Digital Gaming for Improving the Functioning of People With Traumatic Brain Injury: Protocol of a Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) is a critical public health problem. The recovery process for people with TBI is typically slow and dependent on complex and intensive assisted rehabilitation programs. OBJECTIVE: To evaluate the effects and feasibility of digital games for cognitive functioning and general well-being among people with traumatic brain injury. METHODS: This is a single-site feasibility study conducted in Finland, which uses a pragmatic, randomized controlled trial with three arms, and will recruit patients from the Turku University Hospital, Division of Clinical Neurosciences in Finland. Participants must meet the following inclusion criteria: (1) a Finnish speaking adult, aged 18-65 years; (2) diagnosed with a traumatic brain injury (diagnostic criteria ICD-10, S06.X, T90.5) in the University Hospital; (3) access to a TV, a computer, and the Internet at home; (4) not an active digital gamer (5 hours or less a week); (5) willing to participate in the study. Participants must have been discharged from the neurologic treatment period for traumatic brain injury for over 12 months before the commencement of the trial, and they may not have actively participated in cognitive rehabilitation during the 3 months prior to the trial. Written informed consent will be mandatory for acceptance into the trial. Exclusion criteria are as follows: (1) sensory, cognitive, or physical impairment (eg, severe cognitive impairment); (2) a deficiency restricting the use of computers or computer game control system unaided (eg, impairment in vision, severe astigmatism, hemiplegia, disorder in visuospatial perception, dysfunction of the central vestibular system); (3) apathy identified in previous neuropsychological evaluations; (4) diagnosed severe mental disorders (eg, schizophrenia or severe depressive disorders to be identified in medical records as the secondary diagnosis). RESULTS: The preparatory phase for the study is fulfilled. Recruitment started in June 2015 and finished November 2015. Results will be reported in 2016. CONCLUSIONS: The specific outcomes such as primary outcome measures were selected because they are widely used psychological tests and thought to be sensitive to changes in the cognitive functions related to TBI. TRIAL REGISTRATION: Clinicaltrials.gov NCT02425527; https://clinicaltrials.gov/ct2/show/NCT02425527 (Archived by WebCite at http://www.webcitation.org/6esKI1uDH).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".