Utility Of Research Research Articles

Innovative Assessment of Mun River Flow Components through ANN and Isotopic End-Member Mixing Analysis

This study innovatively assesses the Mun River flow components in Thailand, integrating artificial neural networks (ANNs) and isotopic (δ18O) end-member mixing analysis (IEMMA). It quantifies the contributions of the Upper Mun River (UMR) and Chi River (CR) to the overall flow, revealing a discrepancy in their estimated contributions. The ANN method predicts that the UMR and CR contribute approximately 70.5% and 29.5% respectively, while IEMMA indicates a more pronounced disparity with 84% from UMR and 16% from CR. This divergence highlights the distinct perspectives of ANN, focusing on hydrological data patterns, and IEMMA, emphasizing isotopic signatures. Despite discrepancies, both methods validate UMR as a significant contributor to the overall flow, highlighting their utility in hydrological research. The findings emphasize the complexity of river systems and advocate for an integrated approach of river flow analysis for a comprehensive understanding, crucial for effective water resource management and planning.

Postharvest quality and ripening behaviour of un-explored genotypes of Himalayan plain mango diversity

India is renowned for its mango diversity, with more than 1000 genotypes reported. However, the Himalayan plains bear some elite genotypes which supposed to bear high postharvest value, the systemic postharvest study of which is yet to be attempted. The aim of present study is to evaluate the postharvest quality and ripening behviour of these important genotypes. Thus, 15 un-explored mango genotypes of this region were selected and evaluated for ripening behaviour and detailed postharvest profiling via internal (total phenolic and total flavonoid content), nutritional attributes (Brix: acid ratio, total carotenoid concentration, ascorbic acid content and antioxidant activity), sensory evaluation, fruit softening enzymes (polygalactouronase, pectin methylesterase and lipoxygenase), shelf life attributes (respiration rate, physiological loss in weight and storage life in days) external attributes (fruit weight, fruit firmness, peel thickness, fruit shape and dry seed weight) and mineral contents (Calcium, potassium and phosphorous) under ambient storage (25 ± 4 °C and 65 ± 5 % RH). The results revealed that the highest total flavonoid content (682.40 μg g−1), ascorbic acid (46.88 mg 100 g−1) and antioxidant activity (4.84 μmol TE g−1) exhibited by ‘Sukul’. The total phenolic content was recorded as the highest in ‘Safed Malda’ (510.42 μg GAE g-1 FW), and total carotenoid concentration was recorded as the highest in ‘Sipiya’ (7.30 mg 100 g-1) ‘Zardalu’ (7.04 mg 100 g-1) and ‘Mithua’ (6.98 mg 100 g-1). Interestingly, genotypes such as ‘Sukul’, Sipiya’ and ‘Krishna Bhog ‘exhibited a 4–5 days higher storage life than other selected genotypes. Screened genotypes exhibited a high diversity of nutritional and biochemical contents. The results of this study bear practical utility for research (quality improvement programme) and the processing industry.

Plasma pTau181 and pTau217 predict asymptomatic amyloid accumulation equally well as amyloid PET.

