Increasingly aware of the importance of active lifestyles, many people intend to exercise more. One of the main challenges is to translate exercise intentions into actual exercise behaviour, the so-called intention-behaviour gap. To investigate barriers and enablers that affect this gap, we conducted a 7-day diary study with 16 women. Participants indicated what their exercise intentions and behaviour were per day, and whether and why they changed retrospectively during the day. Through the diary study, we gain insights into (i) the intention-behaviour interplay, and (ii) the experienced barriers and enablers that influence this interplay throughout the day. Based on the findings, we contribute new implications for design in supporting people translating their intentions into exercise behaviour. We propose three design concepts to illustrate underlying design opportunities. The focus is on positively influencing the interplay of enablers and barriers of exercising and how these can be addressed through design
DOCUMENT
Agent-based modeling (ABM) is a widely used method for evaluating demand response (DR) strategies. To comprehensively assess the impact of DR strategies on a district cooling system, the integration of building managers’ DR behavior is essential. However, most ABM studies focus on technical optimization while overlooking the behavioral factors that may exist in building managers’ decision-making processes. To address this gap, this paper introduces an agent-based model using the belief-desire-intention (BDI) framework to simulate building managers’ air-conditioning setpoint adjustment behavior under DR, integrating the reasoning capabilities and irrational behavior factors.
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Background: The need for effective continuing education is especially high in in-hospital geriatric care, as older patients have a higher risk of complications, such as falls. It is important that nurses are able to prevent them. However, it remains unknown which interventions change the behavior of nurses. Therefore, the aim of this study is to identify intervention options to change the behavior of hospital nurses regarding fall prevention among older hospitalized patients. Methods: This study used a mixed method design. The Behavior Change Wheel (BCW) was used to identify intervention functions and policy categories to change the behavior of nurses regarding fall prevention. This study followed the eight steps of the BCW and two methods of data collection were used: five focus groups and three Delphi rounds. The focus groups were held with hospital nurses (n = 26). Geriatric experts (n = 11), managers (n = 13) and educators (n = 13) were included in the Delphi rounds. All data were collected within ten tertiary teaching hospitals in the Netherlands. All participants were included based on predefined in- and exclusion criteria and availability. Results: In Geriatric experts’ opinions interventions targeting behavior change of nurses regarding fall prevention should aim at ‘after-care’, ‘estimating fall risk’ and ‘providing information’. However, in nurses’ opinions it should target; ‘providing information’, ‘fall prevention’ and ‘multifactorial fall risk assessment’. Nurses experience a diversity of limitations relating to capability, opportunity and motivation to prevent fall incidents among older patients. Based on these limitations educational experts identified three intervention functions: Incentivisation, modelling and enablement. Managers selected the following policy categories; communication/marketing, regulation and environmental/social planning. Conclusions: The results of this study show there is a discrepancy in opinions of nurses, geriatric experts, managers and educators. Further insight in the role and collaboration of managers, educators and nurses is necessary for the development of education programs strengthening change at the workplace that enable excellence in nursing practice. DOI: https://doi.org/10.1186/s12912-021-00598-z
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SOCIO-BEE proposes that community engagement and social innovation combined with Citizen Science (CS) through emerging technologies and playful interaction can bridge the gap between the capacity of communities to adopt more sustainable behaviours aligned with environmental policy objectives and between the citizen intentions and the real behaviour to act in favour of the environment (in this project, to reduce air pollution). Furthermore, community engagement can raise other citizens’ awareness of climate change and their own responses to it, through experimentation, better monitoring, and observation of the environment. This idea is emphasised in this project through the metaphor of bees’ behaviour (with queens, working and drone bees as main CS actors), interested stakeholders that aim at learning from results of CS evidence-based research (honey bears) and the Citizen Science hives as incubators of CS ideas and projects that will be tested in three different pilot sites (Ancona, Marousi and Ancona) and with different population: elderly people, everyday commuters and young adults, respectively. The SOCIO-BEE project ambitions the scalable activation of changes in citizens’ behaviour in support of pro-environment action groups, local sponsors, voluntary sector and policies in cities. This process will be carried out through low-cost technological innovations (CS enablers within the SOCIO BEE platform), together with the creation of proper instruments for institutions (Whitebook and toolkits with recommendations) that will contribute to the replication, upscaling, massive adoption and to the duration of the SOCIO-BEE project. The solution sustainability and maximum outreach will be ensured by proposing a set of public-private partnerships.For more information see the EU-website.
