Next Article in Journal
High Outcome-Reporting Bias in Randomized-Controlled Trials of Acupuncture for Cancer Chemotherapy-Induced Nausea and Vomiting: A Systematic Review and Meta-Epidemiological Study
Previous Article in Journal
Practical Guidance for the Expanded Implementation and Provision of Bispecific Antibodies for Diffuse Large B-Cell Lymphoma (DLBCL) Across Canada
Previous Article in Special Issue
Sleep Quality Moderates the Impact of Place-Based Social Adversity on Physical Health in Women with Breast Cancer Transitioning from Active Treatment to Survivorship
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Current Oncology
Volume 32
Issue 8
10.3390/curroncol32080461
curroncol-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluating Fatalism Among Breast Cancer Survivors in a Heterogeneous Hispanic Population: A Cross-Sectional Study

by
Liara Lopez Torralba
1,
Brian Sukhu
2,
Maria Eduarda de Azevedo Daruge
2,
Jongik Chung
3,
Victoria Loerzel
4 and
Eunkyung Lee
2,*
1
Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL 32816, USA
2
Department of Health Sciences, College of Health Professions and Sciences, University of Central Florida, Orlando, FL 32816, USA
3
Department of Statistics and Data Science, College of Sciences, University of Central Florida, Orlando, FL 32816, USA
4
Department of Nursing Practice, College of Nursing, University of Central Florida, Orlando, FL 32827, USA
*
Author to whom correspondence should be addressed.
Curr. Oncol. 2025, 32(8), 461; https://doi.org/10.3390/curroncol32080461
Submission received: 30 June 2025 / Revised: 6 August 2025 / Accepted: 12 August 2025 / Published: 15 August 2025
(This article belongs to the Special Issue Pathways to Recovery and Resilience in Breast Cancer Survivorship)
Browse Figures
Review Reports Versions Notes

Simple Summary

A key factor affecting the quality of life among Hispanic breast cancer survivors is fatalism, the belief that events are predetermined and beyond personal control. Our study in Central Florida found that these survivors exhibited moderate fatalism, often linked to strong religious beliefs and an internal locus of control. Individuals from Dominican, Mexican, and Venezuelan backgrounds showed higher fatalism, while those with higher incomes, more education, and greater English use reported lower levels. Healthcare providers should recognize patients with higher fatalism and adapt their approaches accordingly. These insights can help develop culturally sensitive interventions and support strategies to enhance patients’ sense of control

Abstract

Hispanic breast cancer survivors reported worse quality of life, and fatalism is considered one of the mediators for this disparity. This study aimed to identify the factors associated with fatalism within a diverse Hispanic population. Hispanic origin was self-reported, and the Multidimensional Fatalism Measure questionnaire, a validated tool that measures fatalism across multiple dimensions, was used to assess fatalism. A total of 390 women, consisting of 210 Puerto Ricans, 34 Colombians, 29 Dominicans, 25 Cubans, 24 Venezuelans, 22 Mexicans, and 46 individuals of other Hispanic backgrounds, completed the fatalism assessment. The mean fatalism score was 16.4 (95% CI = 15.8–17.0), characterized by a high internal locus of control and strong religious beliefs, along with moderate beliefs in luck and a low external locus of control. The higher fatalism scores were reported in Dominican, Mexican, and Venezuelan groups, while Colombians reported the lowest score. Multivariable analysis showed that Colombians (β = −4.0), individuals with higher household incomes (β = −2.3 for USD 20,000–USD 75,000, β = −2.4 for ≥75,000), higher education levels (β = −1.9), and those using English more frequently at home (β = −2.0) reported lower fatalism compared to their reference group. To enhance the quality of life for these survivors, culturally tailored interventions should focus on improving perceived control and mitigating fatalism.

1. Introduction

Breast cancer is the leading cancer diagnosed among Hispanic/Latina women in the United States (US) [1]. Although they are less likely to be diagnosed with breast cancer and die from this disease compared to their non-Hispanic White counterparts [2], they face unique challenges. These include diagnoses of high-grade tumors at younger ages [3], which entails a worse prognosis. Latina breast cancer survivors report experiencing more severe symptoms, such as fatigue, depression, and difficulties in work and spousal relationships [4,5,6] and a lower overall quality of life (QOL) compared to non-Hispanic survivors [7,8,9,10].
Growing evidence indicates that cultural factors play a significant role in cancer survivorship, particularly concerning QOL disparity [9,11]. Fatalism has been recognized as a dominant belief among Hispanic populations compared to non-Hispanic Whites [12]. Research suggests a substantial association between fatalistic beliefs and adverse outcomes in overall well-being and concerns related to breast cancer survivorship [13,14]. Fatalism, as defined by Merriam-Webster, is the belief that events are predetermined, leaving individuals powerless to change them [15]. This viewpoint implies that people have limited control over their fate concerning cancer incidence or survival [16]. High levels of fatalism reflect a diminished sense of personal control over health outcomes, whereas low levels indicate a greater sense of autonomy [17]. Research shows that fatalism can impede proactive behaviors, such as breast cancer screening and timely medical responses [18,19].
Examining fatalism is crucial, particularly as the Hispanic population continues to grow. Some studies showed that several factors, including acculturation, age, education, religion, locus of control, poverty, and cancer fear, influence fatalism among cancer survivors [20,21]. However, the findings are inconsistent across different study populations. For example, a study of ethnic minorities in the United Kingdom found a negative association between fatalism and fear of cancer [20], while another study involving Chinese breast cancer survivors found a positive association with fear of recurrence [22]. Research on fatalism among Latina breast cancer survivors is limited, as previous studies either excluded Hispanic populations from the study sample or did not explicitly focus on fatalism as the key study variable [16,21,23,24,25]. Additionally, studies did not adequately differentiate between various Hispanic subgroups [7,16,21].
Thus, the main objectives of the present study were twofold. First, it aimed to explore the factors independently associated with fatalism among Hispanic/Latina breast cancer survivors to identify individuals who are at higher risk for experiencing high fatalism. Secondly, the study examined how fatalism varies according to different Hispanic backgrounds. By understanding these perspectives, healthcare providers can develop tailored, culturally responsive strategies to reduce fatalism in these populations.

