Information support for cancer survivors


  • Supplement sponsored by the American Cancer Society's Behavioral Research Center and the National Cancer Institute's Office of Cancer Survivorship.


Survivors' information-seeking behavior has traditionally been documented through analysis of inquiries to hotlines and cancer information services. Data from these self-selected inquiries tend to be restricted to a time around diagnosis, and to those populations possessing the wherewithal and motivation to seek information actively. The current study used data from a general population survey to assess 1) the prevalence of information-seeking behavior among survivors in the general population, 2) characteristics of seekers versus nonseekers, 3) ratings of information-seeking experience, and 4) actual versus preferred sources of information. Data were analyzed from the 2005 administration of the Health Information National Trends Survey (HINTS). HINTS is a cross-sectional, random digit dial telephone survey, weighted to provide estimates for the general population. Nearly half of all Americans (48.7%) indicated that they have looked for cancer information from 1 source or another. Percentages were highest for those who have been touched by cancer (63.1% of cancer survivors and 54.6% of those with family histories) and lowest for those with no cancer history (27.6% of those with no history). Quality concerns topped the list of information-seeking experiences for those recalling the last time they looked. Patterns of information-seeking revealed a discrepancy between preferred and actual source when tracked over years since diagnosis. Information-seeking is prevalent among cancer survivors and does not diminish over time. Prescriptions are given for reengineering the information environment to improve long-term outcomes for survivors. Cancer 2008. © 2008 American Cancer Society.

In a feature article appearing in the Health section of the New York Times on August 14, 2005, journalist Jan Hoffman summarized the modern cancer patient's experience in one, seemingly paradoxical, headline: “Awash in information, patients face a lonely, uncertain road.”1 Describing the experience of Meg Gaines, diagnosed with ovarian cancer and pictured holding mounds of computer printouts and clipped articles, the headline captured an inherent contradiction for cancer patients and survivors in the midst of the information age. Never before has so much information about cancer been made so immediately available to patients and practitioners alike, yet never has it appeared so difficult to integrate the raw data of evidence-based oncology into a coherent lifetime guide for healthy survivorship. As suggested in a subsequent article in the same newspaper by journalist Denise Grady,2 a diagnosis of cancer carries with it a lifetime of “making sense”3 in an environment of uneven care4 and fragmented communications.5


In 2000 the Institute of Medicine (IOM) released its landmark report on patient safety titled To Err is Human.6 The gist of the report was straightforward and direct. Systemic fractures in the organizational practice of medicine have created an epidemic of avoidable medical errors and lost opportunities for treatment that, when factored together, result in an untold number of deaths each year. The fractures are not unique to medicine, they occur in every human-based system in which variation occurs as a natural consequence of normal cognitive and physical limitation.7 What is different is that the culture of healthcare has not yet evolved the safety mechanisms—redundancies in communications, technologic backups, etc—that have been instituted in other high-risk industries.

One of the key fracture points, according to authors of the IOM report, is in the area of communication. At their best, effective communications can ensure that information in the sociotechnical environment8 of modern healthcare can be used to optimize positive outcomes for the patient.9, 10 Patient-centered communications can serve to 1) foster healing relationships between providers and patients over time, 2) bring patients into the informational loop for their own care, 3) address emotional concerns, 4) support decision-making, 5) manage uncertainty, and 6) enable patient self-management.11, 12 When communications fail, when noise enters the system or critical conversations fail to happen, the result can be a catastrophic error or a missed opportunity for intervention.6, 7

The influence of these fractures in cancer survivorship was made apparent by a study of 119 breast cancer patients who failed to receive guideline-recommended adjuvant therapy.4 In deconstructing events leading to the systemic exclusion of treatments, authors of the study concluded that a serious “communication breakdown” occurred in the delivery of care; that “the loop from recommendation to treatment” was not closed. According to the hospital staff interviewed, far too few mechanisms were built into the system of care that would allow surgical staff to follow-up with their patients, to ensure that the patients attended necessary referrals, or to monitor adherence to recommended treatment.4 Similar reviews of patients presenting with late-stage cervical cancer (a cancer that is wholly preventable in the population through early detection) revealed that a lack of adherence to routine screening examinations accounted for a majority of late-stage cases.13


Assessing patients' needs can, and should be, a starting point for improving the delivery of information services to cancer survivors. One way of assessing information needs is to evaluate the data collected systematically by 1 of the publicly or privately funded cancer information services. Indeed, much has already been learned from these centers regarding the nature of callers' questions, the composition of information seekers, and the psychologic motivations associated with looking for answers to self-generated questions.14–17 Going online through Web-based messaging and email has opened up other avenues for collecting data from public inquiries.18–20

