1

INTRODUCTION

Dissociative disorder (), is symptoms and signs affecting voluntary motor or sensory function that cannot be explained by a neurological or general medical condition1.The reported prevalence in the neurology clinics of unexplained symptoms among new patients is very high (between 30 and 60%) and affects between

0.011% and 0.5% of the general population2. Previous prevalence studies found incidence rates of 22 and 11 newly diagnosed cases per 100,000 person-years, in Iceland and US respectively3(Gelder et al 2001). In Western societies the rate of

(conversion disorder), is 1%to 3% in outpatient clinics, whereas in non-

Western societies it is about 10%4(Carson et al 2000).

Dissociative disorder (conversion disorder), may develop at any time between early childhood and late old age, it is reported to be most common between 15 and 35 years of age. Dissociative disorder (conversion disorder), is more prevalent among females compared to males, with a ratio between 2:1 and 10:15(Nimnuan et al 2001).

Dissociative disorder (conversion disorder), is also more prevalent in rural areas, in developing countries, among people of low socioeconomic classes, among undereducated people ,and among those with relatively low medical knowledge6(snijders et al 2004). In our study, we study about socio-demographic profile of the Dissociative disorder

(conversion disorder) in our tertiary care centre.

As far as presentation of dissociative disorders (conversion disorder) is concerned, previous studies reported that almost any physical symptom can be produced but most 2 common manifestations are those of similar to motor manifestations of neurological disease, for example: paraparesis, pseudoseizures and aphonia2. The patients with conversion disorder usually report in emergency department with multiple neurological symptoms including weakness, seizures like activity and loss of consciousness. In a hospital-based study, the commonest presenting symptom was found to be

'pseudoseizures', which presented in 45.71% female subjects as compared with 26.65% in male subjects7 (Tollison et al 2002). Another study revealed that 31.3% cases presented with unresponsiveness - a symptom which does not fit any diagnostic criteria, jerky movements, aphonia and sensory loss, and 18.1% others. Another study reported pseudoseizures, paralysis, tremors, aphonia gait disorders, mutism, blindness and anesthesia in decreasing frequency8(Shahid et al 2015). In our study we study about the types of presentation in Dissociative disorder (conversion disorder.

Previous studies states that dissociative disorder (conversion disorder), have psychiatric comorbidity with the prevalence of 60-90%2.Comorbidities significantly affect the prognosis and the treatment of dissociative disorder (conversion disorder). The most common psychiatric comorbidities are mood disorders, anxiety disorders. In a study by Bowman et al (1996), depressive disorders were reported to accompany Dissociative disorder (conversion disorder), at a rate of 88%9. In another study by Kuloglu et al

(2003)10, comorbidity rates for , anxiety disorders, and adjustment disorders with Dissociative disorder (conversion disorder), were found to be 35.3%, 34.8% and9.6%, respectively. Kaygisiz et al (1999)11 reported that 83.6% of patients with 3

Dissociative disorder (conversion disorder), had at least one psychiatric comorbidity, and rates for depressive disorders were reported to be between 34.3% and 50%.

Personality disorders also accompany Dissociative disorder (conversion disorder) . In a study focusing on patients with Dissociative disorder (conversion disorder),the rates for borderline , histrionic personality disorder, and antisocial personality disorder were 55%, 16%, and 11%, respectively (Feinstein et al, 2011)12.

Thus the aim of the study was to study the types of presentation and psychiatric co- morbidities in Dissociative disorder (conversion disorder) in our tertiary care centre. The objectives of the study was to study the personality profile and stressful life events in

Dissociative disorder (conversion disorder). We also correlated the socio-demographic and clinical profile with types of presentation in dissociative (conversion) disorder patients.

4

AIM & OBJECTIVES

A study on types of presentation and psychiatric co-morbidity in Dissociative

(conversion) disorder patients in a tertiary care centre.

Aims:

To study the types of presentation and psychiatric co-morbidity in dissociative

(conversion) disorder patients.

5

Objectives:

1. Tostudy the socio-demographic and clinical profile of dissociative (conversion)

disorder patients.

2. To study the prevalence of types of presentation in dissociative (conversion)

disorder patients.

3. To study prevalence of psychiatric co-morbidity in dissociative (conversion)

disorder patients.

4. To study the prevalence of personality traits in dissociative (conversion) disorder

patients.

5. To study the stressful life events in dissociative (conversion) disorder patients.

6. To correlate the socio-demographic and clinical profile with types of presentation

in dissociative (conversion) disorder patients.

6

REVIEW OF LITERATURE

The prevalence rates of dissociative (conversion) disorder vary according to the population studied. (Feinstein et al 2011)13 have estimated that 20%–25% of patients in a general hospital have individual symptoms of conversion, and 5% of patients in this sample meet the criteria for the full syndrome. Carson et al 200314 estimated that not surprisingly, percentages increase in a neurologic setting. One in five outpatients seen in a neurology department had symptoms that cannot be explained by neurologic disease.

(Sar et al 2004)15 studied 100 consecutive patients who was newly admitted to a neurology ward found that 14% had no evidence of neurologic disease. Data from psychiatric services give a different picture that the prevalence corresponds to the rate of

11–22/100 000 retrieved from a psychiatric care registry of the general population (Stone et al 2014)37.

In Western societies the prevalence of dissociative (conversion disorder) is 1% to 3% in outpatient psychiatry services, whereas in non-Western population, it is about

10%16(Sar et al 2011).

The dissociative (conversion) disorder may present at any age but is rare in children younger than 10 years or in the elderly. Studies suggest a peak onset in the mid- to-late 30s. The age ranged from 11 to 45 years with a mean of 23.6±8.67 years1(Tezcan et al 2003). 7

Dissociative (conversion disorder) is more prevalent among females compared to males, with a ratio between 2:1 and 10:1 and is also more prevalent in rural areas, and in developing countries, among the people of lower socioeconomic classes, among undereducated people, and among those with relatively low medical knowledge18(Uguz et al 2003).

The dissociative (conversion) disorder is more common in women, with an age of onset across the lifespan. However, the observation made from century ago that the disorder was more frequent among people who lived in rural areas or who had lower levels of education or belonged to a lower socioeconomic class (Deveci et al 2003)19.

