Unique Dimensions Research Articles

YOLOv8 Tabanlı Derin Öğrenme Teknikleri Yoluyla Giardia İntestinalis Görüntü Algılamanın Geliştirilmesi

Giardia intestinalis (G. intestinalis), a parasitic organism that causes gastrointestinal infections, represents a huge challenge in precisely identifying species from microscopic images. The complexities of accurate diagnosis and treatment require a shift towards automated solutions that enhance diagnostic efficiency and accuracy. In this study, we take advantage of the YOLOv8 deep learning model, comparing its performance with traditional methods, to enhance Giardia intestinalis detection.Our dataset, which has been carefully obtained by Burdur Mehmet Akif Ersoy University Faculty of Veterinary Medicine, Department of Pathology adds a unique dimension to our research. The dataset consists of 264 images of G. İntestinalis and is subjected to preprocessing with RGB/grayscale filters and contrast-limited adaptive histogram equalization for optimal model input.Deep learning architectures tested, including YOLOv8, show an accuracy rate of 95%. Notably, the YOLOv8 model shows promising results, indicating its potential to transform the diagnosis of G. intestinalis. Beyond immediate application, our research paves the way for the integration of YOLOv8 into broader healthcare contexts, promising effective tools for managing G. İntestinalis infections.Furthermore, our study allows the transfer of G. İntestinalis diagnostic expertise from expert veterinarians to the AI model. Veterinarians working in this field can now obtain preliminary diagnostic information through a mobile application. This innovative approach enhances the competence of veterinarians and expands their experience in this field.This research significantly pushes the boundaries in G. İntestinalis image analysis but also puts the foundation for the broader use of advanced deep learning techniques in medical applications. The implications of our findings extend beyond G. İntestinalis diagnosis, providing insight into the transformative impact of YOLOv8 in medical and biological image analysis. Our study opens the way for future developments, shaping the path of intelligent computer vision methods in real-world medical applications.

Occupational Safety and Health for Adult Saudi Arabian Women: Utilizing National Anthropometric Data.

In the last five years, the female labor force has increased rapidly in Saudi Arabia. This is due to the new government's vision to empower women. For many decades, Saudi females were excluded from working in certain fields due to cultural restrictions. Nowadays, Saudi women are not only joining the service workforce but are currently employed in more physically demanding careers, such as manufacturing and military jobs, which were previously dominated by males. It becomes necessary to design workplaces, tools, and equipment to safely accommodate the female physical attributes, which include body dimensions. This study presents the anthropometric measurements of Saudi Arabian adult females. In total, 504 female subjects aged 20-70 participated in the study. Thirty-eight body measurements, including weight and triceps skinfold, were taken in sitting and standing postures. The main contribution of this study is to provide a national anthropometric database of Saudi females, which is very limited, especially for females in the age groups under study. The availability of such data will allow foreign and local manufacturers to design usable and safe products and workspaces for a wide range of Saudi adult females. The findings reveal that there are no significant differences in the body dimensions of Saudi females across all age groups, except for stature height, eye height, chest depth, skinfold (mm), sitting height, buttock-knee length, and hip breadth. The study also reveals that Saudi females' body sizes are different from other Asian, Middle Eastern, and British nations, which invalidates the assumption of using other nations' body measurements to estimate Saudis' body measurements. Utilizing the supermarket cashier workstation to assess the appropriateness of commercial station fit for Saudi females' body dimensions, the results underscore the crucial role of anthropometric measurements in addressing differences between product design and the unique body dimensions of Saudi females. The identified anthropometric mismatch highlights potential risks, emphasizing the threat to the working safety of Saudi females. Moreover, the data can be used by health professionals as a base to evaluate the health of Saudi adult females. Descriptive statistics and extreme values are determined. The data are presented in standard anthropometric tables.

