Results

INSIGHT

Figure 4 Distribution of BABS Score in Bipolar disorder and Schizophrenia

Figure 4 shows a comparative histogram of Insight in Bipolar Disorders and Schizophrenia.Insight in Bipolar disorders(lower BABS Score) is better than Schizophrenics.

 

Figure 5 Boxplot of BABS Score in Bipolar disorder and Schizophrenia

Figure 5 shows a comparative Boxplot of Insight in Bipolar Disorders and Schizophrenia.Insight in Bipolar disorders is significantly better than Schizophrenics.\(\Delta M = -1.39\), 95% CI \([-1.49\), \(-1.30]\), \(t(90.59) = -29.09\), \(p < .001\)

 

variable	Bipolar Group	Schizophrenia Group	difference	95%_confidence_interval	p.value	significance
babs	1.27±0.20	2.66±0.27	-1.39	-1.49 - -1.3	<0.001	significant

Figure 6 Dodged Barplot showing Association between BABS Grade and Diagnosis    

 

Figure 6 shows significant association between Diagnosis and Insight with Schizophrenia a higher percent of poor insight as also seen in count table below. \(\chi^2\)(2, N = 100) = 79.43, p < .001, V = .89

	BPAD	SCHIZOPHRENIA
FAIR INSIGHT	9	12
GOOD INSIGHT	41	0
POOR INSIGHT	0	38

STIGMA

Figure 7 Distribution of Stigma in Bipolar disorder and Schizophrenia

  Figure 7 shows a comparative histogram of Stigma in Bipolar Disorders and Schizophrenia.Stigma is higher in Schizophrenics.

Figure 8 Boxplot of ISMI Score in Bipolar disorder and Schizophrenia

Figure 8 shows a comparative Boxplot of Insight in Bipolar Disorders and Schizophrenia.Stigma in Bipolar disorders is significantly better than Schizophrenia.\(\Delta M = -0.36\), 95% CI \([-0.43\), \(-0.29]\), \(t(88.92) = -9.98\), \(p < .001\)

 

variable	Bipolar Group	Schizophrenia Group	difference	95%_confidence_interval	p.value	significance
ismi	2.27±0.21	2.63±0.15	-0.36	-0.43 - -0.29	<0.001	significant

Figure 9 Dodged Barplot showing Association between ISMI Grade and Diagnosis    

 

Figure 9 shows significant association between Diagnosis and Stigma with Schizophrenia having higher grade percent of stigma as also seen in count table below. \(\chi^2\)(1, N = 100) = 43.63, p < .001, V = .66

	BPAD	SCHIZOPHRENIA
high	9	43
not high	41	7

Figure 10 Correlation between INSIGHT and STIGMA

   

Figure 10 shows a grouped scatterplot of correlation between BABS SCORE AND ISMI SCORE We see there is a positive correlation between poor insight and self-stigma in both groups,which is stronger in Bipolar disorders as can also be seen summary correlation statistics below

 

diagnosis	correlation	conf.low	conf.high	p.value
SCHIZOPHRENIA	0.698	0.521	0.818	<0.0001
BPAD	0.644	0.446	0.782	<0.0001

Figure11 Interaction Plot of Stigma and Insight

 

Figure 11 is showing an Interaction Plot with non-parallel regression lines of Bipolar and Schizophrenia group where we see ISMI SCORE is positively correlated with BABS SCORE, But in Schizophrenia patients there is a negative interaction of BABS SCORE with ISMI due to less steeper curve. The interaction term is significant between BABS SCORE and Schizophrenia as can be seen in summary stats .    

