Exposure to maternal mental illness during foetal development may lead to altered development, resulting in permanent changes in offspring functioning.

To assess whether there is an association between prenatal maternal psychiatric disorders and offspring behavioural problems in early childhood, using linked health administrative data and the Australian Early Development Census from New South Wales, Australia.

The sample included all mother–child pairs of children who commenced full-time school in 2009 in New South Wales, and met the inclusion criteria (N = 69 165). Univariable logistic regression analysis assessed unadjusted associations between categories of maternal prenatal psychiatric disorders with indicators of offspring behavioural problems. Multivariable logistic regression adjusted the associations of interest for psychiatric categories and a priori selected covariates. Sensitivity analyses included adjusting the final model for primary psychiatric diagnoses and assessing association of interest for effect modification by child's biological gender.

Children exposed in the prenatal period to maternal psychiatric disorders had greater odds of being developmentally vulnerable in their first year of school. Children exposed to maternal anxiety disorders prenatally had the greatest odds for behavioural problems (adjusted odds ratio 1.98; 95% CI 1.43–2.69). A statistically significant interaction was found between child biological gender and prenatal hospital admissions for substance use disorders, for emotional subdomains, aggression and hyperactivity/inattention.

Children exposed to prenatal maternal mental illness had greater odds for behavioural problems, independent of postnatal exposure. Those exposed to prenatal maternal anxiety were at greatest risk, highlighting the need for targeted interventions for, and support of, families with mental illness.

To evaluate the motor proficiency, identify risk factors for abnormal motor scores, and examine the relationship between motor proficiency and health-related quality of life in school-aged patients with CHD.

Patients ≥ 4 years old referred to the cardiac neurodevelopmental program between June 2017 and April 2020 were included. Motor skills were evaluated by therapist-administered Bruininks-Oseretsky Test of Motor Proficiency Second-Edition Short Form and parent-reported Adaptive Behavior Assessment System and Patient-Reported Outcomes Measurement Inventory System Physical Functioning questionnaires. Neuropsychological status and health-related quality of life were assessed using a battery of validated questionnaires. Demographic, clinical, and educational variables were collected from electronic medical records. General linear modelling was used for multivariable analysis.

The median motor proficiency score was the 10th percentile, and the cohort (n = 272; mean age: 9.1 years) scored well below normative values on all administered neuropsychological questionnaires. In the final multivariable model, worse motor proficiency score was associated with family income, presence of a genetic syndrome, developmental delay recognised in infancy, abnormal neuroimaging, history of heart transplant, and executive dysfunction, and presence of an individualised education plan (p < 0.03 for all predictors). Worse motor proficiency correlated with reduced health-related quality of life. Parent-reported adaptive behaviour (p < 0.001) and physical functioning (p < 0.001) had a strong association with motor proficiency scores.

This study highlights the need for continued motor screening for school-aged patients with CHD. Clinical factors, neuropsychological screening results, and health-related quality of life were associated with worse motor proficiency.

To investigate COVID-19 disparities between Hispanic/Latino persons (H/L) and non-H/L persons in an agricultural community by examining behavioral and demographic differences.

In September 2020, we conducted Community Assessments for Public Health Emergency Response in Wenatchee and East Wenatchee, Washington, to evaluate differences between H/L and non-H/L populations in COVID-19 risk beliefs, prevention practices, household needs, and vaccine acceptability. We produced weighted sample frequencies.

More households from predominately H/L census blocks (H/L-CBHs) versus households from predominately non-H/L census blocks (non-H/L-CBHs) worked in essential services (79% versus 57%), could not telework (70% versus 46%), and reported more COVID-19 cases (19% versus 4%). More H/L-CBHs versus non-H/L-CBHs practiced prevention strategies: avoiding gatherings (81% versus 61%), avoiding visiting friends/family (73% versus 36%), and less restaurant dining (indoor 24% versus 39%). More H/L-CBHs versus non-H/L-CBHs needed housing (16% versus 4%) and food assistance (19% versus 6%). COVID-19 vaccine acceptance in H/L-CBHs and non-H/L-CBHs was 42% versus 46%, respectively.

Despite practicing prevention measures with greater frequency, H/L-CBHs had more COVID-19 cases. H/L-CBHs worked in conditions with a higher likelihood of exposure. H/L-CBHs had increased housing and food assistance needs due to the pandemic. COVID-19 vaccine acceptability was similarly low (<50%) between groups.

