




































 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e1                                              Cancer Health Disparities 

RESEARCH 

Exploring the employment challenges 

and concerns of minority women cancer 

survivors 
Dinorah Martinez Tysona, Silvia Sommarivaa*, Aria Walsh-Felza, Peggie Sherryb, Joanne C. Sandbergc 

a College of Public Health, University of South Florida, 13201 Bruce B. Downs Blvd, MDC56, 

Tampa, FL 33612-3805. 
b Faces of Courage 501(c)(3). Cross Creek Bldv #519, Tampa, FL 33647-2595. 
c Department of Family and Community Medicine, Wake Forest School of Medicine, Medical Center 

Boulevard, Winston-Salem, NC 27157. 

*Corresponding author: Silvia Sommariva, sommarivas@health.usf.edu (929) 264-8128 

ABSTRACT 
Employment plays an essential role in cancer survivorship. The study emerged from needs identified by 

community partners who voiced concerns about employment-related issues encountered by cancer 

survivors. Thus, the purpose of this exploratory study is to understand the experiences of minority 

women cancer survivors after cancer. We explore how type of occupation shapes the employment 

status of minority women cancer survivors after treatment. A community-based purposive sample of 

diverse cancer survivors (n=57) who reported working shortly before being diagnosed with cancer were 

administered a semi-structured questionnaire. Close-ended responses were analyzed using descriptive 

statistics. Open-ended responses were analyzed using applied thematic analysis techniques as well a 

Crisp Set Qualitative Comparative Analysis (QCA). Work-related concerns were similar across 

occupation types, while disparities were observed in reported job loss rates after diagnosis and 

employment rates after treatment. Women’s concerns related to productivity losses at work due to 

treatment side effects, disease management issues, fear of job loss, and economic concerns. The QCA 

pathway that appeared to best explain the outcome of working after treatment completion included the 

following components: working during treatment, having employer-based health insurance and being 

eligible for medical leave (perception of). This study provides relevant insights on the work experience 

and concerns of minority women cancer survivors, a population segment that has been frequently 

underrepresented in the literature on survivors’ work outcomes after cancer diagnosis and treatment. 

KEYWORDS: Cancer disparities, minorities, employment, work 

Citation: Tyson DM et al  (2019) Exploring the employment challenges and concerns of minority women 

cancer survivors. Cancer Health Disparities.e1-13. doi:10.9777/chd.2019.1014. 

 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e2                                              Cancer Health Disparities 

RESEARCH 

Introduction 

Progress in cancer research and treatment has led 

to an increased number of survivors and a 

consequential need to address disease 

management and quality of life after diagnosis 

(Hoffman, 2005). Previous studies on survivorship 

have shown that achieving a sense of normalcy 

includes resuming activities carried out before 

diagnosis such as maintaining/obtaining 

employment (Kennedy, Haslam, Munir, & Pryce, 

2007; Spelten, Sprangers, & Verbeek, 2002), which 

also has a positive influence on wellbeing (Clarke et 

al., 2015). Employment plays an essential role in 

cancer survivorship because of the benefits it 

provides including income, better psychosocial 

health, and possibly employer-based health 

insurance (Amir, Neary, & Luke, 2008; Main, 

Nowels, Cavender, Etschmaier, & Steiner, 2005; 

Nachreiner et al., 2007). Multiple factors affect the 

likelihood that women employed at time of 

diagnosis will work after cancer treatment, including 

federal, state, and employer policies; work 

environment; short and long-term and late effects 

of cancer treatment; and individual factors 

(Mehnert, 2011). Direct physical impacts of disease, 

such as pain and fatigue, as well as treatment side 

effects may impair the survivors’ ability to work 

(Amir, Neary, & Luke, 2008; Jagsi et al., 2014). Co-

workers support and general positive workplace 

climate can also influence the likelihood of return to 

work or continuance of employment during and 

after cancer treatment (Bradley & Wilk, 2014; Islam 

et al., 2014; Pryce, Munir, & Haslam., 2007). 

Characteristics of the work environment, such as 

type of occupation, level of physical demands, and 

work schedule flexibility, also influence job-related 

outcome (Bouknight, Bradley, & Luo, 2006; Islam et 

al., 2014; Spelten, Sprangers, & Verbeek, 2002). 

Thus, understanding how work after cancer 

diagnosis can differ across employment conditions 

is crucial. 

While literature exists on the work-related 

outcomes among women cancer survivors in 

general (Mehnert, de Boer, & Feuerstein, 2013), 

research that examines the work outcomes 

(employment status) for racial and ethnic minority 

women is limited (Blinder et al.. 2012; Bouknight, 

Bradley, & Luo, 2006; Bradley, Neumark, Luo, & 

Schenk, 2007; Bradley, & Wilk, 2014; Mujahid et al., 

2011; Mujahid et al., 2010). Although the evidence is 

not uniform (Bradley & Wilk, 2014), studies generally 

indicate that minority survivors experience greater 

financial problems attributable to a cancer 

diagnosis and its treatment than European 

American women (Jagsi et al., 2014). Moreover, 

minority women may experience racial and ethnic 

discrimination that further disadvantage them in the 

workplace. Still, our overall understanding of 

minority survivors’ work experiences following 

diagnosis remains inadequate. The purpose of this 

study is to understand the experiences of minority 

women cancer survivors in relation to work and the 

factors contributing to their employment status 

after treatment (regardless of type of employment). 

