Behavioral Science Theory Research Articles

To use or not to use behavioural science evidence in designing health promotion interventions: Identification of targets for capacity building.

The behavioural sciences provide useful evidence to design effective health promotion interventions, but evidence is infrequently integrated in practice. This study examined associations between theoretical domains framework (TDF) constructs and public health practitioners' use of behavioural science evidence to plan public health actions. Using a cross-sectional design, a convenience sample of 160 practitioners were recruited from public health agencies across Canada. Respondents completed an online questionnaire assessing TDF constructs and the use of behavioural science theory and approaches (i.e., evidence) in their practice. Logistic regression analyses allowed for identification of factors associated with evidence use and intentions. All analyses were adjusted for sex, years of experience, and type of public health agency. Greater skills (ORadj = 4.1, 95%CI 1.3, 13.5) and stronger intentions/aligned goals (ORadj = 9.2, 95%CI 2.3, 36.1) were associated with greater use of behavioural science evidence to plan public health actions. Greater perceived capacity to overcome widespread absence of use of behavioural science evidence in their organization (ORadj = 7.2, 95%CI 1.7, 30.3) was also associated with greater use. More knowledge (ORadj = 8.6, 95%CI 1.9, 39.1) and stronger beliefs about consequences (ORadj = 4.0, 95%CI 1.1, 14.7) were significantly associated with stronger intentions/aligned goals. Findings show that more knowledge, positive attitudes, and stronger perceived competence are associated with greater likelihood of using behavioural science evidence to plan interventions. The use of behavioural science evidence will also require strengthening the norm pertaining to this professional practice in public health organizations.

Behavioural strategies in simultaneous and alternating prisoner’s dilemma games with/without voluntary participation

The Prisoner’s Dilemma is one of the most classic formats for exploring the principle of direct reciprocity. Although numerous theoretical and experimental studies have been conducted, little attention has been paid to the divergence between theoretical predictions and actual human behaviour. In addition, there are two additional essential challenges of experimental research. First, most experimental approaches have focused on games in which two players decide their actions simultaneously, but little is known about alternating games. Another is that there are few experiments on voluntary participation. Here, we conducted experiments on simultaneous games, alternating games, and games with and without voluntary participation for a total of four game patterns and examined the deviation from theoretical predictions for each. The results showed that, contrary to theoretical predictions, humans chose cooperation even after being exploited. We also observed that, with or without voluntary participation, people tended to take the same action they had taken in the previous round. Our results indicate that to understand the mechanisms of human behaviour, we need to integrate findings from behavioural science, psychology, and game theory.

Behavioral, cognitive and emotional determinants of getting vaccinated for COVID-19 and the mediating role of institutional trust among young adults in Cyprus

BackgroundVaccination uptake is a complex behavior, influenced by numerous factors. Behavioral science theories are commonly used to explain the psychosocial determinants of an individual’s health behavior. This study examined the behavioural, cognitive, and emotional determinants of COVID-19 vaccination intention based on well-established theoretical models: Acceptance and Commitment Therapy (ACT), Capability, Opportunity, Motivation, and Behaviour (COM-B) and the Health Belief Model (HBM). Additionally, it examined the mediating role of institutional trust in the relationship between determinants of these models and vaccination intentions.MethodsA cross-sectional study was conducted from January to May 2022, where university students in Cyprus completed an online survey.ResultsA total of 484 university students completed the online survey, with 23.8% reporting being vaccinated with fewer than three vaccination doses and/or no intention to vaccinate further. Hierarchical logistic regression analysis showed that higher scores in institutional trust, perceived severity, motivation, physical and psychological capability were significantly associated with higher odds of intending to vaccinate. Higher psychological flexibility and not being infected with COVID-19 were also associated with higher odds of vaccination intention, but not in the final model when all determinants were included. Additionally, significant indirect effects of psychological and physical capability, motivation and perceived severity on vaccination intention were found to be mediated by institutional trust.ConclusionsWhen tackling COVID-19 vaccination hesitancy, behavioural, cognitive, and emotional aspects should be considered. Stakeholders and policymakers are advised to implement targeted vaccination programs in young people while at the same time building trust and improving their capabilities and motivation towards getting vaccinated.

