|Year : 2020 | Volume
| Issue : 2 | Page : 102-108
Determinants of psychological distress among school-going girls in a rural district of Haryana, India: A multivariate analysis
Sanjeet Panesar1, Abhishek Singh2, Vikas Gupta3, Pawan Kumar Goel2
1 Department of Community Medicine, Dr. RML Hospital and PGIMER, New Delhi, India
2 Department of Community Medicine, SHKM Government Medical College, Nalhar, Haryana, India
3 Department of Community Medicine, Government Medical College, Shahdol, Madhya Pradesh, India
|Date of Submission||24-Jul-2020|
|Date of Decision||18-Sep-2020|
|Date of Acceptance||05-Oct-2020|
|Date of Web Publication||21-Dec-2020|
Department of Community Medicine, Government Medical College, Shahdol, Madhya Pradesh
Source of Support: None, Conflict of Interest: None
Background: Mental health of children is not adequately explored in India, especially in Haryana. If untreated, these conditions severely influence children's development and their potential to live fulfilling and productive lives. In this study, we aimed to screen school -going adolescent girls for common mental disorders and find potential psycho social and socio demographic determinants.
Materials and Methods: This cross-sectional study was done January to March 2019 and included 649 school-going adolescent girls (12–19 years). This study used a pretested, predesigned, standardized questionnaire and General Health Questionnaire-12 (GHQ-12). Multiple logistic regression had been done to find the strength of association between dependent variable and independent variables. All tests were performed at a 5% level of significance.
Results: The overall mean age (±standard deviation) of study participants was 15.5 ± 1.09 years with nearly equal distribution in each standard. Two hundred and eighty-three participants (43.6%) had a score of 3 or more for GHQ-12, which is suggestive of mental health problems. The GHQ-12 score was higher in young age adolescents (53.3%), those studying in the ninth standard (65.4%), the adolescents belonging to nuclear family, higher socioeconomic status, and having previous exposure to mental health programs.
Conclusion: Mental health problems are highly prevalent among the adolescent population in India. In the scope of preventive health services, health workers shall provide information to the adolescents and their parents about these specific psychiatric changes and provide psychological help for children and adolescents by the guiding the teachers working at the schools. In addition this will help to establish a positive and supportive relationship between the teachers and students.
Keywords: Adolescence, General Health Questionnaire-12, mental health
|How to cite this article:|
Panesar S, Singh A, Gupta V, Goel PK. Determinants of psychological distress among school-going girls in a rural district of Haryana, India: A multivariate analysis. J Curr Res Sci Med 2020;6:102-8
|How to cite this URL:|
Panesar S, Singh A, Gupta V, Goel PK. Determinants of psychological distress among school-going girls in a rural district of Haryana, India: A multivariate analysis. J Curr Res Sci Med [serial online] 2020 [cited 2021 Apr 21];6:102-8. Available from: https://www.jcrsmed.org/text.asp?2020/6/2/102/304207
| Introduction|| |
Worldwide, there is a continuous rise in mental health problems, and a significant section of adolescents, particularly girls, are affected by it. Adolescence is a transitional developmental period characterized by pronounced biological as well as social changes., Puberty along with brain and cognitive maturation leads to enhanced social understanding and self-awareness. Developmental transition in brain circuits is involved in responses to reward and danger, and increased stress levels are reported comparatively higher in girls., The global prevalence of mental disorders among adolescents was found to be around 31% in a recent systematic review and meta-analysis of 43 studies conducted in 19 countries during the period of 1996–2018. In India, the prevalence of adolescent psychiatric disorders at the level of community and schools is estimated to be around 7% and 23%, respectively, which is a remarkably huge burden., About one-fifth (21.4% or 243 million) of India's population is constituted by the adolescents who can transform the social and economic fortunes of the country. Adolescent girls constitute a vulnerable group not only with respect to their social status but also in relation to health. Hence, assessment of mental health in India will, in turn, affect global health. When adolescents are away from home, they spend majority of their time in school. School teachers can play an important role in identification of mental health needs of students, but in the present context, they are not well trained or oriented to pick up the early warning signs. Primary health-care providers, on the other hand, may lack the time and patience required to identify and manage these disorders in their routine, already busy practices. This is where the use of screening tools or procedures would benefit the situation. General Health Questionnaire-12 (GHQ-12) is one of the tools to screen the common mental disorders., Mental health of children is not adequately explored in India, especially in Haryana. If untreated, these conditions severely influence children's development and their potential to live fulfilling and productive lives. In this study, we aimed to screen for common mental disorders and find sociodemographic and psychosocial determinants for positive screened school-going adolescent girls in a rural area in Haryana. This type of study will enlighten about the mental status of adolescent girls and could play an important part in planning and implementation of services and interventions, if required.
