Clinical, technical, and implementation characteristics of real-world health applications using FHIR.

Objective: Understanding the current state of real-world Fast Healthcare Interoperability Resources (FHIR) applications (apps) will benefit biomedical research and clinical care and facilitate advancement of the standard. This study aimed to provide a preliminary assessment of these apps' clinical, technical, and implementation characteristics.

Materials And Methods: We searched public repositories for potentially eligible FHIR apps and surveyed app implementers and other stakeholders.

From promise to practice: towards the realisation of AI-informed mental health care.

In this Series paper, we explore the promises and challenges of artificial intelligence (AI)-based precision medicine tools in mental health care from clinical, ethical, and regulatory perspectives. The real-world implementation of these tools is increasingly considered the prime solution for key issues in mental health, such as delayed, inaccurate, and inefficient care delivery. Similarly, machine-learning-based empirical strategies are becoming commonplace in psychiatric research because of their potential to adequately deconstruct the biopsychosocial complexity of mental health disorders, and hence to improve nosology of prognostic and preventive paradigms.

The promise of a model-based psychiatry: building computational models of mental ill health.

Computational models have great potential to revolutionise psychiatry research and clinical practice. These models are now used across multiple subfields, including computational psychiatry and precision psychiatry. Their goals vary from understanding mechanisms underlying disorders to deriving reliable classification and personalised predictions.

Interventions to mitigate vaping misinformation: protocol for a scoping review.

Background: The impact of misinformation about vapes' relative harms compared with smoking may lead to increased tobacco-related burden of disease. To date, no systematic efforts have been made to chart interventions that mitigate vaping-related misinformation. We plan to conduct a scoping review that seeks to fill gaps in the current knowledge of interventions that mitigate vaping-related misinformation.

Social media-based interventions for adolescent and young adult mental health: A scoping review.

Background: Mental health conditions are common among adolescents and young adults, yet few receive adequate mental health treatment. Many young people seek support and information online through social media, and report preferences for digital interventions. Thus, digital interventions deployed through social media have promise to reach a population not yet engaged in treatment, and at risk of worsening symptoms.

Wearable Seismocardiography-Based Assessment of Stroke Volume in Congenital Heart Disease.

Background Patients with congenital heart disease (CHD) are at risk for the development of low cardiac output and other physiologic derangements, which could be detected early through continuous stroke volume (SV) measurement. Unfortunately, existing SV measurement methods are limited in the clinic because of their invasiveness (eg, thermodilution), location (eg, cardiac magnetic resonance imaging), or unreliability (eg, bioimpedance). Multimodal wearable sensing, leveraging the seismocardiogram, a sternal vibration signal associated with cardiomechanical activity, offers a means to monitoring SV conveniently, affordably, and continuously.

Interventions to mitigate COVID-19 misinformation: protocol for a scoping review.

Background: The duration and impact of the COVID-19 pandemic depends in a large part on individual and societal actions which is influenced by the quality and salience of the information to which they are exposed. Unfortunately, COVID-19 misinformation has proliferated. To date, no systematic efforts have been made to evaluate interventions that mitigate COVID-19-related misinformation.

Effects of object size and task goals on reaching kinematics in a non-immersive virtual environment.

Object size (large vs. small) and task goal (reach at a comfortable pace vs. reach as fast as possible) are well-accepted task constraints that influence reaching kinematics.

Prevalence and predictors of symptoms of Perinatal Mood and anxiety Disorders among a sample of Urban Black Women in the South.

Objectives: Data are scarce regarding the prevalence and predictors of perinatal mood and anxiety disorders (PMADs) among Black women. The purpose of this study was to examine the prevalence and predictors of symptoms of PMADS among Black women.

Methods: Black women completed a paper survey between August 2019 and October 2019.

COVID-19 vaccine perceptions in the initial phases of US vaccine roll-out: an observational study on reddit.

Background: Open online forums like Reddit provide an opportunity to quantitatively examine COVID-19 vaccine perceptions early in the vaccine timeline. We examine COVID-19 misinformation on Reddit following vaccine scientific announcements, in the initial phases of the vaccine timeline.

Methods: We collected all posts on Reddit (reddit.

Interventions to Mitigate Vaping Misinformation: A Meta-Analysis.

The impact of misinformation about vapes' relative harms compared with smoking may lead to increased tobacco-related burden of disease and youth vaping. Unfortunately, vaping misinformation has proliferated. Despite growing attempts to mitigate vaping misinformation, there is still considerable ambiguity regarding the ability to effectively curb the negative impact of misinformation.

Effect of PAIP1 on the metastatic potential and prognostic significance in oral squamous cell carcinoma.

