scholarly journals A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)

2020 ◽  
Author(s):  
Seyed-Mahdi Khaligh-Razavi ◽  
Maryam Sadeghi ◽  
Mahdiyeh Khanbagi ◽  
Chris Kalafatis ◽  
Seyed Massood Nabavi
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Dysfunction ◽  
Cognitive Assessment ◽  
Cognitive Rehabilitation ◽  
Convergent Validity ◽  
Strong Association ◽  
Therapeutic Interventions ◽  
Neurofilament Light ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Background Cognitive impairment is common in patients with MS. Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity. Methods We developed a 5-minute computerized test to measure cognitive dysfunction in patients with MS. The proposed test – named the Integrated Cognitive Assessment (ICA) – is self-administered and language-independent. 91 MS patients and 83 healthy controls (HC) took part in Substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA’s test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In Substudy 2, we recruited 48 MS patients, 38 of which had received an 8-week physical and cognitive rehabilitation programme and 10 MS patients who did not. We examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores and SDMT scores pre- and post-rehabilitation. Results The ICA demonstrated excellent test-retest reliability (r=0.94), with no learning bias, and showed a high level of convergent validity with BICAMS. The ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r=-0.79) between ICA score and the level of NfL in MS patients before and after rehabilitation. Conclusions The ICA has the potential to be used as a digital marker of cognitive impairment and to monitor response to therapeutic interventions. In comparison to standard cognitive tools for MS, the ICA is shorter in duration, does not show a learning bias, and is independent of language.

scholarly journals A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)

2020 ◽  
Author(s):  
Seyed-Mahdi Khaligh-Razavi ◽  
Maryam Sadeghi ◽  
Mahdiyeh Khanbagi ◽  
Chris Kalafatis ◽  
Seyed Massood Nabavi
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Cognitive Dysfunction ◽  
Cognitive Assessment ◽  
Cognitive Rehabilitation ◽  
Convergent Validity ◽  
Strong Association ◽  
Therapeutic Interventions ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Background Cognitive impairment is common in patients with multiple sclerosis (MS). Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity. Methods We developed a 5-minute computerized test to measure cognitive dysfunction in patients with MS. The proposed test – named the Integrated Cognitive Assessment (ICA) – is self-administered and language-independent. 91 MS patients and 83 healthy controls (HC) took part in Substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA’s test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In Substudy 2, we recruited 48 MS patients, 38 of which had received an 8-week physical and cognitive rehabilitation programme and 10 MS patients who did not. We examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores and Symbol Digit Modalities Test (SDMT) scores pre- and post-rehabilitation. Results The ICA demonstrated excellent test-retest reliability (r=0.94), with no learning bias, and showed a high level of convergent validity with BICAMS. The ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r=-0.79) between ICA score and the level of NfL in MS patients before and after rehabilitation. Conclusions The ICA has the potential to be used as a digital marker of cognitive impairment and to monitor response to therapeutic interventions. In comparison to standard cognitive tools for MS, the ICA is shorter in duration, does not show a learning bias, and is independent of language.

scholarly journals A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)

2020 ◽  
Author(s):  
Seyed-Mahdi Khaligh-Razavi ◽  
Maryam Sadeghi ◽  
Mahdiyeh Khanbagi ◽  
Chris Kalafatis ◽  
Seyed Massood Nabavi
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Cognitive Dysfunction ◽  
Cognitive Assessment ◽  
Cognitive Rehabilitation ◽  
Convergent Validity ◽  
Strong Association ◽  
Therapeutic Interventions ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Background Cognitive impairment is common in patients with multiple sclerosis (MS). Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity. Methods We developed a 5-minute computerized test to measure cognitive dysfunction in patients with MS. The proposed test – named the Integrated Cognitive Assessment (ICA) – is self-administered and language-independent. 91 MS patients and 83 healthy controls (HC) took part in Substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA’s test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In Substudy 2, we recruited 48 MS patients, 38 of which had received an 8-week physical and cognitive rehabilitation programme and 10 MS patients who did not. We examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores and Symbol Digit Modalities Test (SDMT) scores pre- and post-rehabilitation. Results The ICA demonstrated excellent test-retest reliability (r=0.94), with no learning bias, and showed a high level of convergent validity with BICAMS. The ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r=-0.79) between ICA score and the level of NfL in MS patients before and after rehabilitation. Conclusions The ICA has the potential to be used as a digital marker of cognitive impairment and to monitor response to therapeutic interventions. In comparison to standard cognitive tools for MS, the ICA is shorter in duration, does not show a learning bias, and is independent of language.