| Materials and Methods|| |
Study area and study period
The present study was conducted during the months of January to March 2019 in the service area of a rural health center, Nalhar, which also happens to be a field practice area under the aegis of the Department of Community Medicine, SHKM GMC, Nalhar, Haryana.
Study design and the participants
This cross-sectional study included school-going adolescent girls (12–19 years) as participants.
Study population and sample size
A total of 15 secondary schools including 10 government and 5 private schools were listed in the study area, and the school principals were approached to obtain permission for conducting the study. Only two government schools provided permission for conducting study and following which interview dates of the study were fixed. The line listing of students from the 9th standard to the 12th standard was done for both the schools; total students were about 840. Out of 840 students, only 649 students gave their assent to participate in the study. Also, written informed consent was obtained from parents for student's participation in the study. Anonymity and confidentiality of the participants was maintained throughout the study. Students who were seriously ill were excluded from the study.
The sample size was calculated (n = 601) considering the proportion of adolescents having mental health problems as 50% (studies not found in rural Haryana) with confidence level of 95% and 4% absolute allowable error by applying the following formula: N = (Z1−a/2)2 × p (1 − p)/d2, where Z = Standard normal variate for level of significance (at 5% type I error [P < 0.05], Z = 1.96 for two-sided test), a = Level of significance (0.05), p = Prevalence (proportion – 50%), d = Absolute allowable error (4%), and n = Sample size. Although the calculated sample size came out to be 601, a sample of 649 study participants was included for the study.
A pretested, predesigned, standardized questionnaire was prepared, and it included details regarding sociodemographic characteristics, psychosocial characteristics, and GHQ-12. The questionnaire was first prepared in English. Then, it was translated into Hindi by an expert in that language keeping semantic equivalence. To check the translation, it was translated back to English by two independent researchers who were unaware of the first English version.
The collected questions were subjected to content validation by a panel of 10 medical experts. The purpose was to identify the items with a high degree of agreement among experts. Aiken's V was used to quantify the concordance between experts for each item. Questions that had an Aiken's V >0.7 were selected for the study. All efforts were made to keep the questions simple and unambiguous according to the objectives of the study.
The psychosocial characteristics included disturbance in the study and sleep, comparison to peers, substance use, feeling of inferiority in academics and looks in comparison with peers. The GHQ-12 is a validated tool with adequate sensitivity and specificity for screening of common mental health problems among adolescents, and it identifies the presence of any possible nonpsychotic mental health disorders in the last 1 month, such as anxiety, depression, and psychological distress among adolescents. Every question was compulsory, and a score of three or more was suggestive of mental health disorders and required further assessment.
The socioeconomic status (SES) was obtained using the modified B.G. Prasad SES classification (revised for the year 2019, CPI 2001 as a base).
Everyday activity included briefing of the study through face-to-face interaction among students of different classes. After interaction session, the self-administered questionnaire was filled by participants under the direct supervision of the investigator and to avoid any discussions with the fellow students during filling of questionnaire, a strict vigilance was followed with the help of school teachers. The participants took part in the batches of 12–15 counts per session, so that day-to-day academic activities of school are not hampered. In this way, all selected students were covered in the study during the defined period. The questionnaire required 30–45 min per batch to be completed. The completed questionnaires were then collected and checked for completeness. Ethical approval was obtained from the Institutional Ethical Committee (Approval letter number: EC/OA-10/2018).
