Frequency Of Usage Research Articles

Ride-Hailing vs. Fixed-Route: Preferences of the Transit-Dependent Populations in U.S. Urbanized Areas

Transportation inequality poses significant challenges in car-dependent cities in the US, especially for Transit-Dependent Populations (TDPs) who rely on public transportation to meet their travel requirements. Research indicates that despite the rapid growth of ride-hailing services like Uber, TDPs primarily depend on conventional transit options such as buses and metros. This study differentiates between two classifications of ride-hailing services: Private Ride-hailing (PRH), represented by platforms like Uber and Lyft, where individuals hire and pay for their rides, occasionally sharing the journey with guests; and ride-sharing (RS), like UberPool, which allows users to divide travel expenses. However, a more profound comprehension is necessary to clarify why TDPs show a preference for one mode of transportation over another and the factors that influence their decision-making. This study utilises Structural Equation Modelling (SEM) to examine the direct and indirect relationships between explanatory and outcome variables, while investigating modal preferences and usage frequency in 48 densely populated urban areas in the US (N = 384). TDPs choose to use transportation services like Uber because of their effectiveness in reducing both travel and waiting time, in contrast to traditional Fixed-Route Transit Services (FRTS), which are relatively less efficient. TDPs’ inclination towards PRH leads to a greater dependence on ride-hailing services, whereas a preference for FRTS reduces this dependence. Significantly, the study demonstrates that TDPs’ modal preferences are not only influenced by their socioeconomic status or rational decision-making, but also by the complex interaction between these factors. These findings provide valuable information for policymakers who want to evaluate the sustainability of ride-hailing services for TDPs and effectively tackle transportation inequalities.

Association of reductions in rescue medication requirements with vagus nerve stimulation: Results of long-term community collected data from a seizure diary app

ObjectiveTo assess the impact of vagus nerve stimulation (VNS) on quality of life contributors such as rescue medications. MethodsUsing the seizure diary application SeizureTracker™ database, we examined trends in rescue administration frequency before and after the first recorded VNS magnet swipe in patients with drug-resistant epilepsy who had 1) At least one VNS magnet swipe recorded in the diary, and 2) Recorded usage of a benzodiazepine rescue medication (RM) within 90 days prior to the first swipe. A paired Wilcoxon rank-sum test was used to assess changes in RM usage frequency between 30-, 60-, 90-, 180- and 360-day intervals beginning 30 days after first magnet swipe. Longitudinal changes in RM usage frequency were assessed with a generalized estimating equation model. ResultsWe analyzed data of 95 patients who met the inclusion criteria. Median baseline seizure frequency was 8.3 seizures per month, with median baseline rescue medication usage frequency of 2.1 administrations per month (SD 3.3). Significant reductions in rescue medication usage were observed in the 91 to 180 day interval after first VNS magnet swipe, and at 181 to 360 days and at 361 to 720 days, with the magnitude of reduction increasing over time. Decreases in rescue medication usage were sustained when controlling for patients who did not record rescue medication use after the first VNS magnet swipe (N=91). Significant predictors of reductions in rescue medication included baseline frequency of rescue medication usage and time after first VNS magnet swipe. SignificanceThis retrospective analysis suggests that usage of rescue medications is reduced following the start of VNS treatment in patients with epilepsy, and that the magnitude of reduction may progressively increase over time.

Rules of medication for leucorrhea in ancient books of traditional Chinese medicine based on latent structure model and association rules

