1. Background
One in 8 women in western countries will experience breast cancer in their lives (1). In Turkey, breast cancer showed rates of 41 in 2009 and 46 per 100.000 women in 2013, respectively (2). Methods of early diagnosis are very crucial to prevent breast cancer (3, 4). However, studies indicate that women’s behaviors regarding early diagnosis are not satisfactory (5-7). There are numbers of factors affecting the attitudes and behaviors of women towards early diagnosis. These include the cultural beliefs of individuals, their perceptions of health/disease, and the support of family and relatives (3, 8, 9). Educational materials developed on this topic will need to be culturally sensitive as their aim will be to increase behaviors leading to the early diagnosis of breast cancer and to decrease women’s fear of cancer and their fatalism with regard to breast cancer screening. Health beliefs, fears and fatalism have been examined in different societies to increase the positive health behaviors associated with breast cancer screening. However, in Turkey is determined to be insufficient studies on this subject.
1.1. Health Belief Model
The Health Belief Model (HBM) is one of the most frequently used models in the examination of personal attitudes such as perceived sensitivity, seriousness, self-efficacy, barriers, benefits, and health behaviors. The model is utilized to explain behavioral changes with regard to health and the maintenance of health and in planning interventions for preventive health behaviors (5, 10). The key concepts and definitions of the Health Belief Model are as follow:
1.1.1. Perceived Sensitivity
1.1.2. Perceived Seriousness
1.1.3. Perceived Benefits
1.1.4. Perceived Barriers
1.1.5. Self-Efficacy
1.1.6. Cues to Action
Cues to action are defined as anything or events that may increase awareness in performing the necessary health-related activity to prevent or treat health problem. Examples of cues include reminders, friends, peers and mass media campaigns about preventing a disease (5, 10).
This model is, thus, helpful in explaining why women don’t want to participate in prevention and screening for breast cancer and the behaviors of women, who participate and those who do not. Moreover, the structure of the model allows for an inter-disciplinary approach to analyze human beliefs and attitudes within the framework of the social and behavioral sciences. This model claims that changes in behavior depend on individuals’ beliefs, specific behavioral patterns, and habits.
The increasing number of campaigns about breast cancer screening may have a psychological influence with regard to breast cancer screening. The present study investigates the relationship between breast cancer fear and fatalism, considered as psychological factors that could have a significant effect on whether women participate in breast cancer screening (1, 3, 11).
1.2. Fear of Cancer
Fear has a negative effect on judgment, behavior, and our every-day practices. Phillips, Cohen, and Moses (1999) reported that fear was one of the barriers to participating in screening. Studies have addressed fears about breast cancer with regard to both barriers and benefits in terms of whether women participate in screening (1, 3, 11-13).
1.3. Cancer Fatalism
Another variable that has an effect on the participation of women in breast cancer screening can be determined as fatalism (14, 15). Fatalism is defined as the belief that everything in life will be determined by a supernatural power (such as God) and that one cannot control his or her life. In other words, it is the opinion that the life of individuals is predetermined (5). There is limited studies investigating the role of fear and fatalism in women’s participation in breast cancer screening. No study focused on this subject has been found in the domestic literature. The findings of this research could, thus, be beneficial in terms of discussing how the psychological perceptions of women-such as their beliefs, attitudes-about participating in breast cancer screening change with respect to other societies.
In today’s globalizing world, nurses take part in health promotion and disease prevention of individuals at each phase, through consultations related to early diagnosis, health assessments, and the transfer and screening of patients (3). Health professionals should be aware of the barriers preventing women from engaging in specific behaviors and consider these factors during treatment. In this regard, this study was conducted to determine the health beliefs, fears, and fatalism of Muslim Turkish women with regard to breast cancer screening. This study is important in terms of determining how women’s health beliefs, breast cancer fears, and their fatalism are related to their behaviors regarding the early diagnosis of breast cancer and to provide the impetus to any future studies.
2. Methods
The study was designed as a cross-sectional study.
