Abstract
Cognitive deficits are prevalent in bipolar disorder even during the euthymic phase, having a negative impact on global functioning and quality of life. As such, more and more mental health professionals agree that neuropsychological assessment should be considered an essential component of the clinical management of bipolar patients. However, no gold standard tool has been established so far. According to bipolar disorder experts targeting cognition, appropriate cognitive tools should be brief, easy to administer, cost-effective and validated in the target population. In this commentary, we critically appraised the strengths and limitations of the tools most commonly used to assess cognitive functioning in bipolar patients, both for screening and diagnostic purposes.
Key words: Bipolar disorder, cognitive neuroscience, psychological assessment, rating scale
There is growing consensus that cognitive impairment is a key feature of bipolar disorder (BD), visible even before the first manifestation of the disease and in both acute and remitted phases (Bora et al., 2010a; Bora and Pantelis, 2015). Cognitive deficits of bipolar patients primarily affect long-term verbal and visual memory skills, working memory, attention and psychomotor speed, executive functions and language (Kurtz and Gerraty, 2009; Baune et al., 2013). Most importantly, these deficits slow down the recovery and worsen educational and occupational attainment (Robinson et al., 2006; Baune et al., 2013), resulting in poorer psychosocial functioning and lower quality of life for the patients (Baune et al., 2013). Current evidence highlights the need to systematically implement neuropsychological assessment in the clinical management of BD as an essential component for planning tailored interventions. Consistently, increasing efforts have been made to develop standardised and validated instruments for assessing cognition in BD, although a gold standard tool has not been established yet(Bakkour et al., 2014).
In this commentary, we critically appraised the strengths and limitations of the tools most commonly used to assess cognition in BD, both for screening purposes or to detect cognitive impairment Fig. 1.
Fig. 1.
A diagram to help healthcare professionals to make the best use of tools commonly used to assess cognition in BD.
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 BD (Miskowiak et al., 2018). The key recommendations were that mental health professionals formally screen cognition of bipolar 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 Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA) and the Screen for Cognitive Impairment in Psychiatry (SCIP) as the most feasible tools for the screening of subjective and objective cognition, respectively (Miskowiak et al., 2018). Both instruments are free of charge, brief, and do not require specific training for their administration.
The COBRA is a self-report rating scale specifically developed to test subjective cognition in BD. The instrument has high practical utility but has shown only small-to-moderate sensitivity and specificity for detecting objective cognitive impairment (Jensen et al., 2015). Therefore, its use is recommended only in combination with other screeners for objective cognition (Miskowiak et al., 2018).
The SCIP is the pencil-and-paper tool most commonly used for screening objective cognition in psychiatric disorders (Guilera et al., 2009; Rojo et al., 2010; Schmid et al., 2021). The test has three parallel versions making it suitable for monitoring performance over time. The SCIP has been validated in BD, showing good sensitivity and specificity for detecting objective cognitive impairment (Guilera et al., 2009; Rojo et al., 2010; Cuesta et al., 2011; Jensen et al., 2015). However, for this tool (as for other prospective cognitive screening tests), there is still a lack of normative data to determine clinically significant change over time at the individual level (Purdon and Psych, 2005).
A modified web-based version of the SCIP was developed in 2019, i.e. the Internet-Based Cognitive Assessment Tool (ICAT) (Hafiz et al., 2019; Miskowiak et al., 2021). The ICAT is a patient-administered test that allows the screening of objective cognitive deficits online, using gold-standard, performance-based cognitive tasks. The ICAT has shown good sensitivity to cognitive impairment of bipolar patients and high concurrent validity with the SCIP (Miskowiak et al., 2021). Overall, ICAT allows assessment and monitoring of patients' cognition at a much larger scale and at a reduced cost than paper-and-pencil tests. Nonetheless, the ability to operate computers/tablets independently and the presence of an internet connection are essential prerequisites for using this instrument.