Pragmatic trials aim to speed translation to practice by integrating study procedures in routine care settings. This study evaluated implementation outcomes related to clinician and patient recruitment and participation in a trial of community paramedicine (CP) and presents successes and challenges of maintaining pragmatic study features.

Adults in the pre-hospital setting, emergency department (ED), or hospital being considered for referral to the ED/hospital or continued hospitalization for intermediate-level care were randomized 1:1 to CP care or usual care. Referral and enrollment data were tracked administratively, and patient characteristics were abstracted from the electronic health record (EHR). Enrolled patients completed baseline surveys, and a subset of intervention patients were interviewed. All CPs and a sample of clinicians and administrators were invited to complete a survey and interview.

Between January 2022 and February 2023, 240 enrolled patients (42% rural) completed surveys, and 22 completed an interview; 63 staff completed surveys and 20 completed an interview. Ninety-three clinicians in 27 departments made at least one referral. Factors related to referrals included program awareness and understanding the CP practice scope. Most patients were enrolled in the hospital, but characteristics were similar to the primary care population and included older and medically complex patients. Challenges to achieving representativeness included limited EHR infrastructure, constraints related to patient consenting, and clinician concerns about patient randomization disrupting preferred care.

Future pragmatic trials in busy clinical settings may benefit from regulatory policies and EHR capabilities that allow for real-world study conduct and representative participation. Trial registration: NCT05232799.

Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.

The aim of this study was to generate an experts’ consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs.

An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health.

Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general.

The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk.

This study aimed to estimate networks of depressive symptoms among Irish adults with and without diabetes at two time points and compare between the two groups at each time point using data from the Irish Longitudinal Study on Ageing (TILDA).

Participants were from Wave 1 (2009–2011) and Wave 4 (2016) of TILDA, with n = 639 participants with diabetes and n = 7,837 without diabetes at Wave 1, and n = 1,151 with diabetes and n = 4,531 without diabetes at Wave 4. Depressive symptoms were measured using the 8 items of the Center for Epidemiologic Studies Depression Scale. Network psychometric analysis was used to examine symptom centrality, symptom-level associations, and network comparisons at each time point.

Stable, strongly connected networks emerged for people with and without diabetes at both time points. The symptoms of feeling depressed, feeling like everything’s an effort, not enjoying life, feeling sad, and couldn’t get going were the most central nodes in all networks, which did not differ between people with and without diabetes. However, for people with diabetes, the network was more densely connected at Wave 4, when the sample was predominately people with newly diagnosed diabetes. Furthermore, the relationship between ‘felt lonely’ and ‘couldn’t get going’ and between ‘not enjoying life’ and ’sad’ was significantly stronger for people with diabetes than for those without.

This study provides a more detailed understanding of the structure of depressive symptoms at two time points in older Irish adults with and without type 1 or type 2 diabetes.

Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada.

We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models’ discriminative values using Uno’s c-statistic, comparing models with versus without PaSSV.

We included 86,142 patients (n = 18,387 in BC, n = 65,082 in Ontario, n = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable.

PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

To determine the association between blood markers of white matter injury (e.g., serum neurofilament light and phosphorylated neurofilament heavy) and a novel neuroimaging technique measuring microstructural white matter changes (e.g., diffusion kurtosis imaging) in regions (e.g., anterior thalamic radiation and uncinate fasciculus) known to be impacted in traumatic brain injury (TBI) and associated with symptoms common in those with chronic TBI (e.g., sleep disruption, cognitive and emotional disinhibition) in a heterogeneous sample of Veterans and non-Veterans with a history of remote TBI (i.e., >6 months).

Participants with complete imaging and blood data (N=24) were sampled from a larger multisite study of chronic mild-moderate TBI. Participants ranged in age from young to middle-aged (mean age = 34.17, SD age = 10.96, range = 19-58) and primarily male (66.7%). The number of distinct TBIs ranged from 1-5 and the time since most recent TBI ranged from 0-30 years. Scores on a cognitive screener (MoCA) ranged from 22-30 (mean = 26.75). We performed bivariate correlations with mean kurtosis (MK) in the anterior thalamic radiation (ATR; left, right) uncinate fasciculus (UF; left, right), and serum neurofilament light (NFL), and phosphorylated neurofilament heavy (pNFH). Both were log transformed for non-normality. Significance threshold was set at p<0.05.

pNFH was significantly and negatively correlated to MK in the right (r=-0.446) and left (r=-0.599) UF and right (r=-0.531) and left (r=-0.469) ATR. NFL showed moderate associations with MK in the right (r=-0.345) and left (r=-0.361) UF and little to small association in the right (r=-0.063) and left (r=-0.215) ATR. In post-hoc analyses, MK in both the left (r=0.434) and right (r=0.514) UF was positively associated with performance on a frontally-mediated list-learning task (California Verbal Learning Test, 2nd Edition; Trials 1-5 total).

