Demonstrating the impact of implementation science presents a new frontier for the field, and operationalizing downstream impact is challenging. The Translational Science Benefits Model (TSBM) offers a new approach for assessing and demonstrating research impact. Here we describe integration of the TSBM into a mentored training network.

Washington University’s Clinical and Translational Science Awards TSBM team collaborated with a National Institute of Mental Health-supported training program, the Implementation Research Institute (IRI), a 2-year training institute in mental health implementation science. This partnership included three phases: (1) introductory workshop on research impact, (2) workshop on demonstrating impact, and (3) sessions to guide dissemination, including interactive tools and consultation with the TSBM research team. Fifteen IRI alumni were invited to participate in the pilot; six responded agreeing to participate in the training, develop TSBM case studies, and provide feedback about their experiences. Participants applied the tools and gave feedback on design, usability, and content. We present their case studies and describe how the IRI used the results to incorporate TSBM into future trainings.

The case studies identified 40 benefits spanning all four TSBM domains, including 21 community, 11 policy, five economic, and three clinical benefits. Participants reported that TSBM training helped them develop a framework for talking about impact. Selecting benefits was challenging for early-stage projects, suggesting the importance of early training.

The case studies showcased the institute’s impact and the fellows’ work and informed refinement of tools and methods for incorporating TSBM into future IRI training.

Cognitive tests requiring spoken responses, such as paragraph recall, are rich in cognitive-related information that is not captured using traditional scoring methods. This study aimed to determine if linguistic features embedded in spoken responses may differentiate between individuals who are and are not cognitively impaired.

Participants in the Long Life Family Study completed a neuropsychological assessment which included the WMS-R Logical Memory I paragraph recall. For a subset of participants (N=709), test responses were digitally recorded and manually transcribed. We used Linguistic Inquiry Word Count, a text analysis program, to quantify word counts, grammatical features (e.g, prepositions, verb tenses), and the use of content words related to specific semantic categories (e.g., work-related, numbers) for immediate (IR) and delayed recall (DR). We used regression models with Generalized Estimating Equations adjusted by age, sex, education, and within-family correlation to select features associated with cognitive status (normal cognition [NC] versus cognitive impairment [CI]; Bonferroni-corrected threshold p<0.001). Next, we developed a “polyfeature score” (PFS) for both immediate and delayed recall, each calculated as a weighted sum of the selected linguistic features. We then built a logistic regression model to evaluate the predictive value of each PFS for identifying cognitively impaired individuals. In secondary analyses, we used regression models as above to identify features associated with mild cognitive impairment subtype (amnestic [aMCI] versus nonamnestic [naMCI]; threshold p< .05).

The sample included 599 participants with NC and 110 with CI (mean age = 72.3 ± 11.0 years, 54% female). The regression identified 8 linguistic features for IR and 7 for DR that significantly predicted cognitive status. Decreased use of content words related to work (e.g., employed, school, police) and biological processes (e.g., cook, cafeteria, eat) and the use of negations (e.g., no, not, can’t) were predictive of cognitive impairment in both recall conditions. In contrast, the use of other content word categories were predictive of cognitive status in only one recall condition (IR: leisure, cognitive processes, space; DR: drives, number). The use of fewer prepositions in IR, more first-person pronouns in DR, and fewer words in the past tense in DR were each associated with cognitive impairment. Word count was not predictive of cognitive status. Both PFSs were highly associated with cognitive status (PFS_IR ß= 0.74, p< 0.001; PFS_DR ß= 0.86, p= 0.001) with high discriminative value (PFS_IR AUC= 0.93, sensitivity = 0.81, specificity= 0.91; PFS_DR AUC= 0.95, sensitivity= 0.77, specificity= 0.88). In the CI subset, linguistic features differed between those classified as aMCI (n= 24) and naMCI (n= 40). Two function word categories predicted aMCI in IR whereas decreased word count, two function word categories, and two content word categories predicted aMCI in DR (all p< .05)

Linguistic features from paragraph recall provide high predictive value for classifying cognitive status increasing its potential as a cognitive screener in clinical settings. Additionally, each recall condition identified unique linguistic features associated with cognitive impairment which may aid differentiation of cognitive impairment subtypes and elucidate processes underlying deficits in learning and recall.

Deaths from suicides, drug poisonings, and alcohol-related diseases (‘deaths of despair’) are well-documented among working-age Americans, and have been hypothesized to be largely specific to the U.S. However, support for this assertion–and associated policies to reduce premature mortality–requires tests concerning these deaths in other industrialized countries, with different institutional contexts. We tested whether the concentration and accumulation of health and social disadvantage forecasts deaths of despair, in New Zealand and Denmark.

We used nationwide administrative data. Our observation period was 10 years (NZ = July 2006–June 2016, Denmark = January 2007–December 2016). We identified all NZ-born and Danish-born individuals aged 25–64 in the last observation year (NZ = 1 555 902, Denmark = 2 541 758). We ascertained measures of disadvantage (public-hospital stays for physical- and mental-health difficulties, social-welfare benefit-use, and criminal convictions) across the first nine years. We ascertained deaths from suicide, drugs, alcohol, and all other causes in the last year.

Deaths of despair clustered within a population segment that disproportionately experienced multiple disadvantages. In both countries, individuals in the top 5% of the population in multiple health- and social-service sectors were at elevated risk for deaths from suicide, drugs, and alcohol, and deaths from other causes. Associations were evident across sex and age.

Deaths of despair are a marker of inequalities in countries beyond the U.S. with robust social-safety nets, nationwide healthcare, and strong pharmaceutical regulations. These deaths cluster within a highly disadvantaged population segment identifiable within health- and social-service systems.

Leukocyte telomere length (LTL) is a widely hypothesized biomarker of biological aging. Persons with shorter LTL may have a greater likelihood of developing dementia. We investigate whether LTL is associated with cognitive function, differently for individuals without cognitive impairment versus individuals with dementia or incipient dementia.

Enrolled subjects belong to the Long Life Family Study (LLFS), a multi-generational cohort study, where enrollment was predicated upon exceptional family longevity. Included subjects had valid cognitive and telomere data at baseline. Exclusion criteria were age ≤ 60 years, outlying LTL, and missing sociodemographic/clinical information. Analyses were performed using linear regression with generalized estimating equations, adjusting for sex, age, education, country, generation, and lymphocyte percentage.

Older age and male gender were associated with shorter LTL, and LTL was significantly longer in family members than spouse controls (p < 0.005). LTL was not associated with working or episodic memory, semantic processing, and information processing speed for 1613 cognitively unimpaired individuals as well as 597 individuals with dementia or incipient dementia (p < 0.005), who scored significantly lower on all cognitive domains (p < 0.005).

Within this unique LLFS cohort, a group of families assembled on the basis of exceptional survival, LTL is unrelated to cognitive ability for individuals with and without cognitive impairment. LTL does not change in the context of degenerative disease for these individuals who are biologically younger than the general population.