Exploring pre-pandemic patterns of vaccine decision-making with the 5C model: results from representative surveys in 2016 and 2018.

BACKGROUND: The 5C psychological antecedents of vaccination (Confidence, Complacency, Constraints, Calculation, and Collective Responsibility) facilitate understanding vaccination decisions in specific target groups as well as the general public's informational needs. This study aims to explain pre-pandemic vaccination behaviour (a) in general, (b) for specific vaccines such as influenza, and (c) for certain target groups (e.g. people over the age of 59 years, parents, healthcare workers), using the 5C model and sociodemographic variables. The intention to get an influenza vaccination was also analysed for target groups. METHODS: The 5C, self-reported vaccination behaviour and the intention to vaccinate were collected in two representative telephone surveys in Germany - one in 2016 (n1 = 5,012) and another in 2018 (n2 = 5,054). Parents, people over the age of 59 years, chronically ill people, people with a migratory background, pregnant women and healthcare workers were target groups. RESULTS: Overall, the 5C model had higher explanatory power than sociodemographic variables. The pattern of vaccine hesitancy slightly differed between vaccinations and target groups. Confidence in safety and effectiveness was always a significant predictor. Complacency (the underestimation of disease risks) and Constraints were significant predictors as well. Calculation (of risks and benefits) was important for influenza vaccination intentions. CONCLUSIONS: This work builds an important benchmark for understanding potential changes in vaccine acceptance due to the pandemic. The benchmark can be used in research on potential effects of the pandemic on vaccination behaviours. Intervention designers can also use the results to understand specific audiences and their vaccination decisions.

Body Composition in Youths Aged 10‒17 Years by Deuterium Oxide Dilution, Air Displacement Plethysmography, and DXA: Validation of the Medical Body Composition Analyzer Bioimpedance Device by a 4-Compartment Model.

BACKGROUND: The medical body composition analyzer (mBCA) incorporates advances in multifrequency technology and has been validated using a 4-compartment (4C) model in adults but not in youths aged <18 y. OBJECTIVES: This study aimed to formulate a 4C model based on 3 reference methods and develop and validate a body composition prediction equation for the mBCA in youths aged 10‒17 y. METHODS: The body density of 60 female and male youths was measured by air displacement plethysmography, total body water by deuterium oxide dilution, and BMC by DXA. Data from the equation group (n = 30) were used to formulate a 4C model. The all-possible-regressions method was used to select variables. The model was validated in a second cohort (n = 30) in a random split design. The accuracy, precision, and potential bias were evaluated by the Bland and Altman procedure. RESULTS: Mean age, weight (W), height (H), waist circumference, and z-score of BMI were 13.6 ± 2.3 y, 54.5 ± 15.5 kg, 156 ± 11.9 cm, 75.5 ± 10.9 cm, and 0.70 ± 1.32 z, respectively. The prediction equation was as follows: FFM in kg (FFMkg) = ([0.2081] ∗ [W] + [0.8814] ∗ [H2cm/RΩ] + [0.2055 ∗ XcΩ])-15.343; R2 = 0.96; standardized root-mean-square error (SRMSE) = 2.18 kg. FFM did not differ between the 4C method (38.9 ± 12.0 kg) and the mBCA (38.4 ± 11.4 kg) (P > 0.05). The relationship between these 2 variables did not deviate from the identity line, was not significantly different from 0, and the slope was not significantly different from 1.0. In the precision prediction model of mBCA, the R2 value was 0.98 and SRMSE was 2.1. No significant bias was found when regressing differences between methods and their means (P = 0.08). CONCLUSIONS: The equation for the mBCA was accurate, precise, had no significant bias, had substantial strength of agreement and could be used in this age group when subjects were preferentially within the constraints of a specified body size.

Estimation of Hydration and Density of Fat-Free Mass in Indian Children Using a 4-Compartment Model: Implications for the Estimation of Body Composition Using 2-Compartment Models.

