Although a high prevalence of olfactory dysfunction was found, no correlation was found between olfactory dysfunction and acute parameters of MTBI.
Aims To gain insight into how direct care staff in Dutch nursing homes experienced work during the COVID‐19 pandemic. Design A qualitative study consisting of semi‐structured, face‐to‐face focus groups was conducted using “the active dialogue approach”. Methods Participants ( n = 29) were care staff from four care teams at Dutch nursing homes. Teams were selected based on the number of COVID‐19 infections amongst residents. Data were analysed with conventional content analysis. Results Themes emerging from the data were the loss of (daily) working structure, interference between work and private life for direct care staff, the importance of social support by the team and a leader, and the effects on relationship‐centred care of the measures. Results offer concrete implications for similar situations in the future: psychological support on‐site; autonomy in daily work of care staff; an active role of a manger on the work floor and the importance of relationship‐centred care.
This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmerc ial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Background As long-term care continues to change, the traditional way of learning for work purposes is no longer sufficient. Long-term care organisations need to become ‘learning organisations’ and facilitate workplace learning for nursing staff teams. Therefore, insight is needed into what conditions are important for establishing workplace learning. The aim and objective of this article is to gain insight into necessary individual, team and organisational conditions for nursing staff to enhance workplace learning in long-term care settings. Methods This study is a qualitative explorative study. A World Café method was used to host group dialogues in which participants (n = 42) discussed certain questions. Group dialogues were held for the nursing home and community care setting separately due to organisational differences. Nursing staff, experts in workplace learning, educational staff, client representatives and experts in the field of work and organisation in healthcare organisations were invited to a Dutch long-term care organisation to discuss questions of interest. Data were analysed using theme-based content analysis. Results Overall themes concerning individual, team and organisational conditions for workplace learning included: facilitating characteristics (e.g. to be given time and room for [team] development); behavioural characteristics (e.g. an open attitude); context and culture (e.g. feeling safe); cooperation and communication (e.g. giving/receiving feedback); and knowledge and skills (e.g. acquiring knowledge from each other). No major differences were found between settings. Conclusions By assessing the themes at the individual, team and organisational level regarding nursing staff, the current workplace learning situation, and its possible improvements, can be detected.
PurposeThe 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.DesignA cross-sectional mixed-methods study in which qualitative data were collected with the narrative quality assessment method Connecting Conversations and interpreted for analysis.MethodsConnecting 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.FindingsA 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).ConclusionsNarrative 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.
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