Impact of a Short Audiovisual Intervention on Skin Cancer Diagnostic Accuracy in Medical Professionals: A Continuing Medical Education Approach

Impact of a Short Audiovisual Intervention on Skin Cancer Diagnostic Accuracy in Medical Professionals: A Continuing Medical Education Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of a Short Audiovisual Intervention on Skin Cancer Diagnostic Accuracy in Medical Professionals: A Continuing Medical Education Approach Jorge Vasquez, Carlos Ruiz-Gonzalez, Josue Ruiz-Gonzalez, Juan Ospina-Gomez, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8283008/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: The incidence of skin cancer continues to rise, and early detection of suspicious lesions is essential to reducing morbidity, mortality, and psychological and aesthetic impact on patients. Healthcare professionals' ability to identify and classify skin lesions is critical in this process, and continuous medical education- particularly through audiovisual tools- has the potential to improve public health outcomes related to skin cancer. Methods: This study used a pre-post-controlled design to assess changes in diagnostic accuracy following a brief audiovisual educational intervention. A digital atlas containing real images of skin cancer-related and non-cancerous lesions was created for the intervention. Results: The study included 84 participants (54.76% female, median age 26). Most were general physicians (36.9%), followed by medical students (32.15%) and residents (22.62%). Before the intervention, 46.43% rated their ability to identify skin lesions as intermediate, and 23.81% rated it as poor. The baseline correct classification rate for malignant lesions was 83.33%, and correct diagnostic selection for skin cancer was 51.85%. After the intervention, these rates increased to 88.89% and 66.67%, respectively. The improvement was most notable in students, interns, and general physicians (increase >20%), and among those with lower pre-intervention self-perceived diagnostic ability. Conclusion: Brief audiovisual educational interventions- particularly those suitable for dissemination through social media- can significantly improve the diagnostic accuracy of medical students and healthcare professionals in identifying skin cancer lesions. Level of evidence: Not gradable. Early Detection of Cancer Diagnosis Differential Skin Neoplasms Education Medical Continuing Educational Technology Audiovisual Aids Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Skin neoplasms are among the most common conditions encountered in clinical practice, and skin cancer represents the most frequently diagnosed cancer in many countries. Globally, its incidence continues to rise, largely driven by increased exposure to risk factors—most notably ultraviolet radiation, which induces DNA damage and promotes oncogenesis. Preventive strategies, including consistent sunscreen use, remain central to risk reduction [ 1 ]. Once cutaneous lesions are identified, evaluation by a trained healthcare professional is essential to determine the need for biopsy and histopathological assessment [ 2 ]. Prognosis varies widely depending on cancer type and stage. Most nonmelanoma skin cancers, such as basal cell carcinoma and squamous cell carcinoma, generally have favorable outcomes with appropriate treatment. In contrast, malignancies such as Merkel cell carcinoma and melanoma often carry a poor prognosis, with survival rates that may fall below 20%. Accurate assessment of both benign and malignant lesions is therefore critical, given the substantial consequences of delayed or missed diagnoses—not only in terms of mortality, but also recurrence, local invasion, tissue destruction, and associated symptoms including pain, pruritus, bleeding, infection, scarring, and functional impairment. Additionally, the psychological burden of skin cancer, including anxiety and depression, is well documented [ 3 – 6 ]. Early recognition and management of suspicious skin lesions are paramount. Primary care clinicians across medical specialties play a key role in this process, with visual examination of lesion morphology, pigmentation, and other surface characteristics serving as the cornerstone of screening and diagnostic decision-making. Continuing medical education (CME), particularly when grounded in interactive visualization of real clinical cases, is essential for improving diagnostic competence and addressing the growing public health impact of skin neoplasms [ 7 ]. With widespread access to the internet, smartphones, and social media, on-demand virtual CME has emerged as an effective educational modality for healthcare providers. In this context, we conducted a brief educational intervention study to assess the diagnostic accuracy of medical professionals and to evaluate the impact of a short audiovisual module on skin cancer detection. Methods This study employed an educational intervention design (artificial manipulation of exposure) with non-probabilistic convenience sampling. The sample included all general physicians, specialty residents, specialists, and fourth- to sixth-year medical students from the Universidad Industrial de Santander and the Hospital Universitario de Santander in Bucaramanga, Colombia. Participants with cognitive impairments and/or physical limitations that prevented completion of the study instruments were excluded. Additionally, individuals without access to audiovisual equipment suitable for proper visualization of digital images—potentially affecting performance on the evaluation and intervention tools—were also excluded. The study adhered to the principles of the Declaration of Helsinki, local regulatory standards, and universal guidelines for good clinical research practice. The research protocol was reviewed and approved by the Research Ethics Committees of the Universidad Industrial de Santander and the Hospital Universitario de Santander (2024). All patients with skin cancer–related lesions whose cases were included in the digital database provided written informed consent after receiving a clear and comprehensive explanation of the study objectives and scope. The medical-surgical interventions performed were fully indicated by the institution’s healthcare providers, and the handling of images and informed consent forms was carried out in accordance with institutional guidelines [ 8 ]. The digital database was constructed using real patient cases from the study sites, with individuals voluntarily agreeing to participate. All personally identifiable information was removed, and no changes were made to the diagnostic or treatment plans of any patient because of participation. Diagnoses of the cases included in the database were confirmed through histopathology, and at least two medical specialists in skin cancer–related lesions validated the quality of the images and the suitability of the response options. Healthcare professionals participating in the educational intervention provided digital informed consent after a thorough explanation of the study objectives and procedures. Sociodemographic data—including age, sex, and level of training—were obtained. Participants’ self-perceived competence and time of academic training to diagnose skin cancer–related lesions were assessed using closed multiple-choice questions. Following these items, participants were shown 15 images of skin cancer–related lesions, which they classified as “probably benign” or “probably malignant,” and subsequently selected the most likely diagnosis from four predefined options. The third