Past Behavior Research Articles

Prevalence of and intent behind motorcyclists' violations at railway crossings in Indonesia: Modeling behavior and learning lessons from a developing country

ObjectiveIndonesia experiences a high number of motorcycle accidents at railway crossings (RLXs). The purpose of this study is to observe motorcyclists' behavior and intent to cross the railway in a dangerous or illegal way and the factors influencing these decisions. MethodTwo hundred and fifty-nine people (mean age = 24.2 years, SD = 7.2 years, 146 males, 113 females) voluntarily participated in this study by filling in an online questionnaire. This questionnaire gathered demographic data and used constructs adapted from the extended Theory of Planned Behavior, asking respondents about their behavior at RLXs when the barrier is open, when it is half closed and when it is fully closed. A five-point Likert scale was used to measure the response of the questionnaire. Data were analyzed using descriptive analysis for demographic data, inferential statistics, and structural equation modeling (SEM) for the construct items of the model. Field observation was also conducted to measure the violation rate at RLXs at both busy and non-busy times, which were then compared. ResultThe results show that factors influencing RLX violation based on the extended Theory of Planned Behavior model are attitude, past behavior, and traffic environments. Demographic factors, occupation, RLX characteristics, and crossing frequency were related to self-reported violations and intentions to violate. Based on our observations and questionnaire, it was found that when accident risk was higher, the observed violation rate decreased significantly, as did intention to violate and previous risky crossing behavior. Conclusionviolations at railway crossings are influenced by individual and environmental factors as well as perceived risk.

Drivers of consumers’ intention to adopt sustainable healthy dietary patterns: evidence from China

IntroductionIn line with the shift towards sustainable consumption, sustainable healthy dietary patterns (SHDP) have received considerable attention, but no study has examined Chinese consumers’ intention to adopt SHDP.MethodsBased on the theory of planned behaviour (TPB), this study integrated health consciousness, environmental concerns, and past eating behaviour to construct an expanded TPB framework for analyzing the factors influencing Chinese consumers’ intention to adopt SHDP. The mediating role of attitude between perceived value and consumers’ intention to adopt SHDP was also analyzed. The study empirically tested the research model using structural equation modelling estimation, based on the data collected from 402 local consumers in Wuxi, China.Results and discussionThe results showed that attitude, perceived behavioural control, health consciousness, and past eating behaviuor positively and significantly influenced consumers’ intention to adopt SHDP, whereas perceived value indirectly influenced adoption intention through attitude. Subjective norms and environmental concerns had no significant influence on adoption intention. Based on these findings, interventions through dietary education and information campaigns are recommended to enhance consumers’ value awareness and attitudes towards SHDP. Interventions, such as nudging, should be designed to enhance consumers’ perceived behavioural control and dietary practises. The findings of this study provide important insights for the development of dietary change intervention strategies.

Cement Pastes with Hygroscopic Polymeric Additions for Potential Building Applications

The development of highly predictive analysis for designing cementitious composite with improved thermal and hygroscopic performance for building and construction poses a significant challenge. To investigate new potential applications, cement pastes have been prepared using a cement, sand, and crystallization admixture, with highly hygroscopic polymer additions (SA-PA) of sodium polyacrylate and/or recycled polyamide fibers. The porosity evolution was investigated at different curing stages and after heat treatment at 200 °C, the temperature at which the paste dehydrates quickly without structural changes. Mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), cyclic shear tests, thermal conductivity, and diffusivity measurements were carried out on the cement pastes to assess their microstructure. The behavior of the cement pastes varied with polymer additions and thermal treatments; ka−0.5 must be maximized in heat storage applications, where a and k are thermal diffusivity and conductivity, respectively. In contrast, the product a0.5k−1 must be maximized in energy-efficient insulation. Cement pastes with SA-PA exhibited the highest values of both 9.191 102 m−2 K−1 s0.5 W and 1.088 10−3 m2 K s−0.5 W−1, respectively. After the thermal treatment at 200 °C, SA-PA samples maintained the highest heat-storing performance of 6.258 102 m−2 K−1 s0.5 W, while the samples with SA-PA and polyamide fibers performed better in energy-efficient insulation, demonstrating performance of 2.552 10−3 m2 K s−0.5 W−1. These results, discussed in terms of pore size distribution, suggest potential applications in the building field and are valuable for designing plaster and concrete for applications such as thermal and hygroscopic control.

