Promoting Student Growth in Supervision and Remediation Using Motivational Interviewing

It is common for students to experience resistance or ambivalence when a supervisor or faculty advisor requests they change their behaviors or perspectives to be a more effective counselor. Motivational interviewing (MI) is used to cultivate motivation for positive change within the context of a helping relationship, and is applied to counselor supervision. Implementing this approach can help improve the effectiveness of supervision and remediation, including students achieving desired outcomes, even if students are initially ambivalent or appear disengaged. In this roundtable, we will describe MI applied to clinical supervision and student remediation. Attendees will be encouraged to apply the material presented in interactive activities, and case examples will illustrate specific applications of MI in supervision and remediation

Outcomes of Motivational Interviewing Training with Probation and Parole Officers: Findings and Lessons Learned

Motivational Interviewing (MI) is an evidence-based approach that provides probation and parole officers with specific skills to enhance their clients\u27 motivations to change problematic behaviors. This study investigated the outcomes of MI training with probation and parole officers whose state agency required them to complete MI training. Results show that officers\u27 MI skills, self-efficacy, and knowledge increased following training, with some exceptions. Recommendations from implementation science literature are provided for improving MI trainings

NORHA: A NORmal Hippocampal Asymmetry Deviation Index Based on One-Class Novelty Detection and 3D Shape Features

Radiologists routinely analyze hippocampal asymmetries in magnetic resonance (MR) images as a biomarker for neurodegenerative conditions like epilepsy and Alzheimer’s Disease. However, current clinical tools rely on either subjective evaluations, basic volume measurements, or disease-specific models that fail to capture more complex differences in normal shape. In this paper, we overcome these limitations by introducing NORHA, a novel NORmal Hippocampal Asymmetry deviation index that uses machine learning novelty detection to objectively quantify it from MR scans. NORHA is based on a One-Class Support Vector Machine model learned from a set of morphological features extracted from automatically segmented hippocampi of healthy subjects. Hence, in test time, the model automatically measures how far a new unseen sample falls with respect to the feature space of normal individuals. This avoids biases produced by standard classification models, which require being trained using diseased cases and therefore learning to characterize changes produced only by the ones. We evaluated our new index in multiple clinical use cases using public and private MRI datasets comprising control individuals and subjects with different levels of dementia or epilepsy. The index reported high values for subjects with unilateral atrophies and remained low for controls or individuals with mild or severe symmetric bilateral changes. It also showed high AUC values for discriminating individuals with hippocampal sclerosis, further emphasizing its ability to characterize unilateral abnormalities. Finally, a positive correlation between NORHA and the functional cognitive test CDR-SB was observed, highlighting its promising application as a biomarker for dementia.La versión final de este artículo fue publicada el 29 de junio de 2023 en Brain Topography (Springer). Se encuentra accesible desde Biblioteca Di Tella a través de Prim

Data analysis on effects of therapeutic drug monitoring, dosing, and age on observed meprobamate concentrations in urine samples

Prior to the development of benzodiazepines (BZDs) in the 1950’s, a class of drugs known as tranquilizers were used in psychiatry to treat patients experiencing anxiety and fear as well as more challenging states of psychosis such as schizophrenia. The first minor tranquilizer and anxiolytic compound that was widely used in the United States and much of the world was meprobamate in the 1950s. Meprobamate is a carbamate compound typically administered in tablet form and ingested orally as its route of administration. Meprobamate is also the major metabolite of the drug carisoprodol, which is sold under the brand name Soma ®. Both meprobamate and carisoprodol are schedule IV substances under the Controlled Substance Act as there is reported abuse with each substance. The primary goal of this research is to determine whether collected patient data reflects appropriate usage of their carisoprodol prescription in treatment of anxiety and if urine drug testing (UDT) and specimen validity testing (SVT) can support or refute the effectiveness of a patient’s treatment by measuring resulting meprobamate concentration. For the purpose of this study, a data set consisting of a population that was prescribed carisoprodol was provided by a therapeutic drug-testing lab. Qualitative results include a known prescription for carisoprodol, the presence of carisoprodol as well as the main anxiolytic metabolite meprobamate, whether a patient’s sample passed or failed SVT, and the sex of the individual. Quantitative results include initial and reported drug dosage, target analyte concentration, age, SVT result and body mass index (BMI). The lab used liquid chromatography tandem mass spectrometry (LC-MS/MS) to run analysis of urine specimen. Data analysis was conducted using R Studio version 3.5.1 (R Foundation, Vienna, Austria). R Studio is a statistical program that is utilized for computation and production of graphics. Statistical analysis and sub setting was used to find relationships and trends of meprobamate concentrations as they relate to age, BMI, dosage and SVT parameters. In this study of 1,672 patients, 1,067 were female and 685 males with females having 63.8% of the patient population. Of the overall population, 33.3% had a carisoprodol dose between 700-1050 mg, equivalent to 2 to 3 doses of 350 mg, in tablet form daily. 70.5% of the patient population was deemed overweight in terms of BMI yet had a lower average meprobamate concentration in urine compared to normal weight patients. The majority of participants in the study, 82.5% of females and 84.3% of males, who had a prescription for carisoprodol were between the ages of 40 and 69. SVT testing parameters were used to filter patient data a second time. Certain samples fell outside of accepted ranges for pH, creatinine and specific gravity. Of all 1,672 submitted samples, 18.2% failed at least one parameter or contained an illicit substance. The average meprobamate concentration for males was 26,896 ng/mL (530-292,133 ng/mL range) and the average concentration for females was 28,802 ng/mL (500 to 336,853 ng/mL range). This research highlights the need for compliance drug testing to ensure that patients are taking their prescribed dose appropriately and monitoring for signs of abuse. The trends discovered in this research can be used to evaluate known carisoprodol dosing and relate it to meprobamate concentration in urine drug testing. There are likely to be variations in patients’ metabolism and overall health but having a sense of how much carisoprodol to prescribe to individuals based on previous data will be effective for treatment of anxiety

VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis

We present a data-driven generative framework for synthesizing blood vessel 3D geometry. This is a challenging task due to the complexity of vascular systems, which are highly variating in shape, size, and structure. Existing model-based methods provide some degree of control and variation in the structures produced, but fail to capture the diversity of actual anatomical data. We developed VesselVAE, a recursive variational Neural Network that fully exploits the hierarchical organization of the vessel and learns a low-dimensional manifold encoding branch connectivity along with geometry features describing the target surface. After training, the VesselVAE latent space can be sampled to generate new vessel geometries. To the best of our knowledge, this work is the first to utilize this technique for synthesizing blood vessels. We achieve similarities of synthetic and real data for radius (.97), length (.95), and tortuosity (.96). By leveraging the power of deep neural networks, we generate 3D models of blood vessels that are both accurate and diverse, which is crucial for medical and surgical training, hemodynamic simulations, and many other purposes. Keywords: Vascular 3D model

VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis

We present a data-driven generative framework for synthesizing blood vessel 3D geometry. This is a challenging task due to the complexity of vascular systems, which are highly variating in shape, size, and structure. Existing model-based methods provide some degree of control and variation in the structures produced, but fail to capture the diversity of actual anatomical data. We developed VesselVAE, a recursive variational Neural Network that fully exploits the hierarchical organization of the vessel and learns a low-dimensional manifold encoding branch connectivity along with geometry features describing the target surface. After training, the VesselVAE latent space can be sampled to generate new vessel geometries. To the best of our knowledge, this work is the first to utilize this technique for synthesizing blood vessels. We achieve similarities of synthetic and real data for radius (.97), length (.95), and tortuosity (.96). By leveraging the power of deep neural networks, we generate 3D models of blood vessels that are both accurate and diverse, which is crucial for medical and surgical training, hemodynamic simulations, and many other purposes.Comment: Accepted for MICCAI 202

Multidisciplinary analysis of bite marks in a fatal human dog attack: A case report

Lethal injuries by animal attacks are a matter of concern for the forensic pathologist; the presented case illustrates a two dogs attack on a 61-year-old man. The authors have focused on a multidisciplinary approach involving forensic pathologists and veterinarians. Materials and Methods: The victim was cycling in the countryside when he was attacked by two dogs that came out of a large house. He was found lying in the street by the homeowners who called for help. The victim was transported to the hospital where he died five days later. According to recovery data and medico-legal autopsy findings the cause of death was septic shock. Results: Forensic pathologists and veterinarians multidisciplinary evaluation revealed lacerations, abrasions, and multiple small punctures constituting bite marks over the entire body. Six skin dowels with bite marks were taken and compared with the dental cast of the dogs. Conclusion: A comparison of the dog dental casts and the bite marks on the victim’s body allowed the identifi-cation of the animals involved in the attack

Motivations to Pursue the Doctoral Degree in Counselor Education and Supervision

Pursuing a doctoral degree in Counselor Education and Supervision (CES) requires a significant commitment. Although there is research on motivations to pursue a doctorate in general, there has not been a specific examination of motivations among those who have pursued a doctorate in CES, which warrants investigation given the diversity of training and potential career paths offered by the degree. In this Q methodology study, 35 students, counselor educators, and practitioners sorted statements pertaining to their motivation for doctoral studies in CES. The sorted statements were correlated and factor analyzed, resulted in four distinct motivations. The motivations are described and implications for CES are discussed

Comparison of Standard Protocols for the Treatment of Canine Leishmaniasis in an Endemic Area with and Without Zinc Oral Supplementation

Successful treatment of canine leishmaniasis (CanL) depends on an effective cellular immune response. Zinc is an essential trace element for the immune system and in dogs with clinical leishmaniasis low serum zinc levels have been reported. The aim of this work was to evaluate the effect of zinc oral administration during treatment of CanL. Eighteen dogs from an endemic area were enrolled showing clinical signs of leishmaniasis and diagnosed by positive parasitological and serological tests. Dogs were subdivided in three treatment groups: MA, meglumineantimoniate 50 mg/kg SC for 30 days with allopurinol 10 mg/kg PO BID for 7 months; MZ, meglumineantimoniate 50 mg/kg SC BID for 30 days with zinc 2.2 mg/kg/die PO for 12 months; MAZ, same as MA group plus supplemented with zinc 2.2 mg/kg/die PO for 12 months. Each dog was monitored for 12 months using clinical and skin scores and some blood biochemical markers. Dogs in MZ and MAZ group showed a better and earlier improvement of clinical and skin scores in comparison to control dogs (MA group). Among few blood markers studied (hemoglobin, albumin, γ globulins and A/G ratio) dogs in MAZ group did improve and earlier than other groups suggesting that zinc improves the condition where allopurinol is also present. The supplementation of zinc in the treatment protocol for CanL increased the serum zinc concentrations. In addition, preliminary data showed in group MZ and MAZ dogs a faster response to therapy and the elongation of the disease-free interval time