ArticleDigital health
Exploring online health information-seeking behaviour for musculoskeletal pain in Europe: A study protocol combining expert panel insights with search trends on social media and Google.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Rising obesity and shifting disease patterns in Saudi Arabia: a nine-year population-based analysis of chronic disease burden and multimorbidity profiles.BMC public health · 2026Article
- Digital Health Engagement Regarding Lumbar Disc Herniation in Terms of Exercise Adherence: Integrating Variable-Centered and Person-Centered Perspectives.Patient preference and adherence · 2026Article
- Global and national public awareness and interest in glomerular diseases from 2004 to 2024.Frontiers in nephrology · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.