Copyright B 2015 Wolters Kluwer Health, Inc. All rights reserved.
Kimberly M. Kelly, PhD Rituparna Bhattacharya, MS Stephanie Dickinson, MAS Hannah Hazard, MD
Health Behaviors Among Breast Cancer Patients and Survivors K E Y
W O R D S
Background: With improved treatments, the survival rate for breast cancer
Breast cancer
patients is increasing. With the improvements in quantity of life, research in the field
Cancer screening
of cancer survivorship has turned its attention to psychosocial functioning and health
Diet
behaviors. Objectives: The purpose of this study was to examine how those
Health behaviors
currently under treatment and those completing treatment engaged in health
Physical activity
behaviors (ie, diet, vitamin use, exercise, and cancer screening) and if psychosocial
Vitamin use
predictors, guided by the Self-regulation Model, also play a role. Methods: Using the Self-regulation Model, the current survey and medical record review examined health behaviors (diet, vitamin use, exercise, cancer screening) in individuals in active treatment for breast cancer and in those completing treatment (n = 141). Results: Regression models revealed that those in active treatment had less healthy food consumption, vitamin use, and clinical examinations than did treatment completers. Greater perceived treatment efficacy was associated with diet and vitamin use but not exercise or cancer screening. Greater perceived risk of recurrence was associated with less exercise. Greater distress was associated with greater mammography use. Those from metro areas had greater healthy food consumption. Results: Qualitative data indicated that chemotherapy interfered with health behaviors for those in active treatment; treatment completers wished to have a healthier lifestyle. Conclusion: Cancer treatment interferes with health behaviors, and these health behaviors might help individuals manage their cancer treatment more effectively. Implications for Practice: Those currently undergoing treatment desire assistance with a healthier lifestyle, and relevant clinical interventions should stress treatment efficacy.
Author Affiliations: School of Pharmacy and Mary Babb Randolph Cancer Center, West Virginia University, Morgantown (Dr Kelly and Ms Bhattacharya); Department of Statistics, Indiana University, Bloomington (Ms Dickinson); Department of Surgery, West Virginia University, Morgantown (Dr Hazard). Funding was provided by the Ohio Division of the American Cancer Society. The authors have no conflicts of interest to disclose.
Health Behaviors Among Cancer Survivors
Correspondence: Kimberly M. Kelly, PhD, West Virginia University School of Pharmacy and Mary Babb Randolph Cancer Center, Robert C. Byrd Health Sciences Center, PO Box 9510, Morgantown, WV 26506 ([email protected]). Accepted for publication April 23, 2014. DOI: 10.1097/NCC.0000000000000167
Cancer NursingTM, Vol. 38, No. 3, 2015
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W
ith improved treatments, the survival rate for breast cancer patients is increasing. Specifically, the 10-year survival rate is 83%,1 resulting in a large and growing population for nursing care. With improvements in quantity of life, research in the field of cancer survivorship has turned its attention to quality of life and psychosocial functioning. With the physical demands of the disease, concerns about social interactions,2 and the number of decisions that must be made about treatment,3Y5 many have expressed concern about cancer patients’ experience of distress or negative affect, which may include depression, anxiety, worry, panic, and isolation,6,7 and a number of scales have been developed to understand the psychosocial experience of cancer patients8 (including concepts such as pain, fear of death, and intrusive thoughts about cancer recurrence). The treatment phase for breast cancer has been associated with increased fear and worry,9,10 and distress may persist following treatment for cancer, particularly fear of recurrence.11 Despite these difficulties, for many, the posttreatment phase is associated with increased wellbeing and posttraumatic growth, leaving cancer survivors with greater appreciation for life.12,13 The decision-making literature in breast cancer patients has mainly focused on treatment choices.3Y5 Meanwhile, less attention has been paid to the health behaviors (eg, diet, exercise, and vitamin use) of breast cancer patients and survivors. Although decision making for cancer screening has been widely studied,14 only a couple of studies have focused on breast cancer screening after being diagnosed with breast cancer, indicating an increased demand for mammograms in the United States.15 However, this literature is growing and will become increasingly important in the context of the Affordable Care Act in the United States, which already protects those with preexisting conditions and will place greater emphasis on prevention of future disease, such as cancer recurrence.16 Of particular concern, those currently under treatment may have the most challenges to leading a healthy lifestyle to prevent cancer recurrence and may be a group in critical need of assistance. Understanding the factors that play a role in performing health behaviors is critical for the overall wellbeing of the patient, as clinical interventions may improve health outcomes. A number of models explore the relationship of health beliefs to behavior (eg, the Health Belief Model, the Theory of Planned Behavior); however, few include the role of affect in behavior. Leventhal’s Self-regulation Model (SRM) posits that affective and cognitive processes interact to influence the performance of health behaviors and is routed in attitudinal research that links cognition, affect, and behavior.17 Specifically, The SRM includes the self-system, cognitive and affective representations, and health behaviors.18,19 The self-system is the combination of self and social environment factors essential to the perception of the health threat.18 Self-system factors are demographic (eg, age, socioeconomic factors), biological (eg, in active treatment), cultural, regional (eg, rural, Appalachian), and so on. Within the self-system, when presented with a stimulus (eg, breast cancer), an individual forms a cognitive and an affective representation of the health threat. The cognitive representation may include a number of salient features of the disease (eg, what the disease is, how effective a given health behavior is). In a pre-
vious study of health behaviors in individuals undergoing genetic counseling for hereditary cancer, beliefs about treatment efficacy were found to be key predictors of health behaviors,20 and this differs from many health behavior models, which include selfefficacy as a predictor (eg, Social Cognitive Theory). In contrast to the cognitive representation, the affective representation includes feelings about the health threat, with research focused on distress/ negative affect.21,22 Distress has been shown to be a potent predictor of cancer screening in individuals without a personal history of cancer.23 In addition, perceived risk, which is largely considered a cognitive factor in determining if one’s self is at risk, is strongly affectively influenced21,22 and is an important consideration in health behavior.21 Cognitive and affective representations drive the health behaviors, which an individual uses to manage the health threat. Thus, based on the model, we hypothesized that those who perceived the greatest threat of cancer (ie, perceived risk), who had the highest beliefs in the efficacy of the treatment/health behavior, and who had the greatest worry about the threat of cancer recurrence will be most likely to engage in the health behavior.
Diet Women consuming better-quality diets have reduced breast cancer mortality.24 Meta-analytic studies and systematic reviews have concluded that increasing vegetable consumption might reduce the risk of breast cancer recurrence.25 Although foods rich in dietary fat have been generally believed to lead to increased risk of breast cancer, the evidence is inconsistent.26 The impact of psychosocial factors such as worry, perceived risk, and perceived treatment efficacy on diet has been understudied in breast cancer patients,27 and of the existing studies, most have focused on newly diagnosed breast cancer patients. One study found greater distress and younger age were associated with greater dietary change in the 12 months after diagnosis.27 However, another study found no association between cancer recurrence worry and risk perception on behaviors such as eating 5 servings of fruit and vegetables per day, finding that beliefs about recurrence were better predictors.28 We identified no studies investigating longer-term survivors in diet quality.
Vitamin Use Few studies have investigated the role of vitamin supplement use in breast cancer patients during treatment and survival. Vitamin use shortly after diagnosis was associated with reduced mortality and recurrence.29 However, Saquib et al,30 in a 9-year prospective study, found that vitamin intake was not associated with allcause mortality. Breast cancer patients have reported increasing vitamin/supplement use after diagnosis, with overall supplement use in long-term survivors being quite high.30 Only 2 studies were identified that examined a psychosocial factor in vitamin use in newly diagnosed breast cancer patients. One study found that megavitamin use was associated with increased psychosocial distress31; another found that it was not, with only beliefs about recurrence being associated with vitamin supplement use.28 Additional study is needed to understand these contrasting findings.
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Physical Activity Results from observational studies, literature reviews, and metaanalytic studies suggest that physical activity after diagnosis helps to improve quality of life and well-being and also reduces mortality.25,32,33 However, despite strong evidence for physical activity in improving breast cancer prognosis, only 32% of breast cancer patients participated in recommended levels of physical activity, and patients were less active in the first year of diagnosis compared with the year prior to diagnosis.34 A study investigating behavior change after cancer diagnosis found that exercise was the least likely behavior to change.35 Depressive symptoms and lower education levels were barriers to physical activity in women throughout breast cancer treatment and survivorship.36 Self-efficacy was associated with increased likelihood of participation in physical activity programs in those currently under treatment.37 Again, our literature review found no studies linking perceived breast cancer recurrence risk with physical activity.
the lead author spent considerable time observing a universityassociated breast oncology clinic in a Midwestern city and conducted interviews with patients and clinical staff (eg, oncology surgeon, nurse practitioner, clinical nurses, and schedulers). Based on information gleaned, a survey was developed, utilizing some previously existing scales and some open-ended items to expand our understanding of current health behaviors in cancer patients. Including both qualitative and quantitative approaches allows for methodological triangulation and complementarity to gain an understanding of a research question both for depth and convergence of results; further development of study design, such as for developing surveys; helping to answer questions or contradictions from 1 approach; and expansion to extend the types of questions that can be asked,43 the latter being most relevant to the current study. Mixed methods also allow for iteration in development of research questions, conduct of the study, and data analysis.43 This approach reflects the applied anthropological nature of clinical research.44,45
Cancer Screening
Participants
Cancer screening for those with a previous history of cancer has been shown to dramatically decrease breast cancer mortality risk,38 although such screening may be underutilized by breast cancer survivors.39 One study reported that while 80% of breast cancer survivors had received a mammogram in the year following treatment; only 63% had a mammogram at the fifth year of follow-up.40 However, other studies reported higher screening rates among breast cancer survivors as compared with those without a history of breast cancer.41 There is a general belief in popular literature that fear and anxiety about recurrence might lead breast cancer survivors to forgo screening.42 We identified no studies investigating the relationship of breast cancer screening and perceived treatment efficacy or perceived risk of breast cancer recurrence in those with a previous breast cancer diagnosis. Thus, the epidemiological literature indicates the types of health behaviors noted above (diet, vitamin use, physical activity, and cancer screening) may be associated with the risk of breast cancer recurrence. However, for the most part, it is unclear how the cancer trajectory may affect the performance of health behaviors, and other key psychosocial factors have been largely neglected for their role in health behaviors among those with a prior history of breast cancer. The objectives of this study were to examine how those currently under treatment and those completing treatment engaged in health behaviors (diet, vitamin use, exercise, and cancer screening) and if SRM factors, including (1) self-system factors: demographics, region; (2) affective factors: distress; and (3) cognitive factors: treatment efficacy, and perceived risk are associated with the performance of these behaviors.
