Introduction: Losing items is a time-consuming occurrence in nursing homes that is ill described. An explorative study was conducted to investigate which items got lost by nursing home residents, and how this affects the residents and family caregivers. Method: Semi-structured interviews and card sorting tasks were conducted with 12 residents with early-stage dementia and 12 family caregivers. Thematic analysis was applied to the outcomes of the sessions. Results: The participants stated that numerous personal items and assistive devices get lost in the nursing home environment, which had various emotional, practical, and financial implications. Significant amounts of time are spent on trying to find items, varying from 1 hr up to a couple of weeks. Numerous potential solutions were identified by the interviewees. Discussion: Losing items often goes together with limitations to the participation of residents. Many family caregivers are reluctant to replace lost items, as these items may get lost again.
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Digitalization enables public organizations to personalize their services, tuning them to the specific situation, abilities, and preferences of the citizens. At the same time, digital services can be experienced as being less personal than face-to-face contact by citizens. The large existing volume of academic literature on personalization mainly represents the service provider perspective. In contrast, in this paper we investigate what makes citizens experience a service as personal. The result are eight dimensions that capture the full range of individual experiences and expectations that citizens expressed in focus groups. These dimensions can serve as a framework for public sector organizations to explore the expectations of citizens of their own services and identify the areas in which they can improve the personal experiences they offer.
MULTIFILE
BACKGROUND: The FI-35 is a valid multidimensional Chinese frailty assessment instrument. Like other scales, functional measures rely on the information the total score provides. Our research aimed to analyze the contribution of each item.METHODS: Descriptive statistics were used to summarize the sample characteristics. The expected item score (EIS) was used to determine how the items contribute to the generic measure of frailty.RESULTS: This study showed that most of the EIS curves increased across the entire range of frailty levels, and most of the items discriminate relatively well over the entire frailty range. Items differentially contributed to the total frailty score and differentially discriminated between frailty levels.CONCLUSIONS: Although nearly all items monotonically increased with frailty levels, there were large differences between items in their ability to differentiate between persons being either weakly, moderately or highly frail.
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