders a patient incapacitated, summed up to one year, is one Disability Adjusted
Life Year (DALY).17 DALY means a healthy year of life lost to disability.17 The aggregate
DALY yields the Years Lost to Disability (YLD).17 The Global Burden of Disease (GBD),
puts depression as the leading cause of DALYs and one of the leading causes of YLD across
all regions and countries of the world.17 The conditions associated with development of
depression which include increasing conflicts, intimate partner violence, child abuse, stressful
events, stroke, diabetes, and Alzheimer’s disease are some of the reported conditions associated
with depression worldwide.17 The individuals socio-economic status, financial constraints,
food insecurity and stressful life events are other factors reported to be associated with
depression.19
26
Depression is a common mental disorder, occurring in all classes of people, sex and age across
all the regions of the world.18 Ferrari et al, in 1990, reported depression as the fourth leading
contributor to the Global Burden of Disease (GBD).17 In GBD 2000, depression became the
third leading contributor to GBD. GBD 2010 also identified depressive disorders as the leading
contributor to the global burden of disease.1 Depression is projected to become the second
largest cause of disability by 2020.17 In addition, depression often occurs with other chronic
diseases and can worsen patients’ health outcomes.18 A co-morbid state of depression worsens
health compared with depression alone, any of the chronic diseases alone, and with any
combination of chronic diseases without depression.20 Without treatment, depression has the
tendency to assume a chronic course, be recurrent, and over time be associated with increasing
disability.20
In Northern Africa, a depression prevalence of 6.3% was found in Egypt’s demographic
survey; the least in that region, while Libya had the highest prevalence of depression in the
Northern African region, with a rate of 9.25%.4,21 Algeria and Tunisia had prevalence rates of
7.34% and 7.07% respectively.4 Morocco had a prevalence rate of 6.85%.22 Conflict in that sub
region, low income and the use of illicit drugs contributed to prevalence of depression in these
countries.4, 22
In an Ethiopian National Health Survey, the prevalence of depression was reported as 9.1% in
contrast to a depression prevalence of 12.0% reported in a rural household study.19,23 This
prevalence was attributed to food insecurity and stressful life of the rural communities.19 In
neighbouring South Sudan, a multistage cross-sectional household survey, reported a
depression prevalence of 50%. The occurrence of depression in the study was attributed to
conflict in the regions.24 A WHO survey in Somalia reported a depression prevalence of 7.69%
among men and a prevalence of 20% in women.25 Insecurity, war, trauma, poverty,
27
unemployment and substance abuse were the factors found to be associated with depression in
the survey.25 A cross-sectional study conducted in general medical facilities in Kenya found
42% of the patients depressed as a result of unemployment, lack of formal education and
poverty that characterized most of the people in the study.26 In a community survey of mental
health disorders in Kenya, however, a much lower depression prevalence of 6.4% was
reported.27 Approximately one-third of the population studied were farmers, unemployed and
casual workers.27
In Uganda, a cross-sectional study of depression in Primary Health Care settings reported a
prevalence of 31.6%.28 and 29.3% in a rural community setting.28,29 and broken families were
some of the identified factors associated with depression.29 Other studies from the Democratic
Republic of Congo reported depression rate of 5.79%, Gabon 7.02%, Congo 6.45% and
Equatorial Guinea 7.05%.4
In a National Household survey of psychiatric disorders in South Africa using the Composite
International Diagnostic Interview (CIDI) questionnaire, a prevalence of 9.8% was reported.30
Low socioeconomic status, female gender and low level of reporting depressive conditions
were responsible for the low prevalence.30 However, higher prevalence rates of 30% and 47%
were reported among People living with HIV/AIDS (PLWHA), and among rural women
attending Antenatal Care Clinic (ANC) respectively.31,32 Poverty, lack of access to treatment
and cultural barriers were the factors reported as responsible for the high depression rate.31, 32
University Students in Botswana were surveyed and a prevalence rate of 47.5% was reported
and attributable to low socio-economic status; while in Lesotho and Swaziland, prevalence
rates of 6.28% and 5.76% were reported.17, 33
28
In the study of burden of diseases and morbidity in Sub-Saharan Africa, the incidence rate of
depression was reported at 15-18% with prevalence rates of 18 – 30%.34 Ghana reported a
depression prevalence of 18.7%, based on a population cross-sectional survey.35 Age, gender,
marital status, education, residential location, region, wealth and self-rated health were
significantly associated with depression in this population.35 Another study in Ghana reported
a prevalence rate of 6.7% among patients 50 years and above.36 Most of those studied were
unemployed and had low socioeconomic status. Similarly, a depression prevalence of 39.2%
was reported in a study among University students in Ghana.37 Lack of social support, heavy
alcohol consumption and traumatic life events were the risk factors for depression identified
among the students.37
In Nigeria, various depression prevalence rates have been reported from different locations and
populations of study. The prevalence rate as high as 52% and as low as 3.3% were reported.6,38
In Lagos, health facility based studies reported a prevalence of 23.7% among Chronic Kidney
Disease (CKD) patients, using a self-administered Zung depression questionnaire.6 Another
study of depression among outpatients of a tertiary health facility, reported a prevalence of
61% using the Structured Clinical Interview for DSM IV disorder (SCID IV).39 In a multistage
community based depression study of all the Yoruba speaking states, a prevalence of 3.3% was
reported using the observer administered World Mental Health, Composite International
Diagnostic Interview (WMH CIDI).38 Among the depressed participants, low socioeconomic
status was reported to be associated with the occurrence of depression, while the culture of
stigmatization of mental illnesses was responsible for low reporting.38
In Ogun state, a depression survey among outpatients in a primary care unit of a tertiary health
facility reported a prevalence of 29.1%.11 Another study of depression among commercial bank
workers in Abeokuta, reported a prevalence of 1.7% using the Self reporting Questionnaire
29
(SRQ-20).40 Long daily working hours, health problems and use of sedative medications were
associated with depression in the study.40
A community based study of depression among urban and rural populations in Oyo State
reported prevalence rates of 7.3% and 4.2% respectively.41 Female gender, adolescent age
group and stressful rural life were among the factors contributing to depression in the study.41
In a similar community-based multistage study of the risk factors of depression among urban
and rural dwellers in Oyo state, a prevalence rate of 18.4% and 28.4% were reported
respectively.42 Unemployment, poor living conditions, physical illness and large family size
were associated risk factors identified.42 Both of these studies utilized the Patient Health
Questionnaire 12 (PHQ 12), which was interviewer-administered.
Among adolescents in a Senior Secondary School in Ife, Osun State, a prevalence of 6.9% was
reported.43 Female gender was significantly associated with depression.43 In a survey of
outpatients of a cardiology unit of a tertiary health facility in Ife, a depression prevalence of
27.5% was reported using the DSM IV.44 Factors contributing to depression in the study
included poverty, unemployment, medical illness and the presence of terminal disease.44
Among women attending the Obstetrics and Gynaecology clinic of a tertiary health institution
in Ife, Osun state, a depression prevalence of 42.9% was reported with women suffering from
infertility having higher psychopathology.45 In another study among women who were victims
of intimate partner violence, a prevalence rate of 15.4% was reported and among patients with
oesophageal stricture, a prevalence rate of 55.6% was reported.46,47 Previous mental illness and
deliberate self-harm were associated with depression in these patients.47
The Schedule for Clinical Assessment of Neuropsychiatry (SCAN), was used, administered by
the observer to assess depression among People Living with HIV/AIDS, (PLWHA), giving a
prevalence of 29.3% in Edo state.48 Female gender and unemployment, were associated with
30
depression while having a child and living with other people was reported as protective in the
study.48 In another study among diabetic outpatients, a depression prevalence of 30% was
reported using the SCAN instrument.49 Poverty, being female and physical comorbidities’ were
associated with depression.49 However, among nurses of a tertiary health facility in Benin, a
prevalence of 50% was reported using the General Health Questionnaire which was a self-
administered tool.50 Family history, work place conflict, large family, female gender and
stressful working conditions were the factors attributed to occurrence of depression in the
study.50
Among inmates of Port Harcourt prison, a depression prevalence of 42% was reported using
the observer administered Beck Depression Inventory (BDI).51 Depression rate was higher
among single males and among inmates under trial compared with those whose sentence had
been passed.51
In the various studies of depression using the interviewer administered Zungs Depression
Scale, the self-administered Mini International Neuropsychiatric Interview (MINI), another
observer administered Geriatric Depression Scale (GDS), and interviewer administered
Structured Clinical Interview for DSM-IV Disorders (SCID) reported prevalence rates that
were overall higher in the hospital facility based population than community based surveys.6-
10 The chronic nature of depression and its association with other diseases as co-morbidity
make its prevalence higher among patients than the prevalence in the general population.18 In
a study on mental health disorders among patients attending outpatient department of a tertiary
health care facility, 15.9% were found to be depressed.51
In the South-East sub region of Nigeria, a depression study among university students reported
a prevalence of 23.3%.52 Age less than 20 years, smoking, female gender and having a
professional exam at hand were factors found to be related to depression.52 Among the resident
31
doctors working at a tertiary hospital in Enugu, a depression prevalence of 17.3% was reported
using the MINI instrument.53 Examination stress was reported to be a contributing factor, and
more females were reported to be depressed than the males.53 In another study of depression
among hospital workers, 18.9% of the workers were found to be depressed.54 Female gender,
family living and difficult working conditions were attributed to occurrence of depression in
the study.54 Among hypertensive and diabetic patients attending the cardiology and
endocrinology clinics of a tertiary hospital in Enugu, 27.8% of the patients were reported to be
depressed.55 The conditions predisposing to depression as reported in the study were being
without a spouse or not married, lack of formal education and unemployment.55
In Maiduguri, North-East Nigeria, a prevalence of 70% was reported among university
students following insurgency in the region.56 Death of a relation, physical encounter with
dead bodies and distressful living were some of the factors that contributed to depression in
the study.56 Among the staff of a tertiary health facility in Maiduguri, a prevalence of 18.3%
was reported with depression rate higher among the clinical staff.57 Work related stress and
burnout were factors associated with depression among the staff.57 In another study that
evaluated outpatients on Highly Active Anti-Retroviral Therapy (HAART), at a tertiary health
facility in Maiduguri, 20% of the patients were found to be depressed.58 Female gender, history
of psychiatric illness and short period of HIV seropositivity were significant predictors of
depression reported in the study.58 Diabetic patients attending outpatient department of the
same health facility were found to have a depression prevalence of 8.3%.59 Youthful age, low
socio-economic status and presence of comorbid medical conditions were associated with
depression.59
In the Northwest sub-region of Nigeria, a study of depression among people with leprosy in
Sokoto, reported a prevalence of 28.4% using the General Health Questionnaire, 28 (GHQ
32
28).60 In this study, depression was found to be significantly associated with female gender,
older age of onset of illness, having no spouse, unemployment, long duration of illness, shorter
years of formal and informal education, and poor drug compliance.60 An evaluation of
psychiatric morbidities among patients with HIV infection in Sokoto reported a depression
prevalence of 15.1% with age < 20 years, female gender and being with an illness > 5 years
associated with occurrence of depression.61 Among patients who survived stroke in a health
facility in Sokoto, a depression prevalence of 16.2% was reported, with disability mainly
contributing to occurrence of depression.62
In Kwara, North Central Nigeria, a survey of inmates’ of a borstal institution found 35.8% of
the inmates depressed.63 Youth criminality, substance abuse and the quest to succeed were
found to be contributory to depression in the study.63 Among patients attending the GOPD of
a Specialist Hospital in Ilorin, 44.5% were found to be depressed using the PHQ 9.64 Lack of
formal education, low income, age above 50 years and female gender were associated with
occurrence of depression in the patients.64 In an evaluation of patients with tuberculosis at a
tertiary health facility in Ilorin, 27.7% of the patients had depression using the PHQ 9.65 The
presence of persistent cough and financial distress were identified risk factors associated with
depression in the study.65
In Jos, a prevalence of 25.5% was reported among patients attending the GOPD of a tertiary
health facility, using the SCID questionnaire.9 The presence of comorbid disease conditions
necessitating frequent hospital attendance was found to be significant in this study.9 At the
same facility, among medical outpatients and using the SCID questionnaire, 19.5% of diabetic
patients were reported to have major depression.66
Among the inmates of Jos prison, using the GHQ-28, a 30.8% depression prevalence was
reported.67 Unemployment, being single and substance use disorder (SUD) were associated
33
with depression in the study. A cross-sectional survey of patients with irritable bowel syndrome
in three tertiary hospitals within Jos metropolis reported a 56.8% prevalence rate using DSM
IV symptoms checklist.68 The presence of distress and discomfort caused by the disease was
associated with depression in the patients studied.68
2.2 OVERVIEW OF THE BURDEN AND IMPACTS OF DEPRESSION
Depression, being the commonest mental health condition does not only affect individuals but
also other family members and the family functioning of the depressed subjects.69 Depression
also impacts negatively on the productivity and socio-economic wellbeing of the society and
the nation at large.69
2.2.1 Burden of Depression on Individuals
Mental disorders have a significant impact on individuals, families and communities.69
Depression is the commonest mental health problem.69 People with depression usually have
depressed mood, loss of interest in activities, lack of concentration, feeling of worthlessness,
guilt, and sometimes thoughts of suicide.1,2 They experience hopelessness, low energy and
difficulty in concentration.2 The courage and vigour to focus on an individual task is usually
lost. The general feeling of unwellness renders depressed patients incapacitated.2 He or she
may not be able to perform satisfactorily or excel in a competitive world.2 A depressed
individual has poor physical functioning.70 His or her level of physical activity also changes
with each episode of depression.70 This usually follows a diminished interest in physical
activities, fatigue or loss of energy. On the other hand, whenever physical functioning
deteriorates, depressive activities tend to worsen.70 The degree of physical activity of a
depressed person correlates positively with the individual’s degree of social functioning and
medication adherence.70
34
A depressed patient has poor outcomes from co-morbid disease conditions due to poor health
seeking behavior, poor adherence to medication and other disease management.71 In its severe
form, depression limits physical, social, work and domestic activities.1, 17
2.2.2 Burden of Depression on Families
Depressed people tend to have poor relationships with spouses, sexual difficulties and
financial problems.72,73 These may culminate in poor outcome of co-morbid conditions.73 The
majority of caregivers of depressed patients have been reported to have high depression
scores compared to caregivers of non-depressed patients.73 The families of depressed patients
have also been reported to have higher marital discord, difficult relationships with children and
spouses as well as domestic violence.74 These manifest as misunderstanding, misbehaviour,
conflicts and disagreement among family members.74 The consequences include poor social
and family functioning resulting in poor health care in the affected patients.74 Among the
members of a dysfunctional family, there exist less family cohesion, commitment, help and
support.74 Poor social and family function causes low family cohesion, family support systems
fail, disease control and prevention, child care and nutrition, as well as adolescent health and
maturation also become affected1,74 There may also be sexual dysfunction, and maternal
depression which has a substantial effect on the entire family.1 Any member of such a
dysfunctional family has increased likelihood of poor disease management and outcome.74
2.2.3 Burden of Depression on Work, Functioning and Productivity
Depressed people suffer medical and psychosocial impairment leading to missing work or
disturbed daily routine, change in sleeping habits and poor or absent recreation.73 Depression
causes a substantial negative impact on the individual and his or her work.75,76 Chronic
depression affects educational attainment thereby affecting employment opportunities.75
35
Depression affects worker productivity by reducing cognitive processing, memory, attention,
concentration and energy levels.75 Depressed people miss work more often than non-depressed
employees thereby leading to work abseentism.75 In performing skilled activities, depressed
workers tend to work slowly and often make more errors.75 This results in poor productivity
and possible occupational injury.75 Depressed workers also tend to have more conflict at work
leading to greater loss of productivity. The negative outcomes of having a depressed worker
include, work impairment, underemployment or loss of job and eventual unemployment. This
dysfunction also involves the areas of disability costs, increased reason for sick leaves and
disability leaves.76,77 This in turn affects the economy and society at large.76 Therefore
depression not only incapacitates the individual sufferers, but also their associates, families,
businesses organizations and the society.69,77
Majority of depressed people are among the active work force required for productivity, but
associated with poor quality of life and reduced performance of their usual roles.3,78,79 People
with mental health problems were reported to be the least employed among other categories of
disabled people in the United Kingdom.80 An average of 11 days absence from work every six
months compared to two days was reported among depressed and non-depressed people
respectively.80 This also contributed to low productivity.80 An American productivity audit
reported that an average of $44 billion was lost due to work absence and impact of depression
annually.80 Similarly, every year in the United Kingdom, an average of €4 billion is lost due to
depression.80
2.2.4 Burden of Depression on Society
The WHO refers to the mental health of an individual as a state of well-being whereby
individuals recognize their abilities, and are able to cope with the normal stresses of life, work
productively and make positive contributions to their communities.76 The physical, mental
36
and social wellbeing of every individual is intertwined.76 Since every society functions as a
system with each individual contributing positively to its existence, if one member of such a
society is depressed, it will affect the society as a whole.76 The ability of such an individual to
work and make productive contributions to his society is hampered.76 His or her personal
income depreciates, and his immediate trade or occupation suffers a setback.76 Consequently,
the goods or services he or she could have produced or rendered to the society is negatively
affected.76
Depressed patients experience social impairment and poor ability to connect emotionally to the
immediate and remote social environment.61 The poor emotional state in depression is
associated with poor decision making, poor social interaction, and poor performance.61
Depression may also create socially uncomfortable situations with negative perceptions and
social skill deficit.27 This might eventually lead to social phobia and stigmatization.61
2.3 FACTORS ASSOCIATED WITH DEPRESSION
Social and economic status have been studied and identified as predictors of the development
of depression.29,30 Age, gender, marital status, education, residential location, wealth, self-rated
health, and religion have been reported to be associated with depression.36 Insecurity, stressful
lifestyle and armed conflict were reported to be associated with depression as well.19,26 Other
factors include unemployment and poor social support.38 Some researchers however, reported
no direct association of depression with the risk factors in the cohorts studied.29,30
2.3.1 Depression and Socio-economic Status
A study comparing country level socio-economic status, and work place organizational level
among the working population found no direct relationship of these indices with the
37
development of depression.17 However, another study reported low socio-economic factor as a
predisposing factor to depression.35
Financial constraints among a similar social class as well as poor working conditions were
identified as directly associated with depression.17 This implies that most of the disadvantaged
conditions that lead to the development of depression, do not have a direct relationship, but
are an interplay of several conditions together.17,35 Asibong et al found that adults aged 18
years but less than 40 years, and being employed were the significant socio-economic
characteristics that determine depression.13 Struggling with meagre wages and coping with
family needs among those employed were some of the conditions predisposing to
depression.10,13 Amoran and Lesibikan also found that depression was more prevalent among
the low socio-economic adolescent, young adults, as well as among rural dwellers than people
staying in affluent cities.38,41 Gureje et al. however, reported increasing age as a factor for
developing depression.79 Young rural dwellers were also noted to be struggling with financial
needs and this was identified as the likely stressor for depression in them.79
2.3.2 Depression and Chronic Illnesses
Chronic illnesses have been associated with depression.20 Gureje et al. reported chronic pain,
musculo-skeletal conditions, ulcers, anxiety and other co-morbidities as predisposing factors
for development of depression.79 However, presence of nonspecific, debilitating and
unexplained somatic symptoms have been described as a possible presentation of a depressive
condition.80 Depression may predispose to the development of some physical conditions, and
vice versa.80
The development of cardiovascular diseases as well as diabetes has been reported in a cohort
of depressed patients.80 The association has been found to be both behavioural and
38
physiological.80 Solitary lifestyle, withdrawal, diminished motivation, not engaging in physical
activities and lack of compliance with medical treatment have been identified as risk factors
for developing or exacerbating several chronic illnesses.80 Similarly, untoward health
behaviours like smoking cigarettes and consuming alcohol have been found to be contributory
to the development of depression.79
The physiological changes leading to excess secretion of cortical hormones, and alteration in
the production and metabolism of neurotransmitters are linked to the development of
cardiovascular diseases.80 On the other hand, the pain from physical illnesses as well as stress
induced by physical problems trigger depression in the sufferers.80
The genetic make-up of an individual could be another risk factor for developing depression
as well as determining the course of depression in such people.80
When there is concurrent inheritance of both genes for the two conditions, patients with both
depression and chronic illness often have poor outcomes, and poor interpersonal relationships
which cause increased stress in their spouses and caregivers.72, 74
2.3.3 Depression and Marital Status
Depression is approximately 1.5-2 times more common in adult married women than men.78
However, the sex difference in prevalence of depression is not based on the differential effect
of marital status, child care or work status.80 In the late teenage years and young adulthood
when the first episode of depression usually occurs, youths are faced with many personal and
societal pressures.80 The youths aspire to achieve educational qualification, career, a
meaningful relationship including marriage, and other interpersonal relationships.80 The
struggle to achieve such needs play a role in the development of depression among young
people.80
39
Among married cohorts, lower levels of depression have been reported than among their
unmarried counterparts.80 First marriage was also reported to be protective against depression
than subsequent marriages in the same cohort.80 Marriage was also reported to be more
protective for men than for women against depression.80
However, being previously married relative to being stably married increases the risk for
depression in both men and women.80 Family pressure associated with child bearing and family
violence have also been found to be contributory to the development of depression among the
married.80
2.3.4 Depression and Ethnicity
A study on the occurrence and distribution of depression in the American population reported
that native Americans had higher rates of depression than other ethnic groups compared; that
is the Africans and the Hispanic.80 Among immigrant ethnic groups, especially those affected
by political unrest or economic deprivation, rates of depression were higher than their host
community.80 However, among the migrant ethnic groups who could speak the language of
their host community or get integrated through socio-economic activities, lower rates of
depression were found.80
In Nigeria, a prevalence of 5.2% was reported among predominantly Yoruba speaking people
of Oyo State.42 There are however several other prevalence studies done but mostly among
heterogeneous ethnic groups. Hence there is paucity of ethnic group based depression studies
in Nigeria.
