Consensus on an Australian Nurse practitioner specialty framework using Delphi methodology: results from the CLLEVER

Aim: The aim of this study was to achieve profession-wide consensus on an Australian nurse practitioner specialty framework. Background: Since its introduction in 1998, the Australian nurse practitioner profession has grown to over 1300 endorsed practitioners, representing over 50 different specialties. To complement better a generalist learning and teaching framework with specialist clinical education, prior research proposed a broad framework of Australian nurse practitioner specialty areas termed metaspecialties. Design: This study employed an online three-round modified Delphi method. Method: Recruitment using purposive sampling and snowballing techniques identified an eligible sample from a population of nurse practitioners with at least 12months' postendorsement experience (n=966). Data were collected using online survey software from September 2014-January 2015 and analysed using descriptive statistics and content analysis. The Content Validity Index and McNemar's Test for Change were used to determine consensus on the nurse practitioner metaspecialties. Results: One-fifth of the total eligible population completed the study. Participants achieved high consensus on four metaspecialties, including: Emergency and acute care, primary health care, child and family health care and mental health care. Two metaspecialties did not achieve consensus and require further investigation. Conclusion: A large sample of nurse practitioners achieved consensus on an Australian metaspecialty framework, increasing the likelihood of widespread acceptance across the profession. This technique may be appropriate for use in jurisdictions with smaller populations of nurse practitioners. Ongoing research is needed to re-evaluate the metaspecialties as the profession grows

Assessing 'What Works' in International Development: Meta-Analysis for Sophisicated Dummies

Many studies of development interventions are individually unable to provide convincing conclusions because of low statistical significance, small size, limited geographical purview and so forth. Systematic reviews and meta-analysis are forms of research synthesis that combine studies of adequate methodological quality to produce more convincing conclusions. In the social sciences, study designs, types of analysis and methodological quality vary tremendously. Combining these studies for meta-analysis entails more demanding risk of bias assessments to ensure that only studies with largely appropriate methodological characteristics are included, and sensitivity analysis should be performed. In this article, we discuss assessing risk of bias and meta-analysis using such diverse studies