Psychiatric prescribers typically assess adherence by patient or caregiver self-report. A new digital medicine (DM) technology provides objective data on adherence by using an ingestible event monitoring (IEM) sensor embedded within oral medication to track ingestion. Despite likely clinical benefit, adoption by prescribers will in part depend on attitudes toward and experience with digital health technology, learning style preference (LSP), and how the technology s utility and value are described.

is to identify attitudes, experiences, and proclivities toward DM platforms that may affect adoption of the IEM platform and provide direction on tailoring educational materials to maximize adoption. Methods A survey of prescribers treating seriously mentally ill patients was conducted to assess drivers/barriers to IEM adoption. Factor analysis was performed on 13 items representing prior experience with and attitudes toward DM. Factor scores were correlated with prescriber characteristics including attitude and experience with digital technologies, LSP, and level of focus on healthcare cost.

A total of 127 prescribers (56% female, 76% physicians, mean age 48.1yrs.) completed the survey. Over 90% agreed medication adherence is important, visits allow enough time to monitor adherence (84.1%), and tailoring treatment to level of adherence would be beneficial (92.9%). The majority (65.9%) preferred relying upon outcomes data as their learning style while 15.9% preferred opinion leader recommendations and 18.3% information about how the technology would affect practice efficiency. Factor analysis revealed four dimensions: Level of comfort with EHR; Concern over current ability to monitor medication adherence; Attitudes about value of DM applications; and Benefits vs cost of DM for payers. Women scored higher on attitudes about the value of digital applications (p<0.01). Providers who perceive non-adherence as costly, and those who believe DM could benefit providers and patients scored higher on the value of DM (p<.05). Those whose LSP focuses on improving efficiency and prescribers with a higher proportion of Medicaid/ uninsured patients displayed concern about their ability to monitor adherence (p<0.05). Willingness to be a Beta Test site for DM applications was positively correlated with concern about their ability to monitor adherence and attitudes about the value of DM (p <0.01).

Prescriber characteristics including LSP, focus on healthcare costs, and attitudes toward DM may be related to adoption of the IEM platform. Those with more Medicaid/ uninsured patients were more concerned about ability to monitor adherence while those focused-on cost and benefit to providers and patients viewed DM as part of a solution for managing outcomes and cost. Overall, LSP, patient panel size by payer type, and focus on healthcare cost containment should be considered when developing IEM provider training materials.

Otsuka Pharmaceutical Development & Commercialization, Inc.

People with CHD are at increased risk for executive functioning deficits. Meta-analyses of these measures in CHD patients compared to healthy controls have not been reported.

To examine differences in executive functions in individuals with CHD compared to healthy controls.

We performed a systematic review of publications from 1 January, 1986 to 15 June, 2020 indexed in PubMed, CINAHL, EMBASE, PsycInfo, Web of Science, and the Cochrane Library.

Inclusion criteria were (1) studies containing at least one executive function measure; (2) participants were over the age of three.

Data extraction and quality assessment were performed independently by two authors. We used a shifting unit-of-analysis approach and pooled data using a random effects model.

The search yielded 61,217 results. Twenty-eight studies met criteria. A total of 7789 people with CHD were compared with 8187 healthy controls. We found the following standardised mean differences: −0.628 (−0.726, −0.531) for cognitive flexibility and set shifting, −0.469 (−0.606, −0.333) for inhibition, −0.369 (−0.466, −0.273) for working memory, −0.334 (−0.546, −0.121) for planning/problem solving, −0.361 (−0.576, −0.147) for summary measures, and −0.444 (−0.614, −0.274) for reporter-based measures (p < 0.001).

Our analysis consisted of cross-sectional and observational studies. We could not quantify the effect of collinearity.

Individuals with CHD appear to have at least moderate deficits in executive functions. Given the growing population of people with CHD, more attention should be devoted to identifying executive dysfunction in this vulnerable group.

Even though sub-Saharan African women spend millions of person-hours per day fetching water and pounding grain, to date, few studies have rigorously assessed the energy expenditure costs of such domestic activities. As a result, most analyses that consider head-hauling water or hand pounding of grain with a mortar and pestle (pilão use) employ energy expenditure values derived from limited research. The current paper compares estimated energy expenditure values from heart rate monitors v. indirect calorimetry in order to understand some of the limitations with using such monitors to measure domestic activities.