The study emerged from needs identified by 

community partners who voiced concerns about 

employment-related issues encountered by the 

cancer survivors they worked with. The analysis 

explores how type of occupation and employment 

benefits (medical leave, insurance) contribute to 

shaping the employment status of women cancer 

survivors after diagnosis and treatment. 

Materials and methods 

Sample and Recruitment 

Recruitment was aided by previously established 

and long-standing partnerships with community-



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e3                                              Cancer Health Disparities 

RESEARCH 

based organizations that serve cancer survivors. A 

purposive sample of cancer survivors was recruited 

at two cancer survivorship workshops in West 

Central Florida. The events were purposefully 

selected as survivors who attend them are from 

culturally and ethnically diverse backgrounds. 

Participation in the study was voluntary. Each 

participant was presented with detailed study 

information verbally consented. Inclusion criteria 

were: being a woman who had ever been 

diagnosed with cancer and being 18 years old or 

older. 

Data Collection 

Based on the literature on work and cancer 

survivorship presented above, input from cancer 

survivor advocates and the authors’ work with 

minority cancer survivors, we developed a semi-

structured questionnaire comprised of 7 open-

ended and 21 close-ended items. The 

questionnaire was pilot-tested with two cancer 

survivors. Information captured included time of 

cancer diagnosis, type of cancer and treatment, 

work status before diagnosis, job loss after cancer 

diagnosis, work status during and after cancer 

treatment, current work status, type of job and 

duties, as well as general socio-demographic data 

such as age, education, and income. These 

variables have been identified as key in influencing 

survivors’ employment status after treatment in 

previous literature. The questionnaire utilized a 

skip pattern. Participants who reported they were 

working three months prior to their cancer 

diagnosis were directed to open-ended questions 

about main duties at their jobs. These participants 

were asked open-ended questions about work-

related concerns or challenges they experienced 

after diagnosis. They were also directed to 

structured questions about their perceived 

eligibility to take a medical leave (yes/no); 

coverage by employer-based health insurance 

(yes/no); and job loss after diagnosis (yes/no). 

Participants were also asked about what type of 

work-related information would be helpful and 

whether they considered programs to support 

working women survivors beneficial. All 

participants were asked to self-rate their health 

using the 2002 WHO World Health Survey scale of 

self-rated health (Subramanian, Huijts, & 

Avendano, 2010). Facilitated by the Standard 

Occupational Classification System (Bureau of 

Labor Statistics, 2010), participants’ occupations 

were placed into one of three categories: (1) 

management or professional; (2) services, sales 

and office support; and (3) construction, 

production and transportation. Due to the limited 

number of survivors whose occupations were 

construction, production and transportation, the 

latter two categories were combined for analysis, 

and will be referred to as “service, office support, 

and production.” The questionnaire was designed 

to be self-administered. However, a few 

participants requested assistance and the items 

were read to them. The questionnaire was 

available in both English and Spanish. The 

Institutional Review Board at the [university name 

masked for blind review] approved this study. 

Data Analysis 

All questions and responses were entered into 

Excel. Close-ended responses were analyzed 

descriptively, with frequencies and proportions 

reported for each question. Qualitative responses 

to open-ended questions were systematically and 

iteratively coded by two bilingual research team 

members using applied thematic analysis 

techniques (Bernard, Wutich, & Ryan, 2016). A 

codebook was developed in Microsoft Excel that 

included a priori and emergent codes. The team 

held debriefing meetings to review and discuss the 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e4                                              Cancer Health Disparities 

RESEARCH 

emerging themes and adjust the codebook. 

Illustrative quotes considered the relevance to the 

research questions were also identified. Qualitative 

data were further analyzed using Crisp Set 

Qualitative Comparative Analysis (QCA) to 

understand if certain combinations of coded 

factors/conditions are part of the outcome set 

“work after treatment completion” (work =1, non-

work =0). Crisp set QCA is an analytic induction 

method, used to build up causal explanations of 

phenomena by analyzing a small number of cases 

(Bernard & Ryan, 2009). The QCA method was 

formalized by Ragin (Ragin, 1987) using a Boolean 

algebra approach to identify contribution of the 

presence or absence of certain factors to an 

outcome of interest. A Crisp set, or Conventional 

set, is dichotomous and can be compared to a 

binary variable with value 1 when the factor is 

present and 0 when it is absent (e.g., if a condition 

represented by a code is present or absent). Using 

the software fs/QCA1, the following factors were 

tested in the analysis to identify which ones/ which 

combinations contribute to work status after 

having received primary treatment for cancer: 

medical leave eligibility (participants’ perception 

of), availability of medical insurance through the 

employer (insurance status), work status while 

receiving primary treatment for cancer, work status 

after having received primary treatment, and type 

of occupation. The QCA applies the rules of logical 

inference to identify which combinations among all 

the possible combinations of variables found in the 

data contribute to the outcome of interest. 

Results 

The following paragraphs detail our findings. First, 

we present participant demographics followed by 

                                                           
1
 Ragin, C., and Davey, S. 2014. fs/QCA [Computer Programme], 

Version [2.5/3.0]. Irvine, CA: University of California. 

the description of work related patterns and 

outcomes by occupation for cancer survivors that 

were working before diagnosis (n=57). This is 

followed by participants’ work-related concerns 

and QCA results. 

Participant demographics 

The researchers were able to successfully recruit 75 

minority women, in a short period of time (two 

days). Of the 75 women cancer survivors for which 

data were collected, 57 reported they were working 

shortly before being diagnosed with cancer. The 

findings reported in the following paragraphs 

consider the results on work during and after 

treatment completion, current work status, and 

work-related challenges for the participants who 

stated that they were working shortly before being 

diagnosed with cancer (n=57). 