(Tabasum et al 2006)20 studied 50 consecutive patients and found that past history of psychiatric illness was found in 22% and family history of psychiatric illness was present in 30% of patients. Stressors were present in 97% patients, out of whom, 64% had primary support group issue, and 20% had educational , social problems in 10%,

4% had employment and economic issues and 1 (2%) had physical health problem.

The Life Events and Difficulties Schedule has been used to study stressful life events in conversion disorder patients, in which they experienced increased rates 90% of severe life events compared to general controls (Harris et al. 1996)21. The Life Events and Difficulties Schedule LEDS also revealed elevated rates of severe events in functional dysphonia for the month before symptom onset. Interestingly 50% of the dysphonia patients had an event regarding ‘conflict over speaking out’ providing evidence for secondary gain (House & Andrews, 1988)22 which has been replicated that 8 more than 50% had stressful life event before the symptoms(Baker et al. 2013)23. There is also evidence for elevated rates of historical stressors such as childhood abuse, particularly for sexual abuse in the convulsion variant of conversion disorder, with a meta-analysis of 16 which gave a pooled odds ratio (OR) of 2.94 [95% confidence interval (CI) 2.29– 3.77] compared to various control groups (Sharpe & Faye, 2006)24

A prospective study of 50 patients with conversion disorder, provided some preliminary evidence for the significant predictive value of both stressors prior to symptom onset and secondary gain which they defined as (Raskin et al. 1966)25 .Finally, recently evidence was found for the relevance of stressful life events in conversion disorder in a fMRI study where the neural correlates of recall of stressors of aetiological relevance, when compared to events of matched severity, revealed differential activation in areas involved in memory control and emotion with associated changes in motor areas, and thus providing a possible ‘conversion’ mechanism (Aybek et al. 2014)26.

As the Personality disorders also accompany the conversion disorder (Rechlin etal 2010) study focusing on patients with conversion disorder, the rates for borderline personality disorder was 55%, histrionic personality disorder was 16%, and antisocial personality disorder was11%, respectively 3. The personality trait of is strongly associated with psychiatric morbidity, in particular the common mental disorders

(CMDs), including anxiety, mood, substance use disorders and unexplained somatic symptoms (Lahey et al 2009)27.. It is clear that personality is more appropriately described by a dimensional trait model that considers personality disorders as extreme 9 variants of common personality traits which merge imperceptibly into one another

(Schmitz et al 2007)28 In regards to the other personality domains, the meta-analysis found that all CMDs examined were defined by high neuroticism, most exhibited low extraversion, only SUD was linked to agreeableness (negatively), and no disorders were associated with Openness(Cramer et al 2012)29.

In a hospital-based study, the commonest presenting symptom was found to be

'dissociative convulsions', which presented in 45.71% female subjects and 26.65% in male subjects (Kamala et al 2007)30.

(Stone et al 2004)3 found that 31.3% cases presented with unresponsiveness - a symptom which does not fit any diagnostic criteria, jerky movements, aphonia and sensory loss, and 18.1% others.

(Tabassum et al 2009) study reported dissociative convulsions, paralysis, tremors, gait disorders, mutism, blindness, aphonia and anesthesia in decreasing frequency.31.

(Kamala et al 2007)28 found that role models were present in 52.5% of the subjects and they had checked for the birth order of the subjects and found that most of the subjects were the third order(27.5%) or second order (25%) or the single child of the family (25%).

Nicholson et al 201132, motor symptoms were the most common type of clinical presentation (87.5%). Amongst the motor symptoms, dissociative convulsions was the 10 commonest presentation (71.4%). Other motor symptoms included paresis (17.1%), aphonia/dysphonia (20%), and limb paralysis (5.7%).

The published studies predicts high comorbidity rates for individuals with dissociative (conversion) disorder. Studies conducted on adult populations also demonstrate high comorbidity. Carson et al.20034 found that 82% of the dissociative disorder patients had at least one comorbid psychiatric disorders. Psychiatric comorbidities significantly affect the prognosis and the treatment of dissociative

(conversion) disorder symptoms. The most common psychiatric comorbidities for conversion disorder are mood disorders, anxiety disorders, dissociative disorders (DDs), and somatoform disorders.

Bowman and Markand et al (1996)9, found that depressive disorders were comorbidly in dissociative (conversion) disorder at the prevalence rate of 88%. In another study of Kuloglu et al (2003)10 , comorbidity rates for depression was 35.3% and for anxiety disorders was 34.8% , respectively. Kaygisiz and Alkin et al (1999)11 reported that 83.6% of patients with conversion disorder had at least one psychiatric comorbidity, and prevalance rates for depressive disorders were to be between 34.3% and 50%.

Sar et al(2004)15 studied the frequencies of psychiatric comorbidity with conversion disorder and reported that 89.5% of patients with conversion disorder had at least one psychiatric comorbidity. In the same study, the most common psychiatric diagnoses were as follows: undifferentiated somatoform disorder, generalized , specific , major depressive disorder, obsessive-compulsive disorder. 11

Blitzein et al33, found that, 93.9% of the adolescent sample with dissociative

(conversion) disorder were found to have a comorbid psychiatric disorder and the most prevalent diagnoses were separation anxiety disorder, major depressive disorder (MDD), attention deficit hyperactivity disorder, and oppositional defiant disorder.

Ron et al (2001)34 investigated the frequencies of psychiatric disorders with correlate the socio-demographic and clinical profile with types of presentation in dissociative

(conversion) disorder patients and reported that 89.5% of patients with correlate the socio-demographic and clinical profile with types of presentation in dissociative

(conversion) disorder patients had at least one psychiatric comorbidity. In the same study, the most common diagnoses were as follows: undifferentiated somatoform disorder, generalized anxiety disorder, , major depressive disorder, obsessive- compulsive disorder. Among inpatients with correlate the socio-demographic and clinical profile with types of presentation in dissociative (conversion) disorder patients, the prevalence of correlate the socio-demographic and clinical profile with types of presentation in dissociative (conversion) disorder patients was found to be 30.5%, and dissociative identity disorder (DID) was the most common diagnosis (Sinyan et al.,

2003)35.

In a study by stone et al 201437, the comorbidity of dissociative (conversion) disorder patients was reported to be up to 47.4% in an outpatient clinical population. The comorbidity in dissociative (conversion) disorder patients may interfere with the treatment of the primary disorder, further complicating the prognosis. Patients in 12 dissociative (conversion) disorder patients usually present with acutelyoccurring symptoms suggestive of an organic disease, which seems frightening to patients and to significant others, causing them to be admitted to emergency units (Tobiano, Wang,

McCausland, & Hammer, 2006)38.