Another web-based, patient-administered cognitive screening tool that can be potentially applied to bipolar patients is the THINC-IT. This test was released prior to ICAT but was originally designed for patients with unipolar depression (McIntyre et al., 2017). THINC-it employs gamified cognitive tasks to engage patients in taking the tests. Similar to ICAT, THINC-IT is free of charge, brief, and user-friendly; however, it lacks an assessment of verbal learning and memory, which (ideally) should always be present in screening tools for BD since impairments in this domain represent a core feature of the disorder that is common also during remitted states (Arts et al., 2008; Bora et al., 2010b) and contributes to poor occupational and daily functioning (Robinson et al., 2006; Baune et al., 2013). Of note, THIC-IT was tested on patients with BD-II only (Zhang et al., 2020). Therefore, further studies including both BD-I and BD-II are needed to verify the suitability and sensitivity of this battery for cognitive assessment in BD.
Overall, cognitive screeners for use in BD take little time to administer, are easy to use and cost-effective and appear feasible in the clinical management of BD. However, they do not measure real-life functions and cannot replace a thorough neuropsychological evaluation (Miskowiak et al., 2018).
As for comprehensive neuropsychological assessments, the MATRICS Consensus Cognitive Battery (MCCB) and the Brief Assessment of Cognition In Affective Disorders (BAC-A) are among the most commonly used tools with bipolar patients (Yatham et al., 2010; Van Rheenen and Rossell, 2014).
The MCCB was developed originally for schizophrenia (Nuechterlein et al., 2008). Then, the cognition task force of the ISBD endorsed the applicability and clinical utility of most MCCB subtests for use in BD, further recommending the inclusion of more complex measures of verbal learning or executive function (Yatham et al., 2010). Preliminary evidence has shown good sensitivity of the MCCB in distinguishing between the cognitive functioning of bipolar and control groups and a need for a more thorough evaluation of specific domains as suggested by the ISBD (Van Rheenen and Rossell, 2014).
The BAC-A has been designed specifically for use in affective disorders (Keefe et al., 2014). The battery includes eight subtests measuring both non-affective and affective cognition. Moreover, it is suitable for test-retest evaluations as the verbal tests include alternative forms. Recent studies have demonstrated that the BAC-A is sensitive to the cognitive impairments of patients with BD in both affective and non-affective cognitive domains and has good test-retest reliability (Keefe et al., 2014; Bauer et al., 2015; Barbosa et al., 2018; Lee et al., 2018; Rossetti et al., 2022).
Overall, evidence suggests that both the MCCB and the BAC-A have proved sensitive to the cognitive impairment of bipolar patients and may be used for diagnostic purposes. However, these tools are expensive, time-consuming and require extensive training for their administration. Such factors limit their applicability in clinical practice.
In this commentary, we critically appraised the strengths and limitations of the tools most commonly used to assess cognition in BD (Table 1). What emerges is that there are no tools more appropriate than others per se, as the suitability and clinical applicability of these instruments may depend on multiple factors. Among others, the target population (e.g. young vs elderly patients; people able vs not able to operate a computer); the purpose of the evaluation (e.g. cognitive screening vs exhaustive diagnostic evaluation; single evaluation vs monitoring over time); the characteristics of the tool itself (e.g., self-report vs performance-based; paper-and-pencil vs computerized; free of charge vs on payment); (iv) the clinical setting (e.g., presence of qualified vs unqualified staff; time and space resources). Based on these factors, we propose a diagram that may help healthcare professionals to make the best use of the instruments described above. The diagram visually summarises both the characteristics of each tool and the cognitive assessment process. As regards the properties of the tools, we used icons under each tool name (and listed in the caption) which refer to administration time, the need for the clinician, the psychometric property of the instrument, whether the tool is performance- or self-report-based and, finally, if it is on payment. As for the assessment process, the clinician is first asked to screen and/or monitor (“screening and/or monitoring” in the upper part of the schema) the patient's cognitive performance using one of four instruments (THINC-it, ICAT and COBRA and SCIP) based on the need for a computer (i.e., PC yes/no). If deficits are found at this point, the healthcare professional can proceed to a II-level assessment, choosing between BACA and MCCB. Otherwise, a stop icon warns the clinician to interrupt the evaluation. We acknowledge that this diagram is a preliminary proposal deriving from our clinical and research experience with BD patients. Thus, it would need to be further studied and possibly endorsed by other research groups.
