Introduction There is still a need for competent breast lump detection palpation skills, especially in developing countries. Our goal is to design, develop, and establish a test to determine whether students can, by touch alone, identify and discriminate between a range of different simulated lesions at different adiposity levels. Methods Common lesions, breast cancers, and cysts were physically simulated and hidden in a test object referred to as the "tactile landscape" (TL). Ribs, intercostal muscle, and nodularity - normal anatomical features - increased their realistic complexity. Varying depths of features simulated varying degrees of adiposity. A testing protocol was created to determine the testee's ability to identify and discriminate different commonly occurring breast masses using palpation. Five experts (four breast surgeons and one general practitioner) and 20 inexperienced medical students were recruited and tested. Results were compared. Results The TL has been based on previously verified breast models and has softness similar to 53% of women's breasts and nodularity similar to 60% as assessed in a breast clinic by breast surgeons. The five experts indicated that the simulated lesions felt like those they might encounter in clinical practice and all of them identified the lesions and nonlesions hidden in the TL 100% correctly, thus indicating the value of the model. In contrast, only one student was able to identify all the lesions. One student identified none of them. The remaining students mean score was 65%. Conclusions All students but one performed poorly in comparison to the experts. This indicates that the test could be useful to test students' ability to identify and discriminate breast masses. If successful, it will add previously missing capability to the mix of assessment instruments already used, thus potentially improving clinical breast examination training and assessment.

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When breast cancer is detected early, and is in the localized stage, the 5-year relative survival rate is 100%. (Australian Institute of Health and Welfare 2019) There is a survival advantage in detecting breast cancer early and treating it quickly (Australian Institute of Health and Welfare, 2019; Cancer Australia, 2004, updated 2009; McDonald, Saslow, and Alciati, 2004; National Breast Cancer Foundation, 2019). Clinical Breast Examination (CBE) is a method which can fast track symptomatic women with a breast lump to scarce medical specialist resources to speed the investigation into their putative cancer and facilitate early treatment if needed. Yet too many medical students and doctors feel they could improve their skills in clinical breast examination. Realistic breast models will help the necessary training (Saslow et al. 2004). But knowing what skills need to be transferred and how to design physical breast models are very different things. What are the important skills in identifying and discriminating breast masses by touch and how do simulation models and a validated testing tool assist skill acquisition? Here’s a good example of the creation and development of a successful design from the following brief: to make physical breast models realistic enough to be integral to training and a subsequent testing package, where medical personnel acquire, maintain and improve the skills required to detect possible breast cancer by palpation. @en

Purpose of the study: Pleural diseases are common in clinical practice. Doctors in training often encounter these patients and are expected to perform diagnostic and therapeutic pleural procedures with confidence and safely. However, pleural procedures can be associated with significant complications, especially when performed by less experienced. Structured training such as use of training manikin and procedural skills workshop may help trainee doctors to achieve competence. However, high costs involved in acquiring simulation technology or attending a workshop may be a hurdle. We hereby describe a training model using a simple manikin developed in our institution and provide an effective way to document skill acquisition and assessment among trainee medical officers. Study design: This was a prospective observational study. The need for training, competence and confidence of trainees in performing pleural procedures was assessed through an online survey. Trainees underwent structured simulation training through a simple manikin developed at our institute. Follow-up survey after the training was then performed to access confidence and competence in performing pleural procedures. Results: Forty-seven trainees responded to an online survey and 91% of those expressed that they would like further training in pleural procedure skills. 81% and 85% of responders, respectively, indicated preferred method of training is either practising on manikin or performing the procedure under supervision. Follow-up survey showed improvement in the confidence and competence. Conclusion: Our pleural procedure training manikin model is a reliable, novel and cost-effective method for acquiring competences in pleural procedures.

