Understanding the role of cancer informational support in relation to health care service use among newly diagnosed individuals
Bibliographic record
Abstract
A qualitative study was undertaken to explore the role of informational support in relation to health care service use among individuals with cancer. In-depth interviews were conducted with participants (N = 20) newly diagnosed with either breast or prostate cancer receiving radiotherapy from an oncology clinic in Montreal, Quebec. Content analysis revealed that participants' perceptions about their experience with cancer informational support in relation to health care services varied along the following dimensions: (1) Cancer informational support was tangible, which enabled, confirmed, normalized, and directed their decisions about reliance on health services; (2) Cancer informational support was somewhat paralyzing, which led to distress, conflict, reduced confidence in the health care system and, at times, misuse of health care services; and (3) Cancer informational support was limiting, with perceptions of having received both helpful and unhelpful cancer information which, in turn, although tolerated, offered little guidance in terms of reliance on the most appropriate services. Knowledge about how and when informational support may be most timely may optimize individuals' well being and further guide their use of cancer-related services.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".