Collected data were entered in the MS Excel spreadsheet, coded appropriately, and later cleaned for any possible errors. The analysis was carried out using IBM SPSS Statistics for Windows, version 22.0 (IBM Corp. Armonk, NY, USA). During data cleaning, more variables were created so as to facilitate the association of variables. Clear values for various outcomes were determined before running frequency tests. Categorical data were presented as percentages (%), and continuous data were presented as mean and standard deviation (SD). Multiple logistic regression had been done to find the strength of association between dependent variable and independent variables. First, a univariate regression was done to ascertain the relationship of the dependent variable with other independent variables. Only those found to be significant were entered into the multiple logistic regression model. All tests were performed at a 5% level of significance; thus, an association was significant if P < 0.05.
| Results|| |
The present study was conducted in two government schools, with a total of 649 participants studying in the 9th to 12th standard. The overall mean age (±SD) of study participants was 15.5 ± 1.09 years, with nearly equal distribution in each standard. Mothers of more than two-fifth participants (43.5%) were illiterate, and majority of the participants (82.2%) belonged to Muslim religion. More than half of the participants (58.1%) were staying in joint families, and more than two-third of the participants (67.5%) had working mothers. Near one-fourth of the participants (26.3%) were never exposed to advertisements regarding mental health. Out of 649 study participants, 283 participants (43.6%, 95% confidence interval [CI]: 39.8–47.5) had a score of 3 or more, which means that 43.6% were having more than three symptoms suggestive of mental health problems, which is an alarming observation [Table 1].
|Table 1: Distribution of responses by study participants for each item of General Health Questionnaire-12 (n=649)|
Click here to view
The GHQ-12 score was higher among more than half of the young age adolescents (53.3%) and those studying in the ninth standard (65.4%). Mother's education and working status played a big role as the GHQ score was higher among more than half of the adolescents whose mothers were either illiterate (59.9%) or nonworking (50.2%). The adolescents belonging to nuclear family, higher SES, and having previous exposure to mental health programs had lower GHQ-12 score [Table 2].
|Table 2: Association between General Health Questionnaire-12 score and sociodemographic characteristics of study participants (n=649)|
Click here to view
[Table 3] shows that the psychosocial variables such as comparison with peers, disturbance in studies, feeling of inferiority in looks or academics when compared with peers, and abnormal sleep were significantly associated with higher GHQ-12 score (P < 0.05).
|Table 3: Association between General Health Questionnaire-12 score and psychosocial characteristics of study participants (n=649)|
Click here to view
Stepwise logistic regression analysis [Table 4] revealed that the higher GHQ-12 score using sociodemographic variables, majority were found to be statistically significant. Study participants belonging to age groups 12–14 years and 15–17 years were nearly 2.3 (adjusted odds ratio [aOR]: 2.29, 95% CI: 1.52–3.42, P = 0.022) and 1.3 times more likely to be have higher GHQ-12 score than study participants belonging to the age group of 18 years or more. Mother's education and family SES showed a trend with higher GHQ-12 score, where study participants with illiterate mothers and lower SES class families had 3.1 and 9 times more odds of practicing higher GHQ-12 score than study participants with mother's higher education level and family with upper SES class (aOR: 3.13, 95% CI: 1.71–5.7, P = 0.031 and aOR: 9.00, 95% CI: 2.27–35.64, P = 0.000). Disturbance in study (aOR: 1.75, 95% CI: 1.23–2.47, P = 0.002), comparison with peers (aOR: 1.97, 95% CI: 1.26–3.08, P = 0.003), and abnormal sleep pattern (aOR: 2.10, 95% CI: 1.29–3.40, P = 0.003) also showed a high positive association with odds of higher GHQ-12 score.
|Table 4: Independent association of variables and General Health Questionnaire-12 score among study participants (logistic regression analysis) (n=649)|
Click here to view
| Discussion|| |
Of 649 adolescent girls in the age group of 12–19 years, nearly half of them (43.6%) had psychological distress measured using GHQ-12. Similar studies conducted by Nayak and Lavania, Kumar et al., Nair et al., Kafle et al., and Antara et al.,,,, in other states of country showed the prevalence of psychological distress as 16.4%, 59.0%, 33.3%, 35.0%, and 19.1%, respectively. A global meta-analysis done by Polanczyk et al., which included 41 studies conducted between 1985 and 2012 in 27 countries, reflected a global prevalence of mental disorders in adolescents of 13%. This is of vital concern as poor mental health is strongly related to other health and development concerns in adolescents, notably lower educational achievements, substance abuse, violence, and poor reproductive and sexual health.
