Validity and reliability of the COgnitive Complaints in Bipolar disorder Rating Assessment (COBRA) in Italian bipolar patients

Validity and reliability of the COgnitive Complaints in Bipolar disorder Rating Assessment (COBRA) in Italian bipolar patients

Caterina Portaluppi1, Elena Teobaldi1, Giorgia Porceddu1,2, Camilla Garrone1, Giuseppe Maina1,2, Eduard Vieta3, Gianluca Rosso1,2

1Department of Neurosciences “Rita Levi Montalcini”, University of Turin, Italy; 2Psychiatric Unit, San Luigi Gonzaga University Hospital, Orbassano (Turin), Italy; 3Institute of Neuroscience, University of Barcelona, Hospital Clinic, IDIBAPS, CIBERSAM, Barcelona, Spain.

Summary. Background. Although bipolar disorder (BD) and cognitive impairment are straightly connected, limited tools exist to capture the patient’s perspective on cognitive decline and its impact on this disorder. The aims of the study are: 1) to assess the reliability and validity of the Italian version of a brief self-report scale (COgnitive Complaints in Bipolar disorder Rating Assessment - COBRA) among euthymic bipolar patients; 2) to investigate the relationship between the self-report scale, COBRA, the objective neurocognitive measure Screen for Cognitive Impairment in Psychiatry (SCIP), and the course of illness in BD. Methods. Western all-white sample (n=216) included 108 BD patients and 108 healthy matched controls. The psychometric properties of the COBRA (e.g., internal consistency, retest reliability, discriminative validity, factorial analysis, ROC curve and feasibility) were analyzed. A screening neuropsychological battery was used for objective cognitive assessment. Results. The Italian version of the COBRA (COBRA-I) had a high internal consistency (Cronbach’s alpha= 0.852) and retest reliability (ICC=0.848). Factor analysis validated the one-factor model, and the cut-off value was obtained with a score of 10.5. BD patients experienced greater cognitive complaints compared to control group suggesting a discriminative validity of the instrument. No significant correlation was found between COBRA and SCIP in the patients group. Higher COBRA scores were associated with BD type II, life-time hypomanic episodes and number of total episodes. Conclusions. The study proved the validity of the COBRA-I as a simple and reliable self-report instrument for screening or monitoring cognitive complaints in adult patients with BD.

Key words. Bipolar disorder, COBRA, cognitive assessment, self-report scale, validity and reliability.

Validità e affidabilità del COgnitive Complaints in Bipolar disorder Rating Assessment (COBRA) nei pazienti bipolari italiani.

Riassunto. Introduzione. Nonostante la stretta correlazione tra disturbo bipolare (DB) e deterioramento cognitivo, gli strumenti disponibili per acquisire la prospettiva del paziente riguardo al declino cognitivo e al suo impatto su questo disturbo sono limitati. Gli obiettivi dello studio sono: 1) valutare l’affidabilità e la validità della versione italiana di una breve scala auto-riferita (COgnitive Complaints in Bipolar disorder Rating Assessment - COBRA) tra pazienti bipolari eutimici; 2) analizzare la relazione tra la scala auto-riferita COBRA, la misura neurocognitiva obiettiva Screen for Cognitive Impairment in Psychiatry (SCIP) e il decorso della malattia nel DB. Metodi. Il campione, proveniente da una popolazione italiana di individui di origine caucasica (n=216), comprendeva 108 pazienti affetti da DB e 108 controlli sani appaiati per genere, età e livello d’istruzione. Sono state analizzate le proprietà psicometriche della COBRA (per es., consistenza interna, affidabilità al test-ripetizione, validità discriminativa, analisi fattoriale, curva ROC e fattibilità). Per la valutazione cognitiva obiettiva è stata utilizzata una batteria neuropsicologica di screening. Risultati. La versione italiana della COBRA (COBRA-I) ha mostrato un’elevata consistenza interna (alpha di Cronbach= 0,852) e una buona affidabilità al test-ripetizione (ICC=0,848). L’analisi fattoriale ha convalidato il modello a un fattore, con un valore di cut-off ottenuto a 10,5. I pazienti con DB hanno riportato un numero maggiore di lamentele cognitive rispetto al gruppo di controllo, suggerendo una validità discriminativa dello strumento. Non è stata trovata una correlazione significativa tra la COBRA e la SCIP nel gruppo di pazienti. Punteggi più elevati della COBRA sono risultati associati al DB di tipo II, alla presenza di episodi ipomaniacali nel corso della vita e al numero totale di episodi. Conclusioni. Lo studio ha dimostrato la validità della COBRA-I come strumento semplice e affidabile per lo screening o il monitoraggio delle lamentele cognitive nei pazienti adulti con DB.

Parole chiave. COBRA, disturbo bipolare, scala auto-riferita, validità e affidabilità, valutazione cognitiva.

