Journal of Health Communication, 20:204–210, 2015 Copyright # Taylor & Francis Group, LLC ISSN: 1081-0730 print/1087-0415 online DOI: 10.1080/10810730.2014.921742
Socioeconomic and Sociodemographic Predictors of Cancer-Related Information Sources Used by Cancer Survivors DANIELLE BLANCH-HARTIGAN1 and KASISOMAYAJULA VISWANATH2,3 1
Department of Natural and Applied Sciences, Bentley University, Waltham, Massachusetts, USA Harvard School of Public Health, Boston, Massachusetts, USA 3 Dana-Farber Cancer Institute, Boston, Massachusetts, USA 2
With 14 million cancer survivors in the United States, identifying and categorizing their use of sources of cancer-related information is vital for targeting effective communications to this growing population. In addition, recognizing socioeconomic and sociodemographic differences in the use of cancer-related information sources is a potential mechanism for reducing health disparities in survivorship. Fourteen sources of information survivors (N ¼ 519) used for cancer-related information were factor-analyzed to create a taxonomy of source use. The association between social determinants and use of these source types was analyzed in regression models. Factor analysis revealed 5 categories of information source use (mass media; Internet and print; support organizations; family and friends; health care providers), and use varied based on sociodemographic and socioeconomic characteristics. Higher education predicted increased use of all source categories except mass media. African American cancer survivors turned to health care providers as a source for cancer-related information less often than did White survivors. Social determinants predicted differences in the type of cancer-related information sources used. Providers and health communicators should target communication platforms based on the demographic profile of specific survivor audiences.
Patients’ health information–seeking behaviors are typically defined as an active, goal-oriented activity, in which an individual seeks information about health, often in response to a health event and often related to a specific topic (Anker, Reinhart, & Feeley, 2011; Galarce et al., 2011; Kelly et al., 2010; Niederdeppe & Levy, 2007). In the patient-centered model of care, providers and patients are encouraged to share responsibility for treatment and decision making (Beach & Inui, 2006; Mead & Bower, 2000) and patients’ health information–seeking is an important component of shared decision making. Information seeking in cancer patients is associated with taking a more active role in their care (Lee, Gray, & Lewis, 2010) and engaging in healthpromoting behaviors (Ramirez, Freres, et al., 2013). Health Information Seeking Behavior in Cancer Survivors There is a wealth of research about health information– seeking in general populations (Anker et al., 2011) and for cancer patients and caregivers in the prevention, detection, diagnosis, and treatment phases of the cancer continuum (Ramanadhan & Viswanath, 2006; Rutten, Arora, Bakos, Address correspondence to Danielle Blanch-Hartigan, Department of Natural and Applied Sciences, Bentley University, Jennison 100, 175 Forest Street, Waltham, MA 02452, USA. E-mail: [email protected]
Aziz, & Rowland, 2005). However, less research has focused on health information–seeking behavior in cancer survivors (Galarce et al., 2011; Rutten et al., 2005). Cancer survivors in the United States number more than 14 million and account for approximately 4% of the population (Howlader, 2011). This sizeable group has unique health care needs including the prevention and detection of recurrence and management of physical and psychosocial effects of treatment; needs which are often left unmet in the transition from active treatment to survivorship (Hewitt et al., 2006). To adequately address these needs and develop effective communication for this population, we must understand the health information–seeking behaviors of cancer survivors. Survivors’ information needs are different from those in earlier stages of the cancer continuum (Eheman et al., 2009; Rutten et al., 2005; Squiers, Finney Rutten, Treiman, Bright, & Hesse, 2005). Survivors may adopt a more passive information-seeking style (Eheman et al., 2009) but are more likely to have sought cancer-related information compared with those without a history of cancer (Hesse, Arora, Burke Beckjord, & Finney Rutten, 2008). Information sought by cancer survivors differs from that of cancer patients and spans a variety of topics, including risk of cancer recurrence, quality of life, prevention, work, finance, and posttreatment complications (Beckjord et al., 2008; Galarce et al., 2011; Squiers et al., 2005).
205
Cancer Survivors’ Information Source Use Health Information Seeking Behavior and Health Disparities Differences in health outcomes by socioeconomic status (SES) and other sociodemographic characteristics are well documented (Berkman & Kawachi, 2000; Williams et al., 2012). Racial=ethnic disparities exist across the cancer continuum, from cancer prevention knowledge and beliefs (Ramirez, Rutten, et al., 2013) to survival and mortality outcomes (Bach et al., 2002; Robbins, Siegel, & Jemal, 2012). Cancer survivors with lower SES, or from medically underserved or rural communities experience poorer physical and psychological health outcomes (Aziz & Rowland, 2002; Weaver, Geiger, Lu, & Case, 2012). Understanding possible mechanisms behind these differences is paramount to reducing disparities. The Structural Influence Model of Health Communication suggests one pathway by which low SES may lead to poorer health outcomes is through inequalities in health communication (Viswanath, Ramanadhan, & Kontos, 2007). Social determinants such as low SES, mediated by sociodemographic factors such as age and gender, lead to differences in health communication—particularly less access and attention to health information, reduced health information seeking, and difficulties with information processing and use of health information. These differential health communication behaviors lead to disparities in health outcomes. For example, members of lower SES may actually acquire information at a slower pace than those of high SES. Information and attentional processing differences may explain why lower SES groups are less likely to engage in health behaviors and as a consequence may suffer worse health outcomes (Viswanath et al., 2007). Therefore, even in an environment rich in information, these groups may have a wide gap in knowledge (Viswanath, 2006). One way to mitigate health disparities is to close this knowledge gap through effective health communication (Viswanath et al., 2006). However, appropriate health information cannot be made available without first understanding the complete picture of health information–seeking behaviors. Research on health information–seeking behavior has increased dramatically in the past 20 years (Anker et al., 2011), and many studies have documented social determinants of cancer-related information needs and informationseeking behaviors in both the general population and in cancer patients (Kelly et al., 2010; Lee, Ramirez, Lewis, Gray, & Hornik, 2012; Nagler et al., 2010; Nguyen & Bellamy, 2006; Vanderpool, Kornfeld, Rutten, & Squiers, 2009). By comparison, relatively few studies have specifically examined socioeconomic and sociodemographic factors associated with health information–seeking behaviors of cancer survivors. Cancer survivors from racial=ethnic minorities report more information needs (Beckjord et al., 2008). However, survivors with lower SES are also less likely to report seeking health information (Hesse et al., 2008; Mayer et al., 2007; Ramanadhan & Viswanath, 2006). The pattern of topics sought by cancer survivors varies across SES (Galarce et al., 2011). Galarce and colleagues analyzed health information–seeking behavior of cancer survivors,
categorizing topics of information sought into four main categories: (a) disease=treatment, including the effects of cancer treatment and likelihood of survival; (b) self-care management, including diet, nutrition, and staying healthy; (c) health services, including information on doctors and health services available; and (d) work=finance, including financial assistance and employment issues. Survivors with less wealth and more debt were the most likely to seek information about work and finance issues. Individuals with lower education levels were less likely to report information seeking for disease=treatment, self-care management, and health services. Few studies focus specifically on sources of information seeking in survivors (Rutten et al., 2005). Younger survivors prefer the Internet over health care providers more often than do older survivors (Hesse et al., 2008). In a study of cancer patients and survivors, higher education level was associated with seeking more cancer treatment information from the Internet, mass media, and medical professionals, but not from nonmedical interpersonal sources like friends and family (Lee et al., 2012). The present analyses extend previous work on information-seeking behaviors in cancer survivors in two ways. First, we investigate which sources of information (Internet, health care providers, etc.) are used by survivors for cancer-related topics by creating a taxonomy for cancerrelated information sources based not on a priori defined categories but on survivors’ reported source use. In addition, this research extends work on social determinants of information source use by investigating how social determinants predict use of categories of information sources specifically in cancer survivors, expanding the work on communication inequalities in health with a particular focus on cancer survivors.
