Clinical Neuropsychologist最新文献

Objective: The prevalence of neuroendocrine dysfunction (NED) following mild traumatic brain injury (mTBI) remains obscure, with widely varying prevalence estimates. This study aimed to determine prevalence of NED among central hypogonadism, central hypothyroidism, and growth hormone deficiency (GHD) in active-duty military service members (SMs) receiving comprehensive TBI and psychological health care and characterize TBI burden, neurobehavioral symptom severity, and NED associations. Methods: Retrospective analysis of baseline, fasting morning serum screening labs of thyroid, gonadal, and growth hormone axes obtained from SMs attending a 4-week treatment program for TBI. NED prevalence was characterized in those who completed full tri-axis screening as well as GHD and central hypogonadism screening independently. Results: Of 1,832 TBI-screened SMs, 493 completed full neuroendocrine testing. Dual-clinician review confirmed NED in 45 (9.1%; 95% CI [6.9%, 12.0%]). Central hypogonadism (n = 33, 6.7%) was most common, followed by central hypothyroidism (n = 10, 2.0%); Screen-positive suspected GHD was 0.2% (1/493); no cases were confirmed by dynamic stimulation testing, so the true prevalence of GHD cannot be determined in this cohort. NED was associated with increased time since injury (OR = 4.15, p<.001) and fewer lifetime TBIs (OR = 0.66, p=.008), but not neurobehavioral symptoms or cognitive function. Conclusions: In the largest military TBI cohort with full NED screening to date, confirmed post-traumatic hypopituitarism prevalence was 9.1%. GHD was least common by IGF-1 (0.2%) screening, but its true prevalence remains indeterminate without systematic stimulation testing. Findings refine prevalence estimates for NED after military mTBI and emphasize the need for standardized diagnostic approaches prioritizing gonadal and thyroid axes.

Background: Technological advancements have boosted neuropsychology development. Recently, the term Digital Neuropsychology (DN) has been introduced to describe the assessment and training of cognitive functions using digital tools. However, little is known about the development and implementation of these tools, particularly in low-and middle-income countries. This study aimed to synthesize state-of-the-art DN tools in Latin America (LA).

Method: Following PRISMA guidelines, a scoping review was conducted between June and December 2024. Three electronic databases were searched: PubMed/MEDLINE, SciELO, and RedALyC. A gray literature search was also performed using Google Scholar and university thesis repositories. Studies published between 2014 and 2024 in English or Spanish were included.

Results: Of the 662 screened studies, 28 met the inclusion criteria and were fully reviewed. Brazil and Chile accounted for the highest number of studies. A likelihood ratio test indicated no significant deviation from equal distribution across countries. Cognitive assessment was the primary focus in 57.1% of studies, and serious video games were the most used technology (39.3%). Tablets (42.9%) and personal computers (32.1%) were the most frequently employed devices. No associations were found between technology and purpose, technology and device type, or country and purpose. Memory and attention were the most frequently assessed cognitive domains (32.1%).

Conclusions: The increasing body of research highlights the potential of digital technology for cognitive assessment in LA. However, the development of DN in the region faces challenges, including the need for ecological validation studies, more extensive and diverse samples, and the establishment of normative data.

Objective: Major innovations are underway in the practice of clinical neuropsychology, as they are in the neurosciences and psychology more generally. Artificial intelligence (AI) is poised to offer numerous advantages over traditional neuropsychological practices, the most important of which is to improve clinical decision-making and thereby reduce diagnostic errors. However, the emergence, rapid availability, and adoption of AI, like other technological advances, has ethical implications. The purpose of this article is to present the ethical issues of primary importance in the adoption and application of AI in clinical neuropsychology and further advance the discussion of AI, ethics, and neuropsychology. Method: Benefits and risks of AI use in clinical neuropsychology are examined in the context of general bioethical principles. Results: Some of the primary anticipated risks that may lead to harmful outcomes for patients include: (1) threats to privacy and security, (2) bias in AI models, (3) lack of professional competence, (4) limitations to informed consent, (5) inequity in access to AI, (6) overreliance on AI, and (7) lack of accountability. Conclusions: Awareness and understanding of the ethical implications of technological advances, including AI, are essential for maintaining patient welfare at the center of clinical care and for preparing clinicians to anticipate ethical challenges and avoid dilemmas or address them effectively when they are encountered. Advanced preparation enables neuropsychologists to promote the ethical and responsible use of AI, for the benefit of both practitioners and patients.

