scholarly journals Partnering With Massage Therapists to Communicate Information on Reducing the Risk of Skin Cancer Among Clients: Longitudinal Study

10.2196/21309 ◽  
2020 ◽  
Vol 4 (11) ◽  
pp. e21309
Author(s):  
Lois Loescher ◽  
Kelly Heslin ◽  
Graciela Silva ◽  
Myra Muramoto
Keyword(s):  
Skin Cancer ◽  
Risk Reduction ◽  
Behavioral Interventions ◽  
Skin Lesions ◽  
Data Capture ◽  
Self Report ◽  
High Knowledge ◽  
Beliefs And Practice ◽  
Massage Therapists ◽  
Self Examination

Background Skin cancer affects millions of Americans and is an important focus of disease prevention efforts. Partnering with non–health care practitioners such as massage therapists (MTs) can reduce the risk of skin cancer. MTs see clients’ skin on a regular basis, which can allow MTs to initiate “helping conversations” (ie, brief behavioral interventions aimed at reducing the risk of skin cancer). Objective The purpose of this study was to evaluate (1) the feasibility of recruiting, enrolling, and retaining Arizona MTs in an online electronic training (e-training) and (2) the preliminary efficacy of e-training on knowledge, attitudes/beliefs, and practice of risk reduction for skin cancer. We explored MTs’ ability to assess suspicious skin lesions. Methods We adapted the existing educational content on skin cancer for applicability to MTs and strategies from previous research on helping conversations. We assessed the feasibility of providing such e-training, using Research Electronic Data Capture (REDCap) tools for data capture. We assessed the preliminary efficacy using established self-report surveys at baseline, immediately post training, and at 3 and 6 months post training. Results A total of 95 participants enrolled in the study, of which 77% (73/95) completed the assessments at 6 months (overall attrition=23%). Project satisfaction and e-training acceptability were high. Knowledge, personal behaviors (skin self-examination, clinical skin examination, sun protection frequency), and practice attitudes (appropriateness and comfort with client-focused communication) of risk reduction for skin cancer improved significantly and were sustained throughout the study. Conclusions The e-training was feasible and could be delivered online successfully to MTs. Participants were highly satisfied with and accepting of the e-training. As such, e-training has potential as an intervention in larger trials with MTs for reducing the risk of skin cancer. International Registered Report Identifier (IRRID) RR2-10.2196/13480

scholarly journals Partnering With Massage Therapists to Communicate Information on Reducing the Risk of Skin Cancer Among Clients: Longitudinal Study (Preprint)

2020 ◽  
Author(s):  
Lois Loescher ◽  
Kelly Heslin ◽  
Graciela Silva ◽  
Myra Muramoto
Keyword(s):  
Skin Cancer ◽  
Risk Reduction ◽  
Behavioral Interventions ◽  
Skin Lesions ◽  
Data Capture ◽  
Self Report ◽  
High Knowledge ◽  
Beliefs And Practice ◽  
Massage Therapists ◽  
Self Examination

BACKGROUND Skin cancer affects millions of Americans and is an important focus of disease prevention efforts. Partnering with non–health care practitioners such as massage therapists (MTs) can reduce the risk of skin cancer. MTs see clients’ skin on a regular basis, which can allow MTs to initiate “helping conversations” (ie, brief behavioral interventions aimed at reducing the risk of skin cancer). OBJECTIVE The purpose of this study was to evaluate (1) the feasibility of recruiting, enrolling, and retaining Arizona MTs in an online electronic training (e-training) and (2) the preliminary efficacy of e-training on knowledge, attitudes/beliefs, and practice of risk reduction for skin cancer. We explored MTs’ ability to assess suspicious skin lesions. METHODS We adapted the existing educational content on skin cancer for applicability to MTs and strategies from previous research on helping conversations. We assessed the feasibility of providing such e-training, using Research Electronic Data Capture (REDCap) tools for data capture. We assessed the preliminary efficacy using established self-report surveys at baseline, immediately post training, and at 3 and 6 months post training. RESULTS A total of 95 participants enrolled in the study, of which 77% (73/95) completed the assessments at 6 months (overall attrition=23%). Project satisfaction and e-training acceptability were high. Knowledge, personal behaviors (skin self-examination, clinical skin examination, sun protection frequency), and practice attitudes (appropriateness and comfort with client-focused communication) of risk reduction for skin cancer improved significantly and were sustained throughout the study. CONCLUSIONS The e-training was feasible and could be delivered online successfully to MTs. Participants were highly satisfied with and accepting of the e-training. As such, e-training has potential as an intervention in larger trials with MTs for reducing the risk of skin cancer. INTERNATIONAL REGISTERED REPORT RR2-10.2196/13480