Method Participants and Procedure The data for this study come from a survey of cancer survivors who were a part of the Well-Informed, Thriving and Surviving study conducted in Eastern United States. The questionnaire explored factors of health information– seeking behavior in 519 survivors. To be eligible, participants had to be English or Spanish speaking, have been diagnosed with stage I, II, or III cancer within the past 5 years, with no evidence of tumor recurrence or metastatic disease, and had no treatment (chemotherapy or radiation therapy) within the last year. Respondents were on average 54 years old (SD ¼ 11.55, range ¼ 21–75), 73% female, and 81% White (Table 1). A questionnaire about health information–seeking behavior was mailed to randomly selected current and former patients of a major U.S. cancer center, with the permission of their physicians. Participants could respond by mail using the self-addressed postage-paid reply envelope, over the Internet, or by phone at a conveniently scheduled time. A $5 gift card was included with the questionnaire. There was a 66% response rate (Galarce et al., 2011). All study
206
D. Blanch-Hartigan and K. Viswanath
Table 1. Sociodemographic and socioeconomic characteristics of participants (N ¼ 519)
Table 1. Continued
n (%) or M (SD) Sociodemographic characteristics Age, M (SD), n ¼ 513 54.32 (11.55) Gender, n (%) Male 138 (26.6) Female 378 (73.3) Unreported 3 (.6) Race, n (%) Non-Hispanic White 420 (80.9) Non-Hispanic Black=African American 37 (7.1) Asian 15 (2.9) Hispanic 27 (5.2) Other=mixed race 16 (3.1) Unreported 4 (.8) Socioeconomic characteristicsa Income, n (%) $75,000 280 (53.9) Don’t know=refused=missing 63 (12.1) Own=rent home (n (%) Rent 72 (13.9) Own 373 (71.9) Not paying rent=mortgage 36 (6.9) Missing=don’t know 38 (7.3) Total savings=assets=property, n (%) $500,000 174 (33.5) Don’t know=refused=missing 135 (26.0) Time with no income, n (%) 1 year 197 (38.0) Missing 40 (7.7) Debt, n (%) $100,000 37 (7.1) Don’t know=refused=missing 100 (19.3) Highest level of education, n (%) Less than high school 18 (3.4) Grade 12 or GED (high school graduate) 61 (11.8) Some post–high school education 143 (27.6) College, 4 years or more (college graduate) 147 (28.3) Post graduate degree from college or university 147 (28.3) Unreported 3 (.6) (Continued )
n (%) or M (SD) Disease characteristics Cancer type, n (%) Breast Colorectal Head=neck Leukemia=blood Lung Lymphoma Prostate Other=don’t know=missing Stage at diagnosis, n (%) Stage I Stage II Stage III Stage IV Other=don’t know=missing
239 26 19 16 23 63 21 112
(46.1) (5.0) (3.7) (3.1) (4.4) (12.1) (4.0) (21.6)
166 119 82 15 137
(32.0) (22.9) (15.8) (2.9) (26.4)
a Wealth index includes the following items: income, own=rent home, total assets, and predicted amount of time person could live at current standard with loss of income. Not all participants chose to report this information. Debt index includes a single debt item.
materials and procedures were approved by the cancer center’s institutional review board and complied with HIPAA standards. Measures Information Sources Participants were asked ‘‘What sources have you used to get information about cancer? Please check all that apply.’’ Participants reported whether they used any of 15 possible sources of information: (a) one or more doctors, (b) another type of health care provider, (c) Internet, (d) family or friends who are in the medical field, (e) family or friends who are not in the medical field, (f) other cancer patients or survivors, (g) coworkers, (h) support groups, (i) pamphlets or books, (j) television, (k) radio, (l) public library, (m) resource center at a hospital or clinic, (n) cancer information or support organization, or (o) other sources. A time frame was not specified. Use of the source was scored 0 if they did not check the source and 1 if they reported using the source. Socioeconomic, Demographic, and Disease Characteristics Participants reported their age, race, gender, and highest level of education completed. Participants also reported cancer type and stage at diagnosis. To measure SES, wealth and debt indices were created from a series of questions about financial status using principal component analyses to yield normally distributed score coefficients, which were saved and analyzed as continuous indices (M ¼ 0, SD ¼ 1; Galarce et al., 2011). The wealth index included responses from four items: 1. Present value of total savings, assets, and property (including home) with response options from less than $500 to $500,000 or more.
207
Cancer Survivors’ Information Source Use 2. Total household income before taxes with response options ranging from under $10,000 to $75,000 or more. 3. Financial stability as measured by length of time the respondent could maintain current residence and standard of living without present income with response options less than 1 month to more than a year. 4. Home ownership status, with the following response options: ‘‘rent home,’’ ‘‘own home,’’ ‘‘not paying rent or mortgage,’’ and ‘‘don’t know.’’ The debt index was a single item: ‘‘Not counting your mortgage or car loans, what is the total amount of debt held by you and other family members living here, including student loans, credit card charges, medical or legal bills, or loans from relatives?’’ Response options were as follows: less than $2000; $2000–$4999; $5000–$9999; $10,000–$19,999; $20,000–$49,999; $50,000–$99,999; $100,000 or more; don’t know; and refused. Analyses To create source categories, the fourteen information sources (excluding ‘‘other’’) were subjected to a principal component analysis with varimax rotation and Kaiser normalization using pairwise deletion. The factors’ regression coefficients were saved as factor based scores and analyzed as continuous indicators (M ¼ 0, SD ¼ 1) of each respondent’s use of each of the source categories. To analyze social determinants of information source use, multiple linear regression models were used to analyze the influence of sociodemographic and socioeconomic predictors on the factored score for use of each information source category. Variables were entered into the model using a forced entry method with pairwise deletion. We did not include disease characteristics (stage at diagnosis and cancer type) in the model due to variation in response and the presence of missing data.
Results The most commonly reported information sources used by cancer survivors were doctor (79%) and the Internet (79%; Table 2). Other common sources of information included: other cancer patients (56%), pamphlets or books (55%), and family and friends who worked in the medical field (48%). Cancer-Related Information Source Categories Principal component analysis of the 14 sources yielded five categories of cancer-related information sources (eigenvalue > 1.0; factor loadings > 0.4) that explained 54.25% of the variance: (a) mass media (television, radio, public library), (b) Internet and print (Internet, pamphlets=books, resource center at hospital=clinic), (c) support organizations (support groups, cancer information or support organization), (d) family and friends (family=friends in medicine, family= friends not in medicine, coworkers, other cancer patients= survivors), and (e) health care providers (doctors, other health care providers).
Table 2. Sources of health information and reported use (n ¼ 519) Source categoriesa 1. Health care providers One or more doctors Another type of health care provider 2. Family=friends Family or friends in the medical field Family or friends not in the medical field Other cancer patients or survivors Coworkers 3. Mass media Television Radio Public library 4. Internet and print Internet Pamphlets=books Resource center at a hospital=clinic 5. Support organizations Support groups Cancer information or support organization Other sourcesb No information sources=nonseeker a b
Use, n (%) 411 (79) 69 (13) 247 162 288 70
(48) (31) (56) (14)
96 (19) 31 (6) 50 (10) 409 (79) 285 (55) 133 (26) 73 94 27 18
(14) (18) (5) (4)
Categories created using principal component analysis. Not included in principal component analysis.
