Effective Screening Process Research Articles

Diabetic retinopathy: Screening, prevention, and treatment.

Internists are integral in the multidisciplinary approach to diabetic retinopathy, contributing significantly to the management of diabetes and diabetes-related complications. Effective screening processes, timely referrals, and strategic diabetes management are imperative to prevent and mitigate the consequences of diabetic retinopathy. The evolution of treatments for diabetic retinopathy has markedly improved vision outcomes and reduced the burden on patients. Despite these advances, a collaborative approach to care is essential to prevent the progression of vision impairment and manage associated complications.

Strategic approaches in oral squamous cell carcinoma diagnostics using liquid biopsy.

Liquid biopsy is a noninvasive diagnostic technique used for monitoring cancer utilizing specific genetic biomarkers present in bodily fluids, such as blood, saliva, or urine. These analyses employ multiple biomolecular sources including circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes (that contain DNA fragments) to detect genetic biomarkers that can predict, disclose, and/or monitor cancers. Levels of these biomarkers can inform on the presence of cancer, its genetic characteristics, and its potential treatment response and also provide predictive genetic predisposition information for specific cancers including oral squamous cell carcinomas (OSCC). Liquid biopsies can aid cancer management as they offer real-time dynamic information on the response to say chemotherapy or radiotherapy and recurrence following surgical excision. Unlike traditional tissue biopsies, which are invasive with a degree of morbidity and require specific tumor location sampling, liquid biopsies are noninvasive and can be repeated frequently. For oral squamous cell carcinoma, on which this review focuses, liquid biopsy of blood or saliva can be valuable in predicting susceptibility, providing early detection, and monitoring the disease's progression and response to therapy. This review gives a general narrative overview of the technology, its current medical usage, and advantages and disadvantages compared with current techniques and discusses a range of current potential biomarkers for disclosing OSCC and predicting its risk. Oral squamous cell carcinoma is all too often detected in the late stages. In future, liquid biopsy may provide an effective screening process such that cancers including OSCC will be detected in the early stages rather than later when prognosis is poor and morbidity and debilitation are greater. In this screening process, periodontists and hygienists have a critical role in that they are adept in examining mucosa, they see patients with shared risk factors for periodontitis and OSCC, namely smoking and poor oral hygiene, and they see patients frequently such that OSCC examinations should be a routine part of the recall visit. With this additional screening manpower, oral medicine and oral surgery colleagues will detect OSCC earlier and this coupled with new techniques such as liquid biopsy may greatly decrease global morbidity in OSCC.

Reducing the risk of missing soil contamination by integrating multi-investigated methods in a retired chrome salt factory

An effective contamination screening process is essential for mitigating the risk of overlooking pollution during site investigations. While Electrical resistivity tomography (ERT) and portable X-ray Fluorescence (XRF) offer quick assessments of contaminated areas, there is a notable gap in research regarding ERT’s application in the unsaturated soil layer, and portable XRF’s use for screening polluted samples in chromium-contaminated sites. This study gathered soil pollution and electrical resistivity data from a decommissioned chrome salt factory, employing drilling, sampling, XRF, and ERT methods. Predominantly, sulfate and chromium emerged as the pollutants, with concentrations ranging from 19.24 to 12700.00 mg/kg for sulfate, 0.65 to 3000.00 mg/kg for Cr(VI), and 12.00 to 27800.00 mg/kg for total Cr, respectively. Polluted hotspots were identified by lower apparent soil resistivity compared to the background levels at corresponding depth. Notably, a significant inverse correlation was observed between sulfate and Cr(VI) concentration and soil resistivity, particularly with sulfate (R2 =0.48) demonstrated through a power function fit at depths ranging from −4 to 0 m. The XRF analysis for total Cr concentration exhibited a significant correlation (Pearson’s r = 0.67) with chemical analysis, confirming 1000 mg/kg as an effective screening threshold. In light of these findings, this study proposes a scientific procedure that integrates drilling, sampling, ERT, and XRF for soil contamination investigation. This framework aims to support similar site assessments, reducing the risk of overlooking contamination.

Improving emotional and psychosexual well-being screening in women living with polycystic ovary syndrome: experiences from the United Kingdom and India.