section consisted of an educational module in which participants viewed a short instructional video on the evaluation of skin cancer–related lesions. The final section replicated the second, requiring participants to classify the same cases again based on the information provided in the video. Statistical analyses were performed using Stata 14 (Stata Corporation, College Station, USA) and Prism 10.2.2 (GraphPad Software). Variables were evaluated according to their level of measurement (mean or median for continuous variables; proportions for categorical variables). The distribution of quantitative variables was assessed using the Shapiro–Wilk test. A P value < 0.05 was considered statistically significant. Results Digital real cases database The database of real patient cases with skin lesions was prospectively constructed, including all patients who voluntarily agreed to participate in the project. Once diagnoses were confirmed through histopathology, the cases were reviewed by two specialists in the diagnosis and management of skin cancer–related lesions in order to select the most relevant cases. Finally, 4 cases of basal cell carcinoma, 2 of melanoma, 3 of squamous cell carcinoma, 1 of pyogenic granuloma, 2 of nevi, 2 of actinic keratosis, and 1 of keratoacanthoma were included ( Fig. 1 ). Sociodemographic characteristics 84 participants were included and completed the study ( Fig. 2 ) . 54.76% (n = 46) were female. The median of age was 26; Interquartile ratio (IQR), 24–29 ( Fig. 3 ) . Most of the participants were general practitioner physicians (36.9%), followed by medical students (32.15%) and residents (22.62%) ( Table 1 ) . Perception of academic training time and diagnostic capacity Before the educational intervention, participants reported their self-perceived duration of academic training and diagnostic ability for identifying skin cancer lesions. Most participants rated their academic training as “intermediate” (39.29%), followed by “low” (34.52%). Similarly, 46.43% described their diagnostic ability as intermediate, while only 7.14% rated it as “very good” ( Table 1 ) . Table 1 Sociodemographic characteristics and self-perceived diagnostic ability Variable Total (n = 84) Sex, n (%) Male 38 (45.24%) Female 46 (54.76%) Level of education, n (%) Student 15 (17.86%) Intern 12 (14.29%) General physician 31 (36.9%) Resident 19 (22.62%) Specialist 7 (8.33%) Academic training time, n (%) Very high 4 (4.76%) High 14 (16.67%) Intermediate 33 (39.29%) Low 29 (34.52%) Very low 4 (4.76%) Diagnostic capacity, n (%) Very good 6 (7.14%) Good 19 (22.62%) Intermediate 39 (46.43%) Poor 19 (22.62%) Very poor 1 (1.19%) Most participants who reported a “low” or “very low” duration of academic training rated their diagnostic ability as “poor” or “very poor.” In contrast, those who reported a “high” or “very high” level of training primarily evaluated their diagnostic ability as “good” or “very good” ( Fig. 4 ) . Initial performance in the classification and identification of lesions Participants correctly classified 60% (IQR 53.3%–66.7%) of cases as “probably benign” or “probably malignant.” However, when identifying lesions according to the most probable diagnosis, this percentage decreased to 42.8% (SD ± 14.1%). Interns performed below the median in classifying lesions as benign or malignant. Students, interns, and general practitioners, also obtained a below-average proportion of correct lesion diagnoses ( Fig. 5 ) . Performance in the classification and identification of lesions after the intervention After the educational intervention, the proportion of correct answers increased by 7% ( Fig. 6 ) . However, the impact was higher in the cases of malignant lesions with an increase of 8% in the benign-malign classification and 14% on the identification of the diagnoses ( Fig. 7 ) compared to benign cases with 5% and 2%, respectively. The impact of the intervention was significantly higher among medical students and interns, with a 20% and 26% increase, respectively, when identifying malignant lesions ( Table 2 ) . A weak negative correlation between age and the impact of educational intervention is presented (Spearman correlation, R = -0.3029, CI 95%: -0.4907 to -0.08829; P = 0.0025) ( Fig. 8 ) . Table 2 Impact of the educational intervention on the change in the proportion of correct answers for the classification of malignant lesions and identification of diagnosis by variables. Data is presented as mean and SD % change when classifying (benign-malign) % change when identifying diagnosis Age 30 6.11 (± 27.8) 12.22 (± 26.71) Level of education Student 7.41 (± 22.87) 20 (± 22.3) Intern 20.37 (± 23.13) 25.93 (± 22.89) General physician 7.53 (± 12.63) 12.19 (± 22.1) Resident 2.92 (± 28.17) 9.94 (± 23.39) Specialist 3.17 (± 5.42) 0 (± 6.42) Academic training time Very high -2.78 (± 13.98) 0 (± 18.14) High 1.59 (± 13.68) 6.35 (± 14.27) Intermediate 10.44 (± 21.68) 15.15 (± 23.7) Low 11.11 (± 22.81) 18.39 (± 25.07) Very low -2.77 (± 10.64) 13.89 (± 5.56) Diagnostic capacity Very good -1.85 (± 10.92) 1.85 (± 14.77) Good 4.68 (± 11.3) 7.6 (± 17.39) Intermediate 11.4 (± 22.44) 16.24 (± 24.96) Poor 7.02 (± 25.45) 19.88 (± 22.09) Very poor 11.11 11.11 The impact of the educational intervention was greater among participants who reported “intermediate”, "low" or "very low" academic training time, as well as among those who considered their diagnostic capacity to identify malignant lesions as "intermediate", "poor" or "very poor" ( Fig. 9 ) . Discussion This study evaluated the diagnostic ability of medical students and physicians to identify skin lesions associated with skin cancer and assessed the impact of a brief audiovisual educational intervention. The results demonstrated an overall 7% improvement in the proportion of correct responses, with a particularly notable increase in the identification of malignant lesions (+ 14%), while the improvement for benign lesions was more modest (+ 2–5%). These findings are consistent with recent literature showing the positive impact of short educational interventions on dermatologic knowledge and diagnostic performance. Analysis by level of training revealed that interns (+ 25.9%) and medical students (+ 20%) achieved the greatest improvement in identifying malignant lesions, followed by general practitioners (+ 12.1%). In contrast, the effect was smaller among residents (+ 9.9%) and nearly absent among specialists (0%), consistent with the principle that knowledge gain tends to be inversely proportional to prior experience. These results align with recent educational research, where short self-guided modules significantly improved both recognition of dermatologic morphologies and self-confidence in performing skin examinations [ 9 ]. This supports the idea that well-structured, concise, and accessible educational interventions can lead to meaningful and sustainable changes in diagnostic competence. Similarly, another study demonstrated that combining a theoretical module with active participation in skin cancer screening clinics increased students’ knowledge scores from approximately 52% to 83% after three months [ 10 ]. Together, these findings suggest that theoretical exposure complemented by practical experience enhances learning retention and consolidates diagnostic skills in dermatology. The negative correlation found between age and improvement in performance (R = − 0.30; p = 0.0025) reinforces these findings: younger participants (< 30 years) achieved greater improvement in identifying malignant lesions (+ 14.6%) compared to those aged ≥ 30 years (+ 