This is a predominantly minority sample, with 

Hispanic participants making up the largest group, 

followed by Black or African American survivors. 

Thirty-seven percent (n=21) of participants’ 

occupation were classified as management or 

professional, while 63% (n=36) of participants’ jobs 

were classified as non-managerial/ non-

professional and primarily worked in the service, 

sales, office support or production. Overall 

participants were moderately to highly educated, 

with the majority of participants having attended 

college. Eighty percent of participants in 

management or professional occupations had at 

least a college degree, compared to 26% of the 

participants who are in service, office support, or 

production occupations. Median income was 

between $24,000 and $47,999. Over 30% reported 

having had some financial difficulties in the recent 

past. Median income for participants in 

management or professional occupations was the 

same as participants in service, office support or 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e5                                              Cancer Health Disparities 

RESEARCH 

production occupations. Seventy-one percent of 

the participants’ report having a household 

income of less than $47,000 per year, even though 

a large proportion (68%) have attended college. 

Ninety-six percent of participants believed that 

having programs that support working women 

diagnosed with cancer would be beneficial. 

 

Table 1. Socio-demographic, economic and health indicators among women employed before cancer 

diagnosis (n=57). 

  Managerial Service/Sales/ 

Production 

Total n 

  n=21 (%) n=36 (%) 57 

Age at interview 18-39 1 (5) 2 (8) 3 

40-54 9 (43) 14 (39) 24 

55-64 6 (29) 11 (31) 16 

65 or older 

 

5 (24) 8 

 

(22) 

 

13 

 

Missing   1 (0) 1 

Education Less than High School Diploma 0 (0) 5 (14) 5 

High School Diploma or GED 0 (0) 11 (31) 11 

Some College, No Degree 4 (20) 10 (29) 14 

Associate/Junior College Degree 0 (0) 6 (17) 6 

Bachelor’s Degree 9 (45) 3 (9) 12 

Graduate or Professional Degree 

 

7 

 

(35) 

 

0 

 

(0) 

 

7 

 

Missing 1 (0) 1 (0) 2 

Ethnicity* 

Race 

Hispanic 8 (43) 25 (74) 33 

White - non Latino 1 (0) 1 (0) 2 

Black or African American 

 

12 

 

(57) 9 

 

(26) 

 

21 

 

Missing   1 (0) 1 

Household income Less than $24,000 4 (19) 17 (49) 21 

$24,000-$47,000 8 (38) 11 (31) 19 

$48-$71,999 4 (19) 2 (6) 6 

$72,000 or more 4 (19) 3 (9) 7 

Unsure 

 

1 

 

(5) 2 

 

(6) 

 

3 

 

Missing   1 (0) 1 

Adequate financial resources 

in the last 30 days 

Yes 17 (70) 21 (60) 38 

Self-reported Health Very good 5 (24) 10 (29) 15 

Good 6 (29) 14 (40) 20 

Moderate 9 43) 10 (29) 19 

Bad 1 (5) 1 

 

(3) 

 

2 

 

Missing   1 (0) 1 

Cancer  Breast 17 (81) 30 (83) 47 

Other 4 (19) 6 (17) 10 

Diagnosed  > 10 years ago 4 (19) 13 (36) 17 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e6                                              Cancer Health Disparities 

RESEARCH 

6- 10 years ago 7 (33) 10 (28) 17 

≤ 5 years ago 10 (48) 13 (36) 23 

Cancer treatment** Surgery  19 (90) 28 (78) 45 

Chemotherapy 17 (81) 27 (75) 44 

Radiation 16 (76) 17 (47) 33 

Support programs for 

women cancer survivors  

Programs to support women 

would be beneficial 

21 (100) 34 (97) 55 

*Participants can be of any race; therefore, percentages do not add up to 100% 
**Participants may have had more than treatment; therefore, percentages do not add up to 100% 

Work patterns, environment and factors affecting 

work outcomes 

Of the 57 participants who were employed before 

diagnosis, twenty-one participants (37%) were 

employed in management or professional 

occupations. Of these 21 participants, two (10%) 

reported losing their job at diagnosis; 12 (57%) 

continued to work during treatment, including 10 

(83% of the 12) at the same job; and seven (33%) 

stopped working during treatment. One person 

who stopped working while receiving treatment 

was older than 55 years at the time. Two of the 

seven participants (29%) who had to stop working 

during treatment were able to return to work 

following treatment completion with their previous 

employer. Five of the seven (71%) who had 

stopped working during treatment did not work 

post-treatment completion. See Table 2. Of the 36 

women employed in service, office support or 

production occupations, twenty-three (64%) 

reported keeping their job at diagnosis, while 13 

(36%) lost their job as a result. During treatment 12 

out of 23 (52%) kept working, all 12 at the same 

job as before diagnosis, while 11 out of 23 (48%) 

stopped working during treatment. Ten of these 11 

(91%) returned to work after treatment was 

completed, 8 at the same job as before and two in 

a different job. 

Job loss rates are higher for women who worked 

in service, office support, or production 

occupations than for women who worked in 

management and professional occupations (36% 

and 10% respectively). However, return rates were 

higher among women who had held service, office 

support, and production occupations compared to 

women who had held management or 

professional occupations (91% and 29% 

respectively). In the long run, employment rates 

were higher for women in management and 

professional occupations, compared to the 

remaining participants (52% and 39% respectively). 

Both groups of respondents reported similar rates 

of disability or difficulties in performing work tasks. 

Table 2. Comparison of work outcomes by occupation type. 

