Uncertainty in serious illness: A national interdisciplinary consensus exercise to identify clinical research priorities

1 1 Uncertainty in serious illness: 2 A national interdisciplinary consensus exercise to identify clinical research priorities 3 4 5 Authors Simon N Etkind1,2*, Stephen Barclay1, Anna Spathis1,2, Sarah A Hopkins1, Ben Bowers1, Jonathan 6 Koffman 3 7 8 Affiliations 9 1. Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge 10 2. Cambridge University Hospitals NHS Foundation Trust 11 3. Hull York Medical School, University of Hull 12 * corresponding author 13 14 15 Corresponding author contact details and address 16 Simon Etkind 17 [email protected] 18 Primary Care Unit, Department of Public Health and Primary Care, East Forvie Building, Addenbrookes 19 Biomedical Campus, CB2 0SR 20 21 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 2 22 Abstract: 23 Background: Serious illness is characterised by uncertainty, particularly in older age groups. Uncertainty 24 may be experienced by patients, family carers, and health professionals about a broad variety of issues. 25 There are many evidence gaps regarding the experience and management of uncertainty. 26 Aim: We aimed to identify priority research areas concerning uncertainty in serious illness, to ensure that 27 future research better meets the needs of those affected by uncertainty and reduce research 28 inefficiencies. 29 Methods: Rapid prioritisation workshop comprising five focus groups to identify research areas, followed 30 by a ranking exercise to prioritise them. Participants were healthcare professionals caring for those with 31 serious illnesses including geriatrics, palliative care, intensive care; researchers; patient/carer 32 representatives, and policymakers. Descriptive analysis of ranking data and qualitative framework 33 analysis of focus group transcripts was undertaken. 34 Results: Thirty-four participants took part; 67% female, mean age 47 (range 33 – 67). The highest priority 35 was communication of uncertainty, ranked first by 15 participants (overall ranking score 1.59/3). 36 Subsequent priorities were: 2) How to cope with uncertainty; 3) healthcare professional 37 education/training; 4) Optimising clinical approaches to uncertainty; and 5) exploring in-depth 38 experiences of uncertainty. Research related to optimally managing uncertainty was given higher priority 39 than research focusing on experiences of uncertainty and its impact. 40 Conclusions: These co-produced, clinically-focused research priorities map out key evidence gaps 41 concerning uncertainty in serious illness. Managing uncertainty is the most pressing issue, and 42 researchers should prioritise how to optimally manage uncertainty in order to reduce distress, unlock 43 decision paralysis and improve illness and care experience. 44 45 Key words 46 Uncertainty; Communication; Serious illness; Palliative care; Qualitative research 47 48 49 Key points 50  Uncertainty is ubiquitous and distressing in serious illness, and can paralyse decision making 51  In this consensus exercise, stakeholders identified research priorities for uncertainty in serious 52 illness 53  Communication of uncertainty was the highest priority 54  Participants prioritised research concerning managing uncertainty above research to understand 55 experiences of uncertainty 56 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 3 57 Background 58 Uncertainty is ubiquitous in serious illnesses across all health settings, especially when living with long- 59 term conditions and frailty.[1-5] Encompassing “known unknowns”, uncertainty is characterised as an 60 inadequate understanding, a sense of incomplete, ambiguous or unreliable information, and conflicting 61 alternatives.[6, 7] It is inherently a complex concept and situations of uncertainty often result from 62 several inter-related factors.[8] 63 64 Irrespective of its origin, uncertainty matters because when suppressed and ignored, it can profoundly 65 negatively impact patients and their family.[9, 10] Older adults may be particularly affected as they 66 commonly experience complex and unpredictable illness, associated with irreducible uncertainties. 67 Uncertainty may precipitate extensive psychological and existential distress, potentially culminating in an 68 experience of ‘Total Uncertainty’ which may threaten an individual’s sense-of-self.[11] 69 70 If uncertainty is not addressed it may impact patient safety, adverse events, healthcare interactions and 71 relationships.[12, 13] One metric where this is recorded are complaints levelled at healthcare, 72 particularly in hospital settings.[14] Uncertainty can also limit patient participation in decision-making, 73 leading to ‘decision paralysis’,[15, 16] which may contribute to sub-optimal care and has repercussions 74 for the allocation of scarce health resources, including hospital admissions and longer inpatient stays.[17, 75 18] 76 77 It is not just patients who are affected by uncertainty. Despite uncertainty in medicine dating back to 78 Hippocrates, there exists a deeply rooted aversion to it in empirical medicine, where acknowledging 79 uncertainty can have connotations of failure.