Effects of limestone calcined clay, fly ash and seawater on early hydrating behavior, mechanical properties, microscopic performance and sustainability of eco-friendly cement-based pastes

Effects of limestone calcined clay, fly ash and seawater on early hydrating behavior, mechanical properties, microscopic performance and sustainability of eco-friendly cement-based pastes

OS-FCM: A semi-supervised clustering approach to investigating consumers’ usage patterns of contactless shopping-delivery (S-D) channel

Investigating the factors that contribute to consumers’ usage patterns of contactless shopping-delivery (S-D) channel is important for e-commerce retailers and logistics operators. However, in the data as collected by a questionnaire survey, distinct usage patterns are not always easily observed due to the existence of outliers, which places a challenge for the investigation. Hence, this study develops a labelling approach, named OS-FCM, to determine the usage patterns. As a semi-supervised clustering approach, OS-FCM integrates One-Class Support Vector Machine and Fuzzy C-Means, which enables it to make a trade-off between subjective judgement and statistical evidence when identifying patterns and to effectively recognize the patterns of outliers. The dataset with the usage patterns is used to train Random Forest, upon which Shapley Additive exPlanations (SHAP) approach is applied to measure the contributions of each factor. The data as collected by a questionnaire survey in Singapore are used for a case study. By using OS-FCM, the participants are clustered into five patterns with each pattern involving three variables, namely, current usage frequency, current behavioral habit, and future continuance intention. The contributions of each potential factor to the patterns are measured by SHAP values. In the case study, two regular patterns and three outlier patterns are identified. It is found that consumers’ past behavior stands out to be the most important factor to the pattern formation from an aggregated perspective. Factors such as fear appeal and behavior maintenance/change motivations exert differentiated impacts on the formation of the five patterns. Besides, as compared to commonly used clustering methods, OS-FCM has better clustering performance and the patterns determined by OS-FCM are more reasonable and rational, which provides a solid basis for better understanding the usage patterns.

Effects of past mating behavior versus past ejaculation on male mate choice and male attractiveness.

Past reproductive effort allows males to assess their ability to acquire mates, but it also consumes resources that can reduce their future competitive ability. Few studies have examined how a male's reproductive history affects his subsequent mate choice, and, to date, no study has determined the relative contribution of past mating behavior and past ejaculate production because these two forms of investment are naturally highly correlated. Here, we disentangled the relative effects of past mating behavior and past ejaculate production in mosquitofish (Gambusia holbrooki) by experimentally preventing some males from ejaculating when trying to mate. We assessed the effect of mating behavior on mate choice by comparing males that had previously been with or without access to females and male rivals for 8 and 16 weeks and assessed the effect of ejaculation on mate choice by comparing males that either could or could not ejaculate when they had access to females for 16 weeks. Reproductive treatment did not affect male attractiveness, but it did affect male mate choice. Somewhat surprisingly, in five of the six treatment-by-age at testing combinations, males preferred a female in the vicinity of a male rival over a solitary female. This preference was marginally stronger for males that had previously engaged in mating behavior but were unaffected by past ejaculate production. We discuss the potential benefits to males of associating with another male when seeking mates. This is the first study to quantify the relative influence of pre- and post-copulatory reproductive investment on male mate choice.

Are eco-sustainable dietary patterns associated with impulsiveness? An insight from Italy

Impulsivity is known to influence food choices. We explored possible differences in its expression between individuals with or without an eco-sustainable diet and its relationship with cognitions and behaviours about eco-sustainable foods. Participants were categorised as having or not having an eco-sustainable diet. Impulsivity traits and cognitions and behaviours about sustainable food products were measured. Among the 332 participants, 92.78% showed an eco-sustainable diet, whereas only 7.22% had an eco-sustainable diet. No difference between groups emerged about impulsive traits, whereas significant differences emerged in cognitions and behaviours about sustainable foods, with the only exceptions of subjective norms and past behaviour. Impulsive traits were linked to cognitions and behaviours differently within groups. Impulsivity traits may be related to actions towards eco-sustainable foods, with the perception of their availability playing a crucial role. Increasing contextual opportunities may be fundamental for having eco-sustainable consumers