The HIV prevention decision-making cascade: Integrating behavioural insights into HIV prevention efforts

The syndemic of HIV, sexually transmitted infections (STIs), and early pregnancy remain a key challenge to global public health. Decision-making around sexual and reproductive health (SRH) behaviours is critical to ensuring the uptake of biomedical technologies. Drawing from behavioural science theories, we propose a novel conceptual framework—the Decision Cascade—to describe the decision-making process that a user will go through as they navigate these decisions. Analogous to the HIV prevention and treatment cascade, this model describes key steps individuals go through when deciding to use HIV prevention technologies. Each step (being cued/triggered to act, reacting to the behaviour, evaluating the behaviour, assessing the feasibility of acting and the timing and final execution of the action), is influenced by a myriad of individual and socio-cultural factors, shaping the ultimate decision and behaviour outcome in a continual cycle. This framework has applications beyond HIV prevention, extending to other SRH technologies and treatments. By prioritizing human-centered design and understanding user decision-making intricacies, interventions can enhance effectiveness and address the complexities of SRH service uptake across diverse populations. The Decision Cascade framework offers a comprehensive lens to inform intervention design, emphasizing the need for nuanced approaches that resonate with the realities of decision-makers. Adopting such approaches is essential to achieving meaningful impact in HIV prevention and broader SRH initiatives.

Occupant-centric control in buildings: Investigating occupant intentions and preferences for indoor environment and grid flexibility interactions

Occupant-centric control (OCC) systems have recently gained attention as they fulfill the energy efficiency goals of buildings while prioritizing occupant comfort and well-being. However, many studies overlook the core principle of focusing on occupants and their preferences. Instead, they assume seamless interaction between individuals and advanced controls reliant on occupant data. This study investigates occupant preferences in control systems, including control access, automation level preferences, interface design, and data sharing. Furthermore, it assesses occupant willingness to interact with OCC by sharing data as feedback for indoor environment control and grid flexibility purposes. This study is based on a survey conducted in six educational buildings involving 959 respondents with varying levels of technical knowledge. The method includes a well-established behavioral science theory called the Theory of Planned Behaviour. Structural equation modeling with SmartPLS statistical software was used for data analysis. The study reveals that 55.6% of occupants are willing to interact with OCC by sharing data. The key influences are occupants’ attitudes, social norms, ease of use, and user trust. The proposed behavioral models predict user interaction with OCC with moderate prediction, with R2 values reaching 63.9%, which is satisfactory in behavioral sciences. The results also show a correlation between willingness to interact with OCC and engagement in grid flexibility. These findings are important for OCC designers and building control practitioners who aim to prioritize occupant needs and preferences. The behavioral prediction models present a tool for assessing occupant data sharing inclination, thereby helping to prevent data shortages.

A behaviour and disease transmission model: incorporating the Health Belief Model for human behaviour into a simple transmission model.

The health and economic impacts of infectious diseases such as COVID-19 affect all levels of a community from the individual to the governing bodies. However, the spread of an infectious disease is intricately linked to the behaviour of the people within a community since crowd behaviour affects individual human behaviour, while human behaviour affects infection spread, and infection spread affects human behaviour. Capturing these feedback loops of behaviour and infection is a well-known challenge in infectious disease modelling. Here, we investigate the interface of behavioural science theory and infectious disease modelling to explore behaviour and disease (BaD) transmission models. Specifically, we incorporate a visible protective behaviour into the susceptible-infectious-recovered-susceptible (SIRS) transmission model using the socio-psychological Health Belief Model to motivate behavioural uptake and abandonment. We characterize the mathematical thresholds for BaD emergence in the BaD SIRS model and the feasible steady states. We also explore, under different infectious disease scenarios, the effects of a fully protective behaviour on long-term disease prevalence in a community, and describe how BaD modelling can investigate non-pharmaceutical interventions that target-specific components of the Health Belief Model. This transdisciplinary BaD modelling approach may reduce the health and economic impacts of future epidemics.

Predicting COVID-19 Vaccination Intentions to Inform Evidence-Based Messaging for Building Vaccine Confidence Among Rural Americans.