The dynamic phase of preclinical Alzheimer's disease, as characterized by accumulating cortical amyloid-β, is a window of opportunity for amyloid-β-lowering therapies to have greater efficacy. Biomarkers that accurately predict amyloid-β accumulation may be of critical importance for participant inclusion in secondary prevention trials and thus enhance development of early Alzheimer's disease therapies. We compared the abilities of baseline plasma pTau181, pTau217 and amyloid-β PET load to predict future amyloid-β accumulation in asymptomatic elderly. In this longitudinal cohort study, baseline plasma pTau181 and pTau217 were quantified using single molecule array assays in cognitively unimpaired elderly selected from the community-recruited F-PACK cohort based on the availability of baseline plasma samples and longitudinal amyloid-β PET data (median time interval = 5 years, range 2-10 years). The predictive abilities of pTau181, pTau217 and PET-based amyloid-β measures for PET-based amyloid-β accumulation were investigated using receiver operating characteristic analyses, correlations and stepwise regression analyses. We included 75 F-PACK subjects (mean age = 70 years, 48% female), of which 16 were classified as amyloid-β accumulators [median (interquartile range) Centiloid rate of change = 3.42 (1.60) Centiloids/year). Plasma pTau181 [area under the curve (95% confidence interval) = 0.72 (0.59-0.86)] distinguished amyloid-β accumulators from non-accumulators with similar accuracy as pTau217 [area under the curve (95% confidence interval) = 0.75 (0.62-0.88) and amyloid-β PET [area under the curve (95% confidence interval) = 0.72 (0.56-0.87)]. Plasma pTau181 and pTau217 strongly correlated with each other (r = 0.93, Pfalse discovery rate < 0.001) and, together with amyloid-β PET, similarly correlated with amyloid-β rate of change (r pTau181 = 0.33, r pTau217 = 0.36, r amyloid-β PET = 0.35, all Pfalse discovery rate ≤ 0.01). Addition of plasma pTau181, plasma pTau217 or amyloid-β PET to a linear demographic model including age, sex and APOE-ε4 carriership similarly improved the prediction of amyloid-β accumulation (ΔAkaike information criterion ≤ 4.1). In a multimodal biomarker model including all three biomarkers, each biomarker lost their individual predictive ability. These findings indicate that plasma pTau181, plasma pTau217 and amyloid-β PET convey overlapping information and therefore predict the dynamic phase of asymptomatic amyloid-β accumulation with comparable performances. In clinical trial recruitment, confirmatory PET scans following blood-based prescreening might thus not provide additional value for detecting participants in these early disease stages who are destined to accumulate cortical amyloid-β. Given the moderate performances, future studies should investigate whether integrating plasma pTau species with other factors can improve performance and thus enhance clinical and research utility.

Enhanced synthesis of antibody-functionalized gold nanoparticles for multiplexed exosome detection via mass signal amplification in LDI-TOF MS.

We present a novel method for sensitive exosomal protein detection using organic matrix-free laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF MS) and gold nanoparticles (AuNPs) functionalized with mass tags for signal amplification (Am-tags). Target exosomes were captured by specific antibodies on AuNPs and a biochip, where the antibody-presenting AuNPs (Ab/Am-tag@AuNPs) contained excess Am-tags. LDI-TOF MS analysis revealed the mass signal of Am-tags on Ab/Am-tag@AuNPs, indicating the presence of target exosomes. Thus, the target signal was amplified by a large number of Am-tags, resulting in enhanced sensitivity. We optimized the protocol to prepare stable Ab/Am-tag@AuNPs, focusing on parameters such as the concentration and ratio of thiol molecules for AuNP functionalization, suitable solvents for the coupling reaction, and amount of antibodies conjugated to the AuNPs. Subsequently, we evaluated the ability of our method to detect exosomes isolated from three cell lines, NIH3T3, MCF7, and HeLa, using an anti-Rab5 immobilized gold chip and anti-CD63/Am-tag@AuNPs with LDI-TOF MS analysis. Calibration curves constructed for the three cell lines showed a linear relationship with an excellent limit of detection. Finally, we emphasized the versatility of our method for the quantitative detection of exosomal proteins CD63 and mucin 1 (MUC1) using two types of Am-tags. LDI-TOF MS analysis revealed the presence of CD63 and MUC1 at different expression levels in HeLa and MCF7 cancer cells. Our findings clearly indicate the potential of Ab/Am-tag@AuNPs as a sensitive and reliable approach for identifying biomarkers in exosomes, providing valuable insights into their utility in biomedical research and clinical settings.

Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study.

Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk individuals. In most countries, including Denmark, smoking habits are not systematically recorded and at best documented within unstructured free-text segments of electronic health records (EHRs). This would require researchers and clinicians to manually navigate through extensive amounts of unstructured data, which is one of the main reasons that smoking habits are rarely integrated into larger studies. Our aim is to develop machine learning models to classify patients' smoking status from their EHRs. This study proposes an efficient natural language processing (NLP) pipeline capable of classifying patients' smoking status and providing explanations for the decisions. The proposed NLP pipeline comprises four distinct components, which are; (1) considering preprocessing techniques to address abbreviations, punctuation, and other textual irregularities, (2) four cutting-edge feature extraction techniques, i.e. Embedding, BERT, Word2Vec, and Count Vectorizer, employed to extract the optimal features, (3) utilization of a Stacking-based Ensemble (SE) model and a Convolutional Long Short-Term Memory Neural Network (CNN-LSTM) for the identification of smoking status, and (4) application of a local interpretable model-agnostic explanation to explain the decisions rendered by the detection models. The EHRs of 23,132 patients with suspected lung cancer were collected from the Region of Southern Denmark during the period 1/1/2009-31/12/2018. A medical professional annotated the data into 'Smoker' and 'Non-Smoker' with further classifications as 'Active-Smoker', 'Former-Smoker', and 'Never-Smoker'. Subsequently, the annotated dataset was used for the development of binary and multiclass classification models. An extensive comparison was conducted of the detection performance across various model architectures. The results of experimental validation confirm the consistency among the models. However, for binary classification, BERT method with CNN-LSTM architecture outperformed other models by achieving precision, recall, and F1-scores between 97% and 99% for both Never-Smokers and Active-Smokers. In multiclass classification, the Embedding technique with CNN-LSTM architecture yielded the most favorable results in class-specific evaluations, with equal performance measures of 97% for Never-Smoker and measures in the range of 86 to 89% for Active-Smoker and 91-92% for Never-Smoker. Our proposed NLP pipeline achieved a high level of classification performance. In addition, we presented the explanation of the decision made by the best performing detection model. Future work will expand the model's capabilities to analyze longer notes and a broader range of categories to maximize its utility in further research and screening applications.

Six factors facilitating teachers’ use of research. An experimental factorial survey of educational stakeholders perspectives

IntroductionTeachers’ use of research has been increasingly advocated for in the past few decades, and some research has documented the factors which positively or negatively influence teachers’ use of research. However, the existing research does not give relevant information to prioritize between different ways to facilitate teachers’ use of research. In addition, different professionals working in education may have divergent opinions about such priorities. This study therefore asks what are the factors that most influence teachers’ use of research according to teachers, teacher trainers, educational decision makers and researchers?MethodsWe conducted a factorial survey experiment on six factors with 100 participants (pilot study) and 340 participants (main study) to identify which factors were perceived as influencing the most teachers’ use of research and to compare respondents’ perceptions according to their main role in education.ResultsThis study shows that support for research use by the institution and instrumental utility of research are the factors that were judged as most impactful. Some categories of respondents had conflicting views about specific factors, for instance researchers perceiving teachers’ involvement in research as less likely to facilitate teachers’ use of research.ConclusionThese findings can help decision-makers and teacher-trainers with limited resources to allocate them in a more effective way, while taking into consideration the disagreements across professions in order to resolve possibly arising conflicts.

Optimization of Formic Acid-Formalin-Based Decalcification Protocol for Rat Calvarial Bone Histology

Decalcification is crucial in histological processing, particularly for studying mineralized tissues like bone. The choice of decalcification method can significantly impact the quality of histological sections and the preservation of tissue morphology. This study aims to establish a standardized protocol for decalcifying rat calvarial bone using a formic acid-formalin-based decalcification solution. The protocol was systematically optimized and evaluated based on various parameters, including decalcification time, formic acid concentration, and tissue integrity preservation. The decalcification process was evaluated through comprehensive assessments, including gross physical examination, chemical analysis, and radiographic imaging techniques. Our result demonstrated that the 10% formic acid concentration proved most effective for decalcifying rat calvarial bone samples within eight days, excelling in mineral content removal while preserving specimen structural integrity. In contrast, the 5% concentration failed to complete decalcification within ten days, and the 15% compromised sample quality within eight days. Histological analyses confirmed the efficacy of the 10% formic acid concentration in maintaining tissue integrity and achieving optimal staining quality. The standardized protocol presented in this study provides an effective and reliable approach for achieving consistent and high-quality histological sections of rat calvarial bone. An ideal decalcification agent should effectively remove calcium salts, preserve structural integrity and molecular components, facilitate rapid yet minimally damaging decalcification, and ensure ease of handling for laboratory personnel. Further exploration of its applicability to different bone types or species is recommended to broaden its research utility.