Objective: To analyze syndrome differentiation and medication rules for leucorrhea in ancient books of traditional Chinese medicine (TCM) based on the “Chinese Medical Code” using the latent structure model. Methods: The formulations for leucorrhea were searched in the Chinese Medical Code (software), based on which an Excel sheet was created to conduct frequency analysis and construct a matrix of high-frequency medications. The high-frequency medications for leucorrhea were then analyzed using the Latent 5.0 software and a latent structure model. With SPSS Modeler and Latent 5.0 as the main analysis methods, Chinese medications with a frequency >1.00% were investigated using the latent structure model and association rules, and the medication rules in treating leucorrhea with TCM were dissected based on the data of frequency. Results: For 373 kinds of Chinese medicines retrieved from 236 TCM prescriptions, the total medication frequency was 2522. Chinese Angelica (Angelicae Sinensis Radix), White Peony Root (Paeoniae Radix Alba), Indian Buead Tuckahoe (Poria), Common Oyster Shell (Ostreae Concha), and Largehead Atractylodes Rhizome (Atractylodis Macrocephalae Rhizoma) were high-frequency medicines for leucorrhea. Tonic, heat-clearing, and qi-regulating medicines had a high frequency of usage. According to a formula-based analysis of the evidence, the main syndromes of leucorrhea included liver qi affecting the spleen pattern, damp heat accumulation pattern, liver qi stagnation pattern, liver-stomach disharmony pattern, yin deficiency of the liver and kidney pattern, and spleen deficiency with dampness pattern, which are generally in line with the etiology and pathogenesis of leucorrhea, namely pathogenic dampness as the detrimental factor together with spleen-kidney dysfunction. However, in ancient books, emphasis was laid out on the regulation of the liver. This study determined 31 association rules for treating leucorrhea, where the primary compatible medicines contained Chinese Angelica (Angelicae Sinensis Radix)-Nutgrass Galingale Rhizome (Cyperus rotundus), Chinese Angelica (Angelicae Sinensis Radix)-Szechwan Lovage Rhizome (Ligusticum chuanxiong Hort.), White Peony Root (Paeoniae Radix Alba)-Szechwan Lovage Rhizome (Ligusticum chuanxiong Hort.), White Peony Root (Paeoniae Radix Alba)-Adhesive Rehmannia Root Tuber (Rehmanniae Radix) and Tangerine Peel (Citri Reticulatae Pericarpium)-Ternate Pinellia (Rhizoma Pinelliae). Conclusion: The medication rules targeting leucorrhea in the Chinese Medical Code were mainly represented by the regulation of qi and blood, as well as the 3 internal organs—the kidney, spleen, and liver.

Evidence-Based Strategies for Warm Compress Therapy in Meibomian Gland Dysfunction.

Despite promising results from technological therapies like intense pulsed light application, warm compress therapy is a mainstay in meibomian gland dysfunction (MGD). However, applying warm compresses (WC) to the eyelids is palliative rather than curative and not always dispensed with specific instructions. The range of eyelid warming treatments available and lack of clear directives for use creates uncertainty for patients accustomed to explicit dosage information. This report examines data from clinical studies across the past 20years to identify effective protocols for three types of WC-hot towel, microwavable eye mask, and self-heating eye mask (EM). Literature search for studies on WC and MGD published between 2004 and 2023 in English was conducted. Studies wherein hot towel, microwavable EM, and self-heating EM were used in a treatment arm were included and those wherein they served only as control or were used in conjunction with another intervention were excluded. 20 resulting studies were separated into 3 groups: 5 on temperature profiles of WC, 6 with single application of WC, and 9 with repeated applications. Study methods and outcomes were tabulated, and a qualitative review was performed, attending to WC protocol and efficacy, as indicated by measures of tear film, meibomian gland health, and dry eye questionnaires. Data from the aforementioned studies revealed that each method can achieve target eyelid temperature of 40°C. A single application of WC-ranging from 5 to 20min-can significantly improve tear quality, while repeated applications significantly relieve symptoms associated with dry eyes from MGD and, in most studies, significantly improve meibomian gland health. Hot towels, however, require frequent reheating to maintain eyelid temperatures above 40°C, rendering them relatively ineffective in longitudinal studies. Microwavable EM retain heat well across 10min and were found to improve tear break-up time and/or meibomian gland score. Self-heating EM have variable activation times and were typically applied for longer periods, showing benefits akin to microwavable EM in short-term studies. Studies monitoring compliance indicate greater deviation from protocol with higher application frequencies or longer-term use. Evidence suggests superior heat retention and therapeutic effects on specific contributing factors in MGD (such as Demodex) with moist-heat compress. Considering decreased patience adherence to therapy with increased usage frequencies, and balancing needs to provide succinct instructions for various compress types, an advisable strategy is for patients to apply a moist-heat generating EM (microwavable or self-heating) to each eye for at least 10min, prepared according to manufacturer's instructions.

