JMIR dermatology最新文献

{"title":"Assessing the Relationship Between Vitiligo and Major Depressive Disorder Severity: Cross-Sectional Study.","authors":"Amr Molla, Raed Jannadi, Hamza Alayoubi, Haya Altouri, Maryam Balkhair, Dareen Hafez","doi":"10.2196/60686","DOIUrl":"10.2196/60686","url":null,"abstract":"<p><strong>Background: </strong>Vitiligo, a common dermatological disorder in Saudi Arabia, is associated with significant psychological impacts. This study explores the relationship between vitiligo and the severity of major depressive disorder (MDD), highlighting the broader implications on mental health among affected individuals.</p><p><strong>Objective: </strong>We aim to assess the prevalence and predictors of depression among adult patients with vitiligo, and to examine the relationship between MDD severity and vitiligo.</p><p><strong>Methods: </strong>Using a cross-sectional design, the research used the vitiligo area severity index and the Patient Health Questionnaire-9 to measure the extent of vitiligo and depression severity, respectively. This study involved 340 diagnosed patients with vitiligo from various health care settings. Logistic and ordinal regression analysis were applied to evaluate the impact of sociodemographic variables and vitiligo types on MDD severity.</p><p><strong>Results: </strong>The prevalence of MDD was 58.8% (200/340) of participants. Depression severity varied notably: 18.2% (62/340) of patients experienced mild depression, 17.9% (61/340) moderate, 11.8% (40/340) moderately severe, and 10.9% (37/340) severe depression. Female patients had higher odds of severe depression than male patients (adjusted odds ratio [aOR] 3.14, 95% CI 1.93-5.1; P<.001). Age was inversely related to depression severity, with patients aged older than 60 years showing significantly lower odds (aOR 0.1, 95% CI 0.03-0.39; P<.001). Lower income was associated with higher depression severity (aOR 10.2, 95% CI 3.25-31.8; P<.001). Vitiligo types also influenced depression severity; vulgaris (aOR 5.3, 95% CI 2.6-10.9; P<.001) and acrofacial vitiligo (aOR 2.8, 95% CI 1.5-5.1; P<.001) were significantly associated with higher depression levels compared to focal vitiligo.</p><p><strong>Conclusions: </strong>The findings suggest that vitiligo contributes to an increased risk of severe depression, highlighting the need for integrated dermatological and psychological treatment approaches to address both the physical and mental health aspects of the disease.</p>","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":" ","pages":"e60686"},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11282388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis.","authors":"Shiva Shankar Marri, Warood Albadri, Mohammed Salman Hyder, Ajit B Janagond, Arun C Inamadar","doi":"10.2196/48811","DOIUrl":"10.2196/48811","url":null,"abstract":"<p><strong>Background: </strong>Dermatology is an ideal specialty for artificial intelligence (AI)-driven image recognition to improve diagnostic accuracy and patient care. Lack of dermatologists in many parts of the world and the high frequency of cutaneous disorders and malignancies highlight the increasing need for AI-aided diagnosis. Although AI-based applications for the identification of dermatological conditions are widely available, research assessing their reliability and accuracy is lacking.</p><p><strong>Objective: </strong>The aim of this study was to analyze the efficacy of the Aysa AI app as a preliminary diagnostic tool for various dermatological conditions in a semiurban town in India.</p><p><strong>Methods: </strong>This observational cross-sectional study included patients over the age of 2 years who visited the dermatology clinic. Images of lesions from individuals with various skin disorders were uploaded to the app after obtaining informed consent. The app was used to make a patient profile, identify lesion morphology, plot the location on a human model, and answer questions regarding duration and symptoms. The app presented eight differential diagnoses, which were compared with the clinical diagnosis. The model's performance was evaluated using sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F₁-score. Comparison of categorical variables was performed with the χ² test and statistical significance was considered at P<.05.</p><p><strong>Results: </strong>A total of 700 patients were part of the study. A wide variety of skin conditions were grouped into 12 categories. The AI model had a mean top-1 sensitivity of 71% (95% CI 61.5%-74.3%), top-3 sensitivity of 86.1% (95% CI 83.4%-88.6%), and all-8 sensitivity of 95.1% (95% CI 93.3%-96.6%). The top-1 sensitivities for diagnosis of skin infestations, disorders of keratinization, other inflammatory conditions, and bacterial infections were 85.7%, 85.7%, 82.7%, and 81.8%, respectively. In the case of photodermatoses and malignant tumors, the top-1 sensitivities were 33.3% and 10%, respectively. Each category had a strong correlation between the clinical diagnosis and the probable diagnoses (P<.001).</p><p><strong>Conclusions: </strong>The Aysa app showed promising results in identifying most dermatoses.