2.1. Participants
Culture and personal religious beliefs affects perceptions of health, illness and death, beliefs about causes of disease, approaches to health promotion and disease prevention. Fatalism plays a key role in Islam’s message; in that case, God knows the future, in which everything will occur and that all things are preordained. In this study, a specific group of Muslim women taking courses on the Quran was used as the sample group; not all Muslim women attend these classes. The research was conducted at the “Quran courses” taught under the administration of the Turkish Directorate of Religious Affairs (TDRA) in a city in Turkey. According to the city directorate of the TDRA, there were 2,726 women registered in the Quran courses in the city in 2015 - 2016. For the sample group, the sampling selection formula for a determinant universe, one of the probability sampling methods, [n = Nt2pq/d2 (N - 1) + t2pq] (N = 2843 p = 0.5, q = 0.5, t = 1.96 (α = 0.05), d = 0.05) (16) was utilized with a 95% significance level and 0.05 margin of error, and the size of the sample group was estimated to be 339 subjects.
2.1.1. The Inclusion Criteria for the Samples in the Study
All 40-year-old or older women, who did not have communication problems and had not been previously diagnosed with breast cancer, were included in the scope of the study.
2.1.2. The Exclusion Criteria for the Samples in the Study
Those who had mental problems or had been previously diagnosed with breast cancer were excluded.
Women from the participants in 23 Quran courses in the city center were included in the sample group on the basis of simple random sampling and 339 women, who agreed to participate in the study, were contacted. A list was made of women, who came to the Quran courses. These women were selected, using a random number table. Survey forms were filled out in the institution during the classes by the women themselves. The course instructors helped collect the data forms. Data collection took approximately 20 minutes. We were unable to contact 28 women (13 women did not agree to participate and 15 women did not meet the sampling criteria for this study).
The approval of the Ethics Committee (15-KAEK-043) was obtained from the relevant institution (Permission Nr: 83116987-175).
2.2. Data Collection Tools
2.2.1. Personal Information Form
This form consisted of 13 questions concerning characteristics such as the women’s age, educational status, marital status, employment, health security, economic status, and family type. The frequency of breast self-examination (BSE), clinical breast examination (CBE) and mammography were measured, using the following questions.
1. Do you examine your own breasts? (a) Never (b) Occasionally (c) Regularly (every month)
2. Do you attend clinical breast examinations? (Does your doctor or nurse examine your breasts?) (a) Never (b) Occasionally (c) Every year/every two years on a regularly basis
3. Do you attend mammograms? (a) Never (b) Occasionally (c) Every year/every two years on a regular basis
In this study, “regularly” is taken to mean that the woman over the age of 40 were engaged in monthly BSE and annual CBE and/or mammography.
2.2.2. Breast Cancer Fear Scale (BCFS)
Champion et al. was developed the BCFS in 2004 (12). Psychometric properties of the BCFS Turkish version was conducted by Secginli and its validity and reliability have been established. The Turkish scale consists of 8 items, can range from 8 - 40 points. The scales were rated on 5-point likert scales scored as 1 = Completely disagree to 5 = Completely agree. The greater the total score gained from the scale, the higher the fear of breast cancer. While the Cronbach’s alpha coefficient was originally estimated at 0.91 for the scale (1), it was estimated at 0.92 for our study.
2.2.3. Powe’s Breast Cancer Fatalism Scale (BCFS)
Powe’s BCFS was developed in the USA (17). Mayo, Ureda, and Parker revised the original scale (18). Maximum score that can be had in the scale is “11” and the minimum one is “0”. The greater the total score gained from the scale, the higher the level of fatalism regarding breast cancer. The internal coefficient of the original scale was reported as 0.89 (18). Powe’s BCFS scale developed by Ersin et al. and consisting of 11 items whose validity and reliability have been done in Turkey (19). The KR-20 coefficient of PFITR-rPFI was estimated at 0.797; total item correlations were determined in the range of 0.264 to 0.530 (19). The Cronbach’s alpha coefficient was estimated at 0.75 for the present study.
