Search Results (10,990)

Objective: This qualitative study sought to explore patient experiences with technologies used in the Community Health in a Virtual Environment (Co-HIVE) pilot trial. Technology is becoming increasingly prevalent in mental healthcare, and user acceptance is critical for successful adoption and therefore clinical impact. The Co-HIVE pilot trialled a model of care whereby community-dwelling patients with symptoms of depression utilised virtual appointments and remote monitoring for the assessment and management of their condition, as an adjunct to routine care. Methods: Using a qualitative descriptive design, participants for this study were patients with symptoms of moderate to severe depression (based on the 9-item Patient Health Questionnaire, PHQ-9), who had completed the Co-HIVE pilot. Data was collected via semi-structured interviews that were audio-recorded, transcribed clean-verbatim, and thematically analysed using the Framework Method. Results: Ten participants completed the semi-structured interviews. Participants reported experiencing more personalised care, improved health knowledge and understanding, and greater self-care, enabled by the remote monitoring technology. Additionally, participants reported virtual appointments supported the clinician–patient relationship and improved access to mental health services. Conclusions: This experience of participants with the Co-HIVE pilot indicates there is a degree of acceptance of health technologies for use with community mental healthcare. This acceptance demonstrates opportunities to innovate existing mental health services by leveraging technology. Full article

The scourge of food waste (FW) is a significant global challenge, impacting climate change, food security, and the sustainability of agrifood systems. The objective of this paper is to identify, analyze, and understand the factors influencing household consumer behaviors in Romania regarding the reduction of FW. Three primary research objectives were established to assess food consumption behaviors within households, to explore attitudes toward FW, and to understand the motivations for reducing FW along with the measures implemented by households to address this issue. Methodology: Data were collected through an online self-administered questionnaire, designed to investigate consumer behaviors related to the avoidance of FW. A descriptive statistical analysis was performed, and a linear regression model was developed to evaluate a composite index measuring Romanian consumers’ behavior towards FW reduction. Results: The resulting model identifies key predictors that drive concrete actions to minimize FW, including the desire to mitigate the environmental impact, household conversations about FW and strategies to reduce it, established food routines, the influence of one’s social circle, individual ecological and social responsibility, and the effectiveness of awareness campaigns addressing the consequences of FW. Practical and social implications: The findings highlight the necessity of education and awareness initiatives to shift attitudes and behaviors concerning FW. Future research is warranted to deepen understanding and enhance interventions. Originality: This study represents a pioneering and innovative inquiry into FW behavior in Romania, filling a gap in the existing literature and contributing to the broader discourse on this pressing environmental issue. Full article

Background/Objectives: There has been limited evidence on the long-term impacts of coffee intake on health. We aimed to investigate the association between coffee intake and the incidence of diseases and mortality risk over 20 years among community-dwelling Chinese adults. Methods: Participants were from the Hong Kong Osteoporosis Study who attended baseline assessments during 1995–2010. Coffee intake was self-reported through a food frequency questionnaire and was previously validated. Disease diagnoses, which were mapped into 1795 distinct phecodes, and mortality data were obtained from linkage with territory-wide electronic health records. Cox models were used to estimate the association between coffee intake and the incidence of each disease outcome and mortality among individuals without a history of the respective medical condition at baseline. All models were adjusted for age, sex, body mass index, smoking, alcohol drinking, and education. Results: Among the 7420 included participants (mean age 53.2 years, 72.2% women), 54.0% were non-coffee drinkers, and only 2.7% consumed more than one cup of coffee per day. Over a median follow-up of 20.0 years, any coffee intake was associated with a reduced risk of dementia, atrial fibrillation, painful respirations, infections, atopic dermatitis, and dizziness at a false discovery rate (FDR) of <0.05. Furthermore, any coffee intake was associated with an 18% reduced risk of all-cause mortality (95% confidence interval = 0.73–0.93). Conclusion: In a population with relatively low coffee consumption, any coffee intake is linked to a lower risk of several neurological, circulatory, and respiratory diseases and symptoms, as well as mortality. Full article

