Katya Sion

Loneliness is a growing concern in long‐duration immersive services, where consumers not only transition into the service but also experience multiple identity transitions and life events while in the service. We argue that loneliness in these settings emerges not only as a chronic experience from a lack of social opportunities, but also episodically from difficulty navigating social landscapes after a life change. Drawing on consumer agency as a differentiating factor between aloneness and loneliness, we reconceptualize onboarding as a dynamic, multi‐actor process through which providers and co‐consumers restore agency and address loneliness throughout the service experience. Using qualitative evidence from retirement villages and residential aged care, we examine the onboarding structures supporting agency within these later‐life immersive services. Onboarding unfolds in three phases, the third of which returns as a cycle: pre‐service experience, initial transition, and cycles of integration and transition. These phases involve distinct social support types (action‐facilitating and nurturant) delivered by individual, vertical (organizational), and horizontal (co‐consumer) actors. Crucially, changes in consumer context create a need for re‐onboarding to foster agency and mitigate loneliness. Comparing the two service settings reveals onboarding stages require different actors, sequencing, and intensity depending on entry conditions. We contribute a dynamic, agency‐centered conceptualization of onboarding and provide guidance for resource allocation to mitigate loneliness risk.

Het Generiek Kompas geeft ouderenzorgorganisaties ruimte om kwaliteit zichtbaar te maken met cijfers en verhalen in een jaarlijks openbaar kwaliteitsbeeld. Het onderzoek laat zien dat de kwaliteitsbeelden in 2025 vergelijkbaar zijn met die van 2024 en nog beperkt inzicht bieden in hoe zorgorganisaties kwaliteitsinformatie gebruiken om te leren, te reflecteren en te ontwikkelen.

Background: The use of data to support decision-making and primary processes is central to establishing data-informed care. Yet, data remain underutilized for quality improvement in long-term care (LTC). Data maturity reflects an organization’s capability to use data, for example, to guide strategic objectives. Objective: This study aimed to assess the data maturity of LTC organizations and evaluate the opinions and ideas of different stakeholders (eg, client representatives, care professionals, and data and IT specialists) within these organizations regarding their data maturity. Methods: An exploratory mixed methods study was conducted in 3 Dutch LTC organizations. Quantitative data were collected using a 7-domain data maturity assessment comprising 77 items with 3 response options (applicable, not applicable, or in progress), which was completed through consensus-based scoring. Each organization established an interprofessional community of practice (CoP), consisting of 5 to 6 purposively recruited stakeholders representing care professionals, managers, client representatives, IT and data specialists, and researchers. Qualitative data were collected through consensus meetings with the same CoP stakeholders to elaborate on and contextualize their data maturity assessments. Quantitative data were analyzed descriptively, while qualitative data were analyzed using hybrid thematic analysis. Results: Findings highlighted that LTC organizations currently operate at a low data maturity level. Domains regarding strategy, governance, and data quality were low yet consistent across organizations, whereas variability and substantial gaps were mainly present in the domain regarding leadership and culture. The consensus meetings with 15 stakeholders in the CoPs (mean age 43, SD 11 y; mean organizational work experience 10, SD 9 y) identified 4 overarching themes: (1) the absence of a clear vision for data-informed care reflects low data maturity, (2) a data culture is a prerequisite for continuous learning and improvement, (3) innovation and transformation are constrained by limited interdisciplinary engagement and ineffective communication, and (4) sustainable data use is hindered by infrastructural capacity and cultural readiness. Conclusions: This study contributes to the limited evidence on data maturity in LTC, revealing generally low levels of data maturity across organizations. Advancing data-informed care requires integrated strategies that align technical, cultural, and interprofessional conditions. Future research should adopt longitudinal designs and broader stakeholder involvement to strengthen data-informed care in LTC.