12.2%). This pattern suggests that virtual learning interventions should be tailored to the generational profiles of learners, incorporating interactive resources and immediate visual feedback to optimize retention. The intervention’s effect was also modulated by participants’ self-perceived diagnostic ability and level of prior training. The largest gains were observed among those who reported low or intermediate educational exposure (+ 15–18%), and among those who rated their diagnostic ability as poor or fair (+ 16–20%). Conversely, participants who self-assessed their training or diagnostic capacity as “very high” showed minimal or even negative changes. This finding supports the hypothesis that significant learning gains occur in individuals with lower baseline knowledge, where greater potential for improvement exists. Furthermore, the larger improvement in the identification of malignant compared to benign lesions may be explained by the fact that the clinical features of cutaneous malignancies—such as asymmetry, irregular borders, color variation, or ulceration—are more easily recognized after targeted audiovisual exposure. This has strong clinical relevance, as diagnostic errors in benign lesions have limited prognostic consequences, whereas failure to identify malignant lesions carries substantial risk. Therefore, an educational gain focused on malignancy detection represents a favorable and clinically meaningful outcome. From the perspective of remote care, teledermatology has proven to be an effective platform for the evaluation of skin lesions. A recent retrospective study involving more than 1,300 consultations reported substantial diagnostic agreement between teledermatology and in-person assessments (Kappa ≈ 0.636), reinforcing the reliability of remote evaluations for skin conditions [ 11 ]. Similarly, another study comparing different methods of image acquisition (patient self-captured, assisted, or clinician-acquired) found that image quality—and consequently diagnostic concordance—improves significantly with proper education and training [ 12 ]. These studies support the concept that educational interventions for both healthcare providers and patients can enhance the effectiveness of teledermatology, complementing diagnostic strategies in settings with limited specialist access. Moreover, in terms of practical implementation, emerging technologies such as mobile teledermoscopy have shown promising results: a recent prospective study demonstrated that patients who submitted dermoscopic smartphone images achieved diagnostic accuracy comparable to in-person evaluations [ 13 ]. This study has several limitations. First, the sample was non-probabilistic and drawn from a single university hospital, which limits the generalizability of the findings. Second, assessment was conducted immediately after the intervention, and thus medium- or long-term knowledge retention was not evaluated. Third, the assessment tool relied exclusively on clinical images, without incorporating dermoscopy, a key technique for enhancing diagnostic accuracy. Finally, the absence of a control group prevents ruling out partial effects related to learning by repetition. Nevertheless, the magnitude of the observed improvement and the consistency of trends across subgroups support the validity of the educational effect. Conclusion The video-based educational intervention proved effective in improving the diagnostic ability of medical students and healthcare professionals in identifying cutaneous lesions, with an overall increase of 7% and a notable 14% improvement in malignant lesion recognition. These findings reinforce the hypothesis that brief, accessible, and structured interventions can strengthen clinical recognition of skin cancer, with potential implications for early detection and prevention. Given that medical students and primary care physicians often receive limited dermatologic training, such targeted educational programs could be integrated into medical curricula to enhance diagnostic competence without imposing a significant time or resource burden. To maximize impact, future studies should incorporate practical components, such as basic dermoscopy training or the use of mobile applications with curated image repositories and assess not only short-term improvements but also long-term retention. At the institutional level, implementing these interventions could complement teledermatology strategies, helping to optimize patient triage and facilitate early referral of suspicious lesions. Declarations Competing interests The authors have no relevant financial or non-financial interests to disclose. Ethics approval The study adhered to the principles of the Declaration of Helsinki, local regulatory standards, and universal guidelines for good clinical research practice. The research protocol was reviewed and approved by the Research Ethics Committees of the XXXXX Consent to participate Informed consent was obtained from all individual participants included in the study Consent to publish The authors affirm that human research participants provided informed consent for publication of the images in Fig. 1. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution All authors contributed to the study conception and design. Material preparation and data collection were performed by Jorge Vasquez, Carlos Ruiz-Gonzalez and Josue Ruiz-Gonzalez; analysis was performed by Carlos Ruiz-Gonzalez. The first draft of the manuscript was written by Jorge Vasquez, Carlos Ruiz-Gonzalez, Josue Ruiz-Gonzalez and Juan Ospina-Gomez and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References Gallagher RP (2005) Sunscreens in melanoma and skin cancer prevention. CMAJ 173:244–245. US Department of Health and Human Services (2014) The Surgeon General’s Call to Action to Prevent Skin Cancer. Office of the Surgeon General (US), Washington (DC). Available from: https://www.ncbi.nlm.nih.gov/books/NBK247164/ Linares MA, Zakaria A, Nizran P (2015) Skin cancer. Prim Care 42:645–659. Balch CM, Soong SJ, Gershenwald JE, Thompson JF, Reintgen DS, Cascinelli N et al (2001) Prognostic factors analysis of 17,600 melanoma patients: validation of the American Joint Committee on Cancer melanoma staging system. J Clin Oncol 19:3622–3634. Chang NB, Feng R, Gao Z, Gao W (2010) Skin cancer incidence is highly associated with ultraviolet-B radiation history. Int J Hyg Environ Health 213:359–368. Fagundo E, Rodríguez-García C, Rodríguez C, González S, Sánchez R, Jiménez A (2011) Analysis of phenotypic characteristics and exposure to UV radiation in a group of patients with cutaneous melanoma. Actas Dermosifiliogr 102:599–604. Wang AT, Sandhu NP, Wittich CM, Mandrekar JN, Beckman TJ (2012) Using social media to improve continuing medical education: a survey of course participants. Mayo Clin Proc 87:1162–1170. https://doi.org/10.1016/j.mayocp.2012.07.024 Sánchez-Álvarez C, Donovan C, Ramírez-Rivero CE, Ruiz-González CE, Navas AG, Villarreal DC (2023) Aesthetic and functional satisfaction after closed reduction of nasal fractures: implementation of the NOSE scale. Cir Plast Iberolatinoam 49:217–224. https://doi.org/10.4321/s0376-78922023000300003 Ricco C, Rao BK, Pappert AS, Coppola KM (2024) Brief teaching intervention improves medical students’ dermatology diagnostic skills and comfort in performing dermatology exams. Healthcare (Basel) 12:1453. https://doi.org/10.3390/healthcare12141453 Desai DD, Pillai R, Agarwal A, Mocharnuk J, James AJ (2025) Improvement of medical student dermatologic knowledge with combined educational module and participation in a skin screening clinic. Arch Dermatol Res 317:391. https://doi.org/10.1007/s00403-025-03865-0 Patel N, Aboukhatwah N, Esdaile B (2024) Effectiveness and diagnostic accuracy of teledermatology for the assessment of skin conditions. Australas J Dermatol 65:342–349. https://doi.org/10.1111/ajd.14239 Saade S, Khoury DM, Abou Shahla W, Stephan C, Charbel N, Joukhdar R, El Bejjani M, Bekdache M, Mansour S, Saade D (2025) Teledermatology diagnostic accuracy: a randomized cohort study comparing three image acquisition techniques. Int J Telemed Appl 2025:5789165. https://doi.org/10.1155/ijta/5789165 Fan W, Mattson G, Twigg A (2024) Direct-to-patient mobile teledermoscopy: prospective observational study. JMIR Dermatol 7:e52400. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Jan, 2026 Reviews received at journal 19 Jan, 2026 Reviewers agreed at journal 13 Jan, 2026 Reviewers invited by journal 13 Jan, 2026 Editor assigned by journal 08 Dec, 2025 Submission checks completed at journal 08 Dec, 2025 First submitted to journal 04 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8283008","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":574097518,"identity":"20180162-c52a-4ddc-aebd-192421f99f14","order_by":0,"name":"Jorge Vasquez","email":"","orcid":"","institution":"Industrial University of Santander","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Vasquez","suffix":""},{"id":574097520,"identity":"4a88a45b-6a99-455c-8b5a-8f4598caf317","order_by":1,"name":"Carlos 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09:06:04","extension":"xml","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":60299,"visible":true,"origin":"","legend":"","description":"","filename":"5d8e7a73a84b49daae6b63adfdfb8b901structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/53b0a78e9c8b54a6476431d3.xml"},{"id":100595579,"identity":"22afd0b4-ca47-455b-9a3f-d201d4c363f9","added_by":"auto","created_at":"2026-01-19 13:48:50","extension":"html","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":68833,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/e86cb420f57e62c32b663c16.html"},{"id":100595815,"identity":"0db53c29-34a8-4acf-9c3d-da3762177bb0","added_by":"auto","created_at":"2026-01-19 13:49:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":651786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSkin cancer related lesions. \u003c/strong\u003eRepresentative images of cases included in the study, including basal cell carcinoma (a), actinic keratosis (b), melanoma (c), nevi (d), squamous cell carcinoma (e) and pigmented nevi (f)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/285f17fee0f2914f92dba356.png"},{"id":100595459,"identity":"c77e99f4-c4a0-4c46-8719-67c2ff668fb5","added_by":"auto","created_at":"2026-01-19 13:48:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32105,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConsort diagram of the study\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/e17c06632989f83480d67f25.png"},{"id":100565691,"identity":"21cce168-bfbe-4485-8a39-08b1334726f0","added_by":"auto","created_at":"2026-01-19 09:06:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":43506,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSociodemographic characteristics of the participants. \u003c/strong\u003eSex (a) and age (b) of the participants included (n = 84)\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/5a7b6eba82974f22781832a0.png"},{"id":100565693,"identity":"85996880-1431-4c3a-8bec-b3dfb9323e01","added_by":"auto","created_at":"2026-01-19 09:06:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35419,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelation between time of academic training and diagnostic ability\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/2ac495f94437b2be3b832f4b.png"},{"id":100594651,"identity":"bb330190-d514-43a5-b108-a356c4207d10","added_by":"auto","created_at":"2026-01-19 13:43:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":54215,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInitial performance in the classification and identification of lesions by academic formation.\u003c/strong\u003e Proportion of correct answers. n = 84 participants\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/d93dbde7ffc7a6f1e8a7123a.png"},{"id":100565697,"identity":"48923d9c-4702-4542-8a9d-85813e3f9a0c","added_by":"auto","created_at":"2026-01-19 09:06:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":48194,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of the educational intervention on the proportion of correct answers at classification of lesions and identification of diagnosis\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/daac998bfbf1b7299d4a5d18.png"},{"id":100595507,"identity":"d3889289-8d17-470b-b28b-81beb1eff25c","added_by":"auto","created_at":"2026-01-19 13:48:38","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":41033,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of the educational intervention on the proportion of correct answers at classification of malignant lesions and identification of the diagnosis\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/cb6e633e938bb5f01acc125a.png"},{"id":100595026,"identity":"84d6fe92-419e-43cd-b3ed-9c6caf72fe65","added_by":"auto","created_at":"2026-01-19 13:47:06","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":30560,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation between the percentage change in the proportion of total correct answers after the intervention and participant age. \u003c/strong\u003eStatistical analysis was performed using Spearman’s r correlation\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/7935b00ea8eca7b338d13dc8.png"},{"id":100565699,"identity":"12a79f24-369d-4333-99d5-16066bb4b581","added_by":"auto","created_at":"2026-01-19 09:06:04","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":30687,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of the educational intervention in classifying and identifying malignant lesions by time of academic formation (a) and diagnostic capacity (b). \u003c/strong\u003eData is presented as the mean and SD of the percentage change in the proportion of correct answers\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/b6395cbc930207206d01b2c0.png"},{"id":100597432,"identity":"87653658-09d0-4deb-80ec-4c9e6c9eb9fc","added_by":"auto","created_at":"2026-01-19 14:17:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2414469,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8283008/v1/0e78830a-7671-4852-b3ab-a2d15132cc00.