bluuebunny/crossref_metadata_2025 huggingface dataset:
Why can parents’ phubbing affect mobile phone addiction? Perspective of the I-PACE model
Authors: Liu Bo , Xu Hemuqing , Wei Hua , Song Yuancai
Published: January 2025

Objective

Based on the I-PACE model, this study investigated the longitudinal relationship between parents’ phubbing and mobile phone addiction, as well as the serial mediating effects of maladaptive cognition and ego depletion.

Methods

A longitudinal study, with data collected at two time points over a six-month interval to test the proposed hypotheses. The independent variable was measured at Time 1 (T1), while the mediators and dependent variables were assessed at Time 2 (T2). A total of 591 middle school students from a city in central China was recruited to complete the parents’ phubbing scale, maladaptive cognition scale, ego depletion scale and mobile phone addiction scale.

Results

(1) The correlation analysis showed a significant positive correlation between T1 parents’ phubbing, T2 maladaptive cognition, T2 ego depletion, and T2 mobile phone addiction. (2) Maladaptive cognition was found to mediate the relationship between parent’s phubbing and mobile phone addiction. Similarly, ego depletion also mediated the relationship between parent’s phubbing and mobile phone addiction. Additionally, both maladaptive cognition and ego depletion functioned as serial mediators between parent’s phubbing and mobile phone addiction.

Conclusion

This study provides evidence that parental phubbing serves as a longitudinal predictor of mobile phone addiction, with maladaptive cognition and ego depletion acting as key mediators in this process.
Associations of pro-inflammatory factors and IL-10 levels with degree of suicide risk in adolescents with depression
Authors: Liu Wenyuan , Zheng Hongyu , Wen Xiaofei , Liu Longxing , Yang Yue , Zhong Hui
Published: January 2025

Background

Depression and suicidal behavior are associated with pro-inflammatory status in adults. However, differences in inflammatory levels among adolescents with depression at different suicide risk levels are unclear, and the connection between anti-inflammatory factors, which serve as vital for the immune system, and suicide needs to be explored.

Methods

This study recruited 111 adolescent patients with depression aged 13-18 and 23 healthy controls. Patients were divided into three subgroups according to suicidal ideation within the past week and history of suicide attempts. Severity of depression, suicidal ideation, and suicide risk were assessed using the Hamilton Depression Scale-17 (HAMD-17) and the Chinese version of the Beck Suicide Ideation Scale (BSI-CV). Plasma levels of IL-6, TNF-α, IFN-γ, IL-1β, and IL-10 in all participants were measured.

Results

Plasma levels of IL-6, TNF-α, IFN-γ, and IL-10 differed between the suicide risk subgroups, and the differences remained significant after controlling for severity of depressive symptoms using covariance analysis. Pairwise comparison indicated that plasma levels of these four cytokines in the high suicide risk group were higher than those in the low suicide risk group (all p<0.05), among which the level of IL-10 was significantly higher than that in the medium and low risk groups. IL-10 was positively correlated with the total score of the HAMD-17, BSI-CV, and suicidal ideation; the other four cytokines were also somewhat correlated with suicidal ideation (all p<0.05). IL-10 correlated positively with these four pro-inflammatory factors. Multiple linear regression analysis showed that IL-10 levels significant were associated with BSI-CV (β = 0.270, t = 2.897, p = 0.005) and HAMA-17 (β = 0.285, t = 3.041, p = 0.003) total scores. In binary logistic regression, after controlling for depressive symptoms, gender, age, BMI, and duration of illness: IL-10 level remained a risk factor for suicidal behavior (OR = 3.224, 95% CI 1.571-6.619 p = 0.001).

Conclusion

Adolescents with different suicide risk levels differed in plasma levels of pro-inflammatory factors and the anti-inflammatory factor IL-10. These differences were independent of depressive symptoms; high IL-10 levels may be a risk factor for suicidal behavior in depressed patients. Further research is needed to explore the relationship between anti-inflammatory factors and suicide.
Determinants of readiness to implement forensic patient-oriented research: a study of barriers and facilitators in a high-secure hospital
Authors: Evans Cara , Deljavan Sevil , Zimmermann Kayla , Allen Kristy , Moghimi Elnaz , Canning Christopher
Published: January 2025

Introduction

Forensic mental health care is intended to promote recovery and reintegration, but is often experienced by patients as punitive and aversive. Forensic patients are rarely engaged in research to explore what matters most to them, and little guidance exists on how this engagement may be facilitated. In this paper, we explore perceived determinants of readiness to implement forensic patient-oriented research in a high-secure setting.

Methods

Following a period of engagement with staff and patients in the high-secure setting, we conducted interviews with 30 staff members (including clinicians, researchers, and hospital leaders) and five patients. We analyzed interviews using a thematic analysis approach. Coding was initially informed by the Consolidated Framework for Implementation Research, and subsequent iterations of analysis extended beyond this framework to explore patterns of meaning encompassing multiple implementation domains.