The GHQ-12 score was higher among more than half of the young age adolescents (53.3%) and those studying in the ninth standard (65.4%). The studies conducted by Mangal et al., and Chauhan and Dhar, also showed that psychological distress was significantly higher among young adolescents when compared to late adolescents., Mother's education and working status played a big role as the GHQ score was higher among more than half of the adolescents whose mothers were either illiterate (59.9%) or nonworking (50.2%). The finding was supported by the studies Roy et al. and Niranjjan et al., whereas it was in contrast with the studies done by Aggarwal and Berk and Lok et al.,,, Mental health status improved in the positive direction as the level of education of mothers got higher. This may be due to the fact that parents with higher education levels are more knowledgeable about approaching the child in adolescence. The parent's relationship to the adolescent contributes to the self-worth of the adolescent. Particularly, parent support is an important factor for adolescents to perceive themselves as important and valuable. Mothers who do not work can spend more time with their children at home and work closely with them.
The adolescents belonging to nuclear family, higher SES, and having previous exposure to mental health programs had lower GHQ-12 score. The findings from the studies done by Mangal et al., Chauhan and Dhar, Jaisoorya et al., and Shukla et al. supported the present study findings,,,, but the studies by Niranjjan et al. and Aggarwal and Berk have shown contrasting findings as the joint families provided immunity against psychological distress when compared to the nuclear families., The psychosocial variables such as comparison with peers, disturbance in studies, feeling of inferiority in looks or academics when compared with peers, and abnormal sleep were significantly associated with higher GHQ-12 score and in coherence with the study done by Mangal et al.
Stepwise logistic regression analysis revealed that the higher GHQ-12 score using sociodemographic variables, majority were found to be statistically significant. The study by Mangal et al. showed that among sociodemographic characteristics, the type of school (adjusted odds of private is 1.8 and government 1.6), mother's higher education (3.0), father's less education (3.1), and working mother (1.5) had shown a significant association with positive cases of the girls. Among psychosocial factors, abnormal sleep patterns (1.9) and disturbance in studies (2.3) have been found statistically significant for the presence of mental health problems among adolescent girls as per the GHQ score. Similar results were obtained in a study by Chauhan and Dhar, where it was found that age, gender, education, caste, household economic status, media exposure, and religion to be significantly associated with mental health problem. However, a study by Shukla et al. showed that on applying the multiple logistic regression, no statistical association was found between mental distress with respect to age group, class, religion, caste and mother's education, and type of family (P > 0.05). The nonparticipation of majority of the schools can be considered as the limitation of the present study as if majority of the schools would have provided permission to conduct the study, the findings of the study would have more generalizability and better representation when compared to the present one.
Although adolescent mental health is an upcoming global issue, it is of more serious concern in low-income and middle-income countries like India (where majority of the adolescent population harbor) owing to resource crunch and limited health-care infrastructure. This is further complicated by stigma related to mental illness in this culture. Identification of significant load builds up a cause for having the “Life skills” education as part of the curriculum and training of school teachers. This study also highlights the advantages of GHQ-12 as a screening tool. It is significantly shorter and easier to use than other similar questionnaires. It is downloadable free of charge and can be used by workers at the community level and even school teachers who are not highly trained in mental health. However, a larger study would help identify the psychometric properties of SDQ better.
| Conclusion|| |
Mental health problems are highly prevalent among the adolescent population in India. A significant proportion of school-going girl adolescents harbor mental health problems, which accounted for 43.6%. In the scope of preventive health services, health workers shall provide information to the adolescents and their parents about these specific psychiatric changes and provide psychological help for children and adolescents by the guiding the teachers working at the schools. In addition this will help to establish a positive and supportive relationship between the teachers and students. Further, it is suggested that adolescents should be evaluated more often in schools for their mental health. This study can bring awareness about the mental health of children among their teachers and parents and can guide them to take necessary intervention.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Patton GC, Viner R. Pubertal transitions in health. Lancet 2007;369:1130-9.
Cyranowski JM, Frank E, Young E, Shear K. Adolescent onset of the gender difference in lifetime rates of major depression. Arch Gen Psychiatry 2000;57:21-7.
Blakemore SJ. The social brain in adolescence. Nat Rev Neurosci 2008;9:267-77.
Silberg J, Pickles A, Rutter M, Hewitt J, Simonoff E, Maes H, et al
. The influence of genetic factors and life stress on depression among adolescent girls. Arch Gen Psychiatry 1999;56:225-32.
Nelson EE, Leibenluft E, McClure EB, Pine DS. The social re-orientation of adolescence: A neuroscience perspective on the process and its relation to psychopathology. Psychol Med 2005;35:163-74.
