Testing a novel account of the dissociation between self‐reported memory problems and memory performance in chemotherapy‐treated breast cancer survivors
Bibliographic record
Abstract
BACKGROUND: A puzzling observation pertaining to the impact of breast cancer on memory is the frequently reported dissociation between breast cancer survivors' self-reported memory problems and memory performance. We evaluated the hypothesis that the dissociation is related to the fact that the objective memory measures previously used assessed retrospective memory (RM) and did not tap prospective memory (PM), a domain about which survivors are complaining. METHODS: In a case-healthy-control (N = 80) cross-sectional study, the Memory for Intention Screening Test was used to assess PM and the Wechsler Logical Memory Test was used to evaluate RM. Self-reported problems were assessed with the Prospective and Retrospective Memory Questionnaire. Measures of depression (Center for Epidemiologic Studies Depression Scale) and fatigue (Functional Assessment of Cancer Therapy: Fatigue) were also administered. RESULTS: Both groups reported more PM than RM problems (P < .001). Survivors reported more fatigue and depression symptoms and more memory problems than controls (all P < .001). Importantly, the group difference in self-reported problems was no longer observed after adjusting for depression and fatigue. Survivors performed worse than controls on both PM and RM tasks. In neither group, however, were associations between self-reported RM and PM problems and RM and PM objective performance observed. CONCLUSIONS: Breast cancer survivors exhibit PM and RM deficits, which do not correlate with self-reported memory problems. Although unrelated to performance, memory complaints should not be dismissed, as they are closely associated with depression and fatigue and reveal an important facet of the cancer experience.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".