Data Collection Period Research Articles

Factor Analysis of Antenatal Care in Women of Fertilizing Age in Nepal

<div><table cellspacing="0" cellpadding="0" align="left"><tbody><tr><td align="left" valign="top"><p><em>The high maternal and infant mortality rate in Nepal is a global problem. Antenatal Care (ANC) services are an effort to reduce maternal and infant mortality rates. This study aims to analyze factors in the utilization of antenatal care among women of childbearing age in Nepal. This research method The Nepal Demographic and Health Survey (NDHS) was carried out in the new era with official approval from the Ministry of Health and Population (MoHP), and the data collection period lasted from January 5 to June 22, 2022. The study population was women aged 15 to 49 years. who have given birth or experienced a stillbirth in the previous two years and have attended at least one antenatal care (ANC) visit. Data collection using questionnaires interviewed after they were discharged from the facility that provides delivery services. Data analysis using the JASP version 18 application to see the influence of the independent variable on the dependent variable. Bivariate data will be analyzed using chi-square analysis, and multivariate data will be analyzed using the logistic regression test. The research results showed that there was a relationship between age (p<0.001), place of residence (p<0.001), zone of residence (p<0.001), economy (p<0.001), education (p<0.001), number of children (p<0.001) women of childbearing age in Nepal with ANC visits. These factors greatly influence women of childbearing age in utilizing ANC services. Therefore, it is necessary to strengthen ANC service policies and remind women of childbearing age to make at least 4 ANC visits during pregnancy so that examinations and visits for pregnant women can be carried out completely.</em></p><p><em> </em></p></td></tr></tbody></table></div><strong><em>Keywords : Antenatal Care, Women of childbearing age, Nepal</em></strong>

Awareness and Practice Regarding Alcohol Consumption among Females in Rural Areas of Nepal

Consuming alcohol is defined as ingesting alcoholic beverages that include ethyl alcohol, such as wine, beer, whiskey, rum, and handmade alcoholic beverages called "Raksi." Excessive alcohol consumption can lead to serious health issues. Thus, this study aimed to assess the awareness regarding alcohol consumption among females in rural areas of Nepal. A cross-sectional and analytical study was designed to assess the level of awareness and practice regarding alcohol consumption. Total 423 females of the 20-50 years age groups, engaged in “Raksi '' preparation sites were selected. The data collection period was from 2021 July to 2022. A face-to-face interview was done with each individual. All questions related to awareness and practice regarding questionnaires were analyzed accordingly in univariate analysis and bi-variate analysis to find out the association between the variables. The result showed that the mean age of the females was 36.08 with a standard deviation of 7.951. and 51.7% were below the mean age of 36. Among 423 females 22.3 % knew AUD, 56.7% were aware of health consequences, and only 13.3% were aware of treatment protocol of health consequences. Females having inappropriate practices of alcohol consumption were 54.2%. There is an association between awareness regarding consumption and religion, marital status, educational status, and occupation with p=0.043, 0.036, 0.046, and 0.033 respectively. Similarly, the inappropriate practice of alcohol consumption has a significant relation with religion, educational status, and occupation with p values of 0.049,0.034, and 0.003 respectively. Even though there is a higher percentage of females were literate, there is a lack of awareness regarding alcohol consumption and inappropriate drinking habits. Further comparative study can be done in this aspect. Simultaneously, awareness and education-related programs can be implemented to address the problem.

