Standardised Data on Initiatives - STARDIT: Alpha Version

Nunn, Jack; Shafee, Thomas; Chang, Steven D.; Stephens, Richard; Elliott, J. K.; Oliver, Sandy; John, Denny; Smith, Maureen A.; Orr, Neil

doi:10.31219/osf.io/5q47h

Cited by 14 publications

(47 citation statements)

References 31 publications

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“…While the follow-up survey attempted to capture the views of all 12, this was unsuccessful so it is hard to understand these patterns. The involvement of relatively small numbers in this study mean that although there is useful learning from our findings, their significance can only be enhanced by standardised data sharing that can then combine with results with other studies 16 .…”

Section: Limitationsmentioning

confidence: 94%

“…The data categories for the two surveys were informed by other similar studies to allow comparison 31 . Questions relating to 'Who should be involved in research' were included in both surveys to allow comparison with other standardised data 16 . Participants could choose from the categories outlined in Figure 2, with a change in direction towards more people being involved labelled as 'widening', the inverse as 'narrowing'.…”

Section: Methodsmentioning

confidence: 99%

“…This process is presented as an 'instrumental' case study, where the purpose is to understand the particular case, and attempt to provide data that could produce useful generalisations by using inferences from the data 39 . In order to aid analysis and comparison with other case studies, we used 'Standardised Data on Initiatives' (STARDIT) Alpha Version to consistently map preferences for involvement and report ways people were involved in the PAR process 16 .…”

Section: Methodsmentioning

confidence: 99%

“…This process overcame such challenges by collecting standardised baseline and follow-up data about views, which meant we were able to show that involving people in online discussions about involvement in research appears to change people's views about who should be involved in research, including participants 'widening' their views to include more people. Similarly, using STARDIT for standardised preference mapping and reporting of involvement meant outcomes from the process could be mapped more effectively 16,43 , including outcomes beyond the date of the initial data collection.…”

Section: Strengthsmentioning

confidence: 99%

“…This case study documents a participatory action research process with members of one of the largest biologically-related (donor-conceived) family groups ever documented (hereafter 'the sibling group') 3, [12][13][14][15] . We report the outcomes using the 'Standardised Data on Initiatives (STARDIT)' Alpha Version for planning and reporting involvement 16 . Members of the sibling group are all offspring of one sperm donor, the scientist Bertold Wiesner, a consulting biologist at the Royal Northern Hospital in the 1940s 17 .…”

Section: Introductionmentioning

confidence: 99%

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Co-Designing Genomics Research With A Large Group of Donor-Conceived Siblings

Nunn

Crawshaw

Lacaze

2020

Preprint

Self Cite

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Background: Human genomics research is growing rapidly. More effective methods are required for co-design and involving people, especially those from vulnerable sub-populations of inherently high interest to medical research. This case study documents how we worked with a large group of donor-conceived siblings who share the same sperm donor father, to explore how they might want to engage with and influence any future genomic research. Method: A participatory action research process was used to explore the views of a group of 18 known donor-conceived siblings; who are part of a larger group of up to 1000 people who share the same biological father. The discussion explored views about how the group would like to be involved in future research. Five members participated in co-design; 12 completed a pre-discussion online survey; and six participated in an online discussion forum and evaluation survey. The online discussion was led by one facilitator, supported by the study team. Results: Co-design informed the research process. Participants reported enjoying the overall experience of the surveys and discussion forum, which were perceived as inclusive and flexible. Most participants’ views regarding the value of involvement in research changed during the process, and ‘widened’ about who should be involved. Participants were supportive of future research being done with the siblings group. All who completed the final survey requested to remain part of the co-design process. Other themes in the online discussion included concerns about conflicting interests and a desire for research participation to improve the situation for people affected by assisted conception. The process informed later discussions in the sibling group about participating in a self-managed biobank and informed decision making about participating in genomics research. Conclusion: Findings from this study help inform how people from certain sub-populations should be involved in planning and defining their participation in genomic research; particularly those from more vulnerable or high-interest populations. This process provides a replicable and practical method of involving potential participants in co-designing genomics research using online discussions, with reported positive outcomes. Reporting this study using ‘Standardised data on initiatives (STARDIT)’ to report the process allows comparison with other studies.