Eligibility requirements included being 18 years or older, having a personal history of breast cancer, and being treated at a universityaffiliated breast oncology clinic. In addition, women were either within 1 year of their diagnosis (active) or 2 to 5 years postdiagnosis (completed).
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Methods
To better understand health behaviors in women with breast cancer, our study had both quantitative and qualitative components. Prior to initiating data collection, an informal ethnographic study was undertaken as part of a qualitative methods course, where
Health Behaviors Among Cancer Survivors
Procedure Recruitment was conducted face-to-face at a university-affiliated breast oncology clinic in a Midwestern state. A Health Insurance Portability and Accountability Act waiver from the institutional review board allowed for a prescreening medical record review of potentially eligible women. Eligible women were approached by a member of the research team (either the first author or a research assistant) at their regularly scheduled clinic visit. For interested individuals, the study was explained, and a consent form was reviewed and signed. Participants were asked to complete a crosssectional survey including questions about breast cancer recurrence and health behaviors. Time to complete the survey was estimated to be 30 minutes. A member of the research team completed a medical chart review for cancer-relevant information. At the completion of the study, women received a $10 gift card.
Measures A medical chart review was completed for each participant, including: treatment status (within 1 year of diagnosis or 2Y5 years from diagnosis), type of cancer, date of diagnosis, stage, grade, ER/PR status, Her-2/neu status, and chemotherapy. In addition, a self-report survey was completed, which included background data (ie, gender, age, education, and incomeVcommon proxy variables for socioeconomic status, race, Appalachian status, rural status, and psychosocial factors). PSYCHOSOCIAL FACTORS
Psychosocial factors included distress, perceived risk, and perceived efficacy of health behaviors. Distress was assessed with the Cancer NursingTM, Vol. 38, No. 3, 2015
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9-item Distress Specific to Breast Cancer Recurrence Scale,10,20 which included 3 items to assess anxiety and 3 to assess depression, focusing on the participant’s feelings about cancer recurrence, as well as worry about disfigurement following breast cancer, fear of dying, and concern about pain on a 5-point Likert-type scale (1 = not at all to 5 = very much). Psychometric properties of this scale have been previously established, with good internal consistency (! = .90; in the current study, ! = .91).10,20 For perceived risk, the survey asked the participant to compare her personal lifetime risk for breast cancer to that of other women: ‘‘Do you think your odds of getting breast cancer again are the same or different than those of other women?’’ Response options included ‘‘higher,’’ ‘‘the same,’’ or ‘‘lower.’’ This item was piloted in a previous study including breast cancer patients.46 Five items assessed the perceived treatment efficacy of health behaviors in relation to cancer. Participants were asked about (1) a healthy diet, (2) vitamins, (3) exercise, being ‘‘effective in preventing or delaying cancer’’ and about (4) mammograms, and (5) clinical breast examinations ‘‘decreasing the risk of cancer recurrence’’ on a 5-point Likert scale (1 = disagree strongly, 5 = agree strongly). This item was utilized in a previous study of breast cancer patients.20 HEALTH BEHAVIORS
For diet, participants were asked to rate how often they consumed certain food items during the past week (high-fiber foods such as grains and legumes, olive, canola, or safflower oil, fish, fruits, cruciferous vegetables, other vegetables), on a 6-point response scale (1 = rarely or never to 6 = 93 times a day). Psychometric properties of this scale have been previously established, with acceptable internal consistencies (! = .73 and .65; in the current study, ! = .79).20 For vitamin use, participants were asked to indicate how often in the past week they took (1) vitamin C, (2) vitamin A, (3) vitamin E, (4) B vitamins, (5) antioxidants, (6) beta carotene, (7) omega fatty acids, and (8) calcium, on a 6-point response scale (1 = rarely or never to 6 = 93 times a day). Psychometric properties of this scale have been previously established, with good internal consistency (! = .90 and .89; in the current study, ! = .82).20 Three items assessed exercise in the past week. The numbers of hours spent doing light and strenuous activities and building and maintaining strength were summed to assess total physical activity. These items were adapted from previous studies of health behaviors (National Health and Nutrition Examination Survey, Rutgers Aging and Health Study) and were the sum of 3 items regarding the total number of hours spent in mild, moderate, and strenuous exercise per week.20 Following each health behavior, women were asked if their performance of a behavior had changed since their diagnosis (yes or no) and, if so, how had the behavior changed (open-ended). In addition, 2 items assessed the self-reported frequency of breast cancer screening. One item reported the frequency of mammograms and the other clinical breast examinations, on a 7-point scale ranging from 1 = never to 7 = every 3 months.
vitamins, exercise, mammogram, and clinical breast exam, as dependent variables) with the following independent variables: treatment status (within 1 year from diagnosis or 2Y5 years postdiagnosis), age, gender, education, income, race, location of residence (Appalachian or not, metro or nonmetro), insurance type, family cancer history, perceived comparative cancer risk, perceived efficacy of the given health behavior, breast cancer type, and cancer distress. Forward stepwise selection was used in linear regression modeling to identify the best set of variables related to each health behavior. After first evaluating univariate models with each predictor separately, each variable was entered into the model one at a time, and backward elimination with an exit criterion of P 9 .10 was used at each step to determine the final model. Treatment status was left in the model even if not significant as a predictor variable of interest. All further tests were performed at significance level ! = .05. Interactions between significant main effects were tested and included if significant. PASS 6.0 power analysis software indicated that each variable entered would result in 91% power to detect an r2 of 0.1 or greater for a sample size of 100, with ! = .05. A model with 4 variables would have 74% power. Thus, our sample is adequate to test for the desired effects.
Analysis of Qualitative Data Immersion/crystallization was used to analyze qualitative data, an approach uniquely suited to clinical research.44,47 Immersion/ crystallization has the added benefit of being useful with preexisting theory.47 Although some caution against utilizing preexisting theory in qualitative research, others believe that preexisting theory can inform and improve their analysis.43,47,48 Thus, this study utilized the SRM as a tentative theoretical framework. Codes were developed and iteratively reviewed for consistency. Codes were then examined in the context of the larger model for their thematic content. Compelling, representative quotations were selected for each code and theme. These were then reviewed in the context of the survey as a check of the context from which the quote was taken.
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Results
Study Participants One hundred forty-one women provided medical record information, and most (n = 114) completed the survey (81.4%). Comparisons of demographic and medical record data for those in active treatment (within 1 year of diagnosis) and those who completed treatment (2Y5 years postdiagnosis) are included in the Table. The two did not differ in terms of demographics but did differ on several treatment variables.
Health Behaviors DIET
Analysis of Quantitative Data Descriptive analyses were generated. Linear regression models were used to test the association of health behavior scales (diet,
There were trends that those who had completed treatment (mean, 3.18 [SE, 0.10]) and those who had higher perceived efficacy of diet (" = .147 [SE, .08]) had higher healthy food consumption
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Table & Individuals With a Prior Breast Cancer Diagnosis as a Function of Time Since Treatment Within 1 y (n = 63)
Diagnosis as a Function of Time Since Treatment, Continued
2Y5 y (n = 51)
Age, mean (SD), y 58.1 (1.4) 59.3 (1.4) Education High school or less 25 (61.0%) 16 (39.0%) Some college or 2-y degree 15 (55.6%) 13 (46.4%) 4-y degree 9 (40.1%) 13 (59.9%) Graduate degree 14 (60.9%) 9 (39.1%) Family income G$15 000 9 (81.8%) 2 (18.2%) $15 000Y$24 999 8 (80.0%) 2 (20.0%) $25 000Y$49 999 11 (39.3%) 17 (60.7%) $50 000Y$99 999 21 (51.2%) 20 (48.8%) Q$100 000 10 (52.6%) 9 (47.4%) Appalachian status Yes 14 (51.9%) 13 (48.1%) No 48 (56.5%) 37 (43.5%) Rural status Metro 39 (63.9%) 22 (36.1%) Nonmetro (rural) 31 (62.0%) 19 (38.0%) Race White 61 (55.5%) 49 (44.5%) Other 2 (50.0%) 2 (50.0%) Insurance Private 40 (56.3%) 31 (43.7%) Medicare/Medicaid 11 (78.6%) 3 (21.4%) Both private and 7 (31.8%) 15 (68.2%) Medicare/Medicaid Self-pay 3 (60.0%) 2 (40.0%) Family cancer history Yes 52 (55.9%) 41 (44.1%) No 11 (52.4%) 10 (47.6%) Perceived risk Higher odds 31 (58.5%) 22 (41.5%) The same odds 18 (51.4%) 17 (48.6%) Lower odds 12 (50.0%) 12 (50.0%) Distress specific to breast cancer 17.7 (6.2) 15.8 (7.3) recurrence, mean (SD) Perceived efficacy of diet, mean (SD) 4.1 (.8) 4.0 (.8) Perceived efficacy of vitamins, 3.5 (1.0) 3.6 (.8) mean (SD) Perceived efficacy of exercise, 3.8 (.9) 3.7 (.8) mean (SD) Perceived efficacy of mammograms, 3.6 (1.4) 3.5 (1.3) mean (SD) Perceived efficacy of clinical 3.9 (1.2) 3.6 (1.3) breast examinations, mean (SD) Medical record data Breast cancer type Lobular only 5 (83.3%) 1 (16.7%) Infiltrating ductal 47 (52.2%) 43 (47.8%) DCIS only 3 (37.5%) 5 (62.5%) Lobular + ductal 2 (100.0%) 0 (0.0%) Paget disease + ductal 2 (66.7%) 1 (33.3%) (+ lobular, n = 1) Invasive mucinous 2 (100.0%) 0 (0.0%) (continues)
Health Behaviors Among Cancer Survivors
Table & Individuals With a Prior Breast Cancer
Within 1 y (n = 63) ER status Positive Negative PR status Positive Negative Her-2/nue status Positive Negative Cancer stage at diagnosis 0 I II III Lumpectomya Yes No Mastectomyb Yes No Radiationa Yes No Chemotherapyb Yes No
2Y5 y (n = 51)
45 (58.4%) 10 (45.5%)
32 (41.6%) 12 (54.5%)
34 (55.7%) 21 (55.3%)
27 (44.3%) 17 (44.7%)
8 (50.0%) 42 (56.0%)
8 (50.0%) 33 (44.0%)
3 8 6 1
(30.0%) (66.7%) (40.0%) (50.0%)
7 4 9 1
(70.0%) (33.3%) (60.0%) (50.0%)
32 (44.4%) 28 (73.7%)
40 (55.6%) 10 (26.3%)
29 (67.4%) 31 (46.3%)
14 (32.6%) 36 (53.7%)
21 (40.4%) 39 (67.2%)
31 (59.6%) 19 (32.8%)
18 (41.9%) 42 (70.0%)
25 (58.1%) 18 (30.0%)
Abbreviations: DCIS, ductal carcinoma in situ; ER, estrogen receptor; PR, progesterone receptor. a P G .005. b P G .05.
