Gesundheit (MDH)
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Despite the enormous number of assistive technologies (ATs) in dementia care, the management of challenging behavior (CB) of persons with dementia (PwD) by informal caregivers in home care is widely disregarded. The first-line strategy to manage CB is to support the understanding of the underlying causes of CB to formulate individualized nonpharmacological interventions. App- and sensor-based approaches combining multimodal sensors (actimetry and other modalities) and caregiver information are innovative ways to support the understanding of CB for family caregivers. The main aim of this study is to describe the design of a feasibility study consisting of an outcome and a process evaluation of a newly developed app- and sensor-based intervention to manage CB of PwD for family caregivers at home. In this feasibility study, we perform an outcome and a process evaluation with a pre-post descriptive design over an 8-week intervention period. The Medical Research Council framework guides the design of this feasibility study. The data on 20 dyads (primary caregiver and PwD) are gathered through standardized questionnaires, protocols, and log files as well as semistructured qualitative interviews. The outcome measures (neuropsychiatric inventory and Cohen-Mansfield agitation inventory) are analyzed by using descriptive statistics and statistical tests relevant to the individual assessments (eg, chi-square test and Wilcoxon signed-rank test). For the analysis of the process data, the Unified Theory of Acceptance and Use of Technology is used. Log files are analyzed by using descriptive statistics, protocols are analyzed by using documentary analysis, and semistructured interviews are analyzed deductively using content analysis. The newly developed app- and sensor-based AT has been developed and was evaluated until July in 2018. The recruitment of dyads started in September 2017 and was concluded in March 2018. The data collection was completed at the end of July 2018. This study presents the protocol of the first feasibility study to encompass an outcome and process evaluation to assess a complex app- and sensor-based AT combining multimodal actimetry sensors for informal caregivers to manage CB. The feasibility study will provide in-depth information about the study procedure and on how to optimize the design of the intervention and its delivery. DERR1-10.2196/11630
BACKGROUND Despite the enormous number of assistive technologies (ATs) in dementia care, the management of challenging behavior (CB) of persons with dementia (PwD) by informal caregivers in home care is widely disregarded. The first-line strategy to manage CB is to support the understanding of the underlying causes of CB to formulate individualized nonpharmacological interventions. App- and sensor-based approaches combining multimodal sensors (actimetry and other modalities) and caregiver information are innovative ways to support the understanding of CB for family caregivers. OBJECTIVE The main aim of this study is to describe the design of a feasibility study consisting of an outcome and a process evaluation of a newly developed app- and sensor-based intervention to manage CB of PwD for family caregivers at home. METHODS In this feasibility study, we perform an outcome and a process evaluation with a pre-post descriptive design over an 8-week intervention period. The Medical Research Council framework guides the design of this feasibility study. The data on 20 dyads (primary caregiver and PwD) are gathered through standardized questionnaires, protocols, and log files as well as semistructured qualitative interviews. The outcome measures (neuropsychiatric inventory and Cohen-Mansfield agitation inventory) are analyzed by using descriptive statistics and statistical tests relevant to the individual assessments (eg, chi-square test and Wilcoxon signed-rank test). For the analysis of the process data, the Unified Theory of Acceptance and Use of Technology is used. Log files are analyzed by using descriptive statistics, protocols are analyzed by using documentary analysis, and semistructured interviews are analyzed deductively using content analysis. RESULTS The newly developed app- and sensor-based AT has been developed and was evaluated until July in 2018. The recruitment of dyads started in September 2017 and was concluded in March 2018. The data collection was completed at the end of July 2018. CONCLUSIONS This study presents the protocol of the first feasibility study to encompass an outcome and process evaluation to assess a complex app- and sensor-based AT combining multimodal actimetry sensors for informal caregivers to manage CB. The feasibility study will provide in-depth information about the study procedure and on how to optimize the design of the intervention and its delivery. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/11630
Adhärenz digitaler Interventionen im Gesundheitswesen: Definitionen, Methoden und offene Fragen
(2021)
AbstractMany digital interventions rely on the participation of their users to have a positive impact. In various areas it can be observed that the use of digital interventions is often reduced or fully discontinued by the users after a short period of time. This is seen as one of the main factors that can limit the effectiveness of digital interventions. In this context, the concept of adherence to digital interventions is becoming increasingly important. Adherence to digital interventions is roughly defined as “the degree to which the user followed the program as it was designed,” which can also be paraphrased as “intended use” or “use as it is designed.” However, both the theoretical–conceptual and practical discussions regarding adherence to digital interventions still receive too little attention.The aim of this narrative review article is to shed more light on the concept of adherence to digital interventions and to distinguish it from related concepts. It also discusses the methods and metrics that can be used to operationalize adherence and the predictors that positively influence adherence. Finally, needs for action to better address adherence are considered critically.
