INTRODUCTION
The construct of resilience has been popular as well as mental health parlance for many years now, but over the last few decades, its understanding has evolved significantly, primarily driven by research in ecology, psychology, and medical sciences. The initial transition of resilience from an ecological and sociological concept occurred via the developmental psychopathology lens, whereby it was conceptualized as a protective factor against inevitable environmental transgressions. But modern-day resilience research has revealed that it is a multidimensional concept involving multiple homeostatic systems. One of the most accepted definitions currently for resilience conceptualizes it as “the capacity of a dynamic system to withstand or recover from significant challenges that threaten its stability, viability, or development”.[1] The contemporary definition takes a much more atheoretical yet dynamic approach, as resilience can be seen to operate at many levels according to this definition. The various systems employed to understand human behavior, including genetic, epigenetic, neurochemical, psychological, psychosocial, or cultural – and the eclectic combination of them – can all be explored for the framework of resilience.
With this new framework of understanding, a fresh look is warranted to understand how resilience affects severe mental illnesses (SMIs). SMIs like schizophrenia and bipolar disorder have a prevalence of 1.9% and tend to affect all domains of life and necessitate long-term care services. The National Mental Health Survey of India 2015–16 found that three out of four persons with a severe mental disorder experienced significant disability in work, social, and family life.[2] It is, hence, pertinent to examine various factors that contribute to this disability. Resilience is emerging as one such important factor.[3]
Any major mental disorder like schizophrenia or bipolar disorder is a state of immense flux for the system, and the body’s natural equilibrium is disrupted. This homeostasis requires active moderation and the systems employed to maintain allostasis – contribute to resilience. The allostasis manifests in the form of adaptive psychophysiological events that can be understood through the psychosocial paradigms as well. Mihali propounded a resilience theory based on this framework whereby “the effects of resilience, which is conferred by environmental, genetic, and social factors, can preclude, reverse, or slow the progression of schizophrenia”.[4] At least a couple of major longitudinal naturalistic studies have suggested the presence of protective factors that contribute to better outcome and sustaining recovery in persons with schizophrenia.[5,6] Among more familiar factors like premorbid personality and attitudinal systems, greater resilience too predicted the severity of symptoms and has been considered as an intervening variable between psychopathology and global functioning.[5]
In bipolar disorder too, resilience has been found to have a strong relationship with relapse rates and residual symptoms.[7–9] Hofer found that once resilience was factored in, remitted patients of bipolar disorder and healthy control had a comparable quality of life.[10] Initial assumptions that resilience might affect functioning indirectly via its effect on neurocognition, self-esteem, or insight have not been translated in the form of evidence. There is a distinct lacuna of knowledge on how resilience is related to functioning, especially disability. While a few studies have explored the same in remitted patients,[10,11] Hofer suggested that including persons with acute illness has significant merits.[10]
While a multitude of treatment outcomes have been examined to understand illnesses, most of them focus on hospital populations, attempting to examine clinical characteristics. While dissecting the different components of mental illnesses is important, the “natural history” of disease remains incomplete without understanding its impact on social adjustment and behavior. Disability assessment aims to quantify the extent to which the manifestations of a certain disorder represent maladaptive responses to particular aspects of the social environment (WHO, 1988). Clinical remission is not the therapeutic end-point, but a means to achieve reintegration of the afflicted into the society. The objective evaluation of disability serves utmost importance for interactions at various levels including treatment, recovery-oriented strategies, assessing the effectiveness of measures, broader socio-political policies, and welfare activities. Disability is not just an eligibility criterion for financial remuneration but a credible clinical variable. Psychiatric disabilities are further unique as, unlike other chronic medical illnesses, the manifestations are different and the translation from clinical to social is less discreet, rather complementary to each other.[12]
Bipolar disorder and schizophrenia are among the most disabling disorders worldwide. While advancements in pharmacotherapeutic and psychosocial interventions are being increasingly diversified and the illnesses being explored across all levels of understanding, including genetic, epigenetic, connectomics, psychological, and social – the framework is still essentially a “deficit model” of psychopathology. Recent research has provided valuable insights into what determines the heterogeneous outcomes associated with these disorders, and positive psychopathology constructs like resilience, coping, and internalized stigma are being seen as possible answers.[11,13] While some major studies have shown that resilience can influence the recurrence of episodes, functioning, and cognitive impairments, they also point out significant cross-cultural differences.[14] There is an urgent need to evaluate resilience in Indian patients to increase this momentum. A focus on resilience in such patients represents an important shift in our understanding of these illnesses and is expected to translate into practical therapeutic endeavors. One interesting avenue for future research would involve an examination of resilience-enhancing interventions customized for patients with bipolar disorder or schizophrenia to limit disability and enhance the quality of life.
