Accurately interpreting cognitive change is an essential aspect of clinical care for older adults. Several approaches to identifying 'true’ cognitive change in a single cognitive measure are available (e.g., reliable change methods, regression-based norms); however, neuropsychologists in clinical settings often rely on simple score differences rather than advanced statistics, especially since multiple scores compose a typical battery. This study sought to establish quick-reference normative criteria to help neuropsychologists identify how frequently significant change occurs across multiple measures in cognitively normal older adults.

Data were obtained from the National Alzheimer’s Coordinating Center (NACC). Participants were 845 older adults who were classified as cognitively normal at baseline and at 24-month follow-up. In NACC, these clinical classifications are made separately from the assessment of cognitive performance, including cognitive change. The sample was 34.9% female, 83.5% White, 13.1% Black 2.3% Asian, and 1.1% other race with a mean age of 70.7 years (SD=10.2). Of the sample, 95.5% identified as non-Hispanic. Mean education was 16.1 years (SD=2.8). The cognitive battery entailed: Craft Story Immediate and Delayed Recall, Benson Copy and Delayed Recall, Number Span (Forward & Backward), Category Fluency (Animals & Vegetables), Trails A&B, Multilingual Naming Test, and Verbal Fluency (F&L). Change scores between baseline performance and follow-up were calculated for each measure. The natural distribution of change scores was examined for each measure and cut points representing the 5th and 10th percentile were applied to each distribution to classify participants who exhibited substantial declines in performance on each measure. We then examined the multivariate frequency of statistically rare change scores for each individual.

As expected in a normal sample, overall cognitive performance was generally stable between baseline and 24-month follow-up. Across cognitive measures, 81.9% of participants had at least one change score fall below the 10th percentile in the distribution of change scores, and 55.7% had at least one score below the 5th percentile, 49.3% of participants had two or more change scores that fell below the 10th percentile and 21.1% with two or more below the 5th percentile. There were 26.7% participants that had three or more change scores below the 10th percentile, and 6.4% of participants had three change scores below the 5th percentile.

Among cognitively normal older adults assessed twice at a 24-month interval with a battery of 13 measures, it was not uncommon for an individual to have at least one score fall below the 10th percentile (82% of the sample) or even the 5th percentile (56%) in the natural distribution of change scores. There were 27% participants that had three or more declines in test performance below the 10th percentile; in comparison, only 6% of the sample had three or more change scores at the 5th percentile. This suggests that individuals who exhibit more multivariate changes in performance than these standards are likely experiencing an abnormal rate of cognitive decline. Our findings provide a preliminary quick-reference approach to identifying clinically significant cognitive change. Future studies will explore additional batteries and examine multivariate frequencies of change in clinical populations.

Accurately interpreting change in cognitive functioning is an essential aspect of clinical care for older adults. Several approaches to identifying ‘true’ cognitive change in a single cognitive measure are available (e.g., reliable change methods, regression-based norms); however, neuropsychologists in clinical settings often rely on simple score differences rather than advanced analytical procedures especially since they examine multiple test performances. This study sought to establish quick-reference normative criteria to help neuropsychologists identify how frequently significant change occurs across multiple cognitive measures in cognitively normal older adults.

Data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants were 401 older adults who were classified as cognitively normal at baseline and at 24-month follow-up. In ADNI, these clinical classifications are made separately from the assessment of cognitive performance, including cognitive change. The sample was 50.1% female, 93.5% non-Hispanic White, 4.0% non-Hispanic Black, 1.5% Asian American, and 1.0% other race/ethnicity, with a mean age of 76.0 years (SD = 4.9). Mean education was 16.4 years (SD = 2.7). The cognitive battery included: Boston Naming Test, Category Fluency Test, Trails A & B, Clock Drawing Test, and Auditory Verbal Learning Test, Trial 1-5 Total and Delayed Recall. Change scores between baseline performance and 24-month follow-up were calculated for each measure. The natural distribution of change scores was examined for each measure and cut points representing the 5th and 10th percentile were applied to each distribution to classify participants who exhibited substantial declines in performance on a given measure. We then examined the multivariate frequency of statistically rare change scores for each individual.

As expected in a normal sample, overall cognitive performance was generally stable between baseline and 24-month followup. Across cognitive measures, 43.6% of participants had at least one change score fall below the 10th percentile in the distribution of change scores, and 21.9% had at least one score below the 5th percentile. 13.0% of participants had two or more change scores that fell below the 10th percentile, in comparison to 4.5% with two or more below the 5th percentile. 3.2% of participants had three or more change scores below the 10th percentile, versus 0.5% of participants who had three change scores below the 5th percentile.

