36-item Form Research Articles

Referral Patterns to an Ophthalmic Outpatient Clinic in a Tertiary Eye Care Center in Iraq

Purpose: We aim to conduct a comprehensive review of outpatients at a tertiary ophthalmology clinic to evaluate various aspects including the spectrum of eye disorders, referral patterns, reasons for referral, and patient self-assessment, with a particular focus on self-referrals. Study Design: A cross-sectional study. Place and Duration of Study: Ibn Al-Haitham Teaching Eye Hospital from April to May, 2023. Methods: Referral letters were grouped into the primary health center (PHC), secondary hospital, internal referral and private clinic. Referral letter quality was assessed based on clinical information and particular request. Results: A total of 1367 individuals aged 40.8 ± 22.17 years were eligible for study. There were 19.2% referrals form PHC, 18.4% from secondary hospitals, 10.7% from private clinics, 3.3% were internal referrals, 37.2% were self-referred and 11.3% had medical or surgical follow-up. Blurred vision was the predominant complaint of 677 (51.6%) patients. Out of 659 referral letters, 25% scored two essential information items, 5.2% scored three, and only 0.8% scored four items. The majority (97.2%) of letters provided specific requests. Among all, 26.3% of PHC, 38.2% of hospitals, 34.9% of private clinics, 21.7% self-referred and 51.1% of internally referred patients considered their situations difficult. Conclusion: Majority of cases seen in ophthalmology tertiary centers consist of common conditions that could be effectively managed by PHCs and general hospitals. Improved referral standards for specialized medical institutions may reduce tertiary hospital over population.

The Impact of Voluntary Reporting on the Creation of Firm’s Value: A Longitudinal Study

The primary objective of this study is to scrutinize the relationship between voluntary reporting and the creation of firm value within the context of Bangladesh. To achieve this, thirty banks listed on the Dhaka Stock Exchange have been chosen as the focal point of investigation, covering the time span from 2016 to 2020. The study relies predominantly on secondary data extracted from the annual reports of the selected banks. The measurement of voluntary reporting is conducted through the utilization of a checklist comprising 116 information items. Panel data regression models are employed to rigorously test the formulated hypotheses. The aggregate-level analysis of voluntary reporting practices reveals an average reporting level of approximately 55.40%. However, the results from the panel data regression analysis indicate that the voluntary reporting level does not exert a statistically significant influence on company value. This research contributes to the existing body of literature by providing empirical evidence that, in the case of a developing country such as Bangladesh, voluntary reporting alone does not lead to a substantial increase in firm value. The findings underscore the importance of considering contextual factors and the specific economic landscape when assessing the impact of voluntary reporting practices on firm value in diverse settings.

Validation of Kannada Version of the Amsterdam Preoperative Anxiety and Information Scale (APAIS).

Preoperative anxiety is a complex and subjective phenomenon, most commonly observed in patients posted for elective surgery. The Amsterdam Preoperative Anxiety Information Scale (APAIS) has been widely used in preoperative settings to measure anxiety quickly. This study aimed to translate the APAIS into Kannada and to evaluate its psychometric properties. The study involved forward and backward translation of APAIS into Kannada followed by a cognitive interview of 10 patients by clinical psychologist to confirm the correct translation. The translated version was then administered to 240 patients who were posted for elective surgery along with the Visual Analogue Scale for Anxiety (VAS-A). Reliability and internal consistency were assessed by calculating Cronbach's alpha. Construct validity was assessed by principal component analysis and confirmatory factor analysis. Criteria validity was assessed by evaluating the correlation between APAIS and VAS-A. The Kannada-translated version of APAIS was completed by 224 patients posted for elective surgery. Cronbach's alpha was 0.82 and 0.83 for anxiety and need for information items, respectively. Root mean square error of approximation (RMSEA), comparative fit index (CFI),and Tucker-Lewis index (TLI) were 0.07, 0.98, and 0.96, respectively, for three-factor model, indicating it to be best fit for Kannada version of APAIS. The Kannada version of APAIS is a valid and reliable tool for measuring preoperative anxiety in patients undergoing elective surgery.

