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Purpose The integrated reporting framework seeks to connect a firm’s financial and non-financial performance in a single report by displaying how different forms of capital contribute to the firm’s value creation. Drawing on impression management and incremental information approaches, the purpose of this paper is to examine how the content and semantic properties of intellectual capital disclosure (ICD) found in integrated reports is associated with firms’ performance. Design/methodology/approach All reports by European listed firms from 2011 to 2016 available via the integrated reporting emerging practice examples database are analysed. Content analysis is used to assesses the quality of ICDs, whereas a regression analysis tests the variation in semantic properties of ICDs according to firms’ performance. Findings ICDs in integrated reports are mainly discursive, with a backward looking orientation and a limited focus on human capital. On average, more than half of each ICD is conveyed in a positive tone. As the optimistic tone in firms’ ICDs increases, so too does their non-financial performance measured in terms of environmental, social and governance aspects. This finding supports the incremental information approach. Originality/value This paper contributes to the current literature on ICDs by introducing new evidence on firms’ motivations for non-financial disclosures in integrated reports. By taking a more comprehensive theoretical approach, namely, testing both impression management and incremental information hypotheses, this research extends on prior studies which tested similar relationships in integrated reports but focussed only on the impression management hypothesis.

Objective To summarize current evidence on patient and public involvement (PPI) in health technology assessment (HTA) in order to synthesize the barriers and facilitators, and to propose a framework to assess its impact. Methods We conducted an update of a systematic review published in 2011 considering the recent scientific literature (qualitative, quantitative, and mixed-methods studies). We searched papers published between March 2009 (end of the initial search) and December 2019 in five databases using specific search strategies. We identified other publications through citation tracking and contacting authors of previous related studies. Reviewers independently selected relevant studies based on prespecified inclusion and exclusion criteria. We extracted information using a pre-established grid. Results We identified a total of 7872 publications from the main search strategy. Ultimately, thirty-one distinct new studies met the inclusion criteria, whereas seventeen studies were included in the previous systematic review. PPI is realized through two main strategies: (i) patients and public members participate directly in decision-making processes (participation) and (ii) patients or public perspectives are solicited to inform decisions (consultation or indirect participation). This review synthesizes the barriers and facilitators to PPI in HTA, and a framework to assess its impact is proposed. Conclusion The number of studies on patients or public involvement in HTA has dramatically increased in recent years. Findings from this updated systematic review show that PPI is done mostly through consultation and that direct involvement is less frequent. Several barriers to PPI in HTA exist, notably the lack of information to patients and public about HTA and the lack of guidance and policies to support PPI in HTA.

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.

This study’s purpose is twofold. On the one hand, it analyzes the relationship between the profitability of firms and the tone of nonfinancial disclosures; on the other hand, it tests the relationship between the environmental, social, and governing (ESG) performance of firms and the tone of nonfinancial disclosures on the automotive sector under two different and competing approaches, which are incremental information and impression management. The sample is composed of 68 nonfinancial reports issued by 17 automotive organizations between the years 2016 and 2020. Data analysis proceeded in two stages. First, a content analysis was performed to assess the linguistic attributes of the nonfinancial disclosure. Second, an inferential regression analysis was performed to test the hypothesized associations between firms’ performance and tone of their disclosures. The results of this study are aimed at providing evidence of the determinants of the verbal tone in the corporate nonfinancial reporting in a specific industry.