Predictors of Source Categories Sociodemographic and socioeconomic differences existed in use of these five information source categories (Table 3). Mass Media Older and female survivors reported greater use of mass media sources for health information. Hispanic survivors had significantly greater use of mass media sources than White survivors. Internet and Print Female survivors used Internet and print sources more than male survivors. Older survivors also reported marginally greater use of this source category. Compared to those with post graduate degrees, those survivors with high school education or less than high school education reported significantly less use of the Internet and print sources for cancer-related information. Support Organizations Male survivors and those with high school degree sought less information from support organizations than female survivors and those with postgraduate degrees. Family and Friends Female survivors reported greater use than male survivors of family and friends as a source of cancer-related information. Health Care Providers Race emerged as the strongest predictor of use of health care providers. African American survivors turned to health care
208
D. Blanch-Hartigan and K. Viswanath
Table 3. Sociodemographic and socioeconomic predictors of categories of sources used for cancer-related information (standardized bs) Source category Health care providers Sociodemographic predictors Age Gendera Raceb African American Asian Hispanic Other=mixed race Socioeconomic predictors Wealth indexc Debt Educationd Four-year college Some college High school=GED Less than high school
–.05 .02
Friends= family
Mass media
Internet=print
Support organizations
–.01 .10
.10 .17
–.09þ .10
–.06 .12
–.15 –.01 –.03 –.05
.03 –.03 –.05 –.01
.08 –.01 .10 .04
–.003 –.03 –.07 .02
.07 –.04 –.03 –.07
.07 .04
.08 .03
–.04 .06
.03 .01
–.06 –.05
–.06 –.08 –.12 –.05
.03 –.07 –.04 –.04
.01 –.06 –.01 .01
–.04 –.09 –.16 –.14
–.07 –.04 –.16 –.10þ
a
Gender coded as 0 ¼ male, 1 ¼ female. Reference group ¼ White. c Wealth index includes the following: income, owning=renting home, total assets, predicted amount of time person believes they could live at current standard with loss of income. d Highest level of education completed, reference group ¼ postgraduate degree from college or university. þ p < .10. p < .05. p < .01. p < .001. b
providers significantly less than White survivors. Those with a high school degree or GED used health care providers as a source of information less than highly educated survivors.
Discussion For these cancer survivors, doctors and the Internet were the most frequently cited sources of information. This is in line with previous research on health information–seeking behavior in the general population and cancer patients (Fox, 2011; Guidry, Aday, Zhang, & Winn, 1998; Nagler et al., 2010), and in cancer survivors (Rutten et al., 2005). This study assessed information sources by asking survivors to indicate all sources used for cancer-related information, not the most trusted, preferred, or frequently used source (Hesse et al., 2008; Mayer et al., 2007). Information sources could therefore be grouped using factor analysis, and yielded five categories: mass media, Internet and print, support organizations, family and friends, and health care providers. Although other studies have presented a priori categories of information sources (Rutten et al., 2005), this is the first study to our knowledge to categorize sources by factor analyzing cancer survivors’ reported use. Allowing source use to determine the taxonomy yielded categories that represent use patterns for cancer survivors. It is interesting that the Internet, which is often placed in the category of mass media with television and radio, emerged in a use category with print materials like books and pamphlets. We offer two plausible explanations for this finding. The Internet is a repository of a large amount of information rivaling print media and seemingly more permanent than radio and
television. Second, use of the Internet is strongly predicated on higher SES which is similar to other print media. It is also worth noting that our population of cancer survivors was somewhat younger than the nationwide estimates for cancer survivors (de Moor et al., 2013) and participants in some previous research on information seeking in cancer survivors (Nagler et al., 2010). Categorizing the Internet with print materials may not generalize to older survivors. Use of the public library for cancer-related information factor loaded with mass media such as radio and television. Although this grouping is somewhat counterintuitive because the library contains printed materials, survivors who use mass media information sources may also use libraries given that these are both public sources of information. However, a small proportion of public library users in our sample limits our ability to draw firm conclusions. Whether this taxonomy replicates in future studies is an empirical question. However, grouping according to use adds a unique piece to our understanding of patterns of information seeking in cancer survivors. Social determinants predicted the categories of information sources used. Survivors with lower education reported decreased use of all categories of information sources except mass media and family and friends. This is consistent with previous literature in cancer patients showing less active information seeking among patients with lower education levels (Galarce et al., 2011; Nagler et al., 2010; Ramanadhan & Viswanath, 2006). Results have implications for not only providing appropriate information sources to survivors but for understanding health disparities in cancer survivorship (Viswanath, 2006). Patients with
209
Cancer Survivors’ Information Source Use higher education may have increased ability and resources to use different types of information sources. African American cancer survivors reported less use of their health care provider as a source of cancer-related information than did White survivors. It is unlikely that this is due to decreased information needs (Beckjord et al., 2008), but perhaps stems from differences in the interpersonal aspects of care experienced by patients of ethnic and racial minority groups (Cooper & Roter, 2003; Cooper et al., 2003). Doctor-patient interactions with minority patients are shorter and characterized by more physician dominance and less psychosocial care (Cooper-Patrick et al., 2000). Some minority patients may not turn to health care providers as a source of information because in their experience providers do not provide the time or space for questions. African American patients may therefore rely more heavily on television and other mass media for their health information needs (Guidry et al., 1998). Encouraging communication about prevention between African American survivors and health care providers could serve as a mechanism to increase intentions to engage in prevention behaviors in African Americans (Smith-McLallen & Fishbein, 2009). There are limitations to the present analysis. As with any survey, there is the potential for bias in self-reports; differences observed may be due to willingness to report use of sources and not actual use. However, a rigorous survey development and validation process including six focus groups, cognitive interviewing, and a Spanish-language version, strengthens the validity of responses. This analysis is based on a cross-sectional survey from a single northeast medical center and may not be representative of the entire country or larger population of cancer survivors. Detecting differences in source use for some sociodemographic and socioeconomic subgroups may have been limited by small subgroup sample sizes. These survivors were younger than the average of cancer survivors (de Moor et al., 2013) and therefore their information source use, particularly the Internet, may not generalize to an older population of survivors, who often report less cancer-related information seeking in general (Mayer et al., 2007) and less information seeking online (Hesse et al., 2008). In addition, we were unable to assess demographic differences between those that responded to the survey and those that did not. The study did not specify a time frame for informationseeking behaviors which must be taken into account when comparing prevalence data for each source to other studies of cancer survivors, which may show lower rates of source use (Nagler et al., 2010). Given our empirically derived categorization by source use, we are unable to determine demographic predictors of specific source used. In some cases, groupings may include information sources which are substantially different in many ways (e.g., Internet and print materials; library and radio). This may have increased noise or masked meaningful demographic differences in source use; for example, if older survivors are more likely to seek information from pamphlets but less likely to seek information from the Internet. Categorizing based on use
furthers our understanding of patterns of information seeking in cancer survivors, but issues of generalizability necessitate replication in additional samples of cancer survivors. Cancer-related information source use fell into five general categories and social determinants predicted differences in the categories of health information sources survivors used for cancer-related information. For those creating health communication messages, results suggest categories of information sources which may be effective when presenting cancer-related information to survivors across sociodemographic and socioeconomic factors. Effectively targeting communication campaigns on the basis of survivors’ sociodemographic and socioeconomic characteristics may be one way to mitigate health disparities in this population.