[18, 19] If poorly tolerated by health professionals, 80 uncertainty can adversely impact their confidence and competence, increasing the risk of moral injury, 81 burnout and depression.[20-23] This was particularly evident during the Covid-19 pandemic.[24, 25] 82 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 4 83 Uncertainty in illness is not necessarily distressing; it may be appraised negatively, neutrally, or in some 84 individuals, illnesses, and care circumstances, positively; for example holding onto prognostic uncertainty 85 can in some circumstances enable people to retain hope.[26-28] The distress caused by uncertainty, and 86 hence the block to decision making is therefore not inevitable; the negative impacts of uncertainty can 87 be at least partially ameliorated if it is addressed and communicated sensitively.[29-31] 88 89 There are innumerable possible situations of uncertainty, each of which may have its own optimal 90 approach. We still do not know how best to approach and address it in older patients living with long- 91 term or life-threatening illnesses in a way that best supports the individual and those involved in their 92 care;[32, 33] although previous work has explored how to support communication of uncertainty, [34] 93 uncertainty management,[12, 32] and shared decision making.[35] We do know that there can be no 94 one-size-fits-all approach to uncertainty, as it is experienced differently in different clinical contexts, by 95 different individuals.[6, 36] Uncertainties in some contexts may be more distressing than others and may 96 require different approaches.[37] Despite the importance of uncertainty for patients and clinicians alike 97 there has, to date, been no attempt to prioritise the most pressing areas to focus applied research on to 98 improve care. 99 100 We aimed to identify stakeholder priority research areas concerning uncertainty in serious illness, [38] to 101 enable future research to more effectively meet the needs of those affected by uncertainty and to 102 reduce research inefficiencies.[39, 40] . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 5 103 Methods 104 Design 105 National interdisciplinary one-day prioritisation workshop with a range of stakeholders: patient and carer 106 representatives, clinicians, researchers, and policymakers. Reporting according to REPRISE guidance (see 107 appendix).[41] 108 109 Patient and public involvement 110 A Patient and public involvement group supported development of the study aims and methods; 3 public 111 contributors participated in the workshop, contributing to focus groups and the ranking exercise, and 112 commented on the findings. 113 114 Participants and participant identification 115 Participants were clinicians, researchers, policymakers, people with lived experience of serious illness 116 and their informal carers. Researchers and policymakers were eligible if they were interested in the area. 117 Clinicians were from any profession or specialty with experience in providing care to people with serious 118 illnesses. The workshop invitation was disseminated widely through clinical and research networks and 119 social media, including: Applied Research Collaborative (ARC) East of England, UK uncertainty in serious 120 illness specialist interest group, the UK-wide Community Nursing Research Forum, regional and national 121 palliative care and gerontology contacts. Invitations were sent from December 2022, and registration 122 was open until 27 th February 2023. The workshop was held on 28th February 2023. Workshop attendees 123 were informed of the research component in advance. 124 125 Workshop process 126 The workshop drew on existing approaches to prioritisation, incorporating idea generation, 127 consolidation, and ranking stages.[42] Written informed consent and self-reported demographic data . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 6 128 were collected from workshop participants at the start of the day, including age, gender, ethnicity, 129 participants’ status as a researcher, clinician, policymaker, or patient representative, and details of their 130 field where relevant. To encourage debate, the workshop began with presentations on the “state of the 131 science” concerning uncertainty in serious illness. Models of uncertainty and evidence gaps from 132 relevant literature reviews were outlined.[11, 32, 34, 43, 44] 133 We then held focus groups with participants to explore their views on uncertainty and identify key areas 134 for future research. This approach mirrored the idea generation stage of the nominal group technique 135 and the first round of a Delphi process.[42, 45] The topic guide was developed by the research team and 136 was informed by literature review: it focused on experiences of uncertainty, views on desired outcomes 137 when addressing uncertainty, and ideas for research questions concerning uncertainty in serious illness. 