BACKGROUND: Accurate methods are needed to measure body fat mass (FM), particularly in South Asian children who are thought to have greater adiposity for a given body size. The accuracy of simple 2-compartment (2C) models of measuring FM depends on the primary measurement of the fat free mass (FFM) and the validity of assumed constants for FFM hydration and density. These have not been measured in this particular ethnic group. OBJECTIVES: To measure FFM hydration and density in South Indian children using a 4-compartment (4C) model and to compare FM estimates from this 4C-model with 2C-model-based estimates from hydrometry and densitometry, using literature-reported FFM hydration and density in children. METHODS: This study included 299 children (45% boys), aged 6-16 y from Bengaluru, India. Total body water (TBW), bone mineral content (BMC), and body volume were measured using deuterium dilution, dual-energy X-ray absorptiometry, and air displacement plethysmography, respectively, to calculate the FFM hydration and density, and the FM using 4C and 2C models. The agreement between FM estimates from 2C and 4C models was also evaluated. RESULTS: Mean FFM hydration and density were 74.2% ± 2.1% and 71.4% ± 2.0% and 1.095 ± 0.008 kg/L and 1.105 ± 0.008 kg/L in boys and girls respectively, which were significantly different from published values. Using the presently estimated constants, the mean hydrometry-based FM (as % body weight) estimates decreased by 3.5% but increased by 5.2% for densitometry-based 2C methods. When 2C-FM (using previously reported FFM hydration and density) were compared with 4C-FM estimates, the mean difference was -1.1 ± 0.9 kg for hydrometry and 1.6 ± 1.1 kg for densitometry. CONCLUSIONS: Previously published constants of hydration and density of FFM may induce errors of -12% to +17% in FM (kg) when using different 2C models in comparison to the 4C models in Indian children. J Nutr 20xx;x:xx.

Doubt in store: vaccine hesitancy among grocery workers during the COVID-19 pandemic.

The objective of this study was to assess the influence of workplace safety conditions alongside the World Health Organization's model of the "3 Cs", on grocery store workers' vaccine hesitancy concerning COVID-19. Data for this study come from the Arizona Frontline Workers Survey, a longitudin web-based survey of 770 grocery store workers in the state of Arizona (US) collected in July 2020 and January 2021. We utilized ordinary least squares and multinomial logistic regression analyses to assess predictors of hesitancy at our Wave 2. Thirty-nine percent of our sample reported being unlikely to get vaccinated against COVID-19. Two aspects of the "3 Cs" model, confidence and convenience, were correlated with lower levels of vaccine hesitancy while the perceptions of being protected by one's employer increased hesitancy. Our findings underscore the importance of workplace conditions for vaccine hesitancy and the need to include vaccine messaging in employers' safety practices.

A study comparing the WHO C-Model caesarean section rates and observed caesarean section rates at Port Moresby General Hospital, Papua New Guinea.

BACKGROUND: Worldwide, there is an increase in caesarean deliveries. Ideal caesarean section (CS) rates continue to be a matter for debate. The World Health Organization (WHO) C-Model, is a mathematical modelling tool to assist health facilities estimate expected CS rates based on the quality middle income facilities practice. AIM: To compare WHO C-Model derived CS rates with actual CS rates at Port Moresby General Hospital. MATERIALS AND METHODS: Clinical and obstetric data for women who delivered during a four months period was used to calculate CS probability using the WHO C-Model online calculator. Comparisons of CS rates were made for the entire cohort, as well as for each Robson Classification group to assess whether there was either 'under' or 'overusage' of CS according to the C-Model estimates. RESULTS: The actual CS rate of 5.5% (246/4437) was lower than the mean C-Model rate of 8%. The C-Model rate equates to an almost 45% increase in CS rates or an additional 111 caesarean deliveries be done during the four months study period. CONCLUSION: The WHO C-Model had good predictability among most of the low-risk Robson groups that accounted for just over 80% of the study population. The suggested additional 111 caesarean deliveries needed to be performed among high-risk Robson groups represented 15% of the study population. Local hospital protocols pertaining to management of both low- and high-risk cases are credited for keeping CS rates to a minimum. A lower threshold for CS in Robson groups two and four could have led to better perinatal outcomes.

Explaining the intention to get vaccinated against COVID-19: General attitudes towards vaccination and predictors from health behavior theories.

