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Record W4416275969 · doi:10.1016/j.jamda.2025.105971

Best Practices for the Design and Evaluation of Bathing Spaces for Older Adults With Cognitive Impairment in Residential Care Settings: A Scoping Review

2025· article· en· W4416275969 on OpenAlexafffund
Vaishnavi Konda, Twinkle Arora, Pia Kontos, Bruce J. Hinds, Maya Desai, Laura Arpiainen, Jessica Babineau, Alexandra Boissonneault, Gail Elliot, Ellen Godson, Gabrielle Rossit, Tony Ross‐Hellauer, Arezoo Talebzadeh, Andrea Iaboni

Bibliographic record

VenueJournal of the American Medical Directors Association · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsIsomer Design (Canada)Toronto Rehabilitation InstituteITS Electronics (Canada)University of TorontoUniversity Health NetworkOntario College of Art and Design
FundersCentre for Aging + Brain Health InnovationCentre d’innovation canadien sur la santé du cerveau et le vieillissement
KeywordsBathingResidential careBest practiceCognitive impairmentDignityDistressAged careLevel design

Abstract

fetched live from OpenAlex

OBJECTIVES: Bathing and hygiene routines can be stressful for individuals living with dementia or other cognitive disabilities in residential care. Cold or unfamiliar bathrooms and limited staff resources often contribute to distress. DESIGN: Scoping review. SETTING AND PARTICIPANTS: This scoping review aimed to (1) synthesize existing evidence on communal bathroom design for adults older than 50 who live with cognitive impairment in residential care settings and identify gaps, and (2) explore methods for evaluating the design of these spaces. METHODS: Following Joanna Briggs Institute guidelines, we searched databases (APA PsycINFO, CINAHL, Bloomsbury Architecture/Design libraries, Embase/Embase Classic, JSTOR, Web of Science Core) and gray literature from inception to July 2023. Eligible sources included English peer-reviewed studies, reviews, opinion pieces, theses, and policy or conference abstracts/papers using qualitative, quantitative, or mixed methods. Key findings and gaps were analyzed using qualitative content analysis and synthesized narratively. A best practices framework was developed through collaborative, iterative discussion. RESULTS: Sixty-four sources (44 empirical; 20 gray literature) met inclusion criteria. The review identified 34 best practices, across 7 categories: planning, aesthetics, safety and accessibility, fixtures and assistive technology, environmental characteristics, sensory simulation, and bathing process and environment. Few validated tools or approaches for evaluating bathing environments or pre-postbathing processes were identified, and the residents' perspectives were largely absent. CONCLUSIONS AND IMPLICATIONS: Our findings emphasize the importance of concealing institutional elements and considering individual bathing habits and preferences. Designs prioritizing functionality, person-centeredness, privacy, and dignity may reduce distress and enhance the bathing experience. Future research addressing gaps in empirical evidence to support novel bathroom designs and validated evaluation tools is needed.

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)0.098
metaresearch head score (Gemma)0.225
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.098
Threshold uncertainty score0.517

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.225
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0080.011
Bibliometrics0.0160.010
Science and technology studies0.0020.004
Scholarly communication0.0120.007
Open science0.0060.005
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.368
Teacher spread0.345 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractno

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