Correlation Model Research Articles

Public Sector Disciplinary practices and implications for Organizational Performance: towards a Recalibrated Sustainable Service Performance model

This study examined the relationship between the nature of staff disciplinary system and sustainable organisational performance. Utilizing descriptive statistics, categorical data correlation models and ordinal logistic regression model as well as t-test statistic, data gathered from both primary and secondary sources categorized and analyzed. Accordingly, findings showed: that delays in releasing of promotion, late payment of salaries and salaries cuts, etc are some of the causes of staff indiscipline; politics/tribal bias in handling disciplinary actions contribute to staff indiscipline. Also, the remuneration policy/salary structure as contained in the conditions of service is far from being individually oriented did not allow for performance-based reward system (PBRs). Thus, the study recommends urgent reform of the university’s conditions of service to allow for Compensatory individual Performance Related Pay (CiPRP) and the payment of salaries and promotion arrears of senior public servants (SPSs) as at when due; amongst others.

Comprehensive phenotypic characterization of an allelic series of zebrafish models of NEB-related nemaline myopathy.

Nemaline myopathy (NM) is a rare congenital neuromuscular disorder characterized by muscle weakness and hypotonia, slow gross motor development, and decreased respiratory function. Mutations in at least twelve genes, all of each encode proteins that are either components of the muscle thin filament or regulate its length and stability, have been associated with NM. Mutations in Nebulin (NEB), a giant filamentous protein localized in the sarcomere, account for more than 50% of NM cases. At present, there remains a lack of understanding of whether NEB genotype influences nebulin function and NM-patient phenotypes. In addition, there is a lack of therapeutically tractable models that can enable drug discovery and address the current unmet treatment needs of patients. To begin to address these gaps, here we have characterized five new zebrafish models of NEB-related NM. These mutants recapitulate most aspects of NEB-based NM, showing drastically reduced survival, defective muscle structure, reduced contraction force, shorter thin filaments, presence of electron-dense structures in myofibers, and thickening of the Z-disks. This study represents the first extensive investigation of an allelic series of nebulin mutants, and thus provides an initial examination in pre-clinical models of potential genotype-phenotype correlations in human NEB patients. It also represents the first utilization of a set of comprehensive outcome measures in zebrafish, including correlation between molecular analyses, structural and biophysical investigations, and phenotypic outcomes. Therefore, it provides a rich source of data for future studies exploring the NM pathomechanisms, and an ideal springboard for therapy identification and development for NEB-related NM.

Exploring correlations between economic indicators with natural and societal factors based on linear regression model

Existing research on the determinants of a nations economic development has predominantly centered on individual factors, including energy, land resources, education, taxes, employment, and healthcare. Regrettably, there is a paucity of studies that holistically examine these factors collectively and assess their respective contributions to economic development. Therefore, the primary objective of this study is to investigate the interrelationships between economic indicators and various natural and societal factors. The article firstly uses the Pearsons correlation coefficient to filter out a portion of the higher degree of correlation from factors that may have an impact on the countrys economic development for further analysis. For the selected factors, using two linear regression models: Ordinary Least Square (OLS) method for preliminary modeling for the extent of affects between each factors and economy; and Fully Modified Ordinary Least Squares (FMOLS) method, as an optimization model, further eliminating the less influential variables. After obtaining the final impact model of the linear correlation, the data is screened based on the variables within the model. A portion of the selected data is used as a training set for training the model and the remaining data is used as a test set for testing the performance. The results of the study show that factors including land area, army size, CO2 emissions, population, minimum wage, would have varying degrees of integrated impact on the economic development of the country.

