Background: Integrating artificial intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insufficient engagement with well-documented sociotechnical pitfalls. Readiness models offer a systematic way to evaluate project preparedness and to build the capabilities needed for successful artificial intelligence in nursing care (AINC) research, development, and implementation. As of yet, an evidence-based AI readiness assessment prioritizing AINC projects and accounting for their diversity in care settings is missing. Objective: This study aimed to develop a comprehensive artificial intelligence nursing care readiness assessment (AINCRA) to support planning, execution, and evaluation of AINC projects. Methods: In a sequential exploratory multimethods bottom-up approach to maturity model development, key AI readiness dimensions and attributes were identified to develop a pilot readiness assessment. The pilot version was grounded on insights from an expert workshop (n=21) and expert interviews (n=14), an online survey (n=53), a rapid review (n=292), and a nominal group consensus process. A systematic literature review (n=7) further triangulated AI readiness attributes. Finally, a think-aloud interview study and focus group discussions involving experts (n=18) from nursing practice, nursing science, and AI research and development who had conducted AINC projects prior to data collection validated the attributes. Results: The resulting AINCRA encompasses 5 core dimensions: regulatory, processual, technical, social, ethical, and community building requirements and aspects. Including 69 attributes and capabilities of AI nursing care readiness, the core dimensions reflect key areas of action where AINC project stakeholders can influence project outcomes. Clinical partners can assess their organization's maturity level in relation to the implementation of AI. An assessment of each dimension and its attributes across 5 maturity levels allows reflecting on and proactively shaping individual project approaches. Overall, experts regarded AINCRA as a useful instrument for the development, management, and evaluation of AINC projects while emphasizing that established principles of good practice in project and data management should not be neglected when using AINCRA as a project management tool. Conclusions: AINCRA enables practitioners from AI research and development, clinical partners, and nursing and health scientists to plan, evaluate, and enhance AI projects across their lifecycle, thereby supporting effective AI integration in nursing care. While AINCRA was developed within the European and German legal framework for AI in health care settings, respective attributes can be adapted to international requirements.

Integrating Artificial Intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insufficient engagement with well-documented socio-technical pitfalls. Readiness models offer a systematic way to evaluate project preparedness and to build the capabilities needed for successful AI in nursing care (AINC) research, development and implementation. A novel AI Nursing Care Readiness Assessment (AINCRA) tool was designed to support planning, execution, and evaluation of AINC projects. A sequential exploratory mixed-methods bottom-up approach to maturity model development identified key AI readiness dimensions and attributes. The initial AINCRA version is grounded on insights from expert workshops, an online survey, and a nominal group consensus process. A systematic literature review further triangulated AI readiness attributes. Lastly, a think aloud interview study and focus group discussions involving experts from diverse disciplines validated the attributes. The resulting AINCRA encompasses five core dimensions: regulatory, processual, technical, social and ethical, and community building requirements and aspects. Across five maturity levels, 69 AINC readiness attributes enable practitioners from AI research and development, clinical partners and nursing and health scientists to plan, evaluate and enhance AI projects across their lifecycle, thereby supporting effective AI integration in nursing care. not applicable

BACKGROUND:Urinary incontinence affects 5% to 35% of the older adult population. Untreated urinary incontinence is associated with reduced quality of life, amongst others. Pelvic floor muscle training is the first-line treatment. Existing evidence on the proportion of physiotherapy care remains limited, particularly regarding men with urinary incontinence, and insufficiently accounts for care situation- or age-specific disparities. This study investigated the proportion of physiotherapy care, differentiated by age, sex, care situation, informal provider networks, and temporal trends, to address these evidence gaps. METHOD:We analysed health insurance fund claims data covering a period of 9 years (2008-2016), from up to 6,433,070 individuals aged 65+, and applied a network approach to identify patient sharing networks. We calculated the proportion of physiotherapy care on a quarterly basis. RESULTS:The proportion of physiotherapy care remained relatively stable over time. In the first quarter of 2016, it was 10.5% for people with incident urinary incontinence in total, 7.9% for those without care, 11.9% for people with home care, and 14.0% for nursing home residents. The lowest proportion of physiotherapy care (3.5%) was found among men with incident urinary incontinence in the 85 to 89 age group receiving no care, and the highest proportion (19.3%) among women with incident urinary incontinence in the age group 70 to 74 years living in a nursing home. The variation in the proportion of physiotherapy care between patient sharing networks was the highest for women and men in nursing homes (SD 9.7% and 9.2%, respectively). CONCLUSIONS:These findings indicate a systematic underuse of physiotherapy services for both sexes across all age groups and care situations. Older men without care needs are particularly at risk for underuse.

