Inclusion of Individuals With Lived Experiences in the Development of a Digital Intervention for Co-Occurring Depression and Cannabis Use: Mixed Methods Investigation.

Background: Existing interventions for co-occurring depression and cannabis use often do not treat both disorders simultaneously and can result in higher rates of symptom relapse. Traditional in-person interventions are often difficult to obtain due to financial and time limitations, which may further prevent individuals with co-occurring depression and cannabis use from receiving adequate treatment. Digital interventions can increase the scalability and accessibility for these individuals, but few digital interventions exist to treat both disorders simultaneously.

Testing domain knowledge and risk of bias of a large-scale general artificial intelligence model in mental health.

Background: With a rapidly expanding gap between the need for and availability of mental health care, artificial intelligence (AI) presents a promising, scalable solution to mental health assessment and treatment. Given the novelty and inscrutable nature of such systems, exploratory measures aimed at understanding domain knowledge and potential biases of such systems are necessary for ongoing translational development and future deployment in high-stakes healthcare settings.

Methods: We investigated the domain knowledge and demographic bias of a generative, AI model using contrived clinical vignettes with systematically varied demographic features.

Digital biomarkers of anxiety disorder symptom changes: Personalized deep learning models using smartphone sensors accurately predict anxiety symptoms from ecological momentary assessments.

Smartphones are capable of passively capturing persons' social interactions, movement patterns, physiological activation, and physical environment. Nevertheless, little research has examined whether momentary anxiety symptoms can be accurately assessed using these methodologies. In this research, we utilize smartphone sensors and personalized deep learning models to predict future anxiety symptoms among a sample reporting clinical anxiety disorder symptoms.

Process Evaluation of Two Interventions to Improve Health Environments in Family Child Care Homes.

Early care and education (ECE) environments influence children's lifelong health behaviors, growth, and development. Although the number of interventions to improve health in ECE environments is increasing, few have been designed for and tested in family child care homes (FCCHs). This study reports the process evaluation of two interventions to improve FCCH health environments, both part of Happy Healthy Homes, a matched-attention randomized-controlled intervention trial conducted in Oklahoma FCCHs.

Polarization-resolved single-molecule tracking reveals strange dynamics of fluorescent tracers through a deep rubbery polymer network.

Tracking the movement of fluorescent single-molecule (SM) tracers has provided several new insights into the local structure and dynamics in complex environments such as soft materials and biological systems. However, SM tracking (SMT) remains unreliable at molecular length scales, as the localization error (LE) of SM trajectories (∼30-50 nm) is considerably larger than the size of molecular tracers (∼1-2 nm). Thus, instances of tracer (im)mobility in heterogeneous media, which provide indicators for underlying anomalous-transport mechanisms, remain obscured within the realms of SMT.

Heterogeneity during Plasticization of Poly(vinylpyrrolidone): Insights from Reorientational Mobility of Single Fluorescent Probes.

While dynamics of single-molecule (SM) fluorescent probes have been used to investigate the structure and relaxation processes in polymers near the glass transition temperature (T), it is difficult to perform SM imaging at elevated temperatures which restricts such studies to a limited number of polymers for which T is close to room temperature (RT). Plasticization, solvent (or additive) induced lowering of T, offers an alternate avenue to access various effective temperatures in the glassy and rubbery phases of polymers under ambient conditions. By investigation of the reorientational propensity of individual Rhodamine 6G (Rh6G) probes, which is governed by rigidity/dynamics of the polymer cavities, we have explored the extent of spatiotemporal heterogeneity during moisture induced plasticization of poly(vinylpyrrolidone) (PVP), far below and near (below and above) bulk T.

Probing differential hydration of poly(vinylpyrrolidone) thin films using tracer mobility: an insight from fluorescence correlation spectroscopy.

Dynamics of small probe molecules have been routinely used to unravel the intrinsic details of charged ion transport in polymer brushes and polyelectrolyte multilayer (PEM) thin films. However, corresponding morphological properties affected with absorption of moisture have been hardly dealt with despite numerous applications of isotropic thin films in material chemistry and medical purposes. We have explored the overall structural changes associated with plasticization of PVP thin films by probing dynamics of small reporter (rhodamine 6G, Rh6G) molecules using fluorescence correlation spectroscopy (FCS).

Plasticization of poly(vinylpyrrolidone) thin films under ambient humidity: insight from single-molecule tracer diffusion dynamics.

Studies on diffusion dynamics of single molecules (SMs) have been useful in revealing inhomogeneity of polymer thin films near and above the glass-transition temperature (T(g)). However, despite several applications of polymer thin films where exposure to solvent (or vapor) is common, the effect of absorbed solvent molecules on local morphology and rigidity of polymer matrices is yet to be explored in detail. High-T(g) hydrophilic polymers such as poly(vinylpyrrolidone) (PVP) are used as pharmaceutical coatings for drug release in aqueous medium, as they readily absorb moisture, which results in effective lowering of the T(g) and thereby leads to plasticization.