MOVIEMATE: MOVIE RECOMMENDATION SYSTEM

Abstract— Nowadays, recommendation systems have revolutionized the way we search for things of interest. These systems employ an information filtering approach to anticipate user preferences. Commonly applied in areas such as books, news, articles, music, videos, and movies, recommendation systems play a pivotal role. In this study, we introduce MOVIEMATE, a movie recommendation system. Using content-based approach, MOVIEMATE examines information provided by users to recommend movies customized to their individual preferences. MOVIEMATE streamlines the movie selection process, leveraging the collective movie experiences of other users to efficiently deliver personalized recommendations. Developed in Python using Jupyter Notebook and Streamlit, this system harnesses various types of user data, item information, and past transactions stored in dedicated databases to generate recommendations. Navigating through these recommendations, users can effortlessly discover movies that align with their preferences. Keywords – recommendation system, recommender system, movies, Content-based filtering

Quality of nutritional uptake of community-dwelling, care-dependent older adults in Zurich

Objective: This study evaluated the quality of nutritional uptake of the care-dependent, community-dwelling older adults.Methods: Community-dwelling care-dependent elders were recruited in this study. The food items along with their nutritional content were extracted from the participants’ refrigerators and categorized according to the NOVA classification (G1: unprocessed/minimally processed; G2: processed culinary ingredients; G3: processed; G4: ultra-processed). The nutritional information of the food items was entered into a dietary analysis software that analyzed the content. Data was verified for a normal distribution and non-parametric tests were applied for statistical analysis (p < 0.05).Results: 100 subjects (mean age = 81.1±9.5 y; mean MMSE: 26.6±6.8) participated in this study. The participants had significantly more G1 than G2, G3 or G4 (p < 0.001) foods. Women had more G1 items in their refrigerators than men (rs = 0.372, p < 0.001). Higher socio-economic status indicated a presence of more G1 (rs = 0.313, p = 0.002), G2 (rs = 0.342, p < 0.001) and G4 (rs = 0.237, p = 0.024) foods.Higher cognitive scores revealed an increase in presence of G4 (rs = 0.238, p = 0.023) items. Participants with an increased need for assistance had less G2 (rs = -0.332, p = 0.001), and G4 (rs = -0.215, p = 0.041) foods; age had no influence.Conclusion: The findings of this study confirm that the majority of care-dependent, community-dwelling adults procured healthy dietary aliments for their daily living; however, whether this correlated to the actual nutritional state of these older adults needs to be further investigated. This highlights the need for further investigation and tailored interventions to ensure good nutrition, emphasizing regular assessments and comprehensive support beyond just food access.Clinical relevance: Clinicians must recognize that access to healthy food alone may not ensure good nutrition in older adults. Regular nutritional assessments, personalized dietary interventions, and additional support services like meal preparation assistance, nutritional counseling, and tailored programs are essential to address specific dietary needs and preferences.

Evaluating emotional and subjective responses in synthetic art-related dialogues: A multi-stage framework with large language models

The appearance of Large Language Models (LLM) has implied a qualitative step forward in the performance of conversational agents, and even in the generation of creative texts. However, previous applications of these models in generating dialogues neglected the impact of ‘hallucinations’ in the context of generating synthetic dialogues, thus omitting this central aspect in their evaluations. For this reason, we propose an open-source and flexible framework called GenEvalGPT framework: a comprehensive multi-stage evaluation strategy utilizing diverse metrics. The objective is two-fold: first, the goal is to assess the extent to which synthetic dialogues between a chatbot and a human align with the specified commands, determining the successful creation of these dialogues based on the provided specifications; and second, to evaluate various aspects of emotional and subjective responses. Assuming that dialogues to be evaluated were synthetically produced from specific profiles, the first evaluation stage utilizes LLMs to reconstruct the original templates employed in dialogue creation. The success of this reconstruction is then assessed in a second stage using lexical and semantic objective metrics. On the other hand, crafting a chatbot’s behaviors demands careful consideration to encompass a diverse range of interactions it is meant to engage in. Synthetic dialogues play a pivotal role in this context, as they can be deliberately synthesized to emulate various behaviors. This is precisely the objective of the third stage: evaluating whether the generated dialogues adhere to the required aspects concerning emotional and subjective responses. To validate the capabilities of the proposed framework, we applied it to recognize whether the chatbot exhibited one of two distinct behaviors in the synthetically generated dialogues: being emotional and providing subjective responses, or remaining neutral. This evaluation will encompass traditional metrics and automatic metrics generated by the LLM. In our use case of art-related dialogues, our findings reveal that the capacity to recover templates or profiles is more effective for information or profile items that are objective and factual, in contrast to those related to mental states or subjective facts. For the emotional and subjective behavior assessment, rule-based metrics achieved a 79% of accuracy in detecting emotions or subjectivity (anthropic), and an 82% on the LLM automatic metrics. The combination of these metrics and stages could help to decide which of the generated dialogues should be maintained depending on the applied policy, which could vary from preserving between 57% to 93% of the initial dialogues.

