A Telehealth-Based Behavioral Intervention for Cancer-Related Cognitive Decline in Older Adults Undergoing Systemic Therapy for Breast Cancer: Development and Usability Testing
Bibliographic record
Abstract
Background: Cancer-related cognitive decline (CRCD) is a significant problem; interventions are needed to mitigate CRCD for older adults (aged ≥65 years). Objective: Our objective was to develop and evaluate the usability of Memory and Attention Adaptation Training-Geriatrics (MAAT-G), a CRCD intervention for older adults with breast cancer undergoing systemic treatment. Methods: We conducted an intervention adaptation study to develop MAAT-G. MAAT-G is a cognitive behavioral therapy-based intervention delivered by a health professional over the course of 10 weekly individual workshops via videoconferencing. To develop MAAT-G, the contextual, cohort-based, maturity, and specific challenge framework was used for preliminary adaptations. Patient advocate collaborators guided further refinement, reviewing MAAT-G workshop content, the participant workbook, and intervention delivery via videoconferencing to optimize relevance and usability for older adults. The usability of MAAT-G and its videoconferencing delivery were subsequently evaluated in 4 older adults with breast cancer using the System Usability Scale (score range 0-100; >67 being above average) and through semistructured qualitative interviews. Results: Numerous adaptations were made to address the unique needs of older patients using the contextual, cohort-based, maturity, and specific challenge framework and patient advocate feedback. Usability testing included 4 female patients with breast cancer (mean age 73.3, SD 3.77; range 67-77 years). Patients were receiving systemic therapy (2 receiving adjuvant therapy and 2 receiving advanced-stage disease therapy). One patient had an educational level lower than high school; 3 had some college education or higher. All 4 patients completed study procedures, including 10 MAAT-G workshop sessions (100% intervention adherence). The mean System Usability Scale score was 90.6 (SD 13.51), indicating good usability. Conclusions: MAAT-G is a behavioral intervention developed to mitigate CRCD. It is designed specifically for older adults and showed above-average usability in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".