Effect of a disease-monitoring smartphone application in combination with a patient educational program on mental health of patients with psoriasis: A randomized intervention study

Beck, Alena; Schulze-Hagen, Theresa; Domogalla, Lena; Herr, Raphael M.; Benecke, Johannes; Schmieder, Astrid

doi:10.1016/j.jaad.2020.12.048

Cited by 9 publications

(10 citation statements)

References 5 publications

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“…Innovative teledermatology models can encourage collaborative care and patient engagement are equivalent to in-person care for improving functional status and psychological health in patients with psoriasis [63][64][65]. A mobile phone-based disease monitoring application for people suffering from psoriasis in combination with a patient educational program was developed and applied [17]. Allay m-health intervention is a 12 weeks bespoke digital therapeutic intervention for patients with psoriasis and is designed as an adjunct to medical management of the condition, which may help patients improve resilience, mood, beliefs on their condition and enhance their QOL [66].…”

Section: Innovative Teledermatology Models Of People With Psoriasismentioning

confidence: 99%

WITHDRAWN: The non-pharmacological interventions of people with psoriasis: a scoping review

Zhang¹,

Lin

et al. 2022

Preprint

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Introduction The ultimate aim of health care is to eradicate a disease and return the person’s life to normal. But until the day comes when this has been achieved there will be a need to support and assist many people with psoriasis in non-pharmacological interventions. These ‘adjuvant’ approaches receive too little attention while dermatologists and researchers strive for better pharmacological therapy. Methods This scoping review identifies and catalogues non-pharmacological interventions in people with psoriasis. EMBASE, PubMed, CINAHL, PsycINFO and Scopus were searched from inception to June 2022. Regardless of the type of study, the research was included for non-pharmacological interventions in people with psoriasis. Following themes were extracted from the included articles. Two reviewers independently screened and analyzed them. Results From 1322 initial records, 71 studies were identified and analyzed. The non-pharmacological interventions for people with psoriasis include two levels of organizational and individual intervention. The organizational non-pharmacological interventions included the following: nationwide health care model (PsPSP, ProvenCare®, PsoHealth German, PsoNet, IMPROVE model and PsoWell clinic), innovative teledermatology models (mHealth APP, eTIPs study and therapist-Guided internet-based cognitive and behavioral treatments) and multidisciplinary intervention. The individual non-pharmacological interventions included educational interventions (therapeutic patient education, psycho-educational intervention and self-management education), psychosocial interventions (cognitive and behavioral treatments, self-help and peer to peer support program) and others (happify and motivational interviewing-based training). Conclusions Based on the previous literatures, a protocol of nationwide health care model was constructed for people with psoriasis. It not only provides a direction for building a new psoriatic health care model, but also a basis for summarizing the non-pharmacological interventions in people suffered from psoriasis to help them adapt to a variety of changes in skin disorder.

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Section: Innovative Teledermatology Models Of People With Psoriasismentioning

confidence: 99%

WITHDRAWN: The non-pharmacological interventions of people with psoriasis: a scoping review

Zhang¹,

Lin

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Innovative teledermatology models can encourage collaborative care, and patient engagement is equivalent to inperson care for improving functional status and psychological health in patients with psoriasis 63–65. A mobile phone-based disease monitoring application for patients with psoriasis in combination with a patient educational programme was developed and applied 17. Allay mHealth intervention, a 12-week bespoke digital therapeutic intervention for patients with psoriasis, is designed as an adjunct to medical management of the condition, which may help patients improve resilience, mood and beliefs on their condition and enhance their QOL 66.…”

Section: Resultsmentioning

confidence: 99%

“…An IMPROVE model was established in Denmark for patients with psoriasis and articular psoriasis to ensure they get the best care and eliminate inappropriate incentives in the current compensation system 9. Notably, many non-pharmacological interventions, such as multidisciplinary teams,6 14 15 educational interventions (therapeutic patient education, psychoeducational intervention and self-management education),2 6 14–40 psychosocial interventions (cognitive and behavioural treatments, self-help and peer-to-peer (P2P) support programme)6 15 18 22 24 41–55 and others (happify and motivational interviewing-based training) have proven to be effective 44 56…”