scholarly journals Web-Based Skin Cancer Prevention Training for Massage Therapists: Protocol for the Massage Therapists Skin Health Awareness, Referral, and Education Study (Preprint)

2019 ◽  
Author(s):  
Lois J Loescher ◽  
Kelly M Heslin ◽  
Laura A Szalacha ◽  
Graciela E Silva ◽  
Myra L Muramoto
Keyword(s):  
Skin Cancer ◽  
Cancer Risk ◽  
Risk Reduction ◽  
The United States ◽  
Skin Cancer Prevention ◽  
Health Awareness ◽  
Web Based ◽  
Skin Cancer Risk ◽  
Massage Therapists ◽  
Cancer Risk Reduction

BACKGROUND Skin cancer, the most common cancer in the United States, is costly and potentially deadly. Its burden can be reduced by early detection and prevention activities. The scope of skin cancer requires going beyond traditional health care providers to promote risk reduction. Partnering with the nonbiomedical workforce, such as massage therapists (MTs), may reach more individuals at risk. MTs see much of their clients’ skin and are amenable to performing skin cancer risk reduction activities during massage appointments. OBJECTIVE The objective of this study is to describe the Massage Therapists Skin Health Awareness, Referral, and Education protocol, presenting an overview of our systematic approach to developing rigorous e-training for MTs to enable them to be partners in skin cancer risk reduction. We also describe procedures for usability and feasibility testing of the training. METHODS We developed an integrated electronic learning system that includes electronic training (e-training) technology, simulated client interactions, online data collection instruments, and in-person assessment of MTs’ application of their training. RESULTS A total of 20 participants nationally scored the e-training as high for usability and satisfaction. We have screened an additional 77 MTs in Arizona for interest and eligibility, and currently have 37 enrolled participants, of whom 32 have completed the Web-based training. CONCLUSIONS The structured and rigorous development approach for this skin cancer risk reduction and brief behavioral intervention e-training for MTs begins to fill a gap in skin cancer risk reduction research. Iterative usability testing of our asynchronous Web-based training resulted in positive participant response. Our e-training approach offers greater learner accessibility, increased convenience, and greater scalability than the few existing programs and has the potential to reach many MTs nationally. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/13480

scholarly journals Screening for Melanoma and Other Skin Cancer Shows a Higher Early Melanoma Incidence: Social Educational Program “Life Fear-Free”

2021 ◽  
Vol 8 (1) ◽  
pp. 54-68
Author(s):  
Lev Demidov ◽  
Igor Samoylenko ◽  
Nina Vand ◽  
Igor Utyashev ◽  
Irina Shubina ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Screening Program ◽  
Excisional Biopsy ◽  
Skin Lesions ◽  
Detection Methods ◽  
Non Melanoma Skin Cancer ◽  
The Social ◽  
Educational Campaign ◽  
Skin Cancer Detection ◽  
The Impact