Table 1.
Characteristics, strengths and limitations of tools commonly used for cognitive assessment in BD
Tool | Characteristics | Strengths | Limitations |
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COBRA | The COBRA is a 16-item self-report instrument that allows measuring subjective cognitive difficulties including executive function, processing speed, working memory, verbal learning and memory, attention and concentration and mental tracking. All items are rated using a 4-point scale: 0 = never, 1 = sometimes, 2 = often and 3 = always. The total score is obtained by adding up the scores of every item. The higher the score, the higher the subjective complaints. Available at: https://www.isbd.org/Cognitive-Assessments |
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SCIP | The SCIP is a brief, easy-to-administer objective screening tool requiring only a pencil and a test sheet, with an administration time of approximately 15 min. It was designed to detect cognitive deficits in psychiatric populations using t verbal learning tests (immediate and delayed), a working memory test, a Verbal Fluency Test, and a processing speed test. Exists in three alternative forms. Available at: https://www.isbd.org/SCIP-registration |
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THINC-it | Web-based screening tool originally developed to assess cognition in MDD. It measures both subjective and objective cognition by employing four objective tests (attention & executive functions, working memory and processing speed) and one self-report questionnaire (PDQ-5-D) measuring attention and concentration, prospective memory, retrospective memory, planning, and organisation. Available at: https://progress.im/en/content/download-thinc-it%C2%AE-tool |
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ICAT | Web-based cognitive test adapted from SCIP. It includes five subtests that evaluate 4 cognitive domains: verbal learning, working memory, delayed verbal learning and psychomotor speed. Available at: https://icat.cachet.dk/ |
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MCCB | Originally developed to assess cognition in SCZ. It evaluates seven cognitive domains: processing speed, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem-solving, and social cognition. Available at: https://www.matricsinc.org/how-to-order/ |
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BACA | The BAC-A is designed to assess cognitive functions in Affective Disorders. The battery lasts approximately 45 min and comprises eight tasks evaluating visuomotor abilities, working memory, learning and declarative memory, attention, verbal fluency, problem-solving, affective interference and affective inhibition. Available at: https://verasci.com/what-we-do/endpoints-assessments/bac/ |
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BACA, Brief Assessment of Cognition in Affective Disorder; BD, Bipolar Disorder; COBRA, Cognitive Complaints in Bipolar Disorder Rating Assessment; ICAT, Internet Based Cognitive Assessment Tool; MCCB, MATRICS Consensus Cognitive Battery; PDQ-5-D, Perceived Deficits Questionnaire for Depression; SCIP, Screen for Cognitive Impairment in Psychiatry; SCZ, Schizophrenia; THINC-it, THINC-integrated tool.
Data
All data used to write this paper is in the reference list.
Acknowledgements
None.
Financial support
This study was partially supported by a grant from the Italian Ministry of Health (GR-2016-02361283 to CP).
Conflicts of interest
None.
