Statistical Software Research Articles

Extending dramaturgical theory to evaluate revisit intention of international tourism: A scenario of COVID-19 tourism recovery

Since 2019, major travel destinations worldwide have issued travel-related restrictions against COVID-19. There is much research on tourism, but few studies have been conducted to explain the relevance of revisiting intention from the perspective of the epidemic or the dramaturgical theory. The purpose of the research is to explore the impact of customer experience on revisit intention during the period of COVID-19 slowdown by using dramaturgical theory. This study used a survey methodology, and the questionnaire was distributed on an online questionnaire platform. The URL of the questionnaire was published on social media (such as Facebook and LINE) to collect data from 389 samples of people who have foreign travel experience. The data was analyzed by employing partial least square structural equation model (PLS-SEM) methodology with the help of the statistical software “SmartPLS”. The research findings are as follows: 1) setting, audience, and performance are the three important elements of dramaturgical theory that impact the experience quality; 2) customer experience of tourists has a significant impact on the experience quality; 3) experience quality has a significant positive impact on the experience value and relationship quality; 4) experience value and relationship quality are important predictors of revisit intention. This study provides academic implications regarding the use of dramaturgical theory in relation to customer experience and relationship constructs in the context of tourism. Furthermore, it also provides some practical implications to tourism practitioners and managers, which would assist tourism industries in developing successful marketing strategies for the possible recovery of COVID-19.

Assessment of knowledge, attitude, and practice of blood donation among paramedical students of a medical college in Chennai, Tamil Nadu

Abstract: BACKGROUND: Blood donation is an essential global need far outweighs the available supply, rendering it a scarce and valuable resource. Within India, blood transfusion services hold significant importance and constitute a crucial aspect of the national health-care framework. Voluntary Non-Remunerated Blood Donation (VNRBD) is deemed the safest among the various ways of donating blood. The student population of educational institutions across the country, particularly those who are young and physically fit, represents one of the most promising sources of blood donations. The aim of the study was to evaluate the knowledge, attitudes, and donation practices of medical college students and motivate them to embrace voluntary blood donation as a regular habit. MATERIAL AND METHODS: The Department of Allied Health Science at Dr MGR Educational and Research Institute in Chennai, Tamil Nadu, India, conducted a questionnaire survey from March 2023 to October 2023. Two thousand and two hundred forty students were invited to participate, with 2331 ultimately willing to partake. The gathered data underwent analysis using the SPSS Statistics software, version 20, with a significance level fixed at a P = 5%. RESULTS: The study included 2331 participants, comprising 840 males (36%) and 1491 females (64%). The age range of the participants was between 17 and 25 years, with a mean age of 18.9 ± 1.3 years. Out of 2331 participants, the majority (66.7%) showed sufficient knowledge with 9 or more correct answers, while the rest (33.2%) showed below-average knowledge. CONCLUSION: The Tamil Nadu Health Professions Colleges possess the potential to make a noteworthy impact on the promotion of blood donation. According to a recent survey, students express a keen interest in donating blood if a camp is organized on the campus. By organizing awareness campaigns and conducting informative sessions, the colleges can inspire and motivate more students to donate blood, thereby playing a vital role in saving lives.

Learning about treatment effects in a new target population under transportability assumptions for relative effect measures.

Investigators often believe that relative effect measures conditional on covariates, such as risk ratios and mean ratios, are "transportable" across populations. Here, we examine the identification of causal effects in a target population using an assumption that conditional relative effect measures are transportable from a trial to the target population. We show that transportability for relative effect measures is largely incompatible with transportability for difference effect measures, unless the treatment has no effect on average or one is willing to make even stronger transportability assumptions that imply the transportability of both relative and difference effect measures. We then describe how marginal (population-averaged) causal estimands in a target population can be identified under the assumption of transportability of relative effect measures, when we are interested in the effectiveness of a new experimental treatment in a target population where the only treatment in use is the control treatment evaluated in the trial. We extend these results to consider cases where the control treatment evaluated in the trial is only one of the treatments in use in the target population, under an additional partial exchangeability assumption in the target population (i.e., an assumption of no unmeasured confounding in the target population with respect to potential outcomes under the control treatment in the trial). We also develop identification results that allow for the covariates needed for transportability of relative effect measures to be only a small subset of the covariates needed to control confounding in the target population. Last, we propose estimators that can be easily implemented in standard statistical software and illustrate their use using data from a comprehensive cohort study of stable ischemic heart disease.

