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Due to the increasing incidence of dementia in Ireland, there is a need to prepare occupational therapy students for future careers in dementia-focused health care. The purpose of this study are to measure the knowledge and attitudes of Irish undergraduate occupational therapy students towards older people with dementia and examine related variables including year of study, personal and placement dementia experiences and future career choice.

Data was gathered using a cross-sectional online survey, incorporating the Alzheimer’s Disease Knowledge Scale and the Dementia Attitudes Scale, which was analysed using descriptive and inferential statistics.

Seventy-five responses were gathered and analysed, indicating more advanced occupational therapy students demonstrate higher levels of dementia knowledge, but dementia attitudes remain similar across different year groups. Students with clinical dementia experiences displayed comparable levels of dementia knowledge and attitudes to those without. However, students with familial dementia experiences displayed significantly more positive attitudes. The likelihood of selecting a future career with older adults with dementia significantly related to students’ positive dementia attitudes but not dementia knowledge.

To the best of the authors’ knowledge, this is the first Irish study that focuses on undergraduate occupational therapy students’ dementia knowledge and attitudes. The results could be used to inform and develop Irish undergraduate occupational therapy programmes.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

The purpose of this article is to examine synergies between a eudaimonic model of psychological well-being (Ryff, 1989) and mental health practice. The model grew out of clinical, developmental, existential and humanistic perspectives that emphasized psychological strengths and capacities, in contrast to the focus on emotional distress and dysfunction in clinical psychology.

Conceptual foundations of the eudaimonic approach are described, along with the six components positive functioning that are used to measure well-being. These qualities may be important in facilitating the recovery experiences, which are of interest in Mental Health and Social Inclusion.

Four categories of empirical evidence about eudaimonia are reviewed: how it changes with aging, how it matters for health, what are its biological and neurological underpinnings and whether it can be promoted. Major contemporary forces against eudaimonia are also considered, including ever-widening inequality, the enduring pandemic and world-wide strife. In contrast, encounters with the arts and nature are put forth as forces for eudaimonia. The relevance of these ideas for mental health research and practice is considered.

Enormous suffering defines our contemporary world. Such realities call for greater attention to factors that undermine as well as nurture the realization of human potential, the core of eudaimonic well-being.

Mental health is often defined as the absence of mental illness. The novelty of the eudaimonic approach is to define mental health as the presence of well-being, assessed with different components of positive functioning.

Older people living in nursing homes have complex care needs and frequently need specialists’ advice and support that can be challenging to deliver in a rural setting. The aim of this paper is to describe a model of integrated care in a rural area supported by a nurse case manager.

A real-world evidence study of people living in Ribes de Freser nursing home, was conducted between specific timeframes in 2019 and 2022, comparing the casemix and outcomes of a traditional care model with the integrated interdisciplinary model.

The integrated care model led to a significant reduction in transfers to the emergency department, hospitalisations, outpatient medical visits and a reduction in the number of medicines. In addition, the number of residents receiving end-of-life care at the nursing home showed a substantial increase.

This case study contributes valuable evidence supporting the implementation of an integrated model of nurse case manager support in nursing homes, particularly in the rural contexts, where access to specialist medical staff may be limited. The findings highlight the potential benefits of person-centred integrated care for older adults, addressing their complex needs and improving end-of-life care in nursing home settings.

Menstruation is a part of the female reproductive cycle that begins with adolescence. Menstruation is a natural change; it relates to several malpractices and misconceptions that may contribute to adverse health outcomes.

The authors have searched relevant papers using Google Scholar and PubMed to write this mini review.

During menstruation, poor hygiene maintenance can cause serious illness, which includes the urinary tract and reproductive tract infection. Menstruation management is a hygienic system, and it is essential for females because poor hygiene maintenance during menstruation can cause some infections and numerous sexually transmitted diseases. There are a few nanotechnology-based products that have come into the market to offer some relief to females during their periods.

This mini review will help researchers to design innovative female hygiene products that can relieve the discomfort caused to women during their reproductive age.

This paper aims to evaluate the effect of consumption of a high-fat diet (HFD) rich with total saturated fats on adiposity and serum levels of vascular cell adhesion molecule (sVCAM-1), a biomarker of endothelial inflammation/dysfunction. Another aim is to evaluate whether supplementation of a phytosomal formulation of curcumin would reduce adiposity measures and sVCAM-1 levels in HFD rats.