scholarly journals A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)

2019 ◽  
Author(s):  
Seyed-Mahdi Khaligh-Razavi ◽  
Maryam Sadeghi ◽  
Mahdiyeh Khanbagi ◽  
Chris Kalafatis ◽  
Seyed Massood Nabavi
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Performance ◽  
Cognitive Dysfunction ◽  
Cognitive Assessment ◽  
Convergent Validity ◽  
Strong Association ◽  
Cognitive Status ◽  
Research Database ◽  
Retest Reliability ◽  
Test Retest Reliability

AbstractBackgroundCognitive impairment is common in patients with MS. Accurate and repeatable measures of cognition have the potential to be used as a marker of disease activity. We developed a 5-minute computerized test to measure cognitive dysfunction in patients with MS. The proposed test –named Integrated Cognitive Assessment (ICA)– is self-administered and language-independent.ObjectiveTo determine ICA’s validity as a digital biomarker for assessing cognitive performance in MS.Methods91 MS patients and 83 healthy controls (HC) took part in substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA’s test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In substudy 2, we recruited 48 MS patients, and examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores.ResultsICA demonstrated excellent test-retest reliability (r=0.94), with no learning bias (i.e. no significant practice effect); and had high level of convergent validity with BICAMS. ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated a high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r=-0.79) between ICA score and the level of NfL in MS patients.ConclusionsICA can be used as a digital biomarker for assessment and monitoring of cognitive performance in MS patients. In comparison to standard cognitive tools for MS (e.g. BICAMS), ICA is shorter in duration, does not show a learning bias, is independent of language, and takes advantage of artificial intelligence (AI) to identify cognitive status of patients more accurately. Being a digital test, it further has the potential for easier electronic health record or research database integration.

scholarly journals A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)

2019 ◽  
Author(s):  
Seyed-Mahdi Khaligh-Razavi ◽  
Maryam Sadeghi ◽  
Mahdiyeh Khanbagi ◽  
Chris Kalafatis ◽  
Seyed Massood Nabavi
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Dysfunction ◽  
Cognitive Assessment ◽  
Convergent Validity ◽  
Strong Association ◽  
Cognitive Status ◽  
Database Integration ◽  
Research Database ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Background Cognitive impairment is common in patients with MS. Accurate and repeatable measures of cognition have the potential to be used as a marker of disease activity. Methods We developed a 5-minute computerized test to measure cognitive dysfunction in patients with MS. The proposed test –named Integrated Cognitive Assessment (ICA)– is self-administered and language-independent. 91 MS patients and 83 healthy controls (HC) took part in substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA’s test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In substudy 2, we recruited 48 MS patients, and examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores. Results ICA demonstrated excellent test-retest reliability (r=0.94), with no learning bias (i.e. no significant practice effect); and had high level of convergent validity with BICAMS. ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated a high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r=-0.79) between ICA score and the level of NfL in MS patients. Conclusions ICA has the potential to be used as a digital biomarker for assessment and monitoring of cognitive performance in MS patients. In comparison to standard cognitive tools for MS (e.g. BICAMS), ICA is shorter in duration, does not show a learning bias, is independent of language, and takes advantage of artificial intelligence (AI) to identify cognitive status of patients more accurately. Being a digital test, it further has the potential for easier electronic health record or research database integration.

scholarly journals A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS)

