Psychological assessment and the role of the psychologist in early palliative care
Bibliographic record
Abstract
Background: Early palliative care (EPC) is a recommended model for improving the quality of life for patients with advanced cancer and their caregivers. However, limited research has focused on the role of psychological evaluation within EPC. The Veneto Institute of Oncology (IOV), a Comprehensive Cancer Centre, employs an interdisciplinary team to assess patients with advanced-stage disease. This study aims to assess the psychological needs of these patients, investigate any correlations between psychological symptoms (PSs) and factors such as awareness of diagnosis and prognosis, symptoms detected using the Edmonton Symptom Assessment System (ESAS), as well as the patient's gender, age, social issues, and survival and to clarify the psychologist's role within the interdisciplinary team. Methods: Data were retrieved from a prospectively maintained database. From 1st January 2018 to 31st December 2021, 819 consecutive patients were evaluated during EPC consultations, with 753 participants enrolled in the study. The ESAS was administered to each patient before the consultation. Results: More than half of the patients (385, 57.1%) reported at least one PS, with an ESAS score of ≥4. Specifically, 34.9% reported depression, 28.7% reported anxiety, and 43.2% indicated feeling "not well." Referring oncologists tended to overestimate the presence of PSs compared to patient self-reports (51.8% versus 41.3%). According to the psychologists' assessment, 29.2% of participants were found to have depression, and 10.8% of participants had anxiety. Additionally, 31 patients (10.8%) with psychological disorders were diagnosed with an adaptation disorder related to a physical condition. The psychology service engaged 47% of patients, while 18.5% declined psychological support. Patients exhibiting other ESAS symptoms with scores of ≥4 had an increased odds ratio for reporting PSs of ≥4. However, multivariable analysis revealed no significant relationship between PSs and awareness of diagnosis and prognosis. Conclusion: The systematic use of self-assessment in EPC is essential for understanding patient's experience, determining whether PSs stem from physical disorders, and prioritizing interventions. Awareness of prognosis does not correlate with increased anxiety and depression in patients. Therefore, EPC is an ideal opportunity to discuss prognosis and facilitate patients' end-of-life choices early in their care journey.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".