2. Materials and Methods

2.1. Study Design and Population

This is a report of an ongoing population-based, cross-sectional study that aims to evaluate the mediators of QOL disparities among breast cancer survivors within the Hispanic community in Central Florida, US. The Florida Cancer Data System (FCDS) provided contact information for individuals who met the eligibility criteria of the study. The eligibility criteria required participants to be adult women presumed to be Hispanic or Latina, aged ≥ 20 years, diagnosed with breast cancer from 2015 to 2023 in Central Florida, and reported to the FCDS. We followed the state-mandated patient recruitment procedure [26]. Our success in this recruitment process has been reported elsewhere (in press) [27]. Briefly, bilingual invitation letters were sent to all individuals deemed eligible to gauge their interest in participating in the study. If there was no response after three weeks, a second letter, accompanied by a telephone opt-out card, was sent to facilitate their participation. If there was no response to the second invitation, the bilingual research team made follow-up phone calls, attempting up to four times to gauge prospective participants’ interest in the study.
Among the 3398 women to whom we sent invitation letters, a total of 1234 women were found to be contactable and eligible for the study. We sent a survey packet to 720 women who expressed interest in participating, either online or via mail, depending on their choice, in their preferred language of English or Spanish. The survey comprised questionnaires measuring QOL, unmet needs, sociodemographic characteristics, lifestyle, comorbidities, social support, fatalism, life satisfaction, and breast cancer worry. Between September 2023 and January 2025, a total of 413 women returned the survey. We excluded two participants who identified as non-Hispanic and 21 individuals due to missing fatalism scores. This results in a final sample of 390 women for data analysis in the current study. All participants provided informed consent for their involvement and received a USD 25 gift card as compensation for their participation. The study was approved by the University of Central Florida Institutional Review Board (IRB) and the Florida Department of Health IRB. The detailed numbers are displayed in Figure 1.

2.2. Measures

2.2.1. Fatalism

The Multidimensional Fatalism Measure (MFM) was used to assess fatalistic beliefs. This questionnaire was developed and validated in both English and Spanish, ensuring linguistic consistency across different populations, and it showed strong psychometric properties, including high reliability and validity [28]. The MFM consists of 30 questions, assessing general fatalism (e.g., if something bad is going to happen to me, it will happen no matter what I do) and four related domains, including divine control (e.g., whatever happens to me in my life, it is because that is the way God wanted it to happen), internality (e.g., what happens to me is a consequence of what I do), helplessness (e.g., I feel that nothing I can do will change things), and luck (e.g., some people are simply born lucky). Each domain has six items on a five-point Likert scale ranging from 1 (not at all) to 5 (very much), with the highest score possible in each domain being 30. A high fatalism score indicates a high belief in general fatalism. A high score in divine control indicates high religious beliefs, while a high score in luck indicates a high belief in luck. A high score in internality indicates a strong internal locus of control, and a high score in helplessness indicates a strong external locus of control. Since there are no cut-off points suggested for the level of belief, we used scores of 6–12, 12–21, and 21–30 to define the levels of belief as low, moderate, and high, respectively, to enhance understanding of the characteristics of fatalism in the current study. Although there are several instruments to measure fatalism, including the Powe Fatalism Inventory or the Breast Cancer Fatalism Scale, we chose the MFM instrument, because MFM can assess multiple dimensions of fatalism, which allows for a more nuanced understanding of fatalistic beliefs [28] compared to other instruments, which are unidimensional, measuring only fatalistic belief for a specific disease outcome [29].

2.2.2. Hispanic Origin

Hispanic origin was self-reported in the survey, and this information was also collected by the cancer registry. Whenever possible, participants were categorized according to their self-reported origin. For the 19 women who did not provide a self-report of their Hispanic origin, supplementary information regarding nationality and Hispanic origin in the FCDS dataset was used. Hispanic origin was classified by country, which included Colombian, Cuban, Dominican, Mexican, Puerto Rican, Venezuelan, and Other Hispanic. Origins with <20 participants were grouped together under the ‘Other Hispanic’ category due to the low sample size.

2.2.3. Acculturation

As acculturation is seen as adapting to the culture and norms of a new environment surrounding a person [30], in our case, it would be Hispanic/Latino participants adopting more American views and beliefs. As language proficiency and time spent in a new culture are common predictors of acculturation [31], two questions from the Behavioral Risk Factor Surveillance System [32] were used to measure acculturation: (1) ‘which language do you use at home (only Spanish, more Spanish than English, equal Spanish and English, more English than Spanish, and only English spoken at home)?’ and (2) ‘how long have you lived in the US (in years)?’ Although some studies used less than 10 years, 10–19 years, and 20 or more years as the cut-off [16,33], we grouped the duration of residence into less than 10 years, 10–29 years, and 30 or more years because more than 50% have lived in the US for more than 30 years in the present study.

2.2.4. Fear of Recurrence

The Lerman Breast Cancer Worry Scale is a three-item questionnaire used to measure the level of breast cancer recurrence worry and its impact on daily lives [34]. For the current study, the question, ‘how worried are you about getting your breast cancer back?’ was used to assess the participants’ level of fear of breast cancer recurrence, with categories of 1 (low), 2–3 (moderate), and 4–5 (high).

2.2.5. Other Covariates

In addition to the above characteristics, age at the time of survey completion, race, smoking, marital status, household income, education level, height, weight, chronic medical conditions, and place of birth were self-reported in the survey. Self-reported comorbid conditions included hypertension, cardiovascular diseases, stroke, gastrointestinal problems, chronic lung diseases, arthritis, sciatica, diabetes, osteoporosis, and depression, and the presence of multimorbidity was defined as having two or more comorbidities [35], excluding cancer. The body mass index (BMI) was calculated with reported height and weight. Cancer-related characteristics, including age at diagnosis, diagnosis date, cancer stage, treatments (surgery, radiation, chemotherapy), and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) were used from the FCDS data.

2.3. Statistical Analysis

Descriptive statistics (mean ± SD for continuous variables; frequencies and percentages for categorical variables) were used to describe characteristics of study participants according to their Hispanic origin. The association between fatalism scores and each of the study characteristics was examined with the least squares mean and 95% confidence interval (CIs) using a generalized linear model. A correlation matrix was conducted to examine the interrelationship among different characteristics of fatalism (i.e., general fatalism, religious belief, belief in luck, and internal and external locus of control). To describe the characteristics of fatalism according to Hispanic origin, a radar plot in Microsoft Excel was used to visualize the distribution of the five domains. A multivariable linear regression model was built with variables found significant in the univariate analyses alongside the potential confounders known from the literature review. The normality assumption of fatalism scores was tested with graphical examinations. As shown in Supplementary Figure S1, the residuals in the multivariable linear model appear to be symmetrically distributed with a bell-shaped pattern, suggesting approximate normality. For missing information found in 11 participants (i.e., education [n = 1], language use at home [n = 2], fear of recurrence [n = 7], and years lived in the US [n = 1]), we employed the discriminant function methods for multiple imputations [36] since all of the missing variables were categorical. We performed 250 burn-in iterations to generate 1000 imputed datasets and subsequently estimated regression coefficients for each one. The combined results from these imputed datasets were summarized and reported as coefficients, standard errors, and associated p-values. Additionally, a sensitivity analysis was conducted using cases with complete data (list-wise deletion) to assess the robustness of the research findings. Statistical analyses were performed using SAS (version 9.4), and a p-value < 0.05 was considered statistically significant.