Qualitative and Quantitative Determination of Hydroquinone Content in Skin Whitening Cosmetics Sold in Lafia-Nigeria

Hydroquinone (HQ) is a whitening or therapeutic constituent in many cosmetic products, but only allowable at a very low concentration. The abuse of HQ via frequent and prolonged usage can lead to health issues such as damage to skin and the sensitive area on the face. In Nigeria, National Agency for Food and Drug Administration and Control (NAFDAC) on its cosmetic products prohibition of bleaching agents regulations 2019, stated that no cosmetic products should contain more than 2 % of HQ alone or 1 % in combination with other lightening ingredients. This study aimed at qualitative and quantitative determination of HQ content in selected skin whitening cosmetics sold in Lafia. A total of twenty-four (24) various skin bleaching cosmetics were sampled from Lafia modern market. Thin Layer Chromatography (TLC) and uv/visible spectrophotometry were used for qualitative (identification) and quantitative (quantitation) determination of their HQ concentration, respectively. Ethanol (96 %) was used to extract HQ, and then TLC analysis at two different laboratories. At the two laboratories,nine samples (same) out of 24 were found to contain hydroquinone. The uv/visible spectrophotometric analysis indicated that the concentration of hydroquinone ranged from 0.99 % to 1.47 % in the cosmetic products studied.This study revealed that some of the products were labelled free from HQ or not labelled, and yet contained HQ, unknown to the consumers. In general, percentage hydroquinone in all the samples was less than 2 % maximum permissible limit recommended by US FDA and NAFDAC.

Explainable artificial intelligence for investigating the effect of lifestyle factors on obesity

Obesity is a critical health issue associated with severe medical conditions. To enhance public health and well-being, early prediction of obesity risk is crucial. This study introduces an innovative approach to predicting obesity levels using explainable artificial intelligence, focusing on lifestyle factors rather than traditional BMI measures. Our best-performing machine learning model, free from BMI parameters, achieved 86.5% accuracy using the Random Forest algorithm. Explainability techniques, including SHAP, PDP and feature importance are employed to gain insights into lifestyle factors’ impact on obesity. Key findings indicate the importance of meal frequency and technology usage. This work demonstrates the significance of lifestyle factors in obesity risk and the power of model-agnostic methods to uncover these relationships.

A cross‐linguistic approach to investigating metacognitive regulation in writing among Chinese EFL learners: Insights for its trait/state distinction

AbstractMetacognitive regulation refers to learners’ ability to use a repertoire of metacognitive strategies to guide, observe, and manage thoughts, actions, and emotions in learning activities. It has been widely acknowledged as a significant predictor of language learning success, including writing. However, this line of research has been conducted in a single language context, and the interactions across L1 and L2 contexts have received insufficient scholarly attention. Situated in mainland China, we raise an innovative attempt to investigate metacognitive strategies in writing with a cross‐linguistic approach, thus illuminating the conceptualization of metacognitive regulation by testing its trait/state distinction. A group of 502 university students from different disciplinary majors were recruited to report their metacognitive strategy use in L1 and L2 task‐situated writing by filling in the assigned post‐task questionnaires. Multigroup confirmatory factor analysis (MGCFA) on the two questionnaire datasets provided empirical evidence for the cross‐language generalizability of metacognitive regulation in writing with the identified measurement invariance of the factor structure between L1 and L2 contexts, indicating its trait facet. However, the latent mean comparison results revealed that the actual usage frequency of metacognitive strategies scored significantly higher in L1 writing than in L2 writing, suggesting the state facet. These results are discussed extensively in this study to inform relevant theories and pedagogical activities.

Chinese character cognitive cards: Factors affecting Chinese characters using forgetting curves

Based on learning strategies, many children require increased accuracy in writing Chinese characters. To address this issue, Chinese character cognitive cards were introduced by the researchers, utilizing the Ebbinghaus forgetting curve (FC) to identify and analyze the factors influencing the retention of Chinese character memory. A questionnaire survey was conducted among 556 children aged 10 to 12 in China. In this study, the technology acceptance model (TAM) and the stimulus organ-response model (SOR) were used to study the factors affecting the intention and behavior of using Chinese character cognitive cards based on the function of the FC. The research also aimed to determine the relationship between the frequency of card usage and memory retention. Preliminary analysis indicated that repeated exposure to the cognitive cards significantly reduces the rate of forgetting. Additionally, the study examined the impact of the cognitive cards on different proficiency levels in Chinese character writing. The results show that the function of the FC in the Chinese character cognitive cards can make learners perceive the ease of use and usefulness of the Chinese character cognitive cards. The use of the FC positively influences Chinese character memory ability, and the influence is strong.