With increasing evidence of emotional well-being disorders associated with polycystic ovary syndrome (PCOS), effective screening processes are of utmost importance. We studied the impact of using questionnaires to screen for emotional and psychosexual well-being across different models of care for PCOS. We analysed the data from the surveys to assess the difference in the prevalence of emotional and psychosexual ill-being across ethnicity and region. In this prospective cohort study, we invited all women attending consultations for PCOS in Birmingham, UK, and Bengaluru and Navi Mumbai, India. Those who consented to participate in the study were invited to complete a pre-clinic survey about socio-demographic data, Hospital Anxiety and Depression Scale (HADS), Body Image Concern Inventory (BICI), Beliefs about Obese Person scale (BAOP), and Female Sexual Function Index score (FSFI) and a post-clinic survey on clinic experience, lifestyle advice, and specialist referral. A total of 115 women were included in this study. The rate of questionnaire completion was 98.3% (113/115), 97.4% (112/115), 93.04% (107/115), and 84.3% (97/115) for HADS, BICI, BAOP, and FSFI, respectively. In the post-clinic survey, 28.8% reported they were screened for anxiety, 27.1% for depression, and 45.8% for body image concerns. The prevalence of anxiety, depression, and body dysmorphic disorder through pre-clinic survey was 56.5% (50.0% UK vs 59.5% India, P = 0.483), 16.5% (13.9% UK vs 17.7% India, P = 0.529), and 29.6% (36.1% UK vs 26.6% India, P = 0.208), respectively. Surveys with validated questionnaires can improve screening for emotional and psychosexual well-being associated with PCOS which may be missed by ad hoc screening during consultations.

Diving deeper into distress screening implementation in oncology care

Background Responding to calls for additional research that identifies effective distress screening (DS) processes, including referral practices subsequent to screening and receipt of recommended care, we engaged in qualitative research as part of a larger (mixed methods) study of distress screening. This qualitative inquiry of oncology professionals across different facilities in the United States examined routine DS implementation, facilitators and challenges staff encounter with DS processes, and staff members’ perceived value of DS. Participants and Methods We conducted key informant interviews and focus groups with staff in 4 Commission on Cancer (CoC)-accredited oncology facilities (a total of 18 participants) to understand implementation of routine DS within oncology care. We used a rigorous data analysis design, including inductive and deductive approaches. Results Respondents believe DS enhances patient care and described ways to improve DS processes, including administering DS at multiple points throughout oncology care, using patient-administrated DS methods, and enhancing electronic health records infrastructure to better collect, record, and retrieve DS data. Respondents also identified the need for additional psychosocial staff at their facilities to provide timely psychosocial care. Conclusions Results reinforce the value of DS in cancer care, including the importance of follow-up to screening with psychosocial oncology providers. Understanding and resolving the barriers and facilitators to implementing DS are important to ensure appropriate psychosocial care for people with cancer. Insights from oncology staff may be used to enhance the quality of DS and subsequent psychosocial care, which is an essential component of oncology care.

To screen or not to screen: Exploring and addressing effective screening processes for trauma among forced migrants

BackgroundExisting literature points to higher rates of trauma disorders for forced migrants than general or immigrant populations. The process of identification and screening for trauma in this population however is not straightforward and is actually controversial in some circles. Furthermore there are no definitive guidelines for mental health and social service providers on the “when” “who”, “what” “why”, “where”, and “how” of trauma screening. ObjectivesImportantly, few studies have included insights into the screening process from service providers and forced migrants themselves through participatory research methods. This study investigates effective screening processes for trauma and examines benefits and pitfalls of current practices from the perspectives of both migrants themselves as well as health service providers that serve them. DesignWe used a qualitative approach to identify and analyze key themes from focus group interviews with key informants (service providers and trauma experts providing social and medical services in the community) and forced migrants (from Cameroon, Ethiopia, Honduras, and Tanzania). ResultsOur results comprise forced migrant definitions of and approaches to coping with trauma, reservations about engaging with providers, positive experiences with and impacts of screening, limitations and negative aspects of screening, helpful screening practices, and effective tools and questions for screening. ConclusionsDrawing on these themes, we offer recommendations that may help inform future screening approaches and trauma-informed service provision. The study ultimately helps those in the field to reflect on current trauma screening practices for forced migrants and consider how new insights derived from rich discussions with migrants and their service providers may alter existing screening processes- which few