Assessment tools for engagement in people with dementia often rely on self-reported measures which restricts their use in people with severe cognitive limitations. The Engagement of a Person with Dementia Scale (EPWDS) is a valid and reliable tool to assess behavioral and emotional expressions and responses of engagement in people with dementia through observation; however, the EPWDS is not yet available in the German language. 1) Translation and cross-culturally adaptation of the original English version of the EPWDS into the German language (EPWDS-GER) and 2) to gain insights into assessing data with the newly developed instrument. International recommendations were followed to cross-culturally adapt the English original version of the EPWDS into the German language in 5 steps: translation by three independent translators, synthesis, back translation, expert committee review (N = 10) and test of the prefinal version in nursing practice (N = 22) on a 5-point Likert scale to assess comprehensibility, practicability and suitability of the EPWDS-GER. The EPWDS-GER achieved high ratings for the five subscales on ease of understanding, ease of answering and importance of single items for assessing engagement. Average agreement for all items ranged from 3.86 to 4.43 (SD = 0.68–1.29). Overall rating of EPWDS-GER resulted in a mean agreement of 4.18 (SD = 0.73) for suitability and of 4.09 (SD = 0.81) for practicability. The EPWDS-GER is an easy to use tool for measuring behavioral and emotional expressions and responses of engagement of a person with dementia and can now be utilized in clinical practice and research.

Robotic manipulators can interact with large, heavy objects through whole-arm manipulation. Combined with direct physical interaction between humans and robots, the patient can be anchored in care. However, the complexity of this scenario requires control by a caregiver. We are investigating how such a complex form of manipulation can be controlled by nurses and whether the use of such a system creates physical relief. The use case chosen was washing the back of a patient in the lateral position. The operability of the remote control from the tele-nurse’s point of view, the change in the posture of the nurse on site, the execution times, the evaluation of the cooperation between human and robot, and the evaluation of the system from the nurse’s point of view and from the patient’s point of view were evaluated. The results show that the posture of the worker improved by 11.93% on average, and by a maximum of 26.13%. Ease of use is rated as marginally high. The manipulator is considered helpful. The study shows that remote whole-arm manipulation can anchor bedridden patients in the lateral position and that this system can be operated by nurses and leads to an improvement in working posture.

Introduction During the COVID-19 pandemic, people in need of long-term care were among the most vulnerable population groups. Home-care services were under exceptional strain, especially at the beginning of the pandemic. The aim of this study is to examine the situation and problems of care services and the people in need of care during the first two waves of the pandemic in Germany.Methods Two cross-sectional studies were conducted during the first two COVID-19 waves (first survey 28 April to 12 May 2020, second survey 12 January to 7 February 2021). In total, data from N = 1029 outpatient care services were included in the analysis. Descriptive measures were used for the analysis.Results The clients of home-care services were severely burdened in the first two waves of the pandemic. This can be seen on the one hand in an increased risk of illness and increased mortality, and on the other in the loss of various care and support services. The latter also has negative effects on the psychosocial condition of those in need of care, for example. Care services were affected by high staff absenteeism and additional work due to protective measures.Discussion The COVID-19 pandemic led to immense burdens for people in need of care and home-care services and to a reduction in care services. The deterioration of care provision met with an already tense situation. It has become clear that the provision of care for those in need of care by outpatient care services is not crisis-proof, and that additional challenges such as a pandemic can have dramatic consequences. For the future, reliable structures and readily available emergency plans should be established with concrete instructions for action.

Background and aim While artificial intelligence (AI) is being adapted for various life domains and applications related to medicine and healthcare, the use of AI in nursing practice is still scarce. The German Ministry for Education and Research funded a study in order to explore needs, application scenarios, requirements, facilitators and barriers for research and development projects in the context of AI in nursing care. Method A sequential explorative mixed methods study including a stakeholder and expert workshop ( N = 21), expert interviews ( N = 14), an online survey ( N = 53) and a Datathon ( N = 80) was conducted with an emphasis on qualitative data. Results Needs and application scenarios encompassed the micro- and meso-level of care and derived from typical phenomena inherent to nursing care as well as from skill- and staff mix and consequences arising from staff shortages, from the extend of informal care and an associated need for information and education of informal caregivers and nursing assistants. Requirements for and characteristics of successful research and development projects included regulatory, processual, technological, ethical and legal aspects and supportive eco-systems. Conclusion A key element in the design of research projects remains participatory and demand-driven development that aims to bring AI solutions out of the lab and into practice. However, influencing factors remain that are outside the sphere of influence of individual projects, in particular the creation of resilient legal foundations for data use and the use of AI in practice, standardization of data structures and the establishment of infrastructures for data exchange across institutions and projects.