Results

We identified three themes in our data: “Navigating a climate of distrust, discrimination, and restricted autonomy”; “Hearing and interpreting patient voices”; and “Experiencing a slow shift in the tide.” The first two themes represent potential challenges, including distrust and stigma; inherent restrictions in forensic care, and perceptions that patient autonomy threatens staff safety; patient fears of repercussions; and barriers to valuing and understanding patient voices. The third theme describes the ongoing shift towards patient-centredness in this setting, and participants’ interest in proceeding with forensic patient-oriented research.

Discussion

Increased attention to relationship-building, trauma-informed principles, and epistemic injustice (i.e., unfair devaluing of knowledge) in high-secure settings can support the involvement of forensic patients in research.
Predicting conversion to psychosis using machine learning: response to Cannon
Authors: Smucny Jason , Cannon Tyrone D. , Bearden Carrie E. , Addington Jean , Cadenhead Kristen S. , Cornblatt Barbara A. , Keshavan Matcheri , Mathalon Daniel H. , Perkins Diana O. , Stone William , Walker Elaine F. , Woods Scott W. , Davidson Ian , Carter Cameron S.
Published: January 2025

Background

We previously reported that machine learning could be used to predict conversion to psychosis in individuals at clinical high risk (CHR) for psychosis with up to 90% accuracy using the North American Prodrome Longitudinal Study-3 (NAPLS-3) dataset. A definitive test of our predictive model that was trained on the NAPLS-3 data, however, requires further support through implementation in an independent dataset. In this report we tested for model generalization using the previous iteration of NAPLS-3, the NAPLS-2, using the identical machine learning algorithms employed in our previous study.

Method

Standard machine learning algorithms were trained to predict conversion to psychosis in clinical high risk individuals on the NAPLS-3 dataset and tested on the NAPLS-2 dataset.

Results

NAPLS-2 and -3 individuals significantly differed on most features used in machine learning models. All models performed above chance, with Naive Bayes and random forest methods showing the best overall performance. Importantly, however, overall performance did not match those previously observed when using only NAPLS-3 data.

Conclusion

The results of this study suggest that a machine learning model trained to predict conversion to psychosis on one dataset can be used to train an independent dataset. Performance on the test set was not in the range necessary for clinical application, however. Possible reasons that limited performance are discussed.
A cross-sectional study of parental perspectives on children about COVID-19 and classification using machine learning models
Authors: Kousar Fahmida , Sultana Arshiya , Albahar Marwan Ali , Shamkuwar Manoj , Heyat Md Belal Bin , Hayat Mohd Ammar Bin , Parveen Saba , Lira John Irish G. , Rahman Khaleequr , Alammari Abdullah , Sayeed Eram
Published: January 2025

Background and objective

This study delves into the parenting cognition perspectives on COVID-19 in children, exploring symptoms, transmission modes, and protective measures. It aims to correlate these perspectives with sociodemographic factors and employ advanced machine-learning techniques for comprehensive analysis.

Method

Data collection involved a semi-structured questionnaire covering parental knowledge and attitude on COVID-19 symptoms, transmission, protective measures, and government satisfaction. The analysis utilised the Generalised Linear Regression Model (GLM), K-Nearest Neighbours (KNN), Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB), and AdaBoost (AB).

Results

The study revealed an average knowledge score of 18.02 ± 2.9, with 43.2 and 52.9% of parents demonstrating excellent and good knowledge, respectively. News channels (85%) emerged as the primary information source. Commonly reported symptoms included cough (96.47%) and fever (95.6%). GLM analysis indicated lower awareness in rural areas (β = −0.137, p < 0.001), lower attitude scores in males compared to females (β = −0.64, p = 0.025), and a correlation between lower socioeconomic status and attitude scores (β = −0.048, p = 0.009). The SVM classifier achieved the highest performance (66.70%) in classification tasks.

Conclusion

This study offers valuable insights into parental attitudes towards COVID-19 in children, highlighting symptom recognition, transmission awareness, and preventive practices. Correlating these insights with sociodemographic factors underscores the need for tailored educational initiatives, particularly in rural areas, and for addressing gender and socioeconomic disparities. The efficacy of advanced analytics, exemplified by the SVM classifier, underscores the potential for informed decision-making in public health communication and targeted interventions, ultimately empowering parents to safeguard their children’s well-being amidst the ongoing pandemic.
Digital technologies as solutions to China’s aging population: a systematic review of their opportunities and challenges in rural development
Authors: Ming Yue , Li Yimin , Liu Yun
Published: January 2025

Introduction

Differences exist in the rate of aging between individuals residing in urban and rural areas in China, with rural areas experiencing a more pronounced impact. Smart aging represents a prevalent future trend in this regard, though its development will inevitably face challenges. However, studies focusing on rural areas are scarce. Future models of aging in less developed regions, including rural areas and townships, are expected to integrate and draw inspiration from the smart aging paradigm.