Examine possible message topics to promote rural vaccination using psychosocial antecedents of vaccination. Cross-sectional survey administered by Research America, Inc. West Virginia (WV). 756 WV adults via convenience sample (n = 370; ∼2% response rate from online panel of ∼20 000 WV residents), and random digit dial of landlines (n = 174; ∼1% response rate from 18 432 numbers) and cellphones (n = 212; ∼1% response rate from 20 486 numbers). Outcome measures included self-reported vaccination intention and behavior. Predictor measures, rooted in theories of social and behavioral science that have been found to be predictive of vaccination outcomes (i.e., Reasoned Action Approach, Extended Parallel Process Model), included perceived severity and susceptibility, negative affect, instrumental and affective attitudes, social norms, self-efficacy, response efficacy, and perceived control. Multivariate linear regression for intention and logistic regression for behavior. Intention was positively predicted by affective attitude, β = .30, P < .05, instrumental attitude, β = .19, P < .05, response efficacy, β = .19, P < .05, negative affect, β = .16, P < .05, self-efficacy, β = .13, P < .05, and subjective norm, β = .13, P < .05, F(10, 267) = 30.12, Adj. R2 = .53. Vaccination status was predicted by instrumental attitude, exp(B) = 2.09, and subjective norm, exp(B) = 2.00, Pseudo R2 = .29, log likelihood = 125.11, χ2(10) = 38.34, P < .05. Promising message targets were instrumental attitude, M = 3.21, SD = 1.46, and subjective norms, M = 3.76, SD = 1.71. COVID-19 vaccine confidence messages should address (1) positive feelings and safety perceptions, (2) vaccination's effectiveness in preventing serious COVID-19, and (3) subjective vaccination norms.

Online Learner Categories Recognition Based on MoE-LSTM Model

Online learner behaviour patterns are comprehensive indicators reflecting the learning status and learning outcomes of online learners, which have a guiding role in the design, implementation and improvement of online education in the post-epidemic era, but the methods for their identification still need to be improved. To improve the accuracy of online learner identification, a model of online learner behaviour identification based on improved long and short-term memory networks with deep learning is established. Firstly, the online learner behaviour characteristics are extracted according to the behavioural science theory, secondly, the online learner type is identified based on the "hybrid expert system-long and short-term memory network" model, and then compared with other identification models, and finally, the results are outputted by the progressive gradient regression tree GBRT in the stacking integration framework and validated using The results were validated using a ten-fold crossover. The results show that the method is effective in portraying online learners, and its accuracy and robustness are improved compared to other algorithms.

Manipulating Auto-Insurance Systems to Minimize Car Accident Rates Among U.S. Teens

This paper explores various auto insurance systems and their impact on teenage driving behaviors and crash rates. The manipulation of auto insurance systems can be effective in minimizing car accident rates among teenage drivers in the United States. Auto insurance systems encompass the regulations governing insurance coverage for motor vehicles, influencing driving behaviors through incentives, penalties, and risk perceptions. The primary auto insurance systems in the U.S. are fault-based, no-fault, add-on, and choice-based systems, each with distinct implications for driving behaviors and road safety. The leading cause of death for teenagers in the U.S. is car accidents, underscoring the urgency of implementing effective strategies to mitigate crash risk among this demographic. The literature review details the factors influencing crash risk among teenagers by highlighting behavioral science theories, and the factors contributing to elevated crash risk among teenage drivers. A meta-analysis was conducted, revealing correlations between insurance system types, driving behaviors, and crash rates among teenagers. Findings suggest that fault-based auto insurance systems, due to their tort liability principles, are the most effective auto insurance systems in promoting safe driving habits among teenage drivers. The fault-based system increases accountability, mitigates moral hazard, and incentivizes cautious driving practices, thereby reducing crash rates. This research provides compelling evidence supporting the adoption of fault-based insurance systems as a critical measure to minimize car accidents among teenage drivers in the United States.

Developing a Pedagogical Approach with the Aim of Empowering Educators and Students to Address Emerging Global Issues such as Climate Change and Social Justice: A Case Study

The “Green Nudges” program, developed within the framework of the United Nations Environment Programme (UNEP), is based on behavioral science and nudge theory. Aimed primarily at universities, it explores ways to adopt a more environmentally friendly lifestyle. Studies show that many young people recognize climate change as a major problem but that it leaves them feeling helpless and anxious—something that our teaching practice confirms. As we had had no success teaching sustainability using conventional approaches, we used the pedagogical design capacity (PDC) principle to develop a novel workshop format and implement it in a pilot series of three repeated workshops. The workshop concept is based on empowering educators and students to tackle emerging global issues while also boosting critical thinking, field research, and teamwork skills. An important part of the integration of different tools was based on supporting students’ self-direction and knowledge- and evidence-based decision making. The results demonstrate that the proposed pedagogical framework resonates with and empowers students. At the same time, the workshop empowers educators to competently navigate complex and sustainability-oriented topics within the field of education for sustainable development (ESD).

Construction of Wu Di Music Culture Education Inheritance Innovation System Based on Clustering Algorithm in the Internet Background

Abstract This paper constructs a blended teaching strategy based on Internet information technology and gives the teaching design of Wu Di music culture education. Behavioral science theory and the K-means clustering algorithm of rough set optimization were used as the guide to construct the behavioral analysis model of students’ learning Wu Di music culture education. The effectiveness of the blended teaching model in the inheritance and innovation of Wu Di music culture education was verified through empirical analysis. The results show that blended teaching can further enhance students’ absorption of Wudi music culture, and the percentage of the experimental class who are very interested in Wudi music culture education is 12.03% higher than that of the control class. The blended teaching mode can enhance students' interest in Wudi music and culture education and contribute to the inheritance and innovation of Wudi music and culture education.

Building the case for a social and behaviour change approach to prevent and respond to the recruitment and use of children by armed forces and armed groups

AbstractOver the last decade, social and behaviour change strategies have increasingly been used to address human rights and child protection concerns, including harmful practices such as child marriage, female genital mutilation and violent discipline. Social and gender norms have also been recognized as key drivers of child recruitment. Nonetheless, the use of social and behaviour change strategies to prevent and respond to the recruitment and use of children in armed conflict has not yet been systematically explored or applied. Building on academic and practical sources, including findings from studies by the International Committee of the Red Cross and United Nations University, social and behavioural science theory, experiences from the Monitoring and Reporting Mechanism on grave violations against children, and academic literature, this article explores how social and behaviour change approaches can inform prevention of and response to the recruitment and use of children in armed conflict. The article concludes that social and behaviour change approaches can effectively inform prevention and reintegration efforts and can facilitate responses that bridge the humanitarian, development and peace nexus. Using social and behaviour change approaches can help to reveal why children are recruited from the perspective of key actors and entities across the socio-ecological framework in order to prevent the practice from becoming more accepted.

Exploration and research of management theory

In this paper, we review the historical changes in the development of four management disciplines, including classical management theory, behavioral science theory and management theory, and modern management theory. Management is then compared and analyzed with other disciplines at the micro and macro levels.

Examining public health practitioners’ perceptions and use of behavioural sciences to design health promotion interventions

BackgroundBehavioural sciences have been shown to support the development of more effective interventions aimed at promoting healthy lifestyles. However, the operationalization of this knowledge seems to be sub-optimal in public health. Effective knowledge transfer strategies are thus needed to optimize the use of knowledge from behavioural sciences in this field. To this end, the present study examined public health practitioners’ perceptions and use of theories and frameworks from behavioural sciences to design health promotion interventions.MethodsThis study adopted an exploratory qualitative design. Semi-structured interviews were conducted among 27 public health practitioners from across Canada to explore current intervention development processes, the extent to which they integrate theory and framework from behavioural sciences, and their perceptions regarding the use of this knowledge to inform intervention design. Practitioners from the public sector or non-profit/private organizations who were involved in the development of interventions aimed at promoting physical activity, healthy eating, or other healthy lifestyle habits (e.g., not smoking) were eligible to participate.ResultsPublic health practitioners generally agreed that behaviour change is an important goal of public health interventions. On the other hand, behavioural science theories and frameworks did not appear to be fully integrated in the design of public health interventions. The main reasons were (1) a perceived lack of fit with current professional roles and tasks; (2) a greater reliance on experiential-produced knowledge rather than academic knowledge (mainly for tailoring interventions to local setting characteristics); (3) the presence of a fragmented knowledge base; (4) the belief that theories and frameworks require too much time and resources to be operationalized; and 4) the belief that using behavioural sciences might undermine partnership building.ConclusionsThis study provided valuable insights that may inform knowledge transfer strategies that could be optimally designed to support the integration of behavioural sciences theories and frameworks into public health practices.