2.3.5 Depression and Age
40
The reported age of onset of depression varies between 19-44years.80 The onset of depression
at a young age was reported to be related to school exclusion or poor educational
achievement.80 Other risk factors for developing depression at young age include financial
adversity, teenage childbearing, marital instability, early childhood and co-morbid mental
health conditions.80 The adult age risk factors for developing depression include social and
economic deprivations.36,39 In the older population, loneliness, death of a spouse and co-morbid
physical conditions was reported to influence the occurrence of depression.80
2.4 DIAGNOSIS OF DEPRESSION IN PRIMARY CARE SETTINGS
The diagnosis of depression in primary care setting is usually done with the aid of structured
manuals and standardized tools such as the Patient Health Questionnaire 9.81 The Diagnostic
and Statistical Manual, IV edition (DSM IV) has symptom-based criteria for diagnosis of
depression.81 The presence of low mood, aversion to activity and anhedonia are common
depressive symptoms.81 To make a diagnosis of depression however, the presence of five (or
more) of the following symptoms in a person during the previous 2-week period is required.81
These include: depressed mood most of the day or nearly every day as indicated by either
subjective report (such as feeling sad or empty) or observation made by others; marked
diminished interest or pleasure in all, or almost all activities previously liked and enjoyed by
the person or subject; weight loss when not dieting, or weight gain or decrease or increase in
appetite nearly every day; Insomnia or hypersomnia present every day or nearly every day.17
Some people may have psychomotor agitation or retardation, with nearly subjective feelings
of restlessness or being slowed down. These symptoms may be obviously noticed by others.
Fatigue or excessive feeling of tiredness, and loss of energy may be another common symptom
which could be experienced nearly every day. Feelings of worthlessness or excessive or
inappropriate guilt could be an expression of depression.17 Similarly, diminished ability to
41
think or concentrate on a task, or indecisiveness is a symptom of depression.17,80 Recurrent
thoughts of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or
a suicide attempt or a specific plan for committing suicide, is a manifestation of severe
depression.81 In the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th
revision), the diagnosis of depression focuses on explicit disorder criteria.82 This includes
specific diagnosis of mild, moderate and severe depression, presence of psychotic features, and
treatment outcomes such as partial or full remission. Other considerations include persistent
depressive disorders wherein dysthymia is classified.82
The DSM IV criteria for depression is a comprehensive symptom diagnosis but the busy nature,
wholistic approach and the pattern of patients presenting at primary care facilities makes the
symptom checklist tools or questionnaires easier and more effective for the diagnosis of
depression in such settings.11,83
In the International Classification of Diseases, 10th edition, (ICD 10), the diagnosis of
depression is based upon the presence of key symptoms, which are: persistent sadness or low
mood, and/or loss of interest or pleasure and fatigue or low energy.82 At least one of these key
symptoms must be present most days; most of the time, for at least two weeks.82 In addition to
these symptoms, there could also be disturbed sleep, poor concentration or indecisiveness, low
self-confidence, poor or increased appetite, agitation or slowing of movement, guilt or self-
blame and suicidal thoughts or acts.16,82 The degree or severity of depression is categorized due
to the number of symptoms present. In this classification, patients with less than four symptoms
are considered as not depressed while those with four symptoms as considered mildly
depressed.82 Moderate depression is diagnosed when there are five–to-six symptoms while a
diagnosis of severe depression is made when there are seven or more symptoms present, for
most of the days and persisting for a month or more.82 Although the ICD 10 diagnosis and
42
classification of depression to mild, moderate and severe are exactly the same with DSM IV
classification, both classifications were based on signs and symptoms that the clinicians
believed are the manifestation of depression. This also applies to all the other validated tools
by the various bodies of psychiatrists.
Several screening tools are also used for diagnosis of depression in primary care setting.83
There are short instruments and long instruments but each has been validated based on either
the DSM or ICD criteria, and are usable in primary care setting.83 The short instruments
include; Mini International Neuropsychiatric Instrument, MINI, Becks Depression Index,
Short Form, (BDI-SF), Patient Health Questionnaire 9 (PHQ-9) and Patient Health
Questionnaire 2 (PHQ-2). Others are General Health Questionnaire 10 (GHQ-10), Revised
Clinical Interview Schedule (CIS-R), Subjective Well-being Subscale, (SWS) Edinburgh
Postpartum Depression Scale, (EPDS) and Kessler Psychological Distress Scale (K10) and
(K6).83
The long instruments include: Centre for Epidemiological Studies Depression scale, (CES-D,
SRQ-20), the Hopkins symptom Check list-25, (HSCL-25), and Becks Depression Index
(BDI). Others are the Zungs Self Rating Depression Scale and Hamilton Depression Rating
Scale, (HADS).10
The short or brief instruments have been studied and proven to be as accurate as the long
instruments.84, 85 In addition, the brief instruments have an edge over the long ones as they are
easier to apply and fit the busy nature of primary care settings.11
Among the screening instruments for depression in primary care settings, the PHQ 9, GHQ 12
and K6 have been validated in Nigeria.86, 15 Other tools that have been validated in Nigeria are
the EPDS and the BDI.44,87, 88
43
The diagnostic properties of PHQ 2 make it suitable for detection of depression in primary care
settings.8,17 It has been used on patients with various diseases and illnesses, with consistent
outcome. It is also easy to administer and interpret.17
Because of its ultra-short nature (made up of two questions only) and the ease of its usability
coupled with good diagnostic properties, the PHQ 2 is suitable for the busy nature of primary
care settings.11,17 PHQ 2 is easily administered and a commonly used tool for depression
screening. In a meta-analysis of its validity, PHQ 2 was found suitable for different groups of
patients seen in primary care settings as well as in the general population in a community based
studies.11,84 It has been validated for use in both in-patients and out-patients. It has also found
use in special situations including paediatrics, obstetrics, postpartum depression, depression in
the elderly, and among medical and surgical patients.84,86 Meta-analysis of the accuracy of PHQ
2 across patients of various ages, different sexes and diversity of diseases all found it consistent
in its diagnosis of depression, in terms of its validity and reliability.86
In elderly patients among whom occurrence of depression is associated with compromised
quality of life, worsening morbidity, and higher health care expenditures, PHQ 2 demonstrated
good diagnostic criteria with a good sensitivity and specificity.89,11
The PHQ 2 has demonstrated good diagnostic qualities in the chronic care conditions
commonly encountered in primary care.81,90 Among patients suffering from migraine
headache, which is usually associated with decreased quality of life because of persistent pain,
the PHQ 2 demonstrated excellent diagnostic properties.90 When used in acute conditions, the
PHQ 2 equally diagnosed depression well.91 In a study on the utility of Patient Health
Questionnaire among in-patients with acute coronary syndrome, PHQ 2 demonstrated good
validity and reliability properties in the diagnosis of depression.91
44
Among alcohol and drug users, where depression is associated with impaired quality of life,
poor adherence to treatment and health outcomes, PHQ 2 as well as the PHQ 9 also
demonstrated diagnostic accuracy.92,93 This makes it a suitable tool for screening drug related
depression.93 Also when used among adolescents where depression is associated with poor
school performance, substance abuse and risk of depression, PHQ 2 demonstrated good
sensitivity and specificity.92 This makes PHQ 2 one of the most widely used instruments for
diagnostic screening in adolescents.93
In a validation study of the PHQ 2 among postpartum women attending a well-child clinic, the
PHQ 2 was highly sensitive in identifying postpartum depression.94 PHQ 2 was found to be
easily self-administered, or completed by mail as well as by phone.94 To find out the reliability
of the PHQ 2 in diagnosing depression among alcohol and drug users, PHQ 2 yielded
satisfactory sensitivity and specificity.92 Together with PHQ 9, their diagnostic properties made
them appropriate for use among people using alcohol or drugs.
In a study to determine the accuracy of specific symptoms in the diagnosis of major depressive
disorders among psychiatric out-patients, the two items of depressed mood and anhedonia in
PHQ 2, were the most accurate predictor items among all other depressive symptoms.95 These
diagnostic qualities of PHQ 2 made it suitable for diagnosing depression among psychiatric
patients.95 In a similar study among general outpatients in a primary care setting, the PHQ 2
demonstrated good reliability and consistency in the diagnosis of depression.96
The PHQ 9 has similarly and consistently demonstrated good screening properties. 90,94 Among
people using alcohol and drugs, PHQ 9 demonstrated a sensitivity of 0.81 and specificity of
0.75.92 The PHQ 9 demonstrated good sensitivity and specificity among different group of
patients similar to PHQ 2, including chronic conditions and malignancies, acute presentations,
45
alcoholics and drug users, postpartum women, psychiatric patients and among patients in
primary care settings..90-96
2.4.1 Recognition of Depression in Primary Care Settings
A WHO study on psychological disorders in general health care found that Primary Care
Physicians detected only 39.1% of cases of depression.42 In the United States, depression
affects approximately 18.8 million adults but only an estimated 50% of the depressed people
are recognized.82 In a cross-sectional study done across PHC centres in Spain, 72.3% of the
depressed patients were unrecognized.97 Most of the patients were receiving treatment for
somatic illnesses.97 In India, a study conducted to find out the prevalence of unrecognized
depression in out-patient attendees of rural hospitals, reported approximately 23.8% of the
patients depressed.98 In a multi-centre prospective cohort study to find out detection rates of
depression in primary care in the Netherlands, only 36% of depressed patients were detected,
missing out 64%.99 Another study done in California, to determine the agreement between
depression symptoms and the documentation of same by physicians in primary care, found
only 37.7% diagnosed as depressed while 62.3% of depressed patients were misdiagnosed.100
Use of routine structured screening for depression was therefore, advocated to reduce
misdiagnosis.100 The study reported that paying little attention to the interactional aspect in the
recognition of depression, and not considering wholistic assessment of the person were
limitations of the primary care physicians that made them misdiagnose depression.100
Since diagnosis and recognition of depression, treatment, and appropriate referral to a mental
health specialist determines the outcome of treatment received by patients, the diagnostic
accuracy of depression is essential in the management of depression.101,102 This calls for
enhanced recognition of depression in primary care settings.102 The recognition of depression
by chart review was found to be higher than that of clinical diagnosis without tools or charts.103
46
The training of primary care health staff with such appropriate charts/tools contributed
significantly to the quality of detection and management of depression in primary care.73
A similar study done to examine the accuracy between depression symptoms using an
assessment tool, and physician documentation of the same symptoms during a clinic visit had
75.3% diagnosed depressed by use of the tool but only 31% were diagnosed by clinical
assessment without the use of tools.100
In Malawi, using the Structured Clinical Interview for DSM IV, questionnaire, a cross-
sectional survey of patients attending primary care centres found a prevalence rate of
depression of 30.3% while detection rate by clinicians was 0%.104 Failure to diagnose
depression was attributed to lack of assessment for mental health disorders.
In Nigeria, a cross-sectional survey of patients attending the general medical out-patient
department of a University Teaching Hospital, reported a depression prevalence of 47.8% but
none of the patients had depression as the primary diagnosis by the attending physicians.105 In
another cross-sectional study done among in-patients of a general hospital in Nigeria,
approximately one third (31%) of the patients had unrecognized psychiatric disorder.12 Among
these patients with unrecognized psychiatric disorders, 61.5% had depression.12 Another
survey of mental health disorders in a primary care setting reported a prevalence of 63% while
only 12.7% were recognized.11 In an out-patient survey of depression done among patients
attending antiretroviral therapy clinic, at Ahmadu Bello University Teaching Hospital Zaria,
14.2% of the patients were found to be depressed.78 All the depressed patients were not
recognized by the attending physicians prior to the study.78 In another similar hospital based
study, more than half of the patients, (56.7%), were found to be depressed.78 Stressful life
events, low socio-economic status, gender and age were factors associated with depression
consequently responsible for poor adherence to treatment.78
47
2.4.2 Screening for Depression in Primary Care Settings
Screening refers to the systematic application of a test or enquiry to identify individuals at high
risk of developing a specific disorder who may benefit from further investigation or preventive
action.82 Screening is the starting point for providing effective treatment for depression because
if the condition is not recognized the patients cannot be treated.82,84 The first point of access is
usually primary care, with the majority of people continuing to be managed for depression in
primary care.91,106 Screening for depression could be described as the use of questionnaires
concerning the symptoms of depression, or small sets of questions about depression, to identify
patients who may have depression but who have not sought treatment and whose depression
has not already been recognized by health care providers.84
The United States Preventive Services Task Force (USPSTF) recommends screening for
depression provided that the screening tool is able to accurately identify a significant number
of previously unrecognized depressed patients and clinicians are willing to engage these
patients in treatment and obtain sufficiently positive results to justify costs and potential
harms.84 However, the problems of poor or suboptimal treatment, inadequate care staff, high
burden of depressed patients, possibility of false positive results and the necessary need for
follow-up interventions in the management of depressed patients are among the reasons why
some clinicians advocate against screening for depression.83 Another reason is that, most
moderate to severe depression are recognized in primary care by virtue of the longitudinal
patient-doctor relationship.98 Only the mild depressive patients are missed without screening,
of which spontaneous recovery usually occurs.84
The widespread, prevalent and debilitating nature of depression, however necessitated the
recommendation for its screening.10 According to the WHO, depression will be the second most
disabling condition by the year 2020.106 The USPSTF found good evidence that screening
48
improves the accurate identification of depressed patients in primary care settings, and also
improves the outcome.100 Early detection and management of depression improves clinical
outcome and decreases morbidity due to depression.106 The USPSTF also advocates
management of depression in primary care through screening and treatment with
antidepressants, psychotherapy, or both as measures to decreases clinical morbidity.107 The
programmes that combine depression screening and feedback, with staff assisted depression
care support improved clinical outcomes in adults and older adults.108
2.4.3 The Patient Health Questionnaire 2 (PHQ 2)
The Patient Health Questionnaire 2, (PHQ 2), is the first set of screening questions of the
Patient Health Questionnaire 9, (PHQ 9) based on the Diagnostic and Statistical Manual of
Mental Health Disorders, fourth edition, (DSM IV). The PHQ 9 is a validated self-administered
tool for screening depression.109 The Patient Health Questionnaire 2 has a good diagnostic
operating characteristic as a two item depression screener. Its diagnostic score ranges from 0-
6, each item with a score range of 0-3. The PHQ 2 was clearly able to differentiate between
patients with and without depression, which confirms its discriminatory validity.109 The PHQ
2 has a sensitivity of 0.84 (0.77-0.89) and a specificity of 0.92(0.90-0.94) in general outpatient
use, and is therefore recommended as well suited for screening depression in general practice.8
In validation studies among different types of patients seen in primary care, PHQ 2
demonstrated consistency in its diagnostics properties.89-96 In a study to determine the validity
of the patient health questionnaire among primary care patients in Hong Kong, PHQ 2
demonstrated good sensitivity of 0.88 and specificity of 0.82.96 In a similar validation study at
a Headache Clinic among patients with migraine, PHQ 2 demonstrated good diagnostic
properties with a sensitivity of 0.67 and specificity of 0.903, a Positive Predictive Value (PPV)
of 74.3%, a Negative Predictive Value (NPV) of 86.6% with Cronbach’s alpha (α) of 0.747.90
49
In the Receiver Operating Curve (ROC) analysis of PHQ 2 performance, the Area Under the
Graph (AUG) was 0.876 (95% CI 0.814-0.938).92 The PHQ 2 scores correlated well with that
of Becks Depression Index (BDI), in the study, (Spearman’s correlation coefficient, 0.739).90
When used among adolescents for diagnosis of depression, PHQ 2 at a score of ≥3
demonstrated good sensitivity, specificity, NPV and PPV of 0.962, 0.823, 99.4% and 42%
respectively.93 This makes PHQ 2 suitable for excluding depression among the youths. The
PPV in the study was however, rather low at 42%.95
In a validation study of PHQ 2 among old people in a primary care setting, good sensitivity of
1.00 and specificity of 0.77 was demonstrated.89 PHQ 2 was able to discriminate depressed
from non-depressed subjects at a score of ≥2. The retest reliability intra-class correlation was
good at 0.70 with a Cronbach’s alpha of 0.76, and Spearman correlation coefficient (r =
0.53).89 Participants in the study with high PHQ 2 scores were reported as having previous
diagnosis of depression or had previous treatment for depression.89
In screening postpartum women for depression, PHQ 2 had a sensitivity of 0.75, specificity of
0.91, NPV of 99% and PPV of 28%.94 This study again, demonstrated the discriminatory
property of PHQ 2.94
Among hospitalized patients with Coronary Artery Disease (CAD), PHQ 2 yielded good
diagnostic properties with a sensitivity of 0.956, specificity of 0.714, NPV 98% and a
consistency index of 0.68.91 In the ROC analysis, PHQ 2 at a score of > 0 AUC was 0.912
(95% CI 0.839-0.960) and Younden Index of 67.08.91 The ROC when compared with that of
PHQ 9 at a score of >4 had not much difference, 0.0141; 95% CI -0.0488-0.0771; P=0.66,
suggesting close similarity of their diagnostic abilities. 91
50
In a validation study of the PHQ 2 among alcohol and drug users, a sensitivity of 0.68,
specificity of 0.70, a retest reliability 0.66 and internal consistency, 0.64 was reported.94 The
diagnostic values also correlated well with that of PHQ 9.
