Open Access

Prevalence and factors associated with depression symptoms among school-going adolescents in Central Uganda

  • Joyce Nalugya-Sserunjogi1, 2Email author,
  • Godfrey Zari Rukundo3,
  • Emilio Ovuga4,
  • Steven M. Kiwuwa5,
  • Seggane Musisi1 and
  • Etheldreda Nakimuli-Mpungu1
Child and Adolescent Psychiatry and Mental Health201610:39

https://doi.org/10.1186/s13034-016-0133-4

Received: 26 January 2016

Accepted: 17 October 2016

Published: 26 October 2016

Abstract

Background

Depression in adolescents constitutes a global public health concern. However, data on its prevalence and associated factors are limited in low income countries like Uganda.

Methods

Using a cross-sectional descriptive study design, 519 adolescent students in 4 secondary schools in Mukono district, Uganda, were randomly selected after meeting study criteria. The 4 school types were: boarding mixed (boys and girls) school; day mixed school; girls’ only boarding school; and, boys’ only boarding school. The 519 participants filled out standardized questionnaires regarding their socio-demographic characteristics and health history. They were then screened for depression using the Children Depression Inventory (CDI) and those with a cut-off of 19 were administered the Mini International Neuro-Psychiatric Interview for Children and Adolescents 2.0 (MINI-KID), to ascertain the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) diagnostic types of depression and any co morbidity. Logistic regression analyses were used to assess factors associated with significant depression symptoms (a score of 19 or more on the CDI).

Results

There were 301 (58 %) boys and 218 (42 %) girls with age range 14–16 years and a mean age of 16 years (SD 2.18). Of 519 participants screened with the CDI, 109 (21 %) had significant depression symptoms. Of the 109 participants with significant depression symptoms, only 74 were evaluated with the MINI-KID and of these, 8 (11 %) met criteria for major depression and 6 (8 %) met criteria for dysthymia. Therefore, among participants that were assessed with both the CDI and the MINI-KID (n = 484), the prevalence of depressive disorders was 2.9 %. In this sample, 15 (3.1 %) reported current suicidal ideation. In the logistic regression analyses, significant depression symptoms were associated with single-sex schools, loss of parents and alcohol consumption.

Limitations

This is a cross-sectional study therefore, causal relationships are difficult to establish. Limited resources and the lack of collateral information precluded the assessment of a number of potential factors that could be associated with adolescent depression. The MINI-KID was administered to only 74 out of 109 students who scored ≥19 on the CDI since 35 students could not be traced again due to limited resources at the time.

Conclusions

Significant depression symptoms are prevalent among school-going adolescents and may progress to full-blown depressive disorders. Culturally sensitive psychological interventions to prevent and treat depression among school-going adolescents are urgently needed.

Keywords

DepressionDepression symptomsAdolescentsOrphan-hoodSecondary schoolsUganda

Background

Adolescence has been described as a period of tremendous emotional upheaval and change [14]. The transition from childhood to adulthood involves major physical, psychological, cognitive and social transformations [58] which may be stressful to the adolescent. These transformational challenges are often associated with emotional turmoil including depression. Indeed a recent review of the mental health burden among children and adolescents world wide indicate that 10–20 % of them in the general population will suffer from at least one mental disorder in a given year [9]. The commonest of these mental health problems is unipolar depressive disorder which has been reported to be associated with a myriad of complications including impaired academic and social functioning and accounting for 40·5 % of disability adjusted life years (DALYs) caused by mental and substance use disorders [10], risky behaviours [11] as well as increased mortality rates through suicide [12].

Considerable literature points to the high prevalence of depression amongst adolescents [1315]. School based studies of adolescent depression have reported various mean scores ranging between 2.6 and 3.6 % [1618]. The variation in rates has been attributed to the great diversity in research instruments and methodologies.

The majority of studies documenting adolescent mental problems such as depression are from developed countries. The few studies conducted in sub Saharan African countries that have documented adolescent depression rates indicate estimates of 15.3–37 % among Egyptian students [19, 20] 6.9–23.8 % among Nigerian student populations [21]. In these studies depression has been associated with female gender, alcohol use, poor family functioning, large family size [21], childhood adversities such as emotional neglect [22] and frequent health services use.

Prior studies in Uganda have focused on mental health problems of adolescents in highly vulnerable and marginalised populations such as war traumatised individuals [23] and persons living with human immune deficiency virus (HIV) infection [24]. Further, studies on mental health issues among secondary school students in Uganda have mostly focused on alcohol and substance use problems. In the present study, we use data from four secondary schools to explore the prevalence of depressive symptoms in school-going adolescents. We sought to answer the following questions: What is the prevalence of depressive symptoms in school-going adolescents aged 13–16 years in central Uganda? And to what extent are socio-demographic factors, alcohol/substance use, chronic physical illness, chronic medication use and orphan hood associated with depressive symptoms in this age range?