Mechanism analysis of solvent selectivity and energy-saving optimization in vapor recompression-assisted extractive distillation for separation of binary azeotrope

Octane and p-xylene are common components in crude gasoline, so their separation process is very important in petroleum industry. The azeotrope and near azeotrope are often separated by extractive distillation in industry, which can realize the recovery and utilization of resources. In this work, the vapor–liquid equilibrium experiment was used to obtain the vapor–liquid equilibrium properties of the difficult separation system, and on this basis, the solvent extraction mechanism was studied. The mechanism of solvent separation plays a guiding role in selecting suitable solvents for industrial separation. The interaction energy, bond length and charge density distribution of p-xylene with solvent are calculated by quantum chemistry method. The quantum chemistry calculation results and experiment results showed that N-formylmorpholine is the best solvent among the alternative solvents in the work. This work provides an effective and complete solvent screening process from phase equilibrium experiments to quantum chemical calculation. An extractive distillation simulation process with N-formylmorpholine as solvent is designed to separate octane and p-xylene. In addition, the feasibility and effectiveness of the intensified vapor recompression assisted extraction distillation are also discussed. In the extractive distillation process, the vapor recompression-assisted extraction distillation process is globally optimal. Compared with basic process, the total annual cost can be reduced by 43.2%. This study provides theoretical guidance for extractive distillation separation technology and solvent selection.

Identifying human trafficking indicators in the UK online sex market

This study identifies the presence of human trafficking indicators in a UK-based sample of sex workers who advertise their services online. To this end, we developed a crawling and scraping software that enabled the collection of information from 17, 362 advertisements for female sex workers posted on the largest dedicated platform for sex work services in the UK. We then established a set of 10 indicators of human trafficking and a transparent and replicable methodology through which to detect their presence in our sample. Most of the advertisements (58.3%) contained only one indicator, while 3,694 of the advertisements (21.3%) presented 2 indicators of human trafficking. Only 1.7% of the advertisements reported three or more indicators, while there were no advertisements that featured more than four. 3, 255 advertisements (19.0%) did not contain any indicators of human trafficking. Based on this analysis, we propose that this approach constitutes an effective screening process for quickly identifying suspicious cases, which can then be examined by more comprehensive and accurate tools to identify if human trafficking is occurring. We conclude by calling for more empirical research into human trafficking indicators.

Autism Spectrum Screening Checklist (ASSC): The Development of a Scale to Identify High-Risk Individuals Within the Children's Mental Health System.

Autism Spectrum Disorder (ASD) is a complex childhood onset neurodevelopmental disorder that has become the fastest growing developmental disability. Due to the increased demand for diagnostic assessments and subsequent increased wait times, standardized screening as part of regular clinical practice is needed. More specifically, there is an important need for the development of a more streamlined screening tool within an existing assessment system to identify those at greatest risk of having ASD. The current study utilized data from ~17,000 assessments obtained within the province of Ontario, based on the interRAI Child and Youth Mental Health (ChYMH) and Child and Youth Mental Health and Developmental Disability (ChYMH-DD), to develop a scale to identify children who have a higher likelihood of having autism. The scale was then tested on a trial population with data from the interRAI Early Years instrument. Further analyses examined the predictive validity of the scale. The Autism Spectrum Screening Checklist (ASSC) was found to be a good predictor of ASD with a sensitivity of 0.73 and specificity of 0.62, at the recommended cut-point of 2+. The results were consistent across several age ranges, specifically from 2 to 21 years of age. The ASSC scale provides an initial screen to help identify children and youth at heightened risk for autism within larger populations being assessed as part of routine practice. The main goal for the development and implementation of the ASSC scale is to harness the power of the existing interRAI assessment system to provide a more efficient, effective screening and referral process. This will ultimately help improve patient outcomes through needs-based care.

