Abstract
Background
Cancer patients often use complementary and alternative medicine (CAM) based on recommendations from family. However, the relationship between family endorsement of CAM and the patient’s expectation of its benefits has never been quantified.
Methods
Between 2010 and 2011, we conducted a cross-sectional survey study among patients with a diagnosis of cancer recruited from thoracic, breast, and gastrointestinal medical oncology clinics at a single academic cancer center. We performed multivariate linear regression analyses to evaluate the relationship between perceived family endorsement of and expected benefits from CAM, adjusting for covariates.
Results
Among the 962 participants, 303 (31.3%) reported family endorsement of CAM use. Younger patients and those who had college or higher education were more likely to report family endorsement (both p < 0.05). Patients with family support had expectation scores that were 15.9 higher than patients without family support (coefficient 15.9, 95% CI 13.5, 18.2, p < 0.001). Participants with family encouragement of CAM use were also more likely to expect CAM to cure their cancer (12 vs. 37%) and prolong their life (24 vs. 61%). These relationships remained highly significant after adjusting for covariates).
Conclusions
Family endorsement of CAM use is strongly associated with patient expectation of its clinical efficacy, including expectations for cure and improved survival. These findings underscore the importance of including family in counseling and education on CAM use in order to achieve realistic patient expectations, maximize benefits, and avoid potential medical adverse effects through herb-drug interactions or rejections of conventional care.
Keywords: Complementary, Alternative, CAM, Family support, Cancer
Introduction
Complementary and alternative medicine (CAM) use is prevalent among cancer patients and survivors. Up to 87% of patients with a diagnosis or history of cancer utilize a form of CAM [1–4], which includes modalities such as massage, mind-body medicine, botanical medicine, traditional Chinese medicine, and other traditional healing models often based on ancient practices. Research for some of these modalities, such as mindfulness meditation for anxiety or acupuncture for pain, has begun to highlight their benefits in the supportive management of cancer patients and survivors [5–7]. However, an absent evidence base for many CAM modalities often leads to increased skepticism and concern among oncologists and primary care providers about the safety and efficacy of CAM treatments.
Patients who are interested in CAM often interpret a provider’s discouragement of its use as a conflict between the patient’s own belief system and the “standard of care” [8]. Such conflict can not only strain the doctor-patient relationship but can also have a serious effect on the treatment choices patients make, such as delaying or abandoning conventional care [9–12]. In order to foster open provider-patient dialog around CAM use, it is important to both understand the various factors that influence a patient’s decision to pursue CAM and patient expectations regarding treatment efficacy.
Because CAM modalities are based on ancient and traditional healing methods transmitted within cultural circles [13], family members’ advice and recommendations for CAM use may hold great significance for patients. Indeed, among the many influencing factors, family and friends’ endorsement of CAM is considered to be a major predictive factor of its use [14–16]. For many cancer patients, the “social network” is the source of CAM-related information [17, 18]. Family endorsement of CAM, which is often based on anecdotal information, may also shape patients’ expectations of CAM’s benefits, ranging from the promise of wellness and relaxation to the hope for a cure for their cancer [16, 19]. Unrealistic expectations of its benefits, such as those for a cure or life prolongation, can lead to rejection of conventional care or adverse effects through unsupervised CAM use [2, 9, 12]. We conducted this study to evaluate the impact of patient-reported family endorsement of CAM on the expectations cancer patients bring to CAM use.
Material and methods
Study design and patients
Between June 2010 and September 2011, we conducted a cross-sectional survey study of 962 patients from the thoracic, breast, and gastrointestinal oncology clinics of the University of Pennsylvania, where we worked with collaborators. Patient eligibility was determined by the following criteria: age ≥18 years, primary diagnosis of cancer, Karnofsky performance score of ≥60, approval of the patient’s oncologist, and ability to understand the study requirements and provide informed consent in English. New patients and those unable to understand the study requirements were also excluded. Recruitment was conducted by trained research assistants who, after obtaining informed consent, administered self-report surveys. Each survey took approximately 20 min to complete, and patients were given a gift card for their participation. The Institutional Review Board of the Hospital of the University of Pennsylvania approved the study protocol.
