Digital phenotyping of student mental health during COVID-19: an observational study of 100 college students.

Objective: This study assessed the feasibility of capturing smartphone based digital phenotyping data in college students during the COVID-19 pandemic with the goal of understanding how digital biomarkers of behavior correlate with mental health. Participants: Participants were 100 students enrolled in 4-year universities. Methods: Each participant attended a virtual visit to complete a series of gold-standard mental health assessments, and then used a mobile app for 28 days to complete mood assessments and allow for passive collection of GPS, accelerometer, phone call, and screen time data. Students completed another virtual visit at the end of the study to collect a second round of mental health assessments. Results: In-app daily mood assessments were strongly correlated with their corresponding gold standard clinical assessment. Sleep variance among students was correlated to depression scores (ρ = .28) and stress scores (ρ = .27). Conclusions: Digital Phenotyping among college students is feasible on both an individual and a sample level. Studies with larger sample sizes are necessary to understand population trends, but there are practical applications of the data today.

The Role of MicroRNAs in Dilated Cardiomyopathy: New Insights for an Old Entity.

Dilated cardiomyopathy (DCM) is a clinical diagnosis characterized by left ventricular or biventricular dilation and systolic dysfunction. In most cases, DCM is progressive, leading to heart failure (HF) and death. This cardiomyopathy has been considered a common and final phenotype of several entities. DCM occurs when cellular pathways fail to maintain the pumping function. The etiology of this disease encompasses several factors, such as ischemia, infection, autoimmunity, drugs or genetic susceptibility. Although the prognosis has improved in the last few years due to red flag clinical follow-up, early familial diagnosis and ongoing optimization of treatment, due to its heterogeneity, there are no targeted therapies available for DCM based on each etiology. Therefore, a better understanding of the mechanisms underlying the pathophysiology of DCM will provide novel therapeutic strategies against this cardiac disease and their different triggers. MicroRNAs (miRNAs) are a group of small noncoding RNAs that play key roles in post-transcriptional gene silencing by targeting mRNAs for translational repression or, to a lesser extent, degradation. A growing number of studies have demonstrated critical functions of miRNAs in cardiovascular diseases (CVDs), including DCM, by regulating mechanisms that contribute to the progression of the disease. Herein, we summarize the role of miRNAs in inflammation, endoplasmic reticulum (ER) stress, oxidative stress, mitochondrial dysfunction, autophagy, cardiomyocyte apoptosis and fibrosis, exclusively in the context of DCM.

Elastocaloric Properties of Polycrystalline Samples of NiMnGaCu Ferromagnetic Shape Memory Alloy under Compression: Effect of Improvement of Thermoelastic Martensitic Transformation.

Shape memory alloys (SMAs) and ferromagnetic shape memory alloys (FeSMAs) have recently attracted interest for solid state refrigeration applications. Among NiMnGa-based quaternary systems, NiMnGaCu exhibits an interesting giant magnetocaloric effect thanks to the overlapping of the temperatures related to the magnetic transition and the thermoelastic martensitic transformation (TMT); in particular, for compositions with Cu content of approximately 6 at%. In the present work, we investigated the improvement effect of TMT on the total entropy change (ΔS) in the elastocaloric performances of polycrystalline Ni50Mn18.5Cu6.5Ga25 at% alloy samples, just above room temperature. We report an extensive calorimetric and thermomechanical characterization to explore correlations between microstructural properties induced by the selected thermal treatment and elastocaloric response, aiming at providing the basis to develop more efficient materials based on this quaternary system. Both ΔT and ΔS values obtained from mechanical curves at different temperatures and strain recovery tests under fixed load vs. T were considered. Maximum values of ΔS = 55.9 J/KgK and ΔT = 4.5 K were attained with, respectively, a stress of 65 MPa and strain of 4%. The evaluation of the coefficient of performance (COP) was carried out from a cyclic test.

A microRNA Signature for the Diagnosis of Statins Intolerance.