EXPLORING THE IMPACT OF PIM 3 SCORE ON CLINICAL DECISION-MAKING: A SINGLE-CENTER STUDY

Objective: In the dynamic landscape of healthcare, the quest for precision in clinical decision-making is pivotal. The Pediatric Index of Mortality 3 (PIM 3) score has emerged as a crucial metric in predicting mortality risk among critically ill children, shaping medical choices in pediatric intensive care units.
 Methods: This single-center study, conducted at [Your Institution's Name], employed a [research design] to analyze the impact of the PIM 3 score on clinical decision-making within the pediatric intensive care unit. The study included [number] critically ill pediatric patients aged 1 mo to 18 y, with data extracted from electronic health records. Statistical analyses, including correlation and regression models, were applied to explore relationships and identify factors influencing clinical decision-making.
 Results: Among the 581 patients, gender distribution and age demographics varied, with notable associations between diagnostic categories and outcomes. Survivors exhibited lower PIM 3 scores compared to nonsurvivors. Probability scores related to outcomes revealed distinct patterns, emphasizing the predictive utility of the PIM 3 score.
 Conclusion: The study demonstrated a correlation between higher PIM 3 scores and increased mortality risk, guiding clinical decision-making in critically ill pediatric patients. Bridging theory and practice, the findings provide valuable insights for enhancing bedside decision-making and improving the quality of care. Acknowledging contextual factors is crucial for a comprehensive understanding of decision-making processes.

Social competence in autism: A structural equation modeling approach.

Autistic individuals present with difficulties in social competence (e.g., navigating social interactions and fostering relationships). Clinical interventions widely target social cognition and social behavior, but there is inconsistent understanding of the underlying components of social competence. The present study used structural equation modeling to examine social cognition and social behavior and explore the relationship between these latent constructs. Autistic youth (ages 10-17; n = 219) and their caregivers participated in this study. Constructs of social cognition and social behavior were captured using caregiver-report and self-report rating scales, as well as observational measures and direct clinical assessments (e.g., NEPSY-II). Measurement models of social cognition and social behavior demonstrated adequate to good fit. Correlational models demonstrated adequate to poor fit, indicating latent constructs of social cognition and social behavior are not closely related in autistic youth. Exploratory examination of a subsample of male youth (n = 157) evidenced improved model fit of social behavior, specifically. Findings tease apart social cognition and social behavior as cohesive and separable constructs; results do not support a structural relationship between social cognition and social behavior. Noted treatment implications include consideration of how targeting social cognition and social behavior together or separately may support autistic youth's progress toward reaching their identified therapeutic goals and supporting their self-directed social development.

Structural modeling of Chinese students’ academic achievement identity and basic psychological needs: do academic self-efficacy, and mindfulness play a mediating role?

BackgroundMindfulness and academic self-efficacy were proposed as mediating variables, with successful academic identity as an exogenous variable. The backdrop for this research centers on the significance of psychological factors in shaping academic identity among first-grade high school students.ObjectivesThe primary aim of the research was to investigate the relationship between fundamental psychological needs, mindfulness, academic self-efficacy, and successful academic identity. Specifically, the study explored the direct and indirect impacts of basic psychological needs on successful academic identity mediated by mindfulness and academic self-efficacy.MethodThe research employed a descriptive method, utilizing correlational studies and structural equation modeling. A sample of 355 undergraduate students at Henan Judicial Police Vocational College, Henan, China, was randomly selected through multistage cluster sampling. Data were collected using established scales, including the Basic Psychological Needs Scale, Baer Mindfulness Scale, Jenkins and Morgan Academic Self-Efficacy Scale, and Vas and Isakson Successful Academic Identity Scale. The data analysis was conducted using AMOS 22 software.FindingsThe research findings revealed that fundamental psychological needs directly and indirectly significantly impact successful academic identity. Mindfulness played a mediating role in this relationship. However, academic self-efficacy did not considerably mediate the influence of fundamental psychological needs on successful academic identity (p > 0.05). These results highlight the complex dynamics between psychological needs, mindfulness, academic self-efficacy, and successful academic identity among high school students in the specified academic year.ConclusionsThe findings suggest targeted interventions, such as workshops for families and teachers to address basic needs and psychologist and school counselor interventions to increase mindfulness. Additionally, organizing educational classes is imperative for fostering a supportive environment conducive to successful academic identity among undergraduate students.

The relationship between fear of old age, loneliness and death anxiety in adults.

