Cumulative Contribution Research Articles

Canonical correlation-based relationships between social support and sleep quality in a hospital psychiatric outpatient population with examining the mediating roles of anxiety and depressive symptoms

Objective: This study aims to examine the associations between various dimensions of social support and sleep quality in a hospital psychiatric outpatient population using canonical correlation analysis, while also investigating the potential mediating roles of anxiety and depressive symptoms. Methods: Employing a cross-sectional design, survey data were collected from 10,071 individuals visiting Hangzhou Seventh People’s Hospital between October 2020 and October 2023. After excluding invalid cases, a total of 10,063 participants were included for analysis. The survey encompassed gathering basic demographic information as well as administering the Social Support Rating Scale, Self-rating Depression Scale, Self-rating Anxiety Scale, and Pittsburgh Sleep Quality Index Scale. Data analysis was conducted using SPSS 27.0 statistical software with canonical correlation analysis employed to examine the relationships. Additionally, the mediating effects of anxiety and depression symptoms were examined using the SPSS PROCESS macro. Results: Canonical correlation analysis reveals a significant positive correlation between social support dimensions and various aspects of sleep quality. The first pair of canonical variables (r = 0.586, p < 0.001) accounts for an impressive 97% of the cumulative contribution. It is found that this pair of canonical variables explains 68.9% of the variance in social support and 49.0% in sleep quality. Mediation analysis revealed that anxiety and depressive symptoms significantly mediated the relationship between social support and sleep quality, accounting for 88% of the total effect. Specifically, anxiety accounted for 47% mediation while depression accounted for 41%. Conclusion: The study findings revealed a significant positive correlation between social support and sleep quality dimensions, indicating a robust association between increased social support and enhanced individual sleep quality. Furthermore, the results indicated that anxiety and depression partially mediated the relationship between social support and sleep quality, offering novel insights into the intricate connection between mental health and sleep quality.

The internal relationship of college students’ physical exercise behavior and related factors based on ecological model

Background: The persistence of college students’ physical exercise behavior has an important impact on their physical health level and their positive psychological effects. The health behavior ecology model is more comprehensive and progressive than other exercise psychology theories in explaining the effect of physical activity intervention on long-term maintenance. Based on this, In this study, using the socio-ecological model theory as the entry point, applying five different levels of influencing factors in the theoretical model to the field of adolescent physical exercise behavior, The aim is to seek the internal connection between the ecological factors that promote college students’ physical exercise behavior through the investigation, so as to provide corresponding intervention strategies for promoting the healthy development of their physical fitness. So as to promote the formation of college students’ physical exercise habits. Methods: In 2023, 1015 college students were surveyed by questionnaire and measurement scale, followed by descriptive statistical analysis of college students’ current physical exercise behavior, and factor analysis of ecological factors affecting college students’ physical exercise. Results: From the behavior characteristics of college students’ physical exercise, different gender of college students in physical exercise, weekly exercise, exercise time is very significant difference (P &lt; 0.001), the boys in sports participation higher than girls 15.2%, choose occasionally exercise boy’s ratio 10% higher than girls, girls do not participate in exercise more than boys. In terms of exercise time, a few boys choose to do physical exercise on weekends; the proportion of boys in more than 60 min of physical exercise is 7 percentage points higher than girls. In the time of extracurricular exercise, support of parents and physical exercise (P &lt; 0.05), there was no significant difference between male and female students in the aspects of intensity of each exercise, participation in sports competition and reasons for not exercise (P &gt; 0.05). The principal component analysis of the influencing factors of college students’ physical exercise behavior was conducted from the individual, family, school, community, and policy levels. The KOM value was 0.984, which met the judgment criteria of factor analysis. Through principal component analysis of the above five levels, according to the requirements of factors greater than 1, the individual level, family level, school level and policy level respectively two factors, corresponding cumulative contribution rate is 56.545%, 595.350%, 64.870% and 85.700% respectively, community level three factors, corresponding to the cumulative contribution rate of 76.450%. Conclusion: The advantage of the health behavior ecology model is that the comprehensive intervention strategies based on multi-level, multi-level effects greatly expand people’s understanding of the intervention. This model is applied to the field of physical health promotion of college students, to study human exercise behavior through the joint action of physiological, psychological and environmental factors, so as to more comprehensively reveal the various factors of exercise behavior, as well as the mutual relationship and influence between them. The results of this study indicate that: among the ecological factors that affect the physical exercise behavior of college students, the individual factors of college students are a necessary condition for physical exercise, while family, school and community factors affect the direction of the change and development of college students’ physical exercise behavior. Policy factors are a powerful driving force for college students’ physical exercise behavior. Only by considering the relationship between the relevant factors can we better understand the characteristics of college students’ physical exercise development, put forward the corresponding intervention strategies, and promote the formation of college students’ physical exercise habits through effective ways.