Methods

We present a systematic review of the current application of digital technologies in caring for older people in rural areas. We conducted extracted and screened 26 articles out of 823, sourced from five databases: Web of Science, IEEE Xplore, Engineering Village, PubMed/MEDLINE and CNKI.

Results

The articles focus on digital technologies that cater to the daily life, medical care, spiritual comfort, and cultural entertainment needs of rural older people. In our review, we focused on four aspects of digital technology: mobile applications (apps), websites and platforms, mobile devices and terminals, and VR technologies or other unspecified technologies.

Discussion

We found that current digital technologies for smart aging have room for improvement in meeting the recreational and mental comfort needs of older adults. Digital technologies are predominantly applied to the smart community/rural and smart healthcare sectors, with limited applications in the smart home sector. Future studies should explore smart-home older adults care services to address digital cognitive barriers faced by older adults.
Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study
Authors: Sun Guo-kang , Xiang Yun-hui , Wang Lu , Xiang Pin-pin , Wang Zi-xin , Zhang Jing , Wu Ling
Published: January 2025

Objective

Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.

Methods

A case-control study was conducted to screen biomarkers for the diagnosis of silicosis using LASSO regression, SVM and RF. A sample of 612 subjects (half cases and half controls) were randomly divided into training and test groups in a 2:1 ratio. Logistic regression analysis and receiver operating characteristic (ROC) curves were used to construct a multiple biomarker-based model for the diagnosis of silicosis, which was applied to both the training and the testing datasets.

Results

The training cohort revealed significant statistical differences (P < 0.05) in multiple hematologic parameters between silicosis patients and healthy individuals. Based on machine learning, eight silicosis biomarkers were screened and identified from routine blood cell, biochemical and coagulation parameters. D-dimer (DD), Albumin/Globulin (A/G), lactate dehydrogenase (LDH) and white blood cells (WBC) were selected for constructing the logistic regression model for silicosis diagnostics. This model had a satisfactory performance in the training cohort with an area under the ROC curve (AUC) of 0.982, a diagnostic sensitivity of 95.4%, and a specificity of 92.2%. In addition, the model had a prediction accuracy of 0.936 with an AUC of 0.979 in the independent test cohort. Moreover, the diagnostic accuracies of the logistic model in silicosis stages 1, 2, and 3 were 88.0, 95.4, and 94.3% with an AUC of 0.968, 0.983, and 0.990 for silicosis, respectively.

Conclusion

A diagnostic model based on DD, A/G, LDH and WBC is successfully proposed for silicosis diagnostics. It is cheap, sensitive, specific, and preliminarily offers a potential strategy for the large-scale screening of silicosis.
The neutrophil–lymphocyte ratio as a risk factor for all-cause mortality among individuals with resolved HBV infection: evidence from the NHANES 1999–2018
Authors: Qiu Chen , Yu Chaojie , Yang Lanlan , Liu Siqi , Zhang Qian , Jia Shengnan , Wang Wenrui , Jin Zhenjing , Yu Dongdong
Published: January 2025

Background

Inflammation is a critical component in the process of resolved hepatitis B virus (HBV) infection. The neutrophil-to-lymphocyte ratio (NLR) serves as a sensitive indicator of systemic inflammation and immune activation. Our study aimed to investigate the correlation between elevated NLR levels and the risk of all-cause mortality in patients with resolved HBV infection. Additionally, we evaluated the potential mediating effect of diabetes mellitus (DM) on this correlation.

Methods

Our study enrolled 1,146 adult patients with resolved HBV infection from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. We utilized the Restricted Cubic Splines (RCS) and Maximum Selection Rank Statistical Method (MSRSM) to analyze the relationship between the NLR and the risk of all-cause mortality. The impact of NLR was evaluated using a weighted multivariate Cox regression model, and the model’s predictive accuracy was assessed using time-dependent Receiver Operating Characteristic (ROC) curves. An intermediary analysis was conducted to explore the potential influence of DM on the observed relationship.

Results

During follow-up period of 103.54 ± 4.90 months, we recorded 207 deaths among the study participants. The analysis using the RCS method revealed a significant positive correlation between the NLR and the risk of all-cause mortality. Those with elevated NLR levels faced a substantially higher mortality risk compared to those with lower levels, as indicated by a Hazard Ratio (HR) of 1.84, with a 95% Confidence Interval (CI) of 1.17 to 2.89 (p < 0.05). The predictive accuracy of the model was substantial, as evidenced by the Area Under the Curve (AUC) for ROC curves at 3, 5, and 10 years, which were 0.873, 0.870, and 0.862, respectively. Furthermore, mediation analysis indicated that DM significantly influenced the relationship between the NLR and mortality, with a mediation effect of 6.57% (95% Confidence Interval [CI]: 0.64 to 15%; p = 0.02).