2.2.4. Health Belief Model Scale (HBMS)
Champion was developed the HBMS in 1984. This scale was adapted by Gozum and Aydin for use with Turkish people (20). The Turkish version of the HBMS consisted of 52 items that were clustered into eight subscales including sensitivity, seriousness, and health motivation, barriers, benefits and self-efficacy about BSE; and benefits and barriers to undergoing mammography. The scale items have a 5-point Likert format with the following coding: Strongly disagree (1), disagree (2), neutral (3), agree (4), and strongly agree (5). Higher scores indicate stronger feelings related to that construct. The Cronbach’s alpha values ranged between 0.69 and 0.83 (21).
2.3. Data Analysis
The data were analyzed by means of the SPSS version 20.0 package software. For the statistical significance of data, a level of P < 0.05 was determined. Percentages and means and standard deviations were used for descriptive statistics. One-way ANOVA, and t test were used in the statistical analysis.
3. Results
The mean age of the respondent women was 52.88 ± 8.72 years. In the present study, it was reported that 62.8% of participants had graduated from primary school, 91.4% were married, 92.9% were unemployed, the majority of them (92.6%) had social insurance, the incomes of 87.3% were equal to their expenditure, 67.8% were from a nuclear family, and 90.9% had no history of breast cancer in their family. When participation in breast cancer screening was considered, the regular BSE, CBE, and mammography rates were 5.3%, 9.7%, and 9.4%, respectively.
As seen in Table 1, women’s breast cancer screening behaviors (regular BSE, CBE and mammography) were found to be low in all age groups. As the educational levels of the women increased, the rates of breast cancer screening through BSE, CBE, and mammography also increased. For unemployed women, the rate of regular BSE was 5.4%, of regular CBE was 9.5% and of regular mammography was 8.4%. For employed women, these rates were 4.2%, 12.5%, and 16.7%, respectively. The regularity of performing breast cancer screening behaviors significantly differed according to marital status and their family history (Table 1).
Table 1.Screening Behaviors According to Descriptive Features of Womena
| Screening Behaviors | Age | Education Level | Employment Status | Marital Status | Family History of Breast Cancer | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| 40 - 50 Age | +51 Age | Primary School and Below | Secondary School and Above | Employed | Unemployed | Married | Single | Yes | No | |
| BSE | ||||||||||
| No | 49 (31.4) | 65 (35.5) | 103 (35.5) | 11 (22.4) | 9 (37.5) | 105 (33.3) | 102 (32.9) | 12 (41.4) | 9 (29.0) | 105 (34.1) |
| Irregular | 100 (64.1) | 107 (58.5) | 173 (59.7) | 34 (69.4) | 14 (58.3) | 193 (61.3) | 193 (62.3) | 14 (48.3) | 19 (61.3) | 188 (61.0) |
| Regular | 7 (4.5) | 11 (6.0) | 14 (4.8) | 4 (8.2) | 1 (4.2) | 17 (5.4) | 15 (4.8) | 3 (10.3) | 3 (9.7) | 15 (4.9) |
| CBE | ||||||||||
| No | 83 (53.2) | 79 (43.2) | 142 (49.0) | 20 (40.9) | 9 (37.5) | 153 (48.6) | 147 (47.4) | 15 (51.7) | 15 (48.4v | 147 (47.7) |
| Irregular | 62 (39.7) | 82 (44.8) | 121 (41.7) | 23 (46.9) | 12 (50.0) | 132 (41.9) | 132 (42.6) | 12 (41.4) | 11 (35.5) | 133 (43.2) |
| Regular | 11 (7.1) | 22 (12.0) | 27 (9.3) | 6 (12.2) | 3 (12.5) | 30 (9.5) | 31 (10.0) | 2 (6.9) | 5 (16.1) | 28 (9.1) |
| Mammography | ||||||||||
| No | 85 (54.5) | 81 (44.3) | 146 (50.3) | 20 (40.9) | 9 (37.5) | 157 (49.8) | 152 (49.0) | 14 (48.3) | 14 (45.2) | 152 (49.4) |
| Irregular | 60 (38.4) | 81 (44.3) | 118 (40.7) | 23 (46.9) | 11 (45.8) | 130 (41.3) | 130 (41.9) | 11 (37.9) | 12 (38.7) | 129 (41.8) |
| Regular | 11 (7.1) | 21 (11.4) | 26 (9.0) | 6 (12.2) | 4 (16.7) | 28 (8.9) | 28 (9.0) | 4 (13.8) | 5 (16.1) | 27 (8.8) |
Abbreviations: BSE, breast self-examination; CBE, clinical breast examination.
aValues are expressed as n (%).