Overview on Spectral Analysis Techniques for Gamma Ray Spectrometry

Gamma-ray spectrometry (GRS) is an exploration technology that distinguishes itself from other non-contact sensing technologies because it provides information from 30 to 50 cm below the ground. This technology has evolved through three significant turning points in mapping output. The first turning point, in the 1960s-1970s, was the transition from U concentration maps to weathered zoning maps utilizing K or eTh. The second turning point, occurring from the 1980s to 1990s, was marked by the application of radionuclide mapping to assess radioactive contamination. A third turning point, in the early 2000s, was the development of soil maps for precision agriculture, supported by the free statistics software R. This paper reviews advances in gamma-ray spectrometry spectral analysis since 2000. Traditionally, the gamma-ray spectrum is depicted as a two-dimensional graph with energy on the horizontal axis and counts on the vertical axis. The NASVD and MNF methods, developed around 2000, necessitate a reevaluation of this concept. By conducting principal component analysis of the gamma-ray spectrum in hyperspace, these techniques have unveiled new spectra, such as ground and sky spectra, and have facilitated the removal of noise components from the gamma-ray spectrum. Naturally occurring gamma-ray spectra typically exhibit energies ranging from 0.04 to 3 MeV. Observations from fusion reactors measure energies up to 20 MeV for diagnostics of nuclear plasma. These spectra may yield valuable insights when applied to innovative statistical analysis techniques. A comprehensive spectral analysis method developed in the early 2000s has demonstrated the potential to extract a variety of information beyond window nuclides, previously unexplored. The regression coefficient plots from the PLSR regression model have revealed novel spectral images. This model is set to influence future research on GRS by expanding the number of objectives and covariates. The innovative calibration method for full-spectrum analysis, which assesses different concentration areas, has proven that calibration is achievable even in the absence of a calibration pad. It is expected to become a formidable approach for spectrum analysis in the upcoming period.

Enhancing percutaneous kyphoplasty efficacy in elderly osteoporotic fractures through optimal cement filling ratio

ObjectiveTo explore the appropriate bone cement filling ratio in percutaneous kyphoplasty (PKP) for the treatment of osteoporotic vertebral compression fractures (OVCF).MethodsClinical and radiological data from 150 OVCF patients treated with PKP were retrospectively analyzed. Patients were categorized into three groups based on bone cement filling ratio: low (<0.4), medium (0.4-0.6), and high (>0.6) filling ratio groups. The clinical characteristics (age, gender, BMI, etc.) and related study data (bone cement leakage and its location, pre/post-operative Visual Analogue Scale (VAS), pre/post-operative Oswestry Disability Index (ODI), vertebral height restoration, kyphotic Cobb angle, etc.) among the three groups were compared using statistical software to compare to identify the most appropriate cement filling ratio.ResultsThe 0.4-0.6 group presented a lower cement leakage rate compared to the >0.6 group, and there were no significant differences in pre-operative VAS, post-operative day 2 VAS, post-operative month 1 VAS, and pre-operative ODI (p>0.05). However, significant differences were observed in post-operative month 3 VAS (p=0.002), post-operative day 2 ODI (p=0.002), post-operative month 1 ODI (p<0.001), and post-operative month 3 ODI (p<0.001). The “0.4-0.6” group showed better pain improvement and functional recovery compared with the “>0.6” group at the 3-month follow-up. While presenting the best vertebral height restoration, the “>0.6” group also exhibited the greatest variability. Additionally, no significant difference in Cobb angle changes was observed among the groups.ConclusionA bone cement filling ratio of 0.4-0.6 in PKP treatment for OVCF strikes a favorable balance between complication reduction and positive patient outcomes, warranting it as an optimal filling volume.

Protein C and S activities in COVID-19: A systematic review and meta-analysis.