The current study aims to assess and compare the influence of resilience and internalized stigma on treatment effectiveness (as reflected in disability scores) among patients diagnosed and treated for bipolar disorder and schizophrenia in a tertiary care facility.
METHODS
The study was conducted at a teaching psychiatric hospital and a tertiary care psychiatric facility in the Northeastern part of India. The study population was persons with schizophrenia or bipolar disorder attending OPD or IPD services of the hospital and fulfilling inclusion criteria. The study had a cross-sectional, comparative design with consecutive sampling procedures and was carried over a period of 6 months. Ethics approval was obtained from the Institutional Ethics Committee, LGBRIMH Tezpur on 24/12/2020.
2.1 Sample size estimation – Previous studies in the study population have shown mean CDRISC scores in patients with schizophrenia and bipolar disorder to be significantly different, and using the previously recorded effect size and sample standard deviation,[15] sample size was calculated as per t-statistic formula [a = 0.05, b = 0.1, q1 = q0 = 0.5, E = 13, S = 17; www.sample-size.net/sample-size-means]. The calculated sample sizes were 38 for each group, but in view of feasibility and previous studies,[16] the sample size of 30 patients, each with schizophrenia and bipolar disorder, was studied.
2.2 Inclusion and exclusion criteria – The inclusion criteria were: a) patients diagnosed with bipolar affective disorder (F31) or schizophrenia (F20) as per ICD 10 (DCR), b) duration of illness at least 2 years and at most 5 years, c) Clinical Global Impression – Severity (CGI-S) score 4 (moderately ill) or less, d) patients aged between 18 and 45 years, and e) patients who gave written informed consent. The exclusion criteria were: a) patients with mood or psychotic disorder secondary to other medical condition, schizoaffective disorder, personality disorders, intellectual disability, b) patients who were receiving electroconvulsive therapy, c) patients with co-morbid debilitating medical illness, and d) patients who were unable to read or write Assamese/English.
2.3 Tools used – a) Connor–Davidson Resilience Scale (CD-RISC) – 25 item self-rated instrument that has been validated in clinical populations and Assamese translation validated in the region.[17] Has been used in patients with CGI-S <4[8]; b) Indian Disability Evaluation and Assessment Scale (IDEAS) – validated for use by mental health professionals in the region. Global disability score >7 is considered a significant disability; c) CGI-S scale – clinician rated with robust efficacy.
2.4 Procedure – Patients from OPD or IPD of the psychiatric hospital were recruited based on the inclusion and exclusion criteria. The treating team comprising of a senior psychiatrist and a resident psychiatrist made clinical diagnoses and referred patients to the investigators who assessed disability in the patients and, based on IDEAS global disability score of more or less than 7, allotted participants in either group – with or without significant disability. Fifteen participants were recruited in each such group, and hence 30 for each disorder group. The CGI-S and CD-RISC scales were eventually used to assess symptom severity and resilience, respectively.
2.5 Statistical analysis - Statistical analysis on the data was done as per plan using the IBM-SPSS v25.0 software. For statistical significance, the P value is considered to be <0.05. Data was checked for normality using the Shapiro–Wilk test. For discreet variables, Chi-square test was used, and for the continuous variables, the independent sample t-test was used. For testing the hypothesis, linear regression analysis was used.