Methods

Study setting and population

Study participants were school-going adolescents recruited from four secondary schools in Mukono district situated in central Uganda where 88 % of the population is rural consisting of peasants who depend on subsistence agriculture for food and as a source of income. Four secondary schools were chosen using stratified random sampling, so that one school was boarding mixed (boys and girls), one day mixed school, one girls’ only boarding school and one boys’ only boarding school.

Of the four selected schools, 3 were boarding schools and 1 was a day school.

Study procedure

Study data were collected between October and November 2003. The eligibility criteria required participants to be present on the days of interview, be enrolled for at least one year in the participating school, provide assent and have parental/guardian written informed consent. Parents of adolescents in boarding schools were provided with information about the study on visiting days and asked to sign the consent forms thereafter. Adolescents in the day school were provided with information to take to their parents at home who then signed consent forms if they allowed their child to participate in the study. The first author together with research assistants reviewed the study questionnaires with local mental health staff and teachers to ensure local validity and were pretested. Class teachers were asked to distribute study questionnaires to students who were present in class on a given day and were eligible to participate in the study. All questionnaires were administered in English, the official language used in schools. The questionnaires were anonymous and self-administered during regular school hours and took approximately an hour to complete. The first author together with the research assistants checked each questionnaire for any missing data immediately after completion before the student left the study room. Support services and mechanisms of referral for mental health services were available to all participants. The research protocol was approved by the Makerere University School of Medicine Research Ethics Committee, as well as the Uganda National Council of Science and Technology.

Study measures

Socio-demographic variables

In a socio-demographic questionnaire, participants reported their age, gender, marital status of parents, whether their parents were still alive or not, had a physical illness or not, were using any medications, alcohol, drugs or not.

Depression symptoms

Depression symptoms were assessed using the self-administered Children’s Depression Inventory (CDI) which is a comprehensive multi-ratter assessment of depressive symptoms in youth aged 7–17 years [25]. The CDI rates symptoms of depression on five subscales namely; negative mood, interpersonal problems, ineffectiveness, anhedonia and negative self-esteem. It comprises of 27 items rated on a 3-point scale [0 (none) to 2 (distinct symptom)]. Total CDI scores range from 0 to 54 with several recommended clinical cut-off scores (e.g., >13; 13–18; ≥19) to indicate elevated depressive symptoms in youth. In this study, participants who scored 19 points or higher were regarded as having significant depression symptoms. The cut-off point of ≥19 was chosen as this has been found more suitable for community participants, with a sensitivity of 94.7 %, a specificity of 95.6 %, a positive predictive value of 0.90, and a negative predictive value of 0.98 [26, 27].

Depressive disorder

Participants with significant depression symptoms were recalled for evaluation using Mini International Neuro-Psychiatric Interview for children and adolescents 2.0 (MINI-KID), to ascertain DSM IV diagnosis of depression and co morbidity. This was done by the first author who is a psychiatrist with special training in child and adolescent psychiatry and mental health. However this assessment was conducted on only 74 (68 %) of 109 students who scored ≥19 on the CDI since 35 (32 %) could not be traced.

The MINI-KID is a diagnostic structured interview that was developed for DSM-IV psychiatric disorders [28]. It is organized in diagnostic sections. Using branching-tree logic, the MINI KID has two screening questions per disorder. Additional symptoms within each disorder section are asked only if the screening questions are positively endorsed. The psychometric properties of the MINI-KID have not been described in Uganda but MINI-KID has been used in several studies [2932].

A diagnosis of current major depression was made if a study participant positively endorsed five or more questions related to depression symptoms and the one question related to functional impairment over the 4-week period prior to the interview. A diagnosis of dysthymia was made if a study participant positively endorsed depressed or irritable mood for at least one year with two or more symptoms related to depression, had not been without the symptoms for more than 2 months at a time, did not meet criteria for major depressive episode, manic or hypomanic episode, psychotic illness, and the symptoms were not due to the direct physiological effects of a substance(e.g., a drug of abuse, a medication) or a general medical condition (e.g., hypothyroidism) and the symptoms caused clinically significant impairment in social, occupational, or other important areas of functioning.

