Mapping the knowledge structure and trends in Australian Indigenous health and wellbeing research from 2003 to 2022: a scientometric analysis.

The health and wellbeing of Australian Indigenous peoples is a nationally sanctioned priority, but despite this, few studies have comprehensively analyzed the features and characteristics of the research in the field. In this regard, a comprehensive scientometric analysis and knowledge mapping to systematically summarize and discuss the current state of research, research trends, and emerging areas of research were conducted. Original articles and reviews published between 2003 and 2022 were obtained from the Web of Science Core Collection. CiteSpace and VOSviewer software were used to perform scientometric analysis and knowledge mapping. An examination of document and citation trends, authors, institutions, countries/regions, journals, and keywords was untaken, while co-citation, co-occurrence, and burst analysis provide insights and future development in this area. A total of 2,468 documents in this field were retrieved. A gradual increase in the number of documents over the past two decades is observed, with the number of documents doubling every ~7.5 years. Author Thompson SC and Charles Darwin University published the most documents, and 85.6% were affiliated with only Australian-based researchers. The Australian and New Zealand Journal of Public Health is the most prominent journal publishing in the field. The most commonly co-occurring keyword was "health," and the keyword "risk" had the longest citation burst. Five keyword clusters were identified; "cultural safety" was the largest. This study articulates the knowledge structure of the research, revealing a shift from population-level and data-driven studies to more applied research that informs Indigenous peoples health and wellbeing. Based on this review, we anticipate emergent research areas to (1) reflect a more comprehensive understanding of the multidimensional factors that shape Indigenous health and wellbeing; (2) move beyond a deficit-based perspective; (3) respect cultural protocols and protect the rights and privacy of Indigenous participants; (4) address racism and discrimination within the healthcare system; (5) foster respectful, equitable, and collaborative research practices with Indigenous peoples; (6) provide culturally appropriate and effective interventions for prevention, early intervention, and treatment; and (7) ensure equitable change in systems to enhance access, quality, and outcomes in health and wellbeing.

Developing a strategy to improve data sharing in health research: A mixed-methods study to identify barriers and facilitators.

BACKGROUND: Data sharing presents new opportunities across the spectrum of research and is vital for science that is open, where data are easily discoverable, accessible, intelligible, reproducible, replicable and verifiable. Despite this, it is yet to become common practice. Global efforts to develop practical guidance for data sharing and open access initiatives are underway, however evidence-based studies to inform the development and implementation of effective strategies are lacking. OBJECTIVE: This study sought to determine the barriers and facilitators to data sharing among health researchers and to identify the target behaviours for designing a behaviour change intervention strategy. METHOD: Data were drawn from a cross-sectional survey of data management practices among health researchers from one Australian research institute. Determinants of behaviour were theoretically derived using well-established behavioural models. RESULTS: Data sharing practices have been described for 77 researchers, and 6 barriers and 4 facilitators identified. The primary barriers to data sharing included perceived negative consequences and lack of competency to share data. The primary facilitators to data sharing included trust in others using the data and social influence related to public benefit. Intervention functions likely to be most effective at changing target behaviours were also identified. CONCLUSION: Results of this study provide a theoretical and evidence-based process to understand the behavioural barriers and facilitators of data sharing among health researchers. IMPLICATIONS: Designing interventions that specifically address target behaviours to promote data sharing are important for open researcher practices.

Research data management in practice: Results from a cross-sectional survey of health and medical researchers from an academic institution in Australia.

BACKGROUND: Building or acquiring research data management (RDM) capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that RDM practices influence the integrity and longevity of data, targeting RDM services and support in recognition of needs is especially valuable in health and medical research. OBJECTIVE: This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia. METHOD: A cross-sectional survey was used to collect information from a convenience sample of 81 members of a research institute (68 academic staff and 13 postgraduate students). A survey was constructed to assess selected data management tasks associated with the earlier stages of the research data life cycle. RESULTS: Our study indicates that RDM tasks associated with creating, processing and analysis of data vary greatly among researchers and are likely influenced by their level of research experience and RDM practices within their immediate teams. CONCLUSION: Evaluating the data management practices of health and medical researchers, contextualised by tasks associated with the research data life cycle, is an effective way of shaping RDM services and support in this group. IMPLICATIONS: This study recognises that institutional strategies targeted at tasks associated with the creation, processing and analysis of data will strengthen researcher capacity, instil good research practice and, over time, improve health informatics and research data quality.

Development of an objective measure of quality and commercial value of Japanese-styled green tea (Camellia L. sinensis): the Quality Index Tool.

A novel approach to evaluate the commercial value of green tea products is explored in this paper. The green tea Quality Index Tool (QI-Tool) is based on high performance liquid chromatography (HPLC), capable of identifying and understanding the constituents that are important to create superior consumer and commercially valuable green tea beverages in the Japanese-style. This tool will allow producers to better identify a product's potential value within the various levels of green tea retail quality structure. Via the quantification of theanine, caffeine and the catechins: epicatechin (EC), epicatechin gallate (ECG), epigallocatchin (EGC), epigallocatechin gallate (EGCG) and gallocatechin gallate (GCG) within a green tea beverage, the QI-Tool provides categorisation of a product against the green tea market retail competitive set. This allows a better understanding of the product's potential commercial value, as well as a comparison to other products within that market category. The QI-Tool is an alternative and promising method for objectively evaluating commercial value of green tea products using HPLC analysis.