Patients With Cancer and Next-of-Kin Response Comparability on Physical and Psychological Symptom Well-being
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Next of kin (NOK) play an integral role in fostering optimal quality of life in symptomatic patients who are coping with cancer in the home setting. Often when patients in advanced stages of cancer are no longer able to meaningfully communicate their illness and symptom needs, healthcare professionals turn to NOK to provide sound estimates of patients' symptom experiences. This overview is based on 37 research studies written between 1987 and 2002 and updates an earlier overview of 13 studies on patient-NOK response comparability. The purpose is to, first, promote a better comprehension of methodologies and statistical techniques commonly employed to measure patterns of response comparability (or levels of agreement) between patient self-reports and NOK estimates on patient quality-of-life experiences of physical or symptom and emotional or psychological well-being. The second aim is to identify conditions where NOK may pose as reasonably accurate judges of patients' health-related quality of life, particularly symptom experiences arising from various diagnoses, including cancer. Third, subsequent to identifying the gaps in current research knowledge and limitations in study designs, recommendations for statistical and methodological techniques are outlined.
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.
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) | 0.002 | 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 | 0.001 |
| 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 it