Demand For Training Research Articles

Workplace aggressions on hospital workers: A current and prevalent problem with a high demand for training.

Workplace aggressions on hospital workers is a very frequent and under-reported problem. The novel objective of our study was to analyze the number of workplace aggressions per hospital worker. Other objectives of the study were to analyze the management knowledge and interest in receiving training on aggressions by hospital workers. An anonymous survey was handed out among all professionals in a university hospital. A total of 1118 anonymous surveys were collected. The responders declared that throughout their working life they had suffered some sort of verbal aggression in the hospital in 766 cases (68.5%) and physical aggression in 393 cases (35.2%). Multiple logistic regression analyses found higher risk of receiving physical and verbal aggression in the nursing category and in the Emergency, Critical Care or Psychiatry Units, and a higher risk of receiving physical aggression in women. The score on the level of personal knowledge regarding the legal, physical, and psychological management of aggressions (score 0-10 for each of the 3 aspects) was 2.91±2.68 in legal management, 2.97±2.77 in psychological management and 2.91±2.76 in physical management. The opinion about the interest of receiving training (score from 0 to 10) on the legal management of hospital aggressions was 8.90±1.72, on psychological management was 8.85±1.78 and on physical management was 8.88±1.78. Workplace aggression on hospital workers mainly affects women, the nursing category and the Emergency, Critical Care or Psychiatry Units. Hospital workers showed little knowledge on the topic but a great interest in receiving training.

Mental health of young talented football players in an African context: A cross-sectional observational study

BackgroundElite sport is a potentially pathogenic environment due to stressors like dual-career, high training demands, and performance pressure. Recent evidence suggests that athletes are at high risk of mental health issues. Even though the FIFA is increasingly paying attention, efforts directed towards young talented footballers are scarce. Few studies have even been conducted on young talented footballers in Africa. The majority of epidemiological studies on athletes also suffer from an analytical approach that does not highlight athletes' mental health profiles. This study aims to describe the mental health profile and their prevalence of young talented footballers in three African representative countries. MethodsThe study applied an observational-based cross-sectional research design with aspiring footballers from three sub-regions of Africa and aged between 10 and 23. The data was collected face-to-face from March to November 2022. Three screening tools were used to measure three mental health outcomes: Satisfaction With Life Scale (subjective well-being), Patient Health Questionnaire 9-item (depression), and Generalized Anxiety Disorder 7-item scale (anxiety). The mental health outcomes were rates and scores of well-being, depression, and anxiety, used in latent profile analysis. Findings507 male young talented footballers (263[51∙9%] Cameroonians, 73[14∙4%] Moroccans, and 171[33∙7%] Ivorians) were included in the analysis with a mean age of 15∙1 (SD 2∙37) years. Screening of mental health states revealed that 367(72∙3%) and 412(81∙8%) of these players experienced anxiety and depressive symptoms respectively and 155(30∙7%) experienced low well-being. Differences in mental health outcomes were noted between countries, age groups and competition levels. Three profiles of mental health condition were also identified, namely moderate mental health (Profile 1), languishing (Profile 2) and flourishing (Profile 3). InterpretationThe youth of football academies in the three African countries studied have a specific mental health profile, revealing a high prevalence of common mental disorders in the African context. These findings underline the need to enhance the awareness of mental health issues in young African players and provide tailored support. FundingFIFA.

DM-GAN: CNN hybrid vits for training GANs under limited data

Generative adversarial network (GAN) training demands substantial data and computational resources. This paper aims to explore an economical approach for generating novel images with limited image data, addressing the challenge of data scarcity. Our contributions involve resolving the few-shot image generation challenge through the development of an unsupervised hybrid generative adversarial network named DM-GAN. We introduce a lightweight hybrid module (DC-Vit) comprising convolution and visual transformation, merging local and global features to enhance image perception, expressiveness, and ensure stable image generation. Additionally, a multi-scale adaptive skip connection module is incorporated to effectively mitigate the feature loss problem arising from inter-layer jumps, thereby producing more complete and regular images. To enhance the texture learning process and improve the quality and realism of synthesized images, we integrate the gray conjugate matrix into the loss function. Empirical evaluations are conducted on small sample datasets at various resolutions, including publicly accessible collections of art paintings, real-life photographs, and proprietary artifact image datasets. The experimental results unequivocally demonstrate the qualitative and quantitative superiority of our model over existing methods, underscoring its efficacy and robustness.