138 Focus groups were led by clinicians and researchers with expertise in facilitation. Conversations were 139 audio recorded and a scribe within each group recorded the research questions identified by 140 participants. 141 Research areas from the focus groups were collated into a summary list during the day. In the final 142 session, this summary list was presented to participants who were invited to anonymously rank the top 143 three areas in order of priority using the online ranking tool “Slido” (© 2023 Cisco Systems, Inc.). Items 144 were presented in random order. See appendix for full workshop programme and topic guide. 145 146 Data analysis 147 Analysis of focus group lists: The lists generated by focus groups were reviewed by two researchers (SE & 148 JK) during the day, taking into account both researchers’ existing knowledge of evidence gaps and 149 previously expressed areas for future research from literature reviews.(9, 28) The researchers combined 150 the lists produced by each focus group by removing duplicates and arranging similar questions under 151 “umbrella terms” to produce a single summary list of priority research areas for use in the subsequent 152 ranking exercise. . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 7 153 154 Analysis of ranking exercise data: Individual-level ranking scores were exported from Slido. We analysed 155 the scores descriptively and reported the number of participants ranking each item within their top 156 three. We calculated an average ranking score by allocating points to each item as follows: the item 157 ranked first received three points; the item ranked second received two points; the item ranked third 158 received one point; all other items received zero points. The average ranking score was calculated by 159 adding the points for each item and dividing by the number of participants. The maximum any item 160 could score was three if every participant ranked it as their top priority and the minimum was zero if no 161 participant ranked it in their top three. 162 163 Analysis of focus group transcripts: Following the workshop the focus group recordings were transcribed 164 verbatim, anonymised and analysed using a framework approach.[46] This stage aimed to identify 165 detailed research questions within the priority areas, as well as any additional areas discussed that were 166 relevant for future research. We used the research priority areas identified during the workshop as a 167 coding framework and one researcher (SE) coded text in the transcripts that described research 168 questions or participants’ views about these areas. A second researcher (JK) independently reviewed one 169 focus group transcript. Coding was reviewed, and where there were differences, these issues were 170 reconsidered and debated by both researchers until consensus was achieved.[46] To avoid making 171 unwarranted claims about patterns and regularities in the data, we examined and coded unusual or non- 172 confirmatory views that did not fit easily into the original framework.[46] The framework was 173 condensed, summarised and discussed with the wider research team to refine it. Anonymised excerpts 174 from the transcripts are presented to illustrate themes and represent a range of views. 175 176 Ethical approval: This study received approval from the University of Cambridge Psychology Research 177 Ethics Committee [Reference:PRE.2022.125]. . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 8 178 Results 179 Participant details 180 Thirty three participants took part in the focus groups, and 34 in the ranking survey, of whom 30 181 provided demographic information. The average age was 47 years (range 33 – 67), and 67% were female. 182 80% were of white ethnicity, 10% Asian, and 10% from mixed or multiple ethnic groups. 70% were 183 clinicians, 43% researchers, 10% patient or carer representatives, and 7% policymakers (participants 184 could state multiple roles). Of the clinician participants, twelve had a background in palliative care, three 185 geriatrics, two nursing and one each of intensive care, general practice, psychology, and physiotherapy. 186 187 Item generation and ranking 188 Five focus groups with six to seven participants in each were of 53 to 64 minutes’ duration. The groups 189 generated 61 research questions, which we condensed to produce the 10 priority areas that were then 190 ranked by participants (Table 1). Communication of uncertainty was the highest-ranked item, scored first 191 by 15 participants. Participants ranked the next four priorities almost equally: coping with uncertainty; 192 training health professionals; optimising clinical approaches to uncertainty; understanding in-depth 193 experiences of uncertainty. The other areas received lower priority scores. 194 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 9 195 Table 1. 