Changes Over Time in the Utilization of Disease-Related Internet Information in Newly Diagnosed Breast Cancer Patients 2007 to 2013

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Original Paper

Changes Over Time in the Utilization of Disease-Related Internet Information in Newly Diagnosed Breast Cancer Patients 2007 to 2013

Christoph Kowalski1, PhD;
Eva Kahana2, PhD;
Kathrin Kuhr3, MSc;
Lena Ansmann1, PhD;
Holger Pfaff1, PhD

1IMVR, University of Cologne, Koeln, Germany
2Department of Sociology and Elderly Care Research Center, Case Western Reserve University, Cleveland, OH, United States
3Institute of Medical Statistics, Informatics and Epidemiology, University of Cologne, Koeln, Germany

Corresponding Author:
Christoph Kowalski, PhD

University of Cologne
Eupener Str 129
Koeln, 50933
Phone: 49 221 47897148
Fax: 49 221 47897142

1,2]. Over the past two decades, this has led to major changes in both the way health information is consumed and the amount of knowledge laypersons can access relatively easily [3,4].

Breast cancer offers an important arena for exploration of patient Internet use. Breast cancer is a major public health concern, as it is the most common form of cancer and the second major cause of cancer-related deaths among women in the United States. In Germany, 1 in 8 women will face a breast cancer diagnosis in her lifetime [5]. In the Internet age, a new role has become available to patients as information managers. Information acquisition through the Internet can help develop patient competence in dealing with challenges of a life-threatening illness, such as breast cancer [6].

Internet accessibility and its use for health purposes are distributed unequally over the population and its effects are not without controversies. Focusing on benefits to patients, a number of studies emphasize that using health information from the Internet is associated with stronger participation in decision making [7], better decisions [8], more frequent change of health behavior [9], and it may enable patients to communicate with doctors more effectively [10,11]. In contrast, other studies argue that using the Internet for health information may lead to erosion of the patient-provider relationship [12,13] or may confuse patients [14]. The early literature on health-related Internet use was particularly concerned with the limited ability of laypersons to evaluate information obtained on the Internet [15].

It is increasingly important for health care providers to give serious consideration to the information patients collect and to address their understanding of that information [16-18]. Taking into account the varying quality of websites providing health information, quality assurance and expert participation is warranted [19]. Nevertheless, there is indication of improvement in the quality of information offered to patients with breast cancer through a growing number of high quality websites (eg, National Institutes of Health [20], Agency for Healthcare Research and Quality [21], and National Cancer Institute [22] in the United States, and [23] and Krebsgesellschaft [24] in Germany). As Eysenbach stated, referring to the accuracy of cancer information websites as far back as 2003: it “is not so bad after all” [10]. The increasing sophistication of Internet sites enables patients to access not only sites designed for patients, but also peer-reviewed scientific articles that describe the latest research relevant to specific problems of the patient.

Patients using the Internet to gain access to health information for various illnesses tend to be younger and of higher socioeconomic status across countries [25-31]. This well-documented “digital divide” might become a major threat to equity in health care once relevant or even necessary information can only be or best be accessed online.

Although reports on the proportion of patients who use the Internet to gain health information vary widely [10,32,33], recent results based on 2011 data suggest that more than 50% of breast cancer patients [25] used the Internet to gain disease-specific information. Because of such widespread reliance on the Internet among female breast cancer patients, there is a clear need for up-to-date information on trends in this form of information acquisition. Differences in the proportion of individuals using the Internet not only differ according to the specific sample and the country or region under investigation, but also study design and the questions posed. Variability among studies in the nature of the disease and time since diagnosis also makes comparisons over time difficult and leaves unanswered questions about trends in the digital divide in relation to health information-seeking [34,35]. Although much research focuses on demographic correlates of online health information use, to our knowledge no study has yet investigated differences across locations of treatment. If variation across locations of treatment persists after controlling for individual characteristics this might offer further important clues to patient motivations for using the Internet for information. Thus, it is possible that unsatisfying experiences in the medical encounter or limited explanations communicated by health care providers would result in increased patient Internet use for health-related information.

The aim of our study was to expand the knowledge base about personal demographic, contextual, and temporal determinants of Internet use among newly diagnosed cancer patients. Specifically, this study aims to (1) present data on the proportion of 7 cohorts of newly diagnosed breast cancer patients treated in German breast center hospitals from 2007 to 2013 who used the Internet for information on their disease, (2) consider stability and change in patient characteristics predicting Internet use over time focusing on the digital divide based on age, education, and insurance status as an indicator of socioeconomic status, and (3) determine if use of information from the Internet varies by the hospital in which the patients were initially treated.

In doing so, we hope to expand existing knowledge by investigating developments over time and addressing the health care organization’s contribution to online health information use while taking clinical data (stage, type of surgery) and potentially relevant patient characteristics (partnership status, native language, gender) into account.