. Patients with pseudoseizures was interviewed in another study39(Couprie et al

1995) to determine the course of illness and current diagnosis, had affective disorders, dissociative disorders and post-traumatic stress disorders. In another study of conversion disorder, co-morbid depression was found in 15.7% cases and anxiety in 37.2% cases.

\ The rate of any psychiatric comorbidity was 87% for the whole study population in Kullgren, 1997 et al10. . In a previously published study, the rate of bipolar disorders was reported to be 2% among patients with pseudoseizures, whereas conversion disorder was accompanying 91% of the study population (Bowman & Markand, 1996)15

13

METHODOLOGY

Study done at:

This is a cross sectional study done in the Department of

Psychiatry in Chengalpattu Medical College and Hospital.

Duration of the study:

This study is done for a period of one year from January 2018 to December 2018.

Study population:

Out-patients attending psychiatry OPD at Chengalpattu Medical College & Hospital.

Sample size:

The sample size of the study was 100.

14

Inclusion criteria:

1. Patients with ICD 10 diagnosis of dissociative (conversion) disorder.

2. Patient between the age group 18-45 years of age.

Exclusion criteria

1. Patients, who are critically ill.

2. Age < 18 years.

3. Age >45 years.

METHODOLOGY:

Out –patients diagnosed with dissociative (conversion) disorder during the study period were included. Informed consent was obtained from patients. The socio-demographic and clinical profile was obtained from the patient. The types of presentation is confirmed by

International Classification of Diseases 10(ICD 10). The psychiatric-comorbidity is assessed using M.I.N.I plus. The Homes and Rahe stress scale was administered to rate the stressors. NEO- five factor inventory was used to assess the personality profile of the patients.

15

SCALES USED:

1. Semi-structured socio-demographic and clinical profile proforma.

2. M.I.N.I plus55.

3. Homes and Rahe stress scale54.

4. NEO- five factor inventory53.

16

HOLMES AND RAHE STRESS SCALE.

In 1967, psychiatrists Thomas Holmes and Richard Rahe examined the medical records of over 5,000 medical patients as a way to determine whether stressful events might cause illnesses. Patients were asked to tally a list of 43 life events based on a relative score.

Their results were published as the Social Readjustment Rating Scale (SRRS), known more commonly as the Holmes and Rahe Stress Scale. Subsequent validation has supported the links between stress and illness.

Rahe carried out a study in 1970 testing the validity of the stress scale as a predictor of illness. The scale was given to 2,500 US sailors and they were asked to rate scores of 'life events' over the previous six months. Over the next six months, detailed records were kept of the sailors' health. There was a +0.118 correlation between stress scale scores and illness, which was sufficient to support the hypothesis of a link between life events and illness.

SCORING:

Score of 300+: At risk of illness.

Score of 150-299: Risk of illness is moderate (reduced by 30% from the above risk).

Score <150: Only have a slight risk of illness.

17

NEO-FFI (NEO Five-Factor Inventory)

NEO-FFI (NEO Five-Factor Inventory) is a personality inventory of 60 items that examines a person's Big Five personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism). In addition, the NEO FFI also reports on six subcategories of each Big Five personality trait

(called facets).

Historically, development of the Revised NEO PI-R began in 1978 with the publication of a personality inventory by Costa and McCrae. These researchers published three updated versions of their personality inventory in 1985, 1992, and 2005 which are called the NEO PI, NEO PI-R (or Revised NEO PI), and NEO PI-3, respectively. The revised inventories feature updated norms.

The inventories have both longer and shorter versions with the full NEO PI-R consisting of 240 items and providing detailed facet scores, whereas the shorter NEO-

FFI (NEO Five-Factor Inventory) has only 60 items (12 per domain). The test was originally developed for use with adult men and women without overt .

It has also been found to be valid for use with children.

In the most recent publication, there are two forms for the NEO, self-report (form S) and observer-report (form R) versions. Both forms consist of 240 items (descriptions of 18 behavior) answered on a five-point Likert scale. Finally, there is a 60-item inventory, the

NEO FFI. There are paper and computer versions of both forms.

The manual reports that administration of the full version should take between 30 and 40 minutes. Costa and McCrae reported that an individual should not be evaluated if more than 40 items are missing. They also state that despite the fact that the assessment is

"balanced" to control for the effects of acquiescence and nay-saying, that if more than 40 responses, or fewer than 10 responses, are "agree" or "strongly agree," the results should be interpreted with caution.

Scores can be reported to most test-takers on "Your NEO Summary," which provides a brief explanation of the assessment, and gives the individuals domain levels and a strengths-based description of three levels (high, medium, and low) in each domain.

For example, low N reads "Secure, hardy, and generally relaxed even under stressful conditions," whereas high N reads "Sensitive, emotional, and prone to experience feelings that are upsetting." For profile interpretation, facet and domain scores are reported in T scores and are recorded visually as compared to the appropriate norming group.

19

MINI-INTERNATIONAL NEUROPSYCHIATRIC INTERVIEW PLUS

The Mini-International Neuropsychiatric Interview (M.I.N.I.) plus is a short structured diagnostic interview, developed jointly by psychiatrists and clinicians in the

United States and Europe, for DSM-V and ICD-10 psychiatric disorders.

The Mini-International Neuropsychiatric Interview (M.I.N.I.) is a short structured diagnostic interview, developed jointly by psychiatrists and clinicians in the United States and Europe, for DSM-IV and ICD-10 psychiatric disorders. With an administration time of approximately 15 minutes, it was designed to meet the need for a short but accurate structured psychiatric interview for multicenter clinical trials and epidemiology studies and to be used as a first step in outcome tracking in nonresearch clinical settings.

The authors describe the development of the M.I.N.I. and its family of interviews: the

M.I.N.I.-Screen, the M.I.N.I.-Plus, and the M.I.N.I.-Kid. They report on validation of the

M.I.N.I. in relation to the Structured Clinical Interview for DSM-III-R, Patient Version, the Composite International Diagnostic Interview, and expert professional opinion, and they comment on potential applications for this interview.

20

STATISTICS:

The data were entered in excel spreadsheet was analyzed using SPSS software Version

21.

Descriptive statistics are done using proportions, percentages.

