Distress experienced by lung cancer patients and their family caregivers in the first year of their cancer journey
Bibliographic record
Abstract
OBJECTIVES: Diagnosis of cancer is emotionally threatening not only for patients but also for their family caregivers (FC) who witness and share much of the illness experience. This study compares distress experienced by lung cancer patients and their FC during the year following the diagnosis. METHODS: A prospective cohort study of 206 patients recently diagnosed with inoperable lung cancer (participation rate 79.5%) and 131 FC (participation rate 63.6%) was conducted in an ambulatory oncology clinic in Quebec City (Canada). They completed validated questionnaires regarding their personal and psychological characteristics (Hospital and Anxiety Depression Scale-HADS), in the first months after the diagnosis of lung cancer and after 6 and 12 months. Univariate, bivariate, and linear mixed models were conducted to compare patient and FC distress. RESULTS: At baseline, 7.8% of patients reported distress (HADS total score >15) and their mean distress score was 7.0 ± 4.9 (range 0-42). In contrast, 33.6% of FC presented significant distress and their mean distress score was 12.0 ± 7.2 (P < 0.0001). Proportions of patients and FC with distress remained relatively stable at 6 and 12 months, and at every time point, FC reported higher levels of distress compared to their relative with cancer (P < 0.0001). Comparable trends were found when looking at the mean scores of distress, anxiety, and depression throughout the study. SIGNIFICANCE OF RESULTS: Being diagnosed with lung cancer and going through its different phases seems to affect more FC than patients. The psychological impact of such diagnosis appears early after the diagnosis and does not significantly change over time. These findings reinforce the importance for oncology teams, to include FC in their systematic distress screening program, in order to help them cope with their own feelings and be able to play their role in patient support and care throughout the cancer 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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".