Research on the Innovation of Education Mode of Art and Design Specialties in Colleges and Universities under the Background of Big Data

Abstract Art and design professional education can not keep up with the development speed of the industry, and there is no reference to the market demand data, failing to keep pace with the times, which brings many negative impacts on the employment of students. This paper suggests an art design professional education model that incorporates VR interactive scene technology for this reason. Through the double camera, we simulate the visual principle of the human eye, collect three-dimensional data from VR interactive scenes, and use the image coordinate system and pixel coordinate system conversion operations to pre-process the collected data. The optimal layout solution is sought by adjusting the layout to generate a realistic 3D model of the teaching scene and to realize the construction of the VR interactive scene. The principle and implementation process of the art professional education model supported by the VR interactive scene is elaborated, and the experimental comparison method is used to empirically analyze the art and design professional education model integrating VR technology. The results show that there is a significant difference between the experimental group and the control group in the dimensions of adaptability (0.004) and uniqueness (0.044) of design thinking and the cultivation of design thinking ability (0.016) (P<0.05), which indicates that the art and design professional education model integrating the VR scene interaction technology constructed in this paper has a significant effect on the enhancement of design thinking ability of college students.

Lean Thinking and Resource Efficiency in the Design of Public Services

Efficiency in public service organisations is often driven by the need to reduce costs and increase productivity due to the economic and government pressure to make the best use of reduced resources. However, efficiency in public services can go beyond cost cutting, thinking about how organisations design and deliver their service offerings to achieve better outcomes while using the government fund more efficiently to turn public money into positive outcomes for both individuals and society. Through a combined method of literature review and interviews, the authors aim to systematically collect and analyse existing contributions on the current public services design and how Lean Thinking can promote resource efficiency in public service organisations, followed by validating the results through interviews in different public organisations focusing on the role of human resources in the services design. The findings suggest that implementing Lean Thinking allows public service organisations to streamline their resource allocation, eliminate waste, and improve productivity, resulting in more efficient service delivery, user satisfaction, and improved organisational performance. The authors took a panoramic view across different public organisation types, which can be extended through future research on specific organisation types or different regions to explore unique dimensions and find relevant conclusions.

Qualitative analytical results of complex order nonlinear fractional differential equations with robust control scheme

In this manuscript, our work was about a qualitative study for a class of multi-complex orders nonlinear fractional differential equations (FDEs). Our methodology utilized the topological degree theory and studied a novel operator tailored for non-singular FDEs with $ \mathrm{T} $-Riemann-Liouville (T-RL) fractional order derivatives. The primary objective was to prove the existence and uniqueness of solutions for both initial and boundary value problems within the intricated framework. With the help of topological degree theory, we contributed to a wider understanding of the structural aspects governing the behavior of the considered FDE. The novel operator proposing for non-singular FDEs added a unique dimension to our analytical problem, offering a versatile and effective means of addressing the challenges posed by these complex systems for their theoretical analysis. For the practical implications of our theoretical framework, we presented two concrete examples that reinforced and elucidated the key concepts introduced. These examples underscored our approach's viability and highlighted its potential applications in diverse scientific and engineering domains. Through this comprehensive exploration, we aimed to contribute significantly to advancing the theoretical foundation related to the study of multi-complex nonlinear FDEs. Moreover, a fixed-time terminal sliding mode control (TSMC) has been developed. This proposed control strategy for eliminating leukemic cells while maintaining normal cells was based on a chemotherapeutic treatment that was not only effective but also widely acknowledged to be safe. This strategy was evaluated using the fixed-time Lyapunov stability theory, and simulations were included to illustrate its performance in terms of tracking and convergence.

Novel Journal Metrics in Cardiothoracic Surgery: How Different Are Contemporary Metrics From the Impact Factor?

Despite shortcomings, impact factor (IF) remains the "gold standard" metric for journal quality. However, novel metrics including the h-index, g-index, and Altmetric Attention Score (AAS; mentions in mainstream/social media) are gaining traction. We assessed correlations between these metrics among cardiothoracic surgery journals. For all cardiothoracic surgery journals with a 2021 Clarivate IF (N = 20), the 2-year IF (2019 to 2020) and 5-year IF (2016 to 2020), h-index, and g-index were obtained. Two-year journal-level AAS (2019 to 2020) was also calculated. Journal Twitter presence and activity was sourced from Twitter and the Twitter application programming interface. Correlations were assessed using Spearman correlation, and coefficients of determination were calculated. IF demonstrated a moderate-strong positive correlation with the h-index (rs = 0.48 to 0.77) and g-index (rs = 0.49 to 0.79) and a moderate correlation with AAS (rs = 0.53 to 0.58). The 2-year IF accounted for 25% to 49% of variability in the h-index, 27% to 55% of variability in the g-index, and 32% of variability in the AAS. Among journals with a Twitter account (N = 10), IF was strongly correlated with Twitter following (rs = 0.81 to 0.86), which was in turn strongly correlated with journal AAS (rs = 0.79). Article-level AAS was moderately correlated with citation count (rs = 0.47). IF accounted for only between 25% and 55% of variability in the h-index and g-index, indicating that these newer metrics measure unique dimensions of citation-based impact. Thus, the academic community must familiarize itself with these newer journal metrics. Social media attention may be associated with scholarly impact, although further work is needed to understand these relationships.