Introduction

Bipolar disorder (BD) is a chronic and severe psychiatric disorder that substantially reduce psycho-social functioning1. Cognitive impairment, an invalidating key feature of BD, affects domains such as attention, memory and executive functioning, influencing work capacity, treatment adherence, self-esteem and quality of life2-5. Evidence has shown that patients with BD experience cognitive difficulties both in the acute episodes (i.e., manic, hypomanic, and depressed) and during euthymic periods6-9. Nevertheless, there is a lack of consensus about the relevance in investigating neurocognitive performance in patients with BD, as well as how to do so10. A complete neurocognitive assessment (i.e., second level assessment used for full diagnostic evaluation) is long to administer and requires substantial training to use, in addition to high costs, which may limit its use, especially in daily clinical practice. Brief instruments such as the Mini Mental State Examination (MMSE)11 or Montreal Cognitive Assessment (MoCA)12, which are routinely used in medicine to screen for dementia or mild cognitive impairment, are insufficient for assessing cognitive decline in psychiatric patients and often insensitive to subtle limitations in younger patients. A brief and reliable method for screening common cognitive impairments in psychiatry, with both objective and subjective tools designed for this purpose, would be critical for multiple reasons: 1) to determine the amount of awareness of the patient’s cognitive performance; 2) to have the patient’s cognitive performance monitored longitudinally, allowing for early intervention if cognitive impairment is suspected (with referral for indepth evaluation); 3) to look for any cognitive alterations as a result of psychopharmacological treatments; 4) to provide patients with more personalized care; 5) to have a prediction of functional capability, which is essential for judgments on long-term outcome and impairment severity. At present, certain scales evaluating subjective experiences of cognitive dysfunction in psychiatric patients exist, but they are designed generically – such as the Perceived Deficits Questionnaire-20 (PDQ-20)13 – or for schizophrenia spectrum disorders14,15 leaving BD patients unable to find their symptoms described properly. The Bipolar Disorder Program at the Hospital Clinic of Barcelona16 developed the Cognitive complaints in BD Rating Assessment (COBRA), focused on key area like memory, concentration and executive function, in order to detect the main daily cognitive complaints experienced by bipolar patients. Moreover, COBRA’s simplicity and ability to capture cognitive changes across different phases of the disorder make it practical for clinical use, outperforming more complex tools such as the Multiple Abilities Self-Report Questionnaire (MASQ)17. In 2018 the task force targeting cognition of the International Society for Bipolar Disorder (ISBD) published consensus-based recommendations on how to assess and manage cognitive impairment in BD18. The key recommendations were that mental health professionals formally screen cognition of BD patients whenever possible, by means of brief, cost-effective and easy-to-administer tools, and refer patients for extensive neuropsychological evaluation when clinically required. Specifically, the task force indicated the COBRA, still to be validated in Italian, and the Screen for Cognitive Impairment in Psychiatry (SCIP)19, already validated in Italian, as the most feasible tools for the screening of subjective and objective cognition, respectively. Both instruments are free of charge, brief, and do not require specific training for their administration. A key advantage of the COBRA is its ability to complement objective neuropsychological assessments, a feature that many other subjective tools, like the Cognitive Failures Questionnaire (CFQ)20, do not provide as effectively. There is little knowledge about the subjective perception of cognitive decline in affective disorders, and an indepth investigation of the subjective in bipolar illness is still lacking in Italy. For this reason, it is of great significance to translate the COBRA into Italian version to assess cognitive complaints reported by patients. The aims of the current study are: 1) to examine the psychometric properties of the COBRA among Italian BD patients and 2) to investigate the relationship between the COBRA, the objective cognitive measures (assessed by SCIP) and the course of illness.

Methods

Participants

A total of 216 subjects participated in the study. We included 108 patients (age 21-75 years) with DSM-5 BD type I (BD-I; n=21, 19.4%) and BD type II (BD-II; n=87, 80.6%) and meeting criteria of remission defined as a score ≤8 on the 17-Hamilton Depression Rating Scale (HAM-D)21 and on the Young Mania Rating Scale (YMRS)22 for at least three months previous to the assessment. Participants diagnosed with intellectual disability or cognitive impairment due to organic conditions were excluded. All subjects with bipolar diagnosis were outpatients enrolled in the psychiatric unit of a University Hospital, from Dec 2022 to Oct 2023. One hundred eight volunteers who did not meet criteria for any psychiatric disorder (according to the DSM-5) were included as healthy controls, matched for age, gender and years of education with patient’s group. The healthy comparison group was recruited from the general population, but we made sure that they had no first- degree relatives with BD. This study was approved by the Ethics Committee of the Hospital. After a complete verbal description of the study, all participants had written informed consent.

Assessments

Clinical and socio-demographic assessment

Socio-demographical and clinical data were collected through a semi-structured interview already used in clinical practice23. The 17-HAMD and YRMS were administered to assess depressive and manic symptoms, respectively.

Subjective cognitive measures

a) The COBRA was developed by the Bipolar Disorder Program at the Hospital Clinic of Barcelona 16 to detect the main daily cognitive complaints experienced by BD patients. The English version of COBRA24 was used to be translated into Italian version according to the British translation model. It was divided into four stages which were forward translation, back-translation, linguistic adaptation and pilot study. The first three stages were finished by cooperation among a clinical psychologist and two psychiatrists. Firstly, two independent psychiatrists translated English version into Italian and comparing the two different versions in order to reach a single one by consensus. Secondly, another psychiatrist finished back-translation then compared it with original English version to ensure conceptual equivalence. Finally, all the translators participated in the proof-reading test and the final Italian version was thus established. Subsequently, the Italian version was reviewed by a panel of experts (two senior psychiatrists and a clinical psychologist). English mother-tongue person evaluated the degree of equivalence between the English version and the Italian version. According to expert criterion, no items were modified. Next, we used the Italian version of the COBRA for a pilot study to evaluate the readability and simplicity among 20 euthymic BD inpatients in the psychiatric ward of the University Hospital. Consequently, after no modifications, the Italian version of the COBRA (COBRA-I) was ready for validation. The COBRA-I is a 16-item self-reported instrument, which allows measure subjective cognitive dysfunction including executive function, processing speed, working memory, verbal learning and memory, attention/concentration and mental tracking. All of items are rated using a 4-point scale, 0= never, 1= sometimes, 2= often, and 3= always (see English and Italian version in Appendix A). The COBRA total score is obtained when the scores of each item are added up. The higher the score, the more subjective complaints.