Among cognitively normal older adults assessed twice at a 24-month interval with a battery of seven measures, it was not uncommon for an individual to have at least one score fall below the 10th percentile (43% of the sample) or even the 5th percentile (21%) in the natural distribution of change scores. However, only 3.2% of normals had more than two declines in test performance below the 10th percentile, and less than 1% of the sample at more than one change score at the 5th percentile. This suggests that individuals who exhibit more multivariate changes in performance than these standards are likely experiencing an abnormal rate of cognitive decline. Our findings provide a preliminary quick-reference approach to identifying clinically significant cognitive change. Future studies will explore additional batteries and examine multivariate frequencies of change in clinical populations.

Craft story recall test in the National Alzheimer’s Coordinating Center Uniformed Data Set 3 (NACC UDS3) neuropsychological battery has been employed to assess verbal memory and assist clinical diagnosis of mild cognitive impairment (MCI) and dementia. While a Chinese version of the test was adapted, no existing literature has examined the diagnostic validity of the test in Chinese Americans. This study aimed to evaluate the predictive validity of both immediate and delayed recall.

The Chinese version of Craft Story was administered in to 78 Chinese participants per their language preference of Mandarin or Cantonese. Outcome measures were verbatim and paraphrase recall of the story immediately and after a 20-minute delay. A multiple linear regression was performed to investigate the association of each outcome measure with age, education, gender, age when moved to the U.S., years in the U.S., and testing language. To assess its diagnostic value, cutoff standard deviation scores of -1.5 and -2.0 from the mean of the clinically cognitive normal participants were generated for MCI and dementia diagnoses, respectively. Due to the small sample size, a normative group fitting the mean age (73 years), years of education (12 years), and the majority gender (female) of the current sample were used to identify standard cut points. A receiver-operating characteristic analysis was used to compare predicted diagnosis with actual clinical diagnosis obtained through patients’ overall performance and a consensus meeting by licensed clinicians.

Younger age (p < 0.05) and being tested in Mandarin (p < .01) were positively associated with immediate and delayed recall. Strong positive correlations between each measure were observed (all p < .001), indicating a significant relationship between information encoded and retained. Among all the participants, 15 (19.2%) were diagnosed with MCI and 22 (28.2%) with dementia. For MCI diagnosis, the standard cutoff scores demonstrated adequate sensitivity (verbatim=82%, paraphrase=91%) but low specificity (verbatim=44%, paraphrase=67%) in all outcome measures. For dementia diagnosis, delayed recall showed strong sensitivity (100%) and adequate specificity (75%) in both verbatim and paraphrasing scores. Immediate recall paraphrase (sensitivity = 95%, specificity = 50%) showed a better sensitivity but lower specificity than verbatim scoring (sensitivity = 86%, specificity = 58%). The accuracy was higher in delayed recall for both MCI and dementia diagnosis. A preliminary analysis on the optimal cut points indicated higher cutoff scores to distinguish MCI and dementia from clinically cognitive normal population, and from each other (e.g., the optimal cut point for delayed verbatim in distinguishing MCI from normal is 8.0 (sensitivity=89%, specificity=73%, AUC=84.3%)).

Consistent with previous literature, Craft Story delayed recall served as a more accurate diagnostic tool for both MCI and dementia compared to immediate recall in older Chinese Americans. However, poor specificity might increase the chance of following false positive subjects in clinical trials. In addition, testing language appeared to impact performance on verbal memory recall of constructed information. Thus, future studies should focus on developing normative scores that address both the overall cultural differences of Chinese Americans and the heterogeneity within this population.

Behavioral interventions are a non-pharmacological treatment that shows improvement in the everyday functioning of people with Mild Cognitive Impairment (MCI). Multiple studies have focused on examining factors that can reduce or enhance adherence to behavioral interventions. However, few studies use adherence as a predictor of functional changes. The goal of this study was to analyze the association between adherence, age, and education in factor score changes of participant impairment, participant adjustment, and partner adjustment in a sample of participants with amnestic MCI (aMCI) and their study partners.

