Clinical Neuropsychologist最新文献

{"title":"Reliability and stability of cognitive intraindividual variability indices among cognitively unimpaired older adults.","authors":"Sidonia E Compton, Troy A Webber, Steven Paul Woods, Andrew M Kiselica","doi":"10.1080/13854046.2025.2552279","DOIUrl":"10.1080/13854046.2025.2552279","url":null,"abstract":"<p><p><b>Objective:</b> Cognitive intraindividual variability (IIV) dispersion measures within-person variability in performance across a neuropsychological test battery and is prognostic of structural and functional decline. Although evidence for the construct validity of cognitive dispersion has grown considerably, its utility in applied settings relies on its stability and reliability. Thus, we examined mean-level stability, test-retest reliability, and reliable change of several cognitive dispersion indices among cognitively unimpaired older adults. <b>Method:</b> Participants were 2224 robustly cognitively unimpaired older adults from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set 3.0. Intraindividual standard deviation (<i>ISD</i>) and coefficient of variation (<i>CoV</i>) dispersion indices were calculated for raw, scaled, and demographically-adjusted normed scores for the neuropsychological test battery at baseline and initial follow-up visit (<i>M</i>_days = 424.99). Analyses included paired samples <i>t</i>-tests and generation of effect sizes for mean-level stability, correlations for test-retest reliability, and practice-adjusted reliable change indices (RCIs) for classifying individuals. <b>Results:</b> The mean-level change effect sizes for <i>ISD</i> and <i>CoV</i> scores were very small (<i>ds</i> < .06); only <i>CoV</i> showed significant improvements. Test-retest reliability was poor (<i>M_r =</i> .41) for cognitive dispersion indices compared to global composite scores (<i>r</i> = .82). RCIs suggested that normed score changes greater than 1.75 standard deviations were significant. <b>Conclusions:</b> Findings showed stable mean-level cognitive dispersion across 424.99 days; however, consistent with process-based neuropsychological test scores literature, test-retest reliability was poor, perhaps reflecting random measurement error among cognitively unimpaired individuals. Change in cognitive dispersion may inform clinical prognosis and serve as supplementary information within broader neuropsychological evaluations given reliability limitations.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"1978-1995"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13330730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining intra-individual variability of ecological momentary assessment with multilevel modeling: A systematic review and recommendations for research and practice.","authors":"Catherine Luna, Shenghai Dai, Carolyn Pagan, Chang Liu, Maureen Schmitter-Edgecombe","doi":"10.1080/13854046.2025.2592660","DOIUrl":"10.1080/13854046.2025.2592660","url":null,"abstract":"<p><p><b>Objective:</b> Ecological momentary assessment (EMA) is a popular method for analyzing intra-individual variability (IIV) of psychological constructs, including cognition. Multilevel modeling (MLM) is a widely used method for analyzing EMA data in intensive longitudinal designs. This systematic review examines how psychologists use and report MLM in EMA studies. It evaluates (1) adherence to the Checklist for Reporting EMA Studies (CREMAS) guidelines, (2) common factors reported in addition to the CREMAS guidelines, and (3) consistency in reporting MLM to analyze EMA data, aiming to improve research design and reporting consistency in the field. <b>Method:</b> Phase 1 searched research databases to explore the commonly used statistical analyses for EMA data. Subsequently, a systematic review was conducted of psychological research articles published between January 2021 and February 2023 which used MLM as the primary method to analyze EMA data. Phase 2 comprised an updated systematic review of articles published from November 2024 to April 2025 to examine whether reporting patterns improved across time. <b>Results:</b> Phase 1 confirmed MLM is the most often statistical procedure used to analyze EMA. 43 articles were reviewed and found (1) generally strong adherence to the CREMAS guidelines, (2) additional components commonly reported, and (3) varied reporting of MLM data preparation and analysis. Phase 2 reviewed 14 articles and found similar results as Phase 1. <b>Conclusions:</b> To further increase transparency and standardize reporting, we recommend several additions to the CREMAS guidelines and a set of Reporting MLM in EMA studies (REMMES) guidelines for future research.