Who will be prosocial consumers? The relationship between environmental value and sustainable consumption

AbstractThis study explores who will be prosocial consumers based on the effect of consumers' environmental value on their sustainable consumption after the COVID‐19 lockdown. The study aims to examine (1) the relationship between environmental value and sustainable consumption and (2) compare the pathways between environmental value and sustainable consumption depending on delivery service usage frequency. This study unitizes Structural Equation Modeling to analyze (1) mediation and (2) multi‐group analysis by SmartPLS. Six hundred thirty‐seven respondents are collected from Mass Rapid Transit and Bangkok Mass Transit System stations in Bangkok and nearby shopping malls using a systematic random sample method. Affective and cognitive sustainable consumption mediates the relationship between consumers' egoistic and biospheric environmental concerns and their conative sustainable consumption. There is no significant difference between groups that utilize fewer or more delivery services on the path between environmental concerns and sustainable consumption. This study demonstrates that prosocial consumers with biospheric environmental concerns must engage in affective and cognitive sustainable consumption to engage in conative sustainable consumption. Prosocial consumers who emphasize the environment and sustainability tend to use delivery services less frequently.

Chemical Substance Exposure of Some Cleaning Workers in Korea: Focusing on Inhalation Exposure

This study aimed to prevent health damage caused by chemical exposure among cleaning workers who use cleaning agents and disinfectants in facility management and kitchen areas. We analyzed 5 years of measurement data (2016–2020) for cleaning workers across various industries in Korea, and conducted an exposure survey and health risk assessment for the two most frequently measured substances (i.e., 2-butoxyethanol and sodium hydroxide) and representative substances generated by their combined use (i.e., chlorine and chloroform). The findings indicate that when chlorine was generated by mixing hypochlorite-based disinfectants (e.g., bleach) with acidic cleaners containing substances such as nitric, hydrochloric, or citric acid, the risk index for chlorine gas (based on the 95th percentile exposure values) was 5.65 in the facility management cleaning industry, exceeding the acceptable threshold of 1. Because of the high usage and exposure frequency of cleaning and disinfecting agents and the common practice of mixing multiple products to enhance cleaning efficacy, it is necessary to manage hazardous risk factors by providing education on appropriate working methods, supplying personal protective equipment, and installing ventilation systems for these workers. Further research on the health risk assessment of combined chemical use is needed.

Fake video detection among secondary school students: The impact of sociocultural, media literacy and media use factors

The harmful political, economic and health effects of fake news on social media are well known. The present study examines the impact of two socio-cultural variables (political orientation and parents' educational attainment), one media literacy variable and two media use variables (news control, platform usage frequency and media addiction) on fake videos detection. The ability to detect fake videos among Hungarian secondary school students (N = 507) was assessed using a 16-item video test. The results of the online survey are partly consistent and partly contradictory to the literature. There is no gender difference in the ability to detect fake videos in the age group studied, and media literacy and media use do not influence the ability to detect fake videos. However, a more conservative worldview and higher parental education are associated with better detection of fake videos. The paper concludes with recommendations.

TripChain2RecDeepSurv: A novel framework to predict transit users’ lifecycle behavior status transitions for user management

Transit users’ lifecycle behavior pattern transition reflects the continuous and multi-phase changes in how frequently and regularly users utilize public transit over their lifetime. Predicting transit users’ lifecycle behavior pattern transition is vital for enhancing the efficiency and responsiveness of transportation systems. Thus, this study incorporates lifecycle analysis in predicting long-term sequential behavioral pattern transition processes to go beyond just examining user churning at a single point in time. Specifically, this study proposes the TripChain2RecDeepSurv, a novel model that pioneers the individual-level analysis of lifecycle behavior status transitions (LBST) within public transit systems. The TripChain2RecDeepSurv is composed of (1) the TripChain2Vec module for encoding transit users’ trip chains; (2) the self-attention Transformer module for exploring the latent features related to spatiotemporal patterns; (3) the recurrent deep survival analysis module for predicting LBSTs. We demonstrate TripChain2RecDeepSurv’s predictive performance for empirical analysis by employing Shenzhen Bus data. Our model achieves a 74.39% accuracy rate in churn determination and over 80% accuracy in status sequence identification on the churn path. In addition, our findings highlight the segmented nature of Kaplan-Meier curves and identify the optimal intervention time against the user churning process. Meanwhile, the proposed model provides individual-level heterogeneity analysis, which emphasizes the significance of customizing user engagement strategies, advocating for interventions that extend users’ engagement in patterns with high-frequency transit usage to curb the transition to less frequent travel usage.