COVID-19 has been associated with alterations in coagulation. Recent reports have shown that protein C and S activities are altered in COVID-19. This may affect the complications and outcome of the disease. However, their exact role in COVID-19 remains uncertain. The aim of the current study was therefore to analyze all papers in the literature on protein C and S activities in COVID-19. We searched three medical electronic databases. Of the 2442 papers, 28 studies were selected for the present meta-analysis. For the meta-analysis, means ± standard deviations with 95% confidence intervals (CI) for protein C and S activities were extracted. Pooled p values were calculated using STATA software. Protein C and S activities were significantly lower in COVID-19 patients than in healthy controls (pooled p values: 0.04 and 0.02, respectively). Similarly, protein C activities were considerably lower in nonsurviving patients (pooled p value = 0.00). There was no association between proteins C or S and thrombosis risk or ICU admission in COVID-19 patients (p value > 0.05). COVID-19 patients may exhibit lower activities of the C and S proteins, which might affect disease outcome; however, additional attention should be given when considering therapeutic strategies for these patients.

Nurses′ knowledge and practice about neonatal pain management in public hospitals in West Oromia, Ethiopia, 2022: multi-centered cross-sectional study

BackgroundIn low-and middle-income countries inadequate neonatal pain management persists as a significant public health issue despite the availability of guidelines. Newborns often experience pain from routine medical and surgical procedures, with limited nurses’ knowledge and suboptimal practices posing common obstacles to effective neonatal pain management in hospital settings. Hence, this study aimed to evaluate nurses’ knowledge and practices related to neonatal pain management and the factors influencing them in public hospitals in West Oromia, Ethiopia, in 2022.MethodsA multicenter cross-sectional study was conducted among 203 nurses working in public hospitals in West Oromia from 8th May-6th June 2022. Data was gathered using structured, self-administered questionnaire and sampled through simple random sampling. The collected data were coded and entered into a computer using Epi-Data version 4.6 Statistical Software. They were analyzed using the Statistical Package for Social Science (SPSS; IBM Corporation) version 26. Binary logistic regression was used to identify significant independent variables at p < 0.05.FindingsIn this study, 127 (62.6%) exhibited adequate knowledge, while 33 (16.3%) nurses demonstrated good practice in neonatal pain management. Attending lectures or receiving training about neonatal pain management was found to be significantly associated with nurses’ knowledge of neonatal pain management [AOR, 2.31, 95%CI; 1.29–4.27]. On the other, having adequate knowledge of neonatal pain management [AOR, 3.3, 95%CI; 1.14–9.32]; the presence of a pain management policy in place [AOR, 5.44, 95% CI; 1.92–15.37] and attending lectures on neonatal pain management [AOR, 2.55, 95% CI; 1.09–5.97] were found to be significantly associated to nurses’ practices.ConclusionGiven the substandard level of nurses’ practice in neonatal pain management. It is suggested to enhance the nurses’ knowledge and practice about neonatal pain management by providing refreshment courses, training sessions, or facilitating nurses’ opportunity access to reading resources about neonatal pain management.

The effect of conscious mindfulness-based informative approaches on managing symptoms in hemodialysis patients

IntroductionThe research was conducted to determine the effect of conscious mindfulness based informative approaches applied in hemodialysis patients on reducing stress and managing symptoms.MethodsThis research was conducted as a real experimental model with a control group. Research population consisted of 160 hemodialysis patients. The sample of the study was determined as 120 hemodialysis patients in total, 60 in the experimental and 60 in the control group, as a result of the power analysis. After the pre-test application, a mindfulness-based stress reduction program was applied to the experimental group. In the analysis of the data collected in the research, percentage, frequency, chi-square analysis, t-test for independent groups, t-test for dependent groups were used by means of SPSS for Windows 22.00 statistical software package.ResultsThe t-test analyses of the differences between pre-test and post-test scores of hemodialysis patients in the experimental group were found to be significant in favor of the post-tests.DiscussionIt was found out that the conscious mindfulness-based informative approaches decreased the perceived stress and anxiety of the patients in the experimental group, whereas increased their levels of conscious mindfulness and symptom management.