The increase in the number of elderly people in the world, individuals' perspectives on older adults, and false beliefs and ideas about old age negatively affect adults in terms of ageing. This study was conducted to determine the relationship between fear of old age, loneliness and death anxiety in adults. This study, which was designed in a correlational cross-sectional descriptive model, was conducted with 1074 adult individuals living in one province in eastern Turkey. Data were collected using Personal Information Form, Fear of Old Age Scale, UCLA Loneliness Scale and Turkish Death Anxiety Scale. Data were analyzed using SPSS 25.0, AMOS 24.0, G*Power 3.1 statistical package programs. In our study, it was determined that the model created in line with the hypotheses was compatible and the model fit indices were within the desired limits as χ2 /df = 4.737, root mean square error of approximation = 0.05, comparative fit index = 0.93, goodness-of-fit index = 0.92, adjusted goodness-of-fit index = 0.90, IFI = 0.93. There is a significant relationship between loneliness and death anxiety (P < 0.05). There is a significant relationship between loneliness and fear of old age (P < 0.05). There is a significant relationship between death anxiety and fear of old age (P < 0.05). It was determined that death anxiety has a mediating role in the effect of loneliness on fear of old age (95% confidence interval: 0.112-0.226; P < 0.05). As the level of loneliness increases, the level of death anxiety and fear of old age increases. Fear of old age also increases in the mediating role of death anxiety. It is recommended to conduct intervention studies to reduce fear of old age. Longitudinal study on fear of old age is recommended.

Unveiling Sri Lanka's brain drain and labour market pressure: A study of macroeconomic factors on migration.

The purpose of this study is to explore the impact of GDP per capita income (GDPPCI), unemployment, higher education (HE), and economic growth (EG) on migration in Sri Lanka. Numerous global and local studies have explored the influence of macroeconomic and socioeconomic factors on migration. In the Sri Lankan context, fewer studies have probed the impact of GDPPCI, unemployment, HE, and EG on migration, particularly concerning brain drain and domestic labour market pressure. An applied research methodology was adopted, utilising annual data from 1986 to 2022. The statistical data were sourced from reports by the Sri Lanka Bureau of Foreign Employment (SLBFE), the Central Bank of Sri Lanka (CBSL), Labor Force Survey Data from the Department of Census and Statistics (LFSDCS), and University Grants Commissions (UGC). This study utilised the Vector Error Correlation model (VECM), Vector Auto-regression (VAR), and Granger Causality test through STATA. The empirical findings of the VAR model highlighted that GDPPCI and EG negatively impact migration, whereas unemployment and HE positively affect migration. The study's implications demonstrated that GDPPCI, unemployment, HE, and EG were the primary factors influencing the country's migration decisions. These findings will hopefully inform and guide the Sri Lankan government and policymakers for more effective decision-making.

The effect of slow wave sleep deprivation on mood in adolescents with depressive symptoms: A pilot study

BackgroundThere is an urgent need for safe, rapid-acting treatment strategies for adolescent depression. In depressed adults, slow wave sleep deprivation (SWSD) improved next-day mood without disrupting sleep duration, but SWSD has not been tested in adolescents. In a pilot study, the aim was to assess the effect of SWSD on sleep physiology and mood outcomes (depression, rumination, anhedonia) among adolescents with depressive symptoms. MethodsSixteen adolescents (17.44 ± 1.46 yr, 12 female) completed three nights of polysomnographic sleep recording: Baseline, SWSD, and Recovery nights. Acoustic stimulation (tones of random pitch, duration, and volume) suppressed slow wave sleep (SWS) in real-time during SWSD. After each night, depression, rumination, and anhedonia severity were assessed. ResultsSWSD successfully suppressed SWS, increased N2, and had minimal impact on Rapid Eye Movement (REM), nocturnal awakenings, and total sleep time. While SWSD did not improve depression or anhedonia severity overall, lower baseline non-REM alpha activity and greater SWS rebound during recovery sleep correlated with SWSD-related reduction in clinician-rated depression severity. Next-day rumination severity decreased after SWSD, with sustained improvements following recovery sleep. However, rumination improvement was not associated with SWS suppression, but rather reduction in total sleep time and REM in exploratory correlation models. LimitationsSmall sample size and large proportion of females. ConclusionSWSD did not improve depression in adolescents overall but a subset with low non-REM alpha activity and intact homeostatic sleep regulation may benefit from this approach. Findings from this pilot study also suggest that partial sleep deprivation may be a beneficial therapeutic strategy for rumination in adolescents.

A patient centered assessment of the 2016 ACR-EULAR Myositis Response Criteria: evaluating the meaningfulness of response.