Diversity Analysis and Comprehensive Evaluation of 101 Soybean (Glycine max L.) Germplasms Based on Sprout Quality Characteristics

Soybean sprouts are a common culinary vegetable due to their high nutrition and tasty flavors. To select soybean varieties with excellent sprout quality, 101 soybean materials were collected from different regions of China, and eight sprout quality parameters were determined for overall evaluation. The results showed that eight sprout quality parameters achieved varying degrees of difference and correlation. Based on the principal component analysis (PCA), three principal components were extracted, with a cumulative contribution rate of 78.314%. Further, the comprehensive evaluation value (D) of soybean sprout quality was calculated by membership function analysis based on PCA, and the quality of soybean sprouts was ranked accordingly. Subsequently, a regression equation for the prediction of soybean sprout quality was established using a stepwise regression analysis, and the model showed a good prediction performance (correlation coefficient of prediction &gt; 0.8; residual predictive deviation &gt; 2.0). On these grounds, it was proposed that the quality of soybean sprouts could be comprehensively predicted by four parameters: hypocotyl length, edible rate, 100-seed weight, and total isoflavone content and saponin content. In conclusion, this study provides excellent varieties for soybean sprout production and new variety breeding, and it provides an important reference for the prediction of soybean sprout quality.

Decomposition analysis of renewable energy demand and coupling effect between renewable energy and energy demand: evidence from China

Driving up demand for renewable energy is key to China's response to the energy crisis and to controlling carbon emissions. Several studies have been conducted to explore the factors affecting renewable energy demand. However, the literature on the importance of technological innovation in fossil energy production in affecting renewable energy demand is scant. Therefore, it is essential to explore the impact of technological innovations in fossil energy production on renewable energy demand, as well as to reveal the dynamic penetration mechanism of renewable energy in the field of energy demand, to provide policy guidelines for China to promote its energy revolution. This study decomposes renewable energy demand into 10 drivers with the extended IDA-PDA (Index Decomposition Analysis and Production-theory Decomposition Analysis) model. Then the dynamic penetration mechanism of renewable energy on the energy demand side is revealed by combining the coupled model and the decomposition results. The results show that the investment intensity effects and energy restructuring contributed the most to renewable energy demand growth, contributing 60.73% and 79.97% respectively. Conversely, technological advances in fossil energy combustion made the largest negative cumulative contribution to renewable energy demand growth, with a cumulative negative contribution of -39.57%. The drivers of renewable energy demand vary considerably across types, regions and resource endowment levels, which means that regions should develop differentiated development strategies based on their own characteristics. In addition, the coupling effect between renewable energy demand and total energy demand is weakening, with market and policy effects becoming the drivers for augmenting the response of renewable energy to total energy demand. The findings of this study provide clear pathways for expanding renewable energy demand, offering important insights for the government to balance between promoting capital-driven interests and policy-driven development.

