Facebook Intervention for Young-Onset Melanoma Patients and Their Family Members: Pilot and Feasibility Study
Bibliographic record
Abstract
Background: Despite their elevated melanoma risk, young-onset melanoma patients and their families exhibit low rates of engagement in skin cancer surveillance and sun protection behaviors. Interventions that improve skin cancer surveillance (total cutaneous exam [TCE] and skin self-exam [SSE]) and prevention (sun protection) practices among young-onset patients and their family members would likely have an impact on skin cancer morbidity and mortality; however, such interventions are lacking. Objective: The objective of our study was to examine the development, feasibility, and preliminary impact of a family-focused Facebook intervention to increase engagement in TCE, SSE, and sun protection among young-onset melanoma patients and their families. Methods: In this study, 48 young-onset melanoma patients and their 40 family members completed measures of knowledge; beliefs; and TCE, SSE, and sun protection intentions before and 1 month after participating in 1 of 5 separate “secret” (ie, private) Facebook groups. The intervention content consisted of daily postings about skin cancer, skin cancer risk factors, TCE, SSE, and sun protection. Results: Patient and family member participation rates differed by recruitment setting, with acceptance rates ranging from 24.6% to 39.0% among families recruited from a cancer center setting and from 12.7% to 61.5% among families recruited from a state registry. Among the 5 consecutive groups conducted, engagement, as measured by comments and likes in response to postings, increased across the groups. In addition, participants positively evaluated the intervention content and approach. Preliminary analyses indicated increases in TCE, SSE, and sun protection intentions. Conclusions: Our family-focused Facebook intervention showed promise as a potentially feasible and efficacious method to increase sun protection and skin cancer surveillance among individuals at increased risk for melanoma.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".