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This paper explores the application of Constructivist Grounded Theory (C-GT) methodology for social work research. First, it argues that C-GT methodology is well aligned with social work as the two value the individual in the context of their environmental influences. Both also prioritise the importance of respecting and valuing the participant or individual, seeing their perspective as unique and significant. Finally, this research methodology's systematic yet flexible guidelines align with social work ethics, which also focus on the importance of professional integrity. The paper then provides an example of a C-GT PhD study in relation to an area of social work practice, that is, stability in statutory kinship care in Queensland, Australia. The paper details the specific recruitment and sampling of participants, data collection and coding analysis examples from the PhD study. The examples evidence the relevance of C-GT methodology and its application for research in the area of social work practice, specifically statutory kinship care. [ABSTRACT FROM AUTHOR]

Introduction: Effective primary healthcare services have been identified by the World Health Organization as the most equitable approach to enhancing universal healthcare. Robust models of mentoring for registered nurses (RNs) transitioning to primary healthcare roles have yet to be described in the Australian context. A robust mentoring model can support RNs to fulfill their potential, bridging the gap between theory and practice. In 2015, the peak body for nurses in primary health care (PHC) began developing a transition to practice program, including embedded mentoring to support newly graduated and more experienced registered and enrolled nurses. This quality improvement study reports the experiences and perspectives of nurses participating as mentors in two separate offerings of the program delivered between 2019 and 2021. Method: A two-phase concurrent mixed methods evaluation utilized data from pre- and post online surveys and post program meetings. Quantitative items underwent descriptive analyses. Thematic analysis of free-text responses and comments was conducted independently by two researchers. Mentors voluntarily provided self-report data and were informed that data is routinely collected to support continuous quality improvement processes for all programs. An Information Sheet informed mentors of data usage, confidentiality, and options to withdraw without penalty from the program at any time. Results: Seventy-nine mentors were recruited to support two groups of nurses (N = 111). Mentor self-rated overall satisfaction with program participation was 86.67% (very or extremely satisfied). Mentors described being "witness to mentee growth," "having facilitated access to learning" and receiving "unexpected benefits" including personal and professional growth and enhanced enthusiasm for their role in PHC. Conclusion: The embedded mentoring reported in this article combined a focus on skills acquisition and professional identity with the provision of a range of resources and support activities. Sustainable mentoring programs will be an important mechanism for supporting the expanding roles required of nurses working in primary health. [ABSTRACT FROM AUTHOR]

Population health data, collected worldwide in an effort to monitor mortality and morbidity of mothers and babies, namely, perinatal data, are mandated at a federal level within Australia. The data are used to monitor patterns in midwifery, obstetric and neonatal practice, health outcomes, used for research purposes, funding allocation and education. Accuracy in perinatal data is most often reported via quantitative validation studies of perinatal data collections both internationally and in Australia. These studies report varying levels of accuracy and suggest researchers need to be more aware of the quality of data they use. This article presents findings regarding issues of concern identified by midwives relating to their perceptions of how technology affects the accuracy of perinatal data records. Perinatal data records are perceived to be more complete when completed electronically. However, issues regarding system functionality, the inconsistent use of terminology, lack of data standards and the absence of clear, written records contribute to midwives’ perceptions of the negative influence of technology on the quality of perinatal data. [ABSTRACT FROM AUTHOR]

The Australian Electricity Market Operator generates one-day ahead electricity demand forecasts for the National Electricity Market in Australia and updates these forecasts over time until the time of dispatch. Despite the fact that these forecasts play a crucial role in the decision-making process of market participants, little attention has been paid to their evaluation and interpretation. Using half-hourly data from 2011 to 2015 for New South Wales and Queensland, it is shown that the official half-hourly demand forecasts do not satisfy the econometric properties required of rational forecasts. Instead there is a relationship between forecasts and forecast horizon similar to a term structure model of interest rates. To study the term structure of demand forecasts, a factor analysis that uses a small set of latent factors to explain the common variation among multiple observables is implemented. A three-factor model is identified with the factors admitting interpretation as the level, slope and curvature of the term structure of forecasts. The validity of the model is reinforced by assessing the economic value of demand forecasts. It is demonstrated that simple adjustments to long-horizon electricity demand forecasts based on the three estimated factors can enhance the informational content of the official forecasts. [ABSTRACT FROM AUTHOR]