Prevalence of psychological morbidity and its correlates among school-going adolescents of urban Puducherry, India

INTRODUCTION

Adolescence—a phase of transition from childhood to adulthood is marked with changes that individuals must endure in spheres of physical, emotional and societal aspects of their life.¹ Supportive parenting, encouraging school environment and strong community support smoothens this transition and helps to attain good well-being in adolescents.² Ensuring adolescent well-being is important, as it enhances self-esteem, academic achievement, problem-solving skills and social connectedness in later adulthood.¹ Fortunately, the adolescent phase is uneventful in many, leaving out a subset of them who would succumb to adverse life experiences and experience poor mental health.

In the global context, studies have estimated that 1 in every 4 to 5 adolescents experience any form of mental disorder in a given year.¹ Further, it has been studied in high-income settings that most of the mental disorders that manifest in early adulthood had their onset as early as 12–24 years of age.¹ In India, depression and anxiety, being part of the spectrum of common mental disorders (CMD), contributed to 34% and 19%, respectively, of the total disability-adjusted life years lost due to mental disorders in 2017.³ Thus, it is important to do research focusing on the burden of CMDs and their predictors from a public health perspective.

Important predictors of CMDs in adolescents are: residing in an urban city, having to face emotional abuse and/or neglect from parents or caregivers.^4,5 The prevailing school environment has a considerable role to play in mental well-being, where adolescents with difficulty in coping with academic pressure and lacking supportive relationships with peers undergo considerable psychological stress.⁶ The background stress accentuates in adolescents, particularly during their higher secondary education, given the existing bottleneck for opportunities to pursue higher education in India, further lowering the threshold for suffering psychological morbidity. Since schools are a better platform for delivering mental health interventions, having school-based estimates of psychological morbidity and risk profiles is important to decide on context-specific interventions. With this background, we estimated the burden of psychological morbidity in school-going adolescents in classes 11 and 12 in schools of urban Puducherry, along with its correlates such as academic, personal and health-related, with a special focus on perceived psychological stress.

METHODS

RESULTS

A total of 820 school-going adolescents in classes 11 and 12 of the selected schools were surveyed, with 627 participants chosen from 3 private and 193 participants from 1 government school. The mean (SD) age of the participants was 16.1 (0.8) years. The survey included 417 (50.9%) males and 415 (50.6%) were studying in class 11. The median (IQR) GHQ scores obtained by the participants was 3 (1–6).

The prevalence of psychological morbidity measured using GHQ-12 was 25.4% (95% CI 22.4–28.5). Psychological morbidity did not vary significantly within the subgroups of gender, type of school and current class of study. Considering academic factors, adolescents reporting peer pressure for academic performance (PRR 1.3; 95% CI 1.0–1.6) and lack of extracurricular activities at school (PRR 1.5; 95% CI 1.1–1.8) had higher chances of having psychological morbidity (Table I).

Personal factors such as having parental conflicts, being subjected to torture by parents and reporting substance abuse by the father had a significant association with psychological morbidity only in univariate analysis and not in multivariate analysis. Among health-related factors, adolescents who reported that they had difficulty in coping with pubertal changes (PRR 1.3; 95% CI 1.1–1.7), being worried about their physical appearance (PRR 1.3; 95% CI 1.0-1.6), reporting substance abuse (PRR 1.8; 95% CI 1.2–2.6) and experiencing sleep disturbances (PRR 1.8; 95% CI 1.4–2.3) had greater chances of being screened with psychological morbidity (Table I).

A total of 384 (46.8%) school-going adolescents were screened to have psychological stress using PSS-10. Median (IQR) PSS scores obtained by the participants were 19 (13–25). Participants with psychological morbidity had a higher median (IQR) PSS scores (26 [20–30]) than those without psychological morbidity (17 [12–22]; Fig. 1). In the multivariate model, participants with psychological stress had 2.4 times higher chances of having psychological morbidity (PRR 2.4; 95% CI 1.8–3.4; Table I).

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FIG 1.

