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To establish research priorities for Australian Nurse Practitioners and develop a robust research agenda.
A descriptive, exploratory approach was used and conducted in two stages.
Data were collected over two stages. Data for Stage 1 were collected from 14 December 2023 to 16 February 2024. For the Delphi rounds (Stage 2), data were collected from 11 March to 24 March 2024 for Delphi Round 1 and from 12 June to 26 June 2024 for Delphi Round 2. An exploratory survey was used in Stage 1 to identify clinical challenges and research themes perceived as important for Australian Nurse Practitioners. In Stage 2, a two-phased modified Delphi survey was conducted to prioritise the research themes identified in Stage 1.
A total of 315 participants responded to the exploratory survey, with a majority being female (77%), aged between 30 and 75 years. Participants were primarily employed in the public healthcare sector (60%), the private sector (23%), while 17% practised across both sectors. A total of 1335 challenges facing Australian Nurse Practitioners were identified. Sixty-nine participants completed the first Delphi round, and 33 the second, giving response rates of 21% (69/315) and 48% (33/69), respectively. The first Delphi round yielded 11 research themes. Seven of these yielded Content Validity Indices of < 0.90. Four research priority areas remained and were ranked in order of importance.
The identified Australian Nurse Practitioner research priorities will play a pivotal role in shaping policies, fostering the efficient integration of Nurse Practitioners into the healthcare system and advancing research capacity.
Nurse Practitioners are established providers of high-quality care internationally; however, they face persistent integration challenges in Australia. This study delivers a nationally relevant, consensus-based research agenda that identifies key priorities across clinical, educational and leadership domains.
No patient or public contribution.
Severe mental disorders are associated with increased risk of metabolic dysfunction. Identifying those subgroups at higher risk may help to inform more effective early intervention. The objective of this study was to compare metabolic profiles across three proposed pathophysiological subtypes of common mood disorders (‘hyperarousal-anxious depression’, ‘circadian-bipolar spectrum’ and ‘neurodevelopmental-psychosis’).
751 young people (aged 16–25 years; mean age 19.67±2.69) were recruited from early intervention mental health services between 2004 and 2024 and assigned to two mood disorder subgroups (hyperarousal-anxious depression (n=656) and circadian-bipolar spectrum (n=95)). We conducted cross-sectional assessments and between-group comparisons of metabolic and immune risk factors. Immune-metabolic markers included body mass index (BMI), fasting glucose (FG), fasting insulin, Homeostasis Model Assessment-Insulin Resistance (HOMA2-IR), C reactive protein and blood lipids.
Individuals in the circadian-bipolar spectrum subgroup had significantly elevated FG (F=5.75, p=0.04), HOMA2-IR (F=4.86, p=0.03) and triglycerides (F=4.98, p=0.03) as compared with those in the hyperarousal-anxious depression subgroup. As the larger hyperarousal-anxious depression subgroup is the most generic type, and weight gain is also a characteristic of the circadian-bipolar subgroup, we then differentiated those with the hyperarousal-anxious subtype on the basis of low versus high BMI (2 vs ≥25 kg/m2, respectively). The ‘circadian-bipolar’ group had higher FG, FI and HOMA2-IR than those in the hyperarousal-anxious-depression group with low BMI.
Circadian disturbance may be driving increased rates of metabolic dysfunction among youth with emerging mood disorders, while increased BMI also remains a key determinant. Implications for assessment and early interventions are discussed.
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