b) The Functional Assessment Short Test (FAST)25 is a both self-report and clinician-administered assessment scale of psychosocial dysfunction26 widely used in patients with BD. This scale includes 24 items that evaluate six functional domains (autonomy, occupational functioning, cognitive functioning, financial issues, interpersonal relationships, and leisure time). The higher the score, the greater the disability.

Objective cognitive measures

The Italian version of Screen for Cognitive Impairment in Psychiatry (SCIP-I)27 is a pencil-and-paper tool designed for rapid and objective quantification of cognitive impairment commonly observed in psychotic and affective disorders19,28-30. It has been validated in BD population, showing good sensitivity and specificity for detecting objective cognitive difficulties29,31-33. The SCIP assess five major cognitive domains that are affected in psychiatric illnesses, including immediate and delayed verbal learning, working memory, verbal fluency, and psychomotor speed. It took from 10 to 15 minutes long, depending on the participants. Cut scores offer a method to quickly identify limitations based on a SCIP total score derived from the sum of the 5 subtest scores. A SCIP total score greater than 74 is within normal limits, but scores less than 75, 65, or 55 may suggest mild, moderate, or severe limitations, respectively31. Three alternate parallel forms were developed to limit practice effects from repeat examination on five subscales selected; the first of the three forms were used in this study. The Verbal List Learning Test (VLT_I) is the first subscale and consists of three trials of a ten-item list, with total recall out of 30 as the primary outcome measure, and secondary measures that include primacy, recency, perseverations, and intrusions. The Working Memory Test (WMT) consists of eight recall trials of three-consonants, equally distributed among four conditions: no delay, or delays of 3, 9, or 18-seconds. The delay conditions are pseudo-randomly assigned to avoid successive repetition, and a three-digit number was randomly assigned from which backwards counting aloud for the delay interval provides distraction to divert resources from rehearsal. The primary outcome measure is the number of individual letters recalled out of twenty-four, regardless of order, and a secondary measure is available for scoring sequence of recall. The Verbal Fluency Test (VFT) consists of two-letters, each of which is offered in a thirty-second-generation task in which the examinee provides words that begin with the letter without producing numbers or proper nouns. The primary measure is the number of rule-consistent words produced from the two letters, with secondary measures available for perseverations, intrusions, and rule infractions. The Delayed List Learning Test (VLT_D) entails another recall trial of the verbal list after administration of the WMT and the VFT. The Psychomotor Speed Test (PST) is a novel task developed from eighteen letters of the Morse code. Six letters were assigned to each of the three forms and the corresponding Morse code dots and dashes were printed below each letter in a response key. A matrix of four rows of nine boxes is also provided, with pseudorandom assignment avoiding successive repetition of four exemplars from each of the six letters to the thirty-six boxes. The first six boxes are used for practice, prior to allowing 30 seconds to complete the remaining letters, the total of which provides the primary outcome measure.

Validity and reliability assessment

a) The internal consistency reliability and item total correlations were examined. In order to evaluate the test-retest reliability of the COBRA, the COBRA was readministered to 20 subjects (42.33 ± 7.12 years old, 12 women, 8 men) 2 weeks after the initial assessment by the same raters, and the intraclass correlation coefficient between the COBRA scores of the two assessments was calculated.

b) Concurrent validity was assessed in three ways:

• examining the relationship between COBRA results and the cognitive domain of the FAST;

• investigating the association between the COBRA and objective measures SCIP;

• studying possible correlations between the COBRA and course of the illness.

c) Discriminative validity to detect the differences between BD patients and healthy controls was analyzed using non-parametric test.

d) The optimal point for the COBRA was determined.

e) An exploratory factor analysis was performed to describe the internal structure of the COBRA.

Feasibility was described as the percentage of patients and controls who did respond to the questionnaire in its entirety.

Statistical analysis

Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS - Version 28.0., IBM Analytics) for Windows. Internal consistency was assessed by the Cronbach’s alpha. Spearman’s correlations coefficient was performed to examine the retest reliability and the possible relationship between the COBRA, FAST, SCIP and clinical course of the illness. Since data from COBRA total score followed a non-normal distribution (Kolmogorov-Smirnov test: 0.044; p<0.001), non-parametric tests were applied: the Mann-Whitney U test for continuous variables and chi-square (χ²) for categorical variables. Non-parametric tests were chosen due to the skewed distribution of the COBRA data, which violated assumptions of normality for parametric tests. The optimal point for the COBRA was determined by means of a receiver operating characteristic (ROC) curve. Exploratory factor analysis was conducted using principal axis factoring and the Quartimax rotation method was selected due to its ability to produce simple, interpretable factors with orthogonal rotation, which is suitable for identifying distinct cognitive complaint factors in this study’s data.