Substance use, chronic illness and medication use

With regard to substance use, students were asked if they ever smoked tobacco, drank alcohol, or took other drugs (such as marijuana, cocaine, inhalants, and hallucinogens) in a 4-week period prior to the interview. With regard to chronic physical illness, students were provided with a list of chronic conditions (e.g. HIV/AIDS, diabetes, asthma and hypertension) and asked to indicate whether or not they had experienced an episode of any those conditions in a 4-week period prior to the interview. With regard to chronic medication use, students were asked if they were required to take medications for the chronic medical condition that they had.

Statistical analyses

Statistical analysis was carried out with SPSS, version 11.5. Frequencies of participants’ characteristics were computed and logistic regression analyses conducted to determine associations between various participant characteristics and significant depression symptoms. For the bivariate analyses, we used Chi square tests or Fisher’s exact test for categorical variables, and independent-sample t tests for continuous variables. Factors that had a significant bivariate association (p ≤ 0.05) with depression symptoms were then included in a multi-variate logistic regression model. We assessed for multicollinearity by computing the variance inflation factor for the variables in the model.

Results

Sample characteristics

Of the 541 study participants that we approached to take part in the study, 519 (96 %) completed the study questionnaires. The majority were males 301 (58 %), and 306 (59 %) were in the age range of 14–16 years with a mean age of 16 years (SD 2.18). A total of 155 (30 %) participants were orphans. Detailed baseline characteristics of the study participants are presented in Table 1.
Table 1

Frequency of demographic characteristics of the adolescents (N = 519)

Variable

n

%

Gender

 Male

301

58.0

 Female

218

42.0

Age (years)

 <14

47

9.0

 ≥14

472

91

Type of school

 Boys only (boarding)

163

31.4

 Girls only (boarding)

80

15.4

 Boarding mixed

118

22.7

 Day mixed

158

30.4

Nature of family

 Single parent

108

20.8

 Polygamous

155

29.9

 Monogamous

256

49.3

Head of household

 Father

342

65.9

 Mother

122

23.5

 Child

10

1.9

 Other

45

8.7

Orphan hood

 Not orphan

364

70.1

 Paternal orphan

84

16.2

 Maternal orphan

34

6.6

 Double orphan

37

7.1

Prevalence and factors associated with depression symptoms

Of 519 participants screened with the CDI, 109 (21 %) had significant depression symptoms. Of the 109 participants with significant depression symptoms, only 74 were evaluated with the MINI-KID (Table 2) and of these, 8 (11 %) met criteria for major depression and 6 (8 %) met criteria for dysthymia. Therefore, among participants that were assessed with both the CDI and the MINI-KID (n = 484), the prevalence of depressive disorders was 2.9 %. In this sample, 15 (3.1 %) reported current suicidal ideation. Table 3 illustrates the results of the bivariate logistic regression analyses. Results from multivariate analysis indicate that gender (adjusted odds ratio [AOR] 1.50, 95 % CI 1.01–2.01, p ≤ 0.05), living in child headed household (AOR 2.20, 95 % CI 1.11–3.62, p ≤ 0.05), chronic physical illness (AOR 1.25, 95 % CI 1.10–3.02, p ≤ 0.05) and orphan hood (AOR 1.20, 95 % CI 1.00–2.02, p ≤ 0.05) were each independently associated with significant depression symptoms. All variables in the model had a variance inflation factor less than 5 indicating that multicollinearity was not of concern in this model. The commonest psychiatric disorders found among those with significant depression symptoms were social phobia (30 %), panic disorder with or without agoraphobia (28 %), specific phobia (26 %), separation anxiety (16 %), obsessive–compulsive disorder (15 %), conduct disorder (11 %) and alcohol dependence disorder (3 %).
Table 2

Current MINI KID psychiatric disorder amongst the students with CDI scores ≥ 19

DSM IV diagnosis

Frequency

Percentage N = 74

Percentage of total population N = 519

Major depression

8

10.8

1.5

Dysthymia

6

8.1

1.2

Panic disorder with agora phobia (current)

3

4.15

0.6

Panic disorder without agoraphobia (current)

18

24.3

3.5

Separation anxiety (current)

12

16.21

2.3

Social phobia (current)

22

29.72

4.2

Specific phobia (current)

19

25.67

3.7

Obsessive compulsive disorders (current)

11

14.86

2.1

Post-traumatic stress disorder (current)

4

5.4

0.8

Alcohol dependence (current)

2

2.7

0.4

Conduct disorder

8

10.8

1.5

Table 3

Comparison of demographic, family and social characteristics of the adolescents by CDI scores for depression

Variable

Study sample (N = 519)

Depression CDI ≥ 19

No depression CDI < 19

OR (95 % CI)

P value

Gender

 Male

301

52 (17)

249 (83)

