“Seeing pain differently”: A qualitative investigation into the differences and similarities of pain and rheumatology specialists interpretation of multi-dimensional mhealth pain data from children and young people with Juvenile Idiopathic Arthritis

Background
In contrast to traditional uni-dimensional paper-based scales, mHealth assessment of pain in children and young people (CYP) with Juvenile Idiopathic Arthritis (JIA) enables comprehensive and complex multidimensional pain data to be captured remotely by individuals with this long-term condition. However, we do not yet know how professionals use multidimensional pain data to interpret and synthesise pain reports gathered using mHealth tools.
Objective
To explore the salience and prioritisation of different mHealth pain features as interpreted by key stakeholders involved in research into and management of CYP with JIA.
Methods
Pain and rheumatology specialists were purposively recruited via professional organisations. We conducted face-to-face focus groups for each separate specialist group. Participants were asked to rank order nine static vignette scenarios created from real patient mHealth multidimensional pain data. These data had been collected by a researcher in a separate study using My Pain Tracker (MPT), a valid and acceptable mHealth iPad pain communication tool which collects information about intensity, severity, location, emotion and pictorial pain qualities. Specialists discussed their decision-making processes behind each rank order in the focus groups. The total group rank ordering of vignette scenarios were calculated. Qualitative data from discussions were analysed using latent thematic analysis.
Results
Nine pain specialists took part in one focus group and ten rheumatology specialists in another. Within groups, consensus for the highest pain experience was poorer in pain specialists (42.86%) compared to their rankings of lowest pain experiences (57.14%). However in rheumatology specialists, consensus for highest pain experience (70%) was stronger than when ranking the lowest pain experience (50%). Pain intensity was a high priority for pain specialists, but intensity and severity taken together were prioritised high by rheumatology specialists. Pain spread was highly prioritised, with the number of pain locations (particular areas or joints) being a high priority for both groups and radiating pain a high priority for pain specialists only. Pain emotion was challenging for both groups and was only perceived to be a high priority when specialists had additional confirmatory evidence (such as information about pain interference or clinical observations) to validate this. Pain qualities such as particular word descriptors, use of the colour red and fire symbols were seen to be high priority by both groups in interpretation of CYP pain reports.
Conclusions
Pain interpretation is complex but findings from this study of specialists decision-making processes indicate which aspects of pain are prioritised and weighted more heavily than others by those interpreting mHealth data. These findings are useful for future research to develop electronic graphical summaries to assist specialists to interpret patient reported mHealth pain data more efficiently in clinical and research settings.