References Anker, A. E., Reinhart, A. M., & Feeley, T. H. (2011). Health information seeking: A review of measures and methods. Patient Education and Counseling, 82, 346–354. doi:10.1016=j.pec.2010. 12.008 Aziz, N. M., & Rowland, J. H. (2002, January). Cancer survivorship research among ethnic minority and medically underserved groups. Oncology Nursing Forum, 29, 789–801. Bach, P. B., Schrag, D., Brawley, O. W., Galaznik, A., Yakren, S., & Begg, C. B. (2002). Survival of blacks and whites after a cancer diagnosis. JAMA, 287, 2106–2113. Beach, M. C., & Inui, T. (2006). Relationship-centered care. A constructive reframing. Journal of General Internal Medicine, 21(Suppl 1), S3–S8. doi:10.1111=j.1525-1497.2006.00302.x Beckjord, E. B., Arora, N. K., McLaughlin, W., Oakley-Girvan, I., Hamilton, A. S., & Hesse, B. W. (2008). Health-related information needs in a large and diverse sample of adult cancer survivors: implications for cancer care. Journal of Cancer Survivorship, 2, 179–189. doi:10.1007=s11764–008-0055–0 Berkman, L. F., & Kawachi, I. (2000). Social epidemiology. New York, NY: Oxford University Press. Cooper, L. A., & Roter, D. L. (2003). Patient-provider communication: The effect of race and ethnicity on process and outcomes of healthcare. In B. D. Smedley, A. Y. Stith, & A. R. Nelson (Eds.), Unequal treatment: Confronting racial and ethnic disparities in health care (pp. 552–593). Washington, DC: National Academies Press. Cooper, L. A., Roter, D. L., Johnson, R. L., Ford, D. E., Steinwachs, D. M., & Powe, N. R. (2003). Patient-centered communication, ratings of care, and concordance of patient and physician race. Annals of Internal Medicine, 139, 907–915. Cooper-Patrick, L., Ford, D., Vu, H., Powe, N., Steinwachs, D., & Roter, D. (2000). Patient-physician race concordance and communication in primary care. Journal of General Internal Medicine, 15, 106. de Moor, J. S., Mariotto, A. B., Parry, C., Alfano, C. M., Padgett, L., Kent, E. E., . . . Rowland, J. H. (2013). Cancer survivors in the United States: Prevalence across the survivorship trajectory and implications for care. Cancer Epidemiology Biomarkers & Prevention, 22, 561–570. Eheman, C. R., Berkowitz, Z., Lee, J., Mohile, S., Purnell, J., Rodriguez, E. M., . . . Morrow, G. (2009). Information-seeking styles among cancer patients before and after treatment by demographics and use of information sources. Journal of Health Communication, 14, 487–502. doi:10.1080=10810730903032945 Fox, S. (2011). Health topics: 80% of Internet users look for health information online. Washington, DC: Pew Internet & American Life Project. Galarce, E. M., Ramanadhan, S., Weeks, J., Schneider, E. C., Gray, S. W., & Viswanath, K. (2011). Class, race, ethnicity and
210 information needs in post-treatment cancer patients. Patient Education and Counseling, 85, 432–439. doi:10.1016=j.pec.2011.01.030 Guidry, J. J., Aday, L. A., Zhang, D., & Winn, R. J. (1998). Information sources and barriers to cancer treatment by racial=ethnic minority status of patients. Journal of Cancer Education, 13, 43–48. doi:10.1080=08858199809528511 Hesse, B. W., Arora, N. K., Burke Beckjord, E., & Finney Rutten, L. J. (2008). Information support for cancer survivors. Cancer, 112(11 Suppl.), 2529–2540. doi:10.1002=cncr.23445 Hewitt, M. E., Ganz, P. A., Institute of Medicine, & American Society of Clinical Oncology. (2006). From cancer patient to cancer survivor: Lost in transition: An American Society of Clinical Oncology and Institute of Medicine Symposium. Washington, DC: National Academies Press. Howlader, N. N. A., Krapcho, M., Neyman, N., Aminou, R., Waldron, W., Altekruse, S. F., . . . Edwards, B. K. (Ed.). (2011). SEER Cancer Statistics Review, 1975–2008. Bethesda, MD:: National Cancer Institute. Kelly, B., Hornik, R., Romantan, A., Schwartz, J. S., Armstrong, K., DeMichele, A., . . . Wong, N. (2010). Cancer information scanning and seeking in the general population. Journal of Health Communication, 15, 734–753. doi:10.1080=10810730.2010.514029 Lee, C. J., Gray, S. W., & Lewis, N. (2010). Internet use leads cancer patients to be active health care consumers. Patient Education and Counseling, 81(Suppl 1), S63–S69. doi:10.1016=j.pec.2010.09.004 Lee, C. J., Ramirez, A. S., Lewis, N., Gray, S. W., & Hornik, R. C. (2012). Looking beyond the Internet: Examining socioeconomic inequalities in cancer information seeking among cancer patients. Health Communication, 27, 806–817. doi:10.1080=10410236. 2011.647621 Mayer, D. K., Terrin, N. C., Kreps, G. L., Menon, U., McCance, K., Parsons, S. K., & Mooney, K. H. (2007). Cancer survivors information seeking behaviors: A comparison of survivors who do and do not seek information about cancer. Patient Education and Counseling, 65, 342–350. doi:10.1016=j.pec.2006.08.015 Mead, N., & Bower, P. (2000). Patient-centredness: A conceptual framework and review of the empirical literature. Social Science and Medicine, 51, 1087–1110. Nagler, R. H., Gray, S. W., Romantan, A., Kelly, B. J., DeMichele, A., Armstrong, K., . . . Hornik, R. C. (2010). Differences in information seeking among breast, prostate, and colorectal cancer patients: Results from a population-based survey. Patient Education and Counseling, 81(Suppl), S54–S62. doi:10.1016=j.pec.2010.09.010 Nguyen, G. T., & Bellamy, S. L. (2006). Cancer information seeking preferences and experiences: disparities between Asian Americans and Whites in the Health Information National Trends Survey (HINTS). Journal of Health Communication, 11(Suppl 1), 173–180. doi:10.1080=10810730600639620 Niederdeppe, J., & Levy, A. G. (2007). Fatalistic beliefs about cancer prevention and three prevention behaviors. Cancer Epidemiology, Biomarkers & Prevention, 16(5), 998–1003. doi:10.1158=1055– 9965.EPI-06–0608
D. Blanch-Hartigan and K. Viswanath Ramanadhan, S., & Viswanath, K. (2006). Health and the information nonseeker: A profile. Health Communication, 20, 131–139. doi:10.1207=s15327027hc2002_4 Ramirez, A. S., Freres, D., Martinez, L. S., Lewis, N., Bourgoin, A., Kelly, B. J., . . . Hornik, R. C. (2013). Information seeking from media and family= friends increases the likelihood of engaging in healthy lifestyle behaviors. Journal of Health Communication, 18, 527–542. doi:10.1080=10810730.2012.743632 Ramirez, A. S., Rutten, L. J., Oh, A., Vengoechea, B. L., Moser, R. P., Vanderpool, R. C., & Hesse, B. W. (2013). Perceptions of cancer controllability and cancer risk knowledge: The moderating role of race, ethnicity, and acculturation. Journal of Cancer Education, 28, 254–261. doi:10.1007=s13187–013-0450–8 Robbins, A. S., Siegel, R. L., & Jemal, A. (2012). Racial disparities in stage-specific colorectal cancer mortality rates from 1985 to 2008. Journal of Clinical Oncology, 30, 401–405. Rutten, L. J., Arora, N. K., Bakos, A. D., Aziz, N., & Rowland, J. (2005). Information needs and sources of information among cancer patients: a systematic review of research (1980–2003). Patient Education and Counseling, 57, 250–261. doi:10.1016=j.pec.2004.06.006 Smith-McLallen, A., & Fishbein, M. (2009). Predicting intentions to engage in cancer prevention and detection behaviors: examining differences between Black and White adults. Psychology Health & Medicine, 14, 180–189. doi:10.1080=13548500802183575 Squiers, L., Finney Rutten, L. J., Treiman, K., Bright, M. A., & Hesse, B. (2005). Cancer patients’ information needs across the cancer care continuum: evidence from the cancer information service. Journal of Health Communication, 10(Suppl 1), 15–34. doi:10.1080= 10810730500263620 Vanderpool, R. C., Kornfeld, J., Rutten, L. F., & Squiers, L. (2009). Cancer information-seeking experiences: the implications of Hispanic ethnicity and Spanish language. Journal of Cancer Education, 24, 141–147. doi:10.1080=08858190902854772 Viswanath, K. (2006). Public communications and its role in reducing and eliminating health disparities. Examining the health disparities research plan of the National Institutes of Health: Unfinished business. Washington, DC: Institute of Medicine. Viswanath, K., Breen, N., Meissner, H., Moser, R. P., Hesse, B., Steele, W. R., & Rakowski, W. (2006). Cancer knowledge and disparities in the information age. Journal of Health Communication, 11(Suppl 1), 1–17. doi:10.1080=10810730600977517 Viswanath, K., Ramanadhan, S., & Kontos, E. Z. (2007). Mass media. In S. Galea (Ed.), Macrosocial determinants of population health (pp. 275–294). New York, NY: Springer. Weaver, K. E., Geiger, A. M., Lu, L., & Case, L. D. (2012). Ruralurban disparities in health status among US cancer survivors. Cancer, 119, 1050–1057. Williams, D. R., Kontos, E. Z., Viswanath, K., Haas, J. S., Lathan, C. S., MacConaill, L. E., . . . Ayanian, J. Z. (2012). Integrating multiple social statuses in health disparities research: The case of lung cancer. Health Services Research, 47(3 Pt 2), 1255–1277. doi:10.1111=j.1475-6773.2012.01404.x
Copyright of Journal of Health Communication is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Socioeconomic and Sociodemographic Predictors of Cancer-Related Information Sources Used by Cancer Survivors DANIELLE BLANCH-HARTIGAN1 and KASISOMAYAJULA VISWANATH2,3 1
Department of Natural and Applied Sciences, Bentley University, Waltham, Massachusetts, USA Harvard School of Public Health, Boston, Massachusetts, USA 3 Dana-Farber Cancer Institute, Boston, Massachusetts, USA 2
With 14 million cancer survivors in the United States, identifying and categorizing their use of sources of cancer-related information is vital for targeting effective communications to this growing population. In addition, recognizing socioeconomic and sociodemographic differences in the use of cancer-related information sources is a potential mechanism for reducing health disparities in survivorship. Fourteen sources of information survivors (N ¼ 519) used for cancer-related information were factor-analyzed to create a taxonomy of source use. The association between social determinants and use of these source types was analyzed in regression models. Factor analysis revealed 5 categories of information source use (mass media; Internet and print; support organizations; family and friends; health care providers), and use varied based on sociodemographic and socioeconomic characteristics. Higher education predicted increased use of all source categories except mass media. African American cancer survivors turned to health care providers as a source for cancer-related information less often than did White survivors. Social determinants predicted differences in the type of cancer-related information sources used. Providers and health communicators should target communication platforms based on the demographic profile of specific survivor audiences.