This report analyzed data drawn from a larger program of research designed to investigate the breast center concept of the German federal state of North Rhine-Westphalia (population 17.5 million). Patients treated for newly diagnosed breast cancer in one of the accredited breast center hospitals were asked to self-administer a questionnaire at home after discharge from the hospital [36]. Patients were included in the survey if they had a first diagnosis of breast cancer, underwent surgery during their current hospital stay, and had at least one malignancy, at least one postoperative histology, and a confirmed diagnosis of breast cancer with an International Classification of Diseases (ICD) code of C50.x or D05.x. Each year between February and June (survey period 6 months), all patients who fulfilled the inclusion criteria were included in the study consecutively. Cross-sectional surveys were performed with samples of patients from all accredited breast center hospitals in the region studied.

Shortly before discharge from the hospital, patients were asked by the hospital staff to give written consent to be included in the survey. Once the patients had given their consent, hospital personnel from the centers provided the research team with clinical information on the patients. The survey was designed according to Dillman’s Total Design Method with 3 contacts [37]. The survey was sent out to the patient’s home address within a week of receiving written consent. The study was approved by the institutional ethics committee of the University Hospital of Cologne, Germany. We analyzed data from each of the 7 years (2007 to 2013). Of the 35,371 patients meeting the inclusion criteria, 31,293 (88.47%) consented to the survey. Of these, 27,491 (87.85%) returned the questionnaire. These patients make up the sample for the analyses.


Dependent Variable

The dependent variable was use of the Internet for breast cancer–specific health information assessed based on response to a survey question that asked about such Internet use (yes/no).

Independent Variables

Patient sociodemographic data and clinical status served as independent variables. Patients were asked to indicate their date of birth, native language, insurance status, highest year of education attained, and partnership status on the questionnaire. Except for age (continuous) the sociodemographic variables are categorized into native language (German vs other), insurance status (statutory health insurance vs partly private/partly private), highest year of education (≥10 years of school vs 10 years of school), partnership status (living with a partner vs not living with a partner), and gender (male vs female).

In addition to the data collected by the patient questionnaire, medical personnel contributed clinical data and information about type of surgery performed after patient consent. The cancer stage was categorized using Union for International Cancer Control (UICC) categories [38]; type of surgery was dichotomized (breast-conserving treatment vs mastectomy).

Statistical Analyses

Proportions of Internet Users

The proportion of patients who used Internet information about breast cancer was calculated separately for each of the 7 cohorts, both overall and stratified for younger patients with more formal education to spotlight the digital divide (age 50 years; ≥10 years of school) and older patients with less formal education (age ≥70 years; 10 years of school). To test for differences over time, the Cochran-Armitage trend test was applied. In addition, the share of the 4 groups that resulted when stratifying for age and education among Internet users was analyzed. We performed bivariate tests to examine associations between the independent variables included in the model. We conducted chi-square tests for associations between all categorical variables (type of surgery, native language, years of schooling, insurance status, living with a partner, gender, cancer stage). Spearman rank correlation was used to examine the correlation between age and the ordinal variable cancer stage. Also, t tests were conducted to examine age differences for the different groups in the dichotomous variables. The cross-year dataset was used for these analyses.

Multilevel Models

Data from each survey cohort were analyzed separately and in an overall model using multilevel analysis. This is the method of choice when accounting for the nested structure of the data, such as patients (level 1) in hospitals (level 2) [39]. Two-level models without predictors were fitted to yield the intraclass correlation coefficient (ICC) for the null model. The ICC represents the proportion of the variance of the dependent variable attributable to the hospital level. In a second step, all patient characteristics were included. A number of patients indicated they did not have access to the Internet in an earlier question and did not respond to the dependent variable. To avoid case deletion, cases that indicated they did not have access to the Internet in the earlier question were coded as not having used the Internet. Cases with missing data in the dependent variable and missing data in this earlier question were excluded from all analyses (n=1022). Patients with missing data in the continuous age variable were excluded in the multilevel models (n=243), leaving 26,226 patients for the multilevel analyses. Missing data on all other independent variables were included in the model as separate categories to avoid case deletion, and omitted in the results tables. The ICCs of these models represent the proportion of variance attributable to the hospital-level characteristics after accounting for variation in the patient characteristics, (ie, the different patient case mix). Because of the small ICCs, no hospital-level characteristics were included in the models. The overall model included a cohort variable to account for the survey year. In addition, we included a gender variable that we did not include in the year-by-year analyses because of small strata. SPSS version 22.0 (IBM Corp, Armonk, NY, USA) was used for descriptive analysis and MLWiN 2.25 (Centre for Multilevel Modelling, Bristol, UK) for multilevel analysis. R 3.0.2 (R Project for Statistical Computing, Vienna, Austria) was used to calculate the Cochran-Armitage trend test.

Table 1 shows the percentage of breast cancer patients who reported they used the Internet to obtain information about their disease. There was a relatively steady, statistically significant increase in this percentage over the 7-year study period (2007: 26.96%, 853/3164; 2013: 37.21%, 1485/3991; χ21=138.0, P.001). No relevant changes were found for the proportion of younger, higher-educated patients who used the Internet (χ21=0.4, P=.51). Proportions for this group remained relatively stable, between 60% and 70% throughout the study period. The proportion of older patients with little formal education who used Internet information increased significantly from 2007 (2.9%, 13/444) to 2013 (4.7%, 29/617; χ21=6.8, P=.009) but remained below 6% for all cohorts. Among men, the overall proportion was only 25.4% (32/126, not presented in a table).

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