References
- Arts B, Jabben N, Krabbendam L and Van Os J (2008) Meta-analyses of cognitive functioning in euthymic bipolar patients and their first-degree relatives. Psychological Medicine 38, 771–785. [DOI] [PubMed] [Google Scholar]
- Bakkour N, Samp J, Akhras K, El Hammi E, Soussi I, Zahra F, Duru G, Kooli A and Toumi M (2014) Systematic review of appropriate cognitive assessment instruments used in clinical trials of schizophrenia, major depressive disorder and bipolar disorder. Psychiatry Research 216, 291–302. [DOI] [PubMed] [Google Scholar]
- Barbosa IG, Ferreira RA, Rocha NP, Mol GC, da Mata Chiaccjio Leite F, Bauer IE and Teixeira AL (2018) Predictors of cognitive performance in bipolar disorder: the role of educational degree and inflammatory markers. Journal of Psychiatric Research 106, 31–37. [DOI] [PubMed] [Google Scholar]
- Bauer IE, Keefe RS, Sanches M, Suchting R, Green CE and Soares JC (2015) Evaluation of cognitive function in bipolar disorder using the brief assessment of cognition in affective disorders (BAC-A). Journal of Psychiatric Research 60, 81–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Baune BT, Li X and Beblo T (2013) Short-and long-term relationships between neurocognitive performance and general function in bipolar disorder. Journal of Clinical and Experimental Neuropsychology 35, 759–774. [DOI] [PubMed] [Google Scholar]
- Bora E and Pantelis C (2015) Meta-analysis of cognitive impairment in first-episode bipolar disorder: comparison with first-episode schizophrenia and healthy controls. Schizophrenia Bulletin 41, 1095–1104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bora E, Yücel M and Pantelis C (2010a) Cognitive impairment in affective psychoses: a meta-analysis. Schizophrenia Bulletin 36, 112–125. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bora E, Yücel M and Pantelis C (2010b) Neurocognitive markers of psychosis in bipolar disorder: a meta-analytic study. Journal of Affective Disorders 127, 1–9. [DOI] [PubMed] [Google Scholar]
- Cuesta MJ, Pino O, Guilera G, Rojo JE, Gómez-Benito J, Purdon SE, Franco M, Martínez-Arán A, Segarra N and Tabarés-Seisdedos R (2011) 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 (SCIP). Schizophrenia Research 130, 137–142. [DOI] [PubMed] [Google Scholar]
- Guilera G, Pino O, Gómez-Benito J, Rojo JE, Vieta E, Tabarés-Seisdedos R, Segarra N, Martínez-Arán A, Franco M and Cuesta MJ (2009) Clinical usefulness of the screen for cognitive impairment in psychiatry (SCIP-S) scale in patients with type I bipolar disorder. Health and Quality of Life Outcomes 7, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hafiz P, Miskowiak KW, Kessing LV, Jespersen AE, Obenhausen K, Gulyas L, Żukowska K and Bardram JE (2019) The internet-based cognitive assessment tool: system design and feasibility study. JMIR Formative Research 3, e13898. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jensen JH, Støttrup MM, Nayberg E, Knorr U, Ullum H, Purdon SE, Kessing LV and Miskowiak KW (2015) Optimising screening for cognitive dysfunction in bipolar disorder: validation and evaluation of objective and subjective tools. Journal of Affective Disorders 187, 10–19. [DOI] [PubMed] [Google Scholar]
- Keefe RS, Fox KH, Davis VG, Kennel C, Walker TM, Burdick KE and Harvey PD (2014) The brief assessment of cognition In affective disorders (BAC-A): performance of patients with bipolar depression and healthy controls. Journal of Affective Disorders 166, 86–92. [DOI] [PubMed] [Google Scholar]
- Kurtz MM and Gerraty RT (2009) A meta-analytic investigation of neurocognitive deficits in bipolar illness: profile and effects of clinical state. Neuropsychology 23, 551. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lee C-Y, Wang L-J, Lee Y, Hung C-F, Huang Y-C, Lee M-I and Lee S-Y (2018) Differentiating bipolar disorders from unipolar depression by applying the brief assessment of cognition in affective disorders. Psychological Medicine 48, 929–938. [DOI] [PubMed] [Google Scholar]