Patients’ health information–seeking behaviors are typically defined as an active, goal-oriented activity, in which an individual seeks information about health, often in response to a health event and often related to a specific topic (Anker, Reinhart, & Feeley, 2011; Galarce et al., 2011; Kelly et al., 2010; Niederdeppe & Levy, 2007). In the patient-centered model of care, providers and patients are encouraged to share responsibility for treatment and decision making (Beach & Inui, 2006; Mead & Bower, 2000) and patients’ health information–seeking is an important component of shared decision making. Information seeking in cancer patients is associated with taking a more active role in their care (Lee, Gray, & Lewis, 2010) and engaging in healthpromoting behaviors (Ramirez, Freres, et al., 2013). Health Information Seeking Behavior in Cancer Survivors There is a wealth of research about health information– seeking in general populations (Anker et al., 2011) and for cancer patients and caregivers in the prevention, detection, diagnosis, and treatment phases of the cancer continuum (Ramanadhan & Viswanath, 2006; Rutten, Arora, Bakos, Address correspondence to Danielle Blanch-Hartigan, Department of Natural and Applied Sciences, Bentley University, Jennison 100, 175 Forest Street, Waltham, MA 02452, USA. E-mail: [email protected]
Aziz, & Rowland, 2005). However, less research has focused on health information–seeking behavior in cancer survivors (Galarce et al., 2011; Rutten et al., 2005). Cancer survivors in the United States number more than 14 million and account for approximately 4% of the population (Howlader, 2011). This sizeable group has unique health care needs including the prevention and detection of recurrence and management of physical and psychosocial effects of treatment; needs which are often left unmet in the transition from active treatment to survivorship (Hewitt et al., 2006). To adequately address these needs and develop effective communication for this population, we must understand the health information–seeking behaviors of cancer survivors. Survivors’ information needs are different from those in earlier stages of the cancer continuum (Eheman et al., 2009; Rutten et al., 2005; Squiers, Finney Rutten, Treiman, Bright, & Hesse, 2005). Survivors may adopt a more passive information-seeking style (Eheman et al., 2009) but are more likely to have sought cancer-related information compared with those without a history of cancer (Hesse, Arora, Burke Beckjord, & Finney Rutten, 2008). Information sought by cancer survivors differs from that of cancer patients and spans a variety of topics, including risk of cancer recurrence, quality of life, prevention, work, finance, and posttreatment complications (Beckjord et al., 2008; Galarce et al., 2011; Squiers et al., 2005).
205
Cancer Survivors’ Information Source Use Health Information Seeking Behavior and Health Disparities Differences in health outcomes by socioeconomic status (SES) and other sociodemographic characteristics are well documented (Berkman & Kawachi, 2000; Williams et al., 2012). Racial=ethnic disparities exist across the cancer continuum, from cancer prevention knowledge and beliefs (Ramirez, Rutten, et al., 2013) to survival and mortality outcomes (Bach et al., 2002; Robbins, Siegel, & Jemal, 2012). Cancer survivors with lower SES, or from medically underserved or rural communities experience poorer physical and psychological health outcomes (Aziz & Rowland, 2002; Weaver, Geiger, Lu, & Case, 2012). Understanding possible mechanisms behind these differences is paramount to reducing disparities. The Structural Influence Model of Health Communication suggests one pathway by which low SES may lead to poorer health outcomes is through inequalities in health communication (Viswanath, Ramanadhan, & Kontos, 2007). Social determinants such as low SES, mediated by sociodemographic factors such as age and gender, lead to differences in health communication—particularly less access and attention to health information, reduced health information seeking, and difficulties with information processing and use of health information. These differential health communication behaviors lead to disparities in health outcomes. For example, members of lower SES may actually acquire information at a slower pace than those of high SES. Information and attentional processing differences may explain why lower SES groups are less likely to engage in health behaviors and as a consequence may suffer worse health outcomes (Viswanath et al., 2007). Therefore, even in an environment rich in information, these groups may have a wide gap in knowledge (Viswanath, 2006). One way to mitigate health disparities is to close this knowledge gap through effective health communication (Viswanath et al., 2006). However, appropriate health information cannot be made available without first understanding the complete picture of health information–seeking behaviors. Research on health information–seeking behavior has increased dramatically in the past 20 years (Anker et al., 2011), and many studies have documented social determinants of cancer-related information needs and informationseeking behaviors in both the general population and in cancer patients (Kelly et al., 2010; Lee, Ramirez, Lewis, Gray, & Hornik, 2012; Nagler et al., 2010; Nguyen & Bellamy, 2006; Vanderpool, Kornfeld, Rutten, & Squiers, 2009). By comparison, relatively few studies have specifically examined socioeconomic and sociodemographic factors associated with health information–seeking behaviors of cancer survivors. Cancer survivors from racial=ethnic minorities report more information needs (Beckjord et al., 2008). However, survivors with lower SES are also less likely to report seeking health information (Hesse et al., 2008; Mayer et al., 2007; Ramanadhan & Viswanath, 2006). The pattern of topics sought by cancer survivors varies across SES (Galarce et al., 2011). Galarce and colleagues analyzed health information–seeking behavior of cancer survivors,
categorizing topics of information sought into four main categories: (a) disease=treatment, including the effects of cancer treatment and likelihood of survival; (b) self-care management, including diet, nutrition, and staying healthy; (c) health services, including information on doctors and health services available; and (d) work=finance, including financial assistance and employment issues. Survivors with less wealth and more debt were the most likely to seek information about work and finance issues. Individuals with lower education levels were less likely to report information seeking for disease=treatment, self-care management, and health services. Few studies focus specifically on sources of information seeking in survivors (Rutten et al., 2005). Younger survivors prefer the Internet over health care providers more often than do older survivors (Hesse et al., 2008). In a study of cancer patients and survivors, higher education level was associated with seeking more cancer treatment information from the Internet, mass media, and medical professionals, but not from nonmedical interpersonal sources like friends and family (Lee et al., 2012). The present analyses extend previous work on information-seeking behaviors in cancer survivors in two ways. First, we investigate which sources of information (Internet, health care providers, etc.) are used by survivors for cancer-related topics by creating a taxonomy for cancerrelated information sources based not on a priori defined categories but on survivors’ reported source use. In addition, this research extends work on social determinants of information source use by investigating how social determinants predict use of categories of information sources specifically in cancer survivors, expanding the work on communication inequalities in health with a particular focus on cancer survivors.
