Evaluation of support groups for women with breast cancer: importance of the navigator role.
Bibliographic record
Abstract
BACKGROUND: At least some forms of breast cancer are increasingly being viewed as a chronic illness, where an emphasis is placed on meeting the various ongoing needs of people living with cancer, their families and other members of their social support networks. This commentary outlines some approaches to the evaluation of cancer-related support groups, with a particular emphasis on those designed to provide long-distance support, via the internet, for women with breast cancer. DISCUSSION: The literature on evaluations of community-based cancer support groups indicates that they offer a number of benefits, and that it is more reasonable to expect an impact of such interventions on psychosocial functioning and/or health-related quality of life than on survival. The literature on both face-to-face and online social support groups suggests that they offer many advantages, although evaluation of the latter delivery mechanism presents some ethical issues that need to be addressed. Many popular online support groups are peer-moderated, rather than professionally-moderated. In an evaluation of online support groups, different models of the role of the "navigator" need to be taken into account. Some conceptual models are outlined for the evaluation of the "navigator role" in meeting the informational, decisional and educational needs of women with breast cancer. The Breast-Cancer Mailing List, an example of an unmoderated internet-based peer-support group, is considered within the context of a Shared or Tacit Model of the navigator role. CONCLUSION: Application of the concept of a "navigator role" to support groups in general, and to unmoderated online ones in particular, has received little or no attention in the research literature. The navigator role should be taken into account in research on this increasingly important aspect of cancer communication.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".