Social media marketing and customer purchase intention: Evidence-based bibliometrics and text analysis

The rapid proliferation of social media platforms has sparked heightened interest among businesses seeking to leverage them to enhance customer purchase intentions. Consequently, there has been a surge in research exploring the intersection of social media marketing and consumer behavior. However, gaps persist regarding the primary themes within this research domain. This study analyzes 282 research papers spanning from 2012 to 2022, sourced from the Web of Science Core Collection, focusing on social media and customer purchase intentions. Leveraging Latent Dirichlet Allocation (LDA) commands in STATA and VOSviewer software, the study investigates emerging trends and prevalent themes, visualizing the dataset. The findings indicate a notable increase in research output, particularly from developed countries, with significant collaboration between developed and developing nations. Moreover, the study identifies five principal research topics: 1) the impact of social media marketing on consumer purchase intention, 2) the consequences of online brand communities on purchase behavior, 3) factors influencing consumer purchase intention, 4) influencer effects on purchase intention, and 5) social media advertising and marketing strategies. Future inquiries should delve into various factors shaping customer purchase intentions, including the role of influencers, word-of-mouth dynamics, and advertising strategies while considering the diverse cultural contexts across different regions. This comprehensive analysis provides valuable insights for researchers and practitioners alike, guiding future endeavors in understanding and harnessing the power of social media in consumer decision-making processes. AcknowledgmentsGiang Hai Ha was funded by the Master, PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF), code VINIF.2022.TS030.

Approaches to Developing the Manufacturing Industry of Small and Medium Enterprises for Readiness Towards Large Businesses in Thailand

This research aims to 1) study the structure and operational characteristics of the manufacturing industry in small and medium-sized enterprises (SMEs) in Thailand for readiness towards becoming large-scale businesses; 2) investigate the components of development approaches for the manufacturing industry in SMEs for readiness towards becoming large-scale businesses; and 3) develop a structural equation model (SEM) for the development approaches of the manufacturing industry in SMEs for readiness towards becoming large-scale businesses. The study employed a mixed-methodology approach, incorporating both quantitative and qualitative research. The qualitative research involved in-depth interviews with a sample of 9 experts from 3 different groups: 3 entrepreneurs or executives in the manufacturing industry, three from the government sector, and three academics. For quantitative research, data was collected via surveys from 500 entrepreneurs or executives and analyzed using frequency, percentage, average, standard deviation, and structural equation modeling (SEM) with the advanced statistical analysis software AMOS. The research on the general characteristics of organizations found that they have been operating for 10-15 years, are predominantly Thai-owned, use financial institutions for funding, are established as limited companies, and mostly have offices located in Thailand. In terms of structure and operational characteristics, the research revealed that the most suitable business strategy for these organizations is creating a product advantage, emphasizing mentorship systems from knowledgeable employees, and key leadership qualities, including treating colleagues with kindness and generosity and developing leadership at various levels focusing on experience, comprehensive knowledge, and business expertise.The study on the importance of different components indicated that all aspects were highly important, with the order of importance from highest to lowest being digital technology, entrepreneurial leadership, knowledge management, and innovative organization. The results of the analysis of the structural equation model for small and medium-sized enterprises management for sustainable strength found that the chi-squared probability (CMIN-r) was 0.128, the relative chi-squared (CMIN/DF) was 1.126, the GFI was 0.955, and the root mean squared index of error estimation (RMSEA) was 0.015. It can be concluded that the model is consistent with the empirical data.

How did we protect children against COVID-19 in Iran? Prevalence of COVID-19 and vaccination in the socio-economic context of COVID-19 epidemic.