Determinants of Economic Sustainability: Exploring the Role of Knowledge Management with the Mediating Influence of Green Innovation in Pakistani Manufacturing SMEs

This study investigates the interconnected dynamics of knowledge management, green innovation, and economic performance within the context of manufacturing Small and Medium-sized Enterprises (SMEs) in Lahore, Pakistan. The primary objective is to explore the impact of knowledge management on the economic performance of SMEs and ascertain the mediating role of green innovation in this relationship. The study adopts a quantitative research design grounded in positivism, targeting a population of manufacturing SMEs operating in Lahore. A sample size of 300 managerial-level employees is selected using a simple random sampling strategy, and data is collected through a survey instrument. The findings of the study reveal a significant positive effect of knowledge management on the economic performance of SMEs, affirming the crucial role of effective knowledge-sharing practices in fostering economic success. Furthermore, the study identifies a significant mediating effect of green innovation, highlighting the importance of incorporating environmentally sustainable practices in the innovation processes of SMEs. This research contributes novelty by contextualizing these relationships within the specific industrial landscape of Lahore, Pakistan, filling a gap in the existing literature. The incorporation of green innovation as a mediator adds a unique dimension to the study, emphasizing the relevance of sustainable practices in driving economic performance for SMEs in Lahore.

A Proof of Concept Study to Assess the Imbalance of Self-Reported Wanting and Liking as a Predictor of Problematic Addictive Behaviors

AbstractTolerance, one of the key features of addiction, is a highly debated criterion for behaviors, considered controversial and difficult to assess. The Incentive-Sensitization Theory of Addiction (IST) provides a robust empirical background on the dynamics of the motivational and hedonic systems underlying addiction, reflecting tolerance. The aim of this proof-of-concept study was to introduce wanting and liking as an IST-based measure of tolerance. Survey data were analyzed on two potentially problematic substance use behaviors (alcohol and nicotine use) and seven potentially problematic behaviors (eating, gaming, pornography use, social media use, internet use, television series watching, and working) of 774 participants (517 women, Mage = 35.8 years, SD = 11.84), using linear regression models. The models describing the relationship between usage frequency and the difference between self-reported wanting and liking were significant for all of the investigated substance use and potential behavioral addictions. As a general pattern, the balance of wanting and liking was disrupted with increasing usage/behavior frequency, with a steady increment in wanting in all investigated cases. The findings indicate that the proposed approach holds promise as an empirically robust tool for addiction research, offering the potential to compare substance and behavioral addictions on a unified dimension.

OLDER ADULTS AND CAREGIVERS AS PARTNERS IN PATIENT- AND FAMILY-CENTERED EDUCATION

Abstract Patient and family-centered education is an approach to the planning, delivery, and evaluation of curricula that is grounded in mutually beneficial partnerships among patients, families, students, and educators. Engaging patients and families in genuine partnerships through health professions education can broaden the student’s perspectives of health to include social, economic, and environmental factors while helping them recognize unique individual dimensions, such as cultural context, capacities, and values, that influence health. While patient-centeredness is a widely recognized component to high-quality healthcare, partnering with older adult patients and caregivers is a less recognized standard in health professions education. This symposium examines the role of older adults and caregivers in co-creating geriatric and gerontology education with a HRSA-funded Geriatric Workforce Enhancement Program (GWEP) to promote the knowledge, skills, and attitudes necessary for patient-centered clinical practice. First, presenters will share educational initiatives involving older adults as mentors and subject matter experts for health professions students and student teams. This is followed by projects engaging and empowering older adults and caregivers as advocates for quality care and advisors for educational improvements. Finally, presenters will explore evaluation tools and strategies to collect input and ensure the patient’s voice remains at the center of education planning, delivery, and improvement. Presenters discuss methods of adapting these models to a local context as well as strategies and opportunities to incorporate the input and feedback from older adults and caregivers into health professions education.