Section: Introductionmentioning

confidence: 99%

Non-pharmacological interventions for patients with psoriasis: a scoping review

Zhang,

Lin,

Feng

et al. 2023

BMJ Open

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ObjectivesHealthcare ultimately aims to eradicate diseases and restore normality to people’s lives. However, until this is achieved for every person, there is a need to support and assist patients with psoriasis using non-pharmacological interventions. These ‘adjuvant’ approaches have received little attention, whereas dermatologists and researchers strive for better pharmacological therapy. Here, we aimed to perform a scoping review to identify and catalogue non-pharmacological interventions for patients with psoriasis.DesignA scoping review.SettingAll healthcare settings.Search strategyEMBASE, PubMed, CINAHL, PsycINFO and Scopus databases were searched from their inception to June 2022. Irrespective of the study type, the studies included non-pharmacological interventions for patients with psoriasis. This theme was extracted from the included articles. Two reviewers independently screened and analysed the data.ResultsFrom 1322 initial records, 71 studies were identified and analysed. Non-pharmacological interventions for patients with psoriasis include two levels: organisational and individual. The organisational non-pharmacological interventions included the nationwide healthcare model (PsPSP, ProvenCare, German PsoHealth and Psoriasis Network, IMPROVE model and PsoWell clinic), innovative teledermatology models (mHealth app, electronic Targeted Intervention for Psoriasis study and therapist-guided internet-based cognitive and behavioural treatments) and multidisciplinary interventions. The individual non-pharmacological interventions included educational interventions (therapeutic patient education, psychoeducational intervention and self-management education), psychosocial interventions (cognitive and behavioural treatments, self-help and peer-to-peer support programmes) and others (happify and motivational interviewing-based training).ConclusionsBased on previous literature, a nationwide healthcare model protocol was constructed for patients with psoriasis. This provided the direction for developing a new psoriasis healthcare model and a basis for summarising the non-pharmacological interventions for patients with psoriasis, which helps them adjust to changes in the skin disease.

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“…A possible explanation for the lower use of mHealth apps among patients could be their unknown effectiveness and the lack of high-quality studies [ 14 ]. We have previously shown that patients with psoriasis undergoing an educational program combined with a monitoring smartphone app had a significantly greater reduction in depression and anxiety symptoms when using the app less than once a month [ 15 ]. Notably, the long-term effects observed for >60 weeks in the same clinical trial showed similar significant reductions in depression and anxiety [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

Bibi,

Schaffert,

Blauth

et al. 2023

J Med Internet Res

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Background Rapid digitalization in health care has led to the adoption of digital technologies; however, limited trust in internet-based health decisions and the need for technical personnel hinder the use of smartphones and machine learning applications. To address this, automated machine learning (AutoML) is a promising tool that can empower health care professionals to enhance the effectiveness of mobile health apps. Objective We used AutoML to analyze data from clinical studies involving patients with chronic hand and/or foot eczema or psoriasis vulgaris who used a smartphone monitoring app. The analysis focused on itching, pain, Dermatology Life Quality Index (DLQI) development, and app use. Methods After extensive data set preparation, which consisted of combining 3 primary data sets by extracting common features and by computing new features, a new pseudonymized secondary data set with a total of 368 patients was created. Next, multiple machine learning classification models were built during AutoML processing, with the most accurate models ultimately selected for further data set analysis. Results Itching development for 6 months was accurately modeled using the light gradient boosted trees classifier model (log loss: 0.9302 for validation, 1.0193 for cross-validation, and 0.9167 for holdout). Pain development for 6 months was assessed using the random forest classifier model (log loss: 1.1799 for validation, 1.1561 for cross-validation, and 1.0976 for holdout). Then, the random forest classifier model (log loss: 1.3670 for validation, 1.4354 for cross-validation, and 1.3974 for holdout) was used again to estimate the DLQI development for 6 months. Finally, app use was analyzed using an elastic net blender model (area under the curve: 0.6567 for validation, 0.6207 for cross-validation, and 0.7232 for holdout). Influential feature correlations were identified, including BMI, age, disease activity, DLQI, and Hospital Anxiety and Depression Scale-Anxiety scores at follow-up. App use increased with BMI >35, was less common in patients aged >47 years and those aged 23 to 31 years, and was more common in those with higher disease activity. A Hospital Anxiety and Depression Scale-Anxiety score >8 had a slightly positive effect on app use. Conclusions This study provides valuable insights into the relationship between data characteristics and targeted outcomes in patients with chronic eczema or psoriasis, highlighting the potential of smartphone and AutoML techniques in improving chronic disease management and patient care.

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Effect of a disease-monitoring smartphone application in combination with a patient educational program on mental health of patients with psoriasis: A randomized intervention study

Cited by 9 publications

References 5 publications

WITHDRAWN: The non-pharmacological interventions of people with psoriasis: a scoping review

WITHDRAWN: The non-pharmacological interventions of people with psoriasis: a scoping review

Non-pharmacological interventions for patients with psoriasis: a scoping review

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

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