Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study
Abstract Introduction Atopic dermatitis (AD) is an incurable, inflammatory skin disease characterized by skin barrier disruption and immune dysregulation. Although AD is considered a childhood disease, adult onset is possible, presenting with daily sleep disturbance and functional impairment associa...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Adis, Springer Healthcare
2020-01-01
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| Series: | Dermatology and Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13555-020-00356-0 |
| _version_ | 1797259531941576704 |
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| author | Bruno Falissard Eric L. Simpson Emma Guttman-Yassky Kim A. Papp Sebastien Barbarot Abhijit Gadkari Grece Saba Laurene Gautier Adeline Abbe Laurent Eckert |
| author_facet | Bruno Falissard Eric L. Simpson Emma Guttman-Yassky Kim A. Papp Sebastien Barbarot Abhijit Gadkari Grece Saba Laurene Gautier Adeline Abbe Laurent Eckert |
| author_sort | Bruno Falissard |
| collection | DOAJ |
| description | Abstract Introduction Atopic dermatitis (AD) is an incurable, inflammatory skin disease characterized by skin barrier disruption and immune dysregulation. Although AD is considered a childhood disease, adult onset is possible, presenting with daily sleep disturbance and functional impairment associated with itch, neuropsychiatric issues (anxiety and depression), and reduced health-related quality of life. Although such aspects of adult AD disease burden have been measured through standardized assessments and based on population-level data, the understanding of the disease experienced at the patient level remains poor. This text-mining study assessed the impact of AD on the lives of adult patients as described from an experiential perspective. Methods Natural language processing (NLP) was applied to qualitative patient response data from two large-scale international cross-sectional surveys conducted in the USA and countries outside of the USA (non-USA; Canada, France, Germany, Italy, Spain, and the UK). Descriptive analysis was conducted on patient responses to an open-ended question on how they felt about their AD and how the disease affected their life. Character length, word count, and stop word (common words) count were evaluated; centrality analysis identified concepts that were most strongly interlinked. Results Patients with AD in all countries were most frequently impacted by itch, pain, and embarrassment across all levels of disease severity. Patients with moderate-to-severe AD were more likely than patients with mild AD to describe sleep disturbances, fatigue, and feelings of depression, anxiety, and a lack of hope that were directly associated with AD. Centrality analysis revealed sleep disturbance was strongly linked with itch. Collectively, these concepts revealed that patients with AD are impacted by both physical and emotional burdens that are intricately connected. Conclusions Qualitative data from NLP, being more patient-centric than data from clinical standardized measures, provide a more comprehensive view of the burden of AD to inform disease management. |
| first_indexed | 2024-04-24T23:10:55Z |
| format | Article |
| id | doaj.art-d7f2497172b147799870d720575581cd |
| institution | Directory Open Access Journal |
| issn | 2193-8210 2190-9172 |
| language | English |
| last_indexed | 2024-04-24T23:10:55Z |
| publishDate | 2020-01-01 |
| publisher | Adis, Springer Healthcare |
| record_format | Article |
| series | Dermatology and Therapy |
| spelling | doaj.art-d7f2497172b147799870d720575581cd2024-03-17T12:16:04ZengAdis, Springer HealthcareDermatology and Therapy2193-82102190-91722020-01-0110229730510.1007/s13555-020-00356-0Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional StudyBruno Falissard0Eric L. Simpson1Emma Guttman-Yassky2Kim A. Papp3Sebastien Barbarot4Abhijit Gadkari5Grece Saba6Laurene Gautier7Adeline Abbe8Laurent Eckert9Paris Sud UniversityDepartment of Dermatology, Oregon Health and Science UniversityDepartment of Dermatology and the Immunology Institute, Icahn School of Medicine at Mount SinaiProbity Medical ResearchCentre Hospitalier Universitaire de NantesRegeneron Pharmaceuticals, Inc.Kantar—Health DivisionKantar—Health DivisionSanofiSanofiAbstract Introduction Atopic dermatitis (AD) is an incurable, inflammatory skin disease characterized by skin barrier disruption and immune dysregulation. Although AD is considered a childhood disease, adult onset is possible, presenting with daily sleep disturbance and functional impairment associated with itch, neuropsychiatric issues (anxiety and depression), and reduced health-related quality of life. Although such aspects of adult AD disease burden have been measured through standardized assessments and based on population-level data, the understanding of the disease experienced at the patient level remains poor. This text-mining study assessed the impact of AD on the lives of adult patients as described from an experiential perspective. Methods Natural language processing (NLP) was applied to qualitative patient response data from two large-scale international cross-sectional surveys conducted in the USA and countries outside of the USA (non-USA; Canada, France, Germany, Italy, Spain, and the UK). Descriptive analysis was conducted on patient responses to an open-ended question on how they felt about their AD and how the disease affected their life. Character length, word count, and stop word (common words) count were evaluated; centrality analysis identified concepts that were most strongly interlinked. Results Patients with AD in all countries were most frequently impacted by itch, pain, and embarrassment across all levels of disease severity. Patients with moderate-to-severe AD were more likely than patients with mild AD to describe sleep disturbances, fatigue, and feelings of depression, anxiety, and a lack of hope that were directly associated with AD. Centrality analysis revealed sleep disturbance was strongly linked with itch. Collectively, these concepts revealed that patients with AD are impacted by both physical and emotional burdens that are intricately connected. Conclusions Qualitative data from NLP, being more patient-centric than data from clinical standardized measures, provide a more comprehensive view of the burden of AD to inform disease management.https://doi.org/10.1007/s13555-020-00356-0Atopic dermatitisNatural language processingPatient perceptionQualitativeText-mining |
| spellingShingle | Bruno Falissard Eric L. Simpson Emma Guttman-Yassky Kim A. Papp Sebastien Barbarot Abhijit Gadkari Grece Saba Laurene Gautier Adeline Abbe Laurent Eckert Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study Dermatology and Therapy Atopic dermatitis Natural language processing Patient perception Qualitative Text-mining |
| title | Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study |
| title_full | Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study |
| title_fullStr | Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study |
| title_full_unstemmed | Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study |
| title_short | Qualitative Assessment of Adult Patients’ Perception of Atopic Dermatitis Using Natural Language Processing Analysis in a Cross-Sectional Study |
| title_sort | qualitative assessment of adult patients perception of atopic dermatitis using natural language processing analysis in a cross sectional study |
| topic | Atopic dermatitis Natural language processing Patient perception Qualitative Text-mining |
| url | https://doi.org/10.1007/s13555-020-00356-0 |
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