This study examined the validity of a visual inspection time (IT) task as a measure of processing speed (PS) in a sample of children with and without cerebral palsy (CP). IT tasks measure visualization speed without focusing on the motor response time to indicate decision making about the properties of those stimuli.

Participants were 113 children ages 8–16, including 45 with congenital CP, and 68 typically developing peers. Measures were a standard visual IT task that required dual key responding and a modified version using an assistive technology button with response option scanning. Performance on these measures was examined against traditional Wechsler PS measures (Coding, Symbol Search).

IT performance shared considerable variance with traditional paper-pencil PS measures for the group with CP, but not necessarily in the typically developing group. Concurrent validity was found for both IT task versions with traditional PS measures in the group with CP. IT classification accuracy for lowered PS showed modest sensitivity and good specificity particularly for the modified IT task.

As measures of PS in children with CP who are unable to validly participate in traditional PS tasks, IT tasks demonstrate adequate concurrent validity and may serve as a beneficial alternative measure of PS in this population.

Adult attention-deficit hyperactivity disorder (ADHD) clinics are in their infancy in Ireland and internationally. There is an urgent need for clinical evaluation of these services. Until now, clinical outcomes have relied mainly on functional scales and/or quality of life. However, adult ADHD is a longstanding disorder with many comorbidities. Although medication for ADHD symptoms can have immediate effects, co-occurring problems may take considerably longer to remediate.

To present the psychometrics of a short outcome measure of key clinical areas including symptoms.

The ADHD Clinical Outcome Scale (ACOS), developed by the authors, is a clinician-rated scale and was administered in consecutive adults attending an ADHD clinic. A modified version was completed by the participant. A second clinician independently administered the scale in a subsample. ACOS consists of 15 items rated on a Likert scale. Two self-report scales, the Adult ADHD Quality of Life Questionnaire (AAQoL) and Weiss Functional Impairment Rating Scale (WFIRS), were also administered.

The mean age of 148 participants was 30.1 years (s.d. = 9.71), and 81 were female (54.7%). The correlation for interrater reliability was r = 0.868, and that between the participant and clinician versions was r = 0.663. The intraclass correlation coefficient for the internal consistency was 0.829, and the correlations for concurrent validity with total AAQoL and WFIRS scores were r = −0.573 and r = 0.477, respectively. Factor analysis revealed four factors: (a) attentional/organisational problems; (b) hyperactivity/impulsivity; (c) comorbidities; and (d) alcohol/drug use, self-harm and tension in relationships.

The psychometrics of the ACOS are promising, and the inclusion of typically co-occurring clinical domains makes it suitable for use as a clinician-rated outcome measure in every contact with patients attending adult ADHD clinics.

Whether the recent rise in adolescent self-reported depressive symptoms is influenced by changing reporting behavior is much debated. Most studies use observed sum scores to document trends but fail to assess whether their measures are invariant across time, a prerequisite for meaningful inferences about change. We examined whether measurement noninvariance, indicative of changing perceptions and reporting of symptoms, may influence the assessment of time trends in adolescent depressive symptoms.

Data stem from the nationwide repeated cross-sectional Ungdata-surveys (2010–2019) of 560 712 responses from adolescents aged 13 to 19 years. Depressive symptoms were measured with the Kandel and Davies' six-item Depressive Mood Inventory. Using structural equation modeling, we examined measurement invariance across time, gender and age, and estimated the consequences of noninvariance on cross-cohort time trends.

Across most conditions, the instrument was found measurement invariant across time. The few noninvariant parameters detected had negligible impact on trend estimates. From 2014, latent mean depressive symptom scores increased among girls. For boys, a U shaped pattern was detected, whereby an initial decrease in symptoms was followed by an increase from 2016. Larger issues of noninvariance were found across age in girls and between genders.

From a measurement perspective, the notion that changed reporting of symptoms has been an important driver of secular trends in depressive symptoms was not supported. Thus, other causes of these trends should be considered. However, noninvariance across age (in girls) and gender highlights that depressive symptoms are not necessarily perceived equivalently from early to late adolescence and across gender.