Table 2 shows the women’s mean scores from the Breast Cancer Fear, Fatalism, and Health Belief Model Scale sub-dimensions. According to Table 2, the women’s mean score from the Breast Cancer Fear Scale was 24.89 ± 9.01 and the mean score from the Breast Cancer Fatalism Scale was 4.18 ± 2.37. Scores from the dimensions of the HBMS were as follow: sensitivity, 7.01 ± 3.05; seriousness, 18.20 ± 5.68; health motivation, 18.97 ± 5.39; benefit of BSE, 14.43 ± 4.24; barriers to BSE, 19.35 ± 6.53; BSE self-efficacy, 32.2 ± 9.04; benefit of mammography, 18.33 ± 4.7, and barriers to mammography, 27.18 ± 8.94 (Table 2).
Table 2.Women’s Mean Scores from the Breast Cancer Fear, Fatalism, and Champion’s Health Belief Model Scale Sub-Dimensions
| Variables | Mean ± SD |
|---|---|
| Breast Cancer Fear Scale | 24.89 ± 9.01 |
| Breast Cancer Fatalism Scale | 4.18 ± 2.37 |
| Champion’s Health Belief Model Scale sub-dimensions | |
| Sensitivity | 7.01 ± 3.05 |
| Seriousness | 18.20 ± 5.68 |
| Health motivation | 18.97 ± 5.39 |
| Benefit of BSE | 14.43 ± 4.24 |
| Barriers to BSE | 19.35 ± 6.53 |
| BSE Self-efficacy | 32.2 ± 9.04 |
| Benefits of mammography | 18.33 ± 4.73 |
| Barriers to mammography | 27.18 ± 8.94 |
Abbreviations: BSE, breast self-examination, SD, standard deviation.
Table 3.Screening Behaviors According to the Breast Cancer Fear and Fatalism of Womena
| Screening Behaviors | Breast Cancer Fear Scale | Breast Cancer Fatalism Scale | ||||
|---|---|---|---|---|---|---|
| Mean ± SD | F | P Value | Mean ± SD | F | P Value | |
| BSE | 0.086 | 0.918 | 0.136 | 0.872 | ||
| No | 25.18 ± 9.32 | 4.13 ± 2.53 | ||||
| Irregular | 24.74 ± 8.79 | 4.19 ± 2.20 | ||||
| Regular | 24.89 ± 10.00 | 4.44 ± 3.15 | ||||
| CBE | 0.199 | 0.819 | 0.480 | 0.619 | ||
| No | 24.84 ± 8.77 | 4.06 ± 2.23 | ||||
| Irregular | 25.15 ± 9.27 | 4.28 ± 2.47 | ||||
| Regular | 24.06 ± 9.28 | 4.39 ± 2.60 | ||||
| Mammography | 0.283 | 0.754 | 2.277 | 0.104 | ||
| No | 24.73 ± 8.88 | 3.97 ± 2.24 | ||||
| Irregular | 25.27 ± 9.29 | 4.27 ± 2.36 | ||||
| Regular | 24.04 ± 8.69 | 4.91 ± 2.93 | ||||
Abbreviations: BSE, breast self-examination, CBE, clinical breast examination, SD, standard deviation.
aF, one-way ANOVA tests and significant P < 0.05.
There was no statistically significant difference found among BSE (F = 0.136, P = 0.872), CBE (F = 0.480, P = 0.619), and mammography (F = 2.277, P = 0.104) behaviors of respondent women with respect to their breast cancer fear and fatalism (Table 3).
