MétaCan
Menu
Back to cohort
Record W4411320216 · doi:10.2196/73378

A Digital Serious Game (Anticip’action) to Support Advance Care Planning Discussions in the General Population: Usability Study

2025· article· en· W4411320216 on OpenAlexvenueno aff
Dafne Campioni, Frédéric Ehrler, A. Berger, Christine Clavien

Bibliographic record

VenueJMIR Aging · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintUsabilityAction (physics)Computer sciencePopulationHuman–computer interactionWorld Wide WebMedicinePhysics

Abstract

fetched live from OpenAlex

BACKGROUND: In the context of an aging population and increasingly medicalized end-of-life practices, it is crucial to promote early discussions to help patients express their view on what is essential in their life as well as articulate their preferences regarding future medical treatments and end-of-life issues. An interprofessional research team at Geneva University and the Geneva University Hospitals has developed Anticip'action, a card game designed to help initiate and conduct advance care planning and end-of-life discussions. It is available for free in paper format in diverse languages and in a digital version in French. OBJECTIVE: This study aims to assess the ergonomic quality of the digital version of the game with primary users. METHODS: Overall, 10 users (women: n=5, 50%; men: n=5, 50%; mean age 41, SD 13.4 years; range 25-65 years; education: upper level; comfortable with smartphones) completed an online usability test. The test began with a rapid desirability test to capture initial impressions of the game's main screen without knowing what it is about. This was followed by a think-aloud procedure, including 26 tasks to perform all steps of the game. Posttest questionnaires were administered to collect participants' subjective perceptions of the usability (System Usability Scale), attractiveness (AttrakDiff), and relevance as well as overall endorsement of the game (Mobile Application Rating Scale). Open-ended questions were used to further explore usability issues. Usability problems were categorized and evaluated using standard evaluation grids. Content readability was assessed with Scolarius. RESULTS: The rapid desirability test revealed an overall good or average impression. In 83.2% (208/250) of the cases, participants successfully completed the think-aloud tasks without assistance. Some of the tasks (4/25, 16%) revealed multiple usability issues requiring assistance. Analysis of the 23 failures and difficulties encountered revealed that 3 (13%) issues were due to suboptimal wording of the task instructions and that there were 9 (39%) major usability problems. All could be addressed through minor modifications. The Scolarius test indicated that the card titles were understandable at an elementary school level, while the explanations on the back of the cards required a high school reading level. Participants rated Anticip'action as good or excellent in usability (79 out of 100 on the System Usability Scale), attractiveness (1.57 on the -3 to +3 AttrakDiff scale), and relevance (4.1 out of 5 on section F of the Mobile Application Rating Scale). Participants provided overall positive qualitative feedback. CONCLUSIONS: The usability testing of the digital French version of Anticip'action produced positive results, with some areas for improvement identified. It can be recommended as a valuable resource for patients, families, and caregivers to prompt reflection, raise awareness, and support advance care planning conversations. Further tests should be conducted on wider population groups, including older patients and individuals less comfortable with digital solutions.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.391
Teacher spread0.366 · 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 designObservational
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

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR AgingSame topicTechnology Use by Older AdultsFrench-language works237,207