Appropriate statistical tests like chi-square test, were used to compare the study parameters and the results are discussed below. chi square (χ2) statistic

A chi square (χ2) statistic is a test that measures how expectations compare to actual observed data (or model results). The data used in calculating a chi square statistic must be random, raw, mutually exclusive, drawn from independent variables, and drawn from a large enough sample.

There are two main kinds of chi square tests: the test of independence for data and tests of goodness of fit for a model. These tests can be used to determine if a certain null hypothesis can be rejected in hypothesis testinng.

In statistical hypothesis testing, the p-value or probability value is the probability of obtaining test results at least as extreme as the results actually observed during the test, assuming that the null hypothesis is correct.

If p value is less than 0.05,the result is statistically significant, If p value is more than 0.05,the result is not statistically significant. 21

RESULTS

The study included 100 patients of dissociative (conversion) disorder. The socio- demographic data are as follow:

1. AGE DISTRIBUTION:

TABLE 1: Age distribution

AGE Frequency Percentage

18-30 44 44%

31-40 33 33%

41-45 23 23%

Total 100 100

The most common age group is between 18-30 years, which is around 44%. 33% of the patient between the age group 31-40 years and 23% belonged to the age group 41-

45years, which is around 23%.

22

Below pie chart depict the age distribution.

23%

44% 18-30 31-40 41-45

33%

FIGURE 1: AGE DISTRIBUTION

23

2.GENDER DISTRIBUTION

Table 2: Gender distribution

Sex Frequency Percentage

Female 76 76%

Male 24 24%

Total 100 100

Table 2 shows the gender distribution. 76% of the patients were females and 24%

of the patients were male. Below is the bar chart depicting the same.

80 76

70

60

50

40 Frequency 30 24 20

10

0 female male

FIGURE 2: GENDER DISTRIBUTION

24

3. RELIGION

TABLE 3: RELIGION

RELIGION Frequency Percentage

Hindu 82 82%

Christian 17 17%

Muslim 1 1%

Total 100 100

This table depicts that 82% of patients belong to Hindu religion, 17% belongs to

Christian religion and 1% to the Muslim religion.

25

4. LANGUAGE

TABLE 4: LANGUAGE

Language Frequency Percentage

Tamil 93 93%

Telugu 7 7%

Total 100 100

This table depicts that majority of the patients are Tamil speaking persons(93%) and

(7%) are Telugu speaking persons.

26

5. SOCIO-ECONOMIC STATUS

TABLE 5: Socio-economic status

SES Frequency Percentage

Lower 0 0

Upper lower 73 73%

Middle 26 26%

Upper middle 1 1%

Upper 0 0

Total 100 100

This table depicts that 26% of patients, belong to the middle socioeconomic group, 73% belong to the upper lower socio-economic group,1% belong to the upper middle socio- economic group.

27

Below pie chart explains the socio-economic status.

FIGURE 3: SOCIO-ECONOMIC STATUS

1%

26% Upper lower Middle Upper middle

73%

28

6. EDUCATION

Table 6: education

Education Frequency Percentage

Not went to formal school 3 3%

Primary 47 47%

Secondary 18 18%

College 32 32%

Total 100 100

This table depicts that 47% educated up to primary level. 18% educated up to secondary education level, 32% were went to college and 3% of population were not went to any formal school.

29

Below figure represents the educational status of the patient.

Figure 6: Education

50 47 45 40 35 32 30 25 20 18 15 10 5 3 0 not went to formal school Primary Secondary College

30

7.OCCUPATION

TABLE 7: OCCUPATION

JOB Frequency PERCENTAGE

Unemployed 9 9%

Semi- skilled 22 22%

Skilled 7 7%

13 13%

Professional

House wife 40 40%

`Student 9 9%

Total 100 100

This table depicts that 40% are housewife,22% of semi-skilled workers, and 7%

are skilled workers, 13% are professional, 9% were unemployed and 9% were

students.

31

Below diagram represent the occupational status of the patient.

40 40 35 30 25 22 20 13 15 9 9 10 7 5 0

Figure 5: Occupation

32

8.MARITAL STATUS

Table 8: Marital status

Marital status Frequency Percentage

Single 28 28%

Married 67 67%

Divorce 2 2%

Widow 3 3%

Total 100 100

This table depicts that 67% are married, 28% are single, 2% are divorce/divorcee

and 3% are widow. Below diagram represents the same.

80

70 67

60

50

40 28 30

20

10 2 3 0 Single Married Divorce Widow

Figure 6: marital status. 33

9.FAMILY TYPE

Table 9: Family type

Family type Frequency Percentage

Nuclear 1 1%

Small 89 89%

Joint 10 10%

Total 100 100

This table depicts that 89% are belongs to small family and 10% belongs to joint

family.

34

10.BIRTH ORDER

Table 10: birth order

Birth order Frequency Percentage

1 30 30%

2 45 45%

3 15 15%

4 10 10%

Total 100 100%

This table indicates that majority of patients around 45% belongs to second order,

30% to first order ,15% belongs to third order and 10% belongs to fourth order of

birth.

35

11: FAMILY HISTORY

Table 11: family history

Family history Frequency Percentage

Yes 58 58%

No 42 42%

Total 100 100

This table depicts that 58% had psychiatric illness in the family. Below figure depicts the same.

Figure 7: family history

70%

60% 58%

50% 42% 40%

30%

20%

10%

0% Yes No

36

12: ROLE MODEL

Table 12: Role model

Role model Frequency Percentage

Yes 54 54%

No 46 46%

Total 100 100

This table depicts that 54% of the patients have role model for their symptoms.

Below figure depicts the same.

Figure 8: role model

56% 54% 54%

52%

50%

48% 46% 46%

44%

42% Yes No

37

Table 13: Gender distribution in role model

Role model Gender distribution Chi- P

Female Male Total square

YES 36 18 54

NO 40 6 46 5.6064 0.0178 Total 76 24 100

The above table depicts the gender differences in role model. 36% of females and

18% of males had role model of their illness. The chi-square statistic is 5.6064. The p- value is .0178. The result is significant at p < .05. below figure represents the same

Figure 9: gender distribution of role model

Female Male 40 36 40

30 18 20

6 10

0 Yes No Role model

38

13. MAGICO- RELIGIOUS BELIEF

Table 14: Magico-religious belief

Magico-religious Frequency Percentage

Yes 46 46%

No 54 54%

Total 100 100%

This table depicts that 46% had magico- religious belief regarding their illness. Below pie chart depicts the same.

