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Web 2.0 has improved interactions among peers on the Internet, especially for the many online patient communities that have emerged over the past decades. Online communities are said to be particularly beneficial peer support resources for patients with breast cancer. However, most studies of online patient communities have focused on those members who post actively (posters), even though there are many members who participate without posting (lurkers). In addition, little attention has been paid to the usage of online communities among non-English-speaking patients.
The present study explored the differences in peer support received by lurkers and posters in online breast cancer communities. It also examined the effects of such support on both groups’ mental health.
We conducted an exploratory, descriptive, cross-sectional, Web-based survey among members of four Japanese online breast cancer communities. In an online questionnaire, we asked questions regarding sociodemographics, disease-related characteristics, mental health, participation in online communities, and peer support received from those communities.
Of the 465 people who accessed the questionnaire, 253 completed it. Of the respondents, 113/220 (51.4%) were lurkers. There was no significant difference between lurkers and posters with regard to sociodemographic variables. About half of the posters had been given a diagnosis of breast cancer less than a year previously, which was a significantly shorter period than that of the lurkers (
We found that posters felt they received more benefits from online communities than lurkers did, including emotional support, helping other patients, and expressing their emotions. Yet even lurkers were found to gain a certain amount of peer support through online communities, especially with regard to advice and insight/universality. The results demonstrate that participation in online communities—even as a lurker—may be beneficial to breast cancer patients’ mental health.
The Internet has become increasingly popular in Japan since the 1990s. The Internet penetration rate in Japan exceeded 75.3% in 2008 [
Online communities are beneficial because of their availability; for instance, they have no time restrictions [
Since there are many treatment options for breast cancer, patients’ informational needs are high. In fact, breast cancer is the most common health topic researched on the Internet. Davison et al [
People can participate in online communities in two ways. Those who participate actively are known as posters, and those who do so passively, without making any postings, are known as lurkers [
Previous researchers have identified some of the reasons why people do not post in online communities, including lack software skills, dislike of the group dynamic, or feeling that the community is a poor fit for them [
To provide further evidence of online communities as a health resource, their effects on users’ health should be explored for both posters and lurkers. Moreover, although the Internet penetration rate in Japan is comparable with that of Western countries [
In this exploratory, descriptive, cross-sectional study, we conducted a Web survey from September to October 2007, referring to the checklist for the quality improvement of Web surveys [
We searched for online communities designed for breast cancer patients using the Google Japan and Yahoo! Japan search engines, which have the largest and second largest numbers of users in Japan, respectively [
We found 12 different breast cancer communities and asked their administrators for survey cooperation via email. During this process, we eliminated those online communities that had participants with non-breast cancers and those in which health care providers served as managers. All of the participating online communities had new posts within 28 days from the start of the survey. Finally, administrators from 4 of the initial 12 online breast cancer communities agreed to cooperate with this survey. The purpose of all of the communities was the exchange of peer support among breast cancer patients.
We developed an online questionnaire form for this open survey. We did not offer any incentive to participate. The four administrators explained the research to their communities’ members and provided the questionnaire URL by posting information on their respective community websites. The explanation of the research included a statement about the purpose of this study, the survey duration, and how to store the data on a secure server. We used secure websites to protect personal data. The usability and technical functions of the site were tested by a group of colleagues before we conducted the real test. The 5-page survey site had an average of 8 items on each page of the questionnaire.
Participants were able to navigate to the questionnaire site directly from the community sites by clicking on a hyperlink, and we explained that accessing the questionnaire site would be regarded as an agreement to participate in the survey. To prevent multiple entries from the same individuals, we checked the IP address of everyone who participated in the survey.
We did not have a valid instrument to precisely measure social support from peers for posters and lurkers, so we developed a new instrument for the purpose of our study. Of course, there are existing instruments that can be used to measure general social support, such as informational support and emotional support [
Our survey inquired about patients’ age, marital status (unmarried, married, or separated/widowed), education (middle school, high school, vocational school/2-year college, university/graduate school or higher), and employment (full-time job, housewife, part-time job, or unemployed). All of the participants were women.
The respondents were asked to report on four disease-related characteristics: (1) time since diagnosis of breast cancer (less than 1 year, 1–2 years, 3–5 years, 6–9 years, and 10 years or more, (2) stage of breast cancer at the time of diagnosis (below stage I to beyond stage III), (3) physical symptoms due to breast cancer or breast cancer treatment (eg, pain, feeling tired, arm paralysis, and nausea—respondents who selected more than 1 symptom were categorized as patients with symptoms, and we also counted the total number of symptoms), and (4) personal daily activity level, indicating physical condition. Activity level was indicated using a 5-point Likert scale that ranged from 5, living completely as usual, to 1, almost staying in bed.