A meta-analysis of various PHQ 2 validity studies to determine its diagnostic accuracy yielded
an overall sensitivity of 0.737, specificity of 0.747, NPV of 93.0% but PPV of only 38.3%.86
The diagnostic properties of the PHQ 2 therefore make it suitable for use in the different groups
of patients in primary care especially in screening for depression.86
2.4.4 The Patient Health Questionnaire 9 (PHQ 9)
The Patient Health Questionnaire 9, (PHQ 9) is a brief tool used to diagnose and to measure
the severity of depression. The PHQ 9 was validated based on the Diagnostic and Statistical
Manual of Mental Disorders, 4th edition (DSM IV); criteria for depression.8 The PHQ 9
consists of all the nine diagnostic symptom criteria used in DSM IV, including the two cardinal
signs of depression: anhedonia and depressed mood. Others include trouble falling or staying
asleep or sleeping too much, feeling tired or having little energy, poor appetite or over eating,
feeling bad about yourself – or that you are a failure or you have let yourself or your family
down, trouble concentrating on reading the newspaper or watching television. Also included
are moving or speaking so slowly that other people could have noticed; or being so fidgety or
restless that you have been moving about a lot or more than usual, and finally the thought that
you are better off dead, or hurting yourself in some way.8
The PHQ 9 is widely used by clinicians in general practice including the Nigerian setting.11 It
is a 27 score tool of nine items outlined in the preceding paragraph. Each of the nine items
scores 0-3, providing a 0-27 severity score. Score of 0-4 is not significant, 5-9 mild depression,
10-14 moderate depression, 15-19 moderately severe depression, while 20-27 is severe
51
depression. The PHQ 9 has been validated among Nigerian students with an internal
consistency of 0.85. At the minimal diagnostic score of 5, it has a sensitivity of 0.897,
specificity of 0.989, a positive predictive value of (PPV) 0.875 and a negative predictive (NPV)
value of 0.981.8
In a different study conducted among patients with migraine attending an outpatient clinic, the
PHQ 9 demonstrated good psychometric properties in a validation study among outpatients
with migraine headache, with a sensitivity 0.795, specificity 0.817, PPV 64.6%, NPV 90.5%,
and cronbach’s consistency index of 0.894.90 In ROC analysis of the study, PHQ 9 at a score
of ≥7 demonstrated good diagnostic properties, with the AUC of 0.806, (95% CI 0.720-
0.892).90 When compared with BDI, PHQ 9 correlated well with a correlation index of 0.754.90
In yet another study of patients with coronary artery syndrome, PHQ 9 displayed good
diagnostic characteristics in a validation study.91 It demonstrated a sensitivity of 0.96 and
specificity of 0.73 at a score of >4.91 The ROC analysis of its diagnostic characteristics
demonstrated an AUC of 0.926 (95% CI 0.856-0.969), with a sensitivity of 95.65%, and a
specificity of 72.73.91
When used to diagnose subjects using substances and alcohol, PHQ 9 at a score of ≥12 had a
sensitivity of 0.81, specificity of 0.75, internal consistency (Cronbach’s alpha 0.84), and retest
reliability (intra-class correlation, 0.78).92 These psychometric properties make it valid for
diagnosing depression in people using drugs and alcohol.92
2.4.5 Suitability, Usability and Historical Development of the PHQ 9 and PHQ 2
The Primary Care Evaluation of Mental Disorders (PRIME MD), was the first instrument
developed for screening mental disorders in primary care based on the Diagnostic and
Statistical Manual of Mental Disorders, the third edition, revised and the fourth edition, (DSM
52
III-R, DSM IV).83 PRIME-MD is a 26 item self-administered questionnaire with two screening
questions: Have you often been bothered about having little interest or pleasure in doing things,
as the 18th and 19th questions.83 The validation was done in eight primary care centers in the
United States.84 The Patient Health Questionnaire 2 was developed and validated from PRIME
MD as a short self-administered version. The Patient Health Questionnaire (PHQ)-2 and PHQ-
9 are commonly used in primary care as well as in specialist clinics.17 The PHQ-2 has an
average of 97% sensitivity and 67% specificity in adults, although another study reported a
sensitivity of 73.7% and a specificity of 74.7%.17,86 PHQ-9 has a 61% sensitivity and 94%
specificity, with a 38 % positive predictive value and 93% negative predictive value.17 Because
of its high sensitivity, the PHQ 2, can easily recognize depression but not make definite
diagnosis of depression, due to its ultra-short nature, not encompassing all the items needed for
depression diagnosis.17 In a meta-analysis of several validation studies of the PHQ 2 and the
PHQ 9, the PHQ 2 was shown to have good sensitivity and specificity in primary care out
patients.84 It however had lower reported sensitivity when used to screen cardiology patients.84
The PHQ-2, which asks two simple questions about mood and anhedonia, has excellent
strengths. It is as effective as longer screening instruments, such as the Beck Depression Inven-
tory or Zungs Depression Scale.17 It is self-administered, quick and easy to understand.17 PHQ
2 is used in adolescents, adult men and women, as well as the geriatric populations.17 The
American Geriatrics Society recommends using the PHQ-2 as an initial screening test for
depression in older adults.17
The Patient Health Questionnaire 9, in the same reviews, demonstrated high sensitivity and
specificity in screening depression.16,84 PHQ 9 could be administered in two to five minutes
and it’s easy to understand by patients.17 PHQ 9 can be used on its own as a screening test, to
monitor treatment and to follow-up patients.17 PHQ 9 is the commonly used depression
53
screening tool for the confirmation of a positive PHQ-2 result.17 The PHQ 2 and PHQ 9 are
the most commonly used self-administered tools for depression screening in different clinical
settings.17,84
2.5 MANAGEMENT STRATEGIES FOR DEPRESSION IN PRIMARY CARE
Since the goal of depression management is to achieve total remission, a wholistic, bio-
psychosocial and comprehensive care is employed in the management of depression in Primary
care.109-111 This is because biological, psychological and social factors all contribute to the
development of depression and its treatment.111 In this context, patients are educated about
their illness and motivated to take active roles in their care.110 The caregivers, on the other hand
are people with needed competence and committed to providing the needed care for the
depressed patients in a collaborative and coordinated manner with other specialists.111 This
approach to management has demonstrated improved treatment outcomes and patient
satisfaction.110
The health system, care providers, patients and their families all play roles in this management
approach.111
2.5.1 System Based Management Approach
The system approach involves the screening and diagnosis of depression among primary care
patients, the use of evidence-based protocol in management and monitoring outcomes and
coordination of all care providers.112 The system based approach management of depression
employs the use of standard depression screening instrument, and utilizes every contact with a
patient with probably depression as an opportunity for screening.112 It also includes effective
patient communication, the use of information technology, and self-management tools.112 The
54
system management approach focuses on monitoring all the management outcomes, patients’
contact tracking, and regular quality report at patient and facility levels.112
The needed expertise in the appropriate application of depression screen instruments, proper
documentation of the screening results and giving the patients the best of care, must always be
considered while integrating the systems approach into patients’ care plan.112 Where either
skills of screening or diagnosis of depression is lacking, or the expertise management could
not be offered, it is advisable not to screen the patient in the first place, as screening may only
add anxiety and worry to the patient if no solution is proffered after diagnosis.112 The use of
PHQ 2 helps in initial diagnosis which is the first thing needed for any subsequent care patients
receive from the health care system.
2.5.2 Collaborative Care
In this care approach fashioned after the Chronic Care Model, the various care providers in
primary care are harnessed in a synergistic manner.113, 114 The care given, is coordinated
profitably to the benefit of the patient and the system, without duplication of functions.115
Patients, primary care providers, mental health specialists like the psychiatrists and
psychotherapists are integrated in the provision of care. In addition, primary care providers of
mental health services also receive consultation and clinical support from the mental health
specialists whenever such is required.113,116 This has been reported to improve depression
management outcomes with decrease in hospital visits.113,116 Collaborative care has
demonstrated improved routine screening and diagnosis of depression, improved provider use
in the evidence-based management of depression, improved clinical and community support
of depressed patients.113,114 In addition, self-support system utilization by the use of self-help
instruments to achieve treatment goals are provided for the patients. Patients who received
treatment through this method showed decreased work absenteeism, increased performance
55
and increased return on investment.81 The network of health care providers and community
support collaborative care appears to make this approach all-encompassing for depression
management.114 The ease of use of PHQ 2 by every health care personnel in collaborative care
model enables every health care provider to appreciate whether a patient is improving or
relapsing. PHQ 2 therefore provides an opportunity for every care provider involved in this
model to assess every patient he or she sees for depression.
2.5.3 Patient Centred Care
In this approach of care, the patient is given attention, education and motivation to overcome
his or her condition, 116 He or she is engaged in monitoring the symptoms, treatment outcomes
and side effects.116 The patient is also familiarized with the treatment protocol, length of
treatment, signs of relapse and prompt communication with care givers in case of any
problem.116 Patient centered care helps the patient to develop skills for early recognition of
signs of relapse, improve adherence, avoiding situations that triggers depression episodes, and
healthy lifestyle. This approach also involves partnership between the patients, the care
providers and evaluating the patient for organic depressive illnesses.116 Care givers partners
with the patients and collaborate with them in a manner that will enhance the best outcome in
the patient.
Because much of the success of this approach lies on the patient, the patient’s ability to develop
the needed skills and effective communication or contact with care givers, individual factors
aiding or militating against effective partnering will determine the success or otherwise of this
approach. Patients in this care model may use PHQ 2, as a self-administered tool, appreciate
56
the scores and take appropriate care needed. This could improve their health seeking behaviour
and utilization of the health care system.
2.5.4 PHARMACOLOGICAL MANAGEMENT
In managing depression, there are various available treatments, including pharmacotherapy.112
Watchful waiting involves frequent face-to-face contact to assess whether symptoms have
resolved, or an additional treatment may initially be considered.112 In patients with mild or
moderate depression, a meta-analysis by Fournier et al, reported that antidepressant medication
had minimal or no benefit compared with placebo. However, in patients with severe
depression, antidepressant drugs provided a substantial benefit compared to a placebo.109,112
Similarly, in individuals with worsening symptoms or with more significant functional
impairment, additional pharmacotherapy is required.112
Among the various drugs used for the management of depression are tricyclic antidepressants
(TCA), selective serotonin re-uptake inhibitors (SSRIs), serotonin and nor-epinephrine re-
uptake inhibitors (SNRIs), Serotonin antagonist (SAs), Nor-epinephrine and dopamine re-
uptake inhibitors (NDRIs). Others include monoamine oxidase inhibitors, MAOIs), Serotonin
reuptake antagonist receptor inhibitors (SARIs) and St. John’s wort.112, 109
TCAs and MAOIs are the classes of the first generation antidepressant medications.
Amitriptyline, clomipramine, desipramine doxepin, imipramine and nortriptyline are some of
the tricyclic antidepressant drugs, while MAOIs used for treatment of depression include
isocarboxazid, phenelzine, selegiline, and tranylcypromine.
TCAs and MAOIs have proved to be effective in treating depression, but they both cause a
wide range of side effects, which are often unpleasant. These include constipation, sweating,
shaking or trembling, insomnia, anxiety, orthostasis, weight gain, and sexual dysfunction.109
57
MAOIs are also used in the treatment of other mood disorders such as anxiety and bipolar
depressive disorder.109
SSRIs are second generation antidepressant drugs, widely used instead of TCAs and MAOIs
as they cause less troublesome side effects. Fluoxetine, citalopram, paroxetine and sertraline.
SSRIs have the advantage of ease of dosing and less toxicity when taken in overdose.109 It is
the preferred drug for treatment of children and adolescents. SSRIs are also the first line
medication for late onset depression.109,112 SSRIs have less effect on the blood pressure, heart
rate, cardiac conduction, and cardiac rhythm, hence are more tolerated by patients with
cardiovascular diseases. The common adverse effects of SSRIs include gastrointestinal upset,
sexual dysfunction, fatigue, and restlessness.109
The third generation antidepressants are the Serotonin-Norepinephrine Reuptake Inhibitors,
SNRIs. The SNRIs include venlafaxine, desvenlafaxine, duloxetine, and levomilnacipran.
They could be used as first-line medications in patients with significant fatigue or pain
syndromes such as diabetic peripheral neuropathy and chronic musculoskeletal pain.109 SNRIs
could also be used as second-line agents in patients who have not responded to SSRIs.109 SNRIs
are also useful in the management of other conditions such as Generalized Anxiety Disorder
(GAD), and fibromyalgia. The side effects of SNRIs are similar to SSRIs, and include nausea,
anorexia, diarrhoea or constipation. They may also cause headache, dizziness and somnolence.
Other side effects include male sexual dysfunction and palpitations.109 These side effects are
more pronounced in patients using alcohol and in patients on MAOIs. Therefore, the use of
SNRIs with other antidepressants is discouraged.
The atypical antidepressant agents used for treatment of atypical depression include bupropion,
mirtazapine, and trazodone. MAOIs and SSRIs are also used for treatment of atypical
depression. These drugs are effective as monotherapy in major depressive disorder, and in
58
combination therapy for more difficult to treat depression. In addition these drugs have less
toxicity in overdose and less side effects.109,112
Some medications are used to augment antidepressant agents in some clinical conditions like
patients with coexisting medical illnesses and in patients with resistant depression.109 These
medications include dextroamphetamine and methylphenidate, which functionally are central
Nervous system (NS) stimulants.109 Dextroamphetamine has been proven effective in
medically ill patients that are depressed.109
Liothyronine, a synthetic salt of endogenous thyroid hormone may convert non-responders to
antidepressant agents to responders by increasing receptor sensitivity and enhancing the effects
of TCAs.
St John’s wort (Hypericum perforatum) is a natural herb used in the treatment of mild to
moderate depressive symptoms. St John’s wort acts as an antidepressant by increasing the
concentrations of CNS neurotransmitters such as serotonin. It is often taken with meals to
prevent gastrointestinal upset.111
Relief of symptoms and a sense of well-being often characterize recovery from ill health. Use
of PHQ 2 during pharmacotherapy could aid in measurement of improvement from depression.
The patients on pharmacotherapy for depression could also use PHQ 2 as an objective measure
of recovery.
2.5.4.1 Duration of Use of Antidepressants
The choice of antidepressant medication is guided by its safety and tolerability, which may aid
in compliance. Physician familiarity, patient education and anticipation of adverse effects also
influences the type of antidepressant to be used.109 The previous treatment with antidepressants,
59
patients preference and whether or not remission was achieved is considered as well. For a
clinical response to become evident at required therapeutic doses and adherence, a treatment
duration of 4-12 weeks is usually required. Treatment should be altered if the patient does not
have an adequate response to pharmacotherapy within 6-8 weeks. When satisfactory response
is achieved, treatment is to be continued for 4-9 months, and gradually tapered over 4-
6weeks.81 The individual’s response to treatment, presence or absence of relapse episode,
occurrence of side effects, previous treatment response, and concurrent physical illness may
determine the duration of treatment.81,109 The American Psychiatric Association recommends
an individualized patient treatment plan based on the clinical assessment, presence of other
disorders, stressors, patient preference, and reactions to previous treatment.109
2.5.4.2 Resistant Depression
Resistant depression is depression that is resistant or refractory when treatment with at least
two different classes of antidepressants adequate in dose, duration, and compliance fail to
produce a significant clinical improvement as a result of the presence of other co-
morbidities.111 Causes of resistant depression include systemic organic illnesses, recreational
or illicit drugs and psychosocial stress.81,112 When a patient therefore is not responsive to
treatment with at least two classes of antidepressants, evaluation for other causes of depression
is expected.10 Patients on medications such as opiates, catecholamines, anticonvulsants,
amphetamine as well as patients taking alcohol or cocaine are at risk of developing resistant
depression.112 Similarly, disease conditions such as heart failure, myocardial infarction and
cardiomyopathy are also contributory to the development of resistant depression. Metabolic
and endocrine problems such as hyperthyroidism, hypothyroidism, diabetes mellitus,
Cushing’s disease and Addison’s disease; thiamine deficiency, vitamin B12 deficiency and
folate deficiencies have also been linked to resistant depression. Hypopituitarism,
60
hypoparathyroidism, hepatic diseases, hyponatremia and hypokalemia have all been found to
be contributory to resistant depression.111 Malignancies, chronic infectious diseases like human
immunodeficiency virus, tuberculosis, encephalitis, infectious endocarditis, and syphilis are
causes of resistant depression as well.111
In such patients, evaluating for, and establishing the cause of the resistance to treatment is done
at first. Treatment for the co-morbid medical condition is then maximized to reduce its effects
on depression. The patients’ antidepressant medication is then optimized, augmented, or
switched to another class altogether while effective psychotherapy is continued.111 The routine
use of PHQ 2 in patients with resistant depression will give an objective assessment of the
degree and periods of resistance. This will as well sound early alarm on possibility of resistance
in depressed patients.