Figure 10: magico- religious beleif

46% YES 54% NO

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Table 15: Gender distribution in magico-religious belief

Magico-religious belief Gender distribution Chi- P

Female Male Total square

YES 35 11 46 0.0004 0.9850

NO 41 13 54

Total 76 24 100

This table depicts the gender differences in magico-religious belief. 35% of females and 11% of males had magico-religious belief about their illness. The chi-square statistic is 0.0004. The p-value is .985007. The result is not significant at p < .05.

Figure 11: Gender distribution in magico-religious belief

45 41 40 35 35 30 25 20 13 15 11 10 5 0 YES NO MAGICO RELIGIOUS BELIEF

FEMALE MALE

40

14. AMOUNT SPENT IN MAGICO-RELIGIOUS TREATMENT

Table 16: Amount spent in magico-religious treatment1

Amount spent Frequency Percentage

<10000 10 10%

10000-50000 17 17%

>50000 19 19%

NIL 54 54%

Total 100 100

This table depicts the amount spent in magico-religious belief. 46% had spent amount in magico-religious belief. 19% of the patients spent above fifty thousand rupees in magico- religious belief. 17% of the patients had spent less than fifty thousand rupees and ten percentage of patients below thousand rupees. Below figure explains the same.

54 60 50 40 30 17 19 20 10 10 0 <10000 10000-50000 >50000 NIL

Figure 12: amount spent in magico-religious treatment 41

15: STRESSORS:

Table 17: stressors

Stressors Frequency Percentage

Yes 90 90%

No 10 10%

Total 100 100

Among the 100 pateints, 90% had stresssors prior to the symptoms and this table shows the percentage of stressors.

42

16. HOMES RAHE SCALE

Table 18: Homes Rahe scale

HR SCALE Frequency Percentage

Slight 29 29%

Moderate 43 43%

At risk 28 28%

Total 100 100%

Stressors assessed using Homes Rahe scale, 29% was at slight risk of illness,

43% was at moderate risk of illness, 28% was at risk of llness.

43% 45 40 35 29% 28% 30 25 20 15 10 5 0 SLIGHT MODERATE AT RISK

FIGURE 13: Homes and Rahe scale 43

Table 19 : Gender distribution in Homes and Rahe scale

Home Rahe scale Gender distribution Chisq P

Female Male Total

SLIGHT 14 15 29 19.15 0.00006

MODERATE 40 3 43

AT RISK 22 6 28

Total 76 24 100

This table depicts the gender distribution of Homes and Rahe scale The chi-square statistic is 19.1537. The p-value is .000069. The result is significant at p < .05

44

Table 20: Age wise distribution of Homes and Rahe scale

HOME RAHE SCALE AGE DISTRIBUTION Chi P

square

18-30 31-40 41-45 Total

Slight 16 7 6 29 3.53 0.7

Moderate 16 15 12 43

At risk 12 11 5 28

Total 44 33 23 100

This table depicts age wise distribution of Homes and Rahe scale. The chi-square statistic is 3.53. The p-value is 0.7. The result is not statistically significant.

Figure 14:Age wise distribution of Homes and Rahe scale

16 16 15 16 14 12 12 11 12 10 7 8 6 5 6 4 2 0 slight Moderate at risk Homes and Rahe scale

18-30 31-40 41-45

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17: PERSONALITY

Table 21 : NEO-FFI- Neuroticism

Neuroticism Frequency Percentage

Very low 0 0

Low 1 1%

Average 9 9%

High 48 48%

Very high 42 42%

Total 100 100%

This table depicts the neuroticism of five-factor inventory. 42% scored very high, 48% scored high, 9% scored average and 1% scored low in neuroticism traits.

48% 50% 42% 45% 40% 35% 30% 25% 20% 15% 9% 10% 5% 0% 1% 0% Very low Low Average High Very high

Figure 15: NEUROTICSM 46

Table 22 : NEO-FFI- Extrovert

EXTROVERT Frequency Percentage

Very low 13% 13%

Low 61% 61%

Average 17% 17%

High 9% 9%

Very high 0 0

Total 100 100

This table depicts the extrovert of five-factor inventory. 61% scored low in extrovert,

17% scored average, 13% scored very low and 9% scored high in extrovert personality

traits.

70% 61% 60%

50%

40%

30% 17% 20% 13% 9% 10% 0 0% Very low Low Average High Very high FIGURE 16: NEO-FFI- Extrovert 47

\ Table 23: NEO-FFI- Openness

0penness Frequency Percentage

Very low 13 13%

Low 62 62%

Average 21 21%

High 4 4%

Very high 0 0

Total 100 100%

This table depicts the openness of five-factor inventory. 62% scored low, 21% scored average, 13% scored very low and 4% scored high in openness personality traits.

70% 62% 60%

50%

40%

30% 21% 20% 13%

10% 4% 0% 0% Very low Low Average High Very high

FIGURE 17:NEO-FFI- Openness 48

Table 24: NEO-FFI- Conscientiousness

Conscientiousness Frequency Percentage

Very low 25 25%

Low 40 40%

Average 13 13%

High 19 19%

Very high 3 3%

Total 100 100%

This table depicts the conscientiousness of five-factor inventory. 40% scored low in conscientiousness, 25% scored very low, 13% scored average and 19% scored high and

3% very high in conscientiousness personality traits.

FIGURE 18:NEO-FFI- Conscientiousness

40% 40% 35% 30% 25% 25% 19% 20% 13% 15% 10% 3% 5% 0% Very low Low Average High Very high

49

Table 25: NEO-FFI- Agreeableness

Agreeableness Frequency Percentage

Very low 15 15%

Low 63 63%

Average 16 16%

High 6 6%

Very high 0 0

Total 100 100%

This table depicts the agreeableness of five-factor inventory. 63% scored low in agreeableness, 15% scored very low, 16% scored average and 6% scored high in agreeableness traits.