The COVID-19 pandemic posed significant risks to children worldwide. This study aimed to assess the COVID-19 protection status of children and explored the relationship between household socio-economic status and COVID-19 morbidity and preventive measures, including vaccination and mask-wearing, in two cities in Iran. A population-based cross-sectional study was conducted from July to October 2022 among 7 to 18-year-old children and their families in Tehran and Karaj. A total of 3,022 samples were selected using stratified multistage cluster sampling. Data were collected through interviews with children and adults, using questionnaires and was analyzed with Stata software version 14. The analysis focused on 2,878 children with a median age of 12. Over half (54%) reported that the pandemic negatively affected their family's financial status, with 45% describing its impact on children's needs as negative or very negative. Just under 50% of respondents consistently wore masks during the study period, and around 54% had received at least one dose of the COVID-19 vaccine. Reasons for not getting vaccinated included concerns about side effects, ineligibility for the target age group, and overcrowding at vaccination sites. The odds of not getting vaccinated were significantly lower for children aged 15-18, with boys more likely to refuse vaccination than girls. The financial impact of the pandemic in Iran affected families' ability to meet their children's needs. Moreover, low vaccination acceptance rates increased children's vulnerability to health problems and contributed to COVID-19 infections. Efforts should be made to increase vaccination acceptance, particularly among immigrant populations.

Association between low birth weight and impaired glucose tolerance in children: a systematic review and meta-analysis

BackgroundA potential association between the onset of diabetes and normal birth weight (NBW) has been discovered. Diverse conclusions and study methodologies exist regarding the connection between low birth weight (LBW) and impaired glucose tolerance in children, underscoring the need for further robust research. Our institution is embarking on this study to thoroughly examine the association between LBW and impaired glucose tolerance in children.MethodsWe conducted searches on Cochrane Library, ScienceDirect, EMBASE, PubMed, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature data (CBM) online database, VIP full-text Database, and Wanfang Database to identify correlation analyses or case-control studies investigating the relationship between LBW and abnormal glucose tolerance in children. The search spanned from January 2010 to September 2023. The quality of observational studies was evaluated using the Newcastle–Ottawa Scale (NOS) tool. Data synthesis was performed using the statistical software RevMan 5.3 for meta-analysis.ResultsBased on the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines, we finally included 10 clinical control studies consisting of a total of 2971 cases. There wasn’t considerably change in blood sugar levels among LBW, NBW and high birth weight (HBW) infants (P &amp;gt; 0.05). There was no significant difference in insulin levels between LBW infants and NBW infants (P &amp;gt; 0.05). The HOMA-IR of LBW infants was considerably higher than that of NBW infants (P &amp;lt; 0.05). The risk of abnormal glucose tolerance in LBW infants was 0.42 times higher than that in NBW and HBW infants [Fisher's Z = 0.42, 95% CI = (0.09, 0.75), P = 0.01].ConclusionLBW is associated with an increased risk of abnormal glucose tolerance, as indicated by elevated HOMA-IR level in LBW infants compared to NBW and HBW pediatric population. Further research is needed to confirm and expand upon these findings to better understand the complex relationship between LBW and impaired glucose tolerance in children.

Midwife-led obstetric triage to increase providers’ knowledge and improve timeliness of care: A pre and posttest design

BackgroundResearch in low- and middle-income countries has shown that maternal mortality is directly related to inadequate or absent obstetric (OB) triage systems. Standard triage systems and knowledge on triaging for obstetric emergencies are often absent or lacking in most healthcare systems in Liberia. ObjectiveThe objective of this research was to address the third delay defined as receiving adequate, quality care when a facility is reached by increasing knowledge through the establishment of a midwife-led, hospital-based OB triage system to stratify care based on risk and imminence of birth and to improve timely assessment at two district referral hospitals. MethodsA quasi-experimental study design using a pre/post survey was employed for a midwife-led OB triage training course. Using a train-the-trainer model, five midwives were trained as champions, who in turn trained an additional 62 providers. Test results were analyzed with the R statistical software using paired sample t-test and descriptive statistics. ResultsPretest results revealed a knowledge and practice gap among OB providers on key components of the standard triage package. However, post-test mean scores were significantly higher (M = 79.6, SD = 2.32) than pre-test mean scores (M = 59.0, SD = 2.30) for participants following a 2-day training (p = <0.001). DiscussionFollowing a structured OB triage training, participants showed significant improvement in post-test OB triage scores. ConclusionStandard OB triage protocols incorporated into the policies and procedures of obstetric wards have the potential to improve knowledge and practice, addressing the third delay and reducing preventable, obstetrics-related deaths.