10 priority areas for future uncertainty research in serious illness (n = 34): Number of participants ranking item in each top 3 positions (%) Overall Ranking Priority #1 #2 #3 Percentage of participants ranking items in top three Ranking score* 1 Communication of uncertainty 15 (44) 3 (9) 3 (9) 62 1.59 2 How to cope with uncertainty 6 (18) 5 (15) 3 (9) 41 0.91 3 Education/training of healthcare professionals 2 (6) 7 (21) 9 (26) 53 0.85 4 Optimising clinical approaches to uncertainty 6 (18) 2 (6) 4 (12) 35 0.76 5 Understanding patient/carer experiences of uncertainty in depth 2 (6) 7 (26) 5 (15) 41 0.74 6 Variation in experience/response to uncertainty between different individuals, groups, professions 1 (3) 4 (12) 1 (3) 18 0.35 7 Explore positive aspects of uncertainty 1 (3) 1 (3) 4 (12) 18 0.26 8 Impact of uncertainty on bereavement 1 (3) 2 (6) 1 (3) 12 0.24 9 Uncertainty in specific conditions/clinical situations 0 (0) 3 (9) 1 (3) 12 0.21 10 Factors associated with different uncertainty experiences 0 (0) 0 (0) 1 (3) 9 0.09 196 *Calculated as follows: item ranked first receives 3 points; item ranked 2nd receives 2 points; item ranked 3rd 197 receives 1 point; all other items receive 0 points. The total points for each item are added and divided by the 198 number of participants. 199 200 Detailed research priorities 201 We explored the 10 priority areas raised by workshop participants during qualitative analysis, and 202 identified detailed sub-questions within each area (Table 2). 203 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 10 204 The highest priority research areas were related to managing uncertainty, by communication, supporting 205 individual coping mechanisms, or providing training. Participants particularly focused on how and when 206 to have conversations about uncertainty, and how to individualise communication to promote 207 psychological wellbeing: 208 “Then there’s a really important research need around understanding more about how we 209 communicate uncertainty and the consequences of how we communicate uncertainty and how 210 we can talk about uncertainty in a way which is more patient-centred and supportive and 211 considers sort of psychological wellbeing.” Social scientist, focus group 3. 212 Training of health professionals at varying stages was a recognised priority. This included training 213 professionals on toleration of their uncertainty as well as how to address the uncertainty experienced by 214 others. One participant highlighted that inadequate training of doctors to manage uncertainty has been 215 a longstanding issue and queried the best timing of such training: 216 “We’ve been inadequate at teaching them [medical students] how to actually manage this 217 complexity for a long time, although you could argue that it’s quite difficult to teach until they 218 really get into the nitty-gritty of practising.” Geriatrician, focus group 1 219 Participants recognised it is unlikely a single intervention can address all the nuanced multilevel aspects 220 of uncertainty, but nevertheless, some felt interventions could play a role in addressing uncertainty, as 221 long as they were situated in a broader societal context: 222 “There are interventions that are being developed out there but there are no interventions that 223 deal with all the different types and layers of uncertainty and they can’t by nature. And I think 224 there is that kind of relational uncertainty, the kind of organisational uncertainties, there are 225 uncertainties on macro, meso, micro levels and you can deal with one component, but you can’t 226 deal with all the different components, and it’s how those interventions work within the broader 227 societal context of uncertainty.” Occupational therapist, focus group 4 228 Older frail patients were seen as a priority for future research into how uncertainty can be managed. 229 Participants noted a lack of knowledge about approaching uncertainty in the context of frailty: 230 “For old and frail elderly there’s no support you know, for that anxiety, fear, so it’s how do we 231 look at that, you know, and how do we maybe look at how we can support, supporting that 232 frailty and older.” Professor of end-of-life care, focus group 5 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 11 233 234 Participants identified research questions concerning experiences of uncertainty, though these were 235 generally given lower priority than questions relating to managing uncertainty. Participants identified 236 illness contexts where uncertainty experiences could be explored further, including critical illness and 237 frailty. They also acknowledged it is important to explore how the experience of uncertainty varies 238 depending on perspective (patient, carer or health professional), or individual characteristics: 239 “We’d want to look at different groups such as sort of learning disability, neurodiversity, sort of 240 hard-to-reach areas whether deprivation, LGBTQ+, sort of that kind of differences you might get.” 241 Palliative care consultant, focus group 1. 