Women's caesarean section preferences: A multicountry cross-sectional survey in low- and middle-income countries

ObjectiveTo measure the proportion of women's preferences for CS in hospitals with high caesarean section rates and to identify related factors. DesignA cross-sectional hospital-based postpartum survey was conducted. We used multilevel multivariate logistic regression and probit models to analyse the association between women's caesarean section preferences and maternal characteristics. Probit models take into account selection bias while excluding women who had no preference. SettingThirty-two hospitals in Argentina, Thailand, Vietnam and Burkina Faso were selected. ParticipantsA total of 1,979 post-partum women with no potential medical need for caesarean section were included among a representative sample of women who delivered at each of the participating facilities during the data collection period. FindingsThe overall caesarean section rate was 23.3 %. Among women who declared a preference in late pregnancy, 9 % preferred caesarean section, ranging from 1.8 % in Burkina Faso to 17.8 % in Thailand. Primiparous women were more likely to prefer a caesarean section than multiparous women (β=+0.16 [+0.01; +0.31]; p = 0.04). Among women who preferred caesarean section, doctors were frequently cited as the main influencers, and “avoid pain in labour” was the most common perceived benefit of caesarean section. Key conclusionsOur results suggest that a high proportion of women prefer vaginal birth and highlight that the preference for caesarean section is linked to women's fear of pain and the influence of doctors. These results can inform the development of interventions aimed at supporting women and their preferences, providing them with evidence-based information and changing doctors' behaviour in order to reduce the number of unnecessary caesarean sections. Clinical trial registryThe QUALI-DEC trial is registered on the Current Controlled Trials website (https://www.isrctn.com/) under the number ISRCTN67214403.

Pengaruh Model Pembelajaran Flipped Classroom Terhadap Hasil Belajar Kognitif Peserta Didik SMAN 44 Jakarta

Indonesia's ranking in the Program for International Student Assessment (PISA) is always decreasing and the problem in the world of Indonesian education is that teachers have not been able to choose, maximize and implement learning models as adaptive learning techniques wisely. This learning pattern must be changed to focus on students (student center). This research aims to determine the effect of the flipped class learning model on the cognitive learning outcomes of students at SMAN 44 Jakarta. The method used is quantitative with an experimental approach. Data collection at SMAN 44 Jakarta, with students at class XI level. For class XI IPS 1 as an experimental class using the flipped class learning model and class XI IPS 3 as a control class using a conventional learning model. The data obtained came from pre-test and post-test scores with a data collection period of 3 meetings. Test the pre-requisites for data analysis using normality and homogeneity tests. The data analysis technique used in this research is the Independent Sample T-Test. The results show that there is a significant influence on the average learning outcomes of students in the experimental class from 39.44 to 75.27, while for the control class the score was 38.47 to 63.47. The conclusion of this research is that there is an influence in using the flipped class learning model.

Naturalistic study of vehicle-bicycle lateral passing distance on high-speed rural two-lane roadways with paved shoulders

In the United States, 91.4 cm (3.0 ft) has been considered a safe lateral distance when passing bicyclists; however, this threshold may be more suitable to urban environments where most bicycle safety research has originated—limited research is available on rural roadways. In this study, a road bicycle was instrumented to collect naturalistic data and analyze vehicle-bicycle lateral passing distances (LPD) on high-speed rural two-lane roadways with paved shoulders. The bicycle was ridden in the center of the shoulder. Overall, 2,119 observations of vehicles passing the instrumented bicycle were obtained from a study segment. The impacts of different variables on distributions of vehicle-bicycle LPD measurements were analyzed. Passing vehicles with opposing traffic passed the bicyclist significantly closer than passing vehicles without opposing traffic. More predominant with opposing traffic, heavy vehicles passed the bicyclist closer than passenger vehicles. Similarly, following vehicles passed the bicyclist closer than leading vehicles. The study segment was repaved during the data collection period, so data before and after the roadway improvement was available. Vehicles with old pavement/marking passed the bicyclist closer than vehicles with new pavement/marking conditions. Distribution of LPD measurements was skewed to the left towards smaller values and had a long tail to the right towards larger values. Through maximum likelihood estimation, the Log-normal distribution was found to best fit the data distribution. Using empirical and theoretical density distributions, LPD was formally specified as a function of opposing traffic with a theoretical mixture distribution and generalized to estimate the probability of vehicles passing bicyclists below a certain threshold.

