Contribution To Variance Research Articles

Exploration of symptom cluster patterns and their trajectory in esophageal cancer surgery patients.

To investigate symptom burden and symptom cluster trajectories in patients undergoing surgery for esophageal cancer. A convenience sample of 210 patients who underwent thoracoscopic surgery for esophageal cancer was included from July to December 2023. The symptoms of the patients were evaluated at the following time points: preoperatively (T0), 1-3 days postoperatively (T1), 7 days postoperatively (T2), 1 month postoperatively (T3), and 3 months postoperatively (T4). This was done via the Chinese version of the MD Anderson Symptom Scale and the Supplementary Questionnaire for Perioperative Esophageal Cancer Symptoms. Exploratory factor analysis was used to identify symptom clusters, and latent class growth modeling was used to analyze the trajectories of each different symptom cluster. Exploratory factor analysis revealed the presence of four symptom clusters: mood-related symptom clusters (worst at T1, T2, and T4), gastrointestinal symptom clusters (worst at T0), fatigue-related symptom clusters (worst at T3), and surgery-related symptom clusters, with cumulative variance contribution rates of 64.34%, 62.29%, 68.23%, 70.29%, and 63.82%, respectively. The latent category growth model identified the existence of 2-3 distinct trajectories in each symptom cluster. This study identified 4 distinct symptom clusters in patients undergoing esophageal cancer surgery. The mood-related and gastrointestinal symptom clusters exhibited worsening and recurrence within 7 days post-surgery, necessitating particular attention. A subset of patients in the fatigue-related symptom cluster showed a tendency for continued exacerbation, emphasizing the need for long-term monitoring. Furthermore, symptom management strategies can be prioritized based on the severity of the symptom clusters.

Assessing validity and reliability of the Transition Shock Scale for Undergraduate Nursing Students (TSS, Chinese version) in associate degree nursing students

BackgroundThe Transition Shock Scale for Undergraduate Nursing Students assesses transition to undergraduate nursing students. The TSS is a tool used in various countries and has been translated into Chinese; however, associate degree nurses dominate China’s nursing workforce, it needs to be validated in associate degree nursing interns. This study aimed to analyze the TSS (Chinese version) validity and reliability in Chinese associate degree nursing interns.MethodThis methodological validity study investigated internal consistency and reliability. The critical ratio (CR) method and correlation analysis are used for item screening of the scale. Eight experts in nursing management and nursing education were invited to assess the scale’s content validity. Construct validity was assessed using Pearson’s correlation between domains, exploratory factor analysis, and Confirmatory Factor Analysis. This methodological validity study investigated internal consistency and reliability using Cronbach’s alpha and intraclass correlation coefficients (ICC). The level of significance was set at 5%.ResultsThis study included 800 associate degree nursing interns from 8 Hunan Province, China hospitals. Validity analysis showed positive and significant correlations between all TSS (Chinese version) domains, ranging from 0.344 to 0.772. The internal consistency and reliability of the total TSS (Chinese version) score were high (Cronbach’s alpha = 0.925; intraclass correlation coefficient = 0.908). The content validity assessment showed that the I-CVI ranged from 0.875 to 1.000, and the S-CVI was 0.951. Exploratory factor analysis was performed by orthogonal rotation of the data using principal component analysis and maximum variance, and three common factors with eigenroots greater than 1.0 were extracted, with a cumulative variance contribution of 61.095%. Furthermore, confirmatory factor analysis demonstrated the following values of goodness of fit: RMSEA = 0.062, CFI = 0.953, TLI = 0.939, SRMR = 0.0389, χ2/df = 4.064. Thus, the TSS (Chinese version) discriminant and concurrent validities were confirmed.ConclusionTSS (Chinese version) contains 6 dimensions and 18 items, which has good reliability and validity among associate degree nursing interns, and can be used as an evaluation tool for transition shock in associate degree nursing interns.