FIGURE 19: NEO-FFI- agreeableness

70% 63%

60%

50%

40%

30% 16% 20% 15% 6% 10% 0% 0% Very low Low Average High Very high

50

18. TYPES OF PRESENTATION

Table 26: Types of presentation

Types of presentation Frequency Pregnancy

Dissociative 1 1%

Dissociative stupor 1 1%

Trance and possession attacks 14 14%

Dissociative motor disorders 29 29%

Dissociative convulsions 48 48%

Anesthesia and sensory loss 1 1%

Mixed 6 6%

Total 100 100

This table shows the types of presentation. Dissociative amnesia present in 1%, 1% had dissociative stupor, Trance and possession attacks present in 14%, dissociative motor disorders present in 29%, the most common presentation is dissociative convulsions, which is present in 48%, anesthesia and sensory loss present in 1% and Mixed presentation in 6% of the patients. 51

Figure 20: types of presentation

60 48 50 40 29 30 20 14 6 10 1 1 1 0 Frequency

Figure 21:Gender distribution in types of presentation

40 37 35 30 25 22 20 15 10 11 10 7 4 5 5 1 0 1 0 0 1 1 0 DissociativeDissociative Trance and DissociativeDissociative Anesthesia Mixed amnesia stupor possession motor convulsions and attacks disorders sensory loss

gender distribution female gender distribution male

52

Table 27: Gender distribution in types of presentation

TYPES GENDER DIFFERENCES Chi P

Female Male Total sq

Dissociative amnesia 1 0 1

Dissociative stupor 1 0 1

Trance and possession attacks 10 4 14

Dissociative motor disorders 22 7 29 18.34 0.005 Dissociative convulsions 37 11 48

Anesthesia and sensory loss 0 1 1

Mixed 5 1 6

Total 76 24 100

This table shows gender differences in types of presentation. The chi-square statistic is

18.34. The p-value is 0.005 The result is significant at p < .05.

53

Table 28 : Age differences in types of presentation

AGE DIFFERENCES Chi-sq P Types 18-30 31-40 41-45 Total

Dissociative amnesia 0 1 0 18

Dissociative stupor 0 1 0 26

Tranceand possession attacks 2 8 4 22

Dissociative motor disorders 16 6 7 4 35.64 0.0001 Dissociative convulsions 22 14 12 21

Anesthesia and sensory loss 0 1 1 3

Mixed 4 2 0 4

Total 43 33 23 100

This table shows age differences in types of presentation. The chi-square statistic is

35.64. The p-value is 0.0001. The result is significant at p value < .05

54

TABLE 29: SOCIO-DEMOGRAPHIC AND CLINICAL VARIABLE

CORRELATION WITH TYPES OF PRESENTATION

VARIABLE CHI-SQUARE P VALUE

Age 35.64 0.0001

Sex 18.34 0.005

Language 12.65 0.05

Religion 11.67 0.07

Socio-economic status 8.73 0.03

Education 35.39 0.001

Birth order 23.43 0.005

Occupation 21.73 0.04

Marital status 3.53 0.07

Family type 9.62 0.156

On correlating, the types of presentation with socio-demographic variables, we found that age, sex, socio-economic status, education, birth order, occupation has got p value < 0.05, which is statistically significant.

55

TABLE 30: SOCIO-DEMOGRAPHIC AND CLINICAL VARIABLE

CORRELATION WITH TYPES OF PRESENTATION

VARIABLE CHI-SQUARE P VALUE

Family history of psychiatric illness 11.87 0.008

Role model 18.34 0.005

Stressors 18.57 0.001

Magico-religious belief 3.89 0.353

Amount spent in magico-religious 31.95 0.06 belief Number of episodes 11.42 0.08

Duration of illness 55.74 0.0001

Psychiatric morbidity 43.99 0.008

On correlating, the types of presentation with clinical variables, we found that family historyof psychiatric illness, role model, stressors and duration of illness, has got p value

< 0.05, which is statistically significant.

56

19. NUMBER OF EPISODES

Table 31: Number of episodes

Episodes Frequency Percentage

1 7 7%

2-5 45 45%

6-10 24 24%

>10 18 18%

Continuous 6 6%

Total 100 100%

Number of episodes of illness varies from 2 to 5 episodes in 45%, 6 to 10 episodes in

24%, more than ten episodes in 6%, 7% had presented with one episode 6% and presented with continuous illness. This was shown in the above table.

57

6% 7%

18% 1 5-Feb 10-Jun

45% >10 24% Continuous

FIGURE 22: NUMBER OF EPISODES

30 30 25 24 25 21

20

15

10

5

0 <1month 1-6month 7mon-12 >1 year month

FIGURE 23: DURATION OF ILLNESS

58

20: DURATION OF ILLNESS

Table32: Duration of illness

Duration Frequency Percentage

<1month 21 21%

1-6month 30 30%

7mon-12 month 25 25%

>1 year 24 24%

Total 100 100%

Duration of illness was one to six month in 30% of individuals and 25% had duration of seven month to twelve month, 24% had duration more than 1 year and 21% presented with less than one month duration of illness. The above table depicts the same.

59

2I. PSYCHIATRIC COMORBIDITY

Table 33 : Psychiatric comorbidity

Psychiatric comorbidity Frequency Percentage

Nil 3 3%

Mild depression 5 5%

Moderate depression 15 15%

Severe depression 17 17%

Mixed anxiety and depression 26 26%

Somatisation disorder 2 2%

Paranoid 1 1%

Generalized anxiety and depression 25 25%

Intellectual disability 2 2%

Substance abuse 1 1%

Adjustment disorder 3 3%

Total 100 100%

60

The above table shows the psychiatric co-morbidity in dissociative (conversion) disorder patients. The most common psychiatric comorbidity is depressive disorders. Mild depression found in 5%, Moderate depression in 15% and Severe depression 17% and the second most common is mixed anxiety and depression which is present in 26%. The generalized anxiety and depression present in 25%, in 3%, in 2%, present in 2%, paranoid schizophrenia in 1%, in 1% and 3% had nil psychiatric comorbidity.

30 Nil 26 25 Mild depression 25 Moderate depression

Severe depression 20 17 Mixed anxiety and 15 depression 15 Somatisation disorder

Paranoid schizophrenia 10 Generalized anxiety and 5 depression 5 3 3 Intellectual disability 2 2 1 1 Substance abuse 0 Frequency Adjustment disorder

Figure 24: psychiatric co-morbidity

61

Table 33 : Gender distribution in Psychiatric comorbidity

TYPES GENDER DISTRIBUTION Chi P

Female Male Total sq

Nil 1 2 3

Mild depression 2 3 5

Moderate depression 12 3 15

Severe depression 14 3 17 14.4 0.04 Mixed anxiety and depression 20 6 26

Somatisation disorder 2 0 2

Paranoid schizophrenia 1 0 1

Generalisied anxiety and depression 21 4 25

Intellectual disability 2 0 2

Substance abuse 0 1 1

Adjustment disorder 1 2 3

Total 76 24 100

This table shows Gender differences in Psychiatric comorbidity. The chi-square statistic is 14.4. The p-value is 0.04. The result is statistically significant at p < .05.