Background: The screening program Life Fear-Free (LFF) aimed at early diagnosis of cutaneous melanoma (CM) was introduced in Samara, Chelyabinsk, Yekaterinburg, and Krasnodar (Russia) in 2019. Objectives: To analyze the impact of the program on early CM and non-melanoma skin cancer (NMSC) detection. Methods: According to the social educational campaign, people were informed about CM risk factors and symptoms and were invited for skin examination. The program planned to involve 3200 participants in total. Participants with suspicious lesions were invited for excisional biopsy. Results: 3143 participants, including 75.4% women, were examined for skin lesions. The average age of the participants was 43.7 years. Mostly skin phototypes II and III were registered (48.2% and 41.0%, respectively); 3 patients had CM, 15 had basal cell carcinoma, and 1 had Bowen’s disease, which were confirmed histologically. All detected melanomas had Breslow’s thickness of 1 mm. Conclusion: The participants showed high interest in early skin cancer detection programs. The incidence rate of CM and NMSCs among the program participants was higher than in general public. The early disease grade was proven for the detected CMs and NMSCs. The study has shown that it is important to continue such programs.

scholarly journals Interventions to Improve Adherence to Antiretroviral Therapy (ART) in Sub-Saharan Africa: An Updated Systematic Review

2021 ◽  
Vol 18 (5) ◽  
pp. 2477
Author(s):  
Panmial Priscilla Damulak ◽  
Suriani Ismail ◽  
Rosliza Abdul Manaf ◽  
Salmiah Mohd Said ◽  
Oche Agbaji
Keyword(s):  
Systematic Review ◽  
Antiretroviral Therapy ◽  
Behavioral Interventions ◽  
Controlled Trial ◽  
Self Report ◽  
Sub Saharan Africa ◽  
Art Adherence ◽  
Study Characteristics ◽  
Combination Study ◽  
Sub Saharan

Optimal adherence to antiretroviral therapy (ART) remains the bedrock of effective therapy and management of human immunodeficiency virus (HIV). This systematic review examines the effect of interventions in improving ART adherence in sub-Saharan Africa (SSA), which bears the largest global burden of HIV infection. In accordance with PRISMA guidelines, and based on our inclusion and exclusion criteria, PUBMED, MEDLINE, and Google Scholar databases were searched for published studies on ART adherence interventions from 2010 to 2019. Thirty-one eligible studies published between 2010 to 2019 were identified, the categories of interventions were structural, behavioral, biological, cognitive, and combination. Study characteristics varied across design, intervention type, intervention setting, country, and outcome measurements. Many of the studies were behavioral interventions conducted in hospitals with more studies being randomized controlled trial (RCT) interventions. Despite the study variations, twenty-four studies recorded improvements. Notwithstanding, more quality studies such as RCTs should be conducted, especially among key affected populations (KAPs) to control transmission of resistant strains of the virus. Reliable objective measures of adherence should replace the conventional subjective self-report. Furthermore, long-term interventions with longer duration should be considered when evaluating the effectiveness of interventions.

scholarly journals Rationale and Design of the National Neuropsychology Network

2021 ◽  
pp. 1-11
Author(s):  
David W. Loring ◽  
Russell M. Bauer ◽  
Lucia Cavanagh ◽  
Daniel L. Drane ◽  
Kristen D. Enriquez ◽  
...  
Keyword(s):  
Los Angeles ◽  
Clinical Research ◽  
Neuropsychological Test ◽  
Data Capture ◽  
Self Report ◽  
Medical College ◽  
Research Initiative ◽  
Level Data ◽  
Report Data ◽  
Self Report Data

