Indian Journal of Private Psychiatry
Volume 13 | Issue 2 | Year 2019

Sociodemographic and Clinical Profile of Patients Attending a Private Psychiatry Clinic in Assam, India

Prosenjit Ghosh1, Monu Doley2, Anshuman Gogoi3

1–3Department of Psychiatry, Silchar Medical College and Hospital, Silchar, Assam, India

Corresponding Author: Prosenjit Ghosh, Department of Psychiatry, Silchar Medical College and Hospital, Silchar, Assam, India, Phone: +91 9435072563, e-mail:

How to cite this article Ghosh P, Doley M, Gogoi A. The Sociodemographic and Clinical Profile of Patients Attending a Private Psychiatry Clinic in Assam, India. Ind J Priv Psychiatry 2019;13(2):52–57.

Source of support: Nil

Conflict of interest: None


Background: Mental illness is a public health issue all over the world. The morbidity pattern in private clinics differs significantly from general hospitals. Private psychiatric clinics provide help for large number of our population, but they have seldom been evaluated systematically. It has been observed that many patients particularly from upper socioeconomic background prefer visiting a private clinic. Hence, the study is planned in this direction. The study was aimed to assess the morbidity pattern of psychiatric patients attending a private psychiatric clinic.

Aim: To analyze the clinical and sociodemographic characteristics of the clients attending the private clinic and to study the pattern of follow-up.

Materials and methods: All records from February 1, 2019 to April 30, 2019 were analyzed. This is a descriptive study.

Results and conclusion: A total of 1,020 new patients visited the clinic in this period. We found that mental disorders comprise a wide variety of disorders—mainly psychotic, mood disorders, and neurotic disorders. They affect the most productive age groups, almost equally affect both the genders, and there was a slight preponderance of rural patients.

Keywords: Analysis of a psychiatric clinic, Demographic profile, Dropout, Morbidity, Private psychiatric clinic.


In developing countries with acute shortages of mental health professionals, the delivery of mental health services through general healthcare is considered as the most viable strategy for increasing the access of underserved populations to mental healthcare. Mental health facilities in the government setup are very limited, and a vast population of this country’s mental healthcare is provided by private practitioners and hospitals. According to the World Mental Health Atlas1 2014, there were 0.3 psychiatrist per lakh of population in India. Psychologists and psychiatric social workers were even fewer.

Mental illnesses are the major source of morbidity across both developed and developing countries. Mental illnesses affect people of all age groups. They are an important health problem that refers to disorders of mood, thought, cognition, intelligence, personality, substance abuse, and adjustment with the people around them. The spectrum of this issue ranges from simple anxiety disorder to depressive disorders to treatment-resistant schizophrenia and even death.2 The global neglect of mental health is well-documented. Mental health issues are neglected in policy, planning, and funding. In all countries, there is a significant gap between the prevalence of mental disorders, on one hand, and the number of people receiving care and treatment, on the other hand.3 In low and middle income countries (LAMIC) countries, the gap is more: 67% treatment gap for major depression in Africa, compared with a 45% gap in Europe.4 It has been estimated that globally more than 400 million people have been affected by some kind of mental illness during their lifetime and majority of them residing in developing countries.5 According to the WHO report of 2014, nearly 83 million people of the United States have been diagnosed with psychiatric disorder; among all the psychiatric illnesses, depression is the most common. The WHO European Region report stated that 1 out of 15 people suffer from major depression, which is remarkably high and quite alarming.6 The study of South Africa7 reported the lifetime prevalence of common mental disorders to be about 30%. The Ministry of Health and Family welfare of India8 suggested the lifetime prevalence of mental disorders to be nearly 12%, which is likely to increase to almost 15% by the year 2020.

The present work was undertaken with the aim to study the sociodemographic characteristics and the clinical profile of patients attending the private psychiatry clinic situated in a district headquarter of southern Assam, India.


To analyze the sociodemographic and diagnostic distribution of the patients attending the clinic and to study the pattern of follow-up.


The first author is running a private psychiatric clinic, and the relevant data of the patients coming to the clinic during the study period were recorded digitally. This is a retrospective study where case records of all new patients attending the private psychiatry clinic and diagnosed according to ICD-109 were analyzed.