Background: Meaning in Life (MiL) represents a key variable in mental health models of personal recovery. There is a need for straightforward and concise instruments to assess this construct quantitatively in individuals diagnosed with severe mental illness (SMI). Objective: The aim of the present study was to test the psychometric properties of the Purpose in Life Test-Short Form (PIL-SF), a brief self-report measuring the presence of MiL, in a sample of individuals with SMI. Methods: The participants were 41 adults (21 women, 51.8% and 20 men, 48.2%) aged 18 to 65 years (M = 50.05; SD = 10.73) with a diagnosis of SMI (schizophrenia, 61%; bipolar disorder, 26.8%; borderline personality disorder, 7.3%; and major depression, 4.9%) and clinically stable. The PIL-SF, Satisfaction with Life Scale (SWLS), Oxford Happiness Questionnaire—6 Item (OHQ-6), Engagement in Meaningful Activities Survey (EMAS), and Seeking of Noetic Goals—8 Item (SONG-8) were used. Descriptive analysis, estimation of the internal consistency, and Confirmatory Factor Analysis of the PIL-SF were conducted. Furthermore, correlations between the PIL-SF, SWLS, OHQ-6, EMAS, and SONG-8 were calculated. Results: The PIL-SF showed acceptable internal consistency (ω = 0.81) and an excellent fit as a unidimensional scale (CFI = 1.000, TLI = 1.070, RMSEA = 0.000, SRMR = 0.021), confirming its factorial structure. Regarding construct validity, correlations between the PIL-SF and the SWLS (ρ = 0.54, p < 0.001), the OHQ-6 (ρ = 0.52, p < 0.001), and EMAS (ρ = 0.44, p < 0.005) were positive and significant, whereas the correlations between the PIL-SF and the SONG-8NfM (ρ = −0.35, p < 0.025) were negative and significant. Conclusions: The Spanish version of the PIL-SF appears to be a reliable and valid instrument to measure the presence of MiL in adults with SMI. Full article

This study introduces AffectiVR, a dataset designed for periocular biometric authentication and emotion evaluation in virtual reality (VR) environments. To maximize immersion in VR environments, interactions must be seamless and natural, with unobtrusive authentication and emotion recognition technologies playing a crucial role. This study proposes a method for user authentication by utilizing periocular images captured by a camera attached to a VR headset. Existing datasets have lacked periocular images acquired in VR environments, limiting their practical application. To address this, periocular images were collected from 100 participants using the HTC Vive Pro and Pupil Labs infrared cameras in a VR environment. Participants also watched seven emotion-inducing videos, and emotional evaluations for each video were conducted. The final dataset comprises 1988 monocular videos and corresponding self-assessment manikin (SAM) evaluations for each experimental video. This study also presents a baseline study to evaluate the performance of biometric authentication using the collected dataset. A deep learning model was used to analyze the performance of biometric authentication based on periocular data collected in a VR environment, confirming the potential for implicit and continuous authentication. The high-resolution periocular images collected in this study provide valuable data not only for user authentication but also for emotion evaluation research. The dataset developed in this study can be used to enhance user immersion in VR environments and as a foundational resource for advancing emotion recognition and authentication technologies in fields such as education, therapy, and entertainment. This dataset offers new research opportunities for non-invasive continuous authentication and emotion recognition in VR environments, and it is expected to significantly contribute to the future development of related technologies. Full article

Background/Objectives: Parents of premature infants experience depression, anxiety, post-traumatic stress disorder, and increased stress, which can negatively impact parent–infant relationships and infant development. To reduce negative consequences and optimally support families, we developed the Transition to Home model (TtH). In this randomized controlled pilot trial (RCT), the feasibility of performing an experimental study to analyse the effects of TtH on parental mental health over time was evaluated. Methods: The following domains were assessed: recruitment, follow-up and study burden, outcome measures used and parental mental health outcomes. We included n = 22 parent couples with their preterm infants in the control group and n = 23 in the intervention group. Depression, anxiety and post-traumatic stress disorders, parenting stress, and parental self-efficacy were assessed at five timepoints. The study burden was evaluated once at the end of the study. Results: The control and intervention groups had similar socio-demographic characteristics. The groups showed no differences in the mental health outcomes except for depression in mothers at T2 (p = 0.042) and T5 (p = 0.027) and state anxiety in fathers at T2 (p = 0.016). Conclusions: This pilot RCT established a framework for the evaluation of the TtH model of care and demonstrated the viability of the evaluation scheme. The results confirm the suitability of the RCT’s structure and the feasibility of the methods and instruments used. Minor adjustments are recommended to include a more diverse sample in future studies. Full article