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations.

Achieving a balance between computational speed, prediction accuracy, and universal applicability in molecular simulations has been a persistent challenge. This paper presents substantial advancements in TorchMD-Net software, a pivotal step forward in the shift from conventional force fields to neural network-based potentials. The evolution of TorchMD-Net into a more comprehensive and versatile framework is highlighted, incorporating cutting-edge architectures such as TensorNet. This transformation is achieved through a modular design approach, encouraging customized applications within the scientific community. The most notable enhancement is a significant improvement in computational efficiency, achieving a very remarkable acceleration in the computation of energy and forces for TensorNet models, with performance gains ranging from 2× to 10× over previous, nonoptimized, iterations. Other enhancements include highly optimized neighbor search algorithms that support periodic boundary conditions and smooth integration with existing molecular dynamics frameworks. Additionally, the updated version introduces the capability to integrate physical priors, further enriching its application spectrum and utility in research. The software is available at https://github.com/torchmd/torchmd-net.

A Social Cognitive Career Theory Study of Agricultural Mechanical Trade Workers

Attracting and retaining skilled workers in agriculture is a global problem. Shortages of essential workers disrupt supplies of goods and services from the point of production on farms through manufacturing, transport, to ultimate consumption. The global pandemic’s effect on food supply was a salutary lesson in the effects of a diminished agricultural workforce. Agricultural mechanics are vital to productivity. The present research used the social cognitive career theory to explore agricultural mechanics’ careers. An exploratory qualitative study deployed interviews to collect data from N = 19 mechanical trade workers. Interviews were centered on participants’ descriptions of their work regarding theoretical constructs including self-efficacy, outcome expectations, satisfaction, dispositional traits, and contextual affordances. Reflective thematic analysis of the data produced concordance with key constructs of the social cognitive career theory sufficient to justify its utility for research with this specific agricultural occupation. This research makes an important contribution to the literature of vocational psychology which can and should contribute to solving the complex problem of supporting a workforce needed for agriculture’s ongoing challenge of feeding and clothing the world’s growing population.

Discovery of the Lysosome-Inhibiting Function of Acremolactone B

Lysosome inhibitors have garnered considerable interest for their utility in lysosome biology research and potential therapeutic applications. We discovered the lysosome-inhibiting function of acremolactone B (1), a scarce azaphilone-type polyketide, leveraging our previous scalable synthesis. This compound significantly reduces lysosomal acidity and impairs the maturation of the lysosomal protease cathepsin D (CTSD) in triple-negative breast cancer cells (MDA-MB-231) and human lung cancer cells (A549). Furthermore, we found that compound 1 suppresses downstream autophagy, as revealed by monitoring autophagic flux and conducting transmission electron microscopy (TEM) analysis. This study unveils the previously unrecognized biological role of 1 and introduces a new scaffold for lysosome inhibitors.