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Clinical Breast Examination (CBE) is the examination of a women's breasts by a healthcare professional, such as a breast surgeon, family physician or breast-care nurse who is trained to recognise many different types of abnormalities and warning signs in the breast [1]. CBE is particularly important in rural areas and developing countries who have limited access to technology such as mammography. CBE needs to be taught to health professionals like any other clinical skill used by medical professionals in the workplace. CBE in part involves palpation of the breast, that is, determining by touch which breast lumps are normal and which are suspicious in feeling. The gold standard for assessing tactile skills in CBE is seeing whether students can accurately identify and discriminate between different breast lumps also known as masses (IDBM) on actual patients in a clinical setting. However, this is not practical in a medical education setting. Usually the testing methods 'go through the motions' of feeling the breast as part of CBE. So the students' technique is examined either using unrealistic simulation models or using an intimate examination associate (IEA), an actor/volunteer who permits students to examine their intimate body parts such as breast or genitals for teaching purposes. These volunteers do not have any abnormalities so this teaching does not include the actual detection of suspicious lumps.We undertook a study of clinical skill with 10 medical students to examine different methods of assessing novice student clinical skills after a brief training in CBE. OBJECTIVES: This study aims to evaluate the effectiveness of current training and assessment of novice students in CBE and their capacity to identify and discriminate breast masses (IDBM) on actual patients. METHODS: We assessed each student's IDBM ability in an actual clinical situation, a breast clinic with a mixture of eight IEAs and one real patient with a large, easily palpable, putative breast cancer. We recruited 10 clinically inexperienced medical students, who were trained for 30 minutes by two breast surgeons using an IEA. Students were tested in a simulated clinical setting, a breast clinic where each examined 4 IEAs and one patient. The students were blind to who was the real patient and who was an IEA. Patients were examined by a breast surgeon in private prior to the commencement in the study. The breast surgeon recorded any clinical finding on the patients during the initial examination. The surgeon coached each patient on how to mark the students and showed the patient their results so the patients had a benchmark. After each examination was finished the students had four different assessments: 1) patients marked each student, 2) students were independently proctored - that is, marked by an expert, 3) students recorded their clinical findings and 4) students recorded how confident they were that they had the correct findings. Results from different kinds of student assessments were compared. RESULTS: A chi-square test for independence between true positive or negative masses versus student-assessed positive or negative masses was not significant at alpha = .05. This means that there was no statistical association in the indication of positive or negative presence of masses versus whether such masses were actually present or absent. By comparison, experts (breast surgeons) were able to detect normal and abnormal breast masses by palpation alone 100% of the time and rate their confidence level as 'certain'. Unlike the experts, student self-reported confidence was unrelated to their competence score (CS). Proctoring was inversely related to the students' CS. CONCLUSIONS: The main conclusion is that novice students do not seem to be able to accurately detect breast masses in a clinical setting even after training. On the basis of these results, we believe that a comprehension component in the current CBE testing is needed in addition to the current methods of testing.

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Our objective was to design, develop and validate better clinical breast examination (CBE) models addressing the deficiencies of previous models. Detailed research and a methodological design approach led to the development of a new technique for creating lifelike models for teaching CBE. Six multi-layered breast models representing a range of normal human variation for durity (hardness/softness), nodularity (fibro-glandular tissue) and adiposity (fatty tissue) were developed and validated. Various construction materials, MRI scans, traditional casting and three-dimensional (3D) printing were used to build models with lifelike look and feel (biofidelic). The models realistic in anthropometry (size and shape), feel (durity and nodularity) and appearance (skin feel and colouring) – visual biofidelity enhances perception of feel – incorporate anatomically correct layering of ribs, soft adipose tissue, nodularity and additional signs of breast disease, both benign and pathological. These were validated by four breast surgeons who compared their feel alongside a sample of breast patients (N = 78). Models were rated as ‘undecided’, ‘similar’ or ‘very similar’ to 81% of patients for nodularity and 82% for durity. These are the first models to incorporate normal human variability and be validated with real patients. These novel biofidelic models provide a standardized way of teaching health professionals normal from abnormal.@en