than did those in active treatment (mean, 2.95, [SE, 0.09]; F1,104 = 2.95; P = .089) and those with lower perceived treatment efficacy (F1,104 = 3.24, P = .075). Those from metro areas (mean, 3.24 [SE, 0.09]) had higher healthy food consumption than did those in more rural areas (mean, 2.89 [SE, 0.11]; F1,104 = 6.30; P = .014]. Most (54.10%) reported that their diet had not changed since diagnosis. Some women in active treatment, particularly those receiving chemotherapy, noted a variety of changes to their diet: ‘‘only eat comfort foods,’’ ‘‘taste buds have changed,’’ ‘‘can’t eat red meat,’’ ‘‘don’t eat as much.’’ However, others reported trying to eat a healthier diet: some avoiding soy and some treatment completers trying to lose weight. VITAMIN USE
There was a trend that those who had completed treatment (mean, 2.11 [SE, 0.12]) had higher vitamin use than did those in active treatment (mean, 1.82 [SE, 0.11); F1,103 = 3.02; P = .085). Those who were older (" = .018 [SE, .01]) and those who had higher perceived efficacy of vitamin use (" = .460 [SE, .09]) had higher vitamin use than did those who were younger (F1,103 = 5.21, P = .024) and those who had lower perceived treatment efficacy (F1,103 = 25.27, P G .001). Cancer NursingTM, Vol. 38, No. 3, 2015
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Most (65.50%) reported that their supplement use had not changed. Some in active treatment noted that they stopped taking some supplements because of chemotherapy. Others reported trying to decrease supplement use and have a healthier diet. However, it was more common for those changing to increase supplement use, including calcium and vitamin D to strengthen bones. EXERCISE
There was a trend that those with perceived risk of getting breast cancer again that was lower than (mean, 14.30 [SE, 2.34]) or same as (mean, 15.82 [SE, 1.97]) the general population had higher physical activity than did those with higher perceived odds (mean, 10.90 [SE, 1.67], F1,101 = 3.06; P = .052). Those who self-paid for insurance exercised more (mean, 22.16 [SE, 4.70]) than did those with private insurance (mean, 8.59 [SE, 1.61]), Medicare/ Medicaid (mean, 13.87 [SE, 2.55]), or both private and Medicare/ Medicaid (mean, 10.078 [SE, 2.06]; F1,101 = 3.61; P = .016). Most (62.3%) reported changing physical activity after their diagnosis. Those in active treatment reported that they decreased exercise, ‘‘chemo causes tiredness.’’ One woman also noted that she had to decrease strength training because of lymphedema. Some women noted other problems that have occurred besides cancer that have limited their activities. Other treatment completers have noted an increase in exercise: ‘‘Exercise is a priority now.’’ CANCER SCREENING
Those who had greater distress had greater frequency of mammography screening (" = .039 [SE, .02]) than did those with less distress (F1,104 = 7.00, P = .009). Those in active treatment (mean, 5.18 [SE, 0.15]) had less frequent clinical breast examinations than did those completing treatment (mean, 5.98 [SE, 0.15]; F1,99 = 13.96; P G .001). Those with greater education (graduate degree: mean, 5.91 [SE, 0.23]; 4-year degree: mean, 5.83 [SE, 0.23]; some college: mean, 5.57 [SE, 0.21]) had more frequent clinical breast examinations than did those with less education (mean, 5.01 [SE, 0.17]; F1,99 = 4.59; P = .005). Those receiving chemotherapy (mean, 5.89 [SE, 0.16]) had more frequent clinical breast examinations than did those not receiving chemotherapy (mean, 5.27 [SE, 0.14, F1,99 = 8.17; P = .005).
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Discussion
This study considered those in active treatment and those completing treatment for breast cancer in terms of diet, vitamin use, exercise, and cancer screening and if SRM factors, including selfsystem factors (eg, socioeconomic factors, region), affective factors (distress), and cognitive factors (treatment efficacy), and perceived risk were associated with the performance of these behaviors. To begin, bivariate analyses indicated that, for the most part, those in active treatment did not differ from those who had completed treatment. The 2 differed only in terms of treatment variables (lumpectomy, mastectomy, radiation, and chemotherapy). This likely reflects the rapidly changing treatment environment for breast cancer patients, including the availability of Oncotype Dx testing49 and Adjuvant! Online risk assessment.50
Those in active and completing treatment also differed on most of the health behaviors of interest, and although the SRM indicates that the self-system is critical in health behavior, these differences have not been widely investigated in the literature. Those in active treatment had less healthy food consumption, less vitamin use, and less frequent clinical examinations than did those who had completed treatment. Qualitative data indicated that active treatment changed the taste for certain foods, increased the desire for comfort foods (leading to a poorer diet), decreased energy levels (leading to less physical activity), and caused concerns about the impact of supplements on chemotherapy efficacy, while those completing treatment were opting for a healthier lifestyle. However, it is surprising that those in active treatment reported fewer clinical breast examinations. It would seem that the availability of healthcare providers during the course of treatment would increase the likelihood that clinical breast examinations would occur. Yet, it is possible that healing from surgery may preclude examination or that patients were unaware that clinical breast examinations were being conducted. Demographic factors, also self-system factors, were found to have associations with health behaviors. Those from metro (nonrural) areas had healthier food consumption, perhaps an indicator of greater access to healthier types of food. Older individuals had greater supplement use than did younger individuals, which is not consistent with the findings in breast cancer patients literature,51 perhaps because of our more restricted assessment of supplements. Furthermore, those who self-paid for insurance were more likely to exercise, perhaps as a way to decrease healthcare utilization, although it is unclear why insurance was not relevant to other health behaviors, such as mammography, which is more reliant on health insurance coverage. Finally, those with greater education, a proxy measure of socioeconomic status, were more likely to have clinical breast examinations. This may be another access issue, or perhaps those with greater education were simply more aware of the need for clinical breast examinations. Income and race did not appear to play a role in health behaviors in our study. Future research will elucidate the impact of the Affordable Care Act on such health behaviors, as individuals will presumably have greater access to energy balance interventions and cancer screening. Although individuals may engage in health behaviors as a way to decrease healthcare costs, educational efforts and preventive interventions that accompany the Act may result in improved overall well-being. Perceived treatment efficacy was positively related to diet and vitamin use but not to exercise or cancer screening. The association is supported by the SRM18; those who have beliefs consistent with a health behavior are more likely to engage in the given behavior. Our results contrast with previous studies indicating that self-efficacy was predictive of exercise behavior.37 Yet, those studies were limited to recently diagnosed patients, and they did not focus on perceived treatment efficacy to prevent or delay cancer, further supporting the theoretical assertion that self-efficacy and perceived treatment efficacy are 2 unique constructs. Rather than efficacy, perceived risk of recurrence appeared to be a better predictor of exercise behavior. Women who believed their risk of recurrence was higher than average were less likely to exercise, perhaps indicating that they believed their risk was so high that engaging in
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exercise would not help. Thus, although the overall findings support the role of the cognitive representation in health behavior, different beliefs (ie, self-relevance of the health threat vs treatment efficacy) were associated with different behaviors. Along with beliefs, the SRM also posits that affect is a key predictor of behavior.23 This was only true of mammograms. Women who were more distressed were more likely to have mammograms, consistent with cancer screening in women who are unaffected with cancer.52 The lack of findings in this case may indicate a floor effect, as distress was quite low in the sample, with little variance. It is possible that a closer relationship between distress and health behavior would be observed in a sample with higher distress. Limitations to the current study should be noted. To begin, the study was cross-sectional and retrospective in nature, which may be subject to recall bias. Furthermore, we relied on self-report data, and participants may overestimate the amount of health behaviors in which they engage. This is less important in modeling of behavior, unless overestimates vary systematically with particular psychosocial characteristics.
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Conclusion
Individuals currently under treatment are less likely to engage in health behaviors than those who have completed treatment. It is possible that health behavior interventions may help those in active treatment to more effectively manage the rigors of cancer treatment, as well as decrease their risk for recurrence. This is clearly an identified need of cancer patients. In clinical practice, nursing interventions may help this population in terms of both psychological coping and physical management of the disease. Furthermore, our data support the importance of treatment efficacy beliefs, a cognitive factor in the SRM, in the health behaviors of cancer patients. Thus, to have the greatest impact, clinical interventions to improve health behaviors in this population should endeavor to (1) increase patients’ beliefs in the efficacy of the health behavior, if merited, to prevent and delay cancer and (2) clarify the sometimes bewildering number of studies with apparently inconsistent results regarding the treatment efficacy of health behaviors. Along with perceived treatment efficacy, perceived risk may be critical to increasing physical activity, and these 2 factors may go hand-in-hand in improving health behavior. Although increasing perceived risk and perceived treatment efficacy may follow from these results, care should be exercised in interventions that endeavor to motivate by increasing distress levels. Excessively elevated distress levels may lead to decreased quality of life and to overutilization of mammograms. Along with psychosocial factors, access to healthcare and education to accomplish health behaviors are key, and these activities may be supported by the Affordable Care Act in the United States in its effort to prevent future disease. Finally, in any nursing intervention, contextual factors (eg, rural areas that may affect access) are very important, and this continues to be a concern for individuals currently undergoing treatment or who have completed treatment.
Health Behaviors Among Cancer Survivors
ACKNOWLEDGMENT
The authors would like to acknowledge Mayank Ajmera, MS, for his assistance with the preparation of the Table.