2019 ◽  
Author(s):  
Seyed-Mahdi Khaligh-Razavi ◽  
Maryam Sadeghi ◽  
Mahdiyeh Khanbagi ◽  
Chris Kalafatis ◽  
Seyed Massood Nabavi
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Dysfunction ◽  
Cognitive Assessment ◽  
Convergent Validity ◽  
Strong Association ◽  
Cognitive Status ◽  
Database Integration ◽  
Research Database ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Background Cognitive impairment is common in patients with MS. Accurate and repeatable measures of cognition have the potential to be used as a marker of disease activity. Methods We developed a 5-minute computerized test to measure cognitive dysfunction in patients with MS. The proposed test –named Integrated Cognitive Assessment (ICA)– is self-administered and language-independent. 91 MS patients and 83 healthy controls (HC) took part in substudy 1, in which each participant took the ICA test and the Brief International Cognitive Assessment for MS (BICAMS). We assessed ICA’s test-retest reliability, its correlation with BICAMS, its sensitivity to discriminate patients with MS from the HC group, and its accuracy in detecting cognitive dysfunction. In substudy 2, we recruited 48 MS patients, and examined the association between the level of serum neurofilament light (NfL) in these patients and their ICA scores. Results ICA demonstrated excellent test-retest reliability (r=0.94), with no learning bias (i.e. no significant practice effect); and had high level of convergent validity with BICAMS. ICA was sensitive in discriminating the MS patients from the HC group, and demonstrated a high accuracy (AUC = 95%) in discriminating cognitively normal from cognitively impaired participants. Additionally, we found a strong association (r=-0.79) between ICA score and the level of NfL in MS patients. Conclusions ICA has the potential to be used as a digital biomarker for assessment and monitoring of cognitive performance in MS patients. In comparison to standard cognitive tools for MS (e.g. BICAMS), ICA is shorter in duration, does not show a learning bias, is independent of language, and takes advantage of artificial intelligence (AI) to identify cognitive status of patients more accurately. Being a digital test, it further has the potential for easier electronic health record or research database integration.

Validity and reliability of the Mandarin version of the Treatment Burden Questionnaire among stroke patients in Mainland China

2021 ◽  
Author(s):  
Qi Zhang ◽  
Ke Zhang ◽  
Miao Li ◽  
Jiaxin Gu ◽  
Xintong Li ◽  
...  
Keyword(s):  
Internal Consistency ◽  
Convergent Validity ◽  
Intraclass Correlation ◽  
Reliability And Validity ◽  
Therapeutic Interventions ◽  
Treatment Burden ◽  
Validity And Reliability ◽  
Stroke Patients ◽  
Retest Reliability ◽  
Test Retest Reliability

Abstract Objectives To examine the validity and reliability of the Mandarin version of the Treatment Burden Questionnaire (TBQ) among stroke patients. Background Stroke patients need long-term management of symptoms and life situation, and treatment burden has recently emerged as a new concept that can influence the health outcomes during the rehabilitation process. Methods The convenience sampling method was used to recruit 187 cases of stroke patients in a tertiary grade hospital in Tianjin for a formal investigation. Item analysis, reliability and validity tests were carried out. The reliability test included internal consistency and test–retest reliability. And as well as content, structure and convergent validity were performed for the validity test. Results Of the 187 completed questionnaires, only 180 (96.3%) were suitable for analysis. According to the experts’ evaluation, the I-CVI of each item was from 0.833 to 1.000, and the S-CVI was 0.967. The exploratory factor analysis yielded three-factor components with a cumulative variation of 53.054%. Convergent validity was demonstrated using measures of Morisky’s Medication Adherence Scale 8 (r = –0.450, P < 0.01). All correlations between items and global scores ranged from 0.403 to 0.638. Internal consistency reliability and test–retest reliability were found to be acceptable, as indicated by a Cronbach’s α of 0.824 and an intraclass correlation coefficient of 0.846, respectively. Conclusions The Mandarin TBQ had acceptable validity and reliability. The use of TBQ in the assessment of treatment burden of stroke survivor may benefit health resources allocation and provide tailor therapeutic interventions to construct minimally disruptive care.

scholarly journals Validity and Reliability of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) in Indonesia and the Correlation with Quality of Life

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Riwanti Estiasari ◽  
Yuhyi Fajrina ◽  
Diatri Nari Lastri ◽  
Syarli Melani ◽  
Kartika Maharani ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Cognitive Function ◽  
Cognitive Assessment ◽  
Verbal Learning ◽  
Retest Reliability ◽  
Cognitive Evaluation ◽  
Test Retest Reliability