Evaluating the strengths and weaknesses of large language models in answering neurophysiology questions

Large language models (LLMs), like ChatGPT, Google’s Bard, and Anthropic’s Claude, showcase remarkable natural language processing capabilities. Evaluating their proficiency in specialized domains such as neurophysiology is crucial in understanding their utility in research, education, and clinical applications. This study aims to assess and compare the effectiveness of Large Language Models (LLMs) in answering neurophysiology questions in both English and Persian (Farsi) covering a range of topics and cognitive levels. Twenty questions covering four topics (general, sensory system, motor system, and integrative) and two cognitive levels (lower-order and higher-order) were posed to the LLMs. Physiologists scored the essay-style answers on a scale of 0–5 points. Statistical analysis compared the scores across different levels such as model, language, topic, and cognitive levels. Performing qualitative analysis identified reasoning gaps. In general, the models demonstrated good performance (mean score = 3.87/5), with no significant difference between language or cognitive levels. The performance was the strongest in the motor system (mean = 4.41) while the weakest was observed in integrative topics (mean = 3.35). Detailed qualitative analysis uncovered deficiencies in reasoning, discerning priorities, and knowledge integrating. This study offers valuable insights into LLMs’ capabilities and limitations in the field of neurophysiology. The models demonstrate proficiency in general questions but face challenges in advanced reasoning and knowledge integration. Targeted training could address gaps in knowledge and causal reasoning. As LLMs evolve, rigorous domain-specific assessments will be crucial for evaluating advancements in their performance.

US County-Level Variation in Availability and Prevalence of Black Physicians in 1906

Black physicians are substantially underrepresented in the US health care workforce, with detrimental effects on the health and health care experiences of Black individuals. These contemporary gaps can be traced to the early days of the medical profession using the first edition of the American Medical Directory (AMD). To identify state- and county-level patterns related to the training and availability of Black physicians relative to their White counterparts in the 1906 AMD. For this cross-sectional study, data for 41 828 physician entries in 18 US states in or adjacent to the South as well as the District of Columbia were extracted from the 1906 AMD and aggregated to 1570 counties. Data analysis was performed between September 2023 and January 2024. County-level exposure variables included population density, racial composition, and illiteracy rate among US-born White residents as well as an index of terrain ruggedness and the number of lynchings in the previous decade. Median values of physicians' distance from place of practice to place of medical training (by race of physician) were also used as an exposure variable. There were 4 county-level outcomes: (1) presence of any Black physician, (2) proportion of Black physicians per Black population, (3) proportion of White physicians per White population, and (4) community representativeness (reported as the community representativeness ratio). The cross-sectional analysis used generalized additive mixed models with state-level random effects. Across 1570 counties, Black physicians comprised 746 (1.8%) of the 41 828 physicians in the dataset. Black physicians tended to train further from their place of practice than their White counterparts. The proportion of Black physicians per 1000 Black residents was 0.08 compared with 1.62 for White physicians; these proportions varied substantially by state. At the county level, the presence of any Black physician was associated with percentage Black population (odds ratio [OR], 28.94 [95% CI, 9.77 to 85.76]; P ≤ .001), population density (OR, 2.63 [95% CI, 2.03 to 3.40]; P ≤ .001), and distance to the nearest Black medical school (OR, 0.62 [95% CI, 0.42 to 0.92]; P = .02). A variety of structural disadvantages are illustrated in this cross-sectional study of county-level sociodemographic and geographic characteristics associated with the prevalence of Black physicians in the earliest days of the profession. To demonstrate its broader utility for health disparities research, the dataset has been made publicly available with a visualization platform.

Global trends in applying decision science in mangrove restoration: are we missing some dimensions?

Mangrove restoration involves complex decision-making processes and can often lack adequate stakeholder engagement and empowerment to inform effective restoration outcomes. Decision science has the potential to overcome such challenges by facilitating structured approaches to make informed, participatory, and defensible decisions through the use of decision-support frameworks and tools. In this paper, we conduct a bibliometric and scoping review of peer-reviewed scientific literature to identify how decision science has been applied to advise mangrove restoration efforts and the extent to which social, economic, and ecological variables have been used to inform these studies. We find a steady increase in the number of mangrove restoration studies that employ decision science from 1990 to 2022, with an annual growth rate of 4.4%. We identified over 300 decision support tools used in mangrove restoration literature. Spatial data was the most documented tool to support mangrove studies. We also find that most papers focused on ecological variables (85.5%), while social (27.2%) and economic (15.1%) variables received less attention. Studies that used decision support frameworks were also sparse, where the most featured framework was Systematic Conservation Planning. The number of studies explicitly incorporating social and economic variables was limited, and there was also a scarcity of studies incorporating variables associated with governance. Regardless of the dominance of ecological variables, this review highlights a shift towards incorporating social dimensions into decision tools, emphasizing concepts like vulnerability to climate change, ecosystem services, and social benefits. Collaboration among countries, scientists, and practitioners is crucial to operationalise a socio-ecological framework within decision science. Enhancing the utility of scientific research for practitioners remains a critical goal in addressing the challenges faced by mangrove restoration projects globally.