Nevertheless, data from the call centers do not represent the full breadth of potential callers' needs. The self-initiated transactions logged at these centers come from those members within the public space who 1) learned about the existence of the call line or Web site, 2) were sufficiently motivated to access the resource, and 3) had the wherewithal to make the call or access the Web.15, 21, 22 Researchers have argued that these self-selected inquiries, although useful, are not generalizable to the full population of cancer information seekers but tend to be limited to callers of higher socioeconomic status. Calls into the hotlines also tend to cluster temporally around diagnosis and treatment decisions, and do not represent the full continuum of cancer survivorship from diagnosis to a lifetime of vigilance and coping. One review found that only 10% of catalogued studies (9 of 92) assessed the current needs of posttreatment survivors.23

The purpose of this study, then, was to gain insight into the information-seeking experiences of cancer survivors as distributed through the general population. To do this, data were analyzed from a national probability sample of adults in the U.S. with sufficient breadth to cover the information needs of people reporting themselves as cancer survivors, those with family members touched by cancer, and those with no personal or family experience of cancer. With such a sample frame in place, the following research questions were identified as important:

  • Research Question 1. How prevalent is cancer information-seeking in the general population and how do cancer survivors compare with other groups in terms of motivated usage of cancer information resources?

  • Research Question 2. Who among cancer survivors, as sampled from the general population, reported taking an active part in information-seeking activities?

  • Research Question 3. Where do information-seeking survivors turn when looking for quality cancer information? Is there a difference between where survivors would prefer to go in contrast to where they actually sought information?

  • Research Question 4. How do information-seeking survivors rate their satisfaction with the existing cancer information environment? Are there points of concern about the information environment that stand out against others?


Data Source

Data for this study are from the 2005 iteration of the Health Information National Trends Survey (HINTS 2005), a nationally representative survey designed to assess the impact of the cancer information environment and the public's knowledge of, attitudes toward, and behaviors related to cancer and cancer prevention. Comprehensive reports on the conceptual framework of HINTS and sample designs are published elsewhere.24, 25

Data for HINTS 2005 were collected from February through August 2005. The cross-sectional survey was administered by trained interviewers to representative samples of American households drawn from all telephone exchanges in the U.S. One adult (aged ≥18 years) was selected from each household to participate in the full survey during a household screening. In 2005, response rates were 34% at the household screening level (ie, the initial contact with the household used for sampling purposes), and 61% at the sampled person interview level (ie, completion of the interview by the sampled household member). Every sampled adult who completed a questionnaire was assigned a final sampling weight and a set of 50 replicate sampling weights. These sampling weights were used for the purpose of computing nationally representative estimates, to adjust for nonresponse, and to reduce the sampling variance of estimators through utilization of information from more robust sources than the corresponding HINTS estimates (eg, estimates obtained through the Current Population Survey, which has much larger sample sizes than HINTS). Data were available from 5586 extended interviews for use in analyses.



HINTS 2005 respondents were asked “Have you ever looked for cancer information from any source?” (yes/no). Respondents also indicated the timing of their most recent information search (within the last year/ > 1 year ago).

Information source preferences

Information source preference was assessed by asking respondents “Imagine that you had a strong need to get information about cancer. Where would you go first?” Responses were combined into 3 groups: Health Care Provider (HCP), Internet, and Other (includes print media, family/friends/coworkers, cancer organization/cancer survivor, and 1–800 telephone numbers).

Information source use

For HINTS respondents who had personally searched for cancer information, source use was assessed by asking “The most recent time you wanted information on cancer, where did you go first?” Responses were coded into the same 3 groups used to assess source preference: Health Care Provider (HCP), Internet, and Other.

Information-seeking experiences

Experiences seeking cancer information were assessed using the Information SEeking Experiences Scale (ISEE).26, 27 HINTS respondents who had personally searched for cancer information indicated their agreement on a 4-point scale to statements about their most recent search: “It took a lot of effort to get the information that you needed”; “You felt frustrated during your search for the information”; “The information you found was too hard to understand”; and “You were concerned about the quality of information.” These items were examined individually and as a continuous scale, in which higher scores indicate better information search experiences (α = .76).

Sociodemographic variables

Sex, age, education, annual household income, race/ethnicity, and whether a respondent had health insurance were included in the current study. Three discrete categories of cancer history were also included: 1) no personal or family history of cancer, 2) no personal but a family history of cancer, and 3) personal history of cancer. For analyses of cancer survivors, time since diagnosis (≤1 year postdiagnosis, 2–5 years postdiagnosis, 6–10 years postdiagnosis, and 11+ years postdiagnosis) was included as well.