The goal of our study was to examine the intention to get vaccinated using predictors from the 5C Model of vaccination attitudes, the Theory of Planned Behavior (TPB) and the Health Belief Model (HBM). Between August and November 2020, an online survey was delivered to 1428 participants in the UK and Germany (mean age = 40.6; 57% women), assessing socio-demographic and health factors, general vaccination attitudes, TBP and HBM variables, and COVID-19 vaccination intention. Vaccination intentions did not differ by country or survey period. Predictors of intention with the highest explanatory power in a relative weight analysis were confidence, collective responsibility (5C) perceived behavioral control, social norms, attitudes (especially negative affect & TPB cognitions), and perceived benefits (HBM). Women reported lower intention, although the effect size was small. Predictors from the TPB and HBM were effective to explain the intention to receive COVID-19 vaccines over and above socio-demographic variables, health-related factors and general vaccination attitudes. The results are interpreted in the context of current vaccination campaigns. Messages promoting sense of autonomy and control over the decision to get vaccinated, approval from significant others and reassurance that getting vaccinated will not be associated with fear or other negative feelings are important facilitators of vaccine uptake.

The Psychological Antecedents to COVID-19 Vaccination among Community Pharmacists in Khartoum State, Sudan.

Background and Objectives: Little is known regarding the 5C psychological antecedents to COVID-19 vaccination among pharmacists in low- and middle-income countries. This study aimed to assess the acceptance of COVID-19 vaccination and its psychological antecedents among community pharmacists in Khartoum State, Sudan. Materials and Methods: A cross-sectional study was conducted from July to September 2022. A self-administered questionnaire was used to collect data about sociodemographic and health status characteristics, vaccine acceptance, and the 5C psychological antecedents to vaccination. Stepwise logistic regression analysis was conducted, and results were presented using odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). Results: A total of 382 community pharmacists participated in the current study, with a mean age of 30.4 ± 5.6 years. Nearly two-thirds of the participants (65.4%) were females, and the majority (74.9%) have received or intended to receive the COVID-19 vaccination. Vaccine acceptance was significantly associated with the following psychological antecedents to vaccination: confidence, complacency, constraints, and calculation (p < 0.001). Results of the logistic regression showed that confidence in vaccines [OR = 6.82 (95% CI = 3.14-14.80)], conspiracy beliefs [OR = 0.44 (95% CI = 0.23-0.85)], and constraints to vaccination [OR = 0.18 (95% CI = 0.06-0.56)] were the significant determinants of vaccine acceptance. Conclusion: The study revealed important predictors of COVID-19 vaccine acceptance that can be used to guide policymakers in designing target-oriented interventions that can improve the vaccine acceptance rate among community pharmacists in Sudan. These findings suggest that interventions to promote vaccine acceptance among pharmacists should focus on building confidence in vaccines and providing accurate information about the safety and efficacy of the COVID-19 vaccine, and reducing constraints to vaccination.

Antecedent, behaviour, and consequence (a-b-c) of deploying the contact tracing app in response to COVID-19: Evidence from Europe.

In response to the current coronavirus (COVID-19) pandemic, countries have or intend to deploy contact tracing apps as a way of containing and or reducing the community spread of the virus. Whilst a few studies have so far been conducted on the acceptability of the app, little is known about the antecedent, behaviour, and consequence (a-b-c) of deploying the app and its success thereof. This study, therefore, proposes and validates an integrated a-b-c and technology acceptance model of deploying the contract tracing app in four European countries. The study adopts a quantitative approach and uses publicly available cross country survey data from the Center for Open Science. An extract of 2512 data is analysed using SEM-PLS. The results confirmed the integrated a-b-c and technology acceptance model that underpins the study and revealed that the chance of achieving a positive outcome with citizens complying with recommendations of the app was only 17.1 % or R2 = 0.171 (±0.020) whilst the chance of negative consequent or deviant response of uninstallation of the app by the citizens was 54.3 % or R2 = 0.543 (±0.021). The results have huge implications for governments and public health institutions in their attempt to deploy the contract tracing app.

