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Service users’ voice is at the forefront of movements within psychiatry that look to create more humanising care. Although genuine co-production of knowledge is limited by the power differential intrinsically functional to the health care setting, the arts have the potential to create collaborative environments and equalise relationships. The purpose of this case study is to describe and discuss the design and pilot evaluation of creative writing workshops in a forensic mental health ward as an innovative method for humanising care.

A creative writing intervention focussing on everyday experiences was implemented in a forensic mental health ward and involved four residents and four mental health professionals working together. Interviews were conducted with the four mental health professionals as part of a service evaluation. Transcripts were analysed using thematic analysis.

Two themes emerged from the analysis of interviews with mental health professionals: “a new way of learning about each other” and “imagining beyond the staff-resident relationship”. The authors discuss the intervention’s benefits in terms of its potential to foster mutuality and empathy beyond the illness narrative.

Creative writing can be used to engage patients and mental health professionals to jointly share everyday experiences and identities beyond illness.

The creative writing workshops present an innovative approach concerning the use of creative arts for humanising care through mutuality.

Machine learning (ML) has recently gained momentum as a method for measurement in strategy research. Yet, little guidance exists regarding how to appropriately apply the method for this purpose in our discipline. We address this by offering a guide to the application of ML in strategy research, with a particular emphasis on data handling practices that should improve our ability to accurately measure our constructs of interest using ML techniques. We offer a brief overview of ML methodologies that can be used for measurement before describing key challenges that exist when applying those methods for this purpose in strategy research (i.e., sample sizes, data noise, and construct complexity). We then outline a theory-driven approach to help scholars overcome these challenges and improve data handling and the subsequent application of ML techniques in strategy research. We demonstrate the efficacy of our approach by applying it to create a linguistic measure of CEOs' motivational needs in a sample of S&P 500 firms. We conclude by describing steps scholars can take after creating ML-based measures to continue to improve the application of ML in strategy research.

Consumer behavior has evolved because of technological development. Nowadays, consumers carry out the different stages of the decision-making process by combining multiple devices which has been defined as multi, cross and omnichannel behavior. These behaviors have attracted the attention of academics and become a hot topic in literature. As a result, vast amounts of studies on the subject need to be revised and clarified. Thus, the aim of this chapter is to synthetize the primary academic literature that analyzes multi, cross and omnichannel behavior from the consumer point of view. To do that, first, the main concepts (multi, cross and omnichannel) and their differences are clarified. Second, the major findings of channel mix literature regarding the topics, channel scope and theories are exposed and described. Third, the opportunities and future lines of research are presented. This chapter contributes to the literature by clarifying the conceptualization of multi, cross and omnichannel behaviors; offering a complete picture of the main topics, channel approaches and theories addressed in channel mix literature; and presenting future research opportunities and open research questions in a channel mix context that could serve as a starting point to build further research.

This study aims to focus on how smartphone addiction impacts young consumer behavior related to mobile technology (i.e. the compulsive app downloading tendency). After a thorough literature review and following the risk and protective factors framework, this study explores factors that could mitigate its effects (resilience, family harmony, perceived social support and social capital).

The study used the covariance-based structural equation modeling approach to analyze data collected from 275 Generation Z (Gen Z) smartphone users in Spain.

Results suggest that resilience is a critical factor in preventing smartphone addiction, and smartphone addiction boosts the compulsive app downloading tendency, a relevant downside for younger Gen Z consumers.

Through the lens of the risk and protective factors framework, this study focuses on protective factors to prevent smartphone addiction and its negative side effects on app consumption. It also offers evidence of younger consumers’ vulnerability to smartphone addiction, not because of the device itself but because of app-consumption-related behaviors.