Study variables
We measured the outcome, expected benefits related to CAM use, with the expected benefit domain of the Attitudes and Beliefs about CAM (ABCAM) instrument, which has been described in detail in a previous publication [20]. ABCAM is based on the Theory of Planned Behavior, and was developed to evaluate specific behavioral predictors of CAM use. The instrument was validated in an outpatient cancer population. The expected benefit domain has nine items. We rated each item on a five-point scale (1 = strongly disagree, 2 = disagree, 3 = not sure/not applicable, 4 = agree, 5 = strongly agree). We summed and normalized ratings, generating an overall “expectation score” between 0 and 100, with a higher score indicating greater expected benefit. In addition, to ease interpretation of each specific type of expectation, we then dichotomized the outcome with those who reported “agree” and “strongly agree” as having the specific expectation. We evaluated family endorsement of CAM use by asking patients to rate the statement, “My family encourages me to use CAM,” by selecting one of the following: 1 (strongly disagree), 2 (disagree), 3 (not sure/not applicable), 4 (agree), and 5 (strongly agree). We then dichotomized the patients, dividing them into those who reported family endorsement (4 and 5) and those who did not report family endorsement (1–3).
Covariates
We collected clinical and demographic variables by self-report and chart abstraction. We obtained demographic information, including age, gender, sex, education, and marital status, through patient self-report. Additionally, we collected the clinical characteristic of diagnosis, treatment (chemotherapy, radiation therapy, and surgery), stage of disease (localized versus metastatic disease), and months since treatment by chart review. We assessed active CAM use and dichotomized participants into those who had used CAM since diagnosis and those who had not used CAM since their diagnosis.
Statistical analyses
We presented descriptive data of participants’ socioeconomic characteristics such as gender; age; employment status; and disease information, including cancer type, time since cancer diagnosis, and family support, expectation scores, and specific expectation benefits. For categorized data, we presented the numbers and proportions of each group. We calculated the mean and standard deviation for continuous data such as age, time since cancer diagnosis, and expectation scores. We then performed univariate regression analysis to determine whether expectation scores differed based on family endorsement and patient characteristics. Next, we used multivariable regression models to determine whether family endorsement was associated with expectation when controlling for patient characteristics that also correlated with expectation in univariate regression models (if p < 0.2). The R2 of the models was calculated for comparison between the models. For specific expectations, we used chi-squared test and then multivariate logistic regression analyses to determine the relationship between family endorsement and specific expected benefit from CAM use. All analyses were conducted with two-sided tests. Because of the multiple outcomes examined, we reduced the p value to less than 0.005 to be considered statistical significant. Analyses were performed using SPSS 24 (IBM Corp.) (Fig. 1).
Fig. 1.
Specific expectations and family support distribution
Results
Among the 1188 patients approached consecutively, 1068 (89.9%) agreed to participate and 120 (10.1%) declined participation. Reasons for declining included inability to complete the survey due to lack of time or sickness (21 patients, 1.8%) and not wanting to participate in research (99 patients, 8.3%). In addition, 31 patients withdrew consent, 33 did not return the survey, and 35 were excluded from the analysis due to incomplete data. Thus, 969 patients formed the final sample size, reflecting a response rate of 81.6% among eligible subjects.
Among all patients, 608 (63.4%) were female, with a mean age of 59 ± 12 years; 758 (78.9%) of the patients were white; and 715 (74.5%) had at least a college education. The major cancer types were breast (33%), gastrointestinal (32%), and lung (31%) cancer. Over half of the participants were early stage cancer survivors (55%), while the majority had been diagnosed within 1 year prior to the survey (45%). Of the respondents, 58.5% had used some form of CAM since their diagnosis (see Table 1). The prevalence of use of specific CAM modalities in this population has been reported in detail previously [20].
