DATA SET for: 'Misdiagnosed and misunderstood'- Poetry as a co-created research methodology across geographical boundaries for rarer dementias: The electronic poems
Notice bibliographique
Résumé
This data set contains 27 completed poems from 71 participants (9 cohort groups), explanations of the poets’ creative process, and source material (original words) from people living with rare dementia and carers who responded to a series of three prompts over a 12 week period. Data was collected between 2021-2022 as part of the Electronic Poems Project within the Rare Dementia Support Impact Study. Study Abstract Purpose: Poetry can convey sensory and emotional information and is a way to understand complex phenomena. This study explored the development of a new co-created form of poetic inquiry to further comprehend the lived experiences of people affected by 6 rarer dementias. These include young onset, inherited and non-memory-led conditions that are often misunderstood and subsequently lack care and support. Methods: Three prompts over about 12 weeks were sent electronically to 71 international participants to solicit responses, which were thematically analysed, creating 27 group poems. Follow-up surveys using content analysis assessed participant experiences producing and responding to the poems. Results: Analysis resulted in 3 - 4 themes per prompt, conveying very difficult aspects of lived experience, often owing to atypical symptoms, younger onset, misunderstandings by professionals and others, lack of support pathways, tremendous future uncertainty and a continuous struggle to adapt. Survey results found 74% had a positive experience contributing to the poems whilst 84% responded positively to the completed poems. Conclusions: As one of the largest empirical poetry-based studies that we are aware of, this novel, accessible approach of co-creating group poems yielded support for poetry as an arts-based qualitative research methodology that was able to gather substantial in-depth information about the experiences and needs of those affected by rarer dementias. Survey responses provided additional significant support for this methodological approach. Future research is suggested. Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is part of the Rare Dementia Support Impact Project (The impact of multicomponent support groups for those living with rare dementias, (ES/S010467/1)) and is funded jointly by Economic and Social Research Council, part of UK Research and Innovation, and the National Institute for Health Research (UK). The views expressed are those of the authors and not necessarily those of the ESRC, UKRI, the NIHR or the Department of Health and Social Care. Rare Dementia Support is generously supported by the National Brain Appeal https://www.nationalbrainappeal.org/). Lead investigator S. J. Crutch and co-investigators: J. Stott, P. M. Camic, G. Windle, R. Tudor-Edwards, Z. Hoare, M.P. Sullivan and R. McKee-Jackson.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,101 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,060 | 0,015 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».