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"1926-1951"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145727320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intra-individual cognitive variability predicts the trajectory of longitudinal neurocognitive and functional decline.","authors":"Shayne S-H Lin, Mengya Xia, Rebecca S Allen","doi":"10.1080/13854046.2025.2541661","DOIUrl":"10.1080/13854046.2025.2541661","url":null,"abstract":"<p><p><b>Objective:</b> Intra-individual cognitive variability (IICV) has been found to predict cognitive decline and dementia incidence among older adults based on a one follow-up testing paradigm while the association between IICV and daily functioning is less studied. The current study intended to investigate the predictability of IICV on the trajectory of decline in cognition and self-report daily functioning among older adults, tracked with multiple time points. <b>Method:</b> The current study employed a diverse, longitudinal, archival data set from the Rush Alzheimer's Disease Center (<i>N</i> = 4,319) and examined 5 waves of data with growth curve modeling. Multiple sensitivity analyses were followed up to scrutinize the robustness of study results, accounting for demographic covariates, baseline mean cognitive performance, skewness, and attrition. <b>Results:</b> Results supported the main hypothesis that the trend of IICV predicted the trajectory of cognition, <i>β</i> = .-57, <i>p</i> = .002, and self-reported daily functioning, β = .48, <i>p</i> = .037, and the results were robust against the inclusion of covariates, skewness, and attrition. <b>Conclusions:</b> With a rigorous methodology and statistical approach, the current study contributed to the scientific and medical understanding of IICV and lent support to the clinical use of IICV in neuropsychological assessment. Methodological strengths and limitations were noted.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"2083-2102"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144876843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intraindividual variability on the NIH Toolbox Cognition Battery: Sociodemographic comparisons and test-retest reliability of dispersion in cognitive test scores.","authors":"Justin E Karr, Sheliza Ali","doi":"10.1080/13854046.2025.2510332","DOIUrl":"10.1080/13854046.2025.2510332","url":null,"abstract":"<p><p><b>Objective:</b> This study examined intraindividual variability for fluid cognition test scores on the NIH Toolbox Cognition Battery (NIHTB-CB) by (a) comparing dispersion across sociodemographic characteristics and (b) estimating test-retest reliability of dispersion scores. <b>Method:</b> Participants completed the NIHTB-CB as part of the norming study (<i>n</i> = 730; <i>M</i> = 47.4 ± 17.6 years-old; 64.4% women; 63.2% White), with a subsample completing retest within 1-2 wk (<i>n</i> = 138; <i>M</i> = 54.8 ± 20.0 years-old; 48.6% women; 68.1% White). Raw NIHTB-CB scores were converted to age-adjusted standard scores and demographic-adjusted T-scores. IIV was estimated <i>via</i> the intraindividual standard deviation (ISD) and intraindividual coefficient of variation (ICV) for the five fluid cognition tests. Participants were compared on the ISD and ICV based on age, gender, race/ethnicity, education, and crystallized composite score. Test-retest reliability was estimated using the intraclass correlation coefficient (ICC) with a 95% confidence interval. <b>Results:</b> Group comparisons indicated significant ICV differences based on race/ethnicity and crystallized composite for standard scores and significant ISD and ICV differences based on gender and crystallized composite for T-scores, but notably, all effect sizes were small in magnitude. The test-retest reliability of the ISD was poor for standard scores (ICC = 0.33 [0.01, 0.55]) and T-scores (ICC = 0.49 [0.23, 0.66]). The test-retest reliability of the ICV was poor for standard scores (ICC = 0.43 [0.16, 0.62]) and moderate for T-scores (ICC = 0.63 [0.43, 0.75]). <b>Conclusions:</b> The ISD and ICV did not substantially differ based on sociodemographic characteristics and both scores lacked stability over a brief test-retest interval, indicating a need for additional psychometric research on dispersion scores to inform research and practice.