Evidence map›Paper›PMID 41648792›Full record

ReviewDigital health

Effectiveness of digital health interventions in improving mental health in older adults with mild cognitive impairment: A systematic review and meta-analysis.

An Gu, An Huang, Bei Wu, Xueqi Liu, Cheng Huang, Xichenhui Qiu, Lina Wang

Abstract readReview
In one paragraph

Review in Digital health. 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

7 authors.

An GuSchool of Medicine, Huzhou Key Laboratory of Precise Prevention and Control of Major Chronic Diseases, Huzhou University, Huzhou, Zhejiang, China.ORCID https://orcid.org/0009-0005-1024-0336
An HuangSchool of Medicine, Huzhou Key Laboratory of Precise Prevention and Control of Major Chronic Diseases, Huzhou University, Huzhou, Zhejiang, China.ORCID https://orcid.org/0009-0008-5649-0404
Bei WuRory Meyers College of Nursing, New York University, New York, NY, USA.ORCID https://orcid.org/0000-0002-6891-244X
Xueqi LiuSchool of Medicine, Huzhou Key Laboratory of Precise Prevention and Control of Major Chronic Diseases, Huzhou University, Huzhou, Zhejiang, China.ORCID https://orcid.org/0009-0002-5067-4524
Cheng HuangHealth Management Center, Deyang People's Hospital, Deyang, Sichuan, China.ORCID https://orcid.org/0000-0001-6035-2508
Xichenhui QiuHealth Science Center, Shenzhen University, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0001-8713-6696
Lina WangSchool of Medicine, Huzhou Key Laboratory of Precise Prevention and Control of Major Chronic Diseases, Huzhou University, Huzhou, Zhejiang, China.ORCID https://orcid.org/0000-0002-8153-7015

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mental health challenges are common among older adults with mild cognitive impairment. Despite growing use of digital health interventions to improve cognitive function, their effects on mental health remain unexplored. Objective: To assess the overall and subgroup-specific effectiveness of digital health interventions on mental health in older adults with mild cognitive impairment. Methods: A systematic review and meta-analysis of randomized controlled trials was conducted following PRISMA guidelines, searching seven databases from inception to March 2024. Evidence quality was assessed using the GRADE framework and risk of bias with the Cochrane Collaboration's tool. Interrater agreement for screening and data extraction was assessed using the Kappa coefficient. Subgroup analyses assessed differences based on intervention characteristics such as type, setting, and duration, while meta-regression and sensitivity analysis identified other sources of heterogeneity and tested robustness. Results: Eleven studies involving 610 participants met the criteria. Digital health interventions significantly reduced depressive symptoms (Standardized Mean Difference [SMD] -0.55, 95% CI -0.92 to -0.19) and anxiety symptoms (SMD -0.47, -0.76 to -0.18), but showed no significant effects on positive (SMD 0.74, -0.46 to 1.94) or negative affect (SMD -0.23, -0.60 to 0.14). Subgroup analyses indicated that hospital or nursing home settings with non-portable modality were optimal. Interventions over 6 weeks, with sessions exceeding 30 min up to 2 per week, were more effective for depressive symptoms. Among intervention types, only robot interventions reduced depressive symptoms. Fully digital interventions showed greater effectiveness than hybrid formats and yielded more favorable outcomes compared to controls. Overall, digital health interventions showed a significant benefit over usual care, while effects compared to waitlist controls were larger but not statistically significant. Conclusions: This review indicates that digital health interventions hold promise for enhancing mental health in older adults with mild cognitive impairment. Future research should integrate digital therapeutic technologies to optimize interventions.

Indexed as

Digital health interventiondigital platformsmental healthmild cognitive impairmentsmart aging

Identifiers

PMID41648792
PMCPMC12868600

What Socratic 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 Socratic graph.