East Asian Arch Psychiatry 2017;27:26-34


Impact of Cognition and Clinical Factors on Functional Outcome in Patients with Bipolar Disorder
A Soni, P Singh, R Shah, S Bagotia

Ms Rosemary Nourse, BS, RN, CCRC, St. Luke’s University Hospital, Bethlehem, Pennsylvania, United States.
Dr Pamela Adamshick, RN, PhD, Moravian College, Bethlehem, Pennsylvania, United States.
Dr Jill Stoltzfus, PhD, Research Institute, St. Luke’s University Hospital, Bethlehem, Pennsylvania, United States.

Address for correspondence: Ms Rosemary Nourse, St. Luke’s University Hospital, Behavioral Health, 801 Ostrum Street, Bethlehem, Pennsylvania, United States 18105.
Tel: (1-484) 526 4421; Fax: (1-484) 526 3840; Email: rinorse@aol.com

Submitted: 2 March 2016; Accepted: 8 August 2016

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Objective: To examine the role of different clinical variables and cognition on functional outcome in patients with bipolar disorder.

Methods: A total of 61 euthymic patients with bipolar disorder and 30 healthy individuals were included in the study. The patients were divided into low functioning (n = 30) or high functioning (n = 31) subgroups based on functioning level measured by Global Assessment of Functioning Scale score. Groups were subjected to neurocognitive and clinical assessment.

Results: Clinical variables differed significantly between low and high functioning patient groups, namely total number of episodes, depressive episodes, and time since the last episode. These variables were also correlated significantly with Global Assessment of Functioning Scale score. All 3 groups differed significantly for digit span backward test, verbal learning and memory test, Trail Making Test, and Stroop Colour Test. Digit span backward test, Trail Making Test, and Stroop Colour Test were significantly correlated with Global Assessment of Functioning Scale score.

Conclusions: Total episodes, depressive episodes, time since the last episode, and cognitive dysfunction correlated with poor functioning. Executive dysfunction was the strongest predictor of psychosocial outcome in euthymic bipolar patients. Long-term therapeutic interventions should target relapse prevention with special consideration given to depressive episodes and cognitive rehabilitation.

Key words: Bipolar disorder; Cognition; Depressive disorder


Bipolar disorder has traditionally been associated with a better outcome than schizophrenia.1 Nonetheless generally little attention has been paid to psychosocial outcomes in patients with bipolar disorder. Recent studies indicate that functioning varies considerably as far as the outcome is concerned: some patients function well in between episodes whereas others have substantial dysfunction in significant functional domains, even during euthymic periods.2-4

Several clinical variables are associated with poor functioning in patients with bipolar disorders including number of episodes,5 persistent subsyndromal symptoms,6 prior number of psychiatric hospitalisations,7 co-morbid substance use disorder,8,9 side-effects of medicine, history of psychotic symptoms,4,10 early age at onset,4,11 longer duration of mood episodes,12 and low premorbid functioning.13 Growing evidence suggests that bipolar disorder patients experience prominent neurocognitive impairment not only during acute mood episodes14,15 but also during euthymia.16,17 The cognitive deficits intrinsic to bipolar disorder itself typically coalesce around problems with attentional processing, executive function, and verbal memory.18,19

Functional outcome in bipolar disorder is significantly influenced by clinical variables related to the illness and cognitive functioning. The current study aimed to assess the relationship of these factors to functional outcomes in bipolar disorder.


This was a cross-sectional hospital-based analytical observational study carried out between 16 February 2014 and 28 December 2014 on euthymic bipolar patients who attended the outpatient department of the psychiatric centre, SMS Medical College Jaipur, India. Ethical approval was obtained from the research review board and ethical committee of the institution. Informed written consent was obtained from all participants prior to participation in the study.

A total of 61 patients were included over a period of 1 year. Male and female patients with bipolar disorder (according to the ICD-10 research criteria and confirmed by clinical interview of the participants and their immediate family members) aged 18 to 55 years who were currently euthymic (defined as Young Mania Rating Scale20 score of ≤ 6 and 17-item Hamilton Rating Scale for Depression21 score of ≤ 8) were recruited. Participants were required to have at least 7 years of formal education to reduce the confounding effect of education on cognitive tests.

Patients with a history of head injury, neurological illness, any other co-morbid psychiatric illness or substance abuse in the last year except nicotine abuse (assessed by the Mini-International Neuropsychiatric Interview [MINI]),22 mental retardation or any clinical condition that could affect cognitive performance, significant medical illness, electroconvulsive therapy in the last year, or physical disability (e.g. blind, deaf, speech problems, paralysis, amputation) were excluded.

