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A 6-Month, Prospective, Randomized Controlled Trial of Customized Adherence Enhancement Versus a Bipolar-Specific Educational Control in Poorly Adherent Adolescents and Young Adults Living with Bipolar Disorder
No full textObjective: Few studies have addressed medication adherence in adolescents and young adults (AYAs) with bipolar disorder (BD). This 6-month prospective randomized-controlled trial (RCT) tested customized adherence enhancement for adolescents and young adults (CAE-AYA), a behavioral intervention for AYAs versus enhanced treatment as usual (ETAU). Methods: Inclusion criteria were AYAs age 13–21 with BD type I or II with suboptimal adherence defined as missing ≥20% of medications. Assessments were conducted at Screening, Baseline, and weeks 8, 12 and 24. Primary outcome was past 7 day self-reported Tablets Routine Questionnaire (TRQ) validated by electronic pillbox monitoring (SimpleMed). Symptom measures included the Hamilton Depression Rating Scale (HAM-D) and Young Mania Rating Scale (YMRS). Results: The mean sample age (N = 36) was 19.1 years (SD = 2.0); 66.7% (N = 24) female, BD Type I (81%). The mean missed medication on TRQ for the total sample was 35.4% (SD = 28.8) at screening and 30.4% (SD = 30.5) at baseline. Both CAE-AYA and ETAU improved on TRQ from screening to baseline. Baseline mean missed medication using SimpleMed was 51.6% (SD = 38.5). Baseline HAM-D and YMRS means were 7.1 (SD = 4.7) and 6.0 (SD = 7.3), respectively. Attrition rate at week 24 was 36%. Baseline to 24-week change on TRQ, adjusting for age, gender, educational level, living situation, family history, race, and ethnicity, showed improvement favoring CAE-AYA versus ETAU of 15%. SimpleMed interpretation was limited due to substantial missing data. There was a significant reduction in depression favoring CAE-AYA. Conclusions: CAE-AYA may improve adherence in AYAs with BD, although conclusions need to be made cautiously given study limitations. Clinical Trials Registration: ClinicalTrials.gov identifier: NCT04348604
Clinical Correlates of Perceived Stigma Among People Living with Epilepsy Enrolled in a Self-Management Clinical Trial
No full textBackground and Purpose: Stigma is a pervasive barrier for people living with epilepsy (PLWE) and can have substantial negative effects. This study evaluated clinical correlates of perceived stigma in a research sample of PLWE considered to be at high risk due to frequent seizures or other negative health events. Methods: Analyses were derived from baseline data from an ongoing Centers for Disease Control and Prevention (CDC)-funded randomized controlled trial (RCT) testing an epilepsy self-management approach. Standardized measures assessed socio-demographics, perceived epilepsy stigma, epilepsy-related self-efficacy, epilepsy self-management competency, health literacy, depressive symptom severity, functional status, social support and epilepsy-related quality of life. Results: There were 160 individuals, mean age of 39.4, (Standard deviation/SD=12.2) enrolled in the RCT, 107 (66.9 %) women, with a mean age of epilepsy onset of 23.9 (SD 14.0) years. The mean seizure frequency in the prior 30 days was 6.4 (SD 21.2). Individual factors correlated with worse perceived stigma were not being married or cohabiting with someone (p = 0.016), lower social support (p \u3c 0.0001), lower self-efficacy (p \u3c 0.0001), and lower functional status for both physical health (p = 0.018) and mental health (p \u3c 0.0001). Perceived stigma was associated with worse depressive symptom severity (p \u3c 0.0001). Multivariable linear regression found significant independent associations between stigma and lower self-efficacy (β −0.05; p = 0.0096), lower social support (β −0.27; p = 2.4x10-5, and greater depression severity (β 0.6; p = 5.8x10-5). Conclusions: Perceived epilepsy stigma was positively correlated with depression severity and negatively correlated with social support and self-efficacy. Providers caring for PLWE may help reduce epilepsy stigma by screening for and treating depression, encouraging supportive social relationships, and providing epilepsy self-management support. Awareness of epilepsy stigma and associated factors may help reduce some of the hidden burden borne by PLWE
Development of an International Standard Set of Outcomes and Measurement Methods for Routine Practice for Adults with Epilepsy: The International Consortium for Health Outcomes Measurement Consensus Recommendations
No full textAt present, there is no internationally accepted set of core outcomes or measurement methods for epilepsy clinical practice. Therefore, the International Consortium for Health Outcomes Measurement (ICHOM) convened an international working group of experts in epilepsy, people with epilepsy and their representatives to develop minimum sets of standardized outcomes and outcomes measurement methods for clinical practice that support patient–clinician decision-making and quality improvement. Consensus methods identified 20 core outcomes. Measurement tools were recommended based on their evidence of strong clinical measurement properties, feasibility, and cross-cultural applicability. The essential outcomes included many non-seizure outcomes: anxiety, depression, suicidality, memory and attention, sleep quality, functional status, and the social impact of epilepsy. The proposed set will facilitate the implementation of the use of patient-centered outcomes in daily practice, ensuring holistic care. They also encourage harmonization of outcome measurement, and if widely implemented should reduce the heterogeneity of outcome measurement, accelerate comparative research, and facilitate quality improvement efforts
A Mechanochemical Approach to Recycle Thermosets Containing Arbonate and Thiourethane Linkages
