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This paper focuses on knowledge sharing in health care. The aim of the paper is to further understand how digital applications can facilitate knowledge sharing between different care providers and health-care professionals.

The paper is based on a qualitative action case study, performed as a formative intervention study as a Change Laboratory, where a digital application concerning wound support was used. The Change Laboratory was used for knowledge sharing in the assessment and treatment process of wounds. The collected data was then thematically analyzed.

The findings show how digital applications can facilitate knowledge sharing, but also the need for complementary collaborative sessions. The main contribution is the rich description of how digital applications together with these sessions can facilitate knowledge sharing.

This paper shows that activities as collaborative sessions performed on the organizational level prove to support knowledge sharing and learning when a new digital application has been implemented in the work process. It also shows that these sessions contributed to identifying new knowledge that has potential for being included in the application and hence are important to keeping the application updated and relevant over time.

This study aims to explore the management learning during a long-term crisis like a pandemic. The paper addresses both what health-care managers have learnt during the COVID-19 pandemic and how the management learning is characterized.

The paper is based on a qualitative case study carried out during the COVID-19 pandemic at two different public hospitals in Sweden. The study, conducted with semi-structured interviews, applies a combination of within-case analysis and cross-case comparison. The data were analyzed using thematic deductive analysis with the themes, i.e. sensemaking, decision-making and meaning-making.

The COVID-19 pandemic was characterized by uncertainty and a need for continuous learning among the managers at the case hospitals. The learning process that arose was circular in nature, wherein trust played a crucial role in facilitating the flow of information and enabling the managers to get a good sense of the situation. This, in turn, allowed the managers to make decisions meaningful for the organization, which improved the trust for the managers. This circular process was iterated with higher frequency than usual and was a prerequisite for the managers’ learning. The practical implications are that a combined management with hierarchical and distributed management that uses the normal decision routes seems to be the most successful management method in a prolonged crisis as a pandemic.

The gained knowledge can benefit hospital organizations, be used in crisis education and to develop regional contingency plans for pandemics.

This study has explored learning during the COVID-19 pandemic and found a circular process, “the management learning wheel,” which supports management learning in prolonged crises.

To meet future healthcare needs, primary care is undergoing a transformation in which innovations and new ways of working play an important role. However, successful innovations depend on joint learning and rewarding collaborations between healthcare and other stakeholders. This study aims to explore how learning develops when entrepreneurs, healthcare professionals and older people collaborate in a primary care living lab.

The study had an action research design and was conducted at a clinically embedded living lab at a primary care centre on the west coast of Sweden. Data consisted of e-mail conversations, recordings from design meetings and three group interviews with each party (entrepreneurs, healthcare professionals and older people). Data were analysed with inductive qualitative content analysis.

An overarching theme, “To share each other’s worlds in an arranged space for learning”, was found, followed by three categories, “Prerequisites for learning”, “Strategies to achieve learning” and “To learn from and with each other”. These three categories comprise eight subcategories.

This research contributes to knowledge regarding the need for arranged spaces for learning and innovation in primary care and how collaborative learning can contribute to the development of practice.

This paper presents findings from a qualitative study of healthcare professionals’ practice, where learning is taking place when a digital artefact is implemented for identification of patients’ cognitive impairment. The use of digital artefacts is increasing in various workplaces, to include professionals in healthcare. This paper aims to explore the following research question: How is the professional learning unfolding in patient-based work when a digital artefact transforms the practice?

Various data collection methods are used for this study, consisting of dialogue meetings, interviews and a reference-group meeting. Thematic analysis is used to inductively bring forth the themes of the collected data.

Professionals’ knowledge and experience are of vital importance in learning and changing work practices. Together with their ability to reflect on changes, their knowledge and experience constitute the prefiguration when the introduction of a digital application brings about indeterminacy in the work practice.

This paper makes a contribution to practice-based research as it consolidates previous research and identifies professionals knowledge and learning in a healthcare context. This can be used to further explore and advance the field, as well as to establish the evidence-based importance of transforming practices based on implementation of digital artefacts.

We investigate how career disruptions in terms of job loss may impact morbidity for individuals diagnosed with type 2 diabetes (T2D). Combining unique, high-quality longitudinal data from the Swedish National Diabetes Register (NDR) with matched employer–employee data, we focus on individuals diagnosed with T2D, who are established on the labor market and who lose their job in a mass layoff. Using a conditional difference-in-differences evaluation approach, our results give limited support for job loss having an impact on health behavior, diabetes progression, and cardiovascular risk factors.

Library and information science (LIS) and the digital humanities are both interested in studying recorded information and often share institutional frameworks. The purpose of this paper is to go beyond outlining these similarities by examining the perceived and real strengths and weaknesses of both disciplines.

Epistemologies and methods of both disciplines are analysed, principally in the light of the growing importance of data-intensive research, taking into consideration that there is a tension about the academic status of these disciplines.

Epistemologies and methods of both disciplines are analysed, principally in the light of the growing importance of data-intensive research, taking into consideration that there is a tension about the academic status of these disciplines.

The paper intends to be an add-on to the recent discussions and the evolving body of knowledge about the relationship of these disciplines with the hope of indicating a possible new direction in the development of LIS.

This paper aims to investigate whether the amount of local governments’ debt can be predicted by the level of political competition.

The study uses the artificial neural network (ANN) to test whether ANN can “learn” from the observed data and make reliable out-of-sample predictions of the target variable value (i.e. a local government’s debt level) for given values of the predictor variables. An ANN is a non-parametric prediction tool, that is, not susceptible to the common limitations of regression-based parametric forecasting models, e.g. multi-collinearity and latent non-linear relations.

The study finds that “political competition” is a useful predictor of a local government’s debt level. Moreover, a positive relationship between political competition and debt level is indicated, i.e. increases in political competition typically leads to increases in a local government’s level of debt.

The study contributes to public sector reporting literature by investigating whether public debt levels can be predicted on the basis of political competition while discounting factors such as “political ideology” and “fragmentation”. The findings of the study are consistent with the expectations posited by public choice theory and have implications for public sector auditing, policy and reporting standards, particularly in terms of minimising potential political opportunism.