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Although previous studies of today's globalised and competitive research landscape have mentioned the research collaborations of CANZUK countries (i.e., Australia, Canada, New Zealand, and the United Kingdom), none have yet studied them in detail. Further, such studies have used different measures of international research collaboration (IRC), resulting in disparate findings. This paper, therefore, analyses the strengths of CANZUK research collaborations, how those collaborations have changed over time, and assesses the effect of three ways of measures on the results (absolute strength, bilateral similarity, and multilateral similarity). We provide a detailed characterisation of the CANZUK research network and its relationships with partner countries, which reveals that the most collaborative CANZUK countries are the UK and Australia, among other findings. We also confirm that many findings differ depending on which measures are used. We offer an explanation of this difference with reference to the nature of the measures (i.e., what they really measure) and make suggestions for suitable measures in future studies depending on their purpose. Finally, we discuss how this study's findings can be used by research policy makers (in CANZUK and elsewhere) in deciding on research strategy and by researchers in appropriately measuring IRC. [ABSTRACT FROM AUTHOR]

The Consolidated Framework for Implementation Research (CFIR) is a well-established framework for systematically identifying key factors influencing the implementation of programs. To enhance the classification of existing CFIR definitions, as well as its +2/-2 scoring system, this study incorporated the views of relevant experts to: i) improve how themes are scored; and ii) utilise more information regarding the frequency with which themes are identified. This structured, frequency-based approach to the CFIR's scoring process has been trialled as the CFIR-frequency (CFIR-f). Researchers thematically analysed semi-structured interview data from four groups of policy and program experts (N = 24) delivering two family-based therapies in New South Wales (NSW), Australia. Themes identified by less than 50% were excluded from further analysis. Themes identified by 50% or more of expert participants in the four groups were classified as enablers or barriers using clearly defined criteria. Each theme was allocated a score according to how many experts identified it as an enabler or barrier, and then mapped back onto the latest adaptation of the CFIR comprising 67 constructs. The CFIR-f successfully determined three enablers of, and six barriers to, implementation. Enablers included the family-based therapy programs, therapist training and participant monitoring systems. Barriers included referral, data collection and staffing difficulties, NSW adaptation issues and the suitability and safety of the programs for Aboriginal families. The same enablers and barriers were identified using both the CFIR-f and the original scoring approach, and the identified themes were successfully mapped to almost all CFIR constructs (65/67). This paper proposes a more frequency-based approach to CFIR's scoring process (the CFIR-f). By specifically utilising the frequency with which these barriers and enablers are identified, the CFIR-f engenders a list of ranked themes that service providers and policymakers can use to inform their decisions about program modification and implementation. [ABSTRACT FROM AUTHOR]