Thirty healthy individuals, carefully matched with participating patients for age, gender, locality and education, were recruited from “bystanders” of the patients (e.g. spouse, distant relative, or the person accompanying the patient) to reduce the effect of confounding variables. Those who had a history of psychiatric illness (by MINI22) or a history of psychiatric illness in a first-degree relative (confirmed by clinical interview) were excluded from the study.

The patients were divided into low functioning (n = 30) and high functioning (n = 31) subgroups based on functioning level as measured by Global Assessment of Functioning Scale (GAF) score.23 The GAF23 assesses psychological, social, and occupational functioning with a possible score of 1 to 100. A score of 60 was set as the cut-off to distinguish patients with high and low functioning. As per the DSM-IV-TR, a score of > 60 (61-70) indicates some mild difficulty in social, occupational or academic activities or satisfactory activity. Nonetheless in general, the patient works quite well and has significant interpersonal relationships. A score of ≤ 60 indicates moderate to severe impairment in functioning. This cut-off has been recommended by earlier studies to distinguish poor functioning patients with psychiatric disorders.12,24 We used the GAF score to measure psychosocial functioning in the month prior to rating. After applying inclusion and exclusion criteria, 3 groups were assessed.

Socio-demographic profile included name, age, gender, name of father / husband, address, marital status, education, occupation, type of family, and monthly income. Clinical variables were recorded following clinical interview of participants and their immediate family members. Number and type of episodes, duration of illness (chronicity), age at onset of the illness, number of hospitalisations, time since the last episode, and history of psychotic symptoms were recorded. The investigator was blinded to the group category.

Neuropsychological assessments used in this study included the digit span forward test25 and the Trail Making Test part A26 for testing attention and concentration; Trail Making Test part B,26 the digit span backward test25 and the Stroop Colour Test27 for executive function; and verbal learning and memory test in Hindi.28

Assessment was performed in a fixed order in a quiet room by a trained psychiatrist who was blinded to the group category and took 45 minutes to 1 hour to complete.

Statistical Analysis

Data were analysed using the Statistical Package for the Social Sciences (SPSS Windows version 19.0; IBM Corp, Armonk [NY], United States). Socio-demographic variables of the 3 groups (high functioning, low functioning, and healthy controls) were compared using analysis of variance and Chi-square test as appropriate. Clinical variables of the 2 patient groups (low and high functioning) were compared using independent-samples t test and Chi-square test as appropriate. Multivariate analysis of variance (MANOVA) was performed to assess the difference in neurocognitive test results between the 3 groups followed by Tukey’s post-hoc analysis that was significant on MANOVA analysis. Descriptive statistics were expressed as mean and frequency as appropriate. Pearson’s correlation was applied to determine correlation among variables. Variables significantly correlated with GAF score were introduced into the linear regression analysis to identify better predictors of functional outcome. A p value < 0.05 was considered significant.


The socio-demographic profiles of the 3 groups were comparable. Most patients were married (78%), Hindu (89%), and male (60%) with a rural background (75%) and belonged to an upper lower or lower middle class family (91%). Most patients (54%) lived in a nuclear family. The mean durations of education were 8.6, 8.5 and 8.9 respectively in low functioning, high functioning, and control groups (Tables 1 and 2).

Table 3 shows the comparison of clinical variables between low and high functioning groups. A significant difference was evident in the total number of episodes (p = 0.003), depressive episodes (p = 0.001), and time since the last episode (p = 0.000).

Table 4 shows the correlation of different clinical variables with GAF score. In Pearson’s correlation analysis, total number of episodes (r = –0.459, p = 0.000), number of manic episodes (r = –0.299, p = 0.02), depressive episodes (r = –0.481, p = 0.000), and time since the last episode (r = 0.698, p = 0.000) were significantly correlated with GAF score.

With regard to neurocognitive variables, MANOVA yielded Pillai’s F of 4.976 (p = 0.000) for the main effect, indicating an overall difference in neurocognitive performance between groups. As shown in Table 5, multivariate analysis revealed that the 3 groups differed significantly for digit span backward test (p = 0.01), verbal learning and memory test (p = 0.001), Trail Making Test part A and B (p = 0.000), and all the 3 Stroop Colour Tests (p = 0.000). Multiple comparisons by Tukey’s post-hoc analysis were made to determine which 2 groups differed significantly in head-to-head comparison. Table 6 shows the mean difference and p value for each comparison. Digit span backward test, Trail Making Test (part A and B), and Stroop Colour Test were significantly correlated with GAF score (Table 7).