References 1. American Cancer Society. Cancer Facts and Figures. 2013. http://www .cancer.org/downloads/STT/CAFF_finalPWSecured.pdf. Accessed May 20, 2013. 2. Helgeson VS, Cohen S. Social support and adjustment to cancer: reconciling descriptive, correlational, and intervention research. Health Psychol. 1996;15(2):135Y148. 3. Lam WW, Chan M, Or A, Kwong A, Suen D, Fielding R. Reducing treatment decision conflict difficulties in breast cancer surgery: a randomized controlled trial. J Clin Oncol. 2013;31(23):2879Y2885. 4. Holt S, Bertelli G, Humphreys I, et al. A decision impact, decision conflict and economic assessment of routine Oncotype DX testing of 146 women with node-negative or pNImi, ER-positive breast cancer in the U.K. Br J Cancer. 2013;108(11):2250Y2258. 5. Drug & Therapeutics Bulletin. An introduction to patient decision aids. BMJ. 2013;347:f4147. 6. Deimling GT, Bowman KF, Sterns S, Wagner LJ, Kahana B. Cancer-related health worries and psychological distress among older adult, long-term cancer survivors. Psychooncology. 2006;15(4):306Y320. 7. National Cancer Institute. Adjustment to cancer: anxiety and distress. http:// www.cancer.gov/cancertopics/pdq/supportivecare/adjustment/HealthProfessional/ page2. Accessed May 20, 2013. 8. Custers JA, van den Berg SW, van Laarhoven HW, Bleiker EM, Gielissen MF, Prins JB. The cancer worry scale: detecting fear of recurrence in breast cancer survivors. Cancer Nurs. 2014;37(1):E44YE50. 9. Lu MH, Lin HR, Lee MD. The experiences among older Taiwanese women facing a new diagnosis of breast cancer. Cancer Nurs. 2010;33(5):398Y405. 10. Kelly KM, Shedlosky-Shoemaker R, Porter K, DeSimone P, Andrykowski M. Cancer recurrence worry, risk perception, and informational coping among Appalachian oncology patients. J Psychosoc Oncol. 2011;29(1):1Y18. 11. Simard S, Thewes B, Humphris G, et al. Fear of cancer recurrence in adult cancer survivors: a systematic review of quantitative studies. J Cancer Surviv. 2013;7(3):300Y322. 12. Costanzo ES, Lutgendorf SK, Mattes ML, et al. Adjusting to life after treatment: distress and quality of life following treatment for breast cancer. Br J Cancer. 2007;97(12):1625Y1631. 13. Documet PI, Trauth JM, Key M, Flatt J, Jernigan J. Breast cancer survivors’ perception of survivorship. Oncol Nurs Forum. 2012;39(3):309Y315. 14. Hoffman RM, Lewis CL, Pignone MP, et al. Decision-making processes for breast, colorectal, and prostate cancer screening: the DECISIONS survey. Med Decis Making. 2010;30(suppl 5):53SY64S. 15. Bellizzi KM, Rowland JH, Jeffery DD, McNeel T. Health behaviors of cancer survivors: examining opportunities for cancer control intervention. J Clin Oncol. 2005;23(34):8884Y8893. 16. US Department of Health & Human Services. Key features of the Affordable Care Act. http://www.hhs.gov/healthcare/facts/timeline/index.html. Accessed July 17, 2013. 17. Hovland C, Rosenberg M, eds. Attitude Organization and Change. New Haven, CT: Yale University Press; 1960. 18. Leventhal H, Benyamini Y, Brownlee S, Diefenbach M, Leventhal EA, Patrick-Miller L. Illness representation: theoretical foundations. In: Weinman J, Petrie K, eds. Perceptions of Health and Illness. London, UK: Harwood Publishers; 1997:19Y45. 19. Leventhal H, Brisette I, Leventhal E. The common-sense model of selfregulation of health and illness. In: Cameron LD, Leventhal H, eds. The Selfregulation of Health and Illness Behaviour. London, UK: Routledge; 2003: 42Y65. 20. Quach J, Porter K, Leventhal H, Kelly K. Health behaviors among Ashkenazi Jewish individuals receiving counseling for BRCA1 and BRCA2 mutations. Fam Cancer. 2009;8(3):241Y250. 21. Leventhal H, Kelly K, Leventhal E. Population risk, actual risk, perceived risk, and cancer control: a discussion. J Natl Cancer Inst Monogr. 1999;25:81Y85.
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22. Cameron LD, Leventhal EA, Leventhal H. Symptom representations and affect as determinants of care seeking in a community-dwelling, adult sample population. Health Psychol. 1993;12(3):171Y179. 23. Hay JL, Buckley TR, Ostroff JS. The role of cancer worry in cancer screening: a theoretical and empirical review of the literature. Psychooncology. 2005; 14(7):517Y534. 24. George SM, Irwin ML, Smith AW, et al. Postdiagnosis diet quality, the combination of diet quality and recreational physical activity, and prognosis after early-stage breast cancer. Cancer Causes Control. 2011;22(4):589Y598. 25. Davies NJ, Batehup L, Thomas R. The role of diet and physical activity in breast, colorectal, and prostate cancer survivorship: a review of the literature. Br J Cancer. 2011;105(suppl 1):S52YS73. 26. Wolin KY, Colditz GA. Cancer and beyond: healthy lifestyle choices for cancer survivors. J Natl Cancer Inst. 2013;105(9):593Y594. 27. Maunsell E, Drolet M, Brisson J, Robert J, Deschenes L. Dietary change after breast cancer: extent, predictors, and relation with psychological distress. J Clin Oncol. 2002;20(4):1017Y1025. 28. Burris JL, Jacobsen PB, Loftus LS, Andrykowski MA. Breast cancer recurrence risk reduction beliefs in breast cancer survivors: prevalence and relation to behavior. Psychooncology. 2012;21(4):427Y435. 29. Nechuta S, Lu W, Chen Z, et al. Vitamin supplement use during breast cancer treatment and survival: a prospective cohort study. Cancer Epidemiol Biomarkers Prev. 2011;20(2):262Y271. 30. Saquib J, Rock CL, Natarajan L, et al. Dietary intake, supplement use, and survival among women diagnosed with early-stage breast cancer. Nutr Cancer. 2011;63(3):327Y333. 31. Burstein HJ, Gelber S, Guadagnoli E, Weeks JC. Use of alternative medicine by women with early-stage breast cancer. N Engl J Med. 1999;340(22): 1733Y1739. 32. Bertram LA, Stefanick ML, Saquib N, et al. Physical activity, additional breast cancer events, and mortality among early-stage breast cancer survivors: findings from the WHEL study. Cancer Causes Control. 2011;22(3): 427Y435. 33. Paxton RJ, Phillips KL, Jones LA, et al. Associations among physical activity, body mass index, and health-related quality of life by race/ethnicity in a diverse sample of breast cancer survivors. Cancer. 2012;118(16):4024Y4031. 34. Irwin ML, Crumley D, McTiernan A, et al. Physical activity levels before and after a diagnosis of breast carcinoma: the Health, Eating, Activity, and Lifestyle (HEAL) study. Cancer. 2003;97(7):1746Y1757. 35. Harper FWK, Schmidt JE, Beacham AO, et al. The role of social cognitive processing theory and optimism in positive psychosocial and physical behavior change after cancer diagnosis and treatment. Psychooncology. 2007;16(1): 79Y91. 36. Emery CF, Yang HC, Frierson GM, Peterson LJ, Suh S. Determinants of physical activity among women treated for breast cancer in a 5-year longitudinal follow-up investigation. Psychooncology. 2009;18(4):377Y386.
37. Mosher CE, Fuemmeler BF, Sloane R, et al. Change in self-efficacy partially mediates the effects of the FRESH START intervention on cancer survivors’ dietary outcomes. Psychooncology. 2008;17(10):1014Y1023. 38. Berry DA, Cronin KA, Plevritis SK, et al. Effect of screening and adjuvant therapy on mortality from breast cancer. N Engl J Med. 2005;353(17): 1784Y1792. 39. Field TS, Doubeni C, Fox MP, et al. Under utilization of surveillance mammography among older breast cancer survivors. J Gen Intern Med. 2008; 23(2):158Y163. 40. Doubeni CA, Field TS, Ulcickas Yood M, et al. Patterns and predictors of mammography utilization among breast cancer survivors. Cancer. 2006;106(11): 2482Y2488. 41. Breslau ES, Jeffery DD, Davis WW, Moser RP, McNeel TS, Hawley S. Cancer screening practices among racially and ethnically diverse breast cancer survivors: results from the 2001 and 2003 California health interview survey. J Cancer Surviv. 2010;4(1):1Y14. 42. Thewes B, Butow P, Bell ML, et al. Fear of cancer recurrence in young women with a history of early-stage breast cancer: a cross-sectional study of prevalence and association with health behaviours. Support Care Cancer. 2012; 20(11):2651Y2659. 43. Hesse-Biber SN. Mixed Methods Research: Merging Theory With Practice. New York, NY: The Guilford Press; 2010. 44. Miller WL, Crabtree BF. Clinical research. In: Denzin NK, Lincoln YS, eds. Handbook of Qualitative Research. Thousand Oaks, CA: Sage Publications; 2000:366Y378. 45. Creswell JW. Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Thousand Oaks, CA: Sage Publications; 1998. 46. Kelly KM, Leventhal H, Andrykowski M, et al. Using the Common Sense Model to understand perceived cancer risk in individuals testing for BRCA1/2 mutations. Psychooncology. 2005;14(1):34Y48. 47. Borkan J. Immersion/crystallization. In: Crabtree BF, Miller WL, eds. Doing Qualitative Research. 2nd ed. Thousand Oaks, CA: Sage Publications; 1999. 48. Miles MB, Huberman AM. Qualitative Data Analysis. Newbury Park, CA: Sage Publications; 1994:10Y12. 49. Beene-Harris RY, Wang C, Bach JV. Barriers to access: results from focus groups to identify genetic service needs in the community. Community Genet. 2007;10(1):10Y18. 50. Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol. 2001;19(4):980Y991. 51. Helyer LK, Chin S, Chui BK, et al. The use of complementary and alternative medicines among patients with locally advanced breast cancerVa descriptive study. BMC Cancer. 2006;6:39. 52. Stefanek ME, Wilcox P. First degree relatives of breast cancer patients: screening practices and provision of risk information. Cancer Detect Prev. 1991;15(5):379Y384.