Prognostic significance of SIRI in patients with late-stage lung adenocarcinoma receiving EGFR-TKI treatment

ObjectiveIn this study, we examined the relationship between the Systemic Inflammatory Response Index (SIRI) and the overall prognosis of patients with late-stage lung adenocarcinoma who harbor epidermal growth factor receptor (EGFR) mutations and are undergoing first-line treatment with EGFR-tyrosine kinase inhibitors (EGFR-TKIs). MethodsA cohort comprising 52 patients with late-stage lung adenocarcinoma, who received treatment at Jinzhou Central Hospital between January 2018 and December 2022, were carefully selected. Patient data spanning from pre-treatment assessments through follow-up periods were meticulously collected from electronic medical records and subsequently subjected to a comprehensive retrospective analysis. The collected data was subjected to in-depth processing and analyzed using SPSS 27.0 statistical software. To determine the optimal cut-off value of the pre-treatment SIRI, a receiver operating characteristic (ROC) curve was employed. Survival analysis was performed using the Kaplan-Meier method, and both univariate and multivariate prognostic analyses were conducted using Cox regression. ResultsThe optimal SIRI cut-off value was determined to be 1.659 (with a specificity of 0.964 and sensitivity of 0.652, P = 0.000). Based on this value, patients were categorized into high and low SIRI groups. Chi-squared tests demonstrated that SIRI exhibited statistically significant correlations with patient age and smoking history (P < 0.05). Survival analysis revealed that the group with a lower SIRI had a significantly extended progression-free survival (PFS) (P < 0.001). Cox univariate analysis identified hypertension, pleural metastasis, liver metastasis, and SIRI as factors associated with PFS (P < 0.05). In the subsequent multivariate analysis, liver metastasis and SIRI ≥ 1.659 (P < 0.001) were identified as independent risk factors for patients. ConclusionPre-treatment SIRI holds predictive significance for the prognosis of patients with late-stage lung adenocarcinoma with EGFR mutations undergoing first-line treatment EGFR-TKI treatment.

Highway Deformation Monitoring by Multiple InSAR Technology

Addressing the challenge of large-scale uneven deformation and the complexities of monitoring road conditions, this study focuses on a segment of the G15 Coastal Highway in Jiangsu Province. It employs PS-InSAR, SBAS-InSAR, and DS-InSAR techniques to comprehensively observe deformation. Analysis of 73 image datasets spanning 2018 to 2021 enables separate derivation of deformation data using distinct InSAR methodologies. Results are then interpreted alongside geological and geomorphological features. Findings indicate widespread deformation along the G15 Coastal Highway, notably significant settlement near Guanyun North Hub and uplift near Guhe Bridge. Maximum deformation rates exceeding 10 mm/year are observed in adjacent areas by all three techniques. To assess data consistency across techniques, identical observation points are identified, and correlation and difference analyses are conducted using statistical software. Results reveal a high correlation between the monitoring outcomes of the three techniques, with an average observation difference of less than 2 mm/year. This underscores the feasibility of employing a combination of these InSAR techniques for road deformation monitoring, offering a reliable approach for establishing real-time monitoring systems and serving as a foundation for ongoing road health assessments.

Advanced machine learning for missing petrophysical property imputation applied to improve the characterization of carbonate reservoirs

