A Skin Cancer Prevention Facial-Aging Mobile App for Secondary Schools in Brazil: Appearance-Focused Interventional Study
Bibliographic record
Abstract
BACKGROUND: The incidence of melanoma is increasing faster than any other major cancer both in Brazil and worldwide. Southeast Brazil has especially high incidences of melanoma, and early detection is low. Exposure to ultraviolet (UV) radiation is a primary risk factor for developing melanoma. Increasing attractiveness is a major motivation among adolescents for tanning. A medical student-delivered intervention that takes advantage of the broad availability of mobile phones and adolescents' interest in their appearance indicated effectiveness in a recent study from Germany. However, the effect in a high-UV index country with a high melanoma prevalence and the capability of medical students to implement such an intervention remain unknown. OBJECTIVE: In this pilot study, our objective was to investigate the preliminary success and implementability of a photoaging intervention to prevent skin cancer in Brazilian adolescents. METHODS: We implemented a free photoaging mobile phone app (Sunface) in 15 secondary school classes in southeast Brazil. Medical students "mirrored" the pupils' altered 3-dimensional (3D) selfies reacting to touch on tablets via a projector in front of their whole grade accompanied by a brief discussion of means of UV protection. An anonymous questionnaire capturing sociodemographic data and risk factors for melanoma measured the perceptions of the intervention on 5-point Likert scales among 356 pupils of both sexes (13-19 years old; median age 16 years) in grades 8 to 12 of 2 secondary schools in Brazil. RESULTS: We measured more than 90% agreement in both items that measured motivation to reduce UV exposure and only 5.6% disagreement: 322 (90.5%) agreed or strongly agreed that their 3D selfie motivated them to avoid using a tanning bed, and 321 (90.2%) that it motivated them to improve their sun protection; 20 pupils (5.6%) disagreed with both items. The perceived effect on motivation was higher in female pupils in both tanning bed avoidance (n=198, 92.6% agreement in females vs n=123, 87.2% agreement in males) and increased use of sun protection (n=197, 92.1% agreement in females vs n=123, 87.2% agreement in males) and independent of age or skin type. All medical students involved filled in a process evaluation revealing that they all perceived the intervention as effective and unproblematic, and that all pupils tried the app in their presence. CONCLUSIONS: The photoaging intervention was effective in changing behavioral predictors for UV protection in Brazilian adolescents. The predictors measured indicated an even higher prospective effectiveness in southeast Brazil than in Germany (>90% agreement in Brazil vs >60% agreement in Germany to both items that measured motivation to reduce UV exposure) in accordance with the theory of planned behavior. Medical students are capable of complete implementation. A randomized controlled trial measuring prospective effects in Brazil is planned as a result of this study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".