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.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder commonly associated with relative impairments on processing speed, working memory, and/or executive functioning. Anxiety commonly co-occurs with ADHD and may also adversely affect these cognitive functions. Additionally, language status (i.e., monolingualism vs bilingualism) has been shown to affect select cognitive domains across an individual’s lifespan. Yet, few studies have examined the potential effects of the interaction between anxiety and language status on various cognitive domains among people with ADHD. Thus, the current study investigated the effects of the interaction of anxiety and language status on processing speed, working memory, and executive functioning among monolingual and bilingual individuals with ADHD.

The sample comprised of 407 consecutive adult patients diagnosed with ADHD. When asked about their language status, 67% reported to be monolingual (English). The Mean age of individuals was 27.93 (SD = 6.83), mean education of 15.8 years (SD = 2.10), 60% female, racially diverse with 49% Non-Hispanic White, 22% Non-Hispanic Black, 13% Hispanic/Latinx, 9% Asian/Pacific Islander, and 6% other race/ethnicity. Processing speed, working memory, and executive function were measured via the Wechsler Adult Intelligence Scale-Fourth Edition Processing Speed Index, Working Memory Index, and Trail Making Test B, respectively. Anxiety was measured via the Beck Anxiety Inventory (BAI). Three separate linear regression models examined the interaction between anxiety (moderator) and cognition (processing speed, working memory, and executive function) on language. Models included sex/gender and education as covariates with Processing Speed Index and Working Memory Index as the outcomes. Age, sex/gender, and education were used as covariates when Trail Making Test B was the outcome.

Monolingual and bilingual patients differed in mean age (p < .05) but did not differ in level of anxiety, education, or sex/gender. Overall, anxiety was not associated with processing speed, working memory, and executive function. However, the interaction between anxiety and language status was significantly associated with processing speed (ß = -0.37, p < .05), and executive functioning (ß = 0.82, p < .05). No associations were found when anxiety was added as a moderator for the associations between language and working memory.

This study found that anxiety moderated the relationship between language status and select cognitive domains (i.e., processing speed and executive functioning) among individuals with ADHD. Specifically, anxiety had a greater association on processing speed and executive functioning performance for bilinguals rather than monolinguals. Future detailed studies are needed to better understand how anxiety modifies the relationship between language and cognitive performance outcomes over time amongst a linguistically diverse sample.

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Although research has shown that exposure to potentially traumatic and morally injurious events is associated with psychological symptoms among veterans, knowledge regarding functioning impacts remains limited.

A population-based sample of post-9/11 veterans completed measures of intimate relationship, health, and work functioning at approximately 9, 15, 21, and 27 months after leaving service. Moral injury, posttraumatic stress, and depression were assessed at ~9 months post-separation. We used Latent Growth Mixture Models to identify discrete classes characterized by unique trajectories of change in functioning over time and to examine predictors of class membership.

Veterans were assigned to one of four functioning trajectories: high and stable, high and decreasing, moderate and increasing, and moderate and stable. Whereas posttraumatic stress, depression, and moral injury associated with perpetration and betrayal predicted worse outcomes at baseline across multiple functioning domains, moral injury associated with perpetration and depression most reliably predicted assignment to trajectories characterized by relatively poor or declining functioning.

Moral injury contributes to functional problems beyond what is explained by posttraumatic stress and depression, and moral injury due to perpetration and depression most reliably predicted assignment to trajectories characterized by functional impairment over time.