 

Management/  

Professional 

Service, Office Support, 

Production 

Working at time of diagnosis n=21 (%) n=36 (%) 

Eligible to take medical leave at diagnosis 17 (81) 24 (67) 

Health insurance through employer at time of diagnosis 18 (86) 23 (64) 

Loss job after diagnosis 2 (10) 13 (36) 

Working at treatment start n=19 (%) n=23 (%) 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e7                                              Cancer Health Disparities 

RESEARCH 

Continued to work during treatment 12 (63) 12 (52) 

Stopped working during treatment n=7 (%) n=11 (%) 

Returned to work post treatment 2 (29) 10 (91) 

 

Work related concerns 

Analysis of the qualitative open-ended questions 

of the questionnaire shows that most frequently 

reported work-related concerns experienced after 

receiving the news of diagnosis were related to 

productivity losses at work due to treatment side 

effects or pain attributable to the disease (20/57), 

followed by disease management issues (12/57), 

fear of job loss (9/57) and economic concerns 

(8/57) (see Table 3). Twelve participants explicitly 

reported not being concerned about their 

employment. 

Table 3. Illustrative example of concerns reported by survivors employed prior to diagnosis. 

Emergent themes Theme/concern Illustrative quotes 

Work productivity loss 

 

Fatigue and other 

treatment side effects 

“I would not be able to continue to work in the same 

capacity due to fatigue and effects of treatment” (participant 

E52) 

“I was worrying about having the strength to work” 

(participant S19) 

Pain “holding babies, not sure if I could hold” (participant E27) 

Fear of job loss 

 

Resulting from 

absence from work 

“not be able to continue to work during treatment. Is my 

attendance record going to affect my future at my place of 

employment” (participant S38) 

Resulting from poor 

productivity 

“not able to do my job for pain and tiredness” (participant 

E31) 

“will they fire me for so many missing days” (participant S77) 

Concern on how to manage 

disease and work duties  

Concern regarding 

benefits (sick days etc.) 

“would I have enough sick leave in case the treatment was 

extensive” (participant S18) 

Due to lack of flexibility 

of the employer 

“My manager gave me a hard time about time off for 

treatment” (participant E5) 

“stress of the job – boss that was a bully” (participant E4) 

General economic concern  Ability to pay medical 

bills, sustain the family 

economically 

“How was I going to cover medical bills and additional cost 

related to cancer treatment” (participant S73) 

No work-related concerns  Focus on health  “I was not so worried about the job because I was more 

worried about the diagnosis which was devastating at the 

time” (participant S15) 

“my only worry was completing the recovery process” 

(participant S11) 

 

QCA results 

The QCA pathway that appeared to best explain 

the outcome of working after treatment 

completion included the following components: 

working during treatment, having employer-based 

health insurance and being eligible for medical 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e8                                              Cancer Health Disparities 

RESEARCH 

leave (perception of). Type of occupation 

(management or professional versus service, office 

support, or production) does not appear to 

influence the outcome of work after treatment 

completion. Considering the intermediate pathway 

resulting from the QCA, the solution terms 

involving presence of working during treatment, 

health insurance and medical leave eligibility 

explain 49% of participant work status following 

treatment completion. Consistency for all the 

pathways were above 0.85, the typically accepted 

threshold (Thygeson et al., 2012). 

Table 4. QCA results: configuration leading to work after treatment outcome. 

 Consistency Raw coverage Unique coverage  

Being eligible for medical leave at diagnosis AND being insured 

through work at diagnosis AND working during treatment 
0.947368 0.486486 0.486486 

 

Discussion 

The purpose of this exploratory study is to explore 

the factors that influence employment status 

among minority women cancer survivors following 

diagnosis and treatment. Our findings delineate 

how work environment, type of occupation and 

job-related concerns contribute to shape the work 

experience of women cancer survivors. Work-

related concerns appear to be similar across 

different occupation types. Initial examination of 

the data suggests that cancer survivors in service, 

office support, and production occupations are 

more likely than survivors working management 

and professional occupations to lose their jobs 

following diagnosis. Furthermore, the QCA analysis 

suggests that working after treatment completion 

was not explained by type of occupation per se, 

but rather by a combination of working during 

treatment, having health insurance and being 

eligible for medical leave. These findings, in 

conjunction with other research, suggest that 

work-based resources are associated with post-

treatment employment. Blinder and colleagues 

(Blinder, Eberle, Patil, Gany, & Bradley, 2017) for 

example, report that when adjusted for ethnicity, 

breast cancer survivors who held non-

management or professional jobs have decreased 

odds of having a job, either at which they are 

currently working or from which they are on leave, 

four months following treatment completion, than 

management and professional workers. They also 

note that survivors who have employer-sponsored 

health insurance, or whose workplaces have at 

least 50 employees have increased odds of having 

a job four months after treatment completion 

(Blinder, Eberle, Patil, Gany, & Bradley, 2017). This 

suggests that type of occupation may be 

associated both with access to job retention and 

access to health insurance. 

Among private sector employees, large 

establishment size is associated with the increased 

likelihood that employees will be offered health 

insurance and medical leave. Due to historical 

circumstances, health insurance is a benefit 

provided by many employers in the U.S. 

