Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = −0.07, p = 0.02) and PFI (ß = −0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = −0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = −1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.

Antibiotic overuse is common across walk-in clinics, but it is unclear which stewardship metrics are most effective for audit and feedback. In this study, we assessed the validity of a metric that captures antibiotic prescribing for respiratory tract diagnoses (RTDs).

We performed a mixed-methods study to evaluate an RTD metric, which quantified the frequency at which a provider prescribed antibiotics for RTD visits after excluding visits with complicating factors.

Seven walk-in clinics across an integrated healthcare system.

We included clinic visits during 2018–2022. We also conducted 17 semi-structured interviews with 10 unique providers to assess metric acceptability.

There were 331,496 visits; 120,937 (36.5%) met RTD criteria and 44,382 (36.7%) of these received an antibiotic. Factors associated with an increased odds of antibiotic use for RTDs included patient age ≥ 65 (OR = 1.40; 95% CI 1.30–1.51), age 0–17 (1.55, 95% CI 1.50–1.60), and ≥1 comorbidity (OR = 1.22; 95% CI = 1.15–1.29). After stratifying providers by their antibiotic-prescribing frequency for RTDs, patient case-mix was similar across tertiles. However, the highest tertile of prescribers more frequently coded suppurative otitis media and more frequently prescribed antibiotics for antibiotic-nonresponsive conditions (eg, viral infections). There was no correlation between antibiotic prescribing for RTDs and the frequency of return visits (r = 0.01, P = 0.96). Interviews with providers demonstrated the acceptability of the metric as an assessment tool.

A provider-level metric that quantifies the frequency of antibiotic prescribing for all RTDs has both construct and face validity. Future studies should assess whether this type of metric is an effective feedback tool.

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.

Future events can spring to mind unbidden in the form of involuntary mental images also known as ‘flashforwards’, which are deemed important for understanding and treating emotional distress. However, there has been little exploration of this form of imagery in youth, and even less so in those with high psychopathology vulnerabilities (e.g. due to developmental differences associated with neurodiversity or maltreatment).

We aimed to test whether flashforwards are heightened (e.g. more frequent and emotional) in autistic and maltreatment-exposed adolescents relative to typically developing adolescents. We also explored their associations with anxiety/depression symptoms.

A survey including measures of flashforward imagery and mental health was completed by a group of adolescents (n=87) aged 10–16 (and one of their caregivers) who met one of the following criteria: (i) had a diagnosis of autism spectrum disorder; (ii) a history of maltreatment; or (ii) no autism/maltreatment.

Flashforwards (i) were often of positive events and related to career, education and/or learning; with phenomenological properties (e.g. frequency and emotionality) that were (ii) not significantly different between groups; but nevertheless (iii) associated with symptoms of anxiety across groups (particularly for imagery emotionality), even after accounting for general trait (non-future) imagery vividness.

As a modifiable cognitive risk factor, flashforward imagery warrants further consideration for understanding and improving mental health in young people. This implication may extend to range of developmental backgrounds, including autism and maltreatment.

Knowledge of sex differences in risk factors for posttraumatic stress disorder (PTSD) can contribute to the development of refined preventive interventions. Therefore, the aim of this study was to examine if women and men differ in their vulnerability to risk factors for PTSD.

As part of the longitudinal AURORA study, 2924 patients seeking emergency department (ED) treatment in the acute aftermath of trauma provided self-report assessments of pre- peri- and post-traumatic risk factors, as well as 3-month PTSD severity. We systematically examined sex-dependent effects of 16 risk factors that have previously been hypothesized to show different associations with PTSD severity in women and men.

Women reported higher PTSD severity at 3-months post-trauma. Z-score comparisons indicated that for five of the 16 examined risk factors the association with 3-month PTSD severity was stronger in men than in women. In multivariable models, interaction effects with sex were observed for pre-traumatic anxiety symptoms, and acute dissociative symptoms; both showed stronger associations with PTSD in men than in women. Subgroup analyses suggested trauma type-conditional effects.

Our findings indicate mechanisms to which men might be particularly vulnerable, demonstrating that known PTSD risk factors might behave differently in women and men. Analyses did not identify any risk factors to which women were more vulnerable than men, pointing toward further mechanisms to explain women's higher PTSD risk. Our study illustrates the need for a more systematic examination of sex differences in contributors to PTSD severity after trauma, which may inform refined preventive interventions.

Anxiety in pregnancy and after giving birth (the perinatal period) is highly prevalent but under-recognised. Robust methods of assessing perinatal anxiety are essential for services to identify and treat women appropriately.

