Abstract
Background: Low back pain (LBP) is growing health concern that affects millions of people around the globe, and there are many misconceptions regarding causes, imaging, and appropriate treatment choices. Common people usually search Google seeking information regarding LBP from different websites. However, the content of these widely
accessible websites have not be evaluated in the light of evidence. The present study aims to analyze the information presented by these websites, summarize the content, and evaluate it against the published literature.
Methods: We conducted a systematic search of Google using search terms “low back pain,” “back pain,” “backache. NVivo software was used to capture the content from the internet. Content analysis (CA) was used to analyze online
consumer information concerning LBP on the included websites.
Results: A total of 53 websites were included in the study by screening the search pages. There were erroneous information present on majority of the websites. Almost all of the websites consisted of nocebic terms. The causes were more oriented towards biomedical model. Treatment options mentioned did not concur with the recent clinical
practice guidelines.
Conclusion: The Online information retrieved from a Google search lacks representation of the current best research. The findings of the study suggest that future development of websites must include information that is more accurate, and evidence driven. Online LBP information should be based on criteria that are more sensitive to the psychosocial factors that contribute to pain.
Keywords: Medical informatics, Low back pain, Biopsychosocial model, Consumer health information
accessible websites have not be evaluated in the light of evidence. The present study aims to analyze the information presented by these websites, summarize the content, and evaluate it against the published literature.
Methods: We conducted a systematic search of Google using search terms “low back pain,” “back pain,” “backache. NVivo software was used to capture the content from the internet. Content analysis (CA) was used to analyze online
consumer information concerning LBP on the included websites.
Results: A total of 53 websites were included in the study by screening the search pages. There were erroneous information present on majority of the websites. Almost all of the websites consisted of nocebic terms. The causes were more oriented towards biomedical model. Treatment options mentioned did not concur with the recent clinical
practice guidelines.
Conclusion: The Online information retrieved from a Google search lacks representation of the current best research. The findings of the study suggest that future development of websites must include information that is more accurate, and evidence driven. Online LBP information should be based on criteria that are more sensitive to the psychosocial factors that contribute to pain.
Keywords: Medical informatics, Low back pain, Biopsychosocial model, Consumer health information
| Original language | English |
|---|---|
| Article number | 23 |
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Bulletin of Faculty of Physical Therapy |
| Volume | 27 |
| Early online date | 8 Jun 2022 |
| DOIs | |
| Publication status | Published online - 8 Jun 2022 |
Data Access Statement
NAFunding
The authors confirm that there is no financial support
Keywords
- Medical informatics
- Low back pain
- Biopsychosocial model
- Consumer health information