Development and Reliability and Validity Test of the Adolescent Global Citizenship Scale

Under the influence of globalization and informatization, the world is gradually becoming a community, and adolescents need corresponding literacy and competence as world citizens in the international community. Based on literature combing and in-depth interviews, this study determines the theoretical conclusions and initial entries of the adolescent global citizenship scale, and revises the entries through the Delphi Method. The final scale was formed through item analysis, factor analysis, reliability, and validity test. The adolescent global citizenship scale includes three-dimensions of global awareness, citizenship, and sustainable development perspective, with a total of 21 items. The exploratory factor analysis extracted three common factors, and the cumulative variance contribution rate was 54.86%; the results of the validation factor analysis showed that the model fit was good. The standardized coefficients of each item in each dimension of the scale were greater than 0.5, the combined reliability was 0.86, 0.89, 0.86, and the total Cronbach’s alpha coefficient of the scale was 0.87. Therefore, the reliability of the Adolescent Global Citizenship Scale is good, and it can be used in related research.

Genotype trait analysis to identify potential resistant types to root knot nematode in tomato (Solanum lycopersicum L.)

Six F1 hybrids were tested for nematode resistance along with their parents and commercial cultivars for two seasons and the pooled mean results were analysed to explore the genetic potential of traits linked to specific genotypes. Nine quantitative, four qualitative and six physiological parameters were analyzed to identify superior hybrids through statistical models viz., analysis of variance, GE biplot and Wards clustering. The hybrids Hisar Arun×HN2 (susceptible), Arka Abha×HN2 and LE 812×HN2 (resistant) were found to be superior for yield per plant under stressed conditions. Higher plant height was observed in IIHR 2868 (86.21cm), primary branch in Arka Abha×HN2 (5.68) and shorter root length in Hisar Lalith (16 cm). Resistant hybrids exhibited earlier flowering i.e., 25 days and less fruit number. The susceptible genotypes expressed lower fruit number (17-20 fruits) on the contrary resistant hybrids had more than 20 fruits. The yield ranged between 667 g in CLN2123A to 1189 g in Hisar Arun×HN2. Under stressed conditions, the resistant hybrids Arka Abha×HN2 and LE 812×HN2 produced yields of 1169 g and 1153 g, respectively. Genotype Trait Biplot revealed that the PC1 and PC2 had contributed 70 % to the total variance and positive contributions to parents and hybrids were capped. The hybrids LE 812×HN2 and Arka Abha×HN2 can be well utilized in root knot nematode infested fields. The contribution of parents and its hybrids, associated traits and their interrelationships provide new dimension for the breeders to select trait specific parents and hybrids for crop improvement programs.

Health literacy assessment and analysis of influencing factors in pregnant women with gestational diabetes mellitus in Southwest China.

The main objectives of our study are evaluating the health literacy level among women with gestational diabetes mellitus (GDM) in Southwest China and explore the influencing factors, using a multidimensional health literacy assessment scale (Chinese version of the HLS-14). Given that the HLS-14 has not been used in GDM previously, its reliability and validity testing was included as a secondary objective. It was a cross-sectional survey with 565 GDM pregnancies. The Maternal and child health information access questionnaire, Chinese version of the HLS-14, Perceived Social Support Scale (PSSS) and General Self-efficacy Scale (GSES) was used to collect health information access behaviors, health literacy, social support and self-efficacy levels, respectively. SPSS 21.0 was used for descriptive statistical, multiple stepwise linear regression analysis and exploratory factor analysis (EFA). Amos 26.0 was used for confirmatory factor analysis (CFA). The Chinese version of HLS-14 has good reliability and validity in GDM pregnancies. The Cronbach's α are 0.849, 0.866, 0.859, and 0.883, respectively. The exploratory factor analysis extracted three common factors with a cumulative variance contribution rate of 68.405%. The confirmatory factor analysis model fit was good (χ2/df = 2.595, RMSEA = 0.055, IFI = 0.970, TLI = 0.963, CFI = 0.970). The HL level in pregnancies with GDM was moderate with a mean score of 3.26 ± 0.41, of which 24.10% had limited HL, 41.87% had moderate HL, and 34.03% had adequate HL. Regression analysis showed that the women with higher family support (β = 0.298, p < 0.001), recording pregnancy management diary (β = 0.199, p < 0.001), higher the family income (β = 0.140, p < 0.001), lower pre-pregnancy BMI (β = -0.116, p = 0.004), longer time spent searching for health information (β = 0.111, p = 0.006), and searching for health information through a medical health information website (β = 0.093, p = 0.019) had higher HL levels. These variables explained 23.1% of the variance in HL. The Chinese version of the HLS-14 has good applicability in the GDM pregnancies. The HL level of them is moderate, needs to be improved. Healthcare professionals should focus on the GDM population with low family income and high pre-pregnancy BMI, fully mobilize their social support system, provide reliable access to information, encourage all GDM pregnancies to use pregnancy management diaries to record their self-management behaviors, and ensure the effectiveness of health education.

