What is the role of online support from the perspective of facilitators of face-to-face support groups? A multi-method study of the use of breast cancer online communities

Bender, Jackie; Katz, Joel; Ferris, Lorraine E.; Jadad, Alejandro R.

doi:10.1016/j.pec.2013.07.009

Cited by 76 publications

(67 citation statements)

References 50 publications

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“…To enable reliable and useful annotation of topics, we established a coding schema of discussion topics through a literature review of information needs in online health communities, with an emphasis on breast cancer communities (Meier et al, 2007b; Civan and Pratt, 2007; Blank et al, 2010; Skeels et al, 2010; Wen et al, 2011; Bender et al, 2013; Kim et al, 2013). Our objectives were (i) to devise a coding scheme that is both relevant to describing the information needs of community members as well as applicable to and robust enough for automatic topic classification; and (ii) to design a coding scheme that can be applied to characterizing topics of discussion for either an entire post or its individual sentences.…”

Section: Methodsmentioning

confidence: 99%

Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks

Zhang

Grave

Sklar

et al. 2017

Journal of Biomedical Informatics

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Identifying topics of discussions in online health communities (OHC) is critical to various applications, but can be difficult because topics of OHC content are usually heterogeneous and domain-dependent. In this paper, we provide a multi-class schema, an annotated dataset, and supervised classifiers based on convolutional neural network (CNN) and other models for the task of classifying discussion topics. We apply the CNN classifier to the most popular breast cancer online community, and carry out a longitudinal analysis to show topic distributions and topic changes throughout members' participation. Our experimental results suggest that CNN outperforms other classifiers in the task of topic classification, and that certain trajectories can be detected with respect to topic changes.

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Section: Methodsmentioning

confidence: 99%

Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks

Zhang

Grave

Sklar

et al. 2017

Journal of Biomedical Informatics

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“…By gathering knowledge from institutional or medical websites, women become able to establish a new relationship with healthcare professionals and health systems. Despite the problem of trustworthiness, as pointed out in other studies [27,28]. there has been an increase in the number of people reading and writing blogs on the breast cancer experience.…”

Section: Discussionmentioning

confidence: 91%

Young women with breast cancer-using the healing tool; writing blogs

Vargens¹,

Berterö²

2017

Nurs Palliat Care

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Purpose: This qualitative study aims to interpret and describe how young women diagnosed with a breast cancer uses blogs to manage daily life.Methods: 14 blogs written by women diagnosed with breast cancer aged between 25 and 38 years. These blogs were analysed using qualitative thematic analysis.Results: Four themes were identified in the data body illustrating what the women were writing about in their blogs: Experiencing frustration, The fear is bigger than death, Preparing for physical changes, Body and mind are in disharmony. These four themes ended up in a concluding theme: The healing effect of writing a blog. Conclusion:The young women used writing blogs as a healing activity. The writing was a channel for emotions and thoughts, but was also a way of sharing experiences and supporting each other. Their narratives revealed the impact of breast cancer experiences on their personal, familial and social lives. Reading blogs is an activity that could allow healthcare professionals to better understand these women's life situation and needs. Implications for practice:Blogs could become a useful tool for healthcare professionals, relatives, patients and the people around them. By reading blogs, not necessarily commenting on or writing them, there will be a better and deeper understanding about the effects of a cancer diagnosis. Using blogs could facilitate the provision of requested and needed health care activities.

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“…Studies most often focused on breast cancer (n = 22; 31.9%),8,10,12,13,16,17,22,25,26,28–30,35,41–43,45,58,60,66,74,75 and prostate cancer (n = 4; 5.8%). 36,56,67,76 Other cancers mentioned were osteosarcoma, 73 rhabdomyosarcoma, 55 testicular, 11 skin, 23 cervical, 37,53,59,65 ovarian, 21, lung, 34 and colorectal.…”

Section: Resultsmentioning

confidence: 99%

“…Other descriptive studies (n = 12; 17.4%; Table 2) used surveys, 11,23,24,28,40,43,46,59,60,63,65,74 in-depth interviews, 47 focus groups, 48 social network analyses, 20,68 a mix of measurement techniques, 8,9,13,22,30,39 Web metrics, 72,73 and frequencies 62 to describe how users employed social media to obtain and receive cancer information. It is important to note that only 1 of these studies reviewed the accuracy of information posted on a social media site (YouTube); it reported that roughly 75% of all videos had either fair or poor information about prostate cancer screening.…”

Section: Resultsmentioning

confidence: 99%

Use and Taxonomy of Social Media in Cancer-Related Research: A Systematic Review

et al. 2014

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Little is known about how social media are used in cancer care. We conducted a systematic review of the use and taxonomy of social media in cancer-related studies, in PubMed, Web of Knowledge, CINAHL, and Google Scholar. We located 1350 articles published through October 2013; 69 met study inclusion criteria. Early research (1996–2007) was predominantly descriptive studies of online forums. Later, researchers began analyzing blogs, videos shared on YouTube, and social networking sites. Most studies (n = 62) were descriptive, and only 7 reported intervention studies published since 2010. Future research should include more intervention studies to determine how social media can influence behavior, and more empirical research is needed on how social media may be used to reduce health disparities.

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What is the role of online support from the perspective of facilitators of face-to-face support groups? A multi-method study of the use of breast cancer online communities

Cited by 76 publications

References 50 publications

Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks

Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks

Young women with breast cancer-using the healing tool; writing blogs

Use and Taxonomy of Social Media in Cancer-Related Research: A Systematic Review

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