Extending Melanoma Awareness Assessment to at‐Risk Populations

We read with great interest the recent study by Hennessey et al. assessing melanoma awareness and knowledge in the Australian adult population through a novel mixed-method survey employing prompted and unprompted recall [1]. This approach captures active versus prompted recall of melanoma signs and symptoms as well as risk factors, illustrating the complexity of the current knowledge and perceptions not found in traditional close-ended questions. Although the study successfully pilots this new methodology, we encourage further investigation using this methodology for the underrepresented, at-risk populations for melanoma in Australia. This study candidly acknowledges the cohort was skewed towards women (79%) and those with higher education (57%), however, this may present a critical barrier to the instrument's utility in real-world public health settings [1]. Dermatological literature is clear that women and patients with prior skin cancer diagnoses have a higher baseline of disease awareness and knowledge [2, 3]. Our concern is that this high literacy cohort may mask the difficulties that underrepresented and at-risk populations could face with this specific survey format. Populations with the highest mortality risk—specifically men and individuals of colour—are often those with lower health literacy and are associated with a higher mortality risk. In contrast to women, men are less likely to perform skin self-examinations, more likely to delay care, and have poorer melanoma outcomes [2-4]. Moreover, there is an established disparity in knowledge and awareness of melanoma across skin types. The Fitzpatrick scale classifies skin based on its response to ultraviolet radiation, ranging from Type I (pale/white skin that always burns) to Type VI (deeply pigmented dark brown to black skin that never burns). Individuals of Fitzpatrick Skin Type I/II have demonstrated greater health understanding, with one study showing 86% of Fitzpatrick Skin Type I/II participants being able to identify melanoma compared to 57.6% of Fitzpatrick Skin Type V/VI. Notably, Fitzpatrick Skin Type IV–VI populations lacked secondary prevention due to misperception that darker skin provides full protection against melanoma alongside a lower likelihood of receiving education on skin cancer signs [5]. This difference is crucial as those in Fitzpatrick skin type I–II have a higher incidence of melanoma, whereas Fitzpatrick skin type III–VI have higher mortality risk in comparison [5, 6]. In this study, a total of five participants (1.3%) identified as Fitzpatrick V or VI compared to the 4%–10% estimated by the Australian Bureau of Statistics [7]. Given their higher mortality risk and difference of health literacy, this provides a great opportunity for further research utilising this novel survey to more accurately characterise melanoma awareness and knowledge of Australians with darker skin tones. Another opportunity to expand these findings is utilising this survey in different regions of Australia. In this study, 61% (n = 238) of participants resided in Queensland, a proportion nearly triple the state's actual Australian population share (Table 1). As a global epicentre of melanoma incidence, Queensland has been the focus of many Australian sun-safety campaigns [10]. This introduces a geographically confounding variable that could skew the ‘national awareness’ baseline. Utilising this survey in other states of Australia could provide meaningful insight of the unprompted melanoma knowledge of the country as a whole. Fitzpatrick Skin Type V–VI Building upon the opportunity to employ Hennessey et al.'s novel methodology for underrepresented and at-risk populations, investigations should refine the survey to ensure validity across these diverse populations. The variance between unprompted and prompted list, differing in items and sub-items, should be carefully considered as it could introduce an increased cognitive load. Although manageable for a high-literacy cohort, this may introduce a disparity when assessing lower-literacy and under-engaged groups. Removing sub-items from the prompted list may lead to a more equitable study design. Moreover, inspecting the prompted list, the list lacks distractors. Introducing common misconceptions regarding melanoma risk factors and symptoms could distinguish true knowledge from acquiescence bias, particularly in underrepresented groups. Lastly, to fully leverage this instrument for public health outreach, utilising multivariate analysis rather than univariate analysis can strengthen results. Currently factors such as ‘age > 50’ or ‘history of melanoma’ are intrinsically linked to each other as melanoma prevalence naturally increases with age. Without multivariable analysis, it remains difficult to determine if the disease history is an independent driver of awareness or a proxy for age and socioeconomic status. This will be critical when surveying those from underrepresented and at-risk backgrounds as health literacy of melanoma can be multifactorial and linked to their social determinants of health [3, 5]. We thank the authors for their work as it has provided a valuable tool for capturing the complexity of melanoma knowledge. The next critical step is to validate the instrument through targeted, multivariate investigations of the populations underrepresented and with higher mortality risk. Focusing efforts on men, diverse ethnic groups, and other Australian states will allow us to accurately capture the knowledge of the Australian public and address specific awareness gaps that may present in specific populations. The authors have nothing to report. This letter received no outside funding. The authors declare no conflicts of interest. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.