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Record W4413107836 · doi:10.2196/67919

Staff Enablement of the Tovertafel for Enrichment in Residential Aged Care: Field Study

2025· article· en· W4413107836 on OpenAlexvenueno aff
Ryan Kelly, Asmita Manchha, Jenny Waycott, Rajna Ogrin, Judy Lowthian

Bibliographic record

VenueJMIR Aging · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsAged careResidential carePsychologyField (mathematics)GerontologyMedicineMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Enrichment activities are essential for enhancing the psychosocial well-being of older adults living in residential aged care homes. There has been increasing interest in using digital technology for enrichment, but the implementation of technology requires careful support and enablement from staff to ensure that residents experience the intended benefits. OBJECTIVE: This study aimed to understand how care staff facilitate aged care residents' use of the Tovertafel ("magic table" in Dutch), a technology that projects images onto a tabletop to enable groups of people to play games. The study further aimed to understand the benefits arising from the Tovertafel when facilitated by staff. METHODS: We conducted a field study in 1 residential aged care home in Queensland, Australia. The methods included semistructured interviews with the staff and residents about their experiences with the Tovertafel, observations of 4 sessions in which the residents and staff played Tovertafel games, and a diary completed by the staff after Tovertafel sessions. Data were analyzed through reflexive thematic analysis. RESULTS: We developed 3 themes through our analysis. Theme 1 highlights the need for the staff to overcome physical and personal barriers before Tovertafel sessions could take place. These included a lack of a dedicated space for playing Tovertafel games and the residents' reluctance to attend Tovertafel sessions. Theme 2 highlights how the staff used creative strategies to make Tovertafel sessions successful. These included helping the residents learn how to interact with the games; adapting the activity to suit the capabilities of the residents; sustaining engagement by choosing appropriate games; and using prompts, questions, and storytelling to make the games more engaging. Theme 3 describes the benefits and outcomes that arose from staff-supported enablement of the Tovertafel, including participation in an enjoyable physical activity, socialization, and reminiscence. CONCLUSIONS: This study suggests that the Tovertafel provides opportunities for aged care staff to engage in creative play and personalization catering to residents with different capabilities. However, the benefits arising from the Tovertafel are unlikely to be achieved without substantial facilitation from the staff, who play a key role in enabling the participation of the residents. Sustaining the engagement of the residents is important during Tovertafel activities and can lead to beneficial outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0060.002
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.333
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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