1

 

 Female

218

57 (26)

161 (74)

1.7 (1.1–2.6)

0.01

Age

 <14

47

9 (19)

38 (81)

1

 

 ≥14

472

100 (21)

372 (79)

0.99 (0.63–1.55)

0.95

Type of school

 Boys only

163

20 (12)

143 (88)

1

 

 Girls only

80

26 (33)

54 (68)

2.07 (1.18–3.60)

0.01

 Boarding mixed

118

29 (25)

89 (75)

1.31 (0.78–2.18)

0.27

 Day mixed

158

34 (22)

124 (78)

1.06 (0.65–1.71)

0.81

Nature of family

 Monogamous

256

43 (17)

213 (83)

1

 

 Polygamous

155

33 (21)

122 (79)

1.03 (0.63–1.66)

0.91

 Single parent

108

33 (31)

75 (69)

1.94 (1.71–3.22)

0.01

Head of household

 Adult

509

104 (20)

405 (80)

1

 

 Child

10

5 (50)

5 (50)

3.85 (1.07–16.70)

0.02

Orphan hood

 Not orphaned

364

59 (16)

305 (84)

1

 

 Orphaned

155

50 (32)

105 (68)

1.4 (1.61–3.84)

0.05

Chronic physical illness

 Absent

381

73 (19)

308 (81)

1

 

 Present

138

36 (26)

102 (74)

1.64 (1.03–2.63)

0.03

Medication

 Absent

381

79 (21)

302 (79)

1

 

 Present

138

30 (22)

108 (78)

0.91 (0.61–0.97)

0.97

Alcohol/substance use

 Absent

471

94 (20)

377 (80)

1

 

 Present

48

15 (31)

33 (69)

1.76 (0.9–3.4)

0.08

Discussion

This study contributes to the research literature on prevalence and factors associated with depression symptoms among school-going adolescents in sub-Saharan Africa. The prevalence estimate of depression symptoms in this study of 21 % is high and is likely to impair the adolescents’ ability to achieve academically and other areas of functioning. The prevalence of 21 % falls within the range of prevalence estimates obtained from previous studies conducted in both developing [14, 19] and developed countries that used depression screening instruments [3335]. Likewise the prevalence rate of depressive disorder of 2.9 % that we found in this study is similar to what has been reported in studies conducted in the United States where a formal diagnosis of depression has been made among study samples of adolescents [36]. In this study, Kessler and colleagues analyzed data from 10,123 school-going adolescents in the age range of 13–17 years and found a prevalence rate of depressive disorder of 2.6 %. The high rates of depressive symptoms may also be due to general psychosocial distress resulting from general hardships in living, school related stress and poverty while the low rates of Major depressive disorder could be explained by the factors that promote resilience. In our study the research participants were secondary school students, and some of them could have come from high social economic class which has been found to be protective against depressive illness. Indeed Klassen et al. in their study on resilience in former Ugandan child soldiers, found that 27.6 % showed posttraumatic resilience as indicated by the absence of posttraumatic stress disorder, depression as well as clinically significant behavioural and emotional problems. This was attributed to better socioeconomic situation in the family, and more perceived spiritual support among other factors [37]. On the other hand, one would think that the low rates of depression (as measured by MINI KID) could have been a consequence of the selection bias as 35 students out of 109 students who had scored ≥19 points on the CDI were not interviewed. However these students may have left school for other reasons such as poverty, peer influence (Table 2).

In keeping with findings from previous studies, the prevalence of depressive symptoms was more than twice as common in girls as in boys. The excess of affected girls is seen in epidemiological as well as clinical samples, and is robust across different methods of assessment. Previous researchers have explained that sex differences in rates of depression are therefore unlikely to be merely due to differences in help-seeking or reporting of symptoms [38]. Although the reasons for this post-pubertal-onset sex difference are not fully understood, recent studies indicate that this difference is probably due to some combination of age-related changes in biological or social circumstances [39, 40].

The significant association between psychosocial stressors such as being a double orphan, living in a child headed household, and the presence of significant depressive symptoms is not surprising as such stressors have been reported to be significantly associated with adolescent depression and suicidality [41]. In South Africa, Cluver and colleagues found that acquired immuno-deficiency syndrome (AIDS)—orphaned children showed higher depression, anxiety, and post-traumatic stress disorder (PTSD) scores when compared with other-orphans and non-orphans [42]. El-Missiry and colleagues, studied depression in adolescent girls in Egypt using the CDI and found that presence of significant depression symptoms was associated with psychosocial stressors such as, quarrelsome family atmosphere, socioeconomic status, and negative life events [19].