242 Participants identified potential positive impacts of uncertainty and its utility in certain situations. They 243 suggested it was important to understand why some health professionals thrive when required to 244 manage uncertainty, whereas others exhibit a lower tolerance. Participants noted the relationship 245 between uncertainty and hope and reasoned that positive aspects of uncertainty should be explored 246 further: 247 “I wonder….whether there’s something about learning to cope with uncertainty or to tolerate 248 uncertainty and whether people, patients and families can see that as a positive as well.” 249 Bereavement practitioner, focus group 4 250 251 Additional areas for future research 252 Some questions identified from focus group transcripts were not identified as research priority areas by 253 participants. Additional areas included consideration of the legal and regulatory implications of 254 uncertainty and its management, the link between uncertainty and patient safety, how to prepare the 255 public for serious illness uncertainty, and the resource impacts of different levels of tolerance to 256 uncertainty: 257 “Have we studied the use of resources around uncertainty? Because I’m sure loads of tests are 258 done completely unnecessarily because people just want to be sure.” Palliative care consultant, 259 group 1 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 260 Table 2. Detailed research priorities from framework analysis* Theme Priority area Detail of priority area Communication of uncertainty (research on how best to communicate about uncertainty)  Understand more about the detailed processes for uncertainty communication: who should be involved, optimum setting & timing, what phrases to use; how much uncertainty to share; how are such conversations received by patients  How to communicate uncertainty openly whilst maintaining a trusting relationship?  Interprofessional communication  How to individualise communication of uncertainty to different settings, situations, individual characteristics?  How does the communication of uncertainty affect decision-making and other outcomes? How to cope with uncertainty (how can individuals best be supported to cope with their uncertainties)  How do health professionals cope when they feel uncertain and how do they achieve resilience/tolerance to it?  How can patients and carers be supported to cope with their uncertainty and develop resilience?  Who copes well and why?  How to cope with the long-term impact of decisions made under conditions of uncertainty?  What is the role of hope in coping with uncertainty? Education/training of healthcare professionals (how can we train health professionals to approach uncertainty)  How to teach uncertainty management to medical students, what would be the goals of such training?  How to train HCPs at different levels to recognise/tolerate/hold their own uncertainty?  How to transfer expertise from areas where uncertainty is well managed?  Development of training interventions including psychological training Uncertainty managemen t Optimising clinical approaches to uncertainty (how can the uncertainty of others best be managed and addressed, what are optimal approaches)  How to individualise the management of uncertainty depending on patient experiences, response to uncertainty, and how to identify how much uncertainty is tolerable to an individual?  Who should 'hold' uncertainty and how to find a balance in terms of information sharing and decision-making  How to maintain trust and manage expectations?  How to gauge the readiness of people to discuss uncertainty and time conversations?  How can technology be used to distil information and reduce/address uncertainty relating to complexity/ information overload?  What is the role of uncertainty management interventions and models of care to address uncertainty, and how effective are these?  What are the key outcomes we should be aiming for when seeking to approach and manage uncertainty?  What are the barriers to addressing uncertainty? . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint  How to manage uncertainty as an MDT and maintain continuity of approach Understanding patient/carer experiences of uncertainty in depth (what are patient and carer experiences of uncertainty)  How does the experience of uncertainty affect decision-making?  What is the lived experience of uncertainty amongst patients and families (what is helpful when faced with uncertainty and what is harmful? How do the multiple layers of uncertainty interact within an individual’s experience (mapping uncertainty)? Are the experiences/impacts of different types of uncertainty different? How do past life or healthcare experiences affect current uncertainty experiences.)?  How is uncertainty transmissible i.e. how can HCP uncertainty be picked up by patients and vice versa and what is the effect of this? Variation in experience/ response to uncertainty (how does the experience of uncertainty vary between different groups)  How does experience and response to uncertainty vary between different medical specialties and health professional groups?  How does experience and response to uncertainty change over time as the illness progresses.  How do individual characteristics e.g. culture, LGBTQ status, neurodiversity, age, affect experience and response to uncertainty?  