MétaCan
Menu
Back to cohort

PROTOTYPING THE “MEMO” MOBILE APPLICATION USING INTERFACE HEURISTICS FOR OLDER ADULTS

2025· article· W4415814707 on OpenAlexaffabout
Dayane Aparecida Scaramal, Sylvie Belleville, Bobby Gilbert, Isabelle Patriciá Freitas Soares Chariglione, Maria do Carmo Fernandez Lourenço Haddad, André Estevam Jaques, Rosângela Aparecida Pimenta Ferrari, Mara Solange Gomes Dellaroza

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2025
Typearticle
Language
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsClinique Neuro-OutaouaisInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsHeuristicsInterface (matter)User interfaceInterface designProcess (computing)Mobile device

Abstract

fetched live from OpenAlex

ABSTRACT Objective: to build a mobile app prototype for the Canadian cognitive training program Méthode d’Entrainement pour une Mémoire Optimale, with an interface and design specifically for older adults. Method: a methodological study of technological production incorporating interface heuristics for small touchscreens for older adults, combined with the Prototyping Paradigm, systematized into: (1) communication; (2) rapid design and modeling; (3) prototype construction; and (4) deployment, delivery, and feedback. The prototyping process took place between February 2022 and August 2023. Results: the prototype included 216 screens divided into six sections, each containing cognitive training activities and information on aging and cognition. A concept map was created covering all content, followed by wireframing of the screens, enabling application of interface heuristics, including cognitive, visual, data entry, touch, and generational aspects. Conclusion: the adopted approach, combined with interface heuristics for the older adult population, resulted in creating a unique prototype whose aspects were meticulously planned and refined to ensure a fluid and seamless user experience, helping to reduce the accessibility gap of technological resources for these individuals.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.185
GPT teacher head0.467
Teacher spread0.283 · 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.

Study designOther design
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueTexto & Contexto - EnfermagemSame topicTechnology Use by Older AdultsFrench-language works237,207