Effect of Networking Capabilities on performance of Small and Medium Enterprises in Kenya. Does Entrepreneurial Self Efficacy Matter?

The general purpose of the study was to examine effect of networking capabilities and entrepreneurial self-efficacy on the performance of Small and Medium Enterprises in selected towns of the North Rift Region -Kenya. The study was anchored by the theoretical approach of Resource Based View and Social Capital theories. Sample size of 323 drawn from a population of 4596 Small and Medium Enterprises registered with the Uasin Gishu, Tranzoia and Nandi Counties was collected using self-administered questionnaires. Hierarchical and multiple regression model using Hayes process Macro were used to analyze data and test the hypothesis. The variables were tested for reliability and validity by computing the Cronbach alpha and factor analysis statistical tests respectively. The study found that; networking capabilities and entrepreneurial self-efficacy significantly affects firm performance. The study found that entrepreneurial self-efficacy moderates the indirect relationship between networking capabilities and small and medium enterprises performance. The study contributes to knowledge by revealing moderation model of self-efficacy between the variables of the study. The new knowledge introduced is that entrepreneurial self-efficacy moderates the indirect links between networking capabilities and Small and Medium Enterprises performance. The government should therefore develop effective strategies that will help improve Small and Medium Enterprises performances by applying the networking capabilities and entrepreneurial self-efficacy unique dimensions.

Systematic discovery and feature analysis of intertwined symmetric protein motifs for topology engineering

Naturally occurring nontrivial protein topologies not only draw increasing attention on the relationships between topology and protein function, but also stimulate research endeavors in harnessing topology as a unique dimension for protein engineering. However, artificial design and synthesis of protein topologies is still in its infancy with successes only on a few simple topologies and its development is limited by the small number of intertwined protein motifs known to date. Herein, we report a systematic framework for the discovery of symmetric intertwined protein motifs from Protein Data Bank. The symmetric protein assemblies were screened based on their calculated Gauss linking number to assess their extent of chain intertwining. Then, the potential of such symmetric intertwined motifs in designing complex protein topologies is evaluated based on several parameters, including buried surface area, N-C terminal distances and so on, giving rise to a library of premium intertwined motifs useful for protein topology engineering. Taking C2 assemblies for example, the potential biological significances of chain intertwining in protein architectures are also discussed based on the analysis of their postulated biological functions. With an expanded toolbox of intertwined motifs, the design space of topological proteins would be greatly expanded to enable a broader scope for the application of protein topology engineering.

Procesy modelowania glottodydaktycznego w ujęciu wybranych współczesnych teorii lingwistycznych

Contemporary glottodidactics uses numerous models of foreign language learning and teaching. Although glottodidactics is a highly interdisciplinary science and its development is determined by many scientific disciplines, linguistic studies have significantly contributed to the development of theoretical foundations for glottodidactics as an independent science for decades. The paper discusses and summarizes the state of research on glottodidactic modeling processes (Grucza 1978, Woźniewicz 1987, Pfeiffer 2001, Dakowska 2010, Grucza 2010b, Gębal 2013 and the author's model) and proposes a new model that integrates the most important elements of earlier systems. The author distinguishes two levels of the glottodidactic modeling process: internal (referring to individual language skills and intrapersonal properties of the learner in the sense of F. Grucza's anthropocentric linguistics, as well as selected theories of cognitive linguistics) and external (teacher and multidimensional determinants of the glottodidactic process that the teacher encounters in this process). The special positioning of the learner in the system emphasizes the individual and unique dimension of the foreign language teaching process of each learner, who, by constructing the structures of a foreign language and, as a result, also communicative competence in a given foreign language, significantly broadens and develops its cognitive framework.

