Background: Continuing professional development (CPD) in nursing is defined as ‘a life-long process of active participation in learning activities that assist in developing and maintaining continuing competences, enhancing professional practice and supporting achievement of career goals’. Research has shown that inability to access resources and activities for CPD influences quality of care and adversely affects nurses’ satisfaction, recruitment and retention. Although more and more research regarding CPD is done, a comprehensive overview about the needs of nurses for successful CPD is missing. Conclusions: All nurses strive for CPD. However, organizations need to recognize nurses' personal goals and unique strategies as this leads to different needs in CPD. In addition, resources must be made available and accessible before CPD can be successfully pursued by all nurses.
MULTIFILE
Over the last two decades, institutions for higher education such as universities and colleges have rapidly expanded and as a result have experienced profound changes in processes of research and organization. However, the rapid expansion and change has fuelled concerns about issues such as educators' technology professional development. Despite the educational value of emerging technologies in schools, the introduction has not yet enjoyed much success. Effective use of information and communication technologies requires a substantial change in pedagogical practice. Traditional training and learning approaches cannot cope with the rising demand on educators to make use of innovative technologies in their teaching. As a result, educational institutions as well as the public are more and more aware of the need for adequate technology professional development. The focus of this paper is to look at action research as a qualitative research methodology for studying technology professional development in HE in order to improve teaching and learning with ICTs at the tertiary level. The data discussed in this paper have been drawn from a cross institutional setting at Fontys University of Applied Sciences, The Netherlands. The data were collected and analysed according to a qualitative approach.
DOCUMENT
Background Clients facing decision-making for long-term care are in need of support and accessible information. Construction of preferences, including context and calculations, for clients in long-term care is challenging because of the variability in supply and demand. This study considers clients in four different sectors of long-term care: the nursing and care of the elderly, mental health care, care of people with disabilities, and social care. The aim is to understand the construction of preferences in real-life situations. Method Client choices were investigated by qualitative descriptive research. Data were collected from 16 in-depth interviews and 79 client records. Interviews were conducted with clients and relatives or informal caregivers from different care sectors. The original client records were explored, containing texts, letters, and comments of clients and caregivers. All data were analyzed using thematic analysis. Results Four cases showed how preferences were constructed during the decision-making process. Clients discussed a wide range of challenging aspects that have an impact on the construction of preferences, e.g. previous experiences, current treatment or family situation. This study describes two main characteristics of the construction of preferences: context and calculation. Conclusion Clients face diverse challenges during the decision-making process on long-term care and their construction of preferences is variable. A well-designed tool to support the elicitation of preferences seems beneficial.
DOCUMENT
Abstract Specialist oncology nurses (SONs) have the potential to play a major role in monitoring and reporting adverse drug reactions (ADRs); and reduce the level of underreporting by current healthcare professionals. The aim of this study was to investigate the long term clinical and educational efects of real-life pharmacovigilance education intervention for SONs on ADR reporting. This prospective cohort study, with a 2-year follow-up, was carried out in the three postgraduate schools in the Netherlands. In one of the schools, the prescribing qualifcation course was expanded to include a lecture on pharmacovigilance, an ADR reporting assignment, and group discussion of self-reported ADRs (intervention). The clinical value of the intervention was assessed by analyzing the quantity and quality of ADR-reports sent to the Netherlands Pharmacovigilance Center Lareb, up to 2 years after the course and by evaluating the competences regarding pharmacovigilance of SONs annually. Eighty-eight SONs (78% of all SONs with a prescribing qualifcation in the Netherlands) were included. During the study, 82 ADRs were reported by the intervention group and 0 by the control group. This made the intervention group 105 times more likely to report an ADR after the course than an average nurse in the Netherlands. This is the frst study to show a signifcant and relevant increase in the number of well-documented ADR reports after a single educational intervention. The real-life pharmacovigilance educational intervention also resulted in a long-term increase in pharmacovigilance competence. We recommend implementing real-life, context- and problem-based pharmacovigilance learning assignments in all healthcare curricula.