Metabolite and mineral contents in root, seed, testa, stem and leaf of Peganum harmala L

In order to investigate the distribution and accumulation characteristics of metabolites and mineral elements in different parts of Peganum harmala L. (P. harmala), and the synergistic or antagonistic effects between them. In this study, nuclear magnetic resonance (NMR), high performance liquid chromatography (HPLC) and inductively coupled plasma optical emission spectrometer (ICP-OES) were used to determine the contents of metabolites (proline, phosphorylcholine, choline, lysine, 4-hydroxyisoleucine, asparagine, acetic acid, sucrose, harmaline and vasicine) and mineral elements (Ca, Mg, K, P, Na, Cr, Cu, Fe, Zn, Mn, Ni, C, N) in five parts of P. harmala, including root, seed, testa, stem and leaf, and to analyze the relationship among the contents of metabolites and mineral elements. The results showed that the contents of acetic acid, proline, lysine, sucrose and Fe in the root were higher than those in other parts, and the contents of harmaline, phosphorylcholine, P, C, N and Zn in the seeds were the highest. The leaves were rich in vasicine, Na, K, Ca, Mg and Mn. The principal component analysis (PCA) showed that the cumulative variance contribution of the first two principal components was 69.00 %, and the loading values of K, Cu and sucrose were higher, which was consistent with the results of biplot and cluster analysis(HCA). Correlation analysis (CA) results showed that there was a strong overall correlation between the different components of seeds and leaves, and the correlation was greater than that of other parts. The results of this study are helpful to understand the correlation of functional traits among different parts of plants, and determine the internal mechanism of controlling functional traits and the proportional relationship between traits, so as to provide a reference for the resource utilization of plants.

Non-Destructive Analysis for Machine-Picked Tea Leaf Composition Using Near-Infrared Spectroscopy Combined Chemometric Methods

This paper aimed to predict the mechanical composition of machine-picked fresh tea leaves (MPFTLs) using near-infrared spectroscopy (NIRS) rapidly and non-destructively. Samples of MPFTL with different mechanical composition ratios were collected and subjected to NIRS analysis. Subsequently, various preprocessing methods were employed to eliminate extraneous noise information. Next, characteristic spectral information was extracted using the backward interval partial least squares (biPLS) method, which was subsequently subjected to principal component analysis (PCA). Finally, a predictive model was constructed by applying the back propagation artificial neural network (BP-ANN) method, which was tested by external samples to assess its predictive efficacy, and the results were expressed as root mean square error and determination coefficient of prediction (Rp2). The optimal spectral pretreatment method was the following: (standard normal variate (SNV) + second derivative (SD)). Four characteristic spectral subintervals of ([2, 3, 7, 10]) were screened out, and the cumulative contribution rate of 95.20%, attributable to the first three principal components, was determined. When the tanh transfer function was applied to construct the BP-ANN-NIRS model, the results demonstrated optimal performance, exhibiting a root mean square error and a determination coefficient of prediction (Rp2) of 0.976 and 0.027, respectively. The absolute values of prediction deviation for all prediction set samples were found to be less than 0.04. The results of the best BP-ANN model for external samples were found to be in close agreement with those of the prediction set model. NIRS technology has successfully achieved the forecasting of the mechanical composition of machine-picked fresh tea leaves rapidly and accurately, providing a fair and convenient new method for purchasing fresh tea raw materials by machines, according to their quality, and promoting the sustainable high-quality and healthy development of the tea industry.