Formative Testing of Items

All measures in the survey were evaluated in a cognitive laboratory using concurrent protocol analysis techniques.28, 29 Items were reviewed up to 3 times, depending on the degree of modification needed to stabilize interpretation and use. The full survey was also pilot-tested before the main field period, and a translated version of the instrument was created in Spanish for non-English-speaking, Hispanic respondents.30

Data Analysis

Analyses were conducted using SAS-callable SUDAAN software (version 9.0)31 to account for the complex survey design of HINTS 2005 and to obtain appropriate standard errors and 95% confidence intervals (95% CIs) for point estimates. Responses of “refused” or “don't know” were counted as missing. Weighted descriptive statistics are presented, and weighted data were used in all inferential statistical analyses. Bivariate analyses (chi-square) estimated associations between sociodemographic characteristics and cancer history as well as information outcomes and cancer history. For cancer survivors, binomial logistic regression estimated associations between sociodemographic characteristics and information-seeking; multinomial logistic regression estimated associations between sociodemographic characteristics and information source preferences. For survivors who had ever searched for cancer information, multinomial logistic regression estimated associations between sociodemographic characteristics and source use; multivariate linear regression estimated associations between survivor characteristics and information-seeking experiences.

Informed Consent

Data were collected as part of HINTS, a national survey of the general population. HINTS went through an expedited review with the National Cancer Institute's Institutional Review Board in 2001 that gave it an “exempt” status; hence, a formal informed consent was not needed. Clearance for conducting the survey was also obtained from the U.S. government's Office of Management and Budget (OMB #0925-0538).


Of the 5586 observations available for analyses, 5553 could be identified in terms of survivorship status. Of these, 865 reported having a personal history of cancer, 3397 reported having a family history of cancer only, and 1291 reported having no personal or family history with cancer. Table 1 depicts the weighted population characteristics along with the accompanying chi-square statistics within each of these groupings. The majority of the demographic variables appeared to be distributed in a way that is reflective of the population at large for adults aged ≥18 years (eg, median income at around the < $50,000 mark; available at Accessed on September 4, 2007). However, differences across groups in demographic characteristics were observed (Table 1). Compared with other groups, respondents with a personal history of cancer were more frequently female and non-Hispanic white. Survey respondents with a history of cancer were also somewhat older and more frequently reported having health insurance than other groups. Among respondents with a personal history of cancer, the most frequently identified types of cancer included skin cancer (29.5%), breast cancer (16.9%), and prostate cancer (10.1%). The distribution of reported cancers among the HINTS sample is consistent with cancer incidence estimates derived during a similar time period, suggesting that the HINTS distribution of survivors is fairly representative of the national population.32

Table 1. Respondent Characteristics Grouped by Survivor Status (n = 5553)
Respondent characteristicWeighted % within survivor status group (95% CI)
Personal history (n = 865)Family history only (n = 3397)No history (n = 1291)
  1. 95% CI indicates 95% confidence interval; DK, did not know; NH, non-Hispanic.

Gender (chi-square = 10.53; P < .01)
 Male44.2 (42.0–46.4)46.8 (46.0–47.6)52.8 (51.2–53.4)
 Female55.8 (53.6–58.0)53.2 (52.4–54.0)47.2 (45.6–48.8)
Age (chi-square = 439.69; P < .01)
 18–34 y4.8 (3.6–6.0)31.8 (31.1–32.5)39.6 (38.0–41.2)
 35–49 y17.7 (15.5–19.9)33.7 (33.1–35.3)27.6 (26.4–28.8)
 50–64 y32.4 (30.4–34.4)22.2 (21.6–22.8)20.4 (19.0–21.8)
 65–74 y22.6 (21.0–24.2)7.6 (7.2–8.0)7.7 (6.9–8.5)
 ≥75 y22.4 (20.6–24.2)4.8 (4.5–5.1)4.7 (4.0–5.4)
Education (chi-square = 22.51; P < .01)
 Less than high school14.1 (12.7–15.5)11.8 (11.1–12.5)21.1 (19.6–22.6)
 High school31.5 (29.6–33.4)30.1 (29.3–30.9)28.5 (26.8–30.2)
 Some college30.7 (28.5–32.9)34.0 (33.1–34.9)27.9 (25.9–29.9)
 College graduate23.7 (22.0–25.4)23.9 (23.3–24.5)22.5 (21.3–23.7)
Annual income (chi-square = 29.30; P < .01)
 < $25K25.9 (24.0–27.8)19.3 (18.2–20.4)26.6 (24.9–28.3)
 $25K to < $50K22.4 (20.5–24.3)21.4 (20.2–22.6)20.3 (18.9–21.7)
 $50K to < $75K16.2 (14.7–17.7)19.4 (18.3–20.5)17.2 (15.9–18.5)
 ≥$75K18.8 (17.2–20.4)26.3 (25.0–27.6)19.4 (18.0–20.8)
 Refused/DK/missing16.7 (15.0–18.4)13.7 (12.7–14.7)16.6 (14.9–18.3)
Race/ethnicity (chi-square = 172.61; P < .01)
 Hispanic/Latino5.1 (4.1–6.1)9.2 (8.5–9.9)26.1 (24.5–27.7)
 NH white84.7 (83.1–86.3)74.0 (65.0–83.0)54.3 (52.8–55.8)
 NH African American5.1 (4.2–6.0)10.6 (9.8–11.4)10.7 (9.6–11.8)
 NH other5.2 (4.1–6.3)6.7 (6.0–7.4)8.9 (7.6–10.2)
Health insurance (chi-square = 74.37; P < .01)
 Have health insurance93.8 (92.5–95.1)86.5 (85.6–87.4)71.5 (69.2–73.8)
 Do not have health insurance6.2 (4.9–7.5)13.5 (12.6–14.4)28.5 (26.2–30.8)
Time since diagnosis
 ≤1 y15.8 (12.3–19.4)  
 2–5 y31.3 (26.0–36.7)  
 6–10 y16.1 (12.9–19.4)  
 ≥11 y36.7 (32.1–41.3)  