Development and evaluation of a microcontrolled solar tracker based on chronological positioning

AbstractCurrently, photovoltaic (PV) solar energy is one of the most promising sources of renewable energy. Solar trackers (ST) are devices that track and maintain the alignment of solar collectors with the sun's rays, thereby increasing energy generation. This article reports on the development of a microcontrolled dual‐axis solar tracker. The system lacks feedback and relies on astronomical equations to calculate the position of the sun. The positioning of the solar panel is controlled by an on–off controller, while the energy generated by the tracker is compared to the output of a stationary panel. Unlike other studies, this work takes into account the energy consumed during the process, including powering the control system and moving the structure. The true tracking gain is estimated using this method. The tracker was analyzed over three days under different climatic conditions, including sunny, partly cloudy, and cloudy weather. After evaluation, the average error of the solar positioning algorithm was 1%. On a sunny day, the tracker produced 52.96% more energy than the fixed system. Considering the energy consumed by the tracking system, the net gain was 48.88%. The average gross gain for the three days analyzed was 45.64%, which is higher than the results of recent studies using the same tracker configuration. For the cloudy day, tracking was not very effective, resulting in a net gain of only 2.14%. In future work, an irradiation sensor could be included to reduce energy consumption on cloudy days. Additional studies are needed to more accurately evaluate the performance of the trigger, preferably with a one‐year data collection period.

Early childhood development and its association with women's empowerment in the context of urban poverty in Ethiopia

BackgroundEmpowered women, with increased access to and control over resources, stronger social networks, greater decision-making power, and a more positive gender attitude, significantly contribute to better family well-being. While there is ample evidence regarding the association between child nutrition and women's empowerment, studies examining the association between early childhood development (ECD) and women's empowerment are scarce. AimsThe aim of this study was to estimate the prevalence of ECD delays among 12–36 months old and investigate its association with women's empowerment among the urban poor in Ethiopia. MethodsThe study included a sample of 432 women who were unemployed or had irregular employment during the data collection period, along with their children in urban Ethiopia. The ECD was assessed using the Age and Stage Questionnaire (ASQ-3), a tool designed to accurately identify developmental delays in infants and young children and categorized as on track, needs monitoring, and possible delays. Women's empowerment was measured using a multidimensional index that captured access to and control over resources, decision-making power, and social capital, and then categorized into lowest, medium, and highest empowerment levels. The association between ECD domains and women's empowerment was analyzed using ordinal logistic regression, after adjusting for confounders. ResultsThe study found a high prevalence of delays in ECD domains, with fine motor domain accounting for the largest delay (40.6 %). Children of less empowered mothers are more likely to have the highest development delays in communication (OR=2.22; 95 % CI: 1.36; 3.62), gross motor (OR=1.69; 95 % CI: 1.04; 2.76), problem solving (OR=1.85; 95 % CI: 1.15; 2.98), and personal-social (OR=2.59; 95 % CI: 1.62; 4.15) skills compared to children of more empowered mothers. ConclusionsThe study highlights the significance of women's empowerment in promoting ECD, especially in developing countries where ECD programs are fragmented and lacks coordination. Therefore, targeted interventions that improve women's empowerment could lead to improved ECD outcomes.

Merging Two Models of One-Dimensional Convolutional Neural Networks to Improve the Differential Diagnosis between Acute Asthma and Bronchitis in Preschool Children.