Development and deployment of an adaptive national elementary reading screening test

Increasingly over the past decade, there has been a demand of more thorough documentation of the quality of reading assessments. Yet, available documentation of high-quality measures are often restricted to general framework descriptions providing psychometric information as a token of test quality. In a modern view of validity, understanding what is being measured and how scores are calculated is a prerequisite for good interpretation and use of test scores. The present article aims to document the research and development process of a national adaptive screening test for reading difficulties, in which the envisioned interpretation and use of test scores is guiding the work. Given the mandatory nature of this test the sample consist of 49,828 third grade students aged 8. Significant outcomes from this design process involve detailed information on: (a) choice of sub-tests and item formats, (b) selection of high quality items, (c) choice and design of adaptive model, and finally, a statement on the challenges that are still to be met for such a test to function optimally. The present paper is among the first to, in an open and detailed manner, describe the development process as well as qualities and challenges of an adaptive reading screening test for students of this young age.

Development of the medical adherence scale in adolescents using psychotropic medication and evaluation of validity and reliability in Turkish population

PurposeAlthough treatment non-adherence is relatively high among adolescents, there is a need for standardized measurement tools that measure adherence to treatment in adolescents. This study aimed to develop a new measurement tool to assess the adherence to treatment of adolescents with mental disorders who use psychotropic medication. MethodsThe data of this methodologically designed study were collected between 01.04.2022 and 01.07.2023 in the Department of Child and Adolescent Psychiatry of a university hospital in the Aegean Region of Turkey. The Medication Adherence Reporting Scale and Adolescent Medical Adherence Scale draft form were used for data collection. The scale items were formed from the themes, sub-themes, and statements in the qualitative study that the researchers had conducted with adolescents with mental disorders and their parents, clinicians' experiences, and systematic reviews and meta-synthesis in the literature. The study sample consisted of 95 adolescents with mental disorders. Exploratory factor analysis was performed with Varimax rotation to determine the factorial construct validity of the scale. Internal consistency analyses were performed in reliability analyses, and Cronbach's alpha coefficient was used. ResultsThe mean age of the adolescents was 14.18 years (1.81); 50.5% were male, and 96.8% were attending school. When the mental disorder diagnoses were analyzed, 65.3% of the adolescents were being followed up with Attention Deficit and Hyperactivity Disorder diagnoses, and 58.8% were using stimulants. The 12-item form of the Adolescent Medical Adherence Scale was found to have a three-factor structure with item-total correlation values ranging between 0.26 and 0.66, and these factors were named functionality, responsibility in treatment, and medication adherence. Factor loadings ranged between 0.44 and 0.86, and the items explained 62.98% of the total variance. The internal consistency coefficients of the scale were between 0.69 and 0.83 for the subscales and 0.82 for the total scale. ConclusionBased on the analysis and results used in this study, the Adolescent Medical Adherence Scale is a valid and reliable new measurement tool. Practice implicationsThis tool can be used in clinical settings to evaluate adolescents' treatment adherence and prognosis. Clinical studies conducted with adolescents can also determine adherence to treatment and affecting factors.

