MétaCan
Menu
Back to cohort
Record 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 on OpenAlexvenueno aff
Isabella Scandurra, Marie Sjölinder

Bibliographic record

VenueMedicine 2 0 · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinesseHealthSocial isolationIsolation (microbiology)Participatory designCitizen journalismPublic relationsComputer scienceSociologyBusinessInternet privacyPsychologyEngineeringWorld Wide WebPolitical scienceEconomic growthHealth careEconomicsSocial psychologyOperations management

Abstract

fetched live from 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.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.319
Teacher spread0.288 · 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 designQualitative
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

Citations37
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueMedicine 2 0Same topicTechnology Use by Older AdultsFrench-language works237,207