Evidence map›Paper›PMID 38746626›Full record

ArticleJournal of Alzheimer's disease reports2024

A Scoping Survey to Inform Design of Digital Dementia Risk Reduction Interventions for Adults Concerned about their Cognitive Health.

Jessica G Amos, Lidan Zheng, Ranmalee Eramudugolla, Sophie C Andrews, Kaarin J Anstey

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jessica G AmosUNSW School of Psychology, The University of New South Wales, Sydney, NSW, Australia.ORCID https://orcid.org/0000-0003-3459-302X
Lidan ZhengUNSW School of Psychology, The University of New South Wales, Sydney, NSW, Australia.
Ranmalee EramudugollaUNSW School of Psychology, The University of New South Wales, Sydney, NSW, Australia.
Sophie C AndrewsUNSW School of Psychology, The University of New South Wales, Sydney, NSW, Australia.
Kaarin J AnsteyUNSW School of Psychology, The University of New South Wales, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital dementia risk reduction interventions are cost-effective and scalable. However, it is unknown how they are perceived by people already experiencing cognitive concerns or decline. Objective: To understand the current use, interest, and preferences for online learning courses and interest in learning about factors influencing brain health and dementia risk among adults ≥45. To explore potential differences between individuals experiencing cognitive concerns and those without. Methods: Adults aged 45 and older completed a survey on technology use and healthy ageing ( Results: Almost all participants (98.4%) reported using two or more digital devices, and 51.8% reported increasing device usage following COVID-19. Most (92.1%) were interested in learning about healthy living and memory within an online course, and over 80% indicated a high interest in learning about dementia risk factors. People with cognitive concerns were more likely to report using a 'routine or system' to aid memory than people without (82.4% versus 62.9%, Conclusions: We conclude that adults 45 years and over are interested in online methods for learning about brain health and offer unique insights into adapting dementia prevention programs for cognitive concerns.

Indexed as

Alzheimer’s diseasecognitiondementiaprevention and controltechnology

Identifiers

PMID38746626
PMCPMC11091727

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.