Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Introduction: Musculoskeletal pain is a significant public health concern in Europe. With the advent of the digital age, online health information-seeking behaviour has become increasingly important, influencing health outcomes and the ability of individuals to make well-informed decisions regarding their own well-being or of those they are responsible for. This study protocol outlines an investigation into how individuals in five European countries (Austria, Denmark, Ireland, Italy, and Spain) seek online health information for musculoskeletal pain.
Methods: The protocol adopts an exploratory and systematic two-phase approach to analyse online health information-seeking behaviour. Phase 1 involves four steps: (1) extraction of an extensive list of keywords using Google Ads Keyword Planner; (2) refinement of the list of keywords by an expert panel; (3) investigation of related topics and queries and their degree of association with keywords using Google Trends; and (4) creation of visual representations (word clouds and simplified network graphs) using R. These visual representations provide insights into how individuals search for online health information for musculoskeletal pain. Phase 2 identifies relevant online sources by conducting platform-specific searches on Google, X, Facebook, and Instagram using the refined list of keywords. These sources are then analysed and categorised with NVivo and R to understand the types of information that individuals encounter.
Conclusions: This innovative protocol has significant potential to advance the state-of-the-art in digital health literacy and musculoskeletal pain through a comprehensive understanding of online health information-seeking behaviour. The results may enable the development of effective online health resources and interventions.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571255 | PMC |
http://dx.doi.org/10.1177/20552076241298480 | DOI Listing |
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