Analysis of supply and demand for sports medicine fellowship training: 2012-2022.

The recruitment of high-quality applicants is critical to the vitality of the sports medicine physician workforce. To analyze changes in the total number of available training positions, applicants, and unfilled training positions in the Sports Medicine Match from 2012 to 2022. This was a retrospective cohort study of sports medicine fellowship applicants. Accreditation Council for Graduate Medical Education-accredited sports medicine fellowship training programs. A total of 3763 individuals applying for sports medicine fellowship training from 2012 to 2022. Not applicable. Annual number of applicants, training positions, and number of unfilled training positions. From 2012 to 2022, the annual number of training positions in sports medicine increased from 177 to 353 (99% increase, p < .001) while the annual number of applicants increased from 256 to 428 (67% increase, p < .001). The annual applicant-to-training position ratio decreased (1.4 to 1.2, p < .001). Annual match rates increased for both U.S. MD graduates (64% to 86%, p < .001) and non-U.S. MD graduates (64% to 77%, p < .001). U.S. MD graduates had higher match rates than non-U.S. MD graduates in 2021 (79% vs 70%, p < .05) and 2022 (86% vs 77%, p < .05). The percentage of applicants who matched at their first (36%-36%, p > .05), second (14%-15%, p > .05), and third (9%-8%, p > .05) ranked programs did not change. The percentage of applicants who did not match decreased (33%-19%, p < .001). The percentage of available fellowship training positions that went unfilled decreased (8%-2%, p < .001). Interest in sports medicine fellowship training is increasing as evidenced by an increasing number of applications and decreasing rate of unfilled training positions. Continued monitoring of future match cycles is important given projected shortages in the physician workforce.

A Comparative Analysis of Machine Learning Models in News Categorization

The constant stream of news nowadays highlights the necessity for meticulous assessment to ensure that the information accurately reaches its intended audience with the least amount of delay least delay. Despite the flexibility and efficiency of Deep Learning (DL) models, their intricate training and substantial resource demands pose significant challenges for their deployment in real-time applications. In this regard, this study evaluates the performance of resource-efficient Machine Learning (ML) techniques – Multinomial Naive Bayes (MNB), Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR) – in categorizing news. Based on the results, all the evaluated models attain a commendable level of accuracy in news categorization. Notably, the SVM excels, achieving an accuracy rate of 98% and a mean squared error of 0.28. This performance exemplifies the robust effectiveness of classical ML models in the categorization of news, particularly when enhanced by a suitably tailored preprocessing pipeline.

Who uses night trains and why? A mixed-method study profiling night train users in Switzerland

Addressing air travel demand is a key open challenge in transitioning to a low-carbon society. In Switzerland, where most flights are from/to nearby European countries, their substitution with night train services is a promising alternative. However, still little research investigates whether the demand for night trains is well-established and the motivations behind it. We aim to bridge this gap through a mixed-method study involving 389 Swiss residents who travelled by night train in 2022/23. A web survey was first conducted to identify latent classes of participants based on their daily and long-distance travel mode choices and evaluate relevant predictors of class membership. Participants of each class were then randomly selected to be involved in an in-depth interview on personal experiences and motivations underlying their choices. Results identify three classes of travellers distinguished by a predominant use of rail and public transport (greens), mixed long-distance travel mode choices and car-oriented daily mobility (pragmatists), preference for flying combined with public transport and active daily mobility (dissonants). Travel cost reduction is the only motivation significantly differentiating pragmatists and dissonants from the greens. This result suggests that fluctuations in ticket prices are the main driving force in shifting demand from flights to night trains.