Figure 12 CORRELATION BETWEEN INSIGHT AND SOCIAL FUNCTIONING

   

Figure 12 shows a grouped scatterplot of correlation between BABS SCORE AND SSFI SCORE . We see there is a negative correlation implying higher BABS SCORE(poorer insight) leads to worse social Functioning. This relationship is more pronounced in Schizophrenia  

diagnosis	correlation	conf.low	conf.high	p.value
SCHIZOPHRENIA	-0.825	-0.897	-0.710	<0.0001
BPAD	-0.719	-0.831	-0.551	<0.0001

Figure 13 Interaction Plot of Social Functioning and Insight

Figure 13 is showing an Interaction Plot with non-parallel regression lines of Bipolar and Schizophrenia group where we see relationship between SSFI SCORE and BABS SCORE is predominantly inverse, But in Schizophrenia patientsthere is a steeper curve(implying higher worsening of social function with decrease in Insight) The interaction term is significant between BABS SCORE and Schizophrenia as can be seen below.    

CORRELATION BETWEEN STIGMA AND SOCIAL FUNCTIONING

diagnosis	correlation	conf.low	conf.high	p.value
SCHIZOPHRENIA	-0.871	-0.925	-0.782	<0.0001
BPAD	-0.771	-0.864	-0.628	<0.0001

we see stigma is negatively correlated with Social functioning in both Bipolar disorders and Schizophrenia.   *Figure 14 showing correlation between Stigma and Social Function**

  Figure 14 shows that social Functioning is inversely correlated with Stigma in both groups.

Figure 15 Interaction Plot between Social Functioning and Stigma

  Figure 15 is showing an Interaction Plot with non-parallel regression lines of Bipolar and Schizophrenia group where we see relationship between SSFI SCORE and ISMI SCORE is predominantly inverse, But in Schizophrenia patientsthere is a steeper curve(implying higher worsening of social function with worsening of Stigma) The interaction term is significant even on linear model.    

##OTHER VARIABLES AFFECTING INSIGHT, SOCIAL FUNCTIONING AND STIGMA##

#Association with Insight

we see family history, gender(male) have worse correlation with INSIGHT (BABS_GRADE)

variable	chisquarestatistic	p.value	significance
ssfi_grade	102.279846	<0.0001	significant
diagnosis	79.428571	<0.0001	significant
ismi_grade	76.250037	<0.0001	significant
family_history	7.821036	0.02	significant
sex	5.797741	0.0551	non-significant
socioeconomic_status	12.076306	0.0603	non-significant
marital_status	10.970050	0.0893	non-significant
level_of_education	7.164988	0.1274	non-significant
occupation	5.811895	0.4446	non-significant
family_type	1.490293	0.8284	non-significant

 

Figure 16 showing Males have poorer Insight

Figure 17 showing poorer insight in those with Family history

#Association with Social Functioning grade

variable	chisquarestatistic	p.value	significance
babs_grade	102.2798460	<0.0001	significant
ismi_grade	67.9487179	<0.0001	significant
diagnosis	63.5200000	<0.0001	significant
family_history	15.9997695	3e-04	significant
marital_status	16.6618482	0.0106	significant
sex	7.7068678	0.0212	significant
level_of_education	9.5961835	0.0478	significant
socioeconomic_status	6.6063269	0.3588	non-significant
occupation	5.6358264	0.4652	non-significant
family_type	0.7782312	0.9413	non-significant

Figure 18 showing poorer Social Function in those with Family history

  Pie chart shows people with Family history have worse social function grades

Figure 19 showing association of Social dysfunction with poor educational attainment

Worse Social Dysfunction grades are associated with poor level of education.\(\chi^2\)(4, N = 100) = 9.60, p = .048, V = .22

Figure 21 showing association of Social dysfunction with gender

 

females have better preserved social Function.\(\chi^2\)(2, N = 100) = 7.71, p = .021, V = .28

Figure 22 showing association of Social dysfunction with marital status

 

Unmarried/Widow/Widower have poor social functioning.\(\chi^2\)(6, N = 100) = 16.66, p = .011, V = .29