Table 1.
Family support and demographic/clinical variables (n = 962)
| n (%) | Family supports CAM use, n (%) | P value | |
|---|---|---|---|
| Age (years) | |||
| > 65 | 306 (32) | 79 (26) | 0.005 |
| 56–65 | 300 (31) | 91 (30) | |
| ≤ 55 | 356 (37) | 133 (37) | |
| Gender | |||
| Male | 354 (37) | 97 (27) | 0.037 |
| Female | 608 (63) | 206 (34) | |
| Race | |||
| White | 758 (79) | 244 (32) | 0.39 |
| Non-white | 203 (21) | 59 (29) | |
| Education | |||
| High school or less | 245 (26) | 52 (21) | < 0.001 |
| College or above | 715 (74) | 250 (35) | |
| Marital status | |||
| Not married | 292 (72) | 87 (30) | 0.38 |
| Married/living with partner | 652 (28) | 213 (33) | |
| Cancer type | |||
| Breast | 313 (33) | 115 (37) | 0.072 |
| Gastrointestinal | 312 (32) | 96 (31) | |
| Lung | 294 (31) | 79 (27) | |
| Other | 42 (4) | 13 (31) | |
| Cancer stage | |||
| Localized disease | 522 (55) | 157 (30) | 0.27 |
| Metastatic disease | 431 (45) | 144 (33) | |
| Surgery | |||
| No | 354 (37) | 108 (30) | 0.67 |
| Yes | 603 (63) | 192 (32) | |
| Radiation | |||
| No | 499 (52) | 161 (32) | 0.52 |
| Yes | 458 (48) | 139 (30) | |
| Chemotherapy | |||
| No | 140 (15) | 45 (32) | 0.83 |
| Yes | 817 (85) | 255 (31) | |
| Months since diagnosis | |||
| ≤ 12 months | 431 (45) | 136 (32) | 0.66 |
| > 12 and ≤ 36 months | 240 (25) | 70 (29) | |
| > 36 months | 280 (30) | 92 (33) | |
| CAM use | |||
| Yes | 566 (59) | 236 (42) | < 0.001 |
| No | 401 (41) | 66 (17) |
Statistically significant p values highlighted in italic numbers
In univariate analysis, among all patients, 303 (31.3%) reported that their family encouraged them to use CAM for cancer care (see Table 1). Patients age ≤ 55 years had more family support than patients aged 56–65 or > 65 years (37 vs. 30% and 26%, p = 0.005). In addition, female and higher educated patients had more family enthusiasm for CAM use than male (34 vs. 27%, p = 0.037) and lower educated patients (35 vs. 21%, p < 0.001). Patients who had previously used CAM had more family support (42 vs. 17%, p < 0.001).
Family endorsement and expectation of benefits score
Among all patients, the mean expectation score (SD) for CAM use was 60.68 ± 19.49. The expectation score increased sequentially as patients endorsed family support for CAM use: “strongly disagree” (37.6 ± 28.3), “disagree” (56.3 ± 17.6), “not sure” (58.9 ± 14.7), “agree” 70.8 ± 15.1), and “strongly agree” (83.4 ± 19.8). Patients whose families encouraged CAM use had a higher expectation score than those patients who did not have family encouragement (73.6 ± 17.0 vs. 56.5 ± 17.7, p < 0.001).
In addition, patients who were female, age ≤55 years, and higher educated had higher expectation scores than others (all p < 0.05; Table 2). Patients with a diagnosis of breast cancer had higher expectations for CAM use than patients with other cancer types (p < 0.001). Patients who had undergone surgery for cancer and those who had a prolonged cancer course also had higher expectation scores (p = 0.011 and 0.0071, respectively; Table 2).
Table 2.