Results suggest that serum pNFH may be a more sensitive blood marker of microstructural complexity in white matter regions frequently impacted by TBI in a chronic mild-moderate TBI sample. Further, it suggests that even years after a mild-moderate TBI, levels of pNFH may be informative regarding white matter integrity in regions related to executive functioning and emotional disinhibition, both of which are common presenting problems when these patients are seen in a clinical setting.

Illness perception, or the ways in which individuals understand and cope with injury, has been extensively studied in the broader medical literature and has been found to have important associations with clinical outcomes across a wide range of medical conditions. However, there is a dearth of knowledge regarding how perceptions of traumatic brain injury (TBI) influence outcome and recovery following injury, especially in military populations. The purpose of this study was to examine relationships between illness perception, as measured via symptom attribution, and neurobehavioral and neurocognitive outcomes in Veterans with TBI history.

This cross-sectional study included 44 treatment-seeking Veterans (86.4% male, 65.9% white) with remote history of TBI (75.0% mild TBI). All Veterans were referred to the TBI Cognitive Rehabilitation Clinic at VA San Diego and completed a clinical interview, self-report questionnaires, and a neuropsychological assessment. A modified version of the Neurobehavioral Symptom Inventory (NSI) was administered to assess neurobehavioral symptom endorsement and symptom attribution. Symptom attribution was assessed by having participants rate whether they believe each NSI item was caused by TBI. A total symptom attribution score was computed, as well as the standard NSI total and symptom cluster scores (i.e., vestibular, somatic, cognitive, and affective symptom domains). Three cognitive composite scores (representing mean performance) were also computed, including memory, attention/processing speed, and executive functioning. Participants were excluded if they did not complete the NSI attribution questions or they failed performance validity testing.

Results showed that the symptoms most frequently attributed to TBI included forgetfulness (82%), poor concentration (80%), and slowed thinking (77%). There was a significant positive association between symptom attribution and the NSI total score (r = 0.62, p < .001), meaning that greater attribution of symptoms to TBI was significantly associated with greater symptom endorsement overall.

Symptom attribution was also significantly associated with all four NSI symptom domains (r’s = 0.47-0.66; all p’s < .001), with the strongest relationship emerging between symptom attribution and vestibular symptoms. Finally, linear regressions demonstrated that symptom attribution but not symptom endorsement was significantly associated with objective cognitive functioning. Specifically, greater attribution of symptoms to TBI was associated with worse memory (ß = -0.33, p = .035) and attention/processing speed (ß = -0.40, p = .013) performance.

Results showed significant associations between symptom attribution and (1) symptom endorsement and (2) objective cognitive performance in Veterans with a remote history of TBI. Taken together, findings suggest that Veterans who attribute neurobehavioral symptoms to their TBI are at greater risk of experiencing poor long-term outcomes. Although more research is needed to understand how illness perception influences outcomes in this population, results highlight the importance of early psychoeducation regarding the anticipated course of recovery following TBI.

Practice effects (PE) on cognitive testing impede our ability to accurately assess change. In particular, they hamper the detection of mild cognitive impairment (MCI) and progression to dementia by delaying the point at which test scores fall below diagnostic impairment cutoffs. When decline over time is expected, as with older adults or progressive diseases, failure to adequately address PEs may lead to inaccurate conclusions because PEs artificially boost scores while pathology-related or age-related decline reduces scores. The participant-replacement method accounts for PEs by comparing performance of demographically-matched replacement participants to returnees who have been tested previously. Unlike most methods, the participant-replacement method can separate pathology- or age-related decline from PEs; however, this method has only been used across two timepoints. Neuropsychologists tend to think that PEs level out after the first follow-up, but this issue has not been evaluated in models that allow PEs in the presence of overall decline. Including more than two timepoints makes it possible to determine if PEs level out after the first follow-up, but it is analytically challenging because individuals may not be assessed at every timepoint.