Neuropsychological assessment of preschool children is essential for early detection of delays and referral for intervention prior to school entry. This is especially pertinent in low- and middle-income countries (LMICs), which are disproportionately impacted by micronutrient deficiencies and teratogenic exposures. The Grenada Learning and Memory Scale (GLAMS) was created for use in limited resource settings and includes a shopping list and face-name association test. Here, we present psychometric and normative data for the GLAMS in a Grenadian preschool sample.

Typically developing children between 36 and 72 months of age, primarily English speaking, were recruited from public preschools in Grenada. Trained Early Childhood Assessors administered the GLAMS and NEPSY-II in schools, homes, and clinics. GLAMS score distributions, reliability, and convergent/divergent validity against NEPSY-II were evaluated.

The sample consisted of 400 children (190 males, 210 females). GLAMS internal consistency, inter-rater agreement, and test-retest reliability were acceptable. Principal components analysis revealed two latent factors, aligned with expected verbal/visual memory constructs. A female advantage was observed in verbal memory. Moderate age effects were observed on list learning/recall and small age effects on face-name learning/recall. All GLAMS subtests were correlated with NEPSY-II Sentence Repetition, supporting convergent validity with a measure of verbal working memory.

The GLAMS is a psychometrically sound measure of learning and memory in Grenadian preschool children. Further adaptation and scale-up to global LMICs are recommended.

Mainstream cognitive behavioural theory stipulates that clinically significant health anxiety persists over time at least partially due to negatively reinforced health-related behaviours, but there exists no broad and psychometrically valid measure of such behaviours.

To draft and evaluate a new self-report scale – the Health Anxiety Behavior Inventory (HABI) – for the measurement of negatively reinforced health anxiety behaviours.

We drafted the HABI from a pool of 20 candidate items administered in a clinical trial at screening, and before and after cognitive behaviour therapy (n=204). A psychometric evaluation focused on factor structure, internal consistency, convergent and discriminant validity, test–retest reliability, and sensitivity to change.

Based on factor analysis, the HABI was completed as a 12-item instrument with a four-dimensional factor structure corresponding to the following scales: (i) bodily preoccupation and checking, (ii) information- and reassurance-seeking, (iii) prevention and planning, and (iv) overt avoidance. Factor inter-correlations were modest. The internal consistency (α=.73–.87) and 2-week test–retest reliability (r=.75–.90) of the scales was adequate. The bodily preoccupation and checking, and information- and reassurance-seeking scales were most strongly correlated with the cognitive and emotional components of health anxiety (r=0.41, 0.48), and to a lower extent correlated to depressive symptoms and disability. Change scores in all HABI scales correlated with improvement in the cognitive and emotional components of health anxiety during cognitive behaviour therapy.

The HABI appears to reliably measure negatively reinforced behaviours commonly seen in clinically significant health anxiety, and might be clinically useful in the treatment of health anxiety.

Access to psychedelic drugs is liberalizing, yet responses are highly unpredictable. It is therefore imperative that we improve our ability to predict the nature of the acute psychedelic experience to improve safety and optimize potential therapeutic outcomes. This study sought to validate the ‘Imperial Psychedelic Predictor Scale’ (IPPS), a short, widely applicable, prospective measure intended to be predictive of salient dimensions of the psychedelic experience.

Using four independent datasets in which the IPPS was completed prospectively – two online surveys of ‘naturalistic’ use (N = 741, N = 836) and two controlled administration datasets (N = 30, N = 28) – we conducted factor analysis, regression, and correlation analyses to assess the construct, predictive, and convergent validity of the IPPS.

Our approach produced a 9-item scale with good internal consistency (Cronbach's α = 0.8) containing three factors: set, rapport, and intention. The IPPS was significantly predictive of ‘mystical’, ‘challenging’, and ‘emotional breakthrough’ experiences. In a controlled administration dataset (N = 28), multiple regression found set and rapport explaining 40% of variance in mystical experience, and simple regression found set explained 16% of variance in challenging experience. In another (N = 30), rapport was related to emotional breakthrough explaining 9% of variance.

