Co-design and evaluation of a digital serious game to promote public awareness about pancreatic cancer
Bibliographic record
Abstract
BACKGROUND: Pancreatic cancer, ranking seventh in global cancer-related deaths, poses a significant public health challenge with increasing incidence and mortality. Most cases are diagnosed at an advanced stage, resulting in low survival rates. Early diagnosis significantly impacts prognosis, making symptom awareness crucial. Symptoms are often subtle, leading to delayed help-seeking behaviour. Patients and their carers prioritise increased public awareness, indicating a need for innovative approaches to promote awareness of the disease. METHODS: This study employed a quasi-experimental pre-test/post-test design to assess the relationship between a serious game and pancreatic cancer awareness. Members of the public (N = 727) were recruited internationally, via social media and with signposting by relevant organisations. Participants completed measures of symptom awareness and help-seeking intentions before and after playing the game. The serious game, co-designed with experts by lived experience, patient advocates and healthcare professionals, presented participants with a human anatomy diagram, with each section linked to a question about pancreatic cancer. RESULTS: The serious game demonstrated a statistically significant improvement on pancreatic cancer awareness based on matched paired t-tests. Due to missing data, paired comparisons were only possible for 489 cases. Symptom awareness scores exhibited a statistically significant increase from pre-test to post-test, with a large effect size (p < 0.001, d = 1.43). Help-seeking intentions also markedly improved, showing a significant increase from pre-test to post-test, with a large effect size (p < 0.001, d = 1.10). Independent-samples t-tests were also conducted to determine if there were any group differences on pre- to post-test changes based on age, gender, and previous knowledge and/or experience of pancreatic cancer. Participants overwhelmingly endorsed the game's usability and educational value, suggesting its potential as an effective tool for enhancing public awareness and proactive health-seeking behaviour. DISCUSSION: This study is the first to explore a serious game's utility in pancreatic cancer awareness. Results suggest that such interventions can effectively increase public awareness and influence help-seeking intentions. The co-design process ensured content relevance, and participant satisfaction was high. Findings highlight the game's potential as an accessible and convenient tool for diverse populations.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".