</p>","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e48811"},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11252620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PatientsLikeMe and Online Patient Support Communities in Dermatology.","authors":"Mindy D Szeto, Michelle Hook Sobotka, Emily Woolhiser, Pritika Parmar, Jieying Wu, Lina Alhanshali, Robert P Dellavalle","doi":"10.2196/50453","DOIUrl":"10.2196/50453","url":null,"abstract":"<p><p>Online patient-oriented platforms such as PatientsLikeMe (PLM) offer a venue for individuals with various diagnoses to share experiences and build community, though they may not be representative of the larger patient population. This potentially limits generalizability and raises concerns about the spread of misinformation, emphasizing the need for informed use and health care provider engagement.</p>","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e50453"},"PeriodicalIF":0.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11237783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141461170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gender Parity Analysis of the Editorial Boards of Influential Dermatology Journals: Cross-Sectional Study.","authors":"Mindy D Szeto, Torunn E Sivesind, Lori S Kim, Katie A O'Connell, Kathryn A Sprague, Yvonne Nong, Daniel M Strock, Annie L Cao, Jieying Wu, Lauren M Toledo, Sophia M Wolfe, Wyatt Boothby-Shoemaker, Robert P Dellavalle","doi":"10.2196/40819","DOIUrl":"10.2196/40819","url":null,"abstract":"<p><p>This study underscores the persistent underrepresentation of women in academic dermatology leadership positions by examining the gender composition of editorial boards across top dermatology journals, emphasizing the urgent need for proactive strategies to promote diversity, equity, and inclusion.</p>","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e40819"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11150886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141077349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Application of Large Language Models in Generating Dermatologic Patient Education Materials According to Reading Level: Qualitative Study.","authors":"Raphaella Lambert, Zi-Yi Choo, Kelsey Gradwohl, Liesl Schroedl, Arlene Ruiz De Luzuriaga","doi":"10.2196/55898","DOIUrl":"10.2196/55898","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Dermatologic patient education materials (PEMs) are often written above the national average seventh- to eighth-grade reading level. ChatGPT-3.5, GPT-4, DermGPT, and DocsGPT are large language models (LLMs) that are responsive to user prompts. Our project assesses their use in generating dermatologic PEMs at specified reading levels.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to assess the ability of select LLMs to generate PEMs for common and rare dermatologic conditions at unspecified and specified reading levels. Further, the study aims to assess the preservation of meaning across such LLM-generated PEMs, as assessed by dermatology resident trainees.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The Flesch-Kincaid reading level (FKRL) of current American Academy of Dermatology PEMs was evaluated for 4 common (atopic dermatitis, acne vulgaris, psoriasis, and herpes zoster) and 4 rare (epidermolysis bullosa, bullous pemphigoid, lamellar ichthyosis, and lichen planus) dermatologic conditions. We prompted ChatGPT-3.5, GPT-4, DermGPT, and DocsGPT to \"Create a patient education handout about [condition] at a [FKRL]\" to iteratively generate 10 PEMs per condition at unspecified fifth- and seventh-grade FKRLs, evaluated with Microsoft Word readability statistics. The preservation of meaning across LLMs was assessed by 2 dermatology resident trainees.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The current American Academy of Dermatology PEMs had an average (SD) FKRL of 9.35 (1.26) and 9.50 (2.3) for common and rare diseases, respectively. For common diseases, the FKRLs of LLM-produced PEMs ranged between 9.8 and 11.21 (unspecified prompt), between 4.22 and 7.43 (fifth-grade prompt), and between 5.98 and 7.28 (seventh-grade prompt). For rare diseases, the FKRLs of LLM-produced PEMs ranged between 9.85 and 11.45 (unspecified prompt), between 4.22 and 7.43 (fifth-grade prompt), and between 5.98 and 7.28 (seventh-grade prompt). At the fifth-grade reading level, GPT-4 was better at producing PEMs for both common and rare conditions than ChatGPT-3.5 (P=.001 and P=.01, respectively), DermGPT (P&lt;.001 and P=.03, respectively), and DocsGPT (P&lt;.001 and P=.02, respectively). At the seventh-grade reading level, no significant difference was found between ChatGPT-3.5, GPT-4, DocsGPT, or DermGPT in producing PEMs for common conditions (all P&gt;.05); however, for rare conditions, ChatGPT-3.5 and DocsGPT outperformed GPT-4 (P=.003 and P&lt;.001, respectively). The preservation of meaning analysis revealed that for common conditions, DermGPT ranked the highest for overall ease of reading, patient understandability, and accuracy (14.75/15, 98%); for rare conditions, handouts generated by GPT-4 ranked the highest (14.5/15, 97%).