The association between alcohol and drug use and the presence of depressive symptoms in this study is consistent with findings from previous studies [43, 44]. We noted a trend towards greater likelihood of alcohol and drug use in participants with significant depression symptoms than in those without. However, as our data are of a cross-sectional nature, it is not possible to make any inferences about whether the depression symptoms led to alcohol use or vice versa. Thus, longitudinal studies are needed to address this issue.

Consistent with findings from a systematic review of 340 studies investigating the relationship between depressive symptoms in children and adolescents with chronic physical illness [45], the adolescents who reported the presence of a chronic physical illness were more likely to have significant depression symptoms than those who did not report such an illness. Previous researchers have explained that the myriad of complex challenges associated with chronic disease conditions may interfere with regular school attendance [4648], lead to peer rejection which may have detrimental effects on their self-concept [49, 50] and may result in inappropriate parental attitudes and behaviors, which may impair psychological well-being [51].

This study has limitations. First, as the study sample consisted of school-going adolescent in one district we cannot generalize our findings other districts elsewhere in Uganda or other sub-Saharan developing countries. Second, this study did not assess for parental factors and other factors such as coping styles or social support all of which have been associated with adolescent depression in previous studies. Third, the absence of collateral information may maximize effects of recall bias. Fourth, information was collected on exposures and outcomes simultaneously, thus causal relationships are difficult to establish. Fifth, the study did not include those who left school for a variety of reasons yet those who left school could have done so for reasons of depression. Indeed 35 students out of 109 students who had scored ≥19 points on the CDI were not interviewed with the MINI KID as they had left school and this could have affected the prevalence rates. Consequently, this study will only give clues as to whether certain factors may or may not be potential etiological factors of depression symptoms in school-going adolescents in central Uganda. Therefore, studies with better epidemiological design such as the case–control study can be used to investigate risk factor for depression in school-going adolescents.

Despite these limitations, this study, to our knowledge, provides the first prevalence estimates of depression symptoms among a sample of school going-adolescents in a non-conflict region in Uganda. Our study has important implications for school health programs in particular the integration of mental health issues into the school health education and health services. First, school health programs need to embrace locally adapted simple tools to measure depression which will enable us to distinguish depressive symptoms from clinical syndromes of depression because management strategies are different. Second, there is a need to offer stress management programs in which stressful situations among adolescent can be addressed before they affect emotional well-being, this research provides an important first step into current understanding of depression among school-going adolescents, which could be useful in designing school interventions for depression. Thirdly, mental health education for all stakeholders in the education sector must be scaled up to enhance early diagnosis and early interventions.

Conclusion

Significant depression symptoms are highly prevalent among this sample of school-going adolescents and may progress to full-blown depressive disorders. Integration of culturally sensitive psychological interventions to prevent and treat depression among school-going adolescents is desperately needed. There is great need for a child and adolescent mental health policy that will be used to plan for mental health services in schools.

Abbreviations

AIDS: 

acquired immuno-deficiency syndrome

CDI: 

Children Depression Inventory

DSM IV: 

Diagnostic and Statistical Manual of Mental Disorders, 4th Edition

DALYs: 

disability-adjusted life years

HIV: 

human immune deficiency virus

MINI: 

KID mini international neuro-psychiatric interview for children and adolescents

PTSD: 

post-traumatic stress disorder

Declarations

Authors’ contributions

JN-S, EO, SM Conceptualized and designed the study protocol. JN-S, GZR, EN-M managed the literature searches. JN-S, SKM undertook the statistical analyses, and wrote the first draft of the manuscript. SM, EN-M, EO, and GZR revised the manuscript critically for important intellectual content. JN-S, GZR, EO, SM, SKM, SM, EN-M, contributed to the final manuscript. All authors read and approved the final manuscript.

Acknowledgements

EN-M is supported by the MQ Fellow Mental Health Science Award 2015. Grant Number: MQ15FIP100024. The authors would like to acknowledge the diligent work of all research assistants. We thank the study participants for their time and trust; Dr. Noeline Nakasujja and Ms Nakitende Jackie for their useful comments on the manuscript; and Dr. James Walugembe (RIP) who was instrumental in supervising this research.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The dataset(s) supporting the conclusions of this article has been provided in the manuscript text and tables.

Consent for publication

Consent was obtained from all participating schools and participants for publication of data.

Ethics approval and consent to participate

The research protocol was approved by the Makerere University School of Medicine Research Ethics Committee, as well as the Uganda National Council of Science and Technology and written consent was obtained from the parents and assent was obtained from all the participants.