3. Results

3.1. Study Participants

The study consisted of 390 participants, and they were grouped based on their self-reported Hispanic origin: Colombian (8.7%), Cuban (6.4%), Dominican (7.4%), Mexican (5.6%), Puerto Rican (53.8%), Venezuelan (6.2%), and Other Hispanics (11.8%), including Peru, Brazil, Honduras, and other countries. Sociodemographic characteristics by Hispanic origin group can be found in Table 1. The mean age of the participants was 59.5 (±11.8) years, with an average of 4.8 (±2.0) years since diagnosis. About half of the participants self-reported their race as White (46.9%) and had a household income of USD 20,000–USD 75,000 (45.1%), while 60% were married and 68.5% had an education of some college or higher. Only 25.4% used more English than Spanish at home, and 79.0% were born outside of the US and have lived in the US for an average of 32.9 (±19.4) years. Most of them were diagnosed at an early stage with ER-positive, PR-positive, or HER2-negative tumors and received surgery, while only less than half of them received radiation (43.6%) and chemotherapy (44.1%) for breast cancer. About 65% showed a moderate or high level of fear of recurrence. Interestingly, Cubans have lived in the US for a longer time than other subgroups (45.4 years), and 48% use English more often at home. A higher proportion of Cubans had an income level of USD 75,000 or more (44.0%), but a smaller proportion had received chemotherapy (28.0%) than other subgroups. In contrast, Venezuelans have lived in the US for the shortest time of 13.5 years. Notably, 83.3% Venezuelans had higher levels of education, 91.7% use Spanish more often at home, and 75.0% have received chemotherapy.

3.2. Fatalism Scores by Participant Characteristics

The estimated mean fatalism score was 16.4 (95% CI = 15.8–17.0), as shown in Table 2. The mean scores varied by Hispanic origin, approaching statistical significance (p = 0.060). Notably, higher fatalism scores were reported among Dominican, Mexican, and Venezuelan groups, with scores of 17.4, 17.8, and 17.4, respectively, whereas Colombians reported the lowest score of 13.3. Participants with higher income levels (p = 0.004), higher education attainment (p = 0.003), an increased use of English at home (p = 0.007), recent diagnoses within two years (p = 0.043), or lower levels of fear of cancer recurrence (p = 0.039) reported lower fatalism scores. Fatalism scores did not differ significantly by age groups, race, BMI, smoking, marital status, place of birth, the presence of multimorbidity, cancer stage, and treatments received, or duration of residence in the US.

3.3. Characteristics of Fatalism

As shown in Figure 2 and Table 3, Hispanic breast cancer survivors endorsed a strong internal locus of control (23.4 ± 5.0) and religious beliefs (21.3 ± 7.5). They also demonstrated a moderate belief in luck (12.6 ± 4.7) and a low external locus of control (10.9 ± 5.3). The fatalism score was positively correlated with all other measures. As anticipated, fatalism had a stronger correlation with external locus of control and religious beliefs compared to internal locus of control and belief in luck. However, no significant correlations were found between internal locus of control and any measures, except for fatalism.
Figure 2 presents a radar plot illustrating the dynamics of MFM based on Hispanic origin. The mean fatalism scores for Dominicans, Mexicans, and Venezuelans were similar; however, their fatalism characteristics differ. For example, all three groups reported a strong internal locus of control. Dominicans reported high religious beliefs but moderate beliefs in luck and external locus of control. Mexicans reported moderate religious beliefs, beliefs in luck, and an external locus of control. Venezuelans reported strong religious beliefs, moderate beliefs in luck, and low external locus of control. In addition, Colombians and Cubans had a strong internal locus of control, moderate religious beliefs, and low beliefs in luck and external locus of control.

3.4. Factors Associated with Fatalism

The multivariable linear regression model included Hispanic origin, current age, race, income level, education level, language use at home, years lived in the US, years since diagnosis, and the level of fear of recurrence, as outlined in Table 4. This model accounted for 14.0% of the variance in fatalism (R2 = 0.140, F (22, 367) = 2.7, p < 0.0001). Relative to the Puerto Rican subgroup, Colombians reported significantly lower fatalism score, with a mean difference of 3.7 points (β = −3.7, p = 0.001). No other subgroups demonstrated significant differences in fatalism scores when compared to Puerto Ricans. Furthermore, participants making between USD 20,000 and USD 74,999 and over USD 75,000 had significantly lower fatalism scores (β = −2.4, p = 0.007 and β = −254, p = 0.029, respectively) compared to participants with incomes below USD 20,000. Individuals possessing some college education or a higher degree had significantly lower fatalism scores (β = −2.0, p = 0.008) compared to those with an education level of high school or below. Participants who primarily use English at home reported a significantly lower fatalism score (β = −1.9, p = 0.043) than those who predominantly use Spanish. There were no significant associations between fatalism scores and current age, race, years lived in the US, and the level of fear of recurrence after adjusting for confounding effects. The results from the sensitivity analysis presented in Supplementary Table S1 align closely with those obtained from the primary analysis shown in Table 4, indicating that the results remain robust.