62

25 20 21 20 14 15 12 10 6 4 5 2 2 3 3 3 2 2 2 1 0 1 0 0 0 1 1 0

gender distribution female gender distribution male

Figure 25: Gender distribution in Psychiatric comorbidity

63

Table 34: Age wise distribution in Psychiatric comorbidity

AGE DIFFERENCES Chi-sq P

Psychiatric co-morbidity 18- 31-40 41-45 Total 30

Nil 2 1 0 3

Mild depression 4 0 1 5

Moderate depression 6 6 3 15

Severe depression 7 8 2 17

Mixed anxiety and depression 14 6 5 25

Somatisation disorder 1 0 1 2 5.03 0.28 Paranoid schizophrenia 0 0 1 1

Generalized anxiety, depression 5 11 10 26

Intellectual disability 2 0 0 2

Substance abuse 1 0 0 1

Adjustment disorder 2 1 0 3

Total 44 33 23 100 64

This table shows age wise distribution in Psychiatric comorbidity. The chi-square statistic is 5.03. The p-value is 0.28. The result is not significant at p value< .05.

65

DISCUSSION

In our study, majority of the patients (44%) belonged to the age group 18-30 years. The prevalence rates decline with age. 33% of the patient were between the age group 31-40 years and 23% belonged to the age group of 41- 45years. This is in accordance with the findings of the study of Tabassum et al in 200631, where the most common age group is between 18- 25 years. This is also similar to the finding ofdeveci et al 200719who found that ages 19-21 years are most common age for dissociative (conversion) disorder. This maybe because that young adults encounters many psychosocial stressors at this age.

Out of 100 dissociative (conversion) disorder patients, 76% of the patients were females and 24% of the patients were male. There was female predominance. This finding has been replicated from several previous studies of Carson et al 20034, Deveci et al 200719,Sar et al 2001115 .The reason maybe that women tend to repress emotion which later reflected as physical symptoms and women encounters more bio-psycho- social stressors than men.

In this study, majority of the patients, 82% belong to Hindu religion and 93% has

Tamil as their mother tongue. This is to be expected because this study was done at

Chengalpattu medical College which predominantly has Hindu religious people and

Tamil speaking person.

In this study, 26% of patients, belong to the middle socioeconomic group and 73% belong to the upper lower socio-economic group and 1% belong to the upper middle 66 socio-economic group. As the study was done in semi-urban area, results are to be expected to be as such.

The majority of the patients educated to the primary level 47%, 32% went to college, 18% educated to the secondary education level and 3% not went for any formal school. These findings are in consistent with Sar et al 201141, Tezcan et al 200342, Uguz et al 200343, which says dissociative (conversion) disorder common among patients educated to the primary level.

In this study, majority of the patients are 40% are housewife, 22% of semi-skilled workers, 7% are skilled workers, 13% are professional and 9% were unemployed and 9% were students. These finding are in consistent withSar et al 201181, Tezcan et al 200382,

Uguz et al 200343, which says the conversion disorder is common in patient who do not have personal income.

Most of the patients were married (67%), these findings are in consistent with

Kamala et al 200730and contradictory to Tabassum et al 200931, which says dissociative

(conversion) disorder more common in single.

The majority of patients 89% are from small family and these findings are contradictory to Kamala et al. 200730, which says it is more common in joint family.

The majority of patients 45% belongs to second order of birth,30% to first order 15% belongs to third order and 10% belongs to fourth order of birth. These findings are in 67 consistent withKamala et al.200774in which most of the subjects were the third (27.5%) or second (25%) or the single child of the family (25%).

Thus the study participants are female predominantly, at low to middle income levels, with primary school education, married and house wife. These findings suggest that dissociative (conversion) disorder is more prevalent among individuals with lower socioeconomic status and lower education levels as in consistent with previous studies.

In this study, 58% of dissociative (conversion) disorders had positive family history of psychiatric illness. These are similar to the findings of Sinyan et al44. In that study nearly

54.8% had positive psychiatric illness history in the family and this stresses the importance of positive history of psychiatric illness in dissociative (conversion) disorder patients. These findings are close to the findings in a previous study done by Deveci et al

200719.

Among 100 patients of dissociative (conversion) disorder patients, 54% had role model for their symptoms. These was in corresponding toSridhar et al 1997 and Kamala et al

200730 in which the role models were present in 52.5% of the subjects. Thus these findings explains the unconscious modelling of the patients symptoms on those of someone important to them.

In our study, we found that 46% had magico- religious belief, this was also in consistent with other studiesRamakrishnan et al. 200245, Bhughra et al 199746 68

We further evaluated the amount spent by the patients for these magico -religious belief and treatment. 46% had spent amount in magico-religious treatment. 19% of the patients spent above fifty thousand rupees in magico-religious treatment. 17% of the patients had spent less than fifty thousand rupees and ten percentage of patients below thousand rupees.

According to Nicholson et al 201132, conversion disorder is characterized by sudden onset of symptoms in clear relation to stress. In our study, we found that had stressors found in 90% of patients. These findings are also in consistent with Feinstein A (2011)11.

In Homes and Rahe scale findings, 29% was at slight risk of illness, 43% was at moderate risk of illness, 28% was at risk of illness. This further emphasis the role of stressors in dissociative (conversion) disorder.

Among the personality traits, 42% are very highly neurotic, 48% are high neurotic, 9% scored average and 1% scored low in neuroticism score. These findings are similar to findings of Ormel et al 201147 that the neurotocism is associated with common psychiatric comorbidity and unexplained somatic symptoms.

On the five-factor inventory model, 61% scored low in extrovert, 17% scored average, 13% scored very low and 9% scored high in extrovert trait. As per Makand et al 200548, low score of extrovert are prone to face problems in relationship, occupation and personal life and they are more vulnerable to stressors. 69

Among the openness trait of five-factor inventory. 62% scored low in openness, 21% scored average, 13% scored very low and 4% scored high in openness. People who are open to experience are intellectually curious, open to emotion, sensitive to beauty and willing to try new things49(Widiger et al 1999 ).These findings suggests that majority of these patients scored less in openness and thus less open to new experiences.

