Effects of Immersive Virtual Therapy as a Method Supporting the Psychological and Physical Well-Being of Women with a Breast Cancer Diagnosis: A Randomized Controlled Trial
Bibliographic record
Abstract
This study aimed to evaluate the effectiveness of virtual reality (VR) in the mental state and quality of sleep improvement and physical activity (PA) increase of patients diagnosed with breast cancer (BC). A total of 33 subjects divided into experimental (EG, n = 17) and control (CG, n = 16) groups were assessed with the Mental Adjustment to Cancer Scale (Mini-MAC), International Physical Activity Questionnaire (IPAQ), Pittsburgh Sleep Quality Index (PSQI), and the Modified Hospital Anxiety and Depression Scale (HADS-M) at four time points. The experimental intervention consisted of eight VR TierOne sessions. Significant differences favoring the EG were identified in the group x time interactions for the main outcomes: destructive style of coping with the disease (p < 0.001), walking (p = 0.04), moderate (p < 0.001) and overall activity (p = 0.004), quality of sleep (p < 0.001), depressive symptoms (p < 0.001), anxiety levels (p < 0.001), aggression levels (p = 0.002), and overall HADS (p < 0.001). Trends, favoring the EG, in the constructive style of coping, sedentary behavior and intensive PA, and sleep efficiency and sleeping time were also found. A VR intervention improves general well-being in terms of the measured parameters.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".