Evidence map›Paper›PMID 40520310›Full record

ReviewFrontiers in public health2025

Type and efficacy of online training for informal carers: a narrative review.

D Bressington, R Gray, K Barclay, C Overy, I Blackberry

Abstract readReview
In one paragraph

Review in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

D BressingtonCare Economy Research Institute, La Trobe University, Albury-Wodonga, VIC, Australia.
R GrayCare Economy Research Institute, La Trobe University, Albury-Wodonga, VIC, Australia.
K BarclayCare Economy Research Institute, La Trobe University, Albury-Wodonga, VIC, Australia.
C OveryCare Economy Research Institute, La Trobe University, Albury-Wodonga, VIC, Australia.
I BlackberryCare Economy Research Institute, La Trobe University, Albury-Wodonga, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The need to provide training and support for unpaid informal carers of people with various health conditions is well established. This narrative literature review was conducted to explore recent evidence of informal carer eLearning education and training programs, and to guide the design of an online training program for Australian carers, including those living in rural and geographically remote settings. Method: Different combinations of relevant search terms were used across three databases: Google Scholar Advanced, MEDLINE with full text incorporating PUBMED, and CINAHL to search for literature published since 2014. Articles within peer-reviewed journals were chosen based on their topic relevance and strength of evidence. Results: The recent systematic reviews highlight that there is a lack of good quality research evidence for the range and efficacy of eLearning programs designed for carers of veterans and adults with disabilities, or mental health conditions, with most evidence related to carers of older people and people with dementia. Conclusion: Online educational programs for carers of older people and/or older people with dementia, and those with mental health conditions can improve carer well-being. Future programs should be co-designed with carers, evaluate care recipient outcomes, and address recruitment, retention, and information technology skills.

Indexed as

CaregiversEducation, DistanceInternetAgedAustraliaDementiaHumanscaregiversdementiaeLearninginformal carersolder peopleonline trainingsupport

Identifiers

PMID40520310
PMCPMC12162675

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.