Together, these data suggest that the IPPS is predictive of relevant acute features of the psychedelic experience in a broad range of contexts. We hope that this brief 9-item scale will be widely adopted for improved knowledge of psychedelic preparedness in controlled settings and beyond.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Identify which NIH Toolbox Cognition Battery (NIHTB-CB) subtest(s) best differentiate healthy controls (HC) from those with amnestic mild cognitive impairment (aMCI) and compare the discriminant accuracy between a model using a priori “Norm Adjusted” scores versus “Unadjusted” standard scores with age, sex, race/ethnicity, and education controlled for within the model. Racial differences were also examined.

Participants were Black/African American (B/AA) and White consensus-confirmed (HC = 96; aMCI = 62) adults 60–85 years old that completed the NIHTB-CB for tablet. Discriminant function analysis (DFA) was used in the Total Sample and separately for B/AA (n = 80) and White participants (n = 78).

Picture Sequence Memory (an episodic memory task) was the highest loading coefficient across all DFA models. When stratified by race, differences were noted in the pattern of the highest loading coefficients within the DFAs. However, the overall discriminant accuracy of the DFA models in identifying HCs and those with aMCI did not differ significantly by race (B/AA, White) or model/score type (Norm Adjusted versus Unadjusted).

Racial differences were noted despite the use of normalized scores or demographic covariates—highlighting the importance of including underrepresented groups in research. While the models were fairly accurate at identifying consensus-confirmed HCs, the models proved less accurate at identifying White participants with an aMCI diagnosis. In clinical settings, further work is needed to optimize computerized batteries and the use of NIHTB-CB norm adjusted scores is recommended. In research settings, demographically corrected scores or within model correction is suggested.

Empathy is a key factor to examine in development, because of its predictive associations with both aggression and successful prosocial behaviour. However, established measures of empathy for Low-to-Middle Income Countries, including South Africa, are lacking. In children, parent-report measures are key. However, a local study examining empathy and aggression (Malcolm-Smith et al., 2015) found poor psychometric performance for a widely used parent-report measure of dispositional empathy, the Griffith Empathy Measure (GEM). We thus investigated which of two questionnaires measuring dispositional cognitive and affective empathy perform better in this context.

We contrasted internal consistency reliability of a simplified version of the GEM (SGEM; n = 160) and a parent-report version of the Questionnaire of Cognitive and Affective Empathy (QCAE; n = 440) in a low-mid socio-economic status sample. Convergence between the measures and factor structure were also assessed.

The parent-report version of the QCAE performed well as a measure of child dispositional cognitive and affective empathy, with good reliability (overall α = 0.90 vs. SGEM α = .63), and confirmatory factor analysis supporting the two-factor structure. The SGEM’s reliability and failure to correlate with QCAE indicated poor psychometric performance.

This is the first psychometric evaluation of the QCAE as a parent-report measure, and our results indicate that it should prove useful for future assessments of dispositional empathy in children across a variety of contexts.

Modified Mini-Mental State Examination (3MSE) is often used to screen for dementia, but little is known about psychometric validity in American Indians.

We recruited 818 American Indians aged 65–95 for 3MSE examinations in 2010–2013; 403 returned for a repeat examination in 2017–2019. Analyses included standard psychometrics inferences for interpretation, generalizability, and extrapolation: factor analysis; internal consistency-reliability; test-retest score stability; multiple indicator multiple cause structural equation models.

This cohort was mean age 73, majority female, mean 12 years education, and majority bilingual. The 4-factor and 2nd-order models fit best, with subfactors for orientation and visuo-construction (OVC), language and executive functioning (LEF), psychomotor and working memory (PMWM), verbal and episodic memory (VEM). Factor structure was supported for both research and clinical interpretation, and factor loadings were moderate to high. Scores were generally consistent over mean 7 years. Younger participants performed better in overall scores, but not in individual factors. Males performed better on OVC and LEF, females better on PMWM. Those with more education performed better on LEF and worse on OVC; the converse was true for bilinguals. All differences were significant, but small.

These findings support use of 3MSE for individual interpretation in clinic and research among American Indians, with moderate consistency, stability, reliability over time. Observed extrapolations across age, sex, education, and bilingual groups suggest some important contextual differences may exist.

