I rely on a little help from my friends: the effect of interpersonal and intrapersonal emotion regulation on the relationship between FOMO and problematic internet use.

BACKGROUND: This study investigated the role of emotion regulation in relation to the links between fear of missing out (i.e., FOMO) and two components of problematic internet use: problematic social media use and doomscrolling. METHODS: Participants (N = 603, Mage = 30.41, SDage = 7.64; 49.1% male-identifying) completed measures of fear of missing out, intrapersonal and interpersonal emotion regulation, and problematic social media use, and doomscrolling. A parallel mediation model was tested to examine the nature of the associations between fear of missing out, intrapersonal, and interpersonal emotion regulation, in accounting for variance in the outcome measures. RESULTS: Analyses revealed that the effect of fear of missing out on problematic social media use was fully mediated by both intrapersonal and interpersonal emotion regulation. In contrast, the effect on doomscrolling was fully mediated by intrapersonal emotion regulation only. CONCLUSIONS: Findings clarify the role of emotion regulation in explaining the relationship between fear of missing out and two types of problematic internet use, indicating a need to consider individual differences in emotion regulation in an evolving social media landscape.

Fully automatic tracking of native knee kinematics from stereo-radiography with digitally reconstructed radiographs.

Precise measurement of joint-level motion from stereo-radiography facilitates understanding of human movement. Conventional procedures for kinematic tracking require significant manual effort and are time intensive. The current work introduces a method for fully automatic tracking of native knee kinematics from stereo-radiography sequences. The framework consists of three computational steps. First, biplanar radiograph frames are annotated with segmentation maps and key points using a convolutional neural network. Next, initial bone pose estimates are acquired by solving a polynomial optimization problem constructed from annotated key points and anatomic landmarks from digitized models. A semidefinite relaxation is formulated to realize the global minimum of the non-convex problem. Pose estimates are then refined by registering computed tomography-based digitally reconstructed radiographs to masked radiographs. A novel rendering method is also introduced which enables generating digitally reconstructed radiographs from computed tomography scans with inconsistent slice widths. The automatic tracking framework was evaluated with stereo-radiography trials manually tracked with model-image registration, and with frames which capture a synthetic leg phantom. The tracking method produced pose estimates which were consistently similar to manually tracked values; and demonstrated pose errors below 1.0 degree or millimeter for all femur and tibia degrees of freedom in phantom trials. Results indicate the described framework may benefit orthopaedics and biomechanics applications through acceleration of kinematic tracking.

Scan-Free and Fully Automatic Tracking of Native Knee Anatomy from Dynamic Stereo-Radiography with Statistical Shape and Intensity Models.

Kinematic tracking of native anatomy from stereo-radiography provides a quantitative basis for evaluating human movement. Conventional tracking procedures require significant manual effort and call for acquisition and annotation of subject-specific volumetric medical images. The current work introduces a framework for fully automatic tracking of native knee anatomy from dynamic stereo-radiography which forgoes reliance on volumetric scans. The method consists of three computational steps. First, captured radiographs are annotated with segmentation maps and anatomic landmarks using a convolutional neural network. Next, a non-convex polynomial optimization problem formulated from annotated landmarks is solved to acquire preliminary anatomy and pose estimates. Finally, a global optimization routine is performed for concurrent refinement of anatomy and pose. An objective function is maximized which quantifies similarities between masked radiographs and digitally reconstructed radiographs produced from statistical shape and intensity models. The proposed framework was evaluated against manually tracked trials comprising dynamic activities, and additional frames capturing a static knee phantom. Experiments revealed anatomic surface errors routinely below 1.0 mm in both evaluation cohorts. Median absolute errors of individual bone pose estimates were below 1.0 ∘ or mm for 15 out of 18 degrees of freedom in both evaluation cohorts. Results indicate that accurate pose estimation of native anatomy from stereo-radiography may be performed with significantly reduced manual effort, and without reliance on volumetric scans.

A Sense of Belonging: Perceptions of the Medical School Learning Environment among URM and Non-URM Students.