Supporting advanced practice: feedback from a mental health, community and primary care advanced practice support project in South Yorkshire, UK

Background: Despite the significant input from Heath Education England (HEE), now NHS England (NHSE), there are still significant variations around advanced practice programmes, support and training, particularly in less developed areas such as mental health, community posts and primary care. To help target these areas, and to support the NHS Long Term Plan (2023) to increase the number of advanced clinical practitioners (ACPs), the Faculty of Advanced Practice South Yorkshire recruited three ACP leads from mental health, community, and primary care backgrounds to establish a support project led by one professional lead. These leads were able to utilise their lived experience of completing the ACP MSc programme and working as an ACP to help trainee advanced clinical practitioners (tACPs) navigate their journey. The ACP leads also developed a variety of educational events, which further supported the trainees' needs. Aim: This article reports the feedback given via an online questionnaire from trainees that accessed the project, which ended in March 2024. Its aim is to highlight the often-undervalued concept of using clinicians personal experience regarding advanced training and practice, to mentor, support and ultimately retain the future ACP workforce. Methods: An email with a link to a questionnaire was sent to 128 tACPs or recently qualified ACPs that had applied for their training via the Faculty of Advanced Practice South Yorkshire. The questionnaire, created in Microsoft Forms, was completed anonymously, and produced both numerical and free-text data. The questionnaire solicited feedback around: the number of contacts they had and how they contacted; the ACP leads; types of support accessed; and the educational events available. Free text answers were analysed by the author (CJ) and a second reviewer (SF) to generate a consensus on themes. Results: A total of 64 clinicians responded, of which 43 were tACPs, 10 were ACPs, five had other job titles (community matron, pharmacist, practice nurse) and five did not state what their job title was. Responses suggest that the support accessed from the project was highly beneficial and could not be gained elsewhere. A key factor in the project's success was the ACP leads' lived experience of having previously completed advanced practice training, as well as their ability to tailor learning events to the trainees' needs. Conclusion: Meeting the demands of ACP training in areas where the role is less established remains an ongoing challenge. It seems some of these challenges relate to the lack of practical support being provided by employers or higher education institutions, such as lived experience of completing the task of ACP training. Support projects, like the one discussed in this article, appear aptly placed to help fulfil these needs and begs the question ‘why aren't there more?’, especially when advanced practitioners are fundamental to the future healthcare workforce.

Current status and needs of in-service training for psychiatric nurses in 24 provinces of China: a cross-sectional survey.

To investigate the current situation and need for post-competence training for psychiatric nurses in China and provide a reference for the development of training programs for psychiatric nurses. A cross-sectional design. A cross-sectional study was conducted from August to October 2023 with 435 psychiatric nurses from 34 hospitals in 24 provinces of mainland China. A self-administered questionnaire was used for data collection. Descriptive statistics, non-parametric tests, and chi-square tests were used for data analysis. The training content for psychiatric nurses is extensive, and the training load is large. Psychiatric nurses have high training demands for first aid knowledge, emergency handling ability, and anti-riot skills. Nurses with different years of experience have different training needs. The training needs of psychiatric nurses in specialized and general hospitals also different. The training status of psychiatric nurses is not consistent with the demand. Managers should combine this with psychiatric nurses' own work needs to develop practical and effective training programs.

High-Intensity Interval Training and Physiological Demands in Wheelchair Tennis Players: A Pilot Study

High-Intensity Interval Training and Physiological Demands in Wheelchair Tennis Players: A Pilot Study

United States Marine Corps Recruit Training Demands Associated With Performance Outcomes.