Study on HPLC fingerprint of Saposhnikovia divaricata lipophilic components and anti-aging effects

Saposhnikovia divaricata is commonly used in clinical practice as a heat-clearing and detoxifying traditional Chinese medicine. Current research on Saposhnikovia divaricata has mostly focused on chromones, while studies on its lipophilic parts remain scarce. In this study, samples of the lipophilic components of Saposhnikovia divaricata (SDL) from different regions in China were collected to establish an HPLC fingerprint. The quality of SDL was evaluated through chemical pattern recognition and multi-component content determination. Furthermore, using the Caenorhabditis elegans (C. elegans) model, the anti-aging ability of SDL was preliminarily studied. In the HPLC fingerprints of 11 batches of SDL, 19 common peaks were identified, and 4 components were characterized as follows: peak 14, linolenic acid (ALA); peak 15, docosahexaenoic acid (DHA); peak 16, linoleic acid (LA); peak 17, oleic acid (OA). The similarity of the fingerprint ranged from 0.704 to 0.929. The results indicate that the content of ALA, DHA, LA, and OA are 0.040–0.440 mg/g, 0.003–0.116 mg/g, 1.047–6.460 mg/g, and 0.040–0.294 mg/g, respectively. HCA analysis divided 11 batches of SDL into two categories, and PCA analysis extracted 6 principal components with a cumulative contribution rate of 85.91%. The anti-aging ability of the SDL was proved by measuring the lifespan, reproductive capacity, body length, mobility, lipofuscin content, and heat stress resistance of C. elegans. The combination of high-performance liquid chromatography fingerprint and chemical pattern recognition for multi-component content determination is a reliable, comprehensive, and promising evaluation of the quality of SDL. The confirmation of SDL’s anti-aging ability provides the possibility for the research of Saposhnikovia divaricata in the field of healthy food and cosmetics.

Genetic Risk Scores for the Clinical Rheumatologist.

The advent of genome-wide sequencing and large-scale genetic epidemiological studies has led to numerous opportunities for the application of genetics in clinical medicine. Leveraging this information toward the formation of clinically useful tools has been an ongoing research goal in this area. A genetic risk score (GRS) is a measure that attempts to estimate the cumulative contribution of established genetic risk factors toward an outcome of interest, taking into account the cumulative risk that each of these individual genetic risk factors conveys. The purpose of this perspective is to provide a systematic framework to evaluate a GRS for clinical application. Since the initial polygenic risk score methodology in 2007, there has been increasing GRS application across the medical literature. In rheumatology, this has included application to rheumatoid arthritis, gout, spondyloarthritis, lupus, and inflammatory arthritis. GRSs are particularly relevant to rheumatology, where common diseases have many complex genetic factors contributing to risk. Despite this, there is no widely accepted method for the critical application of a GRS, which can be a particular challenge for the clinical rheumatologist seeking to clinically apply GRSs. This review provides a framework by which the clinician may systematically evaluate a GRS. As genotyping becomes more accessible and cost-effective, it will become increasingly important to recognize the clinical applicability of GRSs and identify those of the highest utility for patient care. This framework for the evaluation of a GRS will also help ensure reliability among GRS research in rheumatology, thereby helping to advance the field.

Construction and Validation of Academic Support Scale in Middle School (ASSMS)

Research on social support in China has been relatively comprehensive as psychological development cannot be separated from the social environment. Family, teachers, and friends are the main sources of social support for middle school students. If we can fully utilize the academic support provided by families, teachers, and classmates in daily life, improve students’ personal efficacy, stimulate their learning motivation and desire, and provide corresponding emotional, resource, behavioral, and willingness support for middle school students, it will help them better enhance their learning adaptability, increase their investment in learning, and then improve their learning consciousness, ultimately promoting the enhancement of academic achievement and the development of their abilities. Therefore, based on the existing scales of social support and academic support, this study determined the academic support scale for middle school students, exploring the source of academic support from four dimensions: willingness support, resource support, emotional support, and behavioral support. Based on a literature review and questionnaire, a formal scale was formed to measure the academic support of middle school students. In total, 762 students from two middle schools in Shijiazhuang and Hengshui were selected as subjects for data analysis. Exploratory factor analysis showed that the scale was composed of four factors: willingness support, resource support, emotional support, and behavioral support, with a cumulative contribution rate of 54.15%. The factor loadings of the items ranged from 0.423 to 0.783. The indicators obtained by confirmatory factor analysis were χ2/df of 2.98, RMSEA of 0.072, GFI of 0.841, IFI of 0.902, TLI of 0.891, and CFI of 0.901. The Cronbach’s α coefficient was 0.955, the Spearman–Brown coefficient was 0.939, and the correlation coefficients between each dimension and the total scale were 0.892–0.945. The results show that the reliability and validity of the scale are within the acceptable range, in line with the standards of measurement, and can be used as a tool to measure the academic support of middle school students. This measurement can be used to evaluate the multidimensional academic support systems in middle schools and inform the development of targeted interventions to promote student success and well-being.