To determine which assessment measures are most psychometrically robust and effective at identifying women with perinatal anxiety (primary objective) and depression (secondary objective).

We conducted a prospective longitudinal cohort study of 2243 women who completed five measures of anxiety and depression (Generalized Anxiety Disorder scale (GAD) two- and seven-item versions; Whooley questions; Clinical Outcomes in Routine Evaluation (CORE-10); and Stirling Antenatal Anxiety Scale (SAAS)) during pregnancy (15 weeks, 22 weeks and 31 weeks) and after birth (6 weeks). To assess diagnostic accuracy a sample of 403 participants completed modules of the Mini-International Neuropsychiatric Interview (MINI).

The best diagnostic accuracy for anxiety was shown by the CORE-10 and SAAS. The best diagnostic accuracy for depression was shown by the CORE-10, SAAS and Whooley questions, although the SAAS had lower specificity. The same cut-off scores for each measure were optimal for identifying anxiety or depression (SAAS ≥9; CORE-10 ≥9; Whooley ≥1). All measures were psychometrically robust, with good internal consistency, convergent validity and unidimensional factor structure.

This study identified robust and effective methods of assessing perinatal anxiety and depression. We recommend using the CORE-10 or SAAS to assess perinatal anxiety and the CORE-10 or Whooley questions to assess depression. The GAD-2 and GAD-7 did not perform as well as other measures and optimal cut-offs were lower than currently recommended.

Neuropsychiatric symptoms due to Alzheimer’s disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms is needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment.

The identified sample includes those from the NACC UDS (all versions) with complete data on the Neuropsychiatric Inventory Questionnaire (NPI-Q) at initial visit. The NPI-Q is an informant-based estimation of the presence and severity of neuropsychiatric symptoms (delusions, hallucinations, agitation or aggression, depression or dysphoria, anxiety, elation or euphoria, apathy or indifference, disinhibition, irritability or lability, motor disturbance, nighttime behaviors, appetite and eating problems). The following inclusionary criteria were applied for sample identification: age 50+; cognitive status of MCI or dementia; AD was the primary or contributing cause of observed impairment; and at least one symptom on the NPI-Q was endorsed. Participants were excluded if they endorsed “unknown” or “not available” on any NPI-Q items. The final sample (n = 12,507) consisted of older adults (Mage=73.94, SDage=9.41; 46.2% male, 53.8% female) who predominantly identified as non-Hispanic white (NHW) (74.5% NHW, 10.9% non-Hispanic Black, 8.5% other, 5.8% Hispanic white, .3% Hispanic Black). The majority of the sample met criteria for dementia (77.6% dementia, 22.4% MCI) and AD was the presumed primary etiology in 93.9%.

The eLasso method was used to estimate the binary network, wherein nodes represent NPI-Q variables and edges represent their pairwise dependency after controlling for all other symptom variables in the network. In other words, the network represents the conditional probability of an observed binary variable (e.g., presence/absence of delusions) given all other measured variables (e.g., presence/absence of all other NPI-Q symptoms) (Finnemann et al., 2021; van Borkulo et al., 2014). Strength centrality and expected influence were calculated to determine relative importance of each symptom variable in the network. Network accuracy was examined with methods recommended by Epskamp et al. (2018), including edge-weight accuracy, centrality stability, and difference tests.

Edge weights and node centrality (CS(cor=.7)=.75) were stable and interpretable. The network (M=.28) consisted of mostly positive edges and some negative edges. The strongest edges linked nodes within symptom domain (e.g., strong positive associations among externalizing symptoms). Disinhibition and agitation/aggression were the most central and influential symptoms in the network, respectively. Depression or dysphoria was the most frequently endorsed symptom, followed by anxiety, apathy or indifference, and irritability or lability.

Endorsed disinhibition and agitation yielded a higher probability of additional neuropsychiatric symptoms and influenced the activation, persistence, and remission of other neuropsychiatric symptoms within the network. Thus, interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Depression or dysphoria, while highly endorsed, was least influential in the network. This may suggest that depression and dysphoria are common, but not central neuropsychiatric features of AD pathology. Future work will compare neuropsychiatric symptom networks across racial and ethnic groups and between MCI and dementia.

