ArticleDigital health
Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07783074 (Fatigue Investigation Using Digital Outcomes), which is not on this map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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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.
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.
Fatigue Investigation Using Digital Outcomes (FIDO) - An Exploratory Project
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Measuring Fatigue in Multiple Sclerosis: A Rapid Review.The patient · 2025Pooled it
- Fatigue: a common but poorly understood symptom in neurological and non-neurological diseases.Nature reviews. Neurology · 2025Review
- Fatigue prediction needs time: comparing the diagnostic value of short vs. prolonged cognitive load.Journal of neurology · 2025Article
- The Effects and Mechanisms of Ti-Fu-Kang Decoction in Alleviating Central Fatigue: Insights from Network Pharmacology and Metabolomics.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Review
- A New Smartphone-Based Cognitive Screening Battery for Multiple Sclerosis (icognition): Validation Study.Journal of medical Internet research · 2025Article
- Application of telemedicine in fatigue management for patients with multiple sclerosis: A scoping review.PloS one · 2025Article
- Modeling multiple sclerosis using mobile and wearable sensor data.NPJ digital medicine · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Fatigue is a common symptom of many diseases, including multiple sclerosis. It manifests as a cognitive or physical condition. Fatigue is poorly understood, and effective therapies are missing. Furthermore, there is a lack of methods to measure fatigue objectively. Fatigability, the measurable decline in performance during a task, has been suggested as a complementary method to quantify fatigue. Objective: To develop a new and objective measurement of cognitive fatigability and investigate its association with perceived fatigue. Methods: We introduced the cognitive fatigability assessment test (cFAST), a novel smartphone-based test to quantify cognitive fatigability. Forty-two people with multiple sclerosis (23 fatigued and 19 non-fatigued, defined by the Fatigue Scale for Motor and Cognitive Functions) took part in our validation study. Patients completed cFAST twice. We used t-tests, Monte Carlo sampling, and area under the receiver operating characteristic curves to evaluate our approach using two sets of proposed metrics. Results: When classifying fatigue, our fatigability metric Conclusions: We introduce cFAST, a new instrument to quantify cognitive fatigability. Our pilot study provides evidence that cognitive fatigability assessment test produces a quantifiable drop in cognitive performance in a short period. Furthermore, our results indicate that cFAST may have the potential to serve as a surrogate for subjective cognitive fatigue. cFAST is significantly shorter than the existing fatigability assessments and does not require specialized equipment. Thus, it could enable frequent and remote monitoring, which could substantially aid clinicians in better understanding and treating fatigue.
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Registered trials
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.