Development and Validation of the Nursing Information Security Questionnaire.

Ensuring the security of nursing information holds substantial importance to nursing outcomes and healthcare system management. The awareness of information security among nurses in China is generally inadequate, and there is a lack of standardized evaluation tools for nurse information security in nursing practice. The nursing sector necessitates the establishment of a robust culture surrounding information security. The aim of this study was to construct a self-reporting instrument for evaluating nursing information security. The research team utilized literature analysis and group discussions to draft the item pool. After two rounds of Delphi consultation by 15 experts and pilot testing, the initial questionnaire was formed. Item analysis was carried out on the questionnaire, and the validity and reliability of the instrument were statistically tested by computing the Keiser-Meier-Olkin and Bartlett's tests, an exploratory factor analysis (EFA), a confirmatory factor analysis (CFA), convergent and discriminative validity, descriptive statistics, Cronbach's α, and test-retest reliability. A total of 501 nurses participated in the study, supplemented by the inclusion of five experts who were invited to contribute to the assessment of content validity. Four factors were formed using EFA (n = 250), and the cumulative variance contribution rate was found to be 60.10%. The CFA (n = 251) showed that the model fit was good. The overall Cronbach's α coefficient of the questionnaire was 0.948, and the test-retest reliability was 0.837. Finally, the nursing information security questionnaire (NIS-Q) with 38 items and three dimensions of knowledge, attitude, and practice were formed. A promising assessment instrument for gauging the degree of nursing information security was introduced. Further, a foundational platform was established for implementing specific enhancement strategies aimed at advancing nursing information security.

A cultural adaptation and testing on the reliability and validity of the Chinese version of the Menopause Symptom Assessment Scale.

The aim of this study was to modify the Chinese version of the Menopause Symptom Assessment Scale (MSAS) and evaluate its validity and reliability. An expert panel from the gynecology and nursing domain determined items that should remain or be revised, and 30 participants were selected for the pilot study. A total of 255 women who met the criteria for inclusion were enrolled in the investigation. SPSS 25.0 and AMOS 25.0 were used to analyze data. The internal and external reliability of the scale was evaluated using Cronbach's α coefficient, split-half reliability, and test-retest reliability, respectively. Expert review, exploratory factor analysis, and confirmatory factor analysis were used to evaluate the scale's validity, which encompasses both its content validity and structural validity. The Chinese version of the MSAS contains 43 items with 5 dimensions, including sexual function, psychological status, interpersonal anxiety, autonomic balance, and other subjective symptoms. The correlation coefficient (r value) between individual items and the total scale ranged from 0.49 to 0.67 (P < 0.05); the Item-Content Validity Index range from 0.80 to 1.00, and Scale-Content Validity Index was 0.91; the Cronbach's α coefficient was 0.85, and the test-retest reliability was 0.93; exploratory factor analysis revealed a cumulative variance contribution of 76.98%; the fitting index of the scale structure model was good. The updated Chinese version of the MSAS presented good reliability and validity and could be applied in assessing menopausal symptoms in Chinese women.