Trasparency and openness

Materials and analysis code for this study are available by emailing the corresponding author.

Results

A total of 216 subjects (108 with a diagnosis of BD and 108 healthy volunteers) were included in the study. The healthy comparison group matched for age, gender, and years of education with patient’s group (table 1).

Ages of the patients ranged 21-75 years (mean age= 49.82) and ages of the controls ranged 22-76 years (mean age= 48.52). Fifty-six (51.9%) patients and 61 (56.5%) of controls were women (p=0.234). Education years of the patients ranged 8-18 years (mean year= 14.52) and those of the controls ranged 8-18 years (mean year= 14.61). The 17-HAMD score and YMRS score of the patient group ranged 0-7 (mean score= 2.23) and 0-7 (mean score= 0.15); and those of the control group ranged 0-6 (mean score= 3.34) and 0-3 (mean score= 0.72). As expected, there were some significant differences in the number of people living alone and smoking (higher in the patient group) and the number of people engaging in habitual physical activity (higher in the healthy controls) based on the comparison of the two groups’ averages. Socio-demographic and clinical characteristics of the sample are shown in table 1.

Internal consistency analysis

The reliability of COBRA in terms of internal consistency was found to be good (Cronbach’s alpha= 0.862) and item-to-item correlations were between 0.305 and 0.543, suggesting that the items are sufficiently homogeneous. All items were also significantly with the COBRA total score (minus that item) with a range of 0.733-0.836. When test-retest reliability was examined, the results showed a good appropriate stability in the evaluations of patient involvement when no changes in clinical status were detected by the clinicians (ICC=0.848).

Association between COBRA and cognitive domains of FAST

A strong correlation was found between the COBRA total score and the cognitive domain of the FAST scale, indicating the concurrent validity of the instrument (rho 0.818**, p<0.001) (figure 1).

Association between subjective COBRA and neuropsychological tests of SCIP

Spearman correlations were performed to assess relationship between subjective and objective cognitive measures in both groups. In the patient group, no significant correlations were found between the COBRA score and single neuropsychological measures of the SCIP, indicating a possible lack of congruence between the objective patient’s cognitive functioning and complaints reported by, and thus the level of awareness (figure 2).

On the other hand, significant correlations were found between the COBRA total score and all single measures of the SCIP related to VLT_I (p≤0.001) and VLT_D (p≤0.001), WMT (p=0.005), VFT (p=0.005) and PST (p≤0.001) in the control group (table 2).

Association between subjective COBRA and clinical variables

The COBRA score obtained by patient group was also strongly correlated with some clinical variables of BD: duration of illness (rho=0.340, p=0.013), number of total episodes (rho=0.436, p<0.001), number of hypomanic episodes (rho=0.440, p<0.001), number of depressive episodes (rho=0.360, p=0.006), family history of psychiatric disease (rho=0.479, p<0.001) (table 3).

BD-II patients experienced more subjective complaints than subjects with BD-I (U=334, p=0.360).

Validity as a discriminative measure to detect differences between bipolar patients and healthy controls

BD patients experienced higher COBRA score (12.38 ±6.62) than healthy controls (8.42±5.20; p=0.005).

ROC curve

We analyzed the scale’s discriminative capacity between patients and controls by means of the diagnostic performance or ROC curve. The area under the curve was 0.691. 95% CI:(0.593-0.788) (figure 3).

The discriminative capacity analysis indicates that a cut-off point 10.5 obtains the best balance between sensitivity (76.8%) and specificity (57.1%).

Factorial analysis

The study of the internal structure of the COBRA after rotation (using quartimax method) determined a three-factor structure as shown in table 4.

However, as only a few items were loaded in the second and third factor and their values were closer of the first load, we considered one-dimensional structure which was responsible for 39% of the total variance.

Feasibility

Finally, the results showed a high feasibility of the COBRA since that the totality of participants answered all items of the instrument.

Discussion

The results of the present study demonstrated that the COBRA-I is a valid self-report scale to assess cognitive complaints in Italian patients with BD. The instrument exhibited satisfactory properties with high internal consistency, test-retest reliability and convergent validity as indicated by a strong correlation with the cognitive domain of the FAST scale. Furthermore, the COBRA-I results to have one-dimensional construct which means that patients tend to perceive their difficulties as a global cognitive dysfunction and allows clinicians to obtain a simple and global score (ranging from 0 to 48). Our findings are consistent with previous validations of the COBRA tool in Brazil34, China35, Japan36, and Spain24, confirming its effectiveness in assessing cognitive complaints specific to BD (table 5).

These studies highlight its reliability across cultures while noting that cultural differences can affect how cognitive difficulties are perceived and reported. One of the advantages of the COBRA over other cognitive self-reports is because it was specially designed to assess cognitive problems related to BD patients, therefore deprived of those items related to psychotic features and sometimes difficult to understand by many BD patients.