Validation of the Approach-Avoidance Temperament Questionnaire in Individuals with Anxiety and Depression

The Approach-Avoidance Temperament Questionnaire (ATQ) is a well-established measure assessing heightened sensitivity and reactivity to reward/positive stimuli (approach temperament) and to punishment/negative stimuli (avoidance temperament). These basic dimensions of personality are believed to be important for understanding the etiology and maintenance of anxiety and depressive disorders. Despite the ATQ’s potential utility in clinical psychology research, its psychometric properties and factor structure have yet to be examined in a psychiatric sample. The aims of the present study were to 1) conduct confirmatory factor analysis to replicate the ATQ’s factor structure in individuals diagnosed with an anxiety or depressive disorder (N = 244), 2) assess internal consistency and convergent and divergent validity, and 3) explore differences in approach and avoidance temperaments in individuals with versus without a diagnosis of anxiety or depression. Results confirmed the original two-factor structure of the ATQ in a clinical sample, with approach and avoidance temperaments representing orthogonal dimensions. The measure demonstrated strong internal consistency, convergent and divergent validity, and predictive validity. Individuals with anxiety and depression scored higher on avoidance items and lower on approach items compared to those without clinical diagnoses. This study supports the use of the ATQ in clinical populations.

Artificial Intelligence and the National Violent Death Reporting System: A Rapid Review.

As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury and mortality through nursing research are critical. The National Violent Death Reporting System provides public health surveillance of US violent deaths; however, understanding the National Violent Death Reporting System's research utility is limited. The purpose of our rapid review of the 2019-2023 literature was to understand to what extent artificial intelligence methods are being used with the National Violent Death Reporting System. We identified 16 National Violent Death Reporting System artificial intelligence studies, with more than half published after 2020. The text-rich content of National Violent Death Reporting System enabled researchers to center their artificial intelligence approaches mostly on natural language processing (50%) or natural language processing and machine learning (37%). Significant heterogeneity in approaches, techniques, and processes was noted across the studies, with critical methods information often lacking. The aims and focus of National Violent Death Reporting System studies were homogeneous and mostly examined suicide among nurses and older adults. Our findings suggested that artificial intelligence is a promising approach to the National Violent Death Reporting System data with significant untapped potential in its use. Artificial intelligence may prove to be a powerful tool enabling nursing scholars and practitioners to reduce the number of preventable, violent deaths.

SERS characterization of biochemical changes associated with biodesulfurization of dibenzothiophene using Gordonia sp. HS126-4N

In this study, Gordonia sp. HS126-4N was employed for dibenzothiophene (DBT) biodesulfurization, tracked over 9 days using SERS. During the initial lag phase, no significant spectral changes were observed, but after 48 h, elevated metabolic activity was evident. At 72 h, maximal bacterial population correlated with peak spectrum variance, followed by stable spectral patterns. Despite 2-hydroxybiphenyl (2-HBP) induced enzyme suppression, DBT biodesulfurization persisted. PCA and PLS-DA analysis of the SERS spectra revealed distinctive features linked to both bacteria and DBT, showcasing successful desulfurization and bacterial growth stimulation. PLS-DA achieved a specificity of 95.5 %, sensitivity of 94.3 %, and AUC of 74 %, indicating excellent classification of bacteria exposed to DBT. SERS effectively tracked DBT biodesulfurization and bacterial metabolic changes, offering insights into biodesulfurization mechanisms and bacterial development phases. This study highlights SERS' utility in biodesulfurization research, including its use in promising advancements in the field.

