Next Article in Journal
Embryonic Kidney Development, Stem Cells and the Origin of Wilms Tumor
Next Article in Special Issue
Species-Specific Quality Control, Assembly and Contamination Detection in Microbial Isolate Sequences with AQUAMIS
Previous Article in Journal
Genomic Regions Associated with Variation in Pigmentation Loss in Saddle Tan Beagles
Previous Article in Special Issue
Whole Genome Sequencing Applied to Pathogen Source Tracking in Food Industry: Key Considerations for Robust Bioinformatics Data Analysis and Reliable Results Interpretation
Article

Investigating the Adoption of Clinical Genomics in Australia. An Implementation Science Case Study

1
Australian Institute of Health Innovation, Macquarie University, Sydney, NSW 2113, Australia
2
Australian Genomics Health Alliance, Murdoch Childrens Research Institute, Melbourne, VIC 3052, Australia
3
Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute, Melbourne, VIC 3052, Australia
4
Department of Paediatrics, University of Melbourne, Melbourne, VIC 3010, Australia
5
Cancer Research Division, Cancer Council New South Wales, Sydney, NSW 2011, Australia
6
Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2050, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Mehdi Pirooznia
Received: 20 January 2021 / Revised: 10 February 2021 / Accepted: 19 February 2021 / Published: 23 February 2021
Despite the overwhelming interest in clinical genomics, uptake has been slow. Implementation science offers a systematic approach to reveal pathways to adoption and a theory informed approach to addressing barriers presented. Using case study methodology, we undertook 16 in-depth interviews with nongenetic medical specialists to identify barriers and enablers to the uptake of clinical genomics. Data collection and analysis was guided by two evidence-based behaviour change models: the Theoretical Domains Framework (TDF), and the Capability, Opportunity Motivation Behaviour model (COM-B). Our findings revealed the use of implementation science not only provided a theoretical structure to frame the study but also facilitated uncovering of traditionally difficult to access responses from participants, e.g., “safety in feeling vulnerable” (TDF code emotion/COM-B code motivation). The most challenging phase for participants was ensuring appropriate patients were offered genomic testing. There were several consistent TDF codes: professional identity, social influences, and environmental context and resources and COM-B codes opportunity and motivation, with others varying along the patient journey. We conclude that implementation science methods can maximise the value created by the exploration of factors affecting the uptake of clinical genomics to ensure future interventions are designed to meet the needs of novice nongenetic medical specialists. View Full-Text
Keywords: clinical genomics; implementation science; Theoretical Domains Framework; COM.B clinical genomics; implementation science; Theoretical Domains Framework; COM.B
Show Figures

Graphical abstract

MDPI and ACS Style

Best, S.; Long, J.C.; Gaff, C.; Braithwaite, J.; Taylor, N. Investigating the Adoption of Clinical Genomics in Australia. An Implementation Science Case Study. Genes 2021, 12, 317. https://0-doi-org.brum.beds.ac.uk/10.3390/genes12020317

AMA Style

Best S, Long JC, Gaff C, Braithwaite J, Taylor N. Investigating the Adoption of Clinical Genomics in Australia. An Implementation Science Case Study. Genes. 2021; 12(2):317. https://0-doi-org.brum.beds.ac.uk/10.3390/genes12020317

Chicago/Turabian Style

Best, Stephanie, Janet C. Long, Clara Gaff, Jeffrey Braithwaite, and Natalie Taylor. 2021. "Investigating the Adoption of Clinical Genomics in Australia. An Implementation Science Case Study" Genes 12, no. 2: 317. https://0-doi-org.brum.beds.ac.uk/10.3390/genes12020317

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop