Skin cancer on Instagram: implications for adolescents and young adults
Bibliographic record
Abstract
Given the popularity and reach of Instagram among American adolescents and young adults (AYA), the well-known influence of social media on the behaviors of youth, and the rising rates of melanoma in this age group, this study sought to examine and describe the content of a sample of Instagram posts related to skin cancer. At three different times, a search of Instagram was conducted using #skincancer as the hashtag. Descriptive analyses of Instagram characteristics and content was performed. Overall, content focused on prevention (33.3%), skin cancer treatment (29.3%) and preventive measures such as using sunscreen and protective gear (29.3%). Nearly one-quarter discussed the ABCDEs (Asymmetrical; Borders are irregular; Color is not even; Diameter is large; Evolving) of screening and detection. Instagram postings that covered skin cancer prevention (n = 50, 33.3%) more often discussed the role of sun exposure in the development of skin cancer (28.0% vs. 10.0%, p = 0.005) and use of sunscreen and protective gear (62.0% vs. 13.0%, p < 0.001). The findings of this study indicate that a considerable portion of the Instagram posts included in this study focused on prevention. Thus, indicating that Instagram could be used to promote health, particularly among AYA.
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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 | 0.001 |
| 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 | 0.000 |
| 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".