Power of narrative: a case study about documenting private insightful experiences while dealing with pain and associated disability
Notice bibliographique
Résumé
Objective: People adjusting to living with a chronic disability, such as chronic pain, seek support and resources from societal systems, including health systems, to help them cope with this reality. This case study describes the use of a digital health platform designed to help in that quest. Method: MyHealthMyRecord (MHMR), is being developed to record, register and curate personal private experiences of a chronic condition. MHMR allows users to record and log short (30-90s) personal and private audio-videos of their accommodation-seeking journey in a way that can be encrypted, registered, curated and shared privately. This case study describes the use of a prototype version of the platform by a participant co-designer who experienced a sudden onset of a chronic pain condition, of undetermined origin. System use began three months after the onset of the condition and just after being discharged from several months of hospitalization without any definitive diagnosis. Result: During a three-month period, 65 short unstructured contributions were authored and logged. This paper presents a qualitative analysis of that content. The clips used various communication styles that documented experiences, concerns, issues, positive and negative interactions and pain episodes. Using thematic analysis with open coding, three domains (person-facing, accessibility and system-facing) and eight themes (pain, joy, therapy, environmental, recommendations, technical, culture and communication) were identified. Comments about pain, stress, etc., were the most common and occurred in 75% of all videos while technical and therapy/physio related comments were the fewest and occurred in 3 and 9% of the videos, respectively. Conclusion: We conclude that it is possible to create recordings of events, thoughts, reflections and issues on different aspects affecting an individual's health and well-being impact, including effects of the chronic condition as well as tangential outcomes such as accessibility (or lack of it), using MHMR over a longer period of time. The next steps will be to develop functionality to annotate the recordings, automatically analyze and summarize collections of recordings to make them consumable, useful and understandable to the individual and others, and then to share those analyses and summaries with others. In addition, evaluate this functionality longitudinally with more users.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».