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CIN: Computers, Informatics, Nursing:
doi: 10.1097/NCN.0b013e318214093b
Feature Article

Comparison of Social Support Content Within Online Communities for High- and Low-Survival-Rate Cancers


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Author Information

Author Affiliations: College of Nursing-Adult Health, Wayne State University, Detroit, MI (Dr Buis); College of Communication Arts and Sciences, Michigan State University, East Lansing (Dr Whitten).

The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Lorraine R. Buis, PhD, Wayne State University, College of Nursing, 5557 Cass Ave, Room 368, Detroit, MI 48202 (

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People experiencing cancer use the Internet for many reasons, particularly for social support. This study sought to determine how social support content within online support communities for different cancers varied according to cancer survival rate. A quantitative content analysis was conducted on 3717 posts from eight online communities focused on cancers with high and low 5-year relative survival rates. Using Optimal Matching Theory, we predicted that low-survival-rate communities would have more emotional support content than high-survival-rate communities, and high-survival-rate communities would have more informational support content than low-survival-rate communities. Emotional support content was consistently more common than informational support. Overall, high-survival-rate communities had a greater proportion of posts containing emotional support content (75%) than low-survival-rate communities (66%) (χ21 = 20.89 [n = 2235], P < .001). Furthermore, low-survival-rate communities had a greater proportion of posts containing informational support content (46%) than high-survival-rate communities (36%) (χ21 = 21.13 [n = 2235], P< .001). Although the relationships between survival rate and support types were significant, they were not as hypothesized. Deviations from theoretically predicted results suggest that individuals experiencing low-survival-rate cancers may have a greater desire for informational support online than individuals experiencing high-survival-rate cancers.

Cancer is a leading cause of death in America, second only to heart disease. One of every four deaths in the United States is cancer related, and in 2010, the American Cancer Society estimated that approximately 569 490 Americans would die of cancer that year. Although the average 5-year relative survival rate for all cancers is 68%, some forms of cancer have substantially higher or lower 5-year relative survival rates.1 Regardless of the type, any cancer diagnosis can be stressful to the patient, as well as other family members or friends. To help deal with the stress associated with illness, nurses and other healthcare providers often recommend that patients and their families seek out support groups. Although support groups have traditionally been thought of as face-to-face resources within a community, many support groups are now available on the Internet. Online support communities, which are groups of individuals who use electronic communication modalities, such as Internet message boards, mailing lists, chat rooms, and so on, to discuss shared commonalities and/or interests, may provide social support for cancer patients, as well as their caregivers, family, friends, and healthcare providers and may be referred to patients and their family members by health professionals. Understanding more about the kinds of social support available to users from online support communities may provide nurses and other primary care providers valuable insight into the types of interactions that potential users are likely to find within these online spaces.

Social support has often been linked to positive health outcomes and has been found to be negatively related to mortality rates.2-5 Increased social support has also been linked to fewer nonfatal strokes in women with suspected myocardial ischemia.6 Moreover, measures of social support have been found to predict survival in dialysis patients7 and stage II and III breast carcinoma patients,8 as well as future cardiac events in post-myocardial infarction patients.9

With the widespread diffusion of the World Wide Web, people have increasingly turned to online communities for social support for a variety of health issues, including cancer. Active online support communities exist for just about any type of cancer, and the online community literature documents the existence of communities for colorectal,10 breast,11-17 and prostate cancers,13,17 as well as leukemia.18 The presence of emotional and informational social support in cancer-related online communities has been documented,17,19,20 which is important as sources of social support are not always apparent to those who need it. For example, in a survey addressing information and social support needs of thyroid cancer patients, Roberts et al21 found that many patients believe medical professionals and hospital staff provided inadequate guidance on where to receive emotional support. Based on these findings, Roberts et al21 concluded that online support communities are a beneficial resource to connect users with support services and/or groups of other thyroid cancer survivors.21 Moreover, Ramos et al18 found that users of an online community for chronic myelogenous leukemia report that the knowledge they gained through their participation helped them make better decisions regarding treatment. In addition to providing social support for cancer patients, benefits of online support communities can extend to caregivers as they are often faced with barriers that preclude attendance at traditional face-to-face support groups because of time limitations, geographical proximity, or other resource barriers.22