According to Table 4, a statistically significant difference was determined between the educational levels of women and their breast cancer fatalism. Those with a low educational level had higher fatalism (t = 2.229, P = 0.027); and those having a family history of breast cancer in the had a lower perception of self-efficacy (t = -2.311, P = 0.027), but no significant difference was determined between socio-demographic characteristics such as age, employment, and marital status, and health beliefs, fear, and fatalism (Table 4).
4. Discussion
As in other societies, health belief and health behaviors in Turkey may be seriously affected by the cultural and religious values. In parallel to the findings of this study, the participation rates of women in breast cancer screening have been reported to be at a low level in studies in Turkey and around the world (4-7). In this study, regular participation in breast cancer screening was found to be higher among women aged 51 years and older, among those who had graduated from secondary school or above, those who were employed, and those with a history of breast cancer in their family. Whereas the rates of BSE and mammography among single women were higher, the CBE rate was lower with respect to married respondents. In one study, whereas employment status, age, and educational level were not found to be statistically significant in terms of the participation of women in breast cancer screening, married women’s participation in mammography was determined to be significantly higher (22). Austin et al. reported that asymptomatic women and those who did not have a family history found participation in screening unnecessary (23). Breast cancer screening behaviors were influenced by age group except for mammography, and were not influenced by educational level except for CBE. Marital status and exposure to breast cancer were not variables, which influenced CBE or mammography (4).
These different findings may suggest the influence of different cultural and religious beliefs in different countries at different times. Our findings suggest that Turkish women do not attach importance to breast cancer screening. However, no significant specific reason for this behavior was found.
| Characteristics | Breast Cancer Fear Scale | Breast Cancer Fatalism Scale | Champion’s Health Belief Model Scale Sub-dimensions | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Sensitivity | Seriousness | Health Motivation | Benefit of BSE | Barriers to BSE | BSE Self-efficacy | Benefit of Mammography | Barriers to Mammography | |||
| Age | ||||||||||
| 40 - 50 | 25.44 ± 7.98 | 4.09 ± 2.39 | 7.00 ± 2.94 | 18.68 ± 5.77 | 18.87 ± 5.40 | 14.29 ± 4.35 | 19.13 ± 6.37 | 31.59 ± 8.93 | 17.85 ± 4.65 | 27.27 ± 9.04 |
| 51 age+ | 24.43 ± 9.81 | 4.26 ± 2.35 | 7.01 ± 3.14 | 17.80 ± 5.58 | 19.04 ± 5.40 | 14.54 ± 4.15 | 19.53 ± 6.68 | 32.77 ± 9.12 | 18.74 ± 4.78 | 27.10 ± 8.87 |
| t | 1.39 | -0.668 | -0.014 | 1.427 | -0.312 | -0.546 | -0.555 | -1.202 | -1.732 | 0.175 |
| P value | 0.299 | 0.504 | 0.989 | 0.154 | 0.755 | 0.586 | 0.579 | 0.230 | 0.084 | 0.862 |
| Educational level | ||||||||||