(1) Background: Acute asthma and bronchitis are common infectious diseases in children that affect lower respiratory tract infections (LRTIs), especially in preschool children (below six years). These diseases can be caused by viral or bacterial infections and are considered one of the main reasons for the increase in the number of deaths among children due to the rapid spread of infection, especially in low- and middle-income countries (LMICs). People sometimes confuse acute bronchitis and asthma because there are many overlapping symptoms, such as coughing, runny nose, chills, wheezing, and shortness of breath; therefore, many junior doctors face difficulty differentiating between cases of children in the emergency departments. This study aims to find a solution to improve the differential diagnosis between acute asthma and bronchitis, reducing time, effort, and money. The dataset was generated with 512 prospective cases in Iraq by a consultant pediatrician at Fallujah Teaching Hospital for Women and Children; each case contains 12 clinical features. The data collection period for this study lasted four months, from March 2022 to June 2022. (2) Methods: A novel method is proposed for merging two one-dimensional convolutional neural networks (2-1D-CNNs) and comparing the results with merging one-dimensional neural networks with long short-term memory (1D-CNNs + LSTM). (3) Results: The merged results (2-1D-CNNs) show an accuracy of 99.72% with AUC 1.0, then we merged 1D-CNNs with LSTM models to obtain the accuracy of 99.44% with AUC 99.96%. (4) Conclusions: The merging of 2-1D-CNNs is better because the hyperparameters of both models will be combined; therefore, high accuracy results will be obtained. The 1D-CNNs is the best artificial neural network technique for textual data, especially in healthcare; this study will help enhance junior and practitioner doctors' capabilities by the rapid detection and differentiation between acute bronchitis and asthma without referring to the consultant pediatrician in the hospitals.

Physiological, anthropometric and athletic performance adaptations from completing a 1-month pre-season period. A two-year longitudinal study in female collegiate soccer players.

Collegiate coaches and integrative support staff often utilize pre-season as a brief and intense training period to prepare athletes technically, tactically, and physiologically, to meet the demands of competition during a soccer season. This study sought to examine the dose-response from performing on-field soccer activities during a four-week pre-season period in female collegiate soccer players, and if the magnitude in response was associated with accumulated exercise stress. A total of twenty-seven healthy female soccer players training as part of a collegiate soccer program volunteered to participate in this two-year longitudinal study. Data collection commenced prior to the start of each pre-season period, at the beginning of August, and was completed at the beginning of September, when pre-season ended. Data collection periods were separated by a 31-day period. Indices of cardiovascular function, anthropometry, and athletic performance were examined during each data collection period. Internal and external measures of accumulated exercise stress were recorded using the Polar Team Pro® system. When comparing the beginning to the end of pre-season, significant improvements were observed in body fat (%) [24.2 ± 6.0 "vs." 23.3 ± 5.6, p = 0.001], heart rate variability (rMSSD) [51.8 ± 25.1 "vs." 67.9 ± 34.6 ms, p = 0.002], resting heart (bpm) [73.8 ± 12.1 "vs." 64.3 ± 8.8, p = 0.001] and cardiorespiratory performance (YoYo IRTL-1) [925.8 ± 272.8 "vs." 1,062.6 ± 223.3 m, p = 0.001]. Significant reductions in musculoskeletal performance were observed through vertical jump height (cm) [24.9 ± 23.7, p = 0.04]. Change in the end of pre-season body weight (kg) was significantly associated with accumulated accelerations and decelerations [r ≥ 0.49, p = 0.01]. End of pre-season change in cardiorespiratory performance was significantly associated with both accumulated training load (au) and TRIMP (au) [r ≥ 0.63, p = 0.01]. In conclusion, performing a four-week pre-season period, involving only on-field training, can promote positive and significant adaptations in anthropometry, cardiovascular function, and athletic performance measures in female collegiate soccer players. The magnitudes of these adaptations were associated with both internal and external measures of accumulated exercise stress.