Study on Spatial and Temporal Characteristics of Surface Albedo at the Northern Edge of the Badain Jaran Desert Based on C + STNLFFM Model.

Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model.

Accuracy and uncertainty analysis of staple food crop modelling by the process-based Agro-C model.

Accuracy analysis of a process-based model is important for evaluating the reliability of model estimates of crop growth. Uncertainties in projections of crop growth may derive from different sources in modelling. The parameter-induced uncertainty is one of the important aspects. Here we calibrated the parameters for rice, wheat and maize combined with observed data of aboveground biomass (AGB) and leaf area index (LAI) at 16 Chinese Ecosystem Research Network (CERN) sites under different rotation systems and subsequently validated the model at these sites using the data independent of calibration. The results showed that the simulated AGB and LAI exhibited good agreement with the observations. The model performance for rice and maize was better than that for wheat. The statistical analysis of model performance showed that the RMSE (root mean square error), RMD (relative mean deviation) and EF (model efficiency) were 32.52%, - 0.95% and 0.87 of the means, respectively. The three components of the modelling uncertainty, bias of mean (UM), bias of slope (UR) and random residue (UE) accounted 0.1%, 0.9% and 99% of the total errors, respectively. The main contributor to the error was the random disturbances, indicating that the parameters calibration in this study had reached relatively reasonable conditions on the whole. Although the model displayed an overall good prediction in crops AGBs and LAI, there were still notable bias at some sites due to non-random errors (UM and UR). This indicated that there were still uncertainties in the modelling procedure, e.g. the model mechanism or parameterization. The uncertainty of the simulated results may greatly restrict the application of a model. To effectively and reasonably apply a model, it is necessary to evaluate and analyse the main sources of uncertainty in the simulated results. The parameter-induced uncertainty analysis in this study showed that, at the site scale, the range of uncertainty brought by the changes in three parameters (SLA, PL and α) to the modelling results (95% CI) of Agro-C covered more than 90% of the observations and brought approximately 21% uncertainty to the simulated AGBs of the three major crops.

Curcumin: A promising treatment for Cryptosporidium parvum infection in immunosuppressed BALB/c mice.

Members of the genus Cryptosporidium are frequent protozoan pathogens in humans and a wide range of animals. There is no consistently effective treatment against cryptosporidiosis, especially in immunodeficient patients. The present study was carried out to study the therapeutic effects of curcumin against cryptosporidiosis in immunosuppressed BALB/c mice. Mice were divided into five groups and immunosuppressed by dexamethasone. Three groups were inoculated with C. parvum oocysts, administered with curcumin, paromomycin, and without treatment. The reminders were regarded as controls. The oocysts in the fecal smear were counted daily. At days 0, 3, 7, and 11 post-treatment, the mice were sacrificed, and the efficacy of drugs was evaluated by comparing the histopathological alterations in jejunum and ileum, measuring the total antioxidant capacity, and malondialdehyde in the affected tissues. The infection was completely eliminated in the curcumin-treated group, and oocyst shedding stopped with no recurrence after drug withdrawal. On the contrary, paromomycin was unable to eliminate C. parvum infection completely, and oocyst shedding continued even 10 days after the drug withdrawal. Based on these findings, curcumin can be a trustworthy compound for the elimination of infection in immunosuppressed hosts. Further evaluation to find its accurate mechanism of action should be considered.

A full-scale comparison of two hybrid constructed wetlands treating domestic wastewater in Pakistan.

