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1.  Supporting genetics in primary care: investigating how theory can inform professional education 
European Journal of Human Genetics  2016;24(11):1541-1546.
Evidence indicates that many barriers exist to the integration of genetic case finding into primary care. We conducted an exploratory study of the determinants of three specific behaviours related to using breast cancer genetics referral guidelines effectively: ‘taking a family history', ‘making a risk assessment', and ‘making a referral decision'. We developed vignettes of primary care consultations with hypothetical patients, representing a wide range of genetic risk for which different referral decisions would be appropriate. We used the Theory of Planned Behavior to develop a survey instrument to capture data on behavioural intention and its predictors (attitude, subjective norm, and perceived behavioural control) for each of the three behaviours and mailed it to a sample of Canadian family physicians. We used correlation and regression analyses to explore the relationships between predictor and dependent variables. The response rate was 96/125 (77%). The predictor variables explained 38–83% of the variance in intention across the three behaviours. Family physicians' intentions were lower for ‘making a risk assessment' (perceived as the most difficult) than for the other two behaviours. We illustrate how understanding psychological factors salient to behaviour can be used to tailor professional educational interventions; for example, considering the approach of behavioural rehearsal to improve confidence in skills (perceived behavioural control), or vicarious reinforcement as where participants are sceptical that genetics is consistent with their role (subjective norm).
doi:10.1038/ejhg.2016.68
PMCID: PMC5110065  PMID: 27329737
2.  Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration 
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
doi:10.1038/ejhg.2011.27
PMCID: PMC3083630  PMID: 21407270

Results 1-2 (2)