The role of character‐based personal mitigation in sentencing judgments

AbstractPersonal mitigating factors (PMFs) such as good character, remorse and addressing addiction help sentencers evaluate an offender's past, present and future behavior. We analyzed data from the 2011–2014 Crown Court Sentencing Surveys in England and Wales to examine the relationship between these PMFs and custodial sentences passed on assault and burglary offenses, controlling for other sentencing relevant factors. Beyond revealing the distribution and co‐occurrence of the three PMFs, it was found that good character, remorse and addressing addiction all had a significant mitigating effect. The effects of addressing addiction were the strongest of the three across both offense types, while good character had a stronger effect on burglary than assault. In addition, some mitigating factors appear to be underweighted when they occur together. We consider the implications of these findings for sentencing policy and practice.

Modeled variations of tropical cyclone genesis potential during Marine Isotope Stage 3

To advance our understanding of the responses of tropical cyclones (TCs) to abrupt climate transitions, we investigate the variation of genesis potential and the underlying mechanisms during Marine Isotope Stage 3 (MIS 3) that is characterized by frequent millennial-scale oscillations, using a set of coupled model simulations. We illustrate that genesis potential mainly increases over the eastern North Pacific and South Pacific in the storm season during MIS 3 interstadial relative to preindustrial, whereas it decreases over the western North Pacific, North Atlantic, South Indian Ocean, and Australian coast. The relative importance of each genesis factor to genesis potential change varies across oceans. During the transition from warm interstadial to cold stadial induced by freshwater injection, TC genesis potential generally decreases in the Northern Hemisphere, while increases in the Southern Hemisphere. These changes are associated with asymmetric variations of genesis factors between Northern and Southern Hemisphere, which are further tied to the adjustment of large-scale environmental factors in response to the weakened Atlantic meridional overturning circulation. Additionally, TC genesis potential exhibits a regional “overshoot” phenomenon when the freshwater injection is terminated, manifested by an increase over the eastern North Pacific and North Atlantic and a decrease over the South Pacific, compared with the initial interstadial state. Our results may help improve our knowledge on past TC behaviors and shed lights on TC response to potential abrupt climate transitions in a warmer future.

An Impact Assessment of Par-Baking and Storage on the Quality of Wheat, Whole Wheat, and Whole Rye Breads.

Par-baking technology increases the production efficiency of bread. However, the degree of par-baking can vary significantly amongst product types and intended sales markets, leading to substantial differences in the quality attributes of the finished product. The objective of this study was to explore the impact of the degree of par-baking on the technological quality of wheat, whole wheat, and whole rye bread (95, 75, and 50% of full baking time). More specifically, this study focused on the starch pasting behavior of different flour formulations, the crumb core temperature during par-baking, and the influence of the degree of par-baking on the bread characteristics of (composite) wheat bread as a function of storage time. The quality attributes of par-baked bread (0 and 4 days after par-baking) and fully baked bread (0 and 2 days after full baking) were assessed. A reduction in the degree of par-baking from 95 to 50% resulted over time in 19.4% less hardening and 8.6% more cohesiveness for the re-baked wheat breads. Nevertheless, it also negatively impacted springiness (-9.1%) and adhesion (+475%). It is concluded that using the core temperature to define the degree of par-baking is not sufficient for bread loaves intended to be consumed over time, but the results indicate that reducing the degree of par-baking can be beneficial for certain quality aspects of the breads.

Behaviour of alkali-activated fly ash-slag paste at elevated temperatures: An experimental study

As an environmentally friendly material, alkali-activated fly ash-slag (AAFS) is considered as a promising alternative cement because of its excellent mechanical properties and thermal stability. Nevertheless, high temperature induced damage in AAFS can potentially bring serious risks for its practical applications. This paper presents a systematic experimental study on behaviour of AAFS paste subjected to elevated temperatures up to 800 °C in terms of microstructure as well as thermal and mechanical properties. Microstructural evolution was characterised by means of Rietveld-based quantitative X-ray diffraction (QXRD), backscattered scanning electron microscope (BSEM) and X-ray microcomputed tomography (XCT), while thermal and mechanical properties were evaluated from thermogravimetric analysis (TGA), thermal deformation and compressive and flexural strengths. Results indicate that the compressive strength of AAFS paste rises by 77.5 % at 200 °C, followed by a mitigation from 200 to 600 °C and a regain at 800 °C. Different phases in AAFS paste including unreacted particles, reaction products and pores took up 30 %, 67.7 % and 2.31 % at ambient temperature, and 4.95 %, 84.8 % and 10.3 % after exposure to 800 °C, respectively, suggesting the recrystallisation with the formation of nepheline and gehlenite. In addition, the relationships between microstructural characteristics including three-dimensional (3D) pore structure features and thermal and mechanical properties of AAFS paste at elevated temperatures were explored and discussed in depth to gain insights into the underlying degradation mechanisms including pore pressure build-up, thermal gradient and phase transformation.

Neurotechnology in criminal justice: key points for neuroscientists and engineers.

Abstract Neurotechnology encompasses any device (including hardware, testing/stimulation paradigms and data analysis/ interpretation algorithms) that interfaces with the central nervous system to modulate or monitor neural activity. Driven by continuous scientific advances, neurotechnology is increasingly applied in research, clinical and consumer settings. The recent considerable investments in neurotechnology from private sector parties such as Blackrock, Neuralink and Kernel, and the growing interest of policy makers, are likely to further accelerate this trend. 
One area of application for neurotechnology is the criminal justice system. Neurotechnology may provide legally relevant information about people’s past, present and future behavior. In addition, treatment programs in criminal justice may apply neurotechnological risk assessment and interventions. Currently, the use of neurotechnologies in criminal justice is mostly limited to the diagnosis of neurological conditions such as epilepsy, brain trauma, and dementia, incidentally aiding the assessment of fitness to stand trial and legal insanity1. Neurotechnologies have also sporadically been used for other applications in criminal justice2. 
Here, we identify concerns and priorities for responsible implementation of neurotechnology in the criminal justice system beyond its current use (BOX1). For that, we first consider areas where neurotechnology has potential value. Then, we identify key requirements that have to be met for the techniques to be usable in criminal justice settings. These requirements often deviate from standards typically applied in neuroscientific research. Using some of the most prominent developments of neurotechnology as examples, we briefly describe to what extent emerging neurotechnologies currently match these requirements. Finally, we assess human rights issues related to the implementation of neurotechnology in criminal justice. We conclude that responsible real-world implementation requires neurotechnologies to be effective, reliable and compliant with human rights, and argue that research and development of neurotechnologies for use in criminal justice should focus on the user-context and prioritize validation for intended use.




Ultrasonic monitoring of hydration behavior of cement paste doped with triethanolamine using novel piezoelectric ultrasonic transducer

The propagation of ultrasonic wave in cement paste is closely related to its physical properties, and therefore shows a potential application in fields of online monitoring of hydration and hardening properties of the cementitious materials. Here, the hydration characteristics of cement paste doped with triethanolamine were studied based on the ultrasonic transmission method using the tailor-made horizontal omnidirectional piezoelectric ultrasonic transducer. The results show that clear ultrasonic waveforms can be observed at hydration age of 2 h. The dominant frequency of the reception wave is low at early hydration age and shifts towards the high frequency direction with hydration. The amplitude of the head wave increases sharply before hydration of 24 h, and the increasing extent decreases gradually until hydration of 166 h. The hydration process of cement at early hydration age can be classified into three stages based on amplitude changes of the head wave, that is, the induction period before 4 h, the acceleration period during 4–12 h, and the deceleration period after 12 h. The acoustic parameters of cement paste at early hydration age conform well to the logistic function distribution. The research finding might provide a new method to estimate hydration and hardening properties of cementitious materials, especially on large construction sites.

Landslide development model based on tree-ring data and quantification of the magnitude of landslide movements

Analysis of landslide events by studying anomalies in tree-ring series of disturbed trees provides unique data on past landslide behaviour. However, a comprehensive spatio-temporal model of landslide evolution using dendrogeomorphic data has not yet been constructed. In terms of determining landslide hazard, one of the key issues, besides the frequency of movements, is their magnitude. Thus, this study is aimed at constructing a model of landslide area development including quantification of landslide displacements. Moreover, not only standard macroscopic growth disturbance but also quantitative anatomical parameters of tree rings were used as a basis for these objectives. The research was carried out on a landslide of the Váh river bank (Slovakia) using data from 32 disturbed black locust (Robinia pseudoacacia L.) individuals. Anatomical analysis revealed a reduction in the vessel lumen area in response to landslide movements. The response was associated with tension wood formation or damage to the tree root system. The reconstructed chronology of landslide movements revealed the main phase of landslide in 2017 and its subsequent evolution. Based on the chronological information and the morphology of the landslide body, a spatio-temporal model of the landslide evolution from the initial slope failure to the present was constructed. The model showed the interrelationships between vertical displacement of the main block, compression and tension deformations within the landslide body, and lateral erosion of the landslide toe by the river. Quantification of the magnitude of landslide displacements was realized from exposed roots in tension cracks but also from the ruptured tree trunk. The limitations and advantages of both approaches are discussed.