A large-scale meta-analysis (n > 75,000) examining the relationship between all of the Big Five personality traits and found that low conscientiousness yielded consistently strong effects for psychiatric disorders49(Markon et al 2000) . Among the conscientiousness trait of five-factor inventory. 40% scored low in conscientiousness,

25% scored very low, 13% scored average and 19% scored high and 3% very high in conscientiousness and thus the majority of the patient scored low in conscientiousness.

Among the agreeableness trait of five-factor inventory. 63% scored low in agreeableness,

15% scored very low, 16% scored average and 6% scored high in agreeableness. Thus majority of the patient have low agreeableness to the environment and this make them more vulnerable to stress50. (Rothbart et al 2000)

The most common types of presentation is dissociative convulsions which is present in

48%of the patients. This was similar to the study of Devici et al 200719, in which dissociative convulsions was the largest category present in about 35% of patients. In

Kamala et al 200730 dissociative convulsions was present in 35%, in Stone et al

201415dissociative convulsions was present in 34%, Sar et al 201116dissociative convulsions was present in 21%,. The second most common presentation is dissociative 70 motor disorders (29%). In Kamala et al 2007, dissociative motor disorder was found in

26% of cases. These figures are comparable with Akyuz et al 201752 (19%) and Uguz et al 200343 (22%),Trance and possession attacks present in 14%, Mixed presentation in 6% of the patients, Dissociative amnesia present in 1%, 1% had dissociative stupor, anesthesia and sensory loss present in 1%.These findings are in consistent with

Tabassum et al 200631.This difference is also attributable to the difference in the study population, cultural belief, educational status of the population.

Number of episodes of illness varies from 2 to 5 episodes in 45%, 6 to 10 episodes in

24%, more than ten episodes in 6%, 7% had presented with one episode 6% and presented with continuous illness. Duration of illness was one to six month in 30% of individuals and 25% hadduration of seven month to twelve month, 24% had duration more than 1 year and 21% presented with less than one month duration of illness. These findings are in consistent with Akyuz et al 201752. In previous studies Uguz et al 200343, it has been found co-morbid psychiatric disorder increases the treatment duration .As the duration of treatment increases, we should search for co-morbid psychiatric disorders, low socioeconomic conditions, lack of insight, as well as long-hidden, childhood stressful life event or trauma.

The most common psychiatric comorbidity in our study was depressive disorders. Mild depression was found in 5%, Moderate depression was found in 15% and severedepression was found in 17%.This findings are similar to Akyuz et al 201752, in which the most common co-morbid psychiatric diagnoses were depression (54%), and 71 these findings also similar to Uguz et al200343in which is (58%). The second most common comorbidity is mixed anxiety and depression which is present in

26%. The generalized anxiety and depression present in 25%, adjustment disorder in 3%, somatization disorder in 2%, intellectual disability present in 2%, paranoid schizophrenia in 1%, substance abuse in 1% and 3% had nil psychiatric comorbidity. These findings are also similar to theSar et al 201415in which the depressive disorders(55%),anxiety disorders (30%), adjustment disoders (5%) and (2%).91Thus psychiatric comorbidity is present significantly in dissociative (conversion) disorder patients in our study .

72

SUMMARY AND CONCLUSION

In our study of dissociative (conversion) disorder, majority of the patients are young adults belonging to age group of 18-30 and this correlates with the findings of previous studies. Two- third of the patients are female gender, this may be due to the reason, women in developing countries like India are subjected to more bio-psycho-social stressors and also women tend to repress their emotions , which later reflected as physical symptoms.

As the study was done in semi-urban area, where the majority of the study population are Hindu and Tamil speaking persons. The majority of the study participants are female, at low to middle income levels, with primary school education, married and house wife. These findings suggest that dissociative (conversion) disorder is more prevalent among individuals with lower socioeconomic status, lower education levels, and married individuals and among who do not have source of income as in consistent with previous studies.

Majority of the patients had positive psychiatric history in the family. This emphasis that dissociative disorder may run among families, and how they are vulnerable 73 to stress. Appropriate interventions should be taken for treating the family members, as they form the important to the patient. Psychiatricmorbidity in the family like or depression can hinder the recovery of the patient and may precipitate further episodes due to lack of propersupport system.

Most of these patients had role model for their symptoms. The role model is learned behavior, which patient learned, it formed the basis of conversion symptoms, which patient exhibit according to their level of medical knowledge. This helps in understanding the symptoms of the patients.

About half of these patients revealed that they have magico-religious belief and these findings are in consistent with previous studies. It is also clear that majority of patient blame on evil or good spirit for their symptoms and they approach their local faith healer for curing the symptoms. Not surprisingly some patients are sent to the hospital by faith healers and they further continue the treatment, along with their magico-religious practices.

Majority of the patients had stressors prior to the onset of symptoms. These findings are in consistent with previous studies. The pathophysiology of the conversion disorder also states the reaction to the stressors are converted to physical symptoms and this gives primary gain to the patient and further change of environment or escape from that situation gives secondary gain. 74

The most common presentationis dissociative convulsions and second most common is motor disorder. The presentation of dissociative (conversion) patients vary with study population, medical knowledge and cultural aspects of the patients. About

30% of the patients came to the hospital with the duration less than six months. As the duration prolongs, course and prognosis of the disease also altered.

From the previous studies, it is well known that dissociative (conversion) disorders is associated with personality disorders. On big five personality assessment, majority of the patients scored high in neurotic traits, low in extrovert, openness, agreeableness and conscientiousness. Understanding the personality traits will be helpful in psychotherapy and presence of personality disorders may alter the course and prognosis of the disease.

Majority of the patients had psychiatric co-morbidity. Among those with psychiatric morbidity the most common was found to be depressive disorder followed by anxiety disorder. Adequate treatment of the psychiatric morbidity should be done to prevent further episodes.

75

LIMITATIONS

 It is a Hospital based study rather than a community based study.

 We have taken a Small sample size. So we should be cautious in generalizing

the results to the whole population.

 There is lack of a control group.

 This study predominantly had upper lower socio-economic status group. There

could be different presentation for high socio-economic status people and we

must be cautious in generalizing the results to the community.

76

FUTURE IMPLICATIONS

 A Community based study can be done.

 Case control study could be done.

 Follow up study in these patients.

 Study on preventive factors of further episode can be done.

77

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