Understanding shared bike usages toward metros with fewer physical road separations

Physical road separations are normally considered cyclist-friendly, but whether they are unfriendly to the combination of bike-share (BS) and metros is seldom investigated since they might affect the cycling’s flexibility and convenience to cross streets and reach the destination. Although integrating BS and metro is thought to mitigate traffic congestion, how traffic congestion affects the usage of integration remains unknown. This study, conducted in Suzhou, China, examines new factors (road separation and traffic congestion) alongside well-studied factors influencing BS and metro integration. The survey revealed increased BS usage frequency after a new metro’s opening. Variables such as road separations, traffic congestion information, road network density, and proximity to metros are considered. They are processed in a selected area considering cyclable network and Thiessen Polygon corresponding to the selected metro stations. An ordered probit model is established to investigate significant factors. It is found that as more columns of road separations exist, the cyclists are less likely to use BS towards metros, regardless of whether they are cycling weekends or weekdays. Interestingly, after the new metro opened and a new metro hub was formed, proximity to the new metro hub is associated with lower BS transfer demand. A higher congestion level promotes more cycling toward the metro system on weekdays as well as higher parking fees. This indicates that the combination of BS and metro could attract former motor vehicle users and this finding could be instructive for urban planners and road designers.

Regional Variability in MRI Scans with Different Magnetic Field Strengths in Japan: Implications for Healthcare Preparedness for Alzheimer's Disease Treatment.

(1) Background: The 2023 approval of lecanemab for early-stage Alzheimer's disease (AD) highlighted the need for routine 1.5T or 3.0T MRI scans to monitor amyloid-related imaging abnormalities (ARIAs). Regional disparities in MRI scan frequency, MRI scanner availability, and scanner magnetic field strengths could affect readiness for anti-amyloid therapy and lead to inconsistencies in ARIA detection nationwide. (2) Methods: We assessed regional variance in MRI scan frequency and field strength across Japan using the National Database (NDB) Open Data website, which summarizes Japanese public health insurance claims from the fiscal years (FYs) 2015 to 2021. We employed a mixed-effects model with prefecture-level random intercepts and slopes over time, subsequently categorizing prefectures into clusters based on MRI usage. (3) Results: 1.5T MRI was the most common magnetic field strength, remaining stable from FY2015 to FY2021. 3.0T MRI usage slightly increased, although the COVID-19 pandemic in FY2020 led to a maximum reduction of 5%. Prefecture-level variance was higher for 3.0T MRIs, with more frequent usage in western Japan. (4) Conclusions: This study highlights prefecture-level variance in MRI usage across Japan. The insights gained could be instrumental in improving healthcare preparedness for anti-amyloid treatment and patient management.

Awareness Regarding Clear Aligner Disposal Among Orthodontists and General Dentists: A Cross-sectional Survey-based Study

Aim and Objective: To assess the awareness of clear aligner disposal among orthodontists and general dentists. Materials and Methods: A cross-sectional electronic survey (e-survey) was developed based on the use of Google Forms. The survey link was randomly disseminated across social media platforms consisting of orthodontists and general dentists. The responses were subsequently tabulated and analyzed using statistical analysis with the help of Statistical Product and Services Solution software version 23.0. The survey comprised questions consisting of demographics, frequency of usage of clear aligners, and awareness on disposal of clear aligners. Results: The survey gathered responses from 760 participants, including 374 orthodontists and 384 general dentists from the 1,000 dentists and orthodontists who were surveyed, revealing trends in clear aligner usage, disposal practices, and awareness. Orthodontists showed higher frequency and safer disposal practices. A knowledge gap exists among dental practitioners regarding biodegradation characteristics and disposal regulations. Both groups express a shared interest in environmentally responsible practices, emphasizing the necessity for education and comprehensive guidelines from aligner companies to mitigate environmental impact. Conclusion: Clear aligners are popular in orthodontic treatment which contributes to environmental concerns due to improper disposal. The study explored clear aligner disposal practices among general dentists and orthodontists. The study underscores the need for increased awareness among orthodontists and general dentists, emphasizing proper clear aligner disposal methods and the importance of comprehensive instructions from aligner companies.