Atherosclerotic cardiovascular diseases (ASCVD) are the leading cause of morbidity and mortality in Western societies. Statins are the first-choice therapy for dislipidemias and are considered the cornerstone of ASCVD. Statin-associated muscle symptoms are the main reason for dropout of this treatment. There is an urgent need to identify new biomarkers with discriminative precision for diagnosing intolerance to statins (SI) in patients. MicroRNAs (miRNAs) have emerged as evolutionarily conserved molecules that serve as reliable biomarkers and regulators of multiple cellular events in cardiovascular diseases. In the current study, we evaluated plasma miRNAs as potential biomarkers to discriminate between the SI vs. non-statin intolerant (NSI) population. It is a multicenter, prospective, case-control study. A total of 179 differentially expressed circulating miRNAs were screened in two cardiovascular risk patient cohorts (high and very high risk): (i) NSI (n = 10); (ii) SI (n = 10). Ten miRNAs were identified as being overexpressed in plasma and validated in the plasma of NSI (n = 45) and SI (n = 39). Let-7c-5p, let-7d-5p, let-7f-5p, miR-376a-3p and miR-376c-3p were overexpressed in the plasma of SI patients. The receiver operating characteristic curve analysis supported the discriminative potential of the diagnosis. We propose a three-miRNA predictive fingerprint (let-7f, miR-376a-3p and miR-376c-3p) and several clinical variables (non-HDLc and years of dyslipidemia) for SI discrimination; this model achieves sensitivity, specificity and area under the receiver operating characteristic curve (AUC) of 83.67%, 88.57 and 89.10, respectively. In clinical practice, this set of miRNAs combined with clinical variables may discriminate between SI vs. NSI subjects. This multiparametric model may arise as a potential diagnostic biomarker with clinical value.

Cross cultural and global uses of a digital mental health app: results of focus groups with clinicians, patients and family members in India and the United States.

BACKGROUND: Despite significant advancements in healthcare technology, digital health solutions - especially those for serious mental illnesses - continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India. METHODS: Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality. RESULTS: Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement. CONCLUSION: People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary - not substitutive - of therapeutic care from a clinician.

Microstructural and Thermo-Mechanical Characterization of Cast NiTiCu20 Shape Memory Alloy.

Among NiTi-based alloys, one of the most promising and exploited alloys is NiTiCu, since the addition of Cu in substitution of Ni in the binary equiatomic NiTi has a significant influence on the martensitic transformation and the thermomechanical properties of the system. A high content of Cu improves the damping properties at the expense of phase homogeneity and workability. The present study focuses on an alloy with a high copper content, i.e., 20 at.%. For this specific composition, the correlation between the thermal treatments, microstructure, formation of secondary phases, and damping properties are investigated by several analyses. The microscopic observation, together with the compositional analysis, allowed the determination of four different phases in the alloy. Both the calorimetry and dynamic thermo mechanical measurements, which confirmed the high damping ability of the alloy, provided a characterization of the martensitic transition. Finally, the electron backscatter diffraction (EBSD) analysis detected the different crystallographic structures (i.e., cubic austenite, orthorhombic martensite, and cubic (face-centered) NiTi2) and their orientation in the different phases. Therefore, the present work aims to improve the knowledge of the role of secondary phases in the optimization of the NiTiCu20 alloy as a valuable alternative to typical alloys used for damping purposes.

Investigating Associations Between Screen Time and Symptomatology in Individuals With Serious Mental Illness: Longitudinal Observational Study.

BACKGROUND: Increasing screen time exposure from digital devices like smartphones has shown a variety of mixed associations with cognition, behavior, and well-being in adults and children but little is known about its associations with symptomatology in individuals with serious mental illness. OBJECTIVE: To determine the range of associations between screen time and symptoms of individuals with mental illness, we utilized a method called specification curve analysis. METHODS: In this observational study, we recruited smartphone-owning adults (≥18 years old) with schizophrenia and healthy controls. We installed 2 research-source smartphone apps, mindLAMP and Beiwe, to collect survey results, cognitive test results, and screen time metrics over a period of 3 months. Surveys were scheduled for twice a week, but participants were instructed to take the surveys naturally as much or as little as they wanted. Screen time was collected continuously in the background. A total of 140 participants was recruited from the outpatient clinic population as well as through general public advertising. Age-matched, smartphone-owning healthy controls were also part of the recruitment pool. A specification curve analysis was a priori designed to explore the relationship between every combination of independent variable and dependent variable in order to demonstrate to what degree screen time relates to symptoms in individuals with serious mental illness. RESULTS: The sample consisted of 88 participants (54 with schizophrenia and 34 healthy controls) who completed both the initial and follow-up visits, completed at least one self-reported survey, and had a minimum passive data cutoff of 5 consecutive days. While we found an association between smartphone screen time metrics and cognition (adjusted R2=0.107, P<.001), specification curve analysis revealed a wide range of heterogenous associations with screen time from very negative to very positive. The effects differed based on diagnostic group, age bracket, type of regression model used, and the specific independent and dependent variables selected for analysis. CONCLUSIONS: The associations between screen time and mental health in patients with schizophrenia are heterogenous when examined with methods that reduce analytical bias. The heterogeneity in associations suggests that complex and personalized potential effects must be understood in the greater context of an individual. This analysis of longitudinally collected screen time data shows potential for future research that could benefit from high resolution metrics on smartphone use.