Prevalence of menu label use and its association with calorie intake among US adults

The 2018 Federal Menu Labeling regulations require restaurants and similar retail food establishments that are part of a chain with 20 or more locations to provide calorie and other nutrition information for standard menu items. In this study, we describe the sociodemographic correlates of prevalence of menu label use at Food-Away-From-Home (FAFH) establishments and estimate the association between menu label use and calorie intake. We use nationally representative data spanning the years 2007–2018 and multivariable logit regression and ordinary least squares regression models. For FAFH establishments, we find that female respondents have about 26% (95% CI = [1.14, 1.39]) higher odds of using menu labels. Respondents with high school degree have 51 percent higher odds (95% CI = [1.24, 1.85]), respondents with some college education have 107 percent higher odds (95% CI = [1.74, 2.47]) of seeing menu labels. Higher income is associated with 12% (95% CI = [1.08, 1.15]) greater odds of seeing menu labels. Hispanic respondents have 29% (95% CI = [0.62, 0.81]) lower odds of seeing and 79% (95% CI = [1.41, 2.29]) higher odds of using menu labels. Black respondents have 54% (95% CI = [1.35,1.75] higher odds of seeing menu labels at sit-down restaurants. Menu label users at fast-food restaurants reported consuming 202 kcal (95% CI = [-252,-153]) fewer total calories than nonusers and menu label users at sit-down restaurants reported using 181 kcal (95% CI = [-256,-106]) fewer total calories than nonusers. Our findings highlight the sociodemographic disparities in menu label use and provide baseline estimates for future studies evaluating the federal menu labeling regulation.

Insufficient evidence for interactive or animated graphics for communicating probability.

We sought to analyze interactive visualizations and animations of health probability data (such as chances of disease or side effects) that have been studied in head-to-head comparisons with either static graphics or numerical communications. Secondary analysis of a large systematic review on ways to communicate numbers in health. We group the research to show that 4 types of animated or interactive visualizations have been studied by multiple researchers: those that simulate experience of probabilistic events; those that demonstrate the randomness of those events; those that reduce information overload by directing attention sequentially to different items of information; and those that promote elaborative thinking. Overall, these 4 types of visualizations do not show strong evidence of improving comprehension, risk perception, or health behaviors over static graphics. Evidence is not yet strong that interactivity or animation is more effective than static graphics for communicating probabilities in health. We discuss 2 possibilities: that the most effective visualizations haven't been studied, and that the visualizations aren't effective. Future studies should rigorously compare participant performance with novel interactive or animated visualizations against their performance with static visualizations. Such evidence would help determine whether health communicators should emphasize novel interactive visualizations or rely on older forms of visual communication, which may be accessible to broader audiences, including those with limited digital access.

Identification of parameters for electronic distance examinations.

This study investigates the log data and response behavior from invigilated in-person electronic timed exams at the University of Veterinary Medicine Hannover, Foundation, Germany. The primary focus is on understanding how various factors influence the time needed per exam item, including item format, item difficulty, item discrimination and character count. The aim was to use these results to derive recommendations for designing timed online distance examinations, an examination format that has become increasingly important in recent years. Data from 216,625 log entries of five electronic exams, taken by a total of 1,241 veterinary medicine students in 2021 and 2022, were analyzed. Various statistical methods were employed to assess the correlations between the recorded parameters. The analysis revealed that different item formats require varying amounts of time. For instance, image-based question formats and Kprim necessitated more than 60 s per item, whereas one-best-answer multiple-choice questions (MCQs) and individual Key Feature items were effectively completed in less than 60 s. Furthermore, there was a positive correlation between character count and response time, suggesting that longer items require more time. A negative correlation could be verified for the parameters "difficulty" and "discrimination index" towards response time, indicating that more challenging items and those that are less able to differentiate between high- and low-performing students take longer to answer. The findings highlight the need for careful consideration of the ratio of item formats when defining time limits for exams. Regarding exam design, the literature mentions that time pressure is a critical factor, since it can negatively impact students' exam performance and some students, such as those with disabilities, are particularly disadvantaged. Therefore, this study emphasizes finding the right time limits to provide sufficient time for answering questions and reducing time pressure. In the context of unsupervised online exams, the findings of this study support previous recommendations that implementation of a stringent time limit might be a useful strategy to reduce cheating.