Unsupervised Identification for 2-Additive Capacity by Principal Component Analysis and Kendall’s Correlation Coefficient in Multi-Criteria Decision-Making

With the Multi-Criteria Decision-Making (MCDM) problems becoming increasingly complex, traditional MCDM methods cannot effectively handle ambiguous, incomplete, or uncertain data. While several novel types of MCDM methods have been proposed to address this limitation, they fail to consider the potentially complex interactions among decision criteria. An effective capacity identification methodology is definitely needed to conquer this issue. In this paper, we develop a novel unsupervised method for identifying 2-additive capacities by means of Principal Component Analysis (PCA) and Kendall’s correlation coefficient. During the process, some significant results are achieved. Firstly, the Shapley values of decision criteria are derived by using the PCA, through a combination of the variance contribution rate of each Principal Component (PC) and its corresponding eigenvector. Secondly, Kendall’s correlation coefficient stemmed from the decision data created to help identify the Shapley interaction index for each pair of criteria by unsupervised learning. The optimization model equipped with a new form of monotonicity conditions is then established to further determine the optimal Shapley interaction index. With these two kinds of indices, a desired monotone 2-additive capacity is finally identified in an objective and efficient manner. Numerical experiments demonstrate that our proposal can adequately consider the importance of criteria and accurately identify the types of Shapley interaction indices between criteria, and is thus able to produce more convincing and logical results compared with other unsupervised identification methods.

Development of a growth mindset assessment scale for nursing students based on the growth mindset model: A mixed-method study.

The aim was to develop a growth mindset assessment scale based on the growth mindset model. Growth mindset is a critical factor in the development of nursing students, but there are limited tools available to measure growth mindset effectively among nursing students. A Delphi study and cross-sectional study. A questionnaire based on the growth mindset model as the theoretical framework was developed through a literature review, expert consultation and presurvey. From May to July 2024, 755 nursing students from five tertiary hospitals in Shandong Province were randomly recruited as participants and the reliability and validity of the questionnaire were tested. The growth mindset assessment scale for nursing students comprises 3 dimensions and 24 items. The content validity index (CVI) at the scale item level ranged from 0.833 to 1.00 and that at the scale level was 0.856. A total of 3 common factors were extracted from the analysis, with a cumulative variance contribution rate of 68.483 %. The Cronbach's alpha coefficient of the scale was 0.911 and those of the dimensions were 0.910, 0.933 and 0.938, respectively. With respect to the SEM, the following values were obtained: χ2/df = 2.046, RMSEA = 0.012, CFI = 0.961, NFI = 0.926, IFI = 0.961 and TLI = 0.955. The growth mindset assessment scale for nursing students has high reliability and validity. The preliminary evidence provided supports the reliability of the growth mindset assessment scale as a measure of growth mindset.

Global Sensitivity Analysis of Relative Permeability and Capillary Pressure in Unsteady-State Core-Flooding Experiment

Numerical simulation stands as a pivotal method within the petroleum industry, enabling the prediction of fluid flow in porous media. Its primary goal lies in analyzing behavior and forecasting oil production through fluid injection. However, the necessity for numerous simulations, each encompassing diverse multidimensional and compositional characteristics, presents a challenge. This leads to a significant accumulation of physical information, exacerbating the computational demands on the numerical model, particularly in terms of computational cost. To address this challenge, one potential solution is to determine the essential input parameters required for accurate oil production prediction. Global sensitivity analysis emerges as a powerful tool for this purpose, aiming to identify which input parameters exert the most significant influence on the numerical model's response, thus optimizing computation time. Unlike traditional approaches that focus on sensitivity around a single operating point, this study adopts a holistic perspective, assessing sensitivity across the entire sample space of the inputs. Specifically, this research investigates the impact of changes in parameters related to relative permeability and capillary pressure curves within a plug during unsteady-state core-flooding experiments. The key metrics under scrutiny include water saturation profiles, pressure differentials, and cumulative oil production. Sobol indices, a method for quantifying global sensitivity, are employed to assess the contribution of each input parameter's variance to the outputs' variance. The mathematical framework employed here is based on the multiphase (water/oil) Darcy equation, incorporating capillarity effects in one-dimensional longitudinal flow, incompressible flow assumptions, and constant injection flow, commonly known as the Black Oil model. The model is solved utilizing an implicit finite difference methodology with time step control, with relative permeability and capillary pressure parameterized by the LET model. The outcomes of this analysis provide valuable insights, notably in reducing the number of estimable parameters in inverse problems on a global scale. This reduction significantly diminishes computing costs, offering greater flexibility in constructing surrogate models for future simulations.