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Section: Limitationsmentioning

confidence: 94%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Strengthsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Co-Designing Genomics Research With A Large Group of Donor-Conceived Siblings

Nunn

Crawshaw

Lacaze

2020

Preprint

Self Cite

View full text Add to dashboard Cite

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The reported impact of public involvement in biobanks: A scoping review

Puerta

Kendall

Davies

et al. 2020

Health Expectations

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Background Biobanks increasingly employ public involvement and engagement strategies, though few studies have explored their impact. This review aims to (a) investigate how the impact of public involvement in biobanks is reported and conceptualized by study authors; in order to (b) suggest how the research community might re‐conceptualize the impact of public involvement in biobanks. Methods A systematic literature search of three electronic databases and the INVOLVE Evidence Library in January 2019. Studies commenting on the impact of public involvement in a biobank were included, and a narrative review was conducted. Results and discussion Forty‐one studies covering thirty‐one biobanks were included, with varying degrees of public involvement. Impact was categorized according to where it was seen: ‘the biobank’, ‘people involved’ and ‘the wider research community’. Most studies reported involvement in a ‘functional’ way, in relation to improved rates of participation in the biobank. Broader forms of impact were reported but were vaguely defined and measured. This review highlights a lack of clarity of purpose and varied researcher conceptualizations of involvement. We pose three areas for further research and consideration by biobank researchers and public involvement practitioners. Conclusions Functional approaches to public involvement in biobanking limit impact. This conceptualization of involvement emerges from an entrenched technical understanding that ignores its political nature, complicated by long‐standing disagreement about the values of public involvement. This study urges a re‐imagination of impact, re‐conceptualized as a two‐way learning process. More support will help researchers and members of the public to undergo such reflective exercises.

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Involving people affected by a rare condition in shaping future genomic research

Nunn

Gwynne

Gray³

et al. 2021

Res Involv Engagem

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Background There is evidence that involving potential participants and the public in co-designing research can improve the quality of the study design, recruitment and acceptability of the research, but appropriate methodologies for doing this are not always clear. In this study we co-designed a way of involving people affected by a rare genomic disease in shaping future genomic research about the condition. The aim was to report the process, experiences and outcomes of involving people in genomic research in a standardised way, in order to inform future methods of involvement in research co-production. Method Participants were recruited from an online community hosted by an Australian-based rare disease charity and were over the age 18 years. Once people gave consent, we shared learning resources with participants and invited them to complete an online survey before joining a two-week facilitated online discussion, followed by a second online survey. We used the novel tool ‘Standardised Data on Initiatives - Alpha Version 0.1’ (STARDIT) to map preferences, plan involvement and report any outcomes from the process, with quantitative data analysed descriptively and qualitative data thematically analysed. Results Of the 26 people who gave consent and completed the initial survey, 15 participated in the online discussion and 12 completed the follow-up survey. STARDIT was used to report six outcomes from the process, including 60% of participants’ responses showing a change towards ‘widening’ their view of who should be involved in research to include more people. Outcomes also included an improved understanding of research and how to be involved. Participants enjoyed online discussions, found learning resources useful and asked to stay involved in the research process. The partner organisation reported that a similar online discussion will be used in future research prioritisation processes. Conclusion Involving people in co-designing the process improved the study design, ensuring it met the needs of participants. Whilst the study includes participants from only one disease group, using STARDIT allowed us to map people’s preferences and report the methods and outcomes from involving people, providing a way for learning from this case study to inform future research studies beyond the discipline of public health genomics.

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Standardised Data on Initiatives - STARDIT: Alpha Version

Cited by 14 publications

References 31 publications

Co-Designing Genomics Research With A Large Group of Donor-Conceived Siblings

Co-Designing Genomics Research With A Large Group of Donor-Conceived Siblings

The reported impact of public involvement in biobanks: A scoping review

Involving people affected by a rare condition in shaping future genomic research

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