In terms of the instrument’s discriminant validity, we observed that COBRA total scores were higher in patients compared to healthy controls. Additionally, the cut-off point to discriminate subjective cognitive complaints between patients and controls was of 10.5 or above, similar to the original COBRA validation24. However, discussing the discriminative validity of a self-report instrument is challenging and the analysis requires caution, since it involves the implication of self-evaluation. Here, the degree of insight and evaluation accuracy present in objective instruments become determining criteria to be considered. Therefore, combining subjective and objective screening assessment is essential because is the way to collect relevant and complete information on the relationship between difficulties measured by the clinician and complaints reported by the patient33,37. The investigation of relationships between the COBRA self-report measure and the SCIP neuropsychological assessments adds to this. We didn’t find any associations between COBRA and the neuropsychological tests of the SCIP in the patients group. This aligns with previous research that has reported no significant correlations between subjective cognitive complaints and objective neurocognitive measures10,35,38,39. Studies assessing the relationship between subjective and objective cognitive measures have shown controversial results38,40. For instance, Faurholt-Jepsen et al.41 and Toyoshima et al.36 identified discrepancies between subjective perceptions and objective assessments, reflecting the complexities of cognitive self-reporting. Conversely, other studies, such as Lin et al.42 and Van Rheenen & Rossell43, observed a link between cognitive impairment and quality of life, suggesting that subjective and objective measures can align in specific contexts.

Recently, Bonnin et al.44 have reported that the main variable involved in the discrepancies between objective and subjective cognitive impairment are the number of depressive episodes and hospitalizations; hence, the patients with more previous depressive episodes seem to overreport cognitive complaints, whereas those with more hospitalizations (as a likely proxy of more manic episodes and less insight) are more likely to underreport those. This means that some cognitive complaints are related to biographical memories which are not commonly measured by traditional neurocognitive testing. Moreover, social cognition and insight45 may be impaired in BD, but they are not generally assessed in these patients. Specifically, impairments in social cognition, including theory of mind (ToM), can hinder BD patients’ ability to accurately evaluate their cognitive and emotional states. This may lead to biased self-reports of cognitive difficulties46,47. Therefore, future research should include social cognition assessments to enhance the understanding of cognitive complaints in BD. Probably, cognitive complaints are referred to subjective experience of general cognitive problems that are not well characterized when reported by patients (e.g., memory problems). BD patients could be unable to report the cognitive impairment accurately or not be aware of their cognitive deficits but still show significant impairment in neurocognitive testing and impact on daily functioning. These difficulties are generally reported by relatives and observed by clinician48.

Furthermore, factors related to the course of the illness may also contribute to the partial association between both objective and subjective cognitive measures. Investigating possible relationships between COBRA score and clinical characteristics suggestive of the course of bipolar illness, subjective cognitive complaints were strongly associated with higher number of total episodes and hypomanic episodes, and for psychiatric familiarity. We also found that subjects with BD-II experienced more cognitive complaints than those with BD-I subtype. BD-II is widely recognized to be associated with greater number of depressive episodes49, poorer health-related quality of life50, and more anxiety disorder comorbidity51 which may contribute to the increased cognitive complaints observed in this population52. It suggests that this subgroup of patients (e.g., BD-II patients with higher number of episodes) represents a population at risk of experiencing more cognitive complaints, which might affect psychosocial functioning.

The current study has several strengths. We used the objective screening measure SCIP, which has been demonstrated to be effective when combined with the COBRA, making both tools suitable for screening purpose33,53,54. Moreover, the group of healthy controls was matched for age, sex, and years of education with the patient group, providing a well-controlled comparison. Lastly, the enrolled BD patients were euthymic with poor residual symptoms. However, there are several limitations. Firstly, all participants were recruited from a hospital, which may lead to a sample with a more severe illness course, potentially limiting the generalizability of the findings to the wider BD population. Secondly, the homogeneity of our predominantly Western, educated, and industrialized white sample further restricts generalizability, as cultural, socio-economic, and educational factors may influence the perception and reporting of cognitive complaints. Thirdly, the study’s cross-sectional design prevented us from controlling for the influence of medication on subjective and objective cognitive measures since all participants were receiving drug therapies at the time of the study55,56. Medications like mood stabilizers, antipsychotics, and antidepressants, can affect cognitive functions in different ways, complicating the interpretation of cognitive assessments. Lithium is linked to psychomotor slowing and mild memory deficits, while second-generation antipsychotics (SGAs) and antidepressants can impair cognition to varying degrees, with polypharmacy further exacerbating these effects57-60. Lastly, the lack of analysis of mixed features in bipolar episodes represents another limitation, as this could provide a more comprehensive understanding of cognitive impairments in BD.

Given these limitations, future research should focus on several key areas. First, future research should consider stratifying participants by medication regimens and employ longitudinal designs to better understand treatment impacts. Furthermore, while we used a unidimensional COBRA, future studies could consider a multifactorial approach to better capture the diverse cognitive impairments in BD and assess the specific impacts of pharmacological treatments. The lack of analysis of mixed features in BD episodes is another gap that should be addressed in future research. Moreover, exploring the possibility of stratifying results by specific cognitive domains could offer a more detailed understanding of cognitive deficits in BD. Future studies could also examine the role of affective temperaments in potential discrepancies between subjective and objective cognitive findings, as these may influence how cognitive difficulties are perceived and reported61,62. In addition, research suggests that psychoeducational interventions may improve patients’ insight and reduce discrepancies between self-reported and clinician-administered cognitive assessment in BD63,64, an area that future studies could explore further. Lastly, given that sociodemographic factors are known to influence cognitive perception in BD65,66, future research should examine these factors more closely.