The ACR-EULAR Myositis Response Criteria (Total Improvement Score [TIS]) is a composite measure calculated using changes in myositis core set measures. It is unclear if achieving improvement per TIS reflects improvement in any symptoms of myositis patients. In this study, we examined the association between achieving TIS improvement and patient-centered outcome measures (PCOMs). Adults with myositis were enrolled in a prospective study with baseline and 6-month visits. Six core set measures were collected at each visit along with the following PCOMs: Fatigue (visual analogue scale [VAS] and short form 36 [SF36]), pain (VAS, SF36), health-related quality of life (SF-36), physical function (PROMIS-physical function, SF36, sit-to-stand, timed up-and-go, and six-min walk) and physical activity (actigraphy). Mann-Whitney U was used to compare PCOMs between improvement groups. Spearman correlation and regression models were used for correlation and association between TIS and PCOMs, respectively. Of 50 patients (six polymyositis, 24 dermatomyositis, 9 necrotizing myopathy, 11 anti-synthetase syndrome) enrolled (mean age: 52, 60% female), 21 patients satisfied the TIS improvement criteria at 6-months. PCOMs including fatigue, pain, quality of life, physical activity and physical function demonstrated significantly greater improvement in patients who had minimal TIS improvement compared with those with no improvement. Greater PCOM improvements were seen with moderate-major TIS improvement. TIS correlated moderately-strongly with most PCOMs. Achieving improvement criteria was accompanied by significant clinical improvements in fatigue, pain, health-related quality of life, physical function, and physical activity. These results support the use of TIS as a clinically meaningful metric of improvement.

Multiple choice as formative assessment in dental education.

The effectiveness of multiple-choice questions (MCQs) in dental education is pivotal to student performance and knowledge advancement. However, their optimal implementation requires exploration to enhance the benefits. An educational tool incorporating MCQs was administered from the 5th to the 10th semester in a dental curriculum. The students filled out a questionnaire after the MCQ, which was linked to the learning management system. Four cohorts of four semesters generated 2300 data points analysed by Spearmen correlation and mixed model regression analysis. Demonstrated a significant correlation between early exam preparation and improved student performance. Independent study hours and lecture attendance emerged as significant predictors, accounting for approximately 10.27% of the variance in student performance on MCQs. While the number of MCQs taken showed an inverse relationship with study hours, the perceived clarity of these questions positively correlated with academic achievement. MCQs have proven effective in enhancing student learning and knowledge within the discipline. Our analysis underscores the important role of independent study and consistent lecture attendance in positively influencing MCQ scores. The study provides valuable insights into using MCQs as a practical tool for dental student learning. Moreover, the clarity of assessment tools, such as MCQs, remains pivotal in influencing student outcomes. This study underscores the multifaceted nature of learning experiences in dental education and the importance of bridging the gap between student expectations and actual performance.

Comprehensive analysis of Chinese hamster ovary cell viability loss in mini-hydrocyclones

Mini-hydrocyclones are gaining popularity as effective tools for cell retention in perfusion cultivation. As the most widely used mammalian cell for cultivation, Chinese hamster ovary (CHO) cells experience a decline in viability after passing through mini-hydrocyclones. The reasons behind the cell viability loss within mini-hydrocyclones are not understood. This study aims to comprehensively examine the cell viability loss in relation to shear stress and pressure drop through a combination of experimental analysis and numerical simulations. The results show that a larger hydrocyclone conical factor or spigot diameter decreases pressure drop and shear stress, resulting in a lower cell viability loss. To evaluate the dependence of cell viability loss on shear stress and pressure drop, a correlation model is developed and a sensitivity analysis is performed. The results show that mean shear stress has the greatest impact on cell viability loss, followed by pressure drop and maximum shear stress.

Evaluation of hard petroleum asphalt's low-temperature performance and index optimisation based on the grey correlation model

Hard petroleum asphalt (HPA) has good application prospects because of its simple manufacturing process and excellent performance. However, according to previous studies, the performance of HPA at low temperatures cannot be well characterised by commonly used methods. The use of HPA in cold climates is severely constrained. In order to comprehensively evaluate the low-temperature performance of the material, this study used four different types of HPA as the research object, and used the bending beam rheological test ( BBR) to determine the basic rheological properties of the material. On this basis, after fitting and analysing the low-temperature creep compliance curve using the Burgers viscoelastic model, the asphalt was assigned a low-temperature viscoelastic assessment index. The glass transition temperature and sensitivity of HPA were investigated by differential scanning calorimetry (DSC). At the same time, the HPA assessment index at low temperatures was determined systematically by using grey correlation theory.