Although the cognitive profiles of people experiencing homelessness have been described in the literature, the neuropsychological profile of people experiencing complex homelessness has not been delineated. Complex homelessness is homelessness that continues despite the provision of bricks and mortar solutions. People experiencing complex homelessness often have an array of physical health, mental health, substance use, neurodevelopmental and neurocognitive disorders. The present study aimed to delineate the neuropsychological profile of people experiencing complex homelessness and explore the utility of neuropsychological assessment in supporting this population.

19 people experiencing complex homelessness in Sydney, Australia, were consecutively referred by specialist homelessness services for neuropsychological assessment. They underwent comprehensive assessment of intelligence, memory and executive functioning and completed questionnaires to screen for the presence of ADHD, PTSD, depression, anxiety and stress. A range of performance validity measures were included. Referrers were asked to complete questionnaires on history of childhood trauma, psychological functioning, drug and alcohol use, functional cognitive abilities, homelessness factors, personality, risk of cognitive impairment and adaptive functioning and to note existing or suspected mental health, neurodevelopmental and neurocognitive disorders. Referrers also completed a post-assessment pathways questionnaires to identify whether the neuropsychological assessment facilitated referral pathways (e.g., for government housing or financial assistance). Clinicians completed a post-assessment diagnosis survey, which was compared to the pre-assessment known or suspected diagnoses. Finally, referrers were asked to complete a satisfaction questionnaire regarding the neuropsychological assessment.

Mean (SD) WAIS-IV indexes were VCI = 81.1 (14.5), PRI = 86.1 (10.9), WMI = 80.5 (13.0), PSI = 81.6 (10.2). Mean WMS-IV Flexible (LMVR) indexes were AMI = 68.3 (19.6), VMI = 77.1 (19.3), IMI = 72.7 (17.2), and DMI = 70.5 (17.6). The majority of participants showed unusual differences between WAIS-IV and TOPF-predicted WAIS-IV scores and between WAIS-IV General Ability and WMS-IV Flexible (LMVR) scores. Demographically corrected scores on tests of executive functioning were mostly one or more standard deviations below the mean. The majority of participants screened positive on screening measures of executive dysfunction, PTSD and ADHD and had elevated self-reported psychological distress scores. At least one new diagnosis was made for nine (47%) participants, established diagnoses were confirmed for two (11%) participants, diagnoses were supported for 15 (79%) participants, tentative diagnoses were made for 16 (84%) participants, and five (26%) participants had at least one diagnosis disconfirmed/unsupported. Referrers indicated that the majority of post-assessment pathways were more accessible following the neuropsychological assessment and that they were very satisfied with the neuropsychological assessments overall.

This is one of the first studies to delineate the neuropsychological profile of people experiencing complex homelessness using robust psychometric approaches, including performance validity tests. This population experiences a high burden of cognitive impairment and associated substance use, neurodevelopmental and mental health comorbidities. Neuropsychological assessment makes referral pathways more accessible and is valued by referrers of people experiencing complex homelessness.

Existing research has demonstrated that neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis in patients with neurodegenerative conditions (e.g., increased functional dependence, worse quality of life, greater caregiver burden, faster disease progression). BPSD are most commonly measured via the Neuropsychiatric Inventory (NPI), or its briefer, informant-rated questionnaire (NPI-Q). Despite the NPI-Q’s common use in research and practice, there is disarray in the literature concerning the NPI-Q’s latent structure and reliability, possibly related to differences in methods between studies. Also, hierarchical factor models have not been considered, even though such models are gaining favor in the psychopathology literature. Therefore, we aimed to compare different factor structures from the current literature using confirmatory factor analyses (CFAs) to help determine the best latent model of the NPI-Q.

This sample included 20,500 individuals (57% female; 80% White, 12% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Individuals were included if they had completed an NPI-Q during their first visit at one of 33 Alzheimer Disease Research Centers reporting to the National Alzheimer Coordinating Center (NACC). All CFA and reliability analyses were performed with lavaan and semTools R packages, using a diagonally weighted least squares (DWLS) estimator. Eight single-level models using full or modified versions of the NPI-Q were compared, and the top three were later tested in bifactor form.

