Development of a strategy to encourage attendance for screening mammography.
The present study describes a method for the data-driven structuring of interventions to increase participation in screening mammography. We interviewed 668 randomly selected women from the target population of an Australian pilot screening mammography program before this Program commenced.  The aims of the study were to use cross-sectional data to determine factors which predicted women's intentions regarding attendance at the Program, and on the basis of these results to develop optimal strategies to encourage attendances. Of the sample, 64% said they intended to go to the Program, while 11% were unsure.  A number of variables were significantly associated with intention and regression analysis was used to determine the best model for predicting intention.  Ten variables entered the final regression model:  the intensity of thought about getting breast cancer; a belief that early detection is extremely desirable and that screening mammograms are accurate; having had a Pap test within the last 2 years; a belief that health is controlled by chance; perceived ease of getting to the hospital; subjective familiarity with the hospital location of the Program; age; having heard about screening mammography; and a feeling of personal susceptibility to breast cancer.  This model explained 20% of the variance in intention to have a mammogram (R 2 = 0.20, F(10,492) = 12.08; P less than 0.0001).  The practical applications of these findings are discussed in this report.  It is recommended that if a campaign were to concentrate on changing women's perceptions on the dimensions found to be significantly associated with intention, then it would have maximum chance of encouraging attendance amongst women in the target population.  The strategies we have developed based on these findings are discussed in this paper.
Cockburn
J
J
Centre for Behavioural Research in Cancer, Anti-Cancer Council of Victoria, Australia.
Murphy
B
B
Schofield
P
P
Hill
D
D
Borland
R
R
D000368:Aged; D001315:Australia; D001943:Breast Neoplasms / Q000517:prevention & control*; D003430:Cross-Sectional Studies; D005260:Female; D006266:Health Education / Q000379:methods*; D006293:Health Promotion / Q000379:methods*; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data*; D008403:Mass Screening / Q000706:statistics & numerical data*; D008875:Middle Aged; D016730:Program Development; D012044:Regression Analysis