Expected benefits and demographic/clinical variables
| Number | Expected benefit |
||
|---|---|---|---|
| Mean (SD) | P value | ||
| Age (years) | |||
| > 65 | 306 | 57.6 (19.7) | < 0.001 |
| 56–65 | 302 | 62.1 (17.7) | |
| ≤ 55 | 356 | 65.5 (19.3) | |
| Gender | |||
| Male | 354 | 56.3 (19.2) | < 0.001 |
| Female | 610 | 65.2 (18.5) | |
| Race | |||
| White | 758 | 61.8 (19.3) | 0.76 |
| Non-white | 205 | 62.3 (18.8) | |
| Education | |||
| High school or less | 246 | 57.3 (18.6) | < 0.001 |
| College or above | 716 | 63.5 (19.2) | |
| Marital status | |||
| Not married | 292 | 61.6 (19.1) | 0.70 |
| Married/living with partner | 654 | 62.1 (19.4) | |
| Cancer type | |||
| Breast | 315 | 67.9 (17.6) | < 0.001 |
| Gastrointestinal | 313 | 59.4 (18.9) | |
| Lung | 293 | 58.9 (19.7) | |
| Other | 42 | 57.1 (19.6) | |
| Cancer stage | |||
| Localized disease | 524 | 62.3 (19.5) | 0.49 |
| Metastatic disease | 431 | 61.5 (19.0) | |
| Surgery | |||
| No | 354 | 59.8 (18.2) | 0.011 |
| Yes | 605 | 63.1 (19.7) | |
| Radiation | |||
| No | 501 | 62.2 (18.6) | 0.62 |
| Yes | 458 | 61.6 (20.0) | |
| Chemotherapy | |||
| No | 141 | 62.2 (20.3) | 0.85 |
| Yes | 818 | 61.9 (19.1) | |
| Months since diagnosis | |||
| ≤ 12 months | 432 | 59.8 (20.0) | 0.0071 |
| > 12 and ≤ 36 months | 240 | 63.3 (19.3) | |
| > 36 months | 281 | 64.0 (17.7) | |
| Family support | |||
| No | 659 | 56.5 (17.7) | < 0.001 |
| Yes | 302 | 73.6 (17.0) | |
Statistically significant p values highlighted in italic numbers
In multivariate regression models, patients with family support had 15.9 higher expectation scores than patients without family support (coefficient 15.9, 95% CI 13.5, 18.2, p < 0.001; see Table 3). In addition, younger age, being female, having a college or greater degree, and having been diagnosed more than 12 months previously were all associated with increased expected benefit from CAM use. The model incorporating family support had a pseudo-R2 of 0.23, indicating that model 2 (Table 3) substantially explained more variance (1.56 times) about patients’ expectations to the use of CAM for cancer care than model 1 (Table 3) without the family support factor. The magnitude of variance explained by family support is greater than all other sociodemographic and clinical factors combined.
Table 3.