The brain is reliant on mitochondria to carry out a host of vital cellular functions (e.g., energy metabolism, respiration, apoptosis) to maintain neuronal integrity. Clinically relevant, dysfunctional mitochondria have been implicated as central to the pathogenesis of Alzheimer’s disease (AD). Phosphorous magnetic resonance spectroscopy (31p MRS) is a non-invasive and powerful method for examining in vivo mitochondrial function via high energy phosphates and phospholipid metabolism ratios. At least one prior 31p MRS study found temporal-frontal differences for high energy phosphates in persons with mild AD. The goal of the current study was to examine regional (i.e., frontal, temporal) 31p MRS ratios of mitochondrial function in a sample of older adults at-risk for AD. Given the high energy consumption in temporal lobes (i.e., hippocampus) and preferential age-related changes in frontal structure-function, we predicted 31p MRS ratios of mitochondrial function would be greater in temporal as compared to frontal regions.

The current study leveraged baseline neuroimaging data from an ongoing multisite study at the University of Florida and University of Arizona. Participants were older adults with memory complaints and a first-degree family history of AD [N = 70; mean [M] age [years] = 70.9, standard deviation [SD] =5.1; M education [years] = 16.2, SD = 2.2; M MoCA = 26.5, SD = 2.4; 61.4% female; 91.5% non-latinx white]. To achieve optimal sensitivity, we used a single voxel method to examine 31p MRS ratios (bilateral prefrontal and left temporal). Mitochondrial function was estimated by computing 5 ratios for each voxel: summed adenosine triphosphate to total pooled phosphorous (ATP/TP; momentary energy), ATP to inorganic phosphate (ATP/Pi; energy consumption), phosphocreatine to ATP (PCr/ATP; energy reserve), phosphocreatine to inorganic phosphate (PCr/Pi; oxidative phosphorylation), and phosphomonoesters to phosphodiesters (PME/PDE; cellular membrane turnover rate). All ratios were corrected for voxel size and cerebrospinal fluid fraction. Separate repeated measures analyses of variance controlling for scanner site differences (RM ANCOVAs) were performed.

31p MRS ratios were unrelated to demographic characteristics and were not included as additional covariates in analyses. Results of separate RM ANCOVAs revealed all 31p MRS ratios of mitochondrial function were greater in left temporal relative to bilateral prefrontal voxel: ATP/TP (p < .001), ATP/Pi (p = .001), PCr/ATP (p = .004), PCr/Pi (p = .004), and PME/PDE (p = .017). Effect sizes (partial eta squared) ranged from 0.6-.20.

Consistent and extending one prior study, all 31p MRS ratios of mitochondrial function were greater in temporal as compared to frontal regions in older adults at-risk for AD. This may in part be related to the intrinsically high metabolic rate of the temporal region and preferential age-related changes in frontal structure-function. Alternatively, findings may reflect the influence of unaccounted factors (e.g., hemodynamics, auditory stimulation). Longitudinal study designs may inform whether patterns of mitochondrial function across different brain regions are present early in development, occur across the lifespan, or some combination. In turn, this may inform future studies examining differences in mitochondrial function (as measured using 31p MRS) in AD.

We assessed the implementation of telehealth-supported stewardship activities in acute-care units and long-term care (LTC) units in Veterans’ Administration medical centers (VAMCs).

Before-and-after, quasi-experimental implementation effectiveness study with a baseline period (2019–2020) and an intervention period (2021).

The study was conducted in 3 VAMCs without onsite infectious disease (ID) support.

The study included inpatient providers at participating sites who prescribe antibiotics.

During 2021, an ID physician met virtually 3 times per week with the stewardship pharmacist at each participating VAMC to review patients on antibiotics in acute-care units and LTC units. Real-time feedback on prescribing antibiotics was given to providers. Additional implementation strategies included stakeholder engagement, education, and quality monitoring.

The reach–effectiveness–adoption–implementation–maintenance (RE-AIM) framework was used for program evaluation. The primary outcome of effectiveness was antibiotic days of therapy (DOT) per 1,000 days present aggregated across all 3 sites. An interrupted time-series analysis was performed to compare this rate during the intervention and baseline periods. Electronic surveys, periodic reflections, and semistructured interviews were used to assess other RE-AIM outcomes.

The telehealth program reviewed 502 unique patients and made 681 recommendations to 24 providers; 77% of recommendations were accepted. After program initiation, antibiotic DOT immediately decreased in the LTC units (−30%; P < .01) without a significant immediate change in the acute-care units (+16%; P = .22); thereafter DOT remained stable in both settings. Providers generally appreciated feedback and collaborative discussions.

The implementation of our telehealth program was associated with reductions in antibiotic use in the LTC units but not in the smaller acute-care units. Overall, providers perceived the intervention as acceptable. Wider implementation of telehealth-supported stewardship activities may achieve reductions in antibiotic use.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.