Psychiatric rehabilitation through teaching smartphone skills to improve functional outcomes in serious mental illness.

This study measured the impact of a digital competencies and skills course on participants with serious mental illness. Close to 75% of participants reported an improvement in a smartphone related skill, and the majority of participants that reported improvement in one skill reported improvement in at least one other. Qualitative feedback from participants suggests how digital competencies acquired were used to immediately support functional outcomes. OBJECTIVE: To improve functional outcomes in patients with serious mental illness through a multi-session curriculum designed to improve smartphone skills and engage participants in group learning and problem solving, targeting negative and cognitive symptoms of illness. METHODS: An eight-week smartphone digital competencies and skills course was offered to two distinct groups of youth with serious mental illness. Pre and post self-report measurements were captured for each participant for each session. RESULTS: Group participation varied by session, but overall 28 unique patients attended. From survey results, 75% reported improvement in smartphone related skills because of the groups. Qualitative feedback suggests how skills acquired by patients were immediately utilized to gain insight into health and support functional outcomes. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Smartphone skills groups are a means to provide practical psychiatric rehabilitation that may enable some patients to compensate for cognitive and social deficits due to illness. While ensuring groups are responsive to patients with varying degrees of skills remains a challenge, adapting lesson structures and mediums, as well as creating new measurement tools, offers a means to modify the course with the clinical need.

Smartphone Health Assessment for Relapse Prevention (SHARP): a digital solution toward global mental health.

BACKGROUND: Predicting and preventing relapse presents a crucial opportunity and first step to improve outcomes and reduce the care gap for persons living with schizophrenia. Using commercially available smartphones and smartwatches, technology now affords opportunities to capture real-time and longitudinal profiles of patients' symptoms, cognition, physiology and social patterns. This novel data makes it possible to explore relationships between behaviours, physiology and symptoms, which may yield personalised relapse signals. AIMS: Smartphone Health Assessment for Relapse Prevention (SHARP), an international mental health research study supported by the Wellcome Trust, will inform the development of a scalable and sharable digital health solution to monitor personal risk of relapse. The resulting technology will be studied toward predicting and preventing relapse among individuals diagnosed with serious mental illness. METHOD: SHARP is a two-phase study with research sites in Boston, Massachusetts, and Bangalore and Bhopal, India. During phase 1, focus groups will be conducted at each study site to collect feedback on the design and features available on mindLAMP, a digital health platform. Individuals with serious mental illness will use mindLAMP for the duration of a year during phase 2. RESULTS: The results of the research outlined in this protocol will guide the development of technology and digital tools to help address pervasive challenges in global mental health. CONCLUSIONS: The digital tools developed as a result of this study, and participants' experiences using them, may offer insight into opportunities to expand digital mental health resources and optimize their utilisation around the world.

Making mental health more accessible in light of COVID-19: Scalable digital health with digital navigators in low and middle-income countries.

The rapid spread of COVID-19 and the devastating consequences to economies and healthcare systems around the world has highlighted the exigent need for accessible mental health support. Increasing use of mobile devices in Lower Middle-Income Countries (LMIC) such as India offers novel opportunity to expand treatment options and reach underserved populations. Prior efforts have utilized technology to redistribute or supplement clinical care but measurable outcomes of this research are limited. In this paper, we explain the structural barriers that prevent access to care and build on prior research to demonstrate how technology can be utilized to offer treatment if it is aided by education and technical support.

Physical Characterization of Sintered NiMnGa Ferromagnetic Shape Memory Alloy.

The present work focused on the microstructural, thermal, electrical, and damping characterization of NiMnGa samples produced through a powder pressing and a sintering process; the effect of sintering times and of the starting powder size were evaluated. Moreover, an observation of the evolution of martensitic transformation typical of NiMnGa ferromagnetic shape memory alloy was conducted in comparison with the cast material behavior and in correlation with the material densification. The optimum powder size and sintering time for the process, i.e., 50 µm or lower and 72 h, were identified considering the investigated physical properties of the sintered samples in comparison to the cast material. The corresponding sample showed the best compromise between density, thermal and electrical properties, and damping and functional behaviour. In general, the outcomes of this study could be the basis of a useful tool for production processes that include a sintering step as well as being a starting point for the evaluation of an alternative low cost fabrication method of this alloy.

Health Information Technology Resources to Support Measurement-Based Care.

