Abstract
Background: Chronic neck and low back pain are very common and have detrimental effects for people and society. In this study, we explore the experiences of individuals with neck and/or back pain using a written narrative methodology. Materials & methods: A total of 92 individuals explained their pain experience using written narratives. Narratives were analyzed through thematic analysis and text data mining. Results: Participants wrote about their experience in terms of pain characteristics, diagnosis process, pain consequences, coping strategies, pain triggers, well-being and future expectations. Text data mining allowed us to identify concurrent networks that were basically related with pain characteristics, management and triggers. Conclusion: Written narratives are useful to understand individuals’ experiences from their point of view.
A total of 92 participants with recurrent neck and/or low back pain explained their pain experiences by using written narratives.
A thematic qualitative analysis identified seven main themes related to: pain characteristics, diagnosis process, pain consequences, coping strategies, pain triggers, well-being and future expectations.
Using a novel text data mining approach, we identified concurrent networks related in general terms to pain characteristics, management and triggers.
These networks coincided with some of the themes found in the qualitative analysis, probably representing the most frequently commented areas.
Pain varied widely in its characteristics individually, but universally has detrimental consequences to participants (besides coping efforts they described), affecting their whole life and their future expectations.
This, together with the fact that participants were dissatisfied with the healthcare process, suggests a need to improve the care they receive.
Written narratives can be a useful tool in clinical practice, in order to obtain a first idea of the person’s situation and needs from their own point of view.
Future studies are needed to replicate our results and test additional methodologies for performing automatic text analyses.
Author contributions
B Sora, R Nieto and H Vall-Roqué conducted the analyses and manuscript preparation. All the authors were involved in the study design and review of the manuscript.
Financial disclosure
This work is co-financed by the European Regional Development Fund (ERDF) and the Generalitat de Catalunya within the PO FEDER Catalunya 2014-2020 program in the call “Industry of Knowledge-LLAVOR”, through the research grant “PositivethinkingApp and DistractApp: Two Apps for management pain project” (IU68-009895). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Competing interests disclosure
The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Writing disclosure
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
The study was approved by the Ethics Committee of the Universitat Oberta de Catalunya, and we followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. Informed consent was obtained from the participants involved.