CFAs revealed all factor models of the full NPI-Q demonstrated goodness of fit across multiple indices (SRMR = 0.039-0.052, RMSEA = 0.025-0.029, CFI = 0.973-0.983, TLI = 0.9670.977). Modified forms of the NPI-Q also demonstrated goodness of fit across multiple indices (SRMR = 0.025-0.052, RMSEA = 0.0180.031, CFI = 0.976-0.993, TLI = 0.968-0.989). Top factor models later tested in bifactor form all demonstrated consistently stronger goodness of fit regardless of whether they were a full form (SRMR = 0.023-0.035, RMSEA = 0.015-0.02, CFI = 0.992-0.995, TLI = 0.985-0.991) or a modified form (SRMR = 0.023-0.042, RMSEA = 0.015-0.024, CFI = 0.985-0.995, TLI = 0.9770.992). Siafarikas and colleagues’ (2018) 3-factor model demonstrated the best fit among the full-form models, whereas Sayegh and Knight’s (2014) 4-factor model had the best fit among all single-level models, as well as among the bifactor models.

Although all factor models had adequate goodness of fit, the Sayegh & Knight 4-factor model had the strongest fit among both single-level and bifactor models. Furthermore, all bifactor models had consistently stronger fit than single-level models, suggesting that BPSD are best theoretically explained by a hierarchical, non-nested framework of general and specific contributors to symptoms. These findings also inform consistent use of NPI-Q subscales.

The Coma Recovery Scale-Revised (CRS-R) is the gold standard assessment of adults with disorders of consciousness (DoC); however few studies have examined the psychometric properties of the CRS-R in pediatric populations. This study aimed to demonstrate preliminary intra-rater and inter-rater reliability of the CRS-R in children with acquired brain injury (ABI).

Participants included 3 individuals (ages 10, 15, and 17 years) previously admitted to an inpatient pediatric neurorehabilitation unit with DoC after ABI who were followed in an outpatient brain injury clinic due to ongoing severe disability. ABI etiology included traumatic brain injury (TBI; n=2) and encephalitis (n=1). Study participation took place on average 4.6 years after injury (range 2-9). The Glasgow Outcome Scale-Extended, Pediatric Version (GOS-E Peds), a measure of outcome after pediatric brain injury, was administered as part of screening. Two participants were placed in the GOS-E Peds “lower severe disability” category (i.e., score of 6) and one was placed in the “upper severe disability” category (i.e., score of 5). The CRS-R includes 6 subscales measuring responsivity including Auditory (range 0-4), Visual (range 05), Motor (range 0-6), Oromotor/Verbal (range 03), Communication (range 0-2), and Arousal (range 0-3) with higher scores indicating higherlevel function. Subscales are totaled for a CRS-R Total score. Behaviors shown during the CRS-R are used to determine state of DoC [Vegetative State (VS), Minimally Conscious State (MCS) or emergence from a minimally conscious state (eMCS)] based on 2002 Aspen Guidelines. Participants were administered the CRS-R three consecutive times on the same day. Administrations were completed by two raters in this order: Rater 1 (1A), Rater 1 (1B) and Rater 2. Intra-rater reliability was deemed by percent agreement across the 6 subscales between Rater 1A and 1B. Inter-rater reliability was deemed by percent agreement across the 6 subscales between 1A and 2.

Mean CRS-R Total score for Rater 1A was 22 (SD=1.73, range 20-23), Rater 1B was 22 (SD=1.73, range 20-23), and Rater 2 was 21.33 (SD=2.08, range 19-23). Intra-rater reliability was 100% and inter-rater reliability was 94% across all subscales. All participants were deemed eMCS at all 3 ratings.

Data from this very small sample of children suggests that the CRS-R demonstrates both intra-rater and inter-rater reliability in patients with a history of DoC after ABI. Given that all children were at the high end of the scale (eMCS), further research is needed with a larger sample of children with a range of states of DoC.

Neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis of patients with neurodegenerative conditions. BPSD are commonly measured via a brief, informant-rated version of the Neuropsychiatric Inventory (NPI), the NPI-Q. Previously (see our other submission to this conference), we established optimal latent structures by comparing different factor models in the literature using confirmatory factor analyses (CFAs). However, questions remain as to why so many different models were found in the literature. One possibility is sampling differences, including different proportions of individuals across cognitive stages (e.g., mild cognitive impairment, moderate dementia) or syndromes (e.g., Alzheimer’s amnestic syndrome, Dementia with Lewy Bodies). We tested this hypothesis by subjecting candidate models to measurement invariance (MI) analyses stratified by cognitive stage and syndrome.