To increase utilization and convert health information technology into measurement-based care, this article highlights 4 criteria and actions that help distinguish successful mobile mental health interventions: first, interest: draw on pervading interest in mobile mental health; second, engagement: offer personalized design features and recommendations; third, specificity and simplicity: provide simple, specific, and timely feedback; fourth, support: incorporate support from peers, family and friends, and caregivers.

The digital clinic: Implementing technology and augmenting care for mental health.

Increasing both access to and quality of mental healthcare is a global priority. One solution is to integrate technologies such as smartphone apps and sensors directly into care. Acknowledging many prior attempts and barriers, we introduce the Digital Clinic which is an already functioning clinic using smartphone apps to augment and extend care today at Beth Israel Deaconess Medical Center (BIDMC) in Boston, Massachusetts. In this piece, we outline the theoretical foundation of the Digital Clinic and its emphasis on the therapeutic alliance, measurement-based care, and shared decision making. We explore both workflow and engagement challenges as well as solutions including a new care team member, the Digital Navigator, and the customization of technology. Acknowledging that the Digital Clinic is an evolving program, we offer details on our implementation in order to allow others to replicate, expand on, and improve these initial efforts.

Digital technology for management of severe mental disorders in low-income and middle-income countries.

PURPOSE OF REVIEW: Increasingly, digital technologies, especially mobile telecommunications and smartphone apps, are seen as a novel tool for managing severe mental disorders (SMDs) in low-income and middle-income countries (LMICs). However, there is a need to identify best practices in the use of digital technologies to effectively reach, support, and manage care for patients living with SMDs. In this review, we summarize recent studies using digital technology to manage symptoms and support clinical care for this patient population and discuss new opportunities to advance digital psychiatry research and practice in LMICs. RECENT FINDINGS: Studies evaluating digital interventions for clinical populations living with SMDs in LMICs are limited. Yet, across recent articles surveyed, digital technology appears to yield diverse benefits for this at-risk patient population. These benefits include improved medication adherence, appointment adherence, reduced instances of relapse, and fewer re-hospitalizations. SUMMARY: Continued rigorous research evaluating effectiveness and cost-effectiveness of digital technologies in reaching, treating, and managing symptoms and supporting clinical care for patients with SMDs in LMICs is vital. The urgency for remote approaches for delivering specialized psychiatric care is particularly pronounced because of the immediate and long-term impact of the coronavirus (COVID-19) pandemic on access to in-person services. Future research should emphasize participatory approaches rooted in a process of codesign with target users, in order to achieve clinically effective remotely delivered digital mental health interventions.

Technology Evaluation and Assessment Criteria for Health Apps (TEACH-Apps): Pilot Study.

BACKGROUND: Despite the emergence of app evaluation tools, there remains no well-defined process receptive to diverse local needs, rigorous standards, and current content. The need for such a process to assist in the implementation of app evaluation across all medical fields is evident. Such a process has the potential to increase stakeholder engagement and catalyze interest and engagement with present-day app evaluation models. OBJECTIVE: This study aimed to develop and pilot test the Technology Evaluation and Assessment Criteria for Health apps (TEACH-apps). METHODS: Tailoring a well-known implementation framework, Replicating Effective Programs, we present a new process to approach the challenges faced in implementing app evaluation tools today. As a culmination of our experience implementing this process and feedback from stakeholders, we present the four-part process to aid the implementation of mobile health technology. This paper outlines the theory, evidence, and initial versions of the process. RESULTS: The TEACH-apps process is designed to be broadly usable and widely applicable across all fields of health. The process comprises four parts: (1) preconditions (eg, gathering apps and considering local needs), (2) preimplementation (eg, customizing criteria and offering digital skills training), (3) implementation (eg, evaluating apps and creating educational handouts), and (4) maintenance and evolution (eg, repeating the process every 90 days and updating content). TEACH-apps has been tested internally at our hospital, and there is growing interest in partnering health care facilities to test the system at their sites. CONCLUSIONS: This implementation framework introduces a process that equips stakeholders, clinicians, and users with the foundational tools to make informed decisions around app use and increase app evaluation engagement. The application of this process may lead to the selection of more culturally appropriate and clinically relevant tools in health care.

Regulating digital health technologies with transparency: the case for dynamic and multi-stakeholder evaluation.