Research Question 1. Information-seeking Prevalence and Survivorship Status

In Figure 1 we investigate the prevalence of cancer information-seeking, defined as having ever searched for cancer information, as estimated for various segments of the population. For comparison purposes, we begin with an overall estimate for the entire sample frame; that is, for all noninstitutionalized Americans aged ≥18 years. That estimate suggests that a little less than half (46.7%) of the adult population in the U.S. has actively looked for cancer information from any source; among these respondents, 71.2% reported that they had sought said information within the last year. Next to the overall estimate, we overlay estimates for subpopulations based on responses to questions regarding survivorship. The first comparison separates the estimates by survivorship status, with only 27.6% of those who have never been “touched by cancer”33 indicating that they had engaged in active searching. The percentage rises dramatically for the 2 groups most closely influenced by cancer, with up to 54.6% of those with family histories and up to 63.1% of cancer survivors looking for information. The trend shows an overall increase in engagement with the information environment among people who have been touched by cancer either through a family or personal history (χ2 = 185.67; P < .01).

Figure 1.

Information-seeking (ever searched for cancer information). HINTS indicates Health Information National Trends Survey.

In Figure 2, we switch our frame of analysis to just individuals who have searched for cancer information, and from among those we indicate percentages of searchers who have looked for cancer information during the past year. Of note is that information seekers, regardless of cancer status, appear to be highly engaged with the cancer information environment: Overall, 71.2% of information seekers had conducted their most recent search within the past year. Not surprisingly, nearly all cancer survivors diagnosed within the past year had searched for cancer information during that same time period (97.2%). Although smaller percentages of survivors had recently searched further from time of diagnosis, the percentage of survivors who had sought cancer information in the past year was relatively constant across the remaining groups and remained high at approximately half the sample. Finally, compared with survivors overall, information seekers with a family history or no history of cancer were more likely to have searched for cancer information during the past year (χ2 = 17.13; P < .01).

Figure 2.

Information-seeking (searched within the past year). Hx indicates history; HINTS, Health Information National Trends Survey.

Table 2 displays differences in our other information-related study outcomes in relation to survivorship status. Although the majority of all groups reported preferring an HCP as a first source of cancer information, this preference was stronger among HINTS respondents with a personal or no history of cancer (χ2 = 73.70; P < .01). Conversely, although a majority would prefer to use their HCP to get information concerning cancer, only a minority of seekers actually did: significantly more respondents with a personal history of cancer had used an HCP as a first source of cancer information (41.9%) compared with those with a family (21.6%) or no history (16.2%) of cancer (χ2 = 47.0; P < .01). Finally, information search experiences varied by survivorship status. Although suboptimal information search experiences were fairly prevalent among all HINTS respondents, cancer survivors were least likely to report that their most recent search took a lot of effort (χ2 = 7.20; P = .03), and respondents with a family history of cancer were most likely to have been frustrated by their most recent search (χ2 = 7.19; P = .03).

Table 2. Information Outcomes by Survivor Status
Information outcomeWeighted % within survivor status group (SE)
Personal historyFamily historyNo history
  1. SE indicates standard error.