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"1996-2010"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12355382/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144163968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive functioning and intra-individual variability in essential tremor and Parkinson's disease: A comparative study.","authors":"Hannah L Combs, Samantha K Henry, Troy A Webber, Michele K York, Jonathan D Sober","doi":"10.1080/13854046.2025.2518240","DOIUrl":"10.1080/13854046.2025.2518240","url":null,"abstract":"<p><p><b>Objective</b>: Cognitive decline may be more prevalent in essential tremor (ET) than previously recognized. Dispersion-based intraindividual variability (IIV-D) is proposed as a marker of neurological integrity. While elevated IIV-D has been noted in Parkinson's disease (PD), it has not been explored in ET. This study investigated cognitive functioning and IIV-D in ET compared to PD and cognitively intact controls (IC). <b>Method</b>: Neuropsychological data from 188 PD, 53 ET, and 135 IC patients were reviewed. Group comparisons on neuropsychological tests were examined. IIV-D was calculated <i>via</i> the intraindividual standard deviation (iSD) and the coefficient of variance (CoV) across 13 neurocognitive scores. Secondary analyses examined IIV-D among PD, ET, and IC with \"No Cognitive Disorder\" (NCD). <b>Results</b>: PD and ET performed worse than IC on oral processing speed, mental tracking, set-shifting, and semantic fluency tasks. Greater IIV-D was observed in PD and ET using CoV (PD vs. IC: <i>p</i> < .001, <i>d</i> = 0.680; ET vs. IC: <i>p</i> < .001, <i>d</i> = 0.894), but only ET using iSD (<i>p</i> = .001, <i>d</i> = 0.614), after controlling for mean performance and covariates. In the NCD subset, ET showed greater IIV-D than IC (<i>p</i> = .001, <i>d</i> = 0.867) when using CoV. <b>Conclusions</b>: This study is the first to examine IIV-D in ET, revealing individuals with ET exhibit greater IIV-D than IC, even in the absence of a neurocognitive diagnosis. Lack of assessment for clinical confounds (e.g. medications, motor severity) may limit findings. Nevertheless, the research enhances our understanding of cognitive characteristics in ET.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"2121-2141"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the diagnostic contribution of neuropsychological evaluation using natural language processing.","authors":"Brittany Wolff, Laura Glass Umfleet, Daniel L Drane, Joseph M Gullett, Russell M Bauer, Lucia Cavanagh, Adriana M Strutt, Steven P Reise, Keith F Widaman, Douglas S Bell, April D Thames","doi":"10.1080/13854046.2026.2738661","DOIUrl":"https://doi.org/10.1080/13854046.2026.2738661","url":null,"abstract":"<p><p><b>Objective:</b> Diagnostic clarification is regarded as a core function of neuropsychological evaluation, yet its impact has rarely been quantified because diagnoses are typically embedded within unstructured narrative reports. This pilot study quantified the diagnostic contribution of neuropsychological evaluation by examining diagnostic reclassification and diagnostic clarification using a novel natural language processing (NLP) pipeline. <b>Method:</b> A retrospective observational study was conducted using 220 adult outpatient neuropsychological evaluation reports from the National Neuropsychology Network. A rule-based NLP pipeline extracted and harmonized pre-evaluation referral diagnoses and post-evaluation clinician diagnoses from reports in the UCLA electronic health records into structured diagnostic profiles. Diagnostic reclassification, diagnostic specificity gain, and changes in diagnostic category distributions were quantified. Exploratory analyses examined demographic correlates of diagnostic clarification. <b>Results:</b> Diagnostic reclassification was common following neuropsychological evaluation. Overall, 87.7% of patients received at least one new diagnosis, 55.0% had at least one preexisting diagnosis not retained, and 84.5% demonstrated increased diagnostic specificity. Among patients with nonspecific cognitive symptom codes, 