TECHNIQUES FOR TRANSLATING CONTENT ON THE RAMADAN EDITION OF THE IKEA INDONESIA WEBSITE

The purpose of this study is to determine the translation strategies applied on the IKEA Indonesia website for the Ramadan edition and to examine how those strategies are applied considering Molina and Albir's (2002) theory. 121 items of information were gathered from the Ramadan category on the official IKEA Indonesia website using a qualitative descriptive method. This study was conducted in four stages: collecting data from the Ramadan category on the IKEA Indonesia website, identifying words, phrases, or clauses, then categorizing data according to the translation techniques, and analyzing the use of translation techniques from the categorized data. The results show that among 18 techniques proposed by Molina and Albir, the variation translation technique takes the most frequent used translation techniques in translating the content with the total occurrence of 38 data (31,4%), followed by literal translation technique with 32 data (26,4%), as well as ‘adaptation’ technique that occur in 16 data (13,2%). The implication of his study is both theoretically and practically beneficial for the study of translation.

Predicting the remaining useful life of rails based on improved deep spiking residual neural network

the remaining useful life (RUL) of rails is important to ensure safe and reliable operation of railway transportation lines. However, the severity of deterioration of rails from different types of damage varies. Multichannel vibrational data collected by sensors can be utilized to identify the relevant complex correlations and temporal relationships; however, existing methods struggle to predict rail damage accurately. Thus, this paper proposes a RUL prediction method for rails based on an improved deep spiking residual neural network. First, multichannel data collected by sensors are used directly as input to the predictive network without requiring a separate feature extraction step. Additionally, an encoding module is designed to adaptively convert the temporal sequences of data into spiking signals to reduce the information loss during the encoding process. Second, a spiking residual convolutional neural network (CNN) is incorporated into the proposed method to extract optimal features. The separable, spiking CNN can model the relationships among multichannel data accurately, and an attention mechanism is implemented to recalibrate the spiking feature maps such that the predictive network can distinguish between items of information effectively. Third, the spiking residual connections are altered to mitigate network degradation caused by the incompatibility between the conventional residual connections and the spiking neural network. Finally, the obtained spiking features are input to a fully connected layer to predict the rail RUL. Experimental results demonstrated that the proposed method can predict the rail RUL accurately, and validation results obtained on a rolling bearing dataset demonstrated the high generalizability of the proposed method.

Generative artificial intelligence in healthcare from the perspective of digital media: Applications, opportunities and challenges

IntroductionThe emergence and application of generative artificial intelligence/large language models (hereafter GenAI LLMs) have the potential for significant impact on the healthcare industry. However, there is currently a lack of systematic research on GenAI LLMs in healthcare based on reliable data. This article aims to conduct an exploratory study of the application of GenAI LLMs (i.e., ChatGPT) in healthcare from the perspective of digital media (i.e., online news), including the application scenarios, potential opportunities, and challenges. MethodsThis research used thematic qualitative text analysis in five steps: firstly, developing main topical categories based on relevant articles; secondly, encoding the search keywords using these categories; thirdly, conducting searches for news articles via Google ; fourthly, encoding the sub-categories using the elaborate category system; and finally, conducting category-based analysis and presenting the results. Natural language processing techniques, including the TermRaider and AntConc tool, were applied in the aforementioned steps to assist in text qualitative analysis. Additionally, this study built a framework, using for analyzing the above three topics, from the perspective of five different stakeholders, including healthcare demanders and providers. ResultsThis study summarizes 26 applications (e.g., provide medical advice, provide diagnosis and triage recommendations, provide mental health support, etc.), 21 opportunities (e.g., make healthcare more accessible, reduce healthcare costs, improve patients care, etc.), and 17 challenges (e.g., generate inaccurate/misleading/wrong answers, raise privacy concerns, lack of transparency, etc.), and analyzes the reasons for the formation of these key items and the links between the three research topics. ConclusionsThe application of GenAI LLMs in healthcare is primarily focused on transforming the way healthcare demanders access medical services (i.e., making it more intelligent, refined, and humane) and optimizing the processes through which healthcare providers offer medical services (i.e., simplifying, ensuring timeliness, and reducing errors). As the application becomes more widespread and deepens, GenAI LLMs is expected to have a revolutionary impact on traditional healthcare service models, but it also inevitably raises ethical and security concerns. Furthermore, GenAI LLMs applied in healthcare is still in the initial stage, which can be accelerated from a specific healthcare field (e.g., mental health) or a specific mechanism (e.g., GenAI LLMs’ economic benefits allocation mechanism applied to healthcare) with empirical or clinical research.