#Association with Stigma

variable	chisquarestatistic	p.value	significance
babs_grade	76.250037	<0.0001	significant
ssfi_grade	67.948718	<0.0001	significant
diagnosis	43.629808	<0.0001	significant
family_history	15.347314	1e-04	significant
marital_status	10.128438	0.0175	significant
sex	3.151000	0.0759	non-significant
level_of_education	4.462827	0.1074	non-significant
socioeconomic_status	4.585114	0.2048	non-significant
occupation	4.344862	0.2266	non-significant
family_type	1.253963	0.5342	non-significant

 

Figure 23 showing association of Stigma with marital status

 

Pie chart Married couple have significantly lesser have poor social functioning.\(\chi^2\)(3, N = 100) = 10.13, p = .018, V = .32

Figure 24 showing worse Stigma in those with Family history

  Pie chart shows people with Family history have higher ISMI_Grades and worse Stigma.\(\chi^2\)(1, N = 100) = 15.35, p < .001, V = .39

##Multivariable Regression Model

       

we see age family history,poor insight, unmarried status,poor education adversely affect Social Function even while adjusting for confounders in multivariable regression model which has an excellent predictive ability(R square=0.89, explains 89% of variability correctly)

	SSFI SCORE
Predictors	Estimates	std. Beta	CI	standardized CI	p
Intercept	57.19		55.17 – 59.22		<0.001
age	-0.28	-0.17	-0.43 – -0.12	-0.27 – -0.08	0.001
Male sex	-1.47	-0.06	-3.13 – 0.19	-0.14 – 0.01	0.086
Middle school education	-2.47	-0.11	-4.24 – -0.70	-0.18 – -0.03	0.007
Primary School education	-1.39	-0.05	-3.79 – 1.02	-0.12 – 0.03	0.261
Stigma(ISMI SCORE)	-5.71	-0.13	-12.77 – 1.34	-0.28 – 0.03	0.116
INSIGHT(BABS SCORE)	-11.13	-0.71	-13.28 – -8.97	-0.85 – -0.57	<0.001
Family History	-4.08	-0.18	-5.92 – -2.24	-0.25 – -0.10	<0.001
unmarried	-4.43	-0.19	-6.70 – -2.17	-0.28 – -0.09	<0.001
widow	-1.58	-0.01	-9.71 – 6.56	-0.08 – 0.06	0.705
widower	-5.14	-0.08	-10.08 – -0.20	-0.15 – -0.00	0.044
Observations	100
R2 / adjusted R2	0.895 / 0.884

This is a table of of regression coefficients of model including various variables to predict social function .

The Multiple linear regression was conducted to find best combination of BABS score(INSIGHT),ISMI score(STIGMA),Age,Gender, Education,Family history and marital status for predicting Social Functioning(Scarf Social Function iNdex). The continuous variables were centred at their mean to improve interpretation of linear regression model. The combination of these variables significantly predicted SSFI score F(10,89) = 76.25, p<0.001 with Age, education,Insight significantly contributing to education. The adjusted R square was 0.88-implying 88% of variation in social function was predicted by our model. According to Cohen, this is a large effect

Interpretation of linear model

Insight had highest standardized estimate(effect score) and contributed maximum to predicted SSFI score. Participants predicted SSFI score = 57.19- 0.28(age- 33.4) -1.47(Male) -2.47(Middle School education) - 1.39Primary School education -5.71(ISMI Score-2.44) -11.13(BABS Score-1.96) -4.03 Family history -4.43unmarried -1.58widow -5.14 widower.

Figure25 showing estimates in Multivariable Model

WITH all other variables being kept constant at their average values. An increase of age by 1 year decrease SSFI score by -0.28 An increase of BABS score by 1 dereases SSFI score by -11.13 Middle and primary education lead to fall in SSFI score of -2.47 ,-1.39 compared to Higher education. Positive Family history lead to fall in SSFI score of -4.03 compared to no family history. Unmarried and Widower status cause a fall in SSFI score of -4.43 and -5.14 compared to Married status.