United States Marine Corps' (USMC) recruit training is a 13-week program designed to maximize physical and mental performance adaptations. The purpose of this study was to evaluate the training demands and characteristics that are associated with performance outcomes during USMC recruit training. A total of 196 recruits (M = 97 and W = 99) were monitored and tested throughout training. Laboratory-based performance testing occurred at the start of weeks 2 and 11 and consisted of body mass assessments, countermovement vertical jump, and isometric mid-thigh pull. Military-specific performance testing occurred twice within the first 8 weeks of training and included the physical fitness test (PFT) and combat fitness test (CFT) implemented by the USMC. Resilience data were collected at week 2 using the Connor-Davidson Resilience Scale. Workload, sleep, and stress responses were monitored at weeks 2, 7, and 11. Recruits were provided with a wearable tracking device which utilized heart rate and accelerometry-based technology to determine energy expenditure (EE), distances (DIS), and sleep metrics. Data were averaged over a 3-day period. Salivary cortisol testing occurred at the start of each monitoring week. Change scores were calculated for performance tests, and body mass was calculated from data obtained at week 2 to week 11. Area under the curve was calculated for the workload, sleep metrics, and cortisol responses using the trapezoidal method. Pearson product-moment correlations (r) were used to assess the relationships between training demands and performance. An α level of 0.05 was used to establish significance. A moderate positive correlation was found between changes in body mass and peak power (P < .001; r = 0.43). Weak positive correlations were found between changes in body mass and peak force (P = .002; r = 0.28), as well as body mass and resilience (P = .03; r = 0.19). A moderate negative correlation was observed between changes in body mass and PFT (P < .001; r = -0.49). A weak negative correlation was found between changes in body mass and EE (P = .003; r = -0.24). A weak negative correlation was found between changes in peak power and EE (P = .001; r = -0.29). A weak positive correlation was found between changes in peak power and changes in CFT (P = .05; r = 0.19) A weak negative correlation was found between changes in sleep continuity and CFT (P = .02; r = -0.20). A weak negative correlation was found between cortisol and changes in PFT (P = .05; r = -0.20). A weak negative correlation was found between cortisol and both EE (P = .001; r = -0.27) and DIS (P = .045; r = -0.16). A weak negative correlation was found between EE and sleep continuity (P < .001; r = -0.34). Weak negative correlations were found between sleep duration and both DIS (P = .01; r = -0.18) and steps (P = .003; r = -0.21). Increases in body mass throughout training were positively associated with strength and power changes, but negatively related to PFT scores. Changes in peak power related to improvements in CFT scores; however, higher workloads (i.e., EE) were negatively associated with peak power. The identification of the USMC physical and physiological training demands that are associated with performance outcomes may be a valuable resource to guide conditioning efforts to boost military readiness.

Colorectal endoscopic submucosal dissection in the USA: The current state and future perspectives.

Endoscopic submucosal dissection (ESD) is a transformative advancement in the endoscopic management of superficial gastrointestinal lesions. Initially conceived for the treatment of early gastric cancer, ESD has demonstrated proficiency in achieving en-bloc resection of superficial gastrointestinal lesions. ESD has experienced widespread acceptance in Japan and East Asia; however, its adoption in the USA remains delayed. This initial hesitancy could be attributed to procedural complexity and training demands; nonetheless, recently, ESD has been gaining popularity in the USA. This is due to the advancements in endoscopic technology, tailored training programs, and cumulative evidence regarding the efficacy and safety of ESDs. This review aimed to deliberate the historical progress, current implementation, and prospective trajectory of ESDs in the USA. With ongoing clinical research, technological integration, and educational efforts, ESD is likely to become the gold standard for managing large gastrointesitinal lesions. This progress marks an imperative step toward less invasive, more precise, and patient-centric approaches regarding advanced therapeutic endoscopy in the USA.