Sources of funding for the research

No funding agency expects a report or copyright to the published article.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Psychiatry, Makerere University, College of Health Sciences
(2)
Mulago National Referral and Teaching Hospital, Ministry of Health
(3)
Department of Psychiatry, Mbarara University of Science and Technology
(4)
Department of Psychiatry, Gulu University
(5)
Department of Child Health and Development, Makerere University, College of Health Sciences

References

  1. Choudhury S, Blakemore SJ, Charman T. Social cognitive development during adolescence. Social Cogn Affect Neurosci. 2006;1(3):165–74.View ArticleGoogle Scholar
  2. Obradovic J, Burt KB, Masten AS. Pathways of adaptation from adolescence to young adulthood: antecedents and correlates. Ann NY Acad Sci. 2006;1094:340–4.PubMedView ArticleGoogle Scholar
  3. Scherf KS, Behrmann M, Dahl RE. Facing changes and changing faces in adolescence: a new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development. Dev Cogn Neurosci. 2012;2(2):199–219.PubMedView ArticleGoogle Scholar
  4. Somerville LH, Jones RM, Casey BJ. A time of change: behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain Cogn. 2010;72(1):124–33.PubMedView ArticleGoogle Scholar
  5. Blakemore SJ. Development of the social brain during adolescence. Q J Exp Psychol. 2008;61(1):40–9.View ArticleGoogle Scholar
  6. Blakemore SJ, Burnett S, Dahl RE. The role of puberty in the developing adolescent brain. Human Brain Mapp. 2010;31(6):926–33.View ArticleGoogle Scholar
  7. Burnett S, Sebastian C, Cohen Kadosh K, Blakemore SJ. The social brain in adolescence: evidence from functional magnetic resonance imaging and behavioural studies. Neurosci Biobehav Rev. 2011;35(8):1654–6.PubMedView ArticleGoogle Scholar
  8. Belfer ML. Child and adolescent mental disorders: the magnitude of the problem across the globe. J Child Psychol Psychiatry. 2008;49(3):226–36.PubMedView ArticleGoogle Scholar
  9. Kieling C, Baker-Henningham H, Belfer M, Conti G, Ertem I, Omigbodun O, et al. Child and adolescent mental health worldwide: evidence for action. Lancet. 2011;378(9801):1515–25 (PubMed PMID: 22008427).PubMedView ArticleGoogle Scholar
  10. Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine HE, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet. 2013;382(9904):1575–86.PubMedView ArticleGoogle Scholar
  11. Ong J, Wong W, Lee A, Holroyd E, Huang SY. Sexual activity and adolescent health risk behaviours amongst high school students in three ethnic Chinese urban populations. J Clin Nurs. 2013;22(23–24):3270–9.PubMedView ArticleGoogle Scholar
  12. Cook MN, Peterson J, Sheldon C. Adolescent depression: an update and guide to clinical decision making. Psychiatry. 2009;6(9):17–31.PubMedPubMed CentralGoogle Scholar
  13. Ospina-Ospina Fdel C, Hinestrosa-Upegui MF, Paredes MC, Guzman Y, Granados C. Symptoms of anxiety and depression in adolescents between 10 to 17 year-old attending schools in Chia, Colombia. Revista de salud publica (Bogota, Colombia). 2011;13(6):908-20. Sintomas de ansiedad y depresion en adolescentes escolarizados de 10 a 17 anos en Chia, Colombia. spa.Google Scholar
  14. Sajjadi H, Mohaqeqi Kamal SH, Rafiey H, Vameghi M, Forouzan AS, Rezaei M. A systematic review of the prevalence and risk factors of depression among iranian adolescents. Global J Health Sci. 2013;5(3):16–27.Google Scholar
  15. Wang L, Feng Z, Yang G, Yang Y, Dai Q, Hu C, et al. The epidemiological characteristics of depressive symptoms in the left-behind children and adolescents of Chongqing in China. J Affect Disord. 2015;177:36–41.PubMedView ArticleGoogle Scholar
  16. Choi H, Gi Park C. Understanding adolescent depression in ethnocultural context: updated with empirical findings. ANS Adv Nurs Sci. 2006;29(4):E1–12.PubMedView ArticleGoogle Scholar