Introduction. Multiple Sclerosis (MS) can affect cognitive function that might interfere with quality of life. Processing speed and memory are the most common area of cognitive impairment. Cognitive evaluation in daily practice is often difficult to be performed since it needs neuropsychological expert and is time-consuming. Brief International Cognitive Assessment for MS (BICAMS) is valid and practical for cognitive evaluation. This study aims to validate BICAMS in Indonesian MS patients and healthy controls (HC) and to analyse the effect of cognitive impairment on quality of life. Methods. BICAMS, which composes Symbol Digits Modalities Test (SDMT), California Verbal Learning Test-Second Edition (CVLT-II), and Brief Visuospatial Memory Test-Revised (BVMT-R), was translated and cross-culturally adapted to Indonesian from the original BICAMS and then administered to 40 Indonesian MS patients and 66 HC matched by sex, age, and education. Test-retest reliability was performed on 16-MS patients and 42 HC. Quality of life was measured using Multiple Sclerosis Quality of Life (MSQOL-54) instrument. Results. The SDMT, CVLT-II, and BVMT-R score in MS patients were significantly lower than those in HC (effect size, r: 0.61, 0.36, and 0.47, respectively). Test-retest reliability for all tests was satisfactory with correlation coefficient for SDMT, CVLT-II, and BVMT-R in MS subjects 0.86, 0.81, and 0.83, respectively. Using 5th percentile of HC score as cut-off, 15% MS subjects had impairment in one test, 27.5% in two tests, and 40% in three tests. BICAMS was moderately correlated with EDSS but was not correlated with disease duration and relapse rate. SDMT score correlated with physical function and physical and mental role limitation. Conclusion. BICAMS is valid and reliable for assessing cognitive function of Indonesia MS patients.

scholarly journals HIV-Dementia Scale as a screening tool for the detection of subcortical cognitive deficits: validation of the Italian version

2021 ◽  
Author(s):  
C. Montanucci ◽  
E. Chipi ◽  
N. Salvadori ◽  
R. Rinaldi ◽  
P. Eusebi ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Deficits ◽  
Convergent Validity ◽  
Screening Tool ◽  
Neurological Diseases ◽  
Hiv Dementia ◽  
Italian Version ◽  
Retest Reliability ◽  
Test Retest Reliability ◽  
State Examination

AbstractMini-Mental State Examination (MMSE) lacks of sensitivity in detecting cognitive deficits associated with subcortical damage. The HIV-Dementia Scale (HDS), a screening tool originally created for detecting cognitive impairment due to subcortical damage in HIV + patients, has proved to be useful in other neurological diseases. Until now, an Italian version of the HDS is not available. We aimed at: (1) validating the HDS Italian version (HDS-IT) in a cohort of cognitively healthy subjects (CN); (2) exploring the suitability of HDS-IT in detecting cognitive impairment due to subcortical damage (scCI). The psychometric properties of the HDS-IT were assessed in 180 CN (mean age 67.6 ± 8.3, range 41–84) with regard to item-total correlation, test–retest reliability and convergent validity with MMSE. Item-total correlations ranged 0.44–0.72. Test–retest reliability was 0.70 (p < 0.001). The HDS-IT scores were positively associated with MMSE score (rS = 0.49, p < 0.001). Then, both the HDS-IT and the MMSE were administered to 44 scCI subjects (mean age 64.9 ± 10.6, range 41–84). Mean HDS-IT total score was close to the original version and significantly lower in the scCI group compared to CN (8.6 ± 3.6 vs. 12.6 ± 2.5, p < 0.001). ROC analysis yielded an optimal cutoff value of 11, with sensitivity of 0.70 and specificity of 0.82. Patients showed poorer scores on HDS-IT compared to CN (12.6 ± 2.5 vs. 8.6 ± 3.6, p < 0.001). Our results support the use of HDS-IT as a screening tool suitable for detecting cognitive deficits with prevalent subcortical pattern, being complementary to MMSE in clinical practice.

scholarly journals Psychometric Validation of a Novel PRO MEASURE for Assessing Patient-reported Experience of Cognitive Impairment in Schizophrenia (PRECIS)

2020 ◽  
Author(s):  
Raymond C. Rosen ◽  
Jeremiah J. Trudeau ◽  
Steven Silverstein ◽  
David C. Henderson ◽  
Adam Smith ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Convergent Validity ◽  
Discriminant Validity ◽  
Psychometric Validation ◽  
Controlled Study ◽  
Initial Development ◽  
Retest Reliability ◽  
Control Subjects ◽  
Patient Reported ◽  
Test Retest Reliability