| Primary school and- | 24.82 ± 9.25 | 4.30 ± 2.39 | 6.94 ± 3.03 | 18.13 ± 5.66 | 19.05 ± 5.27 | 14.39 ± 4.17 | 19.46 ± 6.32 | 32.10 ± 8.95 | 18.45 ± 4.62 | 27.19 ± 8.65 |
| Secondary school and+ | 25.33 ± 7.51 | 3.49 ± 2.10 | 7.43 ± 3.12 | 18.63 ± 5.84 | 18.49 ± 6.12 | 14.63 ± 4.70 | 18.67 ± 7.69 | 33.00 ± 9.61 | 17.63 ± 5.35 | 27.12 ± 10.60 |
| t | -0.421 | 2.229 | -1.043 | -0.572 | 0.666 | -0.370 | 0.781 | -0.646 | 1.121 | 0.046 |
| P value | 0.675 | 0.027 | 0.298 | 0.568 | 0.506 | 0.711 | 0.435 | 0.519 | 0.263 | 0.963 |
| Employment status | ||||||||||
| Employed | 25.29 ± 9.28 | 3.71 ± 2.07 | 7.42 ± 3.18 | 18.54 ± 5.14 | 19.46 ± 5.96 | 14.04 ± 4.93 | 17.38 ± 7.15 | 31.83 ± 9.72 | 17.75 ± 6.24 | 25.21 ± 8.22 |
| Unemployed | 24.86 ± 9.01 | 4.22 ± 2.39 | 6.98 ± 3.04 | 18.18 ± 5.72 | 18.93 ± 5.36 | 14.45 ± 4.19 | 19.50 ± 6.47 | 32.26 ± 9.00 | 18.38 ± 4.61 | 27.33 ± 8.98 |
| t | 0.224 | -1.019 | 0.680 | 0.302 | 0.465 | -0.458 | -1.538 | -0.221 | -0.483 | -1.120 ± 0.263 |
| P value | 0.823 | 0.309 | 0.497 | 0.763 | 0.642 | 0.647 | 0.125 | 0.825 | 0.633 | |
| Marital status | ||||||||||
| Married | 24.84 ± 8.89 | 4.17 ± 2.38 | 6.94 ± 3.03 | 18.12 ± 5.80 | 18.85 ± 5.47 | 14.35 ± 4.27 | 19.35 ± 6.43 | 32.01 ± 9.02 | 18.21 ± 4.80 | 27.26 ± 8.80 |
| Single | 25.52 ± 10.41 | 4.38 ± 2.29 | 7.76 ± 3.19 | 19.10 ± 4.13 | 20.21 ± 4.35 | 15.21 ± 3.90 | 19.38 ± 7.65 | 34.55 ± 9.01 | 19.66 ± 3.73 | 26.35 ± 10.39 |
| t | -0.389 | -0.467 | -1.387 | -0.892 | -1.299 | -1.038 | -0.023 | -1.450 | -1.576 | 0.524 |
| P value | 0.698 | 0.641 | 0.166 | 0.373 | 0.195 | 0.300 | 0.982 | 0.148 | 0.116 | 0.601 |
| Family history of breast cancer | ||||||||||
| Yes | 24.90 ± 7.84 | 4.00 ± 2.00 | 7.64 ± 3.09 | 18.61 ± 5.50 | 18.48 ± 5.55 | 14.00 ± 4.31 | 19.71 ± 6.42 | 28.84 ± 8.52 | 18.42 ± 4.62 | 29.35 ± 7.59 |
| No | 24.89 ± 9.14 | 4.20 ± 2.40 | 6.95 ± 3.04 | 18.16 ± 5.70 | 19.01 ± 5.38 | 14.47 ± 4.24 | 19.31 ± 6.55 | 32.57 ± 9.03 | 18.33 ± 4.75 | 26.96 ± 9.04 |
| t | 0.006 | -0.451 | 1.221 | 0.421 | -0.520 | -0.584 | 0.323 | -2.311 | 0.106 | 1.426 |
| P value | 0.995 | 0.653 | 0.223 | 0.674 | 0.603 | 0.559 | 0.747 | 0.027 | 0.916 | 0.155 |
Abbreviations: BSE, breast self-examination; SD, standard deviation.
aValues are expressed as mean ± SD.
bt, Student’s t test tests and significant P < 0.05.
This research, the participant’s fear in the breast cancer was determined to be at a high level, while their fatalism was at a medium level. In this study, the degree of fatalism was higher than in other studies (4, 24, 25). It has also been reported that fatalism was higher when self-efficacy was lower and that the belief the cancer could not be prevented were high among the women with a greater fear of cancer (26). The fear and fatalism experienced with regard to cancer are phenomena difficult to understand (27). Fear and fatalism related to breast cancer screening among Turkish women are multi-faceted issues, and this may reflect shared experiences within the health care system and community as well as the psychosocial context, in which Turkish women live. These findings suggest that women should be aware of their own religious and cultural values as well as the health care system they are within in addressing obstacles to their participation in breast cancer screening.