Spatiotemporal gait characteristics post-total hip arthroplasty and its impact on locomotive syndrome: a before-after comparative study in hip osteoarthritis patients.

Understanding the gait pattern of patients eligible for total hip arthroplasty (THA) due to hip osteoarthritis (OA) offers valuable information for improving locomotive syndrome (LS). This study aims to measure the gait patterns of THA-eligible patients using an optical motion capture system and to analyze these patterns using principal component analysis (PCA). Additionally, this study examines the relationship between THA-induced gait patterns and LS. This before-after study included 237 patients who underwent unilateral primary THA due to hip OA. The primary outcome measures were spatiotemporal gait parameters. Secondary outcome measures included three LS risk tests: a stand-up test, a two-step test, a 25-question Geriatric Locomotive Function Scale (GLFS-25), and total clinical decision limits stages. PCA was performed using 16 spatiotemporal gait parameters collected before and three months after THA. Principal components (PC) were selected to achieve a cumulative contribution rate of 90% (0.9) or higher. Each summarized PC was compared using a paired t-test before and three months after THA. Furthermore, multiple regression analysis was conducted to determine how changes in each PC between before and three months after THA related to changes in the four LS evaluation items. PCA identified three principal components (PC1, PC2, PC3) that accounted for a cumulative contribution rate of 0.910 using 16 spatiotemporal gait parameters. When comparing before and three months after THA for all three PCs, significant differences were observed in each PC (p<0.001), with overall walking ability and stance phase being higher three months after THA than before THA, while the asymmetry of support time was lower three months after THA. The results of multiple regression analysis revealed that PC1, PC2, and PC3 were the most influential factors in total clinical decision limits stage. For each LS risk test, the factors related to the stand-up test were identified as PC1, PC2, and PC3, while the factors related to the two-step test were identified as PC1 and PC2. The factors related to the GLFS-25 were also identified as PC1 and PC2. The most important findings of this study indicate that the three PCs represent over 90% of the 16 spatiotemporal gait parameters, which are associated with total clinical decision limits stage and LS risk tests. The present results suggest that PC1 represents overall walking ability, PC2 represents the stance phase, and PC3 represents asymmetry of support time. Gait pattern characteristics, such as overall walking ability, stance phase, and asymmetry of support time, were clearly defined by these PCs. Regarding the relationship between PC and LS, all three PCs are related to total clinical decision limits stage. In addition, PC1 and PC2 related to all three LS risk tests, and PC3 related only to the stand-up test.

Drivers of wind and water erosion for river sediments in a typical coarse sandy area in the middle reaches of the Yellow River