BACKGROUND: The prevalence of smartphones today, paired with the increasing precision and therapeutic potential of digital capabilities, offers unprecedented opportunity in the field of digital medicine. Smartphones offer novel accessibility, unique insights into physical and cognitive behavior, and diverse resources designed to aid health. Many of these digital resources, however, are developed and shared at a faster rate than they can be assessed for efficacy, safety, and security-presenting patients and clinicians with the challenge of distinguishing helpful tools from harmful ones. MAIN TEXT: Leading regulators, such as the FDA in the USA and the NHS in the UK, are working to evaluate the influx of mobile health applications entering the market. Efforts to regulate, however, are challenged by the need for more transparency. They require real-world data on the actual use, effects, benefits, and harms of these digital health tools. Given rapid product cycles and frequent updates, even the most thorough evaluation is only as accurate as the data it is based on. CONCLUSIONS: In this debate piece, we propose a complementary approach to ongoing efforts via a dynamic self-certification checklist. We outline how simple self-certification, validated or challenged by app users, would enhance transparency, engage diverse stakeholders in meaningful education and learning, and incentivize the design of safe and secure medical apps.

Five-factor model of personality disorders: Spanish normative data and validation / Modelo de los cinco factores de los trastornos de personalidad: Baremo español y validación

The categorical approach of personality disorders (PD) has given way to a dimensional paradigm. Within this, the Five-factor model (FFM) proposes theoretical hypotheses describing personality pathologies and PD empirical prototypes based on the DSM (DSM-PD). Moreover, a methodology to score DSM-PD using the NEO PI-R facets was developed. In this ex post-facto study FFM-PD count norms were developed using data from the NEO PI-R Spanish adaptation. Furthermore, the diagnostic agreement with the IPDE and validity of FFM-PD counts was analyzed in a clinical (n = 222) and non-clinical sample (n = 742). Based on NEO PI-R scores, we presented Spanish FFM-PD normative data. FFMPD benchmarks were highly likely to be exceeded if subjects were classified as a subclinical case in the DSM-PD. Convergent correlations of FFM-PD counts with their equivalent subclinical cases of DSM-PD were statistically significant and outperformed any divergent correlation as well as the average divergent correlations in all FFM-PD. The use of a count technique based on NEO PI-R facets and Spanish FFM-PD normative data facilitate PD understanding and interpretation in various applied psychology fields

La concepción categórica de los trastornos de personalidad (TP) ha dado paso al paradigma dimensional, donde el modelo de los Cinco Factores (MCF) propone hipótesis teóricas para describir la patología de la personalidad y prototipos empíricos de los TP del DSM, además de técnicas para valorarlos en base a facetas del NEO PI-R. En este estudio ex post-facto se han elaborado baremos para el recuento de TP-MCF a partir de la adaptación española del NEO PI-R. Además, se ha comprobado la coherencia diagnóstica con IPDE y la validez de los recuentos de TP-MCF en una muestra clínica (n = 222) y otra no clínica (n = 742). A partir de las puntuaciones en NEO PI-R se elaboró el baremo español de los TP-MCF, cuyas cotas significativas son superadas con elevada probabilidad por casos subclínicos detectados con IPDE. Las correlaciones convergentes entre los recuentos de TP-MCF y los equivalentes casos de TP-DSM fueron estadísticamente significativas y superaron a cualquier correlación divergente y a la correlación divergente media en todos los TP-MCF. El recuento de facetas relevantes en TP-MCF y el baremo español resultante facilitan la comprensión e interpretación de los TP en distintos ámbitos de la psicología aplicada

A new design of a Nitinol ring-like wire for suturing in deep surgical field.

The present work proposes a new suturing procedure based on self-accommodating suture points. Each suture point is made of a commercial NiTi wire hot-shaped in a single loop ring; a standard suture needle is then fixed at one end of the NiTi suture. According to this simple geometry, several NiTi suture stitches have been prepared and tested by tensile test to verify the closing force in comparison to that of commercial sutures. Further experimental tests have also been performed on anatomic samples from animals to verify the handiness of the NiTi suture. Moreover, surface quality of sutures has been carefully investigated via microscopy. Results show that the NiTi suture expresses high stiffness and a good surface quality. In addition, the absence of manual knotting allows for a simple, fast and safe procedure.

Design and thermo-mechanical analysis of a new NiTi shape memory alloy fixing clip.

In this work, a new NiTi shape memory alloy (SMA) bone fixator is proposed. Thanks to the shape memory effect, this device does not need any external tool for the fixation, as the anchorage is obtained only by the self-accommodation of the clip during the parent transformation. Calorimetry and thermo-mechanical tests were used to evaluate the phase transformation temperatures and to estimate the forces generated both during the fixing surgical procedure and after the surgical operation. An application on animal anatomical sample was also performed; an appropriate mechanical tightness as well as a good handiness has been found.