(Blumenthal, 2006). Employees who work in the 

public sector have access to employer-provided 

health insurance. For example, among full-time 

state, and local public sector employees, 99% have 

access to health insurance (Bureau of Labor 

Statistics, 2016). Within the private sector, access to 

employer-based coverage varies by size of 

establishment. In 2012, for example, 57% and 94% 

of establishments in the private sector with fewer 

than 50 workers and at least 500 workers, 

respectively, offered health benefits to at least 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e9                                              Cancer Health Disparities 

RESEARCH 

some employees (Wiatrowski, 2013). The Employer 

Shared Responsibility Provision of the Affordable 

Care Act (ACA), implemented in 2015, penalizes 

employers with more than 50 full-time employees 

who decline to offer coverage that meets 

minimum value and affordability standards (Kaiser 

Family Foundation, 2015). The ACA does not, 

however, require employers to provide health 

insurance. Many of our participants underwent 

cancer diagnosis and treatment prior to 

implementation of the ACA. 

Access to employer-provided health care is spread 

unevenly across occupations. Substantially more 

private sector management and professional 

workers have access to employer-based health 

insurance than those in other major occupational 

categories. Sixty percent of private sector workers 

in management and professional occupations 

have access to employer-based healthcare. In 

comparison, only 22% of private sectors workers in 

service occupations, and 38% workers in sales and 

office and administrative support occupations, 

have access to employer-based healthcare 

(Bureau of Labor Statistics, 2016). Cancer patients 

who obtain their health insurance through their 

employer may be particularly motivated to retain 

their jobs to maintain relatively affordable health 

insurance (Nekhlyudov et al., 2016). As Bradley and 

colleagues noted, women who depend on 

employer-based insurance are less likely to reduce 

their labor after a cancer diagnosis (Bradley, 

Neumark, & Barkowski, 2013). Being eligible for 

medical leave is also associated with employer 

size. The Family and Medical Leave Act (FMLA) (29 

U.S.C. 2601 et seq.) applies to private 

establishments with more than 50 employees 

within a 75-mile radius as well as public agencies. 

Covered employers are required to provide up to 

12 weeks of unpaid leave a year to eligible 

employees for qualified medical reasons and to 

maintain health insurance coverage. Eligible 

employees are those whose job tenure is at least 

12 months or who worked at least 1,250 hours 

during the previous year (Hewitt, Greenfield, & 

Stovall, 2005; US Department of Labor). Survivors 

whose employers provide 12 weeks of medical 

leave may experience substantial challenges given 

that cancer treatment and its side- and late-effects 

frequently extend beyond this period. Cancer 

survivors would also benefit from paid leave. 

Again, size of employer matters. Workers 

employed by small employers are less likely than 

those working for larger employers to have access 

to paid sick leave (Hill, 2013). Access to paid leave 

would increase the incentive for cancer patients to 

retain their jobs during treatment. 

Work concerns were similar across participants in 

management and professional occupations, and 

participants in service, office support or production 

occupations, with reduced work productivity and 

management of the disease being the two main 

areas of concern. These concerns and issues are 

well documented among cancer survivors 

(Nekhlyudov et al., 2016; Sandberg, Strom, & 

Arcury, 2014). Our findings are consistent with 

Nekhlyudov’s (Nekhlyudov et al., 2016) who 

suggests cancer survivors felt that cancer 

interfered with physical or mental tasks or 

productivity at work. 

The QCA analysis shows that ability to keep 

working while receiving primary treatment is one 

important factor in explaining whether cancer 

survivors were working after treatment completion. 

Studies have indicated that being able to maintain 

employment while receiving treatment is affected 

by workplace environment, such as the ability of 

employers to accommodate survivors’ needs: such 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e10                                              Cancer Health Disparities 

RESEARCH 

accommodations have been shown to substantially 

increase job retention (Bouknight, Bradley, & Luo, 

2006; Moskowitz, Todd, Chen, & Feuerstein, 2014; 

Torp, Nielsen, Gudbergsson, & Dahl, 2012). It is 

therefore not surprising that ninety-six percent 

(n=55) of participants who were working at the 

time of diagnosis highlighted the need for 

programs to assist working women diagnosed with 

cancer. Encouraging programs that support 

survivors to continue to work during treatment 

could be important to improve work outcomes for 

women in this population. 

While studies have shown that recruitment of 

minorities can be challenging (Ejiogu et al., 2011; 

Ford et al., 2008; Tosti, 2015), we were able to 

successfully recruit minority cancer survivors in a 

relatively short time. Selecting research questions 

that directly affect the community under study can 

be key to recruiting and retaining minority 

participants (Ejiogu et al., 2011; Fouad et al., 2000), 

To this end, collaboration with community partners 

who are informed of issues that are relevant to a 

specific minority population, as done in this study, 

can be an effective strategy for successful inclusion 

of these groups. The study team’s flexibility with 

respect to location and time during which the 

interviews were conducted (over the weekend at 

survivorship events) was also conducive to 

recruitment of participants who work hourly jobs 

and with little freedom to change their work 

schedule to be interviewed. 

The specific focus on minority women adds to a 

literature in which European American women are 

typically disproportionally represented (Bouknight, 

Bradley, & Luo, 2006; Bradley, Neumark, Luo, & 

Schenk, 2007; Bradley & Wilk, 2014; Mujahid et al., 

2011; Mujahid et al., 2010). Inclusion of minority 

segments of the population was made possible 

due to a recruitment strategy that involved 

community-based organizations, which proved to 

be successful. While we recognize the challenges 

of purposive sampling (Hennink, 2011), this 

strategy is commonly used in exploratory studies 

such as the present one (Bernard & Ryan, 2009). 

While it certainly deems caution with respect to 

the generalizability of study results, the 

heterogeneous nature of the sample in terms of 

occupational categories allowed us to explore a 

broad range of occupational experiences that 

could inform future studies. 

