The electronic, personalizable Rosetta system for dementia care: exploring the user-friendliness, usefulness and impact

Hattink, Bart; Meiland, Franka; Overmars-Marx, Tessa; Boer, Moniek de; Ebben, Peter; Blanken, M van; Verhaeghe, Sofie; Stalpers-Croeze, I; Jedlitschka, Andreas; Flick, S E; Leeuw, de; Karkowski, I.; Dröes, Rose-Marie

doi:10.3109/17483107.2014.932022

“…In a review of 24 studies, 64 two RCTs 65,66 and one controlled trial 67 of apps focused on cognitive training showed improved cognition, whereas one RCT did not. 68 Three other RCTs, one of serious games coupled with cognitive training, 69 one with a multicomponent program 70 and another of engagement, 71 showed no effects on various outcomes.…”

Section: Cognitive Impairmentmentioning

confidence: 99%

“…In total, 49 studies were retrieved, 11,25-72 comprising 16 reviews 11,25,29,[31][32][33][34][35][36][37][38][39]42,51,60,64 and 33 individual studies. [26][27][28]30,40,41,[43][44][45][46][47][48][49][50][52][53][54][55][56][57][58][59][61][62][63][65][66][67][68][69][70][71][72] Key findings are presented below; more detailed evidence tables are provided in Appendix 1.…”

Section: Objective No 1: Efficacy Of Apps On Chronic Disease Self-mamentioning

confidence: 99%

Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management

Scott

¹

,

Scuffham²,

Gupta

³

et al. 2020

Aust. Health Review

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Objective Smartphone health applications (apps) are being increasingly used to assist patients in chronic disease self-management. The effects of such apps on patient outcomes are uncertain, as are design features that maximise usability and efficacy, and the best methods for evaluating app quality and utility. Methods In assessing efficacy, PubMed, Cochrane Library and EMBASE were searched for systematic reviews (and single studies if no systematic review was available) published between January 2007 and January 2018 using search terms (and synonyms) of ‘smartphone’ and ‘mobile applications’, and terms for each of 11 chronic diseases: asthma, chronic obstructive lung disease (COPD), diabetes, chronic pain, serious mental health disorders, alcohol and substance addiction, heart failure, ischaemic heart disease, cancer, cognitive impairment, chronic kidney disease (CKD). With regard to design features and evaluation methods, additional reviews were sought using search terms ‘design’, ‘quality,’ ‘usability’, ‘functionality,’ ‘adherence’, ‘evaluation’ and related synonyms. Results Of 13 reviews and six single studies assessing efficacy, consistent evidence of benefit was seen only with apps for diabetes, as measured by decreased glycosylated haemoglobin levels (HbA1c). Some, but not all, studies showed benefit in asthma, low back pain, alcohol addiction, heart failure, ischaemic heart disease and cancer. There was no evidence of benefit in COPD, cognitive impairment or CKD. In all studies, benefits were clinically marginal and none related to morbid events or hospitalisation. Twelve design features were identified as enhancing usability. An evaluation framework comprising 32 items was formulated. Conclusion Evidence of clinical benefit of most available apps is very limited. Design features that enhance usability and maximise efficacy were identified. A provisional ‘first-pass’ evaluation framework is proposed that can help decide which apps should be endorsed by government agencies following more detailed technical assessments and which could then be recommended with confidence by clinicians to their patients. What is known about the topic? Smartphone health apps have attracted considerable interest from patients and health managers as a means of promoting more effective self-management of chronic diseases, which leads to better health outcomes. However, most commercially available apps have never been evaluated for benefits or harms in clinical trials, and there are currently no agreed quality criteria, standards or regulations to ensure health apps are user-friendly, accurate in content, evidence based or efficacious. What does this paper add? This paper presents a comprehensive review of evidence relating to the efficacy, usability and evaluation of apps for 11 common diseases aimed at assisting patients in self-management. Consistent evidence of benefit was only seen for diabetes apps; there was absent or conflicting evidence of benefit for apps for the remaining 10 diseases. Benefits that were detected were of marginal clinical importance, with no reporting of hard clinical end-points, such as mortality or hospitalisations. Only a minority of studies explicitly reported using behaviour change theories to underpin the app intervention. Many apps lacked design features that the literature identified as enhancing usability and potential to confer benefit. Despite a plethora of published evaluation tools, there is no universal framework that covers all relevant clinical and technical attributes. An inclusive list of evaluation criteria is proposed that may overcome this shortcoming. What are the implications for practitioners? The number of smartphone apps will continue to grow, as will the appetite for patients and clinicians to use them in chronic disease self-management. However, the evidence to date of clinical benefit of most apps already available is very limited. Design features that enhance usability and clinical efficacy need to be considered. In making decisions about which apps should be endorsed by government agencies and recommended with confidence by clinicians to their patients, a comprehensive but workable evaluation framework needs to be used by bodies assuming the roles of setting and applying standards.