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of a Short Audiovisual Intervention on Skin Cancer Diagnostic Accuracy in Medical Professionals: A Continuing Medical Education Approach","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSkin neoplasms are among the most common conditions encountered in clinical practice, and skin cancer represents the most frequently diagnosed cancer in many countries. Globally, its incidence continues to rise, largely driven by increased exposure to risk factors\u0026mdash;most notably ultraviolet radiation, which induces DNA damage and promotes oncogenesis. Preventive strategies, including consistent sunscreen use, remain central to risk reduction [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Once cutaneous lesions are identified, evaluation by a trained healthcare professional is essential to determine the need for biopsy and histopathological assessment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrognosis varies widely depending on cancer type and stage. Most nonmelanoma skin cancers, such as basal cell carcinoma and squamous cell carcinoma, generally have favorable outcomes with appropriate treatment. In contrast, malignancies such as Merkel cell carcinoma and melanoma often carry a poor prognosis, with survival rates that may fall below 20%. Accurate assessment of both benign and malignant lesions is therefore critical, given the substantial consequences of delayed or missed diagnoses\u0026mdash;not only in terms of mortality, but also recurrence, local invasion, tissue destruction, and associated symptoms including pain, pruritus, bleeding, infection, scarring, and functional impairment. Additionally, the psychological burden of skin cancer, including anxiety and depression, is well documented [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarly recognition and management of suspicious skin lesions are paramount. Primary care clinicians across medical specialties play a key role in this process, with visual examination of lesion morphology, pigmentation, and other surface characteristics serving as the cornerstone of screening and diagnostic decision-making. Continuing medical education (CME), particularly when grounded in interactive visualization of real clinical cases, is essential for improving diagnostic competence and addressing the growing public health impact of skin neoplasms [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith widespread access to the internet, smartphones, and social media, on-demand virtual CME has emerged as an effective educational modality for healthcare providers. In this context, we conducted a brief educational intervention study to assess the diagnostic accuracy of medical professionals and to evaluate the impact of a short audiovisual module on skin cancer detection.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study employed an educational intervention design (artificial manipulation of exposure) with non-probabilistic convenience sampling. The sample included all general physicians, specialty residents, specialists, and fourth- to sixth-year medical students from the Universidad Industrial de Santander and the Hospital Universitario de Santander in Bucaramanga, Colombia. Participants with cognitive impairments and/or physical limitations that prevented completion of the study instruments were excluded. Additionally, individuals without access to audiovisual equipment suitable for proper visualization of digital images\u0026mdash;potentially affecting performance on the evaluation and intervention tools\u0026mdash;were also excluded.\u003c/p\u003e \u003cp\u003e The study adhered to the principles of the Declaration of Helsinki, local regulatory standards, and universal guidelines for good clinical research practice. The research protocol was reviewed and approved by the Research Ethics Committees of the Universidad Industrial de Santander and the Hospital Universitario de Santander (2024). All patients with skin cancer\u0026ndash;related lesions whose cases were included in the digital database provided written informed consent after receiving a clear and comprehensive explanation of the study objectives and scope. The medical-surgical interventions performed were fully indicated by the institution\u0026rsquo;s healthcare providers, and the handling of images and informed consent forms was carried out in accordance with institutional guidelines [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe digital database was constructed using real patient cases from the study sites, with individuals voluntarily agreeing to participate. All personally identifiable information was removed, and no changes were made to the diagnostic or treatment plans of any patient because of participation. Diagnoses of the cases included in the database were confirmed through histopathology, and at least two medical specialists in skin cancer\u0026ndash;related lesions validated the quality of the images and the suitability of the response options.\u003c/p\u003e \u003cp\u003eHealthcare professionals participating in the educational intervention provided digital informed consent after a thorough explanation of the study objectives and procedures. Sociodemographic data\u0026mdash;including age, sex, and level of training\u0026mdash;were obtained. Participants\u0026rsquo; self-perceived competence and time of academic training to diagnose skin cancer\u0026ndash;related lesions were assessed using closed multiple-choice questions. Following these items, participants were shown 15 images of skin cancer\u0026ndash;related lesions, which they classified as \u0026ldquo;probably benign\u0026rdquo; or \u0026ldquo;probably malignant,\u0026rdquo; and subsequently selected the most likely diagnosis from four predefined options. The third section consisted of an educational module in which participants viewed a short instructional video on the evaluation of skin cancer\u0026ndash;related lesions. The final section replicated the second, requiring participants to classify the same cases again based on the information provided in the video.\u003c/p\u003e \u003cp\u003eStatistical analyses were performed using Stata 14 (Stata Corporation, College Station, USA) and Prism 10.2.2 (GraphPad Software). Variables were evaluated according to their level of measurement (mean or median for continuous variables; proportions for categorical variables). The distribution of quantitative variables was assessed using the Shapiro\u0026ndash;Wilk test. A \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDigital real cases database\u003c/h2\u003e \u003cp\u003eThe database of real patient cases with skin lesions was prospectively constructed, including all patients who voluntarily agreed to participate in the project. Once diagnoses were confirmed through histopathology, the cases were reviewed by two specialists in the diagnosis and management of skin cancer\u0026ndash;related lesions in order to select the most relevant cases. Finally, 4 cases of basal cell carcinoma, 2 of melanoma, 3 of squamous cell carcinoma, 1 of pyogenic granuloma, 2 of nevi, 2 of actinic keratosis, and 1 of keratoacanthoma were included \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSociodemographic characteristics\u003c/h3\u003e\n\u003cp\u003e84 participants were included and completed the study \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. 54.76% (n\u0026thinsp;=\u0026thinsp;46) were female. The median of age was 26; Interquartile ratio (IQR), 24\u0026ndash;29 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Most of the participants were general practitioner physicians (36.9%), followed by medical students (32.15%) and residents (22.62%) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003ePerception of academic training time and diagnostic capacity\u003c/h3\u003e\n\u003cp\u003eBefore the educational intervention, participants reported their self-perceived duration of academic training and diagnostic ability for identifying skin cancer lesions. Most participants rated their academic training as \u0026ldquo;intermediate\u0026rdquo; (39.29%), followed by \u0026ldquo;low\u0026rdquo; (34.52%). Similarly, 46.43% described their diagnostic ability as intermediate, while only 7.14% rated it as \u0026ldquo;very good\u0026rdquo; \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics and self-perceived diagnostic ability\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38 (45.24%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46 (54.76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of education, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (17.86%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (14.29%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral physician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (36.