BACKGROUND:The consequences of the COVID-19 pandemic have posed major challenges to different groups. One of these are informal caregivers. This study investigates the changes the pandemic has caused for informal caregivers and the extent to which quality of life and burden of care have changed for specific subgroups. METHODS:Data for this cross-sectional study was gathered in the summer of 2020 in a convenient sample of informal caregivers (< 67 years of age, N = 1143). In addition to sociodemographic data, information on the care situation, compatibility of care and work, as well as stress and quality of life was collected in an online survey. The analysis of care situations and compatibility of care and work is done descriptively. Logistic regression models are used for a subgroup analysis of quality of life and care burden. RESULTS:The care situation has changed for 54.7% of participants and has become more time consuming. For 70.8% of respondents, the COVID-19 pandemic has made it even more difficult to balance care-giving and work. However, most respondents were satisfied with their employers' pandemic management (65.9%). A sharp decline in the quality of life and an increase in the burden of care for informal caregivers was ascertained. Both developments are stronger for young and female caregivers and for those caring for people with a greater need of support. DISCUSSION:The results indicate that living situations worsened for a substantial proportion of informal caregivers during the COVID-19 pandemic. Policymakers should recognize additional challenges that informal caregivers have faced since the outbreak of the COVID-19 pandemic and how they vary by subgroups. It is important to include home-based informal care as well as other care settings in future pandemic concepts.

Zusammenfassung Hintergrund Die Folgen der COVID-19-Pandemie haben verschiedene Personengruppen vor große Herausforderungen gestellt; eine dieser Gruppen sind pflegende Angehörige. Die vorliegende Studie untersucht, welche Veränderungen die Pandemie für pflegende Angehörige mit sich gebracht hat und in welchem Ausmaß sich Lebensqualität und Pflegebelastung subgruppenspezifisch verändert haben. Methode Die Datenerhebung erfolgte im Sommer 2020 in einer Querschnittsstudie mit pflegenden Angehörigen im erwerbsfähigen Alter ( N = 1143). Neben soziodemografischen Daten wurden Angaben zu Versorgungssituation, Vereinbarkeit von Pflege und Beruf sowie Belastung und Lebensqualität in einer Onlinebefragung erhoben. Versorgungssituation und Vereinbarkeit von Pflege und Beruf wurden deskriptiv analysiert. Für die Analysen der Veränderung der Lebensqualität und der Belastung wurden logistische Regressionsmodelle verwendet. Ergebnisse Die Versorgungssituation hat sich für viele Befragte (54,7 %) während der Pandemie geändert und ist zeitlich aufwendiger geworden. Für 70,8 % ist die Vereinbarkeit von Pflege und Beruf schwieriger geworden. Mit dem Pandemiemanagement der eigenen Arbeitgeber:innen zeigt sich die Mehrheit zufrieden (65,9 %). Die Lebensqualität hat ab- und die Belastung zugenommen, besonders deutlich für jüngere Pflegende, Frauen und Pflegende von Personen mit hohem Pflegebedarf. Diskussion Die Ergebnisse weisen darauf hin, dass sich die Lebenssituationen pflegender Angehöriger während der COVID-19-Pandemie verschlechtert haben. Entscheidungsträger:innen sollten dies anerkennen und besonders betroffene Subgruppen pflegender Angehöriger unterstützen. Zukünftig ist es wichtig, die informelle häusliche Pflege ebenso wie Versorgungssettings der professionellen (Langzeit‑)Pflege in gesundheits- und sozialpolitische Pandemiekonzepte einzubeziehen.

The COVID-19 pandemic constitutes an exceptional risk to people living and working in nursing homes (NHs). There were numerous cases and deaths among NH residents, especially at the beginning of the pandemic when no vaccines had yet been developed. Besides regional differences, individual NHs showed vast differences in the number of cases and deaths: while in some, nobody was affected, in others, many people were infected or died. We examine the relationship between facility structures and their effect on infections and deaths of NH residents and infections of staff, while considering the influence of COVID-19 prevalence among the general population on the incidence of infection in NHs. Two nationwide German surveys were conducted during the first and second pandemic waves, comprising responses from n = 1067 NHs. Different hurdle models, with an assumed Bernoulli distribution for zero density and a negative binomial distribution for the count density, were fitted. It can be shown that the probability of an outbreak, and the number of cases/deaths among residents and staff, increased with an increasing number of staff and the general spread of the virus. Therefore, reverse isolation of NH residents was an inadequate form of protection, especially at the beginning of the pandemic.