Phenomenon: Improving the learning environment (LE), particularly for students underrepresented in medicine (URM), has become an important goal for institutions that provide undergraduate and graduate medical education. Until recently, research and intervention development have been limited by the lack of comprehensive theoretical frameworks. A multi-dimensional conceptual model of the medical school environment, developed by Gruppen and colleagues in 2019, provides a useful framework for guiding research and interventions in this area.Approach: Using Gruppen et al's model, this study investigated experiences of the LE from the perspectives of both URM and non-URM students at a medical school in New York City. In examining experiences of the organizational, social, and physical domains of the LE, we sought to explore the symbolic and experiential links across domains and identify concrete needs for improvement.Findings: Institutional structures and policies, features of the built environment, and social relationships that put learning first and generated a sense of community were highly valued. Although both URM and non-URM students shared many perceptions and experiences, URM students expressed heightened vulnerability to the experiences of devaluation and exclusion.Insights: All participants in the study greatly appreciated aspects of the LE that made them feel like valued members of the community. Medical schools should approach the task of improving the LE for URM students using a comprehensive, multi-dimensional approach.

Fully automatic tracking of native glenohumeral kinematics from stereo-radiography.

The current work introduces a system for fully automatic tracking of native glenohumeral kinematics in stereo-radiography sequences. The proposed method first applies convolutional neural networks to obtain segmentation and semantic key point predictions in biplanar radiograph frames. Preliminary bone pose estimates are computed by solving a non-convex optimization problem with semidefinite relaxations to register digitized bone landmarks to semantic key points. Initial poses are then refined by registering computed tomography-based digitally reconstructed radiographs to captured scenes, which are masked by segmentation maps to isolate the shoulder joint. A particular neural net architecture which exploits subject-specific geometry is also introduced to improve segmentation predictions and increase robustness of subsequent pose estimates. The method is evaluated by comparing predicted glenohumeral kinematics to manually tracked values from 17 trials capturing 4 dynamic activities. Median orientation differences between predicted and ground truth poses were 1.7∘ and 8.6∘ for the scapula and humerus, respectively. Joint-level kinematics differences were less than 2∘ in 65%, 13%, and 63% of frames for XYZ orientation DoFs based on Euler angle decompositions. Automation of kinematic tracking can increase scalability of tracking workflows in research, clinical, or surgical applications.

Moral injury and the hidden curriculum in medical school: comparing the experiences of students underrepresented in medicine (URMs) and non-URMs.

Underrepresented students in medicine (URM) have more negative perceptions of the medical school learning environment (LE), a phenomenon that can contribute to higher rates of burnout and attrition in these populations. The hidden curriculum (HC)-defined as a set of values informally conveyed to learners through clinical role-modeling-is a LE socialization construct that has been critically examined for its role in shaping students' professional identities. Yet differences in how URMs and non-URMs experience the HC remain underexplored. The study used a pragmatic approach that drew on elements of grounded theory and employed both deductive and inductive reasoning. Investigators conducted qualitative, semi-structured interviews with a purposive sample of 13 URM and 21 non-URM participants at a Bronx, NY medical school. Interviews examined student experiences and reactions to the HC. Both cohorts witnessed patient disparagement and mistreatment. However, from these encounters, URM participants expressed more moral injury-the adverse emotional consequence of feeling pressured to accept ideologically incongruent values. URMs were also more likely to describe resisting the HC. Differences in group reactions appeared to arise from URMs' identity resonance with patients' lived experiences. Participants across cohorts emphasized increasing URM recruitment as one step toward mitigating these circumstances. URM participants experienced more distress and offered more resistance to the HC relative to non-URMs. The etiology of these differential reactions may stem from relative barriers in negotiating personal and professional identities. As such, URMs' perceptions of the LE may be adversely impacted given their more negative interactions with the HC.

Joint Track Machine Learning: An Autonomous Method of Measuring Total Knee Arthroplasty Kinematics From Single-Plane X-Ray Images.