RESULTS
Majority of patients in both schizophrenia and bipolar disorder groups were males (66.7% of those with schizophrenia and 63.3% of those with bipolar disorder). Persons with schizophrenia and bipolar disorder both most commonly practiced the Hindu religion (43.3% of those with schizophrenia and 36.7% of those with bipolar disorder). Education level was most commonly secondary in both the groups (40% in the schizophrenia group and 36.7% in the bipolar disorder group). Persons with schizophrenia were most commonly from the lower socioeconomic status (50%), while those with bipolar disorder were most commonly from upper lower strata (40%). A majority of persons with schizophrenia had rural domicile (83.3%), similar to those with bipolar disorder (60%). Family type was joint for a majority of those with schizophrenia (60%), while nuclear and joint family were equally represented in those with bipolar disorder (46.7% each). There was a significant difference between the two groups only for domicile status, where persons with bipolar disorder were significantly more from urban domicile. The mean age of participants with schizophrenia was 30.57 ± 9.34 years, and the mean age of those with bipolar disorder was 31.10 ± 10.77 years. Persons with schizophrenia had on average 5.13 ± 1.92 members in their family, whereas those with bipolar disorder had 4.77 ± 2.01 family members [Table 1].
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Table 1: Comparison of sociodemographic profile of the two groups of disorders (schizophrenia and bipolar disorder) [Discreet variables – Chi-square test; Continuous variables – Independent sample t-test]
The mean symptom severity, as assessed by the CGI-S scale, was 2.30 ± 0.95 for persons with schizophrenia and 2.17 ± 1.12 for persons with bipolar disorder. The mean IDEAS global Disability score for persons with schizophrenia was 7.83 ± 3.34, whereas that for persons with bipolar disorder was 6.30 ± 2.89. There was no statistically significant difference between the groups with respect to any of the clinical variables. The mean CD-RISC 25 score for persons with schizophrenia was 73.60 ± 13.87, whereas that for persons with bipolar disorder was 78.10 ± 15.26. There was no statistically significant difference between the CD-RISC scores of the two populations [Table 1].
Within each disease group, a comparison between those with and without significant disability (IDEAS Global disability score >7) revealed statistically significant differences in both symptom severity and CD-RISC 25 total scores [Table 2].
Table 2: Comparison of clinical variables between persons with and without significant disability, in both schizophrenia and bipolar disorder groups
A Linear regression analysis model is examined with IDEAS Global Disability score as the dependent variable and gender, age, family type, number of family members, domicile, religion, education, socioeconomic status (SES), severity (CGI-S), and resilience (CDRISC-25 score) as predictor variables for each disease group. In the Schizophrenia group, the R-Squared value for the goodness of fit of the model is 0.674. The ANOVA statistic for ascertaining the probability of predictor variables predicting the outcome more than the residual variables is statistically significant (F = 3.932, P = 0.005). Among the individual predictor variables, only CDRISC-25 scores are statistically significant (t = −2.582, P = 0.018) for predicting the dependent variable (IDEAS global disability score). The variance inflation factor (VIF) for assessing multicollinearity is below 10 for all variables, indicating that the variables are not producing said effect due to intercorrelation [Table 3].
Table 3: Relationship between disability and sociodemographic and clinical variables in schizophrenia group [n=30; Linear regression analysis]
Similarly, when analyzed for the bipolar disorder group, the R-squared value of the model is 0.657. The ANOVA statistic for ascertaining the probability of predictor variables predicting the outcome more than the residual variables is statistically significant (F = 3.637, P = 0.008). Among the individual predictor variables, CDRISC-25 scores (t = −2.977, P = 0.008) and CGI-Severity scores (t = 3.135, P = 0.005) are statistically significant for predicting the dependent variable (IDEAS global disability score). Among these two significant predictors, CGI-S has a regression coefficient of 0.554 (positive correlation) and CDRISC-25 has a regression coefficient of − 0.471 (negative correlation). VIF is below 10 for all variables [Table 4].
Table 4: Relationship between disability and sociodemographic and clinical variables in bipolar disorder group [n=30; Linear regression analysis]
CDRISC-25 as an input variable predicts the outcome variable (IDEAS global disability score) in a statistically significant manner (t = −3.706, P < 0.001). The regression coefficients of the CD-RISC score over the disability score are different for schizophrenia (β = −0.531) and bipolar disorder (β = −0.471) groups [Tables 3 and 4]. The interaction effect of the condition variable and input variable is not statistically significant (t = 1.793, P = 0.078), which indicates that disease groups do not significantly affect the relationship between CDRISC-25 scores and IDEAS global disability scores [Table 5].