Objective of the current work was to monitor the year-round response of full-scale hybrid constructed-wetlands (CWs) treating domestic wastewater under variable continuous flow. Two systems were evaluated: system-I consisted of an anaerobic baffled reactor (ABR) followed by a saturated vertical subsurface-flow (VSSF) CW and a free-water-surface (FWS) CW as a tertiary treatment; system-II consisted of an ABR followed by a horizontal subsurface-flow (HSSF) CW and FWS. Maximum reduction of 80 and 78%, 81 and 82%, 63 and 69%, 79 and 89% for chemical oxygen demand (COD), biological oxygen demand (BOD), total kjeldahl nitrogen (TKN) and total suspended solids (TSS) was achieved in Systems I and II respectively. There was also effective removal (94% and 93%) of the bacterial population in both systems while more than 94% of pathogenic microorganisms were removed. Data from both systems were further used to compute the first-order rate constants for the k-C* model commonly used in CW design. The treatment performance was confirmed to follow a first-order reaction rate, in which the k20 values of chemical oxygen demand (COD), biological oxygen demand (BOD), total kjeldahl nitrogen (TKN), total phosphorus (TP) and total suspended solids were calculated as 165, 117, 133, 7.5 and 78 m yr-1 respectively for VSSF and 226, 134, 199, 22 and 73 m yr-1 respectively for HSSF. A positive correlation with temperature was discovered for all parameters in both systems.

Exploring hydrological controls on dissolved organic carbon export dynamics in a typical flash flood catchment using a process-based model.

The dynamics of dissolved organic carbon (DOC) export from headwater catchments are of critical importance for the global carbon balance and are driven by complex runoff processes. Most previous studies have used statistical relationships between runoff and DOC concentration to estimate DOC export dynamics. Thus, the coupling mechanisms between runoff generation and DOC export dynamics at the process level were obscured in the fitting parameters and have rarely been addressed. In this study, high-frequency (hourly) discharge and DOC export from a typical flash flood experimental headwater catchment with an area of 1.8 km2 were simulated using a process-based model (INCA-C). The results showed that the INCA-C model successfully captured the hourly dynamics of both discharge and DOC concentrations with a Nash-Sutcliffe efficiency (NSE) of 0.47-0.81 and 0.28-0.70 among moderate events and 0.81-0.85 and 0.19-0.90 among extreme events, respectively. The DOC was exported with distinct concentration dynamics, fluxes, and contributions from the four flow pathways under different storm intensities. At higher intensities, the DOC fluxes were exported by subsurface flows, particularly from shallow organic soil, with greater peaks and shorter time-to-peaks. Exported DOC is primarily sourced from subsurface runoff from the mineral layer (73 %-77 %) during moderate events, whereas it is primarily sourced from subsurface runoff from the organic layer (61 %-79 %) during extreme events. The two contrasting contributions suggest that hydrological pathway controls and DOC dynamic patterns can shift owing to runoff generation influenced by storm intensity. The distinct and variable controls of different flow pathways on DOC export highlight the need to explain the role of hydrology in regulating DOC storm exports through process-based modelling.

Determination of Material and Fracture Properties of a Case-Hardened Planet Gear and Its Homogenisation Method to Obtain the Damage Mechanism Caused by Fragment Ingestion.

Before a new type of engine is introduced into civil aviation, it must comply with various safety regulations. These regulations include the analysis of secondary damage caused by the re-ingestion of a tooth fragment. The purpose is to prevent crack propagation through the gear rim, which would lead to catastrophic failure. In this context, identification of the initial crack location is crucial to determine the crack propagation path. Therefore, this paper presents a technique to determine and validate a constitutive material model and fracture locus for case-hardened spur gears. As the modelling of the surface-hardened layer is computationally intensive, it is necessary to homogenise the model. This paper comprehensively reviews and discusses the associated effects and errors. To determine the plastic behaviour of the case-hardened external gear (30CrNiMo8) and the nitrided internal gear (35CrAlNi7-10), the widely acknowledged Johnson-Cook material model is implemented using compression and Vickers indenter tests to define the necessary parameters. The fracture locus implementation is also based on the Johnson-Cook method and an axial shift of the fracture locus based on the hardness profile of the spur gears is determined by quasi-static pulsator tests. For validation, a project-specific gearbox test rig is used, enabling consistent ingestion of defined fragments. In addition, to check the likelihood of a tooth flank crack and to validate the results, a simplified ingestion experiment is performed.

Factors associated with HPV vaccine hesitancy among college students: A cross-sectional survey based on 3Cs and structural equation model in China.

