**3. Results**

Of the 480 selected participants, 414 completed the survey with a response rate of 86.3%. Table 1 depicts the background characteristics of the study participants. Of the 414 responses, the majority (68.6%) are Saudi nationals, married (58.0%), bachelor's degree holders (68.8%), nurses, and midwives (45.2%). The mean ± SD age of the studied population was 31.17 ± 6.04 years. Regarding work settings, 23.4%, 43.0%, and 33.6% of the participants worked at PHCs, general hospitals (secondary care), and tertiary care centers, respectively.

Table 2 presents the participants' knowledge regarding breast cancer risk factors and symptoms. Regarding breast cancer risk factors, the highest proportion of correct answers was observed regarding family history of breast cancer (79.0%) and smoking (66.2%). In comparison, the lowest proportion of correct answers was seen with regards to early puberty (26.8%) and late first pregnancy (31.2%). More than three-fourths of the HCW's correctly responded regarding change in size or shape of the breast (80.9%), non-painful lumps in the breast (75.1%), and nipple discharge (74.2%) being the risk factors of breast cancer.


**Table 1.** Background characteristics of the female healthcare workers (HCWs) (*n* = 414).

We found that more than one-third of the participants had barriers in all ten categories. Barriers were commonly found as fear of discovering cancer (57.2%) and apprehension regarding radiation exposure (57%). Nearly half (48.6%) of the HCWs responded that embarrassment due to breast-related tests was their primary barrier to mammogram screening uptake (Table 3).

Of the 414 respondents, 93 (22.5%), 106 (25.6%), and 69 (16.7%) had high scores in the knowledge, attitude, and barriers categories, respectively. In comparison, 201 (79.1%), 79 (19.1%), and 254 (61.4%) had low scores in the knowledge, attitude, and barriers categories, respectively (Figure 1).


**Table 2.** Participants knowledge regarding breast cancer risk factors and symptoms (*n* = 414).

**Table 3.** Barriers towards uptake of mammogram screening among the participants (*n* = 414).


**Figure 1.** Knowledge, attitude, and barrier categories.

Table 4 shows the association between the knowledge subcategories and sociodemographic characteristics of the participating HCWs. Firstly, the univariate analysis was performed to compare each exposure (independent) variable with the knowledge subscales, and then, binomial logistic (multivariate analysis) were performed after adjusted with other covariables. In the univariate analysis, the characteristics that were significantly associated with the knowledge subcategories were age group (ref: up to 30 years: OR = 1.68, 95% CI = 1.06–2.67, *p* = 0.038), nationality (ref: Saudi: OR = 2.60, 95% CI = 1.62–4.19, *p* = 0.001), education (ref: diploma holders: OR = 2.96, 95% CI = 1.53–4.10, *p* = 0.001), HCWs category (ref: other categories: OR = 6.31, 95% CI = 4.91–8.10, *p* = 0.001), and family history of breast cancer (ref: no: OR = 1.93, 95% CI = 1.07–3.34, *p* = 0.037). The binomial logistic regression revealed only the following two characteristics were significantly associated with knowledge subscales, namely education status (ref: diploma holders: Adjusted OR (AOR) = 2.47, 95% CI = 1.54–4.53, *p* = 0.001) and HCW category (ref: other categories: AOR = 4.11, 95% CI = 2.86–5.76, *p* = 0.017).

Attitude subcategories and their association with sociodemographic characteristics are depicted in Table 5. The univariate analysis found that attitude subcategories were significantly associated with nationality (ref: Saudi: AOR = 1.34, 95% CI = 1.02–1.63, *p* = 0.017) and family history of breast cancer (ref: no: AOR = 2.73, 95% CI = 1.89–6.14, *p* = 0.001). However, logistic regression analysis did not reveal any significant association between independent variables and attitude subcategories.

Table 6 shows the association between barriers subcategories and sociodemographic characteristics of the participated HCWs. The binomial logistic regression revealed that only the following two characteristics were significantly associated with barriers subcategories: nationality (ref: Saudi: AOR = 1.66, 95% CI = 1.14–2.3, *p* = 0.015) and marital status (ref: married: AOR = 0.47, 95% CI = 0.28–0.69, *p* = 0.037).

Of the studied population, 66.2% were aware about the MOH, Saudi Arabia's recommendation for mammogram screening for breast cancer In the binomial logistic regression analysis, after adjusting with other covariables of the study, we found only age (ref: up to 30 years: OR = 0.91, 95% CI = 0.83–0.97, *p* = 0.030) and HCWs categories (ref: other categories: OR = 1.83, 95% CI = 1.12–2.98, *p* = 0.001 for nurses and OR = 4.08, 95% CI = 3.01–5.79, *p* = 0.001 for physicians) were significantly associated with the awareness regarding MOH, Saudi Arabia's recommendation for mammogram screening for breast cancer (Table 7).

The spearman's rank correlation test revealed a significant positive correlation between knowledge and attitude scores (rho = 0.195, *p* = 0.001). In addition, we found a negative correlation between knowledge of the breast cancer risk factors and symptoms with the barriers towards uptake of mammogram screening (rho = −0.315, *p* = 0.001) (Table 8).


**Table 4.** Binomial regression analysis between participants' socio-demographic characteristics and knowledge towards breast cancer (*n* = 414).

and family history of breast cancer. \*\* Significant value less than 0.05 (two-tailed test).


**Table 5.** Binomial regression analysis between participants' socio-demographic characteristics and attitude towards breast cancer (*n* = 414).

and family history of breast cancer. \*\* Significant value less than 0.05 (two-tailed test).


**Table 6.** Binomial regression analysis between participants' socio-demographic characteristics and barriers to uptake mammogram screening


**Table 7.** Binomial regression analysis between participants' socio-demographic characteristics and awareness on the MOH, Saudi Arabia's

Yes 56 20 (35.7) 36 (64.3) 1.12 (0.72–2.91) 1.46 (0.79–2.68) 0.223 \* Variables adjusted for logistic regression (enter method): Age category, nationality, marital status, education, work setting, HCWs category, work experience, and family history of breast cancer. \*\* Significant value less than 0.05 (two-tailed test).

No 358 120 (33.5) 238 (66.5) Ref Ref

Family history of breast cancer


**Table 8.** Correlation between knowledge, attitude, and barriers scores (Spearman's rank correlation).

\* Spearman's rank correlation coefficient, \*\* significant at 0.05 level (two-tailed).
