Efficacy of web-based tailored health communication for behavioural modification in sun safety: A comparative study of tailored and response independent information delivery
Bibliographic record
Abstract
Exposure to ultraviolet (UV) radiation is the single most important risk factor for skin cancers. The incidence and severity of skin cancers are on the rise in most parts of the world including Canada. Melanoma is the most aggressive form of skin cancer with a poor prognosis. It is possible to calculate the approximate time required to develop sunburn based on the skin type of an individual and the UV index of the region of residence. A tool was constructed for this purpose using various web technologies such as PHP and JavaScript. The tool was named SUNBUC as an acronym for Sun Burn Calculator. There were two phases of the study: 1. Usability testing and 2. A controlled trial, which was designed to test the impact of the tool on the sun protection behaviour of the respondents over a period of 3 months. The null hypothesis was that tailored information and response independent information has a similar impact on sun safety behaviour as measured by the frequency of usage of sun protection methods such as sunscreen. Ethics board approval was obtained for the study. The usability of the online survey and SUNBUC was tested on five respondents using the think-aloud method and evaluated using the System Usability Scale. The evaluation showed average usability and system modifications were made according to the findings of the think-aloud study. The controlled trial design consisted of the control group with 48 respondents and intervention group with 53 respondents. Post intervention survey responses were obtained from 46(96\%) and 48(91\%) respondents belonging to the control and intervention groups respectively. Having implemented SUNBUC, findings showed no significant difference between the respondents who used the tool and the control group in short-term sun protection behaviour. However, many respondents felt that SUNBUC gave them a sense of control over their behaviour, a proximal determinant of the behaviour itself as per the Theory of Planned Behaviour.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".