Evidence map›Paper›PMID 41768410›Full record

ReviewFrontiers in rehabilitation sciences2026

Rehabilitation strategies for long COVID: integrating human factors engineering.

Tzu-Sui Hung

Abstract readReview
In one paragraph

Review in Frontiers in rehabilitation sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Tzu-Sui HungDepartment of Mechanical and Industrial Engineering, Vanung University, Taoyuan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long COVID presents unique challenges that extend beyond conventional biomedical rehabilitation, necessitating strategies that are adaptive, multidisciplinary, and patient-centered. This mini-review synthesizes current evidence on physical, cognitive, and occupational rehabilitation, and introduces human factors engineering as a framework to optimize the design, delivery, and usability of interventions. Emerging approaches such as telerehabilitation, cognitive ergonomics, and structured return-to-work programs illustrate the value of integrating clinical rehabilitation with user-centered design. Yet critical gaps remain, including the limited number of randomized controlled trials, the heterogeneity of outcome measures, and the lack of systematic integration between rehabilitation and human factors research. Addressing these challenges will be essential to develop effective, scalable, and sustainable interventions. By aligning rehabilitation protocols with the principles of human factors engineering, future practice can better enhance efficacy, promote sustained patient engagement, and ultimately improve the quality of life for individuals living with long COVID.

Indexed as

adaptive strategieshuman factors engineeringlong COVIDpatient-centeredrehabilitation

Identifiers

PMID41768410
PMCPMC12935956

What OpenQuestion holds

Textmetadata
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.