Method Participants and Procedure The data for this study come from a survey of cancer survivors who were a part of the Well-Informed, Thriving and Surviving study conducted in Eastern United States. The questionnaire explored factors of health information– seeking behavior in 519 survivors. To be eligible, participants had to be English or Spanish speaking, have been diagnosed with stage I, II, or III cancer within the past 5 years, with no evidence of tumor recurrence or metastatic disease, and had no treatment (chemotherapy or radiation therapy) within the last year. Respondents were on average 54 years old (SD ¼ 11.55, range ¼ 21–75), 73% female, and 81% White (Table 1). A questionnaire about health information–seeking behavior was mailed to randomly selected current and former patients of a major U.S. cancer center, with the permission of their physicians. Participants could respond by mail using the self-addressed postage-paid reply envelope, over the Internet, or by phone at a conveniently scheduled time. A $5 gift card was included with the questionnaire. There was a 66% response rate (Galarce et al., 2011). All study
206
D. Blanch-Hartigan and K. Viswanath
Table 1. Sociodemographic and socioeconomic characteristics of participants (N ¼ 519)
Table 1. Continued
n (%) or M (SD) Sociodemographic characteristics Age, M (SD), n ¼ 513 54.32 (11.55) Gender, n (%) Male 138 (26.6) Female 378 (73.3) Unreported 3 (.6) Race, n (%) Non-Hispanic White 420 (80.9) Non-Hispanic Black=African American 37 (7.1) Asian 15 (2.9) Hispanic 27 (5.2) Other=mixed race 16 (3.1) Unreported 4 (.8) Socioeconomic characteristicsa Income, n (%) $75,000 280 (53.9) Don’t know=refused=missing 63 (12.1) Own=rent home (n (%) Rent 72 (13.9) Own 373 (71.9) Not paying rent=mortgage 36 (6.9) Missing=don’t know 38 (7.3) Total savings=assets=property, n (%) $500,000 174 (33.5) Don’t know=refused=missing 135 (26.0) Time with no income, n (%) 1 year 197 (38.0) Missing 40 (7.7) Debt, n (%) $100,000 37 (7.1) Don’t know=refused=missing 100 (19.3) Highest level of education, n (%) Less than high school 18 (3.4) Grade 12 or GED (high school graduate) 61 (11.8) Some post–high school education 143 (27.6) College, 4 years or more (college graduate) 147 (28.3) Post graduate degree from college or university 147 (28.3) Unreported 3 (.6) (Continued )
n (%) or M (SD) Disease characteristics Cancer type, n (%) Breast Colorectal Head=neck Leukemia=blood Lung Lymphoma Prostate Other=don’t know=missing Stage at diagnosis, n (%) Stage I Stage II Stage III Stage IV Other=don’t know=missing
239 26 19 16 23 63 21 112
(46.1) (5.0) (3.7) (3.1) (4.4) (12.1) (4.0) (21.6)
166 119 82 15 137
(32.0) (22.9) (15.8) (2.9) (26.4)
a Wealth index includes the following items: income, own=rent home, total assets, and predicted amount of time person could live at current standard with loss of income. Not all participants chose to report this information. Debt index includes a single debt item.
materials and procedures were approved by the cancer center’s institutional review board and complied with HIPAA standards. Measures Information Sources Participants were asked ‘‘What sources have you used to get information about cancer? Please check all that apply.’’ Participants reported whether they used any of 15 possible sources of information: (a) one or more doctors, (b) another type of health care provider, (c) Internet, (d) family or friends who are in the medical field, (e) family or friends who are not in the medical field, (f) other cancer patients or survivors, (g) coworkers, (h) support groups, (i) pamphlets or books, (j) television, (k) radio, (l) public library, (m) resource center at a hospital or clinic, (n) cancer information or support organization, or (o) other sources. A time frame was not specified. Use of the source was scored 0 if they did not check the source and 1 if they reported using the source. Socioeconomic, Demographic, and Disease Characteristics Participants reported their age, race, gender, and highest level of education completed. Participants also reported cancer type and stage at diagnosis. To measure SES, wealth and debt indices were created from a series of questions about financial status using principal component analyses to yield normally distributed score coefficients, which were saved and analyzed as continuous indices (M ¼ 0, SD ¼ 1; Galarce et al., 2011). The wealth index included responses from four items: 1. Present value of total savings, assets, and property (including home) with response options from less than $500 to $500,000 or more.
207
Cancer Survivors’ Information Source Use 2. Total household income before taxes with response options ranging from under $10,000 to $75,000 or more. 3. Financial stability as measured by length of time the respondent could maintain current residence and standard of living without present income with response options less than 1 month to more than a year. 4. Home ownership status, with the following response options: ‘‘rent home,’’ ‘‘own home,’’ ‘‘not paying rent or mortgage,’’ and ‘‘don’t know.’’ The debt index was a single item: ‘‘Not counting your mortgage or car loans, what is the total amount of debt held by you and other family members living here, including student loans, credit card charges, medical or legal bills, or loans from relatives?’’ Response options were as follows: less than $2000; $2000–$4999; $5000–$9999; $10,000–$19,999; $20,000–$49,999; $50,000–$99,999; $100,000 or more; don’t know; and refused. Analyses To create source categories, the fourteen information sources (excluding ‘‘other’’) were subjected to a principal component analysis with varimax rotation and Kaiser normalization using pairwise deletion. The factors’ regression coefficients were saved as factor based scores and analyzed as continuous indicators (M ¼ 0, SD ¼ 1) of each respondent’s use of each of the source categories. To analyze social determinants of information source use, multiple linear regression models were used to analyze the influence of sociodemographic and socioeconomic predictors on the factored score for use of each information source category. Variables were entered into the model using a forced entry method with pairwise deletion. We did not include disease characteristics (stage at diagnosis and cancer type) in the model due to variation in response and the presence of missing data.
Results The most commonly reported information sources used by cancer survivors were doctor (79%) and the Internet (79%; Table 2). Other common sources of information included: other cancer patients (56%), pamphlets or books (55%), and family and friends who worked in the medical field (48%). Cancer-Related Information Source Categories Principal component analysis of the 14 sources yielded five categories of cancer-related information sources (eigenvalue > 1.0; factor loadings > 0.4) that explained 54.25% of the variance: (a) mass media (television, radio, public library), (b) Internet and print (Internet, pamphlets=books, resource center at hospital=clinic), (c) support organizations (support groups, cancer information or support organization), (d) family and friends (family=friends in medicine, family= friends not in medicine, coworkers, other cancer patients= survivors), and (e) health care providers (doctors, other health care providers).
Table 2. Sources of health information and reported use (n ¼ 519) Source categoriesa 1. Health care providers One or more doctors Another type of health care provider 2. Family=friends Family or friends in the medical field Family or friends not in the medical field Other cancer patients or survivors Coworkers 3. Mass media Television Radio Public library 4. Internet and print Internet Pamphlets=books Resource center at a hospital=clinic 5. Support organizations Support groups Cancer information or support organization Other sourcesb No information sources=nonseeker a b
Use, n (%) 411 (79) 69 (13) 247 162 288 70
(48) (31) (56) (14)
96 (19) 31 (6) 50 (10) 409 (79) 285 (55) 133 (26) 73 94 27 18
(14) (18) (5) (4)
Categories created using principal component analysis. Not included in principal component analysis.