Patients rated their levels of anxiety and depression on the Hospital Anxiety and Depression Scale (HADS), which has been used with the general population, cancer patients, and primary care patients [
We asked the participants “How often do you post in online communities?” The response items were every time, sometimes, or never—just lurking. We labeled respondents who selected every time and sometimes as posters and those who selected never—just lurking as lurkers.
On the basis of our previous interviews, we extracted 8 categories of peer support that study participants received by taking part in online communities. These categories were emotional support, informational support/advice, insight, emotional expression, universality, conflict, empowerment, and helper therapy. Emotional support and informational support were the functions of social support that Cohen et al found in their studies [
On the basis of these concepts, we formulated 34 items that described the peer support that took place in the online communities. All items had the format of a statement that began with the phrase “Through my participation in online communities...” Respondents could answer on a 5-point Likert scale that ranged from 5 (strongly agree) to 1 (strongly disagree). Emotional support, informational support/advice, insight, and universality were measured with 4 items; conflict was measured with 7 items; empowerment was measured with 4 items; and helper therapy was measured with 3 items.
The incidence and average scores of the sociodemographic variables and the current status of participation were calculated for posters and lurkers. Metric variables were analyzed by
We conducted an exploratory factor analysis to evaluate the factor structure of the support functions for posters and lurkers. While we knew the expected factors based on the previous research used to construct the items, we chose an exploratory factor analysis to determine the best factors for these data. We used principal axis factoring with promax rotation, an oblique rotation method that minimizes the number of variables with high loadings on each factor. This method simplifies the interpretation of the factors. We specified a precedent cut-off of .35 for acceptable factor loadings. To compare the factor constructions between posters and lurkers, we conducted a separate factor analysis for the extracted factors.
After conducting a factor analysis, we deleted 2 items from empowerment, 2 from helper therapy, and 1 from universality because the factor loadings of these items were all less than .35. Considering the factor loadings of each item and the content validity, we extracted 5 factors from the instrument. We then calculated the sum of the scores for each support function, which we referred to as the support score. To compare support scores between posters and lurkers, we conducted an analysis of variance (ANOVA) using a general linear model, controlling for time since diagnosis. We then calculated the Pearson correlation coefficient to determine the relationship between each health status (HADS) and support scores.
We explained the aim of the research project both verbally and in writing to the administrators of the online communities. They were assured that anonymity would be guaranteed and that refusing to participate or withdrawing consent would have no negative consequences. Since the investigation of patients may lead to psychological stress, we made special efforts to reduce the psychological burden of the questionnaire survey and exercised the utmost caution to protect participants’ privacy. The Ethics Review Committee of the University of Tokyo approved this study (approval number: 1789).
The number of visitors to the questionnaire site, or unique site visitors, was 465. We clarified the number of unique visitors based on IP addresses. The number of people who completed the questionnaire was 253. The completion rate, or the ratio of people who agreed to participate to the number of those who finished the survey, was 0.544.
To ensure valid data from a homogeneous sample, we excluded 33 participants: those who had recurrent breast cancer (n = 21), those who had not undergone any surgery for breast cancer (n = 8), and those who had an extremely low daily activity level (“almost staying in bed”) (n = 4). Ultimately, we analyzed 220 valid responses. We only analyzed completed questionnaires. The average time in which participants answered the questionnaire was 27 minutes. There were no outliers.
The respondents’ active participation in online communities was as follows: every time, n = 14 (6.4%); sometimes, n = 93 (42.2%); and never—just lurking, n = 113 (51.4%).
The characteristics of the survey respondents are shown in
Sociodemographic characteristics of posters and lurkers (n = 220) (excluding missing data)
Posters (n = 107) | Lurkers (n = 113) |
|
||||
n | % | n | % | |||
|
.55a | |||||
≤29 | 2 | 2 | 2 | 2 | ||
30–39 | 24 | 23 | 30 | 27 | ||
40–49 | 60 | 58 | 55 | 50 | ||
50–59 | 16 | 15 | 22 | 20 | ||
60–69 | 2 | 2 | 2 | 2 | ||
Mean (SD) | 43.71 (7.197) | 44.79 (7.474) | .66b | |||
|
.24a | |||||
Unmarried | 16 | 16 | 30 | 28 | ||
Married | 77 | 75 | 62 | 57 | ||
Separated/widowed | 10 | 10 | 16 | 15 | ||
|
.13a | |||||
High school | 22 | 21 | 31 | 29 | ||
Vocational school/2-year college | 34 | 33 | 43 | 40 | ||
University/graduate or higher | 47 | 46 | 34 | 31 | ||
|
.89a | |||||
Full-time | 30 | 28 | 33 | 30 | ||
Housewife | 37 | 35 | 32 | 29 | ||
Part-time | 22 | 21 | 30 | 27 | ||
Unemployed | 18 | 17 | 17 | 15 |
a χ2 test. Degrees of freedom were the number of category –1.