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Kimberly M. Kelly, PhD Rituparna Bhattacharya, MS Stephanie Dickinson, MAS Hannah Hazard, MD
Health Behaviors Among Breast Cancer Patients and Survivors K E Y
W O R D S
Background: With improved treatments, the survival rate for breast cancer
Breast cancer
patients is increasing. With the improvements in quantity of life, research in the field
Cancer screening
of cancer survivorship has turned its attention to psychosocial functioning and health
Diet
behaviors. Objectives: The purpose of this study was to examine how those
Health behaviors
currently under treatment and those completing treatment engaged in health
Physical activity
behaviors (ie, diet, vitamin use, exercise, and cancer screening) and if psychosocial
Vitamin use
predictors, guided by the Self-regulation Model, also play a role. Methods: Using the Self-regulation Model, the current survey and medical record review examined health behaviors (diet, vitamin use, exercise, cancer screening) in individuals in active treatment for breast cancer and in those completing treatment (n = 141). Results: Regression models revealed that those in active treatment had less healthy food consumption, vitamin use, and clinical examinations than did treatment completers. Greater perceived treatment efficacy was associated with diet and vitamin use but not exercise or cancer screening. Greater perceived risk of recurrence was associated with less exercise. Greater distress was associated with greater mammography use. Those from metro areas had greater healthy food consumption. Results: Qualitative data indicated that chemotherapy interfered with health behaviors for those in active treatment; treatment completers wished to have a healthier lifestyle. Conclusion: Cancer treatment interferes with health behaviors, and these health behaviors might help individuals manage their cancer treatment more effectively. Implications for Practice: Those currently undergoing treatment desire assistance with a healthier lifestyle, and relevant clinical interventions should stress treatment efficacy.
Author Affiliations: School of Pharmacy and Mary Babb Randolph Cancer Center, West Virginia University, Morgantown (Dr Kelly and Ms Bhattacharya); Department of Statistics, Indiana University, Bloomington (Ms Dickinson); Department of Surgery, West Virginia University, Morgantown (Dr Hazard). Funding was provided by the Ohio Division of the American Cancer Society. The authors have no conflicts of interest to disclose.
Health Behaviors Among Cancer Survivors
Correspondence: Kimberly M. Kelly, PhD, West Virginia University School of Pharmacy and Mary Babb Randolph Cancer Center, Robert C. Byrd Health Sciences Center, PO Box 9510, Morgantown, WV 26506 ([email protected]). Accepted for publication April 23, 2014. DOI: 10.1097/NCC.0000000000000167
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W
ith improved treatments, the survival rate for breast cancer patients is increasing. Specifically, the 10-year survival rate is 83%,1 resulting in a large and growing population for nursing care. With improvements in quantity of life, research in the field of cancer survivorship has turned its attention to quality of life and psychosocial functioning. With the physical demands of the disease, concerns about social interactions,2 and the number of decisions that must be made about treatment,3Y5 many have expressed concern about cancer patients’ experience of distress or negative affect, which may include depression, anxiety, worry, panic, and isolation,6,7 and a number of scales have been developed to understand the psychosocial experience of cancer patients8 (including concepts such as pain, fear of death, and intrusive thoughts about cancer recurrence). The treatment phase for breast cancer has been associated with increased fear and worry,9,10 and distress may persist following treatment for cancer, particularly fear of recurrence.11 Despite these difficulties, for many, the posttreatment phase is associated with increased wellbeing and posttraumatic growth, leaving cancer survivors with greater appreciation for life.12,13 The decision-making literature in breast cancer patients has mainly focused on treatment choices.3Y5 Meanwhile, less attention has been paid to the health behaviors (eg, diet, exercise, and vitamin use) of breast cancer patients and survivors. Although decision making for cancer screening has been widely studied,14 only a couple of studies have focused on breast cancer screening after being diagnosed with breast cancer, indicating an increased demand for mammograms in the United States.15 However, this literature is growing and will become increasingly important in the context of the Affordable Care Act in the United States, which already protects those with preexisting conditions and will place greater emphasis on prevention of future disease, such as cancer recurrence.16 Of particular concern, those currently under treatment may have the most challenges to leading a healthy lifestyle to prevent cancer recurrence and may be a group in critical need of assistance. Understanding the factors that play a role in performing health behaviors is critical for the overall wellbeing of the patient, as clinical interventions may improve health outcomes. A number of models explore the relationship of health beliefs to behavior (eg, the Health Belief Model, the Theory of Planned Behavior); however, few include the role of affect in behavior. Leventhal’s Self-regulation Model (SRM) posits that affective and cognitive processes interact to influence the performance of health behaviors and is routed in attitudinal research that links cognition, affect, and behavior.17 Specifically, The SRM includes the self-system, cognitive and affective representations, and health behaviors.18,19 The self-system is the combination of self and social environment factors essential to the perception of the health threat.18 Self-system factors are demographic (eg, age, socioeconomic factors), biological (eg, in active treatment), cultural, regional (eg, rural, Appalachian), and so on. Within the self-system, when presented with a stimulus (eg, breast cancer), an individual forms a cognitive and an affective representation of the health threat. The cognitive representation may include a number of salient features of the disease (eg, what the disease is, how effective a given health behavior is). In a pre-
vious study of health behaviors in individuals undergoing genetic counseling for hereditary cancer, beliefs about treatment efficacy were found to be key predictors of health behaviors,20 and this differs from many health behavior models, which include selfefficacy as a predictor (eg, Social Cognitive Theory). In contrast to the cognitive representation, the affective representation includes feelings about the health threat, with research focused on distress/ negative affect.21,22 Distress has been shown to be a potent predictor of cancer screening in individuals without a personal history of cancer.23 In addition, perceived risk, which is largely considered a cognitive factor in determining if one’s self is at risk, is strongly affectively influenced21,22 and is an important consideration in health behavior.21 Cognitive and affective representations drive the health behaviors, which an individual uses to manage the health threat. Thus, based on the model, we hypothesized that those who perceived the greatest threat of cancer (ie, perceived risk), who had the highest beliefs in the efficacy of the treatment/health behavior, and who had the greatest worry about the threat of cancer recurrence will be most likely to engage in the health behavior.
Diet Women consuming better-quality diets have reduced breast cancer mortality.24 Meta-analytic studies and systematic reviews have concluded that increasing vegetable consumption might reduce the risk of breast cancer recurrence.25 Although foods rich in dietary fat have been generally believed to lead to increased risk of breast cancer, the evidence is inconsistent.26 The impact of psychosocial factors such as worry, perceived risk, and perceived treatment efficacy on diet has been understudied in breast cancer patients,27 and of the existing studies, most have focused on newly diagnosed breast cancer patients. One study found greater distress and younger age were associated with greater dietary change in the 12 months after diagnosis.27 However, another study found no association between cancer recurrence worry and risk perception on behaviors such as eating 5 servings of fruit and vegetables per day, finding that beliefs about recurrence were better predictors.28 We identified no studies investigating longer-term survivors in diet quality.
Vitamin Use Few studies have investigated the role of vitamin supplement use in breast cancer patients during treatment and survival. Vitamin use shortly after diagnosis was associated with reduced mortality and recurrence.29 However, Saquib et al,30 in a 9-year prospective study, found that vitamin intake was not associated with allcause mortality. Breast cancer patients have reported increasing vitamin/supplement use after diagnosis, with overall supplement use in long-term survivors being quite high.30 Only 2 studies were identified that examined a psychosocial factor in vitamin use in newly diagnosed breast cancer patients. One study found that megavitamin use was associated with increased psychosocial distress31; another found that it was not, with only beliefs about recurrence being associated with vitamin supplement use.28 Additional study is needed to understand these contrasting findings.
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Physical Activity Results from observational studies, literature reviews, and metaanalytic studies suggest that physical activity after diagnosis helps to improve quality of life and well-being and also reduces mortality.25,32,33 However, despite strong evidence for physical activity in improving breast cancer prognosis, only 32% of breast cancer patients participated in recommended levels of physical activity, and patients were less active in the first year of diagnosis compared with the year prior to diagnosis.34 A study investigating behavior change after cancer diagnosis found that exercise was the least likely behavior to change.35 Depressive symptoms and lower education levels were barriers to physical activity in women throughout breast cancer treatment and survivorship.36 Self-efficacy was associated with increased likelihood of participation in physical activity programs in those currently under treatment.37 Again, our literature review found no studies linking perceived breast cancer recurrence risk with physical activity.
the lead author spent considerable time observing a universityassociated breast oncology clinic in a Midwestern city and conducted interviews with patients and clinical staff (eg, oncology surgeon, nurse practitioner, clinical nurses, and schedulers). Based on information gleaned, a survey was developed, utilizing some previously existing scales and some open-ended items to expand our understanding of current health behaviors in cancer patients. Including both qualitative and quantitative approaches allows for methodological triangulation and complementarity to gain an understanding of a research question both for depth and convergence of results; further development of study design, such as for developing surveys; helping to answer questions or contradictions from 1 approach; and expansion to extend the types of questions that can be asked,43 the latter being most relevant to the current study. Mixed methods also allow for iteration in development of research questions, conduct of the study, and data analysis.43 This approach reflects the applied anthropological nature of clinical research.44,45
Cancer Screening
Participants
Cancer screening for those with a previous history of cancer has been shown to dramatically decrease breast cancer mortality risk,38 although such screening may be underutilized by breast cancer survivors.39 One study reported that while 80% of breast cancer survivors had received a mammogram in the year following treatment; only 63% had a mammogram at the fifth year of follow-up.40 However, other studies reported higher screening rates among breast cancer survivors as compared with those without a history of breast cancer.41 There is a general belief in popular literature that fear and anxiety about recurrence might lead breast cancer survivors to forgo screening.42 We identified no studies investigating the relationship of breast cancer screening and perceived treatment efficacy or perceived risk of breast cancer recurrence in those with a previous breast cancer diagnosis. Thus, the epidemiological literature indicates the types of health behaviors noted above (diet, vitamin use, physical activity, and cancer screening) may be associated with the risk of breast cancer recurrence. However, for the most part, it is unclear how the cancer trajectory may affect the performance of health behaviors, and other key psychosocial factors have been largely neglected for their role in health behaviors among those with a prior history of breast cancer. The objectives of this study were to examine how those currently under treatment and those completing treatment engaged in health behaviors (diet, vitamin use, exercise, and cancer screening) and if SRM factors, including (1) self-system factors: demographics, region; (2) affective factors: distress; and (3) cognitive factors: treatment efficacy, and perceived risk are associated with the performance of these behaviors.