Although there have been several content analysis case studies of individual online support communities,10,23-29 to date, cross-community comparisons of social support content, particularly in the context of cancer, are limited.17,19,20 To help bridge this gap, this investigation sought to understand how emotional and informational support content differs in online communities for cancers for high and low 5-year relative survival rates. This study utilized Optimal Matching Theory (OMT) as a theoretical framework for making predictions about emotional and informational social support content within online communities for high- and low-survival-rate cancers. Developed by Cutrona30 in the 1990s, OMT is a matching theory of social support suggesting that different types of social support may be best matched to different life stressors. Within OMT, five different types of support are identified: emotional, network, esteem, tangible, and informational support.30,31 Cutrona30 also indicates that controllability, referring to the amount of control one perceives to have over a stressor, is the most important influence on the type of support that a person requires. For events with a perceived high level of controllability, instrumental support and informational support are essential, whereas events that are perceived to be uncontrollable require more emotional support.30,31 Medical illnesses are characterized as negative, uncontrollable events,31 and in health-related circumstances, it is posited that emotional support is often more beneficial. Moreover, it stands to reason that just as there exists a range of medical illnesses, the degree to which different illnesses may be controllable, and therefore the degree to which emotional support is more beneficial, exists on a spectrum. As 5-year relative survival rate may indicate how difficult it is to manage a specific type of cancer, in this study survival rate was used as a proxy for the controllability of cancer, and two hypotheses based on OMT were developed:

1. Hypothesis 1: Communities for cancers with low survival rates will contain more emotional support content than communities for cancers with high survival rates.

2. Hypothesis 2: Communities for high-survival-rate cancers will contain more informational support content than communities for low-survival-rate cancers.

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We conducted a quantitative content analysis32 on 3717 postings located in eight online cancer support communities located within the Association of Cancer Online Resources (ACOR) Web site and Yahoo! Groups. The methods utilized in this investigation were declared exempt by the institutional review board at Michigan State University.

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Using 5-year relative survival rates reported by the American Cancer Society, the online support communities included in this investigation focused on high- and low-survival-rate cancers. The low-survival-rate communities were focused on pancreatic and lung cancers, each with a less than 20% 5-year relative survival rate (6% and 16%, respectively, across all stages), while the high-survival-rate communities focused on melanoma and thyroid cancers, each with a more than 90% 5-year relative survival rate (91% and 97%, respectively, across all stages).1

Of the communities included in this sample, one community focused on each of the four cancer types was hosted by Yahoo! Groups, and a second was hosted by ACOR. Yahoo! Groups communities were included in this study as Yahoo! (Sunnyvale, CA) is a popular information portal familiar to many Internet users. Because they do not dedicate their services to any particular topic, Yahoo! is a destination for a very diverse audience, and users do not necessarily visit Yahoo! strictly for cancer-related information. Communities on Yahoo! Groups may or may not be moderated. To post messages in a Yahoo! Groups community, users are required to join the community by registering first with Yahoo! and then with the individual community. Registration with the community requires a Yahoo! login and an e-mail address. Although community members must join an individual Yahoo! community to post, some communities maintain publicly accessible archives that any Internet user can access. At the time of data collection, the Yahoo! communities focused on melanoma and pancreatic cancers had publicly accessible archives, whereas the thyroid and lung cancer communities did not.

The ACOR has become one of the largest and most well-known Web sites for cancer-related information and online cancer support communities and was included in this study because the ACOR Web site is devoted strictly to cancer-related information, resources, and support and is widely recognized within the cancer services community. All ACOR communities are moderated and require registration to join the community. To register, individuals must supply a valid e-mail address and a name. An automated e-mail is then sent to the supplied e-mail address, and individuals are required to confirm their registration by clicking on a link within the confirmation e-mail.

The sample of online support community postings identified for inclusion in this study was pulled in August 2006 and contained postings written by a diverse set of community members including cancer patients, survivors, and caregivers, as well as family members and friends of cancer patients. This study utilized a stratified sample of 12 weeks of posts from each of the eight online support communities. To control for seasonality, we randomly selected 1 week (considered a 7-day period starting on Sunday) from each month between July 2005 and July 2006. It is important to control for seasonality as particular times of the year (particularly around holidays) may not necessarily be representative of the types of interactions that occur throughout the year. We evaluated six communities according to this stratified, randomly selected period. Because the ACOR melanoma and thyroid cancer communities had fewer posts between July 2005 and July 2006, it was not possible to stratify the sample from these communities. As such, we evaluated a census of postings from this corresponding 1-year period for the ACOR melanoma and thyroid cancer communities. The content analyzed in this study consisted of individually posted messages located in the eight online communities, and the unit of analysis was the individual posting. While this method does not control for the fact that multiple posts in the sample may have been written by the same community members, because this investigation centered on understanding the content available within online support communities as a whole, individually posted messages were deemed an appropriate unit of analysis. All archived posts from our sampling period were included in this investigation, and no postings were excluded. In total, we identified 3717 postings for inclusion in this study.