- McIntyre RS, Best MW, Bowie CR, Carmona NE, Cha DS, Lee Y, Subramaniapillai M, Mansur RB, Barry H and Baune BT (2017) The THINC-integrated tool (THINC-it) screening assessment for cognitive dysfunction: validation in patients with major depressive disorder. The Journal of Clinical Psychiatry 78, 20938. [DOI] [PubMed] [Google Scholar]
- Miskowiak KW, Burdick K, Martinez-Aran A, Bonnin C, Bowie C, Carvalho A, Gallagher P, Lafer B, López-Jaramillo C and Sumiyoshi T (2018) Assessing and addressing cognitive impairment in bipolar disorder: the international society for bipolar disorders targeting cognition task force recommendations for clinicians. Bipolar Disorders 20, 184–194. [DOI] [PubMed] [Google Scholar]
- Miskowiak K, Jespersen A, Obenhausen K, Hafiz P, Hestbæk E, Gulyas L, Kessing L and Bardram J (2021) Internet-based cognitive assessment tool: sensitivity and validity of a new online cognition screening tool for patients with bipolar disorder. Journal of Affective Disorders 289, 125–134. [DOI] [PubMed] [Google Scholar]
- Nuechterlein KH, Green MF, Kern RS, Baade LE, Barch DM, Cohen JD, Essock S, Fenton WS, Frese PD III, Frederick J and Gold JM. (2008) The MATRICS consensus cognitive battery, part 1: test selection, reliability, and validity. American Journal of Psychiatry 165, 203–213. [DOI] [PubMed] [Google Scholar]
- Purdon SE and Psych R (2005) The Screen for Cognitive Impairment in Psychiatry. Administration and Psychometric Properties. Edmonton, Alberta, Canada: PNL. [Google Scholar]
- Robinson LJ, Thompson JM, Gallagher P, Goswami U, Young AH, Ferrier IN and Moore PB (2006) A meta-analysis of cognitive deficits in euthymic patients with bipolar disorder. Journal of Affective Disorders 93, 105–115. [DOI] [PubMed] [Google Scholar]
- Rojo E, Pino O, Guilera G, Gómez-Benito J, Purdon SE, Crespo-Facorro B, Cuesta MJ, Franco M, Martínez-Arán A and Segarra N (2010) Neurocognitive diagnosis and cut-off scores of the screen for cognitive impairment in psychiatry (SCIP-S). Schizophrenia Research 116, 243–251. [DOI] [PubMed] [Google Scholar]
- Rossetti MG, Perlini C, Abbiati V, Bonivento C, Caletti E, Fanelli G, Lanfredi M, Lazzaretti M, Pedrini L, Piccin S, Porcelli S, Sala M, Serretti A, Bellani M and Brambilla P (2022) The Italian version of the brief assessment of cognition in affective disorders: performance of patients with bipolar disorder and healthy controls. Comprehensive Psychiatry 117, 152335. [DOI] [PubMed] [Google Scholar]
- Schmid P, Czekaj A, Frick J, Steinert T, Purdon SE and Uhlmann C (2021) The screen for cognitive impairment in psychiatry (SCIP) as a routinely applied screening tool: pathology of acute psychiatric inpatients and cluster analysis. BMC Psychiatry 21, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Van Rheenen TE and Rossell SL (2014) An empirical evaluation of the MATRICS consensus cognitive battery in bipolar disorder. Bipolar Disorders 16, 318–325. [DOI] [PubMed] [Google Scholar]
- Yatham LN, Torres IJ, Malhi GS, Frangou S, Glahn DC, Bearden CE, Burdick KE, Martínez-Arán A, Dittmann S and Goldberg JF (2010) The international society for bipolar disorders–battery for assessment of neurocognition (ISBD-BANC). Bipolar Disorders 12, 351–363. [DOI] [PubMed] [Google Scholar]
- Zhang W, Zhu N, Lai J, Liu J, Ng CH, Chen J, Qian C, Du Y, Hu C and Chen J (2020) Reliability and validity of THINC-it in evaluating cognitive function of patients with bipolar depression. Neuropsychiatric Disease and Treatment 16, 2419. [DOI] [PMC free article] [PubMed] [Google Scholar]