Temperature-based measurement interpretation of the MX3D Bridge

The MX3D Bridge is the world’s first structure produced using metal additive manufacturing (AM, i.e. 3D printing), deposited through wire and arc AM (WAAM). The long-term behaviour of structures built using metal AM is unknown and therefore requires the development of techniques that enable this investigation, to facilitate future widespread adoption of these novel manufacturing processes. The MX3D Bridge is instrumented with a comprehensive sensor network (accelerometers, displacement gauges, inclinometers, load cells, strain gauges and thermistors) to enable condition monitoring through the implementation of data-driven anomaly detection techniques. The structure was exposed to environmental and operational variability (EOV) over an 8-week commissioning period, which demonstrated that its response is predominantly temperature driven. Towards the end of the data collection period the decorative end swirls on the bridge were removed, which is taken as a proxy for damage on a structure built using WAAM. EOV is known to mask the damage-sensitive features used in anomaly detection techniques, such as those produced through the end swirl detachment. This paper explores the use of the temperature-based measurement interpretation (TB-MI) approach to: (i) predict the thermal response of the bridge using the iterative regression-based thermal response prediction (IRBTRP) methodology; (ii) remove the influence of EOV from damage sensitive features; and (iii) detect an anomaly event (e.g. the end swirl removal). Accurate predictions are obtained for the thermal response of the MX3D Bridge across 70 sensor measurement signals through the IRBTRP methodology, with 1.2% and 6.4% average prediction errors for the training/validation and unseen testing subperiods, respectively. Moving principal component analysis and cointegration are used with both the measured and thermal response corrected sensor signals for anomaly detection. The detection of the simulated damage is shown to be significantly improved through the removal of EOV, with damage being detected earlier, with greater certainty and across a wider range of sensor clusters (i.e. groups of sensors). The TB-MI approach and IRBTRP methodology can therefore be used to accurately predict the thermal response and detect damage on components and structures produced using metal AM, enabling the advantages of novel AM techniques to be realised within the built environment.

Comparison of Long Short-Term Memory and Convolutional Neural Network Models for Emergency Department Patients’ Arrival Daily Forecasting

Background: One of the most critical challenges in the emergency department (ED) is overcrowding, which creates negative consequences for patients and staff. Therefore, predicting the rate of patients entering the ED can help manage resources in this department effectively. Objectives: According to the time of data collection, we intended to predict the volume of patient admissions to the ED in epidemic conditions, such as COVID-19 and non-epidemic. In addition, we planned to compare the performance of the LSTM and CNN models. Methods: The collected data consists of three main categories. The first category pertains to air pollutants, provided by the Tehran air quality control organization. The second type relates to data from the Iran Meteorological Organization, and the third category includes the number of patients admitted to the ED of a hospital in Tehran. We also incorporated binary indicators for epidemic and non-epidemic conditions in the dataset. The data collection period spans from February 2018 to March 2022. We employed the Dickey-Fuller test to assess the stationarity of the data. After preprocessing, we independently developed long short-term memory (LSTM) neural network and convolutional neural network (CNN) models, considering various time windows of previous days. Keras and Tensorflow libraries in Python, along with the Google Colab environment, were utilized to execute the models. Results: The LSTM model exhibited the lowest root mean square error (RMSE) and mean absolute error (MAE) with a time window of the last seven days, while the CNN model outperformed the LSTM model with a time window of the previous 13 days. Additionally, the CNN model required less execution time than the LSTM model. Conclusions: In conclusion, deep learning algorithms prove suitable for analyzing multivariate time series data. The CNN model demonstrated the lowest prediction error.

Catastrophic Health Expenditure and Associated Factors Among Hospitalized Cancer Patients in Addis Ababa, Ethiopia.

Out-of-pocket (OOP) health expenditures for cancer care expose households to unanticipated economic consequences. When the available health services are mainly dependent on OOP expenditure, the household faces catastrophic health expenditure (CHE). This study aimed to estimate the incidence and intensity of CHE in hospitalized cancer patients and identify coping strategies and associated factors. Hospital-based cross-sectional study design was conducted on 305 cancer inpatients in Addis Ababa between November 2021 and February 2022. All patients with cancer who were hospitalized during the data collection period were included in the study. The incidence of CHE was estimated at the 40% threshold of households' non-food expenditure and the intensity of CHE was captured based on the amount by which household expenditure exceeded the threshold and mean positive overshoot, the mean level by which CHE exceeds the threshold used. Multivariate logistic regression was used to assess the relationship between CHE levels and the independent variables. The incidence of CHE at the 40% threshold of households' non-food expenditure was 77.7%, while the O and MPO were 36.2% and 46.6%, respectively. CHE for cancer care was significantly associated with patient residence, increased number of chemotherapy cycles, increased duration of hospital admission, lack of insurance enrolment, and lower-income quintiles. Saving and selling assets were identified as the primary coping mechanisms. The incidence and intensity of CHE among inpatients with cancer were high and which could lead to impoverishment of households. Improved quality and coverage of health insurance and decentralizing cancer care to regions standards similar to Addis Ababa will save households from incurring CHE.