b
Health characteristics of posters and lurkers (n = 220) (excluding missing data)
Posters (n = 107) | Lurkers (n = 113) |
|
||||
n | % | n | % | |||
|
.02a | |||||
<1 | 52 | 49 | 31 | 38 | ||
1–2 | 33 | 31 | 39 | 35 | ||
3–5 | 9 | 8 | 23 | 21 | ||
6–9 | 10 | 9 | 9 | 8 | ||
≥10 | 2 | 2 | 8 | 7 | ||
|
.39b | |||||
I | 50 | 47 | 36 | 34 | ||
II | 43 | 41 | 48 | 45 | ||
III+ | 8 | 8 | 13 | 12 | ||
Not known | 5 | 5 | 9 | 8 | ||
|
.26b | |||||
Yes | 93 | 87 | 85 | 75 | ||
No | 14 | 13 | 28 | 25 | ||
Number of symptoms, mean (SD) | 2 (1.685) | 2 (1.456) | .62d | |||
|
.77a | |||||
Living completely as usual | 57 | 53 | 58 | 51 | ||
Living as usual | 50 | 47 | 55 | 49 | ||
|
||||||
Summed scores | 12.6 (6.9) | 13.4 (8.7) | .52d | |||
Depression | 6.2 (3.6) | 6.5 (4.1) | .63d | |||
Anxiety | 6.4 (4.1) | 6.9 (5.4) | .51d |
a Kruskal-Wallis test.
b χ2 test. Degrees of freedom were the number of category –1.
c Respondents checked all of their current symptoms due to breast cancer (eg, pain, tiredness, paralysis of arm, and nausea) and were classified as having symptoms if they chose more than 1 symptom.
d
e Hospital Anxiety and Depression Scale.
The 5 peer support factors that we extracted from the poster and lurker groups were the same (
Factor analysis of peer support functions for posters (n = 107)
Factor (Cronbach alpha) | Factor loading extracted for each factor | |
|
||
I was encouraged when I was supported by peers | .777 | |
I began to respond positively to my peers | .767 | |
I could talk pleasantly with my peers about topics besides breast cancer | .732 | |
I was encouraged when I could help my peers | .644 | |
I wanted to be as cheerful as my happier peers | .613 | |
I wanted to help other patients who were troubled with breast cancer | .574 | |
I wanted to make others aware of breast cancer | .476 | |
|
||
I could straightforwardly express my feelings about relationships in my workplace or family | .848 | |
I could express my feelings about my relationship with my own doctor | .819 | |
I could straightforwardly talk about my condition | .703 | |
I could express my feelings after breast cancer diagnosis | .518 | |
|
||
I received advice about treatment decision making and the side effects of various treatments | .725 | |
I received advice about day-to-day life with breast cancer, such as a wig and mastectomy bra | .672 | |
I received advice about relationships with family members or colleagues in my workplace | .520 | |
I received advice about my relationship with my doctor and about selecting a hospital | .505 | |
|
||
I could not express my feelings out of consideration for others | .605 | |
I was concerned that I might get incorrect information about breast cancer | .580 | |
I became tired when breast cancer became the only topic of conversation | .506 | |
I felt discomfort when I was misunderstood by my peers | .497 | |
I regretted that I learned about a better treatment from peers after finishing my treatment | .484 | |
I felt burdened by the time and cost of the peer support resource | .463 | |
I was in trouble when peers recommended I buy some useless products | .383 | |
|
||
I could help myself recover after I realized that my experience was not unique | .688 | |
I had more insight about myself after meeting other patients | .580 | |
I calmed down when I met other patients who had similar experiences to mine | .573 |
Factor analysis of peer support functions for lurkers (n = 113)
Factor (Cronbach alpha) | Factor loading extracted for each factor | |
|
||
I was encouraged when I was supported by peers | .505 | |
I began to respond positively to my peers | .547 | |
I could talk pleasantly with my peers about topics besides breast cancer | .703 | |
I was encouraged when I could help my peers | .738 | |
I wanted to be as cheerful as my happier peers | .573 | |
I wanted to help other patients who were troubled with breast cancer | .814 | |
I wanted to make others aware of breast cancer | .956 | |
|
||
I could straightforwardly express my feelings about relationships in my workplace or family | .911 | |
I could express my feelings about my relationship with my own doctor | .839 | |
I could straightforwardly talk about my condition | .974 | |
I could express my feelings after breast cancer diagnosis | .925 | |
|
||
I received advice about treatment decision making and the side effects of various treatments | .642 | |
I received advice about day-to-day life with breast cancer, such as a wig and mastectomy bra | .873 | |
I received advice about relationships with family members or colleagues in my workplace | .671 | |
I received advice about my relationship with my doctor and about selecting a hospital | .854 | |
|
||
I could not express my feelings out of consideration for others | .554 | |
I was concerned that I might get incorrect information about breast cancer | .619 | |
I became tired when breast cancer became the only topic of conversation | .747 | |
I felt discomfort when I was misunderstood by my peers | .767 | |
I regretted that I learned about a better treatment from peers after finishing my treatment | .460 | |
I felt burdened by the time and cost of the peer support resource | .652 | |
I was in trouble when peers recommended I buy some useless products | .735 | |
|
||
I could help myself recover after I realized that my experience was not unique | .926 | |
I had more insight about myself after meeting other patients | .627 | |
I calmed down when I met other patients who had similar experiences to mine | .899 |
Each support score, determined based on the extracted factors, is shown in
Support scores for posters and lurkers.
