ArticleOccupational therapy international2023
A Semantic-Based Cognitive Training Programme on Everyday Activities: A Feasibility and Acceptability Study among Cognitively Healthy Older Adults.
Article in Occupational therapy international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- An everyday-task-focused, strategy-based educational program for informal dementia carers: a feasibility and pilot study.Scientific reports · 2026Article
- Tailoring Semantic Interventions for Older Adults: Task-Focused and Person-Centered Approaches.Brain sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: During the normal ageing process, a person's cognitive functions and memory gradually decline, which can affect their ability to perform everyday activities including cooking, cleaning, managing finances, and shopping. Semantic memory encoding strategies benefit older adults' cognitive and functional performance. Such strategies can be taught by an accessible, cost-effective, and flexible app-based programme. Currently, no studies examine such an app-based programme focussed on everyday activities. Objectives: To determine if an app-based programme constructed on the principles of semantic memory encoding strategies, targeted towards older adults, called Enhancing Memory in Daily Life (E-MinD Life) is (1) feasible by examining acceptance, engagement, and attendance and (2) acceptable by examining the perceived effectiveness, relevancy, clarity, and convenience. Methods: Eleven participants were recruited to a nine-week (18 sessions) programme using E-MinD Life. Feasibility was measured by collecting data on recruitment and retention rates, attendance, and duration of sessions. Acceptability was measured via a Likert scale questionnaire and free comments. Likert scale responses were analysed using descriptive statistics; open-ended responses were categorised qualitatively via constant comparative approach. Results: Nine participants completed the programme. Overall, most participants found the programme relevant, convenient, logical, and easy to understand and perceived it to be effective to address functional cognitive problems impacting performance of everyday activities. The results from the qualitative analysis showed that participants found the programme enjoyable and the interaction with the research team throughout the intervention beneficial. Conclusion: E-MinD Life shows promise as the focus of further research to determine the effectiveness of the programme and sematic-based cognitive strategies in maintaining cognition and performance in everyday activities among older adults with and without cognitive impairment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.