Eligibility requirements included being 18 years or older, having a personal history of breast cancer, and being treated at a universityaffiliated breast oncology clinic. In addition, women were either within 1 year of their diagnosis (active) or 2 to 5 years postdiagnosis (completed).
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Methods
To better understand health behaviors in women with breast cancer, our study had both quantitative and qualitative components. Prior to initiating data collection, an informal ethnographic study was undertaken as part of a qualitative methods course, where
Health Behaviors Among Cancer Survivors
Procedure Recruitment was conducted face-to-face at a university-affiliated breast oncology clinic in a Midwestern state. A Health Insurance Portability and Accountability Act waiver from the institutional review board allowed for a prescreening medical record review of potentially eligible women. Eligible women were approached by a member of the research team (either the first author or a research assistant) at their regularly scheduled clinic visit. For interested individuals, the study was explained, and a consent form was reviewed and signed. Participants were asked to complete a crosssectional survey including questions about breast cancer recurrence and health behaviors. Time to complete the survey was estimated to be 30 minutes. A member of the research team completed a medical chart review for cancer-relevant information. At the completion of the study, women received a $10 gift card.
Measures A medical chart review was completed for each participant, including: treatment status (within 1 year of diagnosis or 2Y5 years from diagnosis), type of cancer, date of diagnosis, stage, grade, ER/PR status, Her-2/neu status, and chemotherapy. In addition, a self-report survey was completed, which included background data (ie, gender, age, education, and incomeVcommon proxy variables for socioeconomic status, race, Appalachian status, rural status, and psychosocial factors). PSYCHOSOCIAL FACTORS
Psychosocial factors included distress, perceived risk, and perceived efficacy of health behaviors. Distress was assessed with the Cancer NursingTM, Vol. 38, No. 3, 2015
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9-item Distress Specific to Breast Cancer Recurrence Scale,10,20 which included 3 items to assess anxiety and 3 to assess depression, focusing on the participant’s feelings about cancer recurrence, as well as worry about disfigurement following breast cancer, fear of dying, and concern about pain on a 5-point Likert-type scale (1 = not at all to 5 = very much). Psychometric properties of this scale have been previously established, with good internal consistency (! = .90; in the current study, ! = .91).10,20 For perceived risk, the survey asked the participant to compare her personal lifetime risk for breast cancer to that of other women: ‘‘Do you think your odds of getting breast cancer again are the same or different than those of other women?’’ Response options included ‘‘higher,’’ ‘‘the same,’’ or ‘‘lower.’’ This item was piloted in a previous study including breast cancer patients.46 Five items assessed the perceived treatment efficacy of health behaviors in relation to cancer. Participants were asked about (1) a healthy diet, (2) vitamins, (3) exercise, being ‘‘effective in preventing or delaying cancer’’ and about (4) mammograms, and (5) clinical breast examinations ‘‘decreasing the risk of cancer recurrence’’ on a 5-point Likert scale (1 = disagree strongly, 5 = agree strongly). This item was utilized in a previous study of breast cancer patients.20 HEALTH BEHAVIORS
For diet, participants were asked to rate how often they consumed certain food items during the past week (high-fiber foods such as grains and legumes, olive, canola, or safflower oil, fish, fruits, cruciferous vegetables, other vegetables), on a 6-point response scale (1 = rarely or never to 6 = 93 times a day). Psychometric properties of this scale have been previously established, with acceptable internal consistencies (! = .73 and .65; in the current study, ! = .79).20 For vitamin use, participants were asked to indicate how often in the past week they took (1) vitamin C, (2) vitamin A, (3) vitamin E, (4) B vitamins, (5) antioxidants, (6) beta carotene, (7) omega fatty acids, and (8) calcium, on a 6-point response scale (1 = rarely or never to 6 = 93 times a day). Psychometric properties of this scale have been previously established, with good internal consistency (! = .90 and .89; in the current study, ! = .82).20 Three items assessed exercise in the past week. The numbers of hours spent doing light and strenuous activities and building and maintaining strength were summed to assess total physical activity. These items were adapted from previous studies of health behaviors (National Health and Nutrition Examination Survey, Rutgers Aging and Health Study) and were the sum of 3 items regarding the total number of hours spent in mild, moderate, and strenuous exercise per week.20 Following each health behavior, women were asked if their performance of a behavior had changed since their diagnosis (yes or no) and, if so, how had the behavior changed (open-ended). In addition, 2 items assessed the self-reported frequency of breast cancer screening. One item reported the frequency of mammograms and the other clinical breast examinations, on a 7-point scale ranging from 1 = never to 7 = every 3 months.
vitamins, exercise, mammogram, and clinical breast exam, as dependent variables) with the following independent variables: treatment status (within 1 year from diagnosis or 2Y5 years postdiagnosis), age, gender, education, income, race, location of residence (Appalachian or not, metro or nonmetro), insurance type, family cancer history, perceived comparative cancer risk, perceived efficacy of the given health behavior, breast cancer type, and cancer distress. Forward stepwise selection was used in linear regression modeling to identify the best set of variables related to each health behavior. After first evaluating univariate models with each predictor separately, each variable was entered into the model one at a time, and backward elimination with an exit criterion of P 9 .10 was used at each step to determine the final model. Treatment status was left in the model even if not significant as a predictor variable of interest. All further tests were performed at significance level ! = .05. Interactions between significant main effects were tested and included if significant. PASS 6.0 power analysis software indicated that each variable entered would result in 91% power to detect an r2 of 0.1 or greater for a sample size of 100, with ! = .05. A model with 4 variables would have 74% power. Thus, our sample is adequate to test for the desired effects.
Analysis of Qualitative Data Immersion/crystallization was used to analyze qualitative data, an approach uniquely suited to clinical research.44,47 Immersion/ crystallization has the added benefit of being useful with preexisting theory.47 Although some caution against utilizing preexisting theory in qualitative research, others believe that preexisting theory can inform and improve their analysis.43,47,48 Thus, this study utilized the SRM as a tentative theoretical framework. Codes were developed and iteratively reviewed for consistency. Codes were then examined in the context of the larger model for their thematic content. Compelling, representative quotations were selected for each code and theme. These were then reviewed in the context of the survey as a check of the context from which the quote was taken.
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Results
Study Participants One hundred forty-one women provided medical record information, and most (n = 114) completed the survey (81.4%). Comparisons of demographic and medical record data for those in active treatment (within 1 year of diagnosis) and those who completed treatment (2Y5 years postdiagnosis) are included in the Table. The two did not differ in terms of demographics but did differ on several treatment variables.
Health Behaviors DIET
Analysis of Quantitative Data Descriptive analyses were generated. Linear regression models were used to test the association of health behavior scales (diet,
There were trends that those who had completed treatment (mean, 3.18 [SE, 0.10]) and those who had higher perceived efficacy of diet (" = .147 [SE, .08]) had higher healthy food consumption
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Table & Individuals With a Prior Breast Cancer Diagnosis as a Function of Time Since Treatment Within 1 y (n = 63)
Diagnosis as a Function of Time Since Treatment, Continued
2Y5 y (n = 51)
Age, mean (SD), y 58.1 (1.4) 59.3 (1.4) Education High school or less 25 (61.0%) 16 (39.0%) Some college or 2-y degree 15 (55.6%) 13 (46.4%) 4-y degree 9 (40.1%) 13 (59.9%) Graduate degree 14 (60.9%) 9 (39.1%) Family income G$15 000 9 (81.8%) 2 (18.2%) $15 000Y$24 999 8 (80.0%) 2 (20.0%) $25 000Y$49 999 11 (39.3%) 17 (60.7%) $50 000Y$99 999 21 (51.2%) 20 (48.8%) Q$100 000 10 (52.6%) 9 (47.4%) Appalachian status Yes 14 (51.9%) 13 (48.1%) No 48 (56.5%) 37 (43.5%) Rural status Metro 39 (63.9%) 22 (36.1%) Nonmetro (rural) 31 (62.0%) 19 (38.0%) Race White 61 (55.5%) 49 (44.5%) Other 2 (50.0%) 2 (50.0%) Insurance Private 40 (56.3%) 31 (43.7%) Medicare/Medicaid 11 (78.6%) 3 (21.4%) Both private and 7 (31.8%) 15 (68.2%) Medicare/Medicaid Self-pay 3 (60.0%) 2 (40.0%) Family cancer history Yes 52 (55.9%) 41 (44.1%) No 11 (52.4%) 10 (47.6%) Perceived risk Higher odds 31 (58.5%) 22 (41.5%) The same odds 18 (51.4%) 17 (48.6%) Lower odds 12 (50.0%) 12 (50.0%) Distress specific to breast cancer 17.7 (6.2) 15.8 (7.3) recurrence, mean (SD) Perceived efficacy of diet, mean (SD) 4.1 (.8) 4.0 (.8) Perceived efficacy of vitamins, 3.5 (1.0) 3.6 (.8) mean (SD) Perceived efficacy of exercise, 3.8 (.9) 3.7 (.8) mean (SD) Perceived efficacy of mammograms, 3.6 (1.4) 3.5 (1.3) mean (SD) Perceived efficacy of clinical 3.9 (1.2) 3.6 (1.3) breast examinations, mean (SD) Medical record data Breast cancer type Lobular only 5 (83.3%) 1 (16.7%) Infiltrating ductal 47 (52.2%) 43 (47.8%) DCIS only 3 (37.5%) 5 (62.5%) Lobular + ductal 2 (100.0%) 0 (0.0%) Paget disease + ductal 2 (66.7%) 1 (33.3%) (+ lobular, n = 1) Invasive mucinous 2 (100.0%) 0 (0.0%) (continues)
Health Behaviors Among Cancer Survivors
Table & Individuals With a Prior Breast Cancer
Within 1 y (n = 63) ER status Positive Negative PR status Positive Negative Her-2/nue status Positive Negative Cancer stage at diagnosis 0 I II III Lumpectomya Yes No Mastectomyb Yes No Radiationa Yes No Chemotherapyb Yes No
2Y5 y (n = 51)
45 (58.4%) 10 (45.5%)
32 (41.6%) 12 (54.5%)
34 (55.7%) 21 (55.3%)
27 (44.3%) 17 (44.7%)
8 (50.0%) 42 (56.0%)
8 (50.0%) 33 (44.0%)
3 8 6 1
(30.0%) (66.7%) (40.0%) (50.0%)
7 4 9 1
(70.0%) (33.3%) (60.0%) (50.0%)
32 (44.4%) 28 (73.7%)
40 (55.6%) 10 (26.3%)
29 (67.4%) 31 (46.3%)
14 (32.6%) 36 (53.7%)
21 (40.4%) 39 (67.2%)
31 (59.6%) 19 (32.8%)
18 (41.9%) 42 (70.0%)
25 (58.1%) 18 (30.0%)
Abbreviations: DCIS, ductal carcinoma in situ; ER, estrogen receptor; PR, progesterone receptor. a P G .005. b P G .05.