Background: In long-term care (LTC) for older adults, data on client, employee, and organization levels are collected in various ways, covering quality of care, life, and work. There is, however, a lack of understanding of how to introduce data-informed care in LTC and thus create value from data. Objective: This study aims to investigate the experiences and perceptions of various stakeholders in LTC regarding data and data-informed care. Methods: A qualitative study using the World Café cocreation technique was conducted with a diverse group of LTC stakeholders. Four questions were addressed: (1) What thoughts do you have when you hear the term “data” in relation to LTC? (2) What purposes do data have (in the future) in LTC? (3) What knowledge and skills are needed to enable data-informed care? (4) How can data contribute to and improve multidisciplinary learning? Stakeholders’ notes and the plenary summary were analyzed using conventional content analysis. Results: Stakeholders included nurses, members of client councils, data specialists, researchers, and managers (N=20; mean age 50, SD 13 years). Five themes were identified: (1) despite uncertainty, the benefits of using data outweigh the associated risks; (2) the lack of accessibility and uniformity hinders integrating data-informed care; (3) human resources and finance departments pioneer data usage; however, potential lies in clinical decision-making; (4) data-informed care demands individual, collective, and organizational prerequisites; and (5) multidisciplinary collaboration enriches collective knowledge regarding data. Conclusions: Introducing data-informed care requires enhancing data literacy of health care professionals, establishing clear communication about the role of data within the organization, and introducing new job positions, such as data scientists. Data-informed care was considered a multidisciplinary approach in which data have a supportive role to enhance collective understanding and are considered crucial for improving quality of care.

Het Generiek Kompas markeert een koerswijziging in het kijken naar kwaliteit van de ouderenzorg, met 2024 als transitiejaar. Zorgorganisaties krijgen ruimte om zelf te bepalen hoe zij kwaliteit inzichtelijk maken, met nadruk op zowel cijfers (tellen) als verhalen (vertellen). Jaarlijks publiceren zij verplicht een openbaar kwaliteitsbeeld, waarin zij transparant en reflectief rapporteren. In maart 2025 verschenen deze kwaliteitsbeelden voor het eerst. Dit rapport geeft een eerste weergave van de vorm, inhoud, zichtbaarheid van leren en ontwikkelen, en de balans tussen cijfers en verhalen van 20 kwaliteitsbeelden.

Background: Providing and improving relationship-centered care has gained increased importance in long-term care. However, quality improvement strategies are predominantly based on quantitative quality measures for care professionals. Therefore, the aim of this study was to explore how narrative data collected with Connecting Conversations is used in evaluation meetings to improve RCC. Methods: A qualitative approach using structured observations was used. The participants were care professionals, residents and family members from two nursing home wards. The participating wards organized evaluation meetings to discuss the experienced quality of care based on narrative data collected with Connecting Conversations. To analyze the process of improving RCC, the organization of these meetings and the content were observed by independent researchers, and detailed notes were taken. The data were analyzed thematically by using conventional content analysis. Results: In total, three evaluation meetings were organized. Primarily, care professionals were invited to discuss the results of the interviews. One ward organized a meeting for care professionals, residents and family members, and the other decided not to invite them. The discussion of themes related to experienced quality of care within the evaluation meetings was less profound than during the interviews. In total, 12 overarching themes concerning experienced quality of care were discussed in the Connecting Conversations' interviews. Nine themes were also mentioned in one or more evaluation meetings (i.e., activities for residents, personalized attention and preferences of residents, feeling at home and communication within the care triad). Conclusion: When using narrative data on quality of care to improve relationship-centered care, the full potential of narrative data is underutilized as discussions focussed on incidental problem solving rather than deeper reflections on the meaning of events in providing relationship-centered care. Establishing trust within the care triad of care professionals, family members, and residents is essential to improve relationship-centered care collaboratively.

The purpose of this research is to examine the role of anticipation as a source of well-being in extended service contexts involving constraints on one’s agency (e.g. aged care). In these service contexts, consumers have limited ownership over their time usage and foci of anticipation, which affects their well-being. Semi-structured interviews (n = 35) were conducted with members of the aged care ecosystem (residents, family and staff). Two separate aged care service models were investigated as they typically reflect different levels of agency/constraint: retirement villages and residential aged care facilities. Results indicate that the subjective passage of time is influenced by one’s foci of anticipation. Having regular foci of anticipation both at a micro- and macro-level can generate well-being benefits for recipients. The importance of restabilization and building positive curves to counteract potential negative implications was identified. This research is the first service study to investigate the concept of anticipation and subjective time perception as key components of one’s well-being in extended service encounters. We propose a novel conceptual model that combines micro- and macro-level foci into an iterative package to mitigate the after-effects of anticipation. We also demonstrate how Sustainable Development Goal 3 (SDG3) (good health for well-being) can be addressed through service research.

