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Record W4408382157 · doi:10.1186/s40900-025-00696-1

Convergence of neurodegeneration and the arts: a conversation between researchers about stigma, co-creativity, and transformation

2025· letter· en· W4408382157 on OpenAlexafffund
Naila Kuhlmann, Pia Kontos, Maria Bee Christensen-Strynø, Stefanie Blain‐Moraes

Bibliographic record

VenueResearch Involvement and Engagement · 2025
Typeletter
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity Health NetworkMcGill UniversityToronto Rehabilitation InstituteNational Circus School
FundersFonds de recherche du Québec – Nature et technologies
KeywordsConversationCreativityThe artsStigma (botany)Convergence (economics)PsychologyTransformation (genetics)AestheticsCognitive scienceSociologySocial psychologyVisual artsArtCommunicationPsychiatry

Abstract

fetched live from OpenAlex

Parkinson’s disease and dementia are highly stigmatized, creating social exclusion and inequality by depriving persons living with these conditions of their human rights and threatening their health, well-being, and quality of life. Challenging the stigma associated with these conditions is a key public health priority across national and international settings, and arts-based approaches are advocated to achieve this. We are researchers who use artistic and creative media including documentary films, research-based theatre, dance, circus and graphic narrative to challenge dominant and oppressive cultural and social norms, and to imagine and affect inclusive, compassionate, and socially-just approaches to supporting people to live well with neurodegenerative conditions like dementia and Parkinson’s. This includes fostering opportunities for co-creative engagement with people living with these conditions, to promote their inclusion as co-creators rather than subjects in research initiatives. In this conversation-style article, we draw on our qualitative research and experiential knowledge to reflect on the challenges and opportunities regarding arts-based research with people living with Parkinson’s disease or dementia. We share examples from our own work, across a range of artistic approaches, to illustrate the transformative potential of the arts to affect social change and to bring to light the tensions that arise in co-creative processes. Through this conversation, we hope to inspire and equip others to draw on the power and complexities of arts-based approaches for the co-production of knowledge to transform societal representation of neurological conditions and to foster human flourishing. Stigma associated with Parkinson’s disease and dementia leads to social exclusion and health inequalities, threatening the well-being of individuals living with these conditions. This stigma stems from an assumption that these conditions impede the ability to build and maintain relationships, and therefore to participate meaningfully in society. The arts support human flourishing by opening avenues for self-expression, creativity and relationship-building, and provide an opportunity for persons living with these conditions to be directly engaged in research initiatives as the experts of their own experience. We are researchers who use artistic and creative media to challenge negative representations and misperceptions of Parkinson’s disease and dementia through the arts, and to involve persons living with these conditions as co-creators in our research. In this conversation piece, we share examples of our work in documentary film, theatre, dance, circus and graphic novels to illustrate the transformative power of art for social change, and to discuss the challenges and opportunities that arise along the way—with the hope that it may inspire others to explore the intersection of the arts and neurodegenerative conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.316
GPT teacher head0.407
Teacher spread0.092 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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