MULTIFILE
Offering physical activities matching with the preferences of residents in long-term care facilities could increase compliance and contribute to client-centered care. A measure to investigate meaningful activities by using a photo-interview has been developed (“MIBBO”). In two pilot studies including 133 residents living on different wards in long-term care facilities, feasibility, most chosen activities, and consistency of preferences were investigated. It was possible to conduct the MIBBO on average in 30 min with the majority (86.4%) of residents. The most frequently chosen activities were: gymnastics and orchestra (each 28%), preparing a meal (31%), walking (outside, 33%), watering plants (38%), and feeding pets (40%). In a retest one week after the initial interview 69.4% agreement of chosen activities was seen. The MIBBO seems a promising measure to help health care professionals in identifying residents’ preferred activities. Future research should focus on the implementation of the tailored activity plan, incorporating it into the daily routine.
DOCUMENT
Aim and method: To examine in obese people the potential effectiveness of a six-week, two times weekly aquajogging program on body composition, fitness, health-related quality of life and exercise beliefs. Fifteen otherwise healthy obese persons participated in a pilot study. Results: Total fat mass and waist circumference decreased 1.4 kg (p = .03) and 3.1 cm (p = .005) respectively. The distance in the Six-Minute Walk Test increased 41 meters (p = .001). Three scales of the Impact of Weight on Quality of Life-Lite questionnaire improved: physical function (p = .008), self-esteem (p = .004), and public distress (p = .04). Increased perceived exercise benefits (p = .02) and decreased embarrassment (p = .03) were observed. Conclusions: Aquajogging was associated with reduced body fat and waist circumference, and improved aerobic fitness and quality of life. These findings suggest the usefulness of conducting a randomized controlled trial with long-term outcome assessments.
DOCUMENT
Background: As more and more older adults prefer to stay in their homes as they age, there’s a need for technology to support this. A relevant technology is Artificial Intelligence (AI)-driven lifestyle monitoring, utilizing data from sensors placed in the home. This technology is not intended to replace nurses but to serve as a support tool. Understanding the specific competencies that nurses require to effectively use it is crucial. The aim of this study is to identify the essential competencies nurses require to work with AI-driven lifestyle monitoring in longterm care. Methods: A three round modified Delphi study was conducted, consisting of two online questionnaires and one focus group. A group of 48 experts participated in the study: nurses, innovators, developers, researchers, managers and educators. In the first two rounds experts assessed clarity and relevance on a proposed list of competencies, with the opportunity to provide suggestions for adjustments or inclusion of new competencies. In the third round the items without consensus were bespoken in a focus group. Findings: After the first round consensus was reached on relevance and clarity on n = 46 (72 %) of the competencies, after the second round on n = 54 (83 %) of the competencies. After the third round a final list of 10 competency domains and 61 sub-competencies was finalized. The 10 competency domains are: Fundamentals of AI, Participation in AI design, Patient-centered needs assessment, Personalisation of AI to patients’ situation, Data reporting, Interpretation of AI output, Integration of AI output into clinical practice, Communication about AI use, Implementation of AI and Evaluation of AI use. These competencies span from basic understanding of AIdriven lifestyle monitoring, to being able to integrate it in daily work, being able to evaluate it and communicate its use to other stakeholders, including patients and informal caregivers. Conclusion: Our study introduces a novel framework highlighting the (sub)competencies, required for nurses to work with AI-driven lifestyle monitoring in long-term care. These findings provide a foundation for developing initial educational programs and lifelong learning activities for nurses in this evolving field. Moreover, the importance that experts attach to AI competencies calls for a broader discussion about a potential shift in nursing responsibilities and tasks as healthcare becomes increasingly technologically advanced and data-driven, possibly leading to new roles within nursing.