2.5.5 Electroconvulsive Therapy
Electroconvulsive therapy (ECT) is used for treatment of depression where there is need for a
rapid antidepressant response, established failure of drug therapies, or in patients with risk of
suicide.81 ECT stimulation techniques include Transcranial Magnetic Stimulation (TMS), for
treatment of resistant major depression; and Vagus Nerve Stimulation (VNS) for use in adult
patients who have failed to respond to adequate medication and ECT treatment regimens. The
stimulation device requires expertise skills in its application.109
2.6 DEPRESSION MANAGEMENT OUTCOME IN PRIMARY CARE
Despite the reported poor recognition rates of depression, the comprehensive, bio-psychosocial
patient assessment and wholistic management makes depression treatment in primary care
effective.10,113 The accessibility to the Primary Care staff, early recognition of the condition
and integrated wholistic management adds to patient satisfaction with improved outcomes.115
61
The patients are closer to primary care facilities and primary care staff in their community than
the Specialist, making primary care more accessible and more cost-effective.114 In addition,
patients with other disease conditions presenting to primary care settings may have co-morbid
depression.116 The Family Physician provides longitudinal care to the patients and this allows
the physician and the patient to be partners in the management of the disease condition over a
long period of time.65 The Family Physician can also mobilize social support, guidance and
counseling for the patient and his or her family. Referral to a specialist is made where
necessary.65 These promote collaborative and integrated care needed for the management of
depression with improved outcomes.65, 117
In Nigeria, a programme aimed at integrating mental health into Primary Health Care, (PHC)
showed that frontline PHC workers had a marked improvement in the knowledge and skills for
identification and treatment of persons with depression and increased referral to specialist.118
Primary Health Care workers have been found to successfully provide evidence-based
depression care with correspondent treatment outcomes.119 Another study demonstrated that
psychotherapy given to outpatients, could reduce symptoms among patients with depression
attending general outpatients’ department.120 Psycho-education has been similarly provided to
outpatients in primary care settings.121 PHC remains an essential tool for effective and
accessible health care delivery capable of meeting the demands of the high number of
depressed patients.69 As a result, the overall cost of care, transport, and the time spent in
assessing care are reduced, giving the patient more satisfaction.69
Treatment of depression in primary care using behavioural therapy has been found to be as
effective as pharmacotherapy.122 Behavioural therapy has been given successfully by primary
care workers.122 Cognitive behavioural therapy and interpersonal therapy are also used for
developing personal coping mechanisms, which help to overcome depression.123
62
2.7 PREVENTION OF DEPRESSION IN PRIMARY CARE
Evidence from randomized trials have demonstrated that preventive interventions can reduce
the incidence of new episodes of major depressive disorder by approximately 25%, and by as
much as 50% when preventive interventions are offered in stepped-care format.124,125 These
interventions could be done to the entire population/community or to high risk groups or
individuals.126,127 Universal prevention which targets a whole population, aims at addressing
the determinants of mental health such as social, cultural, economic, political and
environmental factors.126 Other considerations are national policies, social protection, living
standards, working conditions, community and social support.126 In view of the usefulness of
preventive measures, PHQ 2 could be used for diagnosis of depression among high risk
individuals and in general population interventions.
2.7.1 Preventive Measure Categories
These preventive measures could also be considered as primary, secondary or tertiary
prevention.85 In primary prevention, the occurrence of depression is targeted to be stopped in
people without the disease condition, while in secondary prevention the people with depression
but are asymptomatic are identified through screening.85 Early intervention is then
administered to prevent the manifestation and subsequent progression of the disease. In tertiary
prevention, the complications of depression are minimized.85 The primary preventive measures
include the universal strategies targeted at a whole population, the selective strategies directed
at a group of people at risk, and the specific or individual strategies aimed at people with risk
factors for depression.85,119
2.7.2 Universal Prevention of Depression
63
To ensure a healthy society, governments should be committed to the provision of social
amenities, security and universal health coverage to citizens.126 These also include the right and
accessibility to education, employment, and housing.118 Governments at all levels and the
various stakeholders in disaster management, conflict resolution, and humanitarian
emergencies should provide a wholistic approach to the needs of victims of such crises.126
Health system resources should be adequately provided by the government to make treatment
accessible to the depressed patients. The needed health personnel and requisite knowledge and
skills to recognize and appropriately treat depressed patients should be provided by the
government because the number of specialized and general health workers dealing with mental
health especially in low-income and middle-income countries is grossly insufficient.126
2.7.3 Selective or Targeted Prevention of Depression
The goal of the comprehensive mental health plan is to promote mental well-being, prevent
depressive disorders, provide care, enhance recovery, and reduce mortality, morbidity and
disability for persons with mental disorders.126 This is provided in the community where the
depressed patients live.126 Treatment of depressed patients is expected to be integrated into
general hospitals and primary care.
In this approach, high risk groups, individuals and patients with sub-threshold symptoms are
targeted and screened for depression.125 Because people with multiple morbidities also present
with similar symptoms of depression, the preventive interventions which aim at promoting
health through early detection and management, have proven to be effective in reducing onset
of depression.125, 126
Methods or processes proven to be effective in targeted prevention of depression in primary
care settings include; health educational, psychotherapeutic, pharmacological, lifestyle or self-
64
care and nutrition interventions.100 Other interventions are opportunistic screening,
bibiliotherapy, minimal contact psychotherapy, and cognitive behavioural therapy. 124, 125
The early identification and management of depression in targeted populations has been
recommended by Somoye and colleagues, from a study among commercial bank workers
carried out in the south-western part of Nigeria.41
2.7.4 Opportunistic Screening
This is the general practice stepwise approach whereby persons with sub-threshold depression,
are opportunistically screened.102 Those who screen positive for depression go through further
diagnostic testing in a clinical interview to exclude those who meet criteria for depression, and
those who do not.127 This approach helps to recognize patients with symptoms suggestive of
depression at any time they are in contact with care givers.127 Opportunistic screening promotes
health and wellbeing when patients receive treatment early.127
2.8 Lifestyle and Nutrition Interventions
Inflammation and oxidative stress contribute to both somatic and depressive illnesses.128 For
instance, consumption of a Mediterranean-style diet, rich in antioxidants, vitamins, minerals
and fibre, is associated with reduced systemic inflammation, whereas unhealthy dietary
patterns, are associated with increased systemic inflammation and depression.128
Physical activity is associated with reduced markers of systemic inflammation and may have
direct anti-inflammatory effects, while smoking increases inflammation and oxidative stress
predisposing to depression.128
65
Obesity and depression share a bidirectional relationship, with obesity potentially contributing
to depression via increasing the level of circulating pro-inflammatory cytokines, and
depression predisposing to the accumulation of excess adipose tissue.128 Considering that
individual genetic factors, mental, physical illnesses and lifestyle form a triad that preventive
measures should target.127 Health care workers should therefore, not limit interventions to
improving mental health but also attend to the physical health care needs, and vice versa.126
2.8.1 Psychotherapy
Several mindfulness/behavioural strategies have been developed to prevent relapse and
recurrence of depression.129 The strategies that have been found efficacious are cognitive-
behavior therapy, problem-solving therapy, and social skills training.129 Other proven
strategies include brief dynamic therapy, emotion-focused therapy, family-focused therapy,
interpersonal social rhythm therapy and psycho-education.85,129
These interventions are considered efficacious because, when applied, they can achieve
reduction of acute symptoms or they can prevent subsequent relapse or recurrence of
depression.129 Psychotherapeutic treatment of children and adolescents incorporate a parent or
a family member.89 In mild cases, psychosocial interventions are often recommended as first
line treatments and combining psychotherapy with antidepressant medication may be more
appropriate for patients with moderate to severe major depressive disorder.89
However, the several sessions and contacts needed by patients to access psychotherapy may
cause poor compliance, and worsening of the patients’ clinical state.83
2.8.2 Minimal Contact Low Intensity Psychotherapy
66
This strategy combines psychotherapy using self-help manuals with instructions on cognitive-
behavioural mood management. The manual also contains homework assignments aimed at
cognitive restructuring and activity scheduling to increase pleasant activities and relaxation.127
In minimal contact psychotherapy, face-to-face contact between patient and doctor is
minimized through communication and telephone calls to evaluate the successful use of the
manual and patients’ response to treatment.127 Easily applied tools such as PHQ 2 could be
used to assess symptoms of depression and possible improvement. When the respondent
reports absence or improvement of symptoms but there is no actual clinical improvement,
depression may worsen.127 Clinical consultation with the caregiver at intervals is needed to
appraise success of the therapy. Use of PHQ 2 could be a guide to enhance decision on the
need for possible consultation.
CHAPTER THREE- STUDY METHODOLOGY
3.1 STUDY LOCATION
This study was conducted at the General Outpatient Clinic (GOC) of the General Out Patient
Department (GOPD) of Bingham University Teaching Hospital, Jos. The Bingham University
Teaching Hospital (BHUTH), formerly known as ECWA Evangel Hospital, is located in the
cosmopolitan city of Jos, North Central Nigeria. It is a 250 bed hospital providing primary,
secondary and tertiary health care services. It also serves as a Teaching Hospital for medical
students of Bingham University, College of Medicine and Health Sciences. The hospital serves
patients from Plateau state and other neighbouring states of Bauchi, Kaduna, and Nassara with
urgent care services arising from natural and man-made disasters. It provides care for most
categories of patients ranging from Paediatrics, Obstetrics and Gynaecology, Medicine and
67
Surgery at respective departments. The Outpatient Department serves as the ambulatory care
unit where most outpatients receive care.
The hospital’s Anti-Retroviral Therapy (ART) clinic provides care for People Living With
HIV/AIDS (PLWHA) in terms of Voluntary Counselling and Testing (VCT), consultations,
enrolment for medication, counselling, health education, lifestyle modifications.
The hospital has a Vesico-Vaginal fistula centre that provides surgical care and rehabilitation
of women with obstetric fistula from the North Central and North Eastern regions of Nigeria.
BHUTH receives referrals from neighbouring Nassarawa, Kaduna, Bauchi, Gombe, as well as
Adamawa and Yobe States.
The hospital has also provided care for several patients with viral haemorrhagic fever
especially Lassa fever, since the early 1970’s.
The Family Medicine department of the hospital provides training for medical students and
Residents in Family Medicine. It has been accredited by both the National Postgraduate
Medical College of Nigeria and the West African College of Physicians. The department has
31 Doctors various ranks. It has ten Consultants and trainers, spanning from the level of lecturer
1 through to Associate Professor. There are also 20 Doctors at the level of senior Registrars,
junior Registrars and Medical officers.
The hospital has an average of 75 Doctors comprising of about 43 consultants in various
specialties, 20 Residents and 12 House-officers.
3.2 STUDY AREA
The study was done at the Bingham University Teaching Hospital, General Out-patient clinic,
(GOPC). The GOPC offers clinical services to the adult outpatients. It has consulting rooms, a
68
patient waiting area and a nursing station where vital signs, weight, height and waist
circumference of patients are taken. On daily basis, average approximately eight doctors offer
services to the patients at GOPC. The Hospital has a Medical Records Department which serve
as point of entry to patients.
3.3 STUDY POPULATION
The study was conducted among adult patients aged 18 years and above that were newly
registered at the GOPD who met the inclusion criteria.
3.4 STUDY DESIGN
The study was an analytical study of the mean depression score of Patient Health Questionnaire
2, (PHQ 2) tool compared to the Patient Health Questionnaire 9 (PHQ-9), of selected patients
over the period of study. The participants were recruited through systematic random sampling.
Only literate patients were selected. The literacy rate in Jos where the study conducted had
been reported to be 78%, according to a 2010 survey.130
3.5 SAMPLE SIZE
The size of the sampled population studied was obtained from the formula by Bernard
Rosner’s, 131: The formula for calculating similar means,
N= (Zα +Zβ) 22(S)2/(d)2
Where
N= Required minimum sample size
Zα= Standard alpha error units from the mean (for α= 0.05, at 95% confidence level, Zα =
1.96)
69
Zβ=Standard beta error units from the mean, (for usual 20%, β error, β=0.84)
S2= Expected variance, determined from a study of PHQ 2, at Tilburg University, the
Netherlands.109 (S=1.42). This was the closest study reported variance found by the researcher.
d= smallest clinically important difference that differentiates depressed from not depressed
patients score, put at 0.5
= (1.96+0.84)2 2(1.42)2 / (0.5)2
= (2.8)2 2(1.42)2/0.25
= (7.84) 2(2.01264)/0.25)
= (7.84) (4.02528)/0.25
= 31.5581952/0.25, =126.23
Considering an non-response rate of 5% of 126, which is 7; the total sample size was 133
3.6 SAMPLING METHOD
The GOPD attends to approximately 70 to 120 patients daily, registers 20 to 30 new patients
every day and about 400 new cases per month. (Departmental monthly report). From an
average number of 100 newly registered patients expected weekly, 600 new patients were
expected to be seen in 6-8 weeks of the proposed study period. Considering the sample size of
133, the sample interval was 600/133 which is approximately 4.
Over a period of 8 weeks between August and September, 2015, when the study was conducted,
the total number of newly registered literate patients were 655. Considering the sample size of
133 and a sampling interval of 4, every fourth newly registered patient was enrolled for the
study. Using a table of random numbers, the first number was selected from 1 to 4. The selected
number was tallied to the corresponding order of presentation of newly registered patients. The
70
subsequent patient was selected by addition of the sampling interval (4) to the first selected
number until the required sample size was obtained. Patients selected that was not literate were
differentially excluded from the study.
Each participant was administered PHQ-2 by the Researcher assistant 1. The patient then
moved to see Researcher and the PHQ 9 administered. The reported PHQ 2 and PHQ 9 by each
patient were then collected and entered into SPSS version 20 ( SPSS 20 )
for analysis. (Newer SPSS version 20 was available at the time of compilation of the results,
instead of earlier version 17 proposed). PHQ 2 was administered by the Research assistant 1
and PHQ 9 by the Researcher to avoid bias in the study.
Patients’ selection was based on the following criteria.
3.7 INCLUSION CRITERIA
i. Patients aged 18 years -65 years
ii. Newly registered patients
iii. Literate patients (patients who could read a daily newspaper and who also could write)
iv. Patients that consented for the study
3.8 EXCLUSION CRITERIA
i. Patients with altered mental status (Not oriented in time, person and place).
ii. Obviously sick patients (Acutely ill looking patients)
iii. Patients who are not literate
3.9 STUDY PROTOCOL
3.9.1 Pilot study
71
Three Research Assistants I, II and III were trained by the Researcher on the study protocol
and the use of the tools after the thorough study of the protocol by the researcher. Research
Assistants I and II were Senior Registrars whose levels of training were the same as the
Researcher. Research Assistant III was a Chief Nursing Officer serving in the GOPD.
Usability of questionnaire was also tested on patients during the orientation process. Proper
entry of Bio-data by the Medical Record staff was advocated. The whole research protocol was
repeated on three alternate days (three days), a week prior to the study. On each day, five new
patients were administered the research tools in the manner the study was to be done. A total
number of 15 patients were pretested. The ease of understanding the questionnaire, the
corresponding responses and the movement from one research staff to the other and the
subsequent consultation for primary reason for encounter at consulting room 2 was satisfactory.
3.9.2 Study flow
At the medical records department, Patients were registered at the Medical Records
Department and obtained a hospital card, bearing a hospital number and their bio-data. From
there they were directed to the nursing station.
At the nursing station, each participant’s vital signs were taken by Research Assistant III. The
blood pressure was taken using Accoson mercury sphygmomanometer, manufacturer
(Pharmtex, Singapore). Each patient was allowed to sit for approximately 5 minutes, relaxed
in a chair. An adult cuff appropriate for the person’s arm, which was approximately 75% of
the left arm, was wrapped round the arm. The radial pulse was then palpated and the
sphygmomanometer inflated by gentle squeezing of the inflatable bulb. The pressure was then
produced by inflating the bladder of the cuff which compressed the brachial artery thereby
occluding it. The pressure at which the radial pulse disappeared was noted as the systolic blood
72
pressure by palpation. The bladder was then deflated. Placing the diaphragm of a stethoscope
over the radial artery at the cubital fossa, the sphygmomanometer was once more inflated until
its pulsation was lost. The deflation valve was gently released allowing the pressure to reduce
gradually. The first sound made while deflating the cuff was taken as the systolic blood
pressure. The cuff was continually deflated until the sound disappeared. This corresponded to
the diastolic blood pressure. The values were recorded.
The pulse rate was taken by palpation of the radial pulse and the respiratory rate by palpating
abdominal movement during respiration.
The temperature was taken with the aid of an axillary clinical mercury thermometer (HI Proof,
USA) and the values recorded in degree centigrade (oC). After each patient, the thermometer
was cleansed with methylated spirit, shaken so that the mercury returned to the bulb of the
thermometer beyond the zero point. It was then gently placed in the axilla of every subject and
kept for 3 minutes (according to manufacturer’s prescription) then the thermometer was
removed and the temperature was read and recorded.
