Patient Perceptions Of Machine Learning-Enabled Digital Mental Health

Objective: The mental health crisis is accelerating, with 55.8M American adults in treatment in 2022. Digital mental health is a growing field with implications for mental health care. The objective of this study was to understand patients’ mental health treatment experience and the relationship with their perspectives of a novel digital health product geared toward improving care quality. Methods: In December 2023, an IRB-exempt questionnaire was sent to undergraduate and graduate students at campuses across the North-East United States, as well as healthcare-focused Slack® groups. Results: Of the 1,127 respondents, 28% were actively in treatment for their mental health, 25% were treated in the past, and 1% was on a waiting list. Of those with treatment exposure currently or in the past, 85% experienced challenges with communication during their clinical encounter. Among those, 69% experienced a negative emotional impact, began avoiding care, or even terminated care. Over half (57%) currently use or have used a digital health product. With an overview of the novel digital health product, 71% were Very Likely to share data related to sleep and 62% were Very Likely to share activity data. There was a statistically significant association between treatment exposure and likelihood of data sharing (for Sleep: chi squared c2 (df = 2, n = 1,124) = 14.03, p = 0.001; for Activity: c2 (df = 2, n = 1,121) = 22.13, p \u3c 0.001). Fewer respondents were Very Likely to share sleep and activity compared to expected frequencies if they had exposure to treatment with challenges. For mobile application retention, 351 respondents would fill out a 2–3-minute survey daily and 541 would consider it. Conclusion: There exists a Data Gap between patients and clinicians, driven by communication challenges that impact the care experience for patients. There exists a clear role for a digital health product that addresses the Data Gap to improve care quality, assuming privacy concerns and patient retention incentives are addressed and implemented

American National Identification: Does it Predict Prejudice?

There has been growing evidence that ingroup identification is multidimensional (Leidner et. al. 2010). Higher overall ingroup identification has been shown to lead to stronger intergroup bias (e.g., Aberson et al., 2000). On the other hand, past research indicates that ingroup identification does not necessarily lead to outgroup hate (Brewer, 1999). The goal of this study was to explore how different types of American identification relate to attitudes towards Muslims. A correlational study was conducted in a sample of 716 American students (average age 20 years, 47% male). Participants completed several measures of national identification and explicit prejudice towards Muslims. Participants also completed the Implicit Association Test to assess their implicit attitudes towards Muslims (Greenwald, McGhee, & Schwartz, 1998). Traits related to glorification of one\u27s country (glorification, nationalism and social dominance) were correlated with greater implicit and explicit prejudice towards Muslims. On the other hand, traits related to attachment to one\u27s country (patriotism and commitment) were associated with lower implicit and explicit prejudice towards Muslims. These findings suggest that different types of American identity differentially predict implicit and explicit prejudice towards Muslims. Not all aspects of identification have the same negative effects on attitudes towards outgroups

Real-time price discovery in stock, bond and foreign exchange markets

We characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. Our analysis is based on a unique data set of high-frequency futures returns for each of the markets. We find that news surprises produce conditional mean jumps; hence high-frequency stock, bond and exchange rate dynamics are linked to fundamentals. The details of the linkages are particularly intriguing as regards equity markets. We show that equity markets react differently to the same news depending on the state of the economy, with bad news having a positive impact during expansions and the traditionally-expected negative impact during recessions. We rationalize this by temporal variation in the competing "cash flow" and "discount rate" effects for equity valuation. This finding helps explain the time-varying correlation between stock and bond returns, and the relatively small equity market news effect when averaged across expansions and recessions. Lastly, relying on the pronounced heteroskedasticity in the high-frequency data, we document important contemporaneous linkages across all markets and countries over-and-above the direct news announcement effects. JEL Klassifikation: F3, F4, G1, C

Creep stability of the proposed AIDA mission target 65803 Didymos: I. Discrete cohesionless granular physics model