In an attempt to find the predictors of psychosocial functioning, those variables that correlated with psychosocial outcome (p < 0.05) were introduced in the linear regression analysis. Variables significantly correlated with GAF score were total number of episodes, number of manic episodes, number of depressive episodes, time since the last episode, digit span backward test, Trail Making Test (part A and B), and Stroop Colour Test. This model accounted for the 65.5% variance in psychosocial functioning (F = 15.22, t = 5.26, p = 0.000). The better predictors of psychosocial functioning among all the variables were time since the last episode (ß = 0.475, p = 0.000) and interference Stroop Colour Test (ß = –0.290, t = 2.82, p = 0.01).


The present study was designed to assess the impact of clinical and cognitive factors on functional outcome in euthymic patients with bipolar disorder. Patients were divided into low and high functioning groups based on GAF score (cut-off, 60) and several clinical factors compared. Those selected in this study were based on earlier studies.5,6,11,12 Neurocognitive performance was assessed by comparing the low and high functioning groups with the controls for digit span test, Trail Making Test, Stroop Colour Test, and verbal learning and memory test. Further analysis of the relationship of GAF score with clinical and cognitive factors was performed to identify better predictors of functional outcome in bipolar disorder. All 3 groups were comparable for age, gender, locality, education, and other socio-demographic variables.

Impact of Clinical Factors on Functional Outcome

The total number of episodes was associated with functional impairment. The mean total numbers of episodes were 9.2 and 5.7 in low and high functioning groups, respectively. Total number of episodes was negatively correlated with GAF score (Pearson’s correlation r = –0.459, p = 0.000). This finding is in line with earlier studies that reported a higher number of episodes has a more negative impact on social functioning.5,29,30 It is possible that more episodes may cause long-lasting biochemical changes in the brain that may impact global functioning in bipolar patients.31 Another possible explanation is that patients with multi-episode bipolar disorder are more prone to cognitive impairment that may in turn further worsen psychosocial outcome and employment.32-34 Nonetheless this study did not determine the correlation of clinical variables with cognitive functioning. A further possible explanation is that recurrent mood episodes and longer active phase of illness result in interrupted educational and vocational pursuits and repeated disruption of interpersonal engagement.35,36

In this study the number of depressive episodes was more strongly correlated with functional outcome than manic and total number of episodes (Table 4). The mean numbers of depressive episodes were 4.9 and 2.2 in low and high functioning groups, respectively. Another study5 showed similar findings where number of previous depressive episodes was a stronger determinant of outcome than past manias. Other studies37,38 also found that depressive episodes are strongly associated with poor functioning in bipolar disorder. Another study39 found that the number of manic episodes was associated with poor functional outcome only, but not the depressive episodes.

There are several possible explanations for the association between high rates of depressive episodes and impaired functioning. Some authors suggest that bipolar disorder patients perceive depressive phases as weaker than manic episodes.40 Another possible explanation is that depressive episodes are often associated with cognitive impairment that may worsen global functioning along the course of bipolar illness. Alternatively, it is possible that functional impairment may itself have a role in the development of depressive relapses.5

In this study time since the last episode was the best predictor of psychosocial functioning in euthymic patients with bipolar disorder. Time since the last episode also differed significantly between low and high functioning groups (13.8 vs. 43.8 months). It was positively correlated with GAF score and indicates that the longer the time a patient in a euthymic state, the better the outcome. Thus, our study suggests that interventions directed at prevention of relapse into further episodes will result in better psychosocial outcomes.

Impact of Neurocognitive Performance on Functional Outcome

In the present study various neurocognitive tests were performed to assess the cognitive domains of executive functioning (interference Stroop Colour Test, Trail Making Test part B, digit span backward test), attention and concentration (digit span forward test, Trail Making Test part A), and verbal learning and memory (verbal learning and memory test) because these are among the most important cognitive domains for daily functioning.41 Both low and high functioning groups performed poorer than the control group on the digit span backward test, Trail Making Test, verbal learning and memory test, and Stroop Colour Test. These findings show that euthymic patients with bipolar disorder have cognitive deficits in all the domains studied, i.e. executive functioning, attention and concentration, and verbal learning and memory. This is in accordance with existing literature. Meta-analytic studies suggest that euthymic patients with bipolar disorder have neurocognitive impairment in the domains of attention and processing speed, verbal learning, memory, and executive functioning.17,42