Missing data is a common cause of uncertainty in reservoir characterization, especially in core analysis of porosity and permeability. This is due to the high cost and time required to gather core samples while drilling through the entire reservoir thickness. Therefore, the ability to collect core samples and directly assess petrophysical parameters is restricted by the small proportion of the reservoir thickness that can be measured by the retrieved cores. As a result, the absence of data has the potential to lead to inconsistent and imprecise classification of reservoirs and geomodeling, thereby increasing reservoir uncertainty. Therefore, imputation algorithms are needed to estimate petrophysical properties for incomplete intervals. This study comprehensively compares seven imputation techniques for predicting missing horizontal and vertical core permeability and core porosity data in a well drilled through a carbonate reservoir in a southern Iraqi gas field. The performance of each method was assessed using relative bias (RB) and reasonable descriptive statistical distributions (histogram, log view, and box plots of data ratios to compare the imputed and original data), and robustness to outliers (RtO). The results revealed that the random imputation of missing data (RIMD) technique is the most effective algorithm in addressing the 30.5% missing data (vertical permeability), resulting in the attainment of the RB value closest to zero (0.04076191) compared to other algorithms. Principal component analysis (PCA) and random forest (RF) yielded the most favorable results in terms of handling missing values and outliers for the 15% missing ratio dataset (core porosity and horizontal permeability). The advantages of these approaches are related to their capacity to independently and accurately impute the missing data without requiring extra information, such as well logging records. Additionally, the multiple imputation and machine learning algorithms fill missing values with adequate numbers based on dataset variable distributions and correlations. Multiple plausible values quantify the uncertainty in estimating missing data, avoiding false precision (as with single imputation). Also, the novel workflow involving multiple imputation methods accurately take into account the correlations and variances between the variables. The novel workflow developed for missing data imputation has the potential to be applied to other clastic and carbonate reservoirs in oil and gas fields. The entire data imputation workflow was conducted, validated, visualized by codes in R, a robust open-source statistical computing software.

Factors Affecting Loneliness in Older Adults: Evidence from Ardakan Cohort Study on Aging (ACSA)

Introduction: Elderly people usually feel lonely that can have adverse health effects. The purpose of current paper is to determine the loneliness score in the elderly population of the Ardakan Cohort and the factors affecting it. Methods: This is a cross sectional study using data from the Ardakan Cohort Study on Ageing (ACSA). Loneliness was measured using a 6-item De Jong Gierveld short scales. The 11-item Duke Social Support Index (DSSI) was used to measures social support of aging. living arrangement, demographic factors and self-rated health was also collected using a checklist. Linear regression was used to examine the relationship between loneliness and predictor factors. The data was analyzed with Stata software version 17 and a p-value of 0.05 was considered as a significant level. Results: Among the 5,188 participants, 48.13% were male and most of the participants were over 60 years old. Total score of loneliness was 3.27±1.45(95% CI: 3.24 to 3.31). Among covariates, age (p value=0.000), sex (p value=0.000), marital status (p value=0.046), education (p value=0.001) and economic status (p value=0.001) have significant association with loneliness score. People with good self-rated health had a lower loneliness score (p value&lt;0.001). The score of social support has an inverse association with the score of loneliness (p value&lt;0.001). Adults who lived with others had a higher loneliness score (p value&lt;0.001). Conclusion: According to the results, elderly people who have more social support and have better self-rated health feel less lonely.

Burden, causes, and risk factors of perinatal mortality in Eastern Africa: a protocol for systematic review and meta-analysis

Background Although global mortality rates in children under 5 years have decreased substantially in the last 30 years, there remain around 2.6 million stillbirths and 2.9 million neonatal deaths each year. The majority of these deaths occur in Africa and South Asia. To reduce perinatal deaths in East Africa, knowledge of the burden, but also the risk factors and causes of perinatal deaths are crucial. To the best of our knowledge, reviews have previously focused on the burden of perinatal deaths; here we aim to synthesize evidence on the burden, causes, and risk factors for perinatal mortality in East Africa. Methods We will conduct a systematic literature search in Medline, Web of Science, EMBASE, Global Health, SCOPUS, Cochrane Library, CINAHL, HINARI, African Index Medicus, African Journals Online (AJOL), and WHO African Regional Office (AFRO) Library. The study population includes all fetuses and newborns from ≥22 weeks of gestation (birth weight ≥500gm) to 7 days after birth, with reported causes or/and determinants as exposure, and perinatal mortality (stillbirths and/or early neonatal deaths) as an outcome. We will include studies from 2010 to 2022, and to facilitate the inclusion of up-to-date data, we will request recent data from ongoing surveillance in the region. To assess the quality of included studies, we will use the Joanna Briggs Institute quality assessment tool for observational and trial studies. We will analyze the data using STATA version 17 statistical software and assess heterogeneity and publication bias by Higgins’ I2 and funnel plot, respectively. Conclusions This systematic review will search for published studies, and seek unpublished data, on the burden, causes, and risk factors of perinatal mortality in East Africa. Findings will be reported, and gaps in the evidence base identified, with recommendations, with the ultimate aim of reducing perinatal deaths. Protocol registration PROSPERO-CRD42021291719.