How does career stage and knowledge/experience in a clinical role affect health professionals experience?  What are the long-term effects of uncertainty experiences in ITU on ITU survivors? Explore positive aspects of uncertainty (what aspects of uncertainty are positive and how can these be promoted)  What is the relationship between sharing uncertainty and maintaining hope?  Explore positive utility of uncertainty e.g. as a way to promote a quest for knowledge or changing ways of thinking  Explore why some people thrive with uncertainty Impact of uncertainty on bereavement (how does uncertainty in serious illness impact on bereavement experiences)  How does uncertainty in serious illness and at the end of life affect experiences and outcomes of bereavement? Uncertainty experiences Uncertainty in specific conditions/clinical situations (the uncertainties that are experienced in a particular clinical situation such as in ITU)  How do different clinical situations change how uncertainty is experienced and responded to?  Are there situations where the expression of uncertainty is not appropriate?  How to make good decisions in the context of uncertainty in the intensive care unit?  How is uncertainty experienced in children with complex neuro-disability?  How to approach uncertainty in adults with neurodegenerative disease and uncertain illness trajectory?  How to approach uncertainty in frailty with uncertain prognosis? . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint  How to communicate uncertainty at transitions of care Factors associated with different uncertainty experiences (what factors are associated with different experiences of or responses to uncertainty.)  What system factors underlie the challenges of uncertainty?  What factors are associated with uncertainty experiences and tolerance e.g. age, life experience, culture?  How did the COVID-19 pandemic affect experiences and response to uncertainty?  How does trust in clinicians affect uncertainty experiences? 261 *Priority areas are listed in the order they were ranked . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 262 Discussion 263 Summary of findings 264 This study co-produced clinically-focused research priorities to address known evidence gaps 265 concerning uncertainty in serious illness. Optimising communication of uncertainty was the top 266 research priority. Research into managing uncertainty was considered higher priority than research 267 investigating experiences of uncertainty. 268 269 Discussion of main findings 270 Communicating uncertainty was the top priority for participants, reflecting key evidence gaps and 271 recommendations in this field.[32, 47] In their narrative review of uncertainty communication, 272 Simpkin et al identified a number of evidence gaps, including identifying individuals' communication 273 preferences and tailoring communication to those preferences.[34] The question of how to maintain 274 hope whilst communicating uncertainty was noted as a priority; this has been explored in cancer 275 care,[48] but remains a key question in other serious illnesses. Additionally, participants raised 276 several sub-questions in terms of how to discuss uncertainty, reflecting the need for 277 implementation-focused communication research. 278 After communication, participants prioritised other aspects of managing uncertainty: identifying 279 how individuals can be supported to cope with their own uncertainty; investigating how we can 280 optimise clinical approaches to uncertainty; understanding more about how to equip health 281 professionals to deal with uncertainty through training. Though management of uncertainty has 282 been recognised as a core component of medical training for decades, curricula still make limited 283 reference to uncertainty, and filling this gap should be a priority.(2) Whilst we have an improving 284 understanding of how physicians manage uncertainty,[31] the evidence base for other professional 285 groups is very limited, yet nurses and allied healthcare professionals often lead the clinical care and 286 support of older people and their families. To date, uncertainty management and communication 287 interventions have had variable impact in serious illness,[32] and often prove challenging to . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 288 evaluate.[33, 49] There is scope for further intervention development,[50] especially work that 289 focuses on evaluation of uncertainty-focused interventions. 290 Whilst many of the questions identified by participants related to investigating experiences of 291 uncertainty, these were usually considered lower priority, perhaps because much is already known 292 about uncertainty experiences.[7, 51] For example, conceptual taxonomies of uncertainty are well 293 developed,(6) and there have been evidence syntheses of experience in some specific areas e.g. 294 multimorbidity.[11] However, there are still evidence gaps concerning how uncertainty affects 295 individuals in other clinical contexts, in particular older patients living with frailty. Given the rapidly 296 increasing complexity of the healthcare system and unpredictability of the frailty trajectory, this is an 297 area that warrants urgent exploration.