Ever searched for cancer information? (chi-square = 185.67; P < .01)
Yes63.11 (2.23)54.64 (1.14)27.56 (1.74)
No36.89 (2.23)45.36 (1.14)72.44 (1.74)
Most recent search for cancer information (chi-square = 17.13; P < .01)
Within the last y60.47 (2.78)72.75 (1.18)74.97 (3.78)
>1 y ago39.53 (2.78)27.25 (1.18)25.03 (3.78)
Information source preference (chi-square = 73.70; P < .01)
Health care provider68.49 (2.13)50.53 (1.06)61.25 (2.03)
Internet19.99 (1.81)34.14 (1.10)26.36 (1.52)
Other11.52 (1.61)15.32 (0.90)12.39 (1.29)
Source used first in most recent search (chi-square = 47.01; P < .01)
Health care provider41.88 (2.80)21.59 (1.32)16.21 (2.37)
Internet36.04 (2.67)50.07 (1.37)48.87 (3.78)
Other22.08 (2.09)28.34 (1.22)34.92 (3.69)
It took a lot of effort to get the information you needed (chi-square = 7.20; P = .03)
Strongly agree/agree30.47 (2.50)38.69 (2.00)37.56 (3.21)
Strongly disagree/disagree69.53 (2.50)61.31 (2.00)62.44 (3.21)
You felt frustrated during your information search (chi-square = 7.19; P = .03)
Strongly agree/agree23.15 (2.48)28.29 (1.46)22.27 (2.18)
Strongly disagree/disagree76.85 (2.48)71.71 (1.46)77.73 (2.18)
The information you found was too hard to understand (chi-square = 0.39; P = .82)
Strongly agree/agree24.32 (2.51)23.67 (1.03)22.11 (2.72)
Strongly disagree/disagree75.68 (2.51)76.33 (1.03)77.89 (2.72)
You were concerned about the quality of the information (chi-square = 2.18; P = .34)
Strongly agree/agree44.48 (2.96)48.73 (1.55)44.84 (3.20)
Strongly disagree/disagree55.52 (2.96)51.27 (1.55)55.16 (3.20)

Research Question 2: Characteristics of Information-seeking Survivors

We next sought to understand what differentiated information seekers from nonseekers within the survivorship population. Table 3 shows the results of a multivariate regression model estimating the odds of information-seeking. Information-seeking survivors tended to be younger and to be better educated. Compared with survivors aged ≥75 years, survivors ages 35 to 49 years were more than twice as likely to have ever searched for cancer information (odds ratio [OR] of2.71), and survivors ages 50 to 64 years were nearly 4 times more likely to have searched (OR of 3.89). The probability of information-seeking increased steadily with years of education; compared with survivors who did not complete high school, those who did had >3 times the odds of having searched for cancer information (OR of 3.76), and this ratio nearly doubled for survivors with some (OR of 6.11) or completed (OR of 6.66) college education.

Table 3. Multivariate Regression Models of Information Outcomes for Survivors
Survivor characteristicInformation seeking* (OR; 95% CI)Information source preference (OR; 95% CI)Information source use (OR; 95% CI)ISEE§ (ß; SE ß)
  • OR indicates odds ratio; 95% CI, 95% confidence interval; ISEE, Information SEeking Experiences Scale; SE, standard error; DK, does not know; NH, non-Hispanic.

  • *

    Binary logistic model; OR = search/no search.

  • Multinomial logistic model; OR = prefer Internet/prefer healthcare provider.

  • Multinomial logistic model for information seekers only; OR = used Internet/used healthcare provider.

  • §

    Linear model for information seekers only; higher scores indicate better search experiences.