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;GPT-4 appeared to outperform ChatGPT-3.5, DocsGPT, and DermGPT at the fifth-grade FKRL for both common and rare conditions, although both ChatGPT-3.5 and DocsGPT performed better than GPT-4 at the sevent","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e55898"},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11140271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140960950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online Patient Attitudes Toward Cutaneous Immune-Related Adverse Events Attributed to Nivolumab and Pembrolizumab: Sentiment Analysis.","authors":"Camille M Powers, Andrew K Yang, Hannah Verma, Jeremy Orloff, Austin J Piontkowski, Nicholas Gulati","doi":"10.2196/53792","DOIUrl":"10.2196/53792","url":null,"abstract":"","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e53792"},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11099803/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140853789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Survey of Demographics and Treatments in Melanoma Case Reports: Retrospective Bibliometric Analysis.","authors":"Ross O'Hagan, Jessie Ngandjui, Benjamin Ungar, J. Ungar, N. Gulati","doi":"10.2196/56684","DOIUrl":"https://doi.org/10.2196/56684","url":null,"abstract":"Melanoma case reports show variations in treatment by age and sex.","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"42 14","pages":"e56684"},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ichthyosiform Lichen Planus Pigmentosus in a 19-Year-Old Male Patient: Case Report.","authors":"Audi Sugiharto, J. Gatmaitan, Johannes Dayrit","doi":"10.2196/50429","DOIUrl":"https://doi.org/10.2196/50429","url":null,"abstract":"Lichen planus pigmentosus (LPP) is a condition characterized by persistent and asymptomatic brownish-black-to-blue or purple-gray pigmentation, predominantly in the face and sun-exposed areas, commonly in dark-skinned individuals. Several clinical variants of LPP have been reported. However, the ichthyosiform type of LPP has not been reported. We present a 19-year-old male patient who presented with a 7-year history of asymptomatic grayish macules; patches with fine scales on the face, trunk, and upper extremities; and grayish plaques with thick \"ichthyosiform\" scales on the lower extremities. The diagnosis of LPP was proven by histopathological findings on both the macular and ichthyosiform plaques. Cluster differentiation (CD) 68 stain highlights the same density of pigment-laden macrophages in both the gray macule and the ichthyosiform plaque. The cause of LPP is unknown. Transcription factor anomalies may play a role in increased keratinization of lichen planus lesions. It can be assumed that the mechanism of the altered distribution of keratinization may occur on the ichthyosiform lesions in this patient. The terminology \"ichthyosiform lichen planus pigmentosus\" is hereby proposed to be added to the clinical variants of LPP.","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":" 2","pages":"e50429"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140684272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From the Cochrane Library: Leukotriene Receptor Antagonists for Eczema.","authors":"Lauren Marie Toledo, Ramiro Rodriguez, Torunn E Sivesind, Efstratios Vakirlis, Reiji Kojima, Robert P Dellavalle","doi":"10.2196/50434","DOIUrl":"https://doi.org/10.2196/50434","url":null,"abstract":"","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e50434"},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11053388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140869665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The New Media Landscape and Its Effects on Skin Cancer Diagnostics, Prognostics, and Prevention: Scoping Review.","authors":"Priscilla L Haff, Alli Jacobson, Madison M Taylor, Hayden P Schandua, David P Farris, Hung Q Doan, Kelly C Nelson","doi":"10.2196/53373","DOIUrl":"10.2196/53373","url":null,"abstract":"<p><strong>Background: </strong>The wide availability of web-based sources, including social media (SM), has supported rapid, widespread dissemination of health information. This dissemination can be an asset during public health emergencies; however, it can also present challenges when the information is inaccurate or ill-informed. Of interest, many SM sources discuss cancer, specifically cutaneous melanoma and keratinocyte cancers (basal cell and squamous cell carcinoma).</p><p><strong>Objective: </strong>Through a comprehensive and scoping review of the literature, this study aims to gain an actionable perspective of the state of SM information regarding skin cancer diagnostics, prognostics, and prevention.</p><p><strong>Methods: </strong>We performed a scoping literature review to establish the relationship between SM and skin cancer. A literature search was conducted across MEDLINE, Embase, Cochrane Library, Web of Science, and Scopus from January 2000 to June 2023. The included studies discussed SM and its relationship to and effect on skin cancer.</p><p><strong>Results: </strong>Through the search, 1009 abstracts were initially identified, 188 received full-text review, and 112 met inclusion criteria. The included studies were divided into 7 groupings based on a publication's primary objective: misinformation (n=40, 36%), prevention campaign (n=19, 17%), engagement (n=16, 14%), research (n=12, 11%), education (n=11, 10%), demographics (n=10, 9%), and patient support (n=4, 3%), which were the most common identified themes.</p><p><strong>Conclusions: </strong>Through this review, we gained a better understanding of the SM environment addressing skin cancer information, and we gained insight into the best practices by which SM could be used to positively influence the health care information ecosystem.</p>","PeriodicalId":73553,"journal":{"name":"JMIR dermatology","volume":"7 ","pages":"e53373"},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11036192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140864711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}