The study was conducted on 17 male rats which were allocated to one of three feeding regimen groups: normal diet (ND); HFD, or HFD with dietary phytosomal curcumin (HFD-C). Anthropometric measures were recorded weekly up to 20 weeks of feeding intervention, at the end of which, sVCAM-1 levels were also compared with one-way ANOVA and Tukey post-hoc analysis.

The HFD group had the greatest values for raw anthropometric data, and there was a group difference in anthropometric measures, however there was no significant difference between HFD and HFD-C for any measure. The gain at 20 weeks from initial values did reveal significant differences in weight and abdominal circumference between HFD and HFD-C groups. There were significant group differences in sVCAM-1 levels, with only HFD-C displaying significant lower levels than HFD group.

This is the first study that shows the capacity of a phytosomal formulation of curcumin in reducing adiposity and sVCAM-1 levels during daily intake of saturated fats above the recommended level. The results are promising in that this formulation can protect against endothelial inflammation/dysfunction, and can be used as complimentary therapy to suppress dyslipidemia/obesity-related cardiovascular complications.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

This paper presents findings from a qualitative study of healthcare professionals’ practice, where learning is taking place when a digital artefact is implemented for identification of patients’ cognitive impairment. The use of digital artefacts is increasing in various workplaces, to include professionals in healthcare. This paper aims to explore the following research question: How is the professional learning unfolding in patient-based work when a digital artefact transforms the practice?

Various data collection methods are used for this study, consisting of dialogue meetings, interviews and a reference-group meeting. Thematic analysis is used to inductively bring forth the themes of the collected data.

Professionals’ knowledge and experience are of vital importance in learning and changing work practices. Together with their ability to reflect on changes, their knowledge and experience constitute the prefiguration when the introduction of a digital application brings about indeterminacy in the work practice.

This paper makes a contribution to practice-based research as it consolidates previous research and identifies professionals knowledge and learning in a healthcare context. This can be used to further explore and advance the field, as well as to establish the evidence-based importance of transforming practices based on implementation of digital artefacts.

The purpose of this paper is to give an account for preparative collaboration between the police and municipal eldercare in Sweden concerning missing persons with dementia.

Design/methodology/approach used was a qualitative case study design, consisting of one focus group with representatives for the participating organisations, followed by directed content analysis.

The findings showed a lack of current collaboration and reluctance to new collaborative initiatives. However, when focussing on preparative collaboration of coordinated responses to missing incidents, possibilities for improvement could be identified. The improvements concerned updated personnel response checklists, along with suggestions for an elaborate life story document in eldercare, with police access. Finally, better coordination of the return of the found person and a follow up were proposed.

It is suggested that collaboration must be given different meanings and use different approaches adapted to the different phases in a rescue operation. In the preparation and the response phase, the focus should be on coordination of the resources available. In the pre-planning and prevention phases, as well as in evaluation and learning, horizontal collaboration is more suitable. The amount of data in this study is a research limitation which calls for further research.

It is suggested that collaboration must be given different meanings and use different approaches adapted to the different phases in a rescue operation. In the preparation and the response phase, the focus should be on coordination of the resources available. In the pre-planning and prevention phases, as well as in evaluation and learning, horizontal co-operation is more suitable.

The originality/value of this paper can be found in the novelty of missing person research in Sweden, and in practical suggestions for preparative collaboration concerning persons with dementia who go missing. Finally, it can be found in the suggested need for a more dynamic and process-sensitive view of collaboration in SAR or rescue operations.

The purpose of this paper is to share the learning concerning how services and the paid carers working in them can support people living with dementia (PLWD) and their unpaid carers to overcome social isolation. This learning comes from the key findings from a Social Return on Investment (SROI) evaluation of a Shared Lives (SL) Day support service, known as TRIO.

SROI is a form of cost-benefit analysis that captures and monetises stakeholder outcomes. The SROI evaluation included a rapid evidence review, an interview study and a questionnaire study. The learning shared is drawn from the interview and questionnaire data that explored the reported outcomes relating to social connection, which included data related to participating in meaningful activities, confidence and independence.

PLWD who accessed the SL Day support service experienced better social connection, a sense of control over their activities (including their social activities) and community presence. A key foundation of these outcomes was the meaningful relationship that developed between the PLWD, their unpaid carer and the paid carer.

This evaluation was a pilot study with a small, albeit representative sample size.

The learning suggests feasible and effective ways for paid carers to support the social connection of PLWD and their unpaid carers with their wider community.

There has been little exploration of how community-based short breaks (like SL Day support) can enhance social connection. The authors drew on a social relational model lens to illustrate how this service type had supported successful outcomes of community and social inclusion for PLWD.