What do people post on social media relative to low back pain? A content analysis of Australian data
Publication Details
O'Hagan, E. T.,
Traeger, A. C.,
Bunzli, S.,
Leake, H. B.,
Schabrun, S. M.,
Wand, B.,
O'Neill, S.,
Harris, I. A.,
&
McAuley, J. H.
(2021).
What do people post on social media relative to low back pain? A content analysis of Australian data.
Musculoskeletal Science and Practice, 54.
Abstract
Objective: Low back pain is the leading contributor to the global disability burden. The Global Spine Care Initiative (GSCI) recommend patient-centred care to stem the cost of low back pain. One way to enhance patientcentred care is by better understanding what is relevant for people with low back pain. Exploring social media posts about low back pain could offer this insight and provide valuable information for health care professionals to facilitate active participation in patient-centred care.
Methods: We used an inductive content analysis method. In the form of social media posts, data on Twitter and Instagram were collected from June to August 2018. The posts were geo-targeted to Australia. We recorded the number of status broadcasts that contained a low back pain keyword and responses. We developed a codebook to describe the data and applied it to identify low back pain themes.
Results: We analysed 768 posts containing 457 status broadcasts and 311 responses. Almost half (49%) of status broadcasts about low back pain seemed to seek validation. Expressing sympathy (31%) was the most common response to a status broadcast about low back pain. There were no public responses to 76% of status broadcasts about low back pain. Our analysis yielded two core themes, “hear my pain” and “I feel for you".
Conclusions: Posts about low back pain on social media often seem to suggest that the person posting is seeking validation. Responses typically express sympathy or a shared experience; yet, there is no response to most social media posts about low back pain.
Keywords
patient-centred care, low back pain, social media, content analysis