Analysis of the Data

These data are for the period from February 1, 2019 to April 30, 2019. The recordkeeping was started from January 2019 and a 3-month study period was chosen as average attendance per month in the clinic was 300 for last few years. All records were analyzed by the second author. Diagnosis was reassessed after analyzing the record again and many diagnoses were changed. The ICD-10 diagnostic system was used. But, sometimes, symptomatic diagnosis like headache has also been used. Improvement has been recorded as mentioned in the case record on the last entry. The record may have indicated improved, unchanged, or worse. No scales were used, and these could be taken as subjective assessment of the patients, their caretakers, and the clinicians. Data were analyzed using SPSS version 21 and association was seen with the Chi-square test and the significance level was set at 0.05.

Table 1: Sociodemographic details—age, gender, residence, and marital status distribution
Age distribution (years)
    0–10    16    1.6
    11–20  101    9.9
    21–30  244  23.9
    31–40  235  23.0
    41–50  204  20.0
    51–60  105  10.3
    61–70    70    6.9
    71–80    35    3.4
    81–90      8    0.8
    >90      2    0.2
Gender distribution
    Male  535  52.5
    Female  485  47.5
    Rural  566  55.5
    Urban  454  44.5
Marital status
    Married  610  59.8
    Single  345  33.8
    Widowed    46    4.5
    Divorced    19    1.9


After the study period was over, total 1,020 patient’s data were analyzed. A total of 1,020 patients who attended a private psychiatric clinic in a town in Assam during the study period were included in the study. Of the 1,020 patients, 535 (52.5%) were males and 485 (47.5%) were females. Nearly 67% of the study population belonged to the 21–50 years’ age group that is economically most productive. A total of 610 patients (59.8%) were married, 345 (33.8%) were unmarried, 46 (4.5%) were widowed, and 19 (1.9%) were separated (Table 1).

As the study was conducted in a town, 566 patients (55.5%) were from urban area and remaining 454 (45.5%) from rural area. Nearly 94% of the patients were literate, 35% had completed high school and 13.4% completed graduation, and 4.3% had either postgraduation or professional education as shown in Table 2. A majority of the study population was economically well-off with 81.9% belonging to the middle and lower-middle social class. Out of the 1,020 patients, 36.4% were suffering from schizophrenia and other psychotic disorders, 22% were suffering from neurotic, stress-related, and somatoform disorders, 21.3% from mood disorders, 11% others (including migraine, seizure, vertigo, and NPH), 2.6% from organic mental disorders, 2.2% from mental retardation, 2.1% from substance dependence disorders, 1.4% from behavioral problems associated with physiological disturbances, 0.7% from behavioral disorders occurring in childhood and adolescence, and 0.4% from disorders of psychological development (Table 3).

Table 2: Sociodemographic variables—educational status and socioeconomic status
Educational status
Illiterate    62    6.1
Primary school (Std. 1–5)  111  10.9
Middle school (Std. 6–8)  154  15.1
Secondary school (Std. 9–10)  354  34.7
Higher secondary  158  15.5
Graduate  137  13.4
Postgraduate (MA, MSc, MBA, MCA)    27    2.6
Diploma, B.Tech, LLB, MBBS, PhD    17    1.7
Socioeconomic status
Lower  168  16.5
Lower middle  657  64.4
Middle  179  17.5
Upper    16    1.6
Table 3: Diagnostic profile of patients
F00–F09    27    2.6
F10–F19    21    2.1
F20–F29  371  36.4
F30–F39  217  21.3
F40–F48  224  22.0
F50–F59    14    1.4
F60–F69      1    0.1
F70–F79    22    2.2
F80–F89      4    0.4
F90–F98      7    0.7
Others  112  11.0

Majority of our patients (94%) were either referred by family/friends or self-referred. Analysis of the data revealed that almost 40% dropout rate after first visit. The association between diagnostic groups and place of residence was statistically significant (p = 0.002). The association between diagnostic groups and gender was highly significant (p = 0.000). The analysis of association between diagnosis and the socioeconomic status was also significant (p = 0.03).


