Linköping University

Intermediary actors are key catalysts in accelerating sustainability transitions. Over the last decade, the literature on intermediaries and intermediation has expanded rapidly, leading to inconsistent use of the concept, proliferating lists of intermediary activities, and questions about their impact on transition processes. These challenges risk making the concept inaccessible and limiting its practical relevance. This chapter provides an accessible introduction to intermediaries in sustainability transitions, followed by a historical account of the concept's development. It then presents empirical examples of intermediaries and their activities, highlighting a key gap: the lack of an explicit theory on why intermediaries exist in transition processes. To address this gap, we propose a theory on why intermediaries exist in transitions and position intermediaries alongside other actors such as system entanglers, orchestrators, and champions. The chapter ends with future research directions, emphasizing the need to move beyond individual intermediaries to ecologies of intermediation as multiple transitions accelerate and interact.

Recent years have seen a sharply rising interest on the scientific area dedicated to study of use of Artificial Intelligence (AI) for Cognitive Behavioral Therapy (CBT) research and applications (AI4CBT for brevity). Yet, little is known about how this interest is realized and hence the overall status, prospects, and possible challenges of AI4CBT as a field (e.g. breadth of the field, key topics and methods, key producing countries/institutions/authors, interdisciplinary grounding). This paper addresses this gap by developing a broad-spectrum bibliometric analysis towards acquiring a comprehensive overview of the AI4CBT field. Four key dimensions are analyzed (productivity, producers, productions, and contents) along array of bibliographic metrics, including: production trends over time, leading contributors at various levels, co-authorship, citation, and keywords co-occurence networks, publication formats, key venues, methodological trends, and disciplinary assessment. The paper concludes by framing the status of AI4CBT as a scientific field, allowing to tie it to scientific and applicative challenges and opportunities that AI4CBT may encounter and offer as it further develops.

Aim To evaluate healthcare professionals' perspectives on factors that lead to success in the implementation of strategies to strengthen evidence‐based surgical nursing care. Design A qualitative study design with focus group interviews, according to Krueger and Casey in a surgical department at a university hospital in Sweden. Methods Four focus groups were conducted with 18 participants, including specialist nurses in surgical care, registered nurses and assistant nurses. Data were collected in February–March 2024. A semi‐structured interview guide was used, and data were analysed using qualitative content analysis. Results Three themes with seven subthemes were developed to capture the evaluation of health care professionals' perspectives of the implementation strategies to strengthen evidence‐based surgical nursing care. The themes were (1) Roles and leadership, (2) Engagement in the implementation, and (3) Facilitators and barriers to implementation. The implementation has meant the transition from theory to practice and integrating new routines into the surgical department. It was a learning process where the health care professionals needed to familiarise themselves with new concepts and working methods. The positive outcome of the project and support from the nursing leadership were important facilitators in the implementation process. Conclusions The implementation of new ways of working was a complex process with both resistance and learning, but it ultimately led to positive changes in the surgical care environment. Implications for the Profession and Impact The project has entailed that specialist nurses in surgical care have increased nursing power in the department and extended responsibilities. Support from the head of the department and the management team has been crucial to being able to carry out the project, and the implementation of activities in small steps has been successful. Reporting Method Adhered to the SRQR guidelines. Patient or Public Contribution No patient or public contribution.

Background Generative Artificial Intelligence (GAI) has significantly impacted education at all levels, including health professional education. Understanding students’ experiences is essential to enhancing AI literacy, adapting education to GAI, and implementing GAI technology. Therefore, the aim was to explore physiotherapy students’ experiences of and thoughts on GAI in their education, and its potential implications for their future careers in healthcare. Methods Qualitative descriptive design. Focus groups were conducted, using a semi-structured interview guide, at the Physiotherapy program at Linköping University, Sweden, from March to April 2024. The 15 students were organized into three focus groups, one for each education year. The data was analyzed using inductive content analysis. Results An overarching theme “GAI—Great potential if navigating the challenges” emerged from three categories: 1) “Areas of GAI use in the learning process”: Students viewed GAI as a tool for introduction and inspiration, assimilating course content and enhancing clinical reasoning and problem-solving; 2) “Optimizing GAI use in education”: Students found GAI to be timesaving, tailored, and as a virtual study partner and teacher. They discussed the pros and cons of learning, concerns on permitted GAI usage, the need for a critical approach, and how individual experiences and interests influenced their interactions with GAI; 3) “Future with GAI in education and profession”: Students believed future GAI would be more reliable, use subject-specific GAI models and enhance health care delivery, but also pose risks related to profit motives and knowledge gaps. Conclusion Physiotherapy students found GAI beneficial for learning and clinical reasoning but expressed concerns about its impact on learning quality. They emphasized the importance of a critical approach when using GAI and the need for organizational support, including supporting permitted GAI use. Students believed that future advanced GAI models could provide accurate and reliable educational tools and healthcare tools supporting documentation and evidence-based decision-making. However, potential risks include business profit motives and knowledge gaps. Navigating these challenges is essential to fully leveraging GAI’s benefits in education and physiotherapy practice. Therefore, fostering a critical approach and ensuring robust organizational support is crucial for maximizing the positive impact of GAI in physiotherapy.