Abstract MP20: Implementation Of Social Determinants Of Health Screening And Referrals In A Medicaid Accountable Care Organization: A Qualitative Study

Introduction: Systematic screening for social determinants of health (SDOH), such as food and housing insecurity, is increasingly implemented in primary care, particularly in the context of Accountable Care Organizations (ACO), to improve health outcomes. The objective of this study was to explore aspects of implementation of annual SDOH screening and referrals in a Medicaid ACO, including facilitators and barriers and experiences of community resource staff. Methods: Qualitative interviews were conducted between January and March 2020 with fifteen staff (eight frontline resource staff and seven managers) in a large health care system in Massachusetts. Interviews focused on barriers and facilitators of screening for and addressing SDOH and the experiences of staff involved in this process. Interviews were audio recorded, transcribed, coded, and analyzed using the Framework Method of qualitative analysis. Results: Facilitators for addressing SDOH included close collaborations with community organizations, updated resource lists, leadership buy-in, and trusting relationships with patients. Barriers that prevented staff from addressing patients’ social needs effectively included high caseloads, time constraints, inefficiencies in workflows, lack of availability of resources, and patient characteristics (e.g., immigration status, mental health challenges). Resource staff described rewarding and stressful aspects of their jobs, including distress when unable to address challenging social needs such as housing. The Table provides examples of quotes from staff related to the themes identified in this study. Conclusions: Facilitators and barriers for successful SDOH screening and referrals occur at the health system, community, and individual levels and must be considered for developing effective screening and referral processes. The psychological burden on resource staff is an important and underrecognized factor that could impact patient care and contribute to staff burnout.

Early indicators of cardiovascular disease are evident in children and adolescents with cerebral palsy

BackgroundCardiovascular disease (CVD) is a leading cause of early mortality among young adults with cerebral palsy. While low physical activity in childhood has been hypothesized as a potential contributor to increased CVD risk in early adulthood, little is known about timing of vascular disease progression and the presence of subclinical atherosclerosis has not been extensively evaluated in children with cerebral palsy. ObjectiveThe aim of this study was to determine if measures of vascular structure and function are different between children and adolescents with and without cerebral palsy. MethodsIn this cross-sectional study, we measured carotid intima-media thickness (CIMT), and brachial artery flow-mediated dilation (FMD) of children with and without cerebral palsy. Group means for CIMT and brachial artery FMD absolute (FMDA) and percent of relative change (FMDR%) were compared using Wilcoxon rank-sum tests. ResultsA total of 26 children and adolescents with cerebral palsy (46.1% girls, mean age = 15.0 ± 2.0 years) and 19 controls (68.4% girls, mean age = 13.3 ± 2.6 years) participated. Children with cerebral palsy had significantly greater average CIMT (0.43 ± 0.02 mm) than children without cerebral palsy (0.41 ± 0.01 mm, p = 0.04), and lower FMDA (0.16 ± 0.15 mm vs. 0.29 ± 0.20 mm; respectively, p = 0.03). ConclusionsChildren and adolescents with cerebral palsy may exhibit impairments in vascular structure and function which represent an increased risk of premature atherosclerosis compared to children without cerebral palsy. Additional research to identify risk factors specific to children with cerebral palsy that would support the development of effective screening processes for early identification would enable clinicians to implement targeted preventive strategies.

Clinicopathological Variants of Breast Cancer in a Tertiary Care Hospital in Pakistan

Background: Breast cancer is a growing phenomenon among females which has ever-lasting ramifications on the patient as well as the family. The only way of subjugating breast cancer is through an efficient and effective screening and subsequent treatment process. Objective: This study aimed at identifying the different clinicopathological patterns of breast cancer and the age group most frequently targeted by CA breast. Study Design: A prospective study. Settings: Fauji Foundation Hospital (FFH), Rawalpindi and Foundation University Medical College (FUMC) Pakistan. Duration: Six months from January 2018 to June 2018. Methodology: This study included 224 female patients, irrespective of their nationality by convenience sampling, who underwent any kind of breast surgery. The patients were evaluated according to their age, side of breast involved, site of lump in the breast, histopathology report and type of lesion (inflammatory, benign or malignant). The data was entered and analyzed using IBM SPSS version 25. Results: Our study sample of 224 individuals was found to have about 23 different histopathological variants of breast cancer. Invasive ductal carcinoma was found in almost all age groups and it was also the most common variant (80.8%), followed by invasive lobular carcinoma (4%). Majority of the cases were recorded in the elderly age bracket from 55 to 65 years. Right breast was found to be involved in 53.6% of the cases whereas left breast involvement was at 44.2%. 5 patients had lesions in both of their breasts. Upper outer quadrant was affected in 88% females followed by upper inner quadrant (6.7%). All four quadrants were involved in only 3 patients. Conclusion: This study concluded that invasive ductal carcinoma is the commonest clinical as well as pathological type of CA breast. 181 females out of a total of 224 had invasive ductal carcinoma. Therefore, this particular breast cancer type merits our special attention. Our study further concluded that most of the breast pathologies were found in elderly females aged between 55 and 65 years.