High-Performance Technique for Item Recommendation in Social Networks using Multiview Clustering

Recommender Systems have been widely employed in information systems over the past few decades, making it easier for each user to choose their own products based on their past behaviour. Data mining tasks and visualization tools regularly use clustering techniques in the scientific and commercial arenas. It has been shown that clustering-based methods are effective and scalable to big data sets. The accuracy and coverage of clustering-based recommender systems are, however, somewhat low. In this paper, we suggest an improved multi-view clustering method for the recommendation of items in social networks to overcome these problems. To create better partitions, the artificial Bees colony optimization algorithm (ABC) is first used to improve the initial medoids’ selection. After that, users are clustered iteratively using views of both rating patterns as well as social information using multiview clustering (MVC) (i.e. trust and friendships). Ultimately, a framework is suggested for evaluating the various options. This research study suggests a novel MVC clustering approach using the ABC optimization technique. The proposed ABC-MVC algorithm’s usefulness in terms of enhancing accuracy is demonstrated by experimental findings performed on a real-world dataset and it is observed that it performs better than the pre-existing techniques and baselines.

Exploring adolescent participation in football: a gender-differentiated structural equation model based on the theory of planned behavior.

This paper explores the intersection of gender and sports participation in adolescence, focusing on traditionally male-dominated sports like football. We aim to develop a structural model based on the Theory of Planned Behavior (TPB) to examine gender-differentiated patterns and factors influencing adolescent participation in football. We analyzes data from 1,147 adolescents using Structural Equation Modeling (SEM). The results indicate that a blend of attitudes, subjective norms, perceived behavioral control, and past behavior effectively predicts adolescents' willingness to engage in football. Moreover, the study investigates the roles of perceived behavioral control, past behavior, and behavioral intentions in actual football participation, uncovering significant gender disparities in the progression from past behavior to intentions and subsequent behavior. This research highlights the complex role of gender in football participation and provides strategic insights for increasing girls' involvement in the sport. Our study sets the stage for future research on enhancing girls' participation in football.

Cotton farmers’ intention to adopt biochar as climate change adaptation and sustainable land management strategy in Benin

Innovative agricultural practices represent the future of the world in the sustainable improvement of agricultural productivity. Sustainable farming practices have been recognized and accepted by agricultural development stakeholders, to provide a wide range of social, economic, financial, and environmental benefits. Despite this recognition, the application of these practices in the literature has focused on socio-economic and technical aspects while the psychosocial elements of the application have received limited attention. To contribute to a broad understanding of the concept, this study aims at analyzing the psychosociological motivations of cotton farmers to use biochar as a sustainable land management strategy. Adopting a survey research design, a sample of 528 farmers in Benin (West Africa) was interviewed on the pillars of the Theory of Planned Behavior (TPB) (Attitude, Subjective norms, Behavioral Control) and three other aspects (Climate change perception, Past behavior and Productivity risk perception) for an extension of TPB. The data collected were analyzed using the structural equation model of the SmartPLS 4 program. The results of this study confirmed all TPB relationships except for the construction of the “Attitude" pillar where Perceived ease of use had no significant influence. Apart from the classical TPB factors, perception of climate change and past behavior in adopting new agricultural practices positively affect the application of biochar. However, possible yield decreases at the beginning of biochar use demotivate farmers to take initiatives in this direction. The study notes that the role of a good perception and knowledge of the effects of climate change and the benefits of biochar action are elements to be considered in promoting sustainable cotton farming and agricultural practices.

Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data

Smart cities leverage advanced technologies to enhance urban living through the real-time collection, processing, and analysis of contextual information. The potential to improve residents’ outdoor experiences in these cities increases dramatically as smart technologies are integrated into urban environments, making them more interconnected. It helps to explore the pivotal role of real-time data in optimizing various aspects of city management, focusing on key domains such as traffic, public transportation, emergency response, waste management, and environmental monitoring. A variety of datasets, such as those on the weather, air quality, traffic patterns, event schedules, and user activity patterns, are gathered and analyzed as part of the methodology. This data are processed and interpreted using machine learning algorithms, which find correlations, trends, and patterns that affect outdoor activities. Suggestions for appropriate outdoor activities can be generated in real time based on contextual information, past behavior, and user preferences. This model addresses the dynamic and context-aware nature of Smart Cities by proposing a novel framework for real-time contextual information prediction and personalized outdoor activity suggestions for users. Leveraging the vast amount of data generated by Smart City infrastructure, this study integrates advanced data analysis techniques with deep learning models to enhance the urban living experience. A variety of datasets, such as those on the weather, air quality, traffic patterns, event schedules, and user activity patterns, are gathered and analyzed as part of the methodology. This data are processed and interpreted using machine learning algorithms, which find correlations, trends, and patterns that affect outdoor activities. Suggestions for appropriate outdoor activities can be generated in real time based on contextual information, past behavior, and user preferences. The framework begins by collecting and processing diverse datasets from sensors, Internet of Things (IoT) devices, and other urban sources to create a comprehensive understanding of the current city context. Deep learning models, such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), are employed to analyze this data and predict real-time contextual information, including weather conditions, traffic patterns, and social events. It contributes to the growing field of Smart Cities by introducing a scalable and adaptable framework that harnesses the power of deep learning to improve urban living. The result shows that the proposed air pollution model predicted 96.06700 PM2.5 concentration levels, subsequently the temperature model predicted 14.06800∘C. The integration of real-time contextual information prediction and personalized outdoor activity suggestions showcases the potential for creating more engaging and user-centric Smart City ecosystems. This research attempts to provide personalized recommendations that are in line with users’ preferences, the state of the environment at the time, and other pertinent contextual factors by utilizing data from multiple sources, including IoT devices, mobile applications, and environmental sensors.

The influence of ZnO nanoparticles on mechanical and early-age hydration behaviour of cement paste

The influence of ZnO nanoparticles on mechanical and early-age hydration behaviour of cement paste

“I shall not poison my child with your human experiment”: Investigating predictors of parents’ hesitancy about vaccinating younger children (

BackgroundSince the approval of SARS-CoV-2 vaccines for younger children (those under the age of 12), uptake has been low. Despite widespread vaccination among older children and adults, these trends may undermine public health efforts to manage future waves of SARS-CoV-2 or spill over into other childhood vaccines. The objectives of this study were to understand parents’ intentions to vaccinate their children (under age 12) against SARS-CoV-2, and to explore reasons for and against SARS-CoV-2 vaccination. MethodsA representative sample of parents of school-aged children (ages 3–11 years) from Canada’s four largest provinces were invited in June 2021 to complete a survey on the impact of COVID-19 on schooling. The survey included specific questions on parents’ intentions to vaccinate their child(ren) against SARS-CoV-2. Multinomial regression models were run to estimate associations between demographic factors, political affiliation and voting, concerns about individual / family health and vaccination intention. ResultsA total of 74.0 % of parents (n = 288) intended to vaccinate their children with the SARS-CoV-2 vaccine, 18.3 % (n = 71) did not intend to vaccinate and 7.7 % (n = 30) were unsure. The strongest predictor of parental hesitancy was whether a parent had themselves been vaccinated. Other factors including past voting behaviour, dissatisfaction with the government’s response to the pandemic, and relatively less concern about contracting SARS-CoV-2 were also correlated with hesitancy. Parents of older children were more likely to indicate plans to vaccinate their child(ren). Analysis of the reasons for hesitancy showed parents are concerned about the safety and side effects of the vaccine, as well as with processes of testing and approval. InterpretationA considerable proportion of Canadian parents of younger school-aged children (ages 3–11) were unsure and/or hesitant about vaccinating their children against SARS-CoV-2. As well, a much larger proportion who are not necessarily hesitant have also not had their children vaccinated. Given the evolving nature of SARS-CoV-2, including the continued emergence of new variants, reaching younger children will be important for population health. Health providers should continue to work with government institutions to ensure clear communication regarding the safety, efficacy, and importance of child vaccines for reaching public health goals.