ArticlePloS one2015
Increasing patient engagement in rehabilitation exercises using computer-based citizen science.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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Who cites it
13 citing papers in PubMed.
- Trial
- Effectiveness of the Virtual Reality System Toyra on Upper Limb Function in People with Tetraplegia: A Pilot Randomized Clinical Trial.BioMed research international · 2016Trial
- Development, Reliability and Validity of Engagement in Exercise Rehabilitation Scale for Patients with Stroke.Nursing reports (Pavia, Italy) · 2025Article
- Virtual reality in stroke recovery: a meta-review of systematic reviews.Bioelectronic medicine · 2024Review
- Use of Virtual Reality in Physical Therapy as an Intervention and Diagnostic Tool.Rehabilitation research and practice · 2024Review
- Data-Driven Classification of Human Movements in Virtual Reality-Based Serious Games: Preclinical Rehabilitation Study in Citizen Science.JMIR serious games · 2022Article
- Towards a Platform for Robot-Assisted Minimally-Supervised Therapy of Hand Function: Design and Pilot Usability Evaluation.Frontiers in bioengineering and biotechnology · 2021Article
- The Role of Social Interactions in Motor Performance: Feasibility Study Toward Enhanced Motivation in Telerehabilitation.Journal of medical Internet research · 2019Article
- Producing knowledge by admitting ignorance: Enhancing data quality through an "I don't know" option in citizen science.PloS one · 2019Article
- Using demographics toward efficient data classification in citizen science: a Bayesian approach.PeerJ. Computer science · 2019Article
- In Memoriam: Paolo Cappa.Sensors (Basel, Switzerland) · 2017Article
- Article
- The Present and Future of Robotic Technology in Rehabilitation.Current physical medicine and rehabilitation reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patient motivation is an important factor to consider when developing rehabilitation programs. Here, we explore the effectiveness of active participation in web-based citizen science activities as a means of increasing participant engagement in rehabilitation exercises, through the use of a low-cost haptic joystick interfaced with a laptop computer. Using the joystick, patients navigate a virtual environment representing the site of a citizen science project situated in a polluted canal. Participants are tasked with following a path on a laptop screen representing the canal. The experiment consists of two conditions: in one condition, a citizen science component where participants classify images from the canal is included; and in the other, the citizen science component is absent. Both conditions are tested on a group of young patients undergoing rehabilitation treatments and a group of healthy subjects. A survey administered at the end of both tasks reveals that participants prefer performing the scientific task, and are more likely to choose to repeat it, even at the cost of increasing the time of their rehabilitation exercise. Furthermore, performance indices based on data collected from the joystick indicate significant differences in the trajectories created by patients and healthy subjects, suggesting that the low-cost device can be used in a rehabilitation setting for gauging patient recovery.
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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.