Conclusions

The COBRA-I is a brief 16-item, self-reported instrument, which allows us to investigate cognitive dysfunctions focusing on executive function, processing speed, working memory, verbal learning and memory, attention/concentration and mental tracking which are the main cognitive deficits experienced by BD patients. Subjective cognitive measures were not correlated with the objective cognitive assessment but with poor course of bipolar illness. Even though self-report scales could seem biased, we should take into consideration the patient’s perception of cognitive difficulties as valid and useful clinical information67, obtained through an instrument specifically addressed to the difficulties commonly reported by BD patients in both everyday clinical practice and investigation. At the end, those scales speak about what really matters to patients and they are easy to apply, as only patient consent and literacy are necessary.

Conflict of interests: Giuseppe Maina has been a consultant/speaker for Angelini, Boehringer, Fb Health, Innovapharma, Italfarmaco, Janssen, Otsuka, Lundbeck, and Sanofi. Gianluca Rosso has been a speaker and/or consultant from Angelini, Janssen, Lundbeck, Otsuka, Viatris. Eduard Vieta has received grants and served as consultant, advisor or CME speaker for the following entities (unrelated to the present work): AB-Biotics, Abbott, Abbvie, Adamed, Angelini, Biogen, Biohaven, Boehringer Ingelheim, Casen-Recordati, Celon, Compass, Dainippon Sumitomo Pharma, Ethypharm, Ferrer, Gedeon Richter, GH Research, Glaxo Smith-Kline, Idorsia, Janssen, Johnson & Johnson, Lundbeck, Newron, Novartis, Organon, Otsuka, Rovi, Sage, Sanofi-Aventis, Sunovion, Takeda, and Viatris.

The COBRA is property of Dr. Vieta’s team but it can be used for free upon permission.

The data shown have never appeared in previous publications.

References

1. McIntyre RS, Berk M, Brietzke E, et al. Bipolar disorders. Lancet 2020; 396: 1841-56.

2. Bonnín CdM, González-Pinto A, Solé B, et al. Verbal memory as a mediator in the relationship between subthreshold depressive symptoms and functional outcome in bipolar disorder. J Affect Disord 2014; 160: 50-4.

3. Cipriani G, Danti S, Carlesi C, Cammisuli DM, Di Fiorino M. Bipolar disorder and cognitive dysfunction. J Nerv Ment Dis 2017; 205: 743-56.

4. Gitlin MJ, Miklowitz DJ. The difficult lives of individuals with bipolar disorder: a review of functional outcomes and their implications for treatment. J Affect Disord 2017; 209: 147-54.

5. Lima IMM, Peckham AD, Johnson SL. Cognitive deficits in bipolar disorders: implications for emotion. Clin Psychol Rev 2018; 59: 126-36.

6. Robinson LJ, Thompson JM, Gallagher P, et al. A meta-analysis of cognitive deficits in euthymic patients with bipolar disorder. J Affect Disord 2006; 93: 105-15.

7. Jabben N, Arts B, Jongen EMM, Smulders FTY, Van Os J, Krabbendam L. Cognitive processes and attitudes in bipolar disorder: a study into personality, dysfunctional attitudes and attention bias in patients with bipolar disorder and their relatives. J Affect Disord 2012; 143: 265-8.

8. Cullen B, Ward J, Graham NA, et al. Prevalence and correlates of cognitive impairment in euthymic adults with bipolar disorder: a systematic review. J Affect Disord 2016; 205: 165-81.

9. Sadana D, Gupta RK, Jain S, et al. Neurocognitive profile of patients with Bipolar Affective Disorder in the euthymic phase. Asian J Psychiatr 2017; 28: 1-6.

10. Svendsen AM, Kessing LV, Munkholm K, Vinberg M, Miskowiak KW. Is there an association between subjective and objective measures of cognitive function in patients with affective disorders? Nord J Psychiatry 2012; 66: 248-53.

11. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189- 98.

12. Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 2005; 53: 695-9.

13. Strober LB, Binder A, Nikelshpur OM, Chiaravalloti N, DeLuca J. The Perceived Deficits Questionnaire: Perception, Deficit, or Distress? Int J MS Care 2016; 18: 183-90.

14. Cella M, Bodnar M, Lepage M, et al. Investigating subjective cognitive complaints in psychosis: Introducing the brief scale to Investigate cognition in schizophrenia (SSTICS-Brief). Cogn Neuropsychiatry 2020; 25: 190-200.

15. Wagle AC, Berrios GE, Ho L. The cognitive failures questionnaire in psychiatry. Compr Psychiatry 1999; 40: 478-84.

16. Vieta E. Tertiarism in psychiatry: Barcelona clinic Bipolar Disorders Programme. Rev Psiquiatr Salud Ment 2011; 4: 1-4.

17. Seidenberg M, Haltiner A, Taylor MA, Hermann BB, Wyler A. Development and validation of a Multiple Ability Self-Report Questionnaire. J Clin Exp Neuropsychol 1994; 16: 93-104.

18. Miskowiak K, Burdick K, Martinez-Arán A, et al. Assessing and Addressing Cognitive Impairment in Bipolar Disorder: The International Society for Bipolar Disorders Targeting Cognition Task Force Recommendations for Clinicians. Bipolar Disord 2018; 20: 184-94.