Conclusion

Elevated NLR is significantly associated with an increased risk of all-cause mortality in patients with resolved HBV infection. Concurrently, DM acts as a partial mediator of this association.
Genomics costing tool: considerations for improving cost-efficiencies through cross scenario comparison
Authors: Marklewitz Marco , Jaguparov Alexandr , Wilhelm Aude , Akande Oluwatosin Wuraola , Musul Biran , Poates Angela Lee , Afrough Babak , Norberg Ashley , Hull Noah Clayton , Ehsani Soudeh ,   Group members of GCT pilot working group, Salvi Le Garrec Joanna , Whistler Toni
Published: January 2025

Next-generation sequencing (NGS) is crucial for monitoring and investigating infectious disease outbreaks, providing essential data for public health decisions. The COVID-19 pandemic has significantly expanded pathogen sequencing and bioinformatics capacities worldwide, creating an opportunity to leverage these advancements for other pathogens with pandemic and epidemic potential. In response to the need for a systematic cost estimation approach for sustainable genomic surveillance, particularly in low- and middle-income countries, five institutions collaborated to develop the genomics costing tool (GCT). These institutions are the Association of Public Health Laboratories (APHL), FIND, The Global Fund to Fight AIDS, Tuberculosis and Malaria, the UK Health Security Agency (UKHSA), and the World Health Organization (WHO). To validate the GCT, it was piloted in public health laboratories across three WHO regions: African, Eastern Mediterranean, and European. The pilot exercises were intended to assess the tool’s accuracy, utility, and functionality, exploring scenarios for validating past expenditure, routine use, cost optimization, and scaling up sequencing services. Data from these pilots demonstrated significant cost reductions per sample with increased throughput, underscoring the economic benefits of the optimized use of sequencing platforms underpinned by sample throughput. The GCT enables laboratories to estimate and visualize costs, plan budgets, and improve cost-efficiencies for sequencing and bioinformatics based on factors such as equipment purchase and preventative maintenance, reagents and consumables, annual sample throughput, human resources training, quality assurance and management. This publication shares key findings from pilot exercises offering detailed insights into the cost of routine NGS implementation using either short- or long-read sequencing technologies, demonstrating the utility of GCT as an asset to support efforts for sustainable funding and strategic planning in genomic surveillance.
Prediction of tuberculosis-specific mortality for older adult patients with pulmonary tuberculosis
Authors: Wang Sihua , Gu Ruohua , Ren Pengfei , Chen Yu , Wu Di , Li Linlin
Published: January 2025

Background

This study aims to identify risk factors associated with tuberculosis-specific mortality (TSM) in older adult patients with pulmonary tuberculosis (TB) and to develop a competing risk nomogram for TSM prediction.

Methods

We conducted a retrospective cohort study and randomly selected 528 older adult pulmonary TB patients hospitalized in designated hospitals in Henan Province between January 2015 and December 2020. The cumulative incidence function (CIF) was calculated for both TSM and non-tuberculosis-specific mortality (non-TSM). A Fine and Gray proportional subdistribution hazards model and a competing risk nomogram were developed to predict TSM in older adult patients.

Results

The 5-year cumulative incidence functions (CIFs) for TSM and non-TSM were 9.7 and 9.4%, respectively. The Fine and Gray model identified advanced age, retreatment status, chest X-rays (CXR) cavities, and hypoalbuminemia as independent risk factors for TSM. The competing risk nomogram for TSM showed good calibration and excellent discriminative ability, achieving a concordance index (c-index) of 0.844 (95% confidence interval [CI]: 0.830–0.857).

Conclusion

The Fine and Gray model provided an accurate evaluation of risk factors associated with TSM. The competing risk nomogram, developed using the Fine and Gray model, provided accurate and personalized predictions of TSM.
An analysis of artificial intelligence automation in digital music streaming platforms for improving consumer subscription responses: a review
Authors: Mokoena Nontokozo , Obagbuwa Ibidun Christiana
Published: January 2025

The rapid adoption and evolving nature of artificial intelligence (AI) is playing a significant role in shaping the music streaming industry. AI has become a key player in transforming the digital music streaming industry, particularly in enhancing user experiences and driving subscription growth. Through AI automation, platforms personalize music recommendations, optimize subscription offerings, and improve customer support services. This article reviews the role of AI in driving consumer subscription behaviors on digital music streaming platforms (DMSP), with a focus on recommendation algorithms, dynamic pricing models, marketing automation, and the future of AI in the music industry. Potential challenges related to privacy, ethics, and algorithmic biases are also discussed, showcasing how AI is revolutionizing the music streaming industry.
Caregiver perceptions of usual care home programs for persons with acquired brain injury: a qualitative descriptive study
Authors: Donoso Brown Elena V. , Stepansky Kasey , Wallace Sarah E. , Bien Isabella , Buttino Emma
Published: January 2025

Objective

The study explores caregiver perceptions of home programs for clients with acquired brain injury based on current clinical care after transition to the community.

Design

A qualitative descriptive study.

Setting

Within the community, post inpatient rehabilitation.

