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This study aims to examine the associations of collaboration measured as social network characteristics with perceived job demands, job control and social support in primary healthcare professionals.

A cross-sectional study design incorporating social network analysis was utilized. Wellbeing surveys with a network questionnaire were sent to care personnel (physicians, nurses and allied health workers) of Finnish primary healthcare in December 2022 (n = 96). Correlation coefficients and multivariate linear regression modeling were used to analyze the associations.

Higher level of collaboration (measured as number of connections in the network) was associated with lower perceived job demands and higher job control. Care professionals’ frequency of collaboration and proportion of connections with the same occupation (homophily) were borderline associated with social support, indicating further research needs. Larger professional networks, perhaps enabling better teamwork and sharing of workload or information, may directly or indirectly protect from job strain.

Work-related collaboration in primary care should be encouraged and large support networks need to be promoted further. Individuals, especially allied health workers, working in multiple locations or as a sole member of their occupation group in the work community need to be provided with adequate social support.

Social network analysis has been proposed as a tool to investigate care integration and collaboration, but direct analyses of network measures and validated wellbeing instruments have remained absent. This study illuminated the role of collaboration structures in work-related wellbeing of care professionals by showcasing the potential of social network analysis.

The integration of big data with artificial intelligence in the field of digital health has brought a new dimension to healthcare service delivery. AI technologies that provide value by using big data obtained in the provision of health services are being added to each passing day. There are also some problems related to the use of AI technologies in health service delivery. In this respect, it is aimed to understand the use of digital health, AI and big data technologies in healthcare services and to analyze the developments and trends in the sector.

In this research, 191 studies published between 2016 and 2023 on digital health, AI and its sub-branches and big data were analyzed using VOSviewer and Rstudio Bibliometrix programs for bibliometric analysis. We summarized the type, year, countries, journals and categories of publications; matched the most cited publications and authors; explored scientific collaborative relationships between authors and determined the evolution of research over the years through keyword analysis and factor analysis of publications. The content of the publications is briefly summarized.

The data obtained showed that significant progress has been made in studies on the use of AI technologies and big data in the field of health, but research in the field is still ongoing and has not yet reached saturation.

Although the bibliometric analysis study conducted has comprehensively covered the literature, a single database has been utilized and limited to some keywords in order to reach the most appropriate publications on the subject.

The analysis has addressed important issues regarding the use of developing digital technologies in health services and is thought to form a basis for future researchers.

In today’s world, where significant developments are taking place in the field of health, it is necessary to closely follow the development of digital technologies in the health sector and analyze the current situation in order to guide both stakeholders and those who will work in this field.

In marketing and consumer research, the study of Indigenous ideas and rituals remains limited. The authors present an Indigenous-informed study of consumption rituals co-produced with members of the Shipibo–Konibo Indigenous group of the Peruvian Amazon. Specifically, the authors worked with the Comando Matico, a group of Shipibos from Pucallpa, Peru. This study aims to investigate how Indigenous spiritual beliefs shape health-related consumption rituals by focusing on the experience of the Shipibos and their response to COVID-19.

Drawing upon the principles of Indigenous research, the authors co-produced this study with the Comando Matico. The authors collaboratively discussed the research project’s design, analysed and interpreted data and co-authored this study with members of the Comando Matico. This study uses discourse analyses. The corpus of discourse is speech and text produced by the Comando Matico in webinars and online interviews during the COVID-19 pandemic. The full and active participation of the Comando Matico informed the discourse analysis by ensuring Indigenous knowledge, and worldviews were infused throughout the process.

The authors foreground how Indigenous spiritual beliefs act as a force that imbues the knowledge and practice of health, wellbeing and illness, and this process shapes the performance of rituals. In Indigenous contexts, multiple spirits coexist with consumers, who adhere to specific rituals to respond to and relate to these spirits. Indigenous consumption rituals involve the participation of non-human beings (called rao, ibo, yoshin and chaikoni by the Shipibos) and this aspect challenges the traditional notion of rituals and ritual elements in marketing.

The authors demonstrate how Indigenous spiritual beliefs shape consumption rituals in the context of health and draw attention to how the acknowledgement of alternative ontologies and epistemologies can help address dominant hierarchies of knowledge in marketing theory.