Development and validation of the joint function and health assessment scale for juvenile idiopathic arthritis

Objective: To develop, validate and initially apply a joint function and health assessment scale for juvenile idiopathic arthritis patients. Methods: The first draft of the juvenile idiopathic arthritis joint function and health assessment scale was developed through literature analysis, discussion by the research team, semi-structured interviews, Delphi expert correspondence. From March to June 2024, a total of 260 children with juvenile idiopathic arthritis or their parents were prospectively recruited from Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University by convenience sampling method for pre-investigation and formal investigation.The reliability and validity of the scale were tested by item analysis, reliability analysis, exploratory factor analysis, content validity and criterion validity analysis, and the responsiveness of the scale to clinical changes was evaluated by estimating the minimum clinically important difference, and finally the formal scale was formed. Results: The juvenile idiopathic arthritis joint function and health assessment scale included disease activity assessment, daily activity and function assessment, pain, fatigue and disease outcome assessment, with a total of 5 dimensions and 24 items, in which the functional assessment subscale included 4 secondary dimensions and 18 items. The Cronbach's α coefficient of the function assessment subscale was 0.88, the fold-half reliability was 0.86, and the test-retest reliability after 2-4 weeks was 0.84; the item-level content validity index was 0.80-1.00, and the scale-level content validity index was 0.93. Exploratory factor analysis extracted 4 common factors with a cumulative variance contribution of 70.0%. Preliminary application indicated the functional assessment subscale was moderately correlated with childhood health assessment questionnaire (r=0.70, P<0.05), the total scale was strongly correlated with juvenile arthritis disease activity score-27 (r=0.92, P<0.05), and moderately correlated with both active and limited joint count (r=0.77, 0.68, both P<0.05). Reactivity analysis suggested that the minimum clinically important difference between the two visits of 41 children with clinical improvement and 25 children with disease activity was 0.49 (0.44, 0.54) and 0.51 (0.43, 0.58). Conclusion: The juvenile idiopathic arthritis joint function and health assessment scale has good reliability and validity, and has certain responsiveness to clinical changes, is simple and operable, and can be used as a tool for assessing joint function in children with juvenile idiopathic arthritis.

Factor Prioritization in FEMA P-58 Loss Estimation

In recent decades, probabilistic earthquake risk estimation has evolved significantly, with the FEMA P-58 methodology emerging as the method of choice for practical seismic risk assessments of buildings. Few studies, however, have examined the level of contribution of the explicitly modeled sources of uncertainty to the estimated losses. This study quantifies those contributions for intensity-based assessments utilizing variance-based sensitivity analysis (VBSA) and examines how they are affected by a variety of parameters. Considered sources of uncertainty include the variability of engineering demand parameters (EDPs) for a given level of shaking, the uncertain component quantities, the uncertain capacities defined by the fragility curves, and the uncertainty in the damage consequences. Their contributions are examined through the lens of factor prioritization. Our findings highlight the significant role of the building replacement likelihood in altering the variance contributions, with a predominant contribution of its associated sources of uncertainty at high levels of shaking. They also reveal a consistently high contribution of peak floor accelerations (PFAs) and residual interstory drifts (RIDs) compared with other EDPs and demonstrate the implications of crudely defined component damage models. By revealing the contribution breakdown for a variety of cases, the study enables a more effective allocation of resources and offers a broader intuition on the inner workings of loss estimation.