Participants

A convenience sample of eight caregivers of clients with acquired brain injury from one clinical site. All participants spoke English, were between the ages of 18 and 85 years, had no neurodegenerative disorders, and self-identified as caregivers.

Procedures

Two nested semi-structured interviews were completed post-discharge from an inpatient rehabilitation facility. All interviews were audio recorded and transcribed. Qualitative data analysis was performed utilizing MAXQDA© software, consensus coding, and abstraction of themes.

Results

Two themes with subsequent subthemes were identified: (1) Systems, Roles, and Responsibilities Influenced Caregivers' Perceptions of Home Program and Recovery Outlook and (2) Caregivers' Home Program Experience. The first theme addresses topics of caregiver roles and responsibilities, system supports and barriers, and their general outlook on recovery. Within the second theme, results provide a chronological description of home program training, use, and modification.

Conclusions

A caregiver’s outlook on the care receiver’s recovery and home program implementation is influenced by the burden of responsibilities, and system-level supports and barriers. The home program experience of the caregivers was reported to involve limited but satisfactory training. Caregivers saw the value in home programs and advised others to engage in them. Future programs should encourage healthcare providers to provide explicit instruction to the caregiver about their intrinsic value to home program implementation and adherence.
Factors affecting decision making among nurse managers working in government hospitals
Authors: Abeje Wubete , Tegegne Belachew , Tefera Zenebe , Zenebe Yosef , Yimam Wondwossen , Desu Birhanu , Andargie Yismaw , Amare Muluken , Kassa Molla , W/Selassie Mulugeta
Published: January 2025

Background

Effective nursing management and leadership are essential for the provision of desired patient care that will contribute to the improvement of any country's health indicators. However, nurses' views and experiences on the multitude of personal and organizational factors which may impact their decision-making abilities are often neglected in the literature. The study aimed to assess magnitude of poor decision making and its associated factors among nurse managers in South Wollo Zone Governmental Hospitals, Amhara Regional State, Ethiopia, 2023.

Methods

Non experimental cross-sectional study was conducted among 168 nurse managers in South Wollo Zone Public Hospitals from April 01 2023 to May 15/2023. Participants were selected by using a simple random sampling technique. The data were collected by using structured questionnaire from the study participants. Data were entered using EPI data version 4.6 and exported to SPSS version 26 for analysis. The bi-variable logistic regression analysis model was used to identify the potential predictor variable, with p-value <0.25 was fitted into the multivariable logistic regression analysis model; p-value less than 0.05 and an adjusted odds ratio (AOR) with a 95% confidence interval (CI) was used to declare, factors associated with the outcome variable. The model fitness was checked by using the Hosmer and Lemeshow test. Data were presented with frequency tables, graphs, and pie charts.

Results

The study found that the overall magnitude of poor decision-making among nurse managers was 35.7%. Being self-confident [AOR = 0.01, 95% CI: (00.002, 0.05)], receiving feedback [AOR = 0.24, 95% CI: 0.08, 0.76], and getting managerial support [AOR = 0.22, 95% CI: (0.06, 0.81)] were negatively associated with poor decision-making among nurse managers.

Conclusion

Self-confidence, receiving feedback, and getting managerial support were variables significantly associated with poor decision-making. Authors strongly emphasize providing managerial support for nurse managers, increasing their habit of receiving feedback from colleagues, and encouraging them to build their self-confidence.
Patterns of interpopulation variation and physiological trade-offs of the acute thermal tolerance of juvenile Chinook salmon (Oncorhynchus tshawytscha)
Authors: Zillig Kenneth W. , Bell Heather N. , FitzGerald Alyssa M. , Fangue Nann A.
Published: January 2025

Introduction

The capacity of species and populations to respond to rapid environmental change will be pivotal for their resilience in the coming decades. To explore thermal plasticity, physiological trade-offs, and associations with environmental characteristics, we assessed the heat hardening response and acclimation capacity of juvenile Chinook salmon (Oncorhynchus tshawytscha) from seven hatchery populations spanning diverse ecoregions along the West Coast of the United States.

Methods

Progeny from each population were acclimated to one of three temperatures (11, 16, or 20°C) and subjected to two acute thermal maximum (CTMAX) trials 24 h apart. The heat hardening response (ΔCTM) was calculated as the difference between an individual's second and first CTMAX trials. Acclimation capacity was determined as the maximum difference in CTMAX between fish acclimated to 11°C and 20°C during their second trial, capturing the full acclimatory scope. Bayesian models were employed to test the thermal trade-off hypothesis, which posits that individuals or populations with higher thermal tolerance have reduced capacity for acclimation. Trade-offs were analyzed at both individual and population scales. Associations between ΔCTM, acclimation capacity, and source population environmental characteristics were also examined using data from a landscape-scale, regional, river temperature model.