Individuals were included if they had completed an NPI-Q during their first visit at an Alzheimer Disease Research Center reporting to the National Alzheimer Coordinating Center (NACC). This resulted in 20,500 individuals (57% female; 80% White, 13% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Regarding staging, 75.9% of individuals did not meet criteria for all-cause dementia, whereas 24.1% individuals had all-cause dementia. Regarding syndromes, 35.6% had an Alzheimer’s presentation (“AD-type”) and 5.6% had either a behavioral variant frontotemporal dementia or Lewy-Body dementia presentation (“behavioral-type”). A 3-factor and 4-factor model were subject to MI across these groupings. We conducted MI analyses for equal forms, equal loadings, and equal intercepts using the lavaan R package with a diagonally weighted least squares (DWLS) estimator.

The 3-factor model demonstrated good fit among individuals experiencing (CFI = 0.965, TLI = 0.955) and not experiencing (CFI = 0.984, TLI = 0.979) dementia, as well as among AD-type (CFI = 0.983, TLI = 0.978) presentations, but had borderline poor fit for behavioral-type (CFI = 0.932, TLI = 0.912) presentations. The 4-factor model had better fit among those experiencing (CFI = 0.985, TLI = 0.977) and not experiencing (CFI = 0.995, TLI = 0.992) dementia. Additionally, the 4-factor model demonstrated good of fit for AD-type (CFI = 0.993, TLI = 0.989) and poorer fit for behavioral-type (CFI = 0.949, TLI = 0.922) syndromes. Chi-square differences suggested that equal loading and equal intercept hypotheses should be rejected for both 3- and 4-factor models, for both staging and syndromal groupings. However, relative fit indices suggested that the equal form, equal loading, and equal intercept hypotheses could be adequate for only the 4-factor model.

The variability of factor structures in the BPSD literature appears, at least partially, explained by sampling variability among cognitive stages and dementia syndromes. The best models in the literature appear to have good fit in non-demented individuals and, among those who have dementia, in those with an AD syndrome. Only Sayegh & Knight’s 4-factor model had adequate (albeit, not optimal) fit among those with all-cause dementia and, more specifically, among those with a behavioral-type dementia syndrome. These findings inform BPSD theory and practical implementation of NPI-Q subscales.

Alzheimer’s disease (AD) clinical trials lack diverse representation, limiting their generalizability. In addition, the clinical meaningfulness of observed changes during treatment may vary as a function of participant characteristics. Defining meaningful change in AD within diverse ethnoracial groups is therefore greatly needed. Meaningful change in AD trials can be assessed by three different anchors: participants, informants, or clinicians. Previous research has suggested that estimations of the minimal clinically important difference (MCID) vary by disease severity, choice of anchor, and anchor agreement. These relationships have been studied primarily within non-Hispanic white (NHW) samples. This project evaluates anchor-based MCID within and across the three most prevalent ethnoracial groups in the United States, non-Hispanic White (NHW), Hispanic/Latino (H/L), and Black/African-American (B/AA).

Data from the National Alzheimer’s Coordinating Center Uniform Dataset (NACC UDS) were used to investigate MCID within older adults (ages 50+) diagnosed as cognitively normal or cognitively impaired due to suspected AD. Data were taken from all versions of the UDS and consisted of all available participants with two consecutive annual visits. The identified sample (N=22,043) is approximately 83.6% NHW, 4.7% H/L, and 11.7% B/AA. Participant, informant, and clinician anchor variables were utilized to compare proportions of anchor agreement within and across ethnoracial groups. MCID on the Mini-Mental State Exam (MMSE) was estimated within each ethnoracial group and compared across the independent variables of anchor agreement and disease severity (cognitively normal (CN), mild cognitive impairment (MCI), and dementia) in 2x3 ANOVAs.