4. Discussion

This study evaluated fatalism among 390 breast cancer survivors of various Hispanic backgrounds. The results demonstrated that these women had moderate levels of fatalism, characterized by a strong internal locus of control and religious belief, a moderate belief in luck, and a low external locus of control. Additionally, breast cancer survivors of Colombian origin and those with higher income, higher education, or proficiency in English reported lower fatalism, highlighting the need for culturally tailored interventions aimed at enhancing cancer survivorship among Hispanic breast cancer survivors.
Hispanic origin significantly influences levels of fatalism, as shown in a previous study where Mexicans and Puerto Ricans had a more fatalistic (negative) view of cancer [37]. In our study, Colombians reported a lower fatalism score compared to Puerto Ricans, contrasting with Diaz’s research, which suggested Colombians have less power to control their health stemming from a collectivist perspective [38]. The Colombians in our study were immigrants or descendants of Colombian Americans who had adapted to US culture, likely leading to a greater sense of control over their health and lower fatalism, as well as a strong internal locus of control. Although several studies reported differences in fatalism between Caucasians and African Americans [12,39,40], we were not able to observe this difference, which could be because many participants in the current study responded either ‘other’ or ‘prefer not to report,’ with only a few identifying as Black, Asian, Native Indian, or Pacific Islander. According to the Pew Research Center, only about 44% of Hispanics see their identity reflected very well with the traditional categories of the race and ethnicity questions in the US Census, and see origins as central to their identity [41]. These findings underscore the importance of considering patients’ origins, including their ethnic backgrounds, nationality, and culture, to enhance understanding of their health beliefs and behaviors, highlighting the need for cultural competency in healthcare.
Income and education have demonstrated a negative association with fatalism scores, as shown in prior research [23,39,42]. This association could be because individuals with higher household incomes often feel a greater sense of control over their medical care and have access to a more extensive support network compared to those with lower incomes [43]. Additionally, individuals with higher levels of education typically have an enhanced understanding of the available treatment options, their associated outcomes, and effective coping mechanisms [44].
The level of acculturation may be linked to fatalism [42,45]. We assessed acculturation by employing two proxy questions: proficiency in language use and duration of residence. Of these variables, only English language proficiency showed a negative association with fatalism, aligning with previous research findings [16,20]. One potential explanation for the lack of association with the length of residence in the US is that most participants in our study have resided in the country for an extended duration, resulting in minimal variability. Acculturation is defined as the process of adapting to the cultural norms and values of a new environment [30]. Therefore, measuring acculturation solely through language proficiency and duration of residence may not provide a complete representation of acculturation. Future studies should consider participants’ cultural norms, values, and practices to offer a more nuanced understanding of acculturation [46], especially when the majority of the study population consists of long-term immigrants.
Although it did not reach statistical significance, there was a slight increase in the mean fatalism score with increasing levels of fear of cancer recurrence, as demonstrated in previous research [22]. Fear of recurrence is common among breast cancer survivors, particularly those with fatalistic beliefs, and it mediates the association between fatalism and anxiety and depression.
It is noteworthy that the Hispanic breast cancer survivors in our study displayed a strong internal locus of control alongside a strong religious belief. This combination suggests that their sense of fatalism may not be solely linked to a belief in a divine being. While Hispanic survivors acknowledge that God controls every aspect of life, they also display an increased sense of personal control in managing their own lives. Stronger fatalistic beliefs, especially when coupled with medical mistrust, can lead to avoidance of necessary medical procedures [21]. Therefore, it is crucial to approach patients who display high fatalism with an understanding of the origins of these beliefs to enhance adherence to screening and treatment [21,39]. By fostering trust between patients and physicians, patients are more likely to discuss their concerns or symptoms earlier in their breast cancer survivorship care. As a result, they may be more inclined to follow recommended treatment plans, ultimately improving their prognosis and QOL. Furthermore, for those with high fatalism, interventions focusing on enhancing perceived control and reducing reliance on fatalistic beliefs could also be beneficial [22].
This study has some limitations that warrant consideration. It was conducted within a specific geographic area, which may accurately reflect the experiences of all Hispanic breast cancer survivors. However, the distribution of Hispanic origins in the sample aligns closely with the demographics observed in Central Florida, as previously reported (in press), thereby rendering the results applicable to the Hispanic breast cancer population in that region. Additionally, due to the cross-sectional design of the study, a causal relationship among the factors examined cannot be established. There is also a possibility of residual confounding, as not all the variables known to influence fatalism, such as coping mechanisms, religious affiliation, or medical access [19,42,47], were included in the multivariable model.
This study has several strengths. It is one of the first to demonstrate a disparity in fatalism based on country of origin, which is not possible when using an aggregated Hispanic group. Fatalism was measured using a valid instrument (i.e., MFM), ensuring linguistic consistency across different populations [28]. Importantly, this instrument incorporates a multidimensional belief system regarding fatalism, allowing for an evaluation of the interrelationship among various beliefs related to fatalism. The findings demonstrated how these beliefs vary by Hispanic origin, enhancing our understanding of the characteristics of fatalism among Hispanic breast cancer survivors.
In conclusion, Hispanic breast cancer survivors reported a moderate level of fatalism, with significant variations according to their specific Hispanic origin. Notably, Colombians had lower fatalism scores in comparison to Puerto Ricans. In addition, Hispanic breast cancer survivors with higher household income, higher levels of educational attainment, and those who predominantly use English rather than Spanish at home reported lower fatalism. These findings provide valuable insights for healthcare providers in seeking to identify individuals who may be at a greater risk of experiencing high fatalism. By recognizing these factors, healthcare providers can adapt their strategies to mitigate fatalism and enhance patients’ perceived control over their health outcomes and behaviors. We will investigate the role of fatalism as a potential mediator in the disparities of QOL within this Hispanic population in the subsequent phase of our study.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/curroncol32080461/s1, Figure S1: A graphic examination for the residual of the multivariable linear model; Table S1: A sensitivity analysis: Results from a multivariable linear regression model with complete cases (N = 379).

Author Contributions

Conceptualization, E.L. and V.L.; methodology, E.L., B.S. and L.L.T.; software, E.L.; validation, E.L., J.C. and L.L.T.; formal analysis, L.L.T. and J.C.; investigation, L.L.T.; resources, E.L.; data curation, E.L.; writing—original draft preparation, L.L.T.; writing—review and editing, B.S., M.E.d.A.D., E.L., L.L.T., J.C. and V.L.; visualization, E.L.; supervision, E.L.; project administration, B.S. and M.E.d.A.D.; funding acquisition, E.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Florida Breast Cancer Foundation (grant number: SGA1057674) and the University of Central Florida (grant number: AWD00001663).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the University of Central Florida (protocol code: STYDY0000832 and date of approval: 18 March 2022) and the Florida Department of Health (protocol code: 2022-044 and date of approval: 2 March 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Restrictions apply to the availability of the cancer registry’s data. Data were obtained from the Florida Cancer Data System and are available with the permission of the Florida Department of Health and Florida Cancer Registry. The survey data presented in this article are not readily available because the data are part of an ongoing study. Requests to access the survey data should be directed to the corresponding author.

Acknowledgments

The authors are thankful to all the women who participated in the study, the staff at the Florida Department of Health, and the Florida Cancer Data System for their support. The authors also thank the research team for their efforts in data collection.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
QOLQuality of life
USUnited States
FCDSFlorida Cancer Data System
IRBInstitutional Review Board
MFMMultidimensional Fatalism Measure
BMIBody mass index
CIConfidence interval