  17. Heger JP, Brunner R, Parzer P, Fischer G, Resch F, Kaess M. [Depression and risk behavior in adolescence]. Praxis der Kinderpsychologie und Kinderpsychiatrie. 2014;63(3):177-99. PubMed PMID: 24707767. Epub 2014/04/09. Depression und Risikoverhalten bei Jugendlichen. ger.Google Scholar
  18. Ruble AE, Leon PJ, Gilley-Hensley L, Hess SG, Swartz KL. Depression knowledge in high school students: effectiveness of the adolescent depression awareness program. J Affect Disord. 2013;150(3):1025–30.PubMedView ArticleGoogle Scholar
  19. El-Missiry A, Soltan M, Abdel Hadi M, Sabry W. Screening for depression in a sample of Egyptian secondary school female students. Journal of affective disorders. 2012 Jan;136(1-2):e61-8. PubMed PMID: 21783261. Epub 2011/07/26. eng.Google Scholar
  20. Rodrigo C, Welgama S, Gurusinghe J, Wijeratne T, Jayananda G, Rajapakse S. Symptoms of anxiety and depression in adolescent students; a perspective from Sri Lanka. Child Adolesc Psychiatry Mental Health. 2010;4:10.View ArticleGoogle Scholar
  21. Adewuya AO, Ola BA, Aloba OO. Prevalence of major depressive disorders and a validation of the Beck Depression Inventory among Nigerian adolescents. Eur Child Adolesc Psychiatry. 2007;16(5):287–92.PubMedView ArticleGoogle Scholar
  22. Jewkes RK, Dunkle K, Nduna M, Jama PN, Puren A. Associations between childhood adversity and depression, substance abuse and HIV and HSV2 incident infections in rural South African youth. Child Abuse Negl. 2010;34(11):833–41.PubMedPubMed CentralView ArticleGoogle Scholar
  23. Okello J, Onen T, Misisi S. Psychiatric disorders among war-abducted and non-abducted adolescents in Gulu district, Uganda: a comparative study. Afr J Psychiatry. 2007;10(4):225–31.Google Scholar
  24. Musisi S, Kinyanda E. Emotional and behavioural disorders in HIV seropositive adolescents in urban Uganda. East Afr Med J 2009;86(1):16–24.PubMedView ArticleGoogle Scholar
  25. Kovacs M. The Children’s Depression Inventory (CDI) manual North Tanawanda. New York, NY: Multi-Health Systems; 1992.Google Scholar
  26. Figueras Masip A, Amador-Campos JA, Gomez-Benito J, del Barrio Gandara V. Psychometric properties of the Children’s Depression Inventory in community and clinical sample. Span J Psychol. 2010;13(2):990–9.PubMedView ArticleGoogle Scholar
  27. Smucker MR, Craighead WE, Craighead LW, Green BJ. Normative and reliability data for the Children’s Depression Inventory. J Abnormal Child Psychol. 1986;14(1):25–39.View ArticleGoogle Scholar
  28. Sheehan DV, Sheehan KH, Shytle RD, Janavs J, Bannon Y, Rogers JE, et al. Reliability and validity of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID). J Clin Psychiatry. 2010;71(3):313–26.PubMedView ArticleGoogle Scholar
  29. Abbo C, Kinyanda E, Kizza RB, Levin J, Ndyanabangi S, Stein DJ. Prevalence, comorbidity and predictors of anxiety disorders in children and adolescents in rural north-eastern Uganda. Child Adolesc Psychiatry Ment Health. 2013;7(1):21.PubMedPubMed CentralView ArticleGoogle Scholar
  30. Idro R, Kakooza-Mwesige A, Asea B, Ssebyala K, Bangirana P, Opoka RO, et al. Cerebral malaria is associated with long-term mental health disorders: a cross sectional survey of a long-term cohort. Malaria J. 2016;15(1):184.View ArticleGoogle Scholar
  31. Klasen F, Schrage J, Post M, Adam H. [Guiltless guilty–trauma-related guilt and posttraumatic stress disorder in former Ugandan child soldiers]. Praxis der Kinderpsychologie und Kinderpsychiatrie. 2011;60(2):125-42. PubMed PMID: 21425638. Epub 2011/03/24. Schuldlos schuldig–Schuldempfinden und Posttraumatische Belastungsstorung bei ehemaligen Kindersoldaten in Uganda. ger.Google Scholar
  32. Okello J, Onen TS, Musisi S. Psychiatric disorders among war-abducted and non-abducted adolescents in Gulu district, Uganda: a comparative study. Afr J Psychiatry. 2007;10(4):225–31.Google Scholar
  33. Fleming JE, Offord DR. Epidemiology of childhood depressive disorders: a critical review. J Am Acad Child Adolesc Psychiatry. 1990;29(4):571–80.PubMedView ArticleGoogle Scholar