In the present study, the scores obtained from the sub-dimensions of the HBMS were found to be as follow: whereas perceptions of sensitivity and seriousness were at a medium level, perceptions of health and the benefits of BSE, as well as perceived barriers to BSE, BSE self-efficacy, the perceived benefits of mammography, and the perceived barriers to mammography were all at a high level. It was determined that women’s scores for breast cancer fear and fatalism related to BSE, CBE, and mammography were similar. It has been reported that a high level of fatalism reduces actions such as taking precautions and looking for information about diseases such as cancer (28). Although fatalism was not found to be directly related to having a mammogram, a relationship was determined between fatalism and barriers to cancer screening (29). It was found that when women’s perceptions of the benefits of BSE were low, their fatalism regarding breast cancer was high (5). Although it has been reported in the literature that fatalism was a barrier to screening, in one study, Afghan women’s screening rates were low, but this was not apparently related to fatalism (30). Spanish women’s fear of breast cancer was related to a high degree of fatalism and health beliefs regarding having treatment rather than taking preventive measures (23). On the other hand, Latin American women had a higher degree of fatalism, to the extent that they believed that breast cancer could not be prevented no matter what a woman did (23). In the literature, the association between fear and fatalism scores were determined in breast cancer screening (13). Women’s awareness of breast cancer was affected by fatalism with regard to breast cancer (24, 25). Women were more likely to perform BSE if they were less fatalistic (31). The findings of this study suggest that women’s fear and fatalism did not have an effect on their participation in screening. Further investigations into the fear and fatalism of women with different cultural and religious characteristics would help in understanding women’s participation in screening behaviors.
In this study, no statistically significant relationship was determined between women’s age, employment, and marital status and their health beliefs and perceptions of fear and fatalism. A relationship was found between fatalism and age, and education level and behaviors regarding mammography (18). It has been reported that a low educational level increases fatalism and reduces participation in screenings, and that fatalism reduces self-efficacy and motivation in preventive health behaviors (32). Moreover, a low level of sensitivity and high degree of fatalism are correlated with age and education (4). In another study, on highly educated women, sensitivity towards breast cancer was low, self-efficacy was high, but fear and fatalism scores were lower and they were knowledgeable about breast cancer (33). It was determined that following a breast cancer diagnosis, with the exception of women from a higher income group, education, fatalism, age, a history of breast cancer, and marital status did not have an effect on whether women researched their medical condition, and women’s degree of fatalism was at a low level (34). Some studies stress that fatalism increases in parallel to age (33). The present study addresses the relationship between fatalism and age. The findings obtained could suggest that the degree of fatalism experienced and the influence of religion do not change significantly between generations. There is a need for studies that provide solid evidence that fatalism and fear are barriers to participating in cancer screenings.
4.1. Conclusions
This study is important in determining women’s health beliefs, breast cancer fears, and the fatalism associated with the early diagnosis of breast cancer and to provide impetus for future studies. In the present study, it was predicted that women would have higher degrees of fatalism, but there was no association between participating in screening, fear, and fatalism. The findings obtained suggest that women have higher perceptions of the benefits of BSE and mammography and a high degree of self-efficacy. Additionally, it was determined in this study that women’s perceptions of barriers to BSE and mammography were at a high level. Moreover, it was found that the participation of women in breast cancer screenings was not adequate.
When it is considered that breast cancer fear and fatalism among women are a major cultural factor influencing behaviors around health, it can be suggested that this study be repeated with larger and/or more diverse sample groups. There is a need for further national and international cooperation to assess women’s health beliefs, breast cancer fears, and the fatalism they experience associated with an early diagnosis of breast cancer. In the future, researchers could investigate these variables by assessing and questioning the messages given to women by the health care system, the media, and in school.
This study has several limitations. The first is the size of the sample group, which consists only of Muslim women participating in the Quran classes. The research sample could be a limitation and is a barrier to generalizing the results. A larger sample group and comparative descriptive studies would be helpful for generalizing the universe outside the target population. The second limitation is that study’s results assumed that respondents answered the survey questions honestly. However, some women might have given the answers expected from them instead of their own opinions. The third limitation is that the women included in the sample of this study had similar characteristics, rather than coming from distinct groups within society. Since the study is descriptive in nature, the results may not reveal the relationship between factors, which have an effect on breast cancer screening and the fear and fatalism experienced by the women.