Industry 4.0 and sustainable business models: An intercontinental sample

AbstractIn the rapidly evolving contemporary business landscape, the Industry 4.0 revolution has emerged as an immense and transformative force, fundamentally reshaping industries and presenting significant challenges to prevailing business models. As technology components continued to evolve in response to this revolution, it became increasingly evident that understanding the multifaceted implications of these changes for organizational sustainability is of paramount importance. The overarching goal of this research was to elucidate the intricate interplay between Industry 4.0 technologies and organizational sustainability. To achieve this objective, we conducted a comprehensive exploration of real‐world instances where companies boldly embraced Industry 4.0 technologies, subjecting their specific practices and processes to thorough examination. This methodological approach yielded a wealth of invaluable insights into the practical implications of Industry 4.0 on organizational sustainability, effectively bridging the gap between theory and practice. This research underscores the urgent need to provide businesses and decision‐makers with insights of paramount significance. The findings of the study aim to serve as a guiding compass for organizations, offering clarity on potential benefits and challenges associated with Industry 4.0 adoption. Notably, within the scope study, the utilization of semi‐structured interview technique added a unique dimension, enabling in‐depth insights. Interviews were conducted with individuals from diverse nations across different continents, thoughtfully selected based on predefined criteria, setting this research apart in terms of both the sample's size and the remarkable diversity within the participant profile. This diversity enriched the research findings by encompassing various perspectives and experiences, significantly enhancing the depth and breadth of the study's insights.

The impact of professional mentoring on mentors of novice-teachers

PurposeThis article aims to present a unique dimension to mentor studies in that unlike most research that focuses on the novice-teachers-mentee, this study explores the influence of mentoring on the mentors themselves. Two main questions were examined: “Which components of mentoring influence the mentors' professional development?” and “What is the differential impact of each of these components as they are internalized by the mentors?”Design/methodology/approachA total of 765 mentors completed a questionnaire composed of 47 multiple-choice questions and an open-ended question describing the contribution of mentoring. The survey thus generated both quantitative and qualitative data.FindingsThe results show three main components of mentoring that influence mentors' professional development in the following order: personal–emotional, didactic knowledge and systemic–organizational. The findings also illustrate how the mentors used a comparison process to develop their professional perception: first, by comparing their role as a teacher and their role as a mentor, and second, by comparing their own professional identity as a teacher with that of the novice-teacher.Research limitations/implicationsThe implications of the study point to the importance of mentoring for mentors' professional development. Practical implications of this study encourage mentor training courses that combine a body of knowledge of theory and practice, as well as supervision and mentoring for mentors. It may be important for mentors to develop a professional identity as mentors that is distinct from their professional identity as teachers.Practical implicationsThe implications of the study point to the importance of mentoring for mentors' professional development. Practical implications of this study encourage mentor training courses that combine a body of knowledge of theory and practice, as well as supervision and mentoring for mentors. It may be important for mentors to develop a professional identity as mentors that is distinct from their professional identity as teachers.Originality/valueThe manuscript attempts to explore the dynamic relationships within the mentoring process by investigating how mentoring impacts the development of mentors. It presents insights into the benefits of mentoring novice-teachers for the mentors themselves via analysis of a large-scale, nationwide study.

Novel Multidimensional Pain Assessment Tool Is a Feasible, Valid, and Enjoyable Approach to Communication of Pain Symptoms in Pediatric Sickle Cell Disease

