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Record W2326279176 · doi:10.1097/cin.0000000000000145

Adolescent Reactions to Icon-Driven Response Modes in a Tablet-Based Health Screening Tool

2015· article· en· W2326279176 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCIN Computers Informatics Nursing · 2015
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of British ColumbiaBritish Columbia Centre on Substance Use
FundersCanadian Institutes of Health Research
KeywordsIconCLARITYComprehensionPsychologyDemographicsAudience responseCognitionMedical educationApplied psychologyMedicineMultimediaComputer science

Abstract

fetched live from OpenAlex

Increasingly popular touch-screen electronic tablets offer clinics a new medium for collecting adolescent health screening data in the waiting area before visits, but there has been limited evaluation of interactive response modes. This study investigated the clarity, comprehensibility, and utility of icon-driven and gestural response functions employed in one such screening tool, TickiT. We conducted cognitive processing interviews with 30 adolescents from Vancouver (aged 14-20 years, 60% female, 30% English as a second language) as they completed the TickiT survey. Participants used seven different interactive functions to respond to questions across 30 slides, while being prompted to articulate their thoughts and reactions. The audio-recorded, transcribed interviews were analyzed for evidence of comprehension, nuances in response choices, and youth interest in the modes. Participants were quite receptive to the icon response modes. Across demographics and cultural backgrounds, they indicated question prompts were clear, response choices appropriate, and response modes intuitive. Most said they found the format engaging and would be more inclined to fill out such a screening tool than a paper-and-pencil form in a clinical setting. Given the positive responses and ready understanding of these modes among youth, clinicians may want to consider interactive icon-driven approaches for screening.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.110
GPT teacher head0.431
Teacher spread0.321 · 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