Evidence map›Paper›PMID 34255643›Full record

ReviewJMIR aging2021

The Effect of Mixed Reality Technologies for Falls Prevention Among Older Adults: Systematic Review and Meta-analysis.

Anna Nishchyk, Weiqin Chen, Are Hugo Pripp, Astrid Bergland

Open access · goldAbstract readReview
In one paragraph

Review in JMIR aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 4 pooled it
2.9field-weighted citation impact, top 8% of its field
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

17 citing papers in PubMed, 4 syntheses or guidelines pooled it, 35 citations in OpenAlex.

  1. Pooled it
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  11. An Iterative Participatory Design Approach to Develop Collaborative Augmented Reality Activities for Older Adults in Long-Term Care Facilities.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
    Article
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  13. Review
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  17. Benefits of a Wearable Activity Tracker with Safety Features for Older Adults: An Intervention Study.International journal of environmental research and public health · 2022
    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

4 authors at 1 institution in 1 country.

Anna NishchykDepartment of Computer Science, Faculty of Technology, Art and Design, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0000-0002-1184-1353
Weiqin ChenDepartment of Computer Science, Faculty of Technology, Art and Design, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0000-0002-7735-8233
Are Hugo PrippFaculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0000-0002-1678-7309
Astrid BerglandFaculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0000-0003-4349-8200
OsloMet – Oslo Metropolitan University · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFalling is one of the most common and serious age-related issues, and falls can significantly impair the quality of life of older adults. Approximately one-third of people over 65 experience a fall annually. Previous research has shown that physical exercise could help reduce falls among older adults and improve their health. However, older adults often find it challenging to follow and adhere to physical exercise programs. Interventions using mixed reality (MR) technology could help address these issues. MR combines artificial augmented computer-generated elements with the real world. It has frequently been used for training and rehabilitation purposes.

objectiveThe aim of this systematic literature review and meta-analysis was to investigate the use of the full spectrum of MR technologies for fall prevention intervention and summarize evidence of the effectiveness of this approach.

methodsIn our qualitative synthesis, we analyzed a number of features of the selected studies, including aim, type of exercise, technology used for intervention, study sample size, participant demographics and history of falls, study design, involvement of health professionals or caregivers, duration and frequency of the intervention, study outcome measures, and results of the study. To systematically assess the results of the selected studies and identify the common effect of MR interventions, a meta-analysis was performed.

resultsSeven databases were searched, and the initial search yielded 5838 results. With the considered inclusion and exclusion criteria, 21 studies were included in the qualitative synthesis and 12 were included in meta-analysis. The majority of studies demonstrated a positive effect of an MR intervention on fall risk factors among older participants. The meta-analysis demonstrated a statistically significant difference in Berg Balance Scale score between the intervention and control groups (ES: 0.564; 95% CI 0.246-0.882; P<.001) with heterogeneity statistics of I2=54.9% and Q=17.74 (P=.02), and a statistical difference in Timed Up and Go test scores between the intervention and control groups (ES: 0.318; 95% CI 0.025-0.662; P<.001) with heterogeneity statistics of I2=77.6% and Q=44.63 (P<.001). The corresponding funnel plot and the Egger test for small-study effects (P=.76 and P=.11 for Berg Balance Scale and Timed Up and Go, respectively) indicate that a minor publication bias in the studies might be present in the Berg Balance Scale results.

conclusionsThe literature review and meta-analysis demonstrate that the use of MR interventions can have a positive effect on physical functions in the elderly. MR has the potential to help older users perform physical exercises that could improve their health conditions. However, more research on the effect of MR fall prevention interventions should be conducted with special focus given to MR usability issues.

Indexed as

augmented realityfall preventionfallsmixed realityphysical exercisevirtual reality

Identifiers

PMID34255643
PMCPMC8280833
OpenAlexW3174589773

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.