Toward a better understanding of prognostic awareness and its associations with psychosomatic variables in cancer patients
Bibliographic record
Abstract
Cancer patients face an uncertain future and challenging decisions regarding oncological treatments. Prognostic Awareness (PA) assumes particular relevance in promoting informed treatment decision- making in line with individual preferences and values. However, studies in the literature showed a significant percentage of patients unaware of the prognosis and discordant results regarding associations of PA with psychological and quality of life outcomes. Accordingly, further investigating PA and its impact on cancer patients could provide useful clinical indications to support patients in dealing with prognosis. The present study aimed to investigate the associations between PA, struggle with illness, peaceful acceptance, shame, social support, and psychosomatic symptoms (anxiety, depression, perceived pain). Sixty-seven terminally ill cancer patients (F = 30; Mage = 76.16) were recruited from a hospice unit and administered self-report questionnaires including Prognosis and Treatment Perceptions Questionnaire (PTPQ), Peace, Equanimity, and Acceptance in the Cancer Experience (PEACE), Multidimensional Scale of Perceived Social Support (MSPSS), Other As Shamer (OAS), Patient Health Questionnaire (PHQ-4), and Short Form-McGill Pain Questionnaire (SF-MPQ). Data were analyzed using Spearman's rho correlations and a network analysis approach to visually explore the interrelationships among the variables examined. The results showed that only 40.3% of patients were aware of the prognosis and that PA was positively correlated with struggle with illness. Network analysis revealed that PA was positively associated with struggle with illness and shame. Moreover, struggle with illness was positively associated with anxiety and depressive symptoms and perceived pain, and shame with anxiety and depressive symptoms. Differently, peaceful acceptance was negatively associated with perceived pain, and social support was negatively associated with shame and struggle with illness and positively with peaceful acceptance. Struggle with illness and PA were the variables with the highest centrality indices, highlighting their influence within the network structure. The study provides relevant information regarding PA and its complex associations with several psychosomatic variables, suggesting potential clinical implications for healthcare providers in the oncological context.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".