Patient or treatment centre? Where are efforts invested to improve cancer patients' psychosocial outcomes?
Bibliographic record
Abstract
The psychosocial outcomes of cancer patients may be influenced by individual-level, social and treatment centre predictors. This paper aimed to examine the extent to which individual, social and treatment centre variables have been examined as predictors or targets of intervention for psychosocial outcomes of cancer patients. Medline was searched to find studies in which the psychological outcomes of cancer patient were primary variables. Papers published in English between 1999 and 2009 that reported primary data relevant to psychosocial outcomes for cancer patients were included, with 20% randomly selected for further coding. Descriptive studies were coded for inclusion of individual, social or treatment centre variables. Intervention studies were coded to determine if the unit of intervention was the individual patient, social unit or treatment centre. After random sampling, 412 publications meeting the inclusion criteria were identified, 169 were descriptive and 243 interventions. Of the descriptive papers 95.0% included individual predictors, and 5.0% social predictors. None of the descriptive papers examined treatment centre variables as predictors of psychosocial outcomes. Similarly, none of the interventions evaluated the effectiveness of treatment centre interventions for improving psychosocial outcomes. Potential reasons for the overwhelming dominance of individual predictors and individual-focused interventions in psychosocial literature are discussed.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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) | 0.001 | 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 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".