References

  1. American Cancer Society. Cancer Facts Figures for Hispanic/Latino Population 2024–2026; American Cancer Society, Inc.: Atlanta, GA, USA, 2024. [Google Scholar]
  2. Giaquinto, A.N.; Sung, H.; Newman, L.A.; Freedman, R.A.; Smith, R.A.; Star, J.; Jemal, A.; Siegel, R.L. Breast cancer statistics 2024. CA Cancer J. Clin. 2024, 74, 477–495. [Google Scholar] [CrossRef]
  3. American Cancer Society. Breast Cancer Facts Figures 2024–2025; American Cancer Society, Inc.: Atlanta, GA, USA, 2024. [Google Scholar]
  4. Ashing-Giwa, K.T.; Padilla, G.V.; Bohórquez, D.E.; Tejero, J.S.; Garcia, M. Understanding the breast cancer experience of Latina women. J. Psychosoc. Oncol. 2006, 24, 19–52. [Google Scholar] [CrossRef]
  5. Blinder, V.S.; Patil, S.; Thind, A.; Diamant, A.; Hudis, C.A.; Basch, E.; Maly, R.C. Return to work in low-income Latina and non-Latina white breast cancer survivors: A 3-year longitudinal study. Cancer 2012, 118, 1664–1674. [Google Scholar] [CrossRef]
  6. Eversley, R.; Estrin, D.; Dibble, S.; Wardlaw, L.; Pedrosa, M.; Favila-Penney, W. Post-treatment symptoms among ethnic minority breast cancer survivors. Oncol. Nurs. Forum 2005, 32, 250–256. [Google Scholar] [CrossRef] [PubMed]
  7. Almatkyzy, G.; Mojica, C.M.; Stroup, A.M.; Llanos, A.A.; O’Malley, D.; Xu, B.; Tsui, J. Predictors of health-related quality of life among Hispanic and non-Hispanic White breast cancer survivors in New Jersey. J. Psychosoc. Oncol. 2021, 39, 595–612. [Google Scholar] [CrossRef] [PubMed]
  8. Napoles-Springer, A.M.; Ortiz, C.; O’Brien, H.; Diaz-Mendez, M.; Perez-Stable, E.J. Use of cancer support groups among Latina breast cancer survivors. J. Cancer Surviv. 2007, 1, 193–204. [Google Scholar] [CrossRef] [PubMed]
  9. Yanez, B.; Thompson, E.H.; Stanton, A.L. Quality of life among Latina breast cancer patients: A systematic review of the literature. J. Cancer Surviv. 2011, 5, 191–207. [Google Scholar] [CrossRef]
  10. Carver, C.S.; Smith, R.G.; Petronis, V.M.; Antoni, M.H. Quality of life among long-term survivors of breast cancer: Different types of antecedents predict different classes of outcomes. Psychooncology 2006, 15, 749–758. [Google Scholar] [CrossRef]
  11. Yanez, B.; Stanton, A.L.; Maly, R.C. Breast cancer treatment decision making among Latinas and non-Latina Whites: A communication model predicting decisional outcomes and quality of life. Health Psychol. 2012, 31, 552–561. [Google Scholar] [CrossRef]
  12. Powe, B.D.R.; Finnie, R. Cancer Fatalism: The State of Science. Cancer Nurs. 2003, 26, 454–467. [Google Scholar] [CrossRef]
  13. Lopez-Class, M.; Perret-Gentil, M.; Kreling, B.; Caicedo, L.; Mandelblatt, J.; Graves, K.D. Quality of life among immigrant Latina breast cancer survivors: Realities of culture and enhancing cancer care. J. Cancer Educ. 2011, 26, 724–733. [Google Scholar] [CrossRef]
  14. Graves, K.D.; Jensen, R.E.; Canar, J.; Perret-Gentil, M.; Leventhal, K.G.; Gonzalez, F.; Caicedo, L.; Jandorf, L.; Kelly, S.; Mandelblatt, J. Through the lens of culture: Quality of life among Latina breast cancer survivors. Breast Cancer Res. Treat. 2012, 136, 603–613. [Google Scholar] [CrossRef]
  15. Merriam-Webster, s.v. “Fatalism (n)”. Available online: https://www.merriam-webster.com/dictionary/fatalism (accessed on 12 June 2025).
  16. Abraído-Lanza, A.F.; Martins, M.C.; Shelton, R.C.; Flórez, K.R. Breast Cancer Screening Among Dominican Latinas: A Closer Look at Fatalism and Other Social and Cultural Factors. Health Educ. Behav. 2015, 42, 633–641. [Google Scholar] [CrossRef]
  17. Powe, B.D.; Hamilton, J.; Brooks, P. Perceptions of Cancer Fatalism and Cancer Knowledge. J. Psychosoc. Oncol. 2006, 24, 1–13. [Google Scholar] [CrossRef] [PubMed]
  18. Remennick, L. The Challenge of Early Breast Cancer Detection among Immigrant and Minority Women in Multicultural Societies. Breast J. 2006, 12, S103–S110. [Google Scholar] [CrossRef] [PubMed]
  19. Shahid, F.; Beshai, S.; Del Rosario, N. Fatalism and Depressive Symptoms: Active and Passive Forms of Fatalism Differentially Predict Depression. J. Relig. Health 2020, 59, 3211–3226. [Google Scholar] [CrossRef] [PubMed]
  20. Vrinten, C.; Wardle, J.; Marlow, L.A. Cancer fear and fatalism among ethnic minority women in the United Kingdom. Br. J. Cancer 2016, 114, 597–604. [Google Scholar] [CrossRef]
  21. Bustillo, N.E.; McGinty, H.L.; Dahn, J.R.; Yanez, B.; Antoni, M.H.; Kava, B.R.; Penedo, F.J. Fatalism, medical mistrust, and pretreatment health-related quality of life in ethnically diverse prostate cancer patients. Psycho-Oncology 2017, 26, 323–329. [Google Scholar] [CrossRef]
  22. Tsai, W.; Wang, J.H.-Y. Fatalism and Psychological Distress Among Chinese American Breast Cancer Survivors: Mediating Role of Perceived Self-control and Fear of Cancer Recurrence. Int. J. Behav. Med. 2023, 30, 705–713. [Google Scholar] [CrossRef]
  23. Baron-Epel, O.; Friedman, N.; Lernau, O. Fatalism and Mammography in a Multicultural Population. Oncol. Nurs. Forum 2009, 36, 353–361. [Google Scholar] [CrossRef]
  24. Ghaderi, I.; Kaviani, A.; Fakhrejahani, E.; Mehrdad, N.; Hazar, N.; Karbakhsh, M. Religious, Cultural, and Social Beliefs of Iranian Rural Women about Breast Cancer: A Qualitative Study. Arch. Breast Cancer 2014, 1, 25–31. [Google Scholar] [CrossRef]
