Lived experience-centred word clouds may improve research uncertainty gathering in priority setting partnerships

Abstract

Introduction: AO Spine RECODE-DCM was a multi-stakeholder priority setting partnership (PSP) to define the top ten research priorities for degenerative cervical myelopathy (DCM). Priorities were generated and iteratively refined using a series of surveys administered to surgeons, other healthcare professionals (oHCP) and people with DCM (PwDCM). The aim of this work was to utilise word clouds to enable the perspectives of people with the condition to be heard earlier in the PSP process than is traditionally the case. The objective was to evaluate the added value of word clouds in the process of defining research uncertainties in National Institute for Health Research (NIHR) James Lind Alliance (JLA) Priority Setting Partnerships.

Methods: Patient-generated word clouds were created for the four survey subsections of the AO Spine RECODE-DCM PSP: diagnosis, treatment, long-term management and other issues. These were then evaluated as a nested methodological study. Word-clouds were created and iteratively refined by an online support group of people with DCM, before being curated by the RECODE-DCM management committee and expert healthcare professional representatives. The final word clouds were embedded within the surveys administered at random to 50% of participants. DCM research uncertainties suggested by participants were compared pre- and post-word cloud presentation.

Results: A total of 215 (50.9%) participants were randomised to the word cloud stream, including 118 (55%) spinal surgeons, 52 (24%) PwDCM and 45 (21%) oHCP. Participants submitted 434 additional uncertainties after word cloud review: word count was lower and more uniform across each survey subsections compared to pre-word cloud uncertainties. Twenty-three (32%) of the final 74 PSP summary questions did not have a post-word cloud contribution and no summary question was formed exclusively on post-word cloud uncertainties. There were differences in mapping of pre- and post-word cloud uncertainties to summary questions, with greater mapping of post-word cloud uncertainties to the number 1 research question priority: raising awareness. Five of the final summary questions were more likely to map to the research uncertainties suggested by participants after having reviewed the word clouds.

Conclusions: Word clouds may increase the perspective of underrepresented stakeholders in the research question gathering stage of priority setting partnerships. This may help steer the process towards research questions that are of highest priority for people with the condition.

Keywords: Audit, Surveillance; Cervical; Cervical stenosis; Common data elements; Consensus; Disc herniation; Myelopathy; Ossification of posterior longitudinal ligament; Outcome; Research priorities; Spondylosis; Word cloud.

Fig. 1

Word Cloud Development. A 3-stage process was used to collect unique words relating to DCM and survey their popularity to create word clouds. Words were initially submitted by Myelopathy Support, a community of PwDCM and their supporters. These were then processed by the AO Spine RECODE-DCM Management Group and supplemented with the perspectives of a general practitioner and a neurologist; arrows denote added and removed words. The final list of words was re-reviewed by the Myelopathy Support community. Voting was conducted to capture the popularity of each word and further suggestions were also put forward. The four-column tables represent the number of words per subsection, ordered from left to right as: diagnosis, treatment, long-term management and other

Fig. 2

Word clouds generated from the Myelopathy Support group polling. Words were associated with (a) DCM diagnosis, (b) treatment, (c) long-term management and (d) other. The size of the word is proportional to the number of votes it received during polling

Fig. 3

Incorporation of word clouds in the PSP. Participants allocated to the AO Spine RECODE-DCM PSP were categorised by stakeholder group (spinal surgeons, PwDCM and their supporters, other healthcare professionals). Participants within each stakeholder group were randomly allocated to word cloud or no word cloud streams using a computerised 1:1 block randomisation protocol. Participants in the word cloud stream were presented with the word clouds after the standard survey seen by the non-word cloud group and then given the opportunity to submit further uncertainties

Fig. 4

Median number of words submitted per survey subsection (diagnosis, treatment, long-term management and other). Each group of bars represents subsections at different stages: without word clouds (grey), before word clouds (pale orange) and after word clouds (dark orange). Ordered from left to right, the bars represent diagnosis, treatment, long-term management and other. The vertical black line separates the two streams. The number and distribution of submissions across subsections was similar for no words clouds and pre-word clouds. The number of words submitted post word clouds was fewer and consistent across each subsection

Fig. 5

Radar plot of research uncertainties and how they map to the final 74 summary questions (black numbers) and top 26 priorities (green numbers), from uncertainties without (grey) or pre-word cloud (blue) compared to post-word cloud (orange). Post-word cloud uncertainties mapped to different research uncertainties than pre-word cloud uncertainties, including the number 1 research priority: raising awareness