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Record W4225013419 · doi:10.1145/3491102.3517692

Design is Worth a Thousand Words: The Effect of Digital Interaction Design on Picture-Prompted Reminiscence

2022· article· en· W4225013419 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCHI Conference on Human Factors in Computing Systems · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of Toronto
FundersAGE-WELL
KeywordsReminiscenceTouchscreenUsabilityComputer sciencePsychologyHuman–computer interactionRecallCognitive psychology

Abstract

fetched live from OpenAlex

Interactions with our personal and family pictures are essential to continued social reminiscence, leading to long-term benefits, including reduced social isolation. Previous research has identified how designs of digital picture tools fall short of physical options specifically in terms of reminiscence. However, the relative prompting abilities of different digital interactions, including the types of memories prompted like external facts or person-centred memories, have not yet been explored. To investigate this, we present a controlled study of the memories prompted by three digital picture interactions (slideshow, gallery, and tabletop) on personal touchscreen devices. We find differences in how these tools and the interactions they support prompt reminiscence. In particular, gallery views prompt significantly fewer memories than either the tabletop or slideshow. Slideshows prompt significantly more external, factual memories, but not more person-centred memories, which are key to reminiscence. This has implications for the overall social usability of digital picture interactions.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.085
GPT teacher head0.340
Teacher spread0.255 · 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