Abstract Background Cognitive impairment associated with schizophrenia (CIAS) can be a distressing feature that contributes to the burden of the disorder, as well as being a strong predictor of functional impairment. To fully assess the burden to patients living with this illness, there is a need to develop a specific measure of patient-reported outcomes . Methods Following initial development of the Patient-Reported Experience of Cognitive Impairment in Schizophrenia (PRECIS) instrument, the domain structure, reliability (inter-item consistency and test–retest reliability), and validity (discriminant validity, divergent, and convergent validity) of the tool were assessed in patients (aged 18–55 years) with CIAS participating in a 12-week, Phase II, randomized, double-blind, placebo-controlled study to evaluate the efficacy, safety, and tolerability of BI 409306. Healthy control subjects were recruited separately. The PRECIS instrument was completed at baseline, Week 6, Week 9, and Week 12. Results The questionnaire responses of 410 patients with schizophrenia and 88 control subjects were compared. Of the original 35 items included in the draft PRECIS instrument, 11 were eliminated due to poor performance against pre-defined criteria, resulting in a 24-item questionnaire that loaded well onto 5 domains (Attention, Memory, Executive Function, Communication, and Bother). The revised 24-item PRECIS instrument demonstrated adequate discriminant validity between patient and control groups in each of the 5 domains (p<0.0001), convergent validity as shown by a significant correlation between PRECIS scores and the Schizophrenia Cognition Rating Scale (p<0.0001), good internal consistency (Cronbach’s alpha score: 0.942), and adequate test–retest reliability (intra-class correlation coefficient [ICC]: 0.78). A simplified, user-friendly scoring method was identified, which assigned scores to each of the 5 domains using a five-category Likert scale. PRECIS did not correlate with MATRICS or CANTAB composite scores. Conclusions PRECIS is a novel self-completed sensitive instrument designed to measure the subjective experience of cognitive impairment in patients with schizophrenia. The test development process included patient input, perceptions, and feedback, and strong evidence for the validity and reliability of the instrument was demonstrated. The scale provides a patient-based perspective to complement existing objective measures of cognition and serves to define key patient-based endpoints for use in future clinical studies.

scholarly journals Psychometric Validation of a Novel PRO Measure for Assessing Patient-reported Experience of Cognitive Impairment in Schizophrenia (PRECIS)

2019 ◽  
Author(s):  
Raymond C. Rosen ◽  
Jeremiah J. Trudeau ◽  
Steven Silverstein ◽  
David C. Henderson ◽  
Adam Smith ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Convergent Validity ◽  
Discriminant Validity ◽  
Psychometric Validation ◽  
Controlled Study ◽  
Initial Development ◽  
Retest Reliability ◽  
Control Subjects ◽  
Patient Reported ◽  
Test Retest Reliability

Abstract Background Cognitive impairment associated with schizophrenia (CIAS) can be a distressing feature that contributes to the burden of the disorder, as well as being a strong predictor of functional impairment. To fully assess the burden to patients living with this illness, there is a need to develop a specific measure of patient-reported outcomes (PROs). Methods Following initial development of the Patient-Reported Experience of Cognitive Impairment in Schizophrenia (PRECIS) instrument, the domain structure, reliability (inter-item consistency and test-retest reliability), and validity (discriminant validity, divergent, and convergent validity) of the tool were assessed in patients (aged 18–55 years) with CIAS participating in a 12-week, Phase II, randomized, double-blind, placebo-controlled study to evaluate the efficacy, safety, and tolerability of BI 409306. Healthy control subjects were recruited separately. The PRECIS instrument was completed at baseline, Week 6, Week 9, and Week 12. Results The questionnaire responses of 410 patients with schizophrenia and 88 control subjects were compared. Of the original 35 items included in the draft PRECIS instrument, 11 were eliminated due to poor performance against pre-defined criteria, resulting in a 24-item questionnaire. In confirmatory factor analysis, the 24 items loaded well onto 5 domains (Attention, Memory, Executive Function, Communication, and Bother). The revised 24-item PRECIS instrument demonstrated adequate discriminant validity between patient and control groups in each of the 5 domains (p<0.0001), convergent validity as shown by a significant correlation between PRECIS scores and the Schizophrenia Cognition Rating Scale (SCoRS; p<0.0001), good internal consistency (Cronbach’s alpha score: 0.942), and adequate test-retest reliability (intra-class correlation coefficient [ICC]: 0.78). A simplified, user-friendly scoring method was identified, which assigned scores to each of the 5 domains using a 5-category Likert scale. Conclusions PRECIS is a novel self-completed sensitive instrument designed to measure the subjective experience of cognitive impairment in patients with schizophrenia. The test development process included patient input, perceptions, and feedback, and strong evidence for the validity and reliability of the instrument was demonstrated. The scale provides a patient-based perspective to complement existing objective measures of cognition and serves to define key patient-based endpoints for use in future clinical studies.

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