Results

Fish acclimated to 16°C or 20°C exhibited heat hardening (positive ΔCTM), while those acclimated to 11°C exhibited “heat weakening” (negative ΔCTM), a rare phenomenon in the literature. At the individual level, fish adhered to the thermal trade-off hypothesis, with higher thermal tolerance associated with reduced plasticity. However, no such trade-off was observed at the population level. Acclimation capacity was positively correlated with latitude and the temperature of the natural rearing environment. Additionally, ΔCTM performance improved when fish were acclimated to temperatures closer to those of their natural habitats.

Discussion

Individual fish exhibited a trade-off between thermal tolerance and plasticity, while populations did not. Thermal plasticity was associated with environmental conditions, with populations from warmer habitats demonstrating greater acclimation and heat hardening capacities. This study highlights the importance of understanding interpopulation variation to identify at-risk populations, such as those from colder habitats or with limited thermal plasticity, like the Trinity population. These findings emphasize the need to account for interpopulation differences when predicting species responses to climate change and developing conservation strategies.
Evaluation of an oral health education training program for kindergarten teachers
Authors: Hui Joanna Cheuk Yan , Chu Chun Hung , Chen Jieyi
Published: January 2025

Objectives

This study aims to examine kindergarten teachers’ satisfaction and their perceived impact of an oral health education (OHE) training program.

Methods

This study followed the steps outlined in the Program Evaluation Standards in Public Health recommended by the Centers for Disease Control and Prevention. All kindergarten teachers in Hong Kong were invited to attend the OHE training. The training comprised a lecture and a group discussion among six to eight teachers facilitated by trained dentists. The participating teachers were invited to complete an online questionnaire after the training. The questionnaire consisted of seven questions: six close-ended questions to evaluate teachers’ satisfaction with the training, their perceived oral-health-related knowledge, and their perceived competence in delivering OHE, and one open-ended question to collect their comments and suggestions for enhancing the OHE training.

Results

A total of 6,210 teachers joined the OHE training and 4,882 teachers completed the questionnaires (response rate: 79%). The survey found that 4,691 (96%) teachers were satisfied with the training, and the same number agreed that the OHE training was essential for delivering OHE. In addition, 4,680 (96%) teachers found the lecture informative and 4,393 (90%) teachers rated the group discussion as useful. After the OHE training, 4,716 (96%) teachers reported that they were more knowledgeable in recognizing childhood oral diseases and 4,665 (96%) teachers believed they were more skillful in delivering OHE. Regarding comments and suggestions, teachers opined that the OHE was informative and comprehensive. They suggested developing videos and hands-on workshops for the OHE training and expressed a desire to learn more about the dental treatment of common dental diseases. They also recommended providing teaching aids, such as booklets and tooth models, for use in kindergartens.

Conclusion

The kindergarten teachers generally had a better understanding of childhood oral conditions after the OHE training. They were generally satisfied with the training and became more confident in delivering OHE to kindergarten children.
Deep learning and smart energy-based lightweight urban power load forecasting model for sustainable urban growth
Authors: Byeon Haewon , AlGhamdi Azzah , Keshta Ismail , Soni Mukesh , Mekhmonov Sultonali , Singh Gurpreet
Published: January 2025

Introduction

Urban power load forecasting is essential for smart grid planning but is hindered by data imbalance issues. Traditional single-model approaches fail to address this effectively, while multi-model methods mitigate imbalance by splitting datasets but incur high costs and risk losing shared power distribution characteristics.

Methods

A lightweight urban power load forecasting model (DLUPLF) is proposed, enhancing LSTM networks with contrastive loss in short-term sampling, a difference compensation mechanism, and a shared feature extraction layer to reduce costs. The model adjusts predictions by learning distribution differences and employs dynamic class-center contrastive learning loss for regularization. Its performance was evaluated through parameter tuning and comparative analysis.

Results

The DLUPLF model demonstrated improved accuracy in forecasting imbalanced datasets while reducing computational costs. It preserved shared power distribution characteristics and outperformed traditional and multi-model approaches in efficiency and prediction accuracy.

Discussion

DLUPLF effectively addresses data imbalance and model complexity challenges, making it a promising solution for urban power load forecasting. Future work will focus on real-time applications and broader smart grid systems.
The (il) legitimate experts and their impact on manifest and latent social influence on employees educated in distinct socio - historical contexts
Authors: Manushi Sundic Erjona , Mugny Gabriel , Quiamzade Alain , Butera Fabrizio
Published: January 2025

This study investigates how socialization in two different educational environments (during and after the communist regime) affects the level of social influence (manifest and latent) of a director on employees. We compared employees educated during and after the communist regime in Albania and measured the influence of a message delivered in an authoritarian vs. democratic style, by a director of a company labeled as expert vs. non-expert. Results showed that employees educated during the communist regime were more influenced at both the latent and manifest level by an authoritarian expert rather than a democratic one, whereas employees educated after the communist regime were influenced only at a latent level by a democratic expert rather than an authoritarian one. No manifest influence appeared on employees educated after the communist regime independently from the leadership style. This study highlights that the influence of leadership style is context-dependent, with early socialization shaping employees' perceptions of legitimacy and determining the levels of both manifest and latent influence.
Assessment of the physical and psychological aspects of the current life support system on the International Space Station for sustainable space exploration
Authors: Ichimura Shuichi , Yamashiki Yosuke Alexandre
Published: January 2025

