Grasp Your Pain: A Tangible Tool to Explore the Logging and Assessment of Pain
Notice bibliographique
Résumé
Pain is a subjective and innate experience that can be difficult to describe. Chronic pain is associated with decreased quality of life, and it is prevalent in cancer populations. With a growing elderly population, the global cancer burden is expected to rapidly advance in the coming years. Expressing pain and symptom experiences is essential for patients to receive proper treatment and care. Self-reporting tools are useful and reliable measures of patients' symptoms. A commonly used assessment form in palliative care is ESAS-r, the revised Edmonton Symptom Assessment System. It lets the patient rate a list of symptoms, on a scale from 0 to 10, depending on their intensity. Research suggests that ESAS-r only captures a snapshot of the patients' symptom profile, and that is burdensome to patients and clinical staff. There is a need for self-assessment tools that are easy to use, non-intrusive, and can be used in situ. The research in this thesis explores the use of a tangible tool (Grasp), and squeezing as an input method to log pain/symptoms experiences. Grasp consists of a small stone-like object. When squeezed, it logs the time and duration of the interaction. Squeezes are then visualized on an accompanying interface. Through a Mixed Methods Research approach, a pilot study and clinical trial were conducted. The former gathered participant (N=8) opinions on Grasp, and the use of squeeze duration to log experiences. The latter explored the implementation of Grasp alongside ESAS-r in a cancer ward (nurses = 6, patients = 8). Two broad research questions were examined: RQ1: How can tangible interaction through Grasp support the logging of experiences? and RQ2: How do palliative cancer patients and nurses experience Grasp as a tool for the logging, assessment, and communication of pain and symptoms compared to ESAS-r? Findings from the pilot suggest that there is potential in using Grasp and squeeze duration to log events, and that interacting with the tool potentially can help distract or externalize from negative experiences. Participants from both studies found Grasp easy to use, and visualizations intuitive and meaningful. Nurses and patients were generally satisfied with Grasp as a tool, and it helped paint a wider image of the patients' symptoms compared to ESAS-r alone. However, patients were sometimes too ill to use Grasp, and the research was limited by barriers related to clinical environments. Further research is needed to explore the potential of tangible interaction and squeezing as an input method with other patient groups. There is also the aspect of the affective interaction that should be investigated further.
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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,007 |
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 ».