than did those in active treatment (mean, 2.95, [SE, 0.09]; F1,104 = 2.95; P = .089) and those with lower perceived treatment efficacy (F1,104 = 3.24, P = .075). Those from metro areas (mean, 3.24 [SE, 0.09]) had higher healthy food consumption than did those in more rural areas (mean, 2.89 [SE, 0.11]; F1,104 = 6.30; P = .014]. Most (54.10%) reported that their diet had not changed since diagnosis. Some women in active treatment, particularly those receiving chemotherapy, noted a variety of changes to their diet: ‘‘only eat comfort foods,’’ ‘‘taste buds have changed,’’ ‘‘can’t eat red meat,’’ ‘‘don’t eat as much.’’ However, others reported trying to eat a healthier diet: some avoiding soy and some treatment completers trying to lose weight. VITAMIN USE
There was a trend that those who had completed treatment (mean, 2.11 [SE, 0.12]) had higher vitamin use than did those in active treatment (mean, 1.82 [SE, 0.11); F1,103 = 3.02; P = .085). Those who were older (" = .018 [SE, .01]) and those who had higher perceived efficacy of vitamin use (" = .460 [SE, .09]) had higher vitamin use than did those who were younger (F1,103 = 5.21, P = .024) and those who had lower perceived treatment efficacy (F1,103 = 25.27, P G .001). Cancer NursingTM, Vol. 38, No. 3, 2015
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Most (65.50%) reported that their supplement use had not changed. Some in active treatment noted that they stopped taking some supplements because of chemotherapy. Others reported trying to decrease supplement use and have a healthier diet. However, it was more common for those changing to increase supplement use, including calcium and vitamin D to strengthen bones. EXERCISE
There was a trend that those with perceived risk of getting breast cancer again that was lower than (mean, 14.30 [SE, 2.34]) or same as (mean, 15.82 [SE, 1.97]) the general population had higher physical activity than did those with higher perceived odds (mean, 10.90 [SE, 1.67], F1,101 = 3.06; P = .052). Those who self-paid for insurance exercised more (mean, 22.16 [SE, 4.70]) than did those with private insurance (mean, 8.59 [SE, 1.61]), Medicare/ Medicaid (mean, 13.87 [SE, 2.55]), or both private and Medicare/ Medicaid (mean, 10.078 [SE, 2.06]; F1,101 = 3.61; P = .016). Most (62.3%) reported changing physical activity after their diagnosis. Those in active treatment reported that they decreased exercise, ‘‘chemo causes tiredness.’’ One woman also noted that she had to decrease strength training because of lymphedema. Some women noted other problems that have occurred besides cancer that have limited their activities. Other treatment completers have noted an increase in exercise: ‘‘Exercise is a priority now.’’ CANCER SCREENING
Those who had greater distress had greater frequency of mammography screening (" = .039 [SE, .02]) than did those with less distress (F1,104 = 7.00, P = .009). Those in active treatment (mean, 5.18 [SE, 0.15]) had less frequent clinical breast examinations than did those completing treatment (mean, 5.98 [SE, 0.15]; F1,99 = 13.96; P G .001). Those with greater education (graduate degree: mean, 5.91 [SE, 0.23]; 4-year degree: mean, 5.83 [SE, 0.23]; some college: mean, 5.57 [SE, 0.21]) had more frequent clinical breast examinations than did those with less education (mean, 5.01 [SE, 0.17]; F1,99 = 4.59; P = .005). Those receiving chemotherapy (mean, 5.89 [SE, 0.16]) had more frequent clinical breast examinations than did those not receiving chemotherapy (mean, 5.27 [SE, 0.14, F1,99 = 8.17; P = .005).
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Discussion
This study considered those in active treatment and those completing treatment for breast cancer in terms of diet, vitamin use, exercise, and cancer screening and if SRM factors, including selfsystem factors (eg, socioeconomic factors, region), affective factors (distress), and cognitive factors (treatment efficacy), and perceived risk were associated with the performance of these behaviors. To begin, bivariate analyses indicated that, for the most part, those in active treatment did not differ from those who had completed treatment. The 2 differed only in terms of treatment variables (lumpectomy, mastectomy, radiation, and chemotherapy). This likely reflects the rapidly changing treatment environment for breast cancer patients, including the availability of Oncotype Dx testing49 and Adjuvant! Online risk assessment.50
Those in active and completing treatment also differed on most of the health behaviors of interest, and although the SRM indicates that the self-system is critical in health behavior, these differences have not been widely investigated in the literature. Those in active treatment had less healthy food consumption, less vitamin use, and less frequent clinical examinations than did those who had completed treatment. Qualitative data indicated that active treatment changed the taste for certain foods, increased the desire for comfort foods (leading to a poorer diet), decreased energy levels (leading to less physical activity), and caused concerns about the impact of supplements on chemotherapy efficacy, while those completing treatment were opting for a healthier lifestyle. However, it is surprising that those in active treatment reported fewer clinical breast examinations. It would seem that the availability of healthcare providers during the course of treatment would increase the likelihood that clinical breast examinations would occur. Yet, it is possible that healing from surgery may preclude examination or that patients were unaware that clinical breast examinations were being conducted. Demographic factors, also self-system factors, were found to have associations with health behaviors. Those from metro (nonrural) areas had healthier food consumption, perhaps an indicator of greater access to healthier types of food. Older individuals had greater supplement use than did younger individuals, which is not consistent with the findings in breast cancer patients literature,51 perhaps because of our more restricted assessment of supplements. Furthermore, those who self-paid for insurance were more likely to exercise, perhaps as a way to decrease healthcare utilization, although it is unclear why insurance was not relevant to other health behaviors, such as mammography, which is more reliant on health insurance coverage. Finally, those with greater education, a proxy measure of socioeconomic status, were more likely to have clinical breast examinations. This may be another access issue, or perhaps those with greater education were simply more aware of the need for clinical breast examinations. Income and race did not appear to play a role in health behaviors in our study. Future research will elucidate the impact of the Affordable Care Act on such health behaviors, as individuals will presumably have greater access to energy balance interventions and cancer screening. Although individuals may engage in health behaviors as a way to decrease healthcare costs, educational efforts and preventive interventions that accompany the Act may result in improved overall well-being. Perceived treatment efficacy was positively related to diet and vitamin use but not to exercise or cancer screening. The association is supported by the SRM18; those who have beliefs consistent with a health behavior are more likely to engage in the given behavior. Our results contrast with previous studies indicating that self-efficacy was predictive of exercise behavior.37 Yet, those studies were limited to recently diagnosed patients, and they did not focus on perceived treatment efficacy to prevent or delay cancer, further supporting the theoretical assertion that self-efficacy and perceived treatment efficacy are 2 unique constructs. Rather than efficacy, perceived risk of recurrence appeared to be a better predictor of exercise behavior. Women who believed their risk of recurrence was higher than average were less likely to exercise, perhaps indicating that they believed their risk was so high that engaging in
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Kelly et al
exercise would not help. Thus, although the overall findings support the role of the cognitive representation in health behavior, different beliefs (ie, self-relevance of the health threat vs treatment efficacy) were associated with different behaviors. Along with beliefs, the SRM also posits that affect is a key predictor of behavior.23 This was only true of mammograms. Women who were more distressed were more likely to have mammograms, consistent with cancer screening in women who are unaffected with cancer.52 The lack of findings in this case may indicate a floor effect, as distress was quite low in the sample, with little variance. It is possible that a closer relationship between distress and health behavior would be observed in a sample with higher distress. Limitations to the current study should be noted. To begin, the study was cross-sectional and retrospective in nature, which may be subject to recall bias. Furthermore, we relied on self-report data, and participants may overestimate the amount of health behaviors in which they engage. This is less important in modeling of behavior, unless overestimates vary systematically with particular psychosocial characteristics.
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Conclusion
Individuals currently under treatment are less likely to engage in health behaviors than those who have completed treatment. It is possible that health behavior interventions may help those in active treatment to more effectively manage the rigors of cancer treatment, as well as decrease their risk for recurrence. This is clearly an identified need of cancer patients. In clinical practice, nursing interventions may help this population in terms of both psychological coping and physical management of the disease. Furthermore, our data support the importance of treatment efficacy beliefs, a cognitive factor in the SRM, in the health behaviors of cancer patients. Thus, to have the greatest impact, clinical interventions to improve health behaviors in this population should endeavor to (1) increase patients’ beliefs in the efficacy of the health behavior, if merited, to prevent and delay cancer and (2) clarify the sometimes bewildering number of studies with apparently inconsistent results regarding the treatment efficacy of health behaviors. Along with perceived treatment efficacy, perceived risk may be critical to increasing physical activity, and these 2 factors may go hand-in-hand in improving health behavior. Although increasing perceived risk and perceived treatment efficacy may follow from these results, care should be exercised in interventions that endeavor to motivate by increasing distress levels. Excessively elevated distress levels may lead to decreased quality of life and to overutilization of mammograms. Along with psychosocial factors, access to healthcare and education to accomplish health behaviors are key, and these activities may be supported by the Affordable Care Act in the United States in its effort to prevent future disease. Finally, in any nursing intervention, contextual factors (eg, rural areas that may affect access) are very important, and this continues to be a concern for individuals currently undergoing treatment or who have completed treatment.
Health Behaviors Among Cancer Survivors
ACKNOWLEDGMENT
The authors would like to acknowledge Mayank Ajmera, MS, for his assistance with the preparation of the Table.