BACKGROUND: Dynamic radiographic measurements of 3-dimensional (3-D) total knee arthroplasty (TKA) kinematics have provided important information for implant design and surgical technique for over 30 years. However, current methods of measuring TKA kinematics are too cumbersome, inaccurate, or time-consuming for practical clinical application. Even state-of-the-art techniques require human-supervision to obtain clinically reliable kinematics. Eliminating human supervision could potentially make this technology practical for clinical use. METHODS: We demonstrate a fully autonomous pipeline for quantifying 3D-TKA kinematics from single-plane radiographic imaging. First, a convolutional neural network (CNN) segmented the femoral and tibial implants from the image. Second, those segmented images were compared to precomputed shape libraries for initial pose estimates. Lastly, a numerical optimization routine aligned 3D implant contours and fluoroscopic images to obtain the final implant poses. RESULTS: The autonomous technique reliably produces kinematic measurements comparable to human-supervised measures, with root-mean-squared differences of less than 0.7 mm and 4° for our test data, and 0.8 mm and 1.7° for external validation studies. CONCLUSION: A fully autonomous method to measure 3D-TKA kinematics from single-plane radiographic images produces results equivalent to a human-supervised method, and may soon make it practical to perform these measurements in a clinical setting.

Transport of Multispecies Ion Crystals through a Junction in a Radio-Frequency Paul Trap.

We report on the first demonstration of transport of a multispecies ion crystal through a junction in a rf Paul trap. The trap is a two-dimensional surface-electrode trap with an X junction and segmented control electrodes to which time-varying voltages are applied to control the shape and position of potential wells above the trap surface. We transport either a single ^{171}Yb^{+} ion or a crystal composed of a ^{138}Ba^{+} ion cotrapped with the ^{171}Yb^{+} ion to any port of the junction. We characterize the motional excitation by performing multiple round-trips through the junction and back to the initial well position without cooling. The final excitation is then measured using sideband asymmetry. For a single ^{171}Yb^{+} ion, transport with a 4 m/s average speed induces between 0.013±0.001 and 0.014±0.001 quanta of excitation per round-trip, depending on the exit port. For a Ba-Yb crystal, transport at the same speed induces between 0.013±0.001 and 0.030±0.002 quanta per round-trip of excitation to the in-phase axial mode. Excitation in the out-of-phase axial mode ranges from 0.005±0.001 to 0.021±0.001 quanta per round-trip.

Flashcards: The Preferred Online Game-Based Study Tool Self-Selected by Students to Review Medical Histology Image Content.

Medical students use several supplementary digital resources to support learning. Majority of these supplementary resources enhance learning by recall and repetition. A few examples of these resources are concept maps, flashcards (FCs), and self-testing tools. Traditionally, paper-based FCs are used in higher education. The concept of paper-based FCs is extended to the digital world in the form of electronic/web-based FCs. The use of electronic/digital flashcards has been reported to review course material in the medical school curriculum. Some of the medical school coursework requires students to acquire visual skills, for example, histology and pathology. Students, who do not have prior knowledge of the basic content on histology and pathology struggle to identify microscopic tissues and organs. Therefore, students look for other supplementary resources to support visual learning. Digital resources like Anki, Quizlet, and Osmosis provide study tools that support visual skills. A review of the literature revealed only a few publications pertaining to the use of digital testing tools for histology education in medical school curriculum. In the medical histology course at the Albert Einstein College of Medicine (Einstein), Bronx, NY, first-year medical students used a game-based platform (Quizlet) to review image-based histology course content in the form of four Quizlet study sets. Students chose from six Quizlet study tools (Flashcards, Learn, Speller, Test, Match, and Race/Gravity) to review the image-based course material and test their knowledge on accurate identification of histological images. The data on student usage of study tools was tracked and analyzed for 4 years (Graduating Classes of 2018 to 2021) to calculate: the total usage of the game-based study tools (Flashcards, Learn, Speller, Test, Match, and Race/Gravity) over the period of 4 years, total percent usage over 4 years of each game-based study tools (Flashcards, Learn, Speller, Test, Match, and Race/Gravity) in each of the four Quizlet study sets and to identify the preferred game-based study tool. The data showed a consistent year-on-year increase in usage of game-based study tools by 50% (M = 445 in 2018 compared to M = 849 in 2021). For the four Quizlet study sets the percent usage of each study tool Flashcards, Learn, Test, Match, Gravity, and Speller was tracked and combined across the four academic years. It was found that Flashcards were used significantly more frequently than any other tool and this was followed by Learn, Test, Match, Gravity, and Speller (p < 0.0001 using chi-square). The study concludes that flashcards are the preferred study tool used by students to acquire visual skills for identifying histological images and could be incorporated when designing online study tools.

