What Young Women with Breast Cancer Get Versus What They Want in Online Information and Social Media Supports
Bibliographic record
Abstract
Purpose: Young women are high users of social media (SM), but information is lacking on whether online supports including SM meet the needs of young women (<40 years) with breast cancer (YWBC). YWBC are a vulnerable population who experience many psychosocial challenges alongside cancer diagnosis and treatment. This study aimed to gather data on what YWBC get versus what they want in online support. Methods: Semi-structured interviews explored YWBC's perceptions and use of online information/SM, including visions for ideal support. YWBC between the ages of 18–40 were recruited via two urban oncology clinics. Recruitment continued until redundancy of responses was achieved. Results: Thirteen YWBC participated in the study. Some reported benefits of online supports included connection with similar others, emotional support and ease of use. These benefits were balanced by drawbacks, such as a lack of appropriate/credible information and/or distressing information. Respondents spontaneously mentioned coping strategies such as managing information exposure and regulating SM use to mitigate against harms of online supports. Collectively, participants described nine facets of an ideal online support hub, which could function as a one stop shop for informational, practical and emotional supports for YWBC. Conclusion: Developing a multifunction online support hub may help women to find credible and useful information, rapidly, and address current limitations of online supports.
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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 | 0.001 | 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 | 0.003 |
| 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".