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Data Collection and Analysis

Two trained coders analyzed content of the postings in this sample. Coders analyzed each post for the presence or absence of 10 different subtypes of informational and emotional support content identified through thematic content analysis. These categories were not mutually exclusive, and it was possible for each posting to contain multiple subtypes of informational and emotional support. Because we were interested only in the presence or absence of each subtype of support, the quantity of each subtype was not coded. The emotional support subtypes developed through thematic content analysis were guided by previous work by Klemm et al10 and White and Dorman.27 Because of the limits placed on human interaction within an electronic environment, we assumed that the only way to provide a person with instrumental support was to provide information; therefore, tangible aid or instrumental aid support in its purest form was not included in the coding protocol for this study. Table 1 summarizes the operational definitions of social support types used in this study.

Table 1
Table 1
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To establish intercoder reliability, after extensive training and practice, two coders independently analyzed a random subsample consisting of 5% of the total sample (n = 186 posts), which has been suggested by Kaid and Wadsworth33 to be a suitable sample size for establishing intercoder reliability. All variables in this study had a Cohen κ agreement34 of at least 0.85 or higher. We used descriptive statistics to describe the frequencies of emotional and informational support content within high- and low-survival-rate communities, as well as χ2 analyses to make comparisons.

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In total, 587 unique community members posted messages within our sample. The posting activity of community members varied greatly, ranging from one to 245 posts (mean, 6.3 [SD, 14.52] posts per member; median, 2.0 posts per member). For the complete breakdown of number of posts and unique posters per community, see Table 2. Of the 3717 sampled posts, 2235 (60%) contained at least one instance of social support content. The remaining 40% of posts contained instances of emotional and/or informational support seeking or off-topic posts not related to cancer. Of those posts that contained social support content, the number of support subtype themes ranged from one to six per post (mean, 1.51 [SD, 0.83]). At least one type of social support content occurred in approximately half or more of the postings within each community. Table 2 provides a complete breakdown of the percentage of posts within each community that contained at least one instance of social support content.

Table 2
Table 2
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Within the 2235 posts containing social support content, 1537 (69%) included emotional support content, 944 (42%) contained informational support content, and only 246 (11%) contained both emotional and informational support content. Encouragement support, the most frequent emotional support subtype, was present in 54% of posts containing support content. Prayer/spiritual support (16%), understanding support (15%), and sympathy support (11%) were also commonly present. Welcoming/belonging support was the least common emotional support subtype (2%). Within the posts containing social support content, mediated resource information and medication/treatment information were the most common informational support subtypes present (19% and 16%, respectively), while live assistance resource information, disease/symptom information, and general cancer informational support were the least common (4%, 6%, and 7%, respectively).

When looking at the posts with social support content, emotional support content was more common than informational support content in both high- and low-survival-rate communities. Contrary to hypotheses 1 and 2, within the posts containing social support content, high-survival-rate communities contained more emotional support content (75%) than low-survival-rate communities (66%) (χ21 = 20.89 [n = 2235], P < .001). Moreover, within the posts containing social support, low-survival-rate communities contained more informational support content (46%) than high-survival-rate communities (36%) (χ21 = 21.13 [n = 2235], P < .001). Finally, when looking at the posts with social support content, high- and low-survival-rate communities had few posts that contained both emotional and informational support content (11% each).

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In this study, we set out to examine how emotional and informational support content varied between communities for high- and low-survival-rate cancers. Based on OMT, we hypothesized that online communities for low-survival-rate cancers would have more emotional support content than communities for high-survival-rate cancers. Additionally, we hypothesized that online communities for high-survival-rate cancers would have more informational support content than communities low-survival-rate cancers. Our results indicate that while the relationship between 5-year relative survival rate and social support content was significant, the relationship was not as predicted in our hypotheses. Low-survival-rate communities contained less emotional support content and more informational support content than high-survival-rate communities. This finding suggests that Cutrona30 was correct in her assertions that controllability and social support are related, but not in the way we hypothesized.

Because our hypotheses were not supported as stated, we present two possible explanations for our findings. First, it is possible that while Cutrona30 was correct in asserting the relationship between controllability and social support, this relationship is different in online support communities focused on cancer. We suspect that within low controllability contexts, such as when dealing with low-survival-rate cancers, individuals may be desperate for information related to treatment and symptoms and therefore less focused on obtaining emotional support online. In contrast, in higher controllability contexts, such as when dealing with higher-survival-rate cancers, individuals may have less informational support needs, as well as a greater desire for emotional support from others online. Second, it is possible that communities for low-survival-rate cancers have more informational support content because community members have exhausted traditional information sources and are now turning to other people online for additional information. Conversely, it is possible that the information needs of individuals experiencing high-survival-rate cancers are easier to fulfill with traditional offline sources, and additional information from peers is not as necessary.

