Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry
Abstract Backgrounds Digital, online assessments are efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subject...
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BMC
2025-01-01
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| Series: | Alzheimer’s Research & Therapy |
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| Online Access: | https://doi.org/10.1186/s13195-024-01641-2 |
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| author | Jae Myeong Kang Manchumad Manjavong Chengshi Jin Adam Diaz Miriam T. Ashford Joseph Eichenbaum Emily Thorp Elizabeth Wragg Kenton H. Zavitz Francesca Cormack Anna Aaronson R. Scott Mackin Rachana Tank Bernard Landavazo Erika Cavallone Diana Truran Sarah Tomaszewski Farias Michael W. Weiner Rachel L. Nosheny |
| author_facet | Jae Myeong Kang Manchumad Manjavong Chengshi Jin Adam Diaz Miriam T. Ashford Joseph Eichenbaum Emily Thorp Elizabeth Wragg Kenton H. Zavitz Francesca Cormack Anna Aaronson R. Scott Mackin Rachana Tank Bernard Landavazo Erika Cavallone Diana Truran Sarah Tomaszewski Farias Michael W. Weiner Rachel L. Nosheny |
| author_sort | Jae Myeong Kang |
| collection | DOAJ |
| description | Abstract Backgrounds Digital, online assessments are efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subjective change measure, predicts longitudinal change in cognition in the Brain Health Registry (BHR), an online registry for neuroscience research. Methods This study included BHR participants aged 55 + who completed both the baseline ECog and repeated administrations of the CANTAB® Paired Associates Learning (PAL) visual learning and memory test. Both self-reported ECog (Self-ECog) and study partner-reported ECog (SP-ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We estimated associations between multiple ECog scoring outputs (ECog positive [same or above cut-off score], ECog consistent [report of consistent decline in any item], and total score) and longitudinal change in PAL. Additionally we assessed the ability of ECog to identify ‘decliners’, who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below. Results Participants (n = 16,683) had an average age of 69.07 ± 7.34, 72.04% were female, and had an average of 16.66 ± 2.26 years of education. They were followed for an average of 2.52 ± 1.63 visits over a period of 11.49 ± 11.53 months. Both Self-ECog positive (estimate = -0.01, p < 0.001, R²m = 0.56) and Self-ECog consistent (estimate=-0.01, p = 0.002, R²m = 0.56) were associated with longitudinal change in PAL FAMS after adjusting demographics and clinical confounders. Those who were Self-ECog total (Odds ratio [95% confidence interval] = 1.390 [1.121–1.708]) and SP-ECog consistent (2.417 [1.591–3.655]) had higher probability of being decliners based on PAL FAMS. Conclusion In the BHR’s unsupervised online setting, baseline subjective change was feasible in predicting longitudinal decline in neuropsychological tests. Online, self-administered measures of subjective cognitive change might have a potential to predict objective subjective change and identify individuals with cognitive impairments. |
| format | Article |
| id | doaj-art-20946890cc0e4c0392e6ceb793f2cdb3 |
| institution | Kabale University |
| issn | 1758-9193 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Alzheimer’s Research & Therapy |
| spelling | doaj-art-20946890cc0e4c0392e6ceb793f2cdb32025-01-12T12:10:55ZengBMCAlzheimer’s Research & Therapy1758-91932025-01-0117111210.1186/s13195-024-01641-2Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health RegistryJae Myeong Kang0Manchumad Manjavong1Chengshi Jin2Adam Diaz3Miriam T. Ashford4Joseph Eichenbaum5Emily Thorp6Elizabeth Wragg7Kenton H. Zavitz8Francesca Cormack9Anna Aaronson10R. Scott Mackin11Rachana Tank12Bernard Landavazo13Erika Cavallone14Diana Truran15Sarah Tomaszewski Farias16Michael W. Weiner17Rachel L. Nosheny18Department of Psychiatry and Behavioral Sciences, University of California San FranciscoDepartment of Psychiatry and Behavioral Sciences, University of California San FranciscoDepartment of Epidemiology and Biostatistics, University of California San FranciscoVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterCambridge CognitionCambridge CognitionCambridge CognitionCambridge CognitionVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterDepartment of Psychiatry and Behavioral Sciences, University of California San FranciscoDementia Research Centre, UCL Institute of Neurology, University College LondonVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterDepartments of Neurology, University of California DavisVA Advanced Imaging Research Center, San Francisco Veteran’s Administration Medical CenterDepartment of Psychiatry and Behavioral Sciences, University of California San FranciscoAbstract Backgrounds Digital, online assessments are efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subjective change measure, predicts longitudinal change in cognition in the Brain Health Registry (BHR), an online registry for neuroscience research. Methods This study included BHR participants aged 55 + who completed both the baseline ECog and repeated administrations of the CANTAB® Paired Associates Learning (PAL) visual learning and memory test. Both self-reported ECog (Self-ECog) and study partner-reported ECog (SP-ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We estimated associations between multiple ECog scoring outputs (ECog positive [same or above cut-off score], ECog consistent [report of consistent decline in any item], and total score) and longitudinal change in PAL. Additionally we assessed the ability of ECog to identify ‘decliners’, who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below. Results Participants (n = 16,683) had an average age of 69.07 ± 7.34, 72.04% were female, and had an average of 16.66 ± 2.26 years of education. They were followed for an average of 2.52 ± 1.63 visits over a period of 11.49 ± 11.53 months. Both Self-ECog positive (estimate = -0.01, p < 0.001, R²m = 0.56) and Self-ECog consistent (estimate=-0.01, p = 0.002, R²m = 0.56) were associated with longitudinal change in PAL FAMS after adjusting demographics and clinical confounders. Those who were Self-ECog total (Odds ratio [95% confidence interval] = 1.390 [1.121–1.708]) and SP-ECog consistent (2.417 [1.591–3.655]) had higher probability of being decliners based on PAL FAMS. Conclusion In the BHR’s unsupervised online setting, baseline subjective change was feasible in predicting longitudinal decline in neuropsychological tests. Online, self-administered measures of subjective cognitive change might have a potential to predict objective subjective change and identify individuals with cognitive impairments.https://doi.org/10.1186/s13195-024-01641-2Subjective cognitive declineEveryday cognition scalePaired associates learningBrain health registryDigital cognitive assessment |
| spellingShingle | Jae Myeong Kang Manchumad Manjavong Chengshi Jin Adam Diaz Miriam T. Ashford Joseph Eichenbaum Emily Thorp Elizabeth Wragg Kenton H. Zavitz Francesca Cormack Anna Aaronson R. Scott Mackin Rachana Tank Bernard Landavazo Erika Cavallone Diana Truran Sarah Tomaszewski Farias Michael W. Weiner Rachel L. Nosheny Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry Alzheimer’s Research & Therapy Subjective cognitive decline Everyday cognition scale Paired associates learning Brain health registry Digital cognitive assessment |
| title | Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry |
| title_full | Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry |
| title_fullStr | Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry |
| title_full_unstemmed | Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry |
| title_short | Subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the Brain Health Registry |
| title_sort | subjective cognitive decline predicts longitudinal neuropsychological test performance in an unsupervised online setting in the brain health registry |
| topic | Subjective cognitive decline Everyday cognition scale Paired associates learning Brain health registry Digital cognitive assessment |
| url | https://doi.org/10.1186/s13195-024-01641-2 |
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