Anterior cruciate ligament reconstruction: effect of graft type and gender on early to mid-term clinical outcomes

IntroductionAnterior cruciate ligament (ACL) rupture is a debilitating condition and often requires surgery to restore joint stability. Common autografts used for reconstruction include patella tendon and hamstring tendons. The primary aim of this study was to evaluate the early to mid-term clinical outcomes of ACL reconstruction using validated patient-reported outcome measures (PROMs). The secondary aim was to compare clinical outcomes between patella tendon and hamstring tendon autografts. The tertiary aim was to compare clinical outcomes between males and females.MethodsPatients with an ACL rupture were evaluated before and after surgery using PROM scores which included Lysholm, Tegner, International Knee Documentation Committee (IKDC), Knee Injury and Osteoarthritis Outcome Score (KOOS), Short Form-12 Item (SF-12) and EQ-5D-5L.ResultsA total of 87 patients were included in the study. All PROM scores significantly improved following surgery (p < 0.001) at a mean follow-up time of 28 months (range 12 to 88 months). The patella tendon subgroup (n = 27) had superior post-operative results as compared to the hamstring tendon subgroup (n = 60) for KOOS sport and recreation (p = 0.005), KOOS quality of life (p = 0.025), KOOS overall (p = 0.026), Tegner (p = 0.046) and IKDC (p = 0.021) scores. There was no significant difference of PROM scores between males (n = 60) and females (n = 27) (p > 0.05).Conclusions ACL reconstruction significantly improves clinical outcomes for patients with symptomatic instability consequent to ACL rupture. Overall, patella tendon autograft resulted in better clinical outcomes as compared to hamstring tendon autograft following surgery. Gender did not influence clinical outcome following ACL reconstruction.

How consumers with hedonic (vs utilitarian) purchase motive use item-price (vs price-item) presentation order as a mechanism to justify their hedonic purchase

PurposeThis study aims to investigate the moderating role of hedonic and utilitarian purchase motives for the presentation order effect. Although past research finds that presenting item first and price later (e.g. 70 items for $29) increases consumers’ purchase intention more than presenting the information in the opposite order (e.g. $29 for 70 items), the effect was mostly examined in a hedonic consumption context. This study examines whether the effect is applicable for hedonic purchases but is less applicable for utilitarian purchases, and why.Design/methodology/approachSeven experiments tested the moderating effect of purchase motives for the presentation order effect. Two serial mediation analyses were conducted to examine the underlying mechanism.FindingsThe “item-price” (vs “price-item”) order increases hedonic purchases, but not utilitarian purchases. Because consumers feel guilty about hedonic purchases, they engage in motivated information processing to perceive greater value from their hedonic purchase when item (benefit) information is presented first and price (cost) information is presented later. Perceiving greater value reduces guilt, which consequently increases hedonic purchases. In contrast, the order effect is not observed for utilitarian purchases that do not elicit guilt. When a price discount is offered, the order effect is reversed because actual savings justify hedonic purchases better than perceived savings resulting from motivated information processing.Practical implicationsWhen promoting hedonic products, marketers are recommended to present item information before price information, unless a price discount is offered, in which case the price should be presented first.Originality/valueThis research introduces a novel moderator for the presentation order effect and a novel underlying mechanism, driven by the motivation to alleviate guilt associated with hedonic purchases.

SHARP (SHort Answer, Rationale Provision): A New Item Format to Assess Clinical Reasoning.