Differential expression levels of CD151 enable enrichment of atrial cardiomyocytes derived from human induced-pluripotent stem cell

Abstract Introduction Human iPSCs-derived cardiomyocytes (hiPSCs-CMs) are heterogeneous populations that contain ventricular-like CMs (VCMs), atrial-like CMs (ACMs) and pacemaker cells. Isolation of pure populations of each hiPSCs-CM subtype corresponding to the target regions of the heart enables effective drug screening process and stable engraftment of hiPSCs-CMs (e.g. ventricular cardiomyocytes without impurities). Purpose Atrial and ventricular cardiomyocytes develop from distinct mesoderm populations, and many of different genes are expressed between two subtypes. Since our method of cardiomyocytes differentiation from hiPSCs mimics in vivo cardiomyocytes development, we hypothesized that two subtypes could be separated by differentially expressed genes in hiPSCs-CMs differentiation process. In this study, we focused cell surface genes which are useful for analysis by flow cytometry, and then identified cell surface marker that can distinguish atrial and ventricular cardiomyocytes from hiPSCs-CMs. Methods We performed an antibody-based screening using hiPSCs-CMs induced under atrial induction condition (AIC) and ventricular induction condition (VIC) by flow cytometry. To identify cell surface markers which enable discrimination of cardiac subtypes, we isolated the cell populations using the antibodies against the cell surface markers. Quantitative PCR was performed to analyze expression levels of subtype-specific genes in sorted cells. We confirmed subtype classification of cells using patch-clamp method. Results We identified CD151 as a novel candidate of atrial/ventricular selectable marker. The expression level of CD151 was low in most hiPSCs-CMs under AIC. In these cells, CD151-low cells highly expressed atrial genes compared to CD151-high cells. In contrast, the expression level of CD151 was high in most hiPSCs-CMs under VIC. In these cells, CD151-high cells highly expressed ventricular genes compared to CD151-low cells. Furthermore, we investigated the electrophysiological properties of CD151-high and -low cells using patch-clamp experiments. As expected, the cells showing atrial type action potential were enriched in AIC with low expression of CD151 (n=17). On the other hand, CD151-high cells (n=16) contained no atrial CMs, but mostly nodal like cells. In addition, CD151-low cells in AIC were affected with action potential duration by exposure of atrial specific channel blocker (4-aminopyridine) and activator (carbachol). In VIC, CD151-high cells (n=16) demonstrated ventricular type action potential property compared to CD151-low cells (n=21). Conclusion These results suggest that CD151 is a useful marker which can enrich ACMs from hiPSCs-CMs. Because these enriched ACMs are uniform population, it may be appropriate for atrial-selective drug screening. Additionally, this marker can reduce contaminated ACMs from hiPSCs-CMs cultured in VIC. Action potential of CD151-high/low CMs Funding Acknowledgement Type of funding source: Other. Main funding source(s): Takeda pharmaceutical company limited, Japan society for the promotion of science(JSPS) KAKENHI

Cost-Effectiveness Analysis of Prenatal Screening Program for Thalassemia Between Semi-accelerated Screening Step and Current Program

Background: Thalassemia is a genetic blood disorder with high incidence in Thailand. Its treatment includes blood transfusion and iron chelating therapy for life long that lead to high cost. Therefore, effective screening processes are required to prevent the newborn with thalassemia.
 Objective: To determine the cost-effectiveness of prenatal screening program for thalassemia between a semi-accelerated screening program and the current program.
 Methods: Decision tree model was developed under provider perspective. Cost, effectiveness and probabilities data were from literature review. One-way sensitivity analysis was performed to explore around inputs in the model.
 Results: The expected costs of the semi-accelerated screening program and the current program were ฿609.29 and ฿462.44, respectively. The expected outcomes to detect a severe thalassemia in fetuses from the semi-accelerated program and the current program is 34 cases and 8 cases in 10 000 couples, respectively. Incremental cost-effectiveness ratio was ฿57 499.80 per case detected.
 Conclusions: The expected costs of the semi-accelerated screening program was higher than the current programs, but the number of fetuses with thalassemia detected from the semi-accelerated screening program was more than the current programs.