A novel physics-aware graph network using high-order numerical methods in weather forecasting model

In this paper, we present a novel architecture for accurate weather forecasting within the framework of Physics-aware Graph Networks (PaGN), which aims to improve the prediction of weather time series by integrating both data and physical equations defined on sparsely distributed spatial domains. This approach employs geometric deep learning by accounting for both supervised loss and physics loss. Solely in supervised learning, data-driven training demands a large amount of data, whereas integrating physics information can reduce this requirement, resulting in faster training. The physics awareness also provides a stronger inductive bias and better generalization, directing the machine learning process by clarifying the complexity of weather data. Thus, a more accurate discretization of physics equations can enhance the physics awareness of the complex weather dynamics. Meanwhile, weather data is essentially gathered at observatories that are not located densely, since covering the Earth with numerous observatories is prohibitively expensive. Given its reliance on graph structure, the proposed PaGN is well-suited for handling sparsely distributed data particularly defined on arbitrary geometric domain. One of the main contributions of this study is the use of high-order numerical methods approximating physics equations defined on graph neural networks for achieving accuracy improvements. The fractional graph Laplacian operator is further integrated with the physics equations to account for the non-local characteristics of complex weather data. For computational efficiency, the accuracy improved PaGN architecture is smoothly implemented in the embedding space. A series of numerical tests on weather datasets is performed to verify the improved accuracy, robustness, and applicability of the proposed methodology. We first carry out the numerical study on the synthetic datasets obtained from the physics equations with an extra forcing term. We then extensively investigate the accuracies of weather forecasting for various configurations in terms of the geophysical regions and the accuracy-improved PaGN approaches for diffusion and wave equations. Moreover, we emphasize that the fractional graph Laplacian operator incorporated into our PaGN model can further improve the accuracy for weather forecasting.

Case study: Evaluating deep-water start techniques and training demands in seated slalom waterskiing for an athlete with paraplegia.

Recreational and competitive slalom waterskiing is increasingly popular among individuals with spinal cord injuries (SCI), particularly for those with paraplegia using sit-skis. A key component of slalom skiing is the deep-water start (DWS), yet little is known about the physiological and physical demands of this activity when the athlete is seated. This study aims to fill this gap by focusing on the training requirements for a seated slalom athlete. Focusing on a young male athlete with paraplegia, this case study evaluates the effectiveness and efficiency of traditional (TDWS) and alternative (ADWS) DWS techniques during seated slalom waterskiing sessions. It assesses internal training load (TL) through heart rate (HR) zones and session rating of perceived exertion (sRPE), alongside pre- and post-session handgrip strength measurements to gauge peripheral muscle fatigue. Performing the ADWS, achieving a full success rate, proved more effective but slightly more time-consuming than TDWS, which had limited success. HR during DWS maneuvers ranged from 63.2 to 81.3% of maximal HR, with most sessions occurring below the ventilatory threshold, thus perceived as hard effort. A moderate yet non-significant correlation was found between HR and sRPE-based TL. A significant reduction in handgrip strength post-session underscores the activity's demands. These insights illuminate the technical, physiological, and physical challenges in mastering DWS for seated slalom athletes with SCI, providing valuable guidance for the development of tailored training programs and techniques in this sport.

A temporal partial domain adaptation network for transferable prognostics across working conditions with insufficient data

Variations in equipment working conditions cause distribution drifts in condition monitoring data, thus impeding the accuracy of remaining useful life (RUL) prediction. Although numerous transfer learning methods have been developed for cross-domain prognostics, it is still challenging to collect enough target domain data to meet training demands because of economic and safety concerns. Therefore, a temporal partial domain adaptation network (TPDAN) is proposed for transferable prognostics across working conditions without run-to-failure data in the target domain. Firstly, the domain discrepancy is appropriately measured by a stage-weighted maximum mean discrepancy (SW-MMD), allowing for the inconsistency of the RUL distribution of available data between domains. Secondly, the ranking-based feature regularization is developed to align the relative position of samples in the feature space and the label space. It facilitates the exploitation of temporal information inherent in the samples and restrains the destruction of the degradation properties of features. By performing domain adaptation based on the above tools, domain-invariant and degradation-aware features can be extracted by the TPDAN to provide reliable knowledge transfer across working conditions. The effectiveness of TPDAN has been validated, and experimental results demonstrate the compelling transferable RUL prediction performance even when run-to-failure data is unavailable in the target domain.