LINK
As more and more older adults prefer to stay in their homes as they age, there’s a need for technology to support this. A relevant technology is Artificial Intelligence (AI)-driven lifestyle monitoring, utilizing data from sensors placed in the home. This technology is not intended to replace nurses but to serve as a support tool. Understanding the specific competencies that nurses require to effectively use it is crucial. The aim of this study is to identify the essential competencies nurses require to work with AI-driven lifestyle monitoring in longterm care. Methods: A three round modified Delphi study was conducted, consisting of two online questionnaires and one focus group. A group of 48 experts participated in the study: nurses, innovators, developers, researchers, managers and educators. In the first two rounds experts assessed clarity and relevance on a proposed list of competencies, with the opportunity to provide suggestions for adjustments or inclusion of new competencies. In the third round the items without consensus were bespoken in a focus group. Findings: After the first round consensus was reached on relevance and clarity on n = 46 (72 %) of the competencies, after the second round on n = 54 (83 %) of the competencies. After the third round a final list of 10 competency domains and 61 sub-competencies was finalized. The 10 competency domains are: Fundamentals of AI, Participation in AI design, Patient-centered needs assessment, Personalisation of AI to patients’ situation, Data reporting, Interpretation of AI output, Integration of AI output into clinical practice, Communication about AI use, Implementation of AI and Evaluation of AI use. These competencies span from basic understanding of AIdriven lifestyle monitoring, to being able to integrate it in daily work, being able to evaluate it and communicate its use to other stakeholders, including patients and informal caregivers. Conclusion: Our study introduces a novel framework highlighting the (sub)competencies, required for nurses to work with AI-driven lifestyle monitoring in long-term care. These findings provide a foundation for developing initial educational programs and lifelong learning activities for nurses in this evolving field. Moreover, the importance that experts attach to AI competencies calls for a broader discussion about a potential shift in nursing responsibilities and tasks as healthcare becomes increasingly technologically advanced and data-driven, possibly leading to new roles within nursing.
DOCUMENT
Purpose: Collaborative deliberation comprises personal engagement, recognition of alternative actions, comparative learning, preference elicitation, and preference integration. Collaborative deliberation may be improved by assisting preference elicitation during shared decision-making. This study proposes a framework for preference elicitation to facilitate collaborative deliberation in long-term care consultations. Methods: First, a literature overview was conducted comprising current models for the elicitation of preferences in health and social care settings. The models were reviewed and compared. Second, qualitative research was applied to explore those issues that matter most to clients in long-term care. Data were collected from clients in long-term care, comprising 16 interviews, 3 focus groups, 79 client records, and 200 online client reports. The qualitative analysis followed a deductive approach. The results of the literature overview and qualitative research were combined. Results: Based on the literature overview, five overarching domains of preferences were described: “Health”, “Daily life”, “Family and friends”, ”Living conditions”, and “Finances”. The credibility of these domains was confirmed by qualitative data analysis. During interviews, clients addressed issues that matter in their lives, including a “click” with their care professional, safety, contact with loved ones, and assistance with daily structure and activities. These data were used to determine the content of the domains. Conclusion: A framework for preference elicitation in long-term care is proposed. This framework could be useful for clients and professionals in preference elicitation during collaborative deliberation.
DOCUMENT
In this paper, we analyse the development of the term “legal capabilities”. More specifically, we do three things. First, we track the emergence and development of the notion of legal capabilities. The term legal capabilities was used in legal research long before the capability approach was introduced in that field. Early on, its conceptualisation mainly reflected elements of legal literacy. In more recent writings, it is claimed that the notion is based on the capability approach. Second, we critically analyse the current use of the term legal capabilities and show that there is no proper theoretical grounding of this term in the capability approach. This is problematic, because it might give rise to misunderstandings and flawed policy recommendations. Third, we suggest some first steps towards a revision of the notion of legal capabilities. Starting from the concept of “access to justice”, legal capabilities have to be understood as the real opportunities someone has to get access to justice, rather than merely as formal opportunities or internal capabilities.
MULTIFILE
