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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.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

The current study is aimed at identifying the prominent influencers that affect the response behaviour of patients in a hospital environment.

The research is based on the data collected through the participant observation method while interviewing patients about the quality of healthcare services in nine community health centres of the Kashmir division. Thematic analysis was performed on the information collected from patients admitted to various hospital sections.

The analysis of the qualitative data revealed that the presence of hospital staff near respondents, perceived risk of maltreatment, social desirability, the sensitivity of the topic, risk of information sharing and attitude towards surveys are the most frequently observed factors that modulate the patient's tendency to truthfully report critical facts about the problem understudy.

These results can help researchers to exercise caution while communicating with respondents and collecting data related to serious issues in a natural setting.

The study investigates the relationship between hospital environmental factors and the well-being of geriatric in-patients. It aims to identify the impact of architectural design on comfort, safety, privacy and stress levels experienced by elderly patients during their hospital stays.

Employing a mixed-methods approach, the research assesses the experiences of 100 geriatric in-patients across various hospital types through surveys, observational checklists and state anxiety measurements. The methodology involves examining architectural features, patient perceptions and correlations among environmental variables and patient experiences. Statistical analyses, including correlations and chi-square tests, were employed to discern associations between environmental variables and patient experiences.

The research identified key architectural features significantly impacting geriatric patients' experiences. Factors such as sturdy beds, furniture quantity, lighting conditions, proximity to facilities and ward occupancy levels were found to influence spatial, sensory and social comfort. Notably, proximity to facilities and control over the immediate environment were crucial for self-control and safety perceptions. Privacy, highly valued by patients, correlated with the presence of curtains and ward occupancy. Moreover, patient stress levels exhibited correlations with autonomy, privacy and ward occupancy.

This research offers significant insights into the criticality of specific architectural elements in enhancing comfort and reducing stress for geriatric in-patients. These findings hold substantial value for healthcare facility design, emphasizing the need to prioritize certain design aspects to promote the well-being of elderly patients during hospitalization.

This study aims to deal with the paucity of studies in the stages of the development of loyalty behaviour of customers in the healthcare context by incorporating three crucial service quality dimensions (physical environment, personnel quality and technical quality) and also investigating trust and commitment as mediating factors.

Survey data were obtained from 420 respondents admitted to government hospitals in Kerala employing a convenience sampling method. The formulated hypotheses were tested using partial least square structural equation modelling.

Results indicate that patient satisfaction, trust and commitment can create favourable behavioural intentions amongst patients. When patients reveal higher trust, they are more inclined to value healthcare services and willing to commit to a long-term relationship, resulting in increased patient loyalty.

Organisational efforts should improve trust and commitment and build a good relationship between service providers and patients. Efforts should be taken to raise the standard of technical and personnel aspects, and a focus on physical infrastructure should also be considered to build a favourable behavioural intention to revisit and positive referrals.

This is the first empirical study to analyse technical quality, personnel quality and physical environment along with the mediating effect of trust, and commitment in a four-stage loyalty development model in the healthcare context of Kerala, India.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

Ireland’s ageing population has resulted in an increasing number of older adults living with frailty. Despite growing attention towards older adults’ and health professionals’ perspectives of frailty, occupational therapy research is limited. This study aims to explore occupational therapists’ perceptions of frailty and how their perceptions impact their approach to the assessment and management of frailty.

Using qualitative descriptive design, 19 occupational therapists working with older adults participated in online focus groups. Data were analysed using thematic analysis.

Perceptions of occupational therapists were constructed into three main themes: conceptualising frailty; management of frailty; and advancing frailty practice. Findings indicate that occupational therapists perceived frailty as a multidimensional concept but highlight a reluctance to use frailty terminology with patients. Findings also suggest that although occupational therapists are involved in provision of care for older adults living with frailty, the profession’s scope is not optimised in the assessment and management of frailty.

Findings provide insight into occupational therapists’ perceptions of frailty. Development of a shared understanding of frailty between clinicians and patients and enhancement of undergraduate frailty education are recommended to progress occupational therapy’s role in frailty management.

This paper explores total quality management (TQM) soft domain efficacy in social care organizations to determine the extent to which an organization's project success may stem from soft TQM critical success factors (CSFs).

Non-structured interviews were conducted with 16 managers overseeing the prosthetic device regeneration project of the Italian local health unit (located in Salerno) to explore which soft factors could contribute to the success of a social care multifunctional organization.

Organizations' handling of certain projects, such as pivoting on soft TQM issues, may allow them to be configured as multiservice organizations. Therefore, a conceptual model of a multiservice social care organization is proposed.

From a managerial perspective, this study presents an interesting success case of a multiservice social care organization with a total annual expenditure of €20 million on prosthetic assistance. Preliminary data show a 13% reduction in public expenditure for Salerno's local health unit via a refurbishment project.

The paper contributes to the soft TQM literature debate: although Italian local health professionals appear aware of soft TQM issues' implementation and consciously apply them in their organization and projects, this occurs more with specific CSFs emerging from the literature. Therefore, this article paves the way for further quantitative and theoretical investigations on the adoption of TQM soft issues in social care organizations' performance measurement.