Certain limitations should be taken into account 

when considering the study’s results. While the 

majority of participants are minorities, the sample 

was too small to conduct more sophisticated 

statistical analysis. Severity and stage of disease 

progression are not captured in the data, even 

though disease burden is found to be relevant in 

explaining employment outcomes (Tevaarwerk et 

al., 2016), nor are physical and mental job 

demands included in the analysis. Our analysis has 

some limitations as an fs/QCA. The pathways 

resulting from QCA analysis only partially explain 

work outcomes. Further research with a larger 

sample is needed to uncover additional factors not 

captured in this preliminary study. While Crisp set 

calibration was appropriate for the focus of this 

analysis, it required a certain degree of 

simplification with respect to participants’ 

experiences: for instance, we record if the 

participant had health insurance (yes/no) but we 

do no measure to what extent health insurance 

covered their medical needs during cancer 

treatment. Moreover, the data collected did not 

allow us to stratify and compare participants based 

on the type (e.g. private/public, part-time/full-

time) and size of the employer, which affects 

access to benefits and therefore can influence 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e11                                              Cancer Health Disparities 

RESEARCH 

employment status during and after treatment. 

Our data did not distinguish between participants 

who stopped working during treatment while 

continuing to hold their job (e.g., being on a 

medical leave) from those who lost their job 

during treatment. Additionally, our data did not 

capture whether the participant willingly stopped 

working or was fired as a result of circumstances 

related to the cancer diagnosis. 

This preliminary work fills a knowledge gap about 

survivorship experiences of women in underserved 

populations (Tisnado et al., 2017), by exploring 

employment pathways after cancer treatment in a 

predominantly minority sample that includes 

survivors who held different types of jobs. Work 

outcomes after cancer and associated risk factors 

are not fully understood (Tevaarwerk et al., 2016). 

Yet, the employment aspect of cancer survivorship 

is salient as work outcomes have substantial 

implications for cancer survivor’s short and long-

term economic, physical and psychosocial well-

being (Hewitt, Greenfield, & Stovall, 2005; 

Nowrouzi, Lightfoot, Cote, & Watson, 2009). 

Future research could explore the role of federal, 

state, and employer policies and procedures and 

driving organizational characteristics, such as 

employer size and being a public or private sector 

employer, in cancer survivors’ employment 

outcomes. These issues should be explored in light 

of the increase in the number of jobs that do not 

provide stable, full time employment, with good 

wages and benefits (Kalleberg, 2011), the impact of 

the Affordable Care Act on cancer survivors’ 

coverage (Davidoff, 2015), potential consequences 

of the repeal of the law (Goldstein, 2017), and 

resources potentially available to cancer survivors 

under the Americans with Disability Act, which 

covers employers with fewer than 15 employees 

(US Equal Employment Opportunity Commission). 

This study provides relevant insights on the work 

experience and concerns of minority women 

cancer survivors, a population segment that has 

been frequently underrepresented in the literature 

on survivors’ work outcomes after cancer 

diagnosis and treatment. Our findings highlight 

the need for the development of programs that 

assist minority cancer survivors during their work-

related transitions and the importance of tailoring 

such interventions to different work environments. 

Future studies should integrate survivors’ 

perspectives with employers’ views on the impact 

of cancer on work (Grunfeld, Low, & Cooper, 

2010), which would be crucial for the development 

of effective programs to assist working women 

cancer survivors. We also need to examine in 

detail how work experiences following a cancer 

diagnosis may vary by race and ethnicity as well as 

how culture (beliefs, norms and values) and 

discrimination may influence women’s work-

related decisions and work outcomes after cancer 

diagnosis and treatment. 

Acknowledgements 

The authors would like to thank the study 

participants whose involvement made this study 

possible. We would also like to acknowledge the 

ongoing support from LUNA Inc., Hispanic Health 

Initiatives, Creando Conciencia por Reina, Faces of 

Courage, Dr. Cathy Meade, the Florida Prevention 

Research Center and the Tampa Bay Community 

Cancer Network. We would also like to thank Linda 

Bomboka for her editorial assistanceConflict of 

interest 
The authors declare that they have no conflict of 

interest 

Authors’ contributions 
Each author contributed substantially to the final 

manuscript. All authors contributed to the design of 

the study. DMT, AWF, and PS collected the data. 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e12                                              Cancer Health Disparities 

RESEARCH 

DMT, SS and JCS worked on data analysis. DMT, SS 

and JCS wrote the draft paper. All authors 

contributed to outlining the main study implications.  

. 

REFERENCES 
Amir, Z., Neary, D., and Luke, K. (2008). Cancer survivors' 

views of work 3 years post diagnosis: A UK perspective. 

Eur. J. Oncol. Nurs. 12(3), 190-197. 

Bernard, H. R., and Ryan, G. W. (2009). Analyzing Qualitative 

Data: Systematic Approaches. (Thousand Oaks: SAGE). 

Bernard, H. R., Wutich, A., and Ryan, G. W. (2016). Analyzing 

qualitative data: Systematic approaches. (Thousand Oaks: 

SAGE). 

Blinder, V., Eberle, C., Patil, S., Gany, F. M., and Bradley, C. J. 

(2017). Women With Breast Cancer Who Work For 

Accommodating Employers More Likely To Retain Jobs 

After Treatment. Health Aff. 36(2), 274-281. 

Blinder, V. S., Patil, S., Thind, A., Diamant, A., Hudis, C. A., 

Basch, E., and Maly, R. C. (2012). Return to work in low-

income Latina and non-Latina white breast cancer 

survivors: a 3-year longitudinal study. Cancer 118(6), 

1664-1674. 