This study evaluates the relative and combined effectiveness of seaweed rafts and light traps in attracting juvenile fish, focusing on diel variations in juvenile fish assemblage in the tropical coastal waters of Gaolong Bay, Wenchang City, Hainan Province. Sampling was conducted in May 2023 during various time periods using self-made artificial drifting seaweed rafts and light traps. The nonparametric Kruskal–Wallis was employed to compare the diversity and catch per unit effort of juvenile fish across different time periods and sampling methods. The Permutational Multivariate Analysis of Variance, heatmaps, and Principal Coordinates Analysis were used to analyze and visualize the differences between juvenile fish assemblages. Our findings indicate that light traps were particularly effective during nocturnal periods, capturing a diverse array of species and achieving the highest richness and evenness indices. Seaweed rafts demonstrated the lowest diversity indices, largely due to the dominance of specific species, which likely contributed to the competitive exclusion of other species. Seaweed rafts showed significant effectiveness during noon, providing critical habitat and shelter that attracted juvenile fish despite the lower diversity. While each method demonstrated specific advantages, their combined approach did not significantly improve juvenile fish aggregation compared to the individual method. These findings underscore the importance of considering diel and tidal cycles in the selection of sampling methods, as aligning the method with the time of day can greatly enhance the accuracy of biodiversity assessments, leading to more informed conservation and management strategies for tropical coastal waters. Full article

Grasping how scale influences the interactions among ecosystem services (ESs) is vital for the sustainable management of multiple ESs at the regional level. However, it is currently unclear whether the actual ES interactions and their driving mechanisms are consistent across different spatial and temporal scales. Therefore, using the Lishui River Basin of China as a case study, we analyzed the spatial and temporal distribution of five key ESs across three scales (grid, sub-watershed, and county) from 2010 to 2020. We also innovatively used Pearson correlation analysis, Self-organizing Mapping (SOM), and random forest analysis to assess the dynamic trends of trade-offs/synergies among ESs, ecosystem service bundles (ESBs), and their main socio-ecological drivers across different spatiotemporal scales. The findings showed that (1) the spatial distribution of ESs varied with land use types, with high-value areas mainly in the western and northern mountainous regions and lower values in the eastern part. Temporally, significant improvements were observed in soil conservation (SC, 3028.23–5023.75 t/hm²) and water yield (WY, 558.79–969.56 mm), while carbon sequestration (CS) and habitat quality (HQ) declined from 2010 to 2020. (2) The trade-offs and synergies among ESs exhibited enhanced at larger scales, with synergies being the predominant relationship. These relationships remained relatively stable over time, with trade-offs mainly observed in ES pairs related to nitrogen export (NE). (3) ESBs and their socio-ecological drivers varied with scales. At the grid scale, frequent ESB flows and transformations were observed, with land use/land cover (LULC) being the main drivers. At other scales, climate (especially temperature) and topography were dominant. Ecosystem management focused on city bundles or downstream city bundles in the east of the basin, aligning with urban expansion trends. These insights will offer valuable guidance for decision-making regarding hierarchical management strategies and resource allocation for regional ESs. Full article