Warmer temperatures and the combined effects of wind and water erosion leads to serious soil loss. Identifying the contribution of different drivers to wind and water compound erosion can improve soil erosion management in the watershed. Accordingly, we calculated the erosion energy based on energy theory and applied the mutation test and trend analysis to explore environmental drivers, runoff, and sediment changes for the Kuyehe River Basin. Rainfall erosion energy, wind erosion energy, air temperature, NDVI, and land cover were selected as potential drivers to quantify the contribution of sediment change using a partial least squares regression model. The results indicated that rainfall erosion energy decreased, wind erosion energy increased and then decreased, temperature increased, and NDVI increased during the period 1990–2020. The relationship between runoff and sediment transport in the basin shifted from more water and more sediment to more water and less sediment, and the timing of the mutation was different for runoff and sediment, with the runoff mutation occurring in 1997 and the sediment mutation occurring during 2003–2004. After sediment mutations, wind, NDVI, and land cover of forests showed higher importance for sediment transport changes, while precipitation and temperature were less important. In addition, the importance of cropland, shrub and grassland, and other land cover types varied considerably between sub-basins. Over 70 % of the contribution to sediment change was due to land cover change, while the cumulative contribution of forest and NDVI was about 30 %. The study identified the key drivers of sediment transport changes in the basin and provided valuable insights for future studies of wind and water compound erosion at the basin scale.

Psychometric characteristics of the Chinese version of the Pregnancy Exercise Attitudes Scale (C-PEAS)

BackgroundReasonable instruction and promotion of appropriate exercise are crucial to improving the exercise status of pregnant women and safeguarding the health of both mother and fetus. However, there is a lack of validated Pregnancy Exercise Attitude Scales with a complete evaluation system in China. This study aims to assess the validity and reliability of the Pregnancy Exercise Attitude Scale (C-PEAS) in Chinese to give medical professionals a reference for carrying out pregnancy care services and promoting the health of the mother and fetus.MethodsIn this study, the scale was translated, back-translated, and cross-culturally adapted using the Brislin translation model to form the C-PEAS. 528 pregnant women were conveniently selected for the questionnaire survey to evaluate the scale's reliability. The scale's content validity was assessed by the content validity index, while its structural validity was investigated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Cronbach's alpha coefficient, McDonald's omega coefficient, split-half reliability, and retest reliability were used to evaluate the scale's internal consistency.ResultsThe C-PEAS contains two dimensions with 37 entries. The EFA supports a two-factor structure with a cumulative variance contribution of 62.927%. The CFA model was well fitted (χ2/df = 1.597, RMSEA = 0.048, IFI = 0.955, TLI = 0.952, and CFI = 0.955). The C- PEAS' Cronbach's alpha coefficient was 0.973, and the range of Cronbach's alpha values for the dimensions was 0.976, 0.944. McDonald's omega coefficient was 0.971, the half-point reliability of the scale was 0.856, and the retest reliability was 0.966.ConclusionsThe Chinese version of C-PEAS has good psychometric properties. It can be used as an effective measurement tool to evaluate the attitude of pregnant women to exercise during pregnancy.

Reliability and validity test of the Chinese version of the spiritual care-giving scale in nursing undergraduates and its application

Objective: To evaluate the reliability and validity of the Chinese Version of the Spiritual Care-giving Scale (C-SCGS) in nursing undergraduates and its application. Methods: This was a retrospective study. A questionnaire survey was conducted among 262 senior nursing undergraduates from Chengde Medical University, China from May to June, 2023 through convenience sampling method. The C-SCGS and the general demographic data table were employed to investigate the subjects. Results: The C-SCGS retained 34 items, and four common factors were extracted by exploratory factor analysis, with a cumulative contribution rate of 65.15%. The I-CVI value of the scale was 0.88-1.0, and the S-CVI/Ave value was 0.94. The Cronbach’s α coefficient of the total scale was 0.957, that of each dimension ranged from 0.850 to 0.944, with a split-half coefficient of 0.887. Conclusion: The C-SCGS may be used to evaluate the spiritual cognition of Chinese nursing undergraduates by virtue of its good reliability and validity. doi: https://doi.org/10.12669/pjms.40.10.9021 How to cite this: Huang Y, Lv D, Wang T, Zhang H, Zhang L. Reliability and validity test of the Chinese version of the spiritual care-giving scale in nursing undergraduates and its application. Pak J Med Sci. 2024;40(10):2313-2318. doi: https://doi.org/10.12669/pjms.40.10.9021 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Phasic and periodic change of drought under greenhouse effect