Service design for children and young people with common mental health problems: literature review, service mapping and collective case study.

The mental health of children/young people is a growing concern internationally. Numerous reports and reviews have consistently described United Kingdom children's mental health services as fragmented, variable, inaccessible and lacking an evidence base. Little is known about the effectiveness of, and implementation complexities associated with, service models for children/young people experiencing 'common' mental health problems like anxiety, depression, attention deficit hyperactivity disorder and self-harm. To develop a model for high-quality service design for children/young people experiencing common mental health problems by identifying available services, barriers and enablers to access, and the effectiveness, cost effectiveness and acceptability of such services. Evidence syntheses with primary research, using a sequential, mixed-methods design. Inter-related scoping and integrative reviews were conducted alongside a map of relevant services across England and Wales, followed by a collective case study of English and Welsh services. Global (systematic reviews); England and Wales (service map; case study). Literature reviews: relevant bibliographic databases and grey literature. Service map: online survey and offline desk research. Case study: 108 participants (41 children/young people, 26 parents, 41 staff) across nine case study sites. A single literature search informed both reviews. The service map was obtained from an online survey and internet searches. Case study sites were sampled from the service map; because of coronavirus disease 2019, case study data were collected remotely. 'Young co-researchers' assisted with case study data collection. The integrative review and case study data were synthesised using the 'weaving' approach of 'integration through narrative'. A service model typology was derived from the scoping review. The integrative review found effectiveness evidence for collaborative care, outreach approaches, brief intervention services and the 'availability, responsiveness and continuity' framework. There was cost-effectiveness evidence only for collaborative care. No service model appeared to be more acceptable than others. The service map identified 154 English and Welsh services. Three themes emerged from the case study data: 'pathways to support'; 'service engagement'; and 'learning and understanding'. The integrative review and case study data were synthesised into a coproduced model of high-quality service provision for children/young people experiencing common mental health problems. Defining 'service model' was a challenge. Some service initiatives were too new to have filtered through into the literature or service map. Coronavirus disease 2019 brought about a surge in remote/digital services which were under-represented in the literature. A dearth of relevant studies meant few cost-effectiveness conclusions could be drawn. There was no strong evidence to suggest any existing service model was better than another. Instead, we developed a coproduced, evidence-based model that incorporates the fundamental components necessary for high-quality children's mental health services and which has utility for policy, practice and research. Future work should focus on: the potential of our model to assist in designing, delivering and auditing children's mental health services; reasons for non-engagement in services; the cost effectiveness of different approaches in children's mental health; the advantages/disadvantages of digital/remote platforms in delivering services; understanding how and what the statutory sector might learn from the non-statutory sector regarding choice, personalisation and flexibility. This study is registered as PROSPERO CRD42018106219. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/09/08) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 13. See the NIHR Funding and Awards website for further award information.

Verification of the Reliability and Validity of the Chinese Version of the Novelty Need Satisfaction Scale in Physical Education.