Multivariate models for expectation scores with or without family support
| Univariate |
Model 1 |
Model 2 |
|||||||
|---|---|---|---|---|---|---|---|---|---|
| Coefficient | 95% CI | p Value | Coefficient | 95% CI | p Value | Coefficient | 95% CI | p Value | |
| Family support | |||||||||
| No | – | – | – | – | – | – | – | – | – |
| Yes | 17.0 | 14.7, 19.4 | < 0.001 | – | – | – | 15.9 | 13.5, 18.2 | < 0.001 |
| Age (years) | |||||||||
| > 65 | – | – | – | – | – | – | – | – | – |
| 56–65 | 4.5 | 1.5, 7.5 | 0.004 | 2.8 | − 0.2, 5.8 | 0.071 | 2.7 | − 0.1, 5.4 | 0.060 |
| ≤ 55 | 7.0 | 5.0, 10.8 | < 0.001 | 4.7 | 1.6, 7.7 | 0.003 | 3.4 | 0.7, 6.2 | 0.015 |
| Gender | |||||||||
| Male | – | – | – | – | – | – | – | – | – |
| Female | 8.9 | 6.4, 11.4 | < 0.001 | 6.0 | 3.0, 9.0 | < 0.001 | 5.4 | 2.6, 8.1 | < 0.001 |
| Education | |||||||||
| High school or less | – | – | – | – | – | – | – | – | – |
| College or above | 6.2 | 3.4, 8.9 | < 0.001 | 4.7 | 2.0, 7.5 | 0.001 | 2.7 | 0.2, 5.3 | 0.038 |
| Cancer type | |||||||||
| Breast | – | – | – | – | – | – | – | – | – |
| Gastrointestinal | − 8.5 | − 11.5, − 5.6 | < 0.001 | − 3.2 | − 6.7, − 0.3 | 0.075 | − 3.2 | − 6.4, 0.01 | 0.051 |
| Lung | − 9.0 | − 12.0, − 6.1 | < 0.001 | − 3.7 | − 7.1, − 0.2 | 0.038 | − 3.1 | − 6.3, 0.06 | 0.055 |
| Other | − 10.8 | − 16.9, − 4.8 | < 0.001 | − 6.7 | − 12.8, − 0.5 | 0.034 | − 6.7 | − 12.4, − 1.0 | 0.020 |
| Surgery | |||||||||
| No | – | – | – | – | – | – | – | – | – |
| Yes | 3.3 | 0.7, 5.8 | 0.011 | 0.04 | − 2.6, 2.7 | 1.00 | 0.4 | − 2.0, 2.8 | 0.74 |
| Months since diagnosis | |||||||||
| ≤ 12 | – | – | – | – | – | – | – | – | – |
| > 12 and ≤ 36 | 3.5 | 0.5, 6.5 | 0.023 | 3.3 | 0.3, 6.2 | 0.031 | 3.3 | 0.6, 6.0 | 0.018 |
| > 36 | 4.2 | 1.3, 7.1 | 0.004 | 2.9 | 0.03, 5.9 | 0.048 | 2.8 | 0.08, 5.4 | 0.044 |
| R2 | 0.09 | 0.23 | |||||||
Statistically significant p values (>0.05) are highlighted in italic numbers
Specific expectations and family support
When considering the nine benefits of CAM use identified in ABCAM, respondents expected that CAM could help them to reduce stress (55%), cope with cancer (53%), and decrease emotional distress (52%). A few of them expected CAM to help cure their cancer (20%), help them to live longer (35%), or prevent future health problems (35%). Patients with perceived family encouragement for CAM use had a higher likelihood of expecting benefits in all nine areas, even when adjusted for covariants (all p < 0.001; Table 4).
Table 4.
Multivariate models family support vs. specific expected benefit
| Family support CAM use |
Family support CAM use |
|||
|---|---|---|---|---|
| Unadjusted OR (95% CI) | P value | Adjusted OR (95% CI) * | P value | |
| Decrease emotional distress | 4.9 (3.6 to 6.8) | < 0.001 | 4.7 (3.4 to 6.5) | < 0.001 |
| Reduce pain | 4.5 (3.3 to 6.0) | < 0.001 | 4.4 (3.2 to 5.8) | < 0.001 |
| Prevent future health problems | 4.4 (3.3 to 5.9) | < 0.001 | 4.4 (3.2 to 5.8) | < 0.001 |
| Help cope cancer | 5.9 (4.3 to 8.1) | < 0.001 | 5.7 (4.1 to 7.9) | < 0.001 |
| Improve physical health | 6.5 (4.7 to 8.9) | < 0.001 | 6.4 (4.7 to 8.8) | < 0.001 |
| Boost immune | 5.0 (3.7 to 6.7) | < 0.001 | 4.9 (3.6 to 6.6) | < 0.001 |
| Reduce stress | 5.1 (3.7 to 7.1) | < 0.001 | 4.9 (3.5 to 6.8) | < 0.001 |
| Help live longer | 5.1 (3.8 to 6.9) | < 0.001 | 5.2 (3.8 to 7.0) | < 0.001 |
| Help cure cancer | 4.4 (3.2 to 6.2) | < 0.001 | 4.7 (3.3 to 6.6) | < 0.001 |
Statistically significant p values (< 0.05) are highlighted in italic numbers.