Objectives: This study investigated the validity and reliability of subtle errors and slowing in simple everyday tasks (Naturalistic Action Test [NAT]) to assess mild functional difficulties in older adults with mild cognitive impairmen (MCI). Method: Older adults (N = 111, MAge= 73.45; SD= 6.53) classified as having healthy cognition (HC) or MCI completed neuropsychological testing and two NAT tasks (breakfast and lunch) twice, separated by 4-6 wk. NATs were scored for subtle, inefficient actions (i.e., micro-errors) and the average time (in sec) to complete a task step. Results: Participants with MCI made significantly more micro-errors [F (1, 109) = 8.78, p = .004, partial η² = 0.07] and had a significantly longer average time per step [F (1, 109) = 13.98, p < .001, partial η² = 0.11] than participants with HC. Micro-errors correlated with tests of episodic memory (r = -0.237, p = .012) and executive functioning (r = -0.201, p = .035), whereas average time per step correlated only with episodic memory (r = -0.300, p = .0001). Test-retest reliability was good for average time per step (ICC = .872, p < .001) and moderate for micro-errors (ICC = .675, p < .001). Conclusions: Measures of inefficient actions and performance time in familiar everyday tasks demonstrated strong to adequate construct and concurrent validity, as well as test-retest- and inter-rater reliability, supporting their use for the quantifying mild functional difficulties. Future studies should explore this scoring approach to develop early markers of functional disability or dementia risk.

Objective: The Trail Making Test (TMT) is a widely used neuropsychological tool for assessing executive functions. This study aimed to establish regression-based normative data for TMT performance in a Turkish population aged 18-80, accounting for the effects of age, education, and sex on both basic (TMT A and TMT B) and derived scores (TMT B-A and TMT B/A). Method: A total of 462 participants were recruited, with 409 included in the final analysis after applying exclusion criteria. Participants completed the international version of the TMT. Pearson correlation analyses and multiple linear regression models assessed relationships between TMT scores and demographic variables. Education was treated as a continuous variable, and regression-based norms were developed for all TMT scores. Results: Age and education were significant predictors of TMT performance. Age primarily affected TMT A scores, while education was the strongest predictor for TMT B, TMT B-A, and TMT B/A scores. The regression models explained 36-38% of the variance in basic scores and 6-24% in derived scores. Women performed better than men on the TMT B/A ratio score, but overall, sex had a less pronounced effect than age and education. Conclusions: This study provides the first regression-based normative data for the TMT in a Turkish population. These norms are crucial for improving the accuracy of neuropsychological assessments in Turkey and facilitating cross-cultural comparisons in cognitive research. The findings emphasize the importance of adjusting for demographic factors in clinical and research settings to ensure precise evaluations of cognitive functioning.

Objective: At times, patients with Long COVID fail performance validity tests (PVTs) for cognitive measures and symptom validity tests (SVTs) embedded in formal personality measures. This is the first study, to our knowledge, to examine whether self-reported symptoms on the Personality Assessment Inventory (PAI) and the Modified Fatigue Impact Scale (MFIS) were related to performance validity in Long COVID patients. Method: Participants were 175 individuals diagnosed with Long COVID who completed four PVTs, the MFIS, and the PAI. There was evidence for nots based on medical records review for 25.71% of the patients. Based on PVT performances, patients were assigned to one of three groups: Pass group (no PVT failures), Intermediate group (1 PVT failure), or Fail group (2+ PVT failures). Results: 84.57% of participants were in the Pass group, 9.14% in the Intermediate group, and 6.29% in the Fail group. There was a not a significant difference in external incentive frequency between groups. Only one significant group difference on the PAI scales and subscales was found, with slightly greater somatization symptoms (SOM-S) reported in the Fail group relative to the Pass group (η² = .03). The MFIS was not significantly different between groups. Conclusions: These findings suggest that PVT failure is not associated with fatigue or PAI responses, except on the somatization subscale.

Objective: To validate the Spanish version of the Cerebellar Cognitive-Affective Syndrome scale (CCAS-S), originally published in 2018, in patients with cerebellar ataxia and healthy subjects, as an adapted Spanish version based on normative data has not yet been published or validated. Methods: Spanish CCAS-S was -administered prospectively to 158 patients with cerebellar ataxia and 164 matched healthy subjects from -different regions of Spain. Discriminant validity and reliability were evaluated. A subgroup of 30 patients underwent detailed neuropsychological examinations to confirm the construct validity. The Scale for the Assessment and Rating of Ataxia (SARA) and the Brief Ataxia Rating Scale (BARS) were used to assess motor performance. Results: This Spanish instrument demonstrates reliability and exhibits statistically significant differences in performance between patients and healthy subjects. Our analysis revealed lower values for specificity in detecting possible, probable, or definite CCAS compared to those reported in the US validation study when utilizing the original cutoff values. Upon application of the appropriate -correction factor for education, the specificity values approximated those reported for probable and definite CCAS diagnostics in the original investigation. Conclusions: The adapted Spanish CCAS-S has demonstrated validity and good reliability in this cohort. Discriminant validity was satisfactory for probable and definite CCAS when the correction for education was applied, and modified template and instructions have been developed. Further research is necessary to investigate the significance of the possible CCAS category, as diagnosed using the Spanish version, as well as to assess the performance of the corrected scale in other Spanish-speaking countries.

