DSM-5 specifies bulimia nervosa (BN) severity based on specific thresholds of compensatory behavior frequency. There is limited empirical support for such severity groupings. Limited support could be because the DSM-5’s compensatory behavior frequency cutpoints are inaccurate or because compensatory behavior frequency does not capture true underlying differences in severity. In support of the latter possibility, some work has suggested shape/weight overvaluation or use of single versus multiple purging methods may be better severity indicators. We used structural equation modeling (SEM) Trees to empirically determine the ideal variables and cutpoints for differentiating BN severity, and compared the SEM Tree groupings to alternate severity classifiers: the DSM-5 indicators, single versus multiple purging methods, and a binary indicator of shape/weight overvaluation.

Treatment-seeking adolescents and adults with BN (N = 1017) completed self-report measures assessing BN and comorbid symptoms. SEM Trees specified an outcome model of BN severity and recursively partitioned this model into subgroups based on shape/weight overvaluation and compensatory behaviors. We then compared groups on clinical characteristics (eating disorder symptoms, depression, anxiety, and binge eating frequency).

SEM Tree analyses resulted in five severity subgroups, all based on shape/weight overvaluation: overvaluation <1.25; overvaluation 1.25–3.74; overvaluation 3.75–4.74; overvaluation 4.75–5.74; and overvaluation ≥5.75. SEM Tree groups explained 1.63–6.41 times the variance explained by other severity schemes.

Shape/weight overvaluation outperformed the DSM-5 severity scheme and single versus multiple purging methods, suggesting the DSM-5 severity scheme should be reevaluated. Future research should examine the predictive utility of this severity scheme.

Posttraumatic stress disorder (PTSD) has been associated with advanced epigenetic age cross-sectionally, but the association between these variables over time is unclear. This study conducted meta-analyses to test whether new-onset PTSD diagnosis and changes in PTSD symptom severity over time were associated with changes in two metrics of epigenetic aging over two time points.

We conducted meta-analyses of the association between change in PTSD diagnosis and symptom severity and change in epigenetic age acceleration/deceleration (age-adjusted DNA methylation age residuals as per the Horvath and GrimAge metrics) using data from 7 military and civilian cohorts participating in the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (total N = 1,367).

Meta-analysis revealed that the interaction between Time 1 (T1) Horvath age residuals and new-onset PTSD over time was significantly associated with Horvath age residuals at T2 (meta β = 0.16, meta p = 0.02, p-adj = 0.03). The interaction between T1 Horvath age residuals and changes in PTSD symptom severity over time was significantly related to Horvath age residuals at T2 (meta β = 0.24, meta p = 0.05). No associations were observed for GrimAge residuals.

Results indicated that individuals who developed new-onset PTSD or showed increased PTSD symptom severity over time evidenced greater epigenetic age acceleration at follow-up than would be expected based on baseline age acceleration. This suggests that PTSD may accelerate biological aging over time and highlights the need for intervention studies to determine if PTSD treatment has a beneficial effect on the aging methylome.

Functional cognitive disorder is an increasingly recognised subtype of functional neurological disorder for which treatment options are currently limited. We have developed a brief online group acceptance and commitment therapy (ACT)-based intervention.

To assess the feasibility of conducting a randomised controlled trial of this intervention versus treatment as usual (TAU).

The study was a parallel-group, single-blind randomised controlled trial, with participants recruited from cognitive neurology, neuropsychiatry and memory clinics in London. Participants were randomised into two groups: ACT + TAU or TAU alone. Feasibility was assessed on the basis of recruitment and retention rates, the acceptability of the intervention, and signal of efficacy on the primary outcome measure (Acceptance and Action Questionnaire II (AAQ-II)) score, although the study was not powered to demonstrate this statistically. Outcome measures were collected at baseline and at 2, 4 and 6 months post-intervention, including assessments of quality of life, memory, anxiety, depression and healthcare use.

We randomised 44 participants, with a participation rate of 51.1% (95% CI 40.8–61.5%); 36% of referred participants declined involvement, but retention was high, with 81.8% of ACT participants attending at least four sessions, and 64.3% of ACT participants reported being ‘satisfied’ or ‘very satisfied’ compared with 0% in the TAU group. Psychological flexibility as measured using the AAQ-II showed a trend towards modest improvement in the ACT group at 6 months. Other measures (quality of life, mood, memory satisfaction) also demonstrated small to modest positive trends.

It has proven feasible to conduct a randomised controlled trial of ACT versus TAU.

Meaningful medical data are crucial for response teams in the aftermath of disaster. Electronic Medical Record (EMR) systems have revolutionized healthcare by facilitating real-time data collection, storage, and analysis. These capabilities are particularly relevant for post-disaster and austere environments. fEMR, an EMR system designed for such settings, enables rapid documentation of patient information, treatments, and outcomes, ensuring critical data capture.

Data collected through fEMR can be leveraged to perform comprehensive monitoring and evaluation (M&E) of emergency medical services, assess operational needs and efficiency, and support public health syndromic surveillance.

Analyzing these data identifies patterns and trends or assesses treatment effectiveness. This insight facilitates data-driven decision-making and the optimization of medical protocols. fEMR’s real-time reports enhance situational awareness and operational coordination among response units. The aggregated data can detect trends, classify case-mix, and facilitate after-action reviews, contributing to continuous improvement in emergency preparedness and response strategies. The system also supports fulfilling reporting requirements for health agencies and funding organizations, ensuring accountability and transparency.

EMRs like fEMR are vital for emergency response teams, supporting immediate patient care and ongoing M&E of disaster response efforts. Its robust data management capabilities support evidence-based practices and strategic planning, improving the effectiveness of emergency medical services in disaster scenarios.

The effective use of fEMR in disaster response scenarios highlights its significance in enhancing operational efficiency, ensuring accountability, and improving the overall effectiveness of emergency medical services through comprehensive data management and real-time reporting.