Blumenthal, D. (2006). Employer-sponsored health insurance 

in the United States-origins and implications. N. Engl. J. 

Med. 355(1), 82. 

Bouknight, R. R., Bradley, C.J., and Luo, Z. (2006). Correlates of 

Return to Work for Breast Cancer Survivors. J. Clin. 

Oncol. 24(3), 345-353. 

Bradley, C. J., Neumark, D., and Barkowski, S. (2013). Does 

employer-provided health insurance constrain labor 

supply adjustments to health shocks? New evidence on 

women diagnosed with breast cancer. J. Health. Econ. 

32(5), 833-849. 

Bradley, C. J., Neumark, D., Luo, A., and Schenk, M. (2007). 

Employment and cancer: findings from a longitudinal 

study of breast and prostate cancer survivors. Cancer 

Invest. 25(1), 47-54. 

Bradley, C. J., and Wilk, A. (2014). Racial differences in quality 

of life and employment outcomes in insured women with 

breast cancer. J. Cancer Surviv. 8(1), 49-59. 

Bureau of Labor Statistics. (2010). Standard Occupational 

Classification. 2010 SOC Major Groups. Available at: 

https://www.bls.gov/soc/major_groups.htm. Accessed on 

January 24, 2019. 

Bureau of Labor Statistics. (2016). Table 9. Healthcare benefits: 

Access, participation, and take-up rates, State and local 

government workers. Available at: https://www.bls.gov 

/ncs/ebs/benefits/2016/ownership/govt/table09a.pdf. 

Accessed on January 24, 2019. 

Clarke, T. C., Christ, S.L., Soler-Vila, H., Lee, D.J., Arheart, K.L., 

Prado, G., and Fleming, L.E. (2015). Working with cancer: 

Health and employment among cancer survivors. Ann. 

Epidemiol. 25(11), 832-828. 

Davidoff, A. J., Hill, S.C., Bernard, D., and Yabroff, K.R. (2015). 

The Affordable Care Act and Expanded Insurance 

Eligibility Among Nonelderly Adult Cancer Survivors. J. 

Natl. Cancer Inst. 107(9), 1. 

Ejiogu, N., Norbeck, J.H. Mason, M.A., Cromwell, B.C. 

Zonderman, A.B., and Evans, M.K. (2011). Recruitment 

and Retention Strategies for Minority or Poor Clinical 

Research Participants: Lessons From the Healthy Aging in 

Neighborhoods of Diversity Across the Life Span Study. 

Gerontologist 51(Suppl 1), S33-S45. 

Ford, J. G., Howerton, M. W., Lai, G. Y., Gary, T. L., Bolen, S., 

Gibbons, M. C., Tilburt, J., Baffi, C., Tanpitukpongse, T. P., 

Wilson, R. F., Powe, N. R. and Bass, E. B. (2008). Barriers 

to recruiting underrepresented populations to cancer 

clinical trials: A systematic review. Cancer 112, 228-242. 

Fouad, M. N., Partridge, E., Green, B.L. . Kohler, C. Wynn, T., 

Nagy, S., and Churchill, S. (2000). Minority Recruitment In 

Clinical Trials: A Conference at Tuskegee, Researchers 

and the Community. Ann. Epidemiol. 10(8 Suppl 1), S35-

40. 

Goldstein, A. (2017). Cancer survivor who once opposed 

federal health law challenges Ryan on its repeal. The 

Washington Post, 14 January 2017. 

Grunfeld, E. A., Low, E., and Cooper, A.F. (2010). Cancer 

survivors' and employers' perceptions of working 

following cancer treatment. Occup. Med. 60(8), 611-617. 

Hennink, M., Hutter, I., and Bailey, A. (2011). Qualitative 

research methods. (Thousand Oaks: SAGE). 

Hewitt, M. E., Greenfield, S., and Stovall, E. (2005). From 

Cancer Patient to Cancer Survivor: Lost in Transition. 

(Washington, DC: National Academies Press). 

Hill, H. D. (2013). Paid Sick Leave and Job Stability. Work 

Occup. 40(2), 143-173. 

Hoffman, B. (2005). Cancer Survivors at Work: A Generation of 

Progress. C.A. Cancer J. Clin. 55(5), 271-280. 

Islam, T., Dahlui, M., Majid, H.A., Nahar, A.M., Taib, N.A.M., 

and Su, T.T. (2014). Factors associated with return to work 

of breast cancer survivors: a systematic review. BMC 

Public Health 14(suppl 3), s8. 

Jagsi, R., Pottow, J. A. E., Griffith, K. A., Bradley, C., Hamilton, 

A. S., Graff, J., and Hawley, S. T. (2014). Long-term 

financial burden of breast cancer: experiences of a 

diverse cohort of survivors identified through population-

based registries. J. Clin. Oncol. 32(12), 1269-1276. 

Kaiser Family Foundation. (2015). Percent of Private Sector 

Establishments That Offer Health Insurance to 

Employees, by Firm Size. (Kaiser Family Foundation). 



 
 
 
 
 

 

www.companyofscientists.com/index.php/chd                   e13                                              Cancer Health Disparities 

RESEARCH 

Kalleberg, A. L. (2011). Good jobs, bad jobs: the rise of 

polarized and precarious employment systems in the 

United States, 1970s-2000s (Russell Sage Foundation). 

Kennedy, F., Haslam, C., Munir, F., and Pryce, J. (2007). 