The quality, uniqueness, and causality of NMR-based prediction models for low-density lipoprotein cholesterol subfractions in human blood plasma

Low-density lipoprotein (LDL) cholesterol (chol) subfractions are risk biomarkers for cardiovascular diseases (CVD). A reference analysis, ultracentrifugation (UC), is laborious and may be replaced with a rapid prediction using proton NMR spectra of human blood plasma. However, the quality and uniqueness of these prediction models of biologically related subfractions remains unknown. This study, using two independent cohorts (n = 277), investigates the inter-correlations between LDL cholesterol in the main fraction and five subfractions, as well as the independence of their NMR-based prediction models. The results reveal that the prediction models utilize both shared and unique spectral information from the NMR spectra to determine concentrations of LDL subfractions. Analysis of variance contributions for prediction and causality assessments demonstrate that the NMR spectra contain unique predictive information for the LDL1chol, LDL2chol, and LDL5chol subfractions. In contrast, the spectral signatures for LDL3chol and LDL4chol are either insufficient or confounded. Our findings indicate that these five CVD biomarkers represent two independent clusters, reflecting their biosynthetic pathways, and confirm the presence of causal relationships between certain LDL chol subfractions. This highlights the importance of employing caution when interpreting the concentrations of specific LDL subfractions as standalone biomarkers for CVD risk.

Quantitative Analysis of Amorphous Form in Indomethacin by Near Infrared Spectroscopy Combined with Partial Least Squares Regression Analysis.

Indomethacin (INDO) is a synthetic non-steroidal antipyretic, analgesic, and anti-inflammatory drug that commonly exists in both amorphous and crystalline states. Its amorphous state (A-INDO) is utilized by pharmaceutical companies as an active pharmaceutical ingredient (API) in the production of INDO drugs due to its higher apparent solubility and bioavailability. The crystal state also encompasses various crystal forms such as the α-crystal form (α-INDO) and γ-crystal form (γ-INDO), with the highly crystalline and insoluble γ-INDO being commercially available. A-INDO, existing in a thermodynamically high-energy state, is susceptible to several factors during the preparation, storage, and transportation of API leading to its conversion into γ-INDO, thus impacting the bioavailability and efficacy of INDO drugs. Therefore, quantitative analysis of the A-INDO/γ-INDO content in INDO API becomes essential for controlling the production quality of INDO. The primary objective of this study is to investigate the feasibility of NIR for the quantitative analysis of A-INDO in INDO API, and to further elucidate its quantitative analysis mechanism. The NIR spectral data were collected for A-INDO and γ-INDO binary mixture samples with different resolutions, and these spectra were then selected and reconstructed using the interval partial least square (iPLS) method. Different pretreatment methods were employed to enhance the reconstructed spectra by highlighting relevant eigen information while eliminating invalid information caused by environmental factors or physical characteristics of samples. The most suitable PLSR model for quantitative analysis of A-INDO within the range of 0.0000-100.0000% w/w% was established, screened, and validated. From various perspectives, including distribution of spectral effective information, impact of resolution on PLSR model performance, variance contribution/cumulative variance contribution of PLSR model principal components (PCs), PCI loadings, relationship between spectral scores, and A-INDO content, feasibility assessment was conducted for the quantitative analysis of A-INDO in INDO using NIR spectroscopy. Additionally, a detailed investigation on the quantitative analysis mechanism of the optimal PLSR model was undertaken including the correlation between the characteristic peaks of spectra and information regarding hydrogen groups or hydrogen bonds in A-INDO or γ-INDO molecules. This study aims to provide theoretical support for the quantitative analysis of A-INDO in INDO API as well as serve as a reliable reference method for API quantification and quality control in similar drugs.

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.

Validation of the Chinese Maudsley three-item visual analogue scale to measure depressive symptoms in a youth population.