GenderP = .21P = .76P < .01P = .27
 Female1.32 (0.85–2.07)1.07 (0.63–1.83)1.27 (0.69–2.33)3.18 (2.89)
AgeP < .01P < .01P < .01P = .39
 18–34 y2.00 (0.55–7.26)13.31 (1.97–89.70)12.62 (1.02–156.43)7.35 (12.24)
 35–49 y2.71 (1.34–5.45)26.42 (6.67–104.60)10.63 (2.80–40.40)11.58 (4.85)
 50–64 y3.89 (1.95–7.75)25.87 (7.34–91.14)6.71 (1.76–25.62)5.91 (4.95)
 65–74 y1.33 (0.75–2.36)11.07 (2.83–43.25)6.78 (1.87–24.58)5.09 (4.47)
 ≥75 y1.
EducationP < .01P = .08P = .01P = .70
 Less than high school1.
 High school3.76 (1.82–7.77)0.87 (0.23–3.24)1.001.81 (6.09)
 Some college6.11 (2.81–13.28)1.36 (0.42–4.41)1.56 (0.64–3.77)2.18 (5.25)
 College graduate6.66 (2.99–14.87)2.21 (0.61–8.03)2.93 (1.23–6.97)−1.97 (6.60)
Annual incomeP = .32P = .52P = .95P = .09
 $25K to <$50K1.30 (0.67–2.52)0.98 (0.43–2.24)1.00 (0.31–3.18)8.65 (4.72)
 $50K to <$75K2.10 (1.01–4.35)1.35 (0.54–3.38)1.19 (0.30–4.76)9.59 (5.40)
 ≥$75K1.35 (0.62–2.91)1.67 (0.67–4.19)1.34 (0.32–5.65)12.27 (5.84)
 Refused/DK/missing1.00 (0.54–1.84)1.70 (0.64–4.51)1.06 (0.36–3.10)1.14 (4.83)
Race/ethnicityP = .89P = .22P = .42P = .22
 Hispanic/Latino1.28 (0.39–4.15)1.36 (0.27–6.86)0.74 (0.13–4.33)−5.77 (6.02)
 NH white1.
 NH African American0.64 (0.18–2.31)0.31 (0.07–1.41)1.99 (0.63–6.27)−2.58 (6.35)
 NH other1.03 (0.32–3.24)0.36 (0.09–1.47)1.15 (0.28–4.72)−14.15 (8.91)
Health insuranceP = .70P = .61P = .99P = .69
 Have health insurance1.
 Do not have health insurance0.83 (0.32–2.18)0.47 (0.08–2.87)1.04 (0.23–4.77)3.00 (7.53)
Time since diagnosisP = .78P = .60P = .03P = .49
 ≤1 y1.
 2–5 y1.02 (0.48–2.18)1.65 (0.74–3.69)2.56 (0.81–8.14)0.78 (4.31)
 6–10 y0.78 (0.41–1.46)1.60 (0.61–4.21)2.05 (0.71–5.91)−2.47 (3.93)
 ≥11 y0.91 (0.46–1.79)1.35 (0.53–3.47)0.93 (0.34–2.53)−4.18 (4.17)

Research Question 3. Survivors' Actual and Preferred Sources of Information

In HINTS 2005, respondents were asked to imagine a hypothetical situation in which they had a strong need to look for cancer information. Given that need, respondents were asked where they would likely go first for information. Responses for the full survey frame were placed into 1 of 12 categories according to prompts on the Computer Assisted Telephone Interview screen. Categories included books (1.9%), brochures (0.2%), cancer organization (3%), family (4.1%), friend/coworker (1%), healthcare provider (54.3%), Internet (29.9%), library (2.4%), magazines (0.3%), newspapers (0.3%), someone with cancer (0.2%), telephone information services (0.1%), other specified (0.5%), and a residual category of not ascertained or do not know (1.6%). Overwhelmingly, responses clustered into 2 main categories, with HCP leading as the most common preferred source of cancer information (an estimated 54.3% of the entire U.S. adult population) followed by the Internet (an estimated 29.9%). None of the other single categories came close to matching frequencies in these 2 individual categories.

Those in the sample who had reported looking for cancer information were asked to indicate where they had gone first. In this case, the pattern switched for the main categories with the majority indicating that they had gone to the Internet first (46.7%), and a smaller, but still substantive, percentage reporting that they had gone to their HCP first (23%). This overall finding of preferring to go to HCP first, but actually using the Internet first replicates a pattern uncovered previously in the HINTS 2003 data.34

To understand source use and source preference in more detail, we used multinomial logistic regression to compare the odds of having used or preferring the Internet to the odds of having used or preferring an HCP for information-seeking. The results are displayed in Table 3. Of the sociodemographic characteristics examined in this study, only survivors' age was found to be significantly associated with preferring the Internet over an HCP as a first source of cancer information. All survivors aged < 75 years were more likely than those aged ≥75 years to prefer the Internet to an HCP as an information source (P < .01). Similarly, among survivors who had searched for information, those aged < 75 years were more likely than those aged ≥75 years to have used the Internet before an HCP in their most recent search (P < .01). Furthermore, survivors who had completed college were more likely than those who had completed high school or less to have used the Internet before an HCP in their most recent search (P < .05), and post hoc comparisons revealed that survivors 2 to 5 years from diagnosis were more likely to have used the Internet before an HCP compared with those ≥11 years after diagnosis (P < .05).