Evaluation of single-stage vision models for pose estimation of surgical instruments.

PURPOSE: Multiple applications in open surgical environments may benefit from adoption of markerless computer vision depending on associated speed and accuracy requirements. The current work evaluates vision models for 6-degree of freedom pose estimation of surgical instruments in RGB scenes. Potential use cases are discussed based on observed performance. METHODS: Convolutional neural nets were developed with simulated training data for 6-degree of freedom pose estimation of a representative surgical instrument in RGB scenes. Trained models were evaluated with simulated and real-world scenes. Real-world scenes were produced by using a robotic manipulator to procedurally generate a wide range of object poses. RESULTS: CNNs trained in simulation transferred to real-world evaluation scenes with a mild decrease in pose accuracy. Model performance was sensitive to input image resolution and orientation prediction format. The model with highest accuracy demonstrated mean in-plane translation error of 13 mm and mean long axis orientation error of 5[Formula: see text] in simulated evaluation scenes. Similar errors of 29 mm and 8[Formula: see text] were observed in real-world scenes. CONCLUSION: 6-DoF pose estimators can predict object pose in RGB scenes with real-time inference speed. Observed pose accuracy suggests that applications such as coarse-grained guidance, surgical skill evaluation, or instrument tracking for tray optimization may benefit from markerless pose estimation.

Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression.

Tibiofemoral geometry influences knee passive motion and understanding their relationship can provide insight into knee function and mechanisms of injury. However, the complexity of the geometric constraints has made characterizing the relationship challenging. The aim of this study was to determine the tibiofemoral bone geometries that explain the variation in passive motion using a partial least squares regression (PLSR) model. The PLSR model was developed for 29 healthy cadaver specimens (10 female, 19 male) with femur and tibia geometries retrieved from MRI images and six degree-of-freedom tibiofemoral kinematics determined during a flexion cycle with minimal medial pressure. The first 13 partial least squares (PLS) components explained 90% of the variation in the kinematics and accounted for 89% of the variation in geometry. The first three PLS components which shared geometric changes to particular surface congruencies of the tibial and femoral condyles explained the most amount of variation in the kinematics, primarily in anterior-posterior translation. Meanwhile, variations in femoral condyle width and the intercondylar space, tibia plateau size and conformity, and tibia eminences heights in PLS 2 and 4 explained the greatest amount of variation in internal-external rotation. PLS 4 exhibiting variation in overall size of the knee accounted for greatest amount of variation in geometry (50%) and had the greatest influence on the abduction-adduction motion and some on internal-external rotation but, overall, explained only a small proportion of the kinematics (10%). Elucidating the complex relationship between tibiofemoral bone geometry and passive kinematics may help personalize treatments for improved functional outcomes in patients.

Admission practices following pediatric tonsillectomy: A survey of ASPO members.

OBJECTIVES: Although evidence-based Clinical Practice Guidelines (CPGs) have specified postoperative admission criteria for pediatric tonsillectomy, there is substantial variation in guideline implementation and adherence among otolaryngologists in practice. We aimed to assess pediatric otolaryngologists' post-tonsillectomy admission practices and to examine patient and surgeon factors associated with differences in admission practices. METHODS: An electronic cross-sectional survey was distributed to members of the American Society of Pediatric Otolaryngology (ASPO) to determine current practices regarding admission practices following pediatric tonsillectomy. Chi-square and Fisher's exact tests were performed to compare differences in adherence to tonsillectomy CPGs by respondent characteristics. RESULTS: The survey was sent to 644 pediatric otolaryngologists with a response rate of 19.1%. 37% of respondents reported "always" and 60% "often" using the Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) CPG to guide decision for admission. Years in practice was the factor most strongly associated with admission practices, with 10 or fewer years in practice significantly correlated with stricter adherence to the AAO-HNS CPG of overnight observation when Apnea-Hypopnea Index (AHI) ≥10, age <3 years, or O2 nadir <80%) (OR 4.2, p <0.001), as well as specific individual criteria such as an AHI ≥10 (OR 4.1, p = 0.03). Respondents in an academic practice setting were more likely to admit children <3 years of age than those in private practice (OR 5.0, p = 0.01). CONCLUSION: Admission practices varied among pediatric otolaryngologist survey respondents, and strict AAO-HNS CPG adherence was associated with fewer years in practice and academic practice setting. These results suggest that further study investigating factors influencing guideline adherence and post-tonsillectomy admission practices is warranted.