As the target of the proposed Asteroid Impact & Deflection Assessment (AIDA) mission, the near-Earth binary asteroid 65803 Didymos represents a special class of binary asteroids, those whose primaries are at risk of rotational disruption. To gain a better understanding of these binary systems and to support the AIDA mission, this paper investigates the creep stability of the Didymos primary by representing it as a cohesionless self-gravitating granular aggregate subject to rotational acceleration. To achieve this goal, a soft-sphere discrete element model (SSDEM) capable of simulating granular systems in quasi-static states is implemented and a quasi-static spin-up procedure is carried out. We devise three critical spin limits for the simulated aggregates to indicate their critical states triggered by reshaping and surface shedding, internal structural deformation, and shear failure, respectively. The failure condition and mode, and shear strength of an aggregate can all be inferred from the three critical spin limits. The effects of arrangement and size distribution of constituent particles, bulk density, spin-up path, and interparticle friction are numerically explored. The results show that the shear strength of a spinning self-gravitating aggregate depends strongly on both its internal configuration and material parameters, while its failure mode and mechanism are mainly affected by its internal configuration. Additionally, this study provides some constraints on the possible physical properties of the Didymos primary based on observational data and proposes a plausible formation mechanism for this binary system. With a bulk density consistent with observational uncertainty and close to the maximum density allowed for the asteroid, the Didymos primary in certain configurations can remain geo-statically stable without including cohesion.Comment: 66 pages, 24 figures, submitted to Icarus on 25/Aug/201

Phase proper orthogonal decomposition of non-stationary turbulent flow

A phase proper orthogonal decomposition (Phase POD) method is demonstrated, utilizing phase averaging for the decomposition of spatio-temporal behaviour of statistically non-stationary turbulent flows in an optimized manner. The proposed Phase POD method is herein applied to a periodically forced statistically non-stationary lid-driven cavity flow, implemented using the snapshot proper orthogonal decomposition algorithm. Space-phase modes are extracted to describe the dynamics of the chaotic flow, in which four central flow patterns are identified for describing the evolution of the energetic structures as a function of phase. The modal building blocks of the energy transport equation are demonstrated as a function of the phase. The triadic interaction term can here be interpreted as the convective transport of bi-modal interactions. Non-local energy transfer is observed as a result of the non-stationarity of the dynamical processes inducing triadic interactions spanning across a wide range of mode numbers

A novel epigenetic AML1-ETO/THAP10/miR-383 mini-circuitry contributes to t(8;21) leukaemogenesis

DNA methylation patterns are frequently deregulated in t(8;21) acute myeloid leukaemia (AML), but little is known of the mechanisms by which specific gene sets become aberrantly methylated. Here, we found that the promoter DNA methylation signature of t(8;21)(+) AML blasts differs from that of t(8;21)(-) AMLs. This study demonstrated that a novel hypermethylated zinc finger-containing protein, THAP10, is a target gene and can be epigenetically suppressed by AML1-ETO at the transcriptional level in t(8;21) AML. Our findings also show that THAP10 is a bona fide target of miR-383 that can be epigenetically activated by the AML1-ETO recruiting co-activator p300. In this study, we demonstrated that epigenetic suppression of THAP10 is the mechanistic link between AML1-ETO fusion proteins and tyrosine kinase cascades. In addition, we showed that THAP10 is a nuclear protein that inhibits myeloid proliferation and promotes differentiation both in vitro and in vivo Altogether, our results revealed an unexpected and important epigenetic mini-circuit of AML1-ETO/THAP10/miR-383 in t(8;21) AML, in which epigenetic suppression of THAP10 predicts a poor clinical outcome and represents a novel therapeutic target

Thalamocortical relationship in epileptic patients with generalized spike and wave discharges — A multimodal neuroimaging study

AbstractUnlike focal or partial epilepsy, which has a confined range of influence, idiopathic generalized epilepsy (IGE) often affects the whole or a larger portion of the brain without obvious, known cause. It is important to understand the underlying network which generates epileptic activity and through which epileptic activity propagates. The aim of the present study was to investigate the thalamocortical relationship using non-invasive imaging modalities in a group of IGE patients. We specifically investigated the roles of the mediodorsal nuclei in the thalami and the medial frontal cortex in generating and spreading IGE activities. We hypothesized that the connectivity between these two structures is key in understanding the generation and propagation of epileptic activity in brains affected by IGE. Using three imaging techniques of EEG, fMRI and EEG-informed fMRI, we identified important players in generation and propagation of generalized spike-and-wave discharges (GSWDs). EEG-informed fMRI suggested multiple regions including the medial frontal area near to the anterior cingulate cortex, mediodorsal nuclei of the thalamus, caudate nucleus among others that related to the GSWDs. The subsequent seed-based fMRI analysis revealed a reciprocal cortical and bi-thalamic functional connection. Through EEG-based Granger Causality analysis using (DTF) and adaptive DTF, within the reciprocal thalamocortical circuitry, thalamus seems to serve as a stronger source in driving cortical activity from initiation to the propagation of a GSWD. Such connectivity change starts before the GSWDs and continues till the end of the slow wave discharge. Thalamus, especially the mediodorsal nuclei, may serve as potential targets for deep brain stimulation to provide more effective treatment options for patients with drug-resistant generalized epilepsy