  34. Bulhoes C, Ramos E, Lindert J, Dias S, Barros H. Depressive symptoms and its associated factors in 13-year-old urban adolescents. Int J Environ Res Public Health. 2013;10(10):5026–38.PubMedPubMed CentralView ArticleGoogle Scholar
  35. Magklara K, Bellos S, Niakas D, Stylianidis S, Kolaitis G, Mavreas V, et al. Depression in late adolescence: a cross-sectional study in senior high schools in Greece. BMC Psychiatry. 2015;15:199.PubMedPubMed CentralView ArticleGoogle Scholar
  36. Kessler RC, Avenevoli S, Costello EJ, Georgiades K, Green JG, Gruber MJ, et al. Prevalence, persistence, and sociodemographic correlates of DSM-IV disorders in the National Comorbidity Survey Replication Adolescent Supplement. Arch Gen Psychiatry. 2012;69(4):372–80.PubMedView ArticleGoogle Scholar
  37. Klasen F, Oettingen G, Daniels J, Post M, Hoyer C, Adam H. Posttraumatic resilience in former Ugandan child soldiers. Child Dev. 2010;81(4):1096–113.PubMedView ArticleGoogle Scholar
  38. Thapar A, Collishaw S, Pine DS, Thapar AK. Depression in adolescence. Lancet. 2012;379(9820):1056–67.PubMedPubMed CentralView ArticleGoogle Scholar
  39. Garber J. Depression in children and adolescents: linking risk research and prevention. Am J Prev Med. 2006;31(6):104–25.View ArticleGoogle Scholar
  40. Chaplin TM, Gillham JE, Seligman ME. Gender, anxiety, and depressive symptoms a longitudinal study of early adolescents. J Early Adolesc. 2009;29(2):307–27.PubMedPubMed CentralView ArticleGoogle Scholar
  41. Kinyanda E, Kizza R, Levin J, Ndyanabangi S, Abbo C. Adolescent suicidality as seen in rural northeastern Uganda: prevalence and risk factors. Crisis. 2011;32(1):43–51.PubMedView ArticleGoogle Scholar
  42. Cluver LD, Orkin M, Gardner F, Boyes ME. Persisting mental health problems among AIDS-orphaned children in South Africa. J Child Psychol Psychiatry. 2012;53(4):363–70.PubMedView ArticleGoogle Scholar
  43. McCarty CA, Wymbs BT, King KM, Mason WA, Stoep AV, McCauley E, et al. Developmental consistency in associations between depressive symptoms and alcohol use in early adolescence. J Stud Alcohol Drugs. 2012;73(3):444–53.PubMedPubMed CentralView ArticleGoogle Scholar
  44. Brière FN, Rohde P, Seeley JR, Klein D, Lewinsohn PM. Comorbidity between major depression and alcohol use disorder from adolescence to adulthood. Compr Psychiatry. 2014;55(3):526–33.PubMedView ArticleGoogle Scholar
  45. Pinquart M, Shen Y. Depressive symptoms in children and adolescents with chronic physical illness: an updated meta-analysis. J Pediatr Psychol. 2011;36(4):375–84.PubMedView ArticleGoogle Scholar
  46. Gase LN, Kuo T, Coller K, Guerrero LR, Wong MD. Assessing the connection between health and education: identifying potential leverage points for public health to improve school attendance. Am J Public Health. 2014;104(9):e47–54.PubMedPubMed CentralView ArticleGoogle Scholar
  47. Claar RL, Kaczynski KJ, Minster A, McDonald-Nolan L, LeBel AA. School functioning and chronic tension headaches in adolescents improvement only after multidisciplinary evaluation. J Child Neurol. 2013;28(6):719–24.PubMedView ArticleGoogle Scholar
  48. Bould H, Collin SM, Lewis G, Rimes K, Crawley E. Depression in paediatric chronic fatigue syndrome. Arch Dis Child. 2013;98(6):425–8.PubMedView ArticleGoogle Scholar
  49. Gunnarsdottir T, Njardvik U, Olafsdottir A, Craighead L, Bjarnason R. Teasing and social rejection among obese children enrolling in family-based behavioural treatment: effects on psychological adjustment and academic competencies. Int J Obes. 2012;36(1):35–44.View ArticleGoogle Scholar
  50. Sandstrom MJ, Schanberg LE. Peer rejection, social behavior, and psychological adjustment in children with juvenile rheumatic disease. J Pediatr Psychol. 2004;29(1):29–34.PubMedView ArticleGoogle Scholar
  51. Radovic A, Reynolds K, McCauley HL, Sucato GS, Stein BD, Miller E. Parents’ role in adolescent depression care: primary care provider perspectives. J Pediatrics. 2015;167(4):911–8.View ArticleGoogle Scholar

Copyright

© The Author(s) 2016

Advertisement