Although it has been hypothesized that air pollution, particularly PM2.5 and PM10, causes depressed symptoms, their interactions with greenness have not yet been confirmed. This study examined the association between depression symptoms and air pollution, as well as the potential moderating effects of greenness.

A total of 7657 people from all around South Korea were examined using information from the Korean Longitudinal Study of Aging, for the years 2016, 2018 and 2020. Depressive symptoms were assessed using the CES-D 10 score (Center for Epidemiology Studies of Depression scale, Boston form), and annual air pollution levels (PM2.5, PM10) and greenness (NDVI, Landsat Normalized Difference Vegetation Index) at the district level (si-gun-gu) were considered for the association analysis. The investigation was primarily concerned with determining how the CES-D 10 score changed for each 10 ${\mu \text{g/}}{{\text{m}}^{\text{3}}}$ increase in PM2.5 and PM10 according to NDVI quantiles, respectively. The analysis used generalized estimating equation models that were adjusted with both minimal and complete variables. Subgroup analyses were conducted based on age groups (<65, ≥65 years old), sex and exercise status.

The impact of PM10 on depression in the fourth quantile of NDVI was substantially less in the fully adjusted linear mixed model (OR for depression with a 10 ${\mu\text{ g/}}{{\text{m}}^{\text{3}}}$ increment of PM10: 1.29, 95% CI: 1.06, 1.58) than in the first quantile (OR: 1.88, 95% CI: 1.58, 2.25). In a similar vein, the effect of PM2.5 on depression was considerably reduced in the fourth quantile of NDVI (OR for depression with a 10 ${\mu\text{ g/}}{{\text{m}}^{\text{3}}}$ increment of PM2.5: 1.78, 95% CI: 1.30, 2.44) compared to the first (OR: 3.75, 95% CI: 2.75, 5.10). Subgroup analysis results demonstrated beneficial effects of greenness in the relationship between particulate matter and depression.

This longitudinal panel study found that a higher quantile of NDVI was associated with a significantly reduced influence of air pollution (PM10, PM2.5) on depression among older individuals in South Korea.

In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.

A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.

We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.

The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.

Interstage monitoring programs for single ventricle disease have been developed to reduce morbidity and mortality. There is increased use of telemedicine and mobile application monitoring. It is unknown if there are disparities in use based on patient socio-demographic factors.

We conducted a retrospective cohort study of patients enrolled in the single ventricle monitoring program and KidsHeart application at a single centre from 4/21/2021 to 12/31/2023. We investigated the association of socio-demographic factors with telemedicine usage, mobile application enrollment and usage. We assessed resource utilisation and weight changes by program era.

There were 94 children in the cohort. Patients with Norwood and ductal stent had higher mean telemedicine visits per month (1.8 visits, p = 0.004), without differences based on socio-demographic factors. There were differences in application enrollment with more Black patients enrolled compared to White patients (p = 0.016). There were less Hispanic patients enrolled than Non-Hispanic patients (p = 0.034). There were no Spaish speaking patient’s enrolled (p = 0.0015). There were no patients with maternal education of less than high school enrolled and all those with maternal education of advanced degree were enrolled (p = 0.0016). There was decreased mobile application use in those from neighbourhoods in the lowest income quartile. There were decreased emergency department visits with mobile application monitoring. Mean weight-for-age z-scores had increased from start to completion of the program in all eras.

Differences were seen in mobile application enrollment and usage based on socio-demographic factors. Further work is needed to ensure that all patients have access to mobile application usage.

Despite high levels of psychological distress, mental health service use among Syrian refugees in urban settings is low. To address the mental healthcare gap, the World Health Organization developed group problem management plus (gPM+), a scalable psychological intervention delivered by non-specialist peer facilitators. The study aimed to evaluate the effectiveness of gPM+ in reducing symptoms of depression and anxiety among Syrian refugees in Istanbul, Türkiye.