Preparation of the Spin-Mott State: A Spinful Mott Insulator of Repulsively Bound Pairs.

We observe and study a special ground state of bosons with two spin states in an optical lattice: the spin-Mott insulator, a state that consists of repulsively bound pairs that is insulating for both spin and charge transport. Because of the pairing gap created by the interaction anisotropy, it can be prepared with low entropy and can serve as a starting point for adiabatic state preparation. We find that the stability of the spin-Mott state depends on the pairing energy, and observe two qualitatively different decay regimes, one of which exhibits protection by the gap.

Automatic tracking of healthy joint kinematics from stereo-radiography sequences.

Kinematic tracking of healthy joints in radiography sequences is frequently performed by maximizing similarities between computed perspective projections of 3D computer models and corresponding objects' appearances in radiographic images. Significant human effort associated with manual tracking presents a major bottleneck in biomechanics research methods and limits the scale of target applications. The current work introduces a method for fully-automatic tracking of tibiofemoral and patellofemoral kinematics in stereo-radiography sequences for subjects performing dynamic activities. The proposed method involves the application of convolutional neural networks for annotating radiographs and a multi-stage optimization pipeline for estimating bone pose based on information provided by neural net predictions. Predicted kinematics are evaluated by comparing against manually-tracked trends across 20 distinct trials. Median absolute differences below 1.5 millimeters or degrees for 6 tibiofemoral and 3 patellofemoral degrees of freedom demonstrate the utility of our approach, which improves upon previous semi-automatic methods by enabling end-to-end automation. Implementation of a fully-automatic pipeline for kinematic tracking will benefit evaluation of human movement by enabling large-scale studies of healthy knee kinematics.

Machine learning for rapid estimation of lower extremity muscle and joint loading during activities of daily living.

Joint contact and muscle forces estimated with musculoskeletal modeling techniques offer useful metrics describing movement quality that benefit multiple research and clinical applications. The expensive processing of laboratory data associated with generating these outputs presents challenges to researchers and clinicians, including significant time and expertise requirements that limit the number of subjects typically evaluated. The objective of the current study was to develop and compare machine learning techniques for rapid, data-driven estimation of musculoskeletal metrics from derived gait lab data. OpenSim estimates of patient joint and muscle forces during activities of daily living were simulated using laboratory data from 70 total knee replacement patients and used to develop 4 different machine learning algorithms. Trained machine learning models predicted both trend and magnitude of estimated joint contact (mean correlation coefficients ranging from 0.93 to 0.94 during gait) and muscle forces (mean correlation coefficients ranging from 0.83 to 0.91 during gait) based on anthropometrics, ground reaction forces, and joint angle data. Patient mechanics were accurately predicted by recurrent neural networks, even after removing dependence on key subsets of predictor features. The ability to quickly estimate patient mechanics from derived measurements of movement has the potential to broaden the impact of musculoskeletal modeling by enabling faster assessment in both clinical and research settings.

Development of a Positive Psychology Program (LAVENDER) for Preserving Medical Student Well-being: A Single-Arm Pilot Study.