Purpose Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes. Design/methodology/approach The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns. Findings The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%. Research limitations/implications The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution. Practical implications Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland. Originality/value The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

Nursing process performance measurement tool based on bloom’s revised taxonomy: A validity and reliability analysis

AimThis study aimed to develop a measurement tool that could evaluate educational approaches by integrating the cognitive dimensions required at each stage of the nursing process and strengthening the connection between education and clinical practice. BackgroundThe nursing process is a core component of nursing practice and supports nurses and nursing students in systematically performing the problem-solving process necessary for patient health management. DesignCross-sectional, methodological study. MethodsA nursing process performance measurement tool that could measure the cognitive dimensions required at each stage of the nursing process was developed based on Anderson’s and Bloom’s revised taxonomy. The data for this study were collected from July to August 2023 at four universities in South Korea. The reliability and validity of the measurement tool were evaluated through a survey conducted on 406 nursing students. Participants were third- and fourth-year nursing students with clinical practice experience, recruited through purposive sampling. ResultsThe developed tool was designed to systematically measure and evaluate each step of the nursing process. This tool consisted of 28 questions, each of which was divided into five assessment questions, six diagnosis questions, six planning questions, five implementation questions and six evaluation questions. Items were rated on a 5-point Likert scale, ranging from 1 (“not at all”) to 5 (“very much”). The measurement score ranged from 28 to 140 points, with higher scores indicating better nursing process performance. The cumulative variance contribution rate of the tool was 68.1 % and the Cronbach’s α value was 0.85 for all items. ConclusionsThis study provides a basis for evaluating educational approaches in nursing curricula by integrating the cognitive dimensions required at each stage of the nursing process. This approach can strengthen the connection between education and clinical practice and can be used not only as a tool to systematically evaluate the learning outcomes of nursing students but also as a standardized nursing process guide.

Reliability and validity of the Chinese version of the contraceptive knowledge assessment scale in college students

ObjectivesTo translate and revise the Contraceptive Knowledge Assessment (CKA) scale and apply it to Chinese college male/female students. After cross-cultural adjustment of the source scale, the reliability and validity of the Chinese version of the scale were tested.Study designThis study utilized a cross-sectional research design. Translation, cognitive interviews and a psychometric evaluation were carried out. A survey was then conducted among 388 college students in Shanghai to test the reliability and validity of the Chinese version of the CKA scale.ResultsThere were 22 items in the Chinese version. Factor analysis extracted 8 common factors, with a cumulative contribution rate of 58.923%, and 3 items were eliminated. The Cronbach’s α coefficient was 0.793, and the test-retest reliability Pearson correlation coefficient was 0.743.ConclusionThe Chinese version of the CKA scale has good reliability and validity and is suitable for assessing the level of contraceptive knowledge.

The Impact of Sample Quantity, Traceability Scale, and Shelf Life on the Determination of the Near-Infrared Origin Traceability of Mung Beans.

This study aims to address the gap in understanding of the impact of the sample quantity, traceability range, and shelf life on the accuracy of mung bean origin traceability models based on near-infrared spectroscopy. Mung beans from Baicheng City, Jilin Province, Dorbod Mongol Autonomous, Tailai County, Heilongjiang Province, and Sishui County, Shandong Province, China, were used. Through near-infrared spectral acquisition (12,000-4000 cm-1) and preprocessing (Standardization, Savitzky-Golay, Standard Normal Variate, and Multiplicative Scatter Correction) of the mung bean samples, the total cumulative variance contribution rate of the first three principal components was determined to be 98.16% by using principal component analysis, and the overall discriminatory correctness of its four origins combined with the K-nearest neighbor method was 98.67%. We further investigated how varying sample quantities, traceability ranges, and shelf lives influenced the discrimination accuracy. Our results indicated a 4% increase in the overall correct discrimination rate. Specifically, larger traceability ranges (Tailai-Sishui) improved the accuracy by over 2%, and multiple shelf lives (90-180-270-360 d) enhanced the accuracy by 7.85%. These findings underscore the critical role of sample quantity and diversity in traceability studies, suggesting that broader traceability ranges and comprehensive sample collections across different shelf lives can significantly improve the accuracy of origin discrimination models.