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (22.62%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecialist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcademic training time, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (4.76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (16.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33 (39.29%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (34.52%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (4.76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic capacity, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (7.14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (22.62%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (46.43%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (22.62%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (1.19%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMost participants who reported a \u0026ldquo;low\u0026rdquo; or \u0026ldquo;very low\u0026rdquo; duration of academic training rated their diagnostic ability as \u0026ldquo;poor\u0026rdquo; or \u0026ldquo;very poor.\u0026rdquo; In contrast, those who reported a \u0026ldquo;high\u0026rdquo; or \u0026ldquo;very high\u0026rdquo; level of training primarily evaluated their diagnostic ability as \u0026ldquo;good\u0026rdquo; or \u0026ldquo;very good\u0026rdquo; \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eInitial performance in the classification and identification of lesions\u003c/h3\u003e\n\u003cp\u003eParticipants correctly classified 60% (IQR 53.3%\u0026ndash;66.7%) of cases as \u0026ldquo;probably benign\u0026rdquo; or \u0026ldquo;probably malignant.\u0026rdquo; However, when identifying lesions according to the most probable diagnosis, this percentage decreased to 42.8% (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;14.1%). Interns performed below the median in classifying lesions as benign or malignant. Students, interns, and general practitioners, also obtained a below-average proportion of correct lesion diagnoses \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePerformance in the classification and identification of lesions after the intervention\u003c/h2\u003e \u003cp\u003eAfter the educational intervention, the proportion of correct answers increased by 7% \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. However, the impact was higher in the cases of malignant lesions with an increase of 8% in the benign-malign classification and 14% on the identification of the diagnoses \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e compared to benign cases with 5% and 2%, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe impact of the intervention was significantly higher among medical students and interns, with a 20% and 26% increase, respectively, when identifying malignant lesions \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. A weak negative correlation between age and the impact of educational intervention is presented (Spearman correlation, R = -0.3029, CI 95%: -0.4907 to -0.08829; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0025) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eImpact of the educational intervention on the change in the proportion of correct answers for the classification of malignant lesions and identification of diagnosis by variables.\u003c/b\u003e Data is presented as mean and SD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% change when classifying (benign-malign)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% change when identifying diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.51 (\u0026plusmn;\u0026thinsp;17.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.58 (\u0026plusmn;\u0026thinsp;21.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.11 (\u0026plusmn;\u0026thinsp;27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.22 (\u0026plusmn;\u0026thinsp;26.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.41 (\u0026plusmn;\u0026thinsp;22.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (\u0026plusmn;\u0026thinsp;22.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.37 (\u0026plusmn;\u0026thinsp;23.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.93 (\u0026plusmn;\u0026thinsp;22.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral physician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.53 (\u0026plusmn;\u0026thinsp;12.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.19 (\u0026plusmn;\u0026thinsp;22.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.92 (\u0026plusmn;\u0026thinsp;28.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.94 (\u0026plusmn;\u0026thinsp;23.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecialist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.17 (\u0026plusmn;\u0026thinsp;5.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (\u0026plusmn;\u0026thinsp;6.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcademic training time\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.78 (\u0026plusmn;\u0026thinsp;13.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (\u0026plusmn;\u0026thinsp;18.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.59 (\u0026plusmn;\u0026thinsp;13.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.35 (\u0026plusmn;\u0026thinsp;14.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.44 (\u0026plusmn;\u0026thinsp;21.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.15 (\u0026plusmn;\u0026thinsp;23.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.11 (\u0026plusmn;\u0026thinsp;22.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.39 (\u0026plusmn;\u0026thinsp;25.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.77 (\u0026plusmn;\u0026thinsp;10.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.89 (\u0026plusmn;\u0026thinsp;5.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic capacity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.85 (\u0026plusmn;\u0026thinsp;10.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.85 (\u0026plusmn;\u0026thinsp;14.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.68 (\u0026plusmn;\u0026thinsp;11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6 (\u0026plusmn;\u0026thinsp;17.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4 (\u0026plusmn;\u0026thinsp;22.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.24 (\u0026plusmn;\u0026thinsp;24.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.02 (\u0026plusmn;\u0026thinsp;25.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.88 (\u0026plusmn;\u0026thinsp;22.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe impact of the educational intervention was greater among participants who reported \u0026ldquo;intermediate\u0026rdquo;, \"low\" or \"very low\" academic training time, as well as among those who considered their diagnostic capacity to identify malignant lesions as \"intermediate\", \"poor\" or \"very poor\" \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the diagnostic ability of medical students and physicians to identify skin lesions associated with skin cancer and assessed the impact of a brief audiovisual educational intervention. The results demonstrated an overall 7% improvement in the proportion of correct responses, with a particularly notable increase in the identification of malignant lesions (+\u0026thinsp;14%), while the improvement for benign lesions was more modest (+\u0026thinsp;2\u0026ndash;5%). These findings are consistent with recent literature showing the positive impact of short educational interventions on dermatologic knowledge and diagnostic performance.