In this study, instances of emotional and informational support were prevalent in the eight sampled communities. This is consistent with findings from many previous studies of non-cancer-related online communities.24-26,29 Although the presence of emotional and informational support is also consistent with research by Meier et al,20 which found both types of support present within online communities for cancer, they documented that informational support was more prevalent than emotional support in these online spaces. One possible explanation for this difference may reside in the fact that different community members may have different support needs based on factors such as their relationship to cancer. For example, a recent study by Ginossar19 found that family members of cancer patients participated more in an online community focused on lung cancer than in a community for chronic lymphocytic leukemia. It addition, family members of cancer patients were found to utilize online cancer communities differently than patients, suggesting that different types of members have different support needs within an online community. In the present study, it is possible that the communities in our sample had different blends of types of community members than in the study by Meier et al,20 which could possibly lead to differing amounts of emotional and informational support content.

Another possible explanation for why emotional support was more prevalent than informational support in the current study, as compared with the study conducted by Meier et al,20 may possibly be attributed to the lack of consistency in coding schemes across this field of research. As there is no consistency across the different coding schemes of previous content analysis studies investigating the types of social support within online support communities, nor is there even consistency in the way that different types of social support are conceptualized from study to study, it may be impossible to accurately compare findings across studies.17,35,36 This speaks to the need to develop consistent ways of conceptualizing and identifying different types of social support within online support communities to contribute to greater generalizability of research findings.

From this current investigation, it is clear that individuals experiencing cancer, either as a patient, survivor, caregiver, family member, or friend, have a diverse set of social support needs. Results from this investigation demonstrate that emotional and informational support content is available within these online support communities and may help to educate nurses and other health professionals about the potential for these resources to offer social support to patients. This better understanding of online support communities may lead nurses and other health professionals to add referrals to these types of services to their arsenal of cancer-related treatments. This research contributes to the existing body of knowledge in that it is one of the first large-scale, cross-community comparisons of online cancer support communities. As research in the field of online support communities has been largely descriptive in nature, this investigation begins to allow for the understanding of how issues such as the survival rate of a cancer may be associated with the different types of social support content available within online communities.

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As with all research investigations, this study is not without limitations. Although our findings indicate a relationship between 5-year cancer survival rate and social support type, it is possible that our conceptualization of 5-year survival rate as a proxy for controllability was inherently flawed. It is possible that these are two separate constructs, which may suggest that survival rate is not an appropriate measure for operationalizing controllability. To extend OMT within this context, additional work should be done to find a more suitable measure for controllability. To better approximate controllability, perhaps future work should focus on creating and validating an instrument assessing the amount of control an individual feels that he/she has over the management of their cancer. Also, because of the limitations of the content analysis methodology used in this study, we are not able to provide a deeper understanding of people's motivations to provide social support within online support communities, nor were we able to gain an accurate picture of who the individual members of our sample were. Future research should seek to utilize other research methodologies such as surveys and interviews to more fully understand motivations for online support community utilization, as well as demographics. In addition, the quality and quantity of social support content of posted messages are unclear, and we cannot speak to whether the intended support recipients within our sample found the posted support content to be useful and/or beneficial. Additional research needs to determine the quality, quantity, and efficacy of online social support. Furthermore, this study cannot attest to whether the social support content was useful or beneficial to lurkers (individuals who read online community messages without actively participating through posting). As lurkers are thought to make up a substantial percentage of online community members,37 future work should seek to understand the extent to which lurkers may derive emotional and informational social support from online communities. Because this study did not focus on social support seeking, we can make no conclusions regarding how frequently people actively seek social support online. Future work should focus on the entire support process as it occurs online by studying social support seeking in conjunction with the provision of social support. For example, additional research should seek to address how frequently social support is sought and how often responses with social support messages are provided. By more fully understanding the social support process within online support communities, we may be better able to provide effective and efficient support services both online and offline. Finally, the fact that this study did not tie online support community use to actual health outcomes is another limitation of this investigation. If we truly wish to understand the impact of online social support communities within the health context, understanding how the social support that is received within an online environment impacts the actual health outcomes of community members is necessary.

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The authors thank Nicole Ellison, PhD, Charles Steinfield, PhD, Kami Silk, PhD, and Caroline Richardson, MD, for their guidance throughout this project, as well as Reema Kadri, MLS, for assistance with coding.

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Cancer; Internet; Online community; Social support

© 2011 Lippincott Williams & Wilkins, Inc.



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