Background: Digital devices significantly contribute to vision-related problems. In addition, prolonged postural imbalance, owing to excessive use of digital devices, can lead to the tightening of head and neck muscles, resulting in neck pain, a common musculoskeletal discomfort that significantly affects individuals with poor vision. This study aimed to evaluate the prevalence and interrelationships of screen time, visual disorders, and neck pain among students at Majmaah University. Methods: A cross-sectional study was conducted at Majmaah University, Saudi Arabia, enrolling students aged 18 to 25 years. Exclusion criteria included neurological or musculoskeletal disorders. Demographic data and information on visual and neck pain symptoms were collected. The Neck Disability Index questionnaire was used to assess neck pain, and data were analyzed using SPSS version 24.0. Results: Among 263 participants, 53.6% were female. Nearsightedness (38.0%) and dry/itchy eyes (49.0%) were the most common visual disorders and symptoms, respectively. Visual disorders were prevalent in 62.0% of students, while neck pain was reported by 79.5%. Females and those studying for more than 5 h using electronic screens daily reported higher neck disability index scores. A significant association was found between >5 h of study duration [screen time] and neck disability (OR 3.703, 95% CI 1.500–9.144, p = 0.005). Conclusion: The study highlights a relationship between visual problems and neck pain among university students, emphasizing the need for addressing vision-related issues to reduce neck discomfort. High screen time could substantially increase the odds of developing neck disability. However, authors warrant cautious interpretation in the light of following limitations: cross-sectional study, small sample size, lack of statistical power, and self-reported data. Full article

To solve the problem of large residual deformation and high repair cost of traditional frame structures after an earthquake, a new type of assembled shuttle-shaped self-centering mild steel energy dissipation brace (ASSSEDB) with stable stiffness, material saving, and easy replacement was proposed. The plastic deformation of mild steel is used to dissipate energy, and the disc spring system provides a reset function. Based on the working mechanism of energy dissipation brace, a restoring force model for the ASSSEDB was established, and then the numerical analysis was carried out by ANSYS to verify the accuracy of the proposed model. The results confirm that the ASSSEDB has stable energy dissipation ability and a resetting function, with a full hysteresis curve. The finite element analysis results align well with the developed restoring force model, and the maximum deviations of initial stiffness and ultimate capacity are, respectively, 1.4% and 2.3%, which indicates that the established restoring force model can provide a theoretical basis for design of the ASSSEDB. Furthermore, the time history analysis was carried out to assess the seismic performance of a six-story steel frame structure using the proposed ASSSEDB. The results show that compared with the steel frame structure with BRBs, the proposed ASSSEDB can decrease the residual deformation of structures by up to 93.41%. The self-centering ratio of the ASSSEDB is crucial in controlling residual deformation of structures, and it is recommended to be greater than 1.0. Full article

In the context of high academic pressure and inadequate physical activity (PA) among adolescents, it is important to study how the physical environment and students’ perceptions affect their physical activity during school recess. An empirical study was conducted in four secondary schools in Xi’an to gather data on students’ physical activity using DJI Mini Drone recordings and self-reported questionnaires. Three physical activity indices—concentration, type richness and intensity—were visualized and quantified for intercomparison. This study found that physical environmental factors such as the building shape complexity and green space proportion significantly affected the PA concentration and intensity indices, whereas the campus area per student, the average distance to PA facilities and the number of PA facilities indicated a strong correlation with the PA richness index at the school level. Additionally, perceived environmental factors like space safety, facilities enjoyment and visual accessibility exerted influence on the PA intensity and frequency at the individual level. The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. By incorporating spatial, perceptual and behavioral aspects, this approach provides an efficient and integrated analytical methodology to promote adolescents’ health in school. Full article

The objective of the EU project Resilience for Dairy (R4D) is to develop and strengthen a self-sustainable Thematic Network on resilient dairy farms in 15 European countries. This article focusses on those solutions (practices and techniques) that are assessed contributing to a resilient dairy farming sector. The opinions of experts, farmers, and stakeholders were collected and scored through surveys and in a series of local workshops. Six key contributing knowledge fields are included: economic and social resilience, technical efficiency, environment, animal welfare and health, and societal perception. Assessing these knowledge fields proved to be a good predictor for measuring resilience. Only the impact fields of animal welfare and health and societal perception overlapped each other in response. This study shows differences in the choice of solutions across Europe. Experts from South and East Europe are more positive about the contribution of solutions to resilience than their colleagues from North and West Europe, except for social life items. Expert and farmer/stakeholder opinions differ regarding several of the solutions. Technical efficiency is a leading strategy. Priority topics of interest are communication with society, renewable energy production, strategic hoof trimming, early detection of diseases, monitoring fertility and health, and calf rearing. Besides resilience, attractiveness and readiness of the solutions were also assessed. Full article