The weight and height were measured with a “Weighing and Height Scale” (RGZ 160, Maney,
China). The machine was calibrated by test-weighing two different patients on it. Patients were
asked to remove their cell phones and other weights on them including their outer clothes and
shoes, while privacy was maintained by providing a cover. They were then asked to stand on
the “Load Platform” of the machine until the pointer stood still. The value at that point was
read on the scale and recorded in kilograms (Kg).
The height was measured with the patient standing without cap or other headgear on the
platform of the machine with their back towards the vertical rule of the stadiometer. The rule
73
was then stretched out to the patients’ exact height with the horizontal paddle resting flat on
top of the head. The corresponding reading in metres was recorded.
Preselected patients (patients whose assigned number tallied with the number at the OPD
presentation of that day) were briefed about the essence and procedure of the study
74
STUDY FLOW CHART
MEDICAL RECORDS DEPARTMENT
Patient got registered and obtained card
NURSING STATION
Interaction with Research Assistant III, Patients vital signs taken
WAITING AREA
Interaction with Researcher/Consent form administration
Interaction with Research Assistant 1, Administration of PHQ 2
CONSULTING ROOM 1
Interaction with Researcher, Administration of PHQ 9
CONSULTING ROOM 2/Interaction with Research Assistant II,
Patients got consultation for his/her primary reason for encounter including
the results of depression score and appropriate intervention
75
and consent to participate requested. The patients who voluntarily agreed to take part in the
study were then directed to the waiting area to meet Researcher and the Research Assistant 1.
At the waiting area
The details of the information sheet and the consent sheet were discussed with every
participant. The participants were then allowed to choose to enroll or decline in the study. The
participants who consented to the study were then given the consent form, which they signed.
They were then given the PHQ 2 and Socio-demographic report form by Research Assistant 1,
which they filled appropriately in accordance with their experience of the symptoms.
Consulting room 1
At consulting room one, the participants were given the PHQ 9, which they completed. The
scores of the PHQ 9 were entered in the hospital record. The Researcher then directed the
patients to consulting room 2.
Consulting room 2
At Consulting Room 2, the participants met the Physician (Research Assistant II), who then
consulted the patients for their primary reason for encounter, that day. The appropriate
management based on the PHQ 9 score, was incorporated, as required into the treatment of the
primary reason for encounter.
Duration of the study
76
The study was conducted over a period of eight weeks between August and September, 2014.
Ethical considerations
Ethical approval to conduct the study was obtained from the BHUTH Research and Ethics
Committee (appendix I). Written consent was obtained from each individual. (Appendix II).
3.10 TOOLS FOR DATA COLLECTION.
The PHQ 2 and the PHQ 9 were used for collection of data. Details of each tool were described
separately in section 3.10.1 and 3.10.2.
3.10.1 The Patient Health Questionnaire 2 (PHQ 2)
The PHQ 2 score ranges from 0, 1, 2 and 3 for each of its item questions. Score ‘0’ signifying
“not at all” meaning the symptom is not present in the subject at all. A score of ‘1’ represents
77
“several days” denoting the occurrence of the symptom on several days of the week, but not
more than half of the days of the week. A score of ‘2’ denotes presence of the symptoms in the
subject for “more than half of the days” of the week. A score of ‘3’ means “nearly every day”
meaning the symptom is present in the subject for almost every day of the week.11, 132
Its diagnostic score ranges from 0-6, each item with score range of 0-3. Patients who score less
than 3 (scores 0-2) are categorized as not depressed. Patients with score of 3 and above (3-6)
were considered depressed.
Patients were asked to complete the PHQ 2 alongside the PHQ 9 as stated above. Results of
the PHQ 2 based on the total score was then computed to give appropriate screening diagnosis.
3.10.2 The Patient Health Questionnaire 9 (PHQ 9)
The Patient Health Questionnaire 9, (PHQ 9) is a brief tool used to diagnose, monitor remission
and measure the severity of depression.8 The PHQ 9 consists of nine diagnostic symptom
criteria used in DSM IV.8 Each of the nine items on PHQ 9 scores from 0, 1, 2, and 3 as in the
PHQ 2. A score of zero (0) signifying “not at all” meaning the symptom is not present in the
subject at all. A score of ‘1’ represents “several days” meaning presence of the symptom in
the subject on several days of the week but not more than half of the days of the week. A score
of 2 means the presence of the symptoms for “more than half of the days” of the week, while
the score of 3 means “nearly every day” meaning the symptom is present almost every day. Its
sum up to 27. Each of the nine items scores 0-3, providing a 0-27 depression score.
A score of 0-4 is not significant, categorized as no depression in the subject. Score of 5-9 means
mild depression, suggesting that the subject is mildly depressed. A score of 10-14 represents
moderate depression, signifying that the subject is having moderate depression. A score of 15-
78
19 means “moderately severe” depression and corresponds to occurrence of moderately severe
depression in the subject. A score of 20-27 connotes severe depression.
The PHQ 9 was administered to all the subjects in the study as a diagnostic standard. The
corresponding diagnostic significance of the scores was computed and compared for the two
tools, PHQ 2 and PHQ 9.
3.11 DATA ANALYSIS
The data collected was kept and safeguarded in a bag and entered into SPSS version 20, on a
personal computer. Data quality check was run each time data was imputed, to ensure that all
the collected data was accurately entered. Details of the patients seen over the study period,
number of participants meeting inclusion criteria, participants excluded or declined consent
and incompletely filled questionnaires are presented in chapter four.
Both the computer and the data on SPSS were pass-worded, and kept confidential. The
sensitivity, specificity; positive predictive values and the negative predictive values of the PHQ
2 were analyzed using the PHQ 9 as the gold standard.
From the data, the proportions of subjects diagnosed positive for depression on PHQ 2 and
PHQ 9 were collated and compared. The proportion of subjects diagnosed negative on PHQ 2
and PHQ 9 were also collated and analyzed. The diagnostic properties of the two tools were
also analyzed. Using PHQ 9 as the gold standard for the diagnosis of depression, and
comparing the scores of PHQ 2, further analyses was done to find out the patients who were
depressed on the PHQ 9 (Gold Standard) and were as well depressed on PHQ 2. These subjects
constitute the True Positives (TP). The subjects found not depressed on PHQ 9 and were as
well found not depressed on PHQ 2 were the True Negatives (TN). Those reported positive for
depression on PHQ 2 and were ruled out as having no depression were the False Positives (FP),
79
while those diagnosed negative on PHQ 2 but were found depressed on PHQ 9 were the False
Negatives (FN).
For the diagnostic testing, results were analyzed based on the following:
Sensitivity: (Probability that a subject is diagnosed as depressed using the PHQ 2 instrument
when the subject is truly depressed) =
TP/ (TP+FN) = a/(a+c)
Specificity: (Probability that a subject is identified as not being depressed using the PHQ2
instrument when the subject is truly not depressed) =
TN/ (TN+FP) = d/(b+d)
PPV: (Positive Predicted Value Probability of being depressed when the PHQ 2 tool test
result indicates depression) =
TP/(TP+FP)=a/(a+b)
NPV: Negative Predicted Value (The probability that that a subject is not depressed when the
PHQ 2 diagnostic tool indicates the subjects as not being depressed) =TN/(TN+FN)=d/(c+d)
The harmony of the two tools, also called Diagnostic Accuracy (DA) is the ratio of the subjects
absolutely diagnosed positive (TP) and those absolutely diagnosed negative (TN) to the entire
subjects studied (Total Sample).
DIAGNOSTIC TEST RESULT DISEASE STATUS
Present Absent
Positive a (TP) b (FP)
Negative c (FN) d (TN)
Total N1 = a+c N2= b+d
80
The diagnostic accuracy is thus calculated, 133
DA= TP+ TN/ TP+TN+FP+FN
3.12 Cost and Funding of the Research
The study cost approximately ₦40,000, used for buying stationery and producing the books,
the cost of producing the questionnaire and carrying out the various activities involved in the
research, the process of data collection, analysis and generation of the results were borne by
the researcher and token given to research assistants.
CHAPTER FOUR: RESULTS
STUDY FLOW
Patients Seen in OPD during Study
2,336
Subjects Excluded 504
1. Subjects Excluded by
selection process= 412
2. Excluded by Age = 26
3. Subjects obviously
sick = 66
Number meeting inclusion criteria
655
81
Table 1: PERFORMANCE
CHARACTERISTICS OF PHQ 2
4.1 SOCIO-DEMOGRAPHIC CHARACTERISTICS OF RESPONDENTS
Most of the respondents were male (56.8%), within the age range of 26-47 years and married.
The majority had at least primary or secondary school education. Most of the respondents
Subjects consent sought from
151
Declined consent 8
Subjects that consented
143
Selected for Study
143 Incomplete/wrongly
completed
questionnaire 10 Completed Study
133
82
were either artisans or manual workers and majority had an average monthly income of
₦30,000. Other details are as displayed in Table 1.
Performance characteristics Value
Prevalence rate 42.1%
Sensitivity 80.4%
Specificity 81.7%
Positive Predictive Value (PPV) 73.2%
Negative Predictive Value (NPV) 87.01%
True Positive 41
True Negative 67
False Positive 15
False Negative 10
False Positive Error Rate 0.183
False Negative Error Rate 0.196
Likelihood Ratio Positive (LR+) 4.393
Likelihood Ratio Negative (LR-) 0.2400
Diagnostic Odd Ratio 18.31
Accuracy (Diagnostic Accuracy) 81.2%
Area Under the Receiver Operating Curve (AUC) 0.832
Youndex index 0.621
83
TABLE 2: SOCIO-DEMOGRAPHIC CHARACTERISTICS OF RESPONDENTS, N=
133
Variables Frequency Percentage
Sex
Male 75 56.4
Female 58 43.6
Age Group
18-25 20 15.0
26 – 36 30 22.7
37 – 47 40 30.0
48 – 58 26 19.5
59 – 65 17 12.8
Educational Qualification
Primary 32 24.0
Secondary 44 33.0
Tertiary 53 40.0
84
Non-formal education 4 3.0
Marital Status
Single 30 22.6
Married 75 56.4
Separated 17 12.8
Divorced 7 5.2
Widowed 4 3.0
Occupation Frequency Percentage
Variables
Manual Worker 33 24.8
Artisan 26 19.5
Professional 34 25.7
Trading 26 19.5
Non Specified 14 10.5
Income
0-10,000 Naira 38 28.5
10,001-20,000 Naira 25 19.0
20,001-30,000 Naira 26 19.5
30,001-40,000 Naira 18 13.5
>40,000 Naira 26 19.5
4.2 DISTRIBUTION OF DEPRESSION RISK FACTORS AMONG RESPONDENTS
The factors likely to be associated with depression in the subjects are hypertension, natural
disasters and sectarian violence. Details of associated factors are presented in the table below.
TABLE 3: DISTRIBUTION OF RISK FACTORS AMONG RESPONDENTS
Characteristics of Subjects Frequency Percentage
DISEASE CONDITIONS
Hypertension 20 15.0
Thyroid disease 2 1.5
Malignancy 1 0.8
No identifiable morbidity 110 82.7
Total 133 100.0
STRESS EVENTS
Natural disasters 21 15.8
85
Disengagement from work 9 6.8
Sectarian Violence 25 18.8
Family Conflict 4 3.0
No identifiable stress event 74 55.6
Total 133 100.0
MEDICATIONS
Diazepam
Amlodipine
3
3
2.2
2.2
Carbamazepine
1 0.8
Amitriptyline 1 0.8
Non-Specified 125 94.0
Total 133 100.0
PHYSICAL CHARACTERISTIC VARIABLES OF RESPONDENTS
The mean Body Mass Index (BMI), of respondents was 25.2±5.2Kg/m2 with minimum BMI
of 19.1Kg/m2 and maximum BMI of 39.43Kg/m2.
The mean Systolic Blood Pressure (SBP) was 117.1±21.9mmHg, with the lowest SBP of
90mmHg and highest SBP of 190mmHg.
The mean Diastolic Blood Pressure (DBP) was 74.3±12.7mmHg with the lowest DPB of
60mmHg and the highest DPB of 100mmHg.
The mean age of respondents was 40.7±13.5 years with the minimum age of 18 years and the
maximum age of 65 years.
4.3 DIAGNOSTIC OUTCOMES USING THE PHQ 2
The respondents diagnosed by PHQ 2 as depressed, were 56, making 42.1 % while 77 were
not depressed. Details are as displayed in the table below.
TABLE 4: DIAGNOSTIC OUTCOMES USING THE PHQ 2.
86
PHQ 2 Category Frequency Percentage
Depressed 56 42.4
Not Depressed 77 57.9
Total 133 100.0
4.4 DIAGNOSTIC OUTCOMES USING PHQ 9
The respondents diagnosed positive for depression using PHQ 9 were 51 (38.3%). Those not
depressed were 82 (61.7%). The commonest category of depression was moderate depression
with a prevalence of 19.7%, details of the results are as displayed in the table below.
TABLE 5: DIAGNOSTIC OUTCOMES USING PHQ 9
PHQ 9 Class FREQUENCY PERCENTAGE
(%)
Not Depressed (0-4) 82 61.7
Mild Depression (5-9) 15 11.3
Moderate Depression (10-14) 26 19.5
Moderately Severe Depression(15-19) 8 6.0
Severe Depression(20-27) 2 1.5
87
Total 133 100.0
PHQ 9 Category FREQUENCY PERCENTAGE
(%)
Depressed 51 38.3
Not Depressed 82 61.7
Total 133 100.0
4.5 THE RESULTS OF PHQ 2 DIAGNOSTIC CHARACTERISTICS COMPARED
TO PHQ 9
The number of subjects diagnosed as depressed by both PHQ 2 and PHQ 9 were 41 while the
subjects diagnosed non-depressed were 10. Other details as in the table below.
TABLE 6: COMPARISON OF PHQ 2 CHARACTERISTICS WITH PHQ 9
The True Positive was 41, False Positive 15, True Negative 67, and false negative 10.
PHQ 2 Results Gold Standard, PHQ 9
Depressed Non-Depressed Total
Depressed
(Test Positive)
41
15 56
Non-Depressed
(Test Negative)
10 67 77
Total 51 82 133
88
The False Positive Error rate =TP/FP + TN, = 15/82, = 0.183
The False Negative Error rate= FN/TP + FN, = 10/51, = 0.196
Prevalence, on PHQ 2 =56/133 = 42.1%
Prevalence, on PHH 9 = 51/133= 38.3%
4.6 DIAGNOSTIC CHARACTERISTICS OF PHQ 2
The subjects diagnosed depressed on PHQ 2 were 56. The sensitivity of PHQ 2 was 80.4% and
the specificity was 81.7%. Other details of the characteristics are shown in the table below
TABLE 7: DIAGNOSTIC CHARACTERISTICS OF PHQ 2
Sensitivity 80.4%
Specificity 81.7%
Positive Predictive Value 73.2%
Negative Predictive Value 87.01%
Diagnostic Accuracy 81.2%
Sensitivity of PHQ 2 was 80.4% and the Specificity was 81.7%. The Positive predictive
value was 73.2% and the Negative predictive value, 87.01%.
DIAGNOSTIC ACCURACY
Diagnostic Accuracy (81.1%) is defined as the proportion of correctly diagnosed or
classified subjects among all subjects.133
Diagnostic Accuracy (DA) = TP+ TN/ TP+TN+FP+FN
89
DA= 41+67/41+67+15+1 =108/133, = 0.812, = 81.2%
FIGURE 1
THE AREA UNDER THE CURVE (AUC)
Figure Area Under the Curve was 0.832, demonstrating the good discriminatory ability of
PHQ 2.
90
LIKELIHOOD RATIO (LR)
The Likelihood Ratio (LR) is the ratio of the expected test result (positive or negative), in the
subjects with depression to the subjects without depression.
Mathematically, LR+ = Sensitivity/(1-Specificity).
From the test results, The Positive Likelihood ratio is thus,
LR+ = 0.0804/(1-0.817)
= 0.804/0.183
=4.393
Similarly, the Likelihood Ratio of a negative test (LR-),
LR- = (1-Sensitivity)/Specificity
Also from the test results,
LR- = 1- 0.804/0.817
= 0.196/0.817
= 0.2400
Area Std. Error Asymptotic
Sig.
At 95% Confidence Interval
Lower Bound Upper Bound
.832 .038 .000 .759 .906
91
DIAGNOSTIC ODD RATIO
The Diagnostic Odd Ratio (DOR), expressed mathematically as DOR= (TP/FN)/ (FP/TN), is
the ratio of the odds of positivity of the subjects with the disease (depression), relative to the
odds of subjects without the disease (non-depressed)
DOR = (41/10)/ (15/67) = 41/10*67/15
DOR = 2,747/150
= 18.31
YOUDENS INDEX (YI)
The Youdens Index expressed mathematically, is the sum of sensitivity and specificity of a
test from which 1 (one) is subtracted,
YI = (Sensitivity +Specificity)-1, expresses the performance of a test’s discriminatory power
YI is expressed as part of a whole number, with 0 signifying poorest performance and 1 as
the ultimate performance of a test.
YI= (0.804+0.817) -1
YI = 1.621-1
= 0.621
92
YI of 0.621 describes the accuracy of PHQ 2 to differentiate depressed from non-depressed
patients on a scale of 1, and is good for diagnosing depression.
CHAPTER 5: DISCUSSION
The PHQ 2 results in this study compared to the PHQ 9 which was used as a gold standard
indicates that PHQ 2 was suitable for screening depression in a primary care setting.
5.1 THE DEMOGRAPHIC CHARACTERISTICS OF THE RESPONDENTS
5.1.1 Sex Distribution of Respondents
Most of the respondents were male (56.4%) while 43.6% of the respondents were females. This
was similar to the findings of a study by Agbir et al, at Jos University Teaching Hospital
outpatient department, North-Central Nigeria which reported 58.8% males.66 Similarly a study
at an outpatient department of a tertiary hospital in Maiduguri, North- Eastern Nigeria reported
54.1% males.58 However, this pattern was different from a study done at an outpatient
department in Benin City, where 79.3% of the respondents were female.49 Similarly, Adeosun
et al, in an outpatient study of depression in Lagos, had respondents that were predominantly
female, 66.3%.39 There was no reported factor why females were more in that study. However,
another depression survey in an outpatient clinic in Enugu, reported 61.1% male
respondents.134
It is unclear why male respondents were relatively more in this study. This is in contrast with
the findings of a study on regional differences in the utilization of health care facilities, which
reported more women using health facilities than men.135 The fact that only literate adults were
included in this study might have disproportionately excluded women who are known to have
a lower literacy rate than men in the study environment.131
93
Most of the studies are similar in design, as they were comparative studies,48,49,58,66,67 and were
self-administered tool.49,67
5.1.2 Age Distribution of Respondents
The mean age of the respondents was 40.7± 13.5 years. The age distribution ranged from 18
years to 65 years. Respondents below 50 years of age constituted 69.9% of the study group.