Abstract Background Digital technologies are seen as helping to support and improve social interaction and participation of people in need of long-term care. This review aims to synthesize types of digital technologies used in nursing homes worldwide and their effects as reported by residents and staff members. In addition, inhibiting and facilitating factors in the use of these technologies are identified and potential for development is described. Methods A systematic literature review was conducted in April 2022 in the databases PubMed, CINAHL, IEEEXplore and ACM Digital Library from inception onwards for publications written in German or English language. Quantitative and qualitative studies were considered. The studies were selected by two independent reviewers according to predefined criteria. For critical appraisal, the RoB 2 tool was used for RCTs and a level of evidence rating for other studies. Results Of 6212 articles found, 24 studies were included. Different digital technologies were identified. The digital technologies most frequently examined in the included studies were mixed technologies, Information and communication technologies, Robotic pets and Virtual Reality. Two out of three included randomized controlled trails showed positive effects on the social participation of the residents, even if for one of them serious concerns on the risk of bias became visible. Thus, only for one technology, i.e. Paro, positive effects could be shown in an evaluation study with high level of evidence. Lack of infrastructure, high costs, ethical concerns, lack of training and user-unfriendly design were cited as inhibiting factors in the included studies. Conclusion: None of the included studies operationalized ‘social participation’ as a direct construct to measure effects. Instead, constructs of ‘loneliness’ or ‘social isolation’ are often used in the existing studies. Though respective technologies are attributed a high potential, there is no high-level evidence that digital technologies can promote social participation of nursing home residents (yet). Further research with high level of evidence is needed to access the constantly growing body of digital technologies and their impact on social participation. In the future, implementation and use of technologies, guidelines and policies for ethical use should be considered.

Zusammenfassung Einleitung In der COVID-19-Pandemie zählen Pflegebedürftige zu den besonders vulnerablen Bevölkerungsgruppen. Ambulante Pflegedienste befanden sich gerade zu Beginn der Pandemie in einer Ausnahmesituation. In dieser Arbeit sollen die Situation und die Probleme der Pflegedienste und der versorgten Pflegebedürftigen in den ersten beiden Wellen der Pandemie in Deutschland untersucht werden. Methoden Während der ersten beiden COVID-19-Wellen wurden zwei Querschnittstudien durchgeführt (erste Befragung: 28.04.–12.05.2020, zweite Befragung: 12.01.–07.02.2021). Insgesamt wurden Daten aus N = 1029 ambulanten Pflegediensten in die Analyse einbezogen. Die Analyse erfolgte anhand deskriptiver Maßzahlen. Ergebnisse Die Klient:innen von Pflegediensten waren in den ersten beiden Wellen der Pandemie stark belastet. Dies zeigt sich einerseits an einem erhöhten Erkrankungsrisiko und einer erhöhten Mortalität und andererseits am Wegfall verschiedener Versorgungs- und Unterstützungsangebote. Letzteres hat z. B. auch negative Auswirkungen auf die psychosoziale Verfassung der Pflegebedürftigen. Die Pflegedienste waren von hohen Personalausfällen und zusätzlicher Arbeit durch Schutzmaßnahmen betroffen. Diskussion Die COVID-19-Pandemie führte zu großen Belastungen von Pflegebedürftigen und ambulanten Pflegediensten und zu einer Reduzierung der Versorgungsangebote. Die Verschlechterung der Versorgung traf auf eine bereits angespannte Situation. Es zeigt sich, dass die Versorgung Pflegebedürftiger durch ambulante Pflegedienste nicht krisensicher gestaltet ist und dass zusätzliche Herausforderungen wie die einer Pandemie dramatische Folgen haben können. Zukünftig sollte es verlässliche Strukturen und schnell verfügbare Notfallpläne mit konkreten Handlungsanweisungen geben.

Kleinräumige Wohnformen für Pflegebedürftige verbreiteten sich in den letzten Jahren mehr und mehr. Forschung zu der Frage, ob diese Wohnformen im Vergleich zum Pflegeheim Vorteile aufweisen, ist darum wichtig. Internationale Studienergebnisse aus den letzten fünf Jahren weisen auf einen positiven Einfluss kleinräumiger Wohnformen auf die pflegerische Versorgungsqualität, soziale Teilhabe und Interaktion vor allem für Menschen mit Demenz hin. Wie stark sich diese Effekte auch in Wohnformen in Deutschland zeigen, ist weiter zu untersuchen. Das Wissen über diese Effekte kann dazu beitragen, dass Pflegekräfte etwa bei Beratungsanlässen eine gute Passung zwischen pflegebedürftiger Person und (Wohn-)Umwelt unterstützen.

Objective To determine predictors of admission to nursing home by means of secondary data analysis of German statutory health insurance claims data and care needs assessments. Materials and methods A retrospective longitudinal analysis was conducted covering the period 2006-2016 and using routine data. Health insurance data and care needs assessment data for people who became care dependent in 2006 and who lived in their own homes were merged. Cox regression analyses were conducted to identify predictors of admission to a nursing home. Results The study population comprised 48,892 persons. Dementia, cancer of the brain, cognitive impairment, antipsychotics prescriptions, hospitalized fractures, hospital stays over ten days, and higher age had the highest hazard ratios among the predictors. Conclusions Knowledge about the predictors serves to sensitize health care professionals in the care of people in need of care. It facilitates identification of care needs in community-dwelling persons at an increased risk of admission to a nursing home.