Adjusted for education and age
Discussion
In this cross-sectional study of over 900 cancer patients, we found that family endorsement of CAM use was associated with increased expectations for its health benefits. We also found that positive expectations of CAM, including unrealistic expectations, such as those for cancer cure or an increase in life expectancy through CAM use, were strongly correlated with patient-reported family endorsement of CAM use. In the pursuit of patient-centered care, increasing provider awareness of this relationship may have important implications for effective communication about CAM use in the context of cancer care. It may also provide the basis for shared decision-making that ultimately improves the care and safety of patients with cancer.
Our findings contribute to a limited but growing body of literature documenting the role of family in a cancer patient’s decision to use CAM. This is in line with previous observations indicating that the decision-making process preceding CAM use is highly influenced by a patient’s social network, made up predominantly of family and friends [14, 15, 18, 21]. In a survey of a general obstetrics/gynecology patient population and a review of CAM use in breast cancer patients, family and friends were considered to be the patient’s main source of information regarding CAM, exceeding the influence of the Internet, books, or health care providers [17, 18]. A descriptive study of women with breast cancer found that patients experiencing impairment, such as fatigue and side effects of conventional cancer treatment, might be prompted to neglect their own research and fully rely on their social network and family for advice about CAM [14]. The decision to use CAM often bypasses health care providers and remains confined to the patient’s social network [22]. For example, a study of breast cancer patients who perceived their health care providers as being uninformed or having negative attitudes towards complementary therapies did not seek their advice regarding CAM and relied more on their social network [23].
Unrealistic expectations of CAM use can be harmful as they may create a chasm between conventional care and complementary or alternative therapies. This chasm can further foster alienation and frustration among patients, potentially driving them to reject treatment or have poor adherence. Based on previous descriptive studies, patients who harbor unrealistic expectations and whose social networks support CAM use are potentially at risk to abandon, delay, or interrupt cancer treatment in favor of CAM use, possibly affecting their prognosis and outcome [9, 10, 12, 22]. We have previously demonstrated that expected benefit is a major behavioral determinate of CAM use [20]. In this study, we demonstrate the important impact of family endorsement on such expectancy.
We found that the full range of positive expectations towards CAM correlated significantly with perceived family endorsement. Among the surveyed expectations of CAM use, those that indicated a hope for cure or increased life expectancy as a result of using CAM may point towards unrealistic perspectives. It thus seems particularly crucial to identify patients who are at risk to reject conventional treatment. This study highlights a risk profile of patients holding these unrealistic expectations. This subgroup of patients is likely to benefit most from patient-centered counseling and education in regards to both CAM modalities and conventional treatment, with inclusion of family members in the shared decision-making process. To address this particular risk group, providers may consider actively inquiring with patients about their use and expectations of CAM modalities as well as including family and friends in counseling about CAM use. Referral to integrative medicine specialists who are knowledgeable about safe CAM use in the cancer setting may additionally foster trust in a shared decision-making process and help facilitate setting realistic expectations in patients and family members alike.
We need to acknowledge several limitations of this study. While the overall response rate is high, there is still the possibility of selection bias. Because our measurement of family support relied on only one item, it may not capture all nuances of family endorsement of CAM, such as identifying information, purchasing products (e.g., supplements, herbs) or services (e.g., acupuncture, massage), or providing emotional pressure for using specific therapies. Our study relied on patients’ perceptions of family endorsement of CAM use. Since we did not survey the families, we cannot verify patients’ perceptions, and thus, we may not have adequately captured families’ views about CAM. Our study was conducted in a major academic center with predominantly white participants. Additional research is needed in more diverse populations (e.g., racial-ethnic minorities, immigrants).
