The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties.

MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart.

All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability.

Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

Symptom clustering research provides a unique opportunity for understanding complex medical conditions. The objective of this study was to apply a variable-centered analytic approach to understand how symptoms may cluster together, within and across domains of functioning in mild cognitive impairment (MCI) and dementia, to better understand these conditions and potential etiological, prevention, and intervention considerations.

Cognitive, motor, sensory, emotional, and social measures from the NIH Toolbox were analyzed using exploratory factor analysis (EFA) from a dataset of 165 individuals with a research diagnosis of either amnestic MCI or dementia of the Alzheimer’s type.

The six-factor EFA solution described here primarily replicated the intended structure of the NIH Toolbox with a few deviations, notably sensory and motor scores loading onto factors with measures of cognition, emotional, and social health. These findings suggest the presence of cross-domain symptom clusters in these populations. In particular, negative affect, stress, loneliness, and pain formed one unique symptom cluster that bridged the NIH Toolbox domains of physical, social, and emotional health. Olfaction and dexterity formed a second unique cluster with measures of executive functioning, working memory, episodic memory, and processing speed. A third novel cluster was detected for mobility, strength, and vision, which was considered to reflect a physical functioning factor. Somewhat unexpectedly, the hearing test included did not load strongly onto any factor.

This research presents a preliminary effort to detect symptom clusters in amnestic MCI and dementia using an existing dataset of outcome measures from the NIH Toolbox.

A critical need in the neuropsychology field is development and validation of efficient, scalable assessments of cognition. The Mobile Toolbox (MTB), a novel suite of mobile device-compatible, app-based cognitive assessments, was developed to address this need. The goals of this study were (1) To collect longitudinal normative data for the MTB assessments in a large, ethnoculturally and educationally diverse cohort; (2) To assess the feasibility and usability of remote assessment using MTB.

Participants were recruited from the UCSF Brain Health Registry (BHR), an online cohort (N>100,000) that collects longitudinal cognitive, functional, behavioral, and health data using online neuropsychological tests and self- and study-partner report surveys. BHR participants who opted to learning about additional research opportunities were sent automated email invitations to enroll in the MTB study. Those who indicated study interest were provided instructions within the BHR online portal for downloading the MTB app. All participants had the opportunity to complete a single baseline administration of MTB (Word Meaning, Sequences, Spelling, Arranging Pictures, Arrow Matching, Faces and Names, Shape-Color Sorting, Number Match). Those who completed the baseline assessment within three days were invited to continue into the longitudinal study, where they complete MTB assessments at a single, short-term timepoint (day 7, 14, or 21; study arms sequentially assigned), and then at 6-month intervals. Enrollment across demographic groups was monitored, and study invitations were sent to specific demographic groups, with the goal of enrolling a sample of 800 participants in the longitudinal study: equal distribution across eight, 10-year age bands (ages 18-80+); 60% with <16 years of education; 10% non-Latinx Black, 15% Latinx, and 5% non-White other ethnocultural identity.

Between January-June 2022, 48,110 BHR participants were invited to the MTB study. Of those, 8294 (17%) expressed interest, 3401 (7%) completed the baseline assessment, 850 (1.8%) were assigned to the longitudinal study, and 782 (1.6%) completed a short-term longitudinal assessment. Study staff received 797 help tickets submitted by participants asking for email support to complete MTB. The baseline cohort had and average age of 64 years and an average of 16.6 years of education, 76.2% female, 2.1% non-Latinx Black, 7.1% Latinx, 86.8% non-Latinx White, and 4% from other ethnocultural groups. The longitudinal cohort had an average age of 62.3 years and an average of 16.1 years of education, 80% female, 2.8% non-Latinx Black, 8.5% Latinx, 83.5% non-Latinx White; and 5% other ethnocultural group. Compared to those invited to the study, those who enrolled in the longitudinal study were older, had higher educational attainment, and were more likely to be female and self-identify as non-Latinx White (p<0.05 for all).

Efficient enrollment and task completion of a large cohort in a novel, app-based mobile cognitive assessment is feasible in a completely remote setting. Most participants were able to complete MTB without individual support, indicating good usability. This approach can be scaled up to efficiently assess cognition in many research and healthcare settings. A remaining challenge is achieving robust ethnocultural and educational diversity.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Hispanics/Latinos are the largest and fastest-growing minority population in the United States. To facilitate appropriate outcome assessment of this expanding population, the NIH Toolbox for Assessment of Neurological and Behavioral Function® (NIH Toolbox®) was developed with particular attention paid to the cultural and linguistic needs of English- and Spanish-speaking Hispanics/Latinos.

A Cultural Working Group ensured that all included measures were appropriate for use with Hispanics/Latinos in both English and Spanish. In addition, a Spanish Language Working Group assessed all English-language NIH Toolbox measures for translatability.

Measures were translated following the Functional Assessment of Chronic Illness Therapy (FACIT) translation methodology for instances where language interpretation could impact scores, or a modified version thereof for more simplified translations. The Spanish versions of the NIH Toolbox Cognition Battery language measures (i.e., Picture Vocabulary Test, Oral Reading Recognition Test) were developed independently of their English counterparts.

The Spanish-language version of the NIH Toolbox provides a much-needed set of tools that can be selected as appropriate to complement existing protocols being conducted with the growing Hispanic/Latino population in the United States.