Adoption of Artificial Intelligence Chatbot Technology in Academic Activities of Jakarta Students: Ease of Use

Artificial Intelligence (AI) Chatbot technology has garnered significant attention recently as an innovative solution for various needs, from learning to counseling. However, its adoption among university students remains a crucial research area. This study aims to understand the usage patterns of university students in Jakarta regarding Chatbot technology, focusing on usage frequency, ease of use, and factors influencing adoption. Conducted from March to May 2024, the research involved 100 students from various Jakarta universities, selected through convenience sampling to capture diverse characteristics. Data collection methods included document studies and questionnaires. The analysis identified the level of Chatbot technology adoption among Jakarta students and the factors influencing it. Results indicate a high frequency of Chatbot use, with perceived usefulness, ease of use, and comfort being the primary drivers of adoption and positive attitudes toward this technology. This study provides significant insights for companies developing Chatbot technology, offering an in-depth understanding of students' preferences and behaviors. These insights can guide companies in creating more effective marketing strategies and enhancing Chatbot design and functionality to be more user-friendly and aligned with user expectations, thereby increasing adoption rates and user satisfaction.

Affective, semantic, frequency, and descriptive norms for 107 face emojis

We introduce a novel dataset of affective, semantic, and descriptive norms for all facial emojis at the point of data collection. We gathered and examined subjective ratings of emojis from 138 German speakers along five essential dimensions: valence, arousal, familiarity, clarity, and visual complexity. Additionally, we provide absolute frequency counts of emoji use, drawn from an extensive Twitter corpus, as well as a much smaller WhatsApp database. Our results replicate the well-established quadratic relationship between arousal and valence of lexical items, also known for words. We also report associations among the variables: for example, the subjective familiarity of an emoji is strongly correlated with its usage frequency, and positively associated with its emotional valence and clarity of meaning. We establish the meanings associated with face emojis, by asking participants for up to three descriptions for each emoji. Using this linguistic data, we computed vector embeddings for each emoji, enabling an exploration of their distribution within the semantic space. Our description-based emoji vector embeddings not only capture typical meaning components of emojis, such as their valence, but also surpass simple definitions and direct emoji2vec models in reflecting the semantic relationship between emojis and words. Our dataset stands out due to its robust reliability and validity. This new semantic norm for face emojis impacts the future design of highly controlled experiments focused on the cognitive processing of emojis, their lexical representation, and their linguistic properties.

Evaluation of a data-driven youngstock rearing quality system in Dutch dairy herds (2019–2022)

In recent years, the Netherlands exhibited an increased focus on improving youngstock rearing. Several data-driven tools were developed to assess and benchmark calf rearing practices based on key indicators, stimulate farmers to improve their youngstock rearing and reduce calf mortality. KalfOK is such a data-driven tool in which a farm-level overview with 15 indicators of youngstock rearing quality is communicated to participating farmers. In this study we assessed which farm characteristics are associated with A) a continuously high or low KalfOK score and B) frequent usage of KalfOK. Data from KalfOK and the identification and registration system were available for all participating herds over a period between 2019 and 2022 (Dataset A). Additionally, a sample of 324 dairy farmers, randomly selected from the entire Dutch dairy population (Dataset B), participated in a voluntary survey. Multivariable (logistic) regression models were used to A) identify differences in characteristics between farms with a continuously high- and farms with a continuously low KalfOK score and B) assess which farm characteristics were associated with frequent use of the KalfOK report. The results of analysis A showed multiple factors associated with having a low or high KalfOK score, including replacement rate, closed farming system, limited growth in herd size and the region where a farm was located. Sociological factors might also partly explain the difference between high and low scoring farms. Analysis B showed that approximately half of the surveyed farmers indicated that they do not frequently use their KalfOK overview in their calf rearing management. The KalfOK score of farmers who regularly use their KalfOK report was higher – and consequently better - compared to the KalfOK score of farmers who sometimes or never use KalfOK. Additionally, farmers using a milk robot and those discussing KalfOK regularly with their veterinarian, used KalfOK more often. Thirty four percent of the surveyed farmers made adjustments to their youngstock rearing management since the start of participation. The study’s insights into patterns in KalfOK utilization and associations with farm characteristics provide valuable information for ongoing efforts to enhance calf rearing practices via the use of KalfOK. It is important to consider what is needed to convince farmers that do not use the KalfOK tool to frequently start using their KalfOK report. Future research incorporating sociological aspects can provide a more comprehensive understanding of other dynamics influencing calf rearing and contribute valuable insights for enhancing the effectiveness of programs like KalfOK in promoting calf health and welfare.