Life support systems in space have been developed to recover a certain amount of oxygen and water. However, we still rely on resupplies for gas tanks, water bags, and food. To achieve sustainable human space exploration, we must also consider the astronauts’ wellbeing. This research analyzes and assesses the status of essential life support elements, which are air, water, and food, as well as wellbeing elements, including clothing, hygiene, and healthcare, on the International Space Station. The types and quantities of resupplies for each element were estimated by synthesizing data from multiple sources and compared against baseline values established by the National Aeronautics and Space Administration (NASA) for one crew member per day. To evaluate the qualitative and psychological dimensions of dependence on resupply missions, astronaut feedback and comments documented in reports and articles from space agencies were also analyzed as important references. The results show that resupplies involve not only gas tanks and water bags but also a significant number of spare items to maintain recovery systems. Food completely relies on resupplies, and regarding wellbeing elements, although the mass supplied from Earth seems to meet the space agency’s requirements, astronauts feel uncomfortable wearing the same clothes and using the same towels for days, especially exercise clothes, which can develop odors. It was also discovered that each resupply mission is inefficient as resupplies account for only 0.21% of the total launch mass. Relying on resupply missions has been associated with negative effects on both physical and psychological aspects, such as anxiety about the risk of running out of life support consumables, issues with stowage and odors caused by waste, and stress due to complicated cargo unloading and loading transfer operations. As humans explore the Moon and beyond, frequent resupplies will become impractical due to higher launch costs and longer delivery times, and suggestions for developing technologies to realize a sustainable human presence in space are being proposed.
A study of Filipina migrant workers’ subjective health in Hong Kong and an assessment of eight scoring methods for the 12-Item Short Form Health Survey (SF-12)
Authors: Liao Tim F. , Gan Rebecca Yiqing
Published: January 2025

Objectives

The SF-12 version 2 is a survey instrument for collecting data on subjective health. The US-based scoring method is the recommended standard for measuring subjective health with data collected with this instrument. The inadequacy of the US-based scoring method of the SF-12 version 2 instrument for non-US populations is widely documented. However, few studies systematically assessed relative performance of alternative scoring methods against the US-based method, our main objective in this paper. Through this investigation, we also intend to shed light on Filipina migrant workers’ subjective health in Hong Kong, our case study.

Methods

This study investigates the feasibility of eight such scoring methods—six latent-variable models, the raw score index, and the US-based method—for analyzing an SF-12 version 2 instrument via a range of bootstrapped samples of varying sizes and an empirical study of the original 2017 Hong Kong Domestic Workers survey data with a set of covariates associated with Filipina migrant domestic workers’ subjective mental and physical health in Hong Kong.

Findings

Our analyses favor the latent-variable factor model with the normal distribution and the identity link for analyzing the SF-12 version 2 type of data. Our empirical study of the survey data provides evidence for the beneficial effects of education, social support, and positive working conditions on migrant domestic workers’ subjective physical health and especially subjective mental health, with these two types of health analyzed jointly on the same measurement scale.

Conclusion

For studying non-US populations with the SF-12 version 2 instrument, we recommend using the latent confirmatory factor analysis model that assumes a normal distribution and an identity link function for analyzing the MCS and PCS dimensions simultaneously.
Predicting competitive alpine skiing performance by multivariable statistics—the need for individual profiling
Authors: Nilsson Robert , Theos Apostolos , Lindberg Ann-Sofie , Malm Christer
Published: January 2025

Introduction

Predicting competitive alpine skiing performance using conventional statistical methods has proven challenging. Many studies assessing the relationship between physiological performance and skiing outcomes have employed statistical methods of questionable validity. Furthermore, the reliance on Fédération Internationale de Ski (FIS) points as a performance outcome variable presents additional limitations due to its potential unreliability in reflecting short-term, sport-specific performance. These factors complicate the selection of appropriate tests and the accurate prediction of competitive outcomes.

Method

This study aimed to evaluate the predictive power of a generalized physiological test battery for alpine skiing performance, as measured by FIS points, utilizing multivariable data analysis (MVDA). Physiological test results from a total of twelve (n = 12) world-class female skiers were included in the analysis.

Results

The result on goodness of regression (R2) and goodness of prediction (Q2) in this study indicate that valid Orthogonal Projection to Latent Structures (OPLS) models for both Slalom and Giant Slalom can be generated (R2 = 0.39 to 0.40, Q2 = 0.21 to 0.15), but also that competition performance still cannot be predicted at a group level (low Q2). In contrast, higher predictive power of competitive performance was achieved on an individual level using the same data (R2 = 0.88 to 0.99 and Q2 = 0.64 to 0.96).

