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Enregistrement W2010815820 · doi:10.2196/med20.2729

Participatory Design With Seniors: Design of Future Services and Iterative Refinements of Interactive eHealth Services for Old Citizens

2013· article· en· W2010815820 sur OpenAlexvenueno aff
Isabella Scandurra, Marie Sjölinder

Notice bibliographique

RevueMedicine 2 0 · 2013
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueTechnology Use by Older Adults
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLonelinesseHealthSocial isolationIsolation (microbiology)Participatory designCitizen journalismPublic relationsComputer scienceSociologyBusinessInternet privacyPsychologyEngineeringWorld Wide WebPolitical scienceEconomic growthHealth careEconomicsSocial psychologyOperations management

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: There is an increasing social isolation among the elderly today. This will be an even larger issue in the future with growing numbers of elderly and less resources, for example, in terms of economy and staff. Loneliness and social isolation can, however, be addressed in several ways using different interactive eHealth services. OBJECTIVE: This case study investigated novel eHealth services for the elderly, and their usage of a social interactive device designed especially for them. METHODS: In this work, we used an innovative mobile communication device connected to the television (TV), which worked as a remotely controlled large interactive screen. The device was tested by 8 volunteers who visited a senior center. They were between 65 and 80 years of age and lived in their own homes. Throughout the 1.5 year-long project, 7 design workshops were held with the seniors and the staff at the center. During these workshops, demands and preferences regarding existing and new services were gathered. At the end of the project the participants' experience of the device and of the services was elaborated in 3 workshops to get ideas for improved or new meaningful services. During the data analyses and development process, what seniors thought would be useful in relation to what was feasible was prioritized by the development company. RESULTS: Regarding daily usage, the seniors reported that they mainly used the service for receiving information from the senior center and for communication with other participants in the group or with younger relatives. They also read information about events at the senior center and they liked to perform a weekly sent out workout exercise. Further, they played games such as Memory and Sudoku using the device. The service development focused on three categories of services: cognitive activities, social activities, and physical activities. A cognitive activity service that would be meaningful to develop was a game for practicing working memory. In the social activities category, the seniors wanted different quizzes and multi-player games. For physical activities, the seniors desired more workout exercises and suggestions for guided walking routes. A new category, "information and news", was suggested since they lacked services like senior-customized global and local news. CONCLUSIONS: This study showed the importance of input from a group of seniors when designing new services for elderly citizens. Besides input to interactive eHealth service development for seniors, this study showed the importance of a social context around such work. The seniors were very engaged throughout the project and workshops were frequently visited and the seniors became friends. The high amount of input from the seniors could be explained in terms of social inclusion; they belonged to a group and each member was considered important for the work. The friendly workshop atmosphere facilitated new ideas and redesign of the services.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,083
Score d'incertitude au seuil0,551

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,031
Tête enseignante GPT0,319
Écart entre enseignants0,288 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations37
Publié2013
Routes d'admission1
Résumé présentoui

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