Background: Insulin resistance, a key factor in developing type 2 diabetes mellitus, is linked to various health conditions. The basis of its treatment is lifestyle modification. However, adherence to nutritional and other medical recommendations can be challenging for chronic disease patients due to many factors, including demographics, social context, gender, age, and the patient’s baseline health condition. This study aims to evaluate the impact of online support group members on the diet quality of women with insulin resistance. Methods: This study was conducted as an online survey consisting of KomPAN (validated food frequency questionnaire) augmented with questions regarding using professional counseling and membership in support groups. The study covered 1565 women with insulin resistance, 1011 of whom were associated with the online support group. Results: The mean pHDI (pro-health diet index) was 5.18 ± 2.69 in the support groups and 4.86 ± 2.69 in the control group (p = 0.0319. There were no significant differences in the nHDI (non-health diet index). We found that the pHDI is associated with financial situations, the household’s situation, occupation education level, and medical or dietitian care, whereas occupation, medical, and dietitian care affect the nHDI. Membership in support groups is related to a higher pHDI and state of self-assessment of nutritional knowledge. Conclusions: Our study indicates a relationship between participation in online support groups and dietary behaviors and the subjective assessment of nutrition knowledge. Future research should focus on elucidating the mechanisms behind these influences and exploring how these communities can be optimized for broader public health initiatives. Full article

The evolution of landslides is influenced by the complex interplay of internal geological factors and external triggering factors, resulting in nonlinear dynamic changes. Although deep learning methods have demonstrated advantages in predicting multivariate landslide displacement, their performance is often constrained by the challenges of extracting intricate features from extended time-series data. To address this challenge, we propose a novel displacement prediction model that integrates Variational Mode Decomposition (VMD), Self-Attention (SA), and Long Short-Term Memory (LSTM) networks. The model first employs VMD to decompose cumulative landslide displacement into trend, periodic, and stochastic components, followed by an assessment of the correlation between these components and the triggering factors using grey relational analysis. Subsequently, the self-attention mechanism is incorporated into the LSTM model to enhance its ability to capture complex dependencies. Finally, each displacement component is fed into the SA-LSTM model for separate predictions, which are then reconstructed to obtain the cumulative displacement prediction. Using the Zhonghai Village tunnel entrance (ZVTE) landslide as a case study, we validated the model with displacement data from GPS point 105 and made predictions for GPS point 104 to evaluate the model’s generalization capability. The results indicated that the RMSE and MAPE for SA-LSTM, LSTM, and TCN-LSTM at GPS point 105 were 0.3251 and 1.6785, 0.6248 and 2.9130, and 1.1777 and 5.5131, respectively. These findings demonstrate that SA-LSTM outperformed the other models in terms of complex feature extraction and accuracy. Furthermore, the RMSE and MAPE at GPS point 104 were 0.4232 and 1.0387, further corroborating the model’s strong extrapolation capability and its effectiveness in landslide monitoring. Full article

Past research has identified that some individuals with intellectual and developmental disabilities who engage in target behavior (e.g., aggression, self-injury) maintained by negative reinforcement engage in the behavior to escape or avoid social interaction specifically (i.e., social avoidance). However, assessment and treatment strategies for this function are understudied when compared to target behavior maintained by other forms of negative reinforcement. The current study builds on this limited research and demonstrates (a) a replication of functional analysis conditions and a negative reinforcement latency assessment to identify the specific types of social interaction that evoke target behavior, and (b) an intervention that includes stimulus fading, social conditioning, and differential reinforcement for five participants with autism spectrum disorder. Participant target behavior decreased within the intervention phase for four out of five participants. The implications of strategies to guide the use of antecedent-based treatment strategies are discussed for target behavior maintained by social avoidance. Full article