\u003c/p\u003e \u003cp\u003e Analysis by level of training revealed that interns (+\u0026thinsp;25.9%) and medical students (+\u0026thinsp;20%) achieved the greatest improvement in identifying malignant lesions, followed by general practitioners (+\u0026thinsp;12.1%). In contrast, the effect was smaller among residents (+\u0026thinsp;9.9%) and nearly absent among specialists (0%), consistent with the principle that knowledge gain tends to be inversely proportional to prior experience. These results align with recent educational research, where short self-guided modules significantly improved both recognition of dermatologic morphologies and self-confidence in performing skin examinations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This supports the idea that well-structured, concise, and accessible educational interventions can lead to meaningful and sustainable changes in diagnostic competence. Similarly, another study demonstrated that combining a theoretical module with active participation in skin cancer screening clinics increased students\u0026rsquo; knowledge scores from approximately 52% to 83% after three months [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Together, these findings suggest that theoretical exposure complemented by practical experience enhances learning retention and consolidates diagnostic skills in dermatology.\u003c/p\u003e \u003cp\u003eThe negative correlation found between age and improvement in performance (R\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.30; p\u0026thinsp;=\u0026thinsp;0.0025) reinforces these findings: younger participants (\u0026lt;\u0026thinsp;30 years) achieved greater improvement in identifying malignant lesions (+\u0026thinsp;14.6%) compared to those aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years (+\u0026thinsp;12.2%). This pattern suggests that virtual learning interventions should be tailored to the generational profiles of learners, incorporating interactive resources and immediate visual feedback to optimize retention. The intervention\u0026rsquo;s effect was also modulated by participants\u0026rsquo; self-perceived diagnostic ability and level of prior training. The largest gains were observed among those who reported low or intermediate educational exposure (+\u0026thinsp;15\u0026ndash;18%), and among those who rated their diagnostic ability as poor or fair (+\u0026thinsp;16\u0026ndash;20%). Conversely, participants who self-assessed their training or diagnostic capacity as \u0026ldquo;very high\u0026rdquo; showed minimal or even negative changes. This finding supports the hypothesis that significant learning gains occur in individuals with lower baseline knowledge, where greater potential for improvement exists.\u003c/p\u003e \u003cp\u003eFurthermore, the larger improvement in the identification of malignant compared to benign lesions may be explained by the fact that the clinical features of cutaneous malignancies\u0026mdash;such as asymmetry, irregular borders, color variation, or ulceration\u0026mdash;are more easily recognized after targeted audiovisual exposure. This has strong clinical relevance, as diagnostic errors in benign lesions have limited prognostic consequences, whereas failure to identify malignant lesions carries substantial risk. Therefore, an educational gain focused on malignancy detection represents a favorable and clinically meaningful outcome.\u003c/p\u003e \u003cp\u003eFrom the perspective of remote care, teledermatology has proven to be an effective platform for the evaluation of skin lesions. A recent retrospective study involving more than 1,300 consultations reported substantial diagnostic agreement between teledermatology and in-person assessments (Kappa\u0026thinsp;\u0026asymp;\u0026thinsp;0.636), reinforcing the reliability of remote evaluations for skin conditions [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similarly, another study comparing different methods of image acquisition (patient self-captured, assisted, or clinician-acquired) found that image quality\u0026mdash;and consequently diagnostic concordance\u0026mdash;improves significantly with proper education and training [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These studies support the concept that educational interventions for both healthcare providers and patients can enhance the effectiveness of teledermatology, complementing diagnostic strategies in settings with limited specialist access. Moreover, in terms of practical implementation, emerging technologies such as mobile teledermoscopy have shown promising results: a recent prospective study demonstrated that patients who submitted dermoscopic smartphone images achieved diagnostic accuracy comparable to in-person evaluations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the sample was non-probabilistic and drawn from a single university hospital, which limits the generalizability of the findings. Second, assessment was conducted immediately after the intervention, and thus medium- or long-term knowledge retention was not evaluated. Third, the assessment tool relied exclusively on clinical images, without incorporating dermoscopy, a key technique for enhancing diagnostic accuracy. Finally, the absence of a control group prevents ruling out partial effects related to learning by repetition. Nevertheless, the magnitude of the observed improvement and the consistency of trends across subgroups support the validity of the educational effect.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe video-based educational intervention proved effective in improving the diagnostic ability of medical students and healthcare professionals in identifying cutaneous lesions, with an overall increase of 7% and a notable 14% improvement in malignant lesion recognition. These findings reinforce the hypothesis that brief, accessible, and structured interventions can strengthen clinical recognition of skin cancer, with potential implications for early detection and prevention.\u003c/p\u003e \u003cp\u003eGiven that medical students and primary care physicians often receive limited dermatologic training, such targeted educational programs could be integrated into medical curricula to enhance diagnostic competence without imposing a significant time or resource burden. To maximize impact, future studies should incorporate practical components, such as basic dermoscopy training or the use of mobile applications with curated image repositories and assess not only short-term improvements but also long-term retention. At the institutional level, implementing these interventions could complement teledermatology strategies, helping to optimize patient triage and facilitate early referral of suspicious lesions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study adhered to the principles of the Declaration of Helsinki, local regulatory standards, and universal guidelines for good clinical research practice. The research protocol was reviewed and approved by the Research Ethics Committees of the XXXXX\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for publication of the images in Fig.\u0026nbsp;1.