45 Cognitive rehabilitation in neuro-oncology: Program development and evaluation
Bibliographic record
Abstract
Background: Brain tumors present unique challenges to patient and family quality of life (QOL). Cognitive dysfunction is common and functionally limiting, with no established treatments. These studies evaluate feasibility and preliminary efficacy of behavioral interventions developed for neuro-oncology patients. Study 1: A randomized controlled trial (N=25 primary brain tumor patients) compared an adapted version of Goal Management Training (GMT, a neuroscience-based integration of mindfulness and strategy training) and a newly-designed supportive psychoeducational intervention (Brain Health Program, BHP) to standard of care. Each intervention comprised 8 individual sessions and at-home practice between sessions. GMT patients’ executive functions improved immediately (p=.077, d=1.13), with maintenance at 4-month follow-up (p=.046, d=1.09). Both intervention groups reported improvements in everyday cognitive functioning immediately (p=.049; d’s GMT=0.43, BHP=0.79) and at follow-up (p=.001; d’s GMT=0.22, BHP=1.01). BHP patients also reported improved mood (p’s=.026 & .012, d’s=0.61 & 0.62). Study 2: Following a needs assessment about cognitive concerns and QOL in brain metastases patients (N=109) and caregivers (N=31), we developed a novel, brief (3 sessions + homework) Cognitive Support Program to provide education and strategy-training in key areas of concern: executive functions, memory, and communication. Options include caregiver co-training, and in-person or web-based delivery. Preliminary data from a pilot trial in progress demonstrate objective and subjective improvements. Conclusions: Cognitive rehabilitation may be a feasible and effective option for primary or metastatic brain tumor patients, addressing a need that is largely unmet in standard cancer care. Further development and larger trials appear warranted, with capacity for remote delivery recommended.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".