On post-hoc analysis, comparison between low and high functioning groups revealed that the former performed poorer in Trail Making Test and Stroop Colour Test. Furthermore digit span backward test, Trail Making Test (part A and B), and Stroop Colour Test were significantly correlated with GAF score and interference Stroop Colour Test was the best predictor of functional outcome. These findings show dysfunction in attention, psychomotor speed, working memory, ability to shift strategy, inhibitory control, and fluid cognitive flexibility cumulatively denote executive dysfunction in low functioning group. Thus, executive functioning is a better predictor of functional outcome than the other domains studied. These findings were supported by Martino et al43 who found significant associations of functional capacity with measures of attention (digit span forward test, Trail Making Test part A) and executive functions (Trail Making Test part B, verbal fluency test) in a sample of 48 euthymic patients with bipolar disorder. Similarly, Mur et al44 found that impaired executive function and loss of inhibition might be an important feature of bipolar disorder and suggested that these executive-type cognitive traits may constitute an endophenotype for further studies of the aetiology of bipolar disorder. Dixon et al45 have observed a shared pattern of executive dysfunction in manic, depressed and euthymic patients, with respect to strategic thinking, inhibitory control and response initiation, independently of mood state, and it is now apparent that all 3 phases of the illness demonstrate cognitive deficits. In an Indian study by Trivedi et al,46 euthymic bipolar patients showed significant differences in executive functions compared with normal controls.

Martinez-Aran et al12 found that bipolar patients in general showed poorer cognitive performance than healthy controls. This was most evident in low functioning patients and particularly for verbal memory and executive function measures. The best predictor of psychosocial functioning was verbal memory.12 Impaired attention and executive functioning can interfere with almost every facet of human life. Executive domains of cognition are required in every task of daily living. It is possible that cognitive impairment, especially in the executive domain, significantly disrupts functioning of patients, even in the euthymic phase. This poor functioning is one of the main factors that explains why bipolar disorder has been ranked seventh among the worldwide causes of non-fatal disease burden, as measured

in disability-adjusted life years by the World Health Organization.47 Recent studies have highlighted the modest impact of available interventions on functional recovery for a large proportion of bipolar disorders,48 and called for a research agenda that specifically addresses these issues.

The cognitive deficits that persist during the stable phase of illness, even after subsidence of active symptoms, suggest that some illness process is continued that was present before the illness was first diagnosed. Thus, our findings also indicate that these cognitive deficits may be considered endophenotypes of bipolar disorder. Bora et al49 conducted a meta-analyses of 18 cognitive variables in studies that compared performance of euthymic bipolar disorder patients (45 studies; 1423 subjects) or first-degree relatives of bipolar disorder patients (17 studies; 443 subjects) with healthy controls and found that response inhibition deficit, a potential marker of ventral prefrontal dysfunction, was the most prominent endophenotype of bipolar disorder. This study provides some initial confirmatory evidence although further studies are required to establish these findings.


The sample size was small so results cannot be generalised. The main limitation of the present study was the superficial separation of the patients into 2 groups based on a cut-off GAF score. Nonetheless it is probably useful to distinguish patients with no or mild impairment (high functioning group) in psychosocial outcome from those patients with severe or moderate impairment (low functioning group). Another relevant issue is the differences between patients and controls with respect to medication. This could partly explain the differences in neurocognitive performance. Although cognitive dysfunctions may be related to the effects of medication, they do not appear to be a primary effect of pharmacological treatment. The medication profile revealed that our patients were prescribed 4 kinds of medication: lithium, antiepileptics, antipsychotics (no patient was on conventional antipsychotics), and antidepressants. According to the literature there is no or little effect of medicines on cognition. With respect to lithium, a longitudinal study50 showed stable cognitive performance over a 6-year follow-up period. Regarding antiepileptics, research has found only a little evidence of cognitive impairment.51 Antipsychotics also have a neutral effect upon cognition, although some studies report improvement.52 In this study mixed episodes were not included in the results and discussion because we found mixed episodes in few patients only and analysis was not possible with so little data. We were unable to determine the association between clinical variables and cognition.


The present findings suggest that cognitive factors and clinical variables related to illness severity contribute to psychosocial outcome in bipolar disorder. Total number of episodes, depressive episodes, and time since the last episode correlated with poor functioning. Long-term therapeutic interventions that target relapse prevention with special consideration given to depressive episodes are required. Cognitive dysfunction is also correlated with poor functioning. It was most pronounced in low functioning group, but also evident in high functioning group. Executive dysfunction seems to be a strong predictor of psychosocial outcome in euthymic bipolar patients. These factors should be considered more widely with respect to the long-term management of bipolar disorder. The current treatments for bipolar disorder patients are limited with regard to functional recovery. More focus should be placed on psychopharmacological as well as psychosocial interventions, such as psycho-education, family intervention, and cognitive rehabilitation targeting relapse prevention and cognitive improvement.

In future, longitudinal follow-up studies with improved methodology and larger sample size could be planned to assess the progression of illness and cognitive dysfunctions and their impact on psychosocial functioning, as well as to establish the therapeutic efficacy of newer interventions that target relapse prevention and cognitive enhancement.


The authors have disclosed no conflicts of interest in this study.


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