Approaches to Improvement of Digital Health Literacy (eHL) in the Context of Person-Centered Care
(2022)
The skills, knowledge and resources to search for, find, understand, evaluate and apply health information is defined as health literacy (HL). If individuals want to use health information from the Internet, they need Digital Health Literacy (eHL), which in addition to HL also includes, for example, media literacy. If information cannot be found or understood by patients due to low (e)HL, patients will not have the opportunity to make informed decisions. In addition, many health apps for self-management or prevention also require (e)HL. Thus, it follows that active participation in healthcare, in terms of Person-Centered Care (PCC) is only possible through (e)HL. Currently, there is a great need to strengthen these competencies in society to achieve increased empowerment of patients and their health. However, at the same time, there is a need to train and improve competencies in the field of healthcare professionals so that they can counsel and guide patients. This article provides an overview with a focus on HL and eHL in healthcare, shows the opportunities to adapt services and describes the possible handling of patients with low (e)HL. In addition, the opportunities for patients and healthcare professionals to improve (e)HL are highlighted.
Sensor‐based assessment of challenging behaviors in dementia may be useful to support caregivers. Here, we investigated accelerometry as tool for identification and prediction of challenging behaviors. We set up a complex data recording study in two nursing homes with 17 persons in advanced stages of dementia. Study included four‐week observation of behaviors. In parallel, subjects wore sensors 24 h/7 d. Participants underwent neuropsychological assessment including MiniMental State Examination and Cohen‐Mansfield Agitation Inventory. We calculated the accelerometric motion score (AMS) from accelerometers. The AMS was associated with several types of agitated behaviors and could predict subject's Cohen‐Mansfield Agitation Inventory values. Beyond the mechanistic association between AMS and behavior on the group level, the AMS provided an added value for prediction of behaviors on an individual level. We confirm that accelerometry can provide relevant information about challenging behaviors. We extended previous studies by differentiating various types of agitated behaviors and applying long‐term measurements in a real‐world setting.
Contact-Tracing-Apps als unterstützende Maßnahme bei der Kontaktpersonennachverfolgung von COVID-19
(2020)
Die Kontaktpersonennachverfolgung ist derzeit eine der wirksamsten Maßnahmen zur Eindämmung der COVID-19 Pandemie. Digitales Contact Tracing mittels Smartphones scheint eine sinnvolle zusätzliche Maßnahme zur manuellen Kontaktpersonennachverfolgung zu sein, um Personen zu identifizieren, die nicht bekannt oder nicht erinnerlich sind und um den zeitlichen Verzug beim Melden eines Infektionsfalles und beim Benachrichtigen von Kontaktpersonen so gering wie möglich zu halten. Obwohl erste Modellierungsstudien eine positive Wirkung in Bezug auf eine zeitnahe Kontaktpersonennachverfolgung nahelegen, gibt es bislang keine empirisch belastbaren Daten, weder zum bevölkerungsweiten Nutzen noch zum potenziellen Schaden von Contact-Tracing-Apps. Die Beurteilung der Zweckerfüllung und eine wissenschaftliche interdisziplinäre Begleitforschung sowohl zur Wirksamkeit, Risiken und Nebenwirkungen als auch zu Implementierungsprozessen (z. B. Planung und Einbezug verschiedener Beteiligter) sind wesentliche Bestandteile einer Nutzen-Risiko Bewertung. Dieser Beitrag betrachtet daher den möglichen Public-Health-Nutzen sowie technische, soziale, rechtliche und ethische Aspekte einer Contact-Tracing-App zur Kontaktpersonennachverfolgung im Rahmen der COVID-19-Pandemie. Weiterhin werden Bedingungen für eine möglichst breite Nutzung der App aufgezeigt.
Die Reformagenda der sozialen Pflegeversicherung - Herausforderungen für Politik und Gesellschaft
(2015)
Abstract The development and application of digital interventions in health-related topics are gaining momentum in health service research. Digital interventions are often complex and need to be evaluated and implemented in complex settings. Due to their characteristics, this poses methodological challenges for health services research that have to be identified and addressed. Hence, the Working Group on Digital Health of the German Network for Health Services Research (DNVF) has prepared a discussion paper. This paper discusses methodological, practical and theoretical challenges associated with the development and evaluation of digital interventions from the perspective of health services research. Possible solutions are suggested and future research needs to address these methodological challenges are identified.
Abstract The methodological challenges of evaluating digital interventions (DI) for health services research are omnipresent. The Digital Health Working Group of the German Network for Health Services Research (DNVF) presented and discussed these challenges in a two-part discussion paper. The first part addressed challenges in definition, development and evaluation of DI. In this paper, which represents the second part, the definition of outcomes, reporting of results, synthesis of evidence, and implementation are addressed as methodological challenges of DI. Potential solutions are presented and the need to address these challenges in future research are discussed.