Profiling vaccine hesitancy in nursing to tailor public healthcare policies: A cross-sectional international study.

Vaccine hesitancy is a complex issue of global concern. As nurses play a vital role in delivering patient care and shaping public opinions on vaccines, interventions to address vaccine hesitancy in nursing are imperative. As such, identifying profiles of characteristics and attitudes contributing to hesitancy may help identify specific areas of focus to target tailored global vaccination uptake campaigns. The purpose of this study was to profile the characteristics and attitudes contributing to hesitancy toward COVID-19 and Influenza vaccines in the nursing community. This multisite, cross-sectional study recruited 1967 registered nurses and 1230 nursing students from the United Kingdom, Finland, and Italy between March and September 2023. Data collection involved an online survey adopting the Vaccination Attitudes Examination (VAX) Scale, the Bergen Social Media Addiction Scale, and questions pertaining to sociodemographic and occupational characteristics. A k-means cluster analysis was used to identify various clusters of hesitancy based on the VAX Scale. One-way ANOVA and chi-square tests were used to identify significant differences in sociodemographic characteristics, occupational factors, vaccination attitudes, and social media usage between the clusters. Three distinct clusters were identified. Profile A showed high vaccine confidence, profile B displayed slight hesitancy, and profile C reported high levels of hesitancy. In profile C, higher levels of vaccine hesitancy were identified in younger, less experienced nurses with lower educational attainment. While older nurses with higher educational attainment, who were in senior roles, were more vaccine-confident and had a consistent history of accepting the Influenza and COVID-19 vaccinations (profile A). The study found Italian nurses highly hesitant (profile C), British nurses highly confident (profile A), and Finnish nurses evenly distributed between confident, slightly hesitant, and highly hesitant (profiles A, B, and C, respectively). In addition, more frequent usage of Instagram and TikTok was associated with vaccine hesitancy (profiles B and C), and LinkedIn and X were more common among vaccine-confident individuals (profile A). This study has identified specific sociodemographic and occupational factors that are related to vaccine hesitancy in an international sample of nurses. Additionally, attitudes contributing to hesitancy were identified, with worries about unforeseen future effects of the vaccine being identified as a critical attitude that may undermine confidence and increase hesitancy in nursing. This study also sheds light on the influence that social media platforms have on vaccine hesitancy and, as such, indicates which platforms are effective to disseminate vaccination campaigns to global nursing communities. Global vaccination campaigns should focus on specific profiles and clusters to promote vaccination in the international nursing community. Empowering nurses early in their careers will help to instill positive vaccination behaviors, ensuring a sustained uptake of vaccinations throughout the individual's career and beyond, with an impact on promoting vaccination at the public health level as well.

Designing a Real-Time DataLogger Using the Internet of Things for a Basic Imple Home Kwh Meter Capable of 1300 VA

Researchers want to make a kWh meter monitoring tool with estimated usage costs so that the tools made can help people to minimize costs in electricity usage. The purpose of this research is the creation of an IoT-based kWh meter monitoring tool that has the ability to read current, voltage, frequency, power factor and power usage that flows and shows the use of costs that have been used in real time with the display results on the LCD and also on the user's smartphone. In the reading results of usage costs (Rp) on the tool and PLN there is also a difference of Rp. 12,000, where the reading results on the tool are also lower than the results of the payment slip provided by PLN. The cost reading error rate on the tool is 4.4% with a reading accuracy rate of 95.6%.