Conclusions
Despite these limitations, our study has numerous strengths, including a large sample of cancer patients with different tumor types and a validated measure of expected benefit of CAM. To our knowledge, this is the first study to quantify the association between family endorsement of CAM use and patient expectations. Considering the observed importance of family influence, the inclusion of family in educational efforts regarding CAM use is pertinent to ensure realistic expectations in cancer patients. By involving family members in a shared decision-making process, we can help direct patients to CAM use that is supported by evidence and minimize CAM use where there is potential for harm, thereby increasing health outcomes and positive experiences for patients.
Acknowledgements
The study was supported in part by the MSK Integrative Medicine and Translational Research Grant and by the Byrne Fund of Memorial Sloan Kettering Cancer Center. This research was also funded in part by the National Cancer Institute (NCI) Cancer Center Support Grant P30 CA008748. The funding agencies had no role in the design or conduct of the study.
Footnotes
Compliance with ethical standards
Conflicts of interest The authors declare that they have no conflict of interest.
References
- 1.Zachariae R (2016) Complementary and alternative medicine use among patients with cancer: a challenge in the oncologist-patient relationship. JAMA Oncol 2(9):1177–1178. 10.1001/jamaoncol.2016.0713 [DOI] [PubMed] [Google Scholar]
- 2.Cassileth BR, Vickers AJ (2005) High prevalence of complementary and alternative medicine use among cancer patients: implications for research and clinical care. J Clin Oncol 23(12):2590–2592. 10.1200/JCO.2005.11.922 [DOI] [PubMed] [Google Scholar]
- 3.Horneber M, Bueschel G, Dennert G, Less D, Ritter E, Zwahlen M (2012) How many cancer patients use complementary and alternative medicine: a systematic review and meta-analysis. Integr Cancer Ther 11(3):187–203. 10.1177/1534735411423920 [DOI] [PubMed] [Google Scholar]
- 4.Velicer CM, Ulrich CM (2008) Vitamin and mineral supplement use among US adults after cancer diagnosis: a systematic review. J Clin Oncol 26(4):665–673. 10.1200/JCO.2007.13.5905 [DOI] [PubMed] [Google Scholar]
- 5.Bower JE, Crosswell AD, Stanton AL et al. (2015) Mindfulness meditation for younger breast cancer survivors: a randomized controlled trial. Cancer 121(8):1231–1240. 10.1002/cncr.29194 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Cramer H, Rabsilber S, Lauche R, Kummel S, Dobos G (2015) Yoga and meditation for menopausal symptoms in breast cancer survivors—a randomized controlled trial. Cancer 121(13): 2175–2184 [DOI] [PubMed] [Google Scholar]
- 7.Mao JJ, Farrar JT, Bruner D et al. (2014) Electroacupuncture for fatigue, sleep, and psychological distress in breast cancer patients with aromatase inhibitor-related arthralgia: a randomized trial. Cancer 120(23):3744–3751. 10.1002/cncr.28917 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Tasaki K, Maskarinec G, Shumay DM, Tatsumura Y, Kakai H (2002) Communication between physicians and cancer patients about complementary and alternative medicine: exploring patients’ perspectives. Psychooncology 11(3):212–220. 10.1002/pon.552 [DOI] [PubMed] [Google Scholar]
- 9.Citrin DL, Bloom DL, Grutsch JF, Mortensen SJ, Lis CG (2012) Beliefs and perceptions of women with newly diagnosed breast cancer who refused conventional treatment in favor of alternative therapies. Oncologist 17(5):607–612. 10.1634/theoncologist.2011-0468 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Shumay DM, Maskarinec G, Kakai H, Gotay CC (2001) Why some cancer patients choose complementary and alternative medicine instead of conventional treatment. J Fam Pract 50(12):1067. [PubMed] [Google Scholar]