The pattern of source preference versus source usage is more nuanced when evaluating survivors' data than it is for the general population. Figure 3 compares preference against usage across years since diagnosis, using estimated percentages adjusted for the influence of the demographic variables (age, sex, education, race/ethnicity, income, and health insurance). As with the overall population, survivors preferred contacting their HCPs regardless of how long it had been since they were diagnosed. The usage data show a different pattern. During the first year after diagnosis, cancer patients actually reported going to their HCPs as a source of first resort. That pattern changes, however, when examining years 2 through 10. Here Internet usage exceeds provider usage as a first source. The trend reverses again for those living with their cancers for > 11 years (a delay effect that might be confounded with generational effects on Internet use34).

Figure 3.

Cancer survivors' information source preferences and information source use. Weighted percentages are adjusted for gender, age, education, annual income, race/ethnicity, and health insurance status.

Research Question 4. Survivors' Information-seeking Experiences

Survivors who reported looking specifically for cancer information in the past were asked to recall their last searching experience. These respondents were then asked to provide ratings on the ISEE scale. Figure 4 portrays the weighted proportions within this response group of those answering “strongly agree” or “somewhat agree” to each of the scales' constituent items. From a scan of the items in the scale, concerns over quality (“I was concerned about the quality of the information”) stood out as a dimension of particular concern. Nearly half of survivors (44.6%), among those who recounted their experience of looking for information, expressed worry over the quality of the information they retrieved.

Figure 4.

Cancer survivors' (n = 865) information-seeking experiences: weighted.

A continuous index of search experiences was examined using multivariate linear regression, in which a higher ISEE scores indicated better information search experiences. None of the sociodemographic variables considered in this study were found to be significantly associated with search experiences; there was marginal evidence that increasing annual income was associated with more positive information-seeking experiences (P = .09).


From the HINTS 2005 data it is apparent that “looking for information about cancer” is not an experience restricted to a privileged segment of the population but appears to be quite common in the public at large. From the data presented in this article, 46.7% of the general U.S. adult population, or a little over a million Americans, have looked at 1 time or another for information regarding the disease, its causes, its prevention, its treatment, or its sequelae (Fig. 1). These data are consistent with analyses conducted on the HINTS 2003 data.35

Not surprisingly, a motivated use of information resources appears to be the hallmark of many who have been touched by cancer. Nearly two-thirds of cancer survivors and a little more than half of those with family histories of cancer reported having looked for information about cancer from any source. By contrast, barely more than 25% of those with no personal or family experience of cancer reported searching for information about the disease. For cancer survivors, the experience is nearly universal during the first year since diagnosis, with 97% of those with a recent diagnosis having looked for cancer information during the previous 12 months. Interestingly, the need to search for information about cancer appears to continue, with roughly half of those survivors diagnosed in the past (2 to 11 or more years) having reported looking for cancer information within the previous 12 months. These data match analyses of the HINTS 2003 data, suggesting that many (although not all) cancer survivors look for information from a variety of sources, including the Web.36

Information-seeking Beyond the ‘Transition’

Supportive, effective communications should be the hallmark of a world-class healthcare system for cancer survivors. As the authors of the IOM 2006 report From Cancer Patient to Cancer Survivor: Lost in Transition reasoned, a patient-centered approach is essential to survivorship care. This includes a responsiveness to patient needs, and effective communication and information sharing.37 Nevertheless, the authors of the report expressed concern that as patients transitioned to the status of ‘survivor,’ they might find themselves ‘lost’ in an information environment that is fragmented and that has abdicated responsibility for long-term support of survivors' needs.

The data reported in the current study provide at least a preliminary indication of information-seeking patterns at this phase of transition. From the multinomial model we constructed to explain preference for Internet versus Provider, we know that age was the most significant predictor of Internet usage. The finding is consistent with other research on demographics and Internet use.34 In Figure 3, we mapped preference and usage patterns onto years since diagnosis, while controlling statistically for the influence of age and other demographic variables. From the graph, we do not observe many differences because of preference: all survivors showed a strong interest in going to their provider teams first before going to other sources. However, the usage patterns suggest a different story. Those who have just been diagnosed report going to their providers first, as might be expected. Presumably, access to a treatment team would be frequent during this first year and cancer patients would find it easy to pose their questions to medical staff. During Years 2 to 10 after diagnosis, the point of transition, the pattern reverses and the profile resembles that of the general population. Survivors prefer going to their HCP for quality information, but in reporting actual usage revealed going to the Internet as a source of first resort. The Internet, always on and always available, became the first place to look whenever a ‘strong need’ arose to obtain information on cancer and cancer survivorship. Given the uneven and unstructured environment of the World Wide Web,38 it is little wonder that concerns regarding quality topped the list of reactions to information-seeking. Moreover, our multivariate model, in which we regressed a continuous score from our information-seeking experiences scale (ISEE) onto demographics, did not yield any significant relationships: Everyone experienced some degree of confusion when looking for cancer information, a finding that duplicates research done with the scale on the general population.26