This confirmation study estimates the metabolic equivalent of task (MET) value for head-hauling water and hand-pounding grain using both indirect calorimetry and heart rate monitors under laboratory conditions.

The study was conducted in Nampula, Mozambique.

Forty university students in Nampula city who recurrently engaged in water-fetching activities.

Including all participants, the mean MET value for head hauling 20 litres (20·5 kg, including container) of water (2·7 km/h, 0 % slope) was 4·3 (sd 0·9) and 3·7 (sd 1·2) for pilão use. Estimated energy expenditure predictions from a mixed model were found to correlate with observed energy expenditure (r2 0·68, r 0·82). Re-estimating the model with pilão use data excluded improved the fit substantially (r2 0·83, r 0·91).

The current study finds that heart rate monitors are suitable instruments for providing accurate quantification of energy expenditure for some domestic activities, such as head-hauling water, but are not appropriate for quantifying expenditures of other activities, such as hand-pounding grain.

To develop and validate the Discrepancy-based Evidence for Loss of Thinking Abilities (DELTA) score. The DELTA score characterizes the strength of evidence for cognitive decline on a continuous spectrum using well-established psychometric principles for improving detection of cognitive changes.

DELTA score development used neuropsychological test scores from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (two tests each from Memory, Executive Function, and Language domains). We derived regression-based normative reference scores using age, gender, years of education, and word-reading ability from robust cognitively normal ADNI participants. Discrepancies between predicted and observed scores were used for calculating the DELTA score (range 0–15). We validated DELTA scores primarily against longitudinal Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Functional Activities Questionnaire (FAQ) scores (baseline assessment through Year 3) using linear mixed models and secondarily against cross-sectional Alzheimer’s biomarkers.

There were 1359 ADNI participants with calculable baseline DELTA scores (age 73.7 ± 7.1 years, 55.4% female, 100% white/Caucasian). Higher baseline DELTA scores (stronger evidence of cognitive decline) predicted higher baseline CDR-SOB (ΔR2 = .318) and faster rates of CDR-SOB increase over time (ΔR2 = .209). Longitudinal changes in DELTA scores tracked closely and in the same direction as CDR-SOB scores (fixed and random effects of mean + mean-centered DELTA, ΔR2 > .7). Results were similar for FAQ scores. High DELTA scores predicted higher PET-Aβ SUVr (ρ = 324), higher CSF-pTau/CSF-Aβ ratio (ρ = .460), and demonstrated PPV > .9 for positive Alzheimer’s disease biomarker classification.

Data support initial development and validation of the DELTA score through its associations with longitudinal functional changes and Alzheimer’s biomarkers. We provide several considerations for future research and include an automated scoring program for clinical use.

The American Academy of Neurology (AAN) updated their practice parameters in the evaluation of driving risk in dementia and developed a Caregiver Driving Safety Questionnaire, detailed in their original manuscript (Iverson Gronseth, Reger, Classen, Dubinsky, & Rizzo, 2010). They described four factors associated with decreased driving ability in dementia patients: history of crashes or citations, informant-reported concerns, reduced mileage, and aggressive driving.

An informant-reported AAN Caregiver Driving Safety Questionnaire was designed with these elements, and the current study was the first to explore the factor structure of this questionnaire. Additionally, we examined associations between these factors and cognitive and behavioral measures in patients with mild cognitive impairment or early Alzheimer's disease and their informants.

Exploratory factor analysis revealed a four-component structure, consistent with the theory behind the AAN scale composition. These four factor scores also were significantly associated with performance on cognitive screening instruments and informant reported behavioral dysfunction. Regressions revealed that behavioral dysfunction predicted caregiver concerns about driving safety beyond objective patient cognitive dysfunction.

In this first known quantitative exploration of the scale, our results support continued use of this scale in office driving safety assessments. Additionally, patient behavioral changes predicted caregiver concerns about driving safety over and above cognitive status, which suggests that caregivers may benefit from psychoeducation about cognitive factors that may negatively impact driving safety.