We included fifty-two dyads of a person with aMCI and their study partner with intervention data at baseline and 24-week follow-up from the Physical Exercise and Cognitive Engagement Outcomes for Mild Neurocognitive Disorder (PEACEOFMND) study. At baseline, participants were randomized to one of three behavioral interventions: computerized cognitive training (BrainHQ; n=19), yoga (n=15), or wellness education (n=18). Factors were established from a larger clinical sample that used the same measures as PEACEOFMND. The three-factor latent structure was constructed as the following: 1) participant adjustment combined scores of the Center for Epidemiologic Studies Depression Scale (CES-D), Quality of Life in Alzheimer’s Disease (QoL-AD), and Self-Efficacy for managing MCI scales; 2) partner adjustment included study partner’s scores in CES-D, QoLAD and Caregiving Competence and Mastery Components (CCMC) of the Pearlin scales; 3) participant impairment included participant’s scores in E-Cog memory domain, and study partner’s scores in the Functional Activity Questionnaire (FAQ) and Zarit Burden Interview. We calculated factor changes by obtaining the difference between factor scores at follow-up and baseline. Bayesian correlation analysis was performed to investigate the association between age, education, adherence to the combined behavioral interventions, participant adjustment, participant impairment, and partner adjustment.

The Bayesian correlation results showed moderate evidence (BF10=6.8, Pearson’s r=0.38) supporting a positive correlation between adherence and change in participant adjustment. Additionally, there was moderate evidence (BF10=2.18, Pearson’s r=0.32) supporting a positive correlation between change in participant impairment and participant level of education as well as participant age and change in partner adjustment (BF10=2.8, Pearson’s r=0.33).

Bayesian correlations replicated results from previous analysis using a traditional method, showing that increased adherence to combined behavioral interventions is associated with an increase in participant’s quality of life, self-efficacy, and better mood. Thus, commitment to behavioral intervention completion in aMCI participants is related to overall participant adjustment.

While declarative learning is dependent on the hippocampus, procedural learning and repetition priming can operate independently from the hippocampus, making them potential targets for behavioral interventions that utilize non-declarative memory systems to compensate for the declarative learning deficits associated with hippocampal insult. Few studies have assessed procedural learning and repetition priming in individuals with amnestic mild cognitive impairment (aMCI).

This study offers an overview across declarative, conceptual repetition priming, and procedural learning tasks by providing between-group effect sizes and Bayes Factors (BFs) comparing individuals with aMCI and controls. Seventy-six individuals with aMCI and 83 cognitively unimpaired controls were assessed. We hypothesized to see the largest differences between individuals with aMCI and controls on declarative learning, followed by conceptual repetition priming, with the smallest differences on procedural learning.

Consistent with our hypotheses, we found large differences between groups with supporting BFs on declarative learning. For conceptual repetition priming, we found a small-to-moderate between-group effect size and a non-conclusive BF somewhat in favor of a difference between groups. We found more variable but overall trivial differences on procedural learning tasks, with inconclusive BFs, in line with expectations.

The current results suggest that conceptual repetition priming does not remain intact in individuals with aMCI while procedural learning may remain intact. While additional studies are needed, our results contribute to the evidence-base that suggests that procedural learning may remain spared in aMCI and helps inform behavioral interventions that aim to utilize procedural learning in this population.

Lifestyle modifications for those with mild cognitive impairment (MCI) may promote functional stability, lesson disease severity, and improve well-being outcomes such as quality of life. The current analysis of our larger comparative effectiveness study evaluated which specific combinations of lifestyle modifications offered as part of the Mayo Clinic Healthy Action to Benefit Independence in Thinking (HABIT) program contributed to the least functional decline in people with MCI (pwMCI) over 18 months.

We undertook to compare evidence-based interventions with one another rather than to a no-treatment control group. The interventions were five behavioral treatments: computerized cognitive training (CCT), yoga, Memory Support System (MSS) training, peer support group (SG), and wellness education (WE), each delivered to both pwMCI and care partners, in a group-based program. To compare interventions, we randomly withheld one of the five HABIT® interventions in each of the group sessions. We conducted 24 group sessions with between 8 and 20 pwMCI–partner dyads in a session.

Withholding yoga led to the greatest declines in functional ability as measured by the Functional Activities Questionnaire and Clinical Dementia Rating. In addition, memory compensation (calendar) training and cognitive exercise appeared to have associations (moderate effect sizes) with better functional outcomes. Withholding SG or WE appeared to have little effect on functioning at 18 months.

Overall, these results add to the growing literature that physical exercise can play a significant and lasting role in modifying outcomes in a host of medical conditions, including neurodegenerative diseases.