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Record W6948694387 · doi:10.5281/zenodo.11473969

Characterizing the Interaction of the Effects of a Museum Visit on Mobility, Cognition, and Well-being in People with Stroke

2024· dataset· en· W6948694387 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedataset
Languageen
FieldSocial Sciences
TopicHistorical Influence and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionMental healthExploratory researchQuality (philosophy)Action (physics)Quality of life (healthcare)

Abstract

fetched live from OpenAlex

Study description This exploratory small case study operated by Medical Physics Laboratory & Digital Innovation of School of Medicine of Aristotle University of Thessaloniki (AUTH) is a collaborative study between AUTH and McGill-CRIR-Canada, and for this reason it followed and replicated part of the protocol of the Canadian VITALISE partners described above. The aim of this particular small-case study was to investigate the interaction of the effects of a museum visit (Museum of Casts and Antiquities in Aristotle University of Thessaloniki) on mobility, cognition, well-being and the experience of individuals, as well as to investigate whether cognitively and verbally accessible audio guides of exhibits contribute to a better understanding of the descriptions of these exhibits, through measurements made using advanced technologies. In this context, the data collected aimed also to draw some conclusions regarding the feasibility and user satisfaction of conducting a range of different measurements and interventions in a museum setting. Piloting phase: The piloting phase began in May 2023 and was concluded at the end of the year. Prior to the museum visit, the participants were administered some questionnaires in the Thessaloniki Action for HeAlth & Wellbeing Living Lab - Thess-AHALL, aiming to obtain a holistic view on their cognitive status, as well as dimensions of their physical and mental wellbeing and quality of life. Questionnaires during the museum visit.xlsx Afterwards, the participants, one at a time, entered the museum with the members from the project’s research team, where they were asked to wear some specific equipment. In particular, they initially wore a pair of smart insoles (Digitsole Pro Smart Insoles) (Digitsole-pro-museum-dataset.csv) and a smart watch (Smartwatch-Fitbit Charge 5) Fitbit Datasets.zip and were asked to walk at their own pace following a predetermined guided tour route through the museum spaces and exhibits. Breaks were provided whenever requested by the participants.After completing their guided tour in the museum, they were asked to wear eye-tracking glasses (Pupil Labs) Pupils-dataset.zip and headphones to listen to audio descriptions (audio guides) of three selected exhibits, the Tombstone, the Hermes of Praxiteles and the West Pediment from the temple of Zeus at Olympia. Specifically, they were asked to stand in front of three (3) exhibits and listen to the description. For each of the three exhibits, participants first listened to their original description (a description that someone can usually find next to the exhibit or in a relevant educational textbook) and then they listened to the modified, accessible version of the exhibit description (with simpler words, shorter sentences etc.). After each audio description (original and modified), they were asked to answer a number of predetermined questions related to the audio description they had just heard. At the end, after the aforementioned equipment was removed, they were asked to answer a number of questions and questionnaires about their overall museum experience and potential challenges or stress experienced (Satisfaction and feasibility questionnaire, Visual Analog Stress scale, State-Trait Anxiety Inventory) Analysis feasibility & satisfaction questionnaire.xlsx.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.554
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.276
Teacher spread0.261 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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