BACKGROUND: Mental health tends to worsen over the course of medical school, with steep declines in well-being in students' clerkship year (M3). Positive emotion promotes adaptive coping to stress and may help preserve medical student well-being. OBJECTIVE: This study describes the development of LAVENDER (Leveraging Affect and Valuing Empathy for Nurturing Doctors' Emotional Resilience), a program aimed at increasing positive emotion to preserve well-being in medical students. METHODS: We conducted a single-arm pilot of LAVENDER, a positive psychology intervention developed for medical students delivered in an interactive classroom format to a cohort of 157 third-year medical students at the Albert Einstein College of Medicine. Our primary outcome was the acceptability of LAVENDER. We also examined preliminary efficacy using measures of emotion, stress and burnout collected at each intervention session. RESULTS: LAVENDER showed good acceptability: 76% of participants agreed that the LAVENDER skills were useful and 72% agreed that they would recommend the LAVENDER program to others. Qualitative feedback suggested that medical students enjoyed the program and found the skills to be useful for coping with stress, but also reported the following barriers to engagement: lack of time to practice the skills, resistance to the mandatory nature of the wellness sessions, and difficulty integrating the skills in daily life. We did not find support for the preliminary efficacy of LAVENDER for improving medical student well-being in students' clerkship year. Participants showed decreases in positive emotion and increases in symptoms of burnout over the intervention period (ps < .01). CONCLUSION: The current paper describes the development and a single-arm pilot test of LAVENDER, a positive psychology program tailored for medical students. Although we found preliminary evidence for the acceptability of LAVENDER, we did not find support for the preliminary efficacy. Lessons learned and next steps for the program are discussed.

The effect of platelet-rich plasma on female androgenetic alopecia: A randomized controlled trial.

BACKGROUND: Platelet-rich plasma (PRP) may be a useful treatment for androgenetic alopecia (AGA), although objective studies are needed. OBJECTIVE: To determine whether PRP injections improve female AGA. METHOD: Prospective randomized controlled trial of 30 women diagnosed with AGA. Patients received subdermal scalp injections of Eclipse system PRP or placebo saline at weeks 0, 4, and 8. Outcome measures were changes in hair density (hair/cm2), hair caliber (mm), and blinded global photographic assessment (improved or not improved) at week 24. RESULTS: Blinded global photographic assessment indicated that 57% of patients receiving PRP versus 7% of patients receiving saline improved at week 24 from baseline (P < .01). Compared to baseline, there was improvement in mean density in the PRP group versus the placebo group at week 8 (+71.1 vs -26.7 hairs/cm2; P < .01) and week 24 (+105.9 vs -52.4 hairs/cm2; P < .01). Compared to baseline, there was improvement in mean caliber in the PRP group versus the placebo group at week 8 (+0.0043 vs -0.0034 mm; P < .01) and week 24 (+0.0053 vs -0.0060 mm; P < .01). Adverse effects included headache, scalp tightness, swelling, redness, and postinjection bleeding. LIMITATIONS: Two patients lost to follow-up. CONCLUSIONS: PRP with the Eclipse system is a safe and effective intervention for female AGA.

Opioid Overdose and Addiction Treatment: A Collaborative Model of Compassion, Patience, and Respect.

PURPOSE: The purpose of this article is to describe the creation and outcomes of a collaborative model and care facility for opioid overdose and addiction treatment based on compassion, patience, and respect: The Maryhaven Addiction Stabilization Center (MASC). APPROACH: MASC was created with the vision to serve clients who have recently overdosed on opioids. In this article, the research, planning, building, and implementation of an opioid treatment center composed of an admission and triage unit, inpatient withdrawal management unit, and inpatient residential unit are described. A multi-agency and multi-disciplinary approach were used to immediately engage patients and connect them to treatment for opioid addiction. FINDINGS: Implementation of a collaborative model of care offers patients who overdose on opioids with immediate access to admission for treatment. This has resulted in significantly higher numbers of patients seeking and staying in treatment. CONCLUSIONS: Through multi-agency collaboration and a shared commitment to addressing the challenges of the opioid epidemic in innovative ways, more patients who are struggling with addiction have increased opportunities to engage in treatment and move towards recovery. CLINICAL RELEVANCE: Clinicians, first responders, and communities can employ MASC principles to guide their approaches to serve patients who have recently overdosed on opioids or who are in active addiction.