Despite the high effectiveness of HPV vaccines in preventing infection, vaccine hesitancy remains a concern, particularly in China. This study aimed to explore college students' attitudes toward HPV vaccination and identify associated factors. Data was collected through a cross-sectional survey using self-administered questionnaires in four cities from May to June 2022. Chi-square tests and logistic regression analyses were conducted to identify factors. Additionally, an integrated structural equation model (SEM) based on the 3Cs (confidence, convenience, complacency) was developed to understand underlying factors contributing to hesitancy. The results from 2261 valid questionnaires were enlightening. A significant 89.47% (59.4% for females) considered HPV vaccination necessary, with 9.82% remaining neutral and only 0.71% deeming it unnecessary. Factors like higher education, being a medical student, residing in urban areas, having medical insurance, more extraordinary living expenses, a family history of tumors, and a solid understanding of HPV played a role in perceiving the vaccine as necessary. Among the 1438 female respondents, 84.36% had no hesitancy toward HPV vaccination, 13.53% expressed hesitancy, and 2.11% refused vaccination. Factors like age, understanding of HPV, medical staff recommendations, living expenses, and family history influenced hesitancy levels. SEM revealed that the 3Cs significantly affected vaccine hesitancy. Factors like price, booking process, vaccination times, trust in vaccines, medical staff recommendations, efficiency, and risk perception collectively influenced hesitancy. In conclusion, this study found high acceptance of HPV vaccination but acknowledged the complexity of hesitancy factors. It recommends medical staff disseminate scientific knowledge, offer recommendations, simplify booking procedures, and expand vaccination sites to address vaccine hesitancy effectively.

Investigating the effects of climate change and anthropogenic activities on SOC storage and cumulative CO2 emissions in forest soils across altitudinal gradients using the century model.

This study investigated the impact of climate change, grazing, manure application, and liming on soil organic carbon (SOC) stock and cumulative carbon dioxide (CO2) emissions in forest soils across different altitudes. Despite similar soil texture, acidity, and salinity across elevations, SOC stock significantly increased with altitude due to cooler temperatures and higher precipitation. The highest SOC stock (97.46 t ha-1) was observed at 2000-2500 m, compared to the lowest (44.23 t ha-1) at 500-1000 m. The Century C Model accurately predicted SOC stock, with correlation and determination coefficients exceeding 0.98. A climate change scenario projecting decreased precipitation (2.15 mm per decade) and increased temperature (0.4 °C) revealed potential SOC stock losses ranging from 28.36 to 36.35 %, particularly at higher altitudes. Grazing further decreased SOC stock, with a more pronounced effect at higher elevations. However, manure application (40 t ha-1 every four years) and liming (7-10 t ha-1 every three years) had positive effects on SOC stock, again amplified at higher altitudes and with an increase in lime application rate. In scenarios combining climate change with manure application and climate change with liming, manure application and liming mitigated some negative impacts of climate change, but could not fully offset them, resulting in 1.49-5.42 % and 0.39-4.07 % decreases respectively. Simulations of cumulative CO2 emissions mirrored the distribution of SOC stock, with higher emissions observed at higher altitudes and with management practices that increased SOC stock. This study emphasizes the critical role of conserving high-altitude forest soils and implementing optimal forest management strategies to combat climate change by minimizing SOC losses.

Understanding COVID-19 vaccination decisions during pregnancy and while breastfeeding in a Canadian province.

BACKGROUND: Vaccination in pregnancy is important for preventing illness for mothers and babies; however, vaccine uptake in pregnant individuals is lower than non-pregnant females of fertile age. Given the devastating effects of COVID-19 and the increased morbidity and mortality risk for pregnant individuals, it is important to understand the determinants of vaccine hesitancy in pregnancy. The focus of our study was to explore COVID-19 vaccination among pregnant and breastfeeding individuals and its association with their reasons (psychological factors) for vaccination using the 5C scale and other factors. METHODS: An online survey investigating prior vaccinations, level of trust in healthcare providers, demographic information, and the 5C scale was used for, pregnant and breastfeeding individuals in a Canadian province. RESULTS: Prior vaccinations, higher levels of trust in medical professionals, education, confidence, and collective responsibility predicted increased vaccine uptake pregnant and breastfeeding individuals. CONCLUSIONS: There are specific psychological and socio-demographic determinants that affect COVID-19 vaccine uptake in pregnant populations. Implications of these findings include targeting these determinants when informing and developing intervention and educational programs for both pregnant and breastfeeding individuals, as well as healthcare professionals who are making vaccine recommendations to patients. Study limitations include a small sample and lack of ethnic and socioeconomic diversity.

