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Modelling decisions to undergo genetic testing for susceptibility to common health conditions: An ancillary study of the Multiplex Initiative
Authors:Christopher H Wade  Shoshana Shiloh  Samuel W Woolford  J Scott Roberts  Sharon Hensley Alford  Theresa M Marteau
Institution:1. Department of Nursing and Health Studies , University of Washington Bothell , Bothell , WA , USA cwade@uwb.edu;3. Department of Psychology , Tel Aviv University , Tel Aviv , Israel;4. Department of Mathematical Sciences , Bentley University , Waltham , MA , USA;5. Department of Health Behavior and Health Education , University of Michigan School of Public Health , Ann Arbor , MI , USA;6. Department of Biostatistics and Research Epidemiology , Henry Ford Health System , Detroit , MI , USA;7. Department of Psychology , Kings College , London , UK
Abstract:New genetic tests reveal risks for multiple conditions simultaneously, although little is understood about the psychological factors that affect testing uptake. We assessed a conceptual model called the multiplex genetic testing model (MGTM) using structural equation modelling. The MGTM delineates worry, perceived severity, perceived risk, response efficacy and attitudes towards testing as predictors of intentions and behaviour. Participants were 270 healthy insured adults aged 25–40 from the Multiplex Initiative conducted within a health care system in Detroit, MI, USA. Participants were offered a genetic test that assessed risk for eight common health conditions. Confirmatory factor analysis revealed that worry, perceived risk and severity clustered into two disease domains: cancer or metabolic conditions. Only perceived severity of metabolic conditions was correlated with general response efficacy (β?=?0.13, p<0.05), which predicted general attitudes towards testing (β?=?0.24, p<0.01). Consistent with our hypothesised model, attitudes towards testing were the strongest predictors of intentions to undergo testing (β?=?0.49, p<0.01), which in turn predicted testing uptake (OR 17.7, β?=?0.97, p<0.01). The MGTM explained a striking 48% of the variance in intentions and 94% of the variation in uptake. These findings support use of the MGTM to explain psychological predictors of testing for multiple health conditions.
Keywords:genetic testing  Multiplex Initiative  health behaviour  common disease  structural equation modelling  personalised medicine  USA
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