The gut microbiota plays a pivotal role in human life and undergoes dynamic changes throughout the human lifespan, from infancy to old age. During our life, the gut microbiota influences health and disease across life stages. This review summarizes the discussions and presentations from the symposium “Gut microbiota development from infancy to old age” held in collaboration with the Journal of Internal Medicine. In early infancy, microbial colonization is shaped by factors such as mode of delivery, antibiotic exposure, and milk‐feeding practices, laying the foundation for subsequent increased microbial diversity and maturation. Throughout childhood and adolescence, microbial maturation continues, influencing immune development and metabolic health. In adulthood, the gut microbiota reaches a relatively stable state, influenced by genetics, diet, and lifestyle. Notably, disruptions in gut microbiota composition have been implicated in various inflammatory diseases—including inflammatory bowel disease, Type 1 diabetes, and allergies. Furthermore, emerging evidence suggests a connection between gut dysbiosis and neurodegenerative disorders such as Alzheimer's disease. Understanding the role of the gut microbiota in disease pathogenesis across life stages provides insights into potential therapeutic interventions. Probiotics, prebiotics, and dietary modifications, as well as fecal microbiota transplantation, are being explored as promising strategies to promote a healthy gut microbiota and mitigate disease risks. This review focuses on the gut microbiota's role in infancy, adulthood, and aging, addressing its development, stability, and alterations linked to health and disease across these critical life stages. It outlines future research directions aimed at optimizing the gut microbiota composition to improve health.

The design and operation of integrated energy systems requires considering the interaction between multiple infrastructures, each with its distinctive features. For instance, the network topology and the physical phenomena involved in the transmission of different energy vectors hugely affect the energy flows, impacting the efficiency and vulnerability of the energy grid as a whole. Graph-theoretical complex network analysis, and specifically multilayer networks, provide a powerful modelling technique to assess the interdependence between different energy infrastructures. The relevance of this integrated approach becomes evident as the number of installed energy converters, such as cogenerators, fuel cells and electric heat pumps, increases and affects the energy flows across these infrastructures. In this chapter, complex network analysis, commonly employed for individual energy networks, is extended to multi-energy systems, modelled as multilayer networks interacting through energy hubs. The case study, based on a benchmark power grid coupled with a gas network, demonstrates the capabilities of multilayer networks to model multi-energy systems and detect hidden features arising from the interdependence between multiple energy carriers.

Depolarization-evoked opening of CaV2.1 (P/Q-type) Ca²⁺-channels triggers neurotransmitter release, while voltage-dependent inactivation (VDI) limits channel availability to open, contributing to synaptic plasticity. The mechanism of CaV2.1 response to voltage is unclear. Using voltage-clamp fluorometry and kinetic modeling, we optically track and physically characterize the structural dynamics of the four CaV2.1 voltage-sensor domains (VSDs). The VSDs are differentially sensitive to voltage changes, both brief and long-lived. VSD-I seems to directly drive opening and convert between two modes of function, associated with VDI. VSD-II is apparently voltage-insensitive. VSD-III and VSD-IV sense more negative voltages and undergo voltage-dependent conversion uncorrelated with VDI. Auxiliary β-subunits regulate VSD-I-to-pore coupling and VSD conversion kinetics. Hence, the central role of CaV2.1 channels in synaptic release, and their contribution to plasticity, memory formation and learning, can arise from the voltage-dependent conformational changes of VSD-I.