No full textOver the past decades, various industries shifted from traditional materials such as glass and metals to thermoset polymers due to their excellent chemical resistance, thermal stability, reduced weight, and affordability. However, at the end of their life cycle, these highly crosslinked polymers end up as environmental pollutants due to their non-recyclability. To tackle this issue, researchers are exploring vitrimer-type polymers with recyclable qualities, supporting a circular economy and sustainable management of thermoset wastes. This study investigates a new promising method of recycling two commonly used thermosets in commercial applications, poly allyl diglycol carbonate (PADC) and poly thiourethane (PTU), via a mechanochemical process known as vitrimerization. The process involves the cryogenic ball milling of the thermoset with a zinc-based catalyst and a hydroxyl-providing agent, followed by compression molding, enabling the thermoset conversion into a vitrimer. Rheological tests revealed the remarkable stress-relaxation capabilities of the vitrimerized networks, indicating the conversion of the initial permanent crosslinked structures into dynamic networks through vitrimerization. Dynamic mechanical analysis results show that the vitrimerized samples display a consistent rubbery plateau at high temperature, similar to that of permanently crosslinked networks, suggesting a fix crosslink density during the exchange reaction. Differential scanning calorimetry and thermogravimetric analysis results showed that the thermal properties of the vitrimerized samples closely resemble those of the original samples
Exploring 2D X-Ray Diffraction Phase Fraction Analysis with Convolutional Neural Networks: Insights from Kinematic-Diffraction Simulations
No full textDeep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting β-phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure α- or pure β-phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of 9.4×10-4. Graphical abstract: (Figure presented.)
Next Generation Microfluidics: Fulfilling the Promise of Lab-on-a-Chip Technologies
No full textMicrofluidic lab-on-a-chip technologies enable the analysis and manipulation of small fluid volumes and particles at small scales and the control of fluid flow and transport processes at the microscale, leading to the development of new methods to address a broad range of scientific and medical challenges. Microfluidic and lab-on-a-chip technologies have made a noteworthy impact in basic, preclinical, and clinical research, especially in hematology and vascular biology due to the inherent ability of microfluidics to mimic physiologic flow conditions in blood vessels and capillaries. With the potential to significantly impact translational research and clinical diagnostics, technical issues and incentive mismatches have stymied microfluidics from fulfilling this promise. We describe how accessibility, usability, and manufacturability of microfluidic technologies should be improved and how a shift in mindset and incentives within the field is also needed to address these issues. In this report, we discuss the state of the microfluidic field regarding current limitations and propose future directions and new approaches for the field to advance microfluidic technologies closer to translation and clinical use. While our report focuses on using blood as the prototypical biofluid sample, the proposed ideas and research directions can be extrapolated to other areas of hematology, oncology, biology, and medicine
Self-Monitoring with Coping Skills and Lifestyle Education for Hypertension Control in Primary Care
No full textSelf-monitoring with support, lifestyle modifications, and emotion management improves blood pressure (BP). Patients with hypertension need continual support to modify behaviors, but time pressures limit lifestyle education in primary care settings. Using mixed methods, we aimed to study the feasibility and acceptability of an innovative 6-week program that combined self-monitoring with coping skills and lifestyle education for patients with uncontrolled hypertension. Patients with uncontrolled hypertension interested in lifestyle modifications before intensifying medications were enrolled from primary care clinics. Patients self-monitored emotions, behaviors, and BPs and received education from medical providers and mind-body therapists through shared medical appointments (SMAs) with an option of weekly printed materials. Over 6 months, 31 eligible participants completed the program with higher uptake (21/41) from physician referrals (74.2% women, 41.9% Black, median household income $100 000). Fourteen participants opted for weekly educational materials due to upcoming SMA sessions being fully booked or personal schedules. Pre- to post-intervention paired t-test showed improvement in systolic BP of 11.6 mmHg (95% CI, 6.6–16.6, p \u3c 0.0001), and hypertension control rate improved by 36% (11/31) post-intervention. Higher baseline systolic BP was associated with higher BP reduction (p \u3c 0.001). Thematic analysis showed the perceived benefit of self-awareness, education, and peer support, whereas time constraints were perceived as challenges. Self-monitoring with education on coping skills and lifestyle modification is feasible and improved BP and hypertension control across diverse primary care patients interested in lifestyle modifications; however, few low-income patients enrolled. Less burdensome and community-based interventions may improve participation in low-income patients
Preferences, Risk Neutrality and Risk-Sensitive Mdps
No full textA binary preference relation on a real vector space satisfying four (natural) axioms is shown to induce a utility function composed of a linear function to the reals and a weakly monotonic function. The key axiom is decomposition, and the utility function can be taken to be linear if and only if this axiom’s converse is also satisfied. Important consequences follow for risk-sensitive discounted Markov decision processes, decision trees, and the discounted utility model in economics. Since the four axioms imply that preferences correspond to discounting, the four axioms without the converse imply that preferences are consistent with discounting without risk neutrality
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