Mental disorders are an important cause of long-term morbidity, disability, and poor quality of life. Various epidemiological surveys in Asia have indicated that there are 680 million people who are likely to succumb to psychiatric disorder. In terms of services, there is less than 1 mental health professional per 100,000 populations whereas the desirable number is 3–4 psychiatrists per 100,000 populations. People with mental illnesses, in the Indian subcontinent, often seek help from traditional healers. This study was carried out to depict and point out the observed trends through a sociocultural perspective to determine the demographic and clinical characteristics of clients seeking consultation from a private psychiatric clinic in the urban region of northeastern India, during the 3-month period of 2019 (Tables 4 and 5).

Increased prevalence of morbidity (58.4%) is seen in the younger age group in our sample. This trend was earlier demonstrated by many researchers from Asia—Kameshvell et al. (India), Khattri et al. (Nepal), Jaju et al. (Oman), and Soren et al. (India).1013 But, there is no consensus as to which age group is the most vulnerable to mental illness. The rates of psychiatric disorders fluctuate according to geographic, ethnic, and socioeconomic status.14,15 However, it is widely agreed that psychiatric disorders often affect young people who are in the midst of their most productive years of life.12

Earlier studies have reported a strong association between gender and mental illness, with the female gender being the most prominent of the risk factors in certain psychiatric disorders.16,17 In our study sample of 1,020 patients, a small preponderance of males (52.5%) over females was noted, which is consistent with the findings of Regmi et al.,18 Shrestha19 and Kameshvell et al.11 This male preponderance may reflect the gender bias in a patrilineal family system in psychiatric help-seeking behavior. The gender segregation and other sociocultural factors inherent in such paternalistic society may prevent women from going outside to seek help for mental illness.20

In many Asian communities, mental illnesses are often dealt by traditional healing systems. Due to the fact that primary healthcare seldom caters to the needs of people with mental illnesses, the first point of contact for them is tertiary care, and the majority of our clients seeking consultation presented themselves at the clinic or were referred by family. This is consistent with the low observed referrals from other medical specialties. It is possible that patients may think that a referral to a mental health specialist means that they are “crazy.” For these reasons, the majority of referrals (94%) were classified as “self and family referrals.”

As the study place was in a town, majority of the patients (55.5%) were from urban background and from rural area (45.5%). This may be due to easy accessibility, better awareness, and greater vulnerability among urban people. It was observed that 28.3% of the study population were house wives, 16.9% were unemployed, and 14.2% were students. Unemployment that could be attributed to psychiatric disorders was lower when compared to the study by Fahmida et al.21 Family history of mental illness was present in 44.34% of patients, which was higher than with the findings of Shakya et al.22

Table 4: Diagnosis vs residence cross-tabulation (p = 0.002)
% of total1.61.12.6
% of total0.41.72.1
% of total22.114.336.4
% of total11.210.121.3
% of total11.410.622.0
% of total0.70.71.4
% of total0.00.10.1
% of total1.11.12.2
% of total0.10.30.4
% of total0.10.60.7
Seizure, migraine, other headaches, NPH, neuropathy, MCI, parkinsonism, vertigo, CVACount7141112
% of total7.04.011.0
% of total55.544.5100.0
Table 5: Diagnosis vs gender cross-tabulation (p = 0.000)
% of total1.71.02.6
% of total2.10.02.1
% of total16.519.936.4
% of total11.89.521.3
% of total11.610.422.0
% of total1.00.41.4
% of total0.00.10.1
% of total1.40.82.2
% of total0.40.00.4
% of total0.60.10.7
Seizure, migraine, other headaches, NPH, neuropathy, MCI, parkinsonism, vertigo, CVACount5755112
% of total5.65.411.0
% of total52.547.5100.0

In our study sample, approximately 94% subjects were literate and 4.3% had either postgraduation or professional education, and a majority of the study population was economically well-off with 81.9% belonging to middle and lower-middle social class. This may be due to increased awareness among the educated persons, affordability to pay the fee in a private clinic, and accessibility.