  25. Gullatte, M.M.; Brawley, O.; Kinney, A.; Powe, B.; Mooney, K. Religiosity, Spirituality, and Cancer Fatalism Beliefs on Delay in Breast Cancer Diagnosis in African American Women. J. Relig. Health 2010, 49, 62–72. [Google Scholar] [CrossRef]
  26. Florida Department of Health. Procedure Guide for Studies That Utilize Patient Identifiable Data from the Florida Cancer Data System. Available online: https://fcds.med.miami.edu/downloads/datarequest/ProcedureGuide_Revised_March2016.pdf (accessed on 1 June 2025).
  27. Lee, E.; Sukhu, B.D.; de Azevedo Daruge, M.E.; Chung, J.; Hines, R.B.; Loerzel, V. Recruitment Feasibility of Hispanic Women in Breast Cancer Survivorship Research Using State Cancer Registry Procedures. J. Racial Ethn. Health Disparities 2025, 1–10. [Google Scholar] [CrossRef] [PubMed]
  28. Esparza, O.A.; Wiebe, J.S.; Quiñones, J. Simultaneous Development of a Multidimensional Fatalism Measure in English and Spanish. Curr. Psychol. 2015, 34, 597–612. [Google Scholar] [CrossRef] [PubMed]
  29. Valenti, G.D.; Faraci, P. Instruments measuring fatalism: A systematic review. Psychol. Assess. 2022, 34, 159–175. [Google Scholar] [CrossRef] [PubMed]
  30. Berry, J.W. Acculturation: Living successfully in two cultures. Int. J. Intercult. Relat. 2005, 29, 697–712. [Google Scholar] [CrossRef]
  31. Wilson, E.J.; Bennett, K.K.; Clark, J.R.; Harry, K.M.; Tiznado, D.; Eways, K.R.; Ramirez, A.; Marte, R.M. The Interaction between Fatalism and Religious Attendance is Negatively Associated with Mental Health-Related Quality of Life in Hispanic/Latino Americans Low in Acculturation. N. Am. J. Psychol. 2020, 22, 521. [Google Scholar]
  32. U.S. Department of Health and Human Services. Behavioral Risk Factor Surveillance System Survey Questionnaire. Available online: https://www.cdc.gov/brfss/questionnaires/index.htm (accessed on 1 June 2025).
  33. Kandula, N.R.; Diez-Roux, A.V.; Chan, C.; Daviglus, M.L.; Jackson, S.A.; Ni, H.; Schreiner, P.J. Association of Acculturation Levels and Prevalence of Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2008, 31, 1621–1628. [Google Scholar] [CrossRef]
  34. Lerman, C.; Trock, B.; Rimer, B.K.; Jepson, C.; Brody, D.; Boyce, A. Psychological side effects of breast cancer screening. Health Psychol. 1991, 10, 259–267. [Google Scholar] [CrossRef]
  35. Brettschneider, C.; Leicht, H.; Bickel, H.; Dahlhaus, A.; Fuchs, A.; Gensichen, J.; Maier, W.; Riedel-Heller, S.; Schafer, I.; Schon, G.; et al. Relative impact of multimorbid chronic conditions on health-related quality of life--results from the MultiCare Cohort Study. PLoS ONE 2013, 8, e66742. [Google Scholar] [CrossRef]
  36. Brand, J.P.L. Development, Implementation and Evaluation of Multiple Imputation Strategies for the Statistical Analysis of Incomplete Data Sets; Erasmus University: Rotterdam, The Netherlands, 1999; p. 212. [Google Scholar]
  37. Ramirez, A.G.; Suarez, L.; Laufman, L.; Barroso, C.; Chalela, P. Hispanic women’s breast and cervical cancer knowledge, attitudes, and screening behaviors. Am. J. Health Promot. 2000, 14, 292–300. [Google Scholar] [CrossRef]
  38. Díaz, D.; Blanco, A.; Bajo, M.; Stavraki, M. Fatalism and Well-Being Across Hispanic Cultures: The Social Fatalism Scales (SFS). Soc. Indic. Res. 2015, 124, 929–945. [Google Scholar] [CrossRef]
  39. Mayo, R.M.; Ureda, J.R.; Parker, V.G. Importance of Fatalism in Understanding Mammography Screening in Rural Elderly Women. J. Women Aging 2001, 13, 57–72. [Google Scholar] [CrossRef] [PubMed]
  40. Sukkarieh-Haraty, O.; Egede, L.E.; Kharma, J.A.; Bassil, M. Predictors of Diabetes Fatalism Among Arabs: A Cross-Sectional Study of Lebanese Adults with Type 2 Diabetes. J. Relig. Health 2018, 57, 858–868. [Google Scholar] [CrossRef] [PubMed]
  41. Cohn, D.V.; Brown, A.; Lopez, M.H. Black and Hispanic Americans See Their Origins as Central to Who They Are, Less So for White Adults; Pew Research Center: Washington, DC, USA, 2021. [Google Scholar]
  42. Otero-Sabogal, R.; Stewart, S.; Sabogal, F.; Brown, B.A.; Pérez-Stable, E.J. Access and Attitudinal Factors Related to Breast and Cervical Cancer Rescreening: Why are Latinas Still Underscreened? Health Educ. Behav. 2003, 30, 337–359. [Google Scholar] [CrossRef]
  43. Finkelstein, D.M.; Harding, J.F.; Paulsell, D.; English, B.; Hijjawi, G.R.; Ng’andu, J. Economic Well-Being And Health: The Role Of Income Support Programs In Promoting Health And Advancing Health Equity. Health Aff. 2022, 41, 1700–1706. [Google Scholar] [CrossRef]
  44. Berkman, N.D.; Sheridan, S.L.; Donahue, K.E.; Halpern, D.J.; Crotty, K. Low health literacy and health outcomes: An updated systematic review. Ann. Intern. Med. 2011, 155, 97–107. [Google Scholar] [CrossRef]
  45. Harmon, M.P.; Castro, F.G.; Coe, K. Acculturation and cervical cancer: Knowledge, beliefs, and behaviors of Hispanic women. Women Health 1996, 24, 37–57. [Google Scholar] [CrossRef]
  46. Schwartz, S.J.; Unger, J.B.; Zamboanga, B.L.; Szapocznik, J. Rethinking the concept of acculturation: Implications for theory and research. Am. Psychol. 2010, 65, 237–251. [Google Scholar] [CrossRef]
  47. Durmaz, H.; Çapik, C. Are Health Fatalism and Styles of Coping with Stress Affected by Poverty? A Field Study. Iran. J. Public Health 2023, 52, 575–583. [Google Scholar] [CrossRef]
Curroncol 32 00461 g001
Figure 1. Sample selection process.
Figure 1. Sample selection process.
Curroncol 32 00461 g001
Curroncol 32 00461 g002