Poly Adenylate Binding Protein Interacting protein 1 (PAIP1) plays a critical role in translation initiation and is associated with the several cancer types. However, its function and clinical significance have not yet been described in oral squamous cell carcinoma (OSCC) and its associated features like lymph node metastasis (LNM). Here, we used the data available from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) to analyze PAIP1 expression in oral cancer.

An Open-Source Privacy-Preserving Large-Scale Mobile Framework for Cardiovascular Health Monitoring and Intervention Planning With an Urban African American Population of Young Adults: User-Centered Design Approach.

Background: Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are increasingly affecting younger populations, particularly African Americans in the southern United States. Access to preventive and therapeutic services, biological factors, and social determinants of health (ie, structural racism, resource limitation, residential segregation, and discriminatory practices) all combine to exacerbate health inequities and their resultant disparities in morbidity and mortality. These factors manifest early in life and have been shown to impact health trajectories into adulthood.

Interventions to Mitigate COVID-19 Misinformation: A Systematic Review and Meta-Analysis.

The duration and impact of the COVID-19 pandemic depends largely on individual and societal actions which are influenced by the quality and salience of the information to which they are exposed. Unfortunately, COVID-19 misinformation has proliferated. Despite growing attempts to mitigate COVID-19 misinformation, there is still uncertainty regarding the best way to ameliorate the impact of COVID-19 misinformation.

Social Media Discussions Predict Mental Health Consultations on College Campuses.

The mental health of college students is a growing concern, and gauging the mental health needs of college students is difficult to assess in real-time and in scale. To address this gap, researchers and practitioners have encouraged the use of passive technologies. Social media is one such "passive sensor" that has shown potential as a viable "passive sensor" of mental health.

Complex Deep Neural Networks from Large Scale Virtual IMU Data for Effective Human Activity Recognition Using Wearables.

Supervised training of human activity recognition (HAR) systems based on body-worn inertial measurement units (IMUs) is often constrained by the typically rather small amounts of labeled sample data. Systems like IMUTube have been introduced that employ cross-modality transfer approaches to convert videos of activities of interest into virtual IMU data. We demonstrate for the first time how such large-scale virtual IMU datasets can be used to train HAR systems that are substantially more complex than the state-of-the-art.

Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach.

Background: Expanding access to and use of medication for opioid use disorder (MOUD) is a key component of overdose prevention. An important barrier to the uptake of MOUD is exposure to inaccurate and potentially harmful health misinformation on social media or web-based forums where individuals commonly seek information. There is a significant need to devise computational techniques to describe the prevalence of web-based health misinformation related to MOUD to facilitate mitigation efforts.

Modeling and Learning Constraints for Creative Tool Use.

Improvisation is a hallmark of human creativity and serves a functional purpose in completing everyday tasks with novel resources. This is particularly exhibited in tool-using tasks: When the expected tool for a task is unavailable, humans often are able to replace the expected tool with an atypical one. As robots become more commonplace in human society, we will also expect them to become more skilled at using tools in order to accommodate unexpected variations of tool-using tasks.

Clinician Perspectives on Using Computational Mental Health Insights From Patients' Social Media Activities: Design and Qualitative Evaluation of a Prototype.

Background: Previous studies have suggested that social media data, along with machine learning algorithms, can be used to generate computational mental health insights. These computational insights have the potential to support clinician-patient communication during psychotherapy consultations. However, how clinicians perceive and envision using computational insights during consultations has been underexplored.

Categorical Perception of p-Values.

Traditional statistics instruction emphasizes a .05 significance level for hypothesis tests. Here, we investigate the consequences of this training for researchers' mental representations of probabilities - whether .

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study.

Background: Studies that use ecological momentary assessments (EMAs) or wearable sensors to track numerous attributes, such as physical activity, sleep, and heart rate, can benefit from reductions in missing data. Maximizing compliance is one method of reducing missing data to increase the return on the heavy investment of time and money into large-scale studies.

Objective: This paper aims to identify the extent to which compliance can be prospectively predicted from individual attributes and initial compliance.

Lower AM-PAC 6-Clicks Basic Mobility Score Predicts Discharge to a Postacute Care Facility Among Patients in Cardiac Intensive Care Units.

Objective: The objective of this study was to determine the ability of the Activity Measure for Post-Acute Care "6-Clicks" Basic Mobility Short Form to predict patient discharge destination (home vs postacute care [PAC] facility) from the cardiac intensive care unit (ICU), including patients from the cardiothoracic surgical ICU and coronary care unit.

Methods: This retrospective cohort study utilized electronic medical records of patients in cardiac ICU (n = 359) in an academic teaching hospital in the southeastern region of United States from September 1, 2017, through August 31, 2018.

Results: The median interquartile range age of the sample was 68 years (75-60), 55% were men, the median interquartile range 6-Clicks score was 16 (20-12) at the physical therapist evaluation, and 79% of the patients were discharged to home.