- 11.Singh H, Maskarinec G, Shumay DM (2005) Understanding the motivation for conventional and complementary/alternative medicine use among men with prostate cancer. Integr Cancer Ther 4(2): 187–194. 10.1177/1534735405276358 [DOI] [PubMed] [Google Scholar]
- 12.Chang EY, Glissmeyer M, Tonnes S, Hudson T, Johnson N (2006) Outcomes of breast cancer in patients who use alternative therapies as primary treatment. Am J Surg 192(4):471–473. 10.1016/j.amjsurg.2006.05.013 [DOI] [PubMed] [Google Scholar]
- 13.Lee MM, Lin SS, Wrensch MR, Adler SR, Eisenberg D (2000) Alternative therapies used by women with breast cancer in four ethnic populations. J Natl Cancer Inst 92(1):42–47. 10.1093/jnci/92.1.42 [DOI] [PubMed] [Google Scholar]
- 14.Balneaves LG, Truant TL, Kelly M, Verhoef MJ, Davison BJ (2007) Bridging the gap: decision-making processes of women with breast cancer using complementary and alternative medicine (CAM). Support Care Cancer 15(8):973–983. 10.1007/s00520-007-0282-3 [DOI] [PubMed] [Google Scholar]
- 15.Hall JD, Bissonette EA, Boyd JC, Theodorescu D (2003) Motivations and influences on the use of complementary medicine in patients with localized prostate cancer treated with curative intent: results of a pilot study. BJU Int 91(7):603–607. 10.1046/j.1464-410X.2003.04181.x [DOI] [PubMed] [Google Scholar]
- 16.Boon H, Brown JB, Gavin A, Kennard MA, Stewart M (1999) Breast cancer survivors’ perceptions of complementary/alternative medicine (CAM): making the decision to use or not to use. Qual Health Res 9(5):639–653. 10.1177/104973299129122135 [DOI] [PubMed] [Google Scholar]
- 17.Furlow ML, Patel DA, Sen A, Liu JR (2008) Physician and patient attitudes towards complementary and alternative medicine in obstetrics and gynecology. BMC Complement Altern Med 8(1):35–35. 10.1186/1472-6882-8-35 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Wanchai A, Armer JM, Stewart BR (2010) Complementary and alternative medicine use among women with breast cancer: a systematic review. Clin J Oncol Nurs 14(4):E45–E55. 10.1188/10.CJON.E45-E55 [DOI] [PubMed] [Google Scholar]
- 19.Bishop FL, Yardley L, Lewith GT (2008) Treat or treatment: a qualitative study analyzing patients’ use of complementary and alternative medicine. Am J Public Health 98(9):1700–1705. 10.2105/AJPH.2007.110072 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Bauml JM, Chokshi S, Schapira MM et al. (2015) Do attitudes and beliefs regarding complementary and alternative medicine impact its use among patients with cancer? A cross-sectional survey. Cancer 121(14):2431–2438 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Naja F, Fadel RA, Alameddine M, Aridi Y, Zarif A, Hariri D, Mugharbel A, Khalil M, Nahleh Z, Tfayli A (2015) Complementary and alternative medicine use and its association with quality of life among Lebanese breast cancer patients: a cross-sectional study. BMC Complement Altern Med 15(1):444 10.1186/s12906-015-0969-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Verhoef MJ, White MA (2002) Factors in making the decision to forgo conventional cancer treatment. Cancer Pract 10(4):201–207. 10.1046/j.1523-5394.2002.104002.x [DOI] [PubMed] [Google Scholar]
- 23.Truant T, Bottorff JL (1999) Decision making related to complementary therapies: a process of regaining control. Patient Educ Couns 38(2):131–142. 10.1016/S0738-3991(99)00060-9 [DOI] [PubMed] [Google Scholar]