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This paper aims to demonstrate how the design of data visualisations can act as a tool to support social marketing messages in prompting behaviour change to reduce food waste using the Elaboration Likelihood Model (ELM) as a theoretical framework. It also responds to a lack of consumer-led insight to develop campaigns in reducing food waste.

The research uses data collected by the End Food Waste Cooperative Research Centre (EFW CRC) in Australia to determine which text-based campaign messages are most likely to prompt people toward reducing food waste. Behaviour change messages were first identified through workshops with 11 food waste experts, then explored through online focus group discussions with 18 participants from three food-wasting market segments. The messages were further tested via a quantitative survey among 1,000 decision makers in Australian households in their own homes, with the top three performing messages examined using summative content analysis.

The significant findings were that participants want to see 1) evidence of how adopting new behaviours would lead to financial savings and benefit the environment, and 2) concrete steps to reduce food waste. When examined through the ELM, the findings suggest that tools that encourage both cognitive and peripheral processing as a means of persuasion, like data visualisations, may be useful for changing food-wasting behaviours.

Applying principles from the field of communication design to the ELM has uncovered the potential for a cross-disciplinary approach to enhance theoretical frameworks for understanding consumer engagement with messages. This process in turn, may lead to the development of more effective behaviour change marketing strategies.

Six principles for using data visualisations in a social marketing campaign are proposed: personal relevance, ease of use, emotional storytelling, context, prioritising the message itself and long-term usage.

This study proposes that data visualisations could enhance the effectiveness of social marketing campaigns by leveraging consumer-derived insights and the persuasive capacity inherent in their theoretical underpinnings.

Ageing is associated with multi-morbidity, polypharmacy and medication-related harm (MRH). There is limited published literature on MRH in older Egyptian adults. This study aims to determine the incidence and risk factors associated with MRH in an Egyptian cohort of older patients in the 8-weeks period after hospital discharge.

This study recruited 400 Egyptian patients, aged = ≥ 60 years from 3 hospitals in Cairo and followed them up 8 weeks after discharge using a semi-structured telephone interview to verify MRH events (type, probability, severity and preventability) and related factors.

The participants’ ages ranged from 60 to 95 years with 53% females. In the final cohort of 325 patients analyzed, MRH occurred in 99 patients (incidence of 30.5%), of which 26 MRH cases (26.2%) were probable, serious and preventable. MRH included adverse drug reactions (ADRs), non-adherence and medication errors. Multivariate regression analysis showed that non-adherence and inappropriate prescription had highly significant association with MRH (P < 0.001), history of previous ADR, living alone and presence of paid caregiver had significant association (P 0.008, 0.012, 0.02 respectively), while age, medications number, length of stay (LOS) and cognitive impairment were not significantly associated with MRH.

These findings demonstrate the magnitude of MRH in Egypt affecting almost a third of older adults after leaving the hospital. These original data could guide decision-makers to enhance older patients’ medication safety through education, quality improvement and policy.

MRH in Egyptian older adults post-hospital discharge has not been adequately reported in scientific literature.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.