Discussion

The findings of this investigation indicate that the selected tests employed in this study exhibit limited generalizability for the assessment of elite alpine skiers, as the predictive value of specific physiological parameters on competitive performance appears to be highly athlete-dependent.
Bridging the gap: challenges and adoption of climate-resilient agriculture technologies in agricultural landscapes across agro-climatic zones of Bihar, India
Authors: Jat Raj Kumar , Meena Vijay Singh , Durgude Shubham , Sohane Ravindra Kumar , Jha Ratnesh Kumar , Kumar Abhay , Kumar Ujjwal , Kumar Anjani , Singh Raj Narain , Kumar Suneel , Reddy Illathur R. , Pazhanisamy S. , Kumar Rakesh , Meena Sunita Kumari , Prakash Ved , Kumar Sanjay , Mukherjee Anirban , Kumar Brijendu , Umesh Umesh Narayan , Singh Ranjan Kumar , Chaubey Ravikant , Kumar Vikash , Kumar Mukesh , Kumar Vinod , Sharda Kumari , Singh Susheel , Singh Rama Kant , Kumari Seema , Singh Kamleshwari Prasad , Kumar Govind , Tiwari Ravindra Kumar , Kashyap Vineeta , Kushwaha Suneeta , Das Sripriya , Gautam Prem Prakash , Alam Nurnabi Meherul , Kumar Shailesh , Kumar Sanjay , Upadhaya Bharati , Singh Sumit Kumar , Ghosh Sanchita , Bhagat Shubham , Lenka Amit Kumar
Published: January 2025

How effective are climate resilient agricultural technologies (CRATs) in overcoming barriers faced in agri-food system by farmers across the different agro-climatic zones (ACZs) of Bihar? This study examines the barriers that hinder farmers in Bihar from adopting CRATs amidst the growing impacts of climate change on global agri-food systems. It focuses on key CRATs, including zero tillage/minimum tillage (ZT/MT), laser land leveling (LLL), climate-resilient variety selection (CRVS), crop diversification (CD), site-specific nutrient management (SSNM), crop calendar and timely sowing (CCTS), and direct-seeded rice (DSR), and investigates the factors affecting their adoption. Using descriptive statistics, correlation analysis, and logistic regression, key factors that influence the adoption of CRATs were identified. Descriptive statistics showed moderate levels of soil health awareness (mean value = 2.70) and climate change awareness (mean value = 2.63). Correlation analysis found that social factors like training received had a positive correlation with the adoption of DSR (correlation coefficient = 0.410). Logistic regression results highlighted that technology awareness significantly influences the adoption of DSR (coefficient = 0.400, p = 0.253), while initial investment costs are major barriers for ZT/MT and LLL (coefficient = 0.400, p = 0.267). Results highlight the need to improve awareness through educational programs, provide technical support, and offer financial incentives to overcome the various barriers farmers faced. Targeted efforts in these areas can significantly increase the adoption of the CRATs, leading to more resilient and sustainable farming systems. Study supports not only the sustainable agricultural development but also align with the United Nations Sustainable Development Goals (SDGs), particularly SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land).
Surgical management of benign tumors of the parotid gland: the advantages of extracapsular dissection compared to traditional surgical techniques
Authors: Zanghì Antonio , Cavallaro Andrea , Marchi Martine , Marchi Marcello , La Via Luigi , Sanfilippo Filippo , Cappellani Alessandro , Di Majo Simone
Published: January 2025

Introduction

Salivary gland tumors represent only 3%–6% of all head and neck neoplasms, and approximately 70% of these tumors are located in the parotid gland. Most of these tumors are found in the more abundant superficial portion of the parotid gland, lateral to the facial nerve (FN). For many years, the location of the facial nerve between the superficial and deep segments of the parotid gland hindered adequate tumor extirpation. Several surgical options are available for the treatment of benign tumors in the parotid gland, but there remains no universal agreement on what the optimal surgical treatment is. In the early twentieth century, tumor enucleation was the standard treatment for parotid tumors to preserve the facial nerve, but high recurrence rates were the main downside of this procedure. To improve the outcome, superficial parotidectomy (SP) was implemented, which involves excision of the entire lateral segment of the parotid gland, superficial to the facial nerve. However, this surgical procedure may lead to severe postoperative complications, including facial nerve paralysis, in a significant number of patients. In recent years, more gland-preserving techniques were developed to reduce complication rates and improve the safety of procedures and patients' satisfaction, without increasing the risk of recurrence.

Materials and method

This study compares our surgical experience with extracapsular dissection gland-sparing surgery (ECD) to traditional superficial parotidectomy in 56 patients who underwent surgery performed by the same surgical team.

Results

The superiority of ECD procedures compared to SP procedures was shown as far as total complication rates are concerned. In this case, Fisher's exact test statistic value was 0.0043 (significant at P < 0.05).

Conclusion

ECD should be applied in properly selected cases and further prospective studies are needed to clarify the optimal indications.