90.1% transitioned to formal psychiatric, neurological, or neurocognitive diagnoses. Collectively, these changes shifted diagnostic profiles away from nonspecific cognitive diagnoses toward more specific formal psychiatric and neurocognitive diagnoses (all <i>p</i> < .001). Exploratory demographic associations were modest. <b>Conclusions:</b> Neuropsychological evaluation provides substantial incremental diagnostic information beyond referral documentation by increasing diagnostic specificity and refining diagnostic formulation. These pilot findings establish diagnostic clarification as a measurable clinical outcome and demonstrate the potential of NLP to transform routine neuropsychological reports into scalable metrics for evaluating the clinical impact of neuropsychological services.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"1-21"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential sensitivity of intraindividual variability dispersion and global cognition in the prediction of functional outcomes and mortality in precariously housed and homeless adults.","authors":"Michelle J Blumberg, Anna M Petersson, Paul W Jones, Andrea A Jones, William J Panenka, Olga Leonova, Fidel Vila-Rodriguez, Donna J Lang, Alasdair M Barr, G William MacEwan, Tari Buchanan, William G Honer, Kristina M Gicas","doi":"10.1080/13854046.2024.2325167","DOIUrl":"10.1080/13854046.2024.2325167","url":null,"abstract":"<p><strong>Objective: </strong>To examine cognitive intraindividual variability (IIV) dispersion as a predictor of everyday functioning and mortality in persons who are homeless or precariously housed.</p><p><strong>Method: </strong>Participants were 407 community-dwelling adults, followed for up to 13 years. Neurocognition was assessed at baseline and IIV dispersion was derived using a battery of standardized tests. Functional outcomes (social, physical) were obtained at baseline and last follow-up. Mortality was confirmed with Coroner's reports and hospital records (<i>N</i>  = 103 deaths). Linear regressions were used to predict current social and physical functioning from IIV dispersion. Repeated measures Analysis of Covariance were used to predict long-term change in functioning. Cox regression models examined the relation between IIV dispersion and mortality. Covariates included global cognition (i.e. mean-level performance), age, education, and physical comorbidities.</p><p><strong>Results: </strong>Higher IIV dispersion predicted poorer current physical functioning (<i>B</i> = -0.46 <i>p</i> = .010), while higher global cognition predicted better current (<i>B</i>  = 0.21, <i>p</i> = .015) and change in social functioning over a period of up to 13 years (<i>F</i>  = 4.23, <i>p</i> = .040). Global cognition, but not IIV dispersion, predicted mortality in individuals under 55 years old (HR = 0.50, <i>p</i> = .013).</p><p><strong>Conclusions: </strong>Our findings suggest that indices of neurocognitive functioning (i.e. IIV dispersion and global cognition) may be differentially related to discrete dimensions of functional outcomes in an at-risk population. IIV dispersion may be a complimentary marker of emergent physical health dysfunction in precariously housed adults and may be best used in conjunction with traditional neuropsychological indices.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"2244-2267"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140040966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intraindividual variability, how do I measure thee? Let me count the ways.","authors":"Juliana Wall, Kaylee Litson, Ioannis Pavlidis, Paul T Cirino","doi":"10.1080/13854046.2025.2601742","DOIUrl":"10.1080/13854046.2025.2601742","url":null,"abstract":"<p><p><b>Objective:</b> The present study aimed to better understand key conceptualizations and operationalizations of intraindividual variability (IIV). We expected that differing types and metrics of IIV would relate to one another and predict outcomes (academic achievement) similarly. <b>Method:</b> The sample comprised 238 young adults. IIV was computed within and across six measures - three related to math and three more generally cognitive; in each case, score was separated from response time. We computed three types of IIV (inconsistency, dispersion, and dispersion of inconsistency), across several metrics (standard deviation, coefficient of