Symptom clusters and symptom network analysis during immunotherapy in lung cancer patients.

This study analyzes symptoms in lung cancer patients undergoing immunotherapy to identify core symptom clusters through network analysis and lay a foundation for effective symptom management programs. The sample comprised 240 lung cancer patients receiving immunotherapy. Participants were assessed using the Memorial Symptom Assessment Scale. Exploratory factor analysis was used to extract symptom clusters, and network analysis using JASP 0.17.3 was performed to explore the centrality indices and density of the symptom network. Five symptom clusters were identified, i.e., emotion-related, lung cancer-related, physical, skin, and neural symptom clusters, with a cumulative variance contribution rate of 55.819%. Network analysis revealed that sadness was the most intense symptom (rs = 2.189), dizziness was the most central symptom (rc = 1.388), and fatigue was the most significant bridging symptom (rb = 2.575). This study identified five symptom clusters and a symptom network among lung cancer patients during immunotherapy. The network analysis's centrality indices and network density results can assist healthcare professionals in devising more precise symptom management strategies.

Psychometric evaluation of the Chinese version of the Nursing Student Contributions to Clinical Settings scale and analysis of factors influencing nurses' perceptions of nursing students' contributions: a cross-sectional study

BackgroundMost medical organizations accept many nursing students each year who gain clinical practice skills under the supervision of clinical nurses. However, there are no assessment tools to measure the contributions nursing students make to the clinical setting during clinical practicum. This study aimed to translate the 'Nursing Student Contributions to Clinical Settings' scale into Chinese and test its reliability and validity from the perspective of Chinese clinical nurses. And to explore whether nurses' personal and professional characteristics are related to nurses' perception of nursing students' contributions to the clinical settings.MethodsThe original scale was translated into Chinese following the Brislin translation model. A convenience sample of 935 clinical nurses was selected from January to March 2024 for the survey. The content validity of the scale was assessed by expert consultation and content validity index. Exploratory factor analysis and confirmatory factor analysis were performed to assess the construct validity of the scale. The reliability of the scale was measured using internal consistency, split-half reliability, and test–retest reliability. The measurement quality of the scales was assessed according to the COnsensus-based Standards for the selection of health Measurement INstruments. One-way analysis of variance was used to identify variables related to students’ contributions.ResultsThe content validity index of the scale was 0.983. Exploratory factor analysis supported a one-factor structure, and the cumulative variance contribution was 71.177%. Confirmatory factor analysis showed that the model fit indicators were all within the acceptable range. The McDonald's Omega coefficient and Cronbach's alpha coefficient for the scale were 0.983. Nurses perceive that nursing students' contribution to the clinical settings is influenced by nurses' personal characteristics, professional characteristics, and the hospital environment.ConclusionThe Chinese version of the Nursing Student Contributions to Clinical Settings scale has good reliability and validity and can effectively and reliably measure the contributions of Chinese nursing students to clinical settings.

Analysis of pollution status and influencing factors of polybrominated diphenyl ethers in household dust in five cities in northern China

Objective: To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China. Methods: Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust. Results: The M (Q1, Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑12PBDEs in Luoyang and Shijiazhuang (P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [β (95%CI): 0.186 (0.013, 0.359)], infrequent home cooking [β (95%CI):-0.342 (-0.570, -0.114)], and increased residential PM10 concentration [β (95%CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [β (95%CI): 0.093 (0.013, 0.172)], house area less than 90 m2 [β (95%CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [β (95%CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑12PBDEs in household dust. Conclusion: The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.