Abstract Objective. The National Neuropsychology Network (NNN) is a multicenter clinical research initiative funded by the National Institute of Mental Health (NIMH; R01 MH118514) to facilitate neuropsychology’s transition to contemporary psychometric assessment methods with resultant improvement in test validation and assessment efficiency. Method: The NNN includes four clinical research sites (Emory University; Medical College of Wisconsin; University of California, Los Angeles (UCLA); University of Florida) and Pearson Clinical Assessment. Pearson Q-interactive (Q-i) is used for data capture for Pearson published tests; web-based data capture tools programmed by UCLA, which serves as the Coordinating Center, are employed for remaining measures. Results: NNN is acquiring item-level data from 500–10,000 patients across 47 widely used Neuropsychology (NP) tests and sharing these data via the NIMH Data Archive. Modern psychometric methods (e.g., item response theory) will specify the constructs measured by different tests and determine their positive/negative predictive power regarding diagnostic outcomes and relationships to other clinical, historical, and demographic factors. The Structured History Protocol for NP (SHiP-NP) helps standardize acquisition of relevant history and self-report data. Conclusions: NNN is a proof-of-principle collaboration: by addressing logistical challenges, NNN aims to engage other clinics to create a national and ultimately an international network. The mature NNN will provide mechanisms for data aggregation enabling shared analysis and collaborative research. NNN promises ultimately to enable robust diagnostic inferences about neuropsychological test patterns and to promote the validation of novel adaptive assessment strategies that will be more efficient, more precise, and more sensitive to clinical contexts and individual/cultural differences.

Breast Self-Examination, Cancer Knowledge and Breast Disease in a Sample of Hunter Valley Women

1990 ◽  
Vol 7 (3) ◽  
pp. 136-142 ◽  
Author(s):  
Maureen Beckett ◽  
Selina Redman ◽  
Christina Lee
Keyword(s):  
Breast Cancer ◽  
Health Beliefs ◽  
Breast Disease ◽  
Self Report ◽  
Cancer Knowledge ◽  
Breast Self Examination ◽  
History Of ◽  
Breast Lumps ◽  
Knowledge Of Cancer ◽  
Self Examination

Fifty women with a history of breast lumps, and fifty control women matched for age and educational level, were administered a self-report questionnaire to determine knowledge of breast cancer, frequency and proficiency of breast self-examination (BSE), and health beliefs relating to BSE. Although women with previous breast lumps were more knowledgeable about breast cancer than those without, the two groups did not differ in attitudes or preventive behaviours. Overall knowledge of cancer and of BSE practice was low. This suggests a need for educational campaigns to increase knowledge and awareness, as a first step towards behaviour change, and a need for research to identify more effective predictors of BSE practice.

scholarly journals Teaching Skin Cancer Detection to Medical Students Using a Dermoscopic Algorithm

PRiMER ◽  
2021 ◽  
Vol 5 ◽  
Author(s):  
Peggy R. Cyr ◽  
Wendy Craig ◽  
Hadjh Ahrns ◽  
Kathryn Stevens ◽  
Caroline Wight ◽  
...  
Keyword(s):  
Primary Care ◽  
Medical Students ◽  
Skin Cancer ◽  
Primary Care Physicians ◽  
Survival Rates ◽  
Family Physicians ◽  
Skin Lesions ◽  
Posttest Score ◽  
Malignant Skin ◽  
Attending Physicians

Introduction: Early detection of melanoma skin cancer improves survival rates. Training family physicians in dermoscopy with the triage amalgamated dermoscopic algorithm (TADA) has high sensitivity and specificity for identifying malignant skin neoplasms. In this study we evaluated the effectiveness of TADA training among medical students, compared with practicing clinicians. Methods: We incorporated the TADA framework into 90-minute workshops that taught dermoscopy to family physicians, primary care residents, and first- and second-year medical students. The workshop reviewed the clinical and dermoscopic features of benign and malignant skin lesions and included a hands-on interactive session using a dermatoscope. All participants took a 30-image pretest and a different 30-image posttest. Results: Forty-six attending physicians, 25 residents, and 48 medical students participated in the workshop. Mean pretest scores were 20.1, 20.3, and 15.8 for attending physicians, resident physicians and students, respectively (P<.001); mean posttest scores were 24.5, 25.9, and 24.1, respectively (P=.11). Pre/posttest score differences were significant (P<.001) for all groups. The medical students showed the most gain in their pretest and posttest scores. Conclusion: After short dermoscopy workshop, medical students perform as well as trained physicians in identifying images of malignant skin lesions. Dermoscopy training may be a valuable addition to the medical school curriculum as this skill can be used by primary care physicians as well as multiple specialists including dermatologists, gynecologists, otolaryngologists, plastic surgeons, and ophthalmologists, who often encounter patients with concerning skin lesions.