variability, residualized standard deviation), and assessed their interrelations, and their prediction of academic achievement. <b>Results:</b> Differing metrics of variability were related to one another, but variably so. For prediction, whether or not inconsistency IIV metrics were significant was highly dependent on the measure they were derived from, with or without the primary score for a given measure also included. For dispersion of inconsistency and dispersion, variability metrics were often significant, though this was eliminated in most cases when score was also included in models. <b>Conclusions:</b> By concurrently examining multiple metrics and types of IIV within the same set of measures, this study highlights the need to (a) clarify the type of IIV utilized and why; (b) clarify the rationale for the kinds of measures used to compute IIV, particularly dispersion; and (c) include score alongside timing. Doing so will likely improve the generalizability of IIV findings, and prompt future research avenues, both psychometric- (e.g. simulations) and clinical-related (e.g. across ages and populations).</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"1820-1847"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dispersion and inconsistency based intra‑individual variability in neuropsychological test performance accurately identify performance invalidity among adults referred for ADHD evaluation.","authors":"Maya A Marder, G Whitman Kent, Steven A Abalos, J Gabrielle Springer, Tyler J Kukla, Dillon W Sharp, Brian M Cerny, Matthew S Phillips, Troy A Webber, Jason R Soble","doi":"10.1080/13854046.2025.2537903","DOIUrl":"10.1080/13854046.2025.2537903","url":null,"abstract":"<p><strong>Objective: </strong>This study evaluated intra-individual variability (IIV) metrics, dispersion (IIV-D) and inconsistency (IIV-I), for distinguishing the following groups: attention-deficit/hyperactivity disorder (ADHD), non-ADHD psychological diagnoses (PD), no diagnosis (ND), and invalid neuropsychological test performance.</p><p><strong>Method: </strong>A sample of 845 adults (ADHD = 518; PD = 170; ND = 39; invalid = 118) were administered a neuropsychological battery that yielded 12 indicator scores and five performance validity tests (PVTs). intra-individual standard deviation (ISD) and coefficient of variation (CoV) indexed IIV-D across the 12 test indicators, and Continuous Performance Test-3 Hit Reaction Time Standard Deviation (HRT SD), Variability (VAR), and HRT SD and VAR/mean Hit Reaction Time (HRT; e.g. HRT SD/HRT, VAR/HRT) scores indexed IIV-I.</p><p><strong>Results: </strong>ISD (<i>η</i>² = 0.06), CoV (<i>η</i>² = 0.15), HRT SD (<i>η</i>² = 0.09), HRT SD/HRT (<i>η</i>² = 0.04), VAR (<i>η</i>² = 0.06), and VAR/HRT (<i>η</i>² = 0.01), significantly differed across groups, with the Invalid group having higher IIV values than all other groups. Results for ISD, HRT SD, and VAR remained significant even after controlling for each individual's average performance. Higher IIV was often significantly associated with failure on individual PVTs. No IIV metric showed acceptable classification accuracy for ADHD vs. PD vs. ND, whereas all IIV metrics, except VAR/HRT, showed degrees of success in distinguishing groups from invalid performance (ISD: PD vs Invalid AUC = 0.71; CoV: ADHD/PD/ND vs. Invalid AUCs = 0.74/0.80/0.81; HRT SD: PD/ND vs. Invalid AUCs = 0.74/0.83; HRT SD/HRT: ND vs Invalid AUC = 0.76; VAR: PD/ND vs. Invalid AUCs = 0.70/0.81).</p><p><strong>Conclusions: </strong>Results validated IIV metrics as sensitive to cognitive dysfunction and confirmed their utility for clinically distinguishing invalid performance from genuine attentional and psychological impairments among adults undergoing ADHD evaluation.</p>","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":" ","pages":"2142-2172"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introductory editorial to special issue: Intra-individual variability, broadly defined.","authors":"Libby A DesRuisseaux, Maureen Schmitter-Edgecombe","doi":"10.1080/13854046.2026.2720521","DOIUrl":"https://doi.org/10.1080/13854046.2026.2720521","url":null,"abstract":"","PeriodicalId":55250,"journal":{"name":"Clinical Neuropsychologist","volume":"40 7","pages":"1779-1785"},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149042146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}