Systematic Methods on Machine Learning Techniques for Clinical Predictive Modelling

Predictive modelling is a mathematical technique which uses Statistics for prediction, due to the rapid growth of data over the cloud system, data mining plays a significant role. Here, the term data mining is a way of extracting knowledge from huge data sources where it’s increasing the attention in the field of medical application. Specifically, to analyse and extract the knowledge from both known and unknown patterns for effective medical diagnosis, treatment, management, prognosis, monitoring and screening process. But the historical medical data might include noisy, missing, inconsistent, imbalanced and high dimensional data.. This kind of data inconvenience lead to severe bias in predictive modelling and decreased the data mining approach performances. The various pre-processing and machine learning methods and models such as Supervised Learning, Unsupervised Learning and Reinforcement Learning in recent literature has been proposed. Hence the present research focuses on review and analyses the various model, algorithm and machine learning technique for clinical predictive modelling to obtain high performance results from numerous medical data which relates to the patients of multiple diseases.

Development and validation of a method to screen for co-morbid depression by non-behavioral health practitioners treating musculoskeletal pain.

BACKGROUND:Although diagnosis and treatment of depressive illness is outside the scope of practice for non-behavioral health practitioners such as occupational therapists, physical therapists, kinesiotherapists, and chiropractors, it frequently is comorbid with painful musculoskeletal disorders such as low back pain and it negatively affects outcomes, including return to work. As psychologically-informed practice becomes more widely implemented without the immediate availability of behavioral health practitioners, safe and effective methods to screen for and appropriately triage depressive illness by nonbehavioral health practitioners are necessary.OBJECTIVES:To demonstrate the efficacy and validity of a method employed by non-behavioral health practitioners to screen for and appropriately triage musculoskeletal pain patients who also are experiencing depressive illness.METHODS:As part of a previously-published psychometric research study conducted in a community-based musculoskeletal pain rehabilitation program, a method was developed for nonbehavioral health practitioners to screen for and appropriately triage patients for co-morbid depressive illness, thus providing the current opportunity to examine the effects of depressive illness on work outcomes. The first step in the two-step process involves a 22-item questionnaire, providing scores used in the second step to triage for outside consultation with behavioral health practitioners. This paper describes the screening method and its application in an observational study of the impact of depressive illness on work outcomes.RESULTS:Among 156 consecutive patients who were presenting with musculoskeletal pain disorders to an outpatient rehabilitation program, 22.3% also were identified to have co-morbid clinical depression. The screening process allowed all patients to continue in the rehabilitation program. Those who were already receiving behavioral health care were encouraged to inform care providers of their participation in the program. Those who were not receiving behavioral health care were successfully triaged to care outside of the clinic. Depressive illness was found to affect success in the program, confirming the validity of the screening process for outpatient rehabilitation program participants experiencing chronic pain.CONCLUSIONS:A simple and effective depression screening process that triages patients without interruption of musculoskeletal treatment can be employed by nonbehavioral health practitioners. Because return to work outcomes were found to be negatively affected by depressive illness, this approach has the potential to improve overall program efficacy.

The Profiling Game at Border Crossings

Developing effective screening processes in border crossings, in order to identify violators within large groups of mostly innocent people, is an important and difficult task, as it is not possible nor effective to screen every passenger with the same intensity required to detect a violator. Profiling has been applied for several decades as a tool to deal with this task, but there is still no proof of its usefulness. Our main motivation is to study whether profiling is indeed helpful, and if so, how it should be used so as to maximize its effectiveness. We consider an interaction that takes place in some crowded border crossing, where passengers can be affiliated into different groups. We offer a sequential game-model with three players: a defender, who acts first and decides on a screening process, an attacker, who acts second and may recruit a passenger as a violator, and the recruited passenger, who acts last and may choose not to violate, as it has its own private violating motivation. We study variants of the base game, which differ by the choice of screening policy (an announced profiling, an unannounced profiling, no-profiling), the attacker's knowledge of the screening policy, and the costs of recruiting passengers of different groups. These variants help us to answer the extremely challenging social and strategic questions regarding the controversy over the need of profiling.