scholarly journals Intelligent Dermatologist Tool for Classifying Multiple Skin Cancer Subtypes by Incorporating Manifold Radiomics Features Categories

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Omneya Attallah ◽  
Maha Sharkas
Keyword(s):  
Skin Cancer ◽  
Binary Classification ◽  
Survival Rates ◽  
Skin Lesions ◽  
Accurate Diagnosis ◽  
Computer Assisted ◽  
Discrete Wavelet ◽  
Cancer Subtypes ◽  
Low Level ◽  
High Level

The rates of skin cancer (SC) are rising every year and becoming a critical health issue worldwide. SC’s early and accurate diagnosis is the key procedure to reduce these rates and improve survivability. However, the manual diagnosis is exhausting, complicated, expensive, prone to diagnostic error, and highly dependent on the dermatologist’s experience and abilities. Thus, there is a vital need to create automated dermatologist tools that are capable of accurately classifying SC subclasses. Recently, artificial intelligence (AI) techniques including machine learning (ML) and deep learning (DL) have verified the success of computer-assisted dermatologist tools in the automatic diagnosis and detection of SC diseases. Previous AI-based dermatologist tools are based on features which are either high-level features based on DL methods or low-level features based on handcrafted operations. Most of them were constructed for binary classification of SC. This study proposes an intelligent dermatologist tool to accurately diagnose multiple skin lesions automatically. This tool incorporates manifold radiomics features categories involving high-level features such as ResNet-50, DenseNet-201, and DarkNet-53 and low-level features including discrete wavelet transform (DWT) and local binary pattern (LBP). The results of the proposed intelligent tool prove that merging manifold features of different categories has a high influence on the classification accuracy. Moreover, these results are superior to those obtained by other related AI-based dermatologist tools. Therefore, the proposed intelligent tool can be used by dermatologists to help them in the accurate diagnosis of the SC subcategory. It can also overcome manual diagnosis limitations, reduce the rates of infection, and enhance survival rates.

scholarly journals SKIN LESION CLASSIFICATION FROM DERMOSCOPY AND CLINICAL IMAGES WITH A DEEP LEARNING APPROACH

2021 ◽  
Vol 9 (10) ◽  
pp. 1294-1300
Author(s):  
Aigli Korfiati ◽  
◽  
Giorgos Livanos ◽  
Christos Konstandinou ◽  
Sophia Georgiou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Skin Cancer ◽  
Medical Image ◽  
Skin Lesions ◽  
Learning Approaches ◽  
Early Screening ◽  
Clinical Images ◽  
Cad Systems ◽  
Learning Classifier ◽  
Aided Diagnosis

Computer-aided diagnosis (CAD) systems based on deep learning approaches are now feasible due to the availability of big data and the availability of powerful computational resources.The medical image-based CAD systems are of great interest in numerous diseases, but especially for skin cancer diagnosis, deep learning models have been mostly developed for dermoscopy images. Models for clinical images are few, mainly due to the unavailability of big volumes of relevant data. However, CAD systems able to classify skin lesions from clinical images would be of great valueboth for the population and clinicians as an initial early screening of lesions that would leadpatients to visiting a dermatologist in case of suspicious lesions. This is even more pronounced in areas where there is lack of dermoscopy instruments. Thus, in this paper, we aimed to build a classifier based on bothdermoscopy and clinical images able to discriminate skin cancer from skin lesions. The classification is made among three benign and two malignant categories, which include Nevus, Benign but not nevus, Benign but suspicious for malignancy, Melanoma and Non-Melanocytic Carcinoma.The proposed deep learning classifier achieves an Area Under Curve ranging between 0.75 and 0.9 for the five examined categories.

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