This age distribution was also similar to that reported by Agbir et al, where 68% of their study
population were 59 years and below.68 The similarity of the population may not be unconnected
to the fact that both studies were done within Jos metropolis and within the same Local
Government Area of the state. Both studies were also done at outpatient’ clinics.68
This contrasts with a study done among inmates of Jos prison where 70.9 % of the population
was below 34 years.67 This population, however, is different from the general population in the
sense that most inmates are young.
Patients less than 60 years made up approximately 74.9% of the subjects studied by Wakawa
et al, to determine depression among outpatients at a tertiary health institution in Maiduguri.58
In a depression study at a tertiary health facility at Benin City, the population mean age was 35
±9 years, comparatively younger than the population in this study.136
5.1.3 Marital Status of Respondents.
94
More than half of the respondents, (56.4%) were married while 22.6% were single.
Cumulatively, less than half of the respondents, 43.6% were either single, separated, divorced
or widowed. Approximately 18% were either separated or divorced, while 3% were widowed.
This was similar to the study of Agbir et al, where 71.88% of the population were married.66
Wakawa et al in a study of depression among outpatients of a tertiary health facility in
Maiduguri, also reported that 59.1% of the subjects were married.58
These studies showed similarities in the marital status of the respondents because most of the
subjects were married. The married respondents being more in number than the unmarried
could be a reflection of the society where the study was carried out. More so that the study was
done amongst adults of marriageable age.
5.1.4 Educational Status of Respondents
The predominant educational status of the respondents was formal education in 97% of the
subjects, while only 3% had non-formal education but can read and write in English. The
respondents with tertiary education were 40.0%, making it the category with the highest
number of subjects. This might be due to the urban nature of the study location being a
metropolitan city.
This study was carried out among literate adults which makes the educational status of the
respondents different from that of similar studies done in Jos. For instance, Agbir et al in a
study of depression among diabetic out patients reported that 72.5% of the subjects were
educated.66 Still from a study done in Jos but amongst a confined population (Jos Prisons),
Arma’Yau et al, reported 82% of the subjects having formal education.67
5.1.5 Occupational Status of Respondents
95
Most of the respondents, 63.9% were self-employed in non-professional jobs. The respondents
employed in professional jobs were 25.6% Similar to the population of study by Agbir et al,
where 75.6% were employed, this study had 91% of the respondents employed. Shittu et al, in
a study at a Family Practice Centre at Ilorin, North Central Nigeria, had 72.5% of the
respondents who were reported to be self-employed.70 Similarly, in a study of depression at an
outpatient clinic in Benin City by Chikezie et al, 77.3% of the respondents were employed.48
considering that > 50% of the respondents had tertiary education but > 50% were employed in
non-professional jobs, relates to the fact that the subjects had one form of education or the
other, but a significant number of the respondents were either manual workers, artisans or
traders. This might be due to the high rate of unemployment, making many with formal
education to engage in non-professional occupations for livelihood.
5.1.6 Income Distribution of Respondents
The majority of the respondents, (67.3%) had an average income of ₦30,000 and below. That
is approximately $150 per month, and $5 daily income as at August 2015. This pattern of
income is higher than that reported in a study done at Zaria, where 80.2% of the subjects had
a daily income > $1.137
This level of income also corresponds to the nature of their occupation which were
predominantly manual workers, artisans and traders.
Such income no doubt impacts negatively on the quality of life of the subjects. This is because
of the cost of living in terms of prices of goods and services. Many people could not afford to
pay for health care services because of financial constraints. Others find it difficult to meet the
basic needs of food, shelter and clothing. This also predisposes people to psychological stress,
including depression.
96
5.1.7 Morbidity Distribution of Respondents
Approximately 82.7% of the respondents presented with non-specific morbidity, while 15.0%
had hypertension, 1.5% had thyroid disease and 0.8% of them had a malignancy. The “non-
specific” morbidity as used in this study refers to “all other disease conditions” not yet
diagnosed in the patient at the point of administering the two questionnaires (PHQ 2 and PHQ
9). In other words the “non-specific morbidity” also includes the primary reason for encounter
of the patients on the day the study was carried out. This was so because the questionnaires
were administered before consultation. Also the population of study was newly registered
patients who were less likely to know if they had a diagnosed disease condition. However, the
presence of disease condition in an individual or the society has been reported to be associated
with the occurrence of depression.138 The negative impact on health-related quality of life
caused by disease and disability have been attributed to depression in patients with disease
condition.138 Among the respondents who had no previous diagnosis of disease conditions
before participating in the study, some patients may have had depression because of other
factors or disease conditions which might only be diagnosed after consulting a physician.
5.1.8 Occurrence of Stressful Events in Respondents
More than half of the respondents, approximately 55.6%, did not have the experience of any
stressful event. Among the respondents who experienced stressful events, sectarian violence
accounted for 18.8% followed by natural disasters, 15.8%. Other events included
disengagement from work, 6.8% and family conflict 3%. The proportion of respondents who
reported stressful events were approximately 44.4%. This was lower than the proportion
reported in another study in Jos, by Tagurum et al, in which approximately 67.2% of the
respondents reported that they had experienced stressful events.139 The proportion was
97
similarly lower than the proportion of 48% reported in another study but higher than 23%
reported among victims of war and natural disasters.140,141
Plateau state, had experienced social unrest mostly in terms of ethno-religious conflict.139
Several victims of such sectarian violence were either maimed or disabled. Others experienced
loss of businesses, livelihoods, houses, properties, or their loved ones. Some of the victims
suffered both emotional and psychological trauma, while some others were displaced from
their residence making them internally displaced persons.139 The proximity of Jos to the North
East sub-region of Nigeria where violence from insurgency was most intense in Nigeria, made
it a recipient of fleeing internally displaced persons seeking for shelter.
Plateau state has also experienced flooding, washing away vast farmlands and residential
houses depriving them of their means of livelihood and place of abode. The thriving poultry
farming practice in the state had also suffered a bout of bird flu which resulted in the killing of
almost all the birds in affected farms. Such poultry farmers after losing their birds became
jobless.
These conditions may have predisposed the study respondents to psychosocial stress, making
them vulnerable to developing depression.
5.2 CHARACTERISTICS OF DEPRESSION DIAGNOSIS BY PHQ 2 AND PHQ 9
The PHQ 2 and the PHQ 9 which were used in the diagnosis of depression in this study
demonstrated good diagnostic characteristics. Details of their performance are discussed
separately below.
5.2.1 Characteristics of Depression Diagnosis using PHQ 2
98
The prevalence of depression using PHQ 2 was 42.1%, which was much higher than the
reported findings of 38.0% among postpartum women attending a Well Child Clinic, 12%
among youths attending an outpatient department, 20.6% among patients with chronic
conditions of diabetes and heart failure and 9.6% among the general population.96, 142,143 The
varying depression prevalence rates could be due to variations in the population of study.
However, the exposure to sectarian violence and stressful events reported in another study in
Jos, where the proportion of respondents who reported the experience of a stressful event were
approximately 66%, could also be responsible for the reported depression prevalence rate in
this study.139
5.2.2 Characteristics of Depression Diagnosis using PHQ 9
The prevalence of depression using PHQ 9 was 38.3% which was similar to the prevalence of
35.7% and 35.5% reported by Amoran et al and Al-Busaidi et al 144, 145 This prevalence was
much higher than reported prevalence rates of 7.6%-27.8% from various primary care studies.
107, 146-148 The prevalence rate was however, lower than the reported rate of 47.8% in a study by
Obadeji et al.105
Considering the characteristics of the populations studied that were reported above, there was
no difference in the socio-demographics of population of this study and that of a similar study
done at an outpatient department of a tertiary health institution from South-West Nigeria,
where a prevalence rate of 47.8% was found.105 Both studies were carried out among adults
aged 18 years and above. The population under study differed with the populations studied by
Adewuya et al, Al-Busaidi et al and Othieno et al, as all the studies were done among college
and university students who were predominantly young undergraduates.7,145,146 The population
however were similar to the population of this study as those studies were done at outpatient
departments from different regions.47,121,125,147-149
99
The observed rate of depression in this study was probably related to socio-economic factors
and psychosocial stressors in the respondents which include low income, exposure to sectarian
violence and stressful life events. The findings were similar to what was reported by Kiyanda
et al and Baigana et al in different primary care studies.29,34 The occurrence of sectarian
violence and natural disaster in approximately 41.6% of respondents might have contributed
to the reported prevalence. More so, the socioeconomic status of most respondents was rather
low as the majority of respondents (67.4%) had an average daily income of ₦1000 or less. This
could be attributed to lack of employment, underemployment or job losses among the
respondents.
5.2.3 Comparative Diagnostic Characteristics of PHQ 2 and PHQ 9
The prevalence of depression according to the PHQ 2 was 42.1% while that of PHQ 9 was
38.3%. The sensitivity of PHQ 2 was 80.4%. On account of this, the proportion of subjects
screened as depressed each time PHQ 2 was used was about 80 out of 100 depressed patients.
Similarly, the specificity of PHQ 2 was 81.5%. This means that the proportion of subjects
screened as not having depression each time PHQ 2 was used was about 81 out of every 100
non-depressed patients. The Positive Predictive Value was 73.2% and the Negative Predictive
Value was 86.8%.
5.2.4 Performance Characteristic Outcomes of PHQ 2
The discriminatory ability of a test is the ability of that test to differentiate between the presence
or the absence of a condition can be quantified by measures of diagnostic accuracy, which
include its sensitivity, specificity, positive predictive value, negative predictive value, the
100
likelihood ratio, the area under the receiver operating curve (AUC), the Youdens Index (YI)
and the diagnostic odds ratio (DOR). The Accuracy of 81.2% is the proportion of correctively
classified subjects as depressed or non-depressed. This level of Accuracy gives PHQ 2 a good
characteristic for screening depression in Primary Care Settings. The other recorded results of
a sensitivity of 80.4%, specificity of 81.7%, PPV 73.2%, NPV87.01% similarly give the PHQ
2 good screening ability and could be used for that purpose in Primary care setting. The False
positive Error Rate of 0.183 and False Negative Error rate of 0.196 also make PHQ 2 good for
screening depression in Primary Care setting but not for diagnosis of depression.
THE SENSITIVITY of PHQ 2 tool in this study was 80.4%, which is the probability that
PHQ 2 correctly identified depression among subjects. The sensitivity was greater than
reported sensitivity ranging between 70- 77.0% in several primary care studies comparing short
and long screening tools and meta-analysis reports.86, 89, 91, 92,94
This sensitivity was however, lower than a sensitivity of 88.0% reported in a multi-center
primary care study.96 The sensitivity was similarly lower than 90.3% reported from another
primary care study by Jeun-Geon.90 Other studies also reported higher sensitivity of 95.5% and
96.0% 91,93
THE SPECIFICITY of PHQ 2, which means how accurately PHQ 2 correctly classify truly
non depressed respondents as none depressed, was 81.7%. This specificity was greater than a
specificity of 70%-77% reported in various studies of short and long screening tools for
depression in primary care.86, 89,91,92 The specificity was however, lower than 82%, 82.3%,
90.3% and 91% from other studies.96,93,90,94
THE POSITIVE PREDICTIVE VALUE (PPV) of the PHQ 2, which is the proportion of
the respondents with a positive PHQ 2 results who are actually depressed, was 73.2%. The
PPV was higher than PHQ 2, PPV of 46.0% and 42.0% reported by Richardson et al and Boyles
et al respectively.93,150
101
THE NEGATIVE PREDICTIVE VALUE (NPV) of the PHQ 2, which is the proportion of
respondents with a negative PHQ 2 result who were actually without depression was 87.01%.
This NPV was similar to NPV of 86.6% reported by Jong-Geun et al and 82.0% reported by
Boyles et al.90, 150 The NPV was however, lower than 99.4% and 91.2% reported by Richardson
et al and McGuire et al from various primary care studies.93,91
LIKELIHOOD RATIO POSITIVE (LR+)
The LR+, which is the ratio of the probability of a positive PHQ 2 test in respondents with
depression to the probability of positive PHQ 2 test in respondents without the disease, was
4.3459. This means that a respondent with a positive PHQ 2 is much more likely to be
depressed than an occurrence of chance.
THE LIKELIHOOD RATIO NEGATIVE (LR-), was 0.2404 which was the ratio of a
negative test result among the depressed subjects to the negative test result in the non-depressed
subjects. LR- 0.2404 is insignificantly small. Hence a patient with a LR- 0.2404 is much likely
not depressed.
TRUE POSITIVE are the respondents who have depression and were diagnosed as depressed
on PHQ 2, was 41.
TRUE NEGATIVE are the respondents who were without depression and were diagnosed on
PHQ 2 as non-depressed, was 67.
FALSE POSITIVE ERROR RATE is the rate at which respondents without depression are
diagnosed as depressed by PHQ 2 was 0.183. This represents the proportion of respondents
without depression that were tested positive for depression.
102
THE FALSE NEGATIVE ERROR RATE which is the rate at which the respondents with
depression are diagnosed as non-depressed was 0.196. The False Negative Error rate is the
proportion of respondents with depression that were tested non-depressed.
THE ACCURACY (DIAGNOSTIC ACURACY)
The Accuracy of PHQ 2 was 0.812, and it is the proportion of correctly diagnosed subjects
(truly depressed or truly non-depressed) among all the subjects. The Accuracy of 0.812,
approximately (81.2%) demonstrated the accuracy of PHQ 2 in differentiating between
depressed and non-depressed subjects.
DIAGNOSTIC ODD RATIO
The Diagnostic Odd Ratio (DOR) was 18.31. DOR is the ratio of the odds of the subjects being
diagnosed depressed relative to the odds of not been diagnosed depressed. The DOR of 18.31
signifies the likelihood of depression in the subjects with positive results in compared to
subjects with negative result. Diagnostic odds ratio of more than 18 signifies that PHQ 2
discriminates depressed from non-depressed subjects.
PERFORMANCE YIELD OF PHQ 2
The yield of PHQ 2 is the number of previously undiagnosed subjects that were recognized by
use of the tool which include respondents with positive PHQ 2 results (depressed) that were
depressed, respondents with negative PHQ 2 results (non-depressed) that were not depressed,
the probability that a respondent actually has depression when tested positive (PPV), the
probability that a subject is truly depression free given a negative PHQ 2 results and the
prevalence. The sensitivity of PHQ 2 was 80.4%, specificity 81.7%, PPV 73.2%, NPV 87.01%,
and prevalence 42.1%. The performance yield for PHQ 2 was satisfactory in the recognition of
depression.
103
AREA UNDER CURVE/RECEIVER OPERATING CURVE
The Area Under the Curve (AUC)/ Receiver Operating Curve (ROC) is the area under the
graph plotted with 1-Specificity on the X-axis and Sensitivity on the Y-axis. AUC for a test
ranges between 0 and 1. A perfect test had AUC of 1, while a test with AUC of 0.5 had no
discriminatory ability. The higher the area under the curve the higher the discriminatory power
of a test.
The area under the curve was 0.832, 95% CI: 0.79-0.906 showed the characteristics of PHQ 2
was very good, hence its ability to diagnose depression was similarly good. The AUC of 83%,
with lower boundary of 75.9% and higher boundary of 90.6% at 95% Confidence Interval,
demonstrated its good discriminatory ability. The P value was < 0.05, making it statistically
significant. This was similar to the AUC of 0.82, 0.84 and 0.88 reported by Chunyu et al,
Richardson et al and Boyles et al respectively.150,89, 93, The AUC was however lower than 0.91
reported by McGuire.91
YOUDENS INDEX (YI)
The Youdens Index expresses the performance of a test’s discriminatory power ( its accuracy
of diagnosis) The YI was 0.621 which demonstrated the accuracy of PHQ 2 to differentiate
depressed from non-depressed patients on a scale of 1
5.3 STRENGTHS OF THE STUDY
The study was carried out in a primary care setting. It therefore shows that the practice of
diagnosing depression and subsequent treatment could be done in such settings.
Administration of the tool was not time consuming, showing it was convenient and acceptable
for use in primary care settings.
104
Similarly, the diagnosis of depression based on its average score of the administered tool,
classification of depression and the corresponding needed intervention or care, were also easy
to carry out based on the respective category of depression; being mild moderate or severe.
The tool was self-administered, easily understood by the patients who appropriately scored it
leaving the physician with further decisions or clarifications. This partnership with patients in
diagnosis and care of their illness also helps to improve outcome, as patients will see the need
for the required treatment and are likely to adhere to prescribed treatment.
5.4 CONCLUSION
The PHQ 2 was found suitable for use among patients in a primary care setting, based on the
characteristics of the PHQ 2, in comparison with PHQ 9, the reference gold standard.
The proportion of subjects diagnosed with depression using PHQ 2 was 42.1% while the
proportion of subjects diagnosed with depression using the PHQ 9 was 38.3%. The two
proportions were relatively similar with no statistical significance.
The performance characteristics of PHQ 2 found in this study were a sensitivity of 80.4%,
specificity of 81.7%, Positive Predictive Value of 73.2%, Negative Predictive Value of
87.01%, Positive Likelihood Ratio of 4.393, Negative Likelihood Ratio of 0.24, Diagnostic
Odds ratio of 18.31, Diagnostic Accuracy of 0.812 and Youndens Index of 0.621
These diagnostic features (although not a screening tool) make the PHQ 2 a suitable tool for
diagnosing depression in outpatient primary care settings, because it performed reasonably
well when compared with the PHQ 9 which is the gold standard.
PHQ 2 is therefore suitable for use in a primary care setting. Its use will enhance the diagnosis
of depression and subsequent implementation of an appropriate treatment intervention(s) in the
subjects.