Application of implementation mapping to develop strategies for integrating the National Diabetes Prevention Program into primary care clinics.

Diabetes is considered one of the most prevalent and preventable chronic health conditions in the United States. Research has shown that evidence-based prevention measures and lifestyle changes can help lower the risk of developing diabetes. The National Diabetes Prevention Program (National DPP) is an evidence-based program recognized by the Centers for Disease Control and Prevention; it is designed to reduce diabetes risk through intensive group counseling in nutrition, physical activity, and behavioral management. Factors known to influence this program's implementation, especially in primary care settings, have included limited awareness of the program, lack of standard clinical processes to facilitate referrals, and limited reimbursement incentives to support program delivery. A framework or approach that can address these and other barriers of practice is needed. We used Implementation Mapping, a systematic planning framework, to plan for the adoption, implementation, and maintenance of the National DPP in primary care clinics in the Greater Houston area. We followed the framework's five iterative tasks to develop strategies that helped to increase awareness and adoption of the National DPP and facilitate program implementation. We conducted a needs assessment survey and interviews with participating clinics. We identified clinic personnel who were responsible for program use, including adopters, implementers, maintainers, and potential facilitators and barriers to program implementation. The performance objectives, or sub-behaviors necessary to achieve each clinic's goals, were identified for each stage of implementation. We used classic behavioral science theory and dissemination and implementation models and frameworks to identify the determinants of program adoption, implementation, and maintenance. Evidence- and theory-based methods were selected and operationalized into tailored strategies that were executed in the four participating clinic sites. Implementation outcomes are being measured by several different approaches. Electronic Health Records (EHR) will measure referral rates to the National DPP. Surveys will be used to assess the level of the clinic providers and staff's acceptability, appropriateness of use, feasibility, and usefulness of the National DPP, and aggregate biometric data will measure the level of the clinic's disease management of prediabetes and diabetes. Participating clinics included a Federally Qualified Health Center, a rural health center, and two private practices. Most personnel, including the leadership at the four clinic sites, were not aware of the National DPP. Steps for planning implementation strategies included the development of performance objectives (implementation actions) and identifying psychosocial and contextual implementation determinants. Implementation strategies included provider-to-provider education, electronic health record optimization, and the development of implementation protocols and materials (e.g., clinic project plan, policies). The National DPP has been shown to help prevent or delay the development of diabetes among at-risk patients. Yet, there remain many challenges to program implementation. The Implementation Mapping framework helped to systematically identify implementation barriers and facilitators and to design strategies to address them. To further advance diabetes prevention, future program, and research efforts should examine and promote other strategies such as increased reimbursement or use of incentives and a better billing infrastructure to assist in the scale and spread of the National DPP across the U.S.

DASP: A Framework for Driving the Adoption of Software Security Practices

Implementing software security practices is a critical concern in modern software development. Industry practitioners, security tool providers, and researchers have provided standard security guidelines and sophisticated security development tools to ensure a secure software development pipeline. But despite these efforts, there continues to be an increase in the number of vulnerabilities that can be exploited by malicious hackers. There is thus an urgent need to understand why developers still introduce security vulnerabilities into their applications and to understand what can be done to motivate them to write more secure code. To understand and address this problem further, we propose DASP, a framework for diagnosing and driving the adoption of software security practices among developers. DASP was conceived by combining behavioral science theories to shape a cross-sectional interview study with 28 software practitioners. Our interviews lead to a framework that consists of a comprehensive set of 33 drivers grouped into 7 higher-level categories that represent what needs to happen or change so that the adoption of software security practices occurs. Using the DASP framework, organizations can design interventions suitable for developers' specific development contexts that will motivate them to write more secure code.

Making Sense of Theories, Models, and Frameworks in Digital Health Behavior Change Design: Qualitative Descriptive Study.