19. Purdon SE. The Screen for Cognitive Impairment in Psychiatry (SCIP): instructions and three alternate forms. Edmonton AB, Canada: PNL, 2005.

20. Broadbent DE, Cooper PF, FitzGerald P, Parkes KR. The Cognitive Failures Questionnaire (CFQ) and its correlates. Br J Clin Psychol 1982; 21: 1-16.

21. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960; 23: 56-62.

22. Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry 1978; 133: 429-35.

23. Di Salvo G, Porceddu G, Albert U, Maina G, Rosso G. Correlates of long duration of untreated illness (DUI) in patients with bipolar disorder: results of an observational study. Ann Gen Psychiatry 2023; 22: 12.

24. Rosa AR, Mercade C, Sánchez-Moreno J, et al. Validity and reliability of a rating scale on subjective cognitive deficits in bipolar disorder (COBRA). J Affect Disord 2013; 150: 29-36.

25. Rosa AR, Sánchez-Moreno J, Martínez-Aran A, et al. Validity and reliability of the Functioning Assessment Short Test (FAST) in bipolar disorder. Clin Pract Epidemiol Ment Health 2007; 3: 5.

26. Siegel-Ramsay JE, Wu B, Kapczinski F, et al. Functional assessment short test (FAST): self-administration in out-patient mental health settings. J Psychiatr Res 2023; 160: 258-62.

27. Murri MB, Folesani F, Costa S, et al. Italian validation of the Screen for Cognitive Impairment in Psychiatry. Community Ment Health J 2020; 56: 1411-8.

28. Gómez-Benito J, Guilera G, Pino O, et al. The Screen for cognitive impairment in psychiatry: diagnostic specific standardization in psychiatric ill patients. BMC Psychiatry 2013; 13: 127-37.

29. Guilera G, Pino O, Gómez-Benito J, et al. Clinical usefulness of the screen for cognitive impairment in psychiatry (SCIP-S) scale in patients with type I bipolar disorder. Health Qual Life Outcomes 2009; 7: 28.

30. Schmid P, Czekaj A, Frick J, Steinert T, Purdon SE, Uhlmann C. The screen for cognitive impairment in psychiatry (SCIP) as a routinely applied screening tool: pathology of acute psychiatric inpatients and cluster analysis. BMC Psychiatry 2021; 21: 494.

31. Rojo E, Pino O, Guilera G, et al. Neurocognitive diagnosis and cut-off scores of the Screen for Cognitive in Psychiatry (SCIP-S). Schizophr Res 2010; 116: 243-51.

32. Cuesta MJ, Pino O, Guilera G, et al. Brief cognitive assessment instruments in schizophrenia and bipolar patients, and healthy control subjects: A comparison study between the Brief Cognitive Assessment Tool for Schizophrenia (B-CATS) and the Screen for Cognitive Impairment in Psychiatry. Schizophr Res 2011; 130: 134-42.

33. Jensen JH, Støttrup MM, Nayberg E, et al. Optimising screening for cognitive dysfunction in bipolar disorder: Validation and evaluation of objective and subjective tools. J Affect Disord 2015; 15: 10-9.

34. Lima FM, Cardoso TA, Serafim SD, et al. Validity and Reliability of the Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA) in Brazilian bipolar patients. Trends Psychiatry Psychother 2018; 40: 170-8.

35. Xiao L, Lin X, Wang Q, Lu D, Tang S. Adaptation and validation of the “cognitive complaints in bipolar disorder rating assessment” (COBRA) in Chinese bipolar patients. J Affect Disord 2015; 173: 226-31.

36. Toyoshima K, Kako Y, Toyomaki A, et al. Associations between cognitive impairment and quality of life in euthymic bipolar patients. Psychiatry Res 2019; 271: 510-5.

37. Ott CV, Bjertrup AJ, Jensen JH, et al. Screening for cognitive dysfunction in unipolar depression: Validation and evaluation of objective and subjective tools. J Affect Disord 2016; 15: 607-15.

38. Van der Werf-Eldering MJ, Burger H, Jabben N, Holthausen EA, Aleman A, Nolen WA. Is the lack of association between cognitive complaints and objective cognitive functioning in patients with bipolar disorder moderated by depressive symptoms? J Affect Disord 2011; 130: 306-11.

39. Burdick KE, Endick CJ, Goldberg JF. Assessing cognitive deficits in bipolar disorder: are self-reports valid? Psychiatry Res 2005; 136: 43-50.

40. Arts B, Jabben N, Krabbendam L, van OJ. A 2-year naturalistic study on cognitive functioning in bipolar disorder. Acta Psychiatr Scand 2011; 123: 190-205.

41. Faurholt-Jepsen M, Miskowiak K, Frost M, et al. Patient-evaluated cognitive function measured with smartphones and the association with objective cognitive function, perceived stress, quality of life and function capacity in patients with bipolar disorder. Int J Bipolar Disord 2020; 8: 10.

42. Lin X, Lu D, Huang Z, Chen W, Luo X, Zhu Y. The associations between subjective and objective cognitive functioning across manic or hypomanic, depressed, and euthymic states in Chinese bipolar patients. J Affect Disord 2019; 249: 73-81.