A randomized controlled trial was conducted among 368 distressed (Kessler Psychological Distress Scale, K10 > 15) adult Syrian refugees with impaired functioning (World Health Organization Disability Assessment Schedule, WHODAS 2.0 > 16). Participants were recruited between August 2019 and September 2020 through a non-governmental organization providing services to refugees. Participants were randomly allocated to gPM+ and enhanced care as usual (gPM+/E-CAU) (184 participants) or E-CAU only (184 participants). Primary outcomes were symptoms of depression and anxiety (Hopkins Symptom Checklist (HSCL-25)) at 3-month follow-up. Secondary outcomes were post-traumatic stress disorder (PTSD) symptoms (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-5; PCL-5), functional impairment (WHODAS 2.0), and self-identified problems (psychological outcome profiles).

Intent-to-treat analyses showed no significant effect of gPM+ on symptoms of anxiety, depression, PTSD and self-identified problems. Yet, there was a significant reduction in functional impairment in gPM+/E-CAU compared to E-CAU at 3-month follow-up (adjusted mean difference 1.66, 95 % CI 0.04, 3.27, p = 0.045, d = 0.19). Post-hoc subgroup analyses among participants with probable baseline depression or anxiety showed that there was a small but significant reduction in depression (adjusted mean difference −0.17, 95 % CI −0.32, −0.02, p = 0.028, d = 0.27) and anxiety (adjusted mean difference −0.21, 95 % CI −0.37, −0.05, p = 0.009, d = 0.30) symptoms comparing gPM+/E-CAU to E-CAU only at 1-week post assessment, but not at 3-month follow-up. There was a significant difference between conditions on functional impairment at 3-month follow-up, favouring gPM+/E-CAU condition (adjusted mean difference −1.98, 95 % CI −3.93, −0.02, p = 0.048, d = 0.26).

In this study in an urban setting in Türkiye, gPM+ did not alleviate symptoms of depression and anxiety among Syrian refugees experiencing psychological distress and daily living difficulties. However, participants with higher distress at baseline seemed to benefit from gPM+, but treatment gains disappeared in the long term. Current findings highlight the potential benefit of tailored psychosocial interventions for highly distressed refugees in volatile low-resource settings.

High-quality evidence is lacking for the impact on healthcare utilisation of short-stay alternatives to psychiatric inpatient services for people experiencing acute and/or complex mental health crises (known in England as psychiatric decision units [PDUs]). We assessed the extent to which changes in psychiatric hospital and emergency department (ED) activity were explained by implementation of PDUs in England using a quasi-experimental approach.

We conducted an interrupted time series (ITS) analysis of weekly aggregated data pre- and post-PDU implementation in one rural and two urban sites using segmented regression, adjusting for temporal and seasonal trends. Primary outcomes were changes in the number of voluntary inpatient admissions to (acute) adult psychiatric wards and number of ED adult mental health-related attendances in the 24 months post-PDU implementation compared to that in the 24 months pre-PDU implementation.

The two PDUs (one urban and one rural) with longer (average) stays and high staff-to-patient ratios observed post-PDU decreases in the pattern of weekly voluntary psychiatric admissions relative to pre-PDU trend (Rural: −0.45%/week, 95% confidence interval [CI] = −0.78%, −0.12%; Urban: −0.49%/week, 95% CI = −0.73%, −0.25%); PDU implementation in each was associated with an estimated 35–38% reduction in total voluntary admissions in the post-PDU period. The (urban) PDU with the highest throughput, lowest staff-to-patient ratio and shortest average stay observed a 20% (−20.4%, CI = −29.7%, −10.0%) level reduction in mental health-related ED attendances post-PDU, although there was little impact on long-term trend. Pooled analyses across sites indicated a significant reduction in the number of voluntary admissions following PDU implementation (−16.6%, 95% CI = −23.9%, −8.5%) but no significant (long-term) trend change (−0.20%/week, 95% CI = −0.74%, 0.34%) and no short- (−2.8%, 95% CI = −19.3%, 17.0%) or long-term (0.08%/week, 95% CI = −0.13, 0.28%) effects on mental health-related ED attendances. Findings were largely unchanged in secondary (ITS) analyses that considered the introduction of other service initiatives in the study period.

