Crowdsourcing as an Innovative Communication Strategy in Early Melanoma Detection

Background: Skin self-examination (SSE) is the primary method for identifying atypical moles. Unfortunately, past research has shown that SSE has low sensitivity. The current study investigates whether collective effort can improve SSE. Collective effort problem solving, or crowdsourcing, uses the intelligence of a group to make decisions; for example, contestants on game shows use collective effort when they “ask the audience” for help. Contestants can try to answer the question on their own (individual effort) or rely on the opinion of the audience (collective effort). Collective effort can be effective even when a single person has low reliability at a task, as the pattern of the group overcomes the limitations of each individual. Methods: Adults (N = 500) were recruited from a mall in the Midwest. Participants viewed educational pamphlets about SSE and then completed a mole identification task. For the task, participants were asked to circle moles that appeared atypical. Forty mole images were provided; nine of which were clinically diagnosed melanomas. Results: Consistent with past research, individual effort exhibited modest sensitivity (.58) for identifying atypical moles in the mole identification task. As predicted, collective effort overcame the limitations of individual effort. Specifically, a 19% collective effort threshold exhibited superior sensitivity (.90). Conclusion: Modern communication technology facilitates collective effort problem solving. The results of the current study suggest that limitations of SSE can be countered by collective effort, a finding that supports the pursuit of collective effort interventions in early melanoma