Figure 2. Dynamics of Multidimensional Fatalism Measure of Hispanic breast cancer survivors by Hispanic origin. The radar plot displays the dynamics of multidimensional fatalism measures, starting at 0 in the center and reaching a maximum possible score of 30 at the outer edges. This plot helps us understand the characteristics of fatalism across different Hispanic subgroups and identify subgroups with a lower dimension score.
Figure 2. Dynamics of Multidimensional Fatalism Measure of Hispanic breast cancer survivors by Hispanic origin. The radar plot displays the dynamics of multidimensional fatalism measures, starting at 0 in the center and reaching a maximum possible score of 30 at the outer edges. This plot helps us understand the characteristics of fatalism across different Hispanic subgroups and identify subgroups with a lower dimension score.
Curroncol 32 00461 g002
Table 1. Sociodemographic characteristics of study participants according to Hispanic origin (N = 390).
Table 1. Sociodemographic characteristics of study participants according to Hispanic origin (N = 390).
Characteristics/CategoriesTotalColombianCubanDominicanMexicanPuerto RicanVenezuelanOther Hispanic
No. of participants390 (100.0%)34 (8.7%)25 (6.4%)29 (7.4%)22 (5.6%)210 (53.8%)24 (6.2%)46 (11.8%)
Mean (SD)p-value
Age at diagnosis55.0 (11.9)56.4 (9.8)57.1 (12.0)55.7 (13.3)50.0 (12.2)55.7 (11.9)53.5 (12.3)52.3 (11.1)0.177
Current age59.5 (11.8)60.4 (9.6)61.6 (12.3)60.0 (13.0)55.0 (11.7)60.2 (11.8)57.9 (12.2)57.6 (11.6)0.375
Years since diagnosis4.8 (2.0)4.8 (2.1)4.6 (1.9)4.4 (1.9)5.1 (2.1)4.6 (1.9)4.6 (1.8)5.6 (2.9)0.089
Years lived in US32.9 (19.4)33.6 (18.2)45.4 (17.9)40.9 (16.7)37.7 (16.5)31.3 (19.9)13.5 (11.1)35.6 (16.1)<0.001
Body mass index28.7 (5.7)26.7 (4.8)29.3 (5.6)28.1 (5.4)29.5 (6.5)29.2 (5.9)27.8 (6.2)27.9 (4.4)0.194
N (%)p-value
Race 0.029
White183 (46.9)15 (44.1)5 (20.0)20 (69.0)12 (54.5)98 (46.7)9 (37.5)24 (52.2)
Nonwhite207 (53.1)19 (55.9)20 (80.0)9 (31.0)10 (45.5)112 (53.3)15 (62.5)22 (47.8)
Current smoking 0.729
No 372 (95.4)32 (94.1)23 (92.0)29 (100.0)22 (100.0)200 (95.2)23 (95.8)43 (93.5)
Yes15 (3.8)2 (5.9)2 (8.0)0 (0.0)0 (0.0)8 (3.8)1 (4.2)2 (4.3)
Marital status 0.074
Married234 (60.0)20 (58.8)20 (80.0)14 (48.3)15 (68.2)117 (55.7)16 (66.7)32 (69.6)
Divorced/separated/widowed151 (38.7)14 (41.2)4 (16.0)15 (51.7)6 (27.3)90 (42.9)8 (33.3)14 (30.4)
Household income 0.090
<USD 20,00067 (17.2)10 (29.4)3 (12.0)6 (20.7)2 (9.1)37 (17.6)3 (12.5)6 (13.0)
USD 20,000–<USD 75,000176 (45.1)14 (41.2)5 (20.0)11 (37.9)13 (59.1)100 (47.6)13 (54.2)20 (43.5)
≥USD 75,00092 (23.6)7 (20.6)11 (44.0)6 (20.7)3 (13.6)48 (22.9)3 (12.5)14 (30.4)
Prefer not to answer 55 (14.1)3 (8.8)6 (24.0)6 (20.7)4 (18.2)25 (11.9)5 (20.8)6 (13.0)
Education level 0.025
≤High school122 (31.3)13 (38.2)9 (36.0)11 (37.9)13 (59.1)60 (28.6)4 (16.7)12 (26.1)
Some college+267 (68.5)21 (61.8)16 (64.0)18 (62.1)8 (36.4)150 (71.4)20 (83.3)34 (73.9)
Multimorbidity 0.309
No157 (40.3)16 (47.1)10 (40.0)11 (37.9)12 (54.5)75 (35.7)12 (50.0)21 (45.7)
Yes218 (55.9)18 (52.9)14 (56.0)17 (58.6)9 (40.9)129 (61.4)11 (45.8)20 (43.5)
Language used at home <0.001
More Spanish203 (52.1)22 (64.7)9 (36.0013 (44.8)10 (45.5)112 (53.3)22 (91.7)15 (32.6)
Both equally86 (22.1)5 (14.7)4 (16.0)7 (24.1)1 (4.5)57 (27.1)1 (4.2)11 (23.9)
More English99 (25.4)7 (20.6)12 (48.0)9 (31.0)10 (45.5)41 (19.5)1 (4.2)19 (41.3)
Birthplace 0.167
US308 (79.0)31 (91.2)18 (72.0)23 (79.3)18 (81.8)159 (75.7)23 (95.8)36 (78.3)
Non-US81 (20.8)3 (8.8)7 (28.0)6 (20.7)4 (18.2)50 (23.8)1 (4.2)10 (21.7)
Stage 0.441
In situ65 (16.7)7 (20.6)3 (12.0)7 (24.1)4 (18.2)35 (16.7)1 (4.2)8 (17.4)
Localized158 (40.5)12 (35.3)12 (48.0)11 (37.9)7 (31.8)87 (41.4)17 (70.8)12 (26.1)
Regional/distant66 (16.9)4 (11.8)4 (16.0)5 (17.2)3 (13.6)41 (19.5)2 (8.3)7 (15.2)
Surgery 0.467
No 15 (3.8)3 (8.8)1 (4.0)1 (3.4)0 (0.0)7 (3.3)1 (4.2)2 (4.3)
Breast-conserving surgery199 (51.0)20 (58.8)18 (72.0)16 (55.2)12 (54.5)102 (48.6)10 (41.7)21 (45.7)
Mastectomy176 (45.1)11 (32.4)6 (24.0)12 (41.4)10 (45.5)101 (48.1)13 (54.2)23 (50.0)
Radiation therapy 0.160
No209 (53.6)16 (47.1)8 (32.0)15 (51.7)11 (50.0)115 (54.8)13 (54.2)31 (67.4)
Yes170 (43.6)18 (52.9)15 (60.0)14 (48.3)10 (45.5)89 (42.4)11 (45.8)13 (28.3)
Chemotherapy 0.008
No217 (55.6)21 (61.8)18 (72.0)15 (51.7)9 (40.9)117 (55.7)6 (25.0)31 (67.4)
Yes172 (44.1)12 (35.3)7 (28.0)14 (48.3)13 (59.1)93 (44.3)18 (75.0)15 (32.6)
ER status 0.347
Negative54 (13.8)5 (14.7)3 (12.0)4 (13.8)6 (27.3)24 (11.4)6 (25.0)6 (13.0)
Positive319 (81.8)27 (79.4)22 (88.0)22 (75.9)15 (68.2)176 (83.8)18 (75.0)39 (84.8)
PR status 0.673
Negative98 (25.1)8 (23.5)6 (24.0)6 (20.7)9 (40.9)51 (24.3)8 (33.3)10 (21.7)
Positive270 (69.2)22 (64.7)18 (72.0)20 (69.0)12 (54.5)148 (70.5)16 (66.7)34 (73.9)
HER2 status 0.082
Negative253 (64.9)21 (61.8)17 (68.0)20 (69.0)13 (59.1)139 (66.2)14 (58.3)29 (63.0)
Positive60 (15.4)2 (5.9)4 (16.0)1 (3.4)5 (22.7)31 (14.8)9 (37.5)8 (17.4)
Fear of recurrence 0.470
Low132 (33.8)13 (38.2)12 (48.0)8 (27.6)10 (45.5)63 (30.0)10 (41.7)16 (34.8)
Moderate201 (51.5)19 (55.9)11 (44.0)15 (51.7)11 (50.0)109 (51.9)13 (54.2)23 (50.0)
High50 (12.8)2 (5.9)2 (8.0)6 (20.7)1 (4.5)33 (15.7)1 (4.2)5 (10.9)
Percentages may add to less than 100% due to rounding and missing data. Other includes participants from countries in Central or South America (Argentina, Brazil, Peru, Honduras, and Panama) and Europe (Spain and Portugal). ER: estrogen receptor; PR: progesterone receptor.