Background: Pain is the most common symptom of sickle cell disease (SCD) and is especially difficult to assess in the pediatric population. Children have varied developmental stages and cognitive abilities making the communication of this subjective experience hard to operationalize. Both the assessment of pain and validation of these assessments is challenging. No pediatric pain assessment tool has been deemed valid and reliable across all ages and types of pain. Commonly used pediatric tools include the Wong-Baker Faces scale, the numeric rating scale, and the visual analog scale (VAS), which combines the visuals of faces and numeric rating. These are unidimensional - only assessing the severity of pain, and in the case of faces, can cause confusion between pain severity and patient affect. In children with SCD, accurate pain assessment is crucial to current and lifelong management. “Painimation” is a technology-based pain assessment tool that incorporates conceptual animations, rather than numbers or words, to characterize pain. These animations are intended to help clinicians better understand pain from the patient's perspective. They are dynamic and transcend language. For example, animations are designed to communicate dull pulsating pain, sharp electric pain, or anything in between. “Painimation” does not rely on verbal communication skills, making it ideal for use in the pediatric population. “Painimation” has been validated in adults with SCD and is currently in implementation trials. Our study aims to determine the feasibility and validity of “Painimation” in pediatric SCD. Methods: This is a single site non-randomized cross-sectional feasibility and validity study. Participants were 10 - 21 years old with SCD who presented to clinic in baseline health. Participants completed the Painimation application, which consists of a numeric pain rating scale (1-10), a front and back 2-dimensional body image that can be shaded to indicate areas affected by pain, and eight abstract animations intended to represent different pain qualities (tingling, shooting, stabbing, throbbing, pounding, cramping, electrifying, and burning). The patient chose up to three animations and the intensity of each chosen animation was adjusted using a sliding bar without numeric labels. The animations were presented to the patient without labeling the intended quality. The patients then completed a survey consisting of questions regarding the usability of Painimation, clinical questions regarding their disease, Lansky Play-Performance Scale, and validated patient reported outcomes questions (PedsQL, Ped-PRO-CTCAE, PROMIS). Results: We enrolled 30 participants between April 1 and July 31, 2023, with recruitment ongoing. Five records were incomplete and were not analyzed at this time. The mean ratings when asked whether 1) Painimation was easy to use, 2) the patient enjoyed using Painimation, and 3) the patient would use Painimation to communicate pain with their provider were respectively 3.28±.74 (SD), 3.08±.95, and 3.12±1.17 (scale 0-4), indicating a generally favorable result for feasibility. The median VAS score was 5.10 (IQR = 0.25, 8.25). Pain was most reported in the back lower chest (60%), front stomach (48%), and front chest (44%). The stabbing animation was the most chosen at 56% followed by the cramping animation at 20%. Electrifying and Cramping animations had the highest agreement with their intended McGill descriptors at 40%. VAS scores and Painimation severity scores demonstrated excellent positive correlation (Pearson r=.74). Conclusion: Painimation is a feasible pain assessment tool in pediatric SCD with high user satisfaction. Severity scores on Painimation correlate strongly with VAS scores. The pain characteristic conveyed by each animation adds unique dimensions to this measure and will be further analyzed. Painimation is a novel pediatric pain assessment that holds the promise of greatly improving the communication of pain and transforming care in Pediatric SCD.

Circular polarization-resolved ultraviolet photonic artificial synapse based on chiral perovskite

Circularly polarized light (CPL) adds a unique dimension to optical information processing and communication. Integrating CPL sensitivity with light learning and memory in a photonic artificial synapse (PAS) device holds significant value for advanced neuromorphic vision systems. However, the development of such systems has been impeded by the scarcity of suitable CPL active optoelectronic materials. In this work, we employ a helical chiral perovskite hybrid combined with single-wall carbon nanotubes to achieve circularly polarized ultraviolet neuromorphic vision sensing and imaging. The heterostructure demonstrates long-term charge storage as evidenced by multiple-pulsed transient absorption measurements and highly sensitive circular polarization-dependent photodetection, thereby enabling efficient CPL-resolved synaptic and neuromorphic behaviors. Significantly, our PAS sensor arrays adeptly visualize, discriminate, and memorize distinct circularly polarized images with up to 93% recognition accuracy in spiking neural network simulations. These findings underscore the pivotal role of chiral perovskites in advancing PAS technology and circular polarization-enhanced ultraviolet neuromorphic vision systems.

Recent advances ofmicroneedles biosensors for plants.

As the lack of plants can affect the energy operation of the entire ecosystem, monitoring and improving the health status of plants is crucial. However, ordinary biosensing platforms lack accuracy and timeliness in monitoring plant growth status. In addition, the prevention and control of plant diseases often involve spraying and administering drugs, which is inefficient and prone to pollution. Microneedles have unique dimensions and shapes, and they have significant advantages as biosensors in the fields of sensing, detection, and drug delivery. Recent evidence suggests that microneedle biosensors can become effective tools for plant diagnosis and treatment. In this review, the comprehensive development of the application of microneedle biosensors in the field of plants is introduced, as well as their manufacturing processes and sensing and detection functions. Furthermore, the application of microneedle biosensors in this field is discussed, and future development directions are proposed.