Beyond cognitive measures: Empirical evidence supporting holistic medical school admissions practices and professional identity formation.

This article was migrated. The article was marked as recommended. Background: Medical schools seek admissions methods that identify applicants who hold promise to become physicians who will navigate and shape the future medical landscape. The focus on traditional cognitive measures for admission has prompted calls for holistic admissions review during the past five years. Yet, empirical evidence linking selection measures to holistic admissions practices has not been fully established, including their relationship with professional identity formation over time. A non-cognitive admissions situational judgment screening test (CASPer) measuring personal and professional characteristics was added to the University of Illinois College of Medicine admissions process two years ago, as we implemented a new curriculum that emphasizes professional identity development. Purpose: This study examined associations among admissions measures (Medical College Admission Test [MCAT], grade point average [GPA], interview, and CASPer), and their predictive relationships with curricular measures of professional identity formation (Professional Identity Essay [PIE]) and moral reasoning (Defining Issues Test [DIT2]). Methods: Data were taken from two entering cohorts ( n = 596; entering class of 2017 and 2018 across 3 regional sites). Correlations and regression analyses were used to examine associations between admissions and professional identity measures. Results: CASPer and in-person admissions interview ratings had significant positive correlations, suggesting that CASPer can contribute to effective screening processes. In addition, CASPer demonstrated statistically significant positive relationships with professional identity (CASPer and PIE, r=.10, p<.05) and a measure of moral reasoning (CASPer and DIT2 type indicator, r=.09, p<.05). Association between CASPer and PIE remained consistent, even after controlling for MCAT, interview, and GPA. Conclusion: Our institutional focus on professional identity formation has provided new ways to conceptualize students' readiness for medical school - demonstrated academic rigor as well as signs of professionalism, ethics, and motivation. Non-academic factors measured in situational judgment tests may promote better alignment of admissions practices and desired educational outcomes.

Predicting Generalized Anxiety Disorder Among Women Using Decision Tree Based Classification

Mental health presents as one of the greatest challenges to the current generation. It has been reported that about 5% of the population in developed countries are affected by generalised anxiety disorder (GAD) with women twice as likely to be affected as compared to men. Predicting GAD among women is no longer an arduous task especially with the assistance of data mining technology. In this paper, a methodology encompassing data collection, data pre-processing, data analysis and data mining process using random forest approach is drawn for an effective prediction. The random forest approach is one of the classification data mining techniques which is embedded with good predictive characteristic. The result of this study in term of accuracy, sensitivity and specificity conforming to its high predictive performance in GAD prediction based on depressive symptoms. Besides that, several popular machine learning techniques are also applied to the resultant dataset of this study and the comparison result attests to random forest algorithm outperformed other methods. The generated prediction model is expected to provide an effective screening process to detect generalised anxiety disorder earlier among women in Malaysia.

Predicting generalised anxiety disorder among women using decision tree-based classification

Mental health presents as one of the greatest challenges to the current generation. It has been reported that about 5% of the population in developed countries are affected by generalised anxiety disorder (GAD) with women twice as likely to be affected as compared to men. Predicting GAD among women is no longer an arduous task especially with the assistance of data mining technology. In this paper, a methodology encompassing data collection, data pre-processing, data analysis and data mining process using random forest approach is drawn for an effective prediction. The random forest approach is one of the classification data mining techniques which is embedded with good predictive characteristic. The result of this study in term of accuracy, sensitivity and specificity conforming to its high predictive performance in GAD prediction based on depressive symptoms. Besides that, several popular machine learning techniques are also applied to the resultant dataset of this study and the comparison result attests to random forest algorithm outperformed other methods. The generated prediction model is expected to provide an effective screening process to detect generalised anxiety disorder earlier among women in Malaysia.