Silva SA, Silva SU, Ronca DB, Gonçalves VS, Dutra ES, Carvalho KM. Common mental disorders prevalence in adolescents: A systematic review and meta-analyses. PLoS One 2020;15:e0232007.
Malhotra S, Patra BN. Prevalence of child and adolescent psychiatric disorders in India: A systematic review and meta-analysis. Child Adolesc Psychiatry Ment Health 2014;8:22.
Murthy RS. National mental health survey of India 2015-2016. Indian J Psychiatry 2017;59:21-6.
] [Full text]
Jailkhani SM. Patterns and problems of menstruation among the adolescent girls residing in the urban slum. Sch J Appl Med Sci 2014;2:529-34.
Tait RJ, French DJ, Hulse GK. Validity and psychometric properties of the General Health Questionnaire-12 in young Australian adolescents. Aust N Z J Psychiatry 2003;37:374-81.
Baksheev GN, Robinson J, Cosgrave EM, Baker K, Yung AR. Validity of the 12-item General Health Questionnaire (GHQ-12) in detecting depressive and anxiety disorders among high school students. Psychiatry Res 2011;187:291-6.
Hankins M. The reliability of the twelve-item general health questionnaire (GHQ-12) under realistic assumptions. BMC Public Health 2008;8:355.
Pandey V, Aggarwal P, Kakkar R. Modified BG prasad socio-economic classification, update-2019. Indian J Community Health 2019;31:123-5.
Nayak M, Lavania S. Psychiatric morbidity among school students. Int J Contemp Pediatr 2018;5:2048-51.
Kumar S, Dixit V, Chaudhury S, Kenswar DK. Racial differences in suicidal ideation among school going adolescents. Ind Psychiatry J 2013;22:118-24.
] [Full text]
Nair S, Ganjiwale J, Kharod N, Verma J, Nimbalkar SM. Epidemiological survey of mental health in adolescent school children of Gujarat, India. BMJ Paediat Open 2017;1:e000139.
Kafle TK, Mashreky S, Kafle TK, Rimal HS, Sapkota D, Pokhrel A. Behavioral problems among school going adolescents in Eastern Development Region of Nepal. BJHS 2019;4:712-7.
Antara S, Bansal R, Gupta CK. Assessment of mental well-being among school going adolescents using GHQ-12. Indian. J Public Health Res Develop 2019;10:703-6.
Polanczyk GV, Salum GA, Sugaya LS, Caye A, Rohde LA. Annual research review: A meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. J Child Psychol Psychiatry 2015;56:345-65.
Mangal A, Thakur A, Nimavat KA, Dabar D, Yadav SB. Screening for common mental health problems and their determinants among school-going adolescent girls in Gujarat, India. J Family Med Prim Care 2020;9:264-70.
] [Full text]
Chauhan SK, Dhar M. Prevalence and predictors of mental health disorder among the adolescent living in the slums of Lucknow, India: A cross-sectional study. Community Ment Health J 2020;56:383-92.
Roy R, Mukherjee S, Chaturvedi M, Agarwal K, Kannan AT. Prevalence and predictors of psychological distress among school students in Delhi. J Indian Assoc Child Adolescent Ment Health 2014;10:150-66.
Niranjjan R, Sarkar S, Balajee K, Srinivasan M. Psychological distress, hopelessness and health service needs of late adolescents in rural Pondicherry, South India. Int J Community Med Public Health 2018;5:1109-15.
Aggarwal S, Berk M. Evolution of adolescent mental health in a rapidly changing socioeconomic environment: A review of mental health studies in adolescents in India over last 10 years. Asian J Psychiatry 2015;13:3-12.
Lok N, Bademli K, Canbaz M. Factors affecting adolescent mental health. New. Trends. Issues. Proceedings. Humanities. Social. Sciences 2017;4:31-6.
Jaisoorya TS, Geetha D, Beena KV, Beena M, Ellangovan K, Thennarasu K. Prevalence and correlates of psychological distress in adolescent students from India. East Asian Arch Psychiatry 2017;27:56-62.
Shukla NK, Shukla M, Ahmad S, Shukla R, Khan Z. A cross-sectional study on depression among school going adolescent girls in Barabanki district, Uttar Pradesh, India. Int J Contemp Pediatr 2017;4:178-81.
[Table 1], [Table 2], [Table 3], [Table 4]