Objective: Some studies show using neuropsychological-actuarial mild cognitive impairment (MCI) criteria may produce lower reversion rates (i.e. reverting from a cognitive diagnosis to no diagnosis) and higher associations with Alzheimer's disease biomarkers compared to conventional methods, but this has not been evaluated in a Hispanic sample. This study evaluated neuropsychological-actuarial MCI criteria performance in the Texas Alzheimer's Research and Care Consortium (TARCC) cohort compared to clinical-consensus diagnosis. Method: Data from 2,110 TARCC participants (47% Hispanic) were utilized. McNemar tests evaluated the performance of neuropsychological-actuarial versus clinical-consensus criteria in those who remained stable or converted to dementia over 3 annual visits, stratified by ethnicity (Hispanic vs. non-Hispanic). Chi-square analysis was used to compare frequencies of APOE ε4 allele positivity by diagnostic method. Results: Significantly more Hispanic participants were diagnosed with MCI using neuropsychological-actuarial criteria than were non-Hispanics, χ²(1) = 195.3, p < .001, ϕ = 0.32. Hispanic participants meeting neuropsychological-actuarial MCI criteria at baseline were more likely to revert at follow-up, χ²(1) = 10.04, p < .01, ϕ = 0.10. No differences in reversion rate were found between Hispanic and non-Hispanic individuals with clinical-consensus MCI diagnoses, χ²(1) = 0.38, p = .60. There was no association between APOE ε4 allele positivity and neuropsychological-actuarial diagnosis, while there was an association for clinical-consensus diagnoses χ²(1) = 15.1, p < .001, ϕ = 0.09. Conclusions: In TARCC, the clinical-consensus MCI diagnostic method produced fewer cases of reversion compared to the neuropsychological-actuarial method, particularly in Hispanic participants. This is consistent with recent research investigating the use of the neuropsychological-actuarial method in African American/Black individuals. Caution is warranted when using neuropsychological-actuarial criteria among individuals with diverse backgrounds.

Objective: Blood-based biomarkers are valued for their lower cost and less invasive nature, though issues with widespread implementation and accessibility remain. Process-based scores from story recall have been shown to detect neuronal network disturbances typical of Alzheimer's disease (AD) pathology more effectively than traditional metrics. This study examined the associations between process-based scores and concurrent plasma AD biomarkers in older adults without dementia, while also comparing them to traditional metrics. Additionally, it also investigated the diagnostic utility of these metrics in detecting plasma p-tau217 positivity. Methods: Data from 416 participants (mean age = 66.6 ± 7) free of dementia were extracted from the Wisconsin Registry for Alzheimer's Prevention (WRAP). Logical Memory Test (LMT) and plasma p-tau217, p-tau181, p-tau231, Aβ42/Aβ40 ratio, GFAP and NfL levels were analyzed. Bayesian regression models assessed associations between plasma biomarkers and both process-based and traditional LMT scores, controlling for the covariates. Results: The best-fitting model for plasma p-tau217 included Total ratio (Tr) and Immediate recall (BF10=573), but Tr showed stronger evidence of association (mean coefficient = 0.208; BFinclusion=14.4) than Immediate recall (mean coefficient=-0.007; BFinclusion=1.7). Tr was also the best predictor of plasma p-tau181 (mean coefficient = 0.144; BF10=10.5) and GFAP (mean coefficient = 0.141; BF10=5.8), outperforming traditional LMT scores. No memory scores were associated with plasma p-tau231 or Aβ42/40 ratio levels. Tr score was the strongest single predictor of p-tau217 positivity (BF₁₀=38). Conclusions: These findings suggest that process-based memory scores might be useful in enhancing the detection of neuronal network disturbances associated with AD pathology, especially in settings where biomarker testing is unavailable.

Objective: Navigation, the ability to find one's way from one place to another, is an important cognitive skill for maintaining autonomy in daily life. Several findings indicate that navigational ability can be impaired after stroke. However, navigation is rarely assessed in clinical practice, and evidence-based recommendations for suitable diagnostic tools are lacking. Furthermore, the scientific literature does not provide a meta-analytic estimation of the prevalence of post-stroke navigational impairments. This systematic review aims to provide an overview of the tools to assess navigational difficulties after stroke, including their psychometric properties, and determine the prevalence of post-stroke navigational difficulties.

Method: Three investigators independently and systematically searched publications performing assessments of navigation in the stroke population, with a fourth independent investigator consulted when discrepancies were present. References of the retrieved articles were hand searched for relevant articles.

Results: The systematic review included 19 studies, reporting on 19 different approaches to assess objective and/or subjective navigation skills, each with different psychometric properties. The pooled effect size, using a random-effects model including data from a subset of 8 out of the 19 included studies, demonstrated a prevalence of post-stroke navigation impairments of 35% (95% CI: 0.29-0.42). However, this model was significantly heterogeneous.

Conclusions: Navigational difficulties are a common neuropsychological deficit after stroke. However, navigation is a broad construct and a subdivision to reduce heterogeneity in navigation ability is recommended, e.g. by categorizing navigation into landmark-, location-, and path-based navigation impairment. The inclusion of objective and subjective assessments of navigation is recommended in clinical practice.

Registration: The protocol was registered at the PROSPERO international prospective register of systematic reviews (PROSPERO ID: CRD42023491346).