Our study also showed that the most commonly diagnosed mental disorders were schizophrenia and other psychotic disorders (36.4%), followed by neurotic, stress-related, and somatoform disorders (22%); mood disorders (21.3%); others including migraine, seizure, vertigo, and NPH (11%); organic mental disorders (2.6%); mental retardation (2.2%); substance dependence disorders (2.1 %); and behavioral problems associated with physiological disturbances (1.4%), which was consistent with the findings of Shrestha19 and Soren et al.13 Whereas in other studies by Kameshvell,11 Regmi et al.,18 and Shakya et al., neurotic or mood disorders were the main diagnostic groups.23

Soren et al.13 in a study conducted in Jharkhand, India, found affective psychosis (31.9%) as the main psychiatric problem followed by nonaffective psychosis (18.8%), epilepsy (15.8%), and neurotic disorder (11.2%). In the study by Shrestha19 (1987), 63.7% of the patients were suffering from psychosis, 18% from neurosis, and 6% from epilepsy. Studies conducted in the outpatients in other parts of the world are rather similar to the findings of our study, in which most of the patients were suffering from psychotic disorders, and less were suffering from neurotic disorders—Choo24 and Uys et al.25 Our findings are in contrast to the findings of the study by Dubey,26 which was conducted in the rural community of Uttar Pradesh (India), in which about 44% of the patients were suffering from neurotic and related disorders and 9.1% from schizophrenia.

One of the important finding of our study was high number of patients with seizure disorder, headache, and vertigo (11.2%). Similar findings were also reported by earlier researchers—Wig et al.,27 Wright,28 and Sharma.29 Wright et al. had found that 32% of the patients were suffering from epilepsy. Epilepsy was seen in 9.4% of the population in the sample studied by Khattri et al.10 in Nepal. This may be due to lack of a neurologist or neurosurgeon in our study area.

This difference in the morbidity pattern may be due to cultural factors and setup of the study center, i.e., whether it is conducted in mental hospitals, psychiatric OPD of a general hospital, or private clinics. Psychosis predominates in mental hospitals, whereas a wider range including psychosis, mood disorders, neurosis, substance dependence, and organic mental disorder occurs in general hospital psychiatric units and private clinics.

One of the most significant findings of our study is the high dropout rate after one visit. Nearly 40% discontinued treatment after first visit. Agarwal30 found nearly 50% dropout rate after the first visit. Could the dropout rate be a reflection of cultural acceptance of mental disorders in this country? People go to a doctor only when the disease produces discomfort/disability and the treatment is given up as soon as there is relief from the discomfort. Economic factors, distance from the clinic, poor rapport, lack of psychoeducation given to the caregivers, etc., have often been considered as key factors responsible for treatment discontinuation. They may play a role but there appear to be other factors that are responsible for treatment stoppage.

In the present study, gender difference in the morbidity pattern was found to be significant, which was similar to the studies of Reddy and Chandrashekar,31 Venkatesh et al.,32 Mclean et al.,33 and Rahman et al.34 and Kameshvell et al.11

Our study also found significant association between diagnostic subgroups and socioeconomic status, which was also reported by Kameshvell et al.11

Strength of Our Study

Large number of study subjects, assessment of dropout rate, private clinic setup in a multispecialty clinic where the chance of stigma was less.

Limitations of the Study

We did not use any scale for the assessment of severity of illness and level of impairment, we did not assess the cause of dropout, and there was evaluation of the personality profile of the study subjects. Also, this study was limited to a private clinic and the fact is that a walk-in clinic might attract a particular group among the population; the generalization of this study should therefore be considered with caution.


We found that mental disorders comprise a spectrum of disorders, which consist mainly of psychotic, mood, and neurotic disorders. They affect the most productive age groups, affecting the economic status of the person and a country as a whole. They are common in both rural and urban areas and almost equally affect both the genders. The awareness program in public about symptoms of mental disorders will definitely help in early diagnosis and prompt treatment.

Some measures need to be taken to understand the causes of dropout and improve the dropout rates. It could be effective to employ one or two local people who could visit people who have dropped out and try to understand their problems. Future studies should compare the clinical and demographic profiles of patients attending various types of mental healthcare facilities at different levels.


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