This study aims to validate the Chinese version of the Novelty Need Satisfaction Scale (NNSS) within physical education (PE) contexts, incorporating three distinct studies to examine its reliability, validity, and measurement invariance across gender and different samples. Study 1 involved translating the original NNSS into Chinese and evaluating it through confirmatory factor analysis, item analysis, and assessments of internal consistency reliability among 390 students (53.8% male, 46.2% female), averaging 14.5 years in age. Study 2 assessed the discriminant validity of the Chinese NNSS by exploring correlations between novelty need satisfaction and three conventional basic psychological needs (BPNs) - autonomy, competence, and relatedness, in a larger cohort of 845 students (51.7% male, 48.3% female), with an average age of 14.8 years. This study also investigated the relationships between novelty need satisfaction, autonomous motivation, and enjoyment in PE. Study 3 examined the measurement invariance of the Chinese NNSS across gender and different samples, using a sample of 1235 students (52.6% male, 47.4% female), with an average age of 14.6 years. The one-factor, five-item structure of the Chinese NNSS was confirmed in Study 1. Study 2 demonstrated the distinct yet covariant nature of novelty need satisfaction among BPNs and its predictive capability for enjoyment in PE through autonomous motivation. Study 3 confirmed the measurement invariance of the Chinese NNSS across gender and samples, validating its reliability and applicability. The validation of the Chinese NNSS within PE settings not only adds the need for novelty to the motivational sequence proposed by self-determination theory (SDT) but also emphasizes its significant role in enhancing autonomous motivation and enjoyment. This study suggests the scale's utility for future research in exploring the dynamics among BPNs and provides deeper insights into the motivational processes in PE.

The abstinence from smartphone scale (ABSS-10): Psychometric properties and practical utility

In order to frame excessive smartphone use as an addiction, it is important to understand whether this behavior determines abstinence symptoms and which damaging effect it has on emotions and cognition. However, an appropriate tool to assess the presence of smartphone abstinence symptoms is still lacking. In the present study, we propose a scale that is specifically developed to assess the psychological state deriving from smartphone abstinence: The Abstinence from Smartphone Scale (ABSS-10). The aim of this work is to validate ABSS-10 and to investigate its relevance in the context of smartphone addiction. Two studies were conducted to explore ABSS-10 psychometric properties, focusing on discriminant validity, and its relationship with smartphone dependence and emotional attachment. In Study 1, university students were administered the ABSS-10 two times during a two and a half-hour long smartphone restriction period. In Study 2, the scale was administered three times during a five-hour long smartphone restriction period. General state anxiety and smartphone dependence scales were also administered. The findings reveal that ABSS-10 effectively differentiates smartphone abstinence symptoms from general state anxiety and dependence. Moreover, results show that the scale detects changes in abstinence symptoms scores during a five-hour restriction period. The scale's utility in both research and practical settings is discussed, highlighting its potential contributions to understanding the psychological dynamics of smartphone use and abstinence. The present work suggests that ABSS-10 is a robust tool for research on the psychological effects of smartphone usage.

Proximity tracking using ultra-wideband technology for equine social behaviour research

Sociopositive interactions with conspecifics are essential for equine welfare and quality of life. This study aimed to validate the use of wearable ultra-wideband (UWB) technology to quantify the spatial relationships and dynamics of social behaviour in horses by continuous (1/s) measurement of interindividual distances. After testing the UWB devices’ spatiotemporal accuracy in a static environment, the UWB measurement validity, feasibility and utility under dynamic field conditions was assessed in a group of 8 horses. Comparison of the proximity measurements with video surveillance data established the measurement accuracy and validity (r = 0.83, p < 0.0001) of the UWB technology. The utility for social behaviour research was demonstrated by the excellent accordance of affiliative relationships (preferred partners) identified using UWB with video observations. The horses remained a median of 5.82 m (95% CI 5.13–6.41 m) apart from each other and spent 20% (median, 95% CI 14–26%) of their time in a distance ≤ 3 m to their preferred partner. The proximity measurements and corresponding speed calculation allowed the identification of affiliative versus agonistic approaches based on differences in the approach speed and the distance and duration of the resulting proximity. Affiliative approaches were statistically significantly slower (median: 1.57 km/h, 95% CI 1.26–1.92 km/h, p = 0.0394) and resulted in greater proximity (median: 36.75 cm, 95% CI 19.5–62 cm, p = 0.0003) to the approached horse than agonistic approaches (median: 3.04 km/h, 95% CI 2.16–3.74 km/h, median proximity: 243 cm, 95% CI 130–319 cm), which caused an immediate retreat of the approached horse at a significantly greater speed (median: 3.77 km/h, 95% CI 3.52–5.85 km/h, p < 0.0001) than the approach.