The introduction of PDUs was associated with an immediate reduction of voluntary psychiatric inpatient admissions. The extent to which PDUs change long-term trends of voluntary psychiatric admissions or impact on psychiatric presentations at ED may be linked to their configuration. PDUs with a large capacity, short length of stay and low staff-to-patient ratio can positively impact ED mental health presentations, while PDUs with longer length of stay and higher staff-to-patient ratios have potential to reduce voluntary psychiatric admissions over an extended period. Taken as a whole, our analyses suggest that when establishing a PDU, consideration of the primary crisis-care need that underlies the creation of the unit is key.

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.

Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

Assessment of performance validity during neuropsychology evaluation is essential to reliably interpret cognitive test scores. Studies (Webber et al., 2018; Wisdom, et al., 2012) have validated the use of abbreviated measures, such as Trial 1 (T1) of the Test of Memory Malingering (TOMM), to detect invalid performance. Only one study (Bauer et al., 2007) known to these authors has examined the utility of Green’s Word Memory Test (WMT) immediate recall (IR) as a screening tool for invalid performance. This study explores WMT IR as an independent indicator of performance validity in a mild TBI (mTBI) veteran population.

Participants included 211 (Mage = 32.1, SD = 7.4; Medu = 13.1, SD = 1.64; 94.8% male; 67.8% White) OEF/OIF/OND veterans with a history of mTBI who participated in a comprehensive neuropsychological evaluation at one of five participating VA Medical Centers. Performance validity was assessed using validated cut scores from the following measures: WMT IR and delayed recall (DR); TOMM T1; WAIS-IV reliable digit span; CVLT-II forced choice raw score; Wisconsin Card Sorting Test failure to maintain set; and the Rey Memory for Fifteen Items test, combo score. Sensitivity and specificity were calculated for each IR score compared with failure on DR. In addition, sensitivity and specificity were calculated for each WMT IR score compared to failure of at least one additional performance validity measure (excluding DR), two or more measures, and three or more measures, respectively.

Results indicated that 46.8% participants failed to meet cut offs for adequate performance validity based on the standard WMT IR cut score (i.e., 82.5%; M = 81.8%, SD = 17.7%); however, 50.2% participants failed to meet criteria based on the standard WMT DR cut score (M = 79.8% SD = 18.6%). A cut score of 82.5% or below on WMT IR correctly identified 82.4% (i.e., sensitivity) of subjects who performed below cut score on DR, with a specificity of 94.2%. Examination of IR cutoffs compared to failure of one or more other PVTs revealed that the standardized cut score of 82.5% or below had a sensitivity of 78.2% and a specificity of 72.4%; whereas, a cut score of 65% or below had a sensitivity of 41% and a specificity of 91.3%. Similarly, examination of IR cutoffs compared to failure of two or more additional PVTs revealed that the cut score of 60% or below had a sensitivity of 45.7% and specificity of 93.1% ; whereas, a cut score of 57.5% or below had a sensitivity of 57.9% and specificity of 90.9% when using failure of three or more PVTs as the criterion.

Results indicated that a cut score of 82.5% or below on WMT IR may be sufficient to detect invalid performance when considering WMT DR as criterion. Furthermore, WMT IR alone, with adjustments to cut scores, appears to be a reasonable way to assess symptom validity compared to other PVTs. Sensitivity and specificity of WMT IR scores may have been adversely impacted by lower sensitivity of other PVTs to independently identify invalid performance.

Self-compassion (SC) describes an emotionally positive attitude extended toward ourselves when we suffer, consisting of three main components; self-kindness, common humanity, and mindfulness (Germer & Neff, 2013). SC entails being warm and understanding towards ourselves when encountering pain or personal shortcomings, rather than ignoring them or flagellating ourselves with self-criticism. SC also involves recognizing that suffering and failure are part of the shared human experience rather than isolating. In addition, SC requires taking a mindful approach to one’s feelings and thoughts, without judgment of them.

Self-compassion (SC) involves taking an emotionally positive attitude towards oneself when suffering. Although SC has positive effects on mental well-being as well as a protective role in preventing depression and anxiety in healthy individuals, few studies on white matter (WM) microstructures in neuroimaging studies of SC has been studied.

