Awareness of cognitive abilities in the execution of activities of daily living after acquired brain injury: an evaluation protocol
Bibliographic record
Abstract
INTRODUCTION: One of the main limitations that can be observed after acquired brain injury (ABI) is the alteration of the awareness of the deficits that can occur in the cognitive skills necessary for performing activities of daily living (ADL). According to the Dynamic Comprehensive Model of Awareness (DCMA), consciousness is composed of offline component, which contains the information stored about characteristics of the tasks and stable beliefs about one's own capabilities and online awareness, which is activated in the context of the performance of a specific task. The main objective of this project was to generate and validate a detailed cognitive assessment protocol within the context of ADL to evaluate the components of DCMA. METHODS AND ANALYSIS: The proposed protocol consists of two ecological tools: The Cog-Awareness ADL Scale to measure offline component and the Awareness ADL-task: Basic and Instrumental ADL performance-based test to measure online awareness. The aim is to identify the presence of cognitive deficits and anosognosia in patients with ABI within the context of everyday life activities. These two measures will be administered to a group of patients with ABI. In addition, these participants will complete another series of classic tests on anosognosia and cognitive functions in order to find the convergent validity of the two tests proposed in this protocol. The external validity of the Cog-Awareness ADL Scale and the relationships between awareness components within the same ADL domain will be also analysed. ETHICS AND DISSEMINATION: This study was approved by the Ethics Committee of Biomedical Research of Andalusia, on 13 January /2017 (Proceeding 1/2017). All participants are required to provide written informed consent. The findings from this will be disseminated via scientific publication. TRIAL REGISTRATION NUMBER: NCT03712839.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".