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Record W2544745526 · doi:10.1186/s12913-016-1870-z

Assessment of a multimedia-based prospective method to support public deliberations on health technology design: participant survey findings and qualitative insights

2016· article· en· W2544745526 on OpenAlex
Pascale Lehoux, Jaime Jiménez-Pernett, Fiona A. Miller, Bryn Williams–Jones

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

VenueBMC Health Services Research · 2016
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of TorontoUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsQualitative researchHealth informaticsLikert scaleMedical educationQualitative propertyFace-to-facePublic healthPsychologyNursing researchApplied psychologyMedicineNursingComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Using a combination of videos and online short stories, we conducted four face-to-face deliberative workshops in Montreal (Quebec, Canada) with members of the public who later joined additional participants in an online forum to discuss the social and ethical implications of prospective technologies. This paper presents the participants' appraisal of our intervention and provides novel qualitative insights into the use of videos and online tools in public deliberations. METHODS: We applied a mixed-method study design. A self-administered survey contained open- and close-ended items using a 5-level Likert-like scale. Absolute frequencies and proportions for the close-ended items were compiled. Qualitative data included field notes, the transcripts of the workshops and the participants' contributions to the online forum. The qualitative data were used to flesh out the survey data describing the participants' appraisal of: 1) the multimedia components of our intervention; 2) its deliberative face-to-face and online processes; and 3) its perceived effects. RESULTS: Thirty-eight participants contributed to the workshops and 57 to the online forum. A total of 46 participants filled-in the survey, for a response rate of 73 % (46/63). The videos helped 96 % of the participants to understand the fictional technologies and the online scenarios helped 98 % to reflect about the issues raised. Up to 81 % considered the arguments of the other participants to be well thought-out. Nearly all participants felt comfortable sharing their ideas in both the face-to-face (89 %) and online environments (93 %), but 88 % preferred the face-to-face workshop. As a result of the intervention, 85 % reflected more about the pros and cons of technology and 94 % learned more about the way technologies may transform society. CONCLUSIONS: This study confirms the methodological feasibility of a deliberative intervention whose originality lies in its use of videos and online scenarios. To increase deliberative depth and foster a strong engagement by all participants, face-to-face and online components need to be well integrated. Our findings suggest that online tools should be designed by considering, one the one hand, the participants' self-perceived ability to share written comments and, on the other hand, the ease with which other participants can respond to such contributions.

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)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.689
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.357
GPT teacher head0.573
Teacher spread0.217 · 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