Intercept (57.19) represents SSFI score of a Married Female with no female history,average BABS score,average age and average ISMI score in our cohort.

As can be observed in model(and the standardized estimates) , Poor Insight(BABS) cause disproportionate worsening of Social Function as opposed to other significant variables like EducationMarital_status and Stigma as it has the highest absolute and standardized negative coefficient in the regression model.

Figure 25 a Interaction plot between ISMI, BABS and SSFI

	ssfi
Predictors	Estimates	std. Beta	CI	standardized CI	p
(Intercept)	54.80		53.86 – 55.73		<0.001
ISMI	-27.63	-0.61	-32.32 – -22.94	-0.71 – -0.51	<0.001
babs	-5.78	-0.37	-7.37 – -4.18	-0.47 – -0.27	<0.001
ISMI:babs	-22.21	-0.30	-26.62 – -17.79	-0.36 – -0.24	<0.001
Observations	100
R2 / adjusted R2	0.922 / 0.919

This table shows relation o

Figure 26 showing Correlation Matrix of all variables in Scizophrenia patients

   

variable	AGE	DURATION OF ILLNESS	DURATION OF TREATMENT	BABS SCORE	SSFI SCORE	ISMI SCORE
AGE	1.000	0.772	0.755	-0.048	-0.100	0.116
DURATION OF ILLNESS	0.772	1.000	0.973	0.172	-0.302	0.259
DURATION OF TREATMENT	0.755	0.973	1.000	0.126	-0.248	0.214
BABS SCORE	-0.048	0.172	0.126	1.000	-0.879	0.761
SSFI SCORE	-0.100	-0.302	-0.248	-0.879	1.000	-0.871
ISMI SCORE	0.116	0.259	0.214	0.761	-0.871	1.000

In the correlation matrix, variables signifcant at p<0.05 have beeen highlighted,while other crossed for sake of clarity. We see BABS,ISMI and SSSFI scores are correlated as discussed above, while age is correlated with duration of treatment ans illness.

Figure 27 showing Correlation Matrix of all variables in Bipolar Disorders

   

variable	AGE	DURATION OF ILLNESS	DURATION OF TREATMENT	BABS SCORE	SSFI SCORE	ISMI SCORE
AGE	1.000	0.900	0.889	-0.001	-0.059	0.219
DURATION OF ILLNESS	0.900	1.000	0.986	0.108	-0.202	0.354
DURATION OF TREATMENT	0.889	0.986	1.000	0.072	-0.148	0.298
BABS SCORE	-0.001	0.108	0.072	1.000	-0.722	0.643
SSFI SCORE	-0.059	-0.202	-0.148	-0.722	1.000	-0.783
ISMI SCORE	0.219	0.354	0.298	0.643	-0.783	1.000

In the correlation matrix, variables signifcant at p<0.05 have beeen highlighted,while other crossed for sake of clarity. We see BABS,ISMI and SSSFI scores are correlated as discussed above, while age is correlated with duration of treatment ans illness.

Figure 28 showing Correlation Matrix of all variables in overall Population

    In the Figure we see that overall relationship between variables is similar to as seen in subgroups with no directional change albeit there are diffferences in magnitude and interaction in correlation slopes as discussed.

variable	AGE	DURATION OF ILLNESS	DURATION OF TREATMENT	BABS SCORE	SSFI SCORE	ISMI SCORE
AGE	1.000	0.833	0.824	-0.171	0.078	-0.014
DURATION OF ILLNESS	0.833	1.000	0.980	-0.066	-0.080	0.122
DURATION OF TREATMENT	0.824	0.980	1.000	-0.119	-0.011	0.050
BABS SCORE	-0.171	-0.066	-0.119	1.000	-0.878	0.828
SSFI SCORE	0.078	-0.080	-0.011	-0.878	1.000	-0.877
ISMI SCORE	-0.014	0.122	0.050	0.828	-0.877	1.000