Purpose: To describe nurses' support interventions for medication adherence, and patients' experiences and desired improvements with this care. Patients and methods: A two-phase study was performed, including an analysis of questionnaire data and conducted interviews with members of the care panel of the Netherlands Patients Federation. The questionnaire assessed 14 types of interventions, satisfaction (score 0-10) with received interventions, needs, experiences, and desired improvements in nurses' support. Interviews further explored experiences and improvements. Data were analyzed using descriptive statistics and a thematic analysis approach. Results: Fifty-nine participants completed the questionnaire, and 14 of the 59 participants were interviewed. The satisfaction score for interventions was 7.9 (IQR 7-9). The most common interventions were: "noticing when I don't take medication as prescribed" (n = 35), "helping me to find solutions to overcome problems with using medications" (n = 32), "helping me with taking medication" (n = 32), and "explaining the importance of taking medication at the right moment" (n = 32). Fifteen participants missed ≥1 of the 14 interventions. Most mentioned the following: "regularly asking about potential problems with medication use" (33%), "regularly discussing whether using medication is going well" (29%), and "explaining the importance of taking medication at the right moment" (27%). Twenty-two participants experienced the following as positive: improved self-management of adequate medication taking, a professional patient-nurse relationship to discuss adherence problems, and nurses' proactive attitude to arrange practical support for medication use. Thirteen patients experienced the following as negative: insufficient timing of home visits, rushed appearance of nurses, and insufficient expertise about side effects and taking medication. Suggested improvements included performing home visits on time, more time for providing support in medication use, and more expertise about side effects and administering medication. Conclusion: Overall, participants were satisfied, and few participants wanted more interventions. Nurses' support improved participants' self-management of medication taking and enabled patients to discuss their adherence problems. Adequately timed home visits, more time for support, and accurate medication-related knowledge are desired.
BACKGROUND: Patients are increasingly expected to take an active role in their own care. Participation in nursing documentation can support patients to take this active role since it provides opportunities to express care needs and preferences. Yet, patient participation in electronic nursing documentation is not self-evident.OBJECTIVE: To explore how home-care patients perceive their participation in electronic nursing documentation.METHODS: Semi-structured interviews were conducted with 21 home-care patients. Interview transcripts were analysed in an iterative process based on the principles of reflexive inductive thematic analysis.RESULTS: We identified a typology with four patient types: 'high need, high ability', 'high need, low ability', 'low need, high ability' and 'low need, low ability'. Several patients felt a need for participation because of their personal interest in health information. Others did not feel such a need since they trusted nurses to document the information that is important. Patients' ability to participate increased when they could read the documentation and when nurses helped them by talking about the documentation. Barriers to patients' ability to participate were having no electronic devices or lacking digital skills, a lack of support from nurses and the poor usability of electronic patient portals.CONCLUSION: Patient participation in electronic nursing documentation varies between patients since home-care patients differ in their need and ability to participate. Nurses should tailor their encouragement of patient participation to individual patients' needs and abilities. Furthermore, they should be aware of their own role and help patients to participate in the documentation.PATIENT OR PUBLIC CONTRIBUTION: Home-care patients were involved in the interviews.
Purpose The purpose of this paper is to describe whether and how groups of nursing home residents respond to the interactive device “the CRDL”. The CRDL can translate touches between people into sounds. It recognises the type of touch and adjusts the produced sound accordingly. Design/methodology/approach This was as an observational explorative study. Responses were coded and analysed using an existing theoretical framework. Findings – The CRDL creates an atmosphere of playfulness and curiosity. It lowers the threshold to touch, provides an incentive to touch and encourages to experiment with different types of touches on arms and hands. The sounds the CRDL produces sometimes trigger memories and provide themes to start and support conversation. Involving a (large) group of nursing home residents to interact with the CRDL is challenging. Research limitations/implications In order to more fully understand the potential of the CRDL, its use should be studied in different group and individual sessions and the effects of tailored content, adjusted to individual preferences and/or stages of cognition should be explored. Finally, the effects of using the CRDL on the general wellbeing of nursing home residents should be studied. Practical implications The CRDL can help caregivers to use touch to make contact with (groups of their) residents. A session should be guided by an experienced caregiver. Some familiarisation and practice with the CRDL are recommended and a quiet environment is advised. Originality/value This paper demonstrates the potential of interactive objects, such as the CRDL, in the nursing home.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
The findings suggests that participation in music practices can significantly support caregivers' and nurses' contact with the people to whom they give care and the healthcare professionals' insights into the patients' and residents' personhood. Music can create experienced changes in the care environment through kairotic moments of connectivity and intimacy of the musical interaction. The music sessions support and reinforce the person-centred values of care delivery.The meaning of participatory music practices for the well-being and learning of healthcare professionals working with ageing patients and nursing home residents.
Personal factors, team factors, and organizational factors have a strong influence on the adoption of technology used by, for instance, nurses in homecare. This part of the research portfolio in Point of Care Diagnostics regards the adoption of diagnostic technology in the health care domain.