Evaluation of the Physiological and Psychological Impact of Ballet Performances Across Age Cohorts: An Observational Uncontrolled Case Study.

Background: Ballet, epitomized by iconic seasonal performances such as "The Nutcracker," combines artistic expression with considerable physical demands. This study investigated the physiological and psychological responses of ballet dancers to the demands of intensive training and performance, with a specific focus on "The Nutcracker." Methods: Thirty- eight dancers volunteered for the study, including 6 youths (10.5 + 1.8 years, n = 6 female), 7 adolescents (15.4 + 1.1 years, n = 5 female), and 25 adults (21.1 + 2.1 years, n = 20 female). Employing an uncontrolled observational design, this pilot study tracked key biomarkers such as CK-MM for muscle damage and B-ALP for bone health, alongside psychological measures via PANAS-C/PANAS and DASS-21. Results: Significant findings included a post-performance reduction in cortisol and depression levels. Conclusion: These insights advocate for tailored strategies that address the multifaceted needs of dancers, acknowledging the intricate balance required to maintain peak performance and overall health within the demanding realm of professional ballet.

Study on the Alignment Between Talent Training Directions and Employment Market Demands in the Landscape Architecture Industry

Currently, talent training in Chinese universities for landscape architecture is mainly divided into three directions: “landscape planning and design,” “landscape construction management,” and “landscape plant planting and maintenance.” However, with the background of the slowing urbanization process and the widespread demand for composite talents in society, it remains to be verified whether the traditional three major talent training directions in landscape architecture align with the job demands in the current construction market. Based on a survey and analysis of over 300 industry practitioners, this study found a clear trend of merging the three major employment directions into “landscape design and construction” and “landscape plant planting and maintenance.” This presents new requirements and directions for the skill training of landscape architecture majors in universities and provides insights into the alignment between talent training and employment demands in other industries.

Empowering pharmacy professionals to enhance public health nutrition: a mixed methods study

Unhealthy dietary patterns stand as the foremost risk factor for noncommunicable disease- associated morbidity and mortality(1). As widely accessible healthcare providers, pharmacy professionals’ potential to catalyze improvements in public health nutrition is substantial, offering a means to combat the escalating epidemic of obesity and NCDs through tailored interventions, services, and education(2,3).Our study employed a mixed-methods approach to assess the role of pharmacy professionals in promoting nutrition advice and healthy dietary practices.An online questionnaire (N=200) was designed and conducted to evaluate pharmacy professionals’ nutrition knowledge, the advice given in various diet-related conditions (e.g. obesity, type 2 diabetes, cardiovascular disease risk factors, malnutrition, sustainable diets), practices in delivering diet- related guidance within their routine practice and perceived roles and future ambitions of pharmacy professionals towards nutrition counselling, yielding both quantitative and qualitative insights.Subsequently, qualitative interviews and focus group discussions (N=19) were conducted, engaging pharmacists, nutritionists and dietitians to gather insights essential for the development of a comprehensive nutrition toolkit tailored for pharmacy practice.These interviews delved deeper into the subject, with the goal of designing a nutrition toolkit that empowers pharmacists with the knowledge, tools, and resources needed to play a more active and impactful role in promoting nutrition and healthy lifestyle practices among their patients. Thematic analysis was conducted, and emerging themes and subthemes were identified.Our findings indicate that a significant portion of participants in our study are involved in providing nutrition and diet advice for various health conditions. The majority of pharmacists considered diabetes programmes having a high level of importance (84%), followed by weight management services (78%), hypertension management (86%), and healthy diet campaigns (63.5%). However, our knowledge and confidence rating questions revealed a significant gap in training and a clear need for educational materials tailored for pharmacists to enhance their ability to provide nutrition advice effectively. Key themes identified in open-text questions were referrals and collaboration, training and education needs, wider needs (changes in the public health system, materials/resources, integration and implementation of nutrition in pharmacy practice) and perceived roles as pharmacists in providing nutrition advice (patient support, feeling responsible, specialised focus areas).Qualitative findings underscore the pressing demand for nutrition training and education to deliver comprehensive services, as well as the necessity for collaborative efforts with dietitians and nutritionists to ensure effective care and the improvement of referral pathways in pharmacy practice.This research contributes to the advancement of public health nutrition by recognizing the potential role of pharmacy professionals as key players in the dissemination of nutrition knowledge and fostering healthy behaviours within the community. The results will guide us in the collaborative development of a nutrition toolkit tailored for pharmacy practice, employing a co-design approach.