Health-related quality of life among patients with esophageal, gastric, and colorectal cancer at Kenyatta National Hospital.

Despite the advancement of modern treatment approaches, several studies indicated a diminished health-related quality of life (HRQoL) in patients with gastrointestinal cancer. However, there is insufficient data about the HRQoL of gastrointestinal cancer patients in Kenya. The study aimed to investigate HRQoL and its determinants in gastrointestinal cancer patients at Kenyatta National Hospital. A cross-sectional study was employed among 160 esophageal, 103 gastric, and 96 colorectal cancer patients. The patient list, identified by unique hospital identification numbers, was obtained from records. Eligibility was assessed based on predetermined criteria, and the hospital identification numbers were reshuffled. Study participants were then randomly selected daily during the data collection period. Data were collected using a researcher-administered European Organization for Research and Treatment of Cancer quality of life questionnaire. The data entry and analysis were carried out using Statistical Package for the Social Sciences 26.0 statistical software. A bivariate and multivariate binary logistic regression analysis was employed to investigate determinants of HRQoL at a 0.05 level of significance. Most esophageal (N = 118, 73.7%), gastric (N = 75, 72.8%), and colorectal (N = 72, 75%) cancer patients had poor overall HRQoL. In the social (p = .04) and cognitive (p = .02) domain of HRQoL, esophageal cancer patients had a significantly lower mean score as compared to gastric cancer patients. Colorectal cancer patients had the highest mean score in physical functioning (p = .01) as compared with gastric cancer patients. Nonetheless, gastric cancer patients had the highest mean score in emotional functioning domains of quality of life as compared to esophageal (p = .04) and colorectal (p < .001) cancer patients The study revealed a low mean HRQoL score in the majority of the symptom domains of quality of life. A statistically significant difference in all domains of HRQoL was not observed in various treatment modalities of gastrointestinal cancer. Advanced-stage (stages III and IV) and co-morbidities were significant determinants of poor HRQoL. The overall HRQoL of gastrointestinal cancer patients was poor. Advanced-stage cancer and co-morbidities were significant determinants of poor HRQoL. Therefore, intensification of routine monitoring of the disease and the treatments should be actively implemented to improve the HRQoL.

혈액투석 환자의 신체상, 증상 경험이 삶의 질에 미치는 영향

The purpose of this study is to determine the effect of hemodialysis patients' body image and symptom experience on their quality of life. The data was targeted at patients who were diagnosed with end-stage renal failure at a tertiary general hospital located in J province and receiving regular hemodialysis treatment. The data collection period was from July 20, 2023 to August 11, 2023, and 160 structured questionnaires were distributed, of which 153 were used in the final analysis. Data were analyzed using t-test, One-way ANOVA, Pearson correlation coefficients and multiple regression analysis with the SPSS 28.0 program. Through multiple regression analysis, the factors influencing quality of life were body image (β=.46, p&lt;.001), having an average monthly household income (over 3 million won)(β=.22, p=.002), and symptom experience (β=-.20, p=.001). The combined explanatory power for quality of life was determined to be 47%. It is necessary to accurately assess and intervene, develop educational programs and integrated management programs that reduce symptom experience and improve body image, and establish work standard guidelines.

