PURPOSE: Delays in seeking help for symptoms have been found to be associated with poorer outcome in breast-cancer patients. This study explores symptom perceptions and health beliefs as predictors of intentions to seek medical help in a general female population. The utility of the self-regulation model of illness cognition and the theory of planned behaviour were examined in predicting help-seeking intentions for potential symptoms of breast cancer in a general population sample. METHODS: A general population sample of 546 women completed a postal questionnaire comprising items examining components of the self-regulation model and the theory of planned behaviour. Help-seeking intention was determined by asking participants to rate the likelihood of visiting their GP for a range of breast symptoms. RESULTS: Hierarchical multiple regression analysis revealed that the cognitive component of the self-regulation model accounted for approximately 22% of the variance in help-seeking intention. Identity (beta = 0.45, p <.001) emerged as a significant predictor of intention to seek help. Inclusion of the components of the theory of planned behaviour accounted for an additional 7% of the variance; the significant predictors were attitude to help-seeking (beta = 0.19, p <.001) and perceived behavioural control (beta = 0.12, p <.01). CONCLUSIONS: Intention to seek medical help for a potential breast-cancer symptom may be mediated, partly, by cognitive representations of the identity and consequences of breast cancer and by attitudes towards help-seeking and perceived behavioural control. Although less than one-third of the variance was accounted for, these results have important implications for future research (in terms of identifying which variables should be examined) and for the development of a model of help-seeking behaviour in women with breast-cancer symptoms.
PURPOSE: Delays in seeking help for symptoms have been found to be associated with poorer outcome in breast-cancer patients. This study explores symptom perceptions and health beliefs as predictors of intentions to seek medical help in a general female population. The utility of the self-regulation model of illness cognition and the theory of planned behaviour were examined in predicting help-seeking intentions for potential symptoms of breast cancer in a general population sample. METHODS: A general population sample of 546 women completed a postal questionnaire comprising items examining components of the self-regulation model and the theory of planned behaviour. Help-seeking intention was determined by asking participants to rate the likelihood of visiting their GP for a range of breast symptoms. RESULTS: Hierarchical multiple regression analysis revealed that the cognitive component of the self-regulation model accounted for approximately 22% of the variance in help-seeking intention. Identity (beta = 0.45, p <.001) emerged as a significant predictor of intention to seek help. Inclusion of the components of the theory of planned behaviour accounted for an additional 7% of the variance; the significant predictors were attitude to help-seeking (beta = 0.19, p <.001) and perceived behavioural control (beta = 0.12, p <.01). CONCLUSIONS: Intention to seek medical help for a potential breast-cancer symptom may be mediated, partly, by cognitive representations of the identity and consequences of breast cancer and by attitudes towards help-seeking and perceived behavioural control. Although less than one-third of the variance was accounted for, these results have important implications for future research (in terms of identifying which variables should be examined) and for the development of a model of help-seeking behaviour in women with breast-cancer symptoms.
Authors: Thomas Kolben; Susanne Beyer; Sanaz Ghasemi; Kerstin Hermelink; Sarah Meister; Tom Degenhardt; Isabelle Himsl; Franz Edler von Koch; Theresa M Kolben; Rachel Wuerstlein; Sven Mahner; Nadia Harbeck; Anna Hester Journal: Breast Care (Basel) Date: 2020-09-21 Impact factor: 2.268
Authors: Gill Hubbard; Iona Macmillan; Anne Canny; Liz Forbat; Richard D Neal; Ronan E O'Carroll; Sally Haw; Richard G Kyle Journal: BMC Public Health Date: 2014-10-29 Impact factor: 3.295
Authors: Xiaobing Wu; Joseph T F Lau; Winnie W S Mak; Jing Gu; Phoenix K H Mo; Xiaodong Wang Journal: BMC Infect Dis Date: 2018-01-02 Impact factor: 3.090