Several interesting differences in information-seeking by survivorship status were observed. Preference for an HCP as a first source of cancer information was stronger among respondents with a personal or no history of cancer compared with those with a family history. Furthermore, although a majority of respondents indicated a preference to use their HCP to get information about cancer, significantly more respondents with a personal history of cancer had used an HCP as a first source of cancer information compared with those with a family or no history of cancer. These findings, coupled with the greater frustration in information-seeking reported by respondents with a family history of cancer, are consistent with previous research documenting dissatisfaction with regard to information-seeking among family members of cancer patients.39 Although physicians and other healthcare professionals are consistently named as the preferred source of cancer information among family members of cancer patients, in previous research, family members report difficulty obtaining desired information and limited contact with physicians.39

Engineering ‘Deep Support’ Into the Health Information Environment

One implication of these data is to consider ways of providing ‘deep support’ for cancer survivors' information needs well beyond the point of diagnosis and treatment.40 Historically, the business systems that support medicine have been built around a transactional model41: patients present with symptoms, often too late for preemptive care42; they are treated; and then they are dismissed. Transactional systems strain when dealing with chronic disease, preventive care, and personalized service.43 Yet the new systems must evolve to meet the demands of 21st century medicine.44 Medicine in the 21st century must use advances in information technology to create a service that is predictive of upcoming need, preemptive of early disease process, and personalized with individually tailored plans for treatment and self-management.44 The transformation is especially important in oncology, in which continuous monitoring over the lifespan will yield population gains from prevention, early detection, and control over metastasis.42 Following recommendations from IOM, these new systems must become ‘patient centric,’ using information technology to create ‘healing relationships’ with patients and their caregivers over time.

It is easy to imagine from these data how the environment of medicine can be reengineered to support the move to a relationship model. Electronic medical records (EMRs) are being put in place to guarantee patients that their medical records are accessible to all members of the care team within and across life phases.45 Personal Health Records, tethered to the continuity of the EMR, are being used to support self-management by offering patients full and complete access to their own health information and to offer ‘information therapy’ for the different questions that emerge over the lifespan.38 Appointment management systems, with reminders and status checks available to patients as well as providers, can be used to ensure continuity of care well beyond the transition period.

All these implementations are under priority consideration by the Department of Health and Human Services, the IOM, and countless Health Information Technology companies throughout the country.44 Its importance to healthy survivorship is paramount. In fact, some have argued that solving the information dilemma for patients and providers will offer one of the most important contributions to population health in the coming decade.5, 46–48

Limitations of the Data

The data presented in this article come from the 2005 administration of the HINTS, a cross-sectional view of cancer information attitudes and behavior in the general population. Caution should be taken not to overinterpret the observed associations between study variables, given the cross-sectional nature of the survey. The associations should be interpreted in light of converging evidence from other sources. Some of the correlations, such as the association between age and Internet use or sex and information-seeking, have been well documented. Others, such as the curvilinear association between Internet reliance and time since diagnosis, are new. These correlations merit continued study in other venues to substantiate and confirm. Future studies could also offer variations in wording for key items in the survey and could explore issues of convergent, construct, and predictive validity in greater depth.

Another limitation of the data has to do with the falling response rates in random digit dial (RDD) surveys. The HINTS program was designed after the rigorous and exacting procedures for coverage and selection used in other federal surveillance mechanisms. Nevertheless, RDD response rates are falling universally in all federal surveys because of a variety of pressures in the communication environment (telemarketing, the ‘do not call’ list, etc). The implications of these trends for nonresponse bias are not completely known. Fortunately, psychometric reviews suggest that population estimates for the types of items included in HINTS (eg, self-reports of health behaviors such as smoking) have not been affected dramatically by declining response rates.49

To maximize sample size in the multivariate analyses, information-seeking was defined according to having ever sought cancer information, rather than having sought information during the past year. Analysis of more recent cancer information may be more robust and reveal stronger associations with variables of interest.


Some have observed that a diagnosis of cancer signifies a lifetime of ‘making sense’ in an information environment that appears fragmented, uneven, and even disparate in quality to survivors. The data presented in this study confirm those expectations, but they also offer a perspective on survivors' information-seeking behavior across years since their initial diagnosis. The perspective provides a glimpse into how the health information environment can be reengineered to shore up support for the goals of self-vigilance, self-monitoring, and healthy living that characterize life after treatment. Health information technology can play a salubrious role in this reengineering effort, but only if it enhances the ‘healing relationship’ of patients, their families, and their healthcare providers in safeguarding health.