Evidence map›Paper›PMID 41048307›Full record

ArticleFrontiers in public health2025

Economic evaluation of a digital health intervention for preventing dementia in Canadians with mild cognitive impairment.

Seyed-Mohammad Fereshtehnejad, Karim Keshavjee, Peter C Coyte

Abstract read
In one paragraph

Article 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

3 authors.

Seyed-Mohammad FereshtehnejadDivision of Neurology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Karim KeshavjeeInstitute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Peter C CoyteInstitute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dementia poses an on-going Canadian challenge due to an aging population, with cases projected to rise significantly by 2050. This study evaluates the cost-effectiveness of a conceptual digital health intervention designed to prevent dementia in Canadians with mild cognitive impairment (MCI). The analysis is exploratory and conceptual, comparing different scenarios for the possible effectiveness of the digital intervention for dementia prevention. Using data from the Global Burden of Disease (GBD) 2021 study, a long-term economic evaluation was conducted from a healthcare payer perspective, comparing intervention costs to usual care between 2030 and 2050. Health outcome was assessed using disability-adjusted life years (DALYs) averted. The analysis revealed favorable incremental cost-effectiveness ratios (ICERs) well below conventional willingness-to-pay thresholds across all scenarios. Sensitivity analyses confirmed the robustness of these findings, underscoring the intervention's potential to cost-effectively reduce dementia burden. The findings are based on modeled assumptions in the absence of empirical efficacy data and should therefore be interpreted with caution until validated in real-world settings. Yet, these results provide valuable insights for Canadian policymakers on scalable, proactive dementia prevention strategies.

Indexed as

Cognitive DysfunctionCost-Benefit AnalysisDementiaTelemedicineAgedAged, 80 and overCanadaDigital HealthFemaleHumansMaleNorth American PeopleQuality-Adjusted Life Yearscost-effectiveness analyses (CEAs)dementiadigital health interventionmild cognitive impairmentprevention

Identifiers

PMID41048307
PMCPMC12491218

What OpenQuestion holds

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LicenceCC BY
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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.