This chapter offers a reflection in the form of a three-way dialogue, exploring how peer mentoring supports our aim to contribute to the delivery of two interconnected Sustainable Development Goals (SDGs): 3 (Health and well-being) and 11 (Sustainable cities and communities). These goals have been a constant in our practices (as heritage, public health and education professionals), and working together has been pivotal to achieving goals. The reflection is based on the collaborative experience of the three authors since 2016, recognizing how mentoring has shaped the different projects we have imagined and delivered together. Our reflection and experience engage with the notion of ‘authentic mentoring’, whereby we support each other and contribute to each other's gaps in knowledge and practice. This has occurred in a very informal and organic way, outside of more traditional definitions of mentoring, where a certain hierarchy of knowledge transmission is usually expected. This chapter narrates our collaborations across various projects and focuses on the most recent one, Outreach to Ownership (O2O) (2023), delivered for Historic England using Participatory Action Research (PAR) and Student as Partners (SaP) as our main philosophical and methodological frameworks. The O2O project allowed us to reflect on how we worked together and with our students. The students' role has evolved from peer mentors and mentees to authentic collaborators.

The USA’s higher education leaders and professional organizations have called for increased professional development programming at graduate colleges to better prepare US graduate students for their future careers. This study aims to investigate the demographic characteristics of graduate students participating in co-curricular professional development (PD) and sociocultural development (SD) programming at a graduate college at a large, selective and research-intensive public university in the Midwestern USA.

Using institutional data from six semesters, the authors examined the characteristics of students that attended the graduate college’s programs at one university. The authors analyzed which students were most likely to attend PD and SD programs using multinomial logistic regression models.

Female students, students from US historically marginalized racial groups, and US Pell Grant recipients (low-income students) were found to have a higher likelihood of attending both PD and SD programs at the centralized graduate college.

The findings will be of interest to graduate deans and educators who support graduate students. Further evaluative research on the usefulness of such programs at other institutions would help graduate colleges better understand the role they play in meeting graduate students’ needs.

The findings contribute to the understanding of the important role of the US graduate college in the development of graduate students. To the best of the authors’ knowledge, it is the first study to evaluate the backgrounds of graduate students who pursue co-curricular PD and SD opportunities.

The purpose of this paper is to study the impact of the evolution of consumption patterns associated with ageing on the relative importance of industries in Portugal, quantifying the changes in production, value added, imported intermediate inputs and employment.

This paper uses data from the Family Spending Survey to disaggregate the household column of the Portuguese input‐output table in different age groups, projecting their consumption, using the latest demographic projections made by Statistics Portugal (INE).

The study identifies the industries that are likely to be stimulated by the ageing of the Portuguese populations, as well as the industries that will most likely become disadvantaged by the process.

The task of identification of growing and declining industries due to ageing is important to help the design of employment, environmental and social policies.

The contemporary demographic trends in Western societies have added to the importance of studying the economic and social consequences of ageing. The main issues have been the labour market effects, the sustainability of social security systems and long‐term care. In this paper, we address a different research topic, quantifying the sectoral impact of the evolution of consumption patterns associated with ageing. This can be useful in addressing the structural challenges of the rapid ageing of the population, common to most of the developed economies.

This study compared different types of full-time caregiver (e.g., children, older adults, COVID-19 patients) and subgroups (e.g., disability, race/ethnicity, sexual orientation) in the United States during the COVID-19 pandemic for potentially meaningful distinctions.

Data from the 9,854 full-time caregivers identified in Phase 3.2 (July 21–October 11, 2021) of the US Census Household Pulse Survey (HPS) were analyzed in this study using multinomial logistic regression to examine relationships between caregiver types, marginalized subgroups, generation, and vaccination status.

The prevalence of caregiving was low, but the type of full-time caregiving performed varied by demographic group (i.e., disability, race/ethnicity, sexual orientation, gender, generation, and vaccination status). The relative risk of being a COVID-19 caregiver remained significant for being a member of each of the marginalized groups examined after all adjustments.

To date, the HPS has not been analyzed to predict the type of full-time informal caregiving performed during the COVID-19 pandemic or their characteristics. Research limitations of this analysis include the cross-sectional, experimental dataset employed, as well as some variable measurement issues.

Prior informal caregiver research has often focused on the experiences of those caring for older adults or children with special healthcare needs. It may be instructive to learn whether and how informal caregivers excluded from paid employment during infectious disease outbreaks vary in meaningful ways from those engaged in other full-time caregiving. Because COVID-19 magnified equity concerns, examining demographic differences may also facilitate customization of pathways to post-caregiving workforce integration.