43. Van Rheenen T, Rossell S. Objective and subjective psychosocial functioning in bipolar disorder: an investigation of the relative importance of neurocognition, social cognition and emotion regulation. J Affect Disord 2014; 162: 134-41.

44. Bonnín CM, Sánchez-Moreno J, Lima F, et al. Factors associated with the discrepancy between objective and subjective cognitive impairment in bipolar disorder. J Affect Disord 2024; 15: 210-6.

45. Samalin L, Belzeaux R. Why does non-adherence to treatment remain a leading cause of relapse in patients with bipolar disorder? Eur Neuropsychopharmacol 2023; 73: 16-8.

46. Bora E, Pantelis C. Theory of mind impairments in first-episode psychosis, individuals at ultra-high risk for psychosis and in first-degree relatives of schizophrenia: systematic review and meta-analysis. Cambridge, UK: Cambridge University Press, 2016.

47. Rowland JE, Hamilton MK, Vella N, Lino BJ, Mitchell PB, Green MJ. Adaptive associations between social cognition and emotion regulation are absent in schizophrenia and bipolar disorder. Front Psychol 2013; 4: 1-9.

48. Schouws SN, Comijs HC, Stek ML, Beekman AT. Self-reported cognitive complaints in elderly bipolar patients. Am J Geriatr Psychiatry 2012; 20: 700-6.

49. Mantere O, Suominen K, Valtonen HM, et al. Differences in outcome of DSM-IV bipolar I and II disorders. Bipolar Disord 2008; 10: 413-25.

50. Albert U, Rosso G, Maina G, Bogetto F. Impact of anxiety disorder comorbidity on quality of life in euthymic bipolar disorder patients: differences between bipolar I and II subtypes. J Affect Disord 2008; 105: 297-303.

51. Di Salvo G, Pessina E, Aragno E, et al. Impact of comorbid obsessive-compulsive disorder on suicidality in patients with bipolar disorder. Psychiatry Res 2020; 290: 113088.

52. Solé B, Martínez-Arán A, Torrent C, et al. Are bipolar II patients cognitively impaired? A systematic review. Psychol Med 2011; 41: 1791-803.

53. Rossetti MG, Perlini C, Abbiati V, et al. The Italian version of the brief assessment of cognition in affective disorders: performance of patients with bipolar disorder and healthy controls. Compr Psychiatry 2022; 117: 152335.

54. Miskowiak KW, Kjærstad HL. Can cognition screening in the clinic aid personalised treatment in bipolar disorder? Eur Neuropsychopharmacol 2024; 3: 10-1.

55. Torrent C, Martínez-Arán A, Daban C, et al. Effects of atypical antipsychotics on neurocognition in euthymic bipolar patients. Compr Psychiatry 2011; 52: 613-22.

56. Ilzarbe L, Vieta E. The elephant in the room: Medication as confounder. Eur Neuropsychopharmacol 2023; 71: 6-8.

57. Anyfandi E, Owens DA, Psarros C, et al. Bipolar disorder, mood stabilizers, and cognitive flexibility: Translationally dissecting illness from drug effects. Behav Brain Res 2022; 420: 1-9.

58. Jiang X, Mio M, Dimick MK, Zou Y, Sultan AA, Goldstein BI. Association of lithium and second-generation antipsychotics with neurocognition in youth with bipolar disorder. JAMA Psychiatry 2022; 79: 254-62.

59. Amado-Boccara I, Gougoulis N, Poirier Littré MF, Galinowski A, Lôo H. Effects of antidepressants on cognitive functions: a review. Neurosci Biobehav Rev 1995; 19: 479-93.

60. Valtonen J, Karrasch M. Polypharmacy-induced cognitive dysfunction and discontinuation of psychotropic medication: a neuropsychological case report. Neuropsychol Rev 2020; 30: 167-74.

61. Russo M, Mahon K, Shanahan M, et al. Affective temperaments and neurocognitive functioning in bipolar disorder. J Affect Disord 2014; 169: 51-6.

62. Xu G, Lu W, Ouyang H, et al. Association of affective temperaments measured by TEMPS-a with cognitive deficits in patients with bipolar disorder. J Affect Disord 2014; 161: 109-15.

63. Colom F, Vieta E, Reinares M, et al. Psychoeducation efficacy in bipolar disorders: beyond compliance enhancement. J Clin Psychiatry 2003; 64: 1101-5.

64. Bowie CR, Gupta M, Holshausen K, Jokic R, Best M, Milev R. Cognitive remediation for treatment-resistant depression: effects on cognition and functioning and the role of online homework. J Nerv Ment Dis 2013; 201: 680-5.

65. Bora E, Harrison BJ, Yücel M, Pantelis C. Cognitive impairment in euthymic major depressive disorder: a meta-analysis. Psychol Med 2013; 43: 2017-26.

66. Vance DE, Bail J, Enah CC, Palmer JJ, Hoenig AK. The impact of employment on cognition and cognitive reserve: implications across diseases and aging. Neurodegener Dis Res 2016; 6: 61-71.

67. Yoldi-Negrete M, Palacios-Cruz L, Tirado-Durán E, et al. Looking for factors affecting functioning in euthymic patients with bipolar I disorder: the importance of cognitive complaints and BDNF’s Val66Met polymorphism. J Affect Disord 2022; 302: 131-13.