Returning to work following cancer: a qualitative 

exploratory study into the experience of returning to 

work following cancer. Eur. J. Cancer Care 16(1), 17-25. 

Legewie, N. (2013). An introduction to applied data analysis 

with qualitative comparative analysis. Qual. Soc. Res. 

14(3). 

Main, D. S., Nowels, C. T., Cavender, T.A., Etschmaier, M., and 

Steiner, J.F. (2005). A qualitative study of work and work 

return in cancer survivors. Psychooncology 14(11), 992-

1004. 

Mehnert, A. (2011). Employment and work-related issues in 

cancer survivors. Crit. Rev. Oncol. Hematol. 77(2), 109-

130. 

Mehnert, A., de Boer, A., and Feuerstein M. (2013). 

Employment challenges for cancer survivors. Cancer 

119(S11), 2151-2159. 

Moskowitz, M. C., Todd, B.L., Chen, R., and Feuerstein, M. 

(2014). Function and friction at work: a multidimensional 

analysis of work outcomes in cancer survivors. J. Cancer 

Surviv. 8(2), 173-182. 

Mujahid, M. S., Janz, N. K., Hawley, S. T., Griggs, J. J., 

Hamilton, A. S., Graff, J., and Katz, S. J. (2011). 

Racial/ethnic differences in job loss for women with 

breast cancer. J. Cancer Surviv. 5(1), 102-111. 

Mujahid, M. S., Janz, N., Hawley, S., Griggs, J., Hamilton, A., 

and Katz, S. (2010). The impact of sociodemographic, 

treatment, and work support on missed work after breast 

cancer diagnosis. Breast Cancer Res. Treat. 119(1), 213-

220. 

Nachreiner, N. M., Dagher, R.K., Mcgovern, P.M., Baker, B.A., 

Alexander, B.H., and Gerberich S.G. (2007). Successful 

return to work for cancer survivors. AAOHN J. 55(7), 290-

295. 

Nekhlyudov, L., Walker, R., Ziebell, R., Rabin, B., Nutt, S., and 

Chubak, J. (2016). Cancer survivors’ experiences with 

insurance, finances, and employment: results from a 

multisite study. J Cancer Surviv. 10(6), 1104-1111. 

Nowrouzi, B., Lightfoot, N., Cote, K., and Watson, R. (2009). 

Workplace support for employees with cancer. Curr 

Oncol. 16(5), 15-22. 

Pryce, J., Munir, F., and Haslam, C. (2007). Cancer survivorship 

and work: Symptoms, supervisor response, co-worker 

disclosure and work adjustment. J. Occup. Rehabil. 17(1), 

83-92. 

Ragin, C. (1987). The comparative method: moving beyond 

qualitative and quantitative strategies. (Berkeley: 

University of California Press). 

Sandberg, J. C., Strom, C., and Arcury, T. A. (2014). Strategies 

Used by Breast Cancer Survivors to Address Work-

Related Limitations During and After Treatment. Womens 

Health Issues 24(2), e197-e204. 

Schneider, C. Q., and Wagemann, C. (2003). Improving 

Inference with a Two-step Approach: Theory and Limited 

Diversity in fs/QCA (European University Institute). 

Spelten, E. R., Sprangers, M. A. G., and Verbeek, J. (2002). 

Factors reported to influence the return to work of 

cancer survivors: A literature review. Psychooncology 

11(2), 124-131. 

Subramanian, S. V., Huijts, T., and Avendano, M. (2010). Self-

reported health assessments in the 2002 World Health 

Survey: how do they correlate with education? Bulletin of 

the World Health Organization 88(2), 131-138. 

Tevaarwerk, A. J., Lee, J.W, Terhaar, A., Sesto, M.E., Smith, 

M.L., Cleeland, C.S., and Fisch, M.J. (2016). Working after 

a metastatic cancer diagnosis: Factors affecting 

employment in the metastatic setting from ECOG-

ACRIN's Symptom Outcomes and Practice Patterns 

study. Cancer 122(3), 438-446. 

Thygeson, N. M., Solberg, L.I., Asche, S.E., Fontaine, P., 

Pawlson, L.G, and Hudson Scholle, S. (2012). Using Fuzzy 

Set Qualitative Comparative Analysis (fs/QCA) to Explore 

the Relationship between Medical “Homeness” and 

Quality. Health Serv. Res. 47(1), 22-45. 

Tisnado, D. M., Mendez-Luck, C., Metz, J., Peirce, K., and 

Montaño, B. (2017). Perceptions of Survivorship Care 

among Latina Women with Breast Cancer in Los Angeles 

County. Public Health Nurs. 34, 118-129. 

Torp, S., Nielsen, R., Gudbergsson, S., and Dahl, A. (2012). 

Worksite adjustments and work ability among employed 

cancer survivors. Support Care Cancer, 20, 2149-2156. 

Tosti, B. (2015). Improving Minority Recruitment in Clinical 

Trials. Appl Clin Trials. 

US Department of Labor. Wage and Hour Division. The Family 

and Medical Leave Act. Available at: https://www.dol 

.gov/whd/regs/compliance/1421.htm#1a. Accessed on 

January 24, 2019. 

US Equal Employment Opportunity Commission. Facts About 

the American with Disabilities Act. Available at: 

https://www.eeoc/gov/eeoc/publications/fs-ada.cfm. 

Accessed on January 24, 2019. 

Wiatrowski, W. J. (2013). Employment-based health benefits in 

small and large private establishments. Beyond the 

Numbers: Pay & Benefits, U.S. Bureau of Labor Statistics, 

2(8). 

 

 

 


