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Record W4404510143 · doi:10.14519/kjot.2024.32.3.02

A Systematic Review of the Effects of Occupational Therapy on Social Participation in Older Adults with Dementia

2024· review· en· W4404510143 on OpenAlexaboutno aff
Pu-Reum Jeon, Young Ju Yoo

Bibliographic record

Venuenot available
Typereview
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyDementiaGerontologyPsychologyMedicineClinical psychologyPsychiatryDisease

Abstract

fetched live from OpenAlex

Objective: This article aimed to systematically review studies on occupational therapy to improve social participation in older adults with dementia to elucidate associated intervention types, effects, and assessment tools. Methods: Literature published from 2014 to 2024 was searched using RISS, PubMed, and Embase. The main search terms included “dementia”, “social activity”, “leisure activity”, “play activity”, “social interaction activity”, “community based activity”, “social participation” and “occupational therapy”. Nine studies were selected based on the inclusion and exclusion criteria. Results: The selected studies showed high quality and a low risk of bias. The interventions were mainly occupational or activity-based, and cognitive occupational therapy was commonly employed. All studies reported that occupational therapy improves social participation, highlighting improvements in social activities and instrumental activities of daily living. Overall, 23 assessment tools were used, with the Canadian Occupational Performance Measure and Social Behavior Scale being the most frequently used tools. Conclusion: This study confirmed the effectiveness of occupational therapy in improving social participation in older adults with dementia, thereby providing valuable insights for clinical practice.

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)0.029
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 score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0110.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.190
GPT teacher head0.574
Teacher spread0.383 · 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
Published2024
Admission routes1
Has abstractyes

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