[34] Understanding more about the impacts of uncertainty on 298 experiences of illness, care, and bereavement would enable us to develop interventions focused on 299 the real-world problems uncertainty can cause. 300 301 Strengths and limitations 302 The rapid prioritisation approach we used enabled a diverse group of interested individuals to 303 generate and rank research priorities in a single day. Those ranking the priorities had spent the 304 entire day considering uncertainty in serious illness and were well placed to express considered 305 views when ranking the list presented to them. By identifying evidence gaps before the workshop 306 and communicating these to participants during initial presentations, we were able to focus on areas 307 where more research is needed and incorporate the key stages of a traditional prioritisation 308 exercise. By additionally incorporating formal qualitative analysis we increased rigour and developed 309 a robust priority list. This approach was a more feasible and pragmatic alternative to lengthier 310 methodologies such as the Delphi process[52, 53]. However, the rapid nature of the prioritisation 311 process meant there was limited time to condense the findings of the focus group discussions, which 312 risked a loss of accuracy and ranking was limited to broad research areas. We ameliorated this by 313 subsequent analysis of focus group transcripts, which enabled us to identify detailed research . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 314 questions identified by participants, including areas that participants mentioned even when they 315 weren’t identified as priorities at the time. 316 We incorporated patient and carer experiences, but most participants were healthcare professionals 317 or researchers, thus these groups were not equally represented in the ranking process. Whilst not 318 specifically excluded, social care professionals did not attend this workshop, which limits the findings 319 to healthcare. We recruited a UK-wide sample, but this was not an international study, and future 320 work should explore if these findings hold internationally, though literature from 17 countries 321 reported consistent findings on a similar topic.[11] The anonymous nature of the ranking means we 322 could not adjust for the background of participants when analysing ranking data. The largest group 323 of clinical participants were from palliative care backgrounds which may have shaped their views; 324 however, a broad range of health professionals and researchers were represented, and the degree 325 of agreement, particularly regarding the top priority of communication suggests the findings 326 represent true consensus. 327 328 329 Conclusion 330 Through a rapid prioritisation workshop, we have identified 10 ranked priority areas for clinically 331 focused research on uncertainty in serious illness. There was consensus that further research into 332 managing uncertainty, particularly communication, was of higher priority than research to 333 investigate experiences of uncertainty. Future targeted research could result in interventions to 334 reduce the distress associated with uncertainty, unlock decision paralysis and improve illness and 335 care experience. 336 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 24, 2023. ; https://doi.org/10.1101/2023.07.21.23293007doi: medRxiv preprint 337 Acknowledgements 338 Thank you to those who facilitated focus groups: Stephan Barclay, Jonathan Koffman, Anna Spathis, 339 Ben Bowers, Sarah Hopkins, Debbie Critoph, Markus Schichtel, Ikumi Okamoto 340 We would also like to thank our patient and public involvement representatives: Roberta Lovick, 341 Sarah Dixon, Rashmi Kumar 342 Many thanks to the workshop organiser Angela Harper & the professional services team at the 343 Primary Care Unit, University of Cambridge for ensuring the smooth running of this study 344 Thank you to Zoe Fritz for your advice during drafting of the manuscript 345 346 Funding: 347 This study and SB are supported by the National Institute for Health and Care Research (NIHR) 348 Applied Research Collaboration East of England (NIHR ARC EoE) at Cambridgeshire and Peterborough 349 NHS Foundation Trust. BB is supported by the Wellcome Trust [225577/Z/22/Z]. SAH is jointly 350 funded by The Dunhill Medical Trust and British Geriatrics Society [Grant ref. JBGS20\5]. 351 The views expressed are those of the author(s) and not necessarily those of the NIHR or the 352 Department of Health and Social Care.’ 353 354 Contributions: 355 Study design: SE, SB, AS, JK 356 Securing funding: SE, SB 357 Data collection: SE, SB, AS, SAH, BB, JK 358 Analysis: SE JK 359 Paper drafting: SE, SB, AS, SAH, BB, JK 360 Approval of final version: SE, SB, AS, SAH, BB, JK 361 362 Conflicts of Interest: 363 The authors declare that they have no conflicts of interest. 364 365 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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