Age and cohort trends in disability among Chinese older adults.

Objective: This study aimed to examine age and cohort trends in disability among Chinese older adults and explore the disablement process factors that may explain the cohort trends in disability. Methods: This study used data from five waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A hierarchical logistic growth model was used to analyze the A-P-C effects and the contributors of cohort trends. Results: ADL, IADL, and FL among Chinese older adults showed increasing age and cohort trends. FL was more likely to result in IADL disability than ADL disability. Among the disablement process factors, gender, residence, education, health behavior, disease, and family income contributed to most of the cohort trends in disability. Conclusions: As older adults face increasing disability trends, it is necessary to distinguish age and cohort trends and develop more effective interventions according to relative contributors to prevent disability among them.

Extracting factors associated with vaccination from Twitter data and mapping to behavioral models.

Social media platform, particularly Twitter, is a rich data source that allows monitoring of public opinions and attitudes toward vaccines.Established behavioral models like the 5C psychological antecedents model and the Health Belief Model (HBM) provide a well-structured framework for analyzing shifts in vaccine-related behavior. This study examines if the extracted data from Twitter contains valuable insights regarding public attitudes toward vaccines and can be mapped to two behavioral models. This study focuses on the Arab population, and a search was carried out on Twitter using: ' تلقيحي OR تطعيم OR تطعيمات OR لقاح OR لقاحات' for two years from January 2020 to January 2022. Then, BERTopicmodeling was applied, and several topics were extracted. Finally, the topics were manually mapped to the factors of the 5C model and HBM. 1,068,466 unique users posted 3,368,258 vaccine-related tweets in Arabic. Topic modeling generated 25 topics, which were mapped to the 15 factors of the 5C model and HBM. Among the users, 32.87%were male, and 18.06% were female. A significant 55.77% of the users were from the MENA (Middle East and North Africa) region. Twitter users were more inclined to accept vaccines when they trusted vaccine safety and effectiveness, but vaccine hesitancy increased due to conspiracy theories and misinformation. The association of topics with these theoretical frameworks reveals the availability and diversity of Twitter data that can predict behavioral change toward vaccines. It allows the preparation of timely and effective interventions for vaccination programs compared to traditional methods.

Determinants of COVID-19 Vaccine Acceptability among Healthcare Workers in Kenya-A Mixed Methods Analysis.

Healthcare workers (HCWs) were a priority group for COVID-19 vaccination. Adopting the World Health Organization's 3C and the expanded 5C vaccine hesitancy models, we assessed the factors associated with COVID-19 vaccine acceptability among HCWs in Kenya. In a mixed methods study, respondents were from eight selected counties across the country. An online survey (n = 746), key informant interviews (n = 18) and focus group discussions (n = 3) were conducted. The data were analyzed concurrently. Quantitative data showed that all the 3C antecedents were strong predictors of vaccine acceptability. The association of vaccine acceptability was strongest with convenience (aOR 20.13, 95% CI 9.01-44.96), then complacency (aOR 10.15, 95% CI 4.63-22.21) and confidence (aOR 6.37, 95% CI 2.90-14.02). Marital status was a significant independent factor associated with vaccine acceptability (aOR 2.70, 95% CI 1.20-6.08). Qualitatively, convenience presented as the no-cost availability of vaccines at the health facilities, whereas non-complacency manifested from the first-hand observed experience of COVID cases, and the need to protect oneself and family members. Confidence was mainly attributed to increased knowledge, resulting from multiple training sessions and trust in regulatory authorities. Other social factors including workplace pressure, religion and misinformation had a role in influencing HCW vaccination decisions. In the background of a pandemic, the 3C model is a strong predictor of vaccine acceptability, and making the vaccines easily available and convenient to HCWs significantly impacts their uptake.