Many non-workplace-based assessments do not provide good evidence of a learner's problem representation or ability to provide a rationale for a clinical decision they have made. Exceptions include assessment formats that require resource-intensive administration and scoring. This article reports on research efforts toward building a scalable non-workplace-based assessment format that was specifically developed to capture evidence of a learner's ability to justify a clinical decision. The authors developed a 2-step item format called SHARP (SHort Answer, Rationale Provision), referring to the 2 tasks that comprise the item. In collaboration with physician-educators, the authors integrated short-answer questions into a patient medical record-based item starting in October 2021 and arrived at an innovative item format in December 2021. In this format, a test-taker interprets patient medical record data to make a clinical decision, types in their response, and pinpoints medical record details that justify their answers. In January 2022, a total of 177 fourth-year medical students, representing 20 U.S. medical schools, completed 35 SHARP items in a proof-of-concept study. Primary outcomes were item timing, difficulty, reliability, and scoring ease. There was substantial variability in item difficulty, with the average item answered correctly by 44% of students (range, 4%-76%). The estimated reliability (Cronbach α ) of the set of SHARP items was 0.76 (95% confidence interval, 0.70-0.80). Item scoring is fully automated, minimizing resource requirements. A larger study is planned to gather additional validity evidence about the item format. This study will allow comparisons between performance on SHARP items and other examinations, examination of group differences in performance, and possible use cases for formative assessment. Cognitive interviews are also planned to better understand the thought processes of medical students as they work through the SHARP items.

Quality of Life and Clinical Impairment in Spanish Adolescent Anorexia Nervosa Patients.

Eating disorders have serious physical, mental and social consequences that can affect the quality of life of the sufferer. This study aimed to evaluate the relationship between the severity of ED-related psychopathology and clinical impairment in adolescents with anorexia nervosa (AN) as well as their perception of health-related quality of life. Eighty-six Spanish young women with AN completed a set of questionnaires assessing eating disorder pathology, clinical impairment, and quality of life. The set included the following instruments: the Eating Disorder Examination Questionnaire, Clinical Impairment Assessment, Short Form-12 Item Health Survey, and the Eating Disorder-Specific Heath-Related Quality of Life instrument. Descriptive and regression analyses were applied to identify associations between variables. Higher scores on clinical impairment domains were associated with greater impairment of mental and physical health. Moreover, clinical impairment domains and concerns due to ED were related to a lower quality of life. In conclusion, adolescents with AN have a poor quality of life. Moreover, the findings suggest that the clinical features of impairment may serve as severity indicators of quality of life.

State of Knowledge Management among German firefighters

This paper introduces the results of a survey that was conducted among German firefighters in 2023 to investigate the current situation of knowledge management. We want to examine which systems and techniques are in use, what the end users' expectations towards knowledge management are, and which requirements a system should fulfill. We focus on all stages of the crisis management circle, from prevention and preparation to the response to an incident as well as recovery. The goal of this survey is to evaluate firefighters' needs in order to be able to define requirements for a knowledge management system that will be accepted by the users. The exchange of information items between entities (emergency units, authorities, and enterprises) and other IT systems is one important aspect. We identify existing information and knowledge management systems, and means to improve user satisfaction by leveraging users to maintain a system with relevant and up-to-date information and knowledge.

Analysis of ontologies and policy languages to represent information flows in GDPR

This article surveys existing vocabularies, ontologies and policy languages that can be used to represent informational items referenced in GDPR rights and obligations, such as the ‘notification of a data breach’, the ‘controller’s identity’ or a ‘DPIA’. Rights and obligations in GDPR are analyzed in terms of information flows between different stakeholders, and a complete collection of 57 different informational items that are mentioned by GDPR is described. 13 privacy-related policy languages and 9 data protection vocabularies and ontologies are studied in relation to this list of informational items. ODRL and LegalRuleML emerge as the languages that can respond positively to a greater number of the defined comparison criteria if complemented with DPV and GDPRtEXT, since 39 out of the 57 informational items can be modelled. Online supplementary material is provided, including a simple search application and a taxonomy of the identified entities.