Optimizing baseline and post-concussion assessments through identification, confirmation, and equivalence of latent factor structures: Findings from the NCAA-DoD CARE Consortium

Objective: Concussion evaluations use a multidimensional assessment to evaluate unique patient function dimensions (e.g., subjective symptoms differ from balance assessments), but the overarching latent factor structure has not been empirically substantiated. Our objective was to determine the cumulative latent factor structure of pre-injury baseline and acute (<48-h) post-concussion assessment battery outcomes, and determine measurement equivalence among common factors in collegiate student-athletes. Methods: Collegiate student-athletes at baseline (n = 21,865) and post-concussion (n = 1,537) across 25-institutions completed standardized assessments. Individual items were used from the baseline and post-concussion assessments and consisted of: Sport Concussion Assessment Tool, Brief Symptom Inventory-18, Standardized Assessment of Concussion, Balance Error Scoring System, Immediate Post-Concussion Assessment and Cognitive Test, and vestibular-ocular motor screening. Exploratory factor analysis was used on half the baseline data, and confirmatory factor analysis on the remaining baseline data and post-concussion data separately. Measurement equivalence was assessed between sex, sport contact classification, concussion history, and time. Results: A 10-factor exploratory model was established and comprised of: depression, somatic, vestibulo-ocular, headache, postural stability, neurocognition, emotional, fatigue, cognitive, consciousness clouding. The 10-factor model was confirmed at baseline and post-concussion with strong measurement equivalence between timepoints. Strong to strict measurement equivalence was observed for sex, sport contact classification, and concussion history at both timepoints separately. Conclusion: Our findings established a robust 10-factor latent factor model equivalent across timepoints and common factors among healthy and concussed collegiate athletes. Clinicians can use these findings to target specific factors while reducing redundant elements to provide efficient, comprehensive post-concussion assessments.

The Rating of Emotional Abuse in Childhood (REACH) Questionnaire: A new self-report measure assessing history of childhood emotional abuse

BackgroundA history of childhood emotional abuse (CEA) is prevalent among adults with affective disorders; therefore, a comprehensive measure of it is vital. The Rating of Emotional Abuse in Childhood Questionnaire (REACH) was developed to assess history of CEA in relation to parental behaviours of threat, ignoring, humiliation/denigration, scapegoating, antipathy, and overcontrol/conditionality in a single measure. This paper investigated the psychometric properties of REACH in a community sample and proposes values for classifying individuals as high-risk for CEA. MethodA convenience sample of N = 483 adults (Female, 78.3%) was recruited to complete questionnaires that included the REACH alongside measures of mental health, insecure attachment, emotion regulation, and childhood abuse. A subset of participants (n = 198) completed the REACH 7 days later. ResultsFactor analysis indicated a 2-factor model provided a good fit. Factors were named ‘threatening’ and ‘devaluing’. A total scale score of CEA was also recommended. The threatening, devaluing, and total scales demonstrated strong psychometric properties with high internal consistency, test-retest reliability, and convergent validity, while cutoff values for identifying a high-risk CEA group demonstrated good discriminant utility. ConclusionsThe results support REACH as a valid measure and suggest a history of CEA should be measured in relation to threatening and devaluing CEA as they represent unique dimensions of CEA even though they often co-occur.

How many dimensions does posttraumatic stress disorder have? A study in 127 representative samples of a population exposed by an earthquake.

Since its first definition, the number of dimensions of the posttraumatic stress disorder (PTSD) has increased (e.g., 1 to 7). This could be caused by 2 methodological reasons. First, the studies do not select representative samples of the population and do not consider the magnitude of exposure to the same event. Second, they use nonrobust data analysis, which increases the number of dimensions artificially. The aim is to determine how many dimensions PTSD has, when both sources of error are controlled. From 25,400 representative participants of the same population exposed to an earthquake and evaluated with the Davidson Trauma Scale, 127 smaller samples of 200 participants were obtained and classified according to the Mercalli magnitude. Parallel factor analyses (PFA), exploratory structural equations models (ESEM), and classic exploratory factor analysis (EFA) were applied to each sample. There were significant differences in fit and number of dimensions between the high and low Mercalli magnitude. In high exposure conditions: There were 1 dimension according to PFA and 3 according to EFA; ESEM and CFA indicated good fit. The main finding was that PTSD has a unique dimension that includes all of its symptoms. The need to use robust methods of analysis to evaluate data from samples homogeneously exposed to the same potentially traumatic event is argued. (PsycInfo Database Record (c) 2022 APA, all rights reserved).