It is important to evaluate how residents, their significant others, and professional caregivers experience life in a nursing home to improve quality of care based on their needs and wishes. Narratives are a promising method to assess this experienced quality of care as they enable a rich understanding, reflection, and learning. In the Netherlands, narratives are becoming a more substantial element within the quality improvement cycle of nursing homes. The added value of using narrative methods is that they provide space to share experiences, identify dilemmas in care provision, and provide rich information for quality improvements. The use of narratives in practice, however, can also be challenging as this requires effective guidance on how to learn from this data, incorporation of the narrative method in the organizational structure, and national recognition that narrative data can also be used for accountability. In this article, 5 Dutch research institutes reflect on the importance, value, and challenges of using narratives in nursing homes.

Objectives: In nursing homes, narrative data are collected to evaluate quality of care as perceived by residents or their family members. This results in a large amount of textual data. However, as the volume of data increases, it becomes beyond the capability of humans to analyze it. This study aims to explore the usefulness of text mining approaches regarding narrative data gathered in a nursing home setting. Design: Exploratory study showing a variety of text mining approaches. Setting and participants: Data has been collected as part of the project ‘Connecting Conversations’: assessing experienced quality of care by conducting individual interviews with residents of nursing homes (n = 39), family members (n = 37) and care professionals (n = 49). Methods: Several pre-processing steps were applied. A variety of text mining analyses were conducted: individual word frequencies, bigram frequencies, a correlation analysis and a sentiment analysis. A survey was conducted to establish a sentiment analysis model tailored to text collected in long-term care for older adults. Results: Residents, family members and care professionals uttered respectively 285, 362 and 549 words per interview. Word frequency analysis showed that words that occurred most frequently in the interviews are often positive. Despite some differences in word usage, correlation analysis displayed that similar words are used by all three groups to describe quality of care. Most interviews displayed a neutral sentiment. Care professionals expressed a more diverse sentiment compared to residents and family members. A topic clustering analysis showed a total of 12 topics including ‘relations’ and ‘care environment’. Conclusions and implications: This study demonstrates the usefulness of text mining to extend our knowledge regarding quality of care in a nursing home setting. With the rise of textual (narrative) data, text mining can lead to valuable new insights for long-term care for older adults.

Purpose The use of qualitative data to assess quality of care in nursing homes from the resident’s perspective has shown to be valuable, yet more research is needed to determine how this data can be used to gain insight into the quality of care within nursing homes. Whereas it is crucial to stay close to the stories that are the strength of qualitative data, an intermittent step to classify this data can support the interpretation and use. Therefore, this study introduces an approach that enables the use of narrative quality of care data to learn from and improve with. Design A cross-sectional mixed-methods study in which qualitative data were collected with the narrative quality assessment method Connecting Conversations and interpreted for analysis. Methods Connecting Conversations was used to collect narrative data about experienced quality of care in nursing homes according to residents, their families and nursing staff (triads). Data analysis consisted of coding positive/negative valences in each transcript. Findings A stepwise approach can support the use of narrative quality data consisting of four steps: (1) perform and transcribe the conversations (listen); (2) calculate a valence sore, defined as the mean %-positive within a triad (look); (3) calculate an agreement score, defined as the level of agreement between resident-family-nursing staff (link); and (4) plot scores into a graph for interpretation and learning purposes with agreement score (x-axis) and valence score (y-axis) (learn). Conclusions Narrative quality data can be interpreted as a valence and agreement score. These scores need to be related to the raw qualitative data to gain a rich understanding of what is going well and what needs to be improved.