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Record W3163433076 · doi:10.1371/journal.pone.0250761

Virtual tourism for older adults living in residential care: A mixed-methods study

2021· article· en· W3163433076 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

VenuePLoS ONE · 2021
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsToronto Metropolitan University
FundersRyerson University
KeywordsTourismPsychosocialQuality of life (healthcare)AnxietyGerontologyPsychologyQualitative researchResidential careMedicineNursingGeographySociologyPsychiatry

Abstract

fetched live from OpenAlex

Due to financial and mobility barriers, a majority of older adults living in collective dwellings are no longer able to engage in tourism, a leisure activity that contributes to quality of life and wellbeing. Immersive Virtual Reality (VR) may serve as a programmatic tool to facilitate tourism. This pilot study examined the effects of VR tourism exposure on indices of psychosocial wellbeing among older adults living in residential care. Using a mixed-methods study design, 18 older adults were exposed to VR tourism three times a week, over six weeks. Participants reported decreased anxiety and fatigue immediately following exposure, and increased social engagement and quality of life following six weeks of VR tourism. Qualitative data offered additional insight on the process by which VR tourism may enhance wellbeing. Findings suggest that immersive VR tourism may be a viable program for older adults in residential care.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.318
Teacher spread0.286 · 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