Ruben D Potthoff, Sanne B Schagen, Joost A Agelink van Rentergem
{"title":"Process models of verbal memory in cancer survivors: Bayesian process modeling approach to variation in test scores.","authors":"Ruben D Potthoff, Sanne B Schagen, Joost A Agelink van Rentergem","doi":"10.1080/13803395.2024.2313256","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Verbal memory is a complex and fundamental aspect of human cognition. However, traditional sum-score analyses of verbal learning tests oversimplify underlying verbal memory processes. We propose using process models to subdivide memory into multiple processes, which helps in localizing the most affected processes in impaired verbal memory. Additionally, the model can be used to address score and process variability. This study aims to investigate the effects of cancer and its treatment on verbal memory, as well as provide a demonstration of how process models can be used to investigate the uncertainty in neuropsychological test scores.</p><p><strong>Method: </strong>We present an investigation of memory process scores in non-CNS cancer survivors (<i>n</i> = 184) and no-cancer controls (<i>n</i> = 204). The participants completed the Amsterdam Cognition Scan (ACS), in which classical neuropsychological tests are digitally recreated for online at-home administration. We analyzed data from the ACS equivalent of a Verbal Learning Test using both traditional sum scores and a Bayesian process model.</p><p><strong>Results: </strong>Analysis of the sum score indicated that patients scored lower than controls on immediate recall but found no difference for delayed recall. The process model analysis indicated a small difference between patients and controls in immediate retrieval from both the partially learned and learned states, with no differences in learning or delayed retrieval processes. Individual-level analysis shows considerable uncertainty for sum scores. Sum scores were more certain than single trials. Retrieval parameters also showed less uncertainty than learning parameters.</p><p><strong>Conclusion: </strong>The Bayesian process model increased the informativity of Verbal Learning test data, by showing uncertainty of the traditional sum score measurements as well as how the underlying processes differed between populations. Additionally, the model grants insight into underlying memory processes for individuals and how these processes vary within and between them.</p>","PeriodicalId":15382,"journal":{"name":"Journal of clinical and experimental neuropsychology","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of clinical and experimental neuropsychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1080/13803395.2024.2313256","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/7 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Verbal memory is a complex and fundamental aspect of human cognition. However, traditional sum-score analyses of verbal learning tests oversimplify underlying verbal memory processes. We propose using process models to subdivide memory into multiple processes, which helps in localizing the most affected processes in impaired verbal memory. Additionally, the model can be used to address score and process variability. This study aims to investigate the effects of cancer and its treatment on verbal memory, as well as provide a demonstration of how process models can be used to investigate the uncertainty in neuropsychological test scores.
Method: We present an investigation of memory process scores in non-CNS cancer survivors (n = 184) and no-cancer controls (n = 204). The participants completed the Amsterdam Cognition Scan (ACS), in which classical neuropsychological tests are digitally recreated for online at-home administration. We analyzed data from the ACS equivalent of a Verbal Learning Test using both traditional sum scores and a Bayesian process model.
Results: Analysis of the sum score indicated that patients scored lower than controls on immediate recall but found no difference for delayed recall. The process model analysis indicated a small difference between patients and controls in immediate retrieval from both the partially learned and learned states, with no differences in learning or delayed retrieval processes. Individual-level analysis shows considerable uncertainty for sum scores. Sum scores were more certain than single trials. Retrieval parameters also showed less uncertainty than learning parameters.
Conclusion: The Bayesian process model increased the informativity of Verbal Learning test data, by showing uncertainty of the traditional sum score measurements as well as how the underlying processes differed between populations. Additionally, the model grants insight into underlying memory processes for individuals and how these processes vary within and between them.
期刊介绍:
Journal of Clinical and Experimental Neuropsychology ( JCEN) publishes research on the neuropsychological consequences of brain disease, disorders, and dysfunction, and aims to promote the integration of theories, methods, and research findings in clinical and experimental neuropsychology. The primary emphasis of JCEN is to publish original empirical research pertaining to brain-behavior relationships and neuropsychological manifestations of brain disease. Theoretical and methodological papers, critical reviews of content areas, and theoretically-relevant case studies are also welcome.