Demand for abortion training and technical assistance in primary care: Unmet need and programmatic interventions

ObjectiveQuantify primary care provider requests for abortion training and technical assistance (TA) and availability of programs to support abortion provision. Study designWe reviewed requests for training and TA from four programs focused on capacity building for abortion care. Collectively, these programs serve every region of the United States. ResultsBetween January 1, 2021 – September 30, 2022, the programs received 207 requests for training and/or TA from individuals and organizations in 30 states. Approximately 60% of requests went unfulfilled due to programs’ capacity constraints. ConclusionsUnmet demand for training and TA to integrate abortion into primary care is significant. Increasing the availability of training and TA could increase the abortion workforce and improve access to care.

Body checking and avoidance among dancers

Dancers are at heightened risk for eating disorders (EDs) and have job and training demands that obscure ED assessment and likely impede treatment. Two behavioral manifestations of ED psychopathology that may present uniquely in a dance environment are body checking and body avoidance. The current study sought to provide a foundational understanding of the phenomenology of body checking and avoidance among dancers by assessing the reliability (i.e., internal consistency) of existing body checking and avoidance measures and the relationships, or convergent validity, between measures of body checking and avoidance and measures of related constructs. Eighty professional and pre-professional (i.e., conservatory level) dancers (78.8 % female) from seven dance genres completed self-report measures of body checking and avoidance, ED pathology, clinical perfectionism, depression, and anxiety. Across the dancer sample, body checking and avoidance measures demonstrated adequate internal consistency. More frequent body checking and body avoidance was strongly related to higher levels of ED pathology. There were moderate to strong correlations between body checking and body avoidance and clinical perfectionism, depression, and anxiety such that higher body checking and body avoidance was related to higher clinical perfectionism, depression, and anxiety. Exploratory analyses found no significant differences between ballet dancers and dancers of other dance genres; professional dancers scored in the normative range on measures of body checking and body avoidance. Dancers' qualitative descriptions of body checking and avoidance revealed behaviors not included in existing questionnaires, such as unique mirror use behaviors, technology-assisted body checking, and the checking and avoidance of body parts relevant to the dance-specific body ideal. Results support the inclusion of body checking and avoidance interventions in ED treatments for dancers (particularly pre-professional dancers) and emphasize the need for dancer-specific ED assessment methods.

Suicide Risk Among Medical Students Associated With Loneliness, Burnout, and Depressive Symptoms.

Medical students face elevated risks of depression and suicide due to rigorous training demands. However, comparative research between medical and non-medical students is limited, hindering understanding of specific risks. This study compared 337 students (89 medical) on suicide risk, depression, perfectionism, burnout, loneliness, and internet addiction. Medical students showed significantly higher suicide risk, depression, perfectionism, burnout, and loneliness. Regression analysis identified medical student status, depressive symptoms, and loneliness as significant predictors of suicide risk. Mediation analysis revealed loneliness and depressive symptoms mediating the relationship between medical student status and suicide risk. Strategies to address mental health risks among medical students are crucial, including early screening and interventions. However, this study's limitations include self-report measures and a predominantly non-medical student sample. Further research is needed to explore causal relationships and interventions effectively.