Acceptability and feasibility of cognitive assessments with adults with primary brain cancer and brain metastasis: A systematic review
Bibliographic record
Abstract
Routine cognitive assessment for adults with brain cancers is seldom completed but vital for guiding daily living, maintaining quality of life, or supporting patients and families. This study aims to identify cognitive assessments which are pragmatic and acceptable for use in clinical settings. MEDLINE, EMBASE, PsycINFO, CINAHL, and Cochrane were searched to identify studies published in English between 1990 and 2021. Publications were independently screened by two coders and included if they: (1) were peer-reviewed; (2) reported original data relating to adult primary brain tumor or brain metastases; (3) used objective or subjective assessments; (4) reported assessment acceptability or feasibility. The Psychometric And Pragmatic Evidence Rating Scale was used. Consent, assessment commencement and completion, and study completion were extracted along with author-reported acceptability and feasibility data. PROSPERO Registration: CRD42021234794. Across 27 studies, 21 cognitive assessments had been assessed for feasibility and acceptability; 15 were objective assessments. Acceptability data were limited and heterogeneous, particularly consent (not reported in 23 studies), assessment commencement (not reported in 19 studies), and assessment completion (not reported in 21 studies). Reasons for non-completion could be grouped into patient-factors, assessment-factors, clinician-factors, and system-factors. The three cognitive assessments with the most acceptability and feasibility data reported were the MMSE, MoCA, and NIHTB-CB. Further acceptability and feasibility data are needed including consent, commencement and completion rates. Cost, length, time, and assessor burden are needed for the MMSE, MoCA, and NIHTB-CB, along with potentially new computerized assessments suited for busy clinical settings.
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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 | 0.051 | 0.211 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".