105
5.5 LIMITATION OF THE STUDY
The study was limited by the fact that it was carried out in a hospital setting, hence the subjects
may not represent the entire population. People presenting to the hospital, from which the
respondents were selected may likely have comorbid illnesses that might increase their chance
of being depressed in contrast to the general population.
The study was also limited to literate adults. Non-literate adults were excluded thereby limiting
generalization of the findings.
5.6 RELEVANCE OF THE STUDY TO FAMILY MEDICINE
PHQ 2 is suitable for use by Family Physicians in primary care settings for the care of patients
with depression and for the study of depression among patients. It can also be used to teach
patients about self-recognition of depression, and the health management of depression.
Family Physicians as health care providers could use PHQ 2 to screen and categorize depressed
patients based on the severity of their scores. They could also manage the depressed patients
appropriately thereby reducing the burden of depression on the individual, the family and the
society at large. Because PHQ 2 is easy to apply and interpret, its use in the primary care setting
will encourage easy screening of every patient at every encounter for depression. This will
promote early diagnosis of depression as well as early treatment and a better outcome by giving
a wholistic integrated and bio-psychosocial care. Where a depressed patient needs specialist
care, the Family Physician could arrange the visit or referral to the specialist. Similarly when
such patients receive adequate care and are managed at a primary care setting or the community
level, the Family Physician can also coordinate such care.
106
The Family Physician, as a health educator, can also use the PHQ 2 to teach patients about how
to recognize the features of depression by themselves so as to seek health care once they notice
the symptoms. The tool can also be used to teach other health personnel about screening for
depression. Where the number of patients with depression have been identified with PHQ 2
and documented, such data could be used to get the attention of all relevant bodies such as the
government, and donor agencies to the care of depressed patients so as to reduce the enormous
burden of depression in our societies.
Family Physicians as coordinators of care, identify patients with severe depression and refer to
appropriate specialist for advanced care. Similarly, severely depressed patients that get treated
and improve could be referred back to their primary care providers for continuity of care in
their immediate communities.
Family Physicians could use PHQ 2 as a tool for health promotion and health education
concerning depression, depression care, discouraging stigmatization and to improve the hope
and health of depressed patients.
5.7 RECOMMENDATIONS
Further studies could be repeated in primary care settings involving both literate and non-
literate patients in order to extend suitability of the PHQ 2 to all subjects with possible
depression. Trial of the use of PHQ 2 should also be extended to the community.
REFERENCES
107
1. World Health Organization. World suicide prevention day 2012. Available from
http://www.who.int/mediacentre/events/annual/worldsuicidepreventionday/en/Accessed
October 20th, 2014.
2. Armstrong C. APA Releases Guideline on Treatment of Patients with Major Depressive
Disorder. Am Fam Physician 2011; 83(10): 1219-27.
3. WHO fact sheet. Available at .http://www.who.int/mediacentre/factsheets/fs369/en/
(Accessed 22/10/2014).
4. Bromet E, Andrade LH, Hwang I, Sampson NA, Alonso J, Girolamo G, et al. Cross-national
epidemiology of DSM-IV major depressive episode. BMC Med 2011;9(90) :2-16.
5. Lasebikan VO, Ejidokun A, Coker OA. Prevalence of mental disorders and profile of
disablement among primary health care service users in Lagos Island. Epid Res Intern 2012;
10:1155-61.
6. Afolabi, MO, Abioye-Kuteyi EA, Fatoye FO, Bello IS, Adewuya AO. Pattern of depression
among patients in a Nigerian Family Practice population. S Afr Fam Pract 2008; 50(2): 63.
7. Adewuya OA, Ola BA, Aloba OO, Mapayi BM, Oginni OO. Depression amongst Nigerian
University Students, Prevalence and Sociodemographic correlates. Soc Psychiatry Psychiatr
Epidemiol 2006; 41(8): 674-8.
8. Baiyewu O, Smith-Gamble V, Lane KA, Gureje O, Gao S, Ogunniyi A et al. Prevalence
estimates of depression in elderly community-dwelling African Americans in Indianapolis and
Yoruba in Ibadan, Nigeria. Intern Psycho-geriatrics 2007; (19)4; 679-89.
9. Goar SG, Obembe A, Audu MD, Agbir MT. Utilization of health care services by depressed
patients attending the general out-patients department of the Jos University Teaching
Hospital,Jos, Nigeria. Niger J Clin Pract. 2012; 15(1):59-62.
108
10. Akena D, Joska J, Obuku EA, Amos T, Musisi S, Stein DJ. Comparing the accuracy of
brief versus long depression screening instruments which have been validated in low and
middle income countries: a systematic review. BMC Psych 2012; 12: (187)1-7.
11. Ogunsemi OO, Oluwole FA, Abasiubong F, Erinfolami AR, Amoran OE, Ariba AJ. et al.
Detection of mental disorders with the Patient Health Questionnaire in primary care settings in
Nigeria. Ment Illness 2010; 2(1): 46-50.
12. Mohammed A, Said JM, Wakil MA, Rabbebe IB, Sheikh T, Agunbiade S. Unrecognized
psychiatric disorders among adult patients admitted into a general hospital in Maiduguri,
Northeastern Nigeria. Pan Afri Med J. 2014; 19 (197) 1-10.
13. Asibong UE, Udonwa NE, Gyuse AN, Okokon IB, Aluka T, Ekpe EE. Recognition of
mental health problems by Primary Care Physicians in a tertiary care hospital in Nigeria. Niger
Postgrad Med J. 2011; 18(4):266-71.
14. James BO, Jenkins R, Lawani AO, Omoaregba JO. Depression in primary care: the
knowledge, attitudes and practice of general practitioners in Benin City, Nigeria. S Afr Fam
Pract 2012; 54(1):55-60.
15. Adewuya AO, Ola BA, Afolabi OO. Validity of patient health questionnaire (PHQ 9) as a
screening tool for depression amongst Nigerian university students. J Affect Disord 2006;
96(1-2): 89-93.
16. Maurer DM. Screening for Depression. Am Fam Physician. 2012; 85(2):139-44.
17. Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJL et al. Burden
of Depressive Disorders by Country, Sex, Age, and Year: Findings from the Global Burden of
Disease Study 2010. PLOS Med. 2013. Available at
http://dx.doi.org/10.1371%2Fjournal.pmed.1001547 Accessed April 11, 2015.
109
18. Ferrari AJ, Somerville AJ, Baxter AJ, Norman R, Patten SB. Global variation in the
prevalence and incidence of major depressive disorder: A systematic review of the
epidemiological literature. Psychol Med 2013; 43(3): 471–81.
19. Hadley C, Tegegn A, Tessema F, Cowan JA, Asefa M, Galea S. Food insecurity, stressful
life events and symptoms of anxiety and depression in East Africa:Evidence from the Gilgel
Gibe growth and development study. J Epidemiol Com Health 2008; 62(11): 980-6.
20. Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic
diseases, and decrements in Health: Results from the World Health Survey. Lancet 2007; 370
(9590): 851–8.
21. Ghanem M, Gadallah M, Meky FA, Mourad S, El-Kholy G. National Survey of Prevalence
of Mental Disorders in Egypt: Preminary Survey. E Mediterran Health J 2009; 15(1): 65-75.
22. Degenhardt L, Hall W. Extent of illicit drug use and dependence, and their contribution to
the global burden of disease. Lancet 2012; 379(9810): 55-70.
23. Hailemariam S, Tessema F, Asefa M , Tadesse H, Tenkolu G. The prevalence of depression
and associated factors in Ethiopia: Findings from the National Health Survey. Int J Ment Health
Syst 2012; 6(1):23
24. Roberts B, Damundu EY, Lomoro O, Sondorp E. Post-conflict mental health needs: A
cross-sectional survey of trauma, depression and associated factors in Juba, Southern Sudan.
BMC Psych 2009; 9(7): 1-10.
25. WHO. A situation Analysis of Mental Health in Somalia. World Health Organisation
bulletin 2010; 1:17-26.
110
26. Ndetei DM, Khasakhala LI, Kuria MW, Mutiso VN, Ogecha-owuor FA, Kokonya DA. The
prevalence of mental disorders in Adults in different level general medical facilities in Kenya:
A crossectional Study. Annals Gen Psych 2009; 8(1): 1-8.
27. Jenkins R, Njenga F, Okonji M, Kigamwa P, Baraza M, Ayuyo J, et al. Prevalence of
Common Mental Disorders in a Rural District of Kenya and Socio-demographic risk factors.
Int. J. Environ. Res. Public Health 2012; 9(5):1810-9.
28. Muhwezi WW, Agren H, Musisi S. Detection of major depression in Ugandan primary
health care settings using simple questions from a subjective well-being (SWB) subscale. Soc
Psychiatry Psychiatr Epidemiol 2007; 42(1): 61-9.
29. Kinyanda E, Woodburn P, Tugumisirize J, Kagugube J, Ndyanabangi S, Patel V. Poverty,
life events and the risk for depression in Uganda. Soc Psychiatry Psychiatr Psych Epidemiol.
2011; 46(1): 35–44.
30. Stein DJ, Seedat S, Herman A, Moomal H, Heeringa SG, Kessler RC, et al. Lifetime
prevalence of psychiatric disorders in South Africa. Br J Psychol 2008; 192 (2): 112-7.
31. Simbayi LC, Kalichman S, Strebel A, Cloete A, Henda N, Mqeketo A. Internalised stigma,
Discrimination and Depression among Men and Women with HIV/AIDS in Cape Town, South
Africa. Soc Sci Med. 2007; 64(9): 1823–31.
32. Rochat TJ, Tomlinson M, Barnighausen T, Newell ML, Stein A. The Prevalence and
Clinical presentation of Antenatal Depression in rural South Africa. J Affect Disord 2011;
135(1-3) 362–73.
33. Korb I, Plattner IE. Suicide ideation and depression in University Students in Botswana.
J Psychol Africa 2014; 24(5): 420-6.
111
34. Baingana FK, Bos ER. Changing Patterns of Disease and Mortality in Sub-Saharan
Africa: An overview. In: Jamison DT, Feachem RG, Makgoba MW. Disease and Mortality in
Sub-Saharan Africa. Second ed, Washington (DC); World Bank 2006:3-16.
35. Sipsma H, Ofori-Attah A, Canavan M, Osei-Akoto I, Udry C, Bradley EH. Poor mental
health in Ghana: who is at risk? BMC Pub Health 2013;13: 288.
36. Thapa SB, Martinez P, Clausen T. Depression and its correlates in South Africa and
Ghana among people aged 50 and above: Findings from the WHO Study on global Ageing
and adult health. J Psychiatr. 2014; 17(6):1-11.
37. Asante KO, Andoh-Arthur J. Prevalence and determinants of depressive symptoms
among University Students in Ghana. J Aff Disord 2015; 171:161-6.
38. Gureje O, Lesebikan VO, Kola L, Makanjuola VA. Lifetime and 12-month prevalence of
mental disorders in the Nigerian Survey of Mental Health and Well-Being. Br J Psychiatr
2006; 188:465-71.
39. Adeosun II, Jeje O. Symptom profile and Severity in a sample of Nigerians with
Psychotic Versus Non-psychotic Major Depression. Dep Res Treat 2013; 10: 815456.
40. Somoye EB, Babalola EO, Adebowale TO. Prevalence and Risk Factors for Anxiety and
Depression among Commercial Bank Workers in Abeokuta, Southwestern Nigeria. J Behav
Health. 2015; 4(2): 55-62.
41. Amoran O, Lawoyin T, Lasebikan V. Prevalence of Depression among Adults in Oyo State:
A comparative study of rural and urban communities. Aust. J Rural Health 2007; 15(3): 211-
5.
42. Amoran OE, Lawoyin TO, Oni OO. Risk factors associated with mental illness in Oyo
state. Ann Gen Psych 2005; 4: 19.
112
43. Adewuya AO, Ola BA, Aloba OO. Prevalence of Major Depressive Disorders and a
validation of Becks depression Inventory among Nigerian adolescents. Eur Child Adolesc
Psychiatry 2007; 16(5): 287-92.
44. Adewuya AO, Ola BA, Ajayi OE, Oyedeji AO, Balogun MO, Mosaku SK. Prevalence and
correlates of Major Depressive Disorder in Nigerian Outpatients with Heart failure.
Psychosom 2006; 47(6): 479-85.
45. Upkong MD, Orji EO. Mental Health of infertile women in Nigeria. Turk J Psychatr 2006;
17(6): 1-7
46. Mapayi B, Makanjuola RO, Mosaku SK, Adewuya AO, Aloba OO, Akinsulore A et al.
Impact of Intimate Partner Violence on Anxiety and Depression amongst women in Ile-Ife,
Nigeria. Arch Women Ment Health 2013; 16(1): 11-8.
47. Ogunrombi AB, Mosaku KS, Unakpoya UU. The impact of Psychological illness on
outcome of corrosive oesophageal injury. Niger J Clin Practice 2013; 16(1): 49-53.
48. Chikezie UE, Otakpor AN, Kuteyi OB, James BO. Depression among people living with
Human immunodeficiency virus infection/acquired immunodeficiency syndrome in Benin
City, Nigeria: A comparative study. Niger J Clin Pract 2013; 16(2): 238-42.
49. James BO, Morakinyo O, Eze GO, Lawani AO, Omoaregba JO. Depression and Subjective
Quality of life among outpatients with Diabetes mellitus at a Teaching Hospital in Nigeria.
Ment Health Fam Med 2010; 7(3): 179-83.
50. Otakpor AN. Prevalance of Psychiatric Disorders among Nurses of a Nigerian University
Teaching Hospital. J Med Biomed Res 2014; 13(2): 67-71.
51. Nwaopara U, Stanley P. Prevalence of Depression in Port Harcourt Prison. J Psychiatr
2015; 18 (6): 1-8.
113
52. Aniebue PN, Onyema GO. Prevalence of depressive symptoms among Nigerian Medical
Undergraduates. Trop Doct 2008; 38 (3): 157-8.
53. Aguocha GU, Onyeama GM, Bakare MO, Igwe MN. Prevalence of Depression among
Resident Doctors in a Teaching Hospital, South East, Nigeria. Intern J Clin Psychiatr
2015; 3(1): 1-5.
54. Obi IE, Aniebue PN, Okonkwo K, Okeke TA, Ugwunna N. Prevalence of Depression
among Health workers in Enugu, South East Nigeria. Niger J Clin Pract 2015; 18(3): 343-7.
55. Igwe MN, Uwakwe R, Ahanotu CA, Onyema GM, Bakare MO, Ndukuba AC. Factors
associated with depression and suicide among patients with diabetes and essential hypertension
in a Nigerian teaching hospital. Afr Health Sci 2013; 13(1):68-77.
56. Mishara WL, Gbaden EA. Prevalence of Depression among Youths as an aftermath of the
internal Insurgency in Maiduguri. J Hum Soc Sci 2014; 19(10): 32-5.
57. Pindar SK, Wakil MA, Jidda MS, Morakinyo AO, Coker MA. Burn out syndrome and
Depression among Health Care Professionals of Tertiary Hospitals in Maiduguri. Kanem J
Med Sci 2012: 23-8.
58. Wakawa IA, Shehu S, Kwajafa SP, Beida O, Abba WY, Rabbebe IB et al. Depression, self-
stigma and quality of health: A comparative study of adult patients on HAART with diabetes
in a tertiary health institution in North Eastern Nigeria. Int J Med Med Sci 2014; 1(4): 50-9.
59. Ibrahim A, Mubi B, Omeiza B, Wakil M, Rabbebe I, Jidda M et al. An Assessment of
Depression and Quality Of Life among Adults with Diabetes Mellitus in the University Of
Maiduguri Teaching Hospital. Int J Psychiatr 2013; 2(1):1-8.
60. Bakare AT, Yusuf AJ, Habib ZG, Obembe A. Anxiety and Depression: A study of People
with Leprosy in Sokoto. J Psychiatr 2015; 1(4):1-7.
114
61. Yunusa MA, Obembe A. Ethnic density and prevalence of psychiatric morbidity among
patients with HIV infection in Sokoto, North Western Nigeria. Open J Psychiatr 2012; 2: 292-
300.
62. Abubakar SA, Obiakor RO, Sabir AA, Iwuozuo EU, Magaji MI. Depression in long-term
stroke survivors. Sub-Saharan Afr J Med 2014; 1:119-23.
63. Ajiboye PO, Yussuf AD, Issa BA, Adegunloye AO, Buhari ON. Current and Lifetime
Prevalence of Mental Disorders in a Juvenile Borstal Institution in Nigeria. Res J Med Sci
2009; 3(1): 26-30.
64. Shittu RO, Odeigah LO, Issa BA, Olanrewaju GT, Mahmoud AO, Sanni MA. Association
between Depression and Social Demographic Factors in a Nigerian Family Practice Setting.
Open J Dep 2014; 3(1): 18-23.
65. Issa BA, Yussuf AD, Kuranga SI. Depression comorbidity among patients with
tuberculosis in a university teaching hospital outpatient clinic in Nigeria. Ment Health Fam
Med 2009;6(3): 133-8.
66. Agbir TM, Audu MD, Adebowale TO, Goar SG. Depression among medical outpatients
with Diabetes: A cross-sectional study at Jos University Teaching Hospital, Jos, Nigeria. Ann
Afr Med 2010; 9: 5-10.
67. Armiyau AY, Obembe A, Audu MD, Afolarammi TO. Prevalence of Psychiatric morbidity
among inmates in Jos maximum prison. Open J Psychiatr 2013; 3: 12-7.
68. Ladep NG, Obindo TJ, Audu MD, Okeke EN, Malu AO. Depression in Patients with
Irritable bowel syndrome in Jos. World J Gastroenterol 2006; 12(48): 7844-47.
69. Gureje O, Chisholm D, Kola L, Lasebikan V, Sexena S. Cost-effectiveness of an essential
mental health intervention package in Nigeria. World Psychiatr 2007; 6(1):42-8.
115
70. Shittu RO, Issa BA, Olanrewaju GT, Mahmoud AO, Odeigah LO, Salami AK et al.
Prevalence and Correlates of Depressive Disorders among People Living with HIV/AIDS, in
North Central Nigeria. J AIDS Clin Res 2013; 4(11): 251-7.
71. Kauye F, Jenkins R, Rahman A. Training primary health care workers in mental health and
its impact on diagnoses of common mental disorders in primary care of a developing country,
Malawi: A cluster randomized controlled trial. Psychiatr Med. 2014; 44(3): 657-66.
