Data-driven Development of Digital Health Applications on the Example of Dementia Screening

Schinle, Markus; Erler, Christina; Schneider, Timon; Plewnia, Joana; Stork, Wilhelm

doi:10.1109/memea52024.2021.9478676

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…As the instrument could generalize well [ 64 ] in specialties other than dementia, a good external validity was also expected. It can be used for every health app with only minor adjustments—such as in the dimension acceptance of the app , which was adapted to the app DemPredict ( Hypotheses and Schinle et al [ 16 , 46 ]). The Cronbach α indicated a very good reliability with a value of .83 (95% CI 0.8-0.86) [ 65 ].…”

Section: Resultsmentioning

confidence: 99%

“…In this way, the financial burden on the health system can be reduced [ 12 , 13 ] as there is a time saving of up to 30% in comparison with traditional solutions [ 14 ]. There are further studies worldwide that also report time savings by using digital solutions (eg, in Austria [ 15 ], Germany [ 14 , 16 - 18 ], and the United States [ 12 , 13 , 19 ]), including the special case of dementia screening [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

“…To be able to apply the data to an example, special items were developed that capture the independent variable acceptance of the app . For this purpose, the functionality of the digital dementia screening app DemPredict [ 16 , 46 ] was briefly explained in a free field of this study, and some questions on its acceptance were formulated.…”

Section: Introductionmentioning

confidence: 99%

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Digital Health Apps in the Context of Dementia: Questionnaire Study to Assess the Likelihood of Use Among Physicians

Schinle¹,

Erler²,

Kaliciak³

et al. 2022

JMIR Form Res

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Background Age-related diseases such as dementia are playing an increasingly important role in global population development. Thus, prevention, diagnostics, and interventions require more accessibility, which can be realized through digital health apps. With the app on prescription, Germany made history by being the first country worldwide to offer physicians the possibility to prescribe and reimburse digital health apps as of the end of the year 2020. Objective Considering the lack of knowledge about correlations with the likelihood of use among physicians, this study aimed to address the question of what makes the use of a digital health app by physicians more likely. Methods We developed and validated a novel measurement tool—the Digital Health Compliance Questionnaire (DHCQ)—in an interdisciplinary collaboration of experts to assess the role of proposed factors in the likelihood of using a health app. Therefore, a web-based survey was conducted to evaluate the likelihood of using a digital app called DemPredict to screen for Alzheimer dementia. Within this survey, 5 latent dimensions (acceptance, attitude toward technology, technology experience, payment for time of use, and effort of collection), the dependent variable likelihood of use, and answers to exploratory questions were recorded and tested within directed correlations. Following a non–probability-sampling strategy, the study was completed by 331 physicians from Germany in the German language, of whom 301 (90.9%) fulfilled the study criteria (eg, being in regular contact with patients with dementia). These data were analyzed using a range of statistical methods to validate the dimensions of the DHCQ. Results The DHCQ revealed good test theoretical measures—it showed excellent fit indexes (Tucker-Lewis index=0.98; comparative fit index=0.982; standardized root mean square residual=0.073; root mean square error of approximation=0.037), good internal consistency (Cronbach α=.83), and signs of moderate to large correlations between the DHCQ dimensions and the dependent variable. The correlations between the variables acceptance, attitude toward technology, technology experience, and payment for the time of use and the dependent variable likelihood of use ranged from 0.29 to 0.79, and the correlation between effort of the collection and likelihood of use was −0.80. In addition, we found high levels of skepticism regarding data protection, and the age of the participants was found to be negatively related to their technical experience and attitude toward technology. Conclusions In the context of the results, increased communication between the medical and technology sectors and significantly more awareness raising are recommended to make the use of digital health apps more attractive to physicians as they can be adjusted to their everyday needs. Further research could explore the connection between areas such as adherence on the patient side and its impact on the likelihood of use by physicians.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Digital Health Apps in the Context of Dementia: Questionnaire Study to Assess the Likelihood of Use Among Physicians

Schinle¹,

Erler²,

Kaliciak³

et al. 2022

JMIR Form Res

Self Cite

View full text Add to dashboard Cite

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“…Digital medicine technologies and wearables can make a significant impact on conditions wherein symptoms cannot be reported reliably. For example, children under 8 years old are not able to accurately describe abstract emotions and thus are unable to report their own mental health problems [19][20][21][22][23], and adults with dementia [24] or psychosis have an impaired capacity to reliably report on their symptoms [25,26] as a product of the disease. In these cases, digital medicine technologies can capture objective metrics of their symptoms and convey that information directly to clinical decision makers.…”

Section: Areas Of Opportunity For Digital Medicinementioning

confidence: 99%

Advancing Digital Medicine with Wearables in the Wild

McGinnis

2022

Sensors

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“…Online teaching resources are generally divided into two categories: static teaching resources and dynamic teaching resources [9][10][11][12][13][14]. Static resources are teaching resources that exist in text form in the network and do not or rarely add value, such as tools and reference books in digital libraries and online reading rooms [15][16][17][18]; dynamic resources are the opposite of static resources, and they add value in the process of presentation, which requires specialized designers to scientifically design, process, and treat them in a different These resources need to be scientifically designed, processed and handled by specialized designers to interpret the learning content differently so that learners can get more "meaning" from them [19][20][21][22][23]. Currently, there are two main areas of online learning in China: academic education and non-academic education, and many schools, state educational institutions, and commercial online education operators are implementing online education.…”

Section: Introductionmentioning

confidence: 99%

Construction of a personalized learning platform based on genetic algorithm for specialized education in industrial colleges in the context of industry-education integration

Fang

2023

Applied Mathematics and Nonlinear Sciences

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Under the progress trend of the information technology period environment of deepening study curriculum reform, personalized learning in specialized education of industrial colleges has become one of its key contents. This paper mainly studies the necessary system design based on characteristics of genetic calculation for specialized education in industrial colleges under industry-education integration. This paper first introduces the principle of genetic algorithm. It then proceeds to introduce in detail the shortcomings of The advantage of this calculation method is that the standard calculation tendency is unable to move forward in an area extremes, the iteration is relatively slow, and the low accuracy when dealing with optimization problems. Then the design and construction ideas of the personalized platform and the database design from Learners, educators (teachers), and administrators are compared by experimentally analyzing the data diversity and convergence of the three algorithms on the database. Experimentally, the diversity of the self-adaptive genetic algorithm is maintained at 0.8, and the diversity, iteration time, and convergence standard are better compared with the comparison subject. Using a self-adaptive genetic algorithm to evaluate and rank learners’ personality differences and to provide and recommend suitable learning methods for learners helps develop education and improve teaching quality and has great historical significance for China’s development and international status.

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Data-driven Development of Digital Health Applications on the Example of Dementia Screening

Cited by 4 publications

References 15 publications

Digital Health Apps in the Context of Dementia: Questionnaire Study to Assess the Likelihood of Use Among Physicians

Digital Health Apps in the Context of Dementia: Questionnaire Study to Assess the Likelihood of Use Among Physicians

Advancing Digital Medicine with Wearables in the Wild

Construction of a personalized learning platform based on genetic algorithm for specialized education in industrial colleges in the context of industry-education integration

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