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“…decision support systems for guideline compliance [20]); ii) to contribute to the selfreliance of the person in need of care in such a way that direct on-site care assistance can be avoided (e.g. ambient assisted living support at home [21]); iii) to substitute the nursing support by using technology (e.g. robot that measures vital signs prior to consultation) [22]; or iv) to support the training or education of nurses (e.g.…”

Section: Definitionsmentioning

confidence: 99%

Measuring the effectiveness of digital nursing technologies: development of a comprehensive digital nursing technology outcome framework based on a scoping review

Krick

¹

,

Hüter

²

,

Seibert

³

et al. 2020

BMC Health Serv Res

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Background: Digital nursing technologies (DNT) comprise an expanding, highly diverse field of research, explored using a wide variety of methods and tools. Study results are therefore difficult to compare, which raises the question how effectiveness of DNT can be adequately measured. Methods currently used might not be sufficient for certain specific nursing contexts. A comprehensive outcome framework that shows the multitude of possible outcome areas could be useful to generate more comparable results. The aim of the present study is to develop an outcome framework for DNT and to indicate which outcome areas have been most frequently evaluated in previous studies and how this has been done. Methods: We combined an inductive and deductive approach to develop the framework. The numerical analysis is based on a scoping review focussing on the effectiveness of DNT for persons in need of care, formal or informal caregivers or care institutions. Nine databases were included in the screening: Medline, Scopus, CINAHL, Cochrane Library, ACM Digital Library, IEEE Xplore, the Collection of Computer Science Bibliographies, GeroLit and CareLit. Additional literature searches and expert interviews were included. Results: The developed framework comprises four outcome target groups and 47 outcome areas. There are considerable differences in the researched outcome areas for the individual outcome target groups. Persons in need of care were by far the most frequently surveyed, particularly with respect to their psychological health. There are much fewer studies on formal and informal caregivers, and it is particularly noticeable that the quality of life of both groups has rarely been investigated. Care process quality was most frequently researched for organisations.

show abstract

“…decision support systems for guideline compliance [20]); ii) to contribute to the self-reliance of the person in need of care in such a way that direct on-site care assistance can be avoided (e.g. ambient assisted living support at home [21]); iii) to substitute the nursing support by using technology (e.g. robot that measures vital signs prior to consultation) [22]; or iv) to support the training or education of nurses (e.g.…”

Section: Definitionsmentioning

confidence: 99%

Measuring the effectiveness of digital nursing technologies: Development of a comprehensive digital nursing technology outcome framework based on a scoping review

Krick

¹

,

Hüter

²

,

Seibert

³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Digital nursing technologies (DNT) comprise an expanding, highly diverse field of research, explored using a wide variety of methods and tools. Study results are therefore difficult to compare, which raises the question how effectiveness of DNT can be adequately measured. Methods currently used might not be sufficient for certain specific nursing contexts. A comprehensive outcome framework that shows the multitude of possible outcome areas could be useful to generate more comparable results. The aim of the present study is to develop an outcome framework for DNT and to indicate which outcome areas have been most frequently evaluated in previous studies and how this has been done. Methods: We combined an inductive and deductive approach to develop the framework. The numerical analysis is based on a scoping review focussing on the effectiveness of DNT for persons in need of care, formal or informal caregivers or care institutions. Nine databases were included in the screening: Medline, Scopus, CINAHL, Cochrane Library, ACM Digital Library, IEEE Xplore, the Collection of Computer Science Bibliographies, GeroLit and CareLit. Additional literature searches and expert interviews were included. Results: The developed framework comprises four outcome target groups and 47 outcome areas. There are considerable differences in the researched outcome areas for the individual outcome target groups. Persons in need of care were by far the most frequently surveyed, particularly with respect to their psychological health. There are much fewer studies on formal and informal caregivers, and it is particularly noticeable that the quality of life of both groups has rarely been investigated. Care process quality was most frequently researched for organisations. Conclusion: We were able to provide a comprehensive DNT outcome framework, thereby identifying the outcome tools used and the less researched outcome areas. We recommend a detailed investigation of all areas and tools in future research projects with a view to initiating a discussion on the differing importance of existing outcome areas and on a standardisation of outcome tools. We also recommend the development of outcome areas for the macro level of effectiveness assessment. Keywords: Technology, Care, Nursing, Framework, Effectiveness, Effect, Digital, Outcome, Evidence

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The electronic, personalizable Rosetta system for dementia care: exploring the user-friendliness, usefulness and impact

Cited by 60 publications

References 36 publications

Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management

Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management

Measuring the effectiveness of digital nursing technologies: development of a comprehensive digital nursing technology outcome framework based on a scoping review

Measuring the effectiveness of digital nursing technologies: Development of a comprehensive digital nursing technology outcome framework based on a scoping review

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