Wellness is an increasingly important part of public health and can prevent both disease and death. Diet and nutrition are important factors that contribute to wellness and predict health outcomes. Adhering to healthy diets is notoriously difficult for many, and some support is often required. Increasingly, that support may be found in the shape of an app in a smartphone. One such app is Lifesum, with some 65 million users worldwide. Lifesum adopts a more holistic approach to nutrition and well-being, and adopted an evidence-based approach to its development. The aim of this study was to describe the scientific, theoretical basis for the Lifesum app and contribute to advancing science in the field of wellness app development. This was an intervention design analysis, designed to describe the theoretical model and intervention theory used to create the Lifesum app in its current embodiment. A pragmatic theoretical model describing behaviour change in the context of healthy eating was devised based on findings in literature. Factors that drive unhealthy eating behaviours, but that were malleable and whose mechanisms of change were feasible to implement, were identified and used to form an intervention theory. The theoretical model and the intervention theory could then guide the implementation of the Lifesum app, illustrated by a logic model. The theoretical model emphasizes personal goal-attainment and motivation as keys to establishing and maintaining healthy eating behaviours, with proximal outcomes being nutrition knowledge, mindfulness about eating and macro-nutrient balance. Nutrition knowledge is achieved through the provision of nutrition information from a vast database on food items, easily available. Continuous feedback on food choices made will enhance this knowledge and a greater awareness of the impact of nutrition on health remains desirable. A more mindful disposition regarding foods is achieved through support in terms of tracking food intake continuously, as well as recommending meals or recipes. After collecting user preferences on health status, biometrics and goals, these meal plans and recipes can be made to offer the optimal macro-nutrient distribution for each individual user. A theoretical model for diet-related behavior change was developed and key dietary issues were identified, outlining mechanisms for positive impact. These insights informed a mechanistic description of the Lifesum app, providing a foundation for future research on intervention outcomes.

Molecular switches based on the norbornadiene-quadricyclane (NBD-QC) isomer pair are among the most promising candidates for applications in molecular solar thermal energy storage (MOST). In these compounds, solar energy is captured through a photoinduced [2 + 2] cycloaddition reaction whose mechanism is only partially understood. This holds true especially for NBD derivatives containing the type of push-pull substitution pattern that was previously proven necessary to attain reasonable photoisomerization quantum yields. In the present contribution, we report a computational investigation of the photochemistry of NBD-QC switches with precisely such a substitution pattern. Static calculations provide information on the structures of the excited electronic states involved in the photoinduced cycloaddition reaction, and the topographies of the relevant ground- and excited-state potential energy surfaces. Furthermore, nonadiabatic molecular dynamics (NAMD) simulations allow an estimation of the reaction time scale and quantum yield. The simulation results paint a detailed picture of the energy capture process: the photoinduced cycloaddition reaction begins in the spectroscopically bright excited state of the molecular switch. In the model compound for which we performed NAMD simulations, ring closing takes place on a time scale of roughly 150 fs, which makes it one of the fastest known photoisomerization reactions.

This article presents a homothetic tube‐based adaptive model predictive control strategy to handle discrete‐time linear time‐invariant (LTI) systems with parametric uncertainties and hard constraints imposed on the states and the control inputs. The proposed solution systematically fuses a gradient descent‐based adaptive parameter identification strategy with a suitably designed tube‐based model predictive controller (MPC). An estimated model is utilized in the MPC for the purpose of state predictions. The parameters of the estimated plant model are updated at every time instant through an adaptive update law by utilizing the measured states and inputs from the uncertain plant. The task of satisfying the hard constraints in the presence of errors in state predictions, arising due to model mismatch between the estimated model and the uncertain plant, is accounted for by suitably tightening the constraints within the MPC optimization routine. The proposed tube‐based adaptive MPC is analytically proved to be recursively feasible if initially feasible, and the closed‐loop states are guaranteed to be bounded and asymptotically converging to the origin. The claimed properties are further validated through a simulation example.

New research shows the benefits of mobile health (mHealth) interventions for older adults. However, older adults adopt digital technology less than younger ones. This study measures the task effectiveness, perceived usability, and acceptability of a mHealth intervention (i.e., Get FIT +) consisting of a wearable activity tracker, access to the MyFitnessPal app, and personalized text messages to promote healthy behaviors in older adults. Participants used the Get FIT + intervention for 12 weeks and engaged in monthly clinic visits with an advanced practice nurse (APRN) to monitor their progress. The monthly sessions instructed them to use the think-aloud process while doing specific tasks (e.g., using the app). Participants also completed the USABILITY Survey and provided feedback on the intervention’s acceptability after the 12-week trial. Thirty older adults (mean age 66.6 ± 5.9 years, 60% female, 60% married, 50% Asian, 37% White, and 13% Hispanic) participated in this sub-analysis. Participants were able to complete the assigned tasks efficiently. The usability satisfaction assessment suggests a high level of satisfaction. The participants responded positively to Get FIT + and successfully incorporated it into their routines. Our findings show that Get FIT + technologies, including smartphones, smartphone-based applications, and integrated sensors, are practical, usable, and acceptable for older adults at risk for cardiovascular disease. These scalable, low-cost technologies offer methods to monitor and promote a healthy lifestyle and enhance overall well-being.