Table 5: Comparison between the two groups (schizophrenia and bipolar disorder) of the effect of resilience (CDRISC-25) on disability (IDEAS global disability score)
DISCUSSION
The present study is the first study in India to compare the effects of resilience on disability across diagnosis to the best of our knowledge. Previously resilience has been linked to residual functioning in both schizophrenia and bipolar disorder,[14–16] but the current study used a novel methodology to see the association between resilience and disability. By using a consecutive type of sampling to recruit the equal number of persons with and without significant disabilities, selection bias was reduced which has often been reported in studies assessing functional outcomes at tertiary care centers.
Our study also included persons with schizophrenia and bipolar disorder across stages of illness. A number of studies have been done on recovered or remitted patients, but the authors have consistently reported the need for assessing patients with acute illness.[14,15] We found that the use of the CGI-severity scale is a feasible way to recruit participants. Any apprehension regarding the influence of psychopathology on resilience was dealt with by employing appropriate statistical analysis that independently assesses the association between symptom severity and resilience. Also, the use of CD-RISC 25 is appropriate as it assesses personal as well as social factors of resilience. The role of social support and social cognition in sustaining recovery has been well established,[18] and to examine resilience as a possible mediator of this role, it is important to use instruments that assess these factors as well. It has also been found previously that duration of illness is a significant factor associated with disability for both schizophrenia and bipolar disorder.[19,20] In view of this, we only included patients with 2–5 years illness.
The present study found the majority of participants in both groups to be male, Hindu, educated up to secondary, belonging to lower SES and living in a joint family setup. These findings follow a similar trend with other such hospital-based studies on the same population.[21] There was a significant difference between the two groups only in domicile setup, where a greater number of persons with bipolar disorder belonged to urban areas compared to schizophrenia. Our study recruited mildly symptomatic to asymptomatic population and owing to the commonly encountered course of schizophrenia where remission is more commonly seen with medications as compared to the episodic course of bipolar disorder, whereby symptom reduction and relapse-free duration is more common. This can lead to an overrepresentation of those with better access to follow-ups among the bipolar disorder group.
We found that when disability was factored in methodologically, there was no significant difference in resilience levels between persons with schizophrenia and bipolar disorder. Previous studies have reported significantly low resilience levels in people with schizophrenia compared to bipolar disorder,[15] but the important role of disability is reflected in our study.
Linear regression analysis reveals that disability as an outcome depends significantly on sociodemographic variables and individual variables. It is important to note that variables like gender, socioeconomic status, education are broad sociological factors, but there was no significant overlap in how they influence disability, which indicates that each of these factors independently influences the outcome. Resilience has been dismissed as a similar broad psychosocial factor by some early commentators,[22] but our results indicate that it independently and significantly predicts disability in both schizophrenia and bipolar disorder. Additionally, in persons with bipolar disorder, symptom severity significantly predicted disability. This has been reported previously[23] and is expected as asymptomatic stages often show complete functional recovery.
Finally, it is evident that resilience significantly predicts disability in both groups, but on determining the effect of the disorder group on this influence, it is seen that there is no significant impact of the type of disorder on how resilience affects disability. This means that independent of the disorder, resilience predicts disability. Mizuno and his group had described similar findings where the quality of life was associated with resilience and resilience was not significantly different between the two disorders.[14] Our study provides support to the school of thought that resilience influences functional outcomes irrespective of diagnosis.
The current study suffers from some important limitations. The cross-sectional design prevents interpretation of causality, and the small hospital-based sample size limits generalizability. A more comprehensive assessment of symptom severity would have led to a better estimation of the relationship between the psychopathology domain and its effect on resilience. The study also fails to assess its objective in the illiterate subset of patients who are most vulnerable to poor functional outcomes and possibly form a majority of the clinical population, especially for schizophrenia.[24] The study also does not look for the differences in the type of resilience as individual and social factors may be different in the two different disorders.
There is a need to devise future studies addressing these lacunae to enrich our understanding of how resilience mediates and interacts with other clinical and sociodemographic factors and its association with patient-centric outcomes like disability.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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