Don't judge a book or health app by its cover: User ratings and downloads are not linked to quality.

To analyse the relationship between health app quality with user ratings and the number of downloads of corresponding health apps. Utilising a dataset of 881 Android-based health apps, assessed via the 300-point objective Organisation for the Review of Care and Health Applications (ORCHA) assessment tool, we explored whether subjective user-level indicators of quality (user ratings and downloads) correlate with objective quality scores in the domains of user experience, data privacy and professional/clinical assurance. For this purpose, we applied spearman correlation and multiple linear regression models. For user experience, professional/clinical assurance and data privacy scores, all models had very low adjusted R squared values (< .02). Suggesting that there is no meaningful link between subjective user ratings or the number of health app downloads and objective quality measures. Spearman correlations suggested that prior downloads only had a very weak positive correlation with user experience scores (Spearman = .084, p = .012) and data privacy scores (Spearman = .088, p = .009). There was a very weak negative correlation between downloads and professional/clinical assurance score (Spearman = -.081, p = .016). Additionally, user ratings demonstrated a very weak correlation with no statistically significant correlations observed between user ratings and the scores (all p > 0.05). For ORCHA scores multiple linear regression had adjusted R-squared = -.002. This study highlights that widely available proxies which users may perceive to signify the quality of health apps, namely user ratings and downloads, are inaccurate predictors for estimating quality. This indicates the need for wider use of quality assurance methodologies which can accurately determine the quality, safety, and compliance of health apps. Findings suggest more should be done to enable users to recognise high-quality health apps, including digital health literacy training and the provision of nationally endorsed "libraries".

Quantitative evaluation of disc degeneration using dual-energy CT: advantages of R-VH, D-VH values and the IVNCa + CT model.

To evaluate the correlation between dual-energy CT (DECT) virtual calcium free (VNCA), CT attenuation, the ratio and difference of VNCA to CT attenuation, and Pfirrmann grading of lumbar disc degeneration. A retrospective analysis on 135 intervertebral discs from 30 patients who underwent DECT and MR. Discs was graded using the Pfirrmann system. ROIs on the sagittal plane assessed HU value, VNCA value, Rho value, Z value, R-VH value, and D-VH value. Correlation, grade differences, and multivariate regression models were assessed. Diagnostic performance and cut-off values were determined using AUC. VNCA (r = 0.589, P < 0.001), R-VH (r = 0.622, P < 0.001), and D-VH (r = 0.613, P < 0.001) moderately correlated with Pfirrmann grading. HU (r = 0.388, P < 0.001), Rho (r = 0.142, P = 0.102), and Z (r = -0.125, P = 0.153) showed a weak correlation. R-VH, D-VH, and VNCA had significantly higher correlation than HU. Statistically significant differences were observed in P values of VNCA, HU, R-VH, and D-VH in relative groups (P < 0.05), but not in Rho and Z values (P > 0.05). R-VH and D-VH had significant differences between Pfirrmann grades 1 and 2, and grades 2 and 3 (early stage) (P < 0.05). AUC readings of R-VH and D-VH (≥2, ≥3, ≥4) were higher. The multivariate model IVNCa + CT had the highest AUC. The new quantitative indices R-VH value and D-VH value of DECT have advantages over VNCA value and HU value in evaluating early-stage disc degeneration (≥2 grades, ≥3 grades). The multivariate model IVNCa + CT has the best AUC values for evaluating disc degeneration at all stages.

Research on the coupling mechanism and influencing factors of digital economy and green technology innovation in Chinese urban agglomerations

This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent.