Existing self-rated depression measurement tools possess a range of psychometric drawbacks, spanning a range of validity and reliability constructs. The gold standard self-rated depression scales contain several variable items that are often non-specific, require respondents to have a certain level of language understanding and limited scoring options resulting in low sensitivity. The Maudsley three-item visual analogue scale (M3VAS) was developed to address these challenges. This study aimed to translate the M3VAS into Chinese and test its reliability and validity. First, both M3VAS scales (assessing current severity and change in severity) were translated according to a standardised protocol to finalise the Chinese version. Reliability and validity were then examined among 550 young people with moderate to severe depression (patient health questionnaire-9 (PHQ-9) score ≥15) in a cross-sectional opportunistic questionnaire survey. The content validity of each item (six items, across both scales) ranged from 0.83 to 1.00. Exploratory factor analysis denoted a total of two common factors, with a variance contribution rate of 64.34%. The total score correlated positively with the PHQ-9 total score (r = 0.241, P < 0.01). The Chinese version of the M3VAS had good reliability and validity values, and the confirmatory factor model fit well. The psychometric properties of the Chinese version of the M3VAS suggest that this scale can feasibly evaluate depression among young people in China.

Utilizing BIC for the intelligent selection of functional data with principal components

Abstract Functional Principal Component Analysis (FPCA) is a technique for dimension reduction of functional data. Considering the impact of different data ownership, the paper innovatively proposes a weighted B-spline basis function and provides a continuous curve fitting function. Then, smoothing processing is carried out through the basis function expansion method and the maximum penalized likelihood function method. Subsequently, the process of selecting the number of principal components based on the BIC criterion is elaborated. Parameter estimation is realized through the newly proposed BIC-FPCA optimization algorithm. In the empirical analysis section, the paper uses student performance data randomly generated by Python to demonstrate the application of FPCA in data reconstruction. The results show that although the reconstructed data is smoother, there is still room for improvement in the selection of principal components. Finally, the paper summarizes the research findings, suggesting that the BIC criterion be combined with the cumulative variance contribution rate to improve the method of principal component selection, and the algorithm be optimized to reduce computational load. With these improvements, the application effect of FPCA in functional data analysis can be further enhanced.

Psychometric evaluation of the Chinese version of the nurse turnover intention scale: a translation and validation study

BackgroundGlobally, the issue of high nurse turnover rates is prevalent in China. The COVID-19 pandemic exacerbated the attrition rate of nurses. Turnover intention is the most reliable predictor of nurse turnover. However, there is currently a lack of proper evaluation tools in China. This study aimed to translate the Nurses Turnover Intention Scale (NTIS) into Chinese and examine the psychometric characteristics of the Chinese version of the NTIS among clinical nurses in China.MethodsApproximately 418 nurses were recruited from three tertiary general hospitals in Jiangxi, Guangdong, and Zhejiang provinces. This study used Brislin’s double-back translation, back-translation, and cross-cultural adaptation methods to translate the scale. Internal consistency, split-half reliability, and test-retest reliability were used to measure the reliability of the Chinese scale version. The validity of the Chinese scale version’s content was evaluated via the Delphi method. Exploratory and confirmatory factor analyses were carried out to evaluate the construct validity of the Chinese scale versions. In exploratory factor analysis, principal component analysis and maximum variance rotation method were used in this study. In the confirmatory factor analysis, Amos 24.0 software was used for analysis.ResultsThe NTIS in Chinese has ten elements: a Cronbach α coefficient of 0.864, a Cronbach α coefficient of 0.852∼0.903 for the three dimensions, and a split-half reliability and test-retest reliability of 0.878 and 0.960, respectively. This indicates that the Chinese version of the NTIS has good internal consistency and time stability. The scale-level content validity index (S-CVI) was 0.957, which indicated that the Chinese version of NTIS had good content validity. The total variance contribution rate was 79.055%, and three common factors were identified via exploratory factor analysis. The examined three-factor structure was confirmed by confirmatory factor analysis, which confirmed that all fit indices were appropriate.ConclusionsThe Chinese version of the NTIS was appropriate in terms of reliability and validity. This scale can be used to evaluate nurses’ turnover intention, and the outcomes can aid nurse management in designing training initiatives and implementing preventive measures to decrease nurse turnover.

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.

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.