Digital health interventions are increasingly being designed to support health behaviors. Although digital health interventions informed by behavioral science theories, models, and frameworks (TMFs) are more likely to be effective than those designed without them, design teams often struggle to use these evidence-informed tools. Until now, little work has been done to clarify the ways in which behavioral science TMFs can add value to digital health design. The aim of this study was to better understand how digital health design leaders select and use TMFs in design practice. The questions that were addressed included how do design leaders perceive the value of TMFs in digital health design, what considerations do design leaders make when selecting and applying TMFs, and what do design leaders think is needed in the future to advance the utility of TMFs in digital health design? This study used a qualitative description design to understand the experiences and perspectives of digital health design leaders. The participants were identified through purposive and snowball sampling. Semistructured interviews were conducted via Zoom software. Interviews were audio-recorded and transcribed using Otter.ai software. Furthermore, 3 researchers coded a sample of interview transcripts and confirmed the coding strategy. One researcher completed the qualitative analysis using a codebook thematic analysis approach. Design leaders had mixed opinions on the value of behavioral science TMFs in digital health design. Leaders suggested that TMFs added the most value when viewed as a starting point rather than the final destination for evidence-informed design. Specifically, these tools added value when they acted as a gateway drug to behavioral science, supported health behavior conceptualization, were balanced with expert knowledge and user-centered design principles, were complementary to existing design methods, and supported both individual- and systems-level thinking. Design leaders also felt that there was a considerable nuance in selecting the most value-adding TMFs. Considerations should be made regarding their source, appropriateness, complexity, accessibility, adaptability, evidence base, purpose, influence, audience, fit with team expertise, fit with team culture, and fit with external pressures. Design leaders suggested multiple opportunities to advance the use of TMFs. These included improving TMF reporting, design, and accessibility, as well as improving design teams' capacity to use TMFs appropriately in practice. When designing a digital health behavior change intervention, using TMFs can help design teams to systematically integrate behavioral insights. The future of digital health behavior change design demands an easier way for designers to integrate evidence-based TMFs into practice.

Guidance through the jungle of behavioral science theories, models, and concepts for non-behavioral scientists

ABSTRACT Interdisciplinary research is becoming increasingly important to tackle complex problems such as climate change. Human behavior is one key factor that needs to be considered to find solutions to these complex problems. Working in an interdisciplinary field requires scientists to engage in tedious studies of disciplines that are beyond their core expertise. This is also true for the selection of behavioral science approaches best suitable for the research question at hand. To provide a concise introduction to behavioral science, this article provides four clusters of behavioral science approaches. These four clusters, in conjunction with the further developed 4 DBC framework, can assist the analyst in systematically selecting the most suitable behavioral science approach. To illustrate the application of the framework, the examples of cycling and Practice Theory are used.

Occupant preferences on the interaction with human-centered control systems in school buildings

Human-centered control systems in buildings have gained increasing attention in recent years as they foster the integration of user preferences in the decision-making control algorithm. However, such advanced systems are built upon the assumption that occupants are willing to interact as data providers. Introducing technologies reliant on feedback from the users, without initially analysing how users accept them, can lead to impeding the anticipated operation of such systems. Hence, this rare interdisciplinary research presents a nexus of technical and social sciences, that addresses the occupant-related misconceptions regarding the interaction with advanced control systems. This study identifies the occupant preferences and provides a method to predict the willingness of occupants to interact with advanced control for indoor environment control and demand-response actions. Additionally, the proposed approach enables to identify the main drivers and motivators of that interaction. This study is built upon the behavioural science theory called the Theory of Planned Behaviour and 435 school building occupants participated in the study. The findings from this pertinent research show that many common concepts in the building control domain do not comply with the occupants’ viewpoint and need to be reconsidered. For instance, in the post-pandemic era, the most important comfort aspect according to the occupants is the indoor air quality compared to thermal and visual comfort. Furthermore, although higher automation levels are desired, control access through advanced technologies, such as human-centered control, is not easily accepted by occupants. Hence, their willingness for interaction should be predicted instead of assuming that occupants will share data with advanced control systems. The proposed model in this research has predictive potential and yielded an explained variance of 58%, showing that the target occupants of the building are willing to interact with the controller. These findings are important to researchers and practitioners who design and develop human-centered control systems to foresee the engagement level of occupants in indoor environment control or demand-response actions.

Evaluating the effect of short-course rifapentine-based regimens with or without enhanced behaviour-targeted treatment support on adherence and completion of treatment for latent tuberculosis infection among adults in the UK (RID-TB: Treat): protocol for an open-label, multicentre, randomised controlled trial

IntroductionThe successful scale-up of a latent tuberculosis (TB) infection testing and treatment programme is essential to achieve TB elimination. However, poor adherence compromises its therapeutic effectiveness. Novel rifapentine-based regimens and...