72. Lueboonthavatchai P. Role of stress areas, stress severity, and stressful life events on the
onset of depressive disorder: a case-control study. J Med Assoc Thai 2009; 92(9):1240-9.
73. Rhee YS, Yun YH, Park S, Shin DO, Lee KM, Yoo HJ et al. Depression in Family
Caregivers of Cancer Patients: The Feeling of Burden as a Predictor of Depression. J Clin
Oncol 2008; 26: (36) 5890-5.
74. Sayers SL, Farrows VA, Ross J, Oslin D. Family problems among recently returned
Military Veterans referred for mental health evaluation. J Clin Psychiatry 2009; 70(2):163-70.
75. McKnight PE, Kashdan TB. The Importance of Functional Impairement to Mental Health
outcomes: A case for reassessing our goals in depression treatment reseach. Clin Psychol Rev
2009; 29(3): 243-59.
76. Waghorn G, Chant D. Work performance among Australians with depression and anxiety
disorders. A population level second order analysis. J Nerv Ment Dis 2006; 194 (12):898–904.
77. Hoge CW, Auchterlonie JL, Milliken CS. Mental health problems, use of mental health
services, and attrition from military service after returning from deployment to Iraq or
Afghanistan. JAMA 2006, 295:1023–32.
116
78. Olisah VO, Baiyewu O, Sheikh TL. Depression under-diagnosis and the effects on quality
of life in outpatients with HIV at a Nigerian University Teaching Hospital. Afr J Aids Res
2011; 10(3): 247-54.
79. Gureje O, Uwake R, Oladeji B, Makanjuola VO, Esan O. Depression in Adult Nigerians:
Results from the Nigerian Survey of Mental Health and Well-being. J Affect. Disord 2010;
120(3): 158-64.
80. Haddad M, Gunn J. Fast facts, Depression: Brit Lib Health Press bulletin; 2011:3. Available
at www.fastfacts.com. Accessed November 19, 2015.
81. Halverson JL, Bhalla RN, Andrew LB. Depression Treatment and Management. The
Medscape 2015. Available at http://emedicine.medscape.com/article/286759-treatment.
Accessed October 19, 2015.
82. Kennedy SH. Core Symptoms of Major Depressive Disorder: Relevance to diagnosis and
Treatment. Dialogues Clin Neurosci 2008; 10(9): 271-7.
83. Demyttenaere K. Affect modulation, functioning, and depression. Medicographia 2014;
36(4): 441-4.
84. Rice DB, Kloda LA, Shrier I, Thombs BD. Reporting quality in Abstracts of meta-analysis
of depression screening tools accuracy: A review of systematic reviews and meta-analysis. Br
Med J 2016; 6:1-9.
85. Hollon SD. The NICE Guideline on Treatment and Management of depression in adults.
Br Psych Soc 2010. Available at https://www.nice.org.uk/guidance/cg90/evidence/cg90-
depression-in-adults-full-guidance2. Accessed October 7, 2015.
86. Mitchelle AJ, Coyne JC. Do ultra-short screening instruments accurately detect depression
in primary care? Br J Gen Pract 2007; 57(535): 144-55.
117
87. Makanjuola VA, Onyeama M, Nuhu FT, Kola L, Gureje O. Validation of
short screening tools for common mental disorders in Nigerian general practices. Gen Hosp
Psychiatry. 2014; 36(3): 325-9.
88. Adewuya AO, Ola BA, Dada AO, Fasoto OO. Validation of the Edinburgh Postnatal
Depression Scale as a screening tool for depression in late pregnancy among Nigerian women.
J Psychosom Obst Gynaecol. 2006; 27(4):267-72.
89. Chunyu MM, Li C, Friedman B, Conwell Y, Fiscella K. Validity of the Patient Health
Questionnaire 2 in identifying major Depression in Older People. J Am Geriatr Soc 2007;
55(4): 596-602.
90. Jong-Geun S, Sung-Pa P. Validition of PHQ 9 and PHQ 2 in patients with migraine. J
Headache Pain 2015; 16(65): 1-7.
91. McGuire AW, Eastwood JA, Macabasco-O’ Connel A, Hays RD, Doering LV. Utility of
Patient Health Questionnaire in Patients with Acute Coronary syndrome. Am J Crit Care 2013;
22(1): 12-20.
92. Delgadilo J, Gilbody S, Godfrey C, Gore S, Jossep D, Dale V et al. How reliable is
Depression Screening in Alcohol and Drug Users? A Validation of Brief and ultra-Brief
Questionnaires. J Affect Disord 2011; 134(1-3): 266-71.
93. Richardson LP, Rockhill C, Russo JE, Grossman DC, Richards J, Carolyn M et al.
Evaluation of PHQ-2 as a brief screen for detecting Major Depression among Adolescents.
Paed 2010; 125(5): 1097-103.
94. Gjerdingen D, McGovern P, Miner M, Center B, Scott C. Postpartum Depression Screening
at Well-Child visits: Validity of a 2-Question screen and the PHQ 9. Ann Fam Med 2007; 7:
63-70.
118
95. Mitchell AJ, McGlinchey JB, Young D, Chelminski I, Zimmerman M. Accuracy of specific
symptoms in the diagnosis of major depressive disorder in psychiatric out patients: Data from
the MIDAS project. Psychiatr Med 2009; 39(7): 1107-16.
96. Liu S, Yeh Z, Huang HC, Sung FJ, Tjung JJ, Huang LL et al. Validation of Patient Health
Questionnaire for depression screening among primary care patients in Taiwan. Comp
Psychiatr 2011; 52(1): 96-101.
97. Aguera L, Failde I, Cervilla JA, Diaz-Fernandez P, Mico JA. Medically unexplained pain
complaints are associated with underlying unrecognized mood disorders in primary care. BMC
Fam Pract 2010; 11(17):1-8.
98. Kohli C, Kishore J, Agarwal P, Singh SV. Prevalence of Unrecognized Depression Among
Outpatient Department Attendees of a Rural Hospital in Delhi, India. J Clin Diag Res. 2013;
7(9): 1921-5.
99. Khamphuis MH, Steganga BT, Zuitoff MP, King M, Nazareth I, de Wit NJ, Geerling MI.
Recognition of depression in primary care: Does it affect outcome? The PREDICT-NL Study.
Fam Pract 2011; 1:1-8.
100. Ani C, Bazargan M, Hindman D, Bell D, Farooq MA, Akhanjee L et al. Depression
symptomatology and diagnosis: Discordance between Patients and Physicians in Primary Care
Settings. BMC Fam Pract 2008; 9(1):1-9.
119
101. Baik SY, Bowers BJ, Oakley LD, Susman SY. What comprises clinical experience in
recognizing depression? The primary care clinician's perspective. J Am Board Fam Med. 2008;
21(3): 200-10.
102. Vermani, M, Marcus M, Katzman MA. Rates of Detection of Mood and Anxiety
Disorders in Primary Care: A descriptive cross-sectional study. Prim Care Comp CNS Disord.
2011; 13(2):1-26.
103. Cepoiu M, McCusker J, Cole MG, Maida S, Belzile E, Ciampi A. Recognition of
Depression by Non-psychiatric Physicians: A Systematic Literature Review and Meta-
analysis. J Gen Intern Med 2008; 23(1): 25–36.
104. Udedi M. The Prevalence of Depression among patients and its detection by Primary
Health Care Workers at Matawale Health Centre, Zomba. Malaw Med. J 2014; 26 (2): 34-7.
105. Obadeji A, Oluwole LO, Dada MU, Ajiboye AS, Kumolalo BF, Solomon OA.
Assessment of Depression in a Primary Care Setting in Nigeria using the PHQ-9. J Fam Med
Prim Care 2015; 4(1):30-4.
106. WHO. Mental Health Report, management of depression. World Health Organization
2011. Available at www.whoint/mental_health/ management/depression/definition/en/.
Accessed October 6, 2015.
107. Colonge N, Petiti DB, Dewitt DG, Dietrich AJ, Gordis L, Gregory KD, Harris R et al.
Final Recommendation Statement on Depression in Adults Screening. USPSTF
Recommendation for the Primary Care Practice, 2009. Available at
www.uspreventiveservicestaskforce.org. Accessed October 6, 2015.
120
108. Joffres M, Jaramillo A, Dickinson J, Lewin G, Pottie K, Shaw E et al. Canadian Task
Force on Preventive Health Care: Recommendations on screening for depression in adults. Can
Med Assoc J 2013; 185:775–82.
109. Pedersen SS, Denollet J, De Jong P, Simsek C, Serruys PW, VanDomburg RT. Brief
Depression Screening with the PHQ 2 associated with prognosis following Percutaneous
Coronary Intervention with Paclitaxel-Eluting Stenting. J Gen Intern Med. 2009; 24(9): 1037-
42.
110. Bostwick MJ. A Generalist guide to treating patients with depression with an emphasis
on using side effects to tailor antidepressants therapy. Mayo Clin Proc 2010; 85(6): 538-50.
111. Jacob V, Chattopadhyay SK, Sipe TA, Thota AB, Byard GJ, Chapman DP. Economics of
Collaborative Care for Management of depressive Disorders. Am J Prev Med 2012; 42(5): 539-
49.
112. Alakeson V, Frank RG, Katz RE. Speciality Care Medical Homes for people with severe,
persistent mental disorders. Health Affect. 2010; 29(5): 867-73.
113. Thota AB, Sipe TA, Byard GJ, Zometa CS, Hahn RA, McNight-Eily LR, et al.
Collaborative care to improve the management of depressive disorders: a community guide
systematic review and meta-analysis. Am J Prev Med 2012; 42(5):525-38.
114. Goorden M, Huijbregts KM, van Marwijk HW, Beekman AT, van der Feltz-Cornelis CM,
Hakkaart-van RL. Cost-utility of collaborative care for major depressive disorder in primary
care in the Netherlands. J Psychomsom Res 2015; 79(4): 316-23.
115. Gilbody S, Bower P, Whitty P. Costs and consequences of enhanced primary care for
depression: Systematic review of randomised economic evaluations. Br J Psychiatr 2006;
189(4): 297-308.
121
116. Clark MS, Smith PO, Payne TJ Collins LJ. Psychosocial Interventions Delivered by
Primary Care Physicians to Patients with Depression. Am Fam Physician. 2006; 74(9):1580-
1.
117. Gensichen J, Von Koff M, Peirtz M, Muth C, Beyer M, Guthlin C. et al. Case management
for depression by health care assistants in small primary care practices: a cluster randomized
trial. Ann Intern Med 2009; 151(6):369-78.
118. Gureje O, Abdulmalik J, Kola L, Musa E, Yasamy MT, Adebayo K. Integrating mental
health into primary care in Nigeria: report of a demonstration project using the mental health
gap action program intervention guide. BMC Health Serv Res 2015; 15(1): 1-8.
119. Oladeji BD, Kola L, Abiona T, Montgomery AA, Araya R, Gureje O. A pilot randomized
controlled trial of a stepped care intervention package for depression in primary care in Nigeria.
BMC Psych 2015; 15(96): 1-11.
120. Busari AO. Mindfulness –Based Cognitive Therapy; - Impact on Depressed Outpatients
of the State Hospital Oyo State Ibadan, Nigeria. Am J Med Medic Sci 2015, 5(5): 191-200.
121. Gureje O, Oladeji BD, Araya R, Montgomery AA, Kola L, Kirmayer L et al. Expanding
care for perinatal women with depression: A randomized controlled trial of an intervention
package for perinatal depression in primary care. BMC Psych 2015; 15 (136):1-9.
122. Rupke SJ, Blecke B, Renfrow M. Cognitive behavioural therapy for depression. Am Fam
Physician 2006; 73(1):83-6.
123. Clarke MS, Jansen KL, Cloy JA. Treatment of Childhood and Adolescent Depression.
Am Fam Physician. 2012; 86(5):442-8.
122
124. Thombs BD, Coyne JC, Cuijpers P, de Jonge P, Gilbody S, Ioannidis JP. Rethinking
recommendations for screening for depression in primary care. Can Med Assoc J
2012:184(4):413-18.
125. Munoz RF, Cuijpers P, Smit F, Barrera AZ, Leykin Y. Prevention of major depression.
Annu Rev Clin Psychol. 2010; 6:181–212.
126. Benvenouti P, Valoriani V, Vanni D. Prevention of postnatal depression. Clin Neuropsy
2006; (3)1: 39-56.
127. van den Berg M, Smit F, Vos T, van Baal PHM Vos T. Cost-Effectiveness of
Opportunistic Screening and Minimal Contact Psychotherapy to Prevent Depression in
Primary Care Patients. PLoS 2011; 6(8):1-7.
128. WHO. Comprehensive Mental Health Action Plan, 2013-2020. The World Health
Assembly Resolutions 2013, Available at www.aps.who.int/iris/bitstream. Accessed October
10th, 2015.
129. Berk M, Jacka F. Preventive strategies in depression: gathering evidence for risk factors
and potential interventions. Br J Psychiatr 2012; 201 (5): 339-41.
130. The National Commission for Mass Education. Report of the National literacy survey;
The National Bureau of Statistics: 2010. Available from www.nigerianstat.gov.ng. Accessed
20/07/2014.
131. Rosner B. Fundamentals of Biostatistics. Cengage learning, 2015.
132. Chagas MH, Crippa JA, Loureiro SR, Hallak JE, Meneses-Gaya CD, Machado-de-
Sousa JP, et al. Validity of the PHQ 2 for the screening of major depression in Parkinson’s
disease: Two questions and one important answer. Aging Ment Health 2011; 15(7):838-43.
123
133. Simundic AM. Diagnostic Accuracy. Point Care 2012; 11:6-12
134. Onyebueke GC, Okwaraji FE. Depression and Suicide risk among HIV positive
individuals attending an Outpatient HIV/AIDS Clinic of a Nigerian Tertiary Health
Institution. J Psychiatr 2014; 2015: 18 (1):14-54.
135. Adamu HS. Utilization of Maternal Health care Services in Nigeria: An Analysis of
Regional differences in Patterns and Determinants of Maternal Health Care Use. An Msc
Dissertation: University of Liverpool; 2011. Available at www.support.liverpool-
online.com/files/mph/Quanttitative_Desertation. Accessed November 20th, 2016.
136. James BO, Omoaregba JO, Eze G, Morakinyo O. Depression among patients with
diabetes mellitus in a Nigerian teaching hospital. S Afr J Psychiatr 2010; 16(2): 61-4.
137. Yusuf AJ, Maitama HY, Amedu MA, Ahmed M, Mbibu HN. Socio-demographic
correlates of psychological distress among male patient with infertility in Zaria, Nigeria. Afr
J urol 2012; 18(4): 170-4.
138. Strine WT, Mokdad AH, Balluz LS, Gonzalez O, Kroenke K. Depression and Anxiety
in the United States: Findings from the 2006 Behavioural Risk factor Surveillance System.
Psychiatr Serv 2008; 59(12):1383-90.
139. Tagurum TO, Chirdan OO, Obindo T, Bello DA, Afolaranmi TO, Ibrahim W et al.
Prevalence of Violence and symptoms of post-traumatic stress disorder among Victims of
Ethno-Religious conflict in Jos, Nigeria. J Psychiatr 2015; 18(1):1-6.
140. Catani C, Jacob N, Schauer E, Kohila M, Neuner F. Family violence, war and natural
disasters: A study of the effect of extreame stress on children’s mental health in Sri Lanka.
BMC Psychiatr 2008; 8:33.
124
141. Londono A, Romero P, Casas G. The association between armed conflict, violence and
mental health: A cross sectional study comparing two populations in Cundinamarca. BMC
Conflict Health 2012; 6:12.
142. Richardson LP, Rockhill C, Russo JE, Grossman DC, Richards J, McCarty C et al.
Evaluation of PHQ 2 as a Brief Screen for Detecting Major Depression among Adolescents.
Paed 2010; 125(5): 1097-103.
143. Taylor J, Michael S, Wayne JK, Harold PA, Hogan D. Depression Case Finding
Strategies in a Care Management Program for Chronically ill Medicare Recipients. Am J
Man Care 2008; 14(8): 497-504.
144. Amoran OE, Ogunsemi OO, Lasebikan VO. Assessment of mental health disorders
using the Patient Health Questionnaire as a general screening tool in Western Nigeria: A
community based study. J Neurosci Rural Pract 2012; 3(1): 6-11
145. Al-Busaidi Z, Bhargava K, Al- Ismaily A, Al-Lawati H, Al-Kindi R Al-Shafaee M et al.
Prevalence of Depressive symptoms among University Students in Oman. Oman Med J
2011; 26(4): 235-9.
146. Othieno CJ, Okoth RO, Peltzer K, Pengpid S Malla LO. Depression among University
Students in Kenya: Prevalence and Socio-demographic correlates. J Affect Disord 2014; 165:
120-5.
147. Ganguly S, Samanta M, Roy P, Chartterjee S, Kaplan DW, Basu B. Patient Health
Questionnaire 9 As an effective tool for screening of depression among Indian adolescents. J
Adolesc Health 2013; 52(5): 546-51.
125
148. Al-Ghafri G, Al-Sinawi H, Al-Muniri A, Dorvlo AS, Armstrong K, Al-Adawi S.
Prevalence of depressive Symptoms as ilicited by PHQ 9 among Medical Trainees in Oman.
Asian J Psychiatr 2014; 8: 59-62.
146. Glaesmer H, Kallert TW, Brahler E, Hofmeister D, Gunzelmann T. The prevalence of
psychiatric symptomotology in the German eldely population and the impact of
methodological aspects on the identified prevalence. Psychiatr Pract 2010; 37(2): 71-7.
148. Ummo KL, Paul M. Occupational and Mental Health disorders. Pion Med J 2013;
3(6):1-10.
149. Shittu RO, Issa BA, Olarewaju GT, Odeigah LO, Sule AG, Sanni MA et al. Association
between Subjective Sleep Quality, Hypertension Depression and BMI in 27th December
2017.a Nigeria Family Practice setting. J Sleep Disord Ther 2014; 3(157): 2167-77.
150. Boyle LL, Richardson MT, He H, Xia Y, Conwell Y. How do the PHQ 2 and the PHQ 9
perform in aging services clients with cognitive impairment? Int J Geriatr Psychiatr 2011; 26
(9):952-60.