We examined 1190 older adults in the Alzheimer’s Disease Neuroimaging Initiative who were cognitively unimpaired (n=809) or had MCI (n=381) at baseline. Participants completed six neuropsychological measures (Trails A, Trials B, Boston Naming Test, Category Fluency, Logical Memory, Rey Auditory Verbal Learning Task) at three timepoints (baseline, 12-month, 24-month). We implemented the participant-replacement method using generalized estimating equations in comparisons of matched returnees and replacements to calculate PEs. Propensity scores matched individuals on age, education, sex, and an estimate of premorbid functioning. Generalized estimating equations modeled PEs and age-related decline separately for each cognitive measure.

We observed significant PEs for 5 of the 6 measures in the cognitively unimpaired group and 4 measures in the baseline MCI group. PEs did not uniformly decrease across time; some—specifically on episodic memory measures—continued to increase beyond the first follow-up for both groups of participants. Without accounting for PEs, cognitive function appeared to improve or stay the same. In contrast, when PEs were included in the models, cognitive function appeared to decline or stay the same across time.

The replacement method of PE adjustment revealed significant PEs across two follow-ups. PEs for episodic memory, in particular, did not level out, but actually increased after the first follow-up, two years after baseline. As expected in these older adults, accounting for PEs revealed cognitive decline, in some cases, even when PE-unadjusted scores improved. This method of assessing PEs, in turn, means earlier detection of cognitive deficits, including progression to MCI, and more accurate characterization of longitudinal change.

To determine the association between in-vivo spectroscopy metabolite data, the local connectome, and markers of initial injury severity (I.e., history of loss of consciousness; LoC) in traumatic brain injury (TBI), in a heterogenous sample of Veterans and non-Veterans with a history of remote mild-to-moderate TBI (I.e., >6 months).

Participants with complete PRESS magnetic resonance spectroscopy (MRS) and diffusion weighted imaging (DWI) data (N = 41) were sampled from a larger multisite study of chronic mild-to-moderate TBI (Nmiid = 38; Nmoderate = 3; 54% with LoC; 46% with multiple TBI). The sample was predominantly male (76%) with ages ranging from 23-59 (M = 36.9, SD = 10.1), with 98% holding at least a high school degree (M = 14.5 years of education, SD = 2.4). Fully tissue-and-relaxation-corrected metabolite concentration estimates in the dorsal anterior cingulate (30x30x30mm voxel) were modeled using Osprey 2.4.0. Total creatine (tCr), total choline (tCho), total N-acetylaspartate (tNAA), glutamate/glutamine (Glx), and myo-inositol (mI) were analyzed. Logistic regression was used to measure the association between metabolites and history of TBI with LoC. Correlational connectometry using the normalized spin distribution function was performed for metabolites associated with LoC, to characterize the local connectome associated with metabolites of interest, controlling for age and sex, and correcting for multiple comparisons (FDR < .050 with 4000 permutations). A profile approach was used to interpret diffusion metrics, contrasting quantitative anisotropy (QA) with fractional anisotropy (FA). Local connectome tracks were then clustered to identify the larger white matter tract.

Glx (p = .008) and tCr (p = .032) were significantly associated with history of TBI with LoC. Increased Glx was associated with increased QA in 11,001 tracks, accounting for 1.4% of the total white matter tracks in the brain. 90% of tracks were identified in bilateral cingulum (33%), bilateral thalamic (13%), bilateral corticospinal (13%), corpus callosum (12%), left arcuate fasciculus (9%), left frontoparietal aslant tracts (6%), and bilateral inferior fronto-occipital fasciculus (4%) tracts. In contrast, FA was not associated with Glx. The same pattern emerged for tCr, with 10,542 tracks identified predominantly in bilateral cingulum (29%), corpus callosum (21%), bilateral corticospinal (15%), bilateral corticostriatal (7%), bilateral medial lemniscus (7%), left cortico-pontine (3%), left thalamic (2%), and bilateral superior longitudinal fasciculus (2%) tracts. Post-hoc exploratory analyses of mean QA across regions of cingulum found that increased QA was associated with self-report measures of headache intensity, fatigue, and perceived change in executive functioning.

Results provided evidence that multimodal imaging can identify subtle markers of initial TBI severity years after injury. Neurometabolite concentrations were associated with diffuse changes in the local connectome; the pattern of discrepancy between FA and QA was suggestive of reduced potential for neuroplasticity. Exploratory analyses further indicated that variability in white matter density in the cingulum, an important connection for limbic regions, was associated with a range of problems commonly reported in clinical settings, which may be informative for diagnosis and treatment planning.