References 1. American Cancer Society. Cancer Facts and Figures. 2013. http://www .cancer.org/downloads/STT/CAFF_finalPWSecured.pdf. Accessed May 20, 2013. 2. Helgeson VS, Cohen S. Social support and adjustment to cancer: reconciling descriptive, correlational, and intervention research. Health Psychol. 1996;15(2):135Y148. 3. Lam WW, Chan M, Or A, Kwong A, Suen D, Fielding R. Reducing treatment decision conflict difficulties in breast cancer surgery: a randomized controlled trial. J Clin Oncol. 2013;31(23):2879Y2885. 4. Holt S, Bertelli G, Humphreys I, et al. A decision impact, decision conflict and economic assessment of routine Oncotype DX testing of 146 women with node-negative or pNImi, ER-positive breast cancer in the U.K. Br J Cancer. 2013;108(11):2250Y2258. 5. Drug & Therapeutics Bulletin. An introduction to patient decision aids. BMJ. 2013;347:f4147. 6. Deimling GT, Bowman KF, Sterns S, Wagner LJ, Kahana B. Cancer-related health worries and psychological distress among older adult, long-term cancer survivors. Psychooncology. 2006;15(4):306Y320. 7. National Cancer Institute. Adjustment to cancer: anxiety and distress. http:// www.cancer.gov/cancertopics/pdq/supportivecare/adjustment/HealthProfessional/ page2. Accessed May 20, 2013. 8. Custers JA, van den Berg SW, van Laarhoven HW, Bleiker EM, Gielissen MF, Prins JB. The cancer worry scale: detecting fear of recurrence in breast cancer survivors. Cancer Nurs. 2014;37(1):E44YE50. 9. Lu MH, Lin HR, Lee MD. The experiences among older Taiwanese women facing a new diagnosis of breast cancer. Cancer Nurs. 2010;33(5):398Y405. 10. Kelly KM, Shedlosky-Shoemaker R, Porter K, DeSimone P, Andrykowski M. Cancer recurrence worry, risk perception, and informational coping among Appalachian oncology patients. J Psychosoc Oncol. 2011;29(1):1Y18. 11. Simard S, Thewes B, Humphris G, et al. Fear of cancer recurrence in adult cancer survivors: a systematic review of quantitative studies. J Cancer Surviv. 2013;7(3):300Y322. 12. Costanzo ES, Lutgendorf SK, Mattes ML, et al. Adjusting to life after treatment: distress and quality of life following treatment for breast cancer. Br J Cancer. 2007;97(12):1625Y1631. 13. Documet PI, Trauth JM, Key M, Flatt J, Jernigan J. Breast cancer survivors’ perception of survivorship. Oncol Nurs Forum. 2012;39(3):309Y315. 14. Hoffman RM, Lewis CL, Pignone MP, et al. Decision-making processes for breast, colorectal, and prostate cancer screening: the DECISIONS survey. Med Decis Making. 2010;30(suppl 5):53SY64S. 15. Bellizzi KM, Rowland JH, Jeffery DD, McNeel T. Health behaviors of cancer survivors: examining opportunities for cancer control intervention. J Clin Oncol. 2005;23(34):8884Y8893. 16. US Department of Health & Human Services. Key features of the Affordable Care Act. http://www.hhs.gov/healthcare/facts/timeline/index.html. Accessed July 17, 2013. 17. Hovland C, Rosenberg M, eds. Attitude Organization and Change. New Haven, CT: Yale University Press; 1960. 18. Leventhal H, Benyamini Y, Brownlee S, Diefenbach M, Leventhal EA, Patrick-Miller L. Illness representation: theoretical foundations. In: Weinman J, Petrie K, eds. Perceptions of Health and Illness. London, UK: Harwood Publishers; 1997:19Y45. 19. Leventhal H, Brisette I, Leventhal E. The common-sense model of selfregulation of health and illness. In: Cameron LD, Leventhal H, eds. The Selfregulation of Health and Illness Behaviour. London, UK: Routledge; 2003: 42Y65. 20. Quach J, Porter K, Leventhal H, Kelly K. Health behaviors among Ashkenazi Jewish individuals receiving counseling for BRCA1 and BRCA2 mutations. Fam Cancer. 2009;8(3):241Y250. 21. Leventhal H, Kelly K, Leventhal E. Population risk, actual risk, perceived risk, and cancer control: a discussion. J Natl Cancer Inst Monogr. 1999;25:81Y85.
Cancer NursingTM, Vol. 38, No. 3, 2015
Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
n
E33
22. Cameron LD, Leventhal EA, Leventhal H. Symptom representations and affect as determinants of care seeking in a community-dwelling, adult sample population. Health Psychol. 1993;12(3):171Y179. 23. Hay JL, Buckley TR, Ostroff JS. The role of cancer worry in cancer screening: a theoretical and empirical review of the literature. Psychooncology. 2005; 14(7):517Y534. 24. George SM, Irwin ML, Smith AW, et al. Postdiagnosis diet quality, the combination of diet quality and recreational physical activity, and prognosis after early-stage breast cancer. Cancer Causes Control. 2011;22(4):589Y598. 25. Davies NJ, Batehup L, Thomas R. The role of diet and physical activity in breast, colorectal, and prostate cancer survivorship: a review of the literature. Br J Cancer. 2011;105(suppl 1):S52YS73. 26. Wolin KY, Colditz GA. Cancer and beyond: healthy lifestyle choices for cancer survivors. J Natl Cancer Inst. 2013;105(9):593Y594. 27. Maunsell E, Drolet M, Brisson J, Robert J, Deschenes L. Dietary change after breast cancer: extent, predictors, and relation with psychological distress. J Clin Oncol. 2002;20(4):1017Y1025. 28. Burris JL, Jacobsen PB, Loftus LS, Andrykowski MA. Breast cancer recurrence risk reduction beliefs in breast cancer survivors: prevalence and relation to behavior. Psychooncology. 2012;21(4):427Y435. 29. Nechuta S, Lu W, Chen Z, et al. Vitamin supplement use during breast cancer treatment and survival: a prospective cohort study. Cancer Epidemiol Biomarkers Prev. 2011;20(2):262Y271. 30. Saquib J, Rock CL, Natarajan L, et al. Dietary intake, supplement use, and survival among women diagnosed with early-stage breast cancer. Nutr Cancer. 2011;63(3):327Y333. 31. Burstein HJ, Gelber S, Guadagnoli E, Weeks JC. Use of alternative medicine by women with early-stage breast cancer. N Engl J Med. 1999;340(22): 1733Y1739. 32. Bertram LA, Stefanick ML, Saquib N, et al. Physical activity, additional breast cancer events, and mortality among early-stage breast cancer survivors: findings from the WHEL study. Cancer Causes Control. 2011;22(3): 427Y435. 33. Paxton RJ, Phillips KL, Jones LA, et al. Associations among physical activity, body mass index, and health-related quality of life by race/ethnicity in a diverse sample of breast cancer survivors. Cancer. 2012;118(16):4024Y4031. 34. Irwin ML, Crumley D, McTiernan A, et al. Physical activity levels before and after a diagnosis of breast carcinoma: the Health, Eating, Activity, and Lifestyle (HEAL) study. Cancer. 2003;97(7):1746Y1757. 35. Harper FWK, Schmidt JE, Beacham AO, et al. The role of social cognitive processing theory and optimism in positive psychosocial and physical behavior change after cancer diagnosis and treatment. Psychooncology. 2007;16(1): 79Y91. 36. Emery CF, Yang HC, Frierson GM, Peterson LJ, Suh S. Determinants of physical activity among women treated for breast cancer in a 5-year longitudinal follow-up investigation. Psychooncology. 2009;18(4):377Y386.
37. Mosher CE, Fuemmeler BF, Sloane R, et al. Change in self-efficacy partially mediates the effects of the FRESH START intervention on cancer survivors’ dietary outcomes. Psychooncology. 2008;17(10):1014Y1023. 38. Berry DA, Cronin KA, Plevritis SK, et al. Effect of screening and adjuvant therapy on mortality from breast cancer. N Engl J Med. 2005;353(17): 1784Y1792. 39. Field TS, Doubeni C, Fox MP, et al. Under utilization of surveillance mammography among older breast cancer survivors. J Gen Intern Med. 2008; 23(2):158Y163. 40. Doubeni CA, Field TS, Ulcickas Yood M, et al. Patterns and predictors of mammography utilization among breast cancer survivors. Cancer. 2006;106(11): 2482Y2488. 41. Breslau ES, Jeffery DD, Davis WW, Moser RP, McNeel TS, Hawley S. Cancer screening practices among racially and ethnically diverse breast cancer survivors: results from the 2001 and 2003 California health interview survey. J Cancer Surviv. 2010;4(1):1Y14. 42. Thewes B, Butow P, Bell ML, et al. Fear of cancer recurrence in young women with a history of early-stage breast cancer: a cross-sectional study of prevalence and association with health behaviours. Support Care Cancer. 2012; 20(11):2651Y2659. 43. Hesse-Biber SN. Mixed Methods Research: Merging Theory With Practice. New York, NY: The Guilford Press; 2010. 44. Miller WL, Crabtree BF. Clinical research. In: Denzin NK, Lincoln YS, eds. Handbook of Qualitative Research. Thousand Oaks, CA: Sage Publications; 2000:366Y378. 45. Creswell JW. Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Thousand Oaks, CA: Sage Publications; 1998. 46. Kelly KM, Leventhal H, Andrykowski M, et al. Using the Common Sense Model to understand perceived cancer risk in individuals testing for BRCA1/2 mutations. Psychooncology. 2005;14(1):34Y48. 47. Borkan J. Immersion/crystallization. In: Crabtree BF, Miller WL, eds. Doing Qualitative Research. 2nd ed. Thousand Oaks, CA: Sage Publications; 1999. 48. Miles MB, Huberman AM. Qualitative Data Analysis. Newbury Park, CA: Sage Publications; 1994:10Y12. 49. Beene-Harris RY, Wang C, Bach JV. Barriers to access: results from focus groups to identify genetic service needs in the community. Community Genet. 2007;10(1):10Y18. 50. Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol. 2001;19(4):980Y991. 51. Helyer LK, Chin S, Chui BK, et al. The use of complementary and alternative medicines among patients with locally advanced breast cancerVa descriptive study. BMC Cancer. 2006;6:39. 52. Stefanek ME, Wilcox P. First degree relatives of breast cancer patients: screening practices and provision of risk information. Cancer Detect Prev. 1991;15(5):379Y384.
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