Empirical Research on Ethical Leadership and Knowledge Workers’ Innovative Behaviour: The Mediating Role of Job Autonomy

Introduction: This research studied the mediating role of job autonomy in the relationship between ethical leadership and knowledge workers’ innovative behaviour based on self-determination theory. Data were collected from 377 knowledge workers in the IT industry in Sichuan, Henan, and Guangdong province, China. A conceptual model was constructed and tested with the statistical software SMART-PLS. This paper concludes that job autonomy effectively mediates ethical leadership and knowledge workers’ innovative behaviour. The findings also reveal the strong and positive impact of ethical leadership on knowledge workers’ innovative behaviour. This paper enriched the leadership literature and extended the understanding of the predictors of employee innovative behaviour Objective: To investigate the impact of ethical leadership on knowledge workers’ innovative behaviour. To study the relationship between ethical leadership and job autonomy. To examine the impact of job autonomy on knowledge workers’ innovative behaviour. To investigate the mediating effect of job autonomy between ethical leadership and knowledge workers’ innovative behaviour. Theoretical Framework: Knowledge workers are highly skilled workers with professional knowledge, good education, or experience in their respective fields (Davenport, 2006). According to Correia &amp; Dierendonck (2010), three core elements underpin the global meaning framework of knowledge workers: first, knowledge workers perceive their work as a calling; second, they have a strong desire for membership within a community of peers; third, they demand autonomy. These elements are in consistency with SDT. Method: This research used a quantitative approach to test the hypothesis, a closed questionnaire to collect the data, and SMART PLS version 4 to analyze the data. The survey questions were translated into Chinese with a back-translation approach (Brislin, 1986), as the respondents were all Chinese. Results and Discussion: Due to the single source, we first test common method bias. We adopted a full collinearity assessment approach to check the common method bias (Kock, 2015; Kock and Lynn, 2012). In this approach, the constructs were regressed on a new dummy variable with random values. As shown in table 4.1, the variance inflation factor (VIF) is lower than 3.3 (Kock, 2015), the model is indicated free of common method bias. Research Implications: The study constructed a research model to investigate the mediating effect of job autonomy between ethical leadership and knowledge workers' innovative behaviour. Management in knowledge-intensive industries, like the IT industry, can gain inspiration from the research to develop proper management strategies to promote knowledge workers’ innovative behaviour while guarding the ethical line.

Eco-consciousness to eco-consumption: unraveling the drivers of sustainable consumption behavior under the mediated-moderated Model.

The impact of climate change has malformed the world's ecosystem, thus making humans call for environmental protection. Climate change, the biggest trauma of the twenty-first century, has made humans switch towards natural consumption. In this regard, the growing phenomenon of industrialization has spurred consumers to invest more in ecological products. Consuming eco-friendly products has several benefits; however, countries are still unable to satisfy the consumer's concern for the environment. The current study presents literature on environmental concerns, psychological well-being, willingness to pay for pro-environmental products, pro-environmental self-identity, and pro-environmental consumer behavior, which are required to ensure the consumer's organic behavior. The research used a questionnaire-driven methodology to gather data from 379 participants. Data analysis was conducted using statistical software packages, specifically SPSS (Version: 4.1.0.0). The suitability of the measurement model was evaluated through structural equation modeling (SEM), which was performed utilizing the SmartPLS. According to the research findings, there is a positive relationship between variables in the study, and individuals with greater levels of psychological well-being are more likely to engage in behaviors that promote sustainable consumption. In order to foster more sustainable consumption patterns in society, policymakers, marketers, and educators may find these findings to be valuable insights. As a result of its empirical exploration of these relationships, the study contributes to the growing body of literature on environmental psychology and sustainable marketing, emphasizing the important role psychological factors play in promoting a greener environment.