Table 2. Least squares means and 95% confidence intervals of fatalism scores across sociodemographic and clinical characteristics.
Table 2. Least squares means and 95% confidence intervals of fatalism scores across sociodemographic and clinical characteristics.
VariableCategoryNEstimated Mean (95% CI)p-Value
Total 39016.4 (15.8–17.0)
Hispanic origin Colombian3413.3 (11.2–15.4)0.060
Cuban2515.6 (13.1–18.1)
Dominican2917.4 (15.1–19.7)
Mexican2217.8 (15.2–20.5)
Puerto Rican21016.7 (15.9–17.6)
Venezuelan2417.4 (14.9–132.8)
Other Hispanic4615.8 (14.1–17.7)
Current age (years)20–<401518.7 (15.5–21.8)0.377
40–<5513116.6 (15.5–17.7)
55–7015915.9 (14.9–16.9)
≥708516.7 (15.3–18.0)
RaceWhite20715.9 (15.1–16.8)0.111
Non-white18317.0 (16.0–17.9)
Body mass index (kg/m2)<2510916.2 (15.1–17.4)0.709
25–<3014116.3 (15.2–17.3)
≥3013516.8 (15.7–17.9)
Current smokingNo37216.3 (15.7–17.0)0.304
Yes1518.1 (14.8–21.3)
Marital statusMarried23416.6 (15.7–17.4)0.770
Unmarried15116.4 (15.3–17.4)
Household income<USD 20,0006718.5 (17.0–20.0)0.004
USD 20,000–<USD 75,00017616.1 (15.2–17.0)
≥USD 75,0009215.1 (13.8–16.3)
Prefer not to answer5517.1 (15.5–18.8)
Education level≤High school12218.2 (17.1–19.3)<0.001
Some college or more26715.6 (14.8–16.4)
Language use at homeMore Spanish20317.1 (16.2–17.9)0.007
Both equally8617.0 (15.6–18.3)
More English9914.7 (13.5–16.0)
BirthplaceUnited States8115.8 (14.4–17.2)0.314
Outside United States30816.6 (15.9–17.3)
Multimorbidity No15716.7 (15.7–17.7)0.513
Yes21816.2 (15.4–17.1)
Cancer stageIn Situ6516.2 (14.6–17.7)0.574
Localized15816.1 (15.1–17.1)
Regional/distant6617.0 (15.5–18.6)
SurgeryNo1513.8 (10.6–17.0)0.259
Breast-conserving surgery19916.6 (15.7–17.5)
Mastectomy17616.5 (15.5–17.4)
RadiotherapyNo20916.4 (15.6–17.3)0.895
Yes17016.4 (15.4–17.3)
ChemotherapyNo21716.3 (15.4–17.1)0.527
Yes17216.7 (15.7–17.6)
Estrogen receptorNegative5416.3 (14.6–18.0)0.881
Positive31916.4 (15.7–17.1)
Years since diagnosis (years)<24214.1 (12.2–16.1)0.043
2–<521616.8 (16.0–17.7)
5–<1013216.5 (15.4–17.6)
Years lived in US <106416.1 (14.5–17.6)0.718
10–<3011916.8 (15.6–17.9)
≥3020616.3 (15.4–17.2)
Fear of recurrenceLow13215.6 (14.5–16.7)0.039
Moderate20116.6 (15.7–17.4)
High5018.2 (16.5–20.0)
Table 3. Correlation matrix among the Multidimensional Fatalism Measures of Hispanic breast cancer survivors (N = 390).
Table 3. Correlation matrix among the Multidimensional Fatalism Measures of Hispanic breast cancer survivors (N = 390).
VariableFatalismReligious BeliefExternal Locus of ControlInternal Locus of ControlBelief in Luck
Mean (SD)16.4 (6.3)21.3 (7.5)10.9 (5.3)23.4 (5.0)12.6 (4.7)
Correlation Matrix: Correlation Coefficient (p-value)
Religious belief0.394
(p < 0.001)
External locus of control0.400
(p < 0.001)		0.125
(p = 0.014)
Internal locus of control0.150
(p = 0.003)		−0.003
(p = 0.949)		−0.045
(p = 0.677)
Belief in luck0.273
(p < 0.001)		0.156
(p = 0.002)		0.384
(p < 0.001)		0.060
(p = 0.234)
Table 4. Results from a multivariable linear regression model, investigating factors associated with fatalism score among Hispanic breast cancer survivors (N = 390).
Table 4. Results from a multivariable linear regression model, investigating factors associated with fatalism score among Hispanic breast cancer survivors (N = 390).
CharacteristicsParameterbSEp-Value
Intercept19.22.4<0.0001
Hispanic origin (Ref: Puerto Rican)Colombian−3.71.10.001
Cuban−0.91.30.509
Dominican−0.11.20.920
Mexican0.71.40.622
Venezuelan1.41.40.314
Other Hispanic−0.71.00.480
Current age (Ref: 20–<40)40–<55−1.91.70.264
55–<70 −3.01.70.082
70+−3.31.80.069
Race (Ref: white)Non-white 0.70.60.289
Household income (Ref: <USD 20,000)USD 20,000–<USD 75,000−2.40.90.007
≥USD 75,000−2.41.10.029
Prefer not to answer−1.21.10.273
Education (Ref: ≤ high school)Some college+−2.00.70.008
Language use at home (Ref: more Spanish)
Both equally−0.20.90.804
More English−1.90.90.043
Years lived in US (Ref: <10)10–<300.91.00.380
30+1.61.00.110
Years since diagnosis (Ref: <2)2–<52.01.00.061
≥52.11.10.052
Fear of recurrence (Ref: low)Moderate0.80.70.225
High1.81.10.103
b: regression coefficient, SE: standard error.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lopez Torralba, L.; Sukhu, B.; de Azevedo Daruge, M.E.; Chung, J.; Loerzel, V.; Lee, E. Evaluating Fatalism Among Breast Cancer Survivors in a Heterogeneous Hispanic Population: A Cross-Sectional Study. Curr. Oncol. 2025, 32, 461. https://doi.org/10.3390/curroncol32080461

AMA Style

Lopez Torralba L, Sukhu B, de Azevedo Daruge ME, Chung J, Loerzel V, Lee E. Evaluating Fatalism Among Breast Cancer Survivors in a Heterogeneous Hispanic Population: A Cross-Sectional Study. Current Oncology. 2025; 32(8):461. https://doi.org/10.3390/curroncol32080461

Chicago/Turabian Style

Lopez Torralba, Liara, Brian Sukhu, Maria Eduarda de Azevedo Daruge, Jongik Chung, Victoria Loerzel, and Eunkyung Lee. 2025. "Evaluating Fatalism Among Breast Cancer Survivors in a Heterogeneous Hispanic Population: A Cross-Sectional Study" Current Oncology 32, no. 8: 461. https://doi.org/10.3390/curroncol32080461

APA Style

Lopez Torralba, L., Sukhu, B., de Azevedo Daruge, M. E., Chung, J., Loerzel, V., & Lee, E. (2025). Evaluating Fatalism Among Breast Cancer Survivors in a Heterogeneous Hispanic Population: A Cross-Sectional Study. Current Oncology, 32(8), 461. https://doi.org/10.3390/curroncol32080461

Article Metrics

Back to TopTop