We calculated the correlation between each support and mental health score (HADS) for both posters and lurkers, as shown in
For posters, emotional support/helper therapy (
Correlations between support score and mental health as measured by the Hospital Anxiety and Depression Scale (HADS) subscales anxiety and depression (n = 220) (excluding missing data)
Anxiety | Depression | ||||
|
|
|
|
||
|
|||||
Emotional support/helper therapy | –.477 | <.001 | .002 | .99 | |
Emotional expression | .090 | .30 | .045 | .60 | |
Advice | –.399 | <.001 | .082 | .34 | |
Conflict | .132 | .12 | .287 | .001 | |
Insight/universality | .130 | .13 | –.007 | .93 | |
|
|||||
Emotional support/helper therapy | .042 | .47 | .048 | .41 | |
Emotional expression | –.294 | <.001 | –.116 | .05 | |
Advice | –.655 | <.001 | .004 | .95 | |
Conflict | .049 | .40 | .093 | .11 | |
Insight/universality | –.495 | <.001 | –.048 | .41 |
Most of the posters who participated in our study had received a breast cancer diagnosis relatively recently. Notably, this result does not match that of the study of van Uden-Kraan et al [
Also in contrast to the study of van Uden-Kraan et al [
In this study, among the 5 functions of peer support from online communities, emotional support and emotional expression were similar to the peer support provided by face-to-face support groups [
To put it simply, we ascertained that the 5 support functions found by this survey characterized social support from peers. Additionally, both posters and lurkers were found to receive some amount of support. Social support plays an important role as a buffer for stressful events such as the diagnosis of a life-threatening disease [
Among the 5 functions, insight/universality scored the highest among both posters and lurkers. Therefore, it can be said that the main function of online communities is to provide insight and universality. In our study, scores for emotional support/helper therapy and emotional expression differed significantly between posters and lurkers. So emotional support/helper therapy and emotional expression may be considered to be support that can be received by actively participating in online communities. However, lurkers received a certain amount of these support functions. It can thereby be said that lurkers can feel comforted by online communities, and that they express their emotions without posting because of the modeling effect. People can identify with others more easily by reading or hearing about experiences that are similar to their own [
In this study, the more posters felt they received emotional support/helper therapy and advice, the less anxious they felt. Furthermore, the more advice lurkers gained from their peers, the less anxious they felt. Learning from others who have had similar experiences helps people control their emotions by reducing the number of future unknowns [
In our study, the more emotional expression lurkers—who do not express their experiences and feelings directly—received, the less anxious they felt. Iwamitsu et al [
The age group with the most frequent occurrence of breast cancer is women in their 50s [
In this study, we asked for cooperation from administrators of online communities found using Google and Yahoo! Japan. Thus, the population of the study sample is considered to contain those who were already Internet users and those who were likely to seek peer support. Additionally, we could not analyze the characteristics of those who did not complete the questionnaire or those who stopped participating in an online community before the samples were recruited. This could mean that people who had a negative impression of online communities eliminated themselves from the survey. Thus, the results may be biased to indicate more positive conditions than those that actually exist. In future, we should identify the characteristics of those who stop using online communities and determine what kind of population is best suited to using this support resource.
Due to the cross-sectional nature of this study, we were unable to determine the causal relationship between received support and mental health. Therefore, it is possible that people with less initial anxiety were more likely to receive peer support. Although it is theoretically reasonable to expect that greater support leads to better health, a longitudinal study is needed to confirm such a causal relationship.
Despite these limitations, this study suggests that even lurkers, who participate passively in online communities, can gain peer support through the Internet, and that some peer support may have a positive effect on their mental health. Health care providers should therefore provide information about online communities as a support resource for patients with breast cancer.
None declared
analysis of variance
Hospital Anxiety and Depression Scale