User Acceptance and Adoption of the Digital Management Information System by focusing on E-Learning System in Institute of Distance Education (IDE) at the University of Zambia (UNZA)

Digital transformation is conquering the world with a tremendous speed in every aspect of society and education is one important area. This fast advancement in technology is occurring in both the developed and developing societies. As a result, we see e-learning platforms extensively used and make the learning process continue in universities and education institutions almost uninterrupted, despite the restrictions of social interaction by governments during the covid-19 pandemic. The purpose of the study was to evaluate the User Acceptance and Adoption of the Digital Management Information System by focusing on E-Learning System in IDE at UNZA. The study was conducted on the students and lecturers who used the System at the IDE at UNZA. A google questionnaire was sent to the students in their groups and 271 participants answered the questionnaire successfully and this became the sample for the study. Data was analyzed using SPSS where the correlation and multi-variant Regression Analysis Model were used to help understand the data. The study found that the Social Influence (β= .657), was mostly significant in influencing User Acceptance Adoption of the System, seconded by Performance Expectancy ( and Effort Expectancy’s (. The study concludes that all the constructs are positively related to the acceptance and adoption of the E-Learning System. However, Social Influence is the most influenced factor User Acceptance Adoption of the E-Learning System at the University of Zambia when compared to the other constructs. This conclusion has added to the arguments which have found other factors like PE and EE to be factors affecting BI for the adoption of IT systems in other countries. The study recommended that the University of Zambia should link E- Learning system with the online library to assist student get the recommended resources. This can be done by adding a fee to facilitate which will help cater for the running costs while students and lecturers maximize the use of the system.

The Influence Factors of Economic Development of Tourism Industry

Objectives: This paper aims to conduct research on the factors that impact the advancement of the tourism economy in order to adapt to the rapidly changing demands of the tourism market. Methods: A case study was performed using a gray correlation model to analyze the tourism industry in Henan Province. Findings: Among the first-level indicators, tourism economic support had the highest correlation with tourism economic development, followed by tourism physical base, tourism transportation influence, tourism human resources, and tourism information service. Then, relevant suggestions were given according to the analysis results. Novelty:The novelty of this article lies in utilizing the gray correlation model to examine the factors that influence the tourism economy and analyzing the gray system with incomplete information. Doi: 10.28991/HIJ-2024-05-01-03 Full Text: PDF

Investigating the serve life of common earthed materials based on evaluations of the soil corrosion in offshore areas of East China

The serve life of common earthed materials in power systems is essentially affected by the soil environment, especially the potential corrosion problem of sodium chloride contaminated soil in offshore areas. This study measured the corrosion rates of three common earthed metal materials, Q235 carbon steel, pure Al, and H62 brass, in typical chloride saline soil using accelerated and field corrosion tests. The acceleration ratio and kinetic correlation coefficient under different acceleration conditions were calculated, and the laboratory and field corrosion time correlation models of common earthed metal materials were obtained. The results show a good correlation between soil accelerated and field corrosion tests. Under the same temperature and salinity, the correlation degree of Q235 carbon steel is larger when the water content is 30%. In comparison, the correlation degree of pure Al and H62 brass is larger when the water content is 20%. The laboratory and field corrosion time correlation models of Q235 carbon steel, pure Al, and H62 brass in chloride type saline soil environment are T1=18.32T0, T1=95.56T0, T1=15.78T0, which can effectively evaluate the serve life of common earthed metal materials in typical chloride type saline soil in the offshore area of East China.

Characterization of the Ionospheric Vertical Error Correlation Lengths Based on Global Ionosonde Observations

AbstractData assimilation is one of the most important approaches to monitoring the variations of ionospheric electron densities. The construction of the background error covariance matrix is an important component of ionospheric data assimilations. To construct the background error covariance matrix, the information about the spatial ionospheric correlations is required. We present a statistical analysis on the ionospheric vertical error correlation length (VCL) based on a global network of ionosondes and the Neustrelitz Electron Density Model. We show that the locally derived VCL is well‐defined and the VCL does not show a considerable dependency on the geographical seasons while local time dependencies of the VCL are shown to be present. A novel VCL model is also established based on the ionospheric scale heights. We show that the ionospheric VCL can be characterized by the variance ratio between the ionosphere model and ionospheric measurements. The altitudinal variations of VCLs are controlled by the interactions between the inherent VCLs of the ionosphere model and the measurements. Two experiments are conducted at two different latitudes based on the proposed model. The results show that the proposed model is stable and well‐correlated with the observed VCLs, which implies a potential to be generalized for a global correlation model. The proposed model can be used in the temporal evolution of error covariance matrices in the ionospheric 4D‐Variational (4D‐Var) assimilations, which may overcome the main drawbacks of the static error covariance specifications in the ionospheric 4D‐Var assimilations.