“Thanks for Letting Us All Share Your Mammogram Experience Virtually”: Developing a Web-Based Hub for Breast Cancer Screening
Bibliographic record
Abstract
BACKGROUND: The decision around whether to attend breast cancer screening can often involve making sense of confusing and contradictory information on its risks and benefits. The Word of Mouth Mammogram e-Network (WoMMeN) project was established to create a Web-based resource to support decision making regarding breast cancer screening. This paper presents data from our user-centered approach in engaging stakeholders (both health professionals and service users) in the design of this Web-based resource. Our novel approach involved creating a user design group within Facebook to allow them access to ongoing discussion between researchers, radiographers, and existing and potential service users. OBJECTIVE: This study had two objectives. The first was to examine the utility of an online user design group for generating insight for the creation of Web-based health resources. We sought to explore the advantages and limitations of this approach. The second objective was to analyze what women want from a Web-based resource for breast cancer screening. METHODS: We recruited a user design group on Facebook and conducted a survey within the group, asking questions about design considerations for a Web-based breast cancer screening hub. Although the membership of the Facebook group varied over time, there were 71 members in the Facebook group at the end point of analysis. We next conducted a framework analysis on 70 threads from Facebook and a thematic analysis on the 23 survey responses. We focused additionally on how the themes were discussed by the different stakeholders within the context of the design group. RESULTS: Two major themes were found across both the Facebook discussion and the survey data: (1) the power of information and (2) the hub as a place for communication and support. Information was considered as empowering but also recognized as threatening. Communication and the sharing of experiences were deemed important, but there was also recognition of potential miscommunication within online discussion. Health professionals and service users expressed the same broad concerns, but there were subtle differences in their opinions. Importantly, the themes were triangulated between the Facebook discussions and the survey data, supporting the validity of an online user design group. CONCLUSIONS: Online user design groups afford a useful method for understanding stakeholder needs. In contrast to focus groups, they afford access to users from diverse geographical locations and traverse time constraints, allowing more follow-ups to responses. The use of Facebook provides a familiar and naturalistic setting for discussion. Although we acknowledge the limitations in the sample, this approach has allowed us to understand the views of stakeholders in the user-centered design of the WoMMeN hub for breast cancer screening.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".