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation and data collection were performed by Jorge Vasquez, Carlos Ruiz-Gonzalez and Josue Ruiz-Gonzalez; analysis was performed by Carlos Ruiz-Gonzalez. The first draft of the manuscript was written by Jorge Vasquez, Carlos Ruiz-Gonzalez, Josue Ruiz-Gonzalez and Juan Ospina-Gomez and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGallagher RP (2005) Sunscreens in melanoma and skin cancer prevention. CMAJ 173:244\u0026ndash;245.\u003c/li\u003e\n\u003cli\u003eUS Department of Health and Human Services (2014) The Surgeon General\u0026rsquo;s Call to Action to Prevent Skin Cancer. Office of the Surgeon General (US), Washington (DC). Available from: https://www.ncbi.nlm.nih.gov/books/NBK247164/\u003c/li\u003e\n\u003cli\u003eLinares MA, Zakaria A, Nizran P (2015) Skin cancer. Prim Care 42:645\u0026ndash;659.\u003c/li\u003e\n\u003cli\u003eBalch CM, Soong SJ, Gershenwald JE, Thompson JF, Reintgen DS, Cascinelli N et al (2001) Prognostic factors analysis of 17,600 melanoma patients: validation of the American Joint Committee on Cancer melanoma staging system. J Clin Oncol 19:3622\u0026ndash;3634.\u003c/li\u003e\n\u003cli\u003eChang NB, Feng R, Gao Z, Gao W (2010) Skin cancer incidence is highly associated with ultraviolet-B radiation history. Int J Hyg Environ Health 213:359\u0026ndash;368.\u003c/li\u003e\n\u003cli\u003eFagundo E, Rodr\u0026iacute;guez-Garc\u0026iacute;a C, Rodr\u0026iacute;guez C, Gonz\u0026aacute;lez S, S\u0026aacute;nchez R, Jim\u0026eacute;nez A (2011) Analysis of phenotypic characteristics and exposure to UV radiation in a group of patients with cutaneous melanoma. Actas Dermosifiliogr 102:599\u0026ndash;604.\u003c/li\u003e\n\u003cli\u003eWang AT, Sandhu NP, Wittich CM, Mandrekar JN, Beckman TJ (2012) Using social media to improve continuing medical education: a survey of course participants. Mayo Clin Proc 87:1162\u0026ndash;1170. https://doi.org/10.1016/j.mayocp.2012.07.024\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-\u0026Aacute;lvarez C, Donovan C, Ram\u0026iacute;rez-Rivero CE, Ruiz-Gonz\u0026aacute;lez CE, Navas AG, Villarreal DC (2023) Aesthetic and functional satisfaction after closed reduction of nasal fractures: implementation of the NOSE scale. Cir Plast Iberolatinoam 49:217\u0026ndash;224. https://doi.org/10.4321/s0376-78922023000300003\u003c/li\u003e\n\u003cli\u003eRicco C, Rao BK, Pappert AS, Coppola KM (2024) Brief teaching intervention improves medical students\u0026rsquo; dermatology diagnostic skills and comfort in performing dermatology exams. Healthcare (Basel) 12:1453. https://doi.org/10.3390/healthcare12141453\u003c/li\u003e\n\u003cli\u003eDesai DD, Pillai R, Agarwal A, Mocharnuk J, James AJ (2025) Improvement of medical student dermatologic knowledge with combined educational module and participation in a skin screening clinic. Arch Dermatol Res 317:391. https://doi.org/10.1007/s00403-025-03865-0\u003c/li\u003e\n\u003cli\u003ePatel N, Aboukhatwah N, Esdaile B (2024) Effectiveness and diagnostic accuracy of teledermatology for the assessment of skin conditions. Australas J Dermatol 65:342\u0026ndash;349. https://doi.org/10.1111/ajd.14239\u003c/li\u003e\n\u003cli\u003eSaade S, Khoury DM, Abou Shahla W, Stephan C, Charbel N, Joukhdar R, El Bejjani M, Bekdache M, Mansour S, Saade D (2025) Teledermatology diagnostic accuracy: a randomized cohort study comparing three image acquisition techniques. Int J Telemed Appl 2025:5789165. https://doi.org/10.1155/ijta/5789165\u003c/li\u003e\n\u003cli\u003eFan W, Mattson G, Twigg A (2024) Direct-to-patient mobile teledermoscopy: prospective observational study. JMIR Dermatol 7:e52400.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-plastic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejps","sideBox":"Learn more about [European Journal of Plastic Surgery](https://link.springer.com/journal/238)","snPcode":"238","submissionUrl":"https://submission.nature.com/new-submission/238/3","title":"European Journal of Plastic Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Early Detection of Cancer, Diagnosis, Differential, Skin Neoplasms, Education, Medical, Continuing, Educational Technology, Audiovisual Aids","lastPublishedDoi":"10.21203/rs.3.rs-8283008/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8283008/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe incidence of skin cancer continues to rise, and early detection of suspicious lesions is essential to reducing morbidity, mortality, and psychological and aesthetic impact on patients. Healthcare professionals' ability to identify and classify skin lesions is critical in this process, and continuous medical education- particularly through audiovisual tools- has the potential to improve public health outcomes related to skin cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis study used a pre-post-controlled design to assess changes in diagnostic accuracy following a brief audiovisual educational intervention. A digital atlas containing real images of skin cancer-related and non-cancerous lesions was created for the intervention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe study included 84 participants (54.76% female, median age 26). Most were general physicians (36.9%), followed by medical students (32.15%) and residents (22.62%). Before the intervention, 46.43% rated their ability to identify skin lesions as intermediate, and 23.81% rated it as poor. The baseline correct classification rate for malignant lesions was 83.33%, and correct diagnostic selection for skin cancer was 51.85%. After the intervention, these rates increased to 88.89% and 66.67%, respectively. The improvement was most notable in students, interns, and general physicians (increase \u0026gt;20%), and among those with lower pre-intervention self-perceived diagnostic ability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eBrief audiovisual educational interventions- particularly those suitable for dissemination through social media- can significantly improve the diagnostic accuracy of medical students and healthcare professionals in identifying skin cancer lesions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLevel of evidence:\u003c/strong\u003eNot gradable.\u003c/p\u003e","manuscriptTitle":"Impact of a Short Audiovisual Intervention on Skin Cancer Diagnostic Accuracy in Medical Professionals: A Continuing Medical Education Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 09:05:53","doi":"10.21203/rs.3.rs-8283008/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-19T16:59:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T10:00:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279221872992329483704949955139012998175","date":"2026-01-13T17:54:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-13T16:21:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-09T00:58:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-09T00:57:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Plastic Surgery","date":"2025-12-05T00:14:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-plastic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejps","sideBox":"Learn more about [European Journal of Plastic Surgery](https://link.springer.com/journal/238)","snPcode":"238","submissionUrl":"https://submission.nature.com/new-submission/238/3","title":"European Journal of Plastic Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4c2d058d-d6ad-44fb-a7e5-9253e454dcb8","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-11T14:24:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 09:05:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8283008","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8283008","identity":"rs-8283008","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}