Exploring traumatic brain injury survivors’ experiences of completing a remote online cognitive assessment (The Amsterdam Cognition Scan)
Bibliographic record
Abstract
Introduction: In light of the COVID-19 pandemic, digital healthcare has become a rapidly increasing area of research interest. Digital cognitive assessments, which can be completed remotely, without supervision, are being developed and used in both research and clinical contexts with multiple populations. However, very little is known about the way in which these digital assessments are perceived and experienced by survivors of traumatic brain injury (TBI), despite this being a population who commonly undergo cognitive assessment. This study aimed to address this gap by exploring how TBI survivors experience a digital cognitive assessment. Method: Participants who self-reported sustaining a TBI at some point during their life were asked to complete an online digital cognitive test battery (ACS). An adjusted think-aloud protocol was used to encourage participants to share their ‘in the moment’ thought and reactions during the cognitive assessment, they then engaged in a brief retrospective semi-structured interview about their experiences. Data were analysed using reflexive thematic analysis. Results: Analysis identified three core themes which focused on 1. Previous experiences which impact how the cognitive assessment is experienced; 2. In the moment experiences: emotions, thoughts and reactions during the cognitive assessment and interview; 3. The use of remote cognitive testing for TBI in the future. Within the core themes, nine subthemes were identified and a detailed narrative description of each theme is provided. Discussion: Key findings are discussed within the context of the surrounding literature, including the perceived benefits and limitations of utilising digital cognitive assessments, and specifically remote digital assessments with TBI survivors; the in the moment emotional experiences of participants, such as anger, sadness and grief, and factors which were perceived to impact these; and the importance of balancing probable distress with the potential benefits of cognitive assessment. Subsequent recommendations for practice and research are also discussed.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".