Oral Presentation COSA-IPOS Joint Scientific Meeting 2012

Tailoring for colorectal cancer screening: Relationship between stage of decision to screen and Preventive Health Model variables (#58)

Ingrid H Flight 1 , Ian T Zajac 1 , Carlene Wilson 1 2 3 , Deborah Turnbull 4 , Graeme Young 5
  1. CSIRO Preventative Health Research Flagship, Adelaide, SA, Australia
  2. Discipline of Public Health, Flinders University of South Australia, Bedford Park, SA, Australlia
  3. CCSA Chair in Cancer Prevention (Behavioural Science), Flinders Centre for Cancer Prevention and Control, Eastwood, SA, Australia
  4. School of Psychology, University of Adelaide, Adelaide, SA, Australia
  5. Flinders Centre for Innovation in Cancer, Flinders University, Bedford Park, SA, Australia

Aim: To identify whether groups of people at a specific stage of decision to screen for colorectal cancer (CRC) using a Faecal Immunochemical Test (FIT) can be distinguished from people at a different stage in terms of their responses to Preventive Health Model (PHM) variables. Self efficacy and faecal aversion constructs were also included in the analysis.
Methods: N=2240 participants completed a baseline questionnaire and received a FIT. Multivariate logistic regressions (MLR) were conducted to identify differences between CRC decision stages in terms of the PHM variables. For each analysis, one decision stage was compared to stages more proximal to screening. The stages include: unaware of screening; unconcerned; considering screening; decided to screen. An MLR was also used to compare FIT participants (n=1789) and non-participants (n=451) on PHM constructs.
Results: Participants who were unconcerned about screening (n=611) had lower salience and coherence (p=0.001, OR=0.76, 95% CI 0.72-0.81) and self efficacy (p=0.01, OR=.91, 95% CI 0.85-0.98) than those at more proximal stages. Similar effects were noted for the other decision stage comparisons, with additional effects reflecting faecal aversion, social influence, and cancer worries also observed in some models. For example, participants who had decided to screen (n=1130) reported higher social influence (p=0.001, OR=1.06, 95% CI 1.02-1.11), higher salience and coherence (p=0.001, OR=1.35, 95% CI 1.28-1.42) and self efficacy (p=0.001, OR=1.17, 95% CI 1.10-1.25). In terms of actual screening behaviour, FIT participants were more likely at baseline to have lower perceived susceptibility (p=0.01, OR=0.93, 95% CI 0.88-0.98) than non-participants, and greater self efficacy (p=0.001, OR=1.20, 95% CI 1.11-1.29).
Conclusion: These findings indicate that there are quantifiable differences between people of varying decision stages. The identification of such differences can help to inform tailored interventions designed to motivate an individual’s movement to a ‘better’ decision stage for CRC screening.