Yoko Setoyama*, St. Luke's College of Nursing, Tokyo, Japan Kazuhiro Nakayama, St. Luke's College of Nursing, Tokyo, Japan Track: Research Presentation Topic: Building virtual communities and social networking applications for patients and consumers Presentation Type: Poster presentation Submission Type: Single Presentation Last modified: 2012-09-12

If you are the presenter of this abstract (or if you cite this abstract in a talk or on a poster), please show the QR code in your slide or poster (QR code contains this URL).

Background: Internet is widely used among cancer patients during their course of illness in order to seek for informational and emotional support. Recently patients use social media as one of the social support resources. But little is known about relationship between social support via social media and QOL, especially effectiveness of social media among the particular groups of patients in Japan.

Purpose: This study was to explore the social media use, social support and QOL among patients with breast cancer in Japan.

Methods: We conducted a cross-sectional online and mail survey of 977 patients with breast cancer at the same time. The response rates were 41.8% for the online survey and 54.6% for the mail survey. Social support via social media was measured by 7 items, including “Information support”, “Emotional support”, “Disclosure”, “Insight”, “Universality”, “Helper therapy”, and “Modeling”. Each item was rated on a 5-point scale. QOL was measured by the Functional Assessment of Cancer Therapy General (FACT-G). We conducted a multivariate regression analysis to reveal the direct relationship between social support via social media and QOL. Additionally, we estimated relationship between social support via social media and QOL by the level of stress, and physician support.

Results: There were significant main effects between stress (β = -.689, p < .001) and physician support (β = .168, p < .001) on QOL. In addition, the interaction effects on QOL were significant between stress and online support (β = .203, p = .012), stress and physician support (β= -.180, p = .012), and physician support and online support (β = -.245, p = .002).

Conclusion: It is possible that social support via social media had positive effects on QOL among patients with high levels of stress. In addition, although support gained via social media has no direct significant effect on QOL, it can have a positive effect on the QOL among patients with less physician support.