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  • br Table br Number of Barriers and


    Table 5
    Number of Barriers and Facilitators Predicting Prior Screening (Never screened vs. Screened), Adjusted For Age Group (N = 338).
    Table 6
    Individual Barriers and Facilitators in Regards to Prior Screening (Never Screened vs. Prior Screener) (N = 330).
    Never screened n Prior screen n χ2(1)
    Lack of time
    screening was then examined in regards to the individual screening barriers and facilitators, using χ2 Chi-square tests. Results showed that women who had never screened were more likely to report embar-rassment and anxiety as screening barriers, and prior screeners were more likely to report a lack of time as a screening barrier and having a regular GP (see Table 6).
    4. Discussion
    Few studies have examined women's cervical cancer screening be-havior, including screening status (i.e., overdue vs. up-to-date with screening) (Catarino et al., 2016; Eaker et al., 2001; Waller et al., 2009) in regards to the experience of screening barriers and facilitators. No prior studies have explored the factors in relation to women's prior screening (i.e., screened vs. never screened). Thus, this study examined screening barriers and facilitators listed by women with regards to screening status and prior screening. Overall, they PEG300 listed relatively few screening barriers and facilitators without prompting. The most com-monly listed practical barriers were logistical (i.e., lack of time, high cost of test) and the most often listed psychological barriers were dis-comfort, embarrassment, and anxiety about the test. The most often nominated facilitators were practical (i.e., low cost of test, appointment availability, screening reminders) or they described the screening doctor (i.e., friendly/warm attitude, female doctor). Overall, the most often screening barrier listed was a lack of time (practical barrier) and the most often facilitators listed were the PEG300 low cost of the test (practical facilitator) and warm/friendly doctor (psychological facilitator), all of which were mentioned by more than half of the sample. 
    Hypothesis 1 examined whether women's screening status was re-lated to the number screening barriers and facilitators they had named. After controlling for age group, only the number of psychological bar-riers related to screening status, and each psychological barrier in-creased the odds of being overdue for screening by 36%, not supporting the hypothesis. Practical and psychological screening facilitators did not predict significant variance in women's screening status. Hypothesis 2 examined if individual screening barriers and facilitators were related to women's screening status. It was expected that a lack of time (practical barrier) and GP status (practical facilitator) would predict their screening status. Results indicated that women who were overdue for screening were more likely to report embarrassment as a screening barrier. In contrast, those who were up-to-date with screening were more likely to report having a regular GP and the low cost of the test as a screening facilitator, somewhat supporting the hypothesis.
    Results are consistent with prior study results showing that psy-chological response to the Pap test is a significant screening barrier in women of all screening ages (Armstrong et al., 2012; Oscarsson, 2011), including those who have never screened (Al-Naggar et al., 2010; Wong et al., 2008). However, older women reported fewer psychological barriers than young women, inconsistent with the results of Waller et al. (2009) who found that older women endorsed emotional screening barriers more often than practical barriers, whereas younger women more often endorsed practical barriers. Furthermore, only the number of psychological barriers listed by women was related to their screening status, not the number of practical barriers, inconsistent with the results of Waller et al. (2009) and Catarino et al. (2016). Finally, we did not find that a lack of time (practical barrier) individually predicted women's screening status, as did Eaker et al. (2001).
    Differences in the study results may be due to the women naming their own list of barriers and facilitators in this study, rather than en-dorsing a pre-existing list. However, if they had poor insight, they may have failed to properly articulate the barriers and facilitators they had encountered. For example, no participants listed having a regular GP as a screening facilitator, but they often listed the specific attributes of the doctors (e.g., female, friendly/warm) as facilitators; and most were university educated, suggesting they were unlikely to have had defi-cient insight. However, operationalizing the screening barriers and fa-cilitators in this way may have led to significant omissions, but without an explicit comparison, vectors is unclear if the prompted vs. unprompted questioning of women works best in this regard. Additionally, only women aged 25–35-years (young women) or 45–55-years (older women) participated in the study, representing the age groups with lowest and highest screening rates, respectively (AIHW, 2017); but di-chotomizing age group in this way may have obscured the relationship between their age and screening attendance.