전업직장인의 상담학 학습경험에 관한 현상학적 연구

Objectives The purpose of this study is, on the one hand, to examine the experiences of individuals who are full-time employees and enrolled in the process of learning in counselor education, and on the other hand, to phenomenologically reveal the meaning behind their experiences.&#x0D; Methods Interviews were conducted on seven full-time employees who are in counseling graduate school for more than 3 semesters or within 1 year of graduation, and analyzed by Colaizzi's phenomenological research method. Participants consisted of those in their late 30s to early 50s who had more than 10 years of work experience and experienced vocational activities in different occupations from the counseling field. The data collection period was from September to December 2021, and after an in-depth interview of 90 to 120 minutes, additional interviews were conducted by phone or text message if necessary.&#x0D; Results As a result, 5 categories, 19 topic bundles, and 81 topics were derived. The five categories are as follows. ‘studying counseling to break away from current instability’, ‘making good changes during the counseling course of study’, ‘facing psychological difficulties arising from both occupation and academic affairs’, ‘maturing the mind through learning in counselor education’, and ‘running a life as an employee also doing in counseling job’. In conclusion, participants, with over 10 years of full-time work experience and a stable career will go to counseling, a new field, and the world of experience can be summarized as “growth through counseling studies upgrades professionalism in the current workplace and running a life as an employee also doing counseling job.”&#x0D; Conclusions The research results confirmed the experiences and meanings experienced in the course of learning in counselor education, and based on this, provided basic data for future related education and information provision.&#x0D;

Open Dataset for Testing of Visual SLAM Algorithms under Different Weather Conditions

Existing datasets for testing SLAM algorithms in outdoor environments are not suitable for assessing the influence of weather conditions on localization accuracy. Obtaining a suitable dataset from the real world is difficult due to the long data collection period and the inability to exclude dynamic environmental factors. Artificially generated datasets make it possible to bypass the described limitations, but up to date, researchers have not identified testing SLAM algorithms under different weather conditions as a stand-alone task, despite the fact that it is one of the main aspects of the difference between outdoor and indoor environments. This work presents a new open dataset that consists of 36 sequences of robot movement in an urban environment or rough terrain, in the form of images from a stereo camera and the ground truth position of the robot, collected at a frequency of 30 Hz. Movement within one area occurs along a fixed route; the sequences are distinguished only by whether conditions, which can make it possible to correctly assess the influence of weather phenomena on the accuracy of localization.

Surname order and revaccination intentions during the COVID-19 pandemic

Teachers in Japanese schools employ alphabetical surname lists that call students sooner, with surnames appearing early on these lists. We conducted Internet surveys nearly every month from March 2020 to September 2022 with the same participants, wherein we asked participants where the alphabetical columns of their childhood and adult surnames were located. We aimed to identify how surname order is important for the formation of noncognitive skills. During the data collection period, the COVID-19 vaccines became available; Japanese people could receive their third dose starting in December 2021. The 19th wave of the survey was conducted in January 2022. Therefore, to examine how a surname’s alphabetical order could influence intention to revaccinate, we used a subsample of data from December 2021 to September 2022. The major findings were as follows. Women with early surnames had an approximately 4% stronger likelihood of having such intentions than men with early surnames. Early name order was more strongly correlated with revaccination intention among women than among men. The surname effect for women was larger when a mixed-gender list was used compared with when it was not used. This effect was only observed for childhood surnames and not for adult surnames.

Intraoperative Normal Saline Administration and Acute Kidney Injury in Patients Undergoing Liver Transplantation