Participant age (M = 71.56, SD = 9.03) did not significantly differ across ethnoracial groups; years of education significantly differed across groups, p < .001, with NHW (M=15.83 SD=3.05), H/L (M=12.49, SD=5.01), and B/AA (M=14.42, SD=3.22). Across all three anchors (participant, informant, clinician), unanimous agreement about the presence or absence of a decline in functioning was present in about 75.1% of the full sample. To further explore agreement differences across groups, anchor agreement was classified into a 3-level variable: 1) agreement that the participant remained stable over time, 2) agreement that the participant declined, and 3) disagreement. The proportion of each level within each ethnoracial group was significantly different, (x2(4, n = 22,043) = 179.16, p < .001, phi = .09, NHW (34.5% agreement-stable, 41.4% agreement-declined, 24.1% disagreement), H/L (30.5%, 42.6%, 26.9%, respectively), and B/AA (42.2%, 28.1%, 29.7%, respectively). MCID estimates on the MMSE followed similar trends within each ethnoracial group. There was a significant main effect of disease severity, such that MCID estimates increased in magnitude with increasing disease severity. There were no significant main effects of anchor agreement for any ethnoracial group. Within the NHW sample only, an interaction effect between diagnostic severity and anchor agreement was significant (p = .007).

Across ethnoracial groups, MCID estimates on the MMSE are reliably influenced by the severity of disease. However, the benefit of anchor-based MCID estimates may vary by ethnoracial group with respect to both anchor choice and use of anchor agreement. The origins of anchor disagreement and perceived stability in functioning warrant further exploration.

Metamemory is a component of metacognition that includes both the knowledge of factors that affect memory (i.e., declarative metamemory) and knowledge and application of factors in one's own learning and recall performance (i.e., procedural metamemory; Kreutzer et al., 1975). Previous researchers have examined children's metamemory through interviews and found that metamemory abilities are positively associated with age and performance on memory measures (see Godfrey et al., 2022 for review). However, there is not yet a standardized measure to evaluate children's metamemory. The current study aimed to examine the psychometric characteristics of a declarative metamemory questionnaire, the Measure of Metamemory (MoM-10), for children ages 6-12 years old. Based on previous research, we hypothesized that performance on the MoM-10 would not be associated with sex but would be positively associated with age and learning and memory performance.

A total of 75 English-speaking typically developing children between the ages of 6 to 12 years old were recruited for the current study (M age=9.1+1.92; females 49%). Participants completed the MoM-10 which assessed declarative metamemory via 10 multiple choice questions (accuracy score of 0 or 1 points per question) and required participants to provide an explanation for their multiple-choice answer (explanation score of 0, 1, or 2 points per question). The metamemory questionnaire provided two outcome variables: an Accuracy score of 10 possible points, and an Explanation score of 20 possible points. Additionally, participants completed a 3-trial pictorial learning/memory task which provided an Immediate Recall score and Delayed Recall score.

As hypothesized, there were no sex differences on the MoM-10 Accuracy scores (t(73)=0.71, p=0.48) or Explanation scores (t(73)=-73, p=0.47). Consistent with our hypothesis, age was significantly associated with Accuracy (r=0.31, p<0.01) and Explanation scores (r=0.79, p<0.001). Internal consistency of the MOM-10 was moderate for the Explanation score (Cronbach's alpha=0.68) and low for the Accuracy score (KR-20=0.54). Lastly, after controlling for age, participants' MoM-10 Accuracy score was significantly associated with Immediate Recall (r=0.32, p<0.01) on the learning/memory task and the Explanation scores were significantly associated with the Immediate Recall (r=0.36, p<0.01) and Delayed Recall scores (r=0.32, p<0.01) on the learning/memory task.

The current study presents an initial review of psychometric properties of a metamemory questionnaire for children ages 6 to 12 years old. Additionally, as hypothesized, these results suggest the MOM-10 performance is significantly positively associated with participants' age and immediate and delayed recall performance on a pictorial learning/memory task. These associations provide lines of evidence for convergent validity given the expected maturation of metamemory with both age and with improvements in actual memory performance. However, based on the low internal consistency of the accuracy scores, further refinement will be explored including possibly rephrasing questions from the current item set or perhaps excluding current items in future use of the scale.