Distribution of scores of perceived stress scale-10 among school-going adolescents with or without psychological morbidity

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DISCUSSION

This cross-sectional survey conducted in school-going adolescents in higher secondary schools of urban Puducherry showed the prevalence of psychological morbidity of about 25%, using the GHQ-12 questionnaire. Our estimate is comparable to the pooled estimates of psychological morbidity, ranging between 25% and 31%, generated from a meta-analysis of studies done among adolescents using GHQ-12 in global settings.¹⁴ However, the fact that this meta-analysis had a lesser representation of studies from low- and middle-income countries (LMICs) limits the comparability of its estimates to our study and also highlights the need to generate more evidence on burden estimates of psychological morbidity from LMICs, particularly in the Indian setting.¹⁴ In 2015, the population-level estimates of overall mental disorders, from the National Mental Health Survey in India (NMHS), was shown to be 7.3% (5.8–8.7) among Indian adolescents, with depression, anxiety and stress-related disorders contributing to the maximum.¹⁵ Compared to NMHS, our study estimated psychological morbidity almost three times that of the NMHS survey and this difference could be because of having a community-based sampling approach and using a different study tool, the MINI-Kid questionnaire in the NMHS survey.

While looking at various Indian studies on adolescent mental health, as summarized in a recent narrative review, we found heterogeneity in the estimation of psychological morbidity across the Indian study settings.¹⁶ This review highlighted that the study setting, either school-based or community-based, could be a determinant for variation in burden estimates. Further, school-based studies provided a wider estimate of depression ranging between 2% and 80%, compared to community-based studies, which provided more conservative estimates, ranging between 0% and 16%.¹⁶ The probable explanation for having higher estimates of psychological morbidity in school settings could be the clustering effect of risk factors and outcomes, at the level of school. On the contrary, community-based sampling offers scope for a representative sample by eliminating the cluster effect brought in by the schools. Also noted was that the Indian studies based on screening tools such as GHQ or PHQ have estimated psychological morbidity in adolescents on a higher side compared to those studies using tools constructed based on DSM-IV and/or ICD-10 criteria such as Development and Well-being assessment or MINI-KID, which reported a conservative estimate of psychological morbidity ranging between 1.8% and 7.3%.^15,17 Therefore, varied estimates of psychological morbidity in studies included in the review would be due to the use of different tools for evaluation across these studies, application of different cut-offs in classifying caseness even among studies that used the same tools and the set objectives of these studies, to either screen or establish a clinical diagnosis for psychological morbidity, in the population being studied.¹⁶

The significant risk factors for psychological morbidity reported by our study can be broadly categorized under academic factors including peer pressure for academic performance and lack of extracurricular activities and, health-related factors such as unable to cope with pubertal changes, perceived body image, substance abuse, sleep disturbances and perceived psychological stress. In line with our findings, studies from Gujarat and Goa have reported factors such as facing difficulties with education, abnormal sleep patterns, history of physical or verbal abuse and substance abuse to be associated with psychological morbidity in adolescents.^4,17,18 Considering the profile of risk factors identified in this study as well as from other Indian studies, we can infer that there is an interplay of academic and health-related factors in determining mental wellness in adolescents. Thus, strategies for risk prevention and mental health promotion should be incorporated both at school as well as the family level to bring about a decrease in mental morbidity.^5,19

Although there is limited evidence to establish the positive effect of mental health promotive interventions in adolescents from Indian settings, studies from high-income settings have shown that incorporating life skills education in the school curriculum is effective in reducing mental morbidity.⁵ A life skills approach comprising of physical activity, stress management techniques, interpersonal skills and effective communication can mitigate the risk factors noted in our study such as lack of extracurricular activity, perceived psychological stress and difficulty to cope with pubertal changes.^5,19 In addition, a supportive family environment provides a window of opportunity for adolescents to discuss health-related and sensitive issues.⁵ Complementary to these initiatives at the school and family level for promoting adolescent mental health, there is a need to strengthen the existing adolescent-friendly clinics under ‘Rashtriya Kishore Swasthya Karyakram’, a Government of India initiative to address diverse issues on adolescent health and well-being.²⁰

The strengths of this study are a larger sample size, the use of validated instruments such as GHQ and PSS, which have been widely used across Indian settings and having these questionnaires self-administered by participants, thereby avoiding social desirability while responding. The potential limitation with this study would be establishing causality of risk factors to psychological morbidity, as the ascertainment of risk factors and the outcome was made at the same time point.

Conclusions

Our study estimated that one-fourth of school-going adolescents in urban Puducherry suffered psychological morbidity. Factors related to academics and health were attributable to the considerable burden of psychological morbidity in school-going adolescents. This study highlights the need to address these issues through the provision of a supportive school environment and adolescent-friendly health initiatives to reduce the psychological disease burden.