Predictors of Source Categories Sociodemographic and socioeconomic differences existed in use of these five information source categories (Table 3). Mass Media Older and female survivors reported greater use of mass media sources for health information. Hispanic survivors had significantly greater use of mass media sources than White survivors. Internet and Print Female survivors used Internet and print sources more than male survivors. Older survivors also reported marginally greater use of this source category. Compared to those with post graduate degrees, those survivors with high school education or less than high school education reported significantly less use of the Internet and print sources for cancer-related information. Support Organizations Male survivors and those with high school degree sought less information from support organizations than female survivors and those with postgraduate degrees. Family and Friends Female survivors reported greater use than male survivors of family and friends as a source of cancer-related information. Health Care Providers Race emerged as the strongest predictor of use of health care providers. African American survivors turned to health care
208
D. Blanch-Hartigan and K. Viswanath
Table 3. Sociodemographic and socioeconomic predictors of categories of sources used for cancer-related information (standardized bs) Source category Health care providers Sociodemographic predictors Age Gendera Raceb African American Asian Hispanic Other=mixed race Socioeconomic predictors Wealth indexc Debt Educationd Four-year college Some college High school=GED Less than high school
–.05 .02
Friends= family
Mass media
Internet=print
Support organizations
–.01 .10
.10 .17
–.09þ .10
–.06 .12
–.15 –.01 –.03 –.05
.03 –.03 –.05 –.01
.08 –.01 .10 .04
–.003 –.03 –.07 .02
.07 –.04 –.03 –.07
.07 .04
.08 .03
–.04 .06
.03 .01
–.06 –.05
–.06 –.08 –.12 –.05
.03 –.07 –.04 –.04
.01 –.06 –.01 .01
–.04 –.09 –.16 –.14
–.07 –.04 –.16 –.10þ
a
Gender coded as 0 ¼ male, 1 ¼ female. Reference group ¼ White. c Wealth index includes the following: income, owning=renting home, total assets, predicted amount of time person believes they could live at current standard with loss of income. d Highest level of education completed, reference group ¼ postgraduate degree from college or university. þ p < .10. p < .05. p < .01. p < .001. b
providers significantly less than White survivors. Those with a high school degree or GED used health care providers as a source of information less than highly educated survivors.
Discussion For these cancer survivors, doctors and the Internet were the most frequently cited sources of information. This is in line with previous research on health information–seeking behavior in the general population and cancer patients (Fox, 2011; Guidry, Aday, Zhang, & Winn, 1998; Nagler et al., 2010), and in cancer survivors (Rutten et al., 2005). This study assessed information sources by asking survivors to indicate all sources used for cancer-related information, not the most trusted, preferred, or frequently used source (Hesse et al., 2008; Mayer et al., 2007). Information sources could therefore be grouped using factor analysis, and yielded five categories: mass media, Internet and print, support organizations, family and friends, and health care providers. Although other studies have presented a priori categories of information sources (Rutten et al., 2005), this is the first study to our knowledge to categorize sources by factor analyzing cancer survivors’ reported use. Allowing source use to determine the taxonomy yielded categories that represent use patterns for cancer survivors. It is interesting that the Internet, which is often placed in the category of mass media with television and radio, emerged in a use category with print materials like books and pamphlets. We offer two plausible explanations for this finding. The Internet is a repository of a large amount of information rivaling print media and seemingly more permanent than radio and
television. Second, use of the Internet is strongly predicated on higher SES which is similar to other print media. It is also worth noting that our population of cancer survivors was somewhat younger than the nationwide estimates for cancer survivors (de Moor et al., 2013) and participants in some previous research on information seeking in cancer survivors (Nagler et al., 2010). Categorizing the Internet with print materials may not generalize to older survivors. Use of the public library for cancer-related information factor loaded with mass media such as radio and television. Although this grouping is somewhat counterintuitive because the library contains printed materials, survivors who use mass media information sources may also use libraries given that these are both public sources of information. However, a small proportion of public library users in our sample limits our ability to draw firm conclusions. Whether this taxonomy replicates in future studies is an empirical question. However, grouping according to use adds a unique piece to our understanding of patterns of information seeking in cancer survivors. Social determinants predicted the categories of information sources used. Survivors with lower education reported decreased use of all categories of information sources except mass media and family and friends. This is consistent with previous literature in cancer patients showing less active information seeking among patients with lower education levels (Galarce et al., 2011; Nagler et al., 2010; Ramanadhan & Viswanath, 2006). Results have implications for not only providing appropriate information sources to survivors but for understanding health disparities in cancer survivorship (Viswanath, 2006). Patients with
209
Cancer Survivors’ Information Source Use higher education may have increased ability and resources to use different types of information sources. African American cancer survivors reported less use of their health care provider as a source of cancer-related information than did White survivors. It is unlikely that this is due to decreased information needs (Beckjord et al., 2008), but perhaps stems from differences in the interpersonal aspects of care experienced by patients of ethnic and racial minority groups (Cooper & Roter, 2003; Cooper et al., 2003). Doctor-patient interactions with minority patients are shorter and characterized by more physician dominance and less psychosocial care (Cooper-Patrick et al., 2000). Some minority patients may not turn to health care providers as a source of information because in their experience providers do not provide the time or space for questions. African American patients may therefore rely more heavily on television and other mass media for their health information needs (Guidry et al., 1998). Encouraging communication about prevention between African American survivors and health care providers could serve as a mechanism to increase intentions to engage in prevention behaviors in African Americans (Smith-McLallen & Fishbein, 2009). There are limitations to the present analysis. As with any survey, there is the potential for bias in self-reports; differences observed may be due to willingness to report use of sources and not actual use. However, a rigorous survey development and validation process including six focus groups, cognitive interviewing, and a Spanish-language version, strengthens the validity of responses. This analysis is based on a cross-sectional survey from a single northeast medical center and may not be representative of the entire country or larger population of cancer survivors. Detecting differences in source use for some sociodemographic and socioeconomic subgroups may have been limited by small subgroup sample sizes. These survivors were younger than the average of cancer survivors (de Moor et al., 2013) and therefore their information source use, particularly the Internet, may not generalize to an older population of survivors, who often report less cancer-related information seeking in general (Mayer et al., 2007) and less information seeking online (Hesse et al., 2008). In addition, we were unable to assess demographic differences between those that responded to the survey and those that did not. The study did not specify a time frame for informationseeking behaviors which must be taken into account when comparing prevalence data for each source to other studies of cancer survivors, which may show lower rates of source use (Nagler et al., 2010). Given our empirically derived categorization by source use, we are unable to determine demographic predictors of specific source used. In some cases, groupings may include information sources which are substantially different in many ways (e.g., Internet and print materials; library and radio). This may have increased noise or masked meaningful demographic differences in source use; for example, if older survivors are more likely to seek information from pamphlets but less likely to seek information from the Internet. Categorizing based on use
furthers our understanding of patterns of information seeking in cancer survivors, but issues of generalizability necessitate replication in additional samples of cancer survivors. Cancer-related information source use fell into five general categories and social determinants predicted differences in the categories of health information sources survivors used for cancer-related information. For those creating health communication messages, results suggest categories of information sources which may be effective when presenting cancer-related information to survivors across sociodemographic and socioeconomic factors. Effectively targeting communication campaigns on the basis of survivors’ sociodemographic and socioeconomic characteristics may be one way to mitigate health disparities in this population.
References Anker, A. E., Reinhart, A. M., & Feeley, T. H. (2011). Health information seeking: A review of measures and methods. Patient Education and Counseling, 82, 346–354. doi:10.1016=j.pec.2010. 12.008 Aziz, N. M., & Rowland, J. H. (2002, January). Cancer survivorship research among ethnic minority and medically underserved groups. Oncology Nursing Forum, 29, 789–801. Bach, P. B., Schrag, D., Brawley, O. W., Galaznik, A., Yakren, S., & Begg, C. B. (2002). Survival of blacks and whites after a cancer diagnosis. JAMA, 287, 2106–2113. Beach, M. C., & Inui, T. (2006). Relationship-centered care. A constructive reframing. Journal of General Internal Medicine, 21(Suppl 1), S3–S8. doi:10.1111=j.1525-1497.2006.00302.x Beckjord, E. B., Arora, N. K., McLaughlin, W., Oakley-Girvan, I., Hamilton, A. S., & Hesse, B. W. (2008). Health-related information needs in a large and diverse sample of adult cancer survivors: implications for cancer care. Journal of Cancer Survivorship, 2, 179–189. doi:10.1007=s11764–008-0055–0 Berkman, L. F., & Kawachi, I. (2000). Social epidemiology. New York, NY: Oxford University Press. Cooper, L. A., & Roter, D. L. (2003). Patient-provider communication: The effect of race and ethnicity on process and outcomes of healthcare. In B. D. Smedley, A. Y. Stith, & A. R. Nelson (Eds.), Unequal treatment: Confronting racial and ethnic disparities in health care (pp. 552–593). Washington, DC: National Academies Press. Cooper, L. A., Roter, D. L., Johnson, R. L., Ford, D. E., Steinwachs, D. M., & Powe, N. R. (2003). Patient-centered communication, ratings of care, and concordance of patient and physician race. Annals of Internal Medicine, 139, 907–915. Cooper-Patrick, L., Ford, D., Vu, H., Powe, N., Steinwachs, D., & Roter, D. (2000). Patient-physician race concordance and communication in primary care. Journal of General Internal Medicine, 15, 106. de Moor, J. S., Mariotto, A. B., Parry, C., Alfano, C. M., Padgett, L., Kent, E. E., . . . Rowland, J. H. (2013). Cancer survivors in the United States: Prevalence across the survivorship trajectory and implications for care. Cancer Epidemiology Biomarkers & Prevention, 22, 561–570. Eheman, C. R., Berkowitz, Z., Lee, J., Mohile, S., Purnell, J., Rodriguez, E. M., . . . Morrow, G. (2009). Information-seeking styles among cancer patients before and after treatment by demographics and use of information sources. Journal of Health Communication, 14, 487–502. doi:10.1080=10810730903032945 Fox, S. (2011). Health topics: 80% of Internet users look for health information online. Washington, DC: Pew Internet & American Life Project. Galarce, E. M., Ramanadhan, S., Weeks, J., Schneider, E. C., Gray, S. W., & Viswanath, K. (2011). Class, race, ethnicity and
210 information needs in post-treatment cancer patients. Patient Education and Counseling, 85, 432–439. doi:10.1016=j.pec.2011.01.030 Guidry, J. J., Aday, L. A., Zhang, D., & Winn, R. J. (1998). Information sources and barriers to cancer treatment by racial=ethnic minority status of patients. Journal of Cancer Education, 13, 43–48. doi:10.1080=08858199809528511 Hesse, B. W., Arora, N. K., Burke Beckjord, E., & Finney Rutten, L. J. (2008). Information support for cancer survivors. Cancer, 112(11 Suppl.), 2529–2540. doi:10.1002=cncr.23445 Hewitt, M. E., Ganz, P. A., Institute of Medicine, & American Society of Clinical Oncology. (2006). From cancer patient to cancer survivor: Lost in transition: An American Society of Clinical Oncology and Institute of Medicine Symposium. Washington, DC: National Academies Press. Howlader, N. N. A., Krapcho, M., Neyman, N., Aminou, R., Waldron, W., Altekruse, S. F., . . . Edwards, B. K. (Ed.). (2011). SEER Cancer Statistics Review, 1975–2008. Bethesda, MD:: National Cancer Institute. Kelly, B., Hornik, R., Romantan, A., Schwartz, J. S., Armstrong, K., DeMichele, A., . . . Wong, N. (2010). Cancer information scanning and seeking in the general population. Journal of Health Communication, 15, 734–753. doi:10.1080=10810730.2010.514029 Lee, C. J., Gray, S. W., & Lewis, N. (2010). Internet use leads cancer patients to be active health care consumers. Patient Education and Counseling, 81(Suppl 1), S63–S69. doi:10.1016=j.pec.2010.09.004 Lee, C. J., Ramirez, A. S., Lewis, N., Gray, S. W., & Hornik, R. C. (2012). Looking beyond the Internet: Examining socioeconomic inequalities in cancer information seeking among cancer patients. Health Communication, 27, 806–817. doi:10.1080=10410236. 2011.647621 Mayer, D. K., Terrin, N. C., Kreps, G. L., Menon, U., McCance, K., Parsons, S. K., & Mooney, K. H. (2007). Cancer survivors information seeking behaviors: A comparison of survivors who do and do not seek information about cancer. Patient Education and Counseling, 65, 342–350. doi:10.1016=j.pec.2006.08.015 Mead, N., & Bower, P. (2000). Patient-centredness: A conceptual framework and review of the empirical literature. Social Science and Medicine, 51, 1087–1110. Nagler, R. H., Gray, S. W., Romantan, A., Kelly, B. J., DeMichele, A., Armstrong, K., . . . Hornik, R. C. (2010). Differences in information seeking among breast, prostate, and colorectal cancer patients: Results from a population-based survey. Patient Education and Counseling, 81(Suppl), S54–S62. doi:10.1016=j.pec.2010.09.010 Nguyen, G. T., & Bellamy, S. L. (2006). Cancer information seeking preferences and experiences: disparities between Asian Americans and Whites in the Health Information National Trends Survey (HINTS). Journal of Health Communication, 11(Suppl 1), 173–180. doi:10.1080=10810730600639620 Niederdeppe, J., & Levy, A. G. (2007). Fatalistic beliefs about cancer prevention and three prevention behaviors. Cancer Epidemiology, Biomarkers & Prevention, 16(5), 998–1003. doi:10.1158=1055– 9965.EPI-06–0608
D. Blanch-Hartigan and K. Viswanath Ramanadhan, S., & Viswanath, K. (2006). Health and the information nonseeker: A profile. Health Communication, 20, 131–139. doi:10.1207=s15327027hc2002_4 Ramirez, A. S., Freres, D., Martinez, L. S., Lewis, N., Bourgoin, A., Kelly, B. J., . . . Hornik, R. C. (2013). Information seeking from media and family= friends increases the likelihood of engaging in healthy lifestyle behaviors. Journal of Health Communication, 18, 527–542. doi:10.1080=10810730.2012.743632 Ramirez, A. S., Rutten, L. J., Oh, A., Vengoechea, B. L., Moser, R. P., Vanderpool, R. C., & Hesse, B. W. (2013). Perceptions of cancer controllability and cancer risk knowledge: The moderating role of race, ethnicity, and acculturation. Journal of Cancer Education, 28, 254–261. doi:10.1007=s13187–013-0450–8 Robbins, A. S., Siegel, R. L., & Jemal, A. (2012). Racial disparities in stage-specific colorectal cancer mortality rates from 1985 to 2008. Journal of Clinical Oncology, 30, 401–405. Rutten, L. J., Arora, N. K., Bakos, A. D., Aziz, N., & Rowland, J. (2005). Information needs and sources of information among cancer patients: a systematic review of research (1980–2003). Patient Education and Counseling, 57, 250–261. doi:10.1016=j.pec.2004.06.006 Smith-McLallen, A., & Fishbein, M. (2009). Predicting intentions to engage in cancer prevention and detection behaviors: examining differences between Black and White adults. Psychology Health & Medicine, 14, 180–189. doi:10.1080=13548500802183575 Squiers, L., Finney Rutten, L. J., Treiman, K., Bright, M. A., & Hesse, B. (2005). Cancer patients’ information needs across the cancer care continuum: evidence from the cancer information service. Journal of Health Communication, 10(Suppl 1), 15–34. doi:10.1080= 10810730500263620 Vanderpool, R. C., Kornfeld, J., Rutten, L. F., & Squiers, L. (2009). Cancer information-seeking experiences: the implications of Hispanic ethnicity and Spanish language. Journal of Cancer Education, 24, 141–147. doi:10.1080=08858190902854772 Viswanath, K. (2006). Public communications and its role in reducing and eliminating health disparities. Examining the health disparities research plan of the National Institutes of Health: Unfinished business. Washington, DC: Institute of Medicine. Viswanath, K., Breen, N., Meissner, H., Moser, R. P., Hesse, B., Steele, W. R., & Rakowski, W. (2006). Cancer knowledge and disparities in the information age. Journal of Health Communication, 11(Suppl 1), 1–17. doi:10.1080=10810730600977517 Viswanath, K., Ramanadhan, S., & Kontos, E. Z. (2007). Mass media. In S. Galea (Ed.), Macrosocial determinants of population health (pp. 275–294). New York, NY: Springer. Weaver, K. E., Geiger, A. M., Lu, L., & Case, L. D. (2012). Ruralurban disparities in health status among US cancer survivors. Cancer, 119, 1050–1057. Williams, D. R., Kontos, E. Z., Viswanath, K., Haas, J. S., Lathan, C. S., MacConaill, L. E., . . . Ayanian, J. Z. (2012). Integrating multiple social statuses in health disparities research: The case of lung cancer. Health Services Research, 47(3 Pt 2), 1255–1277. doi:10.1111=j.1475-6773.2012.01404.x
Copyright of Journal of Health Communication is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