The present study aimed to describe the prevalence rates of frequent (i.e., at least weekly) dream recall and nightmares with consideration for differences in age, gender and sleep duration in 16 countries using equivalent assessment methods. The study sample included 15,854 participants (69.9% women) aged 18–99 years ( M = 42.39, SD = 16.43) collected by the International COVID‐19 Sleep Study collaboration, which used a unified online survey to collect data from May to November 2021 across 16 countries. Participants provided demographic information as well as self‐reported estimates of their dream recall and nightmare frequency and sleep duration in 2021 and retrospectively for 2019. Frequent dream recall occurred in 54.0% of participants in 2021 and 51.1% in 2019. Frequent nightmares were reported by 11.0% of participants in 2021 and 6.9% in 2019. Ad hoc regression models found dream recall and sleep duration to have a linear relation, whereas nightmare frequency demonstrated a quadratic relation to sleep duration. Frequent dream recall and nightmare prevalence rates are reported for each of the 16 study countries by age, gender and sleep duration. This is the first multi‐continent study to estimate frequent dream recall and nightmare prevalence, which both provides updated prevalence rates during the COVID‐19 pandemic as well as extends existing knowledge to previously never studied countries.

Spatiotemporal metaphors strongly affect our language about time. Time can be construed as an object that moves through space (time flies) or as a landscape through which we move (we are heading towards the weekend). Evidence of how speakers construe time can be found by observing their gestures. This study explores spatial constructions of time in co-speech gestures during programming lectures in Swedish upper-secondary classrooms. Data were collected from teachers' co-speech gestures while lecturing on programming, a context rich in temporal and sequential references. The results show that the teachers gesture in three directions, each with a specific function. Gestures along the vertical axis are used to talk about writing code as events on a vertical timeline. The programming convention where code lines are ordered top-down, indicating events in a particular order, is suggested as an explanation. Gestures along the sagittal axis are used when the teachers take an internal perspective. Gestures along the lateral axis are used when discussing events. This is a first exploration of how time concepts are construed in Swedish programming classrooms. The research provides a foundation for more extensive studies on the role of co-speech gestures in conceptualising time, particularly in educational settings involving technological interfaces.

To study the impact of the COVID‐19 pandemic on sleep and circadian rhythms—two fundamental pillars for health—the collaboration International COVID‐19 Sleep Study (ICOSS) was established. The present overview comprehensively discusses the findings from this collaboration. Involving sleep researchers across the globe, ICOSS used a harmonised questionnaire to cover changes in sleep and sleep disorders, as well as physical and mental health. Two survey waves were conducted, one in 2020 and another one in 2021. In ICOSS‐1, a total of 26,539 people from 14 countries across four continents (Europe, Asia, North and South America) participated. In ICOSS‐2, two more countries joined ICOSS, and 15,813 people participated. The focus in ICOSS‐2 was on Long COVID. Participants accessed the widely disseminated online surveys in their native language. In the 20 papers published so far, the surveys have uncovered several novel findings, including how the pandemic impacted sleep patterns, the prevalence of sleep disorders, chronotype‐based differences and sleep‐immune system interactions. To the best of our knowledge, there is no other large‐scale multinational study targeting the general population investigating the role of sleep and sleep disorders alongside a variety of psychological, biological, social and economic factors during the recent COVID‐19 pandemic.

Purpose The aim of this study was to translate the health-related quality-of-life questionnaire EORTC QLQ-LMC21 into Swedish and to test its clinical and psychometric reliability and validity in patients with liver metastases from colorectal cancer (CRC) undergoing surgical treatment. Methods The Swedish versions of the EORTC QLQ-C30 and EORTC QLQ-LMC21 were administered to 250 patients with liver metastases from CRC in four Swedish hospitals before and 3 months after surgical treatment. Psychometric validation of the questionnaire´s structure, reliability, and convergent and divergent validity was performed. Results Data from 242 (97%) patients were suitable for analysis. The QLQ-LMC21 was found to be sensitive to changes over time. Cronbach´s alpha coefficient indicated good internal consistency, ranging from 0.84 to 0.89. Test–retest reliability was evaluated in 120 patients (49%), and the intraclass correlation coefficient (ICC) indicated good reproducibility, ranging from 0.67 to 0.93. Convergent and discriminant validity were demonstrated adequately in the multitrait scaling analysis. There were weak correlations between the QLQ-C30 and QLQ-LMC21, which confirms that the health problems addressed by the QLQ-LMC21 are different from those addressed by the QLQ-C30. Conclusions The Swedish version of the EORTC QLQ-LMC21 proved to be a valid and reliable questionnaire to use in conjunction with the EORTC QLQ-C30.