Magnetic resonance imaging data were acquired from 71 healthy participants with measured levels of SC and its six subscales. Mirroring network as WM regions of interest were analyzed using tract-based spatial statistics (TBSS). After the WM regions associated with SC were extracted, exploratory correlation analysis with the self-forgiveness scale, the coping scale, and the world health organization quality of life scale abbreviated version was performed.

We found that self-compassion scale (SCS) total scores were negatively correlated with the fractional anisotropy (FA) values of the superior longitudinal fasciculus (SLF) in healthy individuals. The self-kindness and mindfulness subscale scores of SCS were also negatively correlated with FA values of the same regions. The FA values of SLF related to SC were found to be negatively correlated with the total scores of self-forgiveness scale, and self-control coping strategy and confrontation coping strategy.

Our findings suggest that levels of SC and its self-kindness and mindfulness components may be negatively associated with DMN-related WM microstructures in healthy individuals. These less WM microstructures may be associated with positive personal attitudes, such as self-forgiveness, self-control and active confrontational strategies.

None Declared

Three-dimensional chromatin interactions regulate gene expressions. The significance of de novo mutations (DNMs) in chromatin interactions remains poorly understood for autism spectrum disorder (ASD).

To investigate the genomic architecture of ASD in terms of non-coding de novo mutations and 3-dimensional chromatin interactions

We generated 813 whole-genome sequences from 242 Korean simplex families to detect DNMs, and identified target genes which were putatively affected by non-coding DNMs in chromatin interactions.

Non-coding DNMs in chromatin interactions were significantly involved in transcriptional dysregulations related to ASD risk. Correspondingly, target genes showed spatiotemporal expressions relevant to ASD in developing brains and enrichment in biological pathways implicated in ASD, such as histone modification. Regarding clinical features of ASD, non-coding DNMs in chromatin interactions particularly contributed to low intelligence quotient levels in ASD probands. We further validated our findings using two replication cohorts, Simons Simplex Collection (SSC) and MSSNG, and showed the consistent enrichment of non-coding DNM-disrupted chromatin interactions in ASD probands. Generating human induced pluripotent stem cells in two ASD families, we were able to demonstrate that non-coding DNMs in chromatin interactions alter the expression of target genes at the stage of early neural development.

Taken together, our findings indicate that non-coding DNMs in ASD probands lead to early neurodevelopmental disruption implicated in ASD risk via chromatin interactions.

None Declared

Several studies have reported on the feasibility and impact of e-monitoring using computers, or smartphones, in patients with mental disorders, including Bipolar Disorder (BD). Despite some promising early results, concerns have been raised about the motivation and ability of patients with BD to adhere to e-monitoring, in particular when they are depressed or manic. While studies on e-monitoring have examined the role of demographic factors, such as age, gender, or socioeconomic status and use of health apps, to our knowledge, no study has examined clinical characteristics that might impact adherence with e-monitoring of patients with BD.

We analyzed adherence to e-monitoring in patients with BD who participated in an ongoing e-monitoring study and evaluated whether demographic and clinical factors would predict adherence.

Eighty-seven participants with BD in different phases of the illness were included. Patterns of adherence for wearable use, daily and weekly self-rating scales over 15 months were analyzed to identify adherence trajectories using growth mixture models (GMM). Multinomial logistic regression models and Multiple Component Analyses were fitted to compute the effects of predictors on GMM classes.

Adherence rates were 79.5% for the wearable; 78.5% for weekly self-ratings; and 74.6% for daily self-ratings. GMM identified three latent class subgroups: (i) participants with good adherence with the protocol; (ii) participants with partial adherence; (iii) participants with poor adherence. Women, participants with a history of suicide attempt, and those with a history of inpatient admission were more likely to belong to the group with good adherence.

Participants with higher illness burden (e.g., history of admission to hospital, history of suicide attempts) have higher adherence rates to e-monitoring. This is important because our findings debunk myths around illness burden as an obstacle to adhere to e-monitoring studies. Participants might have seen e-monitoring as a tool for better documenting symptom change and better managing their illness, thus motivating their engagement.

None Declared