Normal saline is still used in patients undergoing living donor liver transplantation (LDLT) with normonatremia. We investigated whether the normal saline administered during LDLT is associated with the increased risk of acute kidney injury (AKI) compared with the balanced crystalloids. We reviewed 1011 cases undergoing LDLT. The primary exposure variable was normal saline administered intraoperatively compared with the balanced crystalloid. To compare the risk of AKI after adjusting for potential confounders of baseline characteristics and surgical parameters, a propensity score matching analysis was performed. As a sensitivity analysis, ordinal logistic regression analysis was performed for AKI using inverse probability of treatment weighting (IPTW). The incidence of AKI was significantly higher in the saline group (n = 88/174, 50.6%) than in the balanced group (n = 67/174, 38.5%) after matching (P = .010). The incidence of stage 2 or 3 AKI was also significantly higher in the saline group (n = 26/174, 14.9%) than in the balanced group (n = 43/174, 24.7%) after matching (P = .022). The length of hospital stay was significantly longer in the saline group than in the balanced group after matching. Ordinal logistic regression analysis using IPTW showed that the saline group showed a significant association of saline administration with the risk of AKI (odds ratio 1.23, 95% CI 1.05-1.28, P = .013). Our propensity score analysis using propensity score matching and IPTW showed that normal saline administration during LDLT is associated with a high risk of postoperative AKI and longer hospital stays. However, our results should be interpreted carefully due to the relatively long period of data collection.

Influences of communication ability, organizational intimacy, and trust among colleagues on job satisfaction of nurses in comprehensive nursing care service units.

Communication abilities, organizational intimacy, trust among colleagues, and job satisfaction of nurses in comprehensive nursing care service units are emphasized more than any other ward, and research on this is necessary. The study was to examine the influences of communication ability, organizational intimacy, and trust among colleagues on the job satisfaction of nurses in the comprehensive nursing care service units. This study used a cross-sectional descriptive design. The participants were 155 nurses caring for patients in the comprehensive nursing care service units in Seoul. Measures included the general characteristics of study participants, communication ability, organizational intimacy, trust among colleagues, and job satisfaction. The data were analyzed using the SPSS/WIN version 27.0 program. The data collection period was from August to September 2022. Factors influencing the job satisfaction of nurses at the comprehensive nursing care service units were organizational intimacy (β = 0.36), communication abilities (β = 0.26), trust among colleagues (β = 0.22), and the average number of patients assigned to a nurse (β = -0.19), which explained 67% of the variance. Organizational intimacy was the greatest factor influencing the job satisfaction of nurses in the comprehensive nursing care service units. To increase the job satisfaction of ward nurses working in the comprehensive nursing care service, securing manpower is required, and it is necessary to provide effective nursing care with an average number of patients of 5 or less. In particular, a systematic job training program is needed to increase organizational intimacy among team nurses.

Psychological Preparedness of Psychologists during the COVID-19 Emergency: Are There Any Individual Differences?

The COVID-19 outbreak has posed an unprecedented global challenge. However, despite the large amount of evidence on the psychological consequences of the pandemic, very few studies have focused on psychologists themselves. (1) Background: The present study aimed to characterise the professional and clinical profile of psychologists facing the COVID-19 outbreak and to investigate the relationship between psychological preparedness and a series of potential predictors (e.g., sociodemographic and professional variables and psychological distress). (2) Methods: A total of 1115 psychologists fully completed an online survey. The data collection period started with the first wave of the pandemic. Participants were asked to provide sociodemographic and professional data and to complete three questionnaires assessing psychological preparedness, worry, and anxiety symptoms. (3) Results: Descriptive results showed that the COVID-19 outbreak did not cause an interruption to the psychological practice of professionals (both in the public and in private sectors) and that psychologists accepted the introduction of technological devices within their regime of work in order to guarantee their service to clients. Only a minority of participants reported clinically significant levels of symptoms of anxiety and worry. Regression analyses revealed that being older, having taken part in training courses on the COVID-19 emergency, and experiencing lower levels of worry and anxiety were all significant predictors of both cognitive and affective psychological preparedness. (4) Conclusions: Taken together, these findings seem to highlight that specific